Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.

PubMed

Ma, Xin; Guo, Jing; Sun, Xiao

2015-01-01

The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed by incremental feature selection (IFS). We incorporated features of conjoint triad features and three novel features: binding propensity (BP), nonbinding propensity (NBP), and evolutionary information combined with physicochemical properties (EIPP). The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient). High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

PubMed

Belekar, Vilas; Lingineni, Karthik; Garg, Prabha

2015-01-01

The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this work, a computational model was developed to predict the compounds as BCRP inhibitors or non-inhibitors. Various machine learning approaches like, support vector machine (SVM), k-nearest neighbor (k-NN) and artificial neural network (ANN) were used to develop the models. The Matthews correlation coefficients (MCC) of developed models using ANN, k-NN and SVM are 0.67, 0.71 and 0.77, and prediction accuracies are 85.2%, 88.3% and 90.8% respectively. The developed models were tested with a test set of 99 compounds and further validated with external set of 98 compounds. Distribution plot analysis and various machine learning models were also developed based on druglikeness descriptors. Applicability domain is used to check the prediction reliability of the new molecules.

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

PubMed

Wang, Hsin-Wei; Lin, Ya-Chi; Pai, Tun-Wen; Chang, Hao-Teng

2011-01-01

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%).

HicAB toxin-antitoxin complex from Escherichia coli: expression and crystallization.

PubMed

Yang, Jingsi; Xu, Bingshuang; Gao, Zengqiang; Zhou, Ke; Liu, Peng; Dong, Yuhui; Zhang, Jianjun; Liu, Quansheng

2017-09-01

Toxin-antitoxin (TA) systems are widespread in both bacteria and archaea, where they enable cells to adapt to environmental cues. TA systems play crucial roles in various cellular processes, such as programmed cell death, cell growth, persistence and virulence. Here, two distinct forms of the type II toxin-antitoxin complex HicAB were identified and characterized in Escherichia coli K-12, and both were successfully overexpressed and purified. The two proposed forms, HicAB L and HicAB S , differed in the presence or absence of a seven-amino-acid segment at the N-terminus in the antitoxin HicB. The short form HicAB S readily crystallized under the conditions 0.1 M Tris-HCl pH 8.0, 20%(w/v) PEG 6000, 0.2 M ammonium sulfate. The HicAB S crystal diffracted and data were collected to 2.5 Å resolution. The crystal belonged to space group I222 or I2 1 2 1 2 1 , with unit-cell parameters a = 67.04, b = 66.31, c = 120.78 Å. Matthews coefficient calculation suggested the presence of two molecules each of HicA and HicB S in the asymmetric unit, with a solvent content of 55.28% and a Matthews coefficient (V M ) of 2.75 Å 3  Da -1 .

Hurricane Matthew from Space

NASA Image and Video Library

2017-12-08

The most recent view of Matthew from space shows this massive storm converging on the Florida coast. This visible image was captured Oct. 7 at 4:45 a.m. EDT from NOAA's GOES-East satellite. Read more about Hurricane Matthew at www.nasa.gov/matthew Credits: NASA/NOAA GOES Project

Making it without losing it: Type A, achievement motivation, and scientific attainment revisited.

PubMed

Helmreich, R L; Spence, J T; Pred, R S

1988-09-01

In a study by Matthews, Helmreich, Beane, and Lucker (1980), responses by academic psychologists to the Jenkins Activity Survey for Health Prediction (JAS), a measure of the Type A construct, were found to be significantly, positively correlated with two measures of attainment, citations by others to published work and number of publications. In the present study, JAS responses from the Matthews et al. sample were subjected to a factor analysis with oblique rotation and two new subscales were developed on the basis of this analysis. The first, Achievement Strivings (AS) was found to be significantly correlated with both the publication and citation measures. The second scale, Impatience and Irritability (I/I), was uncorrelated with the achievement criteria. Data from other samples indicate that I/I is related to a number of health symptoms. The results suggest that the current formulation of the Type A construct may contain two components, one associated with positive achievement and the other with poor health.

Making it without losing it: Type A, achievement motivation, and scientific attainment revisited

NASA Technical Reports Server (NTRS)

Helmreich, R. L.; Spence, J. T.; Pred, R. S.

1988-01-01

In a study by Matthews, Helmreich, Beane, and Lucker (1980), responses by academic psychologists to the Jenkins Activity Survey for Health Prediction (JAS), a measure of the Type A construct, were found to be significantly, positively correlated with two measures of attainment, citations by others to published work and number of publications. In the present study, JAS responses from the Matthews et al. sample were subjected to a factor analysis with oblique rotation and two new subscales were developed on the basis of this analysis. The first, Achievement Strivings (AS) was found to be significantly correlated with both the publication and citation measures. The second scale, Impatience and Irritability (I/I), was uncorrelated with the achievement criteria. Data from other samples indicate that I/I is related to a number of health symptoms. The results suggest that the current formulation of the Type A construct may contain two components, one associated with positive achievement and the other with poor health.

Making it without losing it: Type A, achievement motivation, and scientific attainment revisited

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.; Spence, Janet T.; Pred, Robert S.

1987-01-01

In a study by Matthews et al. (1980), responses by academic psychologists to the Jenkins Activity Survey for Health Prediction, a measure of the Type A construct, were found to be significantly, positively correlated with two measures of attainment, citations by others to published work and number of publications. In the present study, JAS responses from the Matthews et al. sample were subjected to a factor analysis with oblique rotation and two new subscales were developed on the basis of this analysis. The first, Achievement Strivings (AS) was found to be significantly correlated with both the publication and citation measures. The second scale, Impatience and Irritability (I/I), was uncorrelated with the achievement criteria. Data from other samples indicate that I/I is related to a number of health symptoms. The results suggest that the current formulation of the Type A construct may contain two components, one associated with positive achievement and the other with poor health.

Matthew M. Yung | NREL

Science.gov Websites

M. Yung Photo of Matthew M. Yung Matthew Yung Senior Engineer, Catalysis & Reaction Engineering comprehensive reaction testing and materials characterization (e.g., kinetic experiments, spectroscopy

Fighting, Anger, Frustration and Tears: Matthew's Story of Hegemonic Masculinity

ERIC Educational Resources Information Center

Keddie, Amanda

2006-01-01

This paper draws on Matthew's story to illustrate the conflicting discourses of being a boy and being a student. Matthew is 12 years old and in Grade Six, his final year at Banrock Primary (a K-6 Australian State School). School is far from a happy place for Matthew--his tearful accounts of his combative relationships with his peers and his…

CloudSat Takes a 3D Slice of Hurricane Matthew

NASA Image and Video Library

2016-10-07

NASA's CloudSat flew east of Hurricane Matthew's center on Oct. 6 at 11:30 a.m. PDT (2:30 p.m. EDT), intersecting parts of Matthew's outer rain bands and revealing Matthew's anvil clouds (thick cirrus cloud cover), with cumulus and cumulonimbus clouds beneath (lower image). Reds/pinks are larger water/ice droplets. http://photojournal.jpl.nasa.gov/catalog/PIA21095

Natural Tasking of Robots Based on Human Interaction Cues

DTIC Science & Technology

2005-06-01

MIT. • Matthew Marjanovic , researcher, ITA Software. • Brian Scasselatti, Assistant Professor of Computer Science, Yale. • Matthew Williamson...2004. 25 [74] Charlie C. Kemp. Shoes as a platform for vision. 7th IEEE International Symposium on Wearable Computers, 2004. [75] Matthew Marjanovic ...meso: Simulated muscles for a humanoid robot. Presentation for Humanoid Robotics Group, MIT AI Lab, August 2001. [76] Matthew J. Marjanovic . Teaching

Expression, purification, crystallization and preliminary X-ray studies of Lactobacillus jensenii enolase

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

Harris, Paul T.; Raghunathan, Kannan; Spurbeck, Rachel R.

2010-09-02

Recombinant Lactobacillus jensenii enolase fused to a C-terminal noncleavable His tag was expressed in Escherichia coli, purified and crystallized by sitting-drop vapor diffusion. A complete data set was collected to 3.25 {angstrom} resolution. The crystals belonged to space group I4, with unit-cell parameters a = b = 145.31, c = 99.79 {angstrom}. There were two protein subunits in the asymmetric unit, which gave a Matthews coefficient V{sub M} of 2.8 {angstrom}{sup 3} Da{sup -1}, corresponding to 55.2% solvent content.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

NASA Astrophysics Data System (ADS)

de Siqueira, Alexandre Fioravante; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Tello Saenz, Carlos Alberto; Job, Aldo Eloizo

2014-08-01

Manual identification of fission tracks has practical problems, such as variation due to observe-observation efficiency. An automatic processing method that could identify fission tracks in a photomicrograph could solve this problem and improve the speed of track counting. However, separation of nontrivial images is one of the most difficult tasks in image processing. Several commercial and free softwares are available, but these softwares are meant to be used in specific images. In this paper, an automatic method based on starlet wavelets is presented in order to separate fission tracks in mineral photomicrographs. Automatization is obtained by the Matthews correlation coefficient, and results are evaluated by precision, recall and accuracy. This technique is an improvement of a method aimed at segmentation of scanning electron microscopy images. This method is applied in photomicrographs of epidote phenocrystals, in which accuracy higher than 89% was obtained in fission track segmentation, even for difficult images. Algorithms corresponding to the proposed method are available for download. Using the method presented here, a user could easily determine fission tracks in photomicrographs of mineral samples.

Predicting protein amidation sites by orchestrating amino acid sequence features

NASA Astrophysics Data System (ADS)

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.

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

Prediction of pi-turns in proteins using PSI-BLAST profiles and secondary structure information.

PubMed

Wang, Yan; Xue, Zhi-Dong; Shi, Xiao-Hong; Xu, Jin

2006-09-01

Due to the structural and functional importance of tight turns, some methods have been proposed to predict gamma-turns, beta-turns, and alpha-turns in proteins. In the past, studies of pi-turns were made, but not a single prediction approach has been developed so far. It will be useful to develop a method for identifying pi-turns in a protein sequence. In this paper, the support vector machine (SVM) method has been introduced to predict pi-turns from the amino acid sequence. The training and testing of this approach is performed with a newly collected data set of 640 non-homologous protein chains containing 1931 pi-turns. Different sequence encoding schemes have been explored in order to investigate their effects on the prediction performance. With multiple sequence alignment and predicted secondary structure, the final SVM model yields a Matthews correlation coefficient (MCC) of 0.556 by a 7-fold cross-validation. A web server implementing the prediction method is available at the following URL: http://210.42.106.80/piturn/.

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

PubMed

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.

lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine.

PubMed

Sun, Lei; Liu, Hui; Zhang, Lin; Meng, Jia

2015-01-01

Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.

Classification of the fragrant styles and evaluation of the aromatic quality of flue-cured tobacco leaves by machine-learning methods.

PubMed

Gu, Li; Xue, Lichun; Song, Qi; Wang, Fengji; He, Huaqin; Zhang, Zhongyi

2016-12-01

During commercial transactions, the quality of flue-cured tobacco leaves must be characterized efficiently, and the evaluation system should be easily transferable across different traders. However, there are over 3000 chemical compounds in flue-cured tobacco leaves; thus, it is impossible to evaluate the quality of flue-cured tobacco leaves using all the chemical compounds. In this paper, we used Support Vector Machine (SVM) algorithm together with 22 chemical compounds selected by ReliefF-Particle Swarm Optimization (R-PSO) to classify the fragrant style of flue-cured tobacco leaves, where the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) were 90.95% and 0.80, respectively. SVM algorithm combined with 19 chemical compounds selected by R-PSO achieved the best assessment performance of the aromatic quality of tobacco leaves, where the PCC and MSE were 0.594 and 0.263, respectively. Finally, we constructed two online tools to classify the fragrant style and evaluate the aromatic quality of flue-cured tobacco leaf samples. These tools can be accessed at http://bioinformatics.fafu.edu.cn/tobacco .

Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

NASA Astrophysics Data System (ADS)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

2013-03-01

The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

MLACP: machine-learning-based prediction of anticancer peptides

PubMed Central

Manavalan, Balachandran; Basith, Shaherin; Shin, Tae Hwan; Choi, Sun; Kim, Myeong Ok; Lee, Gwang

2017-01-01

Cancer is the second leading cause of death globally, and use of therapeutic peptides to target and kill cancer cells has received considerable attention in recent years. Identification of anticancer peptides (ACPs) through wet-lab experimentation is expensive and often time consuming; therefore, development of an efficient computational method is essential to identify potential ACP candidates prior to in vitro experimentation. In this study, we developed support vector machine- and random forest-based machine-learning methods for the prediction of ACPs using the features calculated from the amino acid sequence, including amino acid composition, dipeptide composition, atomic composition, and physicochemical properties. We trained our methods using the Tyagi-B dataset and determined the machine parameters by 10-fold cross-validation. Furthermore, we evaluated the performance of our methods on two benchmarking datasets, with our results showing that the random forest-based method outperformed the existing methods with an average accuracy and Matthews correlation coefficient value of 88.7% and 0.78, respectively. To assist the scientific community, we also developed a publicly accessible web server at www.thegleelab.org/MLACP.html. PMID:29100375

Hurricane Matthew

NASA Image and Video Library

2017-12-08

This is a visible image of Major Hurricane Matthew taken from NASA's Terra satellite on Oct. 7 at 12 p.m. EDT as it continued moving along Florida's East Coast. Matthew was a Category 3 hurricane at the time of this image. Credit: NASA's Goddard MODIS Rapid Response Team

Cumulative (Dis)Advantage and the Matthew Effect in Life-Course Analysis

PubMed Central

Bask, Miia; Bask, Mikael

2015-01-01

To foster a deeper understanding of the mechanisms behind inequality in society, it is crucial to work with well-defined concepts associated with such mechanisms. The aim of this paper is to define cumulative (dis)advantage and the Matthew effect. We argue that cumulative (dis)advantage is an intra-individual micro-level phenomenon, that the Matthew effect is an inter-individual macro-level phenomenon and that an appropriate measure of the Matthew effect focuses on the mechanism or dynamic process that generates inequality. The Matthew mechanism is, therefore, a better name for the phenomenon, where we provide a novel measure of the mechanism, including a proof-of-principle analysis using disposable personal income data. Finally, because socio-economic theory should be able to explain cumulative (dis)advantage and the Matthew mechanism when they are detected in data, we discuss the types of models that may explain the phenomena. We argue that interactions-based models in the literature traditions of analytical sociology and statistical mechanics serve this purpose. PMID:26606386

Additions to the avifauna of St Matthew Island, Bering Sea

USGS Publications Warehouse

Johnson, James A.; Matsuoka, Steven M.; Ruthrauff, Daniel R.; Litzow, Michael A.; Dementyev, Maksim N.

2004-01-01

St. Matthew Island (60°24' N, 172°42' W) is located in the north-central Bering Sea and is renowned for its distinctive Beringian flora and fauna. Because of its central position between the coasts of Russia and Alaska, St. Matthew Island and its nearby satellites, Hall and Pinnacle islands, support a mixture of Palearctic and Nearctic avifaunas. Of special interest to North American ornithologists are the numerous Eurasian bird species that visit the islands each spring and fall. Winker et al. (2002) published the first comprehensive summary of bird records for the 125 species detected on St. Matthew Island from 1899 to 1997. Because of its remote location, however, St. Matthew Island is seldom visited, and the island's avifauna remains poorly described.As part of an island-wide systematic survey for Rock Sandpipers (Calidris ptilocnemis) and McKay's Buntings (Plectrophenax hyperboreus), our crew of five ornithologists was present on St. Matthew Island from 25 May to 9 July 2003. In this paper we provide information for 11 bird species seen for the first time on St. Matthew Island. Phylogenetic sequence and nomenclature follow the American Ornithologists' Union (1998, 2000) and Banks et al. (2002, 2003, 2004). An annotated species list with details of observation is on file at the University of Alaska Museum, Fairbank.

50 CFR Table 46 to Part 679 - St. Matthew Island Habitat Conservation Area

Code of Federal Regulations, 2011 CFR

2011-10-01

... 50 Wildlife and Fisheries 11 2011-10-01 2011-10-01 false St. Matthew Island Habitat Conservation Area 46 Table 46 to Part 679 Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL... ECONOMIC ZONE OFF ALASKA Pt. 679, Table 46 Table 46 to Part 679—St. Matthew Island Habitat Conservation...

50 CFR Table 46 to Part 679 - St. Matthew Island Habitat Conservation Area

Code of Federal Regulations, 2012 CFR

2012-10-01

... 50 Wildlife and Fisheries 13 2012-10-01 2012-10-01 false St. Matthew Island Habitat Conservation Area 46 Table 46 to Part 679 Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL... ECONOMIC ZONE OFF ALASKA Pt. 679, Table 46 Table 46 to Part 679—St. Matthew Island Habitat Conservation...

50 CFR Table 46 to Part 679 - St. Matthew Island Habitat Conservation Area

Code of Federal Regulations, 2014 CFR

2014-10-01

... 50 Wildlife and Fisheries 13 2014-10-01 2014-10-01 false St. Matthew Island Habitat Conservation Area 46 Table 46 to Part 679 Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL... ECONOMIC ZONE OFF ALASKA Pt. 679, Table 46 Table 46 to Part 679—St. Matthew Island Habitat Conservation...

50 CFR Table 46 to Part 679 - St. Matthew Island Habitat Conservation Area

Code of Federal Regulations, 2013 CFR

2013-10-01

... 50 Wildlife and Fisheries 13 2013-10-01 2013-10-01 false St. Matthew Island Habitat Conservation Area 46 Table 46 to Part 679 Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL... ECONOMIC ZONE OFF ALASKA Pt. 679, Table 46 Table 46 to Part 679—St. Matthew Island Habitat Conservation...

50 CFR Table 46 to Part 679 - St. Matthew Island Habitat Conservation Area

Code of Federal Regulations, 2010 CFR

2010-10-01

... 50 Wildlife and Fisheries 9 2010-10-01 2010-10-01 false St. Matthew Island Habitat Conservation Area 46 Table 46 to Part 679 Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL... ECONOMIC ZONE OFF ALASKA Pt. 679, Table 46 Table 46 to Part 679—St. Matthew Island Habitat Conservation...

Toward a Global Vision of Gifted Education: An Interview with Michael S. Matthews

ERIC Educational Resources Information Center

Henshon, Suzanna E.

2017-01-01

Dr. Michael S. Matthews is professor and director of the Academically & Intellectually Gifted graduate programs at the University of North Carolina at Charlotte. He is incoming Coeditor of the "Gifted Child Quarterly" and a member of the Board of Directors of the National Association for Gifted Children. Dr. Matthews also currently…

An Awkward Echo: Matthew Arnold and John Dewey. Research in Curriculum and Instruction

ERIC Educational Resources Information Center

Dietz, Mark David

2010-01-01

Matthew Arnold, 19th century English poet, literary critic and school inspector, felt that each age had to determine that philosophy that was most adequate to its own concerns and contexts. This study looks at the influence that Matthew Arnold had on John Dewey and attempts to fashion a philosophy of education that is adequate for our own…

Social influence and the Matthew mechanism: The case of an artificial cultural market

NASA Astrophysics Data System (ADS)

Bask, Miia; Bask, Mikael

2014-10-01

We show that the Matthew effect, or Matthew mechanism, was present in the artificial cultural market Music Lab in one-fourth of the “worlds” when social influence between individuals was allowed, whereas this effect was not present in the “world” that disallowed social influence between individuals. We also sketch on a class of social network models, derived from social influence theory, that may generate the Matthew effect. Thus, we propose a theoretical framework that may explain why the most popular songs could be much more popular, and the least popular songs could be much less popular, than when disallowing social influence between individuals.

Smart Phones: Platform Enabling Modular, Chemical, Biological, and Explosives Sensing

DTIC Science & Technology

2013-07-01

Smart phones: Platform Enabling Modular, Chemical, Biological, and Explosives Sensing by Amethist S. Finch , Matthew Coppock, Justin R...Chemical, Biological, and Explosives Sensing Amethist S. Finch , Matthew Coppock, Justin R. Bickford, Marvin A. Conn, Thomas J. Proctor, and...Explosives Sensing 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Amethist S. Finch , Matthew Coppock, Justin R

Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

NASA Astrophysics Data System (ADS)

Yu, Jia-Feng; Sui, Tian-Xiang; Wang, Hong-Mei; Wang, Chun-Ling; Jing, Li; Wang, Ji-Hua

2015-12-01

Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. Project supported by the National Natural Science Foundation of China (Grant Nos. 61302186 and 61271378) and the Funding from the State Key Laboratory of Bioelectronics of Southeast University.

e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-Learning Methods

PubMed Central

Zheng, Suqing; Jiang, Mengying; Zhao, Chengwei; Zhu, Rui; Hu, Zhicheng; Xu, Yong; Lin, Fu

2018-01-01

In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypothetical non-bitterant dataset used in the previous works. Based on this experimental dataset, we harness the consensus votes from the multiple machine-learning methods (e.g., deep learning etc.) combined with the molecular fingerprint to build the bitter/bitterless classification models with five-fold cross-validation, which are further inspected by the Y-randomization test and applicability domain analysis. One of the best consensus models affords the accuracy, precision, specificity, sensitivity, F1-score, and Matthews correlation coefficient (MCC) of 0.929, 0.918, 0.898, 0.954, 0.936, and 0.856 respectively on our test set. For the automatic prediction of bitterant, a graphic program “e-Bitter” is developed for the convenience of users via the simple mouse click. To our best knowledge, it is for the first time to adopt the consensus model for the bitterant prediction and develop the first free stand-alone software for the experimental food scientist. PMID:29651416

Optimization of a chemical identification algorithm

NASA Astrophysics Data System (ADS)

Chyba, Thomas H.; Fisk, Brian; Gunning, Christin; Farley, Kevin; Polizzi, Amber; Baughman, David; Simpson, Steven; Slamani, Mohamed-Adel; Almassy, Robert; Da Re, Ryan; Li, Eunice; MacDonald, Steve; Slamani, Ahmed; Mitchell, Scott A.; Pendell-Jones, Jay; Reed, Timothy L.; Emge, Darren

2010-04-01

A procedure to evaluate and optimize the performance of a chemical identification algorithm is presented. The Joint Contaminated Surface Detector (JCSD) employs Raman spectroscopy to detect and identify surface chemical contamination. JCSD measurements of chemical warfare agents, simulants, toxic industrial chemicals, interferents and bare surface backgrounds were made in the laboratory and under realistic field conditions. A test data suite, developed from these measurements, is used to benchmark algorithm performance throughout the improvement process. In any one measurement, one of many possible targets can be present along with interferents and surfaces. The detection results are expressed as a 2-category classification problem so that Receiver Operating Characteristic (ROC) techniques can be applied. The limitations of applying this framework to chemical detection problems are discussed along with means to mitigate them. Algorithmic performance is optimized globally using robust Design of Experiments and Taguchi techniques. These methods require figures of merit to trade off between false alarms and detection probability. Several figures of merit, including the Matthews Correlation Coefficient and the Taguchi Signal-to-Noise Ratio are compared. Following the optimization of global parameters which govern the algorithm behavior across all target chemicals, ROC techniques are employed to optimize chemical-specific parameters to further improve performance.

Identification of metal ion binding sites based on amino acid sequences

PubMed Central

Cao, Xiaoyong; Zhang, Xiaojin; Gao, Sujuan; Ding, Changjiang; Feng, Yonge; Bao, Weihua

2017-01-01

The identification of metal ion binding sites is important for protein function annotation and the design of new drug molecules. This study presents an effective method of analyzing and identifying the binding residues of metal ions based solely on sequence information. Ten metal ions were extracted from the BioLip database: Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+ and Co2+. The analysis showed that Zn2+, Cu2+, Fe2+, Fe3+, and Co2+ were sensitive to the conservation of amino acids at binding sites, and promising results can be achieved using the Position Weight Scoring Matrix algorithm, with an accuracy of over 79.9% and a Matthews correlation coefficient of over 0.6. The binding sites of other metals can also be accurately identified using the Support Vector Machine algorithm with multifeature parameters as input. In addition, we found that Ca2+ was insensitive to hydrophobicity and hydrophilicity information and Mn2+ was insensitive to polarization charge information. An online server was constructed based on the framework of the proposed method and is freely available at http://60.31.198.140:8081/metal/HomePage/HomePage.html. PMID:28854211

Chaotic particle swarm optimization with mutation for classification.

PubMed

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms.

Identification of metal ion binding sites based on amino acid sequences.

PubMed

Cao, Xiaoyong; Hu, Xiuzhen; Zhang, Xiaojin; Gao, Sujuan; Ding, Changjiang; Feng, Yonge; Bao, Weihua

2017-01-01

The identification of metal ion binding sites is important for protein function annotation and the design of new drug molecules. This study presents an effective method of analyzing and identifying the binding residues of metal ions based solely on sequence information. Ten metal ions were extracted from the BioLip database: Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+ and Co2+. The analysis showed that Zn2+, Cu2+, Fe2+, Fe3+, and Co2+ were sensitive to the conservation of amino acids at binding sites, and promising results can be achieved using the Position Weight Scoring Matrix algorithm, with an accuracy of over 79.9% and a Matthews correlation coefficient of over 0.6. The binding sites of other metals can also be accurately identified using the Support Vector Machine algorithm with multifeature parameters as input. In addition, we found that Ca2+ was insensitive to hydrophobicity and hydrophilicity information and Mn2+ was insensitive to polarization charge information. An online server was constructed based on the framework of the proposed method and is freely available at http://60.31.198.140:8081/metal/HomePage/HomePage.html.

Automatic detection of atrial fibrillation in cardiac vibration signals.

PubMed

Brueser, C; Diesel, J; Zink, M D H; Winter, S; Schauerte, P; Leonhardt, S

2013-01-01

We present a study on the feasibility of the automatic detection of atrial fibrillation (AF) from cardiac vibration signals (ballistocardiograms/BCGs) recorded by unobtrusive bedmounted sensors. The proposed system is intended as a screening and monitoring tool in home-healthcare applications and not as a replacement for ECG-based methods used in clinical environments. Based on BCG data recorded in a study with 10 AF patients, we evaluate and rank seven popular machine learning algorithms (naive Bayes, linear and quadratic discriminant analysis, support vector machines, random forests as well as bagged and boosted trees) for their performance in separating 30 s long BCG epochs into one of three classes: sinus rhythm, atrial fibrillation, and artifact. For each algorithm, feature subsets of a set of statistical time-frequency-domain and time-domain features were selected based on the mutual information between features and class labels as well as first- and second-order interactions among features. The classifiers were evaluated on a set of 856 epochs by means of 10-fold cross-validation. The best algorithm (random forests) achieved a Matthews correlation coefficient, mean sensitivity, and mean specificity of 0.921, 0.938, and 0.982, respectively.

e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-learning Methods

NASA Astrophysics Data System (ADS)

Zheng, Suqing; Jiang, Mengying; Zhao, Chengwei; Zhu, Rui; Hu, Zhicheng; Xu, Yong; Lin, Fu

2018-03-01

In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypothetical non-bitterant dataset used in the previous works. Based on this experimental dataset, we harness the consensus votes from the multiple machine-learning methods (e.g., deep learning etc.) combined with the molecular fingerprint to build the bitter/bitterless classification models with five-fold cross-validation, which are further inspected by the Y-randomization test and applicability domain analysis. One of the best consensus models affords the accuracy, precision, specificity, sensitivity, F1-score, and Matthews correlation coefficient (MCC) of 0.929, 0.918, 0.898, 0.954, 0.936, and 0.856 respectively on our test set. For the automatic prediction of bitterant, a graphic program “e-Bitter” is developed for the convenience of users via the simple mouse click. To our best knowledge, it is for the first time to adopt the consensus model for the bitterant prediction and develop the first free stand-alone software for the experimental food scientist.

Predicting lysine glycation sites using bi-profile bayes feature extraction.

PubMed

Ju, Zhe; Sun, Juhe; Li, Yanjie; Wang, Li

2017-12-01

Glycation is a nonenzymatic post-translational modification which has been found to be involved in various biological processes and closely associated with many metabolic diseases. The accurate identification of glycation sites is important to understand the underlying molecular mechanisms of glycation. As the traditional experimental methods are often labor-intensive and time-consuming, it is desired to develop computational methods to predict glycation sites. In this study, a novel predictor named BPB_GlySite is proposed to predict lysine glycation sites by using bi-profile bayes feature extraction and support vector machine algorithm. As illustrated by 10-fold cross-validation, BPB_GlySite achieves a satisfactory performance with a Sensitivity of 63.68%, a Specificity of 72.60%, an Accuracy of 69.63% and a Matthew's correlation coefficient of 0.3499. Experimental results also indicate that BPB_GlySite significantly outperforms three existing glycation sites predictors: NetGlycate, PreGly and Gly-PseAAC. Therefore, BPB_GlySite can be a useful bioinformatics tool for the prediction of glycation sites. A user-friendly web-server for BPB_GlySite is established at 123.206.31.171/BPB_GlySite/. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides.

PubMed

Panwar, Bharat; Raghava, Gajendra P S

2015-04-01

The RNA-protein interactions play a diverse role in the cells, thus identification of RNA-protein interface is essential for the biologist to understand their function. In the past, several methods have been developed for predicting RNA interacting residues in proteins, but limited efforts have been made for the identification of protein-interacting nucleotides in RNAs. In order to discriminate protein-interacting and non-interacting nucleotides, we used various classifiers (NaiveBayes, NaiveBayesMultinomial, BayesNet, ComplementNaiveBayes, MultilayerPerceptron, J48, SMO, RandomForest, SMO and SVM(light)) for prediction model development using various features and achieved highest 83.92% sensitivity, 84.82 specificity, 84.62% accuracy and 0.62 Matthew's correlation coefficient by SVM(light) based models. We observed that certain tri-nucleotides like ACA, ACC, AGA, CAC, CCA, GAG, UGA, and UUU preferred in protein-interaction. All the models have been developed using a non-redundant dataset and are evaluated using five-fold cross validation technique. A web-server called RNApin has been developed for the scientific community (http://crdd.osdd.net/raghava/rnapin/). Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

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

Case Report: Rhabdomyolysis in Service Member Following SERE Physical Training

DTIC Science & Technology

2017-09-19

Member following SERE physical training. Sb. GRANT NUMBER Sc. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Capt Matthew A Pombo Se. TASK...NOTES 14. ABSTRACT Case Report: Rhabdomyolysis in Service Member following SERE physical training. Authors: Matthew A. Pombo, DO (Capt, USAF...in Service Member following SERE physical training. Authors: Matthew A. Pombo, DO (Capt, USAF); Dwaipayan Chakraborti, MD (MAJ, USA); Joseph Marcus

A Comparison of Electrolytic Capacitors and Supercapacitors for Piezo-Based Energy Harvesting

DTIC Science & Technology

2013-07-01

A Comparison of Electrolytic Capacitors and Supercapacitors for Piezo-Based Energy Harvesting by Matthew H. Ervin, Carlos M. Pereira, John R...Capacitors and Supercapacitors for Piezo-Based Energy Harvesting Matthew H. Ervin Sensors and Electronic Devices Directorate, ARL Carlos M. Pereira... Supercapacitors for Piezo-Based Energy Harvesting 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Matthew H

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Beach erosion caused by Hurricane Matthew is visible along the Atlantic shoreline at NASA’s Kennedy Space Center in Florida. Although some sections of shoreline suffered erosion, recently restored portions of beach fared well. Hurricane Matthew, a Category 3 storm, passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion.

MicroRNAfold: pre-microRNA secondary structure prediction based on modified NCM model with thermodynamics-based scoring strategy.

PubMed

Han, Dianwei; Zhang, Jun; Tang, Guiliang

2012-01-01

An accurate prediction of the pre-microRNA secondary structure is important in miRNA informatics. Based on a recently proposed model, nucleotide cyclic motifs (NCM), to predict RNA secondary structure, we propose and implement a Modified NCM (MNCM) model with a physics-based scoring strategy to tackle the problem of pre-microRNA folding. Our microRNAfold is implemented using a global optimal algorithm based on the bottom-up local optimal solutions. Our experimental results show that microRNAfold outperforms the current leading prediction tools in terms of True Negative rate, False Negative rate, Specificity, and Matthews coefficient ratio.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Plant debris caused by Hurricane Matthew is strewn across the dune line along the Atlantic shoreline at NASA’s Kennedy Space Center in Florida. Although some sections of shoreline suffered erosion, recently restored portions of beach fared well. Hurricane Matthew, a Category 3 storm, passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion.

Verification and Enhancement of VIIRS Day-Night Band (DNB) Power Outage Detection Product

NASA Technical Reports Server (NTRS)

Burke, Angela; Schultz, Lori A.; Omitaomu, Olufemi; Molthan, Andrew L.; Cole, Tony; Griffin, Robert

2017-01-01

This case study of Hurricane Matthew (October 2016) uses the NASA Short-Term Prediction Research and Transition (SPoRT) Center DNB power outage product (using GSFC VIIRS DNB preliminary Black Marble product, Roman et al.. 2017) and 2013 LandScan Global population data to look for correlations between the post-event %-of-normal radiance and the utility company-reported outage numbers (obtained from EAGLE-1).

NASA AIRS Examines Hurricane Matthew Cloud Top Temperatures

NASA Image and Video Library

2016-10-07

At 11:29 p.m. PDT on Oct. 6 (2:29 a.m. EDT on Oct. 7), NASA's Atmospheric Infrared Sounder (AIRS) instrument on NASA's Aqua satellite produced this false-color infrared image of Matthew as the storm moved up Florida's central coast. The image shows the temperature of Matthew's cloud tops or the surface of Earth in cloud-free regions, with the most intense thunderstorms shown in purples and blues. http://photojournal.jpl.nasa.gov/catalog/PIA21097

Hurricane Matthew Hits Haiti

NASA Image and Video Library

2017-12-08

Read more from: go.nasa.gov/2duxEeZ On October 4, 2016, Hurricane Matthew made landfall on southwestern Haiti as a category-4 storm—the strongest storm to hit the Caribbean nation in more than 50 years. Just hours after landfall, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image. At the time, Matthew had top sustained winds of about 230 kilometers (145 miles) per hour. Earlier on October 4, temperature data collected by MODIS on NASA’s Aqua satellite revealed that the cloud tops around Matthew were very cold (at least -57° Celsius, or -70° Fahrenheit). Cold cloud tops are known to produce heavy rainfall. The National Hurricane Center called for 380 to 500 millimeters (15 to 20 inches) of rain in Southern Haiti and in the southwestern Dominican Republic. The northward movement of the storm should bring the center of Matthew over eastern Cuba late on October 4. Dangerous conditions can extend far beyond a storm’s center. According to National Hurricane Center forecasters, Matthew is “likely to produce devastating impacts from storm surge, extreme winds, heavy rains, flash floods, and/or mudslides in portions of the watch and warning areas in Haiti, Cuba, and the Bahamas.” NASA Earth Observatory image by Joshua Stevens, using MODIS data from the Land Atmosphere Near real-time Capability for EOS (LANCE). Caption by Kathryn Hansen.

An Automatic Assessment System of Diabetic Foot Ulcers Based on Wound Area Determination, Color Segmentation, and Healing Score Evaluation.

PubMed

Wang, Lei; Pedersen, Peder C; Strong, Diane M; Tulu, Bengisu; Agu, Emmanuel; Ignotz, Ron; He, Qian

2015-08-07

For individuals with type 2 diabetes, foot ulcers represent a significant health issue. The aim of this study is to design and evaluate a wound assessment system to help wound clinics assess patients with foot ulcers in a way that complements their current visual examination and manual measurements of their foot ulcers. The physical components of the system consist of an image capture box, a smartphone for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image. The system was evaluated by assessing foot ulcers for 12 patients in the Wound Clinic at University of Massachusetts Medical School. As performance measures, the Matthews correlation coefficient (MCC) value for the wound area determination algorithm tested on 32 foot ulcer images was .68. The clinical validity of our healing score algorithm relative to the experienced clinicians was measured by Krippendorff's alpha coefficient (KAC) and ranged from .42 to .81. Our system provides a promising real-time method for wound assessment based on image analysis. Clinical comparisons indicate that the optimized mean-shift-based algorithm is well suited for wound area determination. Clinical evaluation of our healing score algorithm shows its potential to provide clinicians with a quantitative method for evaluating wound healing status. © 2015 Diabetes Technology Society.

AllergenFP: allergenicity prediction by descriptor fingerprints.

PubMed

Dimitrov, Ivan; Naneva, Lyudmila; Doytchinova, Irini; Bangov, Ivan

2014-03-15

Allergenicity, like antigenicity and immunogenicity, is a property encoded linearly and non-linearly, and therefore the alignment-based approaches are not able to identify this property unambiguously. A novel alignment-free descriptor-based fingerprint approach is presented here and applied to identify allergens and non-allergens. The approach was implemented into a four step algorithm. Initially, the protein sequences are described by amino acid principal properties as hydrophobicity, size, relative abundance, helix and β-strand forming propensities. Then, the generated strings of different length are converted into vectors with equal length by auto- and cross-covariance (ACC). The vectors were transformed into binary fingerprints and compared in terms of Tanimoto coefficient. The approach was applied to a set of 2427 known allergens and 2427 non-allergens and identified correctly 88% of them with Matthews correlation coefficient of 0.759. The descriptor fingerprint approach presented here is universal. It could be applied for any classification problem in computational biology. The set of E-descriptors is able to capture the main structural and physicochemical properties of amino acids building the proteins. The ACC transformation overcomes the main problem in the alignment-based comparative studies arising from the different length of the aligned protein sequences. The conversion of protein ACC values into binary descriptor fingerprints allows similarity search and classification. The algorithm described in the present study was implemented in a specially designed Web site, named AllergenFP (FP stands for FingerPrint). AllergenFP is written in Python, with GIU in HTML. It is freely accessible at http://ddg-pharmfac.net/Allergen FP. idoytchinova@pharmfac.net or ivanbangov@shu-bg.net.

Characterizing Changes in the Rate of Protein-Protein Dissociation upon Interface Mutation Using Hotspot Energy and Organization

PubMed Central

Agius, Rudi; Torchala, Mieczyslaw; Moal, Iain H.; Fernández-Recio, Juan; Bates, Paul A.

2013-01-01

Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearson's Correlation Coefficient of 0.79 with experimental off-rates and a Matthew's Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within hotregions, we show how the contribution of hotregions of different sizes, changes under different cooperative effects. PMID:24039569

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A construction trailer damaged by Hurricane Matthew is seen in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-13

Roofing materials, blown loose by Hurricane Matthew, are visible on the ground below the deck of the Beach House at NASA’s Kennedy Space Center in Florida. Members of the Disaster Assessment and Recovery Team (DART) are working on repairs to the facility following Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

An ice dispenser damaged by Hurricane Matthew is seen in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-13

Roofing materials, blown loose by Hurricane Matthew, lie on the ground behind the Beach House at NASA’s Kennedy Space Center in Florida. Members of the Disaster Assessment and Recovery Team (DART) are working on repairs to the facility following Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

Matthew Andersen d/b/a Andersen Painting Information Sheet

EPA Pesticide Factsheets

Matthew Andersen d/b/a Andersen Painting (the Company) is located in Omaha, Nebraska. The settlement involves renovation activities conducted on a property constructed prior to 1978, located in Bellevue, Nebraska.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A construction trailer damaged by Hurricane Matthew is seen in front of the Mobile Launcher within the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Hurricane Matthew tore away a section of wall on a support building in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A hole caused by Hurricane Matthew is visible in a section of door on the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A broken window caused by Hurricane Matthew is seen inside a support building in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Siding damage caused by Hurricane Matthew is seen inside a support building in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A small staircase, toppled and relocated by Hurricane Matthew, is seen in front of the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Ceiling and furniture damage caused by Hurricane Matthew is seen inside a support building in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A construction helmet and staircase, both relocated by Hurricane Matthew, is seen in front of the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

A novel Markov Blanket-based repeated-fishing strategy for capturing phenotype-related biomarkers in big omics data.

PubMed

Li, Hongkai; Yuan, Zhongshang; Ji, Jiadong; Xu, Jing; Zhang, Tao; Zhang, Xiaoshuai; Xue, Fuzhong

2016-03-09

We propose a novel Markov Blanket-based repeated-fishing strategy (MBRFS) in attempt to increase the power of existing Markov Blanket method (DASSO-MB) and maintain its advantages in omic data analysis. Both simulation and real data analysis were conducted to assess its performances by comparing with other methods including χ(2) test with Bonferroni and B-H adjustment, least absolute shrinkage and selection operator (LASSO) and DASSO-MB. A serious of simulation studies showed that the true discovery rate (TDR) of proposed MBRFS was always close to zero under null hypothesis (odds ratio = 1 for each SNPs) with excellent stability in all three scenarios of independent phenotype-related SNPs without linkage disequilibrium (LD) around them, correlated phenotype-related SNPs without LD around them, and phenotype-related SNPs with strong LD around them. As expected, under different odds ratio and minor allel frequency (MAFs), MBRFS always had the best performances in capturing the true phenotype-related biomarkers with higher matthews correlation coefficience (MCC) for all three scenarios above. More importantly, since proposed MBRFS using the repeated fishing strategy, it still captures more phenotype-related SNPs with minor effects when non-significant phenotype-related SNPs emerged under χ(2) test after Bonferroni multiple correction. The various real omics data analysis, including GWAS data, DNA methylation data, gene expression data and metabolites data, indicated that the proposed MBRFS always detected relatively reasonable biomarkers. Our proposed MBRFS can exactly capture the true phenotype-related biomarkers with the reduction of false negative rate when the phenotype-related biomarkers are independent or correlated, as well as the circumstance that phenotype-related biomarkers are associated with non-phenotype-related ones.

A new machine-learning method to prognosticate paraquat poisoned patients by combining coagulation, liver, and kidney indices.

PubMed

Hu, Lufeng; Li, Huaizhong; Cai, Zhennao; Lin, Feiyan; Hong, Guangliang; Chen, Huiling; Lu, Zhongqiu

2017-01-01

The prognosis of paraquat (PQ) poisoning is highly correlated to plasma PQ concentration, which has been identified as the most important index in PQ poisoning. This study investigated the predictive value of coagulation, liver, and kidney indices in prognosticating PQ-poisoning patients, when aligned with plasma PQ concentrations. Coagulation, liver, and kidney indices were first analyzed by variance analysis, receiver operating characteristic curves, and Fisher discriminant analysis. Then, a new, intelligent, machine learning-based system was established to effectively provide prognostic analysis of PQ-poisoning patients based on a combination of the aforementioned indices. In the proposed system, an enhanced extreme learning machine wrapped with a grey wolf-optimization strategy was developed to predict the risk status from a pool of 103 patients (56 males and 47 females); of these, 52 subjects were deceased and 51 alive. The proposed method was rigorously evaluated against this real-life dataset, in terms of accuracy, Matthews correlation coefficients, sensitivity, and specificity. Additionally, the feature selection was investigated to identify correlating factors for risk status. The results demonstrated that there were significant differences in the coagulation, liver, and kidney indices between deceased and surviving subjects (p<0.05). Aspartate aminotransferase, prothrombin time, prothrombin activity, total bilirubin, direct bilirubin, indirect bilirubin, alanine aminotransferase, urea nitrogen, and creatinine were the most highly correlated indices in PQ poisoning and showed statistical significance (p<0.05) in predicting PQ-poisoning prognoses. According to the feature selection, the most important correlated indices were found to be associated with aspartate aminotransferase, the aspartate aminotransferase to alanine ratio, creatinine, prothrombin time, and prothrombin activity. The method proposed here showed excellent results that were better than that produced based on blood-PQ concentration alone. These promising results indicated that the combination of these indices can provide a new avenue for prognosticating the outcome of PQ poisoning.

Matthew Reynolds | NREL

Science.gov Websites

food science. Matthew's research at NREL is focused on applying uncertainty quantification techniques . Research Interests Uncertainty quantification Computational multilinear algebra Approximation theory of and the Canonical Tensor Decomposition, Journal of Computational Physics (2017) Randomized Alternating

Publications - GMC 346 | Alaska Division of Geological & Geophysical

Science.gov Websites

'-4357.7') in Milne Point Unit SB #B-02 well Authors: Lowe, Steve, and Matthews, Susan Publication Date Bibliographic Reference Lowe, Steve, and Matthews, Susan, 2007, Palynological data package for cored Ugnu

The public health planners' perfect storm: Hurricane Matthew and Zika virus.

PubMed

Ahmed, Qanta A; Memish, Ziad A

Hurricane Matthew threatened to be one of the most powerful Hurricanes to hit the United States in a century. Fortunately, it avoided making landfall on Florida, the eye of the Hurricane remaining centered 40 miles off the Florida coast. Even so it has resulted in over $7 Billion USD in damage according to initial estimates with much of the damage ongoing in severe flooding. Response to and recovery from Hurricane Matthew challenged Florida's public health services and resources just as emergency Zika-specific congressional funding to combat Zika outbreaks in Florida had become available. Hurricanes can disrupt the urban environment in a way that increases the likelihood of vector-borne illnesses and their aftermath can severely strain the very infectious disease and infection control academe needed to combat vector-borne outbreaks. This commentary attempts to examine the challenges posed by Hurricane Matthew in Florida's efforts to contain Zika. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of helix capping and β-turn motifs from NMR chemical shifts

PubMed Central

Shen, Yang; Bax, Ad

2012-01-01

We present an empirical method for identification of distinct structural motifs in proteins on the basis of experimentally determined backbone and 13Cβ chemical shifts. Elements identified include the N-terminal and C-terminal helix capping motifs and five types of β-turns: I, II, I′, II′ and VIII. Using a database of proteins of known structure, the NMR chemical shifts, together with the PDB-extracted amino acid preference of the helix capping and β-turn motifs are used as input data for training an artificial neural network algorithm, which outputs the statistical probability of finding each motif at any given position in the protein. The trained neural networks, contained in the MICS (motif identification from chemical shifts) program, also provide a confidence level for each of their predictions, and values ranging from ca 0.7–0.9 for the Matthews correlation coefficient of its predictions far exceed that attainable by sequence analysis. MICS is anticipated to be useful both in the conventional NMR structure determination process and for enhancing on-going efforts to determine protein structures solely on the basis of chemical shift information, where it can aid in identifying protein database fragments suitable for use in building such structures. PMID:22314702

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

PubMed

Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

2017-02-01

Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

Combined QSAR and molecule docking studies on predicting P-glycoprotein inhibitors

NASA Astrophysics Data System (ADS)

Tan, Wen; Mei, Hu; Chao, Li; Liu, Tengfei; Pan, Xianchao; Shu, Mao; Yang, Li

2013-12-01

P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter. The over expression of P-gp leads to the development of multidrug resistance (MDR), which is a major obstacle to effective treatment of cancer. Thus, designing effective P-gp inhibitors has an extremely important role in the overcoming MDR. In this paper, both ligand-based quantitative structure-activity relationship (QSAR) and receptor-based molecular docking are used to predict P-gp inhibitors. The results show that each method achieves good prediction performance. According to the results of tenfold cross-validation, an optimal linear SVM model with only three descriptors is established on 857 training samples, of which the overall accuracy (Acc), sensitivity, specificity, and Matthews correlation coefficient are 0.840, 0.873, 0.813, and 0.683, respectively. The SVM model is further validated by 418 test samples with the overall Acc of 0.868. Based on a homology model of human P-gp established, Surflex-dock is also performed to give binding free energy-based evaluations with the overall accuracies of 0.823 for the test set. Furthermore, a consensus evaluation is also performed by using these two methods. Both QSAR and molecular docking studies indicate that molecular volume, hydrophobicity and aromaticity are three dominant factors influencing the inhibitory activities.

Chaotic Particle Swarm Optimization with Mutation for Classification

PubMed Central

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms. PMID:25709937

Discrimination of Active and Weakly Active Human BACE1 Inhibitors Using Self-Organizing Map and Support Vector Machine.

PubMed

Li, Hang; Wang, Maolin; Gong, Ya-Nan; Yan, Aixia

2016-01-01

β-secretase (BACE1) is an aspartyl protease, which is considered as a novel vital target in Alzheimer`s disease therapy. We collected a data set of 294 BACE1 inhibitors, and built six classification models to discriminate active and weakly active inhibitors using Kohonen's Self-Organizing Map (SOM) method and Support Vector Machine (SVM) method. Each molecular descriptor was calculated using the program ADRIANA.Code. We adopted two different methods: random method and Self-Organizing Map method, for training/test set split. The descriptors were selected by F-score and stepwise linear regression analysis. The best SVM model Model2C has a good prediction performance on test set with prediction accuracy, sensitivity (SE), specificity (SP) and Matthews correlation coefficient (MCC) of 89.02%, 90%, 88%, 0.78, respectively. Model 1A is the best SOM model, whose accuracy and MCC of the test set were 94.57% and 0.98, respectively. The lone pair electronegativity and polarizability related descriptors importantly contributed to bioactivity of BACE1 inhibitor. The Extended-Connectivity Finger-Prints_4 (ECFP_4) analysis found some vitally key substructural features, which could be helpful for further drug design research. The SOM and SVM models built in this study can be obtained from the authors by email or other contacts.

A retrospective metagenomics approach to studying Blastocystis.

PubMed

Andersen, Lee O'Brien; Bonde, Ida; Nielsen, Henrik Bjørn; Stensvold, Christen Rune

2015-07-01

Blastocystis is a common single-celled intestinal parasitic genus, comprising several subtypes. Here, we screened data obtained by metagenomic analysis of faecal DNA for Blastocystis by searching for subtype-specific genes in coabundance gene groups, which are groups of genes that covary across a selection of 316 human faecal samples, hence representing genes originating from a single subtype. The 316 faecal samples were from 236 healthy individuals, 13 patients with Crohn's disease (CD) and 67 patients with ulcerative colitis (UC). The prevalence of Blastocystis was 20.3% in the healthy individuals and 14.9% in patients with UC. Meanwhile, Blastocystis was absent in patients with CD. Individuals with intestinal microbiota dominated by Bacteroides were much less prone to having Blastocystis-positive stool (Matthew's correlation coefficient = -0.25, P < 0.0001) than individuals with Ruminococcus- and Prevotella-driven enterotypes. This is the first study to investigate the relationship between Blastocystis and communities of gut bacteria using a metagenomics approach. The study serves as an example of how it is possible to retrospectively investigate microbial eukaryotic communities in the gut using metagenomic datasets targeting the bacterial component of the intestinal microbiome and the interplay between these microbial communities. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest.

PubMed

Manavalan, Balachandran; Shin, Tae Hwan; Lee, Gwang

2018-01-05

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at: http://www.thegleelab.org/DHSpred.html.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest

PubMed Central

Manavalan, Balachandran; Shin, Tae Hwan; Lee, Gwang

2018-01-01

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at: http://www.thegleelab.org/DHSpred.html PMID:29416743

OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

PubMed

Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

2017-03-01

Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

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

PubMed

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.

Prediction of lysine glutarylation sites by maximum relevance minimum redundancy feature selection.

PubMed

Ju, Zhe; He, Jian-Jun

2018-06-01

Lysine glutarylation is new type of protein acylation modification in both prokaryotes and eukaryotes. To better understand the molecular mechanism of glutarylation, it is important to identify glutarylated substrates and their corresponding glutarylation sites accurately. In this study, a novel bioinformatics tool named GlutPred is developed to predict glutarylation sites by using multiple feature extraction and maximum relevance minimum redundancy feature selection. On the one hand, amino acid factors, binary encoding, and the composition of k-spaced amino acid pairs features are incorporated to encode glutarylation sites. And the maximum relevance minimum redundancy method and the incremental feature selection algorithm are adopted to remove the redundant features. On the other hand, a biased support vector machine algorithm is used to handle the imbalanced problem in glutarylation sites training dataset. As illustrated by 10-fold cross-validation, the performance of GlutPred achieves a satisfactory performance with a Sensitivity of 64.80%, a Specificity of 76.60%, an Accuracy of 74.90% and a Matthew's correlation coefficient of 0.3194. Feature analysis shows that some k-spaced amino acid pair features play the most important roles in the prediction of glutarylation sites. The conclusions derived from this study might provide some clues for understanding the molecular mechanisms of glutarylation. Copyright © 2018 Elsevier Inc. All rights reserved.

Markovian negentropies in bioinformatics. 1. A picture of footprints after the interaction of the HIV-1 Psi-RNA packaging region with drugs.

PubMed

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

Many experts worldwide have highlighted the potential of RNA molecules as drug targets for the chemotherapeutic treatment of a range of diseases. In particular, the molecular pockets of RNA in the HIV-1 packaging region have been postulated as promising sites for antiviral action. The discovery of simpler methods to accurately represent drug-RNA interactions could therefore become an interesting and rapid way to generate models that are complementary to docking-based systems. The entropies of a vibrational Markov chain have been introduced here as physically meaningful descriptors for the local drug-nucleic acid complexes. A study of the interaction of the antibiotic Paromomycin with the packaging region of the RNA present in type-1 HIV has been carried out as an illustrative example of this approach. A linear discriminant function gave rise to excellent discrimination among 80.13% of interacting/non-interacting sites. More specifically, the model classified 36/45 nucleotides (80.0%) that interacted with paromomycin and, in addition, 85/106 (80.2%) footprinted (non-interacting) sites from the RNA viral sequence were recognized. The model showed a high Matthews' regression coefficient (C = 0.64). The Jackknife method was also used to assess the stability and predictability of the model by leaving out adenines, C, G, or U. Matthews' coefficients and overall accuracies for these approaches were between 0.55 and 0.68 and 75.8 and 82.7, respectively. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the aforementioned antibiotic (R2 = 0.83,Q2 = 0.825). These kinds of models may play an important role either in the discovery of new anti-HIV compounds or in the elucidation of their mode of action. On request from the corresponding author (humbertogd@cbq.uclv.edu.cu or humbertogd@navegalia.com).

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A damaged construction trailer and several pieces of associated debris, aftermath of Hurricane Matthew, are seen in front of the Mobile Launcher in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

A damaged construction trailer and several pieces of associated debris, aftermath of Hurricane Matthew, are seen near the Mobile Launcher in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Damaged construction trailers and several pieces of associated debris, aftermath of Hurricane Matthew, are seen in front of the Mobile Launcher in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs are in progress at various structures and facilities across the spaceport, part of the ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

Expression, purification, crystallization and preliminary X-ray studies of Vibrio cholerae pseudopilin EpsH

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

Raghunathan, Kannan; Vago, Frank S.; Ball, Terry

2010-01-12

EpsH is a minor pseudopilin protein of the Vibrio cholerae type II secretion system. A truncated form of EpsH with a C-terminal noncleavable His tag was constructed and expressed in Escherichia coli, purified and crystallized by sitting-drop vapor diffusion. A complete data set was collected to 1.71 {angstrom} resolution. The crystals belonged to space group P2{sub 1}2{sub 1}2{sub 1}, with unit-cell parameters a = 53.39, b = 71.11, c = 84.64 {angstrom}. There were two protein molecules in the asymmetric unit, which gave a Matthews coefficient V{sub M} of 2.1 {angstrom}{sup 3} Da{sup -1}, corresponding to 41.5% solvent content.

Chain mapping approach of Hamiltonian for FMO complex using associated, generalized and exceptional Jacobi polynomials

NASA Astrophysics Data System (ADS)

Mahdian, M.; Arjmandi, M. B.; Marahem, F.

2016-06-01

The excitation energy transfer (EET) in photosynthesis complex has been widely investigated in recent years. However, one of the main problems is simulation of this complex under realistic condition. In this paper by using the associated, generalized and exceptional Jacobi polynomials, firstly, we introduce the spectral density of Fenna-Matthews-Olson (FMO) complex. Afterward, we obtain a map that transforms the Hamiltonian of FMO complex as an open quantum system to a one-dimensional chain of oscillatory modes with only nearest neighbor interaction in which the system is coupled only to first mode of chain. The frequency and coupling strength of each mode can be analytically obtained from recurrence coefficient of mentioned orthogonal polynomials.

Hurricane Matthew over Haiti seen by NASA MISR

NASA Image and Video Library

2016-10-04

On the morning of October 4, 2016, Hurricane Matthew passed over the island nation of Haiti. A Category 4 storm, it made landfall around 7 a.m. local time (5 a.m. PDT/8 a.m. EDT) with sustained winds over 145 mph. This is the strongest hurricane to hit Haiti in over 50 years. On October 4, at 10:30 a.m. local time (8:30 a.m. PDT/11:30 a.m. EDT), the Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard NASA's Terra satellite passed over Hurricane Matthew. This animation was made from images taken by MISR's downward-pointing (nadir) camera is 235 miles (378 kilometers) across, which is much narrower than the massive diameter of Matthew, so only the hurricane's eye and a portion of the storm's right side are visible. Haiti is completely obscured by Matthew's clouds, but part of the Bahamas is visible to the north. Several hot towers are visible within the central part of the storm, and another at the top right of the image. Hot towers are enormous thunderheads that punch through the tropopause (the boundary between the lowest layer of the atmosphere, the troposphere, and the next level, the stratosphere). The rugged topography of Haiti causes uplift within the storm, generating these hot towers and fueling even more rain than Matthew would otherwise dump on the country. MISR has nine cameras fixed at different angles, which capture images of the same point on the ground within about seven minutes. This animation was created by blending images from these nine cameras. The change in angle between the images causes a much larger motion from south to north than actually exists, but the rotation of the storm is real motion. From this animation, you can get an idea of the incredible height of the hot towers, especially the one to the upper right. The counter-clockwise rotation of Matthew around its closed (cloudy) eye is also visible. These data were acquired during Terra orbit 89345. An animation is available at http://photojournal.jpl.nasa.gov/catalog/PIA21070

76 FR 7584 - Matthews International Corporation, Bronze Division, Kingwood, WV; Notice of Affirmative...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-10

... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-72,953] Matthews International Corporation, Bronze Division, Kingwood, WV; Notice of Affirmative Determination Regarding Application for.... Conclusion After careful review of the application, I conclude that the claim is of sufficient weight to...

Matthew Arnold and Minimal Competency Testing.

ERIC Educational Resources Information Center

Tuman, Myron C.

1979-01-01

Presents arguments by Robert Lowe and Matthew Arnold on the 19th century British "Payment by Results" Plan, whereby schools received funds for students who passed minimal competency tests. Emphasizes that the Victorian experience produced acrimonious teachers with low morale and encourages contemporary minimal testing advocates not to…

Quantitative and empirical demonstration of the Matthew effect in a study of career longevity

PubMed Central

Petersen, Alexander M.; Jung, Woo-Sung; Yang, Jae-Suk; Stanley, H. Eugene

2011-01-01

The Matthew effect refers to the adage written some two-thousand years ago in the Gospel of St. Matthew: “For to all those who have, more will be given.” Even two millennia later, this idiom is used by sociologists to qualitatively describe the dynamics of individual progress and the interplay between status and reward. Quantitative studies of professional careers are traditionally limited by the difficulty in measuring progress and the lack of data on individual careers. However, in some professions, there are well-defined metrics that quantify career longevity, success, and prowess, which together contribute to the overall success rating for an individual employee. Here we demonstrate testable evidence of the age-old Matthew “rich get richer” effect, wherein the longevity and past success of an individual lead to a cumulative advantage in further developing his or her career. We develop an exactly solvable stochastic career progress model that quantitatively incorporates the Matthew effect and validate our model predictions for several competitive professions. We test our model on the careers of 400,000 scientists using data from six high-impact journals and further confirm our findings by testing the model on the careers of more than 20,000 athletes in four sports leagues. Our model highlights the importance of early career development, showing that many careers are stunted by the relative disadvantage associated with inexperience. PMID:21173276

Operationalization of Burnout.

ERIC Educational Resources Information Center

Matthews, Doris B.

This study was designed to develop instruments to measure employee burnout. The Matthews Burnout Scale for Employees is a 50-item self-report measure. The Matthews Burnout Scale for Supervisors is a 50-item scale for use in evaluating employee burnout. Content-based items were tested for construct validity with a group of employees, and their…

76 FR 9381 - Notice of Availability of Interim Staff Guidance Documents for Spent Fuel Storage Casks

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-17

.... FOR FURTHER INFORMATION CONTACT: Matthew Gordon, Structural Mechanics and Materials Branch, Division... a fee. Comments and questions on ISG-23 should be directed to Matthew Gordon, Structural Mechanics..., 2011. For the U.S. Nuclear Regulatory Commission. Michele Sampson, Acting Chief, Structural Mechanics...

Reducing the Matthew Effect: Lessons from the "ExCELL" Head Start Intervention

ERIC Educational Resources Information Center

Hindman, Annemarie H.; Erhart, Amber C.; Wasik, Barbara A.

2012-01-01

Evidence shows that the Matthew effect is a persistent problem among early education interventions. The current study examined the degree to which the "ExCELL" ("Ex"ceptional "C"oaching for "E"arly "L"anguage and "L"iteracy) language and literacy professional development intervention for…

JPL HAMSR Takes Hurricane Matthew Temperature

NASA Image and Video Library

2016-10-07

JPL's High-Altitude Monolithic Microwave Integrated Circuit Sounding Radiometer (HAMSR) instrument captured this look inside Hurricane Matthew's spiral clouds on Oct. 7, 2016, flying on a NASA Global Hawk unmanned aircraft. Red colors show cloud bands without precipitation; blues show rain bands. http://photojournal.jpl.nasa.gov/catalog/PIA21093

Hurricane Matthew Damage Assessment

NASA Image and Video Library

2016-10-08

An aerial survey of NASA's Kennedy Space Center in Florida was conducted after Hurricane Matthew hit the Space Coast area. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Plant debris left behind by Hurricane Matthew covers a stretch of the NASA Railroad at Kennedy Space Center in Florida. A portion of the line near the ocean was used during the Apollo era, although some portions were used to deliver commodities to the nearby Cape Canaveral Air Force Station through the end of the Titan program. NASA determined it was financially and ecologically advantageous to leave the tracks in place. Hurricane Matthew, a Category 3 storm, passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Erosion caused by Hurricane Matthew has worn away sections of the ground beneath the NASA Railroad at Kennedy Space Center in Florida. A portion of the line near the ocean was used during the Apollo era, although some portions were used to deliver commodities to the nearby Cape Canaveral Air Force Station through the end of the Titan program. NASA determined it was financially and ecologically advantageous to leave the tracks in place. Hurricane Matthew, a Category 3 storm, passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

New Directions for Higher Education: Q&A with Matthew Sigelman on Reading the Labor Market

ERIC Educational Resources Information Center

DiSalvio, Philip

2014-01-01

In April 2013, "NEJHE" launched its "New Directions for Higher Education" series to examine emerging issues, trends and ideas that have an impact on higher education policies, programs and practices. In this installment, DiSalvio interviews Matthew Sigelman, CEO of Burning Glass Technologies, a Boston-based labor market…

78 FR 52784 - National Register of Historic Places; Notification of Pending Nominations and Related Actions

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-26

... MPS) Roughly bounded by Freeman St., Illinois Rd., W. Jefferson & Portage Blvds., Lindenwood & Ardmore...) Roughly bounded by W. 5th, 8th & 7th Aves., Cleveland & Roosevelt Sts., gary, 13000722 Jefferson Street... County Matthews Stone Company Historic District, 6293 N. Matthews Dr., 6445 W. Maple Grove Rd...

"The Philosophy of Childhood," by Gareth B. Matthews. Book Review.

ERIC Educational Resources Information Center

Palermo, James

1998-01-01

Asserts that this text by Matthews is a remedy to the scant attention paid to philosophical questioning by children. Describes the book's attempt to set children's philosophical questions against a re-examination of children's art and literature, legal issues regarding children's autonomy, and psychological models of the child's cognitive and…

Electrical Transport Properties of Polycrystalline Monolayer Molybdenum Disulfide

DTIC Science & Technology

2014-07-14

Lou, Sina Najmaei, Matin Amani, Matthew L. Chin, Zheng Se. TASK NUMBER Liu Sf. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAMES AND ADDRESSES 8...Transport Properties of Polycrystalline Monolayer Molybdenum Disulfide Sina Najmaei,t.§ Matin Ama ni,M Matthew L. Chin,* Zhe ng liu/ ·"·v: A. Gle n

Evaluating Effects of Pump-Storage Water Withdrawals Using an Individual-Based Metapopulation Model of a Benthic Fish Species

DTIC Science & Technology

2011-04-01

Bunn S. E. and Arthington A.H. 2002. Basic principles and ecological consequences of altered flow regimes on aquatic biodiversity . Environmental...cycling in streams: can fish create biogeochemical hotspots ? Ecology 89: 2335-2346. Matthews W.J. and Marsh-Matthews E. 2003. Effects of drought on

The Influence of Reading on Vocabulary Growth: A Case for a Matthew Effect

ERIC Educational Resources Information Center

Duff, Dawna; Tomblin, J. Bruce; Catts, Hugh

2015-01-01

Purpose: Individual differences in vocabulary development may affect academic or social opportunities. It has been proposed that individual differences in word reading could affect the rate of vocabulary growth, mediated by the amount of reading experience, a process referred to as a "Matthew effect" (Stanovich, 1986). Method: In the…

Monitoring storm tide and flooding from Hurricane Matthew along the Atlantic coast of the United States, October 2016

USGS Publications Warehouse

Frantz, Eric R.; Byrne,, Michael L.; Caldwell, Andral W.; Harden, Stephen L.

2017-11-02

IntroductionHurricane Matthew moved adjacent to the coasts of Florida, Georgia, South Carolina, and North Carolina. The hurricane made landfall once near McClellanville, South Carolina, on October 8, 2016, as a Category 1 hurricane on the Saffir-Simpson Hurricane Wind Scale. The U.S. Geological Survey (USGS) deployed a temporary monitoring network of storm-tide sensors at 284 sites along the Atlantic coast from Florida to North Carolina to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Matthew. Storm tide, as defined by the National Oceanic and Atmospheric Administration, is the water-level rise generated by a combination of storm surge and astronomical tide during a coastal storm.The deployment for Hurricane Matthew was the largest deployment of storm-tide sensors in USGS history and was completed as part of a coordinated Federal emergency response as outlined by the Stafford Act (Public Law 92–288, 42 U.S.C. 5121–5207) under a directed mission assignment by the Federal Emergency Management Agency. In total, 543 high-water marks (HWMs) also were collected after Hurricane Matthew, and this was the second largest HWM recovery effort in USGS history after Hurricane Sandy in 2012.During the hurricane, real-time water-level data collected at temporary rapid deployment gages (RDGs) and long-term USGS streamgage stations were relayed immediately for display on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#MatthewOctober2016). These data provided emergency managers and responders with critical information for tracking flood-effected areas and directing assistance to effected communities. Data collected from this hurricane can be used to calibrate and evaluate the performance of storm-tide models for maximum and incremental water level and flood extent, and the site-specific effects of storm tide on natural and anthropogenic features of the environment.

Retinal blood vessel segmentation in high resolution fundus photographs using automated feature parameter estimation

NASA Astrophysics Data System (ADS)

Orlando, José Ignacio; Fracchia, Marcos; del Río, Valeria; del Fresno, Mariana

2017-11-01

Several ophthalmological and systemic diseases are manifested through pathological changes in the properties and the distribution of the retinal blood vessels. The characterization of such alterations requires the segmentation of the vasculature, which is a tedious and time-consuming task that is infeasible to be performed manually. Numerous attempts have been made to propose automated methods for segmenting the retinal vasculature from fundus photographs, although their application in real clinical scenarios is usually limited by their ability to deal with images taken at different resolutions. This is likely due to the large number of parameters that have to be properly calibrated according to each image scale. In this paper we propose to apply a novel strategy for automated feature parameter estimation, combined with a vessel segmentation method based on fully connected conditional random fields. The estimation model is learned by linear regression from structural properties of the images and known optimal configurations, that were previously obtained for low resolution data sets. Our experiments in high resolution images show that this approach is able to estimate appropriate configurations that are suitable for performing the segmentation task without requiring to re-engineer parameters. Furthermore, our combined approach reported state of the art performance on the benchmark data set HRF, as measured in terms of the F1-score and the Matthews correlation coefficient.

Using support vector machine to predict beta- and gamma-turns in proteins.

PubMed

Hu, Xiuzhen; Li, Qianzhong

2008-09-01

By using the composite vector with increment of diversity, position conservation scoring function, and predictive secondary structures to express the information of sequence, a support vector machine (SVM) algorithm for predicting beta- and gamma-turns in the proteins is proposed. The 426 and 320 nonhomologous protein chains described by Guruprasad and Rajkumar (Guruprasad and Rajkumar J. Biosci 2000, 25,143) are used for training and testing the predictive model of the beta- and gamma-turns, respectively. The overall prediction accuracy and the Matthews correlation coefficient in 7-fold cross-validation are 79.8% and 0.47, respectively, for the beta-turns. The overall prediction accuracy in 5-fold cross-validation is 61.0% for the gamma-turns. These results are significantly higher than the other algorithms in the prediction of beta- and gamma-turns using the same datasets. In addition, the 547 and 823 nonhomologous protein chains described by Fuchs and Alix (Fuchs and Alix Proteins: Struct Funct Bioinform 2005, 59, 828) are used for training and testing the predictive model of the beta- and gamma-turns, and better results are obtained. This algorithm may be helpful to improve the performance of protein turns' prediction. To ensure the ability of the SVM method to correctly classify beta-turn and non-beta-turn (gamma-turn and non-gamma-turn), the receiver operating characteristic threshold independent measure curves are provided. (c) 2008 Wiley Periodicals, Inc.

Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning.

PubMed

Liu, Bin; Wang, Shanyi; Dong, Qiwen; Li, Shumin; Liu, Xuan

2016-04-20

DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. With the rapid development of next generation of sequencing technique, the number of protein sequences is unprecedentedly increasing. Thus it is necessary to develop computational methods to identify the DNA-binding proteins only based on the protein sequence information. In this study, a novel method called iDNA-KACC is presented, which combines the Support Vector Machine (SVM) and the auto-cross covariance transformation. The protein sequences are first converted into profile-based protein representation, and then converted into a series of fixed-length vectors by the auto-cross covariance transformation with Kmer composition. The sequence order effect can be effectively captured by this scheme. These vectors are then fed into Support Vector Machine (SVM) to discriminate the DNA-binding proteins from the non DNA-binding ones. iDNA-KACC achieves an overall accuracy of 75.16% and Matthew correlation coefficient of 0.5 by a rigorous jackknife test. Its performance is further improved by employing an ensemble learning approach, and the improved predictor is called iDNA-KACC-EL. Experimental results on an independent dataset shows that iDNA-KACC-EL outperforms all the other state-of-the-art predictors, indicating that it would be a useful computational tool for DNA binding protein identification. .

A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.

PubMed

Flores, David I; Sotelo-Mundo, Rogerio R; Brizuela, Carlos A

2014-01-01

The automatic identification of catalytic residues still remains an important challenge in structural bioinformatics. Sequence-based methods are good alternatives when the query shares a high percentage of identity with a well-annotated enzyme. However, when the homology is not apparent, which occurs with many structures from the structural genome initiative, structural information should be exploited. A local structural comparison is preferred to a global structural comparison when predicting functional residues. CMASA is a recently proposed method for predicting catalytic residues based on a local structure comparison. The method achieves high accuracy and a high value for the Matthews correlation coefficient. However, point substitutions or a lack of relevant data strongly affect the performance of the method. In the present study, we propose a simple extension to the CMASA method to overcome this difficulty. Extensive computational experiments are shown as proof of concept instances, as well as for a few real cases. The results show that the extension performs well when the catalytic site contains mutated residues or when some residues are missing. The proposed modification could correctly predict the catalytic residues of a mutant thymidylate synthase, 1EVF. It also successfully predicted the catalytic residues for 3HRC despite the lack of information for a relevant side chain atom in the PDB file.

Determination of protein folding kinetic types using sequence and predicted secondary structure and solvent accessibility.

PubMed

Zhang, Hua; Zhang, Tuo; Gao, Jianzhao; Ruan, Jishou; Shen, Shiyi; Kurgan, Lukasz

2012-01-01

Proteins fold through a two-state (TS), with no visible intermediates, or a multi-state (MS), via at least one intermediate, process. We analyze sequence-derived factors that determine folding types by introducing a novel sequence-based folding type predictor called FOKIT. This method implements a logistic regression model with six input features which hybridize information concerning amino acid composition and predicted secondary structure and solvent accessibility. FOKIT provides predictions with average Matthews correlation coefficient (MCC) between 0.58 and 0.91 measured using out-of-sample tests on four benchmark datasets. These results are shown to be competitive or better than results of four modern predictors. We also show that FOKIT outperforms these methods when predicting chains that share low similarity with the chains used to build the model, which is an important advantage given the limited number of annotated chains. We demonstrate that inclusion of solvent accessibility helps in discrimination of the folding kinetic types and that three of the features constitute statistically significant markers that differentiate TS and MS folders. We found that the increased content of exposed Trp and buried Leu are indicative of the MS folding, which implies that the exposure/burial of certain hydrophobic residues may play important role in the formation of the folding intermediates. Our conclusions are supported by two case studies.

New antitrichomonal drug-like chemicals selected by bond (edge)-based TOMOCOMD-CARDD descriptors.

PubMed

Meneses-Marcel, Alfredo; Rivera-Borroto, Oscar M; Marrero-Ponce, Yovani; Montero, Alina; Machado Tugores, Yanetsy; Escario, José Antonio; Gómez Barrio, Alicia; Montero Pereira, David; Nogal, Juan José; Kouznetsov, Vladimir V; Ochoa Puentes, Cristian; Bohórquez, Arnold R; Grau, Ricardo; Torrens, Francisco; Ibarra-Velarde, Froylán; Arán, Vicente J

2008-09-01

Bond-based quadratic indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis (LDA) were used to discover novel lead trichomonacidals. The obtained LDA-based quantitative structure-activity relationships (QSAR) models, using nonstochastic and stochastic indices, were able to classify correctly 87.91% (87.50%) and 89.01% (84.38%) of the chemicals in training (test) sets, respectively. They showed large Matthews correlation coefficients of 0.75 (0.71) and 0.78 (0.65) for the training (test) sets, correspondingly. Later, both models were applied to the virtual screening of 21 chemicals to find new lead antitrichomonal agents. Predictions agreed with experimental results to a great extent because a correct classification for both models of 95.24% (20 of 21) of the chemicals was obtained. Of the 21 compounds that were screened and synthesized, 2 molecules (chemicals G-1, UC-245) showed high to moderate cytocidal activity at the concentration of 10 microg/ml, another 2 compounds (G-0 and CRIS-148) showed high cytocidal activity only at the concentration of 100 microg/ml, and the remaining chemicals (from CRIS-105 to CRIS-153, except CRIS-148) were inactive at these assayed concentrations. Finally, the best candidate, G-1 (cytocidal activity of 100% at 10 microg/ml) was in vivo assayed in ovariectomized Wistar rats achieving promising results as a trichomonacidal drug-like compound.

Development and Comparison of hERG Blocker Classifiers: Assessment on Different Datasets Yields Markedly Different Results.

PubMed

Marchese Robinson, Richard L; Glen, Robert C; Mitchell, John B O

2011-05-16

In recent years, considerable effort has been invested in the development of classification models for prospective hERG inhibitors, due to the implications of hERG blockade for cardiotoxicity and the low throughput of functional hERG assays. We present novel approaches for binary classification which seek to separate strong inhibitors (IC50 <1 µM) from 'non-blockers' exhibiting moderate (1-10 µM) or weak (IC50 ≥10 µM) inhibition, as required by the pharmaceutical industry. Our approaches are based on (discretized) 2D descriptors, selected using Winnow, with additional models generated using Random Forest (RF) and Support Vector Machines (SVMs). We compare our models to those previously developed by Thai and Ecker and by Dubus et al. The purpose of this paper is twofold: 1. To propose that our approaches (with Matthews Correlation Coefficients from 0.40 to 0.87 on truly external test sets, when extrapolation beyond the applicability domain was not evident and sufficient quantities of data were available for training) are competitive with those currently proposed in the literature. 2. To highlight key issues associated with building and assessing truly predictive models, in particular the considerable variation in model performance when training and testing on different datasets. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Models for H₃ receptor antagonist activity of sulfonylurea derivatives.

PubMed

Khatri, Naveen; Madan, A K

2014-03-01

The histamine H₃ receptor has been perceived as an auspicious target for the treatment of various central and peripheral nervous system diseases. In present study, a wide variety of 60 2D and 3D molecular descriptors (MDs) were successfully utilized for the development of models for the prediction of antagonist activity of sulfonylurea derivatives for histamine H₃ receptors. Models were developed through decision tree (DT), random forest (RF) and moving average analysis (MAA). Dragon software version 6.0.28 was employed for calculation of values of diverse MDs of each analogue involved in the data set. The DT classified and correctly predicted the input data with an impressive non-error rate of 94% in the training set and 82.5% during cross validation. RF correctly classified the analogues into active and inactive with a non-error rate of 79.3%. The MAA based models predicted the antagonist histamine H₃ receptor activity with non-error rate up to 90%. Active ranges of the proposed MAA based models not only exhibited high potency but also showed improved safety as indicated by relatively high values of selectivity index. The statistical significance of the models was assessed through sensitivity, specificity, non-error rate, Matthew's correlation coefficient and intercorrelation analysis. Proposed models offer vast potential for providing lead structures for development of potent but safe H₃ receptor antagonist sulfonylurea derivatives. Copyright © 2013 Elsevier Inc. All rights reserved.

The prediction of palmitoylation site locations using a multiple feature extraction method.

PubMed

Shi, Shao-Ping; Sun, Xing-Yu; Qiu, Jian-Ding; Suo, Sheng-Bao; Chen, Xiang; Huang, Shu-Yun; Liang, Ru-Ping

2013-03-01

As an extremely important and ubiquitous post-translational lipid modification, palmitoylation plays a significant role in a variety of biological and physiological processes. Unlike other lipid modifications, protein palmitoylation and depalmitoylation are highly dynamic and can regulate both protein function and localization. The dynamic nature of palmitoylation is poorly understood because of the limitations in current assay methods. The in vivo or in vitro experimental identification of palmitoylation sites is both time consuming and expensive. Due to the large volume of protein sequences generated in the post-genomic era, it is extraordinarily important in both basic research and drug discovery to rapidly identify the attributes of a new protein's palmitoylation sites. In this work, a new computational method, WAP-Palm, combining multiple feature extraction, has been developed to predict the palmitoylation sites of proteins. The performance of the WAP-Palm model is measured herein and was found to have a sensitivity of 81.53%, a specificity of 90.45%, an accuracy of 85.99% and a Matthews correlation coefficient of 72.26% in 10-fold cross-validation test. The results obtained from both the cross-validation and independent tests suggest that the WAP-Palm model might facilitate the identification and annotation of protein palmitoylation locations. The online service is available at http://bioinfo.ncu.edu.cn/WAP-Palm.aspx. Copyright © 2013 Elsevier Inc. All rights reserved.

GASS-WEB: a web server for identifying enzyme active sites based on genetic algorithms.

PubMed

Moraes, João P A; Pappa, Gisele L; Pires, Douglas E V; Izidoro, Sandro C

2017-07-03

Enzyme active sites are important and conserved functional regions of proteins whose identification can be an invaluable step toward protein function prediction. Most of the existing methods for this task are based on active site similarity and present limitations including performing only exact matches on template residues, template size restraints, despite not being capable of finding inter-domain active sites. To fill this gap, we proposed GASS-WEB, a user-friendly web server that uses GASS (Genetic Active Site Search), a method based on an evolutionary algorithm to search for similar active sites in proteins. GASS-WEB can be used under two different scenarios: (i) given a protein of interest, to match a set of specific active site templates; or (ii) given an active site template, looking for it in a database of protein structures. The method has shown to be very effective on a range of experiments and was able to correctly identify >90% of the catalogued active sites from the Catalytic Site Atlas. It also managed to achieve a Matthew correlation coefficient of 0.63 using the Critical Assessment of protein Structure Prediction (CASP 10) dataset. In our analysis, GASS was ranking fourth among 18 methods. GASS-WEB is freely available at http://gass.unifei.edu.br/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Expression, Purification And Preliminary X-Ray Analysis of the C-Terminal Domain of An Arginine Repressor Protein From Mycobacterium Tuberculosis

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

Lu, G.J.; Garen, C.R.; Cherney, M.M.

2009-06-03

The gene product of an open reading frame Rv1657 from Mycobacterium tuberculosis is a putative arginine repressor protein (ArgR), a transcriptional factor that regulates the expression of arginine-biosynthetic enzymes. Rv1657 was expressed and purified and a C-terminal domain was crystallized using the hanging-drop vapour-diffusion method. Diffraction data were collected and processed to a resolution of 2.15 {angstrom}. The crystals belong to space group P1 and the Matthews coefficient suggests that the crystals contain six C-terminal domain molecules per unit cell. Previous structural and biochemical studies on the arginine repressor proteins from other organisms have likewise shown the presence of sixmore » molecules per unit cell.« less

On the complex interaction between mathematics and the sciences of living systems. Comment on "Move me, astonish me...delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Bellomo, Nicola; Outada, Nisrine

2017-07-01

Cultural framework: Our comment looks at the general framework given by the interactions between the so-called ;soft; and ;hard; sciences. Specifically, it looks at the development of a mathematics for living systems. Our comment aims at showing how the interesting survey [11] can contribute to the aforementioned challenging task.

Beauty and sublime. Comment on "Move me, astonish me…" delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates; by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid

2017-07-01

The VIMAP model presented in this review [1] is an interesting and detailed model of neural mechanisms of aesthetic perception. In this Comment I address one deficiency of this model: it does not address in details the fundamental notions of the VIMAP, beauty and sublime. In this regard VIMAP is similar to other publications on aesthetics.

I've Completely Changed: The Transforming Impact of the Matthew Shepard Scholarship

ERIC Educational Resources Information Center

Pace, Nicholas J.

2007-01-01

This article describes the impact of receiving the Matthew Shepard Scholarship (a 4-year, full scholarship) on 8 students who were openly gay or lesbian in high school. Previous literature, while limited, paints a decidedly bleak picture of the prospects for gay and lesbian youth. However, this previous research is often based on students in…

Robert Sabuda and Matthew Reinhart: A Cut Above

ERIC Educational Resources Information Center

Patton, Jessica Rae

2006-01-01

No one could argue the appeal for kids and adults alike of pop-up books. This article features two pop-up book author-artists, Robert Sabuda and Matthew Reinhart, whose books are in a league apart, with their stunning production values, well-written narratives, informative content and the sheer sophistication of the movable art. The two pioneered…

SMAP Takes a New Measure of Hurricane Matthew Winds

NASA Image and Video Library

2016-10-07

NASA's SMAP radiometer instrument measured Hurricane Matthew's wind speeds at 4:52 a.m. PDT (7:52 a.m. EDT) at up to 132 miles per hour (59 meters per second). SMAP has excellent sensitivity to extreme winds, far beyond that of typical scatterometer instruments now in orbit. http://photojournal.jpl.nasa.gov/catalog/PIA21096

Carbon Nanotube Based Flexible Supercapacitors

DTIC Science & Technology

2011-04-01

Carbon Nanotube Based Flexible Supercapacitors by Christopher M. Anton and Matthew H. Ervin ARL-TR-5522 April 2011...Carbon Nanotube Based Flexible Supercapacitors Christopher M. Anton and Matthew H. Ervin Sensors and Electron Devices Directorate, ARL...September 2010 4. TITLE AND SUBTITLE Carbon Nanotube Based Flexible Supercapacitors 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Plant debris left behind by Hurricane Matthew covers a stretch of the NASA Railroad near Launch Pads 39A and B at Kennedy Space Center in Florida. A portion of the line near the ocean was used during the Apollo era, although some portions were used to deliver commodities to the nearby Cape Canaveral Air Force Station through the end of the Titan program. NASA determined it was financially and ecologically advantageous to leave the tracks in place. Hurricane Matthew, a Category 3 storm, passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-18

Plant debris and ground erosion left behind by Hurricane Matthew affect a stretch of the NASA Railroad at Kennedy Space Center in Florida. A portion of the line near the ocean was used during the Apollo era, although some portions were used to deliver commodities to the nearby Cape Canaveral Air Force Station through the end of the Titan program. NASA determined it was financially and ecologically advantageous to leave the tracks in place. Hurricane Matthew, a Category 3 storm, passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

Thermal Quantum Correlations in Photosynthetic Light-Harvesting Complexes

NASA Astrophysics Data System (ADS)

Mahdian, M.; Kouhestani, H.

2015-08-01

Photosynthesis is one of the ancient biological processes, playing crucial role converting solar energy to cellular usable currency. Environmental factors and external perturbations has forced nature to choose systems with the highest efficiency and performance. Recent theoretical and experimental studies have proved the presence of quantum properties in biological systems. Energy transfer systems like Fenna-Matthews-Olson (FMO) complex shows quantum entanglement between sites of Bacteriophylla molecules in protein environment and presence of decoherence. Complex biological systems implement more truthful mechanisms beside chemical-quantum correlations to assure system's efficiency. In this study we investigate thermal quantum correlations in FMO protein of the photosynthetic apparatus of green sulfur bacteria by quantum discord measure. The results confirmed existence of remarkable quantum correlations of of BChla pigments in room temperature. This results approve involvement of quantum correlation mechanisms for information storage and retention in living organisms that could be useful for further evolutionary studies. Inspired idea of this study is potentially interesting to practice by the same procedure in genetic data transfer mechanisms.

Nedley Depression Hit Hypothesis: Identifying Depression and Its Causes.

PubMed

Nedley, Neil; Ramirez, Francisco E

2016-11-01

Depression is often diagnosed using the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) criteria. We propose how certain lifestyle choices and non-modifiable factors can predict the development of depression. We identified 10 cause categories (hits or "blows" to the brain) and theorize that four or more active hits could trigger a depression episode. Methods. A sample of 4271 participants from our community-based program (70% female; ages 17-94 years) was assessed at baseline and at the eighth week of the program using a custom test. Ten cause categories were examined as predictors of depression are (1) Genetic, (2)Developmental, (3)Lifestyle, (4)Circadian Rhythm, (5)Addiction, (6)Nutrition, (7)Toxic, (8)Social/Complicated Grief, (9)Medical Condition, and (10)Frontal Lobe. Results. The relationship between the DSM-5 score and a person having four hits categories in the first program week showed a sensitivity of 89.98 % (95% CI: 89.20 % - 90.73%), specificity 48.84% (CI 45.94-51.75) and Matthew Correlation Coefficient (MCC) .41 . For the eight-week test, the results showed a sensitivity 83.6% (CI 81.9-85.5), specificity 53.7% (CI 51.7-55.6) and MCC .38. Overall, the hits that improved the most from baseline after the eighth week were: Nutrition (47%), Frontal lobe (36%), Addiction (24%), Circadian rhythm (24%), Lifestyle (20%), Social (12%) and Medical (10%). Conclusions. The Nedley four-hit hypothesis seems to predict a depressive episode and correlates well with the DSM-5 criteria with good sensitivity and MCC but less specificity. Identifying these factors and applying lifestyle therapies could play an important role in the treatment of depressed individuals.

Our Documents: A National Initiative on American History, Civics, and Service. Teacher Sourcebook, Volume II

ERIC Educational Resources Information Center

Mazzenga, Maria, Ed.; McCullough, Julie, Ed.

2003-01-01

What do Matthew Brady, Carrie Chapman Catt, Ansel Adams, Orson Welles, and J. Howard Miller have to do with the 100 milestone documents? A few hints: Matthew Brady created the first photographic documentation of a war. Carrie Chapman Catt was the president of the National American Woman Suffrage Association in 1920. Orson Welles produced plays for…

50 CFR 600.1104 - Bering Sea and Aleutian Islands (BSAI) crab species fee payment and collection system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Pribilof blue king (the corresponding crab rationalization fishery is Pribilof red king and blue king crab), and (6) St. Matthew blue king (the corresponding crab rationalization fishery is also St. Matthew blue... Aleutian Islands red king, $237,588.04; (5) For Pribilof red king and Pribilof blue king, $1,571,216.35...

Quantum Linear Systems Theory

DTIC Science & Technology

2013-02-15

Matthew James, Andre Carvalho and Michael Hush completed some work analyzing cross-phase modulation using single photon quantum filtering techniques...ANU Michael Hush January – June, 2012, Postdoc, ANU Matthew R. James Professor, Australian National University Ian R. Petersen Professor...appear, IEEE Trans. Aut. Control., 2013. A. R. R. Carvalho, M. R. Hush , and M. R. James, “Cavity driven by a single photon: Conditional dynamics and

Performance-Based Assessment in Schools: A Comment on Hojnoski, Morrison, Brown, and Matthews (2006)

ERIC Educational Resources Information Center

Smith, Steven R.

2007-01-01

This article addresses a 2006 article by Hojnoski, Morrison, Brown, and Matthews on the use of performance-based measurement among school-based practitioners. Their results suggest that many of their survey respondents favor the use of this form of measurement. This line of research is important and addresses an important issue in current clinical…

75 FR 41123 - Fisheries of the Exclusive Economic Zone Off Alaska; Bering Sea Subarea

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-15

... Bering Sea Research Area to establish the Modified Gear Trawl Zone (MGTZ) and to expand the Saint Matthew... Research Area (NBSRA) to establish the MGTZ, and would expand the Saint Matthew Island Habitat Conservation... can be more than 1,000 feet (304.8 m) in length. Based on research by the Alaska Fisheries Science...

When high waters recede and the floodplain reemerges: Evaluating the lingering effects of extreme flooding on stream nitrogen cycling.

NASA Astrophysics Data System (ADS)

Neville, J.; Emanuel, R. E.

2017-12-01

In 2016 Hurricane Matthew brought immense flooding and devastation to the Lumbee (aka Lumber) River basin. Some impacts are obvious, such as deserted homes and businesses, but other impacts, including long-term environmental, are uncertain. Extreme flooding throughout the basin established temporary hydrologic connectivity between aquatic environments and upland sources of nutrients and other pollutants. Though 27% of the basin is covered by wetlands, hurricane-induced flooding was so intense that wetlands may have had no opportunity to mitigate delivery of nutrients into surface waters. As a result, how Hurricane Matthew impacted nitrate retention and uptake in the Lumbee River remains uncertain. The unknown magnitude of nitrate transported into the Lumbee River from surrounding sources may have lingering impacts on nitrogen cycling in this stream. With these potential impacts in mind, we conducted a Lagrangian water quality sampling campaign to assess the ability of the Lumbee River to retain and process nitrogen following Hurricane Matthew. We collected samples before and after flooding and compare first order nitrogen uptake kinetics of both periods. The analysis and comparisons allow us to evaluate the long-term impacts of Hurricane Matthew on nitrogen cycling after floodwaters recede.

The Matthew effect in empirical data

PubMed Central

Perc, Matjaž

2014-01-01

The Matthew effect describes the phenomenon that in societies, the rich tend to get richer and the potent even more powerful. It is closely related to the concept of preferential attachment in network science, where the more connected nodes are destined to acquire many more links in the future than the auxiliary nodes. Cumulative advantage and success-breads-success also both describe the fact that advantage tends to beget further advantage. The concept is behind the many power laws and scaling behaviour in empirical data, and it is at the heart of self-organization across social and natural sciences. Here, we review the methodology for measuring preferential attachment in empirical data, as well as the observations of the Matthew effect in patterns of scientific collaboration, socio-technical and biological networks, the propagation of citations, the emergence of scientific progress and impact, career longevity, the evolution of common English words and phrases, as well as in education and brain development. We also discuss whether the Matthew effect is due to chance or optimization, for example related to homophily in social systems or efficacy in technological systems, and we outline possible directions for future research. PMID:24990288

Major Hurricane Matthew Seen from Space on This Week @NASA – October 7, 2016

NASA Image and Video Library

2016-10-07

Cameras outside the International Space Station captured views of Hurricane Matthew during several passes over the major storm, as it made its way north through the Caribbean Sea during the week of Oct. 3. The storm, which reached Category 4 status with winds up to about 145 miles per hour, impacted Haiti, eastern Cuba and the Bahamas. Forecasters predicted Matthew would threaten the southeast coast of the United States, including Florida’s Space Coast. As a precaution, NASA’s Kennedy Space Center closed Oct. 5 after preparing facilities for what could be a direct hit from the storm. Also, One Mars Year of Science for MAVEN, SLS Hardware Being Stacked for Stress Test, Oceans Melting Greenland, Aspira con NASA, and NASA at White House Events!

iss049e028067

NASA Image and Video Library

2016-10-03

ISS049e028067 (10/03/2016) --- Hurricane Matthew, a huge category 4 level storm, as seen from the International Space Station Oct. 3, 2016. Packing winds of 140 miles an hour as a Category 4 hurricane, Matthew passed over western Haiti and eastern Cuba Oct. 4 before charging north over the Bahamas Oct. 5 and potentially threatening the east coast of the United States later in the week.

Our Public Intellectual: Matthew Battles--Houghton Library, Harvard University, Cambridge, MA

ERIC Educational Resources Information Center

Library Journal, 2004

2004-01-01

Many people take for granted the tools of the librarian's trade: typography, books, even the idea of a library. But when Matthew Battles looks at these things, he sees responses that evolved to meet human needs and wants to know more. What purposes were these tools put to and what do they tell people about the culture that produced them? What does…

Army-UNL Center for Trauma Mechanics

DTIC Science & Technology

2011-03-07

Jung Yul Lim, Dr. Joseph A. Turner, Dr. Florin Bobaru, Dr. Mehrdad Negahban University of Nebraska Research Grants & Contracts 303 Administration...none) 1. Matthew Nienaber,* Jeong Soon Lee,* Ruqiang Feng, Jung Yul Lim. Impulsive pressurization of neuronal cells for traumatic brain injury study...Toronto, Canada, October 16-18, 2010. 11. Jeong Soon Lee, Matthew Nienaber, Ruqiang Feng, Jung Yul Lim. Impulsive pressurization of neuronal cells for

Is It Time to Designate Coast Guard Special Operations Forces

DTIC Science & Technology

2005-06-17

174 Commander Matthew Creelman , USCG Division Chief........................................ 174...February 2005. 9Pailliotet and Phelan. 10Ibid. 11Matthew Creelman , interview by author, Yorktown, VA, 25 January 2005. 12James Perry Stevenson, The $5...doing some research for my master’s thesis at the Army Command and General Staff College. I found out from CDR Creelman that G-CI has ended ITD’s long

Crystallization and preliminary X-ray analysis of a novel halotolerant feruloyl esterase identified from a soil metagenomic library

PubMed Central

Chen, Shang-ke; Wang, Kui; Liu, Yuhuan; Hu, Xiaopeng

2012-01-01

Feruloyl esterase cleaves the ester linkage formed between ferulic acid and polysaccharides in plant cell walls and thus has wide potential industrial applications. A novel feruloyl esterase (EstF27) identified from a soil metagenomic library was crystallized and a complete data set was collected from a single cooled crystal using an in-house X-ray source. The crystal diffracted to 2.9 Å resolution and belonged to space group P212121, with unit-cell parameters a = 94.35, b = 106.19, c = 188.51 Å, α = β = γ = 90.00°. A Matthews coefficient of 2.55 Å3 Da−1, with a corresponding solvent content of 51.84%, suggested the presence of ten protein subunits in the asymmetric unit. PMID:22750860

The trauma signature of 2016 Hurricane Matthew and the psychosocial impact on Haiti

PubMed Central

Shultz, James M.; Cela, Toni; Marcelin, Louis Herns; Espinola, Maria; Heitmann, Ilva; Sanchez, Claudia; Jean Pierre, Arielle; Foo, Cheryl YunnShee; Thompson, Kip; Klotzbach, Philip; Espinel, Zelde; Rechkemmer, Andreas

2016-01-01

ABSTRACT Background. Hurricane Matthew was the most powerful tropical cyclone of the 2016 Atlantic Basin season, bringing severe impacts to multiple nations including direct landfalls in Cuba, Haiti, Bahamas, and the United States. However, Haiti experienced the greatest loss of life and population disruption. Methods. An established trauma signature (TSIG) methodology was used to examine the psychological consequences of Hurricane Matthew in relation to the distinguishing features of this event. TSIG analyses described the exposures of Haitian citizens to the unique constellation of hazards associated with this tropical cyclone. A hazard profile, a matrix of psychological stressors, and a “trauma signature” summary for the affected population of Haiti - in terms of exposures to hazard, loss, and change - were created specifically for this natural ecological disaster. Results. Hazard characteristics of this event included: deluging rains that triggered mudslides along steep, deforested terrain; battering hurricane winds (Category 4 winds in the “eye-wall” at landfall) that dismantled the built environment and launched projectile debris; flooding “storm surge” that moved ashore and submerged villages on the Tiburon peninsula; and pummeling wave action that destroyed infrastructure along the coastline. Many coastal residents were left defenseless to face the ravages of the storm. Hurricane Matthew's slow forward progress as it remained over super-heated ocean waters added to the duration and degree of the devastation. Added to the havoc of the storm itself, the risks for infectious disease spread, particularly in relation to ongoing epidemics of cholera and Zika, were exacerbated. Conclusions. Hurricane Matthew was a ferocious tropical cyclone whose meteorological characteristics amplified the system's destructive force during the storm's encounter with Haiti, leading to significant mortality, injury, and psychological trauma. PMID:28321360

Matthews device arthroplasty presents superior long-term mouth opening than interpositional arthroplasty in the management of temporomandibular joint ankylosis.

PubMed

Denadai, Rafael; Raposo-Amaral, Cassio Eduardo; Buzzo, Celso Luiz; Raposo-Amaral, Cesar Augusto

2016-08-01

The aim of this study is to describe the surgical outcomes of a single-institution experience in the surgical management of temporomandibular joint ankylosis, comparing interpositional arthroplasty with autogenous tissue and Matthews device arthroplasty. A retrospective analysis of temporomandibular joint ankylosis patients (n = 15), who underwent interpositional arthroplasty or Matthews device arthroplasty, was conducted. The surgical outcomes (preoperative, recent [4-6 weeks], intermediate [1 year], and late [3 years] postoperative maximal incisal opening, hospital stay, and complication, relapse, and reoperation rates) were compared. Significant (all p < 0.05) differences were recorded in temporomandibular joint ankylosis patients treated with interpositional arthroplasty with autogenous tissue (53.3%) versus Matthews device arthroplasty (46.7%) according to intermediate (25 ± 7 vs. 34 ± 5 mm) and late (19 ± 8 vs. 33 ± 5 mm) postoperative maximal incisal opening, intermediate (31% vs. 7%) and late (47% vs. 12%) postoperative relapse, and reoperation rate (38% vs. 0%). There was similarity (all p > 0.05) in preoperative (4.8 ± 2.9 vs. 4.9 ± 2.9 mm) and recent (35 ± 4 vs. 37 ± 4 mm) postoperative maximal incisal opening, hospital stay (3.5 ± 0.8 vs. 3.6 ± 0.8 days), and surgery-related complications (13% vs. 14%). Both surgical procedures evaluated were successful in initial management of temporomandibular joint ankylosis, but the Matthews device arthroplasty avoided postoperative relapse. Copyright © 2016 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Effect of spike-timing-dependent plasticity on stochastic burst synchronization in a scale-free neuronal network.

PubMed

Kim, Sang-Yoon; Lim, Woochang

2018-06-01

We consider an excitatory population of subthreshold Izhikevich neurons which cannot fire spontaneously without noise. As the coupling strength passes a threshold, individual neurons exhibit noise-induced burstings. This neuronal population has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). However, STDP was not considered in previous works on stochastic burst synchronization (SBS) between noise-induced burstings of sub-threshold neurons. Here, we study the effect of additive STDP on SBS by varying the noise intensity D in the Barabási-Albert scale-free network (SFN). One of our main findings is a Matthew effect in synaptic plasticity which occurs due to a positive feedback process. Good burst synchronization (with higher bursting measure) gets better via long-term potentiation (LTP) of synaptic strengths, while bad burst synchronization (with lower bursting measure) gets worse via long-term depression (LTD). Consequently, a step-like rapid transition to SBS occurs by changing D , in contrast to a relatively smooth transition in the absence of STDP. We also investigate the effects of network architecture on SBS by varying the symmetric attachment degree [Formula: see text] and the asymmetry parameter [Formula: see text] in the SFN, and Matthew effects are also found to occur by varying [Formula: see text] and [Formula: see text]. Furthermore, emergences of LTP and LTD of synaptic strengths are investigated in details via our own microscopic methods based on both the distributions of time delays between the burst onset times of the pre- and the post-synaptic neurons and the pair-correlations between the pre- and the post-synaptic instantaneous individual burst rates (IIBRs). Finally, a multiplicative STDP case (depending on states) with soft bounds is also investigated in comparison with the additive STDP case (independent of states) with hard bounds. Due to the soft bounds, a Matthew effect with some quantitative differences is also found to occur for the case of multiplicative STDP.

Warrior or Pundit: Ethical Struggle of Army Senior Leaders

DTIC Science & Technology

2011-04-06

flattening and so will warfare in the twenty-first century. James Petras and Henry Veltmeyer described globalization as ―the widening and deepening of...policy sphere. Endnotes 1 General Matthew B. Ridgway, USA, (Ret.) As told to Harold H. Martin , Soldier: The Memoirs of Matthew B. Ridgway (New...8. 44 James Petras and Henry Veltmeyer, Globalization Unmasked: Imperialism in the 21st Century (Halifax, Fernwood Publishing, 2001), 11. 45

The 2015 Transition of Wartime Operational Control: A Threat or Opportunity for the ROK /US Alliance

DTIC Science & Technology

2014-06-13

effects in regional stability. In other words, as Matthew J. Jordan pointed out, multilateral efforts will complement and not supplant established...operations. 46Matthew J. Jordan , “Multilateralism in North East Asia” (Master’s Naval War College...dismantling DPRK’s nuclear program. The impetus for these talks emerged in 2003 when the DPRK revealed its uranium enrichment program. This enrichment

Matthew Jones House: Recommendations for Treatment

DTIC Science & Technology

2016-04-01

strongly recommend that a structural engineer be contracted to provide in depth analysis and monitoring. The decay of the historic timber top plates...of the structure . This report summarizes the research and findings by the NCPTT. It also includes an engineer’s report and other supplemental in...NEEDED. DO NOT RETURN IT TO THE ORIGINATOR. ERDC/CERL CR-16-1 iii Foreword After identifying a variety of structural issues with the Matthew Jones

Copper Doping of Zinc Oxide by Nuclear Transmutation

DTIC Science & Technology

2014-03-27

Copper Doping of Zinc Oxide by Nuclear Transmutation THESIS Matthew C. Recker, Captain, USAF AFIT-ENP-14-M-30 DEPARTMENT OF THE AIR FORCE AIR...NUCLEAR TRANSMUTATION THESIS Presented to the Faculty Department of Engineering Physics Graduate School of Engineering and Management Air Force...COPPER DOPING OF ZINC OXIDE BY NUCLEAR TRANSMUTATION Matthew C. Recker, BS Captain, USAF Approved: //signed// 27 February 2014 John W. McClory, PhD

Senior Leader Perspective on the Air Force Nuclear Enterprise: Todays Issues and the Future

DTIC Science & Technology

2016-09-15

SENIOR LEADER PERSPECTIVE ON THE AIR FORCE NUCLEAR ENTERPRISE: TODAY’S ISSUES AND THE FUTURE GRADUATE RESEARCH PAPER Matthew D. Boone...States. AFIT-ENS-MS-16-S-028 SENIOR LEADER PERSPECTIVE ON THE AIR FORCE NUCLEAR ENTERPRISE: TODAY’S ISSUES AND THE FUTURE GRADUATE... ISSUES AND THE FUTURE Matthew D. Boone, BS, MA Major, USAF Committee Membership: Robert E. Overstreet, Lt Col, USAF, PhD

Security Verification of Secure MANET Routing Protocols

DTIC Science & Technology

2012-03-22

SECURITY VERIFICATION OF SECURE MANET ROUTING PROTOCOLS THESIS Matthew F. Steele, Captain, USAF AFIT/GCS/ ENG /12-03 DEPARTMENT OF THE AIR FORCE AIR...States AFIT/GCS/ ENG /12-03 SECURITY VERIFICATION OF SECURE MANET ROUTING PROTOCOLS THESIS Presented to the Faculty Department of Electrical and Computer...DISTRIBUTION UNLIMITED AFIT/GCS/ ENG /12-03 SECURITY VERIFICATION OF SECURE MANET ROUTING PROTOCOLS Matthew F. Steele, B.S.E.E. Captain, USAF

Force production and time-averaged flow structure around thin, non-slender delta wings

NASA Astrophysics Data System (ADS)

Tu, Han; Green, Melissa

2017-11-01

Experimental force measurement and time-averaged three dimensional flow visualization of low Reynolds number baseline cases have been carried out on a steady flat plate delta wing. Current data will serve as steady reference for future unsteady flow and actuation cases. The comprehensive study will compare force production in highly unsteady environments, which is necessary to consider in unmanned combat aerial vehicle (UCAV) control strategies. Force measurements are carried out at angles of attack 10, 15, 20, 25 and 30 degrees. The coefficient of drag increases with angle of attack, while the coefficient of lift reaches a maximum value at 20 degrees. Time-averaged flow visualization conducted at angles of attack of 20, 25 and 30 degrees shows vortices with larger magnitude that persist farther into wake are generated at higher angles of attack. These results compare analogously with similar steady baseline experiment results of high Reynolds number conducted by collaborators. This work was supported by the Office of Naval Research under ONR Award No. N00014-16-1-2732. We also acknowledge the collaborative support of Dr. David Rival and Mr. Matthew Marzanek at Queen's University.

Coarse-grained representation of the quasi adiabatic propagator path integral for the treatment of non-Markovian long-time bath memory

NASA Astrophysics Data System (ADS)

Richter, Martin; Fingerhut, Benjamin P.

2017-06-01

The description of non-Markovian effects imposed by low frequency bath modes poses a persistent challenge for path integral based approaches like the iterative quasi-adiabatic propagator path integral (iQUAPI) method. We present a novel approximate method, termed mask assisted coarse graining of influence coefficients (MACGIC)-iQUAPI, that offers appealing computational savings due to substantial reduction of considered path segments for propagation. The method relies on an efficient path segment merging procedure via an intermediate coarse grained representation of Feynman-Vernon influence coefficients that exploits physical properties of system decoherence. The MACGIC-iQUAPI method allows us to access the regime of biological significant long-time bath memory on the order of hundred propagation time steps while retaining convergence to iQUAPI results. Numerical performance is demonstrated for a set of benchmark problems that cover bath assisted long range electron transfer, the transition from coherent to incoherent dynamics in a prototypical molecular dimer and excitation energy transfer in a 24-state model of the Fenna-Matthews-Olson trimer complex where in all cases excellent agreement with numerically exact reference data is obtained.

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields.

PubMed

Jahandideh, Samad; Abdolmaleki, Parviz; Movahedi, Mohammad Mehdi

2010-02-01

Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF-MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in "not changed melatonin level" pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF-MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in finding a relationship between electromagnetic fields and different biological processes. (c) 2009 Wiley-Liss, Inc.

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

PubMed

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.

Predicting beta-turns in proteins using support vector machines with fractional polynomials

PubMed Central

2013-01-01

Background β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design. Results We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features. Conclusions In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods. PMID:24565438

Type I and II β-turns prediction using NMR chemical shifts.

PubMed

Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

2014-07-01

A method for predicting type I and II β-turns using nuclear magnetic resonance (NMR) chemical shifts is proposed. Isolated β-turn chemical-shift data were collected from 1,798 protein chains. One-dimensional statistical analyses on chemical-shift data of three classes β-turn (type I, II, and VIII) showed different distributions at four positions, (i) to (i + 3). Considering the central two residues of type I β-turns, the mean values of Cο, Cα, H(N), and N(H) chemical shifts were generally (i + 1) > (i + 2). The mean values of Cβ and Hα chemical shifts were (i + 1) < (i + 2). The distributions of the central two residues in type II and VIII β-turns were also distinguishable by trends of chemical shift values. Two-dimensional cluster analyses on chemical-shift data show positional distributions more clearly. Based on these propensities of chemical shift classified as a function of position, rules were derived using scoring matrices for four consecutive residues to predict type I and II β-turns. The proposed method achieves an overall prediction accuracy of 83.2 and 84.2% with the Matthews correlation coefficient values of 0.317 and 0.632 for type I and II β-turns, indicating that its higher accuracy for type II turn prediction. The results show that it is feasible to use NMR chemical shifts to predict the β-turn types in proteins. The proposed method can be incorporated into other chemical-shift based protein secondary structure prediction methods.

Predicting beta-turns in proteins using support vector machines with fractional polynomials.

PubMed

Elbashir, Murtada; Wang, Jianxin; Wu, Fang-Xiang; Wang, Lusheng

2013-11-07

β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design. We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features. In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods.

PhD7Faster: predicting clones propagating faster from the Ph.D.-7 phage display peptide library.

PubMed

Ru, Beibei; 't Hoen, Peter A C; Nie, Fulei; Lin, Hao; Guo, Feng-Biao; Huang, Jian

2014-02-01

Phage display can rapidly discover peptides binding to any given target; thus, it has been widely used in basic and applied research. Each round of panning consists of two basic processes: Selection and amplification. However, recent studies have showed that the amplification step would decrease the diversity of phage display libraries due to different propagation capacity of phage clones. This may induce phages with growth advantage rather than specific affinity to appear in the final experimental results. The peptides displayed by such phages are termed as propagation-related target-unrelated peptides (PrTUPs). They would mislead further analysis and research if not removed. In this paper, we describe PhD7Faster, an ensemble predictor based on support vector machine (SVM) for predicting clones with growth advantage from the Ph.D.-7 phage display peptide library. By using reduced dipeptide composition (ReDPC) as features, an accuracy (Acc) of 79.67% and a Matthews correlation coefficient (MCC) of 0.595 were achieved in 5-fold cross-validation. In addition, the SVM-based model was demonstrated to perform better than several representative machine learning algorithms. We anticipate that PhD7Faster can assist biologists to exclude potential PrTUPs and accelerate the finding of specific binders from the popular Ph.D.-7 library. The web server of PhD7Faster can be freely accessed at http://immunet.cn/sarotup/cgi-bin/PhD7Faster.pl.

Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection.

PubMed

Pan, Xiaoyong; Hu, Xiaohua; Zhang, Yu Hang; Feng, Kaiyan; Wang, Shao Peng; Chen, Lei; Huang, Tao; Cai, Yu Dong

2018-04-12

Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew's correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles.

The Role of Balanced Training and Testing Data Sets for Binary Classifiers in Bioinformatics

PubMed Central

Wei, Qiong; Dunbrack, Roland L.

2013-01-01

Training and testing of conventional machine learning models on binary classification problems depend on the proportions of the two outcomes in the relevant data sets. This may be especially important in practical terms when real-world applications of the classifier are either highly imbalanced or occur in unknown proportions. Intuitively, it may seem sensible to train machine learning models on data similar to the target data in terms of proportions of the two binary outcomes. However, we show that this is not the case using the example of prediction of deleterious and neutral phenotypes of human missense mutations in human genome data, for which the proportion of the binary outcome is unknown. Our results indicate that using balanced training data (50% neutral and 50% deleterious) results in the highest balanced accuracy (the average of True Positive Rate and True Negative Rate), Matthews correlation coefficient, and area under ROC curves, no matter what the proportions of the two phenotypes are in the testing data. Besides balancing the data by undersampling the majority class, other techniques in machine learning include oversampling the minority class, interpolating minority-class data points and various penalties for misclassifying the minority class. However, these techniques are not commonly used in either the missense phenotype prediction problem or in the prediction of disordered residues in proteins, where the imbalance problem is substantial. The appropriate approach depends on the amount of available data and the specific problem at hand. PMID:23874456

DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.

PubMed

Ma, Xin; Guo, Jing; Sun, Xiao

2016-01-01

DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.

Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

PubMed

Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

2017-11-01

Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improved, ACMG-Compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants.

PubMed

Fortuno, Cristina; James, Paul A; Young, Erin L; Feng, Bing; Olivier, Magali; Pesaran, Tina; Tavtigian, Sean V; Spurdle, Amanda B

2018-05-18

Clinical interpretation of germline missense variants represents a major challenge, including those in the TP53 Li-Fraumeni syndrome gene. Bioinformatic prediction is a key part of variant classification strategies. We aimed to optimize the performance of the Align-GVGD tool used for p53 missense variant prediction, and compare its performance to other bioinformatic tools (SIFT, PolyPhen-2) and ensemble methods (REVEL, BayesDel). Reference sets of assumed pathogenic and assumed benign variants were defined using functional and/or clinical data. Area under the curve and Matthews correlation coefficient (MCC) values were used as objective functions to select an optimized protein multi-sequence alignment with best performance for Align-GVGD. MCC comparison of tools using binary categories showed optimized Align-GVGD (C15 cut-off) combined with BayesDel (0.16 cut-off), or with REVEL (0.5 cut-off), to have the best overall performance. Further, a semi-quantitative approach using multiple tiers of bioinformatic prediction, validated using an independent set of non-functional and functional variants, supported use of Align-GVGD and BayesDel prediction for different strength of evidence levels in ACMG/AMP rules. We provide rationale for bioinformatic tool selection for TP53 variant classification, and have also computed relevant bioinformatic predictions for every possible p53 missense variant to facilitate their use by the scientific and medical community. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Prediction of protein S-nitrosylation sites based on adapted normal distribution bi-profile Bayes and Chou's pseudo amino acid composition.

PubMed

Jia, Cangzhi; Lin, Xin; Wang, Zhiping

2014-06-10

Protein S-nitrosylation is a reversible post-translational modification by covalent modification on the thiol group of cysteine residues by nitric oxide. Growing evidence shows that protein S-nitrosylation plays an important role in normal cellular function as well as in various pathophysiologic conditions. Because of the inherent chemical instability of the S-NO bond and the low abundance of endogenous S-nitrosylated proteins, the unambiguous identification of S-nitrosylation sites by commonly used proteomic approaches remains challenging. Therefore, computational prediction of S-nitrosylation sites has been considered as a powerful auxiliary tool. In this work, we mainly adopted an adapted normal distribution bi-profile Bayes (ANBPB) feature extraction model to characterize the distinction of position-specific amino acids in 784 S-nitrosylated and 1568 non-S-nitrosylated peptide sequences. We developed a support vector machine prediction model, iSNO-ANBPB, by incorporating ANBPB with the Chou's pseudo amino acid composition. In jackknife cross-validation experiments, iSNO-ANBPB yielded an accuracy of 65.39% and a Matthew's correlation coefficient (MCC) of 0.3014. When tested on an independent dataset, iSNO-ANBPB achieved an accuracy of 63.41% and a MCC of 0.2984, which are much higher than the values achieved by the existing predictors SNOSite, iSNO-PseAAC, the Li et al. algorithm, and iSNO-AAPair. On another training dataset, iSNO-ANBPB also outperformed GPS-SNO and iSNO-PseAAC in the 10-fold crossvalidation test.

In silico prediction of multiple-category classification model for cytochrome P450 inhibitors and non-inhibitors using machine-learning method.

PubMed

Lee, J H; Basith, S; Cui, M; Kim, B; Choi, S

2017-10-01

The cytochrome P450 (CYP) enzyme superfamily is involved in phase I metabolism which chemically modifies a variety of substrates via oxidative reactions to make them more water-soluble and easier to eliminate. Inhibition of these enzymes leads to undesirable effects, including toxic drug accumulations and adverse drug-drug interactions. Hence, it is necessary to develop in silico models that can predict the inhibition potential of compounds for different CYP isoforms. This study focused on five major CYP isoforms, including CYP1A2, 2C9, 2C19, 2D6 and 3A4, that are responsible for more than 90% of the metabolism of clinical drugs. The main aim of this study is to develop a multiple-category classification model (MCM) for the major CYP isoforms using a Laplacian-modified naïve Bayesian method. The dataset composed of more than 4500 compounds was collected from the PubChem Bioassay database. VolSurf+ descriptors and FCFP_8 fingerprint were used as input features to build classification models. The results demonstrated that the developed MCM using Laplacian-modified naïve Bayesian method was successful in classifying inhibitors and non-inhibitors for each CYP isoform. Moreover, the accuracy, sensitivity and specificity values for both training and test sets were above 80% and also yielded satisfactory area under the receiver operating characteristic curve and Matthews correlation coefficient values.

Using Heart Rate to Predict Resilience and Susceptibility to PTSD in Soldiers

DTIC Science & Technology

2011-04-01

Predict Resilience and Susceptibility to PTSD in Soldiers Authors Brian Chung Jonathan Lanier Lolita M. Burrell Michael D. Matthews...AUTHOR(S) Brian Chung; Jonathan Lanier; Lolita Burrell; Michael Matthews 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING...members of the control group were matched with one of the trauma or PTSD victims based on age and sex and both individuals were shown the same

Seismic Surveillance. Nuclear Test Ban Verification

DTIC Science & Technology

1990-02-26

e.g., see Matthews and Cheadle, 1986). To summarize, data processing tied to 8 msec sampling is a bit coarse for the sedimentary column but...Continental Extensional Tectonics. Geological Society Special Publication No. 28, 53-65. Matthews , D.H. and Cheadle, M.J. 1986: Deep Reflections from the...Laboratory P. 0. Box 73 P.O. Box 1620 Lexington, MA 02173-0073 (3 copies) La Jolla, CA 92038-1620 Prof Fred K. Lamb Prof. William Menke University of

Collaborative Technologies and their Effect on Operator Workload in BMC2 Domains

DTIC Science & Technology

2007-06-01

Vogel, & Luck, 1998). 16 Like brain measurement techniques, measures of heart rate variability ( HRV ) have been used extensively as a physiological...et al., 2004; Helton, Dember, Warm, & Matthews, 1999; Matthews, et al., 1999; Szalma et al., 2004). Both state and trait anxiety were assessed using...the STAI (State-Trait Anxiety Inventory, Spielberger et al., 1983). Each dimension of the STAI (i.e., state and trait) consists of a 20-item

On Risk: Risk and Decision Making in Military Combat and Training Environments

DTIC Science & Technology

2012-12-01

DECISION MAKING IN MILITARY COMBAT AND TRAINING ENVIRONMENTS by Matthew R. Myer Jason R. Lojka December 2012 Thesis Advisor...SUBTITLE ON RISK: RISK AND DECISION MAKING IN MILITARY COMBAT AND TRAINING ENVIRONMENTS 5. FUNDING NUMBERS 6. AUTHOR(S) Matthew R. Myer and Jason R...of the nation that has sent them abroad. It is paramount, therefore, that we utilize a decision process to reveal how emotions can affect our

Understanding and Controlling the Electronic Properties of Graphene Using Scanning Probe Microscopy

DTIC Science & Technology

2014-07-21

Dirac point in gated bilayer graphene, Applied Physics Letters, (12 2009): 243502. doi : 10.1063/1.3275755 Brian J. LeRoy, Adam T. Roberts, Rolf...of soliton motion and stacking in trilayer graphene, Nature Materials , (04 2014): 0. doi : 10.1038/nmat3965 Matthew Yankowitz, Joel I-Jan Wang...of bilayer graphene via quasiparticle scattering, APL Materials , (09 2014): 92503. doi : Matthew Yankowitz, Fenglin Wang, Chun Ning Lau, Brian J

Local Electric Field Effects on Rhodium-Porphyrin and NHC-Gold Catalysts

DTIC Science & Technology

2015-01-05

AFRL-OSR-VA-TR-2015-0023 (NII) - Local Electric Field Effects on Rhodium -Porphyrin and NHC-Gold Catalysts MATTHEW KANAN LELAND STANFORD JUNIOR UNIV...Effects on Rhodium -Porphyrin and NHC-Gold Catalysts Principal Investigator: Matthew W. Kanan Project Publications: 1. “An Electric Field–Induced Change...Stanford University Grant/Contract Title The full title of the funded effort. (NII)-Local Electric Field Effects on Rhodium -Porphyrin and NHC-Gold

An Analysis of the Navy’s Fiscal Year 2017 Shipbuilding Plan

DTIC Science & Technology

2017-02-01

Navy would build a larger fleet of about 350 ships (see Table 5). Those three alternatives were chosen for illustrative purposes because variations ...3.2 billion. 2. For more on procedures for estimating and applying learning curves, see Matthew S. Goldberg and Anduin E. Touw, Statistical Methods...guidance from Matthew Goldberg (formerly of CBO) and David Mosher. Raymond Hall of CBO’s Budget Analysis Division produced the cost estimates with

October Surprises.

PubMed

2016-10-01

Ushered in with the rampage of Hurricane Matthew, later days brightened in this month that has often been harbinger of both good and bad news for Cuba and the world. Hurricane Matthew ripped through Eastern Cuba, devastating the historic town of Baracoa (Cuba's first capital, founded in 1511) and the village of Maisí, where the morning sun first rises over Cuban territory. Wind and flood leveled hundreds of homes, brought down the power grid and destroyed crops. Yet there was no loss of human life, unlike in neighboring Haiti and other countries in Matthew's path, and unlike in Cuba in 1963, when Hurricane Flora caused more than 1200 deaths. In Haiti, efforts of health workers-including hundreds of Haitian graduates from Cuba's Latin American Medical School and 600 Cuban health professionals already there-were bolstered by dozens of specially trained Cuban disaster medical personnel in the wake of the storm.

A new correlation coefficient for bivariate time-series data

NASA Astrophysics Data System (ADS)

Erdem, Orhan; Ceyhan, Elvan; Varli, Yusuf

2014-11-01

The correlation in time series has received considerable attention in the literature. Its use has attained an important role in the social sciences and finance. For example, pair trading in finance is concerned with the correlation between stock prices, returns, etc. In general, Pearson’s correlation coefficient is employed in these areas although it has many underlying assumptions which restrict its use. Here, we introduce a new correlation coefficient which takes into account the lag difference of data points. We investigate the properties of this new correlation coefficient. We demonstrate that it is more appropriate for showing the direction of the covariation of the two variables over time. We also compare the performance of the new correlation coefficient with Pearson’s correlation coefficient and Detrended Cross-Correlation Analysis (DCCA) via simulated examples.

Expression, purification, crystallization and preliminary X-ray analysis of conjugated polyketone reductase C2 (CPR-C2) from Candida parapsilosis IFO 0708

PubMed Central

Yamamura, Akihiro; Maruoka, Shintaro; Ohtsuka, Jun; Miyakawa, Takuya; Nagata, Koji; Kataoka, Michihiko; Kitamura, Nahoko; Shimizu, Sakayu; Tanokura, Masaru

2009-01-01

Conjugated polyketone reductase C2 (CPR-C2) from Candida parapsilosis IFO 0708 is a member of the NADPH-dependent aldo-keto reductase (AKR) superfamily and catalyzes the stereospecific reduction of ketopantoyl lactone to d-pantoyl lactone. A diffraction-quality crystal of recombinant CPR-C2 was obtained by the sitting-drop vapour-diffusion method using PEG 3350 as the precipitant. The crystal diffracted X-rays to 1.7 Å resolution on beamline NW12A of the Photon Factory-Advanced Ring (Tsukuba, Japan). The crystal belonged to space group P212121, with unit-cell parameters a = 55.02, b = 68.30, c = 68.93 Å. The Matthews coefficient (V M = 1.76 Å3 Da−1) indicated that the crystal contained one CPR-C2 molecule per asymmetric unit. PMID:19923737

Expression, purification, crystallization and preliminary X-ray analysis of conjugated polyketone reductase C2 (CPR-C2) from Candida parapsilosis IFO 0708.

PubMed

Yamamura, Akihiro; Maruoka, Shintaro; Ohtsuka, Jun; Miyakawa, Takuya; Nagata, Koji; Kataoka, Michihiko; Kitamura, Nahoko; Shimizu, Sakayu; Tanokura, Masaru

2009-11-01

Conjugated polyketone reductase C2 (CPR-C2) from Candida parapsilosis IFO 0708 is a member of the NADPH-dependent aldo-keto reductase (AKR) superfamily and catalyzes the stereospecific reduction of ketopantoyl lactone to d-pantoyl lactone. A diffraction-quality crystal of recombinant CPR-C2 was obtained by the sitting-drop vapour-diffusion method using PEG 3350 as the precipitant. The crystal diffracted X-rays to 1.7 angstrom resolution on beamline NW12A of the Photon Factory-Advanced Ring (Tsukuba, Japan). The crystal belonged to space group P2(1)2(1)2(1), with unit-cell parameters a = 55.02, b = 68.30, c = 68.93 angstrom. The Matthews coefficient (V(M) = 1.76 angstrom(3) Da(-1)) indicated that the crystal contained one CPR-C2 molecule per asymmetric unit.

Purification, crystallization, preliminary X-ray diffraction and molecular-replacement studies of great cormorant (Phalacrocorax carbo) haemoglobin.

PubMed

Jagadeesan, G; Malathy, P; Gunasekaran, K; Harikrishna Etti, S; Aravindhan, S

2014-11-01

Haemoglobin is the iron-containing oxygen-transport metalloprotein that is present in the red blood cells of all vertebrates. In recent decades, there has been substantial interest in attempting to understand the structural basis and functional diversity of avian haemoglobins. Towards this end, purification, crystallization, preliminary X-ray diffraction and molecular-replacement studies have been carried out on cormorant (Phalacrocorax carbo) haemoglobin. Crystals were grown by the hanging-drop vapour-diffusion method using PEG 3350, NaCl and glycerol as precipitants. The crystals belonged to the trigonal system P3₁21, with unit-cell parameters a=b=55.64, c=153.38 Å, β=120.00°; a complete data set was collected to a resolution of 3.5 Å. Matthews coefficient analysis indicated that the crystals contained a half-tetramer in the asymmetric unit.

Crystallization and preliminary X-ray analysis of the HA3 component of Clostridium botulinum type C progenitor toxin

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

Nakamura, Toshio; Tonozuka, Takashi; Kotani, Mao

2007-12-01

HA3, a 70 kDa haemagglutinating protein, is a precursor form of HA3a and HA3b, the subcomponents of Clostridium botulinum type C 16S progenitor toxin. In this report, recombinant HA3 protein was overexpressed in Escherichia coli, purified and crystallized. HA3, a 70 kDa haemagglutinating protein, is a precursor form of HA3a and HA3b, the subcomponents of Clostridium botulinum type C 16S progenitor toxin. In this report, recombinant HA3 protein was overexpressed in Escherichia coli, purified and crystallized. Diffraction data were collected to 2.6 Å resolution and the crystal belonged to the hexagonal space group P6{sub 3}. Matthews coefficient and self-rotation functionmore » calculations indicate that there is probably one molecule of HA3 in the asymmetric unit. A search for heavy-atom derivatives has been undertaken.« less

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-13

Members of the Disaster Assessment and Recovery Team (DART) work on flooring repairs to the Beach House at NASA’s Kennedy Space Center in Florida. The effort is part of the spaceport’s ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

Comparison of JP-8 Sprays from a Hydraulically Actuated Electronically Controlled Unit Injector and a Common Rail Injector

DTIC Science & Technology

2015-10-01

acquired of a calibration plate to provide scaling for the injector orifices. The determined scaling factor for the images was 0.3 µm/pixel. A circle...Controlled Unit Injector and a Common Rail Injector by Matthew Kurman, Michael Tess, Luis Bravo, Chol-Bum Kweon, and Craig Hershey Reprinted...Comparison of JP-8 Sprays from a Hydraulically Actuated Electronically Controlled Unit Injector and a Common Rail Injector by Matthew Kurman

The Effect of Fuel Injector Nozzle Configuration on JP-8 Sprays at Diesel Engine Conditions

DTIC Science & Technology

2014-10-01

The Effect of Fuel Injector Nozzle Configuration on JP-8 Sprays at Diesel Engine Conditions by Matthew Kurman, Luis Bravo, Chol-Bum Kweon...Fuel Injector Nozzle Configuration on JP-8 Sprays at Diesel Engine Conditions Matthew Kurman, Luis Bravo, and Chol-Bum Kweon Vehicle Technology...March 2014 4. TITLE AND SUBTITLE The Effect of Fuel Injector Nozzle Configuration on JP-8 Sprays at Diesel Engine Conditions 5a. CONTRACT NUMBER 5b

Students Bring Fresh Perspective and New Technology to Webb Telescope

NASA Image and Video Library

2017-12-08

Matthew Bolcar a graduate student from the University of Rochester, N.Y. now works at Goddard full-time. Credit: NASA/GSFC/Chris Gunn To read more about Matthew go to: www.nasa.gov/topics/technology/features/partnerships.html NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe.

Aviation Logistics in U.S. Pacific Command: A Cost-Based Analysis and Comparative Advantage to Commercial Shipment

DTIC Science & Technology

2012-12-01

IN U.S. PACIFIC COMMAND: A COST- BASED ANALYSIS AND COMPARATIVE ADVANTAGE TO COMMERCIAL SHIPMENT by Tod B. Diffey Matthew J. Beck December...PACIFIC COMMAND: A COST- BASED ANALYSIS AND COMPARATIVE ADVANTAGE TO COMMERCIAL SHIPMENT 5. FUNDING NUMBERS 6. AUTHOR(S) Tod B. Diffey and Matthew...this study will provide a cost based analysis and qualitative evaluation regarding the use of commercial agencies and/or United States Marine Corps

Special Relationship What are the Strategic Choices available to the UK after the US Pivot to Asia

DTIC Science & Technology

2013-02-14

Emergency’ see Jones, Matthew, Conflict and Confrontation in South East Asia , 1961 – 1965, (Cambridge: CUP, 2002). 7 A spokesman at the Bureau of Asian...Stanford: Stanford University Press, 2010. Jones, Matthew. Conflict and Confrontation in South East Asia , 1961 – 1965. Cambridge: CUP, 2002...greater role in influencing events in the Asia -Pacific region. This strategic decision is complicated by the fact that the United States is trying to

Both a frameshift and a missense mutation of the STRA6 gene observed in an infant with the Matthew-Wood syndrome.

PubMed

Sadowski, Samantha; Chassaing, Nicolas; Gaj, Zuzanna; Czichos, Ewa; Wilczynski, Jan; Nowakowska, Dorota

2017-03-01

The Matthew-Wood syndrome is associated with mutations of the STRA6 gene. It combines a pulmonary agenesis/hypoplasia; microphthalmia/anophthalmia; congenital cardiac, digestive, and urogenital malformations; and diaphragmatic defects. A 23-year-old nulliparous woman was referred to our center after a fetal ultrasound examination at 26 weeks of pregnancy revealed an abnormal head shape, a heart malformation, multiple cysts in both kidneys, and dilated ureters. A male baby (46, XY; 3600g; Apgar score 1) was delivered at 38 weeks of gestation and died 1 hr later due to respiratory failure. The diagnosis of Matthew-Wood syndrome was suspected given the association of bilateral anophthalmia, agenesis of the left lung, and heart and kidney defects. It was confirmed by the identification of two deleterious mutations of the STRA6 gene. The child was a compound heterozygote for two previously reported mutations, a paternally inherited missense mutation (c.878C>T [p.Pro293Leu] and a maternally inherited frameshift mutation (c.50_52delACTinsCC [p. Asp17Alafs*55]), producing a premature stop codon. The diagnosis of Matthew-Wood syndrome should be considered in all fetuses with microphthalmia/anophthalmia. It requires an extensive ultrasound/MRI examination of the lung, heart, and diaphragm. Birth Defects Research 109:251-253, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Tests of Hypotheses Arising In the Correlated Random Coefficient Model*

PubMed Central

Heckman, James J.; Schmierer, Daniel

2010-01-01

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model. PMID:21170148

Which brain networks related to art perception are we talking about?. Comment on "Move me, astonish me…" delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates; by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Ayala, Francisco J.; Cela-Conde, Camilo J.

2017-07-01

The proposal by the Vienna Integrated Model of Art Perception (Pelowski et al., [4]; VIMAP, hereafter) is a valuable and much needed attempt to summarize and understand the cognitive processes underlying art perception. Very important in their model is, as expected, to ascertain the psychological and brain processes correlated with the perception of beauty in art works. In this commentary we'll focus exclusively on the consideration of VIMAP's section 5, ;Model stages and corresponding areas of the brain.; We'll examine the evidence advanced by VIMAP in the section about brain networks related to the perception of art.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

NASA's 3D view shows Hurricane Matthew's intensity

NASA Image and Video Library

2017-12-08

Scientists use satellite data to peer into the massive storm – learning how and why it changed throughout its course. More info: www.nasa.gov/matthew NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Addressing Uncertainty in Signal Propagation and Sensor Performance Predictions

DTIC Science & Technology

2008-11-01

Army Engineer Research and Develop- ment Center (ERDC) AT42 work package Environmental Awareness for Sensor Employment (EASE). M. S. Lewis is an Oak...L. Pettit, Sean Mackay, Matthew S. Lewis , and Peter M. Seman November 2008 C ol d R eg io n s R es ea rc h an d E n gi n ee ri n g La b...Propagation and Sensor Performance Predictions D. Keith Wilson, Matthew S. Lewis , and Peter M. Seman Cold Regions Research and Engineering Laboratory

Proceedings of the 2012 Model-Based Systems Engineering Symposium, 27 - 28 November 2012, DSTO Edinburgh, South Australia

DTIC Science & Technology

2013-02-01

2 : REBUILDING THE TOWER OF BABEL – BETTER COMMUNICATION WITH STANDARDS – MATTHEW HAUSE ...................... 99 UNCLASSIFIED UNCLASSIFIED...Communications with  Standards Matthew Hause,  Object Management Group 9:30 A Proposed Pattern of Enterprise Architecture Dr Clive Boughton 10:00...complete a project at lower cost inevitably results in longer schedules or reduced capability/lower quality. As the standard saying goes today, “faster

Proceedings of the 2012 Model-Based Systems Engineering Symposium, 27 - 28 November 2012, DSTO Edinburgh, South Australia

DTIC Science & Technology

2012-11-01

2 : REBUILDING THE TOWER OF BABEL – BETTER COMMUNICATION WITH STANDARDS – MATTHEW HAUSE ...................... 99 UNCLASSIFIED UNCLASSIFIED...Communications with  Standards Matthew Hause,  Object Management Group 9:30 A Proposed Pattern of Enterprise Architecture Dr Clive Boughton 10:00...complete a project at lower cost inevitably results in longer schedules or reduced capability/lower quality. As the standard saying goes today, “faster

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-13

Members of the Disaster Assessment and Recovery Team (DART) repair a section of roof atop the Operations Support Building II at NASA’s Kennedy Space Center in Florida. The effort is part of the spaceport’s ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-13

Tubing provides ventilation through boarded-up windows on the Operations Support Building II at NASA’s Kennedy Space Center in Florida. Members of the Disaster Assessment and Recovery Team (DART) are working on repairs to the facility following Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-13

Members of the Disaster Assessment and Recovery Team (DART) work on repairs to the Operations Support Building II at NASA’s Kennedy Space Center in Florida. The effort is part of the spaceport’s ongoing recovery from Hurricane Matthew, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

Distance correlation methods for discovering associations in large astrophysical databases

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

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P., E-mail: elizabeth.martinez@itam.mx, E-mail: mrichards@astro.psu.edu, E-mail: richards@stat.psu.edu

2014-01-20

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension,more » can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.« less

Clustering Coefficients for Correlation Networks.

PubMed

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.

Clustering Coefficients for Correlation Networks

PubMed Central

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

Phenotypic spectrum of STRA6 mutations: from Matthew-Wood syndrome to non-lethal anophthalmia.

PubMed

Chassaing, Nicolas; Golzio, Christelle; Odent, Sylvie; Lequeux, Léopoldine; Vigouroux, Adeline; Martinovic-Bouriel, Jelena; Tiziano, Francesco Danilo; Masini, Lucia; Piro, Francesca; Maragliano, Giovanna; Delezoide, Anne-Lise; Attié-Bitach, Tania; Manouvrier-Hanu, Sylvie; Etchevers, Heather C; Calvas, Patrick

2009-05-01

Matthew-Wood, Spear, PDAC or MCOPS9 syndrome are alternative names used to refer to combinations of microphthalmia/anophthalmia, malformative cardiac defects, pulmonary dysgenesis, and diaphragmatic hernia. Recently, mutations in STRA6, encoding a membrane receptor for vitamin A-bearing plasma retinol binding protein, have been identified in such patients. We performed STRA6 molecular analysis in three fetuses and one child diagnosed with Matthew-Wood syndrome and in three siblings where two adult living brothers are affected with combinations of clinical anophthalmia, tetralogy of Fallot, and mental retardation. Among these patients, six novel mutations were identified, bringing the current total of known STRA6 mutations to seventeen. We extensively reviewed clinical data pertaining to all twenty-one reported patients with STRA6 mutations (the seven of this report and fourteen described elsewhere) and discuss additional features that may be part of the syndrome. The clinical spectrum associated with STRA6 deficiency is even more variable than initially described. Copyright 2009 Wiley-Liss, Inc.

The Matthew effect in science funding.

PubMed

Bol, Thijs; de Vaan, Mathijs; van de Rijt, Arnout

2018-05-08

A classic thesis is that scientific achievement exhibits a "Matthew effect": Scientists who have previously been successful are more likely to succeed again, producing increasing distinction. We investigate to what extent the Matthew effect drives the allocation of research funds. To this end, we assembled a dataset containing all review scores and funding decisions of grant proposals submitted by recent PhDs in a €2 billion granting program. Analyses of review scores reveal that early funding success introduces a growing rift, with winners just above the funding threshold accumulating more than twice as much research funding (€180,000) during the following eight years as nonwinners just below it. We find no evidence that winners' improved funding chances in subsequent competitions are due to achievements enabled by the preceding grant, which suggests that early funding itself is an asset for acquiring later funding. Surprisingly, however, the emergent funding gap is partly created by applicants, who, after failing to win one grant, apply for another grant less often.

Cumulative advantages and the emergence of social and ethnic inequality: Matthew effects in reading and mathematics development within elementary schools?

PubMed

Baumert, Jürgen; Nagy, Gabriel; Lehmann, Rainer

2012-01-01

This article examines the development of social and ethnic disparities in academic achievement in elementary schooling. It investigated whether reading and mathematics development in 136 mixed-ability classes shows path-dependent processes of cumulative advantage (Matthew effects) from Grades 4 to 6 (Grade 4 mean age = 10.62, SD = 0.57) resulting in growing inequality. Status-dependent processes of cumulative advantage, their interaction with path-dependent processes, and consequences for the degree of social and ethnic inequality are examined. Two complementary methods for analyzing multilevel data are used: growth curve and quasi-simplex models. No evidence for a Matthew effect was found in either domain. A compensation effect emerged for reading, to the benefit of ethnic minorities. A fan-spread effect was found for mathematics, partly attributable to status-dependent processes of cumulative advantage. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

The Attenuation of Correlation Coefficients: A Statistical Literacy Issue

ERIC Educational Resources Information Center

Trafimow, David

2016-01-01

Much of the science reported in the media depends on correlation coefficients. But the size of correlation coefficients depends, in part, on the reliability with which the correlated variables are measured. Understanding this is a statistical literacy issue.

Identification of Correlated GRACE Monthly Harmonic Coefficients Using Pattern Recognition and Neural Networks

NASA Astrophysics Data System (ADS)

Piretzidis, D.; Sra, G.; Sideris, M. G.

2016-12-01

This study explores new methods for identifying correlation errors in harmonic coefficients derived from monthly solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission using pattern recognition and neural network algorithms. These correlation errors are evidenced in the differences between monthly solutions and can be suppressed using a de-correlation filter. In all studies so far, the implementation of the de-correlation filter starts from a specific minimum order (i.e., 11 for RL04 and 38 for RL05) until the maximum order of the monthly solution examined. This implementation method has two disadvantages, namely, the omission of filtering correlated coefficients of order less than the minimum order and the filtering of uncorrelated coefficients of order higher than the minimum order. In the first case, the filtered solution is not completely free of correlated errors, whereas the second case results in a monthly solution that suffers from loss of geophysical signal. In the present study, a new method of implementing the de-correlation filter is suggested, by identifying and filtering only the coefficients that show indications of high correlation. Several numerical and geometric properties of the harmonic coefficient series of all orders are examined. Extreme cases of both correlated and uncorrelated coefficients are selected, and their corresponding properties are used to train a two-layer feed-forward neural network. The objective of the neural network is to identify and quantify the correlation by providing the probability of an order of coefficients to be correlated. Results show good performance of the neural network, both in the validation stage of the training procedure and in the subsequent use of the trained network to classify independent coefficients. The neural network is also capable of identifying correlated coefficients even when a small number of training samples and neurons are used (e.g.,100 and 10, respectively).

Modeling Electronic-Nuclear Interactions for Excitation Energy Transfer Processes in Light-Harvesting Complexes.

PubMed

Lee, Mi Kyung; Coker, David F

2016-08-18

An accurate approach for computing intermolecular and intrachromophore contributions to spectral densities to describe the electronic-nuclear interactions relevant for modeling excitation energy transfer processes in light harvesting systems is presented. The approach is based on molecular dynamics (MD) calculations of classical correlation functions of long-range contributions to excitation energy fluctuations and a separate harmonic analysis and single-point gradient quantum calculations for electron-intrachromophore vibrational couplings. A simple model is also presented that enables detailed analysis of the shortcomings of standard MD-based excitation energy fluctuation correlation function approaches. The method introduced here avoids these problems, and its reliability is demonstrated in accurate predictions for bacteriochlorophyll molecules in the Fenna-Matthews-Olson pigment-protein complex, where excellent agreement with experimental spectral densities is found. This efficient approach can provide instantaneous spectral densities for treating the influence of fluctuations in environmental dissipation on fast electronic relaxation.

General Matthew B. Ridgway: Attributes of Battle Command and Decision-Making

DTIC Science & Technology

1998-02-13

information dominance require the attributes of future battle commanders be different than those of the past? This paper focuses on the intellectual and personality traits of General Matthew B. Ridgway as they apply to operational command and decision-making. These traits are considered essential for analysis and serve as a framework in which to examine their applicability to future command. The essential qualities of an operational commander are divided into two categories: intellect and personality. Each category is further divided into elemental traits. The application

DART Support for Hurricane Matthew

NASA Image and Video Library

2016-10-26

Following Hurricane Matthew, repairs have been made to the roof of the Operations Support Building (OSB) II in the Launch Complex 39 area at NASA's Kennedy Space Center in Florida. Assessments and repairs continue on various structures and facilities across the spaceport, part of the ongoing recovery from the storm, which passed to the east of Kennedy on Oct. 6 and 7, 2016. The center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected.

Legends Lecture Series III

NASA Image and Video Library

2011-07-27

Marina Benigno (far right) at Stennis Space Center, welcomes former administrative assistants and secretaries to the third Legends Lecture Series session. Lecture participants spoke about their work experiences with Stennis directors and deputy directors. Panel participants included Janet Austill (l to r), Mary Lou Matthews, Helen Paul, Wanda Howard, Ann Westendorf and Mary Gene Dick. Austill, Howard and Westendorf all worked with center directors during their Stennis careers. Dick, Matthews and Paul served with deputy directors at Stennis. The Legends Lecture Series is part of a yearlong celebration of the 50th anniversary of Stennis Space Center.

Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways.

PubMed

Chen, Lei; Zhang, Yu-Hang; Wang, ShaoPeng; Zhang, YunHua; Huang, Tao; Cai, Yu-Dong

2017-01-01

Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.

Developing and validating predictive decision tree models from mining chemical structural fingerprints and high-throughput screening data in PubChem.

PubMed

Han, Lianyi; Wang, Yanli; Bryant, Stephen H

2008-09-25

Recent advances in high-throughput screening (HTS) techniques and readily available compound libraries generated using combinatorial chemistry or derived from natural products enable the testing of millions of compounds in a matter of days. Due to the amount of information produced by HTS assays, it is a very challenging task to mine the HTS data for potential interest in drug development research. Computational approaches for the analysis of HTS results face great challenges due to the large quantity of information and significant amounts of erroneous data produced. In this study, Decision Trees (DT) based models were developed to discriminate compound bioactivities by using their chemical structure fingerprints provided in the PubChem system http://pubchem.ncbi.nlm.nih.gov. The DT models were examined for filtering biological activity data contained in four assays deposited in the PubChem Bioassay Database including assays tested for 5HT1a agonists, antagonists, and HIV-1 RT-RNase H inhibitors. The 10-fold Cross Validation (CV) sensitivity, specificity and Matthews Correlation Coefficient (MCC) for the models are 57.2 approximately 80.5%, 97.3 approximately 99.0%, 0.4 approximately 0.5 respectively. A further evaluation was also performed for DT models built for two independent bioassays, where inhibitors for the same HIV RNase target were screened using different compound libraries, this experiment yields enrichment factor of 4.4 and 9.7. Our results suggest that the designed DT models can be used as a virtual screening technique as well as a complement to traditional approaches for hits selection.

COUSCOus: improved protein contact prediction using an empirical Bayes covariance estimator.

PubMed

Rawi, Reda; Mall, Raghvendra; Kunji, Khalid; El Anbari, Mohammed; Aupetit, Michael; Ullah, Ehsan; Bensmail, Halima

2016-12-15

The post-genomic era with its wealth of sequences gave rise to a broad range of protein residue-residue contact detecting methods. Although various coevolution methods such as PSICOV, DCA and plmDCA provide correct contact predictions, they do not completely overlap. Hence, new approaches and improvements of existing methods are needed to motivate further development and progress in the field. We present a new contact detecting method, COUSCOus, by combining the best shrinkage approach, the empirical Bayes covariance estimator and GLasso. Using the original PSICOV benchmark dataset, COUSCOus achieves mean accuracies of 0.74, 0.62 and 0.55 for the top L/10 predicted long, medium and short range contacts, respectively. In addition, COUSCOus attains mean areas under the precision-recall curves of 0.25, 0.29 and 0.30 for long, medium and short contacts and outperforms PSICOV. We also observed that COUSCOus outperforms PSICOV w.r.t. Matthew's correlation coefficient criterion on full list of residue contacts. Furthermore, COUSCOus achieves on average 10% more gain in prediction accuracy compared to PSICOV on an independent test set composed of CASP11 protein targets. Finally, we showed that when using a simple random forest meta-classifier, by combining contact detecting techniques and sequence derived features, PSICOV predictions should be replaced by the more accurate COUSCOus predictions. We conclude that the consideration of superior covariance shrinkage approaches will boost several research fields that apply the GLasso procedure, amongst the presented one of residue-residue contact prediction as well as fields such as gene network reconstruction.

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

PubMed

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.

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images

PubMed Central

Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

2016-01-01

Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions. PMID:28154470

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images.

PubMed

Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

2016-05-26

Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions.

A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts

PubMed Central

Pizzo, Fabiola; Lombardo, Anna; Manganaro, Alberto; Benfenati, Emilio

2016-01-01

The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides in vitro approaches, computational methods in toxicology are drawing attention. We built a structure-activity relationship (SAR) model for evaluating hepatotoxicity. After compiling a data set of 950 compounds using data from the literature, we randomly split it into training (80%) and test sets (20%). We also compiled an external validation set (101 compounds) for evaluating the performance of the model. To extract structural alerts (SAs) related to hepatotoxicity and non-hepatotoxicity we used SARpy, a statistical application that automatically identifies and extracts chemical fragments related to a specific activity. We also applied the chemical grouping approach for manually identifying other SAs. We calculated accuracy, specificity, sensitivity and Matthews correlation coefficient (MCC) on the training, test and external validation sets. Considering the complexity of the endpoint, the model performed well. In the training, test and external validation sets the accuracy was respectively 81, 63, and 68%, specificity 89, 33, and 33%, sensitivity 93, 88, and 80% and MCC 0.63, 0.27, and 0.13. Since it is preferable to overestimate hepatotoxicity rather than not to recognize unsafe compounds, the model's architecture followed a conservative approach. As it was built using human data, it might be applied without any need for extrapolation from other species. This model will be freely available in the VEGA platform. PMID:27920722

Multiple machine learning based descriptive and predictive workflow for the identification of potential PTP1B inhibitors.

PubMed

Chandra, Sharat; Pandey, Jyotsana; Tamrakar, Akhilesh Kumar; Siddiqi, Mohammad Imran

2017-01-01

In insulin and leptin signaling pathway, Protein-Tyrosine Phosphatase 1B (PTP1B) plays a crucial controlling role as a negative regulator, which makes it an attractive therapeutic target for both Type-2 Diabetes (T2D) and obesity. In this work, we have generated classification models by using the inhibition data set of known PTP1B inhibitors to identify new inhibitors of PTP1B utilizing multiple machine learning techniques like naïve Bayesian, random forest, support vector machine and k-nearest neighbors, along with structural fingerprints and selected molecular descriptors. Several models from each algorithm have been constructed and optimized, with the different combination of molecular descriptors and structural fingerprints. For the training and test sets, most of the predictive models showed more than 90% of overall prediction accuracies. The best model was obtained with support vector machine approach and has Matthews Correlation Coefficient of 0.82 for the external test set, which was further employed for the virtual screening of Maybridge small compound database. Five compounds were subsequently selected for experimental assay. Out of these two compounds were found to inhibit PTP1B with significant inhibitory activity in in-vitro inhibition assay. The structural fragments which are important for PTP1B inhibition were identified by naïve Bayesian method and can be further exploited to design new molecules around the identified scaffolds. The descriptive and predictive modeling strategy applied in this study is capable of identifying PTP1B inhibitors from the large compound libraries. Copyright © 2016 Elsevier Inc. All rights reserved.

Signal peptide discrimination and cleavage site identification using SVM and NN.

PubMed

Kazemian, H B; Yusuf, S A; White, K

2014-02-01

About 15% of all proteins in a genome contain a signal peptide (SP) sequence, at the N-terminus, that targets the protein to intracellular secretory pathways. Once the protein is targeted correctly in the cell, the SP is cleaved, releasing the mature protein. Accurate prediction of the presence of these short amino-acid SP chains is crucial for modelling the topology of membrane proteins, since SP sequences can be confused with transmembrane domains due to similar composition of hydrophobic amino acids. This paper presents a cascaded Support Vector Machine (SVM)-Neural Network (NN) classification methodology for SP discrimination and cleavage site identification. The proposed method utilises a dual phase classification approach using SVM as a primary classifier to discriminate SP sequences from Non-SP. The methodology further employs NNs to predict the most suitable cleavage site candidates. In phase one, a SVM classification utilises hydrophobic propensities as a primary feature vector extraction using symmetric sliding window amino-acid sequence analysis for discrimination of SP and Non-SP. In phase two, a NN classification uses asymmetric sliding window sequence analysis for prediction of cleavage site identification. The proposed SVM-NN method was tested using Uni-Prot non-redundant datasets of eukaryotic and prokaryotic proteins with SP and Non-SP N-termini. Computer simulation results demonstrate an overall accuracy of 0.90 for SP and Non-SP discrimination based on Matthews Correlation Coefficient (MCC) tests using SVM. For SP cleavage site prediction, the overall accuracy is 91.5% based on cross-validation tests using the novel SVM-NN model. © 2013 Published by Elsevier Ltd.

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

PubMed

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.

Atorvastatin effect evaluation based on feature combination of three-dimension ultrasound images

NASA Astrophysics Data System (ADS)

Luo, Yongkang; Ding, Mingyue

2016-03-01

In the past decades, stroke has become the worldwide common cause of death and disability. It is well known that ischemic stroke is mainly caused by carotid atherosclerosis. As an inexpensive, convenient and fast means of detection, ultrasound technology is applied widely in the prevention and treatment of carotid atherosclerosis. Recently, many studies have focused on how to quantitatively evaluate local arterial effects of medicine treatment for carotid diseases. So the evaluation method based on feature combination was proposed to detect potential changes in the carotid arteries after atorvastatin treatment. And the support vector machine (SVM) and 10-fold cross-validation protocol were utilized on a database of 5533 carotid ultrasound images of 38 patients (17 atorvastatin groups and 21 placebo groups) at baseline and after 3 months of the treatment. With combination optimization of many features (including morphological and texture features), the evaluation results of single feature and different combined features were compared. The experimental results showed that the performance of single feature is poor and the best feature combination have good recognition ability, with the accuracy 92.81%, sensitivity 80.95%, specificity 95.52%, positive predictive value 80.47%, negative predictive value 95.65%, Matthew's correlation coefficient 76.27%, and Youden's index 76.48%. And the receiver operating characteristic (ROC) curve was also performed well with 0.9663 of the area under the ROC curve (AUC), which is better than all the features with 0.9423 of the AUC. Thus, it is proved that this novel method can reliably and accurately evaluate the effect of atorvastatin treatment.

Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines.

PubMed

Majid, Abdul; Ali, Safdar; Iqbal, Mubashar; Kausar, Nabeela

2014-03-01

This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The structural effects of mutations can aid in differential phenotype prediction of beta-myosin heavy chain (Myosin-7) missense variants.

PubMed

Al-Numair, Nouf S; Lopes, Luis; Syrris, Petros; Monserrat, Lorenzo; Elliott, Perry; Martin, Andrew C R

2016-10-01

High-throughput sequencing platforms are increasingly used to screen patients with genetic disease for pathogenic mutations, but prediction of the effects of mutations remains challenging. Previously we developed SAAPdap (Single Amino Acid Polymorphism Data Analysis Pipeline) and SAAPpred (Single Amino Acid Polymorphism Predictor) that use a combination of rule-based structural measures to predict whether a missense genetic variant is pathogenic. Here we investigate whether the same methodology can be used to develop a differential phenotype predictor, which, once a mutation has been predicted as pathogenic, is able to distinguish between phenotypes-in this case the two major clinical phenotypes (hypertrophic cardiomyopathy, HCM and dilated cardiomyopathy, DCM) associated with mutations in the beta-myosin heavy chain (MYH7) gene product (Myosin-7). A random forest predictor trained on rule-based structural analyses together with structural clustering data gave a Matthews' correlation coefficient (MCC) of 0.53 (accuracy, 75%). A post hoc removal of machine learning models that performed particularly badly, increased the performance (MCC = 0.61, Acc = 79%). This proof of concept suggests that methods used for pathogenicity prediction can be extended for use in differential phenotype prediction. Analyses were implemented in Perl and C and used the Java-based Weka machine learning environment. Please contact the authors for availability. andrew@bioinf.org.uk or andrew.martin@ucl.ac.uk Supplementary data are available at Bioinformatics online. © The Authors 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A novel fractal approach for predicting G-protein-coupled receptors and their subfamilies with support vector machines.

PubMed

Nie, Guoping; Li, Yong; Wang, Feichi; Wang, Siwen; Hu, Xuehai

2015-01-01

G-protein-coupled receptors (GPCRs) are seven membrane-spanning proteins and regulate many important physiological processes, such as vision, neurotransmission, immune response and so on. GPCRs-related pathways are the targets of a large number of marketed drugs. Therefore, the design of a reliable computational model for predicting GPCRs from amino acid sequence has long been a significant biomedical problem. Chaos game representation (CGR) reveals the fractal patterns hidden in protein sequences, and then fractal dimension (FD) is an important feature of these highly irregular geometries with concise mathematical expression. Here, in order to extract important features from GPCR protein sequences, CGR algorithm, fractal dimension and amino acid composition (AAC) are employed to formulate the numerical features of protein samples. Four groups of features are considered, and each group is evaluated by support vector machine (SVM) and 10-fold cross-validation test. To test the performance of the present method, a new non-redundant dataset was built based on latest GPCRDB database. Comparing the results of numerical experiments, the group of combined features with AAC and FD gets the best result, the accuracy is 99.22% and Matthew's correlation coefficient (MCC) is 0.9845 for identifying GPCRs from non-GPCRs. Moreover, if it is classified as a GPCR, it will be further put into the second level, which will classify a GPCR into one of the five main subfamilies. At this level, the group of combined features with AAC and FD also gets best accuracy 85.73%. Finally, the proposed predictor is also compared with existing methods and shows better performances.

Predictions of BuChE inhibitors using support vector machine and naive Bayesian classification techniques in drug discovery.

PubMed

Fang, Jiansong; Yang, Ranyao; Gao, Li; Zhou, Dan; Yang, Shengqian; Liu, Ai-Lin; Du, Guan-hua

2013-11-25

Butyrylcholinesterase (BuChE, EC 3.1.1.8) is an important pharmacological target for Alzheimer's disease (AD) treatment. However, the currently available BuChE inhibitor screening assays are expensive, labor-intensive, and compound-dependent. It is necessary to develop robust in silico methods to predict the activities of BuChE inhibitors for the lead identification. In this investigation, support vector machine (SVM) models and naive Bayesian models were built to discriminate BuChE inhibitors (BuChEIs) from the noninhibitors. Each molecule was initially represented in 1870 structural descriptors (1235 from ADRIANA.Code, 334 from MOE, and 301 from Discovery studio). Correlation analysis and stepwise variable selection method were applied to figure out activity-related descriptors for prediction models. Additionally, structural fingerprint descriptors were added to improve the predictive ability of models, which were measured by cross-validation, a test set validation with 1001 compounds and an external test set validation with 317 diverse chemicals. The best two models gave Matthews correlation coefficient of 0.9551 and 0.9550 for the test set and 0.9132 and 0.9221 for the external test set. To demonstrate the practical applicability of the models in virtual screening, we screened an in-house data set with 3601 compounds, and 30 compounds were selected for further bioactivity assay. The assay results showed that 10 out of 30 compounds exerted significant BuChE inhibitory activities with IC50 values ranging from 0.32 to 22.22 μM, at which three new scaffolds as BuChE inhibitors were identified for the first time. To our best knowledge, this is the first report on BuChE inhibitors using machine learning approaches. The models generated from SVM and naive Bayesian approaches successfully predicted BuChE inhibitors. The study proved the feasibility of a new method for predicting bioactivities of ligands and discovering novel lead compounds.

Quantum coupled mutation finder: predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming.

PubMed

Gültas, Mehmet; Düzgün, Güncel; Herzog, Sebastian; Jäger, Sven Joachim; Meckbach, Cornelia; Wingender, Edgar; Waack, Stephan

2014-04-03

The identification of functionally or structurally important non-conserved residue sites in protein MSAs is an important challenge for understanding the structural basis and molecular mechanism of protein functions. Despite the rich literature on compensatory mutations as well as sequence conservation analysis for the detection of those important residues, previous methods often rely on classical information-theoretic measures. However, these measures usually do not take into account dis/similarities of amino acids which are likely to be crucial for those residues. In this study, we present a new method, the Quantum Coupled Mutation Finder (QCMF) that incorporates significant dis/similar amino acid pair signals in the prediction of functionally or structurally important sites. The result of this study is twofold. First, using the essential sites of two human proteins, namely epidermal growth factor receptor (EGFR) and glucokinase (GCK), we tested the QCMF-method. The QCMF includes two metrics based on quantum Jensen-Shannon divergence to measure both sequence conservation and compensatory mutations. We found that the QCMF reaches an improved performance in identifying essential sites from MSAs of both proteins with a significantly higher Matthews correlation coefficient (MCC) value in comparison to previous methods. Second, using a data set of 153 proteins, we made a pairwise comparison between QCMF and three conventional methods. This comparison study strongly suggests that QCMF complements the conventional methods for the identification of correlated mutations in MSAs. QCMF utilizes the notion of entanglement, which is a major resource of quantum information, to model significant dissimilar and similar amino acid pair signals in the detection of functionally or structurally important sites. Our results suggest that on the one hand QCMF significantly outperforms the previous method, which mainly focuses on dissimilar amino acid signals, to detect essential sites in proteins. On the other hand, it is complementary to the existing methods for the identification of correlated mutations. The method of QCMF is computationally intensive. To ensure a feasible computation time of the QCMF's algorithm, we leveraged Compute Unified Device Architecture (CUDA).The QCMF server is freely accessible at http://qcmf.informatik.uni-goettingen.de/.

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

PubMed

Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M

2007-09-01

We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

2013-09-01

In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

Factors That Attenuate the Correlation Coefficient and Its Analogs.

ERIC Educational Resources Information Center

Dolenz, Beverly

The correlation coefficient is an integral part of many other statistical techniques (analysis of variance, t-tests, etc.), since all analytic methods are actually correlational (G. V. Glass and K. D. Hopkins, 1984). The correlation coefficient is a statistical summary that represents the degree and direction of relationship between two variables.…

Innovation Expo

NASA Image and Video Library

2017-10-31

U.S. Patent plaques were awarded to, second from left, Mark Lewis, Adam Dokos, Robert Mueller, Jeffrey Carlson and Ivan Townsend III, for their invention, Dust Tolerant Connectors, during the 2017 Innovation Expo at NASA's Kennedy Space Center in Florida. Not pictured: Gary Basin, Matthew Branch, Kevin Murtland, Matthew Nugent and Gabor Tamasy. At left is Kelvin Manning, Kennedy's associate director. At far right is Dave Makufka, Kennedy's Technology Transfer Program manager. The purpose of the annual two-day expo is to help foster innovation and creativity among the Kennedy workforce. The event included several keynote speakers, training opportunities, an innovation showcase and the KSC Kickstart competition.

A new method for probabilistic assessment of regional climate impacts in dependence of cumulative GHG emission budgets

NASA Astrophysics Data System (ADS)

Frieler, Katja; Meinshausen, Malte; Braun, Nadine; Hare, Bill

2010-05-01

Given the expected and already observed impacts of climate change there is growing agreement that global mean temperature rise should be limited to below 2 or 1.5 degrees. The translation of such a temperature target into guidelines for global emission reduction over the coming decades has become one of the most important and urgent tasks. In fact, there are four recent studies (Meinshausen et al. 2009, Allen et al. 2009, Matthews et al. 2009 and Zickfeld et al. 2009) which take a very comprehensive approach to quantifying the current uncertainties related to the question of what are the "allowed amounts" of global emissions given specific limits of global warming. Here, we present an extension of this budget approach allowing to focus on specific regional impacts. The method is based on probabilistic projections of regional temperature and precipitation changes providing the input for available impact functions. Using the example of Greenland's surface mass balance (Gregory et al., 2006) we will demonstrate how the probability of specific impacts can be described in dependence of global GHG emission budgets taking into account the uncertainty of global mean temperature projections as well as uncertainties of regional climate patterns varying from AOGCM to AOGCM. The method utilizes the AOGCM based linear relation between global mean temperature changes and regionally averaged changes in temperature and precipitation. It allows to handle the variations of regional climate projections from AR4 AOGCM runs independent of the uncertainties of global mean temperature change that are estimated by a simple climate model (Meinshausen et al., 2009). While the linearity of this link function is already established for temperature and to a lesser degree (depending on the region) also for precipitation (Santer et al. 1990; Mitchell et al. 1999; Giorgi et al., 2008; Solomon et al., 2009), we especially focus on the quantification of the uncertainty (in particularly the inter-AOGCM variations) of the associated scaling coefficients. Our approach is based on a linear mixed effects model (e.g. Bates and Pinheiro, 2001). In comparison to other scaling approaches we do not fit separate models for the temperature and precipitation data but we apply a two-dimensional model, i.e., we explicitly account for the fact that models (scenarios or runs) showing an especially high temperature increase may also show high precipitation increases or vice versa. Coupling the two-dimensional distribution of the scaling coefficients with the uncertainty distributions of global mean temperature change given different GHG emission trajectories finally provides time series of two dimensional uncertainty distributions of regional changes in temperature and precipitation, where both components might be correlated. These samples provide the input for regional specific impact functions. In case of Greenland we use a function by Gregory et al., 2006 that allows us to calculate changes in sea level rise due to changes in Greenland's surface mass balance in dependence of regionally averaged changes in temperature and precipitation. The precipitation signal turns out to be relatively strong for Greenland with AOGCMs consistently showing increasing precipitation with increasing global mean temperature. In addition, temperature and precipitation increases turned out to be highly correlated for Greenland: Models showing an especially high temperature increase also show high precipitation increases reflected by a correlation coefficient of 0.88 for the inter-model variations of both components of the scaling coefficients. Taking these correlations into account is especially important because the surface mass balance of the Greenland ice sheet critically depends on the interaction of the temperature and precipitation component of climate change: Increasing precipitation may at least partly balance the loss due to increasing temperatures.

ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.

PubMed

Kim, Seongho

2015-11-01

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market

NASA Astrophysics Data System (ADS)

Sun, Xuelian; Liu, Zixian

2016-02-01

In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.

Relationships among the slopes of lines derived from various data analysis techniques and the associated correlation coefficient

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1980-01-01

A technique for fitting a straight line to a collection of data points is given. The relationships between the slopes and correlation coefficients, and between the corresponding standard deviations and correlation coefficient are given.

Extracellular overproduction and preliminary crystallographic analysis of a family I.3 lipase

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

Angkawidjaja, Clement; You, Dong-Ju; Matsumura, Hiroyoshi

2007-03-01

A family I.3 lipase from Pseudomonas sp. MIS38 was secreted from Escherichia coli cells to the external medium, purified and crystallized and preliminary crystallographic studies were performed. A family I.3 lipase from Pseudomonas sp. MIS38 was secreted from Escherichia coli cells to the external medium, purified and crystallized and preliminary crystallographic studies were performed. The crystal was grown at 277 K by the hanging-drop vapour-diffusion method. Native X-ray diffraction data were collected to 1.7 Å resolution using synchrotron radiation at station BL38B1, SPring-8. The crystal belongs to space group P2{sub 1}, with unit-cell parameters a = 48.79, b = 84.06,more » c = 87.04 Å. Assuming the presence of one molecule per asymmetric unit, the Matthews coefficient V{sub M} was calculated to be 2.73 Å{sup 3} Da{sup −1} and the solvent content was 55%.« less

Purification, crystallization, preliminary X-ray diffraction and molecular-replacement studies of great cormorant (Phalacrocorax carbo) haemoglobin

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

Jagadeesan, G.; Malathy, P.; Gunasekaran, K.

2014-10-25

The great cormorant hemoglobin has been isolated, purified and crystallized and the three dimensional structure is solved using molecular replacement technique. Haemoglobin is the iron-containing oxygen-transport metalloprotein that is present in the red blood cells of all vertebrates. In recent decades, there has been substantial interest in attempting to understand the structural basis and functional diversity of avian haemoglobins. Towards this end, purification, crystallization, preliminary X-ray diffraction and molecular-replacement studies have been carried out on cormorant (Phalacrocorax carbo) haemoglobin. Crystals were grown by the hanging-drop vapour-diffusion method using PEG 3350, NaCl and glycerol as precipitants. The crystals belonged to themore » trigonal system P3{sub 1}21, with unit-cell parameters a = b = 55.64, c = 153.38 Å, β = 120.00°; a complete data set was collected to a resolution of 3.5 Å. Matthews coefficient analysis indicated that the crystals contained a half-tetramer in the asymmetric unit.« less

Synthesis, purification and crystallographic studies of the C-terminal sterol carrier protein type 2 (SCP-2) domain of human hydroxysteroid dehydrogenase-like protein 2.

PubMed

Cheng, Zhong; Li, Yao; Sui, Chun; Sun, Xiaobo; Xie, Yong

2015-07-01

Human hydroxysteroid dehydrogenase-like protein 2 (HSDL2) is a member of the short-chain dehydrogenase/reductase (SDR) subfamily of oxidoreductases and contains an N-terminal catalytic domain and a C-termianl sterol carrier protein type 2 (SCP-2) domain. In this study, the C-terminal SCP-2 domain of human HSDL2, including residues Lys318-Arg416, was produced in Escherichia coli, purified and crystallized. X-ray diffraction data were collected to 2.10 Å resolution. The crystal belonged to the trigonal space group P3(1)21 (or P3(2)21), with unit-cell parameters a = b = 70.4, c = 60.6 Å, α = β = 90, γ = 120°. Two protein molecules are present in the asymmetric unit, resulting in a Matthews coefficient of 2.16 Å(3) Da(-1) and an approximate solvent content of 43%.

Expression, purification and preliminary X-ray analysis of the C-terminal domain of an arginine repressor protein from Mycobacterium tuberculosis

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

Lu, George J.; Garen, Craig R.; Cherney, Maia M.

2007-11-01

The C-terminal portion of the arginine repressor protein from M. tuberculosis H37Rv has been crystallized. The complete transcriptional factor regulates arginine biosynthesis by binding operator DNA when arginine is bound at the C-terminal domain. The gene product of an open reading frame Rv1657 from Mycobacterium tuberculosis is a putative arginine repressor protein (ArgR), a transcriptional factor that regulates the expression of arginine-biosynthetic enzymes. Rv1657 was expressed and purified and a C-terminal domain was crystallized using the hanging-drop vapour-diffusion method. Diffraction data were collected and processed to a resolution of 2.15 Å. The crystals belong to space group P1 and themore » Matthews coefficient suggests that the crystals contain six C-terminal domain molecules per unit cell. Previous structural and biochemical studies on the arginine repressor proteins from other organisms have likewise shown the presence of six molecules per unit cell.« less

Crystallization of Δ1-tetrahydrocannabinolic acid (THCA) synthase from Cannabis sativa

PubMed Central

Shoyama, Yoshinari; Takeuchi, Ayako; Taura, Futoshi; Tamada, Taro; Adachi, Motoyasu; Kuroki, Ryota; Shoyama, Yukihiro; Morimoto, Satoshi

2005-01-01

Δ1-Tetrahydrocannabinolic acid (THCA) synthase is a novel oxidoreductase that catalyzes the biosynthesis of the psychoactive compound THCA in Cannabis sativa (Mexican strain). In order to investigate the structure–function relationship of THCA synthase, this enzyme was overproduced in insect cells, purified and finally crystallized in 0.1 M HEPES buffer pH 7.5 containing 1.4 M sodium citrate. A single crystal suitable for X-ray diffraction measurement was obtained in 0.09 M HEPES buffer pH 7.5 containing 1.26 M sodium citrate. The crystal diffracted to 2.7 Å resolution at beamline BL41XU, SPring-8. The crystal belonged to the primitive cubic space group P432, with unit-cell parameters a = b = c = 178.2 Å. The calculated Matthews coefficient was approximately 4.1 or 2.0 Å3 Da−1 assuming the presence of one or two molecules of THCA synthase in the asymmetric unit, respectively. PMID:16511162

Expression, crystallization and preliminary crystallographic analysis of the extracellular IgV-like domain of the human natural killer cell inhibitory receptor p75/AIRM1.

PubMed

Dimasi, Nazzareno; Moretta, Lorenzo; Biassoni, Roberto; Mariuzza, Roy A

2003-10-01

p75/AIRM1 (Siglec-7) is a sialic acid-binding Ig-like lectin recently identified as an inhibitory receptor on natural killer cells. The expression, in vitro folding, circular-dichroism spectroscopy, crystallization and preliminary X-ray characterization of the Ig-V like domain of p75/AIRM1 are reported. X-ray data were collected from a single crystal at 100 K, with a maximum useful diffraction pattern extending to 1.45 A resolution on a synchrotron source. The crystal belongs to a primitive monoclinic space group, with unit-cell parameters a = 32.65, b = 49.72, c = 39.79 A, alpha = gamma = 90, beta = 113 degrees. The systematic absences indicate that the space group is P2(1). Assuming one molecule per asymmetric unit, V(M) (the Matthews coefficient) was calculated to be 1.879 A(3) Da(-1) and the solvent content was estimated to be 32.01%.

Crystallization and preliminary X-ray crystallographic analysis of carboxyl-terminal region 4 of SigR from Streptomyces coelicolor A3(2)

PubMed Central

Kim, Keon Young; Kim, Sunmin; Park, Jeong Kuk; Song, HyoJin; Park, SangYoun

2014-01-01

Full-length SigR from Streptomyces coelicolor A3(2) was overexpressed in Escherichia coli, purified and submitted to crystallization trials using either polyethylene glycol 3350 or 4000 as a precipitant. X-ray diffraction data were collected to 2.60 Å resolution under cryoconditions using synchrotron X-rays. The crystal packs in space group P43212, with unit-cell parameters a = b = 42.14, c = 102.02 Å. According to the Matthews coefficient, the crystal asymmetric unit cannot contain the full-length protein. Molecular replacement with the known structures of region 2 and region 4 as independent search models indicates that the crystal contains only the −35 element-binding carboxyl-terminal region 4 of full-length SigR. Mass-spectrometric analysis of the harvested crystal confirms this, suggesting a crystal volume per protein weight (V M) of 2.24 Å3 Da−1 and 45.1% solvent content. PMID:24915084

3,6-Anhydro-L-galactonate cycloisomerase from Vibrio sp. strain EJY3: crystallization and X-ray crystallographic analysis.

PubMed

Lee, Saeyoung; Yun, Eun Ju; Kim, Kyoung Heon; Kim, Hye Yeon; Choi, In Geol

2017-09-01

3,6-Anhydro-L-galactonate cycloisomerase (ACI), which is found in the marine bacterium Vibrio sp. strain EJY3, converts 3,6-anhydro-L-galactonate into 2-keto-3-deoxygalactonate. ACI is a key enzyme in the metabolic pathway of 3,6-anhydro-L-galactose (AHG). Study of AHG metabolism is important for the efficient fermentation of agar and biofuel production, because AHG is a sugar that is non-fermentable by commercial microorganisms. The aci gene from Vibrio sp. strain EJY3 was cloned, and the recombinant protein was overexpressed and crystallized in order to determine the structure and understand the function of the protein. The crystals diffracted to 2.2 Å resolution and belonged to space group P4 1 2 1 2 or P4 3 2 1 2, with unit-cell parameters a = b = 87.9, c = 143.5 Å. The Matthews coefficient was 2.3 Å 3  Da -1 , with a solvent content of 47%.

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2017-07-01

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (p<0.0001), I 2 =73%, test for overall effect Z=8.67 (p<0.00001). ADC min correlated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Correlation of human papillomavirus status with apparent diffusion coefficient of diffusion-weighted MRI in head and neck squamous cell carcinomas.

PubMed

Driessen, Juliette P; van Bemmel, Alexander J M; van Kempen, Pauline M W; Janssen, Luuk M; Terhaard, Chris H J; Pameijer, Frank A; Willems, Stefan M; Stegeman, Inge; Grolman, Wilko; Philippens, Marielle E P

2016-04-01

Identification of prognostic patient characteristics in head and neck squamous cell carcinoma (HNSCC) is of great importance. Human papillomavirus (HPV)-positive HNSCCs have favorable response to (chemo)radiotherapy. Apparent diffusion coefficient, derived from diffusion-weighted MRI, has also shown to predict treatment response. The purpose of this study was to evaluate the correlation between HPV status and apparent diffusion coefficient. Seventy-three patients with histologically proven HNSCC were retrospectively analyzed. Mean pretreatment apparent diffusion coefficient was calculated by delineation of total tumor volume on diffusion-weighted MRI. HPV status was analyzed and correlated to apparent diffusion coefficient. Six HNSCCs were HPV-positive. HPV-positive HNSCC showed significantly lower apparent diffusion coefficient compared to HPV-negative. This correlation was independent of other patient characteristics. In HNSCC, positive HPV status correlates with low mean apparent diffusion coefficient. The favorable prognostic value of low pretreatment apparent diffusion coefficient might be partially attributed to patients with a positive HPV status. © 2015 Wiley Periodicals, Inc. Head Neck 38: E613-E618, 2016. © 2015 Wiley Periodicals, Inc.

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

PubMed Central

Someswara Rao, Chinta; Viswanadha Raju, S.

2016-01-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc. PMID:26981409

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures.

PubMed

Someswara Rao, Chinta; Viswanadha Raju, S

2016-03-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.

Simulation study of 2D spectrum of molecular aggregates coupled to correlated vibrations

NASA Astrophysics Data System (ADS)

Abramavicius, Darius; Butkus, Vytautas; Valkunas, Leonas; Mukamel, Shaul

2011-03-01

Oscillatory dynamics of two-dimensional (2D) spectra of photosynthetic pigment-protein complexes raise the questions of how to disentangle various origins of these oscillations, which may include quantum beats, quantum transport, or molecular vibrations. We study the effects of correlated overdamped fluctuations and under-damped vibrations on the 2D spectra of Fenna-Matthews-Olson (FMO) aggregate, which has well-resolved exciton resonances, and a circular porphyrin aggregate (P6), whose absorption shows vibrational progression. We use a generic exciton Hamiltonian coupled to a bath, characterized by a spectral density. Fluctuations have smooth, while vibtations have δ -type spectral densities. We show how various scenarios of correlated molecular fluctuations lead to some highly oscillatory crosspeaks. Molecular vibrations cause progression of diagonal peaks in the 2D spectrum and make their corresponding cross-peaks highly oscillatory. We, thus, demonstrate that bath fluctuations and molecular vibrations of realistic molecular aggregates are highly entangled in 2D spectroscopy. DA acknowledges grant VP1-3.1-SMM-07-V, SM - the grants CHE0745892 (NSF), DRPA BAA-10-40 QUBE.

Correlation coefficient measurement of the mode-locked laser tones using four-wave mixing.

PubMed

Anthur, Aravind P; Panapakkam, Vivek; Vujicic, Vidak; Merghem, Kamel; Lelarge, Francois; Ramdane, Abderrahim; Barry, Liam P

2016-06-01

We use four-wave mixing to measure the correlation coefficient of comb tones in a quantum-dash mode-locked laser under passive and active locked regimes. We study the uncertainty in the measurement of the correlation coefficient of the proposed method.

Challenge of assessing symptoms in seriously ill intensive care unit patients: can proxy reporters help?

PubMed

Puntillo, Kathleen A; Neuhaus, John; Arai, Shoshana; Paul, Steven M; Gropper, Michael A; Cohen, Neal H; Miaskowski, Christine

2012-10-01

Determine levels of agreement among intensive care unit patients and their family members, nurses, and physicians (proxies) regarding patients' symptoms and compare levels of mean intensity (i.e., the magnitude of a symptom sensation) and distress (i.e., the degree of emotionality that a symptom engenders) of symptoms among patients and proxy reporters. Prospective study of proxy reporters of symptoms in seriously ill patients. Two intensive care units in a tertiary medical center in the Western United States. Two hundred and forty-five intensive care unit patients, 243 family members, 103 nurses, and 92 physicians. None. On the basis of the magnitude of intraclass correlation coefficients, where coefficients from .35 to .78 are considered to be appropriately robust, correlation coefficients between patients' and family members' ratings met this criterion (≥.35) for intensity in six of ten symptoms. No intensity ratings between patients and nurses had intraclass correlation coefficients >.32. Three symptoms had intensity correlation coefficients of ≥.36 between patients' and physicians' ratings. Correlation coefficients between patients and family members were >.40 for five symptom-distress ratings. No symptoms had distress correlation coefficients of ≥.28 between patients' and nurses' ratings. Two symptoms had symptom-distress correlation coefficients between patients' and physicians' ratings at >.39. Family members, nurses, and physicians reported higher symptom-intensity scores than patients did for 80%, 60%, and 60% of the symptoms, respectively. Family members, nurses, and physicians reported higher symptom-distress scores than patients did for 90%, 70%, and 80% of the symptoms, respectively. Patient-family intraclass correlation coefficients were sufficiently close for us to consider using family members to help assess intensive care unit patients' symptoms. Relatively low intraclass correlation coefficients between intensive care unit clinicians' and patients' symptom ratings indicate that some proxy raters overestimate whereas others underestimate patients' symptoms. Proxy overestimation of patients' symptom scores warrants further study because this may influence decisions about treating patients' symptoms.

Empirical correlations for axial dispersion coefficient and Peclet number in fixed-bed columns.

PubMed

Rastegar, Seyed Omid; Gu, Tingyue

2017-03-24

In this work, a new correlation for the axial dispersion coefficient was obtained using experimental data in the literature for axial dispersion in fixed-bed columns packed with particles. The Chung and Wen correlation, the De Ligny correlation are two popular empirical correlations. However, the former lacks the molecular diffusion term and the latter does not consider bed voidage. The new axial dispersion coefficient correlation in this work was based on additional experimental data in the literature by considering both molecular diffusion and bed voidage. It is more comprehensive and accurate. The Peclet number correlation from the new axial dispersion coefficient correlation on the average leads to 12% lower Peclet number values compared to the values from the Chung and Wen correlation, and in many cases much smaller than those from the De Ligny correlation. Copyright © 2017 Elsevier B.V. All rights reserved.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Ugliness as the fourth wall-breaker. Comment on "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Ishizu, Tomohiro; Sakamoto, Yasuhiro

2017-07-01

In this extensive and valuable theoretical article, Pelowski et al. propose a psychological architecture in art appreciation by introducing the concepts of early/bottom-up and relatively late/top-down stages. The former is dictated as automatic processing on perceptual features of visual images, while the latter comprises cognitive and evaluative processes where modulations from acquired knowledge and memories come into play with recurrent loops to form final experiences, as well as brain areas/networks which possibly have a role in each processing component [9].

Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

PubMed Central

Ackerman, Matthew S.; Johri, Parul; Spitze, Ken; Xu, Sen; Doak, Thomas G.; Young, Kimberly; Lynch, Michael

2017-01-01

Population structure can be described by genotypic-correlation coefficients between groups of individuals, the most basic of which are the pairwise relatedness coefficients between any two individuals. There are nine pairwise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates all seven reduced coefficients from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone mates. Statistically significant negative estimates of these pairwise relatedness coefficients, including inbreeding coefficients that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent. PMID:28341647

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

A beach area is seen during a survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

NASA SAVE Award Winner

NASA Image and Video Library

2012-01-09

NASA Goddard Space Flight Center Financial Manager and White House 2011 SAVE award winner Matthew Ritsko is seen during a television interview at NASA Headquarters shortly after meeting with President Obama at the White House on Monday, Jan. 9, 2011, in Washington. The Presidential Securing Americans' Value and Efficiency (SAVE) program gives front-line federal workers the chance to submit their ideas on how their agencies can save money and work more efficiently. Matthew's proposal calls for NASA to create a "lending library" where specialized space tools and hardware purchased by one NASA organization will be made available to other NASA programs and projects. Photo Credit: (NASA/Bill Ingalls)

Remembering John M. Olson (1929-2017).

PubMed

Blankenship, Robert E; Brune, Daniel C; Olson, Jon C

2018-02-19

Here we provide reflections of and a tribute to John M. Olson, a pioneering researcher in photosynthesis. We trace his career, which began at Wesleyan University and the University of Pennsylvania, and continued at Utrech in The Netherlands, Brookhaven National Laboratory, and Odense University in Denmark. He was the world expert on pigment organization in the green photosynthetic bacteria, and discovered and characterized the first chlorophyll-containing protein, which has come to be known as the Fenna-Matthews-Olson (FMO) protein. He also thought and wrote extensively on the origin and early evolution of photosynthesis. We include personal comments from Brian Matthews, Raymond Cox, Paolo Gerola, Beverly Pierson and Jon Olson.

Global data bases on distribution, characteristics and methane emission of natural wetlands: Documentation of archived data tape

NASA Technical Reports Server (NTRS)

Matthews, Elaine

1989-01-01

Global digital data bases on the distribution and environmental characteristics of natural wetlands, compiled by Matthews and Fung (1987), were archived for public use. These data bases were developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. Five global 1 deg latitude by 1 deg longitude arrays are included on the archived tape. The arrays are: (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type. The first three data bases on wetland locations were published by Matthews and Fung (1987). The last two arrays contain ancillary information about these wetland locations: vegetation type is from the data of Matthews (1983) and soil type from the data of Zobler (1986). Users should consult original publications for complete discussion of the data bases. This short paper is designed only to document the tape, and briefly explain the data sets and their initial application to estimating the annual emission of methane from natural wetlands. Included is information about array characteristics such as dimensions, read formats, record lengths, blocksizes and value ranges, and descriptions and translation tables for the individual data bases.

Living shorelines enhanced the resilience of saltmarshes to Hurricane Matthew (2016).

PubMed

Smith, Carter S; Puckett, Brandon; Gittman, Rachel K; Peterson, Charles H

2018-06-01

Nature-based solutions, such as living shorelines, have the potential to restore critical ecosystems, enhance coastal sustainability, and increase resilience to natural disasters; however, their efficacy during storm events compared to traditional hardened shorelines is largely untested. This is a major impediment to their implementation and promotion to policy-makers and homeowners. To address this knowledge gap, we evaluated rock sill living shorelines as compared to natural marshes and hardened shorelines (i.e., bulkheads) in North Carolina, USA for changes in surface elevation, Spartina alterniflora stem density, and structural damage from 2015 to 2017, including before and after Hurricane Matthew (2016). Our results show that living shorelines exhibited better resistance to landward erosion during Hurricane Matthew than bulkheads and natural marshes. Additionally, living shorelines were more resilient than hardened shorelines, as they maintained landward elevation over the two-year study period without requiring any repair. Finally, rock sill living shorelines were able to enhance S. alterniflora stem densities over time when compared to natural marshes. Our results suggest that living shorelines have the potential to improve coastal resilience while supporting important coastal ecosystems. © 2018 by the Ecological Society of America.

Hurricane Matthew (2016) and its Storm Surge Inundation under Global Warming Scenarios: Application of an Interactively Coupled Atmosphere-Ocean Model

NASA Astrophysics Data System (ADS)

Jisan, M. A.; Bao, S.; Pietrafesa, L.; Pullen, J.

2017-12-01

An interactively coupled atmosphere-ocean model was used to investigate the impacts of future ocean warming, both at the surface and the layers below, on the track and intensity of a hurricane and its associated storm surge and inundation. The category-5 hurricane Matthew (2016), which made landfall on the South Carolina coast of the United States, was used for the case study. Future ocean temperature changes and sea level rise (SLR) were estimated based on the projection of Inter-Governmental Panel on Climate Change (IPCC)'s Representative Concentration Pathway scenarios RCP 2.6 and RCP 8.5. After being validated with the present-day observational data, the model was applied to simulate the changes in track, intensity, storm surge and inundation that Hurricane Matthew would cause under future climate change scenarios. It was found that a significant increase in hurricane intensity, storm surge water level, and inundation area for Hurricane Matthew under future ocean warming and SLR scenarios. For example, under the RCP 8.5 scenario, the maximum wind speed would increase by 17 knots (14.2%), the minimum sea level pressure would decrease by 26 hPa (2.85%), and the inundated area would increase by 401 km2 (123%). By including the effect of SLR for the middle-21st-century scenario, the inundated area will further increase by up to 49.6%. The increase in the hurricane intensity and the inundated area was also found for the RCP 2.6 scenario. The response of sea surface temperature was analyzed to investigate the change in intensity. A comparison was made between the impacts when only the sea surface warming is considered versus when both the sea surface and the underneath layers are considered. These results showed that even without the effect of SLR, the storm surge level and the inundated area would be higher due to the increased hurricane intensity under the influence of the future warmer ocean temperature. The coupled effect of ocean warming and SLR would cause the hurricane-induced storm surge and inundation to be amplified. The relative importance of the ocean warming versus the SLR was evaluated. Keywords: Hurricane Matthew, Global Warming, Coupled Atmosphere-Ocean Model, Air-Sea interactions, Storm Surge, Inundation

Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…

Thin and Slow Smoke Detection by Using Frequency Image

NASA Astrophysics Data System (ADS)

Zheng, Guang; Oe, Shunitiro

In this paper, a new method to detect thin and slow smoke for early fire alarm by using frequency image has been proposed. The correlation coefficient of the frequency image between the current stage and the initial stage are calculated, so are the gray image correlation coefficient of the color image. When the thin smoke close to transparent enters into the camera view, the correlation coefficient of the frequency image becomes small, while the gray image correlation coefficient of the color image hardly change and keep large. When something which is not transparent, like human beings, etc., enters into the camera view, the correlation coefficient of the frequency image becomes small, as well as that of color image. Based on the difference of correlation coefficient between frequency image and color image in different situations, the thin smoke can be detected. Also, considering the movement of the thin smoke, miss detection caused by the illustration change or noise can be avoided. Several experiments in different situations are carried out, and the experimental results show the effect of the proposed method.

Statistical Study of Turbulence: Spectral Functions and Correlation Coefficients

NASA Technical Reports Server (NTRS)

Frenkiel, Francois N.

1958-01-01

In reading the publications on turbulence of different authors, one often runs the risk of confusing the various correlation coefficients and turbulence spectra. We have made a point of defining, by appropriate concepts, the differences which exist between these functions. Besides, we introduce in the symbols a few new characteristics of turbulence. In the first chapter, we study some relations between the correlation coefficients and the different turbulence spectra. Certain relations are given by means of demonstrations which could be called intuitive rather than mathematical. In this way we demonstrate that the correlation coefficients between the simultaneous turbulent velocities at two points are identical, whether studied in Lagrange's or in Euler's systems. We then consider new spectra of turbulence, obtained by study of the simultaneous velocities along a straight line of given direction. We determine some relations between these spectra and the correlation coefficients. Examining the relation between the spectrum of the turbulence measured at a fixed point and the longitudinal-correlation curve given by G. I. Taylor, we find that this equation is exact only when the coefficient is very small.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

PubMed

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient

NASA Astrophysics Data System (ADS)

Wang, Fang; Wang, Lin; Chen, Yuming

2018-03-01

Recently, based on analogous height cross-correlation analysis (AHXA), a cross-correlation coefficient ρ×(L) has been proposed to quantify the levels of cross-correlation on different temporal scales for bivariate series. A limitation of this coefficient is that it cannot capture the full information of cross-correlations on amplitude of fluctuations. In fact, it only detects the cross-correlation at a specific order fluctuation, which might neglect some important information inherited from other order fluctuations. To overcome this disadvantage, in this work, based on the scaling of the qth order covariance and time delay L, we define a two-parameter dependent cross-correlation coefficient ρq(L) to detect and quantify the range and level of cross-correlations. This new version of ρq(L) coefficient leads to the formation of a ρq(L) surface, which not only is able to quantify the level of cross-correlations, but also allows us to identify the range of fluctuation amplitudes that are correlated in two given signals. Applications to the classical ARFIMA models and the binomial multifractal series illustrate the feasibility of this new coefficient ρq(L) . In addition, a statistical test is proposed to quantify the existence of cross-correlations between two given series. Applying our method to the real life empirical data from the 1999-2000 California electricity market, we find that the California power crisis in 2000 destroys the cross-correlation between the price and the load series but does not affect the correlation of the load series during and before the crisis.

Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander's overlap coefficient.

PubMed

Adler, Jeremy; Parmryd, Ingela

2010-08-01

The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.

Can Imaging Parameters Provide Information Regarding Histopathology in Head and Neck Squamous Cell Carcinoma? A Meta-Analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2018-04-01

Our purpose was to provide data regarding relationships between different imaging and histopathological parameters in HNSCC. MEDLINE library was screened for associations between different imaging parameters and histopathological features in HNSCC up to December 2017. Only papers containing correlation coefficients between different imaging parameters and histopathological findings were acquired for the analysis. Associations between 18 F-FDG positron emission tomography (PET) and KI 67 were reported in 8 studies (236 patients). The pooled correlation coefficient was 0.20 (95% CI = [-0.04; 0.44]). Furthermore, in 4 studies (64 patients), associations between 18 F-fluorothymidine PET and KI 67 were analyzed. The pooled correlation coefficient between SUV max and KI 67 was 0.28 (95% CI = [-0.06; 0.94]). In 2 studies (23 patients), relationships between KI 67 and dynamic contrast-enhanced magnetic resonance imaging were reported. The pooled correlation coefficient between K trans and KI 67 was -0.68 (95% CI = [-0.91; -0.44]). Two studies (31 patients) investigated correlation between apparent diffusion coefficient (ADC) and KI 67. The pooled correlation coefficient was -0.61 (95% CI = [-0.84; -0.38]). In 2 studies (117 patients), relationships between 18 F-FDG PET and p53 were analyzed. The pooled correlation coefficient was 0.0 (95% CI = [-0.87; 0.88]). There were 3 studies (48 patients) that investigated associations between ADC and tumor cell count in HNSCC. The pooled correlation coefficient was -0.53 (95% CI = [-0.74; -0.32]). Associations between 18 F-FDG PET and HIF-1α were investigated in 3 studies (72 patients). The pooled correlation coefficient was 0.44 (95% CI = [-0.20; 1.08]). ADC may predict cell count and proliferation activity, and SUV max may predict expression of HIF-1α in HNSCC. SUV max cannot be used as surrogate marker for expression of KI 67 and p53. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

In silico models for predicting ready biodegradability under REACH: a comparative study.

PubMed

Pizzo, Fabiola; Lombardo, Anna; Manganaro, Alberto; Benfenati, Emilio

2013-10-01

REACH (Registration Evaluation Authorization and restriction of Chemicals) legislation is a new European law which aims to raise the human protection level and environmental health. Under REACH all chemicals manufactured or imported for more than one ton per year must be evaluated for their ready biodegradability. Ready biodegradability is also used as a screening test for persistent, bioaccumulative and toxic (PBT) substances. REACH encourages the use of non-testing methods such as QSAR (quantitative structure-activity relationship) models in order to save money and time and to reduce the number of animals used for scientific purposes. Some QSAR models are available for predicting ready biodegradability. We used a dataset of 722 compounds to test four models: VEGA, TOPKAT, BIOWIN 5 and 6 and START and compared their performance on the basis of the following parameters: accuracy, sensitivity, specificity and Matthew's correlation coefficient (MCC). Performance was analyzed from different points of view. The first calculation was done on the whole dataset and VEGA and TOPKAT gave the best accuracy (88% and 87% respectively). Then we considered the compounds inside and outside the training set: BIOWIN 6 and 5 gave the best results for accuracy (81%) outside training set. Another analysis examined the applicability domain (AD). VEGA had the highest value for compounds inside the AD for all the parameters taken into account. Finally, compounds outside the training set and in the AD of the models were considered to assess predictive ability. VEGA gave the best accuracy results (99%) for this group of chemicals. Generally, START model gave poor results. Since BIOWIN, TOPKAT and VEGA models performed well, they may be used to predict ready biodegradability. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of ready biodegradation estimation methods for fragrance materials.

PubMed

Boethling, Robert

2014-11-01

Biodegradability is fundamental to the assessment of environmental exposure and risk from organic chemicals. Predictive models can be used to pursue both regulatory and chemical design (green chemistry) objectives, which are most effectively met when models are easy to use and available free of charge. The objective of this work was to evaluate no-cost estimation programs with respect to prediction of ready biodegradability. Fragrance materials, which are structurally diverse and have significant exposure potential, were used for this purpose. Using a database of 222 fragrance compounds with measured ready biodegradability, 10 models were compared on the basis of overall accuracy, sensitivity, specificity, and Matthews correlation coefficient (MCC), a measure of quality for binary classification. The 10 models were VEGA© Non-Interactive Client, START (Toxtree©), Biowin©1-6, and two models based on inductive machine learning. Applicability domain (AD) was also considered. Overall accuracy was ca. 70% and varied little over all models, but sensitivity, specificity and MCC showed wider variation. Based on MCC, the best models for fragrance compounds were Biowin6, VEGA and Biowin3. VEGA performance was slightly better for the <50% of the compounds it identified as having "high reliability" predictions (AD index >0.8). However, removing compounds with one and only one quaternary carbon yielded similar improvement in predictivity for VEGA, START, and Biowin3/6, with a smaller penalty in reduced coverage. Of the nine compounds for which the eight models (VEGA, START, Biowin1-6) all disagreed with the measured value, measured analog data were available for seven, and all supported the predicted value. VEGA, Biowin3 and Biowin6 are judged suitable for ready biodegradability screening of fragrance compounds. Published by Elsevier B.V.

An Ensemble Method to Distinguish Bacteriophage Virion from Non-Virion Proteins Based on Protein Sequence Characteristics.

PubMed

Zhang, Lina; Zhang, Chengjin; Gao, Rui; Yang, Runtao

2015-09-09

Bacteriophage virion proteins and non-virion proteins have distinct functions in biological processes, such as specificity determination for host bacteria, bacteriophage replication and transcription. Accurate identification of bacteriophage virion proteins from bacteriophage protein sequences is significant to understand the complex virulence mechanism in host bacteria and the influence of bacteriophages on the development of antibacterial drugs. In this study, an ensemble method for bacteriophage virion protein prediction from bacteriophage protein sequences is put forward with hybrid feature spaces incorporating CTD (composition, transition and distribution), bi-profile Bayes, PseAAC (pseudo-amino acid composition) and PSSM (position-specific scoring matrix). When performing on the training dataset 10-fold cross-validation, the presented method achieves a satisfactory prediction result with a sensitivity of 0.870, a specificity of 0.830, an accuracy of 0.850 and Matthew's correlation coefficient (MCC) of 0.701, respectively. To evaluate the prediction performance objectively, an independent testing dataset is used to evaluate the proposed method. Encouragingly, our proposed method performs better than previous studies with a sensitivity of 0.853, a specificity of 0.815, an accuracy of 0.831 and MCC of 0.662 on the independent testing dataset. These results suggest that the proposed method can be a potential candidate for bacteriophage virion protein prediction, which may provide a useful tool to find novel antibacterial drugs and to understand the relationship between bacteriophage and host bacteria. For the convenience of the vast majority of experimental Int. J. Mol. Sci. 2015, 16,21735 scientists, a user-friendly and publicly-accessible web-server for the proposed ensemble method is established.

Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds.

PubMed

Cannon, Edward O; Amini, Ata; Bender, Andreas; Sternberg, Michael J E; Muggleton, Stephen H; Glen, Robert C; Mitchell, John B O

2007-05-01

We investigate the classification performance of circular fingerprints in combination with the Naive Bayes Classifier (MP2D), Inductive Logic Programming (ILP) and Support Vector Inductive Logic Programming (SVILP) on a standard molecular benchmark dataset comprising 11 activity classes and about 102,000 structures. The Naive Bayes Classifier treats features independently while ILP combines structural fragments, and then creates new features with higher predictive power. SVILP is a very recently presented method which adds a support vector machine after common ILP procedures. The performance of the methods is evaluated via a number of statistical measures, namely recall, specificity, precision, F-measure, Matthews Correlation Coefficient, area under the Receiver Operating Characteristic (ROC) curve and enrichment factor (EF). According to the F-measure, which takes both recall and precision into account, SVILP is for seven out of the 11 classes the superior method. The results show that the Bayes Classifier gives the best recall performance for eight of the 11 targets, but has a much lower precision, specificity and F-measure. The SVILP model on the other hand has the highest recall for only three of the 11 classes, but generally far superior specificity and precision. To evaluate the statistical significance of the SVILP superiority, we employ McNemar's test which shows that SVILP performs significantly (p < 5%) better than both other methods for six out of 11 activity classes, while being superior with less significance for three of the remaining classes. While previously the Bayes Classifier was shown to perform very well in molecular classification studies, these results suggest that SVILP is able to extract additional knowledge from the data, thus improving classification results further.

O-GlcNAcPRED-II: an integrated classification algorithm for identifying O-GlcNAcylation sites based on fuzzy undersampling and a K-means PCA oversampling technique.

PubMed

Jia, Cangzhi; Zuo, Yun; Zou, Quan; Hancock, John

2018-02-06

Protein O-GlcNAcylation (O-GlcNAc) is an important post-translational modification of serine (S)/threonine (T) residues that involves multiple molecular and cellular processes. Recent studies have suggested that abnormal O-G1cNAcylation causes many diseases, such as cancer and various neurodegenerative diseases. With the available protein O-G1cNAcylation sites experimentally verified, it is highly desired to develop automated methods to rapidly and effectively identify O-G1cNAcylation sites. Although some computational methods have been proposed, their performance has been unsatisfactory, particularly in terms of prediction sensitivity. In this study, we developed an ensemble model O-GlcNAcPRED-II to identify potential O-G1cNAcylation sites. A K-means principal component analysis oversampling technique (KPCA) and fuzzy undersampling method (FUS) were first proposed and incorporated to reduce the proportion of the original positive and negative training samples. Then, rotation forest, a type of classifier-integrated system, was adopted to divide the eight types of feature space into several subsets using four sub-classifiers: random forest, k-nearest neighbour, naive Bayesian and support vector machine. We observed that O-GlcNAcPRED-II achieved a sensitivity of 81.05%, specificity of 95.91%, accuracy of 91.43% and Matthew's correlation coefficient of 0.7928 for five-fold cross-validation run 10 times. Additionally, the results obtained by O-GlcNAcPRED-II on two independent datasets also indicated that the proposed predictor outperformed five published prediction tools. http://121.42.167.206/OGlcPred/. cangzhijia@dlmu.edu.cn or zouquan@nclab.net. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Indexing molecules for their hERG liability.

PubMed

Rayan, Anwar; Falah, Mizied; Raiyn, Jamal; Da'adoosh, Beny; Kadan, Sleman; Zaid, Hilal; Goldblum, Amiram

2013-07-01

The human Ether-a-go-go-Related-Gene (hERG) potassium (K(+)) channel is liable to drug-inducing blockage that prolongs the QT interval of the cardiac action potential, triggers arrhythmia and possibly causes sudden cardiac death. Early prediction of drug liability to hERG K(+) channel is therefore highly important and preferably obligatory at earlier stages of any drug discovery process. In vitro assessment of drug binding affinity to hERG K(+) channel involves substantial expenses, time, and labor; and therefore computational models for predicting liabilities of drug candidates for hERG toxicity is of much importance. In the present study, we apply the Iterative Stochastic Elimination (ISE) algorithm to construct a large number of rule-based models (filters) and exploit their combination for developing the concept of hERG Toxicity Index (ETI). ETI estimates the molecular risk to be a blocker of hERG potassium channel. The area under the curve (AUC) of the attained model is 0.94. The averaged ETI of hERG binders, drugs from CMC, clinical-MDDR, endogenous molecules, ACD and ZINC, were found to be 9.17, 2.53, 3.3, -1.98, -2.49 and -3.86 respectively. Applying the proposed hERG Toxicity Index Model on external test set composed of more than 1300 hERG blockers picked from chEMBL shows excellent performance (Matthews Correlation Coefficient of 0.89). The proposed strategy could be implemented for the evaluation of chemicals in the hit/lead optimization stages of the drug discovery process, improve the selection of drug candidates as well as the development of safe pharmaceutical products. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

New clustered regularly interspaced short palindromic repeat locus spacer pair typing method based on the newly incorporated spacer for Salmonella enterica.

PubMed

Li, Hao; Li, Peng; Xie, Jing; Yi, Shengjie; Yang, Chaojie; Wang, Jian; Sun, Jichao; Liu, Nan; Wang, Xu; Wu, Zhihao; Wang, Ligui; Hao, Rongzhang; Wang, Yong; Jia, Leili; Li, Kaiqin; Qiu, Shaofu; Song, Hongbin

2014-08-01

A clustered regularly interspaced short palindromic repeat (CRISPR) typing method has recently been developed and used for typing and subtyping of Salmonella spp., but it is complicated and labor intensive because it has to analyze all spacers in two CRISPR loci. Here, we developed a more convenient and efficient method, namely, CRISPR locus spacer pair typing (CLSPT), which only needs to analyze the two newly incorporated spacers adjoining the leader array in the two CRISPR loci. We analyzed a CRISPR array of 82 strains belonging to 21 Salmonella serovars isolated from humans in different areas of China by using this new method. We also retrieved the newly incorporated spacers in each CRISPR locus of 537 Salmonella isolates which have definite serotypes in the Pasteur Institute's CRISPR Database to evaluate this method. Our findings showed that this new CLSPT method presents a high level of consistency (kappa = 0.9872, Matthew's correlation coefficient = 0.9712) with the results of traditional serotyping, and thus, it can also be used to predict serotypes of Salmonella spp. Moreover, this new method has a considerable discriminatory power (discriminatory index [DI] = 0.8145), comparable to those of multilocus sequence typing (DI = 0.8088) and conventional CRISPR typing (DI = 0.8684). Because CLSPT only costs about $5 to $10 per isolate, it is a much cheaper and more attractive method for subtyping of Salmonella isolates. In conclusion, this new method will provide considerable advantages over other molecular subtyping methods, and it may become a valuable epidemiologic tool for the surveillance of Salmonella infections. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.

PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

PubMed

Islam, S M Ashiqul; Sajed, Tanvir; Kearney, Christopher Michel; Baker, Erich J

2015-07-05

Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology. We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB. PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

Predicting the Functional Impact of KCNQ1 Variants of Unknown Significance.

PubMed

Li, Bian; Mendenhall, Jeffrey L; Kroncke, Brett M; Taylor, Keenan C; Huang, Hui; Smith, Derek K; Vanoye, Carlos G; Blume, Jeffrey D; George, Alfred L; Sanders, Charles R; Meiler, Jens

2017-10-01

An emerging standard-of-care for long-QT syndrome uses clinical genetic testing to identify genetic variants of the KCNQ1 potassium channel. However, interpreting results from genetic testing is confounded by the presence of variants of unknown significance for which there is inadequate evidence of pathogenicity. In this study, we curated from the literature a high-quality set of 107 functionally characterized KCNQ1 variants. Based on this data set, we completed a detailed quantitative analysis on the sequence conservation patterns of subdomains of KCNQ1 and the distribution of pathogenic variants therein. We found that conserved subdomains generally are critical for channel function and are enriched with dysfunctional variants. Using this experimentally validated data set, we trained a neural network, designated Q1VarPred, specifically for predicting the functional impact of KCNQ1 variants of unknown significance. The estimated predictive performance of Q1VarPred in terms of Matthew's correlation coefficient and area under the receiver operating characteristic curve were 0.581 and 0.884, respectively, superior to the performance of 8 previous methods tested in parallel. Q1VarPred is publicly available as a web server at http://meilerlab.org/q1varpred. Although a plethora of tools are available for making pathogenicity predictions over a genome-wide scale, previous tools fail to perform in a robust manner when applied to KCNQ1. The contrasting and favorable results for Q1VarPred suggest a promising approach, where a machine-learning algorithm is tailored to a specific protein target and trained with a functionally validated data set to calibrate informatics tools. © 2017 American Heart Association, Inc.

Experimental validation of the RATE tool for inferring HLA restrictions of T cell epitopes.

PubMed

Paul, Sinu; Arlehamn, Cecilia S Lindestam; Schulten, Veronique; Westernberg, Luise; Sidney, John; Peters, Bjoern; Sette, Alessandro

2017-06-21

The RATE tool was recently developed to computationally infer the HLA restriction of given epitopes from immune response data of HLA typed subjects without additional cumbersome experimentation. Here, RATE was validated using experimentally defined restriction data from a set of 191 tuberculosis-derived epitopes and 63 healthy individuals with MTB infection from the Western Cape Region of South Africa. Using this experimental dataset, the parameters utilized by the RATE tool to infer restriction were optimized, which included relative frequency (RF) of the subjects responding to a given epitope and expressing a given allele as compared to the general test population and the associated p-value in a Fisher's exact test. We also examined the potential for further optimization based on the predicted binding affinity of epitopes to potential restricting HLA alleles, and the absolute number of individuals expressing a given allele and responding to the specific epitope. Different statistical measures, including Matthew's correlation coefficient, accuracy, sensitivity and specificity were used to evaluate performance of RATE as a function of these criteria. Based on our results we recommend selection of HLA restrictions with cutoffs of p-value < 0.01 and RF ≥ 1.3. The usefulness of the tool was demonstrated by inferring new HLA restrictions for epitope sets where restrictions could not be experimentally determined due to lack of necessary cell lines and for an additional data set related to recognition of pollen derived epitopes from allergic patients. Experimental data sets were used to validate RATE tool and the parameters used by the RATE tool to infer restriction were optimized. New HLA restrictions were identified using the optimized RATE tool.

A Novel Computational Method for Detecting DNA Methylation Sites with DNA Sequence Information and Physicochemical Properties.

PubMed

Pan, Gaofeng; Jiang, Limin; Tang, Jijun; Guo, Fei

2018-02-08

DNA methylation is an important biochemical process, and it has a close connection with many types of cancer. Research about DNA methylation can help us to understand the regulation mechanism and epigenetic reprogramming. Therefore, it becomes very important to recognize the methylation sites in the DNA sequence. In the past several decades, many computational methods-especially machine learning methods-have been developed since the high-throughout sequencing technology became widely used in research and industry. In order to accurately identify whether or not a nucleotide residue is methylated under the specific DNA sequence context, we propose a novel method that overcomes the shortcomings of previous methods for predicting methylation sites. We use k -gram, multivariate mutual information, discrete wavelet transform, and pseudo amino acid composition to extract features, and train a sparse Bayesian learning model to do DNA methylation prediction. Five criteria-area under the receiver operating characteristic curve (AUC), Matthew's correlation coefficient (MCC), accuracy (ACC), sensitivity (SN), and specificity-are used to evaluate the prediction results of our method. On the benchmark dataset, we could reach 0.8632 on AUC, 0.8017 on ACC, 0.5558 on MCC, and 0.7268 on SN. Additionally, the best results on two scBS-seq profiled mouse embryonic stem cells datasets were 0.8896 and 0.9511 by AUC, respectively. When compared with other outstanding methods, our method surpassed them on the accuracy of prediction. The improvement of AUC by our method compared to other methods was at least 0.0399 . For the convenience of other researchers, our code has been uploaded to a file hosting service, and can be downloaded from: https://figshare.com/s/0697b692d802861282d3.

COMSAT: Residue contact prediction of transmembrane proteins based on support vector machines and mixed integer linear programming.

PubMed

Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A

2016-03-01

In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/. © 2016 Wiley Periodicals, Inc.

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

PubMed Central

Fu, Chien-wei; Lin, Thy-Hou

2017-01-01

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. PMID:28072829

Language Individuation and Marker Words: Shakespeare and His Maxwell's Demon.

PubMed

Marsden, John; Budden, David; Craig, Hugh; Moscato, Pablo

2013-01-01

Within the structural and grammatical bounds of a common language, all authors develop their own distinctive writing styles. Whether the relative occurrence of common words can be measured to produce accurate models of authorship is of particular interest. This work introduces a new score that helps to highlight such variations in word occurrence, and is applied to produce models of authorship of a large group of plays from the Shakespearean era. A text corpus containing 55,055 unique words was generated from 168 plays from the Shakespearean era (16th and 17th centuries) of undisputed authorship. A new score, CM1, is introduced to measure variation patterns based on the frequency of occurrence of each word for the authors John Fletcher, Ben Jonson, Thomas Middleton and William Shakespeare, compared to the rest of the authors in the study (which provides a reference of relative word usage at that time). A total of 50 WEKA methods were applied for Fletcher, Jonson and Middleton, to identify those which were able to produce models yielding over 90% classification accuracy. This ensemble of WEKA methods was then applied to model Shakespearean authorship across all 168 plays, yielding a Matthews' correlation coefficient (MCC) performance of over 90%. Furthermore, the best model yielded an MCC of 99%. Our results suggest that different authors, while adhering to the structural and grammatical bounds of a common language, develop measurably distinct styles by the tendency to over-utilise or avoid particular common words and phrasings. Considering language and the potential of words as an abstract chaotic system with a high entropy, similarities can be drawn to the Maxwell's Demon thought experiment; authors subconsciously favour or filter certain words, modifying the probability profile in ways that could reflect their individuality and style.

Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set.

PubMed

Lenselink, Eelke B; Ten Dijke, Niels; Bongers, Brandon; Papadatos, George; van Vlijmen, Herman W T; Kowalczyk, Wojtek; IJzerman, Adriaan P; van Westen, Gerard J P

2017-08-14

The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different validation strategies, and different metrics. In this study, different methods were compared using one single standardized dataset obtained from ChEMBL, which is made available to the public, using standardized metrics (BEDROC and Matthews Correlation Coefficient). Specifically, the performance of Naïve Bayes, Random Forests, Support Vector Machines, Logistic Regression, and Deep Neural Networks was assessed using QSAR and proteochemometric (PCM) methods. All methods were validated using both a random split validation and a temporal validation, with the latter being a more realistic benchmark of expected prospective execution. Deep Neural Networks are the top performing classifiers, highlighting the added value of Deep Neural Networks over other more conventional methods. Moreover, the best method ('DNN_PCM') performed significantly better at almost one standard deviation higher than the mean performance. Furthermore, Multi-task and PCM implementations were shown to improve performance over single task Deep Neural Networks. Conversely, target prediction performed almost two standard deviations under the mean performance. Random Forests, Support Vector Machines, and Logistic Regression performed around mean performance. Finally, using an ensemble of DNNs, alongside additional tuning, enhanced the relative performance by another 27% (compared with unoptimized 'DNN_PCM'). Here, a standardized set to test and evaluate different machine learning algorithms in the context of multi-task learning is offered by providing the data and the protocols. Graphical Abstract .

Language Individuation and Marker Words: Shakespeare and His Maxwell's Demon

PubMed Central

Marsden, John; Budden, David; Craig, Hugh; Moscato, Pablo

2013-01-01

Background Within the structural and grammatical bounds of a common language, all authors develop their own distinctive writing styles. Whether the relative occurrence of common words can be measured to produce accurate models of authorship is of particular interest. This work introduces a new score that helps to highlight such variations in word occurrence, and is applied to produce models of authorship of a large group of plays from the Shakespearean era. Methodology A text corpus containing 55,055 unique words was generated from 168 plays from the Shakespearean era (16th and 17th centuries) of undisputed authorship. A new score, CM1, is introduced to measure variation patterns based on the frequency of occurrence of each word for the authors John Fletcher, Ben Jonson, Thomas Middleton and William Shakespeare, compared to the rest of the authors in the study (which provides a reference of relative word usage at that time). A total of 50 WEKA methods were applied for Fletcher, Jonson and Middleton, to identify those which were able to produce models yielding over 90% classification accuracy. This ensemble of WEKA methods was then applied to model Shakespearean authorship across all 168 plays, yielding a Matthews' correlation coefficient (MCC) performance of over 90%. Furthermore, the best model yielded an MCC of 99%. Conclusions Our results suggest that different authors, while adhering to the structural and grammatical bounds of a common language, develop measurably distinct styles by the tendency to over-utilise or avoid particular common words and phrasings. Considering language and the potential of words as an abstract chaotic system with a high entropy, similarities can be drawn to the Maxwell's Demon thought experiment; authors subconsciously favour or filter certain words, modifying the probability profile in ways that could reflect their individuality and style. PMID:23826143

Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS).

PubMed

Lajnef, Tarek; O'Reilly, Christian; Combrisson, Etienne; Chaibi, Sahbi; Eichenlaub, Jean-Baptiste; Ruby, Perrine M; Aguera, Pierre-Emmanuel; Samet, Mounir; Kachouri, Abdennaceur; Frenette, Sonia; Carrier, Julie; Jerbi, Karim

2017-01-01

Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Reilly et al., 2014). Importantly, the obtained scores were compared to alternative methods that were previously tested on the same database. With respect to spindle detection, our method achieved higher performance than most of the alternative methods. This was corroborated with statistic tests that took into account both sensitivity and precision (i.e., Matthew's coefficient of correlation (MCC), F1, Cohen κ). Our proposed method has been made available to the community via an open-source tool named Spinky (for spindle and K-complex detection). Thanks to a GUI implementation and access to Matlab and Python resources, Spinky is expected to contribute to an open-science approach that will enhance replicability and reliable comparisons of classifier performances for the detection of sleep EEG microstructure in both healthy and patient populations.

Defining and predicting structurally conserved regions in protein superfamilies

PubMed Central

Huang, Ivan K.; Grishin, Nick V.

2013-01-01

Motivation: The structures of homologous proteins are generally better conserved than their sequences. This phenomenon is demonstrated by the prevalence of structurally conserved regions (SCRs) even in highly divergent protein families. Defining SCRs requires the comparison of two or more homologous structures and is affected by their availability and divergence, and our ability to deduce structurally equivalent positions among them. In the absence of multiple homologous structures, it is necessary to predict SCRs of a protein using information from only a set of homologous sequences and (if available) a single structure. Accurate SCR predictions can benefit homology modelling and sequence alignment. Results: Using pairwise DaliLite alignments among a set of homologous structures, we devised a simple measure of structural conservation, termed structural conservation index (SCI). SCI was used to distinguish SCRs from non-SCRs. A database of SCRs was compiled from 386 SCOP superfamilies containing 6489 protein domains. Artificial neural networks were then trained to predict SCRs with various features deduced from a single structure and homologous sequences. Assessment of the predictions via a 5-fold cross-validation method revealed that predictions based on features derived from a single structure perform similarly to ones based on homologous sequences, while combining sequence and structural features was optimal in terms of accuracy (0.755) and Matthews correlation coefficient (0.476). These results suggest that even without information from multiple structures, it is still possible to effectively predict SCRs for a protein. Finally, inspection of the structures with the worst predictions pinpoints difficulties in SCR definitions. Availability: The SCR database and the prediction server can be found at http://prodata.swmed.edu/SCR. Contact: 91huangi@gmail.com or grishin@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics Online PMID:23193223

Prediction of hot spots in protein interfaces using a random forest model with hybrid features.

PubMed

Wang, Lin; Liu, Zhi-Ping; Zhang, Xiang-Sun; Chen, Luonan

2012-03-01

Prediction of hot spots in protein interfaces provides crucial information for the research on protein-protein interaction and drug design. Existing machine learning methods generally judge whether a given residue is likely to be a hot spot by extracting features only from the target residue. However, hot spots usually form a small cluster of residues which are tightly packed together at the center of protein interface. With this in mind, we present a novel method to extract hybrid features which incorporate a wide range of information of the target residue and its spatially neighboring residues, i.e. the nearest contact residue in the other face (mirror-contact residue) and the nearest contact residue in the same face (intra-contact residue). We provide a novel random forest (RF) model to effectively integrate these hybrid features for predicting hot spots in protein interfaces. Our method can achieve accuracy (ACC) of 82.4% and Matthew's correlation coefficient (MCC) of 0.482 in Alanine Scanning Energetics Database, and ACC of 77.6% and MCC of 0.429 in Binding Interface Database. In a comparison study, performance of our RF model exceeds other existing methods, such as Robetta, FOLDEF, KFC, KFC2, MINERVA and HotPoint. Of our hybrid features, three physicochemical features of target residues (mass, polarizability and isoelectric point), the relative side-chain accessible surface area and the average depth index of mirror-contact residues are found to be the main discriminative features in hot spots prediction. We also confirm that hot spots tend to form large contact surface areas between two interacting proteins. Source data and code are available at: http://www.aporc.org/doc/wiki/HotSpot.

Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review

PubMed Central

Cordero, David; Riccadonna, Samantha; Solé, Xavier; Crous-Bou, Marta; Guinó, Elisabet; Sanjuan, Xavier; Biondo, Sebastiano; Soriano, Antonio; Jurman, Giuseppe; Capella, Gabriel; Furlanello, Cesare; Moreno, Victor

2012-01-01

Introduction The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic. PMID:23145004

BP network for atorvastatin effect evaluation from ultrasound images features classification

NASA Astrophysics Data System (ADS)

Fang, Mengjie; Yang, Xin; Liu, Yang; Xu, Hongwei; Liang, Huageng; Wang, Yujie; Ding, Mingyue

2013-10-01

Atherosclerotic lesions at the carotid artery are a major cause of emboli or atheromatous debris, resulting in approximately 88% of ischemic strokes in the USA in 2006. Stroke is becoming the most common cause of death worldwide, although patient management and prevention strategies have reduced stroke rate considerably over the past decades. Many research studies have been carried out on how to quantitatively evaluate local arterial effects for potential carotid disease treatments. As an inexpensive, convenient and fast means of detection, ultrasonic medical testing has been widespread in the world, so it is very practical to use ultrasound technology in the prevention and treatment of carotid atherosclerosis. This paper is dedicated to this field. Currently, many ultrasound image characteristics on carotid plaque have been proposed. After screening a large number of features (including 26 morphological and 85 texture features), we have got six shape characteristics and six texture characteristics in the combination. In order to test the validity and accuracy of these combined features, we have established a Back-Propagation (BP) neural network to classify atherosclerosis plaques between atorvastatin group and placebo group. The leave-one-case-out protocol was utilized on a database of 768 carotid ultrasound images of 12 patients (5 subjects of placebo group and 7 subjects of atorvastatin group) for the evaluation. The classification results showed that the combined features and classification have good recognition ability, with the overall accuracy 83.93%, sensitivity 82.14%, specificity 85.20%, positive predictive value 79.86%, negative predictive value 86.98%, Matthew's correlation coefficient 67.08%, and Youden's index 67.34%. And the receiver operating characteristic (ROC) curve in our test also performed well.

Sensitivity of MRI parameters within intervertebral discs to the severity of adolescent idiopathic scoliosis.

PubMed

Huber, Maxime; Gilbert, Guillaume; Roy, Julien; Parent, Stefan; Labelle, Hubert; Périé, Delphine

2016-11-01

To measure magnetic resonance imaging (MRI) parameters including relaxation times (T 1 ρ, T 2 ), magnetization transfer (MT) and diffusion parameters (mean diffusivity [MD], fractional anisotropy [FA]) of intervertebral discs in adolescents with idiopathic scoliosis, and to investigate the sensitivity of these MR parameters to the severity of the spine deformities. Thirteen patients with adolescent idiopathic scoliosis and three control volunteers with no history of spine disease underwent an MRI acquisition at 3T including the mapping of T 1 ρ, T 2 , MT, MD, and FA. The apical zone included all discs within the scoliotic curve while the control zone was composed of other discs. The severity was analyzed through low (<32°) versus high (>40°) Cobb angles. One-way analysis of variance (ANOVA) and agglomerative hierarchical clustering (AHC) were performed. Significant differences were found between the apical zone and the control zone for T 2 (P = 0.047), and between low and high Cobb angles for T 2 (P = 0.014) and MT (P = 0.002). AHC showed two distinct clusters, one with mainly low Cobb angles and one with mainly high Cobb angles, for the MRI parameters measured within the apical zone, with an accuracy of 0.9 and a Matthews correlation coefficient (MCC) of 0.8. Within the control zone, the AHC showed no clear classification (accuracy of 0.6 and MCC of 0.2). We successfully performed an in vivo multiparametric MRI investigation of young patients with adolescent idiopathic scoliosis. The MRI parameters measured within the intervertebral discs were found to be sensitive to intervertebral disc degeneration occurring with scoliosis and to the severity of scoliosis. J. Magn. Reson. Imaging 2016;44:1123-1131. © 2016 International Society for Magnetic Resonance in Medicine.

A Support Vector Machine based method to distinguish proteobacterial proteins from eukaryotic plant proteins

PubMed Central

2012-01-01

Background Members of the phylum Proteobacteria are most prominent among bacteria causing plant diseases that result in a diminution of the quantity and quality of food produced by agriculture. To ameliorate these losses, there is a need to identify infections in early stages. Recent developments in next generation nucleic acid sequencing and mass spectrometry open the door to screening plants by the sequences of their macromolecules. Such an approach requires the ability to recognize the organismal origin of unknown DNA or peptide fragments. There are many ways to approach this problem but none have emerged as the best protocol. Here we attempt a systematic way to determine organismal origins of peptides by using a machine learning algorithm. The algorithm that we implement is a Support Vector Machine (SVM). Result The amino acid compositions of proteobacterial proteins were found to be different from those of plant proteins. We developed an SVM model based on amino acid and dipeptide compositions to distinguish between a proteobacterial protein and a plant protein. The amino acid composition (AAC) based SVM model had an accuracy of 92.44% with 0.85 Matthews correlation coefficient (MCC) while the dipeptide composition (DC) based SVM model had a maximum accuracy of 94.67% and 0.89 MCC. We also developed SVM models based on a hybrid approach (AAC and DC), which gave a maximum accuracy 94.86% and a 0.90 MCC. The models were tested on unseen or untrained datasets to assess their validity. Conclusion The results indicate that the SVM based on the AAC and DC hybrid approach can be used to distinguish proteobacterial from plant protein sequences. PMID:23046503

Structural protein descriptors in 1-dimension and their sequence-based predictions.

PubMed

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

PubMed

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

The forgotten artist: Why to consider intentions and interaction in a model of aesthetic experience. Comment on "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Brattico, Elvira; Brattico, Pauli; Vuust, Peter

2017-07-01

In their target article published in this journal issue, Pelowski et al. [1] address the question of how humans experience, and respond to, visual art. They propose a multi-layered model of the representations and processes involved in assessing visual art objects that, furthermore, involves both bottom-up and top-down elements. Their model provides predictions for seven different outcomes of human aesthetic experience, based on few distinct features (schema congruence, self-relevance, and coping necessity), and connects the underlying processing stages to ;specific correlates of the brain; (a similar attempt was previously done for music by [2-4]). In doing this, the model aims to account for the (often profound) experience of an individual viewer in front of an art object.

Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

PubMed

Wang, Fang; Wang, Lin; Chen, Yuming

2017-08-31

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

Limits of the memory coefficient in measuring correlated bursts

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Hiraoka, Takayuki

2018-03-01

Temporal inhomogeneities in event sequences of natural and social phenomena have been characterized in terms of interevent times and correlations between interevent times. The inhomogeneities of interevent times have been extensively studied, while the correlations between interevent times, often called correlated bursts, are far from being fully understood. For measuring the correlated bursts, two relevant approaches were suggested, i.e., memory coefficient and burst size distribution. Here a burst size denotes the number of events in a bursty train detected for a given time window. Empirical analyses have revealed that the larger memory coefficient tends to be associated with the heavier tail of the burst size distribution. In particular, empirical findings in human activities appear inconsistent, such that the memory coefficient is close to 0, while burst size distributions follow a power law. In order to comprehend these observations, by assuming the conditional independence between consecutive interevent times, we derive the analytical form of the memory coefficient as a function of parameters describing interevent time and burst size distributions. Our analytical result can explain the general tendency of the larger memory coefficient being associated with the heavier tail of burst size distribution. We also find that the apparently inconsistent observations in human activities are compatible with each other, indicating that the memory coefficient has limits to measure the correlated bursts.

Correlation Coefficients: Appropriate Use and Interpretation.

PubMed

Schober, Patrick; Boer, Christa; Schwarte, Lothar A

2018-05-01

Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.

Correlates of anxiety and depression among patients with type 2 diabetes mellitus.

PubMed

Balhara, Yatan Pal Singh; Sagar, Rajesh

2011-07-01

Research has established the relation between diabetes and depression. Both diabetes and anxiety/depression are independently associated with increased morbidity and mortality. The present study aims at assessing the prevalence of anxiety/depression among outpatients receiving treatment for type 2 diabetes. The study was conducted in the endocrinology outpatient department of an urban tertiary care center. The instruments used included a semi-structured questionnaire, HbA1c levels, fasting blood glucose and postprandial blood glucose, Brief Patient Health Questionnaire, and Hospital Anxiety and Depression Scale (HADS). Analysis was carried out using the SPSS version 16.0. Pearson's correlation coefficient was calculated to find out the correlations. ANOVA was carried out for the in between group comparisons. There was a significant correlation between the HADS-Anxiety scale and Body Mass Index (BMI) with a correlation coefficient of 0.34 (P = 0.008). Also, a significant correlation existed between HADS-Depression scale and BMI (correlation coefficient, 0.36; P = 0.004). Significant correlation were observed between the duration of daily physical exercise and HADS-Anxiety (coefficient of correlation, -0.25; P = 0.04) scores. HADS-Anxiety scores were found to be related to HbA1c levels (correlation-coefficient, 0.41; P = 0.03) and postprandial blood glucose levels (correlation-coefficient, 0.51; P = 0.02). Monitoring of biochemical parameters like HbA1c and postprandial blood glucose levels and BMI could be a guide to development of anxiety in these patients. Also, physical exercise seems to have a protective effect on anxiety in those with type 2 diabetes mellitus.

Prediction of friction coefficients for gases

NASA Technical Reports Server (NTRS)

Taylor, M. F.

1969-01-01

Empirical relations are used for correlating laminar and turbulent friction coefficients for gases, with large variations in the physical properties, flowing through smooth tubes. These relations have been used to correlate friction coefficients for hydrogen, helium, nitrogen, carbon dioxide and air.

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

PubMed

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

The Robustness of Designs for Trials with Nested Data against Incorrect Initial Intracluster Correlation Coefficient Estimates

ERIC Educational Resources Information Center

Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.

2010-01-01

In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…

Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

PubMed

Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia

2018-07-14

In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The Central Campus construction site is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

A support building is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The roof of the Operations Support Building I is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The roof of the Operations Support Building II is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

Bob Cabana, director of NASA's Kennedy Space Center in Florida, begins an aerial survey of the center on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The NASA News Center is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The Beach House is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The Vehicle Assembly Building is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The Launch Complex 39 area is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

Launch Complex 39B is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

Launch Complex 39B is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The NASA TV Support Building at the NASA News Center is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The Kennedy Space Center Visitor Complex is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

A display area in front of the Vehicle Assembly Building is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

A tree is seen across a road during a survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

Damage to a facility roof is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

Damaged power lines are seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

The Beach House is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Damage Survey

NASA Image and Video Library

2016-10-08

Damage to a facility roof is seen during an aerial survey of NASA's Kennedy Space Center in Florida on Saturday. The survey was performed to identify structures and facilities that may have sustained damage from Hurricane Matthew as the storm passed to the east of Kennedy on Oct. 6 and 7, 2016. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Rideout Team was on the center as the storm approached and passed.

Hurricane Matthew Recovery Briefing with Center Director Bob Cabana

NASA Image and Video Library

2016-10-11

In the Press Site auditorium of NASA's Kennedy Space Center in Florida, NASA officials speak to media about efforts to recover from Hurricane Matthew. From the left are Mike Curie of NASA Communications, Center Director Bob Cabana and Bob Holl, chief of the Kennedy Damage Assessment and Recovery Team. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Ride-out Team was on the center as the storm approached and passed.

On Growth and Form in context - an interview with Matthew Jarron.

PubMed

Maartens, Aidan

2017-12-01

D'Arcy Thompson was born in 1860, trained in Edinburgh and Cambridge, and held positions in Dundee and St Andrews, where he worked until his death in 1948. On Growth and Form , his classic work on the mathematical patterns and physical rules underlying biological forms, was first published in 1917. To learn more about the book's context, we met Matthew Jarron, Curator of Museum Services at the University of Dundee, in the University's D'Arcy Thompson Zoology Museum. Surrounded by specimens, many of which were collected by Thompson himself, we discussed the legacy of On Growth and Form and the life of the man behind it. © 2017. Published by The Company of Biologists Ltd.

Hurricane Matthew Recovery Briefing

NASA Image and Video Library

2016-10-11

In the Press Site auditorium of NASA's Kennedy Space Center in Florida, NASA officials speak to media about efforts to recover from Hurricane Matthew. From the left are Mike Curie of NASA Communications, Center Director Bob Cabana and Bob Holl, chief of the Kennedy Damage Assessment and Recovery Team. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Ride-out Team was on the center as the storm approached and passed.

Hurricane Matthew Recovery Briefing

NASA Image and Video Library

2016-10-11

In the Press Site auditorium of NASA's Kennedy Space Center in Florida, NASA officials speak to media about efforts to recover from Hurricane Matthew. From the left are Bob Holl, chief of the Kennedy Damage Assessment and Recovery Team, Center Director Bob Cabana and Mike Curie of NASA Communications. Officials determined that the center received some isolated roof damage, damaged support buildings, a few downed power lines, and limited water intrusion. Beach erosion also occurred, although the storm surge was less than expected. NASA closed the center ahead of the storm’s onset and only a small team of specialists known as the Ride-out Team was on the center as the storm approached and passed.

Evaluation of the Correlation Coefficient of Polyethylene Glycol Treated and Direct Prolactin Results and Comparability with Different Assay System Results.

PubMed

Pal, Shyamali

2017-12-01

The presence of Macro prolactin is a significant cause of elevated prolactin resulting in misdiagnosis in all automated systems. Poly ethylene glycol (PEG) pretreatment is the preventive process but such process includes the probability of loss of a fraction of bioactive prolactin. Surprisingly, PEG treated EQAS & IQAS samples in Cobas e 411 are found out to be correlating with direct results of at least 3 immunoassay systems and treated and untreated Cobas e 411 results are comparable by a correlation coefficient. Comparison of EQAS, IQAS and patient samples were done to find out the trueness of such correlation factor. Study with patient's results have established the correlation coefficient is valid for very small concentration of prolactin also. EQAS, IQAS and 150 patient samples were treated with PEG and prolactin results of treated and untreated samples obtained from Roche Cobas e 411. 25 patient's results (treated) were compared with direct results in Advia Centaur, Architect I & Access2 systems. Correlation coefficient was obtained from trend line of the treated and untreated results. Two tailed p-value obtained from regression coefficient(r) and sample size. The correlation coefficient is in the range (0.761-0.771). Reverse correlation range is (1.289-1.301). r value of two sets of calculated results were 0.995. Two tailed p- value is zero approving dismissal of null hypothesis. The z-score of EQAS does not always assure authenticity of resultsPEG precipitation is correlated by the factor 0.761 even in very small concentrationsAbbreviationsGFCgel filtration chromatographyPEGpolyethylene glycolEQASexternal quality assurance systemM-PRLmacro prolactinPRLprolactinECLIAelectro-chemiluminescence immunoassayCLIAclinical laboratory improvement amendmentsIQASinternal quality assurance systemrregression coefficient.

Anthropometry of Women of the U.S. Army--1977. Report Number 4. Correlation Coefficients

DTIC Science & Technology

1980-02-01

S.... •, 0 76 x:. ADo5 //64 ! TECHNICAL REPORT NATICK/TR-80/016 (/ II ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY-1977 Report No. 4 Correlation...NUMBER NATICK/TR-80/016 4. TITLE (and Subtitle) 5. TYPE OF REPORT & PERIOD COVERED ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY--1977 Technical Report REPORT NO... Anthropometry Survey(s) Coefficients of correlation Measurement(s) U.S. Army Correlation coefficients Body size Military personnel Equation(s) Sizes

DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

NASA Astrophysics Data System (ADS)

Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

2018-01-01

Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

Representing the sublime in the VIMAP and empirical aesthetics: Reviving Edmund Burke's A Philosophical Enquiry into the Origins of Our Ideas of the Sublime and Beautiful. Comment on "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Hur, Y.-J.; McManus, I. C.

2017-07-01

This commentary considers the role of the sublime in the Vienna Integrated Model of Art Perception (VIMAP; Pelowski, Markey, Forster, Gerger, & Leder [17]), and suggest that it is not precisely conceptualised in the model. In part that reflects different views and usages of the sublime in the literature, and here it is recommended that Burke's [2] view of the sublime is used as a primary framework for empirical research on the sublime.

Top-down and bottom-up: Front to back. Comment on "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Nadal, Marcos; Skov, Martin

2017-07-01

The model presented here [1] is the latest in an evolving series of psychological models aimed at explaining the experience of art, first proposed by Leder and colleagues [2]. The aim of this new version is to ;explicitly connect early bottom-up, artwork-derived processing sequence and outputs to top-down, viewer-derived contribution to the processing sequence; [1, p. 5f & 6]. The ;meeting; of these two processing sequences, the authors contend, is crucial to the understanding of people's responses to art [sections 3.6ff & 4], and therefore the new model's principal motivation.

A latent class analysis of friendship network types and their predictors in the second half of life.

PubMed

Miche, Martina; Huxhold, Oliver; Stevens, Nan L

2013-07-01

Friendships contribute uniquely to well-being in (late) adulthood. However, studies on friendship often ignore interindividual differences in friendship patterns. The aim of this study was to investigate such differences including their predictors. The study builds on Matthews's qualitative model of friendship styles. Matthews distinguished 3 approaches to friendship differing by number of friends, duration of friendships, and emotional closeness. We used latent class analysis to identify friendship network types in a sample of middle-aged and older adults aged 40-85 years (N = 1,876). Data came from the German Aging Survey (DEAS). Our analysis revealed 4 distinct friendship network types that were in high congruence with Matthews's typology. We identified these as a discerning style, which focuses on few close relationships, an independent style, which refrains from close engagements, and 2 acquisitive styles that both acquire new friends across their whole life course but differ regarding the emotional closeness of their friendships. Socioeconomic status, gender, health, and network-disturbing and network-sustaining variables predicted affiliations with network types. We argue that future studies should consider a holistic view of friendships in order to better understand the association between friendships and well-being in the second half of life.

Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

PubMed

Mukaka, M M

2012-09-01

Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.

[Correlation of molecular weight and nanofiltration mass transfer coefficient of phenolic acid composition from Salvia miltiorrhiza].

PubMed

Li, Cun-Yu; Wu, Xin; Gu, Jia-Mei; Li, Hong-Yang; Peng, Guo-Ping

2018-04-01

Based on the molecular sieving and solution-diffusion effect in nanofiltration separation, the correlation between initial concentration and mass transfer coefficient of three typical phenolic acids from Salvia miltiorrhiza was fitted to analyze the relationship among mass transfer coefficient, molecular weight and concentration. The experiment showed a linear relationship between operation pressure and membrane flux. Meanwhile, the membrane flux was gradually decayed with the increase of solute concentration. On the basis of the molecular sieving and solution-diffusion effect, the mass transfer coefficient and initial concentration of three phenolic acids showed a power function relationship, and the regression coefficients were all greater than 0.9. The mass transfer coefficient and molecular weight of three phenolic acids were negatively correlated with each other, and the order from high to low is protocatechualdehyde >rosmarinic acid> salvianolic acid B. The separation mechanism of nanofiltration for phenolic acids was further clarified through the analysis of the correlation of molecular weight and nanofiltration mass transfer coefficient. The findings provide references for nanofiltration separation, especially for traditional Chinese medicine with phenolic acids. Copyright© by the Chinese Pharmaceutical Association.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Snapping Sharks, Maddening Mindreaders, and Interactive Images: Teaching Correlation.

ERIC Educational Resources Information Center

Mitchell, Mark L.

Understanding correlation coefficients is difficult for students. A free computer program that helps introductory psychology students distinguish between positive and negative correlation, and which also teaches them to understand the differences between correlation coefficients of different size is described in this paper. The program is…

The Matthew Effect and widely prescribed pharmaceuticals lacking environmental monitoring: case study of an exposure-assessment vulnerability.

PubMed

Daughton, Christian G

2014-01-01

Assessing ambient exposure to chemical stressors often begins with time-consuming and costly monitoring studies to establish environmental occurrence. Both human and ecological toxicology are currently challenged by the unknowns surrounding low-dose exposure/effects, compounded by the reality that exposure undoubtedly involves mixtures of multiple stressors whose identities and levels can vary over time. Long absent from the assessment process, however, is whether the full scope of the identities of the stressors is sufficiently known. The Matthew Effect (a psychosocial phenomenon sometimes informally called the "bandwagon effect" or "iceberg effect," among others) may adversely bias or corrupt the exposure assessment process. The Matthew Effect is evidenced by decisions that base the selection of stressors to target in environmental monitoring surveys on whether they have been identified in prior studies, rather than considering the possibility that additional, but previously unreported, stressors might also play important roles in an exposure scenario. The possibility that the Matthew Effect might influence the scope of environmental stressor research is explored for the first time in a comprehensive case study that examines the preponderance of "absence of data" (in contrast to positive data and "data of absence") for the environmental occurrence of a very large class of potential chemical stressors associated with ubiquitous consumer use - active pharmaceutical ingredients (APIs). Comprehensive examination of the published data for an array of several hundred of the most frequently used drugs for whether their APIs are environmental contaminants provides a prototype example to catalyze discussion among the many disciplines involved with assessing risk. The findings could help guide the selection of those APIs that might merit targeting for environmental monitoring (based on the absence of data for environmental occurrence) as well as the prescribing of those medications that might have minimal environmental impact (based on data of absence for environmental occurrence). © 2013. Published by Elsevier B.V. All rights reserved.

40 CFR 53.34 - Test procedure for methods for PM10 and Class I methods for PM2.5.

Code of Federal Regulations, 2011 CFR

2011-07-01

... linear regression parameters (slope, intercept, and correlation coefficient) describing the relationship... correlation coefficient. (2) To pass the test for comparability, the slope, intercept, and correlation...

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

Temporal correlation coefficient for directed networks.

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

Previous studies dealing with network theory focused mainly on the static aggregation of edges over specific time window lengths. Thus, most of the dynamic information gets lost. To assess the quality of such a static aggregation the temporal correlation coefficient can be calculated. It measures the overall possibility for an edge to persist between two consecutive snapshots. Up to now, this measure is only defined for undirected networks. Therefore, we introduce the adaption of the temporal correlation coefficient to directed networks. This new methodology enables the distinction between ingoing and outgoing edges. Besides a small example network presenting the single calculation steps, we also calculated the proposed measurements for a real pig trade network to emphasize the importance of considering the edge direction. The farm types at the beginning of the pork supply chain showed clearly higher values for the outgoing temporal correlation coefficient compared to the farm types at the end of the pork supply chain. These farm types showed higher values for the ingoing temporal correlation coefficient. The temporal correlation coefficient is a valuable tool to understand the structural dynamics of these systems, as it assesses the consistency of the edge configuration. The adaption of this measure for directed networks may help to preserve meaningful additional information about the investigated network that might get lost if the edge directions are ignored.

Correlation characteristics of phase and amplitude chimeras in an ensemble of nonlocally coupled maps

NASA Astrophysics Data System (ADS)

Vadivasova, T. E.; Strelkova, G. I.; Bogomolov, S. A.; Anishchenko, V. S.

2017-01-01

Correlation characteristics of chimera states have been calculated using the coefficient of mutual correlation of elements in a closed-ring ensemble of nonlocally coupled chaotic maps. Quantitative differences between the coefficients of mutual correlation for phase and amplitude chimeras are established for the first time.

Comparison of RNFL thickness and RPE-normalized RNFL attenuation coefficient for glaucoma diagnosis

NASA Astrophysics Data System (ADS)

Vermeer, K. A.; van der Schoot, J.; Lemij, H. G.; de Boer, J. F.

2013-03-01

Recently, a method to determine the retinal nerve fiber layer (RNFL) attenuation coefficient, based on normalization on the retinal pigment epithelium, was introduced. In contrast to conventional RNFL thickness measures, this novel measure represents a scattering property of the RNFL tissue. In this paper, we compare the RNFL thickness and the RNFL attenuation coefficient on 10 normal and 8 glaucomatous eyes by analyzing the correlation coefficient and the receiver operator curves (ROCs). The thickness and attenuation coefficient showed moderate correlation (r=0.82). Smaller correlation coefficients were found within normal (r=0.55) and glaucomatous (r=0.48) eyes. The full separation between normal and glaucomatous eyes based on the RNFL attenuation coefficient yielded an area under the ROC (AROC) of 1.0. The AROC for the RNFL thickness was 0.9875. No statistically significant difference between the two measures was found by comparing the AROC. RNFL attenuation coefficients may thus replace current RNFL thickness measurements or be combined with it to improve glaucoma diagnosis.

Channel correlation of free space optical communication systems with receiver diversity in non-Kolmogorov atmospheric turbulence

NASA Astrophysics Data System (ADS)

Ma, Jing; Fu, Yulong; Tan, Liying; Yu, Siyuan; Xie, Xiaolong

2018-05-01

Spatial diversity as an effective technique to mitigate the turbulence fading has been widely utilized in free space optical (FSO) communication systems. The received signals, however, will suffer from channel correlation due to insufficient spacing between component antennas. In this paper, the new expressions of the channel correlation coefficient and specifically its components (the large- and small-scale channel correlation coefficients) for a plane wave with aperture effects are derived for horizontal link in moderate-to-strong turbulence, using a non-Kolmogorov spectrum that has a generalized power law in the range of 3-4 instead of the fixed classical Kolmogorov power law of 11/3. And then the influence of power law variations on the channel correlation coefficient and its components are analysed. The numerical results indicated that various value of the power law lead to varying effects on the channel correlation coefficient and its components. This work will help with the further investigation on the fading correlation in spatial diversity systems.

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

Gavira, José A.; Jesus, Walleska de; Camara-Artigas, Ana

The haemoglobin II from the clam L. pectinata has been crystallized using counter-diffusion in single capillary in the presence of agarose to improve crystal quality. Initial phases have been obtained by molecular replacement. Haemoglobin II is one of three haemoglobins present in the cytoplasm of the Lucina pectinata mollusc that inhabits the Caribbean coast. Using HBII purified from its natural source, crystallization screening was performed using the counter-diffusion method with capillaries of 0.2 mm inner diameter. Crystals of HbII suitable for data collection and structure determination were grown in the presence of agarose at 0.1%(w/v) in order to improve theirmore » quality. The crystals belong to the tetragonal space group P4{sub 2}2{sub 1}2, with unit-cell parameters a = b = 73.92, c = 152.35 Å, and diffracted X-rays to a resolution of better than 2.0 Å. The asymmetric unit is a homodimer with a corresponding Matthews coefficient (V{sub M}) of 3.15 Å{sup 3} Da{sup −1} and a solvent content of 61% by volume.« less

Cloning, overexpression, purification and preliminary crystallographic studies of a mitochondrial type II peroxiredoxin from Pisum sativum.

PubMed

Barranco-Medina, Sergio; López-Jaramillo, Francisco Javier; Bernier-Villamor, Laura; Sevilla, Francisca; Lázaro, Juan José

2006-07-01

A cDNA encoding an open reading frame of 199 amino acids corresponding to a type II peroxiredoxin from Pisum sativum with its transit peptide was isolated by RT-PCR. The 171-amino-acid mature protein (estimated molecular weight 18.6 kDa) was cloned into the pET3d vector and overexpressed in Escherichia coli. The recombinant protein was purified and crystallized by the hanging-drop vapour-diffusion technique. A full data set (98.2% completeness) was collected using a rotating-anode generator to a resolution of 2.8 angstroms from a single crystal flash-cooled at 100 K. X-ray data revealed that the protein crystallizes in space group P1, with unit-cell parameters a = 61.88, b = 66.40, c = 77.23 angstroms, alpha = 102.90, beta = 104.40, gamma = 99.07 degrees, and molecular replacement using a theoretical model predicted from the primary structure as a search model confirmed the presence of six molecules in the unit cell as expected from the Matthews coefficient. Refinement of the structure is in progress.

Crystallization and preliminary X-ray diffraction analysis of mouse 3(17)α-hydroxysteroid dehydrogenase

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

El-Kabbani, Ossama, E-mail: ossama.el-kabbani@vcp.monash.edu.au; Ishikura, Syuhei; Wagner, Armin

2005-07-01

Orthorhombic crystals of mouse 3(17)α-hydroxysteroid dehydrogenase were obtained from buffered polyethylene glycol solutions. The crystals diffracted to a resolution of 1.8 Å at the Swiss Light Source beamline X06SA. The 3(17)α-hydroxysteroid dehydrogenase from mouse is involved in the metabolism of oestrogens, androgens, neurosteroids and xenobiotic compounds. The enzyme was crystallized by the hanging-drop vapour-diffusion method in space group P222{sub 1}, with unit-cell parameters a = 84.91, b = 84.90, c = 95.83 Å. The Matthews coefficient (V{sub M}) and the solvent content were 2.21 Å{sup 3} Da{sup −1} and 44.6%, respectively, assuming the presence of two molecules in the asymmetricmore » unit. Diffraction data were collected to a resolution of 1.8 Å at the Swiss Light Source beamline X06SA using a MAR CCD area detector and gave a data set with an overall R{sub merge} of 6.8% and a completeness of 91.1%.« less

Expression, purification, crystallization and preliminary crystallographic analysis of MxiH, a subunit of the Shigella flexneri type III secretion system needle

PubMed Central

Deane, Janet E.; Cordes, Frank S.; Roversi, Pietro; Johnson, Steven; Kenjale, Roma; Picking, William D.; Picking, Wendy L.; Lea, Susan M.; Blocker, Ariel

2006-01-01

A monodisperse truncation mutant of MxiH, the subunit of the needle from the Shigella flexneri type III secretion system (TTSS), has been overexpressed and purified. Crystals were grown of native and selenomethionine-labelled MxiHCΔ5 and diffraction data were collected to 1.9 Å resolution. The crystals belong to space group C2, with unit-cell parameters a = 183.4, b = 28.1, c = 27.8 Å, β = 96.5°. An anomalous difference Patterson map calculated with the data from the SeMet-labelled crystals revealed a single peak on the Harker section v = 0. Inspection of a uranyl derivative also revealed one peak in the isomorphous difference Patterson map on the Harker section v = 0. Analysis of the self-rotation function indicates the presence of a twofold non-crystallographic symmetry axis approximately along a. The calculated Matthews coefficient is 1.9 Å3 Da−1 for two molecules per asymmetric unit, corresponding to a solvent content of 33%. PMID:16511329

Expression, purification, crystallization and preliminary crystallographic analysis of MxiH, a subunit of the Shigella flexneri type III secretion system needle.

PubMed

Deane, Janet E; Cordes, Frank S; Roversi, Pietro; Johnson, Steven; Kenjale, Roma; Picking, William D; Picking, Wendy L; Lea, Susan M; Blocker, Ariel

2006-03-01

A monodisperse truncation mutant of MxiH, the subunit of the needle from the Shigella flexneri type III secretion system (TTSS), has been overexpressed and purified. Crystals were grown of native and selenomethionine-labelled MxiH(CDelta5) and diffraction data were collected to 1.9 A resolution. The crystals belong to space group C2, with unit-cell parameters a = 183.4, b = 28.1, c = 27.8 A, beta = 96.5 degrees. An anomalous difference Patterson map calculated with the data from the SeMet-labelled crystals revealed a single peak on the Harker section v = 0. Inspection of a uranyl derivative also revealed one peak in the isomorphous difference Patterson map on the Harker section v = 0. Analysis of the self-rotation function indicates the presence of a twofold non-crystallographic symmetry axis approximately along a. The calculated Matthews coefficient is 1.9 A3 Da(-1) for two molecules per asymmetric unit, corresponding to a solvent content of 33%.

Expression, purification, crystallization and preliminary X-ray crystallographic analysis of human histidine triad nucleotide-binding protein 2 (hHINT2)

PubMed Central

Dolot, Rafał; Włodarczyk, Artur; Bujacz, Grzegorz D.; Nawrot, Barbara

2013-01-01

Histidine triad nucleotide-binding protein 2 (HINT2) is a mitochondrial adenosine phosphoramidase mainly expressed in the pancreas, liver and adrenal gland. HINT2 possibly plays a role in apoptosis, as well as being involved in steroid biosynthesis, hepatic lipid metabolism and regulation of hepatic mitochondria function. The expression level of HINT2 is significantly down-regulated in hepatocellular carcinoma patients. To date, endogenous substrates for this enzyme, as well as the three-dimensional structure of human HINT2, are unknown. In this study, human HINT2 was cloned, overexpressed in Escherichia coli and purified. Crystallization was performed at 278 K using PEG 4000 as the main precipitant; the crystals, which belonged to the tetragonal space group P41212 with unit-cell parameters a = b = 76.38, c = 133.25 Å, diffracted to 2.83 Å resolution. Assuming two molecules in the asymmetric unit, the Matthews coefficient and the solvent content were calculated to be 2.63 Å3 Da−1 and 53.27%, respectively. PMID:23832208

Purification, crystallization and preliminary X-ray crystallographic analysis of a cysteine-rich secretory protein (CRISP) from Naja atra venom.

PubMed

Wang, Yu-Ling; Goh, King-Xiang; Wu, Wen-guey; Chen, Chun-Jung

2004-10-01

Cysteine-rich secretory proteins (CRISPs) play an important role in the innate immune system and are transcriptionally regulated by androgens in several tissues. The proteins are mostly found in the epididymis and granules of mammals, whilst a number of snake venoms also contain CRISP-family proteins. The natrin protein from the venom of Naja atra (Taiwan cobra), which belongs to a family of CRISPs and has a cysteine-rich C-terminal amino-acid sequence, has been purified using a three-stage chromatography procedure and crystals suitable for X-ray analysis have been obtained using the hanging-drop vapour-diffusion method. X-ray diffraction data were collected to 1.58 A resolution using synchrotron radiation; the crystals belong to space group C222(1), with unit-cell parameters a = 59.172, b = 65.038, c = 243.156 A. There are two protein molecules in the asymmetric unit and the Matthews coefficient is estimated to be 2.35 A3 Da(-1), corresponding to a solvent content of 47.60%.

Crystallization and preliminary X-ray crystallographic analysis of a putative feruloyl esterase from Talaromyces cellulolyticus

PubMed Central

Watanabe, Masahiro; Ishikawa, Kazuhiko

2014-01-01

Feruloyl esterase (FAE; EC 3.1.1.73) catalyzes the cleavage of the ester bond between ferulic acid and polysaccharides in plant cell walls, and thus holds significant potential for the industrial utilization of biomass saccharification. A feruloyl esterase was identified from the genome database of Talaromyces cellulolyticus (formerly known as Acremonium cellulolyticus). The gene consists of the catalytic domain and a carbohydrate-binding module connected through a serine/threonine-rich linker region. The recombinant enzyme was prepared, purified and crystallized at 293 K using 0.1 M imidazole pH 8.0, 0.2 M calcium acetate, 14% PEG 8000 as the precipitant. The crystal diffracted to 2.6 Å resolution and the crystal system is primitive orthorhombic, with unit-cell parameters a = 90.9, b = 123.4, c = 135.4 Å. Four molecules are assumed to be present per asymmetric unit, corresponding to a Matthews coefficient of 2.50 Å3 Da−1 and a solvent content of 50.88%(v/v). PMID:25484222

Crystallization and preliminary X-ray crystallographic analysis of a putative feruloyl esterase from Talaromyces cellulolyticus.

PubMed

Watanabe, Masahiro; Ishikawa, Kazuhiko

2014-12-01

Feruloyl esterase (FAE; EC 3.1.1.73) catalyzes the cleavage of the ester bond between ferulic acid and polysaccharides in plant cell walls, and thus holds significant potential for the industrial utilization of biomass saccharification. A feruloyl esterase was identified from the genome database of Talaromyces cellulolyticus (formerly known as Acremonium cellulolyticus). The gene consists of the catalytic domain and a carbohydrate-binding module connected through a serine/threonine-rich linker region. The recombinant enzyme was prepared, purified and crystallized at 293 K using 0.1 M imidazole pH 8.0, 0.2 M calcium acetate, 14% PEG 8000 as the precipitant. The crystal diffracted to 2.6 Å resolution and the crystal system is primitive orthorhombic, with unit-cell parameters a = 90.9, b = 123.4, c = 135.4 Å. Four molecules are assumed to be present per asymmetric unit, corresponding to a Matthews coefficient of 2.50 Å(3) Da(-1) and a solvent content of 50.88%(v/v).

A preliminary crystallographic analysis of the putative mevalonate diphosphate decarboxylase from Trypanosoma brucei

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

Byres, Emma; Martin, David M. A.; Hunter, William N., E-mail: w.n.hunter@dundee.ac.uk

2005-06-01

The gene encoding the putative mevalonate diphosphate decarboxylase, an enzyme from the mevalonate pathway of isoprenoid precursor biosynthesis, has been cloned from T. brucei. Recombinant protein has been expressed, purified and highly ordered crystals obtained and characterized to aid the structure–function analysis of this enzyme. Mevalonate diphosphate decarboxylase catalyses the last and least well characterized step in the mevalonate pathway for the biosynthesis of isopentenyl pyrophosphate, an isoprenoid precursor. A gene predicted to encode the enzyme from Trypanosoma brucei has been cloned, a highly efficient expression system established and a purification protocol determined. The enzyme gives monoclinic crystals in spacemore » group P2{sub 1}, with unit-cell parameters a = 51.5, b = 168.7, c = 54.9 Å, β = 118.8°. A Matthews coefficient V{sub M} of 2.5 Å{sup 3} Da{sup −1} corresponds to two monomers, each approximately 42 kDa (385 residues), in the asymmetric unit with 50% solvent content. These crystals are well ordered and data to high resolution have been recorded using synchrotron radiation.« less

Cloning, expression, purification, crystallization and preliminary crystallographic analysis of pseudo death-effector domain of HIPPI, a molecular partner of Huntingtin-interacting protein HIP-1

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

Banerjee, Manisha; Majumder, Pritha; Bhattacharyya, Nitai P.

2006-12-01

A pseudo death-effector domain (pDED) of HIPPI, a partner of Huntingtin-interacting protein HIP1, has been cloned, overexpressed and crystallized. The crystals of pDED-HIPPI diffracted to 2.2 Å. The formation of a heterodimer between Huntingtin-interacting protein-1 (HIP-1) and its novel partner HIPPI (HIP-1 protein interactor) through their pseudo death-effector domains (pDEDs) is a key step that recruits caspase-8 and initiates apoptosis. This could be one of the pathways by which apoptosis is increased in Huntington’s disease (HD). A construct consisting of the pDED of HIPPI has been cloned and overexpressed as 6NH-tagged protein and purified by Ni–NTA affinity chromatography. Crystals ofmore » the pDED of HIPPI were grown in space group P4{sub 1}, with unit-cell parameters a = b = 77.42, c = 33.31 Å and a calculated Matthews coefficient of 1.88 Å{sup 3} Da{sup −1} (33% solvent content) with two molecules per asymmetric unit.« less

The Physical Significance of the Synthetic Running Correlation Coefficient and Its Applications in Oceanic and Atmospheric Studies

NASA Astrophysics Data System (ADS)

Zhao, Jinping; Cao, Yong; Wang, Xin

2018-06-01

In order to study the temporal variations of correlations between two time series, a running correlation coefficient (RCC) could be used. An RCC is calculated for a given time window, and the window is then moved sequentially through time. The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient, calculated with the data within the time window, which we call the local running correlation coefficient (LRCC). The LRCC is calculated via the two anomalies corresponding to the two local means, meanwhile, the local means also vary. It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means. To address this problem, two unchanged means obtained from all available data are adopted to calculate an RCC, which is called the synthetic running correlation coefficient (SRCC). When the anomaly variations are dominant, the two RCCs are similar. However, when the variations of the means are dominant, the difference between the two RCCs becomes obvious. The SRCC reflects the correlations of both the anomaly variations and the variations of the means. Therefore, the SRCCs from different time points are intercomparable. A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data. The SRCC always meets this criterion, while the LRCC sometimes fails. Therefore, the SRCC is better than the LRCC for running correlations. We suggest using the SRCC to calculate the RCCs.

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

PubMed Central

Knox, Stephanie A; Chondros, Patty

2004-01-01

Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. PMID:15613248

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Pearson's Correlation between Three Variables; Using Students' Basic Knowledge of Geometry for an Exercise in Mathematical Statistics

ERIC Educational Resources Information Center

Vos, Pauline

2009-01-01

When studying correlations, how do the three bivariate correlation coefficients between three variables relate? After transforming Pearson's correlation coefficient r into a Euclidean distance, undergraduate students can tackle this problem using their secondary school knowledge of geometry (Pythagoras' theorem and similarity of triangles).…

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

PubMed

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Adding Gestalt to the picture. Comment on "Move me, astonish me…" delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates; by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Wagemans, Johan

2017-07-01

Matthew Pelowski and his colleagues from the Helmut Leder lab [17] have made a remarkable contribution to the field of art perception by reviewing the extensive and varied literature (+300 references) on all the factors involved, from a coherent, synthetic perspective-The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP). VIMAP builds on earlier attempts from the same group to provide a comprehensive theoretical framework, but it is much wider in scope and richer in the number of levels and topics covered under its umbrella. It is particularly strong in its discussion of the different psychological processes that lead to a wide range of possible responses to art-from mundane, superficial reactions to more profound responses characterized as moving, disturbing, and transformative. By including physiological, emotional, and evaluative factors, the model is able to address truly unique, even intimate responses to art such as awe, chills, thrills, and the experience of the sublime. The unique way in which this rich set of possible responses to art is achieved is through a series of five mandatory consecutive processing steps (each with their own typical duration), followed by two conditional additional steps (which take more time). Three processing checks along this cascade lead to three more or less spontaneous outcomes (<60 sec) and two more time-consuming ones (see their Fig. 1 for an excellent overview). I have no doubt that VIMAP will inspire a whole generation of scientists investigating perception and appreciation of art, testing specific hypotheses derived from this framework for decades to come.

Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.

PubMed

Peng, Shouyong; Kuroda, Mitzi I; Park, Peter J

2010-07-27

Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. We develop the Quantized correlation coefficient (QCC) that is much less dependent on the amount of signal. This involves discretization of data into set of quantiles (quantization), a merging procedure to group the background probes, and recalculation of the Pearson correlation coefficient. This procedure reduces the influence of the background noise on the statistic, which then properly focuses more on the reproducibility of the signal. The performance of this procedure is tested in both simulated and real ChIP-chip data. For replicates with different levels of enrichment over background and coverage, we find that QCC reflects reproducibility more accurately and is more robust than the standard Pearson or Spearman correlation coefficients. The quantization and the merging procedure can also suggest a proper quantile threshold for separating signal from background for further analysis. To measure reproducibility of ChIP-chip data correctly, a correlation coefficient that is robust to the amount of signal present should be used. QCC is one such measure. The QCC statistic can also be applied in a variety of other contexts for measuring reproducibility, including analysis of array CGH data for DNA copy number and gene expression data.

Correlation Between Geometric Similarity of Ice Shapes and the Resulting Aerodynamic Performance Degradation: A Preliminary Investigation Using WIND

NASA Technical Reports Server (NTRS)

Wright, William B.; Chung, James

1999-01-01

Aerodynamic performance calculations were performed using WIND on ten experimental ice shapes and the corresponding ten ice shapes predicted by LEWICE 2.0. The resulting data for lift coefficient and drag coefficient are presented. The difference in aerodynamic results between the experimental ice shapes and the LEWICE ice shapes were compared to the quantitative difference in ice shape geometry presented in an earlier report. Correlations were generated to determine the geometric features which have the most effect on performance degradation. Results show that maximum lift and stall angle can be correlated to the upper horn angle and the leading edge minimum thickness. Drag coefficient can be correlated to the upper horn angle and the frequency-weighted average of the Fourier coefficients. Pitching moment correlated with the upper horn angle and to a much lesser extent to the upper and lower horn thicknesses.

Confidence Intervals and "F" Tests for Intraclass Correlation Coefficients Based on Three-Way Mixed Effects Models

ERIC Educational Resources Information Center

Zhou, Hong; Muellerleile, Paige; Ingram, Debra; Wong, Seok P.

2011-01-01

Intraclass correlation coefficients (ICCs) are commonly used in behavioral measurement and psychometrics when a researcher is interested in the relationship among variables of a common class. The formulas for deriving ICCs, or generalizability coefficients, vary depending on which models are specified. This article gives the equations for…

Uses and Misuses of the Correlation Coefficient.

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Daniel, Larry G.

The purpose of this paper is to provide an in-depth critical analysis of the use and misuse of correlation coefficients. Various analytical and interpretational misconceptions are reviewed, beginning with the egregious assumption that correlational statistics may be useful in inferring causality. Additional misconceptions, stemming from…

Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

NASA Technical Reports Server (NTRS)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

Family Reintegration Experiences of Soldiers with Mild Traumatic Brain Injury

DTIC Science & Technology

2014-02-26

depression scores in the spouse. Weak within-couple correlation were indicated on the other measures. Table 3 presents the Spearman correlation matrix...separately. Table 2: Spearman Correlation Coefficients for Couples Spouse MAT Spouse Depression Spouse...Anxiety Soldier MAT -0.06 Soldier Depression -0.61 Soldier Anxiety -0.12 Table 3: Spearman Correlation Coefficients for Soldiers and

Correlation tests of the engine performance parameter by using the detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Gao, You; Jing, Liming

2015-02-01

The presence of cross-correlation in complex systems has long been noted and studied in a broad range of physical applications. We here focus on an aero-engine system as an example of a complex system. By applying the detrended cross-correlation (DCCA) coefficient method to aero-engine time series, we investigate the effects of the data length and the time scale on the detrended cross-correlation coefficients ρ DCCA ( T, s). We then show, for a twin-engine aircraft, that the engine fuel flow time series derived from the left engine and the right engine exhibit much stronger cross-correlations than the engine exhaust-gas temperature series derived from the left engine and the right engine do.

Prediction of Very High Reynolds Number Compressible Skin Friction

NASA Technical Reports Server (NTRS)

Carlson, John R.

1998-01-01

Flat plate skin friction calculations over a range of Mach numbers from 0.4 to 3.5 at Reynolds numbers from 16 million to 492 million using a Navier Stokes method with advanced turbulence modeling are compared with incompressible skin friction coefficient correlations. The semi-empirical correlation theories of van Driest; Cope; Winkler and Cha; and Sommer and Short T' are used to transform the predicted skin friction coefficients of solutions using two algebraic Reynolds stress turbulence models in the Navier-Stokes method PAB3D. In general, the predicted skin friction coefficients scaled well with each reference temperature theory though, overall the theory by Sommer and Short appeared to best collapse the predicted coefficients. At the lower Reynolds number 3 to 30 million, both the Girimaji and Shih, Zhu and Lumley turbulence models predicted skin-friction coefficients within 2% of the semi-empirical correlation skin friction coefficients. At the higher Reynolds numbers of 100 to 500 million, the turbulence models by Shih, Zhu and Lumley and Girimaji predicted coefficients that were 6% less and 10% greater, respectively, than the semi-empirical coefficients.

Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF).

PubMed

Gissi, Andrea; Lombardo, Anna; Roncaglioni, Alessandra; Gadaleta, Domenico; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio; Benfenati, Emilio

2015-02-01

The bioconcentration factor (BCF) is an important bioaccumulation hazard assessment metric in many regulatory contexts. Its assessment is required by the REACH regulation (Registration, Evaluation, Authorization and Restriction of Chemicals) and by CLP (Classification, Labeling and Packaging). We challenged nine well-known and widely used BCF QSAR models against 851 compounds stored in an ad-hoc created database. The goodness of the regression analysis was assessed by considering the determination coefficient (R(2)) and the Root Mean Square Error (RMSE); Cooper's statistics and Matthew's Correlation Coefficient (MCC) were calculated for all the thresholds relevant for regulatory purposes (i.e. 100L/kg for Chemical Safety Assessment; 500L/kg for Classification and Labeling; 2000 and 5000L/kg for Persistent, Bioaccumulative and Toxic (PBT) and very Persistent, very Bioaccumulative (vPvB) assessment) to assess the classification, with particular attention to the models' ability to control the occurrence of false negatives. As a first step, statistical analysis was performed for the predictions of the entire dataset; R(2)>0.70 was obtained using CORAL, T.E.S.T. and EPISuite Arnot-Gobas models. As classifiers, ACD and logP-based equations were the best in terms of sensitivity, ranging from 0.75 to 0.94. External compound predictions were carried out for the models that had their own training sets. CORAL model returned the best performance (R(2)ext=0.59), followed by the EPISuite Meylan model (R(2)ext=0.58). The latter gave also the highest sensitivity on external compounds with values from 0.55 to 0.85, depending on the thresholds. Statistics were also compiled for compounds falling into the models Applicability Domain (AD), giving better performances. In this respect, VEGA CAESAR was the best model in terms of regression (R(2)=0.94) and classification (average sensitivity>0.80). This model also showed the best regression (R(2)=0.85) and sensitivity (average>0.70) for new compounds in the AD but not present in the training set. However, no single optimal model exists and, thus, it would be wise a case-by-case assessment. Yet, integrating the wealth of information from multiple models remains the winner approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Comparison of vessel enhancement algorithms applied to time-of-flight MRA images for cerebrovascular segmentation.

PubMed

Phellan, Renzo; Forkert, Nils D

2017-11-01

Vessel enhancement algorithms are often used as a preprocessing step for vessel segmentation in medical images to improve the overall segmentation accuracy. Each algorithm uses different characteristics to enhance vessels, such that the most suitable algorithm may vary for different applications. This paper presents a comparative analysis of the accuracy gains in vessel segmentation generated by the use of nine vessel enhancement algorithms: Multiscale vesselness using the formulas described by Erdt (MSE), Frangi (MSF), and Sato (MSS), optimally oriented flux (OOF), ranking orientations responses path operator (RORPO), the regularized Perona-Malik approach (RPM), vessel enhanced diffusion (VED), hybrid diffusion with continuous switch (HDCS), and the white top hat algorithm (WTH). The filters were evaluated and compared based on time-of-flight MRA datasets and corresponding manual segmentations from 5 healthy subjects and 10 patients with an arteriovenous malformation. Additionally, five synthetic angiographic datasets with corresponding ground truth segmentation were generated with three different noise levels (low, medium, and high) and also used for comparison. The parameters for each algorithm and subsequent segmentation were optimized using leave-one-out cross evaluation. The Dice coefficient, Matthews correlation coefficient, area under the ROC curve, number of connected components, and true positives were used for comparison. The results of this study suggest that vessel enhancement algorithms do not always lead to more accurate segmentation results compared to segmenting nonenhanced images directly. Multiscale vesselness algorithms, such as MSE, MSF, and MSS proved to be robust to noise, while diffusion-based filters, such as RPM, VED, and HDCS ranked in the top of the list in scenarios with medium or no noise. Filters that assume tubular-shapes, such as MSE, MSF, MSS, OOF, RORPO, and VED show a decrease in accuracy when considering patients with an AVM, because vessels may vary from its tubular-shape in this case. Vessel enhancement algorithms can help to improve the accuracy of the segmentation of the vascular system. However, their contribution to accuracy has to be evaluated as it depends on the specific applications, and in some cases it can lead to a reduction of the overall accuracy. No specific filter was suitable for all tested scenarios. © 2017 American Association of Physicists in Medicine.

A Practical Theory of Micro-Solar Power Sensor Networks

DTIC Science & Technology

2009-04-20

Simulation Platform TOSSIM [LLWC03] ns-2 Matlab C++ AVRORA [TLP05] Reference Hardware Mica2 WINS, Medusa Mica Mica2, Medusa Mica2 Simulated Power Power...scale. From this raw data, we can 162 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 2 4 Correlation coefficient F re qu en cy Histogram of correlation...0.5 0.6 0.7 0.8 0.9 1 0 1 2 Correlation coefficient F re qu en cy Histogram of correlation coefficient with solar radiation measurement (Turbidity at

Impacts of Extreme Flooding on Hydrologic Connectivity and Water Quality in the Atlantic Coastal Plain and Implications for Vulnerable Populations

NASA Astrophysics Data System (ADS)

Riveros-Iregui, D. A.; Moser, H. A.; Christenson, E. C.; Gray, J.; Hedgespeth, M. L.; Jass, T. L.; Lowry, D. S.; Martin, K.; Nichols, E. G.; Stewart, J. R.; Emanuel, R. E.

2017-12-01

In October 2016, Hurricane Matthew brought extreme flooding to eastern North Carolina, including record regional flooding along the Lumber River and its tributaries in the North Carolina Coastal Plain. Situated in a region dominated by large-scale crop-cultivation and containing some of the highest densities of concentrated animal feeding operations (CAFOs) and animal processing operations in the U.S., the Lumber River watershed is also home to the Lumbee Tribe of American Indians. Most of the tribe's 60,000+ members live within or immediately adjacent to the 3,000 km2 watershed where they maintain deep cultural and historical connections. The region, however, also suffers from high rates of poverty and large disparities in healthcare, education, and infrastructure, conditions exacerbated by Hurricane Matthew. We summarize ongoing efforts to characterize the short- and long-term impacts of extreme flooding on water quality in (1) low gradient streams and riverine wetlands of the watershed; (2) surficial aquifers, which provide water resources for the local communities, and (3) public drinking water supplies, which derive from deeper, confined aquifers but whose infrastructure suffered widespread damage following Hurricane Matthew. Our results provide mechanistic understanding of flood-related connectivity across multiple hydrologic compartments, and provide important implications for how hydrological natural hazards combine with land use to drive water quality impacts and affect vulnerable populations.

Haiti and the politics of governance and community responses to Hurricane Matthew

PubMed Central

Marcelin, Louis Herns; Cela, Toni; Shultz, James M.

2016-01-01

ABSTRACT This article examines disaster preparedness and community responses to Hurricane Matthew in semi-urban and rural towns and villages in Grande-Anse, Haiti. Based on an ethnographic study conducted in the department of Grande-Anse one week after the hurricane made landfall in Haiti, the article focuses on the perspectives of citizens, community-based associations and local authorities in the affected areas. Sixty-three (63) interviews and 8 community meetings (focus groups) were conducted in 11 impacted sites in 8 communes. Results suggest that preexisting conditions in impacted communities, rather than deliberate and coordinated disaster management strategies, shaped levels of preparedness for and response to the disaster. Affected populations relied primarily on family networks and local forms of solidarity to attend to basic needs such as shelter, health and food. The main argument presented is that Haiti, by virtue of its geographic location, lack of resources, institutional fragility and vulnerability, must systematically integrate community-based assets and capacities in its responses to and management of disasters. Further, it is critical for the government, Haitian institutions, and society to apply integrated risk reduction and management and disaster preparedness measures in all aspects of life, if the country is to survive the many disasters to come in a time of climate change. These measures should be embedded in recovery and reconstruction efforts after Hurricane Matthew. PMID:28321361

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

NASA Astrophysics Data System (ADS)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Matthew O'Connell | NREL

Science.gov Websites

operation, especially in the WECC interconnection (Western US) Data analysis and analysis code development Research Interests Impact of increased renewables on electric grid operation and architechture Optimizing

Repeatability of chemical-shift-encoded water-fat MRI and diffusion-tensor imaging in lower extremity muscles in children.

PubMed

Ponrartana, Skorn; Andrade, Kristine E; Wren, Tishya A L; Ramos-Platt, Leigh; Hu, Houchun H; Bluml, Stefan; Gilsanz, Vicente

2014-06-01

The purpose of this study was to assess the repeatability of water-fat MRI and diffusion-tensor imaging (DTI) as quantitative biomarkers of pediatric lower extremity skeletal muscle. MRI at 3 T of a randomly selected thigh and lower leg of seven healthy children was studied using water-fat separation and DTI techniques. Muscle-fat fraction, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) values were calculated. Test-retest and interrater repeatability were assessed by calculating the Pearson correlation coefficient, intraclass correlation coefficient, and Bland-Altman analysis. Bland-Altman plots show that the mean difference between test-retest and interrater measurements of muscle-fat fraction, ADC, and FA was near 0. The correlation coefficients and intraclass correlation coefficients were all between 0.88 and 0.99 (p < 0.05), suggesting excellent reliability of the measurements. Muscle-fat fraction measurements from water-fat MRI exhibited the highest intraclass correlation coefficient. Interrater agreement was consistently better than test-retest comparisons. Water-fat MRI and DTI measurements in lower extremity skeletal muscles are objective repeatable biomarkers in children. This knowledge should aid in the understanding of the number of participants needed in clinical trials when using these determinations as an outcome measure to noninvasively monitor neuromuscular disease.

Aesthetic episodes, domains, and the mind. Comment on: "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Jacobsen, Thomas

2017-07-01

Aesthetic episodes, as all behavior, are situated. They take place as an interaction of person and situation variables [1]. There are different artistic and aesthetic domains that afford, in part, mutual mental processes, but also fundamentally different, e.g., modality-specific ones [2]. For the infinite number of possible aesthetic episodes a plethora of component processes can be selectively combined and dynamically configured. Following psychophysics' pragmatic dualism of mind and body, this results in dynamically configured (neuro-) biological networks subserving these mental processes [1]. These are, of course, also subject to evolutionary, biological, historical, cultural, and social change [1,3].

Observations of copolar correlation coefficient through a bright band at vertical incidence

NASA Technical Reports Server (NTRS)

Zrnic, D. S.; Raghavan, R.; Chandrasekar, V.

1994-01-01

This paper discusses an application of polarimetric measurements at vertical incidence. In particular, the correlation coefficients between linear copolar components are examined, and measurements obtained with the National Severe Storms Laboratory (NSSL)'s and National Center for Atmospheric Research (NCAR)'s polarimetric radars are presented. The data are from two well-defined bright bands. A sharp decrease of the correlation coefficient, confined to a height interval of a few hundred meters, marks the bottom of the bright band.

Relationship of body mass index to percent body fat and waist circumference among schoolchildren in Japan--the influence of gender and obesity: a population-based cross-sectional study.

PubMed

Ochiai, Hirotaka; Shirasawa, Takako; Nishimura, Rimei; Morimoto, Aya; Shimada, Naoki; Ohtsu, Tadahiro; Kujirai, Emiko; Hoshino, Hiromi; Tajima, Naoko; Kokaze, Akatsuki

2010-08-18

Although the correlation coefficient between body mass index (BMI) and percent body fat (%BF) or waist circumference (WC) has been reported, studies conducted among population-based schoolchildren to date have been limited in Japan, where %BF and WC are not usually measured in annual health examinations at elementary schools or junior high schools. The aim of the present study was to investigate the relationship of BMI to %BF and WC and to examine the influence of gender and obesity on these relationships among Japanese schoolchildren. Subjects included 3,750 schoolchildren from the fourth and seventh grade in Ina-town, Saitama Prefecture, Japan between 2004 and 2008. Information about subject's age, sex, height, weight, %BF, and WC was collected from annual physical examinations. %BF was measured with a bipedal biometrical impedance analysis device. Obesity was defined by the following two criteria: the obese definition of the Centers for Disease Control and Prevention, and the definition of obesity for Japanese children. Pearson's correlation coefficients between BMI and %BF or WC were calculated separately for sex. Among fourth graders, the correlation coefficients between BMI and %BF were 0.74 for boys and 0.97 for girls, whereas those between BMI and WC were 0.94 for boys and 0.90 for girls. Similar results were observed in the analysis of seventh graders. The correlation coefficient between BMI and %BF varied by physique (obese or non-obese), with weaker correlations among the obese regardless of the definition of obesity; most correlation coefficients among obese boys were less than 0.5, whereas most correlations among obese girls were more than 0.7. On the other hand, the correlation coefficients between BMI and WC were more than 0.8 among boys and almost all coefficients were more than 0.7 among girls, regardless of physique. BMI was positively correlated with %BF and WC among Japanese schoolchildren. The correlations could be influenced by obesity as well as by gender. Accordingly, it is essential to consider gender and obesity when using BMI as a surrogate for %BF and WC for epidemiological use.

A Method for Approximating the Bivariate Normal Correlation Coefficient.

ERIC Educational Resources Information Center

Kirk, David B.

Improvements of the Gaussian quadrature in conjunction with the Newton-Raphson iteration technique (TM 000 789) are discussed as effective methods of calculating the bivariate normal correlation coefficient. (CK)

Semi-quantitative spectrographic analysis and rank correlation in geochemistry

USGS Publications Warehouse

Flanagan, F.J.

1957-01-01

The rank correlation coefficient, rs, which involves less computation than the product-moment correlation coefficient, r, can be used to indicate the degree of relationship between two elements. The method is applicable in situations where the assumptions underlying normal distribution correlation theory may not be satisfied. Semi-quantitative spectrographic analyses which are reported as grouped or partly ranked data can be used to calculate rank correlations between elements. ?? 1957.

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Robust Approximations to the Non-Null Distribution of the Product Moment Correlation Coefficient I: The Phi Coefficient.

ERIC Educational Resources Information Center

Edwards, Lynne K.; Meyers, Sarah A.

Correlation coefficients are frequently reported in educational and psychological research. The robustness properties and optimality among practical approximations when phi does not equal 0 with moderate sample sizes are not well documented. Three major approximations and their variations are examined: (1) a normal approximation of Fisher's Z,…

Correcting Coefficient Alpha for Correlated Errors: Is [alpha][K]a Lower Bound to Reliability?

ERIC Educational Resources Information Center

Rae, Gordon

2006-01-01

When errors of measurement are positively correlated, coefficient alpha may overestimate the "true" reliability of a composite. To reduce this inflation bias, Komaroff (1997) has proposed an adjusted alpha coefficient, ak. This article shows that ak is only guaranteed to be a lower bound to reliability if the latter does not include correlated…

Prediction of stream volatilization coefficients

USGS Publications Warehouse

Rathbun, Ronald E.

1990-01-01

Equations are developed for predicting the liquid-film and gas-film reference-substance parameters for quantifying volatilization of organic solutes from streams. Molecular weight and molecular-diffusion coefficients of the solute are used as correlating parameters. Equations for predicting molecular-diffusion coefficients of organic solutes in water and air are developed, with molecular weight and molal volume as parameters. Mean absolute errors of prediction for diffusion coefficients in water are 9.97% for the molecular-weight equation, 6.45% for the molal-volume equation. The mean absolute error for the diffusion coefficient in air is 5.79% for the molal-volume equation. Molecular weight is not a satisfactory correlating parameter for diffusion in air because two equations are necessary to describe the values in the data set. The best predictive equation for the liquid-film reference-substance parameter has a mean absolute error of 5.74%, with molal volume as the correlating parameter. The best equation for the gas-film parameter has a mean absolute error of 7.80%, with molecular weight as the correlating parameter.

A unified framework for the pareto law and Matthew effect using scale-free networks

NASA Astrophysics Data System (ADS)

Hu, M.-B.; Wang, W.-X.; Jiang, R.; Wu, Q.-S.; Wang, B.-H.; Wu, Y.-H.

2006-09-01

We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth P(m)˜m-(v+1) with 1.6 < v <2.0 (which is in agreement with that of U.S. or Japan). Particularly, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.

Optical properties of poly-HCN and their astronomical applications

NASA Technical Reports Server (NTRS)

Khare, B. N.; Sagan, C.; Thompson, W. R.; Arakawa, E. T.; Meisse, C.; Tuminello, P. S.

1994-01-01

Matthews (1992) has proposed that HCN "polymer" is ubiquitous in the solar system. We apply vacuum deposition and spectroscopic techniques previously used on synthetic organic heteropolymers (tholins), kerogens, and meteoritic organic residues to the measurement of the optical constants of poly-HCN in the wavelength range 0.05-40 micrometers. These measurements allow quantitative comparison with spectrophotometry of organic-rich bodies in the outer solar system. In a specific test of Matthews' hypothesis, poly-HCN fails to match the optical constants of the haze of the Saturnian moon, Titan, in the visible and near-infrared derived from astronomical observations and standard models of the Titan atmosphere. In contrast, a tholin produced from a simulated Titan atmosphere matches within the probable errors. Poly-HCN is much more N-rich than Titan tholin.

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods

PubMed Central

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-01-01

Background Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. Objectives The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. Materials and Methods In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Results Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist’s coefficient was not confirmed by visual methods. Conclusions Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data. PMID:27621916

Python Waveform Cross-Correlation

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

Templeton, Dennise

PyWCC is a tool to compute seismic waveform cross-correlation coefficients on single-component or multiple-component seismic data across a network of seismic sensors. PyWCC compares waveform data templates with continuous seismic data, associates the resulting detections, identifies the template with the highest cross-correlation coefficient, and outputs a catalog of detections above a user-defined absolute cross-correlation threshold value.

Hadamard multimode optical imaging transceiver

DOEpatents

Cooke, Bradly J; Guenther, David C; Tiee, Joe J; Kellum, Mervyn J; Olivas, Nicholas L; Weisse-Bernstein, Nina R; Judd, Stephen L; Braun, Thomas R

2012-10-30

Disclosed is a method and system for simultaneously acquiring and producing results for multiple image modes using a common sensor without optical filtering, scanning, or other moving parts. The system and method utilize the Walsh-Hadamard correlation detection process (e.g., functions/matrix) to provide an all-binary structure that permits seamless bridging between analog and digital domains. An embodiment may capture an incoming optical signal at an optical aperture, convert the optical signal to an electrical signal, pass the electrical signal through a Low-Noise Amplifier (LNA) to create an LNA signal, pass the LNA signal through one or more correlators where each correlator has a corresponding Walsh-Hadamard (WH) binary basis function, calculate a correlation output coefficient for each correlator as a function of the corresponding WH binary basis function in accordance with Walsh-Hadamard mathematical principles, digitize each of the correlation output coefficient by passing each correlation output coefficient through an Analog-to-Digital Converter (ADC), and performing image mode processing on the digitized correlation output coefficients as desired to produce one or more image modes. Some, but not all, potential image modes include: multi-channel access, temporal, range, three-dimensional, and synthetic aperture.

Relative validity of an FFQ to estimate daily food and nutrient intakes for Chilean adults.

PubMed

Dehghan, Mahshid; Martinez, Solange; Zhang, Xiaohe; Seron, Pamela; Lanas, Fernando; Islam, Shofiqul; Merchant, Anwar T

2013-10-01

FFQ are commonly used to rank individuals by their food and nutrient intakes in large epidemiological studies. The purpose of the present study was to develop and validate an FFQ to rank individuals participating in an ongoing Prospective Urban and Rural Epidemiological (PURE) study in Chile. An FFQ and four 24 h dietary recalls were completed over 1 year. Pearson correlation coefficients, energy-adjusted and de-attenuated correlations and weighted kappa were computed between the dietary recalls and the FFQ. The level of agreement between the two dietary assessment methods was evaluated by Bland-Altman analysis. Temuco, Chile. Overall, 166 women and men enrolled in the present study. One hundred men and women participated in FFQ development and sixty-six individuals participated in FFQ validation. The FFQ consisted of 109 food items. For nutrients, the crude correlation coefficients between the dietary recalls and FFQ varied from 0.14 (protein) to 0.44 (fat). Energy adjustment and de-attenuation improved correlation coefficients and almost all correlation coefficients exceeded 0.40. Similar correlation coefficients were observed for food groups; the highest de-attenuated energy adjusted correlation coefficient was found for margarine and butter (0.75) and the lowest for potatoes (0.12). The FFQ showed moderate to high agreement for most nutrients and food groups, and can be used to rank individuals based on energy, nutrient and food intakes. The validation study was conducted in a unique setting and indicated that the tool is valid for use by adults in Chile.

[Habitat suitability index of larval Japanese Halfbeak (Hyporhamphus sajori) in Bohai Sea based on geographically weighted regression.

PubMed

Zhao, Yang; Zhang, Xue Qing; Bian, Xiao Dong

2018-01-01

To investigate the early supplementary processes of fishre sources in the Bohai Sea, the geographically weighted regression (GWR) was introduced to the habitat suitability index (HSI) model. The Bohai Sea larval Japanese Halfbeak HSI GWR model was established with four environmental variables, including sea surface temperature (SST), sea surface salinity (SSS), water depth (DEP), and chlorophyll a concentration (Chl a). Results of the simulation showed that the four variables had different performances in August 2015. SST and Chl a were global variables, and had little impacts on HSI, with the regression coefficients of -0.027 and 0.006, respectively. SSS and DEP were local variables, and had larger impacts on HSI, while the average values of absolute values of their regression coefficients were 0.075 and 0.129, respectively. In the central Bohai Sea, SSS showed a negative correlation with HSI, and the most negative correlation coefficient was -0.3. In contrast, SSS was correlated positively but weakly with HSI in the three bays of Bohai Sea, and the largest correlation coefficient was 0.1. In particular, DEP and HSI were negatively correlated in the entire Bohai Sea, while they were more negatively correlated in the three bays of Bohai than in the central Bohai Sea, and the most negative correlation coefficient was -0.16 in the three bays. The Poisson regression coefficient of the HSI GWR model was 0.705, consistent with field measurements. Therefore, it could provide a new method for the research on fish habitats in the future.

Psychometric properties of the modified RESIDE physical activity questionnaire among low-income overweight women.

PubMed

Jones, Sydney A; Evenson, Kelly R; Johnston, Larry F; Trost, Stewart G; Samuel-Hodge, Carmen; Jewell, David A; Kraschnewski, Jennifer L; Keyserling, Thomas C

2015-01-01

This study explored the criterion-related validity and test-retest reliability of the modified RESIDential Environment physical activity questionnaire and whether the instrument's validity varied by body mass index, education, race/ethnicity, or employment status. Validation study using baseline data collected for randomized trial of a weight loss intervention. Participants recruited from health departments wore an ActiGraph accelerometer and self-reported non-occupational walking, moderate and vigorous physical activity on the modified RESIDential Environment questionnaire. We assessed validity (n=152) using Spearman correlation coefficients, and reliability (n=57) using intraclass correlation coefficients. When compared to steps, moderate physical activity, and bouts of moderate/vigorous physical activity measured by accelerometer, these questionnaire measures showed fair evidence for validity: recreational walking (Spearman correlation coefficients 0.23-0.36), total walking (Spearman correlation coefficients 0.24-0.37), and total moderate physical activity (Spearman correlation coefficients 0.18-0.36). Correlations for self-reported walking and moderate physical activity were higher among unemployed participants and women with lower body mass indices. Generally no other variability in the validity of the instrument was found. Evidence for reliability of RESIDential Environment measures of recreational walking, total walking, and total moderate physical activity was substantial (intraclass correlation coefficients 0.56-0.68). Evidence for questionnaire validity and reliability varied by activity domain and was strongest for walking measures. The questionnaire may capture physical activity less accurately among women with higher body mass indices and employed participants. Capturing occupational activity, specifically walking at work, may improve questionnaire validity. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Nonlinearity of the forward-backward correlation function in the model with string fusion

NASA Astrophysics Data System (ADS)

Vechernin, Vladimir

2017-12-01

The behavior of the forward-backward correlation functions and the corresponding correlation coefficients between multiplicities and transverse momenta of particles produced in high energy hadronic interactions is analyzed by analytical and MC calculations in the models with and without string fusion. The string fusion is taking into account in simplified form by introducing the lattice in the transverse plane. The results obtained with two alternative definitions of the forward-backward correlation coefficient are compared. It is shown that the nonlinearity of correlation functions increases with the width of observation windows, leading at small string density to a strong dependence of correlation coefficient value on the definition. The results of the modeling enable qualitatively to explain the experimentally observed features in the behavior of the correlation functions between multiplicities and mean transverse momenta at small and large multiplicities.

The relationship between the managerial skills and results of "performance evaluation "tool among nursing managers in teaching hospitals of Iran University of Medical Science.

PubMed

Isfahani, Haleh Mousavi; Aryankhesal, Aidin; Haghani, Hamid

2014-09-25

Performance of different organizations, such as hospitals is mainly influenced by their managers' performance. Nursing managers have an important role in hospital performance and their managerial skills can improve the quality of the services. Hence, the present study was conducted in order to assess the relationship between the managerial skills and the results of their performance evaluation in Teaching Hospitals of Iran University of Medical Science in 2013. The research used the cross sectional method in 2013. It was done by distributing a managerial skills assessment questionnaire, with close-ended questions in 5 choice Likert scale, among 181 managers and head nurses of hospitals of Iran university of Medical Sciences; among which 131 answered the questions. Another data collection tools was a forms to record evaluation marks from the personnel records. We used Pearson and Spearman correlation tests and SPSS for analysis and description (frequency, mean and standard deviation). Results showed that the managerial skills of the nursing mangers were fair (2.57 out of 5) and the results of the performance evaluation were in a good condition (98.44). The mangers' evaluation results and the managerial skills scores were not in a meaningful correlation (r=0.047 np=0.856). The research showed no correlation between different domains of managerial skills and the performance evaluation marks: decision making skills (r=0.074 and p=0.399), leadership (correlation coefficient 0.028 and p=0.654), motivation (correlation coefficient 0.118 and p=0.163), communication  (correlation coefficient 0.116 and p=0.122), systematic thinking  (correlation coefficient 0.028 and p=0.828), time management (correlation coefficient 0.077 and p=0.401) and strategic thinking  (correlation coefficient 0.041 and p=0.756). Lack of any correlation and relation between managers' managerial skills and their performance evaluation results shows need to a fundamental revision at managers' performance evaluation form.

Pulmonary Catherization Data Correlate Poorly with Renal Function in Heart Failure.

PubMed

Masha, Luke; Stone, James; Stone, Danielle; Zhang, Jun; Sheng, Luo

2018-04-10

The mechanisms of renal dysfunction in heart failure are poorly understood. We chose to explore the relationship of cardiac filling pressures and cardiac index (CI) in relation to renal dysfunction in advanced heart failure. To determine the relationship between renal function and cardiac filling pressures using the United Network of Organ Sharing (UNOS) pulmonary artery catherization registry. Patients over the age of 18 years who were listed for single-organ heart transplantation were included. Exclusion criteria included a history of mechanical circulatory support, previous transplantation, any use of renal replacement therapy, prior history of malignancy, and cardiac surgery, amongst others. Correlations between serum creatinine (SCr) and CI, pulmonary capillary wedge pressure (PCWP), pulmonary artery systolic pressure (PASP), and pulmonary artery diastolic pressure (PADP) were assessed by Pearson correlation coefficients and simple linear regression coefficients. Pearson correlation coefficients between SCr and PCWP, PASP, and PADP were near zero with values of 0.1, 0.07, and 0.08, respectively (p < 0.0001). A weak negative correlation coefficient between SCr and CI was found (correlation coefficient, -0.045, p = 0.027). In a subgroup of young patients unlikely to have noncardiac etiologies, no significant correlations between these values were identified. These findings suggest that, as assessed by pulmonary artery catherization, none of the factors - PCWP, PASP, PADP, or CI - play a prominent role in cardiorenal syndromes. © 2018 S. Karger AG, Basel.

Apparent Diffusion Coefficient and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Pancreatic Cancer: Characteristics and Correlation With Histopathologic Parameters.

PubMed

Ma, Wanling; Li, Na; Zhao, Weiwei; Ren, Jing; Wei, Mengqi; Yang, Yong; Wang, Yingmei; Fu, Xin; Zhang, Zhuoli; Larson, Andrew C; Huan, Yi

2016-01-01

To clarify diffusion and perfusion abnormalities and evaluate correlation between apparent diffusion coefficient (ADC), MR perfusion and histopathologic parameters of pancreatic cancer (PC). Eighteen patients with PC underwent diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Parameters of DCE-MRI and ADC of cancer and non-cancerous tissue were compared. Correlation between the rate constant that represents transfer of contrast agent from the arterial blood into the extravascular extracellular space (K, volume of the extravascular extracellular space per unit volume of tissue (Ve), and ADC of PC and histopathologic parameters were analyzed. The rate constant that represents transfer of contrast agent from the extravascular extracellular space into blood plasma, K, tissue volume fraction occupied by vascular space, and ADC of PC were significantly lower than nontumoral pancreases. Ve of PC was significantly higher than that of nontumoral pancreas. Apparent diffusion coefficient and K values of PC were negatively correlated to fibrosis content and fibroblast activation protein staining score. Fibrosis content was positively correlated to Ve. Apparent diffusion coefficient values and parameters of DCE-MRI can differentiate PC from nontumoral pancreases. There are correlations between ADC, K, Ve, and fibrosis content of PC. Fibroblast activation protein staining score of PC is negatively correlated to ADC and K. Apparent diffusion coefficient, K, and Ve may be feasible to predict prognosis of PC.

Horizontal Cross Bracing Detail, Vertical Cross Bracing Detail, Horizontal Cross ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Horizontal Cross Bracing Detail, Vertical Cross Bracing Detail, Horizontal Cross Bracing Detail, Vertical Cross Bracing-End Detail - Cumberland Covered Bridge, Spanning Mississinewa River, Matthews, Grant County, IN

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

PubMed Central

2017-01-01

Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient. PMID:28202589

A comparison of two indices for the intraclass correlation coefficient.

PubMed

Shieh, Gwowen

2012-12-01

In the present study, we examined the behavior of two indices for measuring the intraclass correlation in the one-way random effects model: the prevailing ICC(1) (Fisher, 1938) and the corrected eta-squared (Bliese & Halverson, 1998). These two procedures differ both in their methods of estimating the variance components that define the intraclass correlation coefficient and in their performance of bias and mean squared error in the estimation of the intraclass correlation coefficient. In contrast with the natural unbiased principle used to construct ICC(1), in the present study it was analytically shown that the corrected eta-squared estimator is identical to the maximum likelihood estimator and the pairwise estimator under equal group sizes. Moreover, the empirical results obtained from the present Monte Carlo simulation study across various group structures revealed the mutual dominance relationship between their truncated versions for negative values. The corrected eta-squared estimator performs better than the ICC(1) estimator when the underlying population intraclass correlation coefficient is small. Conversely, ICC(1) has a clear advantage over the corrected eta-squared for medium and large magnitudes of population intraclass correlation coefficient. The conceptual description and numerical investigation provide guidelines to help researchers choose between the two indices for more accurate reliability analysis in multilevel research.

Prediction of mass transfer coefficient in rotating bed contactor (Higee) using artificial neural network

NASA Astrophysics Data System (ADS)

Saha, Dipendu

2009-02-01

The feasibility of drastically reducing the contactor size in mass transfer processes utilizing centrifugal field has generated a lot of interest in rotating packed bed (Higee). Various investigators have proposed correlations to predict mass transfer coefficients in Higee, but, none of the correlations was more than 20-30% accurate. In this work, artificial neural network (ANN) is employed for predicting mass transfer coefficient data. Results show that ANN provides better estimation of mass transfer coefficient with accuracy 5-15%.

Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…

Precancerous esophageal epithelia are associated with significantly increased scattering coefficients

PubMed Central

Su, Jing-Wei; Lin, Yang-Hsien; Chiang, Chun-Ping; Lee, Jang-Ming; Hsieh, Chao-Mao; Hsieh, Min-Shu; Yang, Pei-Wen; Wang, Chen-Ping; Tseng, Ping-Huei; Lee, Yi-Chia; Sung, Kung-Bin

2015-01-01

The progression of epithelial precancers into cancer is accompanied by changes of tissue and cellular structures in the epithelium. Correlations between the structural changes and scattering coefficients of esophageal epithelia were investigated using quantitative phase images and the scattering-phase theorem. An ex vivo study of 14 patients demonstrated that the average scattering coefficient of precancerous epithelia was 37.8% higher than that of normal epithelia from the same patient. The scattering coefficients were highly correlated with morphological features including the cell density and the nuclear-to-cytoplasmic ratio. A high interpatient variability in scattering coefficients was observed and suggests identifying precancerous lesions based on the relative change in scattering coefficients. PMID:26504630

Comparison between uroflowmetry and sonouroflowmetry in recording of urinary flow in healthy men.

PubMed

Krhut, Jan; Gärtner, Marcel; Sýkora, Radek; Hurtík, Petr; Burda, Michal; Luňáček, Libor; Zvarová, Katarína; Zvara, Peter

2015-08-01

To evaluate the accuracy of sonouroflowmetry in recording urinary flow parameters and voided volume. A total of 25 healthy male volunteers (age 18-63 years) were included in the study. All participants were asked to carry out uroflowmetry synchronous with recording of the sound generated by the urine stream hitting the water level in the urine collection receptacle, using a dedicated cell phone. From 188 recordings, 34 were excluded, because of voided volume <150 mL or technical problems during recording. Sonouroflowmetry recording was visualized in a form of a trace, representing sound intensity over time. Subsequently, the matching datasets of uroflowmetry and sonouroflowmetry were compared with respect to flow time, voided volume, maximum flow rate and average flow rate. Pearson's correlation coefficient was used to compare parameters recorded by uroflowmetry with those calculated based on sonouroflowmetry recordings. The flow pattern recorded by sonouroflowmetry showed a good correlation with the uroflowmetry trace. A strong correlation (Pearson's correlation coefficient 0.87) was documented between uroflowmetry-recorded flow time and duration of the sound signal recorded with sonouroflowmetry. A moderate correlation was observed in voided volume (Pearson's correlation coefficient 0.68) and average flow rate (Pearson's correlation coefficient 0.57). A weak correlation (Pearson's correlation coefficient 0.38) between maximum flow rate recorded using uroflowmetry and sonouroflowmetry-recorded peak sound intensity was documented. The present study shows that the basic concept utilizing sound analysis for estimation of urinary flow parameters and voided volume is valid. However, further development of this technology and standardization of recording algorithm are required. © 2015 The Japanese Urological Association.

Combinatorial Algorithms for Portfolio Optimization Problems - Case of Risk Moderate Investor

NASA Astrophysics Data System (ADS)

Juarna, A.

2017-03-01

Portfolio optimization problem is a problem of finding optimal combination of n stocks from N ≥ n available stocks that gives maximal aggregate return and minimal aggregate risk. In this paper given N = 43 from the IDX (Indonesia Stock Exchange) group of the 45 most-traded stocks, known as the LQ45, with p = 24 data of monthly returns for each stock, spanned over interval 2013-2014. This problem actually is a combinatorial one where its algorithm is constructed based on two considerations: risk moderate type of investor and maximum allowed correlation coefficient between every two eligible stocks. The main outputs resulted from implementation of the algorithms is a multiple curve of three portfolio’s attributes, e.g. the size, the ratio of return to risk, and the percentage of negative correlation coefficient for every two chosen stocks, as function of maximum allowed correlation coefficient between each two stocks. The output curve shows that the portfolio contains three stocks with ratio of return to risk at 14.57 if the maximum allowed correlation coefficient between every two eligible stocks is negative and contains 19 stocks with maximum allowed correlation coefficient 0.17 to get maximum ratio of return to risk at 25.48.

Hurricane Impacts on Small Island Communities: Case study of Hurricane Matthew on Great Exuma, The Bahamas

NASA Astrophysics Data System (ADS)

Sullivan Sealey, Kathleen; Bowleg, John

2017-04-01

Great Exuma has been a UNESCO Eco-hydrology Project Site with a focus on coastal restoration and flood management. Great Exuma and its largest settlement, George Town, support a population of just over 8.000 people on an island dominated by extensive coastal wetlands. The Victoria Pond Eco-Hydrology project restored flow and drainage to highly-altered coastal wetlands to reduce flooding of the built environment as well as regain ecological function. The project was designed to show the value of a protected wetland and coastal environment within a populated settlement; demonstrating that people can live alongside mangroves and value "green" infrastructure for flood protection. The restoration project was initiated after severe storm flooding in 2007 with Tropical Storm Noel. In 2016, the passing of Hurricane Matthew had unprecedented impacts on the coastal communities of Great Exuma, challenging past practices in restoration and flood prevention. This talk reviews the loss of natural capital (for example, fish populations, mangroves, salt water inundation) from Hurricane Matthew based on a rapid response survey of Great Exuma. The surprisingly find was the impact of storm surge on low-lying areas used primarily for personal farms and small-scale agriculture. Although women made up the overwhelming majority of people who attended Coastal Restoration workshops, women were most adversely impacted by the recent hurricane flooding with the loss of their small low-lying farms and gardens. Although increasing culverts in mangrove creeks in two areas did reduce building flood damage, the low-lying areas adjacent to mangroves, mostly ephemeral freshwater wetlands, were inundated with saltwater, and seasonal crops in these areas were destroyed. These ephemeral wetlands were designed as part of the wetland flooding system, it was not known how important these small areas were to artisanal farming on Great Exuma. The size and scope of Hurricane Matthew passing through the entire country presents a unique opportunity use a rapid response method to document coastal impacts to better understand how to plan coastal restoration. Small farms managed primarily by women accounted for about 35% of the fresh produce eaten by local Bahamians (not tourists), and the loss of local production may be permanent.

AN EMPIRICAL INVESTIGATION OF THE EFFECTS OF NONNORMALITY UPON THE SAMPLING DISTRIBUTION OF THE PROJECT MOMENT CORRELATION COEFFICIENT.

ERIC Educational Resources Information Center

HJELM, HOWARD; NORRIS, RAYMOND C.

THE STUDY EMPIRICALLY DETERMINED THE EFFECTS OF NONNORMALITY UPON SOME SAMPLING DISTRIBUTIONS OF THE PRODUCT MOMENT CORRELATION COEFFICIENT (PMCC). SAMPLING DISTRIBUTIONS OF THE PMCC WERE OBTAINED BY DRAWING NUMEROUS SAMPLES FROM CONTROL AND EXPERIMENTAL POPULATIONS HAVING VARIOUS DEGREES OF NONNORMALITY AND BY CALCULATING CORRELATION COEFFICIENTS…

Gender and Age Analyses of NIRS/STAI Pearson Correlation Coefficients at Resting State.

PubMed

Matsumoto, T; Fuchita, Y; Ichikawa, K; Fukuda, Y; Takemura, N; Sakatani, K

2016-01-01

According to the valence asymmetry hypothesis, the left/right asymmetry of PFC activity is correlated with specific emotional responses to mental stress and personality traits. In a previous study we measured spontaneous oscillation of oxy-Hb concentrations in the bilateral PFC at rest in normal adults employing two-channel portable NIRS and computed the laterality index at rest (LIR). We investigated the Pearson correlation coefficient between the LIR and anxiety levels evaluated by the State-Trait Anxiety Inventory (STAI) test. We found that subjects with right-dominant activity at rest showed higher STAI scores, while those with left dominant oxy-Hb changes at rest showed lower STAI scores such that the Pearson correlation coefficient between LIR and STAI was positive. This study performed Bootstrap analysis on the data and showed the following statistics of the target correlation coefficient: mean=0.4925 and lower confidence limit=0.177 with confidence level 0.05. Using the KS-test, we demonstrated that the correlation did not depend on age, whereas it did depend on gender.

Nuclear anxiety: a test-construction study

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

Braunstein, A.L.

1986-01-01

The Nuclear Anxiety Scale was administered to 263 undergraduate and graduate studies (on eight occasions in December, 1985 and January, 1986). (1) The obtained alpha coefficient was .91. This was significant at the .01 level, and demonstrated that the scale was internally homogeneous and consistent. (2) Item discrimination indices (point biserial correlation coefficients) computered for the thirty (30) items yielded a range of .25 to .64. All coefficients were significant at the .01 level, and all 30 items were retained as demonstrating significant discriminability. (3) The correlation between two administrations of the scale (with a 48-hour interval) was .83. Thismore » was significant at the .01 level, and demonstrated test-retest reliability and stability over time. (4) The point-biserial correlation coefficient between scores on the Nuclear Anxiety Scale, and the students' self-report of nuclear anxiety as being either a high or low ranked stressor, was .59. This was significant at the .01 level, and demonstrated concurrent validity. (5) The correlation coefficient between scores on the Nuclear Anxiety Scale and the Spielberger State-Trait Anxiety Inventory, A-Trait, (1970), was .41. This was significant at the .01 level, and demonstrated convergent validity. (6) The correlation coefficient between positively stated and negatively stated items (with scoring reversed) was .76. This was significant at the .01 level, and demonstrated freedom from response set bias.« less

Channel correlation and BER performance analysis of coherent optical communication systems with receive diversity over moderate-to-strong non-Kolmogorov turbulence.

PubMed

Fu, Yulong; Ma, Jing; Tan, Liying; Yu, Siyuan; Lu, Gaoyuan

2018-04-10

In this paper, new expressions of the channel-correlation coefficient and its components (the large- and small-scale channel-correlation coefficients) for a plane wave are derived for a horizontal link in moderate-to-strong non-Kolmogorov turbulence using a generalized effective atmospheric spectrum which includes finite-turbulence inner and outer scales and high-wave-number "bump". The closed-form expression of the average bit error rate (BER) of the coherent free-space optical communication system is derived using the derived channel-correlation coefficients and an α-μ distribution to approximate the sum of the square root of arbitrarily correlated Gamma-Gamma random variables. Analytical results are provided to investigate the channel correlation and evaluate the average BER performance. The validity of the proposed approximation is illustrated by Monte Carlo simulations. This work will help with further investigation of the fading correlation in spatial diversity systems.

Technical characterization of dialysis fluid flow and mass transfer rate in dialyzers with various filtration coefficients using dimensionless correlation equation.

PubMed

Fukuda, Makoto; Yoshimura, Kengo; Namekawa, Koki; Sakai, Kiyotaka

2017-06-01

The objective of the present study is to evaluate the effect of filtration coefficient and internal filtration on dialysis fluid flow and mass transfer coefficient in dialyzers using dimensionless mass transfer correlation equations. Aqueous solution of vitamin B 12 clearances were obtained for REXEED-15L as a low flux dialyzer, and APS-15EA and APS-15UA as high flux dialyzers. All the other design specifications were identical for these dialyzers except for filtration coefficient. The overall mass transfer coefficient was calculated, moreover, the exponents of Reynolds number (Re) and film mass transfer coefficient of the dialysis-side fluid (k D ) for each flow rate were derived from the Wilson plot and dimensionless correlation equation. The exponents of Re were 0.4 for the low flux dialyzer whereas 0.5 for the high flux dialyzers. Dialysis fluid of the low flux dialyzer was close to laminar flow because of its low filtration coefficient. On the other hand, dialysis fluid of the high flux dialyzers was assumed to be orthogonal flow. Higher filtration coefficient was associated with higher k D influenced by mass transfer rate through diffusion and internal filtration. Higher filtration coefficient of dialyzers and internal filtration affect orthogonal flow of dialysis fluid.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Dioxin Exposure Initiative

EPA Pesticide Factsheets

The Dioxin Exposure Initiative (DEI) is no longer active. This page contains a summary of the dioxin exposure initiative with illustrations, contact and background information.Originally supported by scientist Matthew Lorber, who retired in Mar 2017.

Influences of sampling size and pattern on the uncertainty of correlation estimation between soil water content and its influencing factors

NASA Astrophysics Data System (ADS)

Lai, Xiaoming; Zhu, Qing; Zhou, Zhiwen; Liao, Kaihua

2017-12-01

In this study, seven random combination sampling strategies were applied to investigate the uncertainties in estimating the hillslope mean soil water content (SWC) and correlation coefficients between the SWC and soil/terrain properties on a tea + bamboo hillslope. One of the sampling strategies is the global random sampling and the other six are the stratified random sampling on the top, middle, toe, top + mid, top + toe and mid + toe slope positions. When each sampling strategy was applied, sample sizes were gradually reduced and each sampling size contained 3000 replicates. Under each sampling size of each sampling strategy, the relative errors (REs) and coefficients of variation (CVs) of the estimated hillslope mean SWC and correlation coefficients between the SWC and soil/terrain properties were calculated to quantify the accuracy and uncertainty. The results showed that the uncertainty of the estimations decreased as the sampling size increasing. However, larger sample sizes were required to reduce the uncertainty in correlation coefficient estimation than in hillslope mean SWC estimation. Under global random sampling, 12 randomly sampled sites on this hillslope were adequate to estimate the hillslope mean SWC with RE and CV ≤10%. However, at least 72 randomly sampled sites were needed to ensure the estimated correlation coefficients with REs and CVs ≤10%. Comparing with all sampling strategies, reducing sampling sites on the middle slope had the least influence on the estimation of hillslope mean SWC and correlation coefficients. Under this strategy, 60 sites (10 on the middle slope and 50 on the top and toe slopes) were enough to ensure the estimated correlation coefficients with REs and CVs ≤10%. This suggested that when designing the SWC sampling, the proportion of sites on the middle slope can be reduced to 16.7% of the total number of sites. Findings of this study will be useful for the optimal SWC sampling design.

NT-pro-BNP levels in patients with acute pulmonary embolism are correlated to right but not left ventricular volume and function.

PubMed

Pasha, Sharif M; Klok, Frederikus A; van der Bijl, Noortje; de Roos, Albert; Kroft, Lucia J M; Huisman, Menno V

2012-08-01

N-terminal pro-Brain Natriuretic Peptide (NT-pro-BNP) is primarily secreted by left ventricular (LV) stretch and wall tension. Notably, NT-pro-BNP is a prognostic marker in acute pulmonary embolism (PE), which primarily stresses the right ventricle (RV). We sought to evaluate the relative contribution of the RV to NT-pro-BNP levels during PE. A post-hoc analysis of an observational prospective outcome study in 113 consecutive patients with computed tomography (CT)-proven PE and 226 patients in whom PE was clinically suspected but ruled out by CT. In all patients RV and LV function was established by assessing ECG-triggered-CT measured ventricular end-diastolic-volumes and ejection fraction (EF). NT-pro-BNP was assessed in all patients. The correlation between RV and LV end-diastolic-volumes and systolic function was evaluated by multiple linear regression corrected for known confounders. In the PE cohort increased RVEF (β-coefficient (95% confidence interval [CI]) -0.044 (± -0.011); p<0.001) and higher RV end-diastolic-volume (β-coefficient 0.005 (± 0.001); p<0.001) were significantly correlated to NT-pro-BNP, while no correlation was found with LVEF (β-coefficient 0.005 (± 0.010); p=0.587) and LV end-diastolic-volume (β-coefficient -0.003 (± 0.002); p=0.074). In control patients without PE we found a strong correlation between NT-pro-BNP levels and LVEF (β-coefficient -0.027 (± -0.006); p<0.001) although not LV end-diastolic-volume (β-coefficient 0.001 (± 0.001); p=0.418). RVEF (β-coefficient -0.002 (± -0.006); p=0.802) and RV end-diastolic-volume (β-coefficient <0.001 (± 0.001); p=0.730) were not correlated in patients without PE. In PE patients, lower RVEF and higher RV end-diastolic-volume were significantly correlated to NT-pro-BNP levels as compared to control patients without PE. These observations provide pathophysiological ground for the well-known prognostic value of NT-pro-BNP in acute PE.

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

Matthew Oliver | NREL

Science.gov Websites

Process Development Unit. NREL's Thermal and Catalytic Process Development Unit can process 1/2 ton per biomass to fuels and chemicals Affiliated Research Programs Thermochemical Process Integration, Scale-Up

ARC-2010-ACD10-0244-011

NASA Image and Video Library

2010-12-28

A Minotaur IV rocket, carrying NASA's Organism/Organic Exposure to Orbital Stresses (O/OREOS) nano satellite launches from the Alaska Aerospace Corporation's Kodiak Launch Complex on Nov. 19, 2010. Image credit: NASA/Matthew Daniels

Some correlations between sugar maple tree characteristics and sap and sugar yields

Treesearch

Barton M. Blum

1971-01-01

Simple correlation coefficients between various characteristics of sugar maple trees and sap sugar concentration, sap volume yield, and total sugar production are given for the 1968 sap season. Correlation coefficients in general indicated that individual tree characteristics that express tree and crown size are significantly related to sap volume yield and total sugar...

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

ERIC Educational Resources Information Center

Bishara, Anthony J.; Hittner, James B.

2015-01-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…

Relationship of body mass index to percent body fat and waist circumference among schoolchildren in Japan - the influence of gender and obesity: a population-based cross-sectional study

PubMed Central

2010-01-01

Background Although the correlation coefficient between body mass index (BMI) and percent body fat (%BF) or waist circumference (WC) has been reported, studies conducted among population-based schoolchildren to date have been limited in Japan, where %BF and WC are not usually measured in annual health examinations at elementary schools or junior high schools. The aim of the present study was to investigate the relationship of BMI to %BF and WC and to examine the influence of gender and obesity on these relationships among Japanese schoolchildren. Methods Subjects included 3,750 schoolchildren from the fourth and seventh grade in Ina-town, Saitama Prefecture, Japan between 2004 and 2008. Information about subject's age, sex, height, weight, %BF, and WC was collected from annual physical examinations. %BF was measured with a bipedal biometrical impedance analysis device. Obesity was defined by the following two criteria: the obese definition of the Centers for Disease Control and Prevention, and the definition of obesity for Japanese children. Pearson's correlation coefficients between BMI and %BF or WC were calculated separately for sex. Results Among fourth graders, the correlation coefficients between BMI and %BF were 0.74 for boys and 0.97 for girls, whereas those between BMI and WC were 0.94 for boys and 0.90 for girls. Similar results were observed in the analysis of seventh graders. The correlation coefficient between BMI and %BF varied by physique (obese or non-obese), with weaker correlations among the obese regardless of the definition of obesity; most correlation coefficients among obese boys were less than 0.5, whereas most correlations among obese girls were more than 0.7. On the other hand, the correlation coefficients between BMI and WC were more than 0.8 among boys and almost all coefficients were more than 0.7 among girls, regardless of physique. Conclusions BMI was positively correlated with %BF and WC among Japanese schoolchildren. The correlations could be influenced by obesity as well as by gender. Accordingly, it is essential to consider gender and obesity when using BMI as a surrogate for %BF and WC for epidemiological use. PMID:20716379

Zero Pearson coefficient for strongly correlated growing trees

NASA Astrophysics Data System (ADS)

Dorogovtsev, S. N.; Ferreira, A. L.; Goltsev, A. V.; Mendes, J. F. F.

2010-03-01

We obtained Pearson’s coefficient of strongly correlated recursive networks growing by preferential attachment of every new vertex by m edges. We found that the Pearson coefficient is exactly zero in the infinite network limit for the recursive trees (m=1) . If the number of connections of new vertices exceeds one (m>1) , then the Pearson coefficient in the infinite networks equals zero only when the degree distribution exponent γ does not exceed 4. We calculated the Pearson coefficient for finite networks and observed a slow power-law-like approach to an infinite network limit. Our findings indicate that Pearson’s coefficient strongly depends on size and details of networks, which makes this characteristic virtually useless for quantitative comparison of different networks.

Zero Pearson coefficient for strongly correlated growing trees.

PubMed

Dorogovtsev, S N; Ferreira, A L; Goltsev, A V; Mendes, J F F

2010-03-01

We obtained Pearson's coefficient of strongly correlated recursive networks growing by preferential attachment of every new vertex by m edges. We found that the Pearson coefficient is exactly zero in the infinite network limit for the recursive trees (m=1). If the number of connections of new vertices exceeds one (m>1), then the Pearson coefficient in the infinite networks equals zero only when the degree distribution exponent gamma does not exceed 4. We calculated the Pearson coefficient for finite networks and observed a slow power-law-like approach to an infinite network limit. Our findings indicate that Pearson's coefficient strongly depends on size and details of networks, which makes this characteristic virtually useless for quantitative comparison of different networks.

Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

ERIC Educational Resources Information Center

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

Effect of degree correlations above the first shell on the percolation transition

NASA Astrophysics Data System (ADS)

Valdez, L. D.; Buono, C.; Braunstein, L. A.; Macri, P. A.

2011-11-01

The use of degree-degree correlations to model realistic networks which are characterized by their Pearson's coefficient, has become widespread. However the effect on how different correlation algorithms produce different results on processes on top of them, has not yet been discussed. In this letter, using different correlation algorithms to generate assortative networks, we show that for very assortative networks the behavior of the main observables in percolation processes depends on the algorithm used to build the network. The different alghoritms used here introduce different inner structures that are missed in Pearson's coefficient. We explain the different behaviors through a generalization of Pearson's coefficient that allows to study the correlations at chemical distances l from a root node. We apply our findings to real networks.

Evaluation of generalized heat-transfer coefficients in pilot AFBC units

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

Grewal, N.S.

Experimental data for heat transfer rates as obtained in a 0.209m/sup 2/ AFBC unit at the GFETC is examined in the light of the existing four correlations for heat transfer coefficient between an immersed staggered array of horizontal tubes and a gas-solid fluidized bed. The predicted values of heat transfer coefficient from the correlations proposed by Grewal and Bansal are found to be in good agreement with the experimental values of heat transfer coefficient when the contribution due to radiation is also included.

Evaluation of generalized heat transfer coefficients in pilot AFBC units

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

Grewal, N.S.

Experimental data for heat transfer rates as obtained in a 0.209m/sup 2/ AFBC unit at the GFETC is examined in the light of the existing four correlations for heat transfer coefficient between an immersed staggered array of horizontal tubes and a gas-solid fluidized bed. The predicted values of heat transfer coefficient from the correlations proposed by Grewal and Bansal are found to be in good agreement with the experimental values of heat transfer coefficient when the contribution due to radiation is also included.

Variability in the Correlation between Asian Dust Storms and Chlorophyll a Concentration from the North to Equatorial Pacific

PubMed Central

Tan, Sai-Chun; Yao, Xiaohong; Gao, Hui-Wang; Shi, Guang-Yu; Yue, Xu

2013-01-01

A long-term record of Asian dust storms showed seven high-occurrence-frequency centers in China. The intrusion of Asian dust into the downwind seas, including the China seas, the Sea of Japan, the subarctic North Pacific, the North Pacific subtropical gyre, and the western and eastern Equatorial Pacific, has been shown to add nutrients to ocean ecosystems and enhance their biological activities. To explore the relationship between the transported dust from various sources to the six seas and oceanic biological activities with different nutrient conditions, the correlation between monthly chlorophyll a concentration in each sea and monthly dust storm occurrence frequencies reaching the sea during 1997–2007 was examined in this study. No correlations were observed between dust and chlorophyll a concentration in the <50 m China seas because atmospheric deposition is commonly believed to exert less impact on coastal seas. Significant correlations existed between dust sources and many sea areas, suggesting a link between dust and chlorophyll a concentration in those seas. However, the correlation coefficients were highly variable. In general, the correlation coefficients (0.54–0.63) for the Sea of Japan were highest, except for that between the subarctic Pacific and the Taklimakan Desert, where it was as high as 0.7. For the >50 m China seas and the North Pacific subtropical gyre, the correlation coefficients were in the range 0.32–0.57. The correlation coefficients for the western and eastern Equatorial Pacific were relatively low (<0.36). These correlation coefficients were further interpreted in terms of the geographical distributions of dust sources, the transport pathways, the dust deposition, the nutrient conditions of oceans, and the probability of dust storms reaching the seas. PMID:23460892

Variability in the correlation between Asian dust storms and chlorophyll a concentration from the North to Equatorial Pacific.

PubMed

Tan, Sai-Chun; Yao, Xiaohong; Gao, Hui-Wang; Shi, Guang-Yu; Yue, Xu

2013-01-01

A long-term record of Asian dust storms showed seven high-occurrence-frequency centers in China. The intrusion of Asian dust into the downwind seas, including the China seas, the Sea of Japan, the subarctic North Pacific, the North Pacific subtropical gyre, and the western and eastern Equatorial Pacific, has been shown to add nutrients to ocean ecosystems and enhance their biological activities. To explore the relationship between the transported dust from various sources to the six seas and oceanic biological activities with different nutrient conditions, the correlation between monthly chlorophyll a concentration in each sea and monthly dust storm occurrence frequencies reaching the sea during 1997-2007 was examined in this study. No correlations were observed between dust and chlorophyll a concentration in the <50 m China seas because atmospheric deposition is commonly believed to exert less impact on coastal seas. Significant correlations existed between dust sources and many sea areas, suggesting a link between dust and chlorophyll a concentration in those seas. However, the correlation coefficients were highly variable. In general, the correlation coefficients (0.54-0.63) for the Sea of Japan were highest, except for that between the subarctic Pacific and the Taklimakan Desert, where it was as high as 0.7. For the >50 m China seas and the North Pacific subtropical gyre, the correlation coefficients were in the range 0.32-0.57. The correlation coefficients for the western and eastern Equatorial Pacific were relatively low (<0.36). These correlation coefficients were further interpreted in terms of the geographical distributions of dust sources, the transport pathways, the dust deposition, the nutrient conditions of oceans, and the probability of dust storms reaching the seas.

Correlations between symptoms, nasal endoscopy, and in-office computed tomography in post-surgical chronic rhinosinusitis patients.

PubMed

Ryan, William R; Ramachandra, Tara; Hwang, Peter H

2011-03-01

To determine correlations between symptoms, nasal endoscopy findings, and computed tomography (CT) scan findings in post-surgical chronic rhinosinusitis (CRS) patients. Cross-sectional. A total of 51 CRS patients who had undergone endoscopic sinus surgery (ESS) completed symptom questionnaires, underwent endoscopy, and received an in-office sinus CT scan during one clinic visit. For metrics, we used the Sinonasal Outcomes Test-20 (SNOT-20) questionnaire, visual analog symptom scale (VAS), Lund-Kennedy endoscopy scoring scale, and Lund-MacKay (LM) CT scoring scale. We determined Pearson correlation coefficients, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) between scores for symptoms, endoscopy, and CT. The SNOT-20 score and most VAS symptoms had poor correlation coefficients with both endoscopy and CT scores (0.03-0.24). Nasal drainage of pus, nasal congestion, and impaired sense of smell had moderate correlation coefficients with endoscopy and CT (0.24-0.42). Endoscopy had a strong correlation coefficient with CT (0.76). Drainage, edema, and polyps had strong correlation coefficients with CT (0.80, 0.69, and 0.49, respectively). Endoscopy had a PPV of 92.5% and NPV of 45.5% for detecting an abnormal sinus CT (LM score ≥1). In post-ESS CRS patients, most symptoms do not correlate well with either endoscopy or CT findings. Endoscopy and CT scores correlate well. Abnormal endoscopy findings have the ability to confidently rule in the presence of CT opacification, thus validating the importance of endoscopy in clinical decision making. However, a normal endoscopy cannot assure a normal CT. Thus, symptoms, endoscopy, and CT are complementary in the evaluation of the post-ESS CRS patient. Copyright © 2011 The American Laryngological, Rhinological, and Otological Society, Inc., Rhinological, and Otological Society, Inc.

An experimental study on the noise correlation properties of CBCT projection data

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ouyang, Luo; Ma, Jianhua; Huang, Jing; Chen, Wufan; Wang, Jing

2014-03-01

In this study, we systematically investigated the noise correlation properties among detector bins of CBCT projection data by analyzing repeated projection measurements. The measurements were performed on a TrueBeam on-board CBCT imaging system with a 4030CB flat panel detector. An anthropomorphic male pelvis phantom was used to acquire 500 repeated projection data at six different dose levels from 0.1 mAs to 1.6 mAs per projection at three fixed angles. To minimize the influence of the lag effect, lag correction was performed on the consecutively acquired projection data. The noise correlation coefficient between detector bin pairs was calculated from the corrected projection data. The noise correlation among CBCT projection data was then incorporated into the covariance matrix of the penalized weighted least-squares (PWLS) criterion for noise reduction of low-dose CBCT. The analyses of the repeated measurements show that noise correlation coefficients are non-zero between the nearest neighboring bins of CBCT projection data. The average noise correlation coefficients for the first- and second- order neighbors are 0.20 and 0.06, respectively. The noise correlation coefficients are independent of the dose level. Reconstruction of the pelvis phantom shows that the PWLS criterion with consideration of noise correlation results in a lower noise level as compared to the PWLS criterion without considering the noise correlation at the matched resolution.

Investigation of the construct of trait emotional intelligence in children.

PubMed

Mavroveli, Stella; Petrides, K V; Shove, Chloe; Whitehead, Amanda

2008-12-01

This paper discusses the construct of trait emotional intelligence (trait EI or trait emotional self-efficacy) with emphasis on measurement in children. The Trait Emotional Intelligence Questionnaire-Child Form (TEIQue-CF) is introduced and its development and theoretical background are briefly explained. It is shown in two independent studies that the TEIQue-CF has satisfactory levels of internal consistency (alpha = 0.76 and alpha = 0.73, respectively) and temporal stability [r = 0.79 and r ((corrected)) = 1.00]. Trait EI scores were generally unrelated to proxies of cognitive ability, as hypothesized in trait EI theory (Petrides et al. in Matthews et al. (eds) Emotional intelligence: knowns and unknowns -- series in affective science. Oxford University Press, Oxford, pp 151-166). They also differentiated between pupils with unauthorized absences or exclusions from school and controls. Trait EI correlated positively with teacher-rated positive behavior and negatively with negative behavior (emotional symptoms, conduct problems, peer problems, and hyperactivity).

On viewer motivation, unit of analysis, and the VIMAP. Comment on "Move me, astonish me ... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Tinio, Pablo P. L.

2017-07-01

The Vienna Integrated Model of Art Perception (VIMAP; [5]) is the most comprehensive model of the art experience today. The model incorporates bottom-up and top-down cognitive processes and accounts for different outcomes of the art experience, such as aesthetic evaluations, emotions, and physiological and neurological responses to art. In their presentation of the model, Pelowski et al. also present hypotheses that are amenable to empirical testing. These features make the VIMAP an ambitious model that attempts to explain how meaningful, complex, and profound aspects of the art experience come about, which is a significant extension of previous models of the art experience (e.g., [1-3,10]), and which gives the VIMAP good explanatory power.

Multi-layer multi-configuration time-dependent Hartree (ML-MCTDH) approach to the correlated exciton-vibrational dynamics in the FMO complex

NASA Astrophysics Data System (ADS)

Schulze, Jan; Shibl, Mohamed F.; Al-Marri, Mohammed J.; Kühn, Oliver

2016-05-01

The coupled quantum dynamics of excitonic and vibrational degrees of freedom is investigated for high-dimensional models of the Fenna-Matthews-Olson complex. This includes a seven- and an eight-site model with 518 and 592 harmonic vibrational modes, respectively. The coupling between local electronic transitions and vibrations is described within the Huang-Rhys model using parameters that are obtained by discretization of an experimental spectral density. Different pathways of excitation energy flow are analyzed in terms of the reduced one-exciton density matrix, focussing on the role of vibrational and vibronic excitations. Distinct features due to both competing time scales of vibrational and exciton motion and vibronically assisted transfer are observed. The question of the effect of initial state preparation is addressed by comparing the case of an instantaneous Franck-Condon excitation at a single site with that of a laser field excitation.

Closure and ratio correlation analysis of lunar chemical and grain size data

NASA Technical Reports Server (NTRS)

Butler, J. C.

1976-01-01

Major element and major element plus trace element analyses were selected from the lunar data base for Apollo 11, 12 and 15 basalt and regolith samples. Summary statistics for each of the six data sets were compiled, and the effects of closure on the Pearson product moment correlation coefficient were investigated using the Chayes and Kruskal approximation procedure. In general, there are two types of closure effects evident in these data sets: negative correlations of intermediate size which are solely the result of closure, and correlations of small absolute value which depart significantly from their expected closure correlations which are of intermediate size. It is shown that a positive closure correlation will arise only when the product of the coefficients of variation is very small (less than 0.01 for most data sets) and, in general, trace elements in the lunar data sets exhibit relatively large coefficients of variation.

Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

PubMed

Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong

2017-05-01

The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.

[Examination of diagnosis procedure combination survey data that influence function evaluation coefficient II].

PubMed

Nakajima, Hisato; Yano, Kouya; Nagasawa, Kaoko; Kobayashi, Eiji; Yokota, Kuninobu

2015-01-01

On the basis of Diagnosis Procedure Combination (DPC) survey data, the factors that increase the value of function evaluation coefficient II were considered. A total of 1,505 hospitals were divided into groups I, II, and III, and the following items were considered. 1. Significant differences in function evaluation coefficient II and DPC survey data. 2. Examination of using the Mahalanobis-Taguchi (MT) method. 3. Correlation between function evaluation coefficient II and each DPC survey data item. 1. Function evaluation coefficient II was highest in group II. Group I hospitals showed the highest bed capacity, and numbers of hospitalization days, operations, chemotherapies, radiotherapies and general anesthesia procedures. 2. Using the MT method, we found that the number of ambulance conveyances was effective factor in group I hospitals, the number of general anesthesia procedures was effective factor in group II hospitals, and the bed capacity was effective factor in group III hospitals. 3. In group I hospitals, function evaluation coefficient II significantly correlated to the numbers of ambulance conveyances and chemotherapies. In group II hospitals, function evaluation coefficient II significantly correlated to bed capacity, the numbers of ambulance conveyances, hospitalization days, operations, general anesthesia procedures, and mean hospitalization days. In group III hospitals, function evaluation coefficient II significantly correlated to all items. The factors that improve the value of function evaluation coefficient II were the increases in the numbers of ambulance conveyances, chemotherapies and radiotherapies in group I hospitals, increases in the numbers of hospitalization days, operations, ambulance conveyances and general anesthesia procedures in group II hospitals, and increases in the numbers of hospitalization days, operations and ambulance conveyances. These results indicate that the profit of a hospital will increase, which will lead to medical services of good quality.

Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

PubMed

Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

2015-09-01

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

75 FR 44941 - Sunshine Act; Notice of Public Meeting Accessibility Roundtable Discussion

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-30

... with relevant information and implementable suggestions that the Commission can use as it attempts to... meeting and hearing will be open to the public. PERSON TO CONTACT FOR INFORMATION: Matthew Masterson...

Understanding Magnetic Anomalies and Their Significance.

ERIC Educational Resources Information Center

Shea, James H.

1988-01-01

Describes a laboratory exercise testing the Vine-Matthews-Morley hypothesis of plate tectonics. Includes 14 questions with explanations using graphs and charts. Provides a historical account of the current plate tectonic and magnetic anomaly theory. (MVL)

Genetics Home Reference: atopic dermatitis

MedlinePlus

... JK, Weinreich MA, Hauk PJ, Reynolds PR, Lyons JJ, Nelson CG, Ruffo E, Dorjbal B, Glauzy S, Yamakawa ... J, Niemela J, Zhang Y, Rosenzweig SD, McElwee JJ, DiMaggio T, Matthews HF, Jones N, Stone KD, ...

Crystallization and preliminary X-ray crystallographic analysis of YfcM: an important factor for EF-P hydroxylation

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

Kobayashi, Kan; RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198; Suzuki, Takehiro

2014-08-27

E. coli YfcM was expressed, purified and crystallized. Crystals of YfcM were obtained by the in situ proteolysis crystallization method. Using these crystals, an X-ray diffraction data set was collected at 1.45 Å resolution. Elongation factor P (EF-P) plays an essential role in the translation of polyproline-containing proteins in bacteria. It becomes functional by the post-translational modification of its highly conserved lysine residue. It is first β-lysylated by PoxA and then hydroxylated by YfcM. In this work, the YfcM protein from Escherichia coli was overexpressed, purified and crystallized. The crystal of YfcM was obtained by the in situ proteolysis crystallizationmore » method and diffracted X-rays to 1.45 Å resolution. It belonged to space group C2, with unit-cell parameters a = 124.4, b = 37.0, c = 37.6 Å, β = 101.2°. The calculated Matthews coefficient (V{sub M}) of the crystal was 1.91 Å{sup 3} Da{sup −1}, indicating that one YfcM molecule is present in the asymmetric unit with a solvent content of 35.7%.« less

Expression, purification, crystallization and preliminary X-ray crystallographic analysis of a novel plant-type ferredoxin/thioredoxin reductase-like protein from Methanosarcina acetivorans

PubMed Central

Kumar, Adepu K.; Yennawar, Neela H.; Yennawar, Hemant P.; Ferry, James G.

2011-01-01

The genome of Methanosarcina acetivorans contains a gene (ma1659) that is predicted to encode an uncharacterized chimeric protein containing a plant-type ferredoxin/thioredoxin reductase-like catalytic domain in the N-terminal region and a bacterial-like rubredoxin domain in the C-terminal region. To understand the structural and functional properties of the protein, the ma1659 gene was cloned and overexpressed in Escherichia coli. Crystals of the MA1659 protein were grown by the sitting-drop method using 2 M ammonium sulfate, 0.1 M HEPES buffer pH 7.5 and 0.1 M urea. Diffraction data were collected to 2.8 Å resolution using the remote data-collection feature of the Advanced Light Source, Lawrence Berkeley National Laboratory. The crystal belonged to the primitive cubic space group P23 or P213, with unit-cell parameters a = b = c = 92.72 Å. Assuming the presence of one molecule in the asymmetric unit gave a Matthews coefficient (V M) of 3.55 Å3 Da−1, corresponding to a solvent content of 65%. PMID:21795791

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

Zhou, Dongwen; Sun, Jianping; Zhao, Wei

The CRD domain of GRP from H. sapiens has been expressed, purified and crystallized and X-ray diffraction data have been collected to a resolution of 2.0 Å. Galectins are a family of animal lectins which share similar carbohydrate-recognition domains (CRDs) and an affinity for β-galactosides. A novel human galectin-related protein named GRP (galectin-related protein; previously known as HSPC159) comprises only one conserved CRD with 38 additional N-terminal residues. The C-terminal fragment of human GRP (GRP-C; residues 38–172) containing the CRD has been expressed and purified. The protein was crystallized using the hanging-drop vapour-diffusion method from a solution containing 2% PEGmore » 400 and 2M ammonium sulfate in 100 mM Tris–HCl buffer pH 7.5. Diffraction data were collected to a resolution limit of 2.0 Å at beamline 3W1A of Beijing Synchrotron Radiation Facility at 100 K. The crystals belong to the monoclinic space group C2, with unit-cell parameters a = 123.07, b = 96.67, c = 61.56 Å, β = 118.72°. The estimated Matthews coefficient was 2.6 Å{sup 3} Da{sup −1}, corresponding to 51.8% solvent content.« less

Crystallization of Δ{sup 1}-tetrahydrocannabinolic acid (THCA) synthase from Cannabis sativa

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

Shoyama, Yoshinari; Takeuchi, Ayako; Taura, Futoshi

Δ{sup 1}-Tetrahydrocannabinolic acid (THCA) synthase from C. sativa was crystallized. The crystal diffracted to 2.7 Å resolution with sufficient quality for further structure determination. Δ{sup 1}-Tetrahydrocannabinolic acid (THCA) synthase is a novel oxidoreductase that catalyzes the biosynthesis of the psychoactive compound THCA in Cannabis sativa (Mexican strain). In order to investigate the structure–function relationship of THCA synthase, this enzyme was overproduced in insect cells, purified and finally crystallized in 0.1 M HEPES buffer pH 7.5 containing 1.4 M sodium citrate. A single crystal suitable for X-ray diffraction measurement was obtained in 0.09 M HEPES buffer pH 7.5 containing 1.26 Mmore » sodium citrate. The crystal diffracted to 2.7 Å resolution at beamline BL41XU, SPring-8. The crystal belonged to the primitive cubic space group P432, with unit-cell parameters a = b = c = 178.2 Å. The calculated Matthews coefficient was approximately 4.1 or 2.0 Å{sup 3} Da{sup −1} assuming the presence of one or two molecules of THCA synthase in the asymmetric unit, respectively.« less

Insect-cell expression, crystallization and X-ray data collection of the bradyzoite-specific antigen BSR4 from Toxoplasma gondii

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

Grujic, Ognjen; Grigg, Michael E.; Boulanger, Martin J., E-mail: mboulang@uvic.ca

2008-05-01

Preliminary X-ray diffraction studies of the bradyzoite-specific surface antigen BSR4 from T. gondii are described. Toxoplasma gondii is an important global pathogen that infects nearly one third of the world’s adult population. A family of developmentally expressed structurally related surface-glycoprotein adhesins (SRSs) mediate attachment to and are utilized for entry into host cells. The latent bradyzoite form of T. gondii persists for the life of the host and expresses a distinct family of SRS proteins, of which the bradyzoite-specific antigen BSR4 is a prototypical member. Structural studies of BSR4 were initiated by first recombinantly expressing BSR4 in insect cells, whichmore » was followed by crystallization and preliminary X-ray data collection to 1.95 Å resolution. Data processing showed that BSR4 crystallized with one molecule in the asymmetric unit of the P4{sub 1}2{sub 1}2 or P4{sub 3}2{sub 1}2 space group, with a solvent content of 60% and a corresponding Matthews coefficient of 2.98 Å{sup 3} Da{sup −1}.« less

Expression, purification, crystallization and preliminary X-ray analysis of the ligand-binding domain of metabotropic glutamate receptor 7

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

Muto, Takanori; Tsuchiya, Daisuke; Morikawa, Kosuke, E-mail: morikako@protein.osaka-u.ac.jp

2007-07-01

The ligand-binding domain of metabotropic glutamate receptor 7 has been overexpressed, purified, and crystallized by the hanging-drop vapour-diffusion method. A complete data set has been collected to 3.30 Å. Glutamate is the major excitatory neurotransmitter and its metabotropic glutamate receptor (mGluR) plays an important role in the central nervous system. The ligand-binding domain (LBD) of mGluR subtype 7 (mGluR7) was produced using the baculovirus expression system and purified from the culture medium. The purified protein was characterized by gel-filtration chromatography, SDS–PAGE and a ligand-binding assay. Crystals of mGluR7 LBD were grown at 293 K by the hanging-drop vapour-diffusion method. Themore » crystals diffracted X-rays to 3.30 Å resolution using synchrotron radiation and belong to the trigonal space group P3{sub 1}21, with unit-cell parameters a = b = 92.4, c = 114.3 Å. Assuming the presence of one protomer per crystallographic asymmetric unit, the Matthews coefficient V{sub M} was calculated to be 2.5 Å{sup 3} Da{sup −1} and the solvent content was 51%.« less

Purification, crystallization and X-ray diffraction analysis of a novel ring-cleaving enzyme (BoxC{sub C}) from Burkholderia xenovorans LB400

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

Bains, Jasleen; Boulanger, Martin J., E-mail: mboulang@uvic.ca

2008-05-01

Preliminary X-ray diffraction studies of a novel ring-cleaving enzyme from B. xenovorans LB400 encoded by the benzoate-oxidation (box) pathway. The assimilation of aromatic compounds by microbial species requires specialized enzymes to cleave the thermodynamically stable ring. In the recently discovered benzoate-oxidation (box) pathway in Burkholderia xenovorans LB400, this is accomplished by a novel dihydrodiol lyase (BoxC{sub C}). Sequence analysis suggests that BoxC{sub C} is part of the crotonase superfamily but includes an additional uncharacterized region of approximately 115 residues that is predicted to mediate ring cleavage. Processing of X-ray diffraction data to 1.5 Å resolution revealed that BoxC{sub C} crystallizedmore » with two molecules in the asymmetric unit of the P2{sub 1}2{sub 1}2{sub 1} space group, with a solvent content of 47% and a Matthews coefficient of 2.32 Å{sup 3} Da{sup −1}. Selenomethionine BoxC{sub C} has been purified and crystals are currently being refined for anomalous dispersion studies.« less

Cloning, purification, crystallization and preliminary structural studies of penicillin V acylase from Bacillus subtilis

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

Rathinaswamy, Priya; Pundle, Archana V.; Prabhune, Asmita A.

An unannotated protein reported from B. subtilis has been expressed in E. coli and identified as possessing penicillin V acylase activity. The crystallization and preliminary crystallographic analysis of this penicillin V acylase is presented. Penicillin acylase proteins are amidohydrolase enzymes that cleave penicillins at the amide bond connecting the side chain to their β-lactam nucleus. An unannotated protein from Bacillus subtilis has been expressed in Escherichia coli, purified and confirmed to possess penicillin V acylase activity. The protein was crystallized using the hanging-drop vapour-diffusion method from a solution containing 4 M sodium formate in 100 mM Tris–HCl buffer pH 8.2.more » Diffraction data were collected under cryogenic conditions to a spacing of 2.5 Å. The crystals belonged to the orthorhombic space group C222{sub 1}, with unit-cell parameters a = 111.0, b = 308.0, c = 56.0 Å. The estimated Matthews coefficient was 3.23 Å{sup 3} Da{sup −1}, corresponding to 62% solvent content. The structure has been solved using molecular-replacement methods with B. sphaericus penicillin V acylase (PDB code 2pva) as the search model.« less

Recombinant production, crystallization and X-ray crystallographic structure determination of the peptidyl-tRNA hydrolase of Pseudomonas aeruginosa

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

Hughes, Ronny C.; McFeeters, Hana; Coates, Leighton

The peptidyl-tRNA hydrolase enzyme from the pathogenic bacterium Pseudomonas aeruginosa (Pth; EC 3.1.1.29) has been cloned, expressed in Escherichia coli and crystallized for X-ray structural analysis. Suitable crystals were grown using the sitting-drop vapour-diffusion method after one week of incubation against a reservoir solution consisting of 20% polyethylene glycol 4000, 100 mM Tris pH 7.5, 10%(v/v) isopropyl alcohol. The crystals were used to obtain the three-dimensional structure of the native protein at 1.77 Å resolution. The structure was determined by molecular replacement of the crystallographic data processed in space group P6122 with unit-cell parameters a = b = 63.62,c =more » 155.20 Å, α = β = 90, γ = 120°. The asymmetric unit of the crystallographic lattice was composed of a single copy of the enzyme molecule with a 43% solvent fraction, corresponding to a Matthews coefficient of 2.43 Å3 Da-1. The crystallographic structure reported here will serve as the foundation for future structure-guided efforts towards the development of novel small-molecule inhibitors specific to bacterial Pths.« less

QSAR modeling of flotation collectors using principal components extracted from topological indices.

PubMed

Natarajan, R; Nirdosh, Inderjit; Basak, Subhash C; Mills, Denise R

2002-01-01

Several topological indices were calculated for substituted-cupferrons that were tested as collectors for the froth flotation of uranium. The principal component analysis (PCA) was used for data reduction. Seven principal components (PC) were found to account for 98.6% of the variance among the computed indices. The principal components thus extracted were used in stepwise regression analyses to construct regression models for the prediction of separation efficiencies (Es) of the collectors. A two-parameter model with a correlation coefficient of 0.889 and a three-parameter model with a correlation coefficient of 0.913 were formed. PCs were found to be better than partition coefficient to form regression equations, and inclusion of an electronic parameter such as Hammett sigma or quantum mechanically derived electronic charges on the chelating atoms did not improve the correlation coefficient significantly. The method was extended to model the separation efficiencies of mercaptobenzothiazoles (MBT) and aminothiophenols (ATP) used in the flotation of lead and zinc ores, respectively. Five principal components were found to explain 99% of the data variability in each series. A three-parameter equation with correlation coefficient of 0.985 and a two-parameter equation with correlation coefficient of 0.926 were obtained for MBT and ATP, respectively. The amenability of separation efficiencies of chelating collectors to QSAR modeling using PCs based on topological indices might lead to the selection of collectors for synthesis and testing from a virtual database.

Different hip and knee priority score systems: are they good for the same thing?

PubMed

Escobar, Antonio; Quintana, Jose Maria; Espallargues, Mireia; Allepuz, Alejandro; Ibañez, Berta

2010-10-01

The aim of the present study was to compare two priority tools used for joint replacement for patients on waiting lists, which use two different methods. Two prioritization tools developed and validated by different methodologies were used on the same cohort of patients. The first, an IRYSS hip and knee priority score (IHKPS) developed by RAND method, was applied while patients were on the waiting list. The other, a Catalonia hip-knee priority score (CHKPS) developed by conjoint analysis, was adapted and applied retrospectively. In addition, all patients fulfilled pre-intervention the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Correlation between them was studied by Pearson correlation coefficient (r). Agreement was analysed by means of intra-class correlation coefficient (ICC), Kendall coefficient and Cohern kappa. The relationship between IHKPS, CHKPS and baseline WOMAC scores by r coefficient was studied. The sample consisted of 774 consecutive patients. Pearson correlation coefficient between IHKPS and CHKPS was 0.79. The agreement study showed that ICC was 0.74, Kendall coefficient 0.86 and kappa 0.66. Finally, correlation between CHKPS and baseline WOMAC ranged from 0.43 to 0.64. The results according to the relationship between IHKPS and WOMAC ranged from 0.50 to 0.74. Results support the hypothesis that if the final objective of the prioritization tools is to organize and sort patients on the waiting list, although they use different methodologies, the results are similar. © 2010 Blackwell Publishing Ltd.

High-resolution correlation

NASA Astrophysics Data System (ADS)

Nelson, D. J.

2007-09-01

In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.

Development of stock correlation networks using mutual information and financial big data.

PubMed

Guo, Xue; Zhang, Hu; Tian, Tianhai

2018-01-01

Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices.

Development of stock correlation networks using mutual information and financial big data

PubMed Central

Guo, Xue; Zhang, Hu

2018-01-01

Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices. PMID:29668715

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

PubMed

Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

2017-12-04

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further using multiple metrics with much larger scale comparisons, prospective testing as well as assessment of different fingerprints and DNN architectures beyond those used.

Validity and reliability of two brief physical activity questionnaires among Spanish-speaking individuals of Mexican descent.

PubMed

Vega-López, Sonia; Chavez, Adrian; Farr, Kristin J; Ainsworth, Barbara E

2014-01-13

Mexican Americans are the largest minority group in the US and suffer disproportionate rates of diseases related to the lack of physical activity (PA). Since many of these Mexican Americans are Spanish-speaking, it is important to validate a Spanish language physical activity assessment tool that can be used in epidemiology as well as clinical practice. This study explored the utility of two Spanish translated physical activity questionnaires, the Stanford Brief Activity Survey (SBAS) and the Rapid Assessment of Physical Activity (RAPA), for use among Spanish-speaking Mexican Americans. Thirty-four participants (13 M, 21 F; 37.6 ± 9.5 y) completed each of the two PA surveys twice, one week apart. During that week 31 participants also wore an ActiGraph GT1M accelerometer for 7 days to objectively measure PA. Minutes of moderate and vigorous PA (MVPA) were determined from the accelerometer data using Freedson and Matthews cut points. Validity, determined by Spearman correlation coefficients between questionnaire scores and minutes of ActiGraph measured MVPA were 0.38 and 0.45 for the SBAS and RAPA, respectively. Test-retest reliability was 0.61 for the SBAS and 0.65 for the RAPA. Sensitivity and specificity were 0.60 and 0.47 for the SBAS, and 0.73 and 0.75 for the RAPA. Participants who were classified as meeting the 2008 National Physical Activity Guidelines by the RAPA engaged in significantly (p < 0.05) more minutes of MVPA than those who were not, while there were no significant differences in minutes of MVPA classified by the SBAS. The SBAS and the RAPA are both reasonably valid measures for quickly assessing PA and determining compliance to the PA guidelines in Spanish-speaking Mexican Americans. Although the two questionnaires had comparable reliability, the RAPA was better able to distinguish between those who met and did not meet National PA Guidelines.

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

PubMed Central

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 the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors. PMID:22701576

Supervised embedding of textual predictors with applications in clinical diagnostics for pediatric cardiology.

PubMed

Perry, Thomas Ernest; Zha, Hongyuan; Zhou, Ke; Frias, Patricio; Zeng, Dadan; Braunstein, Mark

2014-02-01

Electronic health records possess critical predictive information for machine-learning-based diagnostic aids. However, many traditional machine learning methods fail to simultaneously integrate textual data into the prediction process because of its high dimensionality. In this paper, we present a supervised method using Laplacian Eigenmaps to enable existing machine learning methods to estimate both low-dimensional representations of textual data and accurate predictors based on these low-dimensional representations at the same time. We present a supervised Laplacian Eigenmap method to enhance predictive models by embedding textual predictors into a low-dimensional latent space, which preserves the local similarities among textual data in high-dimensional space. The proposed implementation performs alternating optimization using gradient descent. For the evaluation, we applied our method to over 2000 patient records from a large single-center pediatric cardiology practice to predict if patients were diagnosed with cardiac disease. In our experiments, we consider relatively short textual descriptions because of data availability. We compared our method with latent semantic indexing, latent Dirichlet allocation, and local Fisher discriminant analysis. The results were assessed using four metrics: the area under the receiver operating characteristic curve (AUC), Matthews correlation coefficient (MCC), specificity, and sensitivity. The results indicate that supervised Laplacian Eigenmaps was the highest performing method in our study, achieving 0.782 and 0.374 for AUC and MCC, respectively. Supervised Laplacian Eigenmaps showed an increase of 8.16% in AUC and 20.6% in MCC over the baseline that excluded textual data and a 2.69% and 5.35% increase in AUC and MCC, respectively, over unsupervised Laplacian Eigenmaps. As a solution, we present a supervised Laplacian Eigenmap method to embed textual predictors into a low-dimensional Euclidean space. This method allows many existing machine learning predictors to effectively and efficiently capture the potential of textual predictors, especially those based on short texts.

Stratiform/convective rain delineation for TRMM microwave imager

NASA Astrophysics Data System (ADS)

Islam, Tanvir; Srivastava, Prashant K.; Dai, Qiang; Gupta, Manika; Wan Jaafar, Wan Zurina

2015-10-01

This article investigates the potential for using machine learning algorithms to delineate stratiform/convective (S/C) rain regimes for passive microwave imager taking calibrated brightness temperatures as only spectral parameters. The algorithms have been implemented for the Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI), and calibrated as well as validated taking the Precipitation Radar (PR) S/C information as the target class variables. Two different algorithms are particularly explored for the delineation. The first one is metaheuristic adaptive boosting algorithm that includes the real, gentle, and modest versions of the AdaBoost. The second one is the classical linear discriminant analysis that includes the Fisher's and penalized versions of the linear discriminant analysis. Furthermore, prior to the development of the delineation algorithms, a feature selection analysis has been conducted for a total of 85 features, which contains the combinations of brightness temperatures from 10 GHz to 85 GHz and some derived indexes, such as scattering index, polarization corrected temperature, and polarization difference with the help of mutual information aided minimal redundancy maximal relevance criterion (mRMR). It has been found that the polarization corrected temperature at 85 GHz and the features derived from the "addition" operator associated with the 85 GHz channels have good statistical dependency to the S/C target class variables. Further, it has been shown how the mRMR feature selection technique helps to reduce the number of features without deteriorating the results when applying through the machine learning algorithms. The proposed scheme is able to delineate the S/C rain regimes with reasonable accuracy. Based on the statistical validation experience from the validation period, the Matthews correlation coefficients are in the range of 0.60-0.70. Since, the proposed method does not rely on any a priori information, this makes it very suitable for other microwave sensors having similar channels to the TMI. The method could possibly benefit the constellation sensors in the Global Precipitation Measurement (GPM) mission era.

Using experts feedback in clinical case resolution and arbitration as accuracy diagnosis methodology.

PubMed

Rodríguez-González, Alejandro; Torres-Niño, Javier; Valencia-Garcia, Rafael; Mayer, Miguel A; Alor-Hernandez, Giner

2013-09-01

This paper proposes a new methodology for assessing the efficiency of medical diagnostic systems and clinical decision support systems by using the feedback/opinions of medical experts. The methodology behind this work is based on a comparison between the expert feedback that has helped solve different clinical cases and the expert system that has evaluated these same cases. Once the results are returned, an arbitration process is carried out in order to ensure the correctness of the results provided by both methods. Once this process has been completed, the results are analyzed using Precision, Recall, Accuracy, Specificity and Matthews Correlation Coefficient (MCC) (PRAS-M) metrics. When the methodology is applied, the results obtained from a real diagnostic system allow researchers to establish the accuracy of the system based on objective facts. The methodology returns enough information to analyze the system's behavior for each disease in the knowledge base or across the entire knowledge base. It also returns data on the efficiency of the different assessors involved in the evaluation process, analyzing their behavior in the diagnostic process. The proposed work facilitates the evaluation of medical diagnostic systems, having a reliable process based on objective facts. The methodology presented in this research makes it possible to identify the main characteristics that define a medical diagnostic system and their values, allowing for system improvement. A good example of the results provided by the application of the methodology is shown in this paper. A diagnosis system was evaluated by means of this methodology, yielding positive results (statistically significant) when comparing the system with the assessors that participated in the evaluation process of the system through metrics such as recall (+27.54%) and MCC (+32.19%). These results demonstrate the real applicability of the methodology used. Copyright © 2013 Elsevier Ltd. All rights reserved.

Prediction of Carbohydrate Binding Sites on Protein Surfaces with 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

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

2012-01-01

Non-covalent protein-carbohydrate interactions mediate molecular targeting in many biological processes. Prediction of non-covalent carbohydrate binding sites on protein surfaces not only provides insights into the functions of the query proteins; information on key carbohydrate-binding residues could suggest site-directed mutagenesis experiments, design therapeutics targeting carbohydrate-binding proteins, and provide guidance in engineering protein-carbohydrate interactions. In this work, we show that non-covalent carbohydrate binding sites on protein surfaces can be predicted with relatively high accuracy when the query protein structures are known. The prediction capabilities were based on a novel encoding scheme of the three-dimensional probability density maps describing the distributions of 36 non-covalent interacting atom types around protein surfaces. One machine learning model was trained for each of the 30 protein atom types. The machine learning algorithms predicted tentative carbohydrate binding sites on query proteins by recognizing the characteristic interacting atom distribution patterns specific for carbohydrate binding sites from known protein structures. The prediction results for all protein atom types were integrated into surface patches as tentative carbohydrate binding sites based on normalized prediction confidence level. The prediction capabilities of the predictors were benchmarked by a 10-fold cross validation on 497 non-redundant proteins with known carbohydrate binding sites. The predictors were further tested on an independent test set with 108 proteins. The residue-based Matthews correlation coefficient (MCC) for the independent test was 0.45, with prediction precision and sensitivity (or recall) of 0.45 and 0.49 respectively. In addition, 111 unbound carbohydrate-binding protein structures for which the structures were determined in the absence of the carbohydrate ligands were predicted with the trained predictors. The overall prediction MCC was 0.49. Independent tests on anti-carbohydrate antibodies showed that the carbohydrate antigen binding sites were predicted with comparable accuracy. These results demonstrate that the predictors are among the best in carbohydrate binding site predictions to date. PMID:22848404

Quantification of knee vibroarthrographic signal irregularity associated with patellofemoral joint cartilage pathology based on entropy and envelope amplitude measures.

PubMed

Wu, Yunfeng; Chen, Pinnan; Luo, Xin; Huang, Hui; Liao, Lifang; Yao, Yuchen; Wu, Meihong; Rangayyan, Rangaraj M

2016-07-01

Injury of knee joint cartilage may result in pathological vibrations between the articular surfaces during extension and flexion motions. The aim of this paper is to analyze and quantify vibroarthrographic (VAG) signal irregularity associated with articular cartilage degeneration and injury in the patellofemoral joint. The symbolic entropy (SyEn), approximate entropy (ApEn), fuzzy entropy (FuzzyEn), and the mean, standard deviation, and root-mean-squared (RMS) values of the envelope amplitude, were utilized to quantify the signal fluctuations associated with articular cartilage pathology of the patellofemoral joint. The quadratic discriminant analysis (QDA), generalized logistic regression analysis (GLRA), and support vector machine (SVM) methods were used to perform signal pattern classifications. The experimental results showed that the patients with cartilage pathology (CP) possess larger SyEn and ApEn, but smaller FuzzyEn, over the statistical significance level of the Wilcoxon rank-sum test (p<0.01), than the healthy subjects (HS). The mean, standard deviation, and RMS values computed from the amplitude difference between the upper and lower signal envelopes are also consistently and significantly larger (p<0.01) for the group of CP patients than for the HS group. The SVM based on the entropy and envelope amplitude features can provide superior classification performance as compared with QDA and GLRA, with an overall accuracy of 0.8356, sensitivity of 0.9444, specificity of 0.8, Matthews correlation coefficient of 0.6599, and an area of 0.9212 under the receiver operating characteristic curve. The SyEn, ApEn, and FuzzyEn features can provide useful information about pathological VAG signal irregularity based on different entropy metrics. The statistical parameters of signal envelope amplitude can be used to characterize the temporal fluctuations related to the cartilage pathology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Laser Raman detection for oral cancer based on a Gaussian process classification method

NASA Astrophysics Data System (ADS)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

2013-06-01

Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive.

Comprehensive evaluation of AmpliSeq transcriptome, a novel targeted whole transcriptome RNA sequencing methodology for global gene expression analysis.

PubMed

Li, Wenli; Turner, Amy; Aggarwal, Praful; Matter, Andrea; Storvick, Erin; Arnett, Donna K; Broeckel, Ulrich

2015-12-16

Whole transcriptome sequencing (RNA-seq) represents a powerful approach for whole transcriptome gene expression analysis. However, RNA-seq carries a few limitations, e.g., the requirement of a significant amount of input RNA and complications led by non-specific mapping of short reads. The Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq) was recently introduced by Life Technologies as a whole-transcriptome, targeted gene quantification kit to overcome these limitations of RNA-seq. To assess the performance of this new methodology, we performed a comprehensive comparison of AmpliSeq with RNA-seq using two well-established next-generation sequencing platforms (Illumina HiSeq and Ion Torrent Proton). We analyzed standard reference RNA samples and RNA samples obtained from human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). Using published data from two standard RNA reference samples, we observed a strong concordance of log2 fold change for all genes when comparing AmpliSeq to Illumina HiSeq (Pearson's r = 0.92) and Ion Torrent Proton (Pearson's r = 0.92). We used ROC, Matthew's correlation coefficient and RMSD to determine the overall performance characteristics. All three statistical methods demonstrate AmpliSeq as a highly accurate method for differential gene expression analysis. Additionally, for genes with high abundance, AmpliSeq outperforms the two RNA-seq methods. When analyzing four closely related hiPSC-CM lines, we show that both AmpliSeq and RNA-seq capture similar global gene expression patterns consistent with known sources of variations. Our study indicates that AmpliSeq excels in the limiting areas of RNA-seq for gene expression quantification analysis. Thus, AmpliSeq stands as a very sensitive and cost-effective approach for very large scale gene expression analysis and mRNA marker screening with high accuracy.

Obstructive Sleep Apnea in Obese Hospitalized Patients: A Single Center Experience

PubMed Central

Sharma, Sunil; Mather, Paul J.; Efird, Jimmy T.; Kahn, Daron; Shiue, Kristin Y.; Cheema, Mohammed; Malloy, Raymond; Quan, Stuart F.

2015-01-01

Study Objectives: Obstructive sleep apnea (OSA) is an important health problem associated with significant morbidity and mortality. This condition often is underrecognized in hospitalized patients. The aim of this study was to conduct a clinical pathway evaluation (CPE) among obese patients admitted to a tertiary care hospital. We also assessed oxygen desaturation index (ODI, measured by overnight pulse oximetry) as a potential low-cost screening tool for identifying OSA. Methods: This was a prospective study of 754 patients admitted to an academic medical center between February 2013 and February 2014. Consecutive obese patients (body mass index ≥ 30) admitted to the hospital (medical services) were screened and evaluated for OSA with the snoring, tiredness during daytime, observed apnea, high blood pressure (STOP) questionnaire. The admitting team was advised to perform follow-up evaluation, including polysomnography, if the test was positive. Results: A total of 636 patients were classified as high risk and 118 as low risk for OSA. Within 4 w of discharge, 149 patients underwent polysomnography, and of these, 87% (129) were shown to have OSA. An optimal screening cutoff point for OSA (apnea-hypopnea index ≥ 10/h) was determined to be ODI ≥ 10/h [Matthews correlation coefficient = 0.36, 95% confidence interval = 0.24–0.47]. Significantly more hospitalized patients were identified and underwent polysomnography compared with the year prior to introduction of the CPE. Conclusions: Our results indicate that the CPE increased the identification of OSA in this population. Furthermore, ODI derived from overnight pulse oximetry may be a cost-effective strategy to screen for OSA in hospitalized patients. Citation: Sharma S, Mather PJ, Efird JT, Kahn D, Shiue KY, Cheema M, Malloy R, Quan SF. Obstructive sleep apnea in obese hospitalized patients: a single center experience. J Clin Sleep Med 2015;11(7):717–723. PMID:25766715

Validity and reliability of two brief physical activity questionnaires among Spanish-speaking individuals of Mexican descent

PubMed Central

2014-01-01

Background Mexican Americans are the largest minority group in the US and suffer disproportionate rates of diseases related to the lack of physical activity (PA). Since many of these Mexican Americans are Spanish-speaking, it is important to validate a Spanish language physical activity assessment tool that can be used in epidemiology as well as clinical practice. This study explored the utility of two Spanish translated physical activity questionnaires, the Stanford Brief Activity Survey (SBAS) and the Rapid Assessment of Physical Activity (RAPA), for use among Spanish-speaking Mexican Americans. Methods Thirty-four participants (13 M, 21 F; 37.6 ± 9.5 y) completed each of the two PA surveys twice, one week apart. During that week 31 participants also wore an ActiGraph GT1M accelerometer for 7 days to objectively measure PA. Minutes of moderate and vigorous PA (MVPA) were determined from the accelerometer data using Freedson and Matthews cut points. Results Validity, determined by Spearman correlation coefficients between questionnaire scores and minutes of ActiGraph measured MVPA were 0.38 and 0.45 for the SBAS and RAPA, respectively. Test-retest reliability was 0.61 for the SBAS and 0.65 for the RAPA. Sensitivity and specificity were 0.60 and 0.47 for the SBAS, and 0.73 and 0.75 for the RAPA. Participants who were classified as meeting the 2008 National Physical Activity Guidelines by the RAPA engaged in significantly (p < 0.05) more minutes of MVPA than those who were not, while there were no significant differences in minutes of MVPA classified by the SBAS. Conclusions The SBAS and the RAPA are both reasonably valid measures for quickly assessing PA and determining compliance to the PA guidelines in Spanish-speaking Mexican Americans. Although the two questionnaires had comparable reliability, the RAPA was better able to distinguish between those who met and did not meet National PA Guidelines. PMID:24410978

Spaced antenna diversity in temperate latitude meteor burst systems operating near 40 MHz - Variation of signal cross-correlation coefficients with antenna separation

NASA Astrophysics Data System (ADS)

Cannon, Paul S.; Shukla, Anil K.; Lester, Mark

1993-04-01

We have studied 37-MHz signals received over an 800-km temperate latitude path using 400-W continuous wave transmissions. Signals collected during a 9-day period in February 1990 on two antennas at separations of 5, 10, and 20 lambda were analyzed. Three signal categories were identified (overdense, underdense, and not known (NK)) and cross-correlation coefficients between the signals received by the two antennas were calculated for each signal category. No spatial variation, and in particular no decrease, in average cross-correlation coefficient was observed for underdense or NK signals as the antenna spacing was increased from 5 to 20 lambda. At each antenna separation the cross-correlation coefficients of these two categories were strongly dependent on time. Overdense signals, however, showed no cross-correlation time dependency at 5 and 10 lambda, but there was a strong time dependency at 20 lambda. Recommendations are made in regard to the optimum antenna spacing for a meteor burst communication system using spaced antenna diversity.

Transcultural adaptation and psychometric properties of Spanish version of Pregnancy Physical Activity Questionnaire: the PregnActive project.

PubMed

Oviedo-Caro, Miguel Ángel; Bueno-Antequera, Javier; Munguía-Izquierdo, Diego

2018-03-19

To transculturally adapt the Spanish version of Pregnancy Physical Activity Questionnaire (PPAQ) analyzing its psychometric properties. The PPAQ was transculturally adapted into Spanish. Test-retest reliability was evaluated in a subsample of 109 pregnant women. The validity was evaluated in a sample of 208 pregnant women who answered the questionnaire and wore the multi-sensor monitor for 7 valid days. The reliability (intraclass correlation coefficient), concordance (concordance correlation coefficient), correlation (Pearson correlation coefficient), agreement (Bland-Altman plots) and relative activity levels (Jonckheere-Terpstra test) between both administrations and methods were examined. Intraclass correlation coefficients between both administrations were good for all categories except transportation. A low but significant correlation was found for total activity (light and above) whereas no correlation was found for other intensities between both methods. Relative activity levels analysis showed a significant linear trend for increased total activity between both methods. Spanish version of PPAQ is a brief and easily interpretable questionnaire with good reliability and ability to rank individuals, and poor validity compared with multi-sensor monitor. The use of PPAQ provides information of pregnancy-specific activities in order to establish physical activity levels of pregnant women and adapt health promotion interventions. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Cross-Correlations and Structures of Aero-Engine Gas Path System Based on DCCA Coefficient and Rooted Tree

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Fan, Jie; Gao, You

2015-12-01

Identifying the mutual interaction is a crucial problem that facilitates the understanding of emerging structures in complex system. We here focus on aero-engine dynamic as an example of complex system. By applying the detrended cross-correlation analysis (DCCA) coefficient method to aero-engine gas path system, we find that the low-spool rotor speed (N1) and high-spool rotor speed (N2) fluctuation series exhibit cross-correlation characteristic. Further, we employ detrended cross-correlation coefficient matrix and rooted tree to investigate the mutual interactions of other gas path variables. The results can infer that the exhaust gas temperature (EGT), N1, N2, fuel flow (WF) and engine pressure ratio (EPR) are main gas path parameters.

Colocalization analysis in fluorescence micrographs: verification of a more accurate calculation of pearson's correlation coefficient.

PubMed

Barlow, Andrew L; Macleod, Alasdair; Noppen, Samuel; Sanderson, Jeremy; Guérin, Christopher J

2010-12-01

One of the most routine uses of fluorescence microscopy is colocalization, i.e., the demonstration of a relationship between pairs of biological molecules. Frequently this is presented simplistically by the use of overlays of red and green images, with areas of yellow indicating colocalization of the molecules. Colocalization data are rarely quantified and can be misleading. Our results from both synthetic and biological datasets demonstrate that the generation of Pearson's correlation coefficient between pairs of images can overestimate positive correlation and fail to demonstrate negative correlation. We have demonstrated that the calculation of a thresholded Pearson's correlation coefficient using only intensity values over a determined threshold in both channels produces numerical values that more accurately describe both synthetic datasets and biological examples. Its use will bring clarity and accuracy to colocalization studies using fluorescent microscopy.