WorldWideScience

Sample records for multiple dataset correlation

  1. ASSISTments Dataset from Multiple Randomized Controlled Experiments

    Science.gov (United States)

    Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil

    2016-01-01

    In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…

  2. Compilation and analysis of multiple groundwater-quality datasets for Idaho

    Science.gov (United States)

    Hundt, Stephen A.; Hopkins, Candice B.

    2018-05-09

    Groundwater is an important source of drinking and irrigation water throughout Idaho, and groundwater quality is monitored by various Federal, State, and local agencies. The historical, multi-agency records of groundwater quality include a valuable dataset that has yet to be compiled or analyzed on a statewide level. The purpose of this study is to combine groundwater-quality data from multiple sources into a single database, to summarize this dataset, and to perform bulk analyses to reveal spatial and temporal patterns of water quality throughout Idaho. Data were retrieved from the Water Quality Portal (https://www.waterqualitydata.us/), the Idaho Department of Environmental Quality, and the Idaho Department of Water Resources. Analyses included counting the number of times a sample location had concentrations above Maximum Contaminant Levels (MCL), performing trends tests, and calculating correlations between water-quality analytes. The water-quality database and the analysis results are available through USGS ScienceBase (https://doi.org/10.5066/F72V2FBG).

  3. Sparse Group Penalized Integrative Analysis of Multiple Cancer Prognosis Datasets

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Xie, Yang; Ma, Shuangge

    2014-01-01

    SUMMARY In cancer research, high-throughput profiling studies have been extensively conducted, searching for markers associated with prognosis. Because of the “large d, small n” characteristic, results generated from the analysis of a single dataset can be unsatisfactory. Recent studies have shown that integrative analysis, which simultaneously analyzes multiple datasets, can be more effective than single-dataset analysis and classic meta-analysis. In most of existing integrative analysis, the homogeneity model has been assumed, which postulates that different datasets share the same set of markers. Several approaches have been designed to reinforce this assumption. In practice, different datasets may differ in terms of patient selection criteria, profiling techniques, and many other aspects. Such differences may make the homogeneity model too restricted. In this study, we assume the heterogeneity model, under which different datasets are allowed to have different sets of markers. With multiple cancer prognosis datasets, we adopt the AFT (accelerated failure time) model to describe survival. This model may have the lowest computational cost among popular semiparametric survival models. For marker selection, we adopt a sparse group MCP (minimax concave penalty) approach. This approach has an intuitive formulation and can be computed using an effective group coordinate descent algorithm. Simulation study shows that it outperforms the existing approaches under both the homogeneity and heterogeneity models. Data analysis further demonstrates the merit of heterogeneity model and proposed approach. PMID:23938111

  4. Using Multiple Big Datasets and Machine Learning to Produce a New Global Particulate Dataset: A Technology Challenge Case Study

    Science.gov (United States)

    Lary, D. J.

    2013-12-01

    A BigData case study is described where multiple datasets from several satellites, high-resolution global meteorological data, social media and in-situ observations are combined using machine learning on a distributed cluster using an automated workflow. The global particulate dataset is relevant to global public health studies and would not be possible to produce without the use of the multiple big datasets, in-situ data and machine learning.To greatly reduce the development time and enhance the functionality a high level language capable of parallel processing has been used (Matlab). A key consideration for the system is high speed access due to the large data volume, persistence of the large data volumes and a precise process time scheduling capability.

  5. Correction of elevation offsets in multiple co-located lidar datasets

    Science.gov (United States)

    Thompson, David M.; Dalyander, P. Soupy; Long, Joseph W.; Plant, Nathaniel G.

    2017-04-07

    IntroductionTopographic elevation data collected with airborne light detection and ranging (lidar) can be used to analyze short- and long-term changes to beach and dune systems. Analysis of multiple lidar datasets at Dauphin Island, Alabama, revealed systematic, island-wide elevation differences on the order of 10s of centimeters (cm) that were not attributable to real-world change and, therefore, were likely to represent systematic sampling offsets. These offsets vary between the datasets, but appear spatially consistent within a given survey. This report describes a method that was developed to identify and correct offsets between lidar datasets collected over the same site at different times so that true elevation changes over time, associated with sediment accumulation or erosion, can be analyzed.

  6. Visual Comparison of Multiple Gene Expression Datasets in a Genomic Context

    Directory of Open Access Journals (Sweden)

    Borowski Krzysztof

    2008-06-01

    Full Text Available The need for novel methods of visualizing microarray data is growing. New perspectives are beneficial to finding patterns in expression data. The Bluejay genome browser provides an integrative way of visualizing gene expression datasets in a genomic context. We have now developed the functionality to display multiple microarray datasets simultaneously in Bluejay, in order to provide researchers with a comprehensive view of their datasets linked to a graphical representation of gene function. This will enable biologists to obtain valuable insights on expression patterns, by allowing them to analyze the expression values in relation to the gene locations as well as to compare expression profiles of related genomes or of di erent experiments for the same genome.

  7. A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

    Science.gov (United States)

    Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

    2017-06-01

    Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

  8. Multivariate Analysis of Multiple Datasets: a Practical Guide for Chemical Ecology.

    Science.gov (United States)

    Hervé, Maxime R; Nicolè, Florence; Lê Cao, Kim-Anh

    2018-03-01

    Chemical ecology has strong links with metabolomics, the large-scale study of all metabolites detectable in a biological sample. Consequently, chemical ecologists are often challenged by the statistical analyses of such large datasets. This holds especially true when the purpose is to integrate multiple datasets to obtain a holistic view and a better understanding of a biological system under study. The present article provides a comprehensive resource to analyze such complex datasets using multivariate methods. It starts from the necessary pre-treatment of data including data transformations and distance calculations, to the application of both gold standard and novel multivariate methods for the integration of different omics data. We illustrate the process of analysis along with detailed results interpretations for six issues representative of the different types of biological questions encountered by chemical ecologists. We provide the necessary knowledge and tools with reproducible R codes and chemical-ecological datasets to practice and teach multivariate methods.

  9. Imputation and quality control steps for combining multiple genome-wide datasets

    Directory of Open Access Journals (Sweden)

    Shefali S Verma

    2014-12-01

    Full Text Available The electronic MEdical Records and GEnomics (eMERGE network brings together DNA biobanks linked to electronic health records (EHRs from multiple institutions. Approximately 52,000 DNA samples from distinct individuals have been genotyped using genome-wide SNP arrays across the nine sites of the network. The eMERGE Coordinating Center and the Genomics Workgroup developed a pipeline to impute and merge genomic data across the different SNP arrays to maximize sample size and power to detect associations with a variety of clinical endpoints. The 1000 Genomes cosmopolitan reference panel was used for imputation. Imputation results were evaluated using the following metrics: accuracy of imputation, allelic R2 (estimated correlation between the imputed and true genotypes, and the relationship between allelic R2 and minor allele frequency. Computation time and memory resources required by two different software packages (BEAGLE and IMPUTE2 were also evaluated. A number of challenges were encountered due to the complexity of using two different imputation software packages, multiple ancestral populations, and many different genotyping platforms. We present lessons learned and describe the pipeline implemented here to impute and merge genomic data sets. The eMERGE imputed dataset will serve as a valuable resource for discovery, leveraging the clinical data that can be mined from the EHR.

  10. fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

    Science.gov (United States)

    Madrigal, Pedro

    2017-03-01

    Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  11. Multiplicities and Correlations at LEP

    International Nuclear Information System (INIS)

    Sarkisyan, E.K.G.

    2002-01-01

    A brief review on recent charge multiplicity and correlation measurements at LEP is given. The measurements of un biased gluon jet multiplicity are discussed. Recent results on charged particle Bose-Einstein and Fermi-Dirac correlations at LEP1 are reported. New results on two-particle correlations of neutral pions are given. Correlations of more than two particles (high-order correlations) obtained using different methods are performed. Recent Bose-Einstein correlation measurements at LEP2 are discussed. (author)

  12. Multiplicities and correlations at LEP

    CERN Document Server

    Sarkisyan-Grinbaum, E

    2002-01-01

    A brief review on recent charge multiplicity and correlation measurements at LEP is given. The measurements of unbiased gluon jet multiplicity are discussed. Recent results on charged particle Bose- Einstein and Fermi-Dirac correlations at LEP1. are reported. New results on two-particle correlations of neutral pions are given. Correlations of more than two particles (high-order correlations) obtained using different methods are performed. Recent Bose-Einstein correlation measurements at LEP2 are discussed. (13 refs).

  13. Functional Multiple-Set Canonical Correlation Analysis

    Science.gov (United States)

    Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

    2012-01-01

    We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

  14. A Bayesian trans-dimensional approach for the fusion of multiple geophysical datasets

    Science.gov (United States)

    JafarGandomi, Arash; Binley, Andrew

    2013-09-01

    We propose a Bayesian fusion approach to integrate multiple geophysical datasets with different coverage and sensitivity. The fusion strategy is based on the capability of various geophysical methods to provide enough resolution to identify either subsurface material parameters or subsurface structure, or both. We focus on electrical resistivity as the target material parameter and electrical resistivity tomography (ERT), electromagnetic induction (EMI), and ground penetrating radar (GPR) as the set of geophysical methods. However, extending the approach to different sets of geophysical parameters and methods is straightforward. Different geophysical datasets are entered into a trans-dimensional Markov chain Monte Carlo (McMC) search-based joint inversion algorithm. The trans-dimensional property of the McMC algorithm allows dynamic parameterisation of the model space, which in turn helps to avoid bias of the post-inversion results towards a particular model. Given that we are attempting to develop an approach that has practical potential, we discretize the subsurface into an array of one-dimensional earth-models. Accordingly, the ERT data that are collected by using two-dimensional acquisition geometry are re-casted to a set of equivalent vertical electric soundings. Different data are inverted either individually or jointly to estimate one-dimensional subsurface models at discrete locations. We use Shannon's information measure to quantify the information obtained from the inversion of different combinations of geophysical datasets. Information from multiple methods is brought together via introducing joint likelihood function and/or constraining the prior information. A Bayesian maximum entropy approach is used for spatial fusion of spatially dispersed estimated one-dimensional models and mapping of the target parameter. We illustrate the approach with a synthetic dataset and then apply it to a field dataset. We show that the proposed fusion strategy is

  15. Spatial photon correlations in multiple scattering media

    DEFF Research Database (Denmark)

    Smolka, Stephan; Muskens, O.; Lagendijk, A.

    2010-01-01

    We present the first angle-resolved measurements of spatial photon correlations that are induced by multiple scattering of light. The correlation relates multiple scattered photons at different spatial positions and depends on incident photon fluctuations.......We present the first angle-resolved measurements of spatial photon correlations that are induced by multiple scattering of light. The correlation relates multiple scattered photons at different spatial positions and depends on incident photon fluctuations....

  16. Using data from multiple studies to develop a child growth correlation matrix.

    Science.gov (United States)

    Anderson, Craig; Xiao, Luo; Checkley, William

    2018-04-26

    In many countries, the monitoring of child growth does not occur in a regular manner, and instead, we may have to rely on sporadic observations that are subject to substantial measurement error. In these countries, it can be difficult to identify patterns of poor growth, and faltering children may miss out on essential health interventions. The contribution of this paper is to provide a framework for pooling together multiple datasets, thus allowing us to overcome the issue of sparse data and provide improved estimates of growth. We use data from multiple longitudinal growth studies to construct a common correlation matrix that can be used in estimation and prediction of child growth. We propose a novel 2-stage approach: In stage 1, we construct a raw matrix via a set of univariate meta-analyses, and in stage 2, we smooth this raw matrix to obtain a more realistic correlation matrix. The methodology is illustrated using data from 16 child growth studies from the Bill and Melinda Gates Foundation's Healthy Birth Growth and Development knowledge integration project and identifies strong correlation for both height and weight between the ages of 4 and 12 years. We use a case study to provide an example of how this matrix can be used to help compute growth measures. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  17. Northern Chinese dental ages estimated from southern Chinese reference datasets closely correlate with chronological age

    Directory of Open Access Journals (Sweden)

    Hai Ming Wong

    2016-12-01

    Full Text Available While northern and southern Chinese are genetically correlated, there exists notable environmental differences in their living conditions. This study aimed to evaluate validity of the southern Chinese reference dataset for dental age estimation applied to northern Chinese. Dental panoramic tomographs of 437 northern Chinese aged 3 to 21 years were analysed. All the left maxillary and mandibular permanent teeth plus the 2 third molars on the right side were scored based on Demirjian’s classification of tooth development stages. Mean and standard error of dental age were obtained for each tooth development stage, followed by random effect meta-analysis for mean dental age estimation. Validity of the method was examined through measures of agreement (95% limits of agreement, standard error of measurement, and Lin’s concordance correlation coefficient and measure of reliability (Intraclass correlation coefficient. On average, the estimated dental age overestimated chronological age by only around 1 month in both females and males. The Intraclass correlation coefficient values were 0.99 for both sexes, suggesting excellent reliability of the method. Reference dataset for dental age estimation developed on the basis of southern Chinese was applicable for use among the northern Chinese.

  18. Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

    Directory of Open Access Journals (Sweden)

    Karacali Bilge

    2007-10-01

    Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

  19. The SAIL databank: linking multiple health and social care datasets.

    Science.gov (United States)

    Lyons, Ronan A; Jones, Kerina H; John, Gareth; Brooks, Caroline J; Verplancke, Jean-Philippe; Ford, David V; Brown, Ginevra; Leake, Ken

    2009-01-16

    Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage) databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF) to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage) was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR), to assess the efficacy of this process, and the optimum matching technique. The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL) at the 50% threshold, and error rates were SAIL databank represents a research-ready platform for record-linkage studies.

  20. Particle correlations in high-multiplicity reactions

    International Nuclear Information System (INIS)

    Hayot, Fernand.

    1976-01-01

    A comprehensive review of the results obtained in the study of short range correlations in high-multiplicity events is presented: introduction of the fundamental short-range order hypothesis, introduction of clusters in nondiffractive events (only the production of identical, independent, and neutral clusters was considered); search for short range dynamical effects between particles coming from the decay of a same cluster by studying two-particle rapidity correlations in inclusive and semi-inclusive experiments; study of transverse momentum correlations [fr

  1. A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

    Science.gov (United States)

    Zhai, Xuetong; Chakraborty, Dev P

    2017-06-01

    The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics

  2. An integrated pan-tropical biomass map using multiple reference datasets

    NARCIS (Netherlands)

    Avitabile, V.; Herold, M.; Heuvelink, G.B.M.; Lewis, S.L.; Phillips, O.L.; Asner, G.P.; Armston, J.; Asthon, P.; Banin, L.F.; Bayol, N.; Berry, N.; Boeckx, P.; Jong, De B.; Devries, B.; Girardin, C.; Kearsley, E.; Lindsell, J.A.; Lopez-gonzalez, G.; Lucas, R.; Malhi, Y.; Morel, A.; Mitchard, E.; Nagy, L.; Qie, L.; Quinones, M.; Ryan, C.M.; Slik, F.; Sunderland, T.; Vaglio Laurin, G.; Valentini, R.; Verbeeck, H.; Wijaya, A.; Willcock, S.

    2016-01-01

    We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of

  3. The SAIL databank: linking multiple health and social care datasets

    Directory of Open Access Journals (Sweden)

    Ford David V

    2009-01-01

    Full Text Available Abstract Background Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Methods Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR, to assess the efficacy of this process, and the optimum matching technique. Results The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL at the 50% threshold, and error rates were Conclusion With the infrastructure that has been put in place, the reliable matching process that has been developed enables an ALF to be consistently allocated to records in the databank. The SAIL databank represents a research-ready platform for record-linkage studies.

  4. Correlations in multiple production on nuclei and Glauber model of multiple scattering

    International Nuclear Information System (INIS)

    Zoller, V.R.; Nikolaev, N.N.

    1982-01-01

    Critical analysis of possibility for describing correlation phenomena during multiple production on nuclei within the framework of the Glauber multiple seattering model generalized for particle production processes with Capella, Krziwinski and Shabelsky has been performed. It was mainly concluded that the suggested generalization of the Glauber model gives dependences on Ng(Np) (where Ng-the number of ''grey'' tracess, and Np-the number of protons flying out of nucleus) and, eventually, on #betta# (where #betta#-the number of intranuclear interactions) contradicting experience. Independent of choice of relation between #betta# and Ng(Np) in the model the rapidity corrletor Rsub(eta) is overstated in the central region and understated in the region of nucleus fragmentation. In mean multiplicities these two contradictions of experience are disguised with random compensation and agreement with experience in Nsub(S) (function of Ng) cannot be an argument in favour of the model. It is concluded that eiconal model doesn't permit to quantitatively describe correlation phenomena during the multiple production on nuclei

  5. SRV: an open-source toolbox to accelerate the recovery of metabolic biomarkers and correlations from metabolic phenotyping datasets.

    Science.gov (United States)

    Navratil, Vincent; Pontoizeau, Clément; Billoir, Elise; Blaise, Benjamin J

    2013-05-15

    Supervised multivariate statistical analyses are often required to analyze the high-density spectral information in metabolic datasets acquired from complex mixtures in metabolic phenotyping studies. Here we present an implementation of the SRV-Statistical Recoupling of Variables-algorithm as an open-source Matlab and GNU Octave toolbox. SRV allows the identification of similarity between consecutive variables resulting from the high-resolution bucketing. Similar variables are gathered to restore the spectral dependency within the datasets and identify metabolic NMR signals. The correlation and significance of these new NMR variables for a given effect under study can then be measured and represented on a loading plot to allow a visual and efficient identification of candidate biomarkers. Further on, correlations between these candidate biomarkers can be visualized on a two-dimensional pseudospectrum, representing a correlation map, helping to understand the modifications of the underlying metabolic network. SRV toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) and in GNU Octave. It is available free of charge at http://www.prabi.fr/redmine/projects/srv/repository with a tutorial. benjamin.blaise@chu-lyon.fr or vincent.navratil@univ-lyon1.fr.

  6. Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Ma, Shuangge

    2012-01-01

    Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

  7. Effective capacity of multiple antenna channels: Correlation and keyhole

    KAUST Repository

    Zhong, Caijun

    2012-01-01

    In this study, the authors derive the effective capacity limits for multiple antenna channels which quantify the maximum achievable rate with consideration of link-layer delay-bound violation probability. Both correlated multiple-input single-output and multiple-input multiple-output keyhole channels are studied. Based on the closed-form exact expressions for the effective capacity of both channels, the authors look into the asymptotic high and low signal-to-noise ratio regimes, and derive simple expressions to gain more insights. The impact of spatial correlation on effective capacity is also characterised with the aid of a majorisation theory result. It is revealed that antenna correlation reduces the effective capacity of the channels and a stringent quality-of-service requirement causes a severe reduction in the effective capacity but can be alleviated by increasing the number of antennas. © 2012 The Institution of Engineering and Technology.

  8. Forward-backward multiplicity correlations and the clusterization

    International Nuclear Information System (INIS)

    Kostenko, B.F.; Musul'manbekov, Zh.Zh.

    1990-01-01

    An analysis of the forward-backward multiplicity correlations for pp- and p-barp-collisions has been fulfilled in the framework of the statistical cluster model. Connection between the strength of correlations and sizes of clusters is investigated. The dependence of masses and sizes of clusters on the energy of colliding hadrons is obtained. 15 refs.; 9 figs.; 1 tab

  9. An integrated pan-tropical biomass map using multiple reference datasets

    OpenAIRE

    Avitabile, V.; Herold, M.; Heuvelink, G. B. M.; Lewis, S. L.; Phillips, O. L.; Asner, G. P.; Armston, J.; Ashton, P. S.; Banin, L.; Bayol, N.; Berry, N. J.; Boeckx, P.; de Jong, B. H. J.; DeVries, B.; Girardin, C. A. J.

    2016-01-01

    We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging...

  10. On dealing with multiple correlation peaks in PIV

    Science.gov (United States)

    Masullo, A.; Theunissen, R.

    2018-05-01

    A novel algorithm to analyse PIV images in the presence of strong in-plane displacement gradients and reduce sub-grid filtering is proposed in this paper. Interrogation windows subjected to strong in-plane displacement gradients often produce correlation maps presenting multiple peaks. Standard multi-grid procedures discard such ambiguous correlation windows using a signal to noise (SNR) filter. The proposed algorithm improves the standard multi-grid algorithm allowing the detection of splintered peaks in a correlation map through an automatic threshold, producing multiple displacement vectors for each correlation area. Vector locations are chosen by translating images according to the peak displacements and by selecting the areas with the strongest match. The method is assessed on synthetic images of a boundary layer of varying intensity and a sinusoidal displacement field of changing wavelength. An experimental case of a flow exhibiting strong velocity gradients is also provided to show the improvements brought by this technique.

  11. Effective capacity of multiple antenna channels: Correlation and keyhole

    KAUST Repository

    Zhong, Caijun; Ratnarajah, Tharm; Wong, Kaikit; Alouini, Mohamed-Slim

    2012-01-01

    In this study, the authors derive the effective capacity limits for multiple antenna channels which quantify the maximum achievable rate with consideration of link-layer delay-bound violation probability. Both correlated multiple-input single

  12. Design of an audio advertisement dataset

    Science.gov (United States)

    Fu, Yutao; Liu, Jihong; Zhang, Qi; Geng, Yuting

    2015-12-01

    Since more and more advertisements swarm into radios, it is necessary to establish an audio advertising dataset which could be used to analyze and classify the advertisement. A method of how to establish a complete audio advertising dataset is presented in this paper. The dataset is divided into four different kinds of advertisements. Each advertisement's sample is given in *.wav file format, and annotated with a txt file which contains its file name, sampling frequency, channel number, broadcasting time and its class. The classifying rationality of the advertisements in this dataset is proved by clustering the different advertisements based on Principal Component Analysis (PCA). The experimental results show that this audio advertisement dataset offers a reliable set of samples for correlative audio advertisement experimental studies.

  13. Observation of spatial quantum correlations induced by multiple scattering of nonclassical light

    DEFF Research Database (Denmark)

    Smolka, Stephan; Huck, Alexander; Andersen, Ulrik Lund

    2009-01-01

    and negative spatial quantum correlations are observed when varying the quantum state incident to the multiple scattering medium, and the strength of the correlations is controlled by the number of photons. The experimental results are in excellent agreement with recent theoretical proposals by implementing......We present the experimental realization of spatial quantum correlations of photons that are induced by multiple scattering of squeezed light. The quantum correlation relates photons propagating along two different light paths through the random medium and is infinite in range. Both positive...... the full quantum model of multiple scattering....

  14. Combining results of multiple search engines in proteomics.

    Science.gov (United States)

    Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

    2013-09-01

    A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

  15. Combining Results of Multiple Search Engines in Proteomics*

    Science.gov (United States)

    Shteynberg, David; Nesvizhskii, Alexey I.; Moritz, Robert L.; Deutsch, Eric W.

    2013-01-01

    A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. PMID:23720762

  16. Improved nonparametric inference for multiple correlated periodic sequences

    KAUST Repository

    Sun, Ying

    2013-08-26

    This paper proposes a cross-validation method for estimating the period as well as the values of multiple correlated periodic sequences when data are observed at evenly spaced time points. The period of interest is estimated conditional on the other correlated sequences. An alternative method for period estimation based on Akaike\\'s information criterion is also discussed. The improvement of the period estimation performance is investigated both theoretically and by simulation. We apply the multivariate cross-validation method to the temperature data obtained from multiple ice cores, investigating the periodicity of the El Niño effect. Our methodology is also illustrated by estimating patients\\' cardiac cycle from different physiological signals, including arterial blood pressure, electrocardiography, and fingertip plethysmograph.

  17. Continuous-wave spatial quantum correlations of light induced by multiple scattering

    DEFF Research Database (Denmark)

    Smolka, Stephan; Ott, Johan Raunkjær; Huck, Alexander

    2012-01-01

    and reflectance. Utilizing frequency-resolved quantum noise measurements, we observe that the strength of the spatial quantum correlation function can be controlled by changing the quantum state of an incident bright squeezed-light source. Our results are found to be in excellent agreement with the developed......We present theoretical and experimental results on spatial quantum correlations induced by multiple scattering of nonclassical light. A continuous-mode quantum theory is derived that enables determining the spatial quantum correlation function from the fluctuations of the total transmittance...... theory and form a basis for future research on, e. g., quantum interference of multiple quantum states in a multiple scattering medium....

  18. An integrated pan-tropical biomass map using multiple reference datasets.

    Science.gov (United States)

    Avitabile, Valerio; Herold, Martin; Heuvelink, Gerard B M; Lewis, Simon L; Phillips, Oliver L; Asner, Gregory P; Armston, John; Ashton, Peter S; Banin, Lindsay; Bayol, Nicolas; Berry, Nicholas J; Boeckx, Pascal; de Jong, Bernardus H J; DeVries, Ben; Girardin, Cecile A J; Kearsley, Elizabeth; Lindsell, Jeremy A; Lopez-Gonzalez, Gabriela; Lucas, Richard; Malhi, Yadvinder; Morel, Alexandra; Mitchard, Edward T A; Nagy, Laszlo; Qie, Lan; Quinones, Marcela J; Ryan, Casey M; Ferry, Slik J W; Sunderland, Terry; Laurin, Gaia Vaglio; Gatti, Roberto Cazzolla; Valentini, Riccardo; Verbeeck, Hans; Wijaya, Arief; Willcock, Simon

    2016-04-01

    We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. © 2015 John Wiley & Sons Ltd.

  19. Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

    International Nuclear Information System (INIS)

    Zin, M H M; Ahmad, B

    2014-01-01

    The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest

  20. Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

    Science.gov (United States)

    Zin, M. H. M.; Ahmad, B.

    2014-02-01

    The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest.

  1. Multivendor Spectral-Domain Optical Coherence Tomography Dataset, Observer Annotation Performance Evaluation, and Standardized Evaluation Framework for Intraretinal Cystoid Fluid Segmentation

    Directory of Open Access Journals (Sweden)

    Jing Wu

    2016-01-01

    Full Text Available Development of image analysis and machine learning methods for segmentation of clinically significant pathology in retinal spectral-domain optical coherence tomography (SD-OCT, used in disease detection and prediction, is limited due to the availability of expertly annotated reference data. Retinal segmentation methods use datasets that either are not publicly available, come from only one device, or use different evaluation methodologies making them difficult to compare. Thus we present and evaluate a multiple expert annotated reference dataset for the problem of intraretinal cystoid fluid (IRF segmentation, a key indicator in exudative macular disease. In addition, a standardized framework for segmentation accuracy evaluation, applicable to other pathological structures, is presented. Integral to this work is the dataset used which must be fit for purpose for IRF segmentation algorithm training and testing. We describe here a multivendor dataset comprised of 30 scans. Each OCT scan for system training has been annotated by multiple graders using a proprietary system. Evaluation of the intergrader annotations shows a good correlation, thus making the reproducibly annotated scans suitable for the training and validation of image processing and machine learning based segmentation methods. The dataset will be made publicly available in the form of a segmentation Grand Challenge.

  2. Increasing occurrence of multiple sclerosis in women correlates to hygiene level

    Directory of Open Access Journals (Sweden)

    Wojciech Cendrowski

    2014-12-01

    Full Text Available Introduction: The increasing incidence of multiple sclerosis, particularly among women in Europe and North America, has a multifactorial aetiology. Method: The aim of the current study was to ascertain the relation between the hygiene level and occurrence of multiple sclerosis in women in Poland. The study was based on a large cohort of 14,200 multiple sclerosis individuals (male – 6,106, female – 8,094 who died in the years 1981–2010 in Poland. The female to male ratio (the F:M ratio in the multiple sclerosis group was calculated using the number of deaths per year. The rate of late mortality in infants (LMI per 1,000 live births yearly was used as a marker of the hygiene level. A correlation analysis was carried out between the rate of LMI and the F:M ratio in the multiple sclerosis cohort in the years 1981–2010. Demographic data were obtained from the Central Statistical Office in Warsaw. Results: The F:M ratio in the multiple sclerosis group evidently increased (range 1.08–1.79 in the years 1981–2010, showing increasing occurrence of multiple sclerosis in women (p < 0.0001. A significant, strong and inverse correlation was found between the marker of the hygiene level (LMI rate and the F:M ratio in the multiple sclerosis group over three decades: linear correlation coefficient by Pearson: r = –0.693, p < 0.0001. By contrast with this result, no correlation was established between the hygiene level marker and proportion of women to men in the general population on account of extremely low variance of the F:M ratio (0.000025. Conclusion: The improvement of the hygiene level showed association with the increasing occurrence of multiple sclerosis in women in the years 1981–2010. The higher the hygiene level was, the greater the occurrence of female multiple sclerosis in Poland.

  3. Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

    Science.gov (United States)

    Taylor, Sandra L; Ruhaak, L Renee; Weiss, Robert H; Kelly, Karen; Kim, Kyoungmi

    2017-01-01

    High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. Time-localized wavelet multiple regression and correlation

    Science.gov (United States)

    Fernández-Macho, Javier

    2018-02-01

    This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multiscale analysis of the comovements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial 'contagion'.

  5. Analysis of Naïve Bayes Algorithm for Email Spam Filtering across Multiple Datasets

    Science.gov (United States)

    Fitriah Rusland, Nurul; Wahid, Norfaradilla; Kasim, Shahreen; Hafit, Hanayanti

    2017-08-01

    E-mail spam continues to become a problem on the Internet. Spammed e-mail may contain many copies of the same message, commercial advertisement or other irrelevant posts like pornographic content. In previous research, different filtering techniques are used to detect these e-mails such as using Random Forest, Naïve Bayesian, Support Vector Machine (SVM) and Neutral Network. In this research, we test Naïve Bayes algorithm for e-mail spam filtering on two datasets and test its performance, i.e., Spam Data and SPAMBASE datasets [8]. The performance of the datasets is evaluated based on their accuracy, recall, precision and F-measure. Our research use WEKA tool for the evaluation of Naïve Bayes algorithm for e-mail spam filtering on both datasets. The result shows that the type of email and the number of instances of the dataset has an influence towards the performance of Naïve Bayes.

  6. Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

    Science.gov (United States)

    Wang, Huiqin; Wang, Xue; Cao, Minghua

    2017-02-01

    The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

  7. Multiplicity distribution and forward-backward correlations in the hydrodynamic theory of multiple production

    International Nuclear Information System (INIS)

    Tarasov, Yu.A.

    1992-01-01

    A hydrodynamic model for the collisions of gluon clusters is used to calculate the charge-particle multiplicity distributions in collisions of nucleons at ISR and collider energies. The separation temperature of the hydrodynamic system is calculated as a function of the rapidity [T k (γ 1 )] for each value of the inelasticity coefficient K. In the central region, this temperature is higher at collider energies than at the ISR energy. The average number of resonance clusters which decay into various (fixed) numbers of charged hadrons is found for each value of K. The number of these clusters fluctuates in accordance with a Poisson distribution. A hadron multiplicity distribution which incorporates these fluctuations is found. This distribution is averaged over the inelasticity coefficient. The distributions p(n ch ) and the KNO functions Ψ(z) are calculated for the overall and central regions of the rapidity, |y| ≤ 1.5. The broadening of the distributions and the violation of KNO scaling at collider energies results from increased contributions from the decays of resonances. The front-back multiplicity correlations are also studied; the decay of resonances is taken into account. The distributions and slope coefficients of the correlation function which are found for the various energies agree with experimental data

  8. Rapidity and multiplicity correlations in high energy hadronic collisions

    International Nuclear Information System (INIS)

    Heiselberg, H.

    1993-01-01

    Rapidity and multiplicity correlations of particle production in high energy hadronic collisions are studied. A simple model including short range correlations in rapidity due to clustering and long range correlations due to energy conservation is able to describe the two-body correlation functions well hadron-nucleon collisions around lab energies of 250 GeV. In this model fractional moments are calculated and compared to data. The strong rise of the factorial moments in rapidity intervals by size δy∝1 can be explained by long and short range correlation alone whereas the factorial moments approach a constant value at very small δy due to lack of correlations also in agreement with experiment. There is therefore no need for introducing intermittency in the particle production in hadronic collisions at these energies. (orig.)

  9. SAR image dataset of military ground targets with multiple poses for ATR

    Science.gov (United States)

    Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc

    2017-10-01

    Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.

  10. Quantum correlations induced by multiple scattering of quadrature squeezed light

    DEFF Research Database (Denmark)

    Lodahl, Peter

    2006-01-01

    Propagating quadrature squeezed light through a multiple scattering random medium is found to induce pronounced spatial quantum correlations that have no classical analogue. The correlations are revealed in the number of photons transported through the sample that can be measured from the intensity...... fluctuations of the total transmission or reflection. In contrast, no pronounced spatial quantum correlations appear in the quadrature amplitudes where excess noise above the shot noise level is found....

  11. A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

    Science.gov (United States)

    Forkan, Abdur Rahim Mohammad; Khalil, Ibrahim

    2017-02-01

    In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly correlated. They are also patient-centric and can be either recurrent or can fluctuate. The objective of this study is to develop an intelligent method for personalized monitoring and clinical decision support through early estimation of patient-specific vital sign values, and prediction of anomalies using the interrelation among multiple vital signs. In this paper, multi-label classification algorithms are applied in classifier design to forecast these values and related abnormalities. We proposed a completely new approach of patient-specific vital sign prediction system using their correlations. The developed technique can guide healthcare professionals to make accurate clinical decisions. Moreover, our model can support many patients with various clinical conditions concurrently by utilizing the power of cloud computing technology. The developed method also reduces the rate of false predictions in remote monitoring centres. In the experimental settings, the statistical features and correlations of six vital signs are formulated as multi-label classification problem. Eight multi-label classification algorithms along with three fundamental machine learning algorithms are used and tested on a public dataset of 85 patients. Different multi-label classification evaluation measures such as Hamming score, F1-micro average, and accuracy are used for interpreting the prediction performance of patient-specific situation classifications. We achieved 90-95% Hamming score values across 24 classifier combinations for 85 different patients used in our experiment. The results are compared with single-label classifiers and without considering the correlations among the vitals. The comparisons show that multi-label method is the best technique for this problem

  12. Dataset associated with the paper Nanoscale correlation of iron biochemistry with amyloid plaque morphology in Alzheimer’s disease transgenic mouse cortex" to be published in "Cell Chemical Biology"

    OpenAIRE

    Telling, ND; Everett, J; Collingwood, JF; Dobson, J; van der Laan, G; Gallagher, JJ; Wang, J; Hitchcock, AP

    2017-01-01

    This dataset is composed of images used to construct figures in the paper, as well as text files containing the spectral data plotted in these figures. In addition, images and plots showing the cross-correlation data used to determine the correlation co-efficients are included.

  13. Nature of multiplicity correlations in 12C-nucleus reaction at 4.5 AGeV

    International Nuclear Information System (INIS)

    Saleem Khan, M.; Shukla, Praveen Prakash; Khushnood, H.

    2011-01-01

    Multiplicity correlations in high energy hadron-nucleus and nucleus-nucleus interactions are considered one of the most important parameter to study the dynamics of particles production. In the present work, an attempt has been made to understand the nature of the multiplicity correlations

  14. Soil chemistry in lithologically diverse datasets: the quartz dilution effect

    Science.gov (United States)

    Bern, Carleton R.

    2009-01-01

    National- and continental-scale soil geochemical datasets are likely to move our understanding of broad soil geochemistry patterns forward significantly. Patterns of chemistry and mineralogy delineated from these datasets are strongly influenced by the composition of the soil parent material, which itself is largely a function of lithology and particle size sorting. Such controls present a challenge by obscuring subtler patterns arising from subsequent pedogenic processes. Here the effect of quartz concentration is examined in moist-climate soils from a pilot dataset of the North American Soil Geochemical Landscapes Project. Due to variable and high quartz contents (6.2–81.7 wt.%), and its residual and inert nature in soil, quartz is demonstrated to influence broad patterns in soil chemistry. A dilution effect is observed whereby concentrations of various elements are significantly and strongly negatively correlated with quartz. Quartz content drives artificial positive correlations between concentrations of some elements and obscures negative correlations between others. Unadjusted soil data show the highly mobile base cations Ca, Mg, and Na to be often strongly positively correlated with intermediately mobile Al or Fe, and generally uncorrelated with the relatively immobile high-field-strength elements (HFS) Ti and Nb. Both patterns are contrary to broad expectations for soils being weathered and leached. After transforming bulk soil chemistry to a quartz-free basis, the base cations are generally uncorrelated with Al and Fe, and negative correlations generally emerge with the HFS elements. Quartz-free element data may be a useful tool for elucidating patterns of weathering or parent-material chemistry in large soil datasets.

  15. The Correlation of Multiple Intelligences for the Achievements of Secondary Students

    Science.gov (United States)

    Ahvan, Yaghoob Raissi; Pour, Hossein Zainali

    2016-01-01

    The present study attempts to investigate the relationship between the multiple intelligences and the academic performance achievement levels of high school students based on Gardner's multiple intelligences theory. This was a descriptive correlation study. To accomplish this purpose, 270 students of high school of Bandar Abbas selected by…

  16. Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

    Science.gov (United States)

    Rios Velazquez, Emmanuel; Meier, Raphael; Dunn, William D; Alexander, Brian; Wiest, Roland; Bauer, Stefan; Gutman, David A; Reyes, Mauricio; Aerts, Hugo J W L

    2015-11-18

    Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

  17. Charged multiplicity distributions and correlations in e+e- annihilation at PETRA energies

    International Nuclear Information System (INIS)

    Braunschweig, W.; Gerhards, R.; Kirschfink, F.J.; Martyn, H.U.; Kolanoski, H.; Bowler, M.G.; Burrows, P.N.; Veitch, M.E.; Brandt, S.; Holder, M.; Caldwell, A.; Muller, D.; Ritz, S.; Strom, D.; Takashima, M.; Wu Saulan; Zobernig, G.

    1989-01-01

    We report on an analysis of the multiplicity distributions of charged particles produced in e + e - annihilation into hadrons at c.m. energies between 14 and 46.8 GeV. The charged multiplicity distributions of the whole event and single hemisphere deviate significantly from the Poisson distribution but follow approximate KNO scaling. We have also studied the multiplicity distributions in various rapidity intervals and found that they can be well described by the negative binomial distribution only for small central intervals. We have also analysed forward-backward multiplicity correlations for different energies and selections of particle charge and shown that they can be understood in terms of the fragmentation properties of the different quark flavours and by the production and decay of resonances. These correlations are well reproduced by the Lund string model. (orig.)

  18. ATLAS File and Dataset Metadata Collection and Use

    CERN Document Server

    Albrand, S; The ATLAS collaboration; Lambert, F; Gallas, E J

    2012-01-01

    The ATLAS Metadata Interface (“AMI”) was designed as a generic cataloguing system, and as such it has found many uses in the experiment including software release management, tracking of reconstructed event sizes and control of dataset nomenclature. The primary use of AMI is to provide a catalogue of datasets (file collections) which is searchable using physics criteria. In this paper we discuss the various mechanisms used for filling the AMI dataset and file catalogues. By correlating information from different sources we can derive aggregate information which is important for physics analysis; for example the total number of events contained in dataset, and possible reasons for missing events such as a lost file. Finally we will describe some specialized interfaces which were developed for the Data Preparation and reprocessing coordinators. These interfaces manipulate information from both the dataset domain held in AMI, and the run-indexed information held in the ATLAS COMA application (Conditions and ...

  19. VideoWeb Dataset for Multi-camera Activities and Non-verbal Communication

    Science.gov (United States)

    Denina, Giovanni; Bhanu, Bir; Nguyen, Hoang Thanh; Ding, Chong; Kamal, Ahmed; Ravishankar, Chinya; Roy-Chowdhury, Amit; Ivers, Allen; Varda, Brenda

    Human-activity recognition is one of the most challenging problems in computer vision. Researchers from around the world have tried to solve this problem and have come a long way in recognizing simple motions and atomic activities. As the computer vision community heads toward fully recognizing human activities, a challenging and labeled dataset is needed. To respond to that need, we collected a dataset of realistic scenarios in a multi-camera network environment (VideoWeb) involving multiple persons performing dozens of different repetitive and non-repetitive activities. This chapter describes the details of the dataset. We believe that this VideoWeb Activities dataset is unique and it is one of the most challenging datasets available today. The dataset is publicly available online at http://vwdata.ee.ucr.edu/ along with the data annotation.

  20. Rapidity correlations at fixed multiplicity in cluster emission models

    CERN Document Server

    Berger, M C

    1975-01-01

    Rapidity correlations in the central region among hadrons produced in proton-proton collisions of fixed final state multiplicity n at NAL and ISR energies are investigated in a two-step framework in which clusters of hadrons are emitted essentially independently, via a multiperipheral-like model, and decay isotropically. For n>or approximately=/sup 1///sub 2/(n), these semi-inclusive distributions are controlled by the reaction mechanism which dominates production in the central region. Thus, data offer cleaner insight into the properties of this mechanism than can be obtained from fully inclusive spectra. A method of experimental analysis is suggested to facilitate the extraction of new dynamical information. It is shown that the n independence of the magnitude of semi-inclusive correlation functions reflects directly the structure of the internal cluster multiplicity distribution. This conclusion is independent of certain assumptions concerning the form of the single cluster density in rapidity space. (23 r...

  1. Correlation between transverse momentum and multiplicity of C-jets

    International Nuclear Information System (INIS)

    Shibuya, E.H.

    1989-01-01

    Studies on hadronic interactions at high energies done by Brazil-Japan Cooperation of cosmic rays are presented. The chamber of photo emulsions-lead used as detector is described. The correlation between transverse momentum and multiplicity is obtained and compared with results obtained from particle accelerators. (M.C.K.)

  2. Overcoming multicollinearity in multiple regression using correlation coefficient

    Science.gov (United States)

    Zainodin, H. J.; Yap, S. J.

    2013-09-01

    Multicollinearity happens when there are high correlations among independent variables. In this case, it would be difficult to distinguish between the contributions of these independent variables to that of the dependent variable as they may compete to explain much of the similar variance. Besides, the problem of multicollinearity also violates the assumption of multiple regression: that there is no collinearity among the possible independent variables. Thus, an alternative approach is introduced in overcoming the multicollinearity problem in achieving a well represented model eventually. This approach is accomplished by removing the multicollinearity source variables on the basis of the correlation coefficient values based on full correlation matrix. Using the full correlation matrix can facilitate the implementation of Excel function in removing the multicollinearity source variables. It is found that this procedure is easier and time-saving especially when dealing with greater number of independent variables in a model and a large number of all possible models. Hence, in this paper detailed insight of the procedure is shown, compared and implemented.

  3. Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

    Directory of Open Access Journals (Sweden)

    Nilotpal Chowdhury

    Full Text Available Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis.The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets.Four microarray series (having 742 patients were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA.Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed.To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and

  4. Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

    Science.gov (United States)

    Chowdhury, Nilotpal; Sapru, Shantanu

    2015-01-01

    Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting

  5. Forward-backward multiplicity correlations in sNN=200 GeV Au+Au collisions

    Science.gov (United States)

    Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Budzanowski, A.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; Gburek, T.; George, N.; Gulbrandsen, K.; Gushue, S.; Halliwell, C.; Hamblen, J.; Hauer, M.; Heintzelman, G. A.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Hołyński, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Katzy, J.; Khan, N.; Kucewicz, W.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; McLeod, D.; Mignerey, A. C.; Noucier, R.; Olszewski, A.; Pak, R.; Park, I. C.; Pernegger, H.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Rosenberg, L.; Sagerer, J.; Sarin, P.; Sawicki, P.; Seals, H.; Sedykh, I.; Skulski, W.; Smith, C. E.; Stankiewicz, M. A.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tang, J.-L.; Tonjes, M. B.; Trzupek, A.; Vale, C.; Nieuwenhuizen, G. J. Van; Vaurynovich, S. S.; Verdier, R.; Veres, G. I.; Wenger, E.; Wolfs, F. L. H.; Wosiek, B.; Woźniak, K.; Wuosmaa, A. H.; Wysłouch, B.

    2006-07-01

    Forward-backward correlations of charged-particle multiplicities in symmetric bins in pseudorapidity are studied to gain insight into the underlying correlation structure of particle production in Au+Au collisions. The PHOBOS detector is used to measure integrated multiplicities in bins centered at η, defined within |η|<3, and covering intervals Δη. The variance σC2 of a suitably defined forward-backward asymmetry variable C is calculated as a function of η,Δη, and centrality. It is found to be sensitive to short-range correlations, and the concept of “clustering” is used to interpret comparisons to phenomenological models.

  6. Two-particle correlations from droplet formation in high multiplicity anti pp events

    International Nuclear Information System (INIS)

    Ruuskanen, P.V.; Seibert, D.

    1988-01-01

    We study the correlations that arise from the formation of plasma droplets in high multiplicity events observed in recent FNAL anti pp collisions at √s=1.8 TeV. We show how the correlation between the final particles depends on the droplet size and density and on correlations between the droplets. We find that the two-particle correlation function R 2 could provide a clear signal for the formation of droplets. (orig.)

  7. Spatio-Temporal Data Model for Integrating Evolving Nation-Level Datasets

    Science.gov (United States)

    Sorokine, A.; Stewart, R. N.

    2017-10-01

    Ability to easily combine the data from diverse sources in a single analytical workflow is one of the greatest promises of the Big Data technologies. However, such integration is often challenging as datasets originate from different vendors, governments, and research communities that results in multiple incompatibilities including data representations, formats, and semantics. Semantics differences are hardest to handle: different communities often use different attribute definitions and associate the records with different sets of evolving geographic entities. Analysis of global socioeconomic variables across multiple datasets over prolonged time is often complicated by the difference in how boundaries and histories of countries or other geographic entities are represented. Here we propose an event-based data model for depicting and tracking histories of evolving geographic units (countries, provinces, etc.) and their representations in disparate data. The model addresses the semantic challenge of preserving identity of geographic entities over time by defining criteria for the entity existence, a set of events that may affect its existence, and rules for mapping between different representations (datasets). Proposed model is used for maintaining an evolving compound database of global socioeconomic and environmental data harvested from multiple sources. Practical implementation of our model is demonstrated using PostgreSQL object-relational database with the use of temporal, geospatial, and NoSQL database extensions.

  8. Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.

    Science.gov (United States)

    Kohli, Marc D; Summers, Ronald M; Geis, J Raymond

    2017-08-01

    At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues. The common theme from attendees was that everyone participating in medical image evaluation with machine learning is data starved. There is an urgent need to find better ways to collect, annotate, and reuse medical imaging data. Unique domain issues with medical image datasets require further study, development, and dissemination of best practices and standards, and a coordinated effort among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial, academic, and government entities. High-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products should be better described. NIH and other government agencies should promote and, where applicable, enforce, access to medical image datasets. We should improve communication among medical imaging domain experts, medical imaging informaticists, academic clinical and basic science researchers, government and industry data scientists, and interested commercial entities.

  9. Observed climate variability over Chad using multiple observational and reanalysis datasets

    Science.gov (United States)

    Maharana, Pyarimohan; Abdel-Lathif, Ahmat Younous; Pattnayak, Kanhu Charan

    2018-03-01

    Chad is the largest of Africa's landlocked countries and one of the least studied region of the African continent. The major portion of Chad lies in the Sahel region, which is known for its rapid climate change. In this study, multiple observational datasets are analyzed from 1950 to 2014, in order to examine the trend of precipitation and temperature along with their variability over Chad to understand possible impacts of climate change over this region. Trend analysis of the climatic fields has been carried out using Mann-Kendall test. The precipitation over Chad is mostly contributed during summer by West African Monsoon, with maximum northward limit of 18° N. The Atlantic Ocean as well as the Mediterranean Sea are the major source of moisture for the summer rainfall over Chad. Based on the rainfall time series, the entire study period has been divided in to wet (1950 to 1965), dry (1966 to 1990) and recovery period (1991 to 2014). The rainfall has decreased drastically for almost 3 decades during the dry period resulted into various drought years. The temperature increases at a rate of 0.15 °C/decade during the entire period of analysis. The seasonal rainfall as well as temperature plays a major role in the change of land use/cover. The decrease of monsoon rainfall during the dry period reduces the C4 cover drastically; this reduction of C4 grass cover leads to increase of C3 grass cover. The slow revival of rainfall is still not good enough for the increase of shrub cover but it favors the gradual reduction of bare land over Chad.

  10. Social Cognitive Correlates of Physical Activity in Inactive Adults with Multiple Sclerosis

    Science.gov (United States)

    Dlugonski, Deirdre; Wojcicki, Thomas R.; McAuley, Edward; Motl, Robert W.

    2011-01-01

    Persons with multiple sclerosis (MS) are often physically inactive. This observation has prompted the search for modifiable constructs derived from established theories that act as correlates of physical activity. This study investigated self efficacy, outcome expectations, impediments, and goal setting as correlates of physical activity in…

  11. Power-law Exponent in Multiplicative Langevin Equation with Temporally Correlated Noise

    Science.gov (United States)

    Morita, Satoru

    2018-05-01

    Power-law distributions are ubiquitous in nature. Random multiplicative processes are a basic model for the generation of power-law distributions. For discrete-time systems, the power-law exponent is known to decrease as the autocorrelation time of the multiplier increases. However, for continuous-time systems, it is not yet clear how the temporal correlation affects the power-law behavior. Herein, we analytically investigated a multiplicative Langevin equation with colored noise. We show that the power-law exponent depends on the details of the multiplicative noise, in contrast to the case of discrete-time systems.

  12. Neural correlates of alerting and orienting impairment in multiple sclerosis patients.

    Directory of Open Access Journals (Sweden)

    Manuel Vázquez-Marrufo

    Full Text Available BACKGROUND: A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. RESULTS: After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05. ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05 and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01. With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01 and an ERP parameter (CNV amplitude. CONCLUSIONS: Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention

  13. Viking Seismometer PDS Archive Dataset

    Science.gov (United States)

    Lorenz, R. D.

    2016-12-01

    The Viking Lander 2 seismometer operated successfully for over 500 Sols on the Martian surface, recording at least one likely candidate Marsquake. The Viking mission, in an era when data handling hardware (both on board and on the ground) was limited in capability, predated modern planetary data archiving, and ad-hoc repositories of the data, and the very low-level record at NSSDC, were neither convenient to process nor well-known. In an effort supported by the NASA Mars Data Analysis Program, we have converted the bulk of the Viking dataset (namely the 49,000 and 270,000 records made in High- and Event- modes at 20 and 1 Hz respectively) into a simple ASCII table format. Additionally, since wind-generated lander motion is a major component of the signal, contemporaneous meteorological data are included in summary records to facilitate correlation. These datasets are being archived at the PDS Geosciences Node. In addition to brief instrument and dataset descriptions, the archive includes code snippets in the freely-available language 'R' to demonstrate plotting and analysis. Further, we present examples of lander-generated noise, associated with the sampler arm, instrument dumps and other mechanical operations.

  14. A Research Graph dataset for connecting research data repositories using RD-Switchboard.

    Science.gov (United States)

    Aryani, Amir; Poblet, Marta; Unsworth, Kathryn; Wang, Jingbo; Evans, Ben; Devaraju, Anusuriya; Hausstein, Brigitte; Klas, Claus-Peter; Zapilko, Benjamin; Kaplun, Samuele

    2018-05-29

    This paper describes the open access graph dataset that shows the connections between Dryad, CERN, ANDS and other international data repositories to publications and grants across multiple research data infrastructures. The graph dataset was created using the Research Graph data model and the Research Data Switchboard (RD-Switchboard), a collaborative project by the Research Data Alliance DDRI Working Group (DDRI WG) with the aim to discover and connect the related research datasets based on publication co-authorship or jointly funded grants. The graph dataset allows researchers to trace and follow the paths to understanding a body of work. By mapping the links between research datasets and related resources, the graph dataset improves both their discovery and visibility, while avoiding duplicate efforts in data creation. Ultimately, the linked datasets may spur novel ideas, facilitate reproducibility and re-use in new applications, stimulate combinatorial creativity, and foster collaborations across institutions.

  15. Theoretical investigations of quantum correlations in NMR multiple-pulse spin-locking experiments

    Science.gov (United States)

    Gerasev, S. A.; Fedorova, A. V.; Fel'dman, E. B.; Kuznetsova, E. I.

    2018-04-01

    Quantum correlations are investigated theoretically in a two-spin system with the dipole-dipole interactions in the NMR multiple-pulse spin-locking experiments. We consider two schemes of the multiple-pulse spin-locking. The first scheme consists of π /2-pulses only and the delays between the pulses can differ. The second scheme contains φ-pulses (0Quantum discord is obtained for the first scheme of the multiple-pulse spin-locking experiment at different temperatures.

  16. Multiplicity correlations of intermediate-mass fragments with pions and fast protons in 12C + 197AU

    International Nuclear Information System (INIS)

    Turzo, K.; Begemann-Blaich, M.L.; Auger, G.

    2003-12-01

    Low-energy π + (E π 12 C+ 197 Au collisions at incident energies from 300 to 1800 MeV per nucleon were detected with the Si-Si(Li)-CsI(Tl) calibration telescopes of the INDRA multidetector. The inclusive angular distributions are approximately isotropic, consistent with multiple rescattering in the target spectator. The multiplicity correlations of the low-energy pions and of energetic protons (E p >or ≤ 150 MeV) with intermediate-mass fragments were determined from the measured coincidence data. The deduced correlation functions 1 + R ∼ 1.3 for inclusive event samples reflect the strong correlations evident from the common impact-parameter dependence of the considered multiplicities. For narrow impact-parameter bins (based on charged-particle multiplicity), the correlation functions are close to unity and do not indicate strong additional correlations. Only for pions at high particle multiplicities (central collisions) a weak anticorrelation is observed, probably due to a limited competition between these emissions. Overall, the results are consistent with the equilibrium assumption made in statistical multifragmentation scenarios. Predictions obtained with intranuclear cascade models coupled to the statistical multifragmentation model are in good agreement with the experimental data. (orig.)

  17. Interactive visualization and analysis of multimodal datasets for surgical applications.

    Science.gov (United States)

    Kirmizibayrak, Can; Yim, Yeny; Wakid, Mike; Hahn, James

    2012-12-01

    Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this paper, we present a visualization approach that displays the information from various sources in a single coherent view. The system allows the user to explore and manipulate volumetric datasets, display analysis of dataset values in local regions, combine 2D and 3D imaging modalities and display results of vector-based computer simulations. Several interaction methods are discussed: in addition to traditional interfaces including mouse and trackers, gesture-based natural interaction methods are shown to control these visualizations with real-time performance. An example of a medical application (medialization laryngoplasty) is presented to demonstrate how the combination of different modalities can be used in a surgical setting with our approach.

  18. SPICE: exploration and analysis of post-cytometric complex multivariate datasets.

    Science.gov (United States)

    Roederer, Mario; Nozzi, Joshua L; Nason, Martha C

    2011-02-01

    Polychromatic flow cytometry results in complex, multivariate datasets. To date, tools for the aggregate analysis of these datasets across multiple specimens grouped by different categorical variables, such as demographic information, have not been optimized. Often, the exploration of such datasets is accomplished by visualization of patterns with pie charts or bar charts, without easy access to statistical comparisons of measurements that comprise multiple components. Here we report on algorithms and a graphical interface we developed for these purposes. In particular, we discuss thresholding necessary for accurate representation of data in pie charts, the implications for display and comparison of normalized versus unnormalized data, and the effects of averaging when samples with significant background noise are present. Finally, we define a statistic for the nonparametric comparison of complex distributions to test for difference between groups of samples based on multi-component measurements. While originally developed to support the analysis of T cell functional profiles, these techniques are amenable to a broad range of datatypes. Published 2011 Wiley-Liss, Inc.

  19. Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias.

    Directory of Open Access Journals (Sweden)

    Thomas Pfeiffer

    2011-03-01

    Full Text Available Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63% relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%. Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%. Such dynamic patterns in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust

  20. Exploring massive, genome scale datasets with the genometricorr package

    KAUST Repository

    Favorov, Alexander; Mularoni, Loris; Cope, Leslie M.; Medvedeva, Yulia; Mironov, Andrey A.; Makeev, Vsevolod J.; Wheelan, Sarah J.

    2012-01-01

    We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.

  1. Exploring massive, genome scale datasets with the genometricorr package

    KAUST Repository

    Favorov, Alexander

    2012-05-31

    We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.

  2. Long-term dataset on aquatic responses to concurrent climate change and recovery from acidification

    Science.gov (United States)

    Leach, Taylor H.; Winslow, Luke A.; Acker, Frank W.; Bloomfield, Jay A.; Boylen, Charles W.; Bukaveckas, Paul A.; Charles, Donald F.; Daniels, Robert A.; Driscoll, Charles T.; Eichler, Lawrence W.; Farrell, Jeremy L.; Funk, Clara S.; Goodrich, Christine A.; Michelena, Toby M.; Nierzwicki-Bauer, Sandra A.; Roy, Karen M.; Shaw, William H.; Sutherland, James W.; Swinton, Mark W.; Winkler, David A.; Rose, Kevin C.

    2018-04-01

    Concurrent regional and global environmental changes are affecting freshwater ecosystems. Decadal-scale data on lake ecosystems that can describe processes affected by these changes are important as multiple stressors often interact to alter the trajectory of key ecological phenomena in complex ways. Due to the practical challenges associated with long-term data collections, the majority of existing long-term data sets focus on only a small number of lakes or few response variables. Here we present physical, chemical, and biological data from 28 lakes in the Adirondack Mountains of northern New York State. These data span the period from 1994-2012 and harmonize multiple open and as-yet unpublished data sources. The dataset creation is reproducible and transparent; R code and all original files used to create the dataset are provided in an appendix. This dataset will be useful for examining ecological change in lakes undergoing multiple stressors.

  3. The Wind Integration National Dataset (WIND) toolkit (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Caroline Draxl: NREL

    2014-01-01

    Regional wind integration studies require detailed wind power output data at many locations to perform simulations of how the power system will operate under high penetration scenarios. The wind datasets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as being time synchronized with available load profiles.As described in this presentation, the WIND Toolkit fulfills these requirements by providing a state-of-the-art national (US) wind resource, power production and forecast dataset.

  4. Exploring massive, genome scale datasets with the GenometriCorr package.

    Directory of Open Access Journals (Sweden)

    Alexander Favorov

    2012-05-01

    Full Text Available We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features, for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets.The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor.

  5. Multiple-scattering formalism for correlated systems: A KKR-DMFT approach

    International Nuclear Information System (INIS)

    Minar, J.; Perlov, A.; Ebert, H.; Chioncel, L.; Katsnelson, M. I.; Lichtenstein, A.I.

    2005-01-01

    We present a charge and self-energy self-consistent computational scheme for correlated systems based on the Korringa-Kohn-Rostoker (KKR) multiple scattering theory with the many-body effects described by the means of dynamical mean field theory (DMFT). The corresponding local multiorbital and energy dependent self-energy is included into the set of radial differential equations for the single-site wave functions. The KKR Green's function is written in terms of the multiple scattering path operator, the later one being evaluated using the single-site solution for the t-matrix that in turn is determined by the wave functions. An appealing feature of this approach is that it allows to consider local quantum and disorder fluctuations on the same footing. Within the coherent potential approximation (CPA) the correlated atoms are placed into a combined effective medium determined by the DMFT self-consistency condition. Results of corresponding calculations for pure Fe, Ni, and Fe x Ni 1-x alloys are presented

  6. SPATIO-TEMPORAL DATA MODEL FOR INTEGRATING EVOLVING NATION-LEVEL DATASETS

    Directory of Open Access Journals (Sweden)

    A. Sorokine

    2017-10-01

    Full Text Available Ability to easily combine the data from diverse sources in a single analytical workflow is one of the greatest promises of the Big Data technologies. However, such integration is often challenging as datasets originate from different vendors, governments, and research communities that results in multiple incompatibilities including data representations, formats, and semantics. Semantics differences are hardest to handle: different communities often use different attribute definitions and associate the records with different sets of evolving geographic entities. Analysis of global socioeconomic variables across multiple datasets over prolonged time is often complicated by the difference in how boundaries and histories of countries or other geographic entities are represented. Here we propose an event-based data model for depicting and tracking histories of evolving geographic units (countries, provinces, etc. and their representations in disparate data. The model addresses the semantic challenge of preserving identity of geographic entities over time by defining criteria for the entity existence, a set of events that may affect its existence, and rules for mapping between different representations (datasets. Proposed model is used for maintaining an evolving compound database of global socioeconomic and environmental data harvested from multiple sources. Practical implementation of our model is demonstrated using PostgreSQL object-relational database with the use of temporal, geospatial, and NoSQL database extensions.

  7. Sparse canonical correlation analysis: new formulation and algorithm.

    Science.gov (United States)

    Chu, Delin; Liao, Li-Zhi; Ng, Michael K; Zhang, Xiaowei

    2013-12-01

    In this paper, we study canonical correlation analysis (CCA), which is a powerful tool in multivariate data analysis for finding the correlation between two sets of multidimensional variables. The main contributions of the paper are: 1) to reveal the equivalent relationship between a recursive formula and a trace formula for the multiple CCA problem, 2) to obtain the explicit characterization for all solutions of the multiple CCA problem even when the corresponding covariance matrices are singular, 3) to develop a new sparse CCA algorithm, and 4) to establish the equivalent relationship between the uncorrelated linear discriminant analysis and the CCA problem. We test several simulated and real-world datasets in gene classification and cross-language document retrieval to demonstrate the effectiveness of the proposed algorithm. The performance of the proposed method is competitive with the state-of-the-art sparse CCA algorithms.

  8. Secret-key agreement over spatially correlated fast-fading multiple-antenna channels with public discussion

    KAUST Repository

    Zorgui, Marwen

    2015-06-14

    We consider secret-key agreement with public discussion over multiple-input multiple-output (MIMO) Rayleigh fast-fading channels under correlated environment. We assume that transmit, legitimate receiver and eavesdropper antennas are correlated. The legitimate receiver and the eavesdropper are assumed to have perfect channel knowledge while the transmitter has only knowledge of the correlation matrices. First, we derive the expression of the secret-key capacity under the considered setup. Then, we prove that the optimal transmit strategy achieving the secret-key capacity consists in transmitting independent Gaussian signals along the eingenvectors of the transmit correlation matrix. The powers allocated to each channel mode are determined as the solution to a numerical optimization problem that we derive. A necessary and sufficient condition for beamforming (i.e., transmitting along the strongest channel mode) to be capacity-achieving is derived. Finally, we analyze the impact of correlation matrices on the system performance and provide closed-form expressions of the gain/loss due to correlation in the high power regime.

  9. Multiplicity fluctuations and correlations in limited momentum space bins in relativistic gases

    International Nuclear Information System (INIS)

    Hauer, Michael; Torrieri, Giorgio; Wheaton, Spencer

    2009-01-01

    Multiplicity fluctuations and correlations are calculated within thermalized relativistic ideal quantum gases. These are shown to be sensitive to the choice of statistical ensemble as well as to the choice of acceptance window in momentum space. It is furthermore shown that global conservation laws introduce nontrivial correlations between disconnected regions in momentum space, even in the absence of any dynamics.

  10. A robust post-processing workflow for datasets with motion artifacts in diffusion kurtosis imaging.

    Science.gov (United States)

    Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X; Wan, Mingxi

    2014-01-01

    The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (pworkflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (pworkflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.

  11. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Yu-Wei [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Simmons, Blake A. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Singer, Steven W. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-10-29

    The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here, we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments. Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Supplementary information: Supplementary data are available at Bioinformatics online.

  12. Correlation functions with fusion-channel multiplicity in W3 Toda field theory

    International Nuclear Information System (INIS)

    Belavin, Vladimir; Estienne, Benoit; Foda, Omar; Santachiara, Raoul

    2016-01-01

    Current studies of W N Toda field theory focus on correlation functions such that the W N highest-weight representations in the fusion channels are multiplicity-free. In this work, we study W 3 Toda 4-point functions with multiplicity in the fusion channel. The conformal blocks of these 4-point functions involve matrix elements of a fully-degenerate primary field with a highest-weight in the adjoint representation of sl 3 , and a fully-degenerate primary field with a highest-weight in the fundamental representation of sl 3 . We show that, when the fusion rules do not involve multiplicities, the matrix elements of the fully-degenerate adjoint field, between two arbitrary descendant states, can be computed explicitly, on equal footing with the matrix elements of the semi-degenerate fundamental field. Using null-state conditions, we obtain a fourth-order Fuchsian differential equation for the conformal blocks. Using Okubo theory, we show that, due to the presence of multiplicities, this differential equation belongs to a class of Fuchsian equations that is different from those that have appeared so far in W N theories. We solve this equation, compute its monodromy group, and construct the monodromy-invariant correlation functions. This computation shows in detail how the ambiguities that are caused by the presence of multiplicities are fixed by requiring monodromy-invariance.

  13. Multiplicity dependence of 2-particle correlations in proton-proton collisions measured with ALICE at the LHC

    International Nuclear Information System (INIS)

    Sicking, E.

    2014-01-01

    We investigate properties of jets in proton-proton collisions using 2-particle angular correlations. By choosing an analysis approach based on 2-particle angular correlations, also the properties of low-energetic jets can be accessed. Observing the strength of the correlation as a function of the charged particle multiplicity reveals jet fragmentation properties as well as the contribution of jets to the overall charged particle multiplicity. Furthermore, the analysis discloses information on the underlying multiple parton interactions. We present results from proton-proton collisions at the center-of-mass energies √(s) = 0.9, 2.76 and 7 TeV recorded by the ALICE experiment. The ALICE data are compared to Pythia6, Pythia8 and Phojet simulations. (author)

  14. Multiplicity Dependence of Two-Particle Correlations in Proton-Proton Collisions Measured with ALICE at the LHC

    CERN Document Server

    Sicking, Eva

    2012-01-01

    We investigate properties of jets in proton-proton collisions using two-particle angular correlations. By choosing an analysis approach based on two-particle angular correlations, also the properties of low-energetic jets can be accessed. Observing the strength of the correlation as a function of the charged particle multiplicity reveals jet fragmentation properties as well as the contribution of jets to the overall charged particle multiplicity. Furthermore, the analysis discloses information on the underlying multiple parton interactions. We present results from proton-proton collisions at the center-of-mass energies $\\sqrt{s}$ = 0.9, 2.76, and 7.0 TeV recorded by the ALICE experiment. The ALICE data are compared to Pythia6, Pythia8, and Phojet simulations.

  15. GUDM: Automatic Generation of Unified Datasets for Learning and Reasoning in Healthcare.

    Science.gov (United States)

    Ali, Rahman; Siddiqi, Muhammad Hameed; Idris, Muhammad; Ali, Taqdir; Hussain, Shujaat; Huh, Eui-Nam; Kang, Byeong Ho; Lee, Sungyoung

    2015-07-02

    A wide array of biomedical data are generated and made available to healthcare experts. However, due to the diverse nature of data, it is difficult to predict outcomes from it. It is therefore necessary to combine these diverse data sources into a single unified dataset. This paper proposes a global unified data model (GUDM) to provide a global unified data structure for all data sources and generate a unified dataset by a "data modeler" tool. The proposed tool implements user-centric priority based approach which can easily resolve the problems of unified data modeling and overlapping attributes across multiple datasets. The tool is illustrated using sample diabetes mellitus data. The diverse data sources to generate the unified dataset for diabetes mellitus include clinical trial information, a social media interaction dataset and physical activity data collected using different sensors. To realize the significance of the unified dataset, we adopted a well-known rough set theory based rules creation process to create rules from the unified dataset. The evaluation of the tool on six different sets of locally created diverse datasets shows that the tool, on average, reduces 94.1% time efforts of the experts and knowledge engineer while creating unified datasets.

  16. Bose-Einstein correlations in pp and PbPb collisions with ALICE at the LHC

    CERN Multimedia

    CERN. Geneva

    2011-01-01

    We report on the results of identical pion femtoscopy at the LHC. The Bose-Einstein correlation analysis was performed on the large-statistics ALICE p+p at sqrt{s}= 0.9 TeV and 7 TeV datasets collected during 2010 LHC running and the first Pb+Pb dataset at sqrt{s_NN}= 2.76 TeV. Detailed pion femtoscopy studies in heavy-ion collisions have shown that emission region sizes ("HBT radii") decrease with increasing pair momentum, which is understood as a manifestation of the collective behavior of matter. 3D radii were also found to universally scale with event multiplicity. In p+p collisions at 7 TeV one measures multiplicities which are comparable with those registered in peripheral AuAu and CuCu collisions at RHIC, so direct comparisons and tests of scaling laws are now possible. We show the results of double-differential 3D pion HBT analysis, as a function of multiplicity and pair momentum. The results for two collision energies are compared to results obtained in the heavy-ion collisions at similar multipl...

  17. Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants.

    Science.gov (United States)

    Sauzet, Odile; Peacock, Janet L

    2017-07-20

    The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins) and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

  18. Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants

    Directory of Open Access Journals (Sweden)

    Odile Sauzet

    2017-07-01

    Full Text Available Abstract Background The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Methods Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. Results The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. Conclusions This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

  19. Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

    Science.gov (United States)

    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)

  20. Forward-backward multiplicity correlations in pp collisions at = 0.9, 2.76 and 7 TeV

    Science.gov (United States)

    Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmed, I.; Ahn, S. U.; Aimo, I.; Aiola, S.; Ajaz, M.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anielski, J.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Armesto, N.; Arnaldi, R.; Aronsson, T.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Bach, M.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baltasar Dos Santos Pedrosa, F.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biswas, S.; Bjelogrlic, S.; Blanco, F.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botje, M.; Botta, E.; Böttger, S.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Cavicchioli, C.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deloff, A.; Dénes, E.; D'Erasmo, G.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Dobrowolski, T.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Erazmus, B.; Erdal, H. A.; Eschweiler, D.; Espagnon, B.; Esposito, M.; Estienne, M.; Esumi, S.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Felea, D.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Germain, M.; Gheata, A.; Gheata, M.; Ghidini, B.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Gomez Ramirez, A.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Graczykowski, L. K.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gulkanyan, H.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hanratty, L. D.; Hansen, A.; Harris, J. W.; Hartmann, H.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Heide, M.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hilden, T. E.; Hillemanns, H.; Hippolyte, B.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Ilkiv, I.; Inaba, M.; Ionita, C.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Jacholkowski, A.; Jacobs, P. M.; Jahnke, C.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jung, H.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Khan, K. H.; Khan, M. M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, B.; Kim, D. W.; Kim, D. J.; Kim, H.; Kim, J. S.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobayashi, T.; Kobdaj, C.; Kofarago, M.; Köhler, M. K.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kovalenko, V.; Kowalski, M.; Kox, S.; Koyithatta Meethaleveedu, G.; Kral, J.; Králik, I.; Kravčáková, A.; Krelina, M.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kucheriaev, Y.; Kugathasan, T.; Kuhn, C.; Kuijer, P. G.; Kulakov, I.; Kumar, J.; Kumar, L.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Legrand, I.; Lehnert, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; Leoncino, M.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loggins, V. R.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Lu, X.-G.; Luettig, P.; Lunardon, M.; Luparello, G.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manceau, L.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martashvili, I.; Martin, N. A.; Martin Blanco, J.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martynov, Y.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Morando, M.; Moreira De Godoy, D. A.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Müller, H.; Mulligan, J. D.; Munhoz, M. G.; Murray, S.; Musa, L.; Musinsky, J.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Nilsen, B. S.; Noferini, F.; Nomokonov, P.; Nooren, G.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Onderwaater, J.; Oppedisano, C.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pajares, C.; Pal, S. K.; Pan, J.; Pandey, A. K.; Pant, D.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Patalakha, D. I.; Paticchio, V.; Paul, B.; Pawlak, T.; Peitzmann, T.; Pereira Da Costa, H.; Pereira De Oliveira Filho, E.; Peresunko, D.; Pérez Lara, C. E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Rauf, A. W.; Razazi, V.; Read, K. F.; Real, J. S.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reicher, M.; Reidt, F.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Rettig, F.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rivetti, A.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salgado, C. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sanchez Castro, X.; Šándor, L.; Sandoval, A.; Sano, M.; Santagati, G.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Seeder, K. S.; Segato, G.; Seger, J. E.; Sekiguchi, Y.; Selyuzhenkov, I.; Senosi, K.; Seo, J.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Skjerdal, K.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Soltz, R.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stefanek, G.; Steinpreis, M.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Sultanov, R.; Šumbera, M.; Symons, T. J. M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Takahashi, J.; Tanaka, N.; Tangaro, M. A.; Tapia Takaki, J. D.; Tarantola Peloni, A.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Valencia Palomo, L.; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Wang, Y.; Watanabe, D.; Weber, M.; Weber, S. G.; Wessels, J. P.; Westerhoff, U.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yamaguchi, Y.; Yang, H.; Yang, P.; Yano, S.; Yasnopolskiy, S.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zhu, X.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.

    2015-05-01

    The strength of forward-backward (FB) multiplicity correlations is measured by the ALICE detector in proton-proton (pp) collisions at = 0 .9, 2 .76 and 7 TeV. The measurement is performed in the central pseudorapidity region (| η| 0 .3 GeV /c. Two separate pseudorapidity windows of width ( δη) ranging from 0.2 to 0.8 are chosen symmetrically around η = 0. The multiplicity correlation strength ( b corr) is studied as a function of the pseudorapidity gap ( η gap) between the two windows as well as the width of these windows. The correlation strength is found to decrease with increasing η gap and shows a non-linear increase with δη. A sizable increase of the correlation strength with the collision energy, which cannot be explained exclusively by the increase of the mean multiplicity inside the windows, is observed. The correlation coefficient is also measured for multiplicities in different configurations of two azimuthal sectors selected within the symmetric FB η-windows. Two different contributions, the short-range (SR) and the long-range (LR), are observed. The energy dependence of b corr is found to be weak for the SR component while it is strong for the LR component. Moreover, the correlation coefficient is studied for particles belonging to various transverse momentum intervals chosen to have the same mean multiplicity. Both SR and LR contributions to b corr are found to increase with p T in this case. Results are compared to PYTHIA and PHOJET event generators and to a string-based phenomenological model. The observed dependencies of b corr add new constraints on phenomenological models. [Figure not available: see fulltext.

  1. Social Cognitive Correlates of Physical Activity in Black Individuals With Multiple Sclerosis.

    Science.gov (United States)

    Kinnett-Hopkins, Dominique; Motl, Robert W

    2016-04-01

    To examine variables from social cognitive theory as correlates of physical activity in black and white individuals with multiple sclerosis (MS). Cross-sectional. National survey. Black (n=151) and white (n=185) individuals with MS were recruited through the North American Research Committee on Multiple Sclerosis Registry. Not applicable. The battery of questionnaires included information on demographic and clinical characteristics, physical activity, exercise self-efficacy, function, social support, exercise outcome expectations, and exercise goal setting and planning. Black individuals with MS reported significantly lower levels of physical activity compared with white individuals with MS. Physical activity levels were significantly correlated with self-efficacy, outcome expectations, functional limitations as impediments, and goal setting in black participants with MS. The pattern and magnitude of correlations were comparable with those observed in white participants based on Fisher z tests. Researchers should consider applying behavioral interventions that target social cognitive theory variables for increasing physical activity levels among black individuals with MS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  2. Forward-backward multiplicity correlations in pp collisions at $\\sqrt{s}$=0.9, 2.76 and 7 TeV

    CERN Document Server

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Paic, Guy; Pajares Vales, Carlos; Pal, Susanta Kumar; Pan, Jinjin; Pant, Divyash; Papikyan, Vardanush; Pappalardo, Giuseppe; Pareek, Pooja; Park, Woojin; Parmar, Sonia; Passfeld, Annika; Patalakha, Dmitry; Paticchio, Vincenzo; Paul, Biswarup; Pawlak, Tomasz Jan; Peitzmann, Thomas; Pereira Da Costa, Hugo Denis Antonio; Pereira De Oliveira Filho, Elienos; Peresunko, Dmitry Yurevich; Perez Lara, Carlos Eugenio; Peskov, Vladimir; Pestov, Yury; Petracek, Vojtech; Petrov, Viacheslav; Petrovici, Mihai; Petta, Catia; Piano, Stefano; Pikna, Miroslav; Pillot, Philippe; Pinazza, Ombretta; Pinsky, Lawrence; Piyarathna, Danthasinghe; Ploskon, Mateusz Andrzej; Planinic, Mirko; Pluta, Jan Marian; Pochybova, Sona; Podesta Lerma, Pedro Luis Manuel; Poghosyan, Martin; Polishchuk, Boris; Poljak, Nikola; Poonsawat, Wanchaloem; Pop, Amalia; Porteboeuf, Sarah Julie; Porter, R Jefferson; Pospisil, Jan; Prasad, Sidharth Kumar; Preghenella, Roberto; Prino, Francesco; Pruneau, Claude Andre; Pshenichnov, Igor; Puccio, Maximiliano; Puddu, Giovanna; Pujahari, Prabhat Ranjan; Punin, Valery; Putschke, Jorn Henning; Qvigstad, Henrik; Rachevski, Alexandre; Raha, Sibaji; Rajput, Sonia; Rak, Jan; Rakotozafindrabe, Andry Malala; Ramello, Luciano; Raniwala, Rashmi; Raniwala, Sudhir; Rasanen, Sami Sakari; Rascanu, Bogdan Theodor; Rathee, Deepika; Rauf, Aamer Wali; Razazi, Vahedeh; Read, Kenneth Francis; Real, Jean-Sebastien; Redlich, Krzysztof; Reed, Rosi Jan; Rehman, Attiq Ur; Reichelt, Patrick Simon; Reicher, Martijn; Reidt, Felix; Renfordt, Rainer Arno Ernst; Reolon, Anna Rita; Reshetin, Andrey; Rettig, Felix Vincenz; Revol, Jean-Pierre; Reygers, Klaus Johannes; Riabov, Viktor; Ricci, Renato Angelo; Richert, Tuva Ora Herenui; Richter, Matthias Rudolph; Riedler, Petra; Riegler, Werner; Riggi, Francesco; Ristea, Catalin-Lucian; Rivetti, Angelo; Rocco, Elena; Rodriguez Cahuantzi, Mario; Rodriguez Manso, Alis; Roeed, Ketil; Rogochaya, Elena; Rohr, David Michael; Roehrich, Dieter; Romita, Rosa; Ronchetti, Federico; Ronflette, Lucile; Rosnet, Philippe; Rossi, Andrea; Roukoutakis, Filimon; Roy, Ankhi; Roy, Christelle Sophie; Roy, Pradip Kumar; Rubio Montero, Antonio Juan; Rui, Rinaldo; Russo, Riccardo; Ryabinkin, Evgeny; Ryabov, Yury; Rybicki, Andrzej; Sadovskiy, Sergey; Safarik, Karel; Sahlmuller, Baldo; Sahoo, Pragati; Sahoo, Raghunath; Sahoo, Sarita; Sahu, Pradip Kumar; Saini, Jogender; Sakai, Shingo; Saleh, Mohammad Ahmad; Salgado Lopez, Carlos Alberto; Salzwedel, Jai Samuel Nielsen; Sambyal, Sanjeev Singh; Samsonov, Vladimir; Sanchez Castro, Xitzel; Sandor, Ladislav; Sandoval, Andres; Sano, Masato; Santagati, Gianluca; Sarkar, Debojit; Scapparone, Eugenio; Scarlassara, Fernando; Scharenberg, Rolf Paul; Schiaua, Claudiu Cornel; Schicker, Rainer Martin; Schmidt, Christian Joachim; Schmidt, Hans Rudolf; Schuchmann, Simone; Schukraft, Jurgen; Schulc, Martin; Schuster, Tim Robin; Schutz, Yves Roland; Schwarz, Kilian Eberhard; Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Rebecca Michelle; Seeder, Karin Soraya; Segato, Gianfranco; Seger, Janet Elizabeth; Sekiguchi, Yuko; Selyuzhenkov, Ilya; Senosi, Kgotlaesele; Seo, Jeewon; Serradilla Rodriguez, Eulogio; Sevcenco, Adrian; Shabanov, Arseniy; Shabetai, Alexandre; Shadura, Oksana; Shahoyan, Ruben; Shangaraev, Artem; Sharma, Ankita; Sharma, Natasha; Shigaki, Kenta; Shtejer Diaz, Katherin; Sibiryak, Yury; Siddhanta, Sabyasachi; Sielewicz, Krzysztof Marek; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Silvestre, Catherine Micaela; Simatovic, Goran; Singaraju, Rama Narayana; Singh, Ranbir; Singha, Subhash; Singhal, Vikas; Sinha, Bikash; Sarkar - Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Skjerdal, Kyrre; Slupecki, Maciej; Smirnov, Nikolai; Snellings, Raimond; Snellman, Tomas Wilhelm; Soegaard, Carsten; Soltz, Ron Ariel; Song, Jihye; Song, Myunggeun; Song, Zixuan; Soramel, Francesca; Sorensen, Soren Pontoppidan; Spacek, Michal; Spiriti, Eleuterio; Sputowska, Iwona Anna; Spyropoulou-Stassinaki, Martha; Srivastava, Brijesh Kumar; Stachel, Johanna; Stan, Ionel; Stefanek, Grzegorz; Steinpreis, Matthew Donald; Stenlund, Evert Anders; Steyn, Gideon Francois; Stiller, Johannes Hendrik; Stocco, Diego; Strmen, Peter; Alarcon Do Passo Suaide, Alexandre; Sugitate, Toru; Suire, Christophe Pierre; Suleymanov, Mais Kazim Oglu; Sultanov, Rishat; Sumbera, Michal; Symons, Timothy; Szabo, Alexander; Szanto De Toledo, Alejandro; Szarka, Imrich; Szczepankiewicz, Adam; Szymanski, Maciej Pawel; Takahashi, Jun; Tanaka, Naoto; Tangaro, Marco-Antonio; Tapia Takaki, Daniel Jesus; Tarantola Peloni, Attilio; Tariq, Mohammad; Tarzila, Madalina-Gabriela; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terasaki, Kohei; Terrevoli, Cristina; Teyssier, Boris; Thaeder, Jochen Mathias; Thomas, Deepa; Tieulent, Raphael Noel; Timmins, Anthony Robert; Toia, Alberica; Trogolo, Stefano; Trubnikov, Victor; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ullaland, Kjetil; Uras, Antonio; Usai, Gianluca; Utrobicic, Antonija; Vajzer, Michal; Vala, Martin; Valencia Palomo, Lizardo; Vallero, Sara; Van Der Maarel, Jasper; Van Hoorne, Jacobus Willem; Van Leeuwen, Marco; Vanat, Tomas; Vande Vyvre, Pierre; Varga, Dezso; Diozcora Vargas Trevino, Aurora; Vargyas, Marton; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vauthier, Astrid; Vechernin, Vladimir; Veen, Annelies Marianne; Veldhoen, Misha; Velure, Arild; Venaruzzo, Massimo; Vercellin, Ermanno; Vergara Limon, Sergio; Vernet, Renaud; Verweij, Marta; Vickovic, Linda; Viesti, Giuseppe; Viinikainen, Jussi Samuli; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Vinogradov, Alexander; Vinogradov, Leonid; Vinogradov, Yury; Virgili, Tiziano; Vislavicius, Vytautas; Viyogi, Yogendra; Vodopyanov, Alexander; Volkl, Martin Andreas; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; Von Haller, Barthelemy; Vorobyev, Ivan; Vranic, Danilo; Vrlakova, Janka; Vulpescu, Bogdan; Vyushin, Alexey; Wagner, Boris; Wagner, Jan; Wang, Hongkai; Wang, Mengliang; Wang, Yifei; Watanabe, Daisuke; Weber, Michael; Weber, Steffen Georg; Wessels, Johannes Peter; Westerhoff, Uwe; Wiechula, Jens; Wikne, Jon; Wilde, Martin Rudolf; Wilk, Grzegorz Andrzej; Wilkinson, Jeremy John; Williams, Crispin; Windelband, Bernd Stefan; Winn, Michael Andreas; Yaldo, Chris G; Yamaguchi, Yorito; Yang, Hongyan; Yang, Ping; Yano, Satoshi; Yasnopolskiy, Stanislav; Yin, Zhongbao; Yokohama, Hiroki; Yoo, In-Kwon; Yurchenko, Volodymyr; Yushmanov, Igor; Zaborowska, Anna; Zaccolo, Valentina; Zaman, Ali; Zampolli, Chiara; Correia Zanoli, Henrique Jose; Zaporozhets, Sergey; Zarochentsev, Andrey; Zavada, Petr; Zavyalov, Nikolay; Zbroszczyk, Hanna Paulina; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhang, Yonghong; Zhao, Chengxin; Zhigareva, Natalia; Zhou, Daicui; Zhou, You; Zhou, Zhuo; Zhu, Hongsheng; Zhu, Jianhui; Zhu, Xiangrong; Zichichi, Antonino; Zimmermann, Alice; Zimmermann, Markus Bernhard; Zinovjev, Gennady; Zyzak, Maksym

    2015-05-20

    The strength of forward-backward (FB) multiplicity correlations is measured by the ALICE detector in proton-proton (pp) collisions at $\\sqrt{s}=0.9$, 2.76 and 7 TeV. The measurement is performed in the central pseudorapidity region ($|\\eta| 0.3$ GeV/$c$. Two separate pseudorapidity windows of width ($\\delta \\eta$) ranging from 0.2 to 0.8 are chosen symmetrically around $\\eta=0$. The multiplicity correlation strength ($b_{\\rm cor}$) is studied as a function of the pseudorapidity gap ($\\eta_{\\rm gap}$) between the two windows as well as the width of these windows. The correlation strength is found to decrease with increasing $\\eta_{\\rm gap}$ and shows a non-linear increase with $\\delta\\eta$. A sizable increase of the correlation strength with the collision energy, which cannot be explained exclusively by the increase of the mean multiplicity inside the windows, is observed. The correlation coefficient is also measured for multiplicities in different configurations of two azimuthal sectors selected within the sy...

  3. Multiplicities and forward-backward correlations in anti pp interactions at 22.4 GeV/c

    International Nuclear Information System (INIS)

    Boos, E.G.; Samojlov, V.V.; Tashimov, M.A.

    1977-01-01

    Forward-backward multiplicity correlations in anti pp -interactions at 22.4 GeV/c and multiplicities in a simple icle multiplicity distribution is divided into even and odd components, the probability of producting an odd state is found to be higher than that of producing an even state, which may be interpreted to be due to diffraction forward-backward and to everall multiplicities is discussed

  4. Correlation between MRI findings, blood pressure and mental ability in patients with multiple lacunar infarcts

    International Nuclear Information System (INIS)

    Fukuda, Hitoshi; Kobayashi, Shotai; Okada, Kazunori; Tsunematsu, Tokugoro

    1991-01-01

    We studied the association between mental ability as rated by Hasegawa's scale, the severity of hypertension, the severity of brain atrophy, and the severity of lesions in the cerebral white matter on magnetic resonance imaging in 34 patients with multiple cerebral infarcts but without obvious cortical lesions. Data were analyzed using multiple regression analysis. The patients having both marked brain atrophy and severe white matter lesions showed an impairment of mental ability. Brain atrophy was correlated with aging and the severity of white matter lesions. There was a significant positive correlation between the diastolic blood pressure and the severity of white matter lesions. These findings suggest that the white matter lesions in patients with multiple cerebral infarcts are correlated with brain atrophy and mental deterioration, and that uncontrolled hypertension is an important risk factor in exacerbating the lesions in the cerebral white matter. (author)

  5. The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets

    Directory of Open Access Journals (Sweden)

    Carroll Adam J

    2010-07-01

    Full Text Available Abstract Background Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Description Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.. Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP their own data to the server for online processing via a novel raw data processing pipeline. Conclusions MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to

  6. Further evidence for jet structure in large transverse momentum reactions from rapidity correlations and associated multiplicities

    International Nuclear Information System (INIS)

    Ranft, J.; Ranft, G.

    1976-10-01

    Using the hard collision model and a simple parametrisation for jet fragmentation expressions for same side and opposite side two-particle correlations and multiplicities associated with large transverse momentum trigger particles are derived. Recent data on rapidity correlations and associated multiplicities can be well understood in such a model. This result is interpreted as further evidence for the presence of jets in large transverse momentum reactions. (author)

  7. The NASA Subsonic Jet Particle Image Velocimetry (PIV) Dataset

    Science.gov (United States)

    Bridges, James; Wernet, Mark P.

    2011-01-01

    Many tasks in fluids engineering require prediction of turbulence of jet flows. The present document documents the single-point statistics of velocity, mean and variance, of cold and hot jet flows. The jet velocities ranged from 0.5 to 1.4 times the ambient speed of sound, and temperatures ranged from unheated to static temperature ratio 2.7. Further, the report assesses the accuracies of the data, e.g., establish uncertainties for the data. This paper covers the following five tasks: (1) Document acquisition and processing procedures used to create the particle image velocimetry (PIV) datasets. (2) Compare PIV data with hotwire and laser Doppler velocimetry (LDV) data published in the open literature. (3) Compare different datasets acquired at the same flow conditions in multiple tests to establish uncertainties. (4) Create a consensus dataset for a range of hot jet flows, including uncertainty bands. (5) Analyze this consensus dataset for self-consistency and compare jet characteristics to those of the open literature. The final objective was fulfilled by using the potential core length and the spread rate of the half-velocity radius to collapse of the mean and turbulent velocity fields over the first 20 jet diameters.

  8. Tracking of multiple objects with time-adjustable composite correlation filters

    Science.gov (United States)

    Ruchay, Alexey; Kober, Vitaly; Chernoskulov, Ilya

    2017-09-01

    An algorithm for tracking of multiple objects in video based on time-adjustable adaptive composite correlation filtering is proposed. For each frame a bank of composite correlation filters are designed in such a manner to provide invariance to pose, occlusion, clutter, and illumination changes. The filters are synthesized with the help of an iterative algorithm, which optimizes the discrimination capability for each object. The filters are adapted to the objects changes online using information from the current and past scene frames. Results obtained with the proposed algorithm using real-life scenes are presented and compared with those obtained with state-of-the-art tracking methods in terms of detection efficiency, tracking accuracy, and speed of processing.

  9. Spatial Correlation of Pathology and Perfusion Changes within the Cortex and White Matter in Multiple Sclerosis.

    Science.gov (United States)

    Mulholland, A D; Vitorino, R; Hojjat, S-P; Ma, A Y; Zhang, L; Lee, L; Carroll, T J; Cantrell, C G; Figley, C R; Aviv, R I

    2018-01-01

    The spatial correlation between WM and cortical GM disease in multiple sclerosis is controversial and has not been previously assessed with perfusion MR imaging. We sought to determine the nature of association between lobar WM, cortical GM, volume and perfusion. Nineteen individuals with secondary-progressive multiple sclerosis, 19 with relapsing-remitting multiple sclerosis, and 19 age-matched healthy controls were recruited. Quantitative MR perfusion imaging was used to derive CBF, CBV, and MTT within cortical GM, WM, and T2-hyperintense lesions. A 2-step multivariate linear regression (corrected for age, disease duration, and Expanded Disability Status Scale) was used to assess correlations between perfusion and volume measures in global and lobar normal-appearing WM, cortical GM, and T2-hyperintense lesions. The Bonferroni adjustment was applied as appropriate. Global cortical GM and WM volume was significantly reduced for each group comparison, except cortical GM volume of those with relapsing-remitting multiple sclerosis versus controls. Global and lobar cortical GM CBF and CBV were reduced in secondary-progressive multiple sclerosis compared with other groups but not for relapsing-remitting multiple sclerosis versus controls. Global and lobar WM CBF and CBV were not significantly different across groups. The distribution of lobar cortical GM and WM volume reduction was disparate, except for the occipital lobes in patients with secondary-progressive multiple sclerosis versus those with relapsing-remitting multiple sclerosis. Moderate associations were identified between lobar cortical GM and lobar normal-appearing WM volume in controls and in the left temporal lobe in relapsing-remitting multiple sclerosis. No significant associations occurred between cortical GM and WM perfusion or volume. Strong correlations were observed between cortical-GM perfusion, normal appearing WM and lesional perfusion, with respect to each global and lobar region within HC, and

  10. Correlation functions with fusion-channel multiplicity in W{sub 3} Toda field theory

    Energy Technology Data Exchange (ETDEWEB)

    Belavin, Vladimir [I.E. Tamm Department of Theoretical Physics, P.N. Lebedev Physical Institute,Leninsky Avenue 53, 119991 Moscow (Russian Federation); Department of Quantum Physics, Institute for Information Transmission Problems,Bolshoy Karetny per. 19, 127994 Moscow (Russian Federation); Estienne, Benoit [LPTHE, CNRS and Université Pierre et Marie Curie,Sorbonne Universités, 4 Place Jussieu, 75252 Paris Cedex 05 (France); Foda, Omar [School of Mathematics and Statistics, University of Melbourne,Parkville, Victoria 3010 (Australia); Santachiara, Raoul [LPTMS, CNRS (UMR 8626), Université Paris-Saclay,15 rue Georges Clémenceau, 91405 Orsay (France)

    2016-06-22

    Current studies of W{sub N} Toda field theory focus on correlation functions such that the W{sub N} highest-weight representations in the fusion channels are multiplicity-free. In this work, we study W{sub 3} Toda 4-point functions with multiplicity in the fusion channel. The conformal blocks of these 4-point functions involve matrix elements of a fully-degenerate primary field with a highest-weight in the adjoint representation of sl{sub 3}, and a fully-degenerate primary field with a highest-weight in the fundamental representation of sl{sub 3}. We show that, when the fusion rules do not involve multiplicities, the matrix elements of the fully-degenerate adjoint field, between two arbitrary descendant states, can be computed explicitly, on equal footing with the matrix elements of the semi-degenerate fundamental field. Using null-state conditions, we obtain a fourth-order Fuchsian differential equation for the conformal blocks. Using Okubo theory, we show that, due to the presence of multiplicities, this differential equation belongs to a class of Fuchsian equations that is different from those that have appeared so far in W{sub N} theories. We solve this equation, compute its monodromy group, and construct the monodromy-invariant correlation functions. This computation shows in detail how the ambiguities that are caused by the presence of multiplicities are fixed by requiring monodromy-invariance.

  11. Magnetic resonance imaging correlates of bee sting induced multiple organ dysfunction syndrome: A case report.

    Science.gov (United States)

    Das, Sushant K; Zeng, Li-Chuan; Li, Bing; Niu, Xiang-Ke; Wang, Jing-Liang; Bhetuwal, Anup; Yang, Han-Feng

    2014-09-28

    Occasionally systemic complications with high risk of death, such as multiple organ dysfunction syndrome (MODS), can occur following multiple bee stings. This case study reports a patient who presented with MODS, i.e., acute kidney injury, hepatic and cardiac dysfunction, after multiple bee stings. The standard clinical findings were then correlated with magnetic resonance imaging (MRI) findings, which demonstrates that MRI may be utilized as a simpler tool to use than other multiple diagnostics.

  12. Unsupervised multiple kernel learning for heterogeneous data integration.

    Science.gov (United States)

    Mariette, Jérôme; Villa-Vialaneix, Nathalie

    2018-03-15

    Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

  13. Forward-backward multiplicity correlations in $pp$, $p$+Pb and Pb+Pb collisions with the ATLAS detector

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00241915; The ATLAS collaboration

    2016-01-01

    Two-particle pseudorapidity correlations are measured in $\\sqrt{s_{\\rm{NN}}}$=2.76 TeV Pb+Pb, $\\sqrt{s_{\\rm{NN}}}$=5.02 TeV $p$+Pb and $\\sqrt{s}$ =13 TeV $pp$ collisions~\\cite{ATLAS}. Correlation function is measured using charged particles in the pseudorapidity range $|\\eta|0.2$ GeV, and it is measured as a function of event multiplicity, defined by number of charged particles with $|\\eta|0.4$ GeV. The correlation function is decomposed into a short-range component (SRC) and a long-range component (LRC). The SRC differs significantly between the opposite-charge pairs and same-charge pairs, and between the three collision systems at similar multiplicity. The LRC is described approximately by $1+\\left\\langle a_1^2\\right\\rangle\\eta_1\\eta_2$ in all collision systems over the full multiplicity range. The values of $\\left\\langle a_1^2\\right\\rangle$ are consistent between the opposite-charge and same-charge pairs, and are similar for the three collision systems at similar multiplicity. The values of $\\left\\langle a...

  14. Stochastic resonance in a time-delayed mono-stable system with correlated multiplicative and additive white noise

    International Nuclear Information System (INIS)

    Zhou Yu-Rong

    2011-01-01

    This paper considers the stochastic resonance for a time-delayed mono-stable system, driven by correlated multiplicative and additive white noise. It finds that the output signal-to-noise ratio (SNR) varies non-monotonically with the delayed times. The SNR varies non-monotonically with the increase of the intensities of the multiplicative and additive noise, with the increase of the correlation strength between the two noises, as well as with the system parameter. (general)

  15. Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line

    Directory of Open Access Journals (Sweden)

    Yum Eryanti

    2016-12-01

    Full Text Available The dataset of curcumin derivatives consists of 45 compounds (Table 1 with their anti cancer biological activity (IC50 against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r2 values of 0.88 were obtained for the test set.

  16. Correlation expansion: a powerful alternative multiple scattering calculation method

    International Nuclear Information System (INIS)

    Zhao Haifeng; Wu Ziyu; Sebilleau, Didier

    2008-01-01

    We introduce a powerful alternative expansion method to perform multiple scattering calculations. In contrast to standard MS series expansion, where the scattering contributions are grouped in terms of scattering order and may diverge in the low energy region, this expansion, called correlation expansion, partitions the scattering process into contributions from different small atom groups and converges at all energies. It converges faster than MS series expansion when the latter is convergent. Furthermore, it takes less memory than the full MS method so it can be used in the near edge region without any divergence problem, even for large clusters. The correlation expansion framework we derive here is very general and can serve to calculate all the elements of the scattering path operator matrix. Photoelectron diffraction calculations in a cluster containing 23 atoms are presented to test the method and compare it to full MS and standard MS series expansion

  17. Anonymising the Sparse Dataset: A New Privacy Preservation Approach while Predicting Diseases

    Directory of Open Access Journals (Sweden)

    V. Shyamala Susan

    2016-09-01

    Full Text Available Data mining techniques analyze the medical dataset with the intention of enhancing patient’s health and privacy. Most of the existing techniques are properly suited for low dimensional medical dataset. The proposed methodology designs a model for the representation of sparse high dimensional medical dataset with the attitude of protecting the patient’s privacy from an adversary and additionally to predict the disease’s threat degree. In a sparse data set many non-zero values are randomly spread in the entire data space. Hence, the challenge is to cluster the correlated patient’s record to predict the risk degree of the disease earlier than they occur in patients and to keep privacy. The first phase converts the sparse dataset right into a band matrix through the Genetic algorithm along with Cuckoo Search (GCS.This groups the correlated patient’s record together and arranges them close to the diagonal. The next segment dissociates the patient’s disease, which is a sensitive value (SA with the parameters that determine the disease normally Quasi Identifier (QI.Finally, density based clustering technique is used over the underlying data to  create anonymized groups to maintain privacy and to predict the risk level of disease. Empirical assessments on actual health care data corresponding to V.A.Medical Centre heart disease dataset reveal the efficiency of this model pertaining to information loss, utility and privacy.

  18. Correlation between white matter damage and gray matter lesions in multiple sclerosis patients

    Directory of Open Access Journals (Sweden)

    Xue-mei Han

    2017-01-01

    Full Text Available We observed the characteristics of white matter fibers and gray matter in multiple sclerosis patients, to identify changes in diffusion tensor imaging fractional anisotropy values following white matter fiber injury. We analyzed the correlation between fractional anisotropy values and changes in whole-brain gray matter volume. The participants included 20 patients with relapsing-remitting multiple sclerosis and 20 healthy volunteers as controls. All subjects underwent head magnetic resonance imaging and diffusion tensor imaging. Our results revealed that fractional anisotropy values decreased and gray matter volumes were reduced in the genu and splenium of corpus callosum, left anterior thalamic radiation, hippocampus, uncinate fasciculus, right corticospinal tract, bilateral cingulate gyri, and inferior longitudinal fasciculus in multiple sclerosis patients. Gray matter volumes were significantly different between the two groups in the right frontal lobe (superior frontal, middle frontal, precentral, and orbital gyri, right parietal lobe (postcentral and inferior parietal gyri, right temporal lobe (caudate nucleus, right occipital lobe (middle occipital gyrus, right insula, right parahippocampal gyrus, and left cingulate gyrus. The voxel sizes of atrophic gray matter positively correlated with fractional anisotropy values in white matter association fibers in the patient group. These findings suggest that white matter fiber bundles are extensively injured in multiple sclerosis patients. The main areas of gray matter atrophy in multiple sclerosis are the frontal lobe, parietal lobe, caudate nucleus, parahippocampal gyrus, and cingulate gyrus. Gray matter atrophy is strongly associated with white matter injury in multiple sclerosis patients, particularly with injury to association fibers.

  19. Uranium mass and neutron multiplication factor estimates from time-correlation coincidence counts

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Wenxiong [China Academy of Engineering Physics, Center for Strategic Studies, Beijing 100088 (China); Li, Jiansheng [China Academy of Engineering Physics, Institute of Nuclear Physics and Chemistry, Mianyang 621900 (China); Zhu, Jianyu [China Academy of Engineering Physics, Center for Strategic Studies, Beijing 100088 (China)

    2015-10-11

    Time-correlation coincidence counts of neutrons are an important means to measure attributes of nuclear material. The main deficiency in the analysis is that an attribute of an unknown component can only be assessed by comparing it with similar known components. There is a lack of a universal method of measurement suitable for the different attributes of the components. This paper presents a new method that uses universal relations to estimate the mass and neutron multiplication factor of any uranium component with known enrichment. Based on numerical simulations and analyses of 64 highly enriched uranium components with different thicknesses and average radii, the relations between mass, multiplication and coincidence spectral features have been obtained by linear regression analysis. To examine the validity of the method in estimating the mass of uranium components with different sizes, shapes, enrichment, and shielding, the features of time-correlation coincidence-count spectra for other objects with similar attributes are simulated. Most of the masses and multiplications for these objects could also be derived by the formulation. Experimental measurements of highly enriched uranium castings have also been used to verify the formulation. The results show that for a well-designed time-dependent coincidence-count measuring system of a uranium attribute, there are a set of relations dependent on the uranium enrichment by which the mass and multiplication of the measured uranium components of any shape and size can be estimated from the features of the source-detector coincidence-count spectrum.

  20. ClimateNet: A Machine Learning dataset for Climate Science Research

    Science.gov (United States)

    Prabhat, M.; Biard, J.; Ganguly, S.; Ames, S.; Kashinath, K.; Kim, S. K.; Kahou, S.; Maharaj, T.; Beckham, C.; O'Brien, T. A.; Wehner, M. F.; Williams, D. N.; Kunkel, K.; Collins, W. D.

    2017-12-01

    Deep Learning techniques have revolutionized commercial applications in Computer vision, speech recognition and control systems. The key for all of these developments was the creation of a curated, labeled dataset ImageNet, for enabling multiple research groups around the world to develop methods, benchmark performance and compete with each other. The success of Deep Learning can be largely attributed to the broad availability of this dataset. Our empirical investigations have revealed that Deep Learning is similarly poised to benefit the task of pattern detection in climate science. Unfortunately, labeled datasets, a key pre-requisite for training, are hard to find. Individual research groups are typically interested in specialized weather patterns, making it hard to unify, and share datasets across groups and institutions. In this work, we are proposing ClimateNet: a labeled dataset that provides labeled instances of extreme weather patterns, as well as associated raw fields in model and observational output. We develop a schema in NetCDF to enumerate weather pattern classes/types, store bounding boxes, and pixel-masks. We are also working on a TensorFlow implementation to natively import such NetCDF datasets, and are providing a reference convolutional architecture for binary classification tasks. Our hope is that researchers in Climate Science, as well as ML/DL, will be able to use (and extend) ClimateNet to make rapid progress in the application of Deep Learning for Climate Science research.

  1. SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets.

    Science.gov (United States)

    Gosline, Sara J C; Spencer, Sarah J; Ursu, Oana; Fraenkel, Ernest

    2012-11-01

    The rapid development of high throughput biotechnologies has led to an onslaught of data describing genetic perturbations and changes in mRNA and protein levels in the cell. Because each assay provides a one-dimensional snapshot of active signaling pathways, it has become desirable to perform multiple assays (e.g. mRNA expression and phospho-proteomics) to measure a single condition. However, as experiments expand to accommodate various cellular conditions, proper analysis and interpretation of these data have become more challenging. Here we introduce a novel approach called SAMNet, for Simultaneous Analysis of Multiple Networks, that is able to interpret diverse assays over multiple perturbations. The algorithm uses a constrained optimization approach to integrate mRNA expression data with upstream genes, selecting edges in the protein-protein interaction network that best explain the changes across all perturbations. The result is a putative set of protein interactions that succinctly summarizes the results from all experiments, highlighting the network elements unique to each perturbation. We evaluated SAMNet in both yeast and human datasets. The yeast dataset measured the cellular response to seven different transition metals, and the human dataset measured cellular changes in four different lung cancer models of Epithelial-Mesenchymal Transition (EMT), a crucial process in tumor metastasis. SAMNet was able to identify canonical yeast metal-processing genes unique to each commodity in the yeast dataset, as well as human genes such as β-catenin and TCF7L2/TCF4 that are required for EMT signaling but escaped detection in the mRNA and phospho-proteomic data. Moreover, SAMNet also highlighted drugs likely to modulate EMT, identifying a series of less canonical genes known to be affected by the BCR-ABL inhibitor imatinib (Gleevec), suggesting a possible influence of this drug on EMT.

  2. Towards interoperable and reproducible QSAR analyses: Exchange of datasets.

    Science.gov (United States)

    Spjuth, Ola; Willighagen, Egon L; Guha, Rajarshi; Eklund, Martin; Wikberg, Jarl Es

    2010-06-30

    QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but

  3. Towards interoperable and reproducible QSAR analyses: Exchange of datasets

    Directory of Open Access Journals (Sweden)

    Spjuth Ola

    2010-06-01

    Full Text Available Abstract Background QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. Results We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Conclusions Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join

  4. An Adaptive Model for Calculating the Correlation Degree of Multiple Adjacent Signalized Intersections

    Directory of Open Access Journals (Sweden)

    Linhong Wang

    2013-01-01

    Full Text Available As an important component of the urban adaptive traffic control system, subarea partition algorithm divides the road network into some small subareas and then determines the optimal signal control mode for each signalized intersection. Correlation model is the core of subarea partition algorithm because it can quantify the correlation degree of adjacent signalized intersections and decides whether these intersections can be grouped into one subarea. In most cases, there are more than two intersections in one subarea. However, current researches only focus on the correlation model for two adjacent intersections. The objective of this study is to develop a model which can calculate the correlation degree of multiple intersections adaptively. The cycle lengths, link lengths, number of intersections, and path flow between upstream and downstream coordinated phases were selected as the contributing factors of the correlation model. Their jointly impacts on the performance of the coordinated control mode relative to the isolated control mode were further studied using numerical experiments. The paper then proposed a correlation index (CI as an alternative to relative performance. The relationship between CI and the four contributing factors was established in order to predict the correlation, which determined whether adjacent intersections could be partitioned into one subarea. A value of 0 was set as the threshold of CI. If CI was larger than 0, multiple intersections could be partitioned into one subarea; otherwise, they should be separated. Finally, case studies were conducted in a real-life signalized network to evaluate the performance of the model. The results show that the CI simulates the relative performance well and could be a reliable index for subarea partition.

  5. Sensitivity of a numerical wave model on wind re-analysis datasets

    Science.gov (United States)

    Lavidas, George; Venugopal, Vengatesan; Friedrich, Daniel

    2017-03-01

    Wind is the dominant process for wave generation. Detailed evaluation of metocean conditions strengthens our understanding of issues concerning potential offshore applications. However, the scarcity of buoys and high cost of monitoring systems pose a barrier to properly defining offshore conditions. Through use of numerical wave models, metocean conditions can be hindcasted and forecasted providing reliable characterisations. This study reports the sensitivity of wind inputs on a numerical wave model for the Scottish region. Two re-analysis wind datasets with different spatio-temporal characteristics are used, the ERA-Interim Re-Analysis and the CFSR-NCEP Re-Analysis dataset. Different wind products alter results, affecting the accuracy obtained. The scope of this study is to assess different available wind databases and provide information concerning the most appropriate wind dataset for the specific region, based on temporal, spatial and geographic terms for wave modelling and offshore applications. Both wind input datasets delivered results from the numerical wave model with good correlation. Wave results by the 1-h dataset have higher peaks and lower biases, in expense of a high scatter index. On the other hand, the 6-h dataset has lower scatter but higher biases. The study shows how wind dataset affects the numerical wave modelling performance, and that depending on location and study needs, different wind inputs should be considered.

  6. On the Ergodic Secret-Key Agreement over Spatially Correlated Multiple-Antenna Channels with Public Discussion

    KAUST Repository

    Zorgui, Marwen

    2015-09-28

    We consider secret-key agreement with public discussion over multiple-input multiple-output (MIMO) Rayleigh fast-fading channels under correlated environment. We assume that transmit, legitimate receiver and eavesdropper antennas are correlated. The legitimate receiver and the eavesdropper are assumed to have perfect channel knowledge while the transmitter has only knowledge of the correlation matrices. First, we derive the expression of the secret-key capacity under the considered setup. We prove that the optimal transmit strategy achieving the secret-key capacity consists in transmitting independent Gaussian signals along the eingenvectors of the transmit correlation matrix. The powers allocated to each channel mode are determined as the solution to a numerical optimization problem. A necessary and sufficient condition for beamforming (i.e., transmitting along the strongest channel mode) to be capacity-achieving is derived. Moreover, we analyze the impact of correlation matrices on the system performance. Finally, we study the system’s performance in the two extreme power regimes. In the high-power regime, we provide closed-form expressions of the gain/loss due to correlation. In the low signal-to-noise ratio (SNR) regime, we investigate the energy efficiency of the system by determining the minimum energy required for sharing a secret-key bit and the wideband slope while highlighting the impact of correlation matrices.

  7. Spatially varying cross-correlation coefficients in the presence of nugget effects

    KAUST Repository

    Kleiber, William; Genton, Marc G.

    2012-01-01

    We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction matrix, which can be either diagonal, implying a parsimonious formulation, or a fully general contraction matrix, yielding greater flexibility but added model complexity. We illustrate the approach with a bivariate minimum and maximum temperature dataset in Colorado, allowing the two variables to be positively correlated at low elevations and nearly independent at high elevations, while still yielding a positive definite covariance matrix. © 2012 Biometrika Trust.

  8. Spatially varying cross-correlation coefficients in the presence of nugget effects

    KAUST Repository

    Kleiber, William

    2012-11-29

    We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction matrix, which can be either diagonal, implying a parsimonious formulation, or a fully general contraction matrix, yielding greater flexibility but added model complexity. We illustrate the approach with a bivariate minimum and maximum temperature dataset in Colorado, allowing the two variables to be positively correlated at low elevations and nearly independent at high elevations, while still yielding a positive definite covariance matrix. © 2012 Biometrika Trust.

  9. EPA Nanorelease Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — EPA Nanorelease Dataset. This dataset is associated with the following publication: Wohlleben, W., C. Kingston, J. Carter, E. Sahle-Demessie, S. Vazquez-Campos, B....

  10. The linearized inversion of the generalized interferometric multiple imaging

    KAUST Repository

    Aldawood, Ali

    2016-09-06

    The generalized interferometric multiple imaging (GIMI) procedure can be used to image duplex waves and other higher order internal multiples. Imaging duplex waves could help illuminate subsurface zones that are not easily illuminated by primaries such as vertical and nearly vertical fault planes, and salt flanks. To image first-order internal multiple, the GIMI framework consists of three datuming steps, followed by applying the zero-lag cross-correlation imaging condition. However, the standard GIMI procedure yields migrated images that suffer from low spatial resolution, migration artifacts, and cross-talk noise. To alleviate these problems, we propose a least-squares GIMI framework in which we formulate the first two steps as a linearized inversion problem when imaging first-order internal multiples. Tests on synthetic datasets demonstrate the ability to localize subsurface scatterers in their true positions, and delineate a vertical fault plane using the proposed method. We, also, demonstrate the robustness of the proposed framework when imaging the scatterers or the vertical fault plane with erroneous migration velocities.

  11. A Hidden Markov Model Representing the Spatial and Temporal Correlation of Multiple Wind Farms

    DEFF Research Database (Denmark)

    Fang, Jiakun; Su, Chi; Hu, Weihao

    2015-01-01

    To accommodate the increasing wind energy with stochastic nature becomes a major issue on power system reliability. This paper proposes a methodology to characterize the spatiotemporal correlation of multiple wind farms. First, a hierarchical clustering method based on self-organizing maps is ado....... The proposed statistical modeling framework is compatible with the sequential power system reliability analysis. A case study on optimal sizing and location of fast-response regulation sources is presented.......To accommodate the increasing wind energy with stochastic nature becomes a major issue on power system reliability. This paper proposes a methodology to characterize the spatiotemporal correlation of multiple wind farms. First, a hierarchical clustering method based on self-organizing maps...... is adopted to categorize the similar output patterns of several wind farms into joint states. Then the hidden Markov model (HMM) is then designed to describe the temporal correlations among these joint states. Unlike the conventional Markov chain model, the accumulated wind power is taken into consideration...

  12. A conceptual prototype for the next-generation national elevation dataset

    Science.gov (United States)

    Stoker, Jason M.; Heidemann, Hans Karl; Evans, Gayla A.; Greenlee, Susan K.

    2013-01-01

    In 2012 the U.S. Geological Survey's (USGS) National Geospatial Program (NGP) funded a study to develop a conceptual prototype for a new National Elevation Dataset (NED) design with expanded capabilities to generate and deliver a suite of bare earth and above ground feature information over the United States. This report details the research on identifying operational requirements based on prior research, evaluation of what is needed for the USGS to meet these requirements, and development of a possible conceptual framework that could potentially deliver the kinds of information that are needed to support NGP's partners and constituents. This report provides an initial proof-of-concept demonstration using an existing dataset, and recommendations for the future, to inform NGP's ongoing and future elevation program planning and management decisions. The demonstration shows that this type of functional process can robustly create derivatives from lidar point cloud data; however, more research needs to be done to see how well it extends to multiple datasets.

  13. The multiple imputation method: a case study involving secondary data analysis.

    Science.gov (United States)

    Walani, Salimah R; Cleland, Charles M

    2015-05-01

    To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

  14. A geospatial database model for the management of remote sensing datasets at multiple spectral, spatial, and temporal scales

    Science.gov (United States)

    Ifimov, Gabriela; Pigeau, Grace; Arroyo-Mora, J. Pablo; Soffer, Raymond; Leblanc, George

    2017-10-01

    In this study the development and implementation of a geospatial database model for the management of multiscale datasets encompassing airborne imagery and associated metadata is presented. To develop the multi-source geospatial database we have used a Relational Database Management System (RDBMS) on a Structure Query Language (SQL) server which was then integrated into ArcGIS and implemented as a geodatabase. The acquired datasets were compiled, standardized, and integrated into the RDBMS, where logical associations between different types of information were linked (e.g. location, date, and instrument). Airborne data, at different processing levels (digital numbers through geocorrected reflectance), were implemented in the geospatial database where the datasets are linked spatially and temporally. An example dataset consisting of airborne hyperspectral imagery, collected for inter and intra-annual vegetation characterization and detection of potential hydrocarbon seepage events over pipeline areas, is presented. Our work provides a model for the management of airborne imagery, which is a challenging aspect of data management in remote sensing, especially when large volumes of data are collected.

  15. Multiple Improvements of Multiple Imputation Likelihood Ratio Tests

    OpenAIRE

    Chan, Kin Wai; Meng, Xiao-Li

    2017-01-01

    Multiple imputation (MI) inference handles missing data by first properly imputing the missing values $m$ times, and then combining the $m$ analysis results from applying a complete-data procedure to each of the completed datasets. However, the existing method for combining likelihood ratio tests has multiple defects: (i) the combined test statistic can be negative in practice when the reference null distribution is a standard $F$ distribution; (ii) it is not invariant to re-parametrization; ...

  16. Advanced Neuropsychological Diagnostics Infrastructure (ANDI): A Normative Database Created from Control Datasets.

    Science.gov (United States)

    de Vent, Nathalie R; Agelink van Rentergem, Joost A; Schmand, Ben A; Murre, Jaap M J; Huizenga, Hilde M

    2016-01-01

    In the Advanced Neuropsychological Diagnostics Infrastructure (ANDI), datasets of several research groups are combined into a single database, containing scores on neuropsychological tests from healthy participants. For most popular neuropsychological tests the quantity, and range of these data surpasses that of traditional normative data, thereby enabling more accurate neuropsychological assessment. Because of the unique structure of the database, it facilitates normative comparison methods that were not feasible before, in particular those in which entire profiles of scores are evaluated. In this article, we describe the steps that were necessary to combine the separate datasets into a single database. These steps involve matching variables from multiple datasets, removing outlying values, determining the influence of demographic variables, and finding appropriate transformations to normality. Also, a brief description of the current contents of the ANDI database is given.

  17. Vector Nonlinear Time-Series Analysis of Gamma-Ray Burst Datasets on Heterogeneous Clusters

    Directory of Open Access Journals (Sweden)

    Ioana Banicescu

    2005-01-01

    Full Text Available The simultaneous analysis of a number of related datasets using a single statistical model is an important problem in statistical computing. A parameterized statistical model is to be fitted on multiple datasets and tested for goodness of fit within a fixed analytical framework. Definitive conclusions are hopefully achieved by analyzing the datasets together. This paper proposes a strategy for the efficient execution of this type of analysis on heterogeneous clusters. Based on partitioning processors into groups for efficient communications and a dynamic loop scheduling approach for load balancing, the strategy addresses the variability of the computational loads of the datasets, as well as the unpredictable irregularities of the cluster environment. Results from preliminary tests of using this strategy to fit gamma-ray burst time profiles with vector functional coefficient autoregressive models on 64 processors of a general purpose Linux cluster demonstrate the effectiveness of the strategy.

  18. Forward-backward multiplicity correlations in pp collisions at √s=0.9, 2.76 and 7 TeV

    International Nuclear Information System (INIS)

    Adam, J.; Adamová, D.; Aggarwal, M.M.; Rinella, G. Aglieri

    2015-01-01

    The strength of forward-backward (FB) multiplicity correlations is measured by the ALICE detector in proton-proton (pp) collisions at √s=0.9, 2.76 and 7 TeV. The measurement is performed in the central pseudorapidity region (|η| 0.3 GeV/c. Two separate pseudorapidity windows of width (δη) ranging from 0.2 to 0.8 are chosen symmetrically around η=0. The multiplicity correlation strength (b_c_o_r_r) is studied as a function of the pseudorapidity gap (η_g_a_p) between the two windows as well as the width of these windows. The correlation strength is found to decrease with increasing η_g_a_p and shows a non-linear increase with δη. A sizable increase of the correlation strength with the collision energy, which cannot be explained exclusively by the increase of the mean multiplicity inside the windows, is observed. The correlation coefficient is also measured for multiplicities in different configurations of two azimuthal sectors selected within the symmetric FB η-windows. Two different contributions, the short-range (SR) and the long-range (LR), are observed. The energy dependence of b_c_o_r_r is found to be weak for the SR component while it is strong for the LR component. Moreover, the correlation coefficient is studied for particles belonging to various transverse momentum intervals chosen to have the same mean multiplicity. Both SR and LR contributions to b_c_o_r_r are found to increase with p_T in this case. Results are compared to PYTHIA and PHOJET event generators and to a string-based phenomenological model. The observed dependencies of b_c_o_r_r add new constraints on phenomenological models.

  19. Yields of correlated fragment pairs and neutron multiplicity in spontaneous fission of {sup 242}Pu

    Energy Technology Data Exchange (ETDEWEB)

    Veselsky, M.; Kliman, J.; Morhaccaron, M. [Institute of Physics of Slovak Academy of Sciences, Dubravska 9, 84228 Bratislava (Slovakia); Ramayya, A.V.; Kormicki, J.; Daniel, A.V. [Physics Department, Vanderbilt University, Nashville (United States)] Rasmussen, J.O. [Lawrence Berkeley National Laboratory, Berkeley (United States)] Stoyer, M.A. [Lawrence Livermore National Laboratory, Livermore (United States); Daniel, A.V.; Popeko, G.S.; Oganessian, Yu. Ts. [Joint Institute for Nuclear Research, Dubna (Russia)] Greiner, W. [Institut fur Theoretische Physik, J. W. Goethe Universitaet, Frankfurt a. M. (Germany); Aryaeinejad, R. [Idaho National Engineering Laboratory, Idaho Falls (United States)

    1998-10-01

    Yields of correlated fragment pairs were obtained in spontaneous fission of {sup 242}Pu. Charge, mass and neutron multiplicity distributions of fragment pairs were determined and compared to available data. The yield of cold fission without neutron emission was determined to about 10{percent} for the set of observed correlated fragment pairs. {copyright} {ital 1998 American Institute of Physics.}

  20. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    The datasets presented in this article are related to the research articles entitled “Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies” (Bennike et al., 2015 [1]), and “Proteome Analysis of Rheumatoid Arthritis Gut Mucosa” (Bennike et al., 2017 [2])...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  1. Multiplicity dependence of two-particle azimuthal correlations in pp collisions at the LHC

    CERN Document Server

    Abelev, Betty; Adamova, Dagmar; Adare, Andrew Marshall; Aggarwal, Madan; Aglieri Rinella, Gianluca; Agnello, Michelangelo; Agocs, Andras Gabor; Agostinelli, Andrea; Ahammed, Zubayer; Ahmad, Arshad; Ahmad, Nazeer; Ahmed, Ijaz; Ahn, Sang Un; Ahn, Sul-Ah; Aimo, Ilaria; Ajaz, Muhammad; Akindinov, Alexander; Aleksandrov, Dmitry; Alessandro, Bruno; Alexandre, Didier; Alici, Andrea; Alkin, Anton; Alme, Johan; Alt, Torsten; Altini, Valerio; Altinpinar, Sedat; Altsybeev, Igor; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anielski, Jonas; Anson, Christopher Daniel; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshauser, Harald; Arbor, Nicolas; Arcelli, Silvia; Arend, Andreas; Armesto, Nestor; Arnaldi, Roberta; Aronsson, Tomas Robert; Arsene, Ionut Cristian; Arslandok, Mesut; Asryan, Andzhey; Augustinus, Andre; Averbeck, Ralf Peter; Awes, Terry; Aysto, Juha Heikki; Azmi, Mohd Danish; Bach, Matthias Jakob; Badala, Angela; Baek, Yong Wook; Bailhache, Raphaelle Marie; Bala, Renu; Baldisseri, Alberto; Baltasar Dos Santos Pedrosa, Fernando; Ban, Jaroslav; Baral, Rama Chandra; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Barret, Valerie; Bartke, Jerzy Gustaw; Basile, Maurizio; Bastid, Nicole; Basu, Sumit; Bathen, Bastian; Batigne, Guillaume; Batyunya, Boris; Batzing, Paul Christoph; Baumann, Christoph Heinrich; Bearden, Ian Gardner; Beck, Hans; Behera, Nirbhay Kumar; Belikov, Iouri; Bellini, Francesca; Bellwied, Rene; Belmont-Moreno, Ernesto; Bencedi, Gyula; Beole, Stefania; Berceanu, Ionela; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Bergognon, Anais Annick Erica; Bertens, Redmer Alexander; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhati, Ashok Kumar; Bhom, Jihyun; Bianchi, Livio; Bianchi, Nicola; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Bjelogrlic, Sandro; Blanco, F; Blanco, Francesco; Blau, Dmitry; Blume, Christoph; Boccioli, Marco; Bock, Friederike Bock; Boettger, Stefan; Bogdanov, Alexey; Boggild, Hans; Bogolyubsky, Mikhail; Boldizsar, Laszlo; Bombara, Marek; Book, Julian; Borel, Herve; Borissov, Alexander; Bornschein, Joerg; Bossu, Francesco; Botje, Michiel; Botta, Elena; Braidot, Ermes; Braun-Munzinger, Peter; Bregant, Marco; Breitner, Timo Gunther; Broker, Theo Alexander; Browning, Tyler Allen; Broz, Michal; Brun, Rene; Bruna, Elena; Bruno, Giuseppe Eugenio; Budnikov, Dmitry; Buesching, Henner; Bufalino, Stefania; Buncic, Predrag; Busch, Oliver; Buthelezi, Edith Zinhle; Caffarri, Davide; Cai, Xu; Caines, Helen Louise; Caliva, Alberto; Calvo Villar, Ernesto; Camerini, Paolo; Canoa Roman, Veronica; Cara Romeo, Giovanni; Carena, Francesco; Carena, Wisla; Carlin Filho, Nelson; Carminati, Federico; Casanova Diaz, Amaya Ofelia; Castillo Castellanos, Javier Ernesto; Castillo Hernandez, Juan Francisco; Casula, Ester Anna Rita; Catanescu, Vasile; Cavicchioli, Costanza; Ceballos Sanchez, Cesar; Cepila, Jan; Cerello, Piergiorgio; Chang, Beomsu; Chapeland, Sylvain; Charvet, Jean-Luc Fernand; Chattopadhyay, Subhasis; Chattopadhyay, Sukalyan; Cherney, Michael Gerard; Cheshkov, Cvetan; Cheynis, Brigitte; Chibante Barroso, Vasco Miguel; Chinellato, David; Chochula, Peter; Chojnacki, Marek; Choudhury, Subikash; Christakoglou, Panagiotis; Christensen, Christian Holm; Christiansen, Peter; Chujo, Tatsuya; Chung, Suh-Urk; Cicalo, Corrado; Cifarelli, Luisa; Cindolo, Federico; Cleymans, Jean Willy Andre; Colamaria, Fabio; Colella, Domenico; Collu, Alberto; Conesa Balbastre, Gustavo; Conesa del Valle, Zaida; Connors, Megan Elizabeth; Contin, Giacomo; Contreras, Jesus Guillermo; Cormier, Thomas Michael; Corrales Morales, Yasser; Cortese, Pietro; Cortes Maldonado, Ismael; Cosentino, Mauro Rogerio; Costa, Filippo; Cotallo, Manuel Enrique; Crescio, Elisabetta; Crochet, Philippe; Cruz Alaniz, Emilia; Cruz Albino, Rigoberto; Cuautle, Eleazar; Cunqueiro, Leticia; Czopowicz, Tobiasz Roman; Dainese, Andrea; Dang, Ruina; Danu, Andrea; Das, Indranil; Das, Supriya; Das, Debasish; Das, Kushal; Dash, Sadhana; Dash, Ajay Kumar; De, Sudipan; de Barros, Gabriel; De Caro, Annalisa; de Cataldo, Giacinto; de Cuveland, Jan; De Falco, Alessandro; De Gruttola, Daniele; Delagrange, Hugues; Deloff, Andrzej; De Marco, Nora; Denes, Ervin; De Pasquale, Salvatore; Deppman, Airton; D'Erasmo, Ginevra; de Rooij, Raoul Stefan; Diaz Corchero, Miguel Angel; Di Bari, Domenico; Dietel, Thomas; Di Giglio, Carmelo; Di Liberto, Sergio; Di Mauro, Antonio; Di Nezza, Pasquale; Divia, Roberto; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Dobrowolski, Tadeusz Antoni; Donigus, Benjamin; Dordic, Olja; Dubey, Anand Kumar; Dubla, Andrea; Ducroux, Laurent; Dupieux, Pascal; Dutta Majumdar, AK; Elia, Domenico; Elwood, Brian Gerard; Emschermann, David Philip; Engel, Heiko; Erazmus, Barbara; Erdal, Hege Austrheim; Eschweiler, Dominic; Espagnon, Bruno; Estienne, Magali Danielle; Esumi, Shinichi; Evans, David; Evdokimov, Sergey; Eyyubova, Gyulnara; Fabris, Daniela; Faivre, Julien; Falchieri, Davide; Fantoni, Alessandra; Fasel, Markus; Fehlker, Dominik; Feldkamp, Linus; Felea, Daniel; Feliciello, Alessandro; Fenton-Olsen, Bo; Feofilov, Grigory; Fernandez Tellez, Arturo; Ferretti, Alessandro; Festanti, Andrea; Figiel, Jan; Figueredo, Marcel; Filchagin, Sergey; Finogeev, Dmitry; Fionda, Fiorella; Fiore, Enrichetta Maria; Floratos, Emmanuel; Floris, Michele; Foertsch, Siegfried Valentin; Foka, Panagiota; Fokin, Sergey; Fragiacomo, Enrico; Francescon, Andrea; Frankenfeld, Ulrich Michael; Fuchs, Ulrich; Furget, Christophe; Fusco Girard, Mario; Gaardhoje, Jens Joergen; Gagliardi, Martino; Gago, Alberto; Gallio, Mauro; Gangadharan, Dhevan Raja; Ganoti, Paraskevi; Garabatos, Jose; Garcia-Solis, Edmundo; Gargiulo, Corrado; Garishvili, Irakli; Gerhard, Jochen; Germain, Marie; Gheata, Mihaela; Gheata, Andrei George; Ghidini, Bruno; Ghosh, Premomoy; Gianotti, Paola; Giubellino, Paolo; Gladysz-Dziadus, Ewa; Glassel, Peter; Goerlich, Lidia; Gomez, Ramon; Gonzalez Ferreiro, Elena; Gonzalez-Zamora, Pedro; Gorbunov, Sergey; Goswami, Ankita; Gotovac, Sven; Graczykowski, Lukasz Kamil; Grajcarek, Robert; Grelli, Alessandro; Grigoras, Alina Gabriela; Grigoras, Costin; Grigoriev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grinyov, Boris; Grion, Nevio; Gros, Philippe; Grosse-Oetringhaus, Jan Fiete; Grossiord, Jean-Yves; Grosso, Raffaele; Guber, Fedor; Guernane, Rachid; Guerzoni, Barbara; Guilbaud, Maxime Rene Joseph; Gulbrandsen, Kristjan Herlache; Gulkanyan, Hrant; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Haake, Rudiger; Haaland, Oystein Senneset; Hadjidakis, Cynthia Marie; Haiduc, Maria; Hamagaki, Hideki; Hamar, Gergoe; Han, Byounghee; Hanratty, Luke David; Hansen, Alexander; Harris, John William; Harton, Austin; Hatzifotiadou, Despoina; Hayashi, Shinichi; Hayrapetyan, Arsen; Heckel, Stefan Thomas; Heide, Markus Ansgar; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Herrmann, Norbert; Hess, Benjamin Andreas; Hetland, Kristin Fanebust; Hicks, Bernard; Hippolyte, Boris; Hori, Yasuto; Hristov, Peter Zahariev; Hrivnacova, Ivana; Huang, Meidana; Humanic, Thomas; Hutter, Dirk; Hwang, Dae Sung; Ichou, Raphaelle; Ilkaev, Radiy; Ilkiv, Iryna; Inaba, Motoi; Incani, Elisa; Innocenti, Pier Giorgio; Innocenti, Gian Michele; Ionita, Costin; Ippolitov, Mikhail; Irfan, Muhammad; Ivanov, Andrey; Ivanov, Vladimir; Ivanov, Marian; Ivanytskyi, Oleksii; Jacholkowski, Adam Wlodzimierz; Jacobs, Peter; Jahnke, Cristiane; Jang, Haeng Jin; Janik, Malgorzata Anna; Jayarathna, Sandun; Jena, Satyajit; Jha, Deeptanshu Manu; Jimenez Bustamante, Raul Tonatiuh; Jones, Peter Graham; Jung, Hyung Taik; Jusko, Anton; Kaidalov, Alexei; Kalcher, Sebastian; Kalinak, Peter; Kalliokoski, Tuomo Esa Aukusti; Kalweit, Alexander Philipp; Kang, Ju Hwan; Kaplin, Vladimir; Kar, Somnath; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karpechev, Evgeny; Kazantsev, Andrey; Kebschull, Udo Wolfgang; Keidel, Ralf; Ketzer, Bernhard Franz; Khan, Kamal Hussain; Khan, Palash; Khan, Shuaib Ahmad; Khan, Mohisin Mohammed; Khanzadeev, Alexei; Kharlov, Yury; Kileng, Bjarte; Kim, Jonghyun; Kim, Jin Sook; Kim, Taesoo; Kim, Mimae; Kim, Minwoo; Kim, Dong Jo; Kim, Se Yong; Kim, Beomkyu; Kim, Do Won; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Kiss, Gabor; Klay, Jennifer Lynn; Klein, Jochen; Klein-Bosing, Christian; Kliemant, Michael; Kluge, Alexander; Knichel, Michael Linus; Knospe, Anders Garritt; Kohler, Markus; Kollegger, Thorsten; Kolojvari, Anatoly; Kompaniets, Mikhail; Kondratiev, Valery; Kondratyeva, Natalia; Konevskih, Artem; Kovalenko, Vladimir; Kowalski, Marek; Kox, Serge; Koyithatta Meethaleveedu, Greeshma; Kral, Jiri; Kralik, Ivan; Kramer, Frederick; Kravcakova, Adela; Krelina, Michal; Kretz, Matthias; Krivda, Marian; Krizek, Filip; Krus, Miroslav; Kryshen, Evgeny; Krzewicki, Mikolaj; Kucera, Vit; Kucheriaev, Yury; Kugathasan, Thanushan; Kuhn, Christian Claude; Kuijer, Paul; Kulakov, Igor; Kumar, Jitendra; Kurashvili, Podist; Kurepin, A; Kurepin, AB; Kuryakin, Alexey; Kushpil, Vasily; Kushpil, Svetlana; Kvaerno, Henning; Kweon, Min Jung; Kwon, Youngil; Ladron de Guevara, Pedro; Lagana Fernandes, Caio; Lakomov, Igor; Langoy, Rune; La Pointe, Sarah Louise; Lara, Camilo Ernesto; Lardeux, Antoine Xavier; La Rocca, Paola; Lea, Ramona; Lechman, Mateusz; Lee, Sung Chul; Lee, Graham Richard; Legrand, Iosif; Lehnert, Joerg Walter; Lemmon, Roy Crawford; Lenhardt, Matthieu Laurent; Lenti, Vito; Leon, Hermes; Leoncino, Marco; Leon Monzon, Ildefonso; Levai, Peter; Li, Shuang; Lien, Jorgen; Lietava, Roman; Lindal, Svein; Lindenstruth, Volker; Lippmann, Christian; Lisa, Michael Annan; Ljunggren, Hans Martin; Lodato, Davide Francesco; Loenne, Per-Ivar; Loggins, Vera; Loginov, Vitaly; Lohner, Daniel; Loizides, Constantinos; Loo, Kai Krister; Lopez, Xavier Bernard; Lopez Torres, Ernesto; Lovhoiden, Gunnar; Lu, Xianguo; Luettig, Philipp; Lunardon, Marcello; Luo, Jiebin; Luparello, Grazia; Luzzi, Cinzia; Ma, Rongrong; Ma, Ke; Madagodahettige-Don, Dilan Minthaka; Maevskaya, Alla; Mager, Magnus; Mahapatra, Durga Prasad; Maire, Antonin; Malaev, Mikhail; Maldonado Cervantes, Ivonne Alicia; Malinina, Ludmila; Mal'Kevich, Dmitry; Malzacher, Peter; Mamonov, Alexander; Manceau, Loic Henri Antoine; Mangotra, Lalit Kumar; Manko, Vladislav; Manso, Franck; Manzari, Vito; Marchisone, Massimiliano; Mares, Jiri; Margagliotti, Giacomo Vito; Margotti, Anselmo; Marin, Ana Maria; Markert, Christina; Marquard, Marco; Martashvili, Irakli; Martin, Nicole Alice; Martin Blanco, Javier; Martinengo, Paolo; Martinez, Mario Ivan; Martinez Garcia, Gines; Martynov, Yevgen; Mas, Alexis Jean-Michel; Masciocchi, Silvia; Masera, Massimo; Masoni, Alberto; Massacrier, Laure Marie; Mastroserio, Annalisa; Matyja, Adam Tomasz; Mayer, Christoph; Mazer, Joel; Mazumder, Rakesh; Mazzoni, Alessandra Maria; Meddi, Franco; Menchaca-Rocha, Arturo Alejandro; Mercado Perez, Jorge; Meres, Michal; Miake, Yasuo; Mikhaylov, Konstantin; Milano, Leonardo; Milosevic, Jovan; Mischke, Andre; Mishra, Aditya Nath; Miskowiec, Dariusz; Mitu, Ciprian Mihai; Mlynarz, Jocelyn; Mohanty, Bedangadas; Molnar, Levente; Montano Zetina, Luis Manuel; Monteno, Marco; Montes, Esther; Moon, Taebong; Morando, Maurizio; Moreira De Godoy, Denise Aparecida; Moretto, Sandra; Morreale, Astrid; Morsch, Andreas; Muccifora, Valeria; Mudnic, Eugen; Muhuri, Sanjib; Mukherjee, Maitreyee; Muller, Hans; Munhoz, Marcelo; Murray, Sean; Musa, Luciano; Musinsky, Jan; Nandi, Basanta Kumar; Nania, Rosario; Nappi, Eugenio; Nasar, Mahmoud; Nattrass, Christine; Nayak, Tapan Kumar; Nazarenko, Sergey; Nedosekin, Alexander; Nicassio, Maria; Niculescu, Mihai; Nielsen, Borge Svane; Nikolaev, Sergey; Nikolic, Vedran; Nikulin, Sergey; Nikulin, Vladimir; Nilsen, Bjorn Steven; Nilsson, Mads Stormo; Noferini, Francesco; Nomokonov, Petr; Nooren, Gerardus; Nyanin, Alexandre; Nyatha, Anitha; Nygaard, Casper; Nystrand, Joakim Ingemar; Ochirov, Alexander; Oeschler, Helmut Oskar; Oh, Saehanseul; Oh, Sun Kun; Olah, Laszlo; Oleniacz, Janusz; Oliveira Da Silva, Antonio Carlos; 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Watanabe, Daisuke; Weber, Michael; Wessels, Johannes; Westerhoff, Uwe; Wiechula, Jens; Wielanek, Daniel; Wikne, Jon; Wilde, Martin Rudolf; Wilk, Grzegorz Andrzej; Wilkinson, Jeremy; Williams, Crispin; Windelband, Bernd Stefan; Winn, Michael Winn; Xiang, Changzhou; Yaldo, Chris G; Yamaguchi, Yorito; Yang, Hongyan; Yang, Shiming; Yang, Ping; Yano, Satoshi; Yasnopolsky, Stanislav; Yi, JunGyu; Yin, Zhongbao; Yoo, In-Kwon; Yoon, Jongik; Yushmanov, Igor; Zaccolo, Valentina; Zach, Cenek; Zampolli, Chiara; Zaporozhets, Sergey; Zarochentsev, Andrey; Zavada, Petr; Zaviyalov, Nikolai; Zbroszczyk, Hanna Paulina; Zelnicek, Pierre; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhang, Fan; Zhang, Yonghong; Zhou, Daicui; Zhou, Fengchu; Zhou, You; Zhu, Hongsheng; Zhu, Xiangrong; Zhu, Jianlin; Zhu, Jianhui; Zichichi, Antonino; Zimmermann, Alice; Zinovjev, Gennady; Zoccarato, Yannick Denis; Zynovyev, Mykhaylo; Zyzak, Maksym

    2013-01-01

    We present the measurements of particle pair yields per trigger particle obtained from di-hadron azimuthal correlations in pp collisions at $\\sqrt{s}$=0.9, 2.76, and 7 TeV recorded with the ALICE detector. The yields are studied as a function of the charged particle multiplicity. Taken together with the single particle yields the pair yields provide information about parton fragmentation at low transverse momenta, as well as on the contribution of multiple parton interactions to particle production. Data are compared to calculations using Pythia6, Pythia8, and Phojet event generators.

  2. EVALUATION OF LAND USE/LAND COVER DATASETS FOR URBAN WATERSHED MODELING

    International Nuclear Information System (INIS)

    S.J. BURIAN; M.J. BROWN; T.N. MCPHERSON

    2001-01-01

    Land use/land cover (LULC) data are a vital component for nonpoint source pollution modeling. Most watershed hydrology and pollutant loading models use, in some capacity, LULC information to generate runoff and pollutant loading estimates. Simple equation methods predict runoff and pollutant loads using runoff coefficients or pollutant export coefficients that are often correlated to LULC type. Complex models use input variables and parameters to represent watershed characteristics and pollutant buildup and washoff rates as a function of LULC type. Whether using simple or complex models an accurate LULC dataset with an appropriate spatial resolution and level of detail is paramount for reliable predictions. The study presented in this paper compared and evaluated several LULC dataset sources for application in urban environmental modeling. The commonly used USGS LULC datasets have coarser spatial resolution and lower levels of classification than other LULC datasets. In addition, the USGS datasets do not accurately represent the land use in areas that have undergone significant land use change during the past two decades. We performed a watershed modeling analysis of three urban catchments in Los Angeles, California, USA to investigate the relative difference in average annual runoff volumes and total suspended solids (TSS) loads when using the USGS LULC dataset versus using a more detailed and current LULC dataset. When the two LULC datasets were aggregated to the same land use categories, the relative differences in predicted average annual runoff volumes and TSS loads from the three catchments were 8 to 14% and 13 to 40%, respectively. The relative differences did not have a predictable relationship with catchment size

  3. Magnetic resonance spectroscopy of normal appearing white matter in early relapsing-remitting multiple sclerosis: correlations between disability and spectroscopy

    Directory of Open Access Journals (Sweden)

    Foronda Jesus

    2004-06-01

    Full Text Available Abstract Background What currently appears to be irreversible axonal loss in normal appearing white matter, measured by proton magnetic resonance spectroscopy is of great interest in the study of Multiple Sclerosis. Our aim is to determine the axonal damage in normal appearing white matter measured by magnetic resonance spectroscopy and to correlate this with the functional disability measured by Multiple Sclerosis Functional Composite scale, Neurological Rating Scale, Ambulation Index scale, and Expanded Disability Scale Score. Methods Thirty one patients (9 male and 22 female with relapsing remitting Multiple Sclerosis and a Kurtzke Expanded Disability Scale Score of 0–5.5 were recruited from four hospitals in Andalusia, Spain and included in the study. Magnetic resonance spectroscopy scans and neurological disability assessments were performed the same day. Results A statistically significant correlation was found (r = -0.38 p Conclusions There is correlation between disability (measured by Expanded Disability Scale Score and the NAA/Cr ratio in normal appearing white matter. The lack of correlation between the NAA/Cr ratio and the Multiple Sclerosis Functional Composite score indicates that the Multiple Sclerosis Functional Composite is not able to measure irreversible disability and would be more useful as a marker in stages where axonal damage is not a predominant factor.

  4. Advanced Neuropsychological Diagnostics Infrastructure (ANDI: A Normative Database Created from Control Datasets.

    Directory of Open Access Journals (Sweden)

    Nathalie R. de Vent

    2016-10-01

    Full Text Available In the Advanced Neuropsychological Diagnostics Infrastructure (ANDI, datasets of several research groups are combined into a single database, containing scores on neuropsychological tests from healthy participants. For most popular neuropsychological tests the quantity and range of these data surpasses that of traditional normative data, thereby enabling more accurate neuropsychological assessment. Because of the unique structure of the database, it facilitates normative comparison methods that were not feasible before, in particular those in which entire profiles of scores are evaluated. In this article, we describe the steps that were necessary to combine the separate datasets into a single database. These steps involve matching variables from multiple datasets, removing outlying values, determining the influence of demographic variables, and finding appropriate transformations to normality. Also, a brief description of the current contents of the ANDI database is given.

  5. An innovative privacy preserving technique for incremental datasets on cloud computing.

    Science.gov (United States)

    Aldeen, Yousra Abdul Alsahib S; Salleh, Mazleena; Aljeroudi, Yazan

    2016-08-01

    Cloud computing (CC) is a magnificent service-based delivery with gigantic computer processing power and data storage across connected communications channels. It imparted overwhelming technological impetus in the internet (web) mediated IT industry, where users can easily share private data for further analysis and mining. Furthermore, user affable CC services enable to deploy sundry applications economically. Meanwhile, simple data sharing impelled various phishing attacks and malware assisted security threats. Some privacy sensitive applications like health services on cloud that are built with several economic and operational benefits necessitate enhanced security. Thus, absolute cyberspace security and mitigation against phishing blitz became mandatory to protect overall data privacy. Typically, diverse applications datasets are anonymized with better privacy to owners without providing all secrecy requirements to the newly added records. Some proposed techniques emphasized this issue by re-anonymizing the datasets from the scratch. The utmost privacy protection over incremental datasets on CC is far from being achieved. Certainly, the distribution of huge datasets volume across multiple storage nodes limits the privacy preservation. In this view, we propose a new anonymization technique to attain better privacy protection with high data utility over distributed and incremental datasets on CC. The proficiency of data privacy preservation and improved confidentiality requirements is demonstrated through performance evaluation. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Quantum correlation approach to criticality in the XX spin chain with multiple interaction

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, W.W., E-mail: weien.cheng@gmail.com [Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunication, Nanjing 210003 (China); Department of Physics, Hubei Normal University, Huangshi 435002 (China); Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education (China); Shan, C.J. [Department of Physics, Hubei Normal University, Huangshi 435002 (China); Sheng, Y.B.; Gong, L.Y.; Zhao, S.M. [Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunication, Nanjing 210003 (China); Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education (China)

    2012-09-01

    We investigate the quantum critical behavior in the XX spin chain with a XZY-YZX type multiple interaction by means of quantum correlation (Concurrence C, quantum discord D{sub Q} and geometric discord D{sub G}). Around the critical point, the values of these quantum correlations and corresponding derivatives are investigated numerically and analytically. The results show that the non-analyticity property of the concurrence cannot signal well the quantum phase transition, but both the quantum discord and geometric discord can characterize the critical behavior in such model exactly.

  7. Respiratory correlated cone beam CT

    International Nuclear Information System (INIS)

    Sonke, Jan-Jakob; Zijp, Lambert; Remeijer, Peter; Herk, Marcel van

    2005-01-01

    A cone beam computed tomography (CBCT) scanner integrated with a linear accelerator is a powerful tool for image guided radiotherapy. Respiratory motion, however, induces artifacts in CBCT, while the respiratory correlated procedures, developed to reduce motion artifacts in axial and helical CT are not suitable for such CBCT scanners. We have developed an alternative respiratory correlated procedure for CBCT and evaluated its performance. This respiratory correlated CBCT procedure consists of retrospective sorting in projection space, yielding subsets of projections that each corresponds to a certain breathing phase. Subsequently, these subsets are reconstructed into a four-dimensional (4D) CBCT dataset. The breathing signal, required for respiratory correlation, was directly extracted from the 2D projection data, removing the need for an additional respiratory monitor system. Due to the reduced number of projections per phase, the contrast-to-noise ratio in a 4D scan reduced by a factor 2.6-3.7 compared to a 3D scan based on all projections. Projection data of a spherical phantom moving with a 3 and 5 s period with and without simulated breathing irregularities were acquired and reconstructed into 3D and 4D CBCT datasets. The positional deviations of the phantoms center of gravity between 4D CBCT and fluoroscopy were small: 0.13±0.09 mm for the regular motion and 0.39±0.24 mm for the irregular motion. Motion artifacts, clearly present in the 3D CBCT datasets, were substantially reduced in the 4D datasets, even in the presence of breathing irregularities, such that the shape of the moving structures could be identified more accurately. Moreover, the 4D CBCT dataset provided information on the 3D trajectory of the moving structures, absent in the 3D data. Considerable breathing irregularities, however, substantially reduces the image quality. Data presented for three different lung cancer patients were in line with the results obtained from the phantom study. In

  8. Multiplicity and transverse momentum dependence of two- and four-particle correlations in pPb and PbPb collisions

    Energy Technology Data Exchange (ETDEWEB)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C. -E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Luyckx, S.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Staykova, Z.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; DʼHondt, J.; Kalogeropoulos, A.; Keaveney, J.; Maes, M.; Olbrechts, A.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Clerbaux, B.; De Lentdecker, G.; Favart, L.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Dildick, S.; Garcia, G.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jez, P.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Popov, A.; Selvaggi, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins Junior, M.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Malek, M.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Asawatangtrakuldee, C.; Ban, Y.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, D.; Zhang, L.; Zou, W.; Avila, C.; Carrillo Montoya, C. A.; Chaparro Sierra, L. F.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Mekterovic, D.; Morovic, S.; Tikvica, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Mahmoud, M. A.; Mahrous, A.; Radi, A.; Kadastik, M.; Müntel, M.; Murumaa, M.; Raidal, M.; Rebane, L.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. 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B.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Novgorodova, O.; Nowak, F.; Olzem, J.; Perrey, H.; Petrukhin, A.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Riedl, C.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Schmidt, R.; Schoerner-Sadenius, T.; Sen, N.; Stein, M.; Walsh, R.; Wissing, C.; Blobel, V.; Enderle, H.; Erfle, J.; Garutti, E.; Gebbert, U.; Görner, M.; Gosselink, M.; Haller, J.; Heine, K.; Höing, R. S.; Kaussen, G.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Marchesini, I.; Peiffer, T.; Pietsch, N.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Schröder, M.; Schum, T.; Seidel, M.; Sibille, J.; Sola, V.; Stadie, H.; Steinbrück, G.; Thomsen, J.; Troendle, D.; Usai, E.; Vanelderen, L.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Guthoff, M.; Hartmann, F.; Hauth, T.; Held, H.; Hoffmann, K. H.; Husemann, U.; Katkov, I.; Komaragiri, J. R.; Kornmayer, A.; Lobelle Pardo, P.; Martschei, D.; Müller, Th.; Niegel, M.; Nürnberg, A.; Oberst, O.; Ott, J.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Röcker, S.; Schilling, F. -P.; Schott, G.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Zeise, M.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Kesisoglou, S.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Ntomari, E.; Gouskos, L.; Mertzimekis, T. J.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Radics, B.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Karancsi, J.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Beri, S. B.; Bhatnagar, V.; Dhingra, N.; Gupta, R.; Kaur, M.; Mehta, M. Z.; Mittal, M.; Nishu, N.; Saini, L. K.; Sharma, A.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Saxena, P.; Sharma, V.; Shivpuri, R. K.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Modak, A.; Mukherjee, S.; Roy, D.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Chatterjee, R. M.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Banerjee, S.; Dugad, S.; Arfaei, H.; Bakhshiansohi, H.; Etesami, S. M.; Fahim, A.; Hesari, H.; Jafari, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Paktinat Mehdiabadi, S.; Safarzadeh, B.; Zeinali, M.; Grunewald, M.; Abbrescia, M.; Barbone, L.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Marangelli, B.; My, S.; Nuzzo, S.; Pacifico, N.; Pompili, A.; Pugliese, G.; Selvaggi, G.; Silvestris, L.; Singh, G.; Venditti, R.; Verwilligen, P.; Zito, G.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Meneghelli, M.; Montanari, A.; Navarria, F. L.; Odorici, F.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; DʼAlessandro, R.; Focardi, E.; Frosali, S.; Gallo, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Fabbricatore, P.; Musenich, R.; Tosi, S.; Benaglia, A.; De Guio, F.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Cosa, A.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dorigo, T.; Dosselli, U.; Galanti, M.; Gasparini, F.; Gasparini, U.; Giubilato, P.; Gonella, F.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Lazzizzera, I.; Margoni, M.; Meneguzzo, A. T.; Montecassiano, F.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Sgaravatto, M.; Simonetto, F.; Torassa, E.; Tosi, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Riccardi, C.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Nappi, A.; Romeo, F.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; DʼAgnolo, R. T.; DellʼOrso, R.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Kraan, A.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-navarro, A.; Serban, A. 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V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Demiyanov, A.; Ershov, A.; Gribushin, A.; Kodolova, O.; Korotkikh, V.; Lokhtin, I.; Markina, A.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Vardanyan, I.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Krpic, D.; Milosevic, J.; Aguilar-Benitez, M.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Ferrando, A.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Merino, G.; Navarro De Martino, E.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Santaolalla, J.; Soares, M. S.; Willmott, C.; Albajar, C.; de Trocóniz, J. F.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Lloret Iglesias, L.; Piedra Gomez, J.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Chuang, S. H.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Gonzalez Sanchez, J.; Graziano, A.; Jorda, C.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Bendavid, J.; Benitez, J. F.; Bernet, C.; Bianchi, G.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Christiansen, T.; Coarasa Perez, J. A.; Colafranceschi, S.; dʼEnterria, D.; Dabrowski, A.; David, A.; De Roeck, A.; De Visscher, S.; Di Guida, S.; Dobson, M.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Funk, W.; Georgiou, G.; Giffels, M.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Giunta, M.; Glege, F.; Gomez-Reino Garrido, R.; Gowdy, S.; Guida, R.; Hammer, J.; Hansen, M.; Harris, P.; Hartl, C.; Hinzmann, A.; Innocente, V.; Janot, P.; Karavakis, E.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lee, Y. -J.; Lourenço, C.; Magini, N.; Malberti, M.; Malgeri, L.; Mannelli, M.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moser, R.; Mulders, M.; Musella, P.; Nesvold, E.; Orsini, L.; Palencia Cortezon, E.; Perez, E.; Perrozzi, L.; Petrilli, A.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Quertenmont, L.; Racz, A.; Reece, W.; Rolandi, G.; Rovere, M.; Sakulin, H.; Santanastasio, F.; Schäfer, C.; Schwick, C.; Segoni, I.; Sekmen, S.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Stoye, M.; Tsirou, A.; Veres, G. I.; Vlimant, J. R.; Wöhri, H. K.; Worm, S. D.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Gabathuler, K.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; König, S.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Bortignon, P.; Buchmann, M. A.; Casal, B.; Chanon, N.; Deisher, A.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Freudenreich, K.; Grab, C.; Hits, D.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Mohr, N.; Moortgat, F.; Nägeli, C.; Nef, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pape, L.; Pauss, F.; Peruzzi, M.; Ronga, F. J.; Rossini, M.; Sala, L.; Sanchez, A. K.; Starodumov, A.; Stieger, B.; Takahashi, M.; Tauscher, L.; Thea, A.; Theofilatos, K.; Treille, D.; Urscheler, C.; Wallny, R.; Weber, H. A.; Amsler, C.; Chiochia, V.; Favaro, C.; Ivova Rikova, M.; Kilminster, B.; Millan Mejias, B.; Otiougova, P.; Robmann, P.; Snoek, H.; Taroni, S.; Tupputi, S.; Verzetti, M.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Li, S. W.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Bartalini, P.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Dietz, C.; Grundler, U.; Hou, W. -S.; Hsiung, Y.; Kao, K. Y.; Lei, Y. J.; Lu, R. -S.; Majumder, D.; Petrakou, E.; Shi, X.; Shiu, J. G.; Tzeng, Y. M.; Wang, M.; Asavapibhop, B.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sogut, K.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Aliev, T.; Bilin, B.; Bilmis, S.; Deniz, M.; Gamsizkan, H.; Guler, A. M.; Karapinar, G.; Ocalan, K.; Ozpineci, A.; Serin, M.; Sever, R.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Isildak, B.; Kaya, M.; Kaya, O.; Ozkorucuklu, S.; Sonmez, N.; Bahtiyar, H.; Barlas, E.; Cankocak, K.; Günaydin, Y. O.; Vardarlı, F. I.; Yücel, M.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Frazier, R.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Kreczko, L.; Metson, S.; Newbold, D. M.; Nirunpong, K.; Poll, A.; Senkin, S.; Smith, V. J.; Williams, T.; Basso, L.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Jackson, J.; Olaiya, E.; Petyt, D.; Radburn-Smith, B. C.; Shepherd-Themistocleous, C. H.; Tomalin, I. R.; Womersley, W. J.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Ferguson, W.; Fulcher, J.; Futyan, D.; Gilbert, A.; Guneratne Bryer, A.; Hall, G.; Hatherell, Z.; Hays, J.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A. -M.; Marrouche, J.; Mathias, B.; Nandi, R.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Pioppi, M.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Sparrow, A.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Wakefield, S.; Wardle, N.; Whyntie, T.; Chadwick, M.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Heister, A.; Lawson, P.; Lazic, D.; Rohlf, J.; Sperka, D.; St. John, J.; Sulak, L.; Alimena, J.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Houtz, R.; Ko, W.; Kopecky, A.; Lander, R.; Mall, O.; Miceli, T.; Nelson, R.; Pellett, D.; Ricci-Tam, F.; Rutherford, B.; Searle, M.; Smith, J.; Squires, M.; Tripathi, M.; Wilbur, S.; Yohay, R.; Andreev, V.; Cline, D.; Cousins, R.; Erhan, S.; Everaerts, P.; Farrell, C.; Felcini, M.; Hauser, J.; Ignatenko, M.; Jarvis, C.; Rakness, G.; Schlein, P.; Takasugi, E.; Traczyk, P.; Valuev, V.; Weber, M.; Babb, J.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Liu, H.; Long, O. R.; Luthra, A.; Nguyen, H.; Paramesvaran, S.; Sturdy, J.; Sumowidagdo, S.; Wilken, R.; Wimpenny, S.; Andrews, W.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Evans, D.; Holzner, A.; Kelley, R.; Lebourgeois, M.; Letts, J.; Macneill, I.; Padhi, S.; Palmer, C.; Petrucciani, G.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Wasserbaech, S.; Würthwein, F.; Yagil, A.; Yoo, J.; Barge, D.; Bellan, R.; Campagnari, C.; DʼAlfonso, M.; Danielson, T.; Flowers, K.; Geffert, P.; George, C.; Golf, F.; Incandela, J.; Justus, C.; Kalavase, P.; Kovalskyi, D.; Krutelyov, V.; Lowette, S.; Magaña Villalba, R.; Mccoll, N.; Pavlunin, V.; Ribnik, J.; Richman, J.; Rossin, R.; Stuart, D.; To, W.; West, C.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Di Marco, E.; Duarte, J.; Kcira, D.; Ma, Y.; Mott, A.; Newman, H. B.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Veverka, J.; Wilkinson, R.; Xie, S.; Yang, Y.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carroll, R.; Ferguson, T.; Iiyama, Y.; Jang, D. W.; Liu, Y. F.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Drell, B. R.; Ford, W. T.; Gaz, A.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Eggert, N.; Gibbons, L. K.; Hopkins, W.; Khukhunaishvili, A.; Kreis, B.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Burkett, K.; Butler, J. N.; Chetluru, V.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Gottschalk, E.; Gray, L.; Green, D.; Gutsche, O.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kunori, S.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Newman-Holmes, C.; OʼDell, V.; Prokofyev, O.; Ratnikova, N.; Sexton-Kennedy, E.; Sharma, S.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitmore, J.; Wu, W.; Yang, F.; Yun, J. C.; Acosta, D.; Avery, P.; Bourilkov, D.; Chen, M.; Cheng, T.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Dobur, D.; Drozdetskiy, A.; Field, R. D.; Fisher, M.; Fu, Y.; Furic, I. K.; Hugon, J.; Kim, B.; Konigsberg, J.; Korytov, A.; Kropivnitskaya, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Remington, R.; Rinkevicius, A.; Skhirtladze, N.; Snowball, M.; Yelton, J.; Zakaria, M.; Gaultney, V.; Hewamanage, S.; Lebolo, L. M.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Chen, J.; Diamond, B.; Gleyzer, S. V.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Dorney, B.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Betts, R. R.; Bucinskaite, I.; Callner, J.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Lacroix, F.; Moon, D. H.; OʼBrien, C.; Silkworth, C.; Strom, D.; Turner, P.; Varelas, N.; Akgun, U.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Griffiths, S.; Merlo, J. -P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Newsom, C. R.; Ogul, H.; Onel, Y.; Ozok, F.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Giurgiu, G.; Gritsan, A. V.; Hu, G.; Maksimovic, P.; Swartz, M.; Whitbeck, A.; Baringer, P.; Bean, A.; Benelli, G.; Kenny III, R. P.; Murray, M.; Noonan, D.; Sanders, S.; Stringer, R.; Wang, Q.; Wood, J. S.; Barfuss, A. F.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Shrestha, S.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Peterman, A.; Skuja, A.; Temple, J.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Dutta, V.; Gomez Ceballos, G.; Goncharov, M.; Kim, Y.; Klute, M.; Lai, Y. S.; Levin, A.; Luckey, P. D.; Ma, T.; Nahn, S.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Wolf, R.; Wyslouch, B.; Yang, M.; Yilmaz, Y.; Yoon, A. S.; Zanetti, M.; Zhukova, V.; Dahmes, B.; De Benedetti, A.; Franzoni, G.; Gude, A.; Haupt, J.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Sasseville, M.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Cremaldi, L. M.; Kroeger, R.; Perera, L.; Rahmat, R.; Sanders, D. A.; Summers, D.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Eads, M.; Gonzalez Suarez, R.; Keller, J.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Dolen, J.; Godshalk, A.; Iashvili, I.; Jain, S.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Wan, Z.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Nash, D.; Orimoto, T.; Trocino, D.; Wood, D.; Zhang, J.; Anastassov, A.; Hahn, K. A.; Kubik, A.; Lusito, L.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Berry, D.; Brinkerhoff, A.; Chan, K. M.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kolb, J.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Morse, D. M.; Pearson, T.; Planer, M.; Ruchti, R.; Slaunwhite, J.; Valls, N.; Wayne, M.; Wolf, M.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Vuosalo, C.; Williams, G.; Winer, B. L.; Wolfe, H.; Berry, E.; Elmer, P.; Halyo, V.; Hebda, P.; Hegeman, J.; Hunt, A.; Jindal, P.; Koay, S. A.; Lopes Pegna, D.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Raval, A.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zenz, S. C.; Zuranski, A.; Brownson, E.; Lopez, A.; Mendez, H.; Ramirez Vargas, J. E.; Alagoz, E.; Benedetti, D.; Bolla, G.; Bortoletto, D.; De Mattia, M.; Everett, A.; Hu, Z.; Jones, M.; Jung, K.; Koybasi, O.; Kress, M.; Leonardo, N.; Maroussov, V.; Merkel, P.; Miller, D. H.; Neumeister, N.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Vidal Marono, M.; Wang, F.; Xu, L.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Guragain, S.; Parashar, N.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Miner, D. C.; Petrillo, G.; Vishnevskiy, D.; Zielinski, M.; Bhatti, A.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Malik, S.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Rekovic, V.; Robles, J.; Salur, S.; Schnetzer, S.; Seitz, C.; Somalwar, S.; Stone, R.; Thomas, S.; Walker, M.; Cerizza, G.; Hollingsworth, M.; Rose, K.; Spanier, S.; Yang, Z. C.; York, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Safonov, A.; Sakuma, T.; Suarez, I.; Tatarinov, A.; Toback, D.; Akchurin, N.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Jeong, C.; Kovitanggoon, K.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Lin, C.; Neu, C.; Wood, J.; Gollapinni, S.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sakharov, A.; Belknap, D. A.; Borrello, L.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Friis, E.; Grothe, M.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Kaadze, K.; Klabbers, P.; Klukas, J.; Lanaro, A.; Loveless, R.; Mohapatra, A.; Mozer, M. U.; Ojalvo, I.; Pierro, G. A.; Polese, G.; Ross, I.; Savin, A.; Smith, W. H.; Swanson, J.

    2013-07-01

    Measurements of two- and four-particle angular correlations for charged particles emitted in pPb collisions are presented over a wide range in pseudorapidity and full azimuth. The data, corresponding to an integrated luminosity of approximately 31 inverse nanobarns, were collected during the 2013 LHC pPb run at a nucleon-nucleon center-of-mass energy of 5.02 TeV by the CMS experiment. The results are compared to 2.76 TeV semi-peripheral PbPb collision data, collected during the 2011 PbPb run, covering a similar range of particle multiplicities. The observed correlations are characterized by the near-side (abs(Delta(phi)~0) associated pair yields and the azimuthal anisotropy Fourier harmonics (v[n]). The second-order (v[2]) and third-order (v[3]) anisotropy harmonics are extracted using the two-particle azimuthal correlation technique. A four-particle correlation method is also applied to obtain the value of v[2] and further explore the multi-particle nature of the correlations. Both associated pair yields and anisotropy harmonics are studied as a function of particle multiplicity and transverse momentum. The associated pair yields, the four-particle v[2], and the v[3] become apparent at about the same multiplicity. A remarkable similarity in the v[3] signal as a function of multiplicity is observed between the pPb and PbPb systems. Predictions based on the color glass condensate and hydrodynamic models are compared to the experimental results.

  9. Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient

    Science.gov (United States)

    Krishnamoorthy, K.; Xia, Yanping

    2008-01-01

    The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…

  10. CoVennTree: A new method for the comparative analysis of large datasets

    Directory of Open Access Journals (Sweden)

    Steffen C. Lott

    2015-02-01

    Full Text Available The visualization of massive datasets, such as those resulting from comparative metatranscriptome analyses or the analysis of microbial population structures using ribosomal RNA sequences, is a challenging task. We developed a new method called CoVennTree (Comparative weighted Venn Tree that simultaneously compares up to three multifarious datasets by aggregating and propagating information from the bottom to the top level and produces a graphical output in Cytoscape. With the introduction of weighted Venn structures, the contents and relationships of various datasets can be correlated and simultaneously aggregated without losing information. We demonstrate the suitability of this approach using a dataset of 16S rDNA sequences obtained from microbial populations at three different depths of the Gulf of Aqaba in the Red Sea. CoVennTree has been integrated into the Galaxy ToolShed and can be directly downloaded and integrated into the user instance.

  11. Visualization of conserved structures by fusing highly variable datasets.

    Science.gov (United States)

    Silverstein, Jonathan C; Chhadia, Ankur; Dech, Fred

    2002-01-01

    Skill, effort, and time are required to identify and visualize anatomic structures in three-dimensions from radiological data. Fundamentally, automating these processes requires a technique that uses symbolic information not in the dynamic range of the voxel data. We were developing such a technique based on mutual information for automatic multi-modality image fusion (MIAMI Fuse, University of Michigan). This system previously demonstrated facility at fusing one voxel dataset with integrated symbolic structure information to a CT dataset (different scale and resolution) from the same person. The next step of development of our technique was aimed at accommodating the variability of anatomy from patient to patient by using warping to fuse our standard dataset to arbitrary patient CT datasets. A standard symbolic information dataset was created from the full color Visible Human Female by segmenting the liver parenchyma, portal veins, and hepatic veins and overwriting each set of voxels with a fixed color. Two arbitrarily selected patient CT scans of the abdomen were used for reference datasets. We used the warping functions in MIAMI Fuse to align the standard structure data to each patient scan. The key to successful fusion was the focused use of multiple warping control points that place themselves around the structure of interest automatically. The user assigns only a few initial control points to align the scans. Fusion 1 and 2 transformed the atlas with 27 points around the liver to CT1 and CT2 respectively. Fusion 3 transformed the atlas with 45 control points around the liver to CT1 and Fusion 4 transformed the atlas with 5 control points around the portal vein. The CT dataset is augmented with the transformed standard structure dataset, such that the warped structure masks are visualized in combination with the original patient dataset. This combined volume visualization is then rendered interactively in stereo on the ImmersaDesk in an immersive Virtual

  12. Relaxation dynamics in the presence of pulse multiplicative noise sources with different correlation properties

    Science.gov (United States)

    Kargovsky, A. V.; Chichigina, O. A.; Anashkina, E. I.; Valenti, D.; Spagnolo, B.

    2015-10-01

    The relaxation dynamics of a system described by a Langevin equation with pulse multiplicative noise sources with different correlation properties is considered. The solution of the corresponding Fokker-Planck equation is derived for Gaussian white noise. Moreover, two pulse processes with regulated periodicity are considered as a noise source: the dead-time-distorted Poisson process and the process with fixed time intervals, which is characterized by an infinite correlation time. We find that the steady state of the system is dependent on the correlation properties of the pulse noise. An increase of the noise correlation causes the decrease of the mean value of the solution at the steady state. The analytical results are in good agreement with the numerical ones.

  13. Mock Quasar-Lyman-α forest data-sets for the SDSS-III Baryon Oscillation Spectroscopic Survey

    Energy Technology Data Exchange (ETDEWEB)

    Bautista, Julian E.; Busca, Nicolas G. [APC, Université Paris Diderot-Paris 7, CNRS/IN2P3, CEA, Observatoire de Paris, 10, rue A. Domon and L. Duquet, Paris (France); Bailey, Stephen; Font-Ribera, Andreu; Schlegel, David [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA (United States); Pieri, Matthew M. [Aix Marseille Université, CNRS, LAM (Laboratoire d' Astrophysique de Marseille) UMR 7326, 38 rue Frédéric Joliot-Curie, 13388, Marseille (France); Miralda-Escudé, Jordi; Gontcho, Satya Gontcho A. [Institut de Ciències del Cosmos, Universitat de Barcelona/IEEC, 1 Martí i Franquès, Barcelona 08028, Catalonia (Spain); Palanque-Delabrouille, Nathalie; Rich, James; Goff, Jean Marc Le [CEA, Centre de Saclay, Irfu/SPP, D128, F-91191 Gif-sur-Yvette (France); Dawson, Kyle [Department of Physics and Astronomy, University of Utah, 115 S 100 E, RM 201, Salt Lake City, UT 84112 (United States); Feng, Yu; Ho, Shirley [McWilliams Center for Cosmology, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213 (United States); Ge, Jian [Department of Astronomy, University of Florida, 211 Bryant Space Science Center, Gainesville, FL 32611-2055 (United States); Noterdaeme, Pasquier; Pâris, Isabelle [Université Paris 6 et CNRS, Institut d' Astrophysique de Paris, 98bis blvd. Arago, 75014 Paris (France); Rossi, Graziano, E-mail: bautista@astro.utah.edu [Department of Astronomy and Space Science, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 143-747 (Korea, Republic of)

    2015-05-01

    We describe mock data-sets generated to simulate the high-redshift quasar sample in Data Release 11 (DR11) of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). The mock spectra contain Lyα forest correlations useful for studying the 3D correlation function including Baryon Acoustic Oscillations (BAO). They also include astrophysical effects such as quasar continuum diversity and high-density absorbers, instrumental effects such as noise and spectral resolution, as well as imperfections introduced by the SDSS pipeline treatment of the raw data. The Lyα forest BAO analysis of the BOSS collaboration, described in Delubac et al. 2014, has used these mock data-sets to develop and cross-check analysis procedures prior to performing the BAO analysis on real data, and for continued systematic cross checks. Tests presented here show that the simulations reproduce sufficiently well important characteristics of real spectra. These mock data-sets will be made available together with the data at the time of the Data Release 11.

  14. Integrative analysis of multiple diverse omics datasets by sparse group multitask regression

    Directory of Open Access Journals (Sweden)

    Dongdong eLin

    2014-10-01

    Full Text Available A variety of high throughput genome-wide assays enable the exploration of genetic risk factors underlying complex traits. Although these studies have remarkable impact on identifying susceptible biomarkers, they suffer from issues such as limited sample size and low reproducibility. Combining individual studies of different genetic levels/platforms has the promise to improve the power and consistency of biomarker identification. In this paper, we propose a novel integrative method, namely sparse group multitask regression, for integrating diverse omics datasets, platforms and populations to identify risk genes/factors of complex diseases. This method combines multitask learning with sparse group regularization, which will: 1 treat the biomarker identification in each single study as a task and then combine them by multitask learning; 2 group variables from all studies for identifying significant genes; 3 enforce sparse constraint on groups of variables to overcome the ‘small sample, but large variables’ problem. We introduce two sparse group penalties: sparse group lasso and sparse group ridge in our multitask model, and provide an effective algorithm for each model. In addition, we propose a significance test for the identification of potential risk genes. Two simulation studies are performed to evaluate the performance of our integrative method by comparing it with conventional meta-analysis method. The results show that our sparse group multitask method outperforms meta-analysis method significantly. In an application to our osteoporosis studies, 7 genes are identified as significant genes by our method and are found to have significant effects in other three independent studies for validation. The most significant gene SOD2 has been identified in our previous osteoporosis study involving the same expression dataset. Several other genes such as TREML2, HTR1E and GLO1 are shown to be novel susceptible genes for osteoporosis, as confirmed

  15. Clinical and MRI correlation in multiple system atrophy

    Energy Technology Data Exchange (ETDEWEB)

    Negoro, Kiyoshi; Morimatsu, Mitsunori (Yamaguchi Univ., Ube (Japan). School of Medicine)

    1994-05-01

    By using magnetic resonance imaging (MRI), we studied 11 patients with multiple system atrophy (MSA): 5 olivo-pontocerebellar atrophy (OPCA), 2 Shy-Drager syndrome (SDS), and 4 striatonigral degeneration (SND). The diagnoses of OPCA, SDS and SND were clinically made. The MR images were performed on 1.5 tesla MRI unit (Siemens Asahi Medical, Magnetom H15), using a T[sub 2]-weighted spin echo (SE) sequence (TR: 2000-3000 ms, TE: 80-90 ms), a T[sub 1]-weighted SE sequence (TR: 550, TE: 15), and a proton density-weighted (PD) SE sequence (TR: 2000-3000, TE: 12-22). In the patients with OPCA, MRI revealed cerebellar and brainstem atrophy and degeneration of pontine transverse fibers more marked than in the patients with SDS and SND. T[sub 2]-weighted images showed low intensity in posterolateral putamina in one OPCA patient and all of SDS and SND patients. PD images demonstrated the abnormal slit-like high signals in posterolateral putamina in three SND. The degree of cerebellar ataxia was not well correlated with cerebellar and brainstem atrophy and degeneration of pontine transverse fibers. There was a positive correlation between the atrophy of cerebellum and brainstem and the duration of cerebellar ataxia. In most of the patients with Parkinsonism, MRI demonstrated abnormal low signals in putamina on T[sub 2]-weighted images. There were positive correlations between the abnormal low signals putamina and the duration and severity of Parkinsonism. Though abnormal low signals in lateral putamina may be seen in normal aging and other disorders on T[sub 2]-weighted images, it is useful to evaluate Parkinsonism in MSA. We believe that the abnormal slit-like high signals in posterolateral putamina in MSA may suggest loss of neurons and gliosis. (author).

  16. Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

    Science.gov (United States)

    Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

    2017-07-15

    This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Quality Controlling CMIP datasets at GFDL

    Science.gov (United States)

    Horowitz, L. W.; Radhakrishnan, A.; Balaji, V.; Adcroft, A.; Krasting, J. P.; Nikonov, S.; Mason, E. E.; Schweitzer, R.; Nadeau, D.

    2017-12-01

    As GFDL makes the switch from model development to production in light of the Climate Model Intercomparison Project (CMIP), GFDL's efforts are shifted to testing and more importantly establishing guidelines and protocols for Quality Controlling and semi-automated data publishing. Every CMIP cycle introduces key challenges and the upcoming CMIP6 is no exception. The new CMIP experimental design comprises of multiple MIPs facilitating research in different focus areas. This paradigm has implications not only for the groups that develop the models and conduct the runs, but also for the groups that monitor, analyze and quality control the datasets before data publishing, before their knowledge makes its way into reports like the IPCC (Intergovernmental Panel on Climate Change) Assessment Reports. In this talk, we discuss some of the paths taken at GFDL to quality control the CMIP-ready datasets including: Jupyter notebooks, PrePARE, LAMP (Linux, Apache, MySQL, PHP/Python/Perl): technology-driven tracker system to monitor the status of experiments qualitatively and quantitatively, provide additional metadata and analysis services along with some in-built controlled-vocabulary validations in the workflow. In addition to this, we also discuss the integration of community-based model evaluation software (ESMValTool, PCMDI Metrics Package, and ILAMB) as part of our CMIP6 workflow.

  18. RARD: The Related-Article Recommendation Dataset

    OpenAIRE

    Beel, Joeran; Carevic, Zeljko; Schaible, Johann; Neusch, Gabor

    2017-01-01

    Recommender-system datasets are used for recommender-system evaluations, training machine-learning algorithms, and exploring user behavior. While there are many datasets for recommender systems in the domains of movies, books, and music, there are rather few datasets from research-paper recommender systems. In this paper, we introduce RARD, the Related-Article Recommendation Dataset, from the digital library Sowiport and the recommendation-as-a-service provider Mr. DLib. The dataset contains ...

  19. Large Scale Flood Risk Analysis using a New Hyper-resolution Population Dataset

    Science.gov (United States)

    Smith, A.; Neal, J. C.; Bates, P. D.; Quinn, N.; Wing, O.

    2017-12-01

    Here we present the first national scale flood risk analyses, using high resolution Facebook Connectivity Lab population data and data from a hyper resolution flood hazard model. In recent years the field of large scale hydraulic modelling has been transformed by new remotely sensed datasets, improved process representation, highly efficient flow algorithms and increases in computational power. These developments have allowed flood risk analysis to be undertaken in previously unmodeled territories and from continental to global scales. Flood risk analyses are typically conducted via the integration of modelled water depths with an exposure dataset. Over large scales and in data poor areas, these exposure data typically take the form of a gridded population dataset, estimating population density using remotely sensed data and/or locally available census data. The local nature of flooding dictates that for robust flood risk analysis to be undertaken both hazard and exposure data should sufficiently resolve local scale features. Global flood frameworks are enabling flood hazard data to produced at 90m resolution, resulting in a mis-match with available population datasets which are typically more coarsely resolved. Moreover, these exposure data are typically focused on urban areas and struggle to represent rural populations. In this study we integrate a new population dataset with a global flood hazard model. The population dataset was produced by the Connectivity Lab at Facebook, providing gridded population data at 5m resolution, representing a resolution increase over previous countrywide data sets of multiple orders of magnitude. Flood risk analysis undertaken over a number of developing countries are presented, along with a comparison of flood risk analyses undertaken using pre-existing population datasets.

  20. FASTQSim: platform-independent data characterization and in silico read generation for NGS datasets.

    Science.gov (United States)

    Shcherbina, Anna

    2014-08-15

    High-throughput next generation sequencing technologies have enabled rapid characterization of clinical and environmental samples. Consequently, the largest bottleneck to actionable data has become sample processing and bioinformatics analysis, creating a need for accurate and rapid algorithms to process genetic data. Perfectly characterized in silico datasets are a useful tool for evaluating the performance of such algorithms. Background contaminating organisms are observed in sequenced mixtures of organisms. In silico samples provide exact truth. To create the best value for evaluating algorithms, in silico data should mimic actual sequencer data as closely as possible. FASTQSim is a tool that provides the dual functionality of NGS dataset characterization and metagenomic data generation. FASTQSim is sequencing platform-independent, and computes distributions of read length, quality scores, indel rates, single point mutation rates, indel size, and similar statistics for any sequencing platform. To create training or testing datasets, FASTQSim has the ability to convert target sequences into in silico reads with specific error profiles obtained in the characterization step. FASTQSim enables users to assess the quality of NGS datasets. The tool provides information about read length, read quality, repetitive and non-repetitive indel profiles, and single base pair substitutions. FASTQSim allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software. In this regard, in silico datasets generated with the FASTQsim tool hold several advantages over natural datasets: they are sequencing platform independent, extremely well characterized, and less expensive to generate. Such datasets are valuable in a number of applications, including the training of assemblers for multiple platforms, benchmarking bioinformatics algorithm performance, and creating challenge

  1. Isfahan MISP Dataset.

    Science.gov (United States)

    Kashefpur, Masoud; Kafieh, Rahele; Jorjandi, Sahar; Golmohammadi, Hadis; Khodabande, Zahra; Abbasi, Mohammadreza; Teifuri, Nilufar; Fakharzadeh, Ali Akbar; Kashefpoor, Maryam; Rabbani, Hossein

    2017-01-01

    An online depository was introduced to share clinical ground truth with the public and provide open access for researchers to evaluate their computer-aided algorithms. PHP was used for web programming and MySQL for database managing. The website was entitled "biosigdata.com." It was a fast, secure, and easy-to-use online database for medical signals and images. Freely registered users could download the datasets and could also share their own supplementary materials while maintaining their privacies (citation and fee). Commenting was also available for all datasets, and automatic sitemap and semi-automatic SEO indexing have been set for the site. A comprehensive list of available websites for medical datasets is also presented as a Supplementary (http://journalonweb.com/tempaccess/4800.584.JMSS_55_16I3253.pdf).

  2. T1- Thresholds in Black Holes Increase Clinical-Radiological Correlation in Multiple Sclerosis Patients.

    Science.gov (United States)

    Thaler, Christian; Faizy, Tobias; Sedlacik, Jan; Holst, Brigitte; Stellmann, Jan-Patrick; Young, Kim Lea; Heesen, Christoph; Fiehler, Jens; Siemonsen, Susanne

    2015-01-01

    Magnetic Resonance Imaging (MRI) is an established tool in diagnosing and evaluating disease activity in Multiple Sclerosis (MS). While clinical-radiological correlations are limited in general, hypointense T1 lesions (also known as Black Holes (BH)) have shown some promising results. The definition of BHs is very heterogeneous and depends on subjective visual evaluation. We aimed to improve clinical-radiological correlations by defining BHs using T1 relaxation time (T1-RT) thresholds to achieve best possible correlation between BH lesion volume and clinical disability. 40 patients with mainly relapsing-remitting MS underwent MRI including 3-dimensional fluid attenuated inversion recovery (FLAIR), magnetization-prepared rapid gradient echo (MPRAGE) before and after Gadolinium (GD) injection and double inversion-contrast magnetization-prepared rapid gradient echo (MP2RAGE) sequences. BHs (BHvis) were marked by two raters on native T1-weighted (T1w)-MPRAGE, contrast-enhancing lesions (CE lesions) on T1w-MPRAGE after GD and FLAIR lesions (total-FLAIR lesions) were detected separately. BHvis and total-FLAIR lesion maps were registered to MP2RAGE images, and the mean T1-RT were calculated for all lesion ROIs. Mean T1 values of the cortex (CTX) were calculated for each patient. Subsequently, Spearman rank correlations between clinical scores (Expanded Disability Status Scale and Multiple Sclerosis Functional Composite) and lesion volume were determined for different T1-RT thresholds. Significant differences in T1-RT were obtained between all different lesion types with highest T1 values in visually marked BHs (BHvis: 1453.3±213.4 ms, total-FLAIR lesions: 1394.33±187.38 ms, CTX: 1305.6±35.8 ms; p1500 ms (Expanded Disability Status Scale vs. lesion volume: rBHvis = 0.442 and rtotal-FLAIR = 0.497, p<0.05; Multiple Sclerosis Functional Composite vs. lesion volume: rBHvis = -0.53 and rtotal-FLAIR = -0.627, p<0.05). Clinical-radiological correlations in MS patients are

  3. Measurement of forward-backward multiplicity correlations in lead-lead, proton-lead and proton-proton collisions with the ATLAS detector

    CERN Document Server

    Aaboud, Morad; Abbott, Brad; Abdallah, Jalal; Abdinov, Ovsat; Abeloos, Baptiste; Aben, Rosemarie; AbouZeid, Ossama; Abraham, Nicola; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Adelman, Jahred; Adomeit, Stefanie; Adye, Tim; Affolder, Tony; Agatonovic-Jovin, Tatjana; Agricola, Johannes; Aguilar-Saavedra, Juan Antonio; Ahlen, Steven; Ahmadov, Faig; Aielli, Giulio; Akerstedt, Henrik; Åkesson, Torsten Paul Ake; Akimov, Andrei; Alberghi, Gian Luigi; Albert, Justin; Albrand, Solveig; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexopoulos, Theodoros; Alhroob, Muhammad; Ali, Babar; Aliev, Malik; Alimonti, Gianluca; Alison, John; Alkire, Steven Patrick; Allbrooke, Benedict; Allen, Benjamin William; Allport, Phillip; Aloisio, Alberto; Alonso, Alejandro; Alonso, Francisco; Alpigiani, Cristiano; Alstaty, Mahmoud; Alvarez Gonzalez, Barbara; Άlvarez Piqueras, Damián; Alviggi, Mariagrazia; Amadio, Brian Thomas; Amako, Katsuya; Amaral Coutinho, Yara; Amelung, Christoph; Amidei, Dante; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anders, John Kenneth; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Angelidakis, Stylianos; Angelozzi, Ivan; Anger, Philipp; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antel, Claire; Antonelli, Mario; Antonov, Alexey; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Arabidze, Giorgi; Arai, Yasuo; Araque, Juan Pedro; Arce, Ayana; Arduh, Francisco Anuar; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Armitage, Lewis James; Arnaez, Olivier; Arnold, Hannah; Arratia, Miguel; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Artz, Sebastian; Asai, Shoji; Asbah, Nedaa; Ashkenazi, Adi; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Augsten, Kamil; Avolio, Giuseppe; Axen, Bradley; Ayoub, Mohamad Kassem; Azuelos, Georges; Baak, Max; Baas, Alessandra; Baca, Matthew John; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Bagiacchi, Paolo; Bagnaia, Paolo; Bai, Yu; Baines, John; Baker, Oliver Keith; Baldin, Evgenii; Balek, Petr; Balestri, Thomas; Balli, Fabrice; Balunas, William Keaton; Banas, Elzbieta; Banerjee, Swagato; Bannoura, Arwa A E; Barak, Liron; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisits, Martin-Stefan; Barklow, Timothy; Barlow, Nick; Barnes, Sarah Louise; Barnett, Bruce; Barnett, Michael; Barnovska, Zuzana; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barranco Navarro, Laura; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Basalaev, Artem; Bassalat, Ahmed; Bates, Richard; Batista, Santiago Juan; Batley, Richard; Battaglia, Marco; Bauce, Matteo; Bauer, Florian; Bawa, Harinder Singh; Beacham, James; Beattie, Michael David; Beau, Tristan; Beauchemin, Pierre-Hugues; Bechtle, Philip; Beck, Hans~Peter; Becker, Kathrin; Becker, Maurice; Beckingham, Matthew; Becot, Cyril; Beddall, Andrew; Beddall, Ayda; Bednyakov, Vadim; Bedognetti, Matteo; Bee, Christopher; Beemster, Lars; Beermann, Thomas; Begel, Michael; Behr, Janna Katharina; Belanger-Champagne, Camille; Bell, Andrew Stuart; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belotskiy, Konstantin; Beltramello, Olga; Belyaev, Nikita; Benary, Odette; Benchekroun, Driss; Bender, Michael; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez, Jose; Benjamin, Douglas; Bensinger, James; Bentvelsen, Stan; Beresford, Lydia; Beretta, Matteo; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Beringer, Jürg; Berlendis, Simon; Bernard, Nathan Rogers; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertoli, Gabriele; Bertolucci, Federico; Bertram, Iain Alexander; Bertsche, Carolyn; Bertsche, David; Besjes, Geert-Jan; Bessidskaia Bylund, Olga; Bessner, Martin Florian; Besson, Nathalie; Betancourt, Christopher; Bethani, Agni; Bethke, Siegfried; Bevan, Adrian John; Bianchi, Riccardo-Maria; Bianchini, Louis; Bianco, Michele; Biebel, Otmar; Biedermann, Dustin; Bielski, Rafal; Biesuz, Nicolo Vladi; Biglietti, Michela; Bilbao De Mendizabal, Javier; Billoud, Thomas Remy Victor; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Biondi, Silvia; Bisanz, Tobias; Bjergaard, David Martin; Black, Curtis; Black, James; Black, Kevin; Blackburn, Daniel; Blair, Robert; Blanchard, Jean-Baptiste; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blum, Walter; Blumenschein, Ulrike; Blunier, Sylvain; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Bock, Christopher; Boehler, Michael; Boerner, Daniela; Bogaerts, Joannes Andreas; Bogavac, Danijela; Bogdanchikov, Alexander; Bohm, Christian; Boisvert, Veronique; Bokan, Petar; Bold, Tomasz; Boldyrev, Alexey; Bomben, Marco; Bona, Marcella; Boonekamp, Maarten; Borisov, Anatoly; Borissov, Guennadi; Bortfeldt, Jonathan; Bortoletto, Daniela; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Bossio Sola, Jonathan David; Boudreau, Joseph; Bouffard, Julian; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Boutle, Sarah Kate; Boveia, Antonio; Boyd, James; Boyko, Igor; Bracinik, Juraj; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Breaden Madden, William Dmitri; Brendlinger, Kurt; Brennan, Amelia Jean; Brenner, Lydia; Brenner, Richard; Bressler, Shikma; Bristow, Timothy Michael; Britton, Dave; Britzger, Daniel; Brochu, Frederic; Brock, Ian; Brock, Raymond; Brooijmans, Gustaaf; Brooks, Timothy; Brooks, William; Brosamer, Jacquelyn; Brost, Elizabeth; Broughton, James; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Bruni, Alessia; Bruni, Graziano; Bruni, Lucrezia Stella; Brunt, Benjamin; Bruschi, Marco; Bruscino, Nello; Bryant, Patrick; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Buchholz, Peter; Buckley, Andrew; Budagov, Ioulian; Buehrer, Felix; Bugge, Magnar Kopangen; Bulekov, Oleg; Bullock, Daniel; Burckhart, Helfried; Burdin, Sergey; Burgard, Carsten Daniel; Burghgrave, Blake; Burka, Klaudia; Burke, Stephen; Burmeister, Ingo; Burr, Jonathan Thomas Peter; Busato, Emmanuel; Büscher, Daniel; Büscher, Volker; Bussey, Peter; Butler, John; Buttar, Craig; Butterworth, Jonathan; Butti, Pierfrancesco; Buttinger, William; Buzatu, Adrian; Buzykaev, Aleksey; Cabrera Urbán, Susana; Caforio, Davide; Cairo, Valentina; Cakir, Orhan; Calace, Noemi; Calafiura, Paolo; Calandri, Alessandro; Calderini, Giovanni; Calfayan, Philippe; Callea, Giuseppe; Caloba, Luiz; Calvente Lopez, Sergio; Calvet, David; Calvet, Samuel; Calvet, Thomas Philippe; Camacho Toro, Reina; Camarda, Stefano; Camarri, Paolo; Cameron, David; Caminal Armadans, Roger; Camincher, Clement; Campana, Simone; Campanelli, Mario; Camplani, Alessandra; Campoverde, Angel; Canale, Vincenzo; Canepa, Anadi; Cano Bret, Marc; Cantero, Josu; Cantrill, Robert; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capua, Marcella; Caputo, Regina; Carbone, Ryne Michael; Cardarelli, Roberto; Cardillo, Fabio; Carli, Ina; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Sascha; Carquin, Edson; Carrillo-Montoya, German D; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Casolino, Mirkoantonio; Casper, David William; Castaneda-Miranda, Elizabeth; Castelijn, Remco; Castelli, Angelantonio; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Caudron, Julien; Cavaliere, Viviana; Cavallaro, Emanuele; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerda Alberich, Leonor; Cerio, Benjamin; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cerv, Matevz; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chan, Stephen Kam-wah; Chan, Yat Long; Chang, Philip; Chapman, John Derek; Charlton, Dave; Chatterjee, Avishek; Chau, Chav Chhiv; Chavez Barajas, Carlos Alberto; Che, Siinn; Cheatham, Susan; Chegwidden, Andrew; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Karen; Chen, Shenjian; Chen, Shion; Chen, Xin; Chen, Ye; Cheng, Hok Chuen; Cheng, Huajie; Cheng, Yangyang; Cheplakov, Alexander; Cheremushkina, Evgenia; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Chevalier, Laurent; Chiarella, Vitaliano; Chiarelli, Giorgio; Chiodini, Gabriele; Chisholm, Andrew; Chitan, Adrian; Chizhov, Mihail; Choi, Kyungeon; Chomont, Arthur Rene; Chouridou, Sofia; Chow, Bonnie Kar Bo; Christodoulou, Valentinos; Chromek-Burckhart, Doris; Chudoba, Jiri; Chuinard, Annabelle Julia; Chwastowski, Janusz; Chytka, Ladislav; Ciapetti, Guido; Ciftci, Abbas Kenan; Cinca, Diane; Cindro, Vladimir; Cioara, Irina Antonela; Ciocca, Claudia; Ciocio, Alessandra; Cirotto, Francesco; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Brian Lee; Clark, Michael; Clark, Philip James; Clarke, Robert; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Colasurdo, Luca; Cole, Brian; Colijn, Auke-Pieter; Collot, Johann; Colombo, Tommaso; Compostella, Gabriele; Conde Muiño, Patricia; Coniavitis, Elias; Connell, Simon Henry; Connelly, Ian; Consorti, Valerio; Constantinescu, Serban; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cormier, Kyle James Read; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Corso-Radu, Alina; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Cottin, Giovanna; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Crawley, Samuel Joseph; Cree, Graham; Crépé-Renaudin, Sabine; Crescioli, Francesco; Cribbs, Wayne Allen; Crispin Ortuzar, Mireia; Cristinziani, Markus; Croft, Vince; Crosetti, Giovanni; Cueto, Ana; Cuhadar Donszelmann, Tulay; Cummings, Jane; Curatolo, Maria; Cúth, Jakub; Czirr, Hendrik; Czodrowski, Patrick; D'amen, Gabriele; D'Auria, Saverio; D'Onofrio, Monica; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dado, Tomas; Dai, Tiesheng; Dale, Orjan; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Dandoy, Jeffrey Rogers; Dang, Nguyen Phuong; Daniells, Andrew Christopher; Dann, Nicholas Stuart; Danninger, Matthias; Dano Hoffmann, Maria; Dao, Valerio; Darbo, Giovanni; Darmora, Smita; Dassoulas, James; Dattagupta, Aparajita; Davey, Will; David, Claire; Davidek, Tomas; Davies, Merlin; Davison, Peter; Dawe, Edmund; Dawson, Ian; Daya-Ishmukhametova, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Benedetti, Abraham; De Castro, Stefano; De Cecco, Sandro; De Groot, Nicolo; de Jong, Paul; De la Torre, Hector; De Lorenzi, Francesco; De Maria, Antonio; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dedovich, Dmitri; Dehghanian, Nooshin; Deigaard, Ingrid; Del Gaudio, Michela; Del Peso, Jose; Del Prete, Tarcisio; Delgove, David; Deliot, Frederic; Delitzsch, Chris Malena; Dell'Acqua, Andrea; Dell'Asta, Lidia; Dell'Orso, Mauro; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delsart, Pierre-Antoine; DeMarco, David; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Denisov, Sergey; Denysiuk, Denys; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deterre, Cecile; Dette, Karola; Deviveiros, Pier-Olivier; Dewhurst, Alastair; Dhaliwal, Saminder; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Clemente, William Kennedy; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Di Valentino, David; Diaconu, Cristinel; Diamond, Miriam; Dias, Flavia; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Diglio, Sara; Dimitrievska, Aleksandra; Dingfelder, Jochen; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Djuvsland, Julia Isabell; Barros do Vale, Maria Aline; Dobos, Daniel; Dobre, Monica; Doglioni, Caterina; Dolejsi, Jiri; Dolezal, Zdenek; Donadelli, Marisilvia; Donati, Simone; Dondero, Paolo; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dova, Maria-Teresa; Doyle, Tony; Drechsler, Eric; Dris, Manolis; Du, Yanyan; Duarte-Campderros, Jorge; Duchovni, Ehud; Duckeck, Guenter; Ducu, Otilia Anamaria; Duda, Dominik; Dudarev, Alexey; Dudder, Andreas Christian; Duffield, Emily Marie; Duflot, Laurent; Dührssen, Michael; Dumancic, Mirta; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Durglishvili, Archil; Duschinger, Dirk; Dutta, Baishali; Dyndal, Mateusz; Eckardt, Christoph; Ecker, Katharina Maria; Edgar, Ryan Christopher; Edwards, Nicholas Charles; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Ekelof, Tord; El Kacimi, Mohamed; Ellajosyula, Venugopal; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Elliot, Alison; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Ennis, Joseph Stanford; Erdmann, Johannes; Ereditato, Antonio; Ernis, Gunar; Ernst, Jesse; Ernst, Michael; Errede, Steven; Ertel, Eugen; Escalier, Marc; Esch, Hendrik; Escobar, Carlos; Esposito, Bellisario; Etienvre, Anne-Isabelle; Etzion, Erez; Evans, Hal; Ezhilov, Alexey; Fabbri, Federica; Fabbri, Laura; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Falla, Rebecca Jane; Faltova, Jana; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farina, Christian; Farina, Edoardo Maria; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Faucci Giannelli, Michele; Favareto, Andrea; Fawcett, William James; Fayard, Louis; Fedin, Oleg; Fedorko, Wojciech; Feigl, Simon; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenyuk, Alexander; Feremenga, Last; Fernandez Martinez, Patricia; Fernandez Perez, Sonia; Ferrando, James; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiedler, Frank; Filipčič, Andrej; Filipuzzi, Marco; Filthaut, Frank; Fincke-Keeler, Margret; Finelli, Kevin Daniel; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Adam; Fischer, Cora; Fischer, Julia; Fisher, Wade Cameron; Flaschel, Nils; Fleck, Ivor; Fleischmann, Philipp; Fletcher, Gareth Thomas; Fletcher, Rob Roy MacGregor; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Flowerdew, Michael; Forcolin, Giulio Tiziano; Formica, Andrea; Forti, Alessandra; Foster, Andrew Geoffrey; Fournier, Daniel; Fox, Harald; Fracchia, Silvia; Francavilla, Paolo; Franchini, Matteo; Francis, David; Franconi, Laura; Franklin, Melissa; Frate, Meghan; Fraternali, Marco; Freeborn, David; Fressard-Batraneanu, Silvia; Friedrich, Felix; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fusayasu, Takahiro; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gach, Grzegorz; Gadatsch, Stefan; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Louis Guillaume; Gagnon, Pauline; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallop, Bruce; Gallus, Petr; Galster, Gorm Aske Gram Krohn; Gan, KK; Gao, Jun; Gao, Yanyan; Gao, Yongsheng; Garay Walls, Francisca; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gascon Bravo, Alberto; Gasnikova, Ksenia; Gatti, Claudio; Gaudiello, Andrea; Gaudio, Gabriella; Gauthier, Lea; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Gecse, Zoltan; Gee, Norman; Geich-Gimbel, Christoph; Geisen, Marc; Geisler, Manuel Patrice; Gemme, Claudia; Genest, Marie-Hélène; Geng, Cong; Gentile, Simonetta; Gentsos, Christos; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghasemi, Sara; Ghazlane, Hamid; Ghneimat, Mazuza; Giacobbe, Benedetto; Giagu, Stefano; Giannetti, Paola; Gibbard, Bruce; Gibson, Stephen; Gignac, Matthew; Gilchriese, Murdock; Gillam, Thomas; Gillberg, Dag; Gilles, Geoffrey; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giorgi, Filippo Maria; Giorgi, Francesco Michelangelo; Giraud, Pierre-Francois; Giromini, Paolo; Giugni, Danilo; Giuli, Francesco; Giuliani, Claudia; Giulini, Maddalena; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gkougkousis, Evangelos Leonidas; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glaysher, Paul; Glazov, Alexandre; Goblirsch-Kolb, Maximilian; Godlewski, Jan; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Giulia; Gonella, Laura; Gongadze, Alexi; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Goudet, Christophe Raymond; Goujdami, Driss; Goussiou, Anna; Govender, Nicolin; Gozani, Eitan; Graber, Lars; Grabowska-Bold, Iwona; Gradin, Per Olov Joakim; Grafström, Per; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Gratchev, Vadim; Gravila, Paul Mircea; Gray, Heather; Graziani, Enrico; Greenwood, Zeno Dixon; Grefe, Christian; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Grevtsov, Kirill; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grivaz, Jean-Francois; Groh, Sabrina; Grohs, Johannes Philipp; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Grout, Zara Jane; Guan, Liang; Guan, Wen; Guenther, Jaroslav; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Guo, Jun; Guo, Yicheng; Gupta, Ruchi; Gupta, Shaun; Gustavino, Giuliano; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haber, Carl; Hadavand, Haleh Khani; Haddad, Nacim; Hadef, Asma; Hageböck, Stephan; Hajduk, Zbigniew; Hakobyan, Hrachya; Haleem, Mahsana; Haley, Joseph; Halladjian, Garabed; Hallewell, Gregory David; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamilton, Andrew; Hamity, Guillermo Nicolas; Hamnett, Phillip George; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Haney, Bijan; Hanisch, Stefanie; Hanke, Paul; Hanna, Remie; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Maike Christina; Hansen, Peter Henrik; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Hariri, Faten; Harkusha, Siarhei; Harrington, Robert; Harrison, Paul Fraser; Hartjes, Fred; Hartmann, Nikolai Marcel; Hasegawa, Makoto; Hasegawa, Yoji; Hasib, A; Hassani, Samira; Haug, Sigve; Hauser, Reiner; Hauswald, Lorenz; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hayakawa, Daiki; Hayden, Daniel; Hays, Chris; Hays, Jonathan Michael; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Jochen Jens; Heinrich, Lukas; Heinz, Christian; Hejbal, Jiri; Helary, Louis; Hellman, Sten; Helsens, Clement; Henderson, James; Henderson, Robert; Heng, Yang; Henkelmann, Steffen; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Herbert, Geoffrey Henry; Herget, Verena; Hernández Jiménez, Yesenia; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hetherly, Jeffrey Wayne; Hickling, Robert; Higón-Rodriguez, Emilio; Hill, Ewan; Hill, John; Hiller, Karl Heinz; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hinman, Rachel Reisner; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoenig, Friedrich; Hohn, David; Holmes, Tova Ray; Homann, Michael; Hong, Tae Min; Hooberman, Benjamin Henry; Hopkins, Walter; Horii, Yasuyuki; Horton, Arthur James; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hrynevich, Aliaksei; Hsu, Catherine; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Qipeng; Hu, Shuyang; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Huo, Peng; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Ideal, Emma; Idrissi, Zineb; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikeno, Masahiro; Ilchenko, Iurii; Iliadis, Dimitrios; Ilic, Nikolina; Ince, Tayfun; Introzzi, Gianluca; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Ishijima, Naoki; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Ito, Fumiaki; Iturbe Ponce, Julia Mariana; Iuppa, Roberto; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jabbar, Samina; Jackson, Brett; Jackson, Paul; Jain, Vivek; Jakobi, Katharina Bianca; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansky, Roland; Janssen, Jens; Janus, Michel; Jarlskog, Göran; Javadov, Namig; Javůrek, Tomáš; Jeanneau, Fabien; Jeanty, Laura; Jejelava, Juansher; Jeng, Geng-yuan; Jennens, David; Jenni, Peter; Jeske, Carl; Jézéquel, Stéphane; Ji, Haoshuang; Jia, Jiangyong; Jiang, Hai; Jiang, Yi; Jiggins, Stephen; Jimenez Pena, Javier; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Jivan, Harshna; Johansson, Per; Johns, Kenneth; Johnson, William Joseph; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Sarah; Jones, Tim; Jongmanns, Jan; Jorge, Pedro; Jovicevic, Jelena; Ju, Xiangyang; Juste Rozas, Aurelio; Köhler, Markus Konrad; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kahn, Sebastien Jonathan; Kaji, Toshiaki; Kajomovitz, Enrique; Kalderon, Charles William; Kaluza, Adam; Kama, Sami; Kamenshchikov, Andrey; Kanaya, Naoko; Kaneti, Steven; Kanjir, Luka; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kaplan, Laser Seymour; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karamaoun, Andrew; Karastathis, Nikolaos; Kareem, Mohammad Jawad; Karentzos, Efstathios; Karnevskiy, Mikhail; Karpov, Sergey; Karpova, Zoya; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kasahara, Kota; Kashif, Lashkar; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Kato, Chikuma; Katre, Akshay; Katzy, Judith; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazanin, Vassili; Keeler, Richard; Kehoe, Robert; Keller, John; Kempster, Jacob Julian; Kentaro, Kawade; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Keyes, Robert; Khader, Mazin; Khalil-zada, Farkhad; Khanov, Alexander; Kharlamov, Alexey; Khoo, Teng Jian; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kido, Shogo; Kilby, Callum; Kim, Hee Yeun; Kim, Shinhong; Kim, Young-Kee; Kimura, Naoki; Kind, Oliver Maria; King, Barry; King, Matthew; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kiss, Florian; Kiuchi, Kenji; Kivernyk, Oleh; Kladiva, Eduard; Klein, Matthew Henry; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klioutchnikova, Tatiana; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Knapik, Joanna; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Aine; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koehler, Nicolas Maximilian; Koffas, Thomas; Koffeman, Els; Koi, Tatsumi; Kolanoski, Hermann; Kolb, Mathis; Koletsou, Iro; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kondrashova, Nataliia; Köneke, Karsten; König, Adriaan; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Kortner, Oliver; Kortner, Sandra; Kosek, Tomas; Kostyukhin, Vadim; Kotwal, Ashutosh; Kourkoumeli-Charalampidi, Athina; Kourkoumelis, Christine; Kouskoura, Vasiliki; Kowalewska, Anna Bozena; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozakai, Chihiro; Kozanecki, Witold; Kozhin, Anatoly; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitriy; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kravchenko, Anton; Kretz, Moritz; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Peter; Krizka, Karol; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Krumnack, Nils; Kruse, Amanda; Kruse, Mark; Kruskal, Michael; Kubota, Takashi; Kucuk, Hilal; Kuday, Sinan; Kuechler, Jan Thomas; Kuehn, Susanne; Kugel, Andreas; Kuger, Fabian; Kuhl, Andrew; Kuhl, Thorsten; Kukhtin, Victor; Kukla, Romain; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunigo, Takuto; Kupco, Alexander; Kurashige, Hisaya; Kurochkin, Yurii; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; Kwan, Tony; Kyriazopoulos, Dimitrios; La Rosa, Alessandro; La Rosa Navarro, Jose Luis; La Rotonda, Laura; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Lammers, Sabine; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lanfermann, Marie Christine; Lang, Valerie Susanne; Lange, J örn Christian; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Lanza, Agostino; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Lasagni Manghi, Federico; Lassnig, Mario; Laurelli, Paolo; Lavrijsen, Wim; Law, Alexander; Laycock, Paul; Lazovich, Tomo; Lazzaroni, Massimo; Le, Brian; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Quilleuc, Eloi; LeBlanc, Matthew Edgar; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Claire Alexandra; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Benoit; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leight, William Axel; Leisos, Antonios; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzi, Bruno; Leone, Robert; Leone, Sandra; Leonidopoulos, Christos; Leontsinis, Stefanos; Lerner, Giuseppe; Leroy, Claude; Lesage, Arthur; Lester, Christopher; Levchenko, Mikhail; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levy, Mark; Lewis, Dave; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Changqiao; Li, Haifeng; Li, Ho Ling; Li, Lei; Li, Liang; Li, Qi; Li, Shu; Li, Xingguo; Li, Yichen; Liang, Zhijun; Liberti, Barbara; Liblong, Aaron; Lichard, Peter; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limosani, Antonio; Lin, Simon; Lin, Tai-Hua; Lindquist, Brian Edward; Lionti, Anthony Eric; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Dong; Liu, Hao; Liu, Hongbin; Liu, Jian; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanlin; Liu, Yanwen; Livan, Michele; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loew, Kevin Michael; Loginov, Andrey; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Long, Brian Alexander; Long, Jonathan David; Long, Robin Eamonn; Longo, Luigi; Looper, Kristina Anne; Lopes, Lourenco; Lopez Mateos, David; Lopez Paredes, Brais; Lopez Paz, Ivan; Lopez Solis, Alvaro; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Lösel, Philipp Jonathan; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lu, Haonan; Lu, Nan; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Luedtke, Christian; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Olof; Lund-Jensen, Bengt; Luzi, Pierre Marc; Lynn, David; Lysak, Roman; Lytken, Else; Lyubushkin, Vladimir; Ma, Hong; Ma, Lian Liang; Ma, Yanhui; Maccarrone, Giovanni; Macchiolo, Anna; Macdonald, Calum Michael; Maček, Boštjan; Machado Miguens, Joana; Madaffari, Daniele; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeda, Junpei; Maeland, Steffen; Maeno, Tadashi; Maevskiy, Artem; Magradze, Erekle; Mahlstedt, Joern; Maiani, Camilla; Maidantchik, Carmen; Maier, Andreas Alexander; Maier, Thomas; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Malaescu, Bogdan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyukov, Sergei; Mamuzic, Judita; Mancini, Giada; Mandelli, Beatrice; Mandelli, Luciano; Mandić, Igor; Maneira, José; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany; Mann, Alexander; Manousos, Athanasios; Mansoulie, Bruno; Mansour, Jason Dhia; Mantifel, Rodger; Mantoani, Matteo; Manzoni, Stefano; Mapelli, Livio; Marceca, Gino; March, Luis; Marchiori, Giovanni; Marcisovsky, Michal; Marjanovic, Marija; Marley, Daniel; Marroquim, Fernando; Marsden, Stephen Philip; Marshall, Zach; Marti-Garcia, Salvador; Martin, Brian Thomas; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Mario; Martinez Outschoorn, Verena; Martin-Haugh, Stewart; Martoiu, Victor Sorin; Martyniuk, Alex; Marx, Marilyn; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massa, Lorenzo; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mättig, Peter; Mattmann, Johannes; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazza, Simone Michele; Mc Fadden, Neil Christopher; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McClymont, Laurie; McDonald, Emily; Mcfayden, Josh; Mchedlidze, Gvantsa; McMahon, Steve; McPherson, Robert; Medinnis, Michael; Meehan, Samuel; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melini, Davide; Mellado Garcia, Bruce Rafael; Melo, Matej; Meloni, Federico; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mergelmeyer, Sebastian; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Meyer Zu Theenhausen, Hanno; Miano, Fabrizio; Middleton, Robin; Miglioranzi, Silvia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Milesi, Marco; Milic, Adriana; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Minaenko, Andrey; Minami, Yuto; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mistry, Khilesh; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Miucci, Antonio; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mochizuki, Kazuya; Mohapatra, Soumya; Molander, Simon; Moles-Valls, Regina; Monden, Ryutaro; Mondragon, Matthew Craig; Mönig, Klaus; Monk, James; Monnier, Emmanuel; Montalbano, Alyssa; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Morange, Nicolas; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Mori, Daniel; Mori, Tatsuya; Morii, Masahiro; Morinaga, Masahiro; Morisbak, Vanja; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Mortensen, Simon Stark; Morvaj, Ljiljana; Mosidze, Maia; Moss, Josh; Motohashi, Kazuki; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Ralph Soeren Peter; Mueller, Thibaut; Muenstermann, Daniel; Mullen, Paul; Mullier, Geoffrey; Munoz Sanchez, Francisca Javiela; Murillo Quijada, Javier Alberto; Murray, Bill; Musheghyan, Haykuhi; Muškinja, Miha; Myagkov, Alexey; Myska, Miroslav; Nachman, Benjamin Philip; Nackenhorst, Olaf; Nagai, Koichi; Nagai, Ryo; Nagano, Kunihiro; Nagasaka, Yasushi; Nagata, Kazuki; Nagel, Martin; Nagy, Elemer; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Naranjo Garcia, Roger Felipe; Narayan, Rohin; Narrias Villar, Daniel Isaac; Naryshkin, Iouri; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Negri, Andrea; Negrini, Matteo; Nektarijevic, Snezana; Nellist, Clara; Nelson, Andrew; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen, Duong Hai; Nguyen Manh, Tuan; Nickerson, Richard; Nicolaidou, Rosy; Nielsen, Jason; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolopoulos, Konstantinos; Nilsen, Jon Kerr; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nomachi, Masaharu; Nomidis, Ioannis; Nooney, Tamsin; Norberg, Scarlet; Nordberg, Markus; Norjoharuddeen, Nurfikri; Novgorodova, Olga; Nowak, Sebastian; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nurse, Emily; Nuti, Francesco; O'grady, Fionnbarr; O'Neil, Dugan; O'Rourke, Abigail Alexandra; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Obermann, Theresa; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Ochoa-Ricoux, Juan Pedro; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohman, Henrik; Oide, Hideyuki; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Oleiro Seabra, Luis Filipe; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onogi, Kouta; Onyisi, Peter; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Owen, Mark; Owen, Rhys Edward; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; Pacheco Pages, Andres; Pacheco Rodriguez, Laura; Padilla Aranda, Cristobal; Pagáčová, Martina; Pagan Griso, Simone; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Palestini, Sandro; Palka, Marek; Pallin, Dominique; Panagiotopoulou, Evgenia; Pandini, Carlo Enrico; Panduro Vazquez, William; Pani, Priscilla; Panitkin, Sergey; Pantea, Dan; Paolozzi, Lorenzo; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Parker, Adam Jackson; Parker, Michael Andrew; Parker, Kerry Ann; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pascuzzi, Vincent; Pasqualucci, Enrico; Passaggio, Stefano; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Pater, Joleen; Pauly, Thilo; Pearce, James; Pearson, Benjamin; Pedersen, Lars Egholm; Pedersen, Maiken; Pedraza Lopez, Sebastian; Pedro, Rute; Peleganchuk, Sergey; Penc, Ondrej; Peng, Cong; Peng, Haiping; Penwell, John; Peralva, Bernardo; Perego, Marta Maria; Perepelitsa, Dennis; Perez Codina, Estel; Perini, Laura; Pernegger, Heinz; Perrella, Sabrina; Peschke, Richard; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petroff, Pierre; Petrolo, Emilio; Petrov, Mariyan; Petrucci, Fabrizio; Pettersson, Nora Emilia; Peyaud, Alan; Pezoa, Raquel; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Piccinini, Maurizio; Pickering, Mark Andrew; Piegaia, Ricardo; Pilcher, James; Pilkington, Andrew; Pin, Arnaud Willy J; Pinamonti, Michele; Pinfold, James; Pingel, Almut; Pires, Sylvestre; Pirumov, Hayk; Pitt, Michael; Plazak, Lukas; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Plucinski, Pawel; Pluth, Daniel; Poettgen, Ruth; Poggioli, Luc; Pohl, David-leon; Polesello, Giacomo; Poley, Anne-luise; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Pollard, Christopher Samuel; Polychronakos, Venetios; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Poppleton, Alan; Pospisil, Stanislav; Potamianos, Karolos; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Pozo Astigarraga, Mikel Eukeni; Pralavorio, Pascal; Pranko, Aliaksandr; Prell, Soeren; Price, Darren; Price, Lawrence; Primavera, Margherita; Prince, Sebastien; Prokofiev, Kirill; Prokoshin, Fedor; Protopopescu, Serban; Proudfoot, James; Przybycien, Mariusz; Puddu, Daniele; Purohit, Milind; Puzo, Patrick; Qian, Jianming; Qin, Gang; Qin, Yang; Quadt, Arnulf; Quayle, William; Queitsch-Maitland, Michaela; Quilty, Donnchadha; Raddum, Silje; Radeka, Veljko; Radescu, Voica; Radhakrishnan, Sooraj Krishnan; Radloff, Peter; Rados, Pere; Ragusa, Francesco; Rahal, Ghita; Raine, John Andrew; Rajagopalan, Srinivasan; Rammensee, Michael; Rangel-Smith, Camila; Ratti, Maria Giulia; Rauscher, Felix; Rave, Stefan; Ravenscroft, Thomas; Ravinovich, Ilia; Raymond, Michel; Read, Alexander Lincoln; Readioff, Nathan Peter; Reale, Marilea; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Rehnisch, Laura; Reichert, Joseph; Reisin, Hernan; Rembser, Christoph; Ren, Huan; Rescigno, Marco; Resconi, Silvia; Rezanova, Olga; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Richter, Stefan; Richter-Was, Elzbieta; Ricken, Oliver; Ridel, Melissa; Rieck, Patrick; Riegel, Christian Johann; Rieger, Julia; Rifki, Othmane; Rijssenbeek, Michael; Rimoldi, Adele; Rimoldi, Marco; Rinaldi, Lorenzo; Ristić, Branislav; Ritsch, Elmar; Riu, Imma; Rizatdinova, Flera; Rizvi, Eram; Rizzi, Chiara; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Roda, Chiara; Rodina, Yulia; Rodriguez Perez, Andrea; Rodriguez Rodriguez, Daniel; Roe, Shaun; Rogan, Christopher Sean; Røhne, Ole; Romaniouk, Anatoli; Romano, Marino; Romano Saez, Silvestre Marino; Romero Adam, Elena; Rompotis, Nikolaos; Ronzani, Manfredi; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Peyton; Rosenthal, Oliver; Rosien, Nils-Arne; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rosten, Jonatan; Rosten, Rachel; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexandre; Rozen, Yoram; Ruan, Xifeng; Rubbo, Francesco; Rudolph, Matthew Scott; Rühr, Frederik; Ruiz-Martinez, Aranzazu; Rurikova, Zuzana; Rusakovich, Nikolai; Ruschke, Alexander; Russell, Heather; Rutherfoord, John; Ruthmann, Nils; Ryabov, Yury; Rybar, Martin; Rybkin, Grigori; Ryu, Soo; Ryzhov, Andrey; Rzehorz, Gerhard Ferdinand; Saavedra, Aldo; Sabato, Gabriele; Sacerdoti, Sabrina; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Saha, Puja; Sahinsoy, Merve; Saimpert, Matthias; Saito, Tomoyuki; Sakamoto, Hiroshi; Sakurai, Yuki; Salamanna, Giuseppe; Salamon, Andrea; Salazar Loyola, Javier Esteban; Salek, David; Sales De Bruin, Pedro Henrique; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sammel, Dirk; Sampsonidis, Dimitrios; Sanchez, Arturo; Sánchez, Javier; Sanchez Martinez, Victoria; Sandaker, Heidi; Sandbach, Ruth Laura; Sander, Heinz Georg; Sandhoff, Marisa; Sandoval, Carlos; Sandstroem, Rikard; Sankey, Dave; Sannino, Mario; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapp, Kevin; Sapronov, Andrey; Saraiva, João; Sarrazin, Bjorn; Sasaki, Osamu; Sasaki, Yuichi; Sato, Koji; Sauvage, Gilles; Sauvan, Emmanuel; Savage, Graham; Savard, Pierre; Savic, Natascha; Sawyer, Craig; Sawyer, Lee; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scanlon, Tim; Scannicchio, Diana; Scarcella, Mark; Scarfone, Valerio; Schaarschmidt, Jana; Schacht, Peter; Schachtner, Balthasar Maria; Schaefer, Douglas; Schaefer, Leigh; Schaefer, Ralph; Schaeffer, Jan; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R Dean; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Schiavi, Carlo; Schier, Sheena; Schillo, Christian; Schioppa, Marco; Schlenker, Stefan; Schmidt-Sommerfeld, Korbinian Ralf; Schmieden, Kristof; Schmitt, Christian; Schmitt, Stefan; Schmitz, Simon; Schneider, Basil; Schnoor, Ulrike; Schoeffel, Laurent; Schoening, Andre; Schoenrock, Bradley Daniel; Schopf, Elisabeth; Schott, Matthias; Schovancova, Jaroslava; Schramm, Steven; Schreyer, Manuel; Schuh, Natascha; Schulte, Alexandra; Schultens, Martin Johannes; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwartzman, Ariel; Schwarz, Thomas Andrew; Schweiger, Hansdieter; Schwemling, Philippe; Schwienhorst, Reinhard; Schwindling, Jerome; Schwindt, Thomas; Sciolla, Gabriella; Scuri, Fabrizio; Scutti, Federico; Searcy, Jacob; Seema, Pienpen; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Sekhon, Karishma; Sekula, Stephen; Seliverstov, Dmitry; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Sessa, Marco; Seuster, Rolf; Severini, Horst; Sfiligoj, Tina; Sforza, Federico; Sfyrla, Anna; Shabalina, Elizaveta; Shaikh, Nabila Wahab; Shan, Lianyou; Shang, Ruo-yu; Shank, James; Shapiro, Marjorie; Shatalov, Pavel; Shaw, Kate; Shaw, Savanna Marie; Shcherbakova, Anna; Shehu, Ciwake Yusufu; Sherwood, Peter; Shi, Liaoshan; Shimizu, Shima; Shimmin, Chase Owen; Shimojima, Makoto; Shiyakova, Mariya; Shmeleva, Alevtina; Shoaleh Saadi, Diane; Shochet, Mel; Shojaii, Seyed Ruhollah; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Sicho, Petr; Sickles, Anne Marie; Sidebo, Per Edvin; Sidiropoulou, Ourania; Sidorov, Dmitri; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silva, José; Silverstein, Samuel; Simak, Vladislav; Simic, Ljiljana; Simion, Stefan; Simioni, Eduard; Simmons, Brinick; Simon, Dorian; Simon, Manuel; Sinervo, Pekka; Sinev, Nikolai; Sioli, Maximiliano; Siragusa, Giovanni; Sivoklokov, Serguei; Sjölin, Jörgen; Skinner, Malcolm Bruce; Skottowe, Hugh Philip; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Slawinska, Magdalena; Sliwa, Krzysztof; Slovak, Radim; Smakhtin, Vladimir; Smart, Ben; Smestad, Lillian; Smiesko, Juraj; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Matthew; Smith, Russell; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snyder, Scott; Sobie, Randall; Socher, Felix; Soffer, Abner; Soh, Dart-yin; Sokhrannyi, Grygorii; Solans Sanchez, Carlos; Solar, Michael; Soldatov, Evgeny; Soldevila, Urmila; Solodkov, Alexander; Soloshenko, Alexei; Solovyanov, Oleg; Solovyev, Victor; Sommer, Philip; Son, Hyungsuk; Song, Hong Ye; Sood, Alexander; Sopczak, Andre; Sopko, Vit; Sorin, Veronica; Sosa, David; Sotiropoulou, Calliope Louisa; Soualah, Rachik; Soukharev, Andrey; South, David; Sowden, Benjamin; Spagnolo, Stefania; Spalla, Margherita; Spangenberg, Martin; Spanò, Francesco; Sperlich, Dennis; Spettel, Fabian; Spighi, Roberto; Spigo, Giancarlo; Spiller, Laurence Anthony; Spousta, Martin; St Denis, Richard Dante; Stabile, Alberto; Stamen, Rainer; Stamm, Soren; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanescu-Bellu, Madalina; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Giordon; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Stärz, Steffen; Staszewski, Rafal; Steinberg, Peter; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoebe, Michael; Stoicea, Gabriel; Stolte, Philipp; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Stramaglia, Maria Elena; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Stroynowski, Ryszard; Strubig, Antonia; Stucci, Stefania Antonia; Stugu, Bjarne; Styles, Nicholas Adam; Su, Dong; Su, Jun; Suchek, Stanislav; Sugaya, Yorihito; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Siyuan; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Susinno, Giancarlo; Sutton, Mark; Suzuki, Shota; Svatos, Michal; Swiatlowski, Maximilian; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Taccini, Cecilia; Tackmann, Kerstin; Taenzer, Joe; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takai, Helio; Takashima, Ryuichi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tan, Kong Guan; Tanaka, Junichi; Tanaka, Masahiro; Tanaka, Reisaburo; Tanaka, Shuji; Tannenwald, Benjamin Bordy; Tapia Araya, Sebastian; Tapprogge, Stefan; Tarem, Shlomit; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tavares Delgado, Ademar; Tayalati, Yahya; Taylor, Aaron; Taylor, Geoffrey; Taylor, Pierre Thor Elliot; Taylor, Wendy; Teischinger, Florian Alfred; Teixeira-Dias, Pedro; Temming, Kim Katrin; Temple, Darren; Ten Kate, Herman; Teng, Ping-Kun; Teoh, Jia Jian; Tepel, Fabian-Phillipp; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Theveneaux-Pelzer, Timothée; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Emily; Thompson, Paul; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Tibbetts, Mark James; Ticse Torres, Royer Edson; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tipton, Paul; Tisserant, Sylvain; Todome, Kazuki; Todorov, Theodore; Todorova-Nova, Sharka; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tolley, Emma; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Tong, Baojia(Tony); Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Trefzger, Thomas; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Tripiana, Martin; Trischuk, William; Trocmé, Benjamin; Trofymov, Artur; Troncon, Clara; Trottier-McDonald, Michel; Trovatelli, Monica; Truong, Loan; Trzebinski, Maciej; Trzupek, Adam; Tseng, Jeffrey; Tsiareshka, Pavel; Tsipolitis, Georgios; Tsirintanis, Nikolaos; Tsiskaridze, Shota; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsui, Ka Ming; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsuno, Soshi; Tsybychev, Dmitri; Tu, Yanjun; Tudorache, Alexandra; Tudorache, Valentina; Tuna, Alexander Naip; Tupputi, Salvatore; Turchikhin, Semen; Turecek, Daniel; Turgeman, Daniel; Turra, Ruggero; Turvey, Andrew John; Tuts, Michael; Tyndel, Mike; Ucchielli, Giulia; Ueda, Ikuo; Ughetto, Michael; Ukegawa, Fumihiko; Unal, Guillaume; Undrus, Alexander; Unel, Gokhan; Ungaro, Francesca; Unno, Yoshinobu; Unverdorben, Christopher; Urban, Jozef; Urquijo, Phillip; Urrejola, Pedro; Usai, Giulio; Usanova, Anna; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Valderanis, Chrysostomos; Valdes Santurio, Eduardo; Valencic, Nika; Valentinetti, Sara; Valero, Alberto; Valery, Loic; Valkar, Stefan; Valls Ferrer, Juan Antonio; Van Den Wollenberg, Wouter; Van Der Deijl, Pieter; van der Graaf, Harry; van Eldik, Niels; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; van Woerden, Marius Cornelis; Vanadia, Marco; Vandelli, Wainer; Vanguri, Rami; Vaniachine, Alexandre; Vankov, Peter; Vardanyan, Gagik; Vari, Riccardo; Varnes, Erich; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vasquez, Jared Gregory; Vazeille, Francois; Vazquez Schroeder, Tamara; Veatch, Jason; Veeraraghavan, Venkatesh; Veloce, Laurelle Maria; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Venturi, Manuela; Venturi, Nicola; Venturini, Alessio; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Viazlo, Oleksandr; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Vigani, Luigi; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinogradov, Vladimir; Vittori, Camilla; Vivarelli, Iacopo; Vlachos, Sotirios; Vlasak, Michal; Vogel, Marcelo; Vokac, Petr; Volpi, Guido; Volpi, Matteo; von der Schmitt, Hans; von Toerne, Eckhard; Vorobel, Vit; Vorobev, Konstantin; Vos, Marcel; Voss, Rudiger; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vuillermet, Raphael; Vukotic, Ilija; Vykydal, Zdenek; Wagner, Peter; Wagner, Wolfgang; Wahlberg, Hernan; Wahrmund, Sebastian; Wakabayashi, Jun; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wallangen, Veronica; Wang, Chao; Wang, Chao; Wang, Fuquan; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Kuhan; Wang, Rui; Wang, Song-Ming; Wang, Tan; Wang, Tingting; Wang, Wenxiao; Wang, Xiaoxiao; Wanotayaroj, Chaowaroj; Warburton, Andreas; Ward, Patricia; Wardrope, David Robert; Washbrook, Andrew; Watkins, Peter; Watson, Alan; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Ben; Webb, Samuel; Weber, Michele; Weber, Stefan Wolf; Webster, Jordan S; Weidberg, Anthony; Weinert, Benjamin; Weingarten, Jens; Weiser, Christian; Weits, Hartger; Wells, Phillippa; Wenaus, Torre; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Matthias; Werner, Michael David; Werner, Per; Wessels, Martin; Wetter, Jeffrey; Whalen, Kathleen; Whallon, Nikola Lazar; Wharton, Andrew Mark; White, Andrew; White, Martin; White, Ryan; Whiteson, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik-Fuchs, Liv Antje Mari; Wildauer, Andreas; Wilk, Fabian; Wilkens, Henric George; Williams, Hugh; Williams, Sarah; Willis, Christopher; Willocq, Stephane; Wilson, John; Wingerter-Seez, Isabelle; Winklmeier, Frank; Winston, Oliver James; Winter, Benedict Tobias; Wittgen, Matthias; Wittkowski, Josephine; Wolf, Tim Michael Heinz; Wolter, Marcin Wladyslaw; Wolters, Helmut; Worm, Steven D; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wozniak, Krzysztof; Wu, Mengqing; Wu, Miles; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wyatt, Terry Richard; Wynne, Benjamin; Xella, Stefania; Xu, Da; Xu, Lailin; Yabsley, Bruce; Yacoob, Sahal; Yamaguchi, Daiki; Yamaguchi, Yohei; Yamamoto, Akira; Yamamoto, Shimpei; Yamanaka, Takashi; Yamauchi, Katsuya; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Hongtao; Yang, Yi; Yang, Zongchang; Yao, Weiming; Yap, Yee Chinn; Yasu, Yoshiji; Yatsenko, Elena; Yau Wong, Kaven Henry; Ye, Jingbo; Ye, Shuwei; Yeletskikh, Ivan; Yen, Andy L; Yildirim, Eda; Yorita, Kohei; Yoshida, Rikutaro; Yoshihara, Keisuke; Young, Charles; Young, Christopher John; Youssef, Saul; Yu, David Ren-Hwa; Yu, Jaehoon; Yu, Jiaming; Yu, Jie; Yuan, Li; Yuen, Stephanie P; Yusuff, Imran; Zabinski, Bartlomiej; Zaidan, Remi; Zaitsev, Alexander; Zakharchuk, Nataliia; Zalieckas, Justas; Zaman, Aungshuman; Zambito, Stefano; Zanello, Lucia; Zanzi, Daniele; Zeitnitz, Christian; Zeman, Martin; Zemla, Andrzej; Zeng, Jian Cong; Zeng, Qi; Zengel, Keith; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zhang, Dongliang; Zhang, Fangzhou; Zhang, Guangyi; Zhang, Huijun; Zhang, Jinlong; Zhang, Lei; Zhang, Rui; Zhang, Ruiqi; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Xiandong; Zhao, Yongke; Zhao, Zhengguo; Zhemchugov, Alexey; Zhong, Jiahang; Zhou, Bing; Zhou, Chen; Zhou, Lei; Zhou, Li; Zhou, Mingliang; Zhou, Ning; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhukov, Konstantin; Zibell, Andre; Zieminska, Daria; Zimine, Nikolai; Zimmermann, Christoph; Zimmermann, Stephanie; Zinonos, Zinonas; Zinser, Markus; Ziolkowski, Michael; Živković, Lidija; Zobernig, Georg; Zoccoli, Antonio; zur Nedden, Martin; Zwalinski, Lukasz

    2017-06-28

    Two-particle pseudorapidity correlations are measured in $\\sqrt{s_{\\rm{NN}}}$ = 2.76 TeV Pb+Pb, $\\sqrt{s_{\\rm{NN}}}$ = 5.02 TeV $p$+Pb, and $\\sqrt{s}$ = 13 TeV $pp$ collisions at the LHC, with total integrated luminosities of approximately 7 $\\mu\\mathrm{b}^{-1}$, 28 $\\mathrm{nb}^{-1}$, and 65 $\\mathrm{nb}^{-1}$, respectively. The correlation function $C_{\\rm N}(\\eta_1,\\eta_2)$ is measured as a function of event multiplicity using charged particles in the pseudorapidity range $|\\eta|<2.4$. The correlation function contains a significant short-range component, which is estimated and subtracted. After removal of the short-range component, the shape of the correlation function is described approximately by $1+\\langle{a_1^2}\\rangle \\eta_1\\eta_2$ in all collision systems over the full multiplicity range. The values of $\\sqrt{\\langle{a_1^2}\\rangle}$ are consistent between the opposite-charge pairs and same-charge pairs, and for the three collision systems at similar multiplicity. The values of $\\sqrt{\\langle{a_1^...

  4. Accounting for inertia in modal choices: some new evidence using a RP/SP dataset

    DEFF Research Database (Denmark)

    Cherchi, Elisabetta; Manca, Francesco

    2011-01-01

    effect is stable along the SP experiments. Inertia has been studied more extensively with panel datasets, but few investigations have used RP/SP datasets. In this paper we extend previous work in several ways. We test and compare several ways of measuring inertia, including measures that have been...... proposed for both short and long RP panel datasets. We also explore new measures of inertia to test for the effect of “learning” (in the sense of acquiring experience or getting more familiar with) along the SP experiment and we disentangle this effect from the pure inertia effect. A mixed logit model...... is used that allows us to account for both systematic and random taste variations in the inertia effect and for correlations among RP and SP observations. Finally we explore the relation between the utility specification (especially in the SP dataset) and the role of inertia in explaining current choices....

  5. Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model

    DEFF Research Database (Denmark)

    Silvennoinen, Annestiina; Terasvirta, Timo

    A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations...

  6. Accurate projected augmented wave datasets for BaFe2As2

    International Nuclear Information System (INIS)

    Cao Chao; Wu Yuing; Hamdan, Rashid; Wang, Yunpeng; Cheng Haiping

    2010-01-01

    By carefully choosing parameters and including more semi-core orbitals as valence electrons, we have constructed a high-quality projected augmented wave dataset that yields results comparable to existing full-potential linearized augmented plane-wave calculations. The dataset was then applied to BaFe 2 As 2 to study the effects of different levels of structure optimization, as well as different choices of exchange-correlation functionals. It was found that the local density approximation exchange-correlation functional fails to find the correct spin-density-wave anti-ferromagnetic (SDW-AFM) ground state under full optimization, while the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional obtains the correct state but significantly overestimates the magnetism. The electronic structure of the SDW-AFM state is not very sensitive to structure optimizations with the PBE exchange-correlation functional because the positions of the As atoms are preserved under optimizations. We further investigated the Ba atom diffusion process on the BaFe 2 As 2 surface using the nudged elastic bands method. The Ba atom was found to be stable above the center of the squares formed by the surface As atoms, and a diffusion barrier of 1.2 eV was found. Our simulated scanning tunneling microscopy image suggests an ordered surface Ba atom structure, in agreement with Massee et al (2009 Phys. Rev. B 80 140507; van Heumen E et al 2010 arXiv:1009.3493v1).

  7. Forward-backward multiplicity correlations of target fragments in nucleus-emulsion collisions at a few hundred MeV/u

    International Nuclear Information System (INIS)

    Zhang Donghai; Chen Yanling; Wang Guorong; Li Wangdong; Wang Qing; Yao Jijie; Zhou Jianguo; Li Rong; Li Junsheng; Li Huiling

    2015-01-01

    The forward-backward multiplicity and correlations of a target evaporated fragment (black track particle) and target recoiled proton (grey track particle) emitted from 150 A MeV "4He, 290 A MeV "1"2C, 400 A MeV "1"2C, 400 A MeV "2"0Ne and 500 A MeV "5"6Fe induced different types of nuclear emulsion target interactions are investigated. It is found that the forward and backward averaged multiplicity of a grey, black and heavily ionized track particle increases with the increase of the target size. The averaged multiplicity of a forward black track particle, backward black track particle, and backward grey track particle do not depend on the projectile size and energy, but the averaged multiplicity of a forward grey track particle increases with an increase of projectile size and energy. The backward grey track particle multiplicity distribution follows an exponential decay law and the decay constant decreases with an increase of target size. The backward-forward multiplicity correlations follow linear law which is independent of the projectile size and energy, and the saturation effect is observed in some heavy target data sets. (authors)

  8. New results of novel long-range correlations in high-multiplicity pp collisions at 7 and 13 TeV from CMS

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    In 2010, CMS reported the observation of a novel long-range two-particle angular correlation in high-multiplicity pp collisions at 7 TeV, where an enhanced correlation for particles emitted at similar azimuthal angle (phi) over a wide range in pseudorapidity (known as the ``ridge'') is observed. This ridge correlation phenomenon was not seen in pp collisions before but reminiscent of similar effect first seen in high-energy nucleus-nucleus collisions, which is attributed to collective flow of a strongly interacting, expanding quark-gluon medium. Later on, similar ridge correlations were also observed in high-multiplicity pPb collisions and studied in great detail by all LHC experiments. The start of the LHC run 2 brought new opportunities of exploring novel QCD emergent phenomena in pp collisions at the highest energy ever achieved. First CMS results on QCD physics in pp collisions at 13 TeV are presented and compared to the 7 TeV data. This includes the measurement of charged particle multipl...

  9. Open University Learning Analytics dataset.

    Science.gov (United States)

    Kuzilek, Jakub; Hlosta, Martin; Zdrahal, Zdenek

    2017-11-28

    Learning Analytics focuses on the collection and analysis of learners' data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students' interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.

  10. Development of a SPARK Training Dataset

    Energy Technology Data Exchange (ETDEWEB)

    Sayre, Amanda M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Olson, Jarrod R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-03-01

    In its first five years, the National Nuclear Security Administration’s (NNSA) Next Generation Safeguards Initiative (NGSI) sponsored more than 400 undergraduate, graduate, and post-doctoral students in internships and research positions (Wyse 2012). In the past seven years, the NGSI program has, and continues to produce a large body of scientific, technical, and policy work in targeted core safeguards capabilities and human capital development activities. Not only does the NGSI program carry out activities across multiple disciplines, but also across all U.S. Department of Energy (DOE)/NNSA locations in the United States. However, products are not readily shared among disciplines and across locations, nor are they archived in a comprehensive library. Rather, knowledge of NGSI-produced literature is localized to the researchers, clients, and internal laboratory/facility publication systems such as the Electronic Records and Information Capture Architecture (ERICA) at the Pacific Northwest National Laboratory (PNNL). There is also no incorporated way of analyzing existing NGSI literature to determine whether the larger NGSI program is achieving its core safeguards capabilities and activities. A complete library of NGSI literature could prove beneficial to a cohesive, sustainable, and more economical NGSI program. The Safeguards Platform for Automated Retrieval of Knowledge (SPARK) has been developed to be a knowledge storage, retrieval, and analysis capability to capture safeguards knowledge to exist beyond the lifespan of NGSI. During the development process, it was necessary to build a SPARK training dataset (a corpus of documents) for initial entry into the system and for demonstration purposes. We manipulated these data to gain new information about the breadth of NGSI publications, and they evaluated the science-policy interface at PNNL as a practical demonstration of SPARK’s intended analysis capability. The analysis demonstration sought to answer the

  11. Measurement of forward-backward multiplicity correlations in lead-lead, proton-lead, and proton-proton collisions with the ATLAS detector

    Energy Technology Data Exchange (ETDEWEB)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M-S; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J. -B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. 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F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nomachi, M.; Nomidis, I.; Nooney, T.; Norberg, S.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O' grady, F.; O' Neil, D. C.; O' Rourke, A. A.; O' Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. 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    2017-06-28

    Two-particle pseudorapidity correlations are measured in √sNN = 2.76TeV Pb + Pb, √sNN = 5.02TeV p + Pb, and √s = 13 TeV pp collisions at the Large Hadron Collider (LHC), with total integrated luminosities of approximately 7μb–1, 28 nb–1, and 65 nb–1, respectively. The correlation function CN12) is measured as a function of event multiplicity using charged particles in the pseudorapidity range |η| < 2.4. The correlation function contains a significant short-range component, which is estimated and subtracted. After removal of the short-range component, the shape of the correlation function is described approximately by 1 + < a21 > 1/2η1η2 in all collision systems over the full multiplicity range. The values of < a21 >1/2 are consistent for the opposite-charge pairs and same-charge pairs, and for the three collision systems at similar multiplicity. The values of < a21 >1/2 and the magnitude of the short-range component both follow a power-law dependence on the event multiplicity. Here, the short-range component in p + Pb collisions, after symmetrizing the proton and lead directions, is found to be smaller at a given η than in pp collisions with comparable multiplicity.

  12. Efficient multiple-trait association and estimation of genetic correlation using the matrix-variate linear mixed model.

    Science.gov (United States)

    Furlotte, Nicholas A; Eskin, Eleazar

    2015-05-01

    Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM. Copyright © 2015 by the Genetics Society of America.

  13. Resampling-based methods in single and multiple testing for equality of covariance/correlation matrices.

    Science.gov (United States)

    Yang, Yang; DeGruttola, Victor

    2012-06-22

    Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients.

  14. Differential models of twin correlations in skew for body-mass index (BMI).

    Science.gov (United States)

    Tsang, Siny; Duncan, Glen E; Dinescu, Diana; Turkheimer, Eric

    2018-01-01

    Body Mass Index (BMI), like most human phenotypes, is substantially heritable. However, BMI is not normally distributed; the skew appears to be structural, and increases as a function of age. Moreover, twin correlations for BMI commonly violate the assumptions of the most common variety of the classical twin model, with the MZ twin correlation greater than twice the DZ correlation. This study aimed to decompose twin correlations for BMI using more general skew-t distributions. Same sex MZ and DZ twin pairs (N = 7,086) from the community-based Washington State Twin Registry were included. We used latent profile analysis (LPA) to decompose twin correlations for BMI into multiple mixture distributions. LPA was performed using the default normal mixture distribution and the skew-t mixture distribution. Similar analyses were performed for height as a comparison. Our analyses are then replicated in an independent dataset. A two-class solution under the skew-t mixture distribution fits the BMI distribution for both genders. The first class consists of a relatively normally distributed, highly heritable BMI with a mean in the normal range. The second class is a positively skewed BMI in the overweight and obese range, with lower twin correlations. In contrast, height is normally distributed, highly heritable, and is well-fit by a single latent class. Results in the replication dataset were highly similar. Our findings suggest that two distinct processes underlie the skew of the BMI distribution. The contrast between height and weight is in accord with subjective psychological experience: both are under obvious genetic influence, but BMI is also subject to behavioral control, whereas height is not.

  15. Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

    Energy Technology Data Exchange (ETDEWEB)

    Li, Jun-Hao; Liu, Shun; Zheng, Ling-Ling; Wu, Jie; Sun, Wen-Ju; Wang, Ze-Lin; Zhou, Hui; Qu, Liang-Hu, E-mail: lssqlh@mail.sysu.edu.cn; Yang, Jian-Hua, E-mail: lssqlh@mail.sysu.edu.cn [RNA Information Center, Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou (China)

    2015-01-14

    Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

  16. Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

    International Nuclear Information System (INIS)

    Li, Jun-Hao; Liu, Shun; Zheng, Ling-Ling; Wu, Jie; Sun, Wen-Ju; Wang, Ze-Lin; Zhou, Hui; Qu, Liang-Hu; Yang, Jian-Hua

    2015-01-01

    Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

  17. On the performance of dual-hop systems with multiple antennas: Effects of spatial correlation, keyhole, and co-channel interference

    KAUST Repository

    Yang, Liang

    2012-12-01

    In this paper, taking into account realistic propagation conditions, namely, spatial correlation, keyhole channels, and unequal-power co-channel interference, we investigate the performance of a wireless relay network where all the nodes are equipped with multiple antennas. Considering channel state information assisted amplify-and-forward protocol, we present analytical expressions for the symbol error rate (SER) and outage probability. More specifically, we first derive the SER expressions of a relay system with orthogonal space-time block coding (OSTBC) over correlated/keyhole fading channels. We also analyze the outage probability of interference corrupted relay systems with maximal ratio combing (MRC) at the receiver as well as multiple-input multiple-output MRC (MIMO MRC). Numerical results are given to illustrate and verify the analytical results. © 2012 IEEE.

  18. On the performance of dual-hop systems with multiple antennas: Effects of spatial correlation, keyhole, and co-channel interference

    KAUST Repository

    Yang, Liang; Alouini, Mohamed-Slim; Qaraqe, Khalid A.; Liu, Weiping

    2012-01-01

    In this paper, taking into account realistic propagation conditions, namely, spatial correlation, keyhole channels, and unequal-power co-channel interference, we investigate the performance of a wireless relay network where all the nodes are equipped with multiple antennas. Considering channel state information assisted amplify-and-forward protocol, we present analytical expressions for the symbol error rate (SER) and outage probability. More specifically, we first derive the SER expressions of a relay system with orthogonal space-time block coding (OSTBC) over correlated/keyhole fading channels. We also analyze the outage probability of interference corrupted relay systems with maximal ratio combing (MRC) at the receiver as well as multiple-input multiple-output MRC (MIMO MRC). Numerical results are given to illustrate and verify the analytical results. © 2012 IEEE.

  19. Correlated Heterospectral Lipidomics for Biomolecular Profiling of Remyelination in Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Mads S. Bergholt

    2017-12-01

    Full Text Available Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS, and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models.

  20. Multiplicity dependence of jet-like two-particle correlations in p-Pb collisions at $\\sqrt{s_NN}$ = 5.02 TeV with ALICE at LHC

    CERN Document Server

    Abelev, Betty Bezverkhny; Adamova, Dagmar; Aggarwal, Madan Mohan; Agnello, Michelangelo; Agostinelli, Andrea; Agrawal, Neelima; Ahammed, Zubayer; Ahmad, Nazeer; Ahmed, Ijaz; Ahn, Sang Un; Ahn, Sul-Ah; Aimo, Ilaria; Aiola, Salvatore; Ajaz, Muhammad; Akindinov, Alexander; Alam, Sk Noor; Aleksandrov, Dmitry; Alessandro, Bruno; Alexandre, Didier; Alici, Andrea; Alkin, Anton; Alme, Johan; Alt, Torsten; Altinpinar, Sedat; Altsybeev, Igor; Alves Garcia Prado, Caio; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anielski, Jonas; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshaeuser, Harald; Arcelli, Silvia; Armesto Perez, Nestor; Arnaldi, Roberta; Aronsson, Tomas; Arsene, Ionut Cristian; Arslandok, Mesut; Augustinus, Andre; Averbeck, Ralf Peter; Awes, Terry; Azmi, Mohd Danish; Bach, Matthias Jakob; Badala, Angela; Baek, Yong Wook; Bagnasco, Stefano; Bailhache, Raphaelle Marie; Bala, Renu; Baldisseri, Alberto; Baltasar Dos Santos Pedrosa, Fernando; Baral, Rama Chandra; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Ramillien Barret, Valerie; Bartke, Jerzy Gustaw; Basile, Maurizio; Bastid, Nicole; Basu, Sumit; Bathen, Bastian; Batigne, Guillaume; Batista Camejo, Arianna; Batyunya, Boris; Batzing, Paul Christoph; Baumann, Christoph Heinrich; Bearden, Ian Gardner; Beck, Hans; Bedda, Cristina; Behera, Nirbhay Kumar; Belikov, Iouri; Bellini, Francesca; Bellwied, Rene; Belmont Moreno, Ernesto; Belmont Iii, Ronald John; Belyaev, Vladimir; Bencedi, Gyula; Beole, Stefania; Berceanu, Ionela; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Berger, Martin Emanuel; Bertens, Redmer Alexander; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhat, Inayat Rasool; Bhati, Ashok Kumar; Bhattacharjee, Buddhadeb; Bhom, Jihyun; Bianchi, Livio; Bianchi, Nicola; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Bjelogrlic, Sandro; Blanco, Fernando; Blau, Dmitry; Blume, Christoph; Bock, Friederike; Bogdanov, Alexey; Boggild, Hans; Bogolyubskiy, Mikhail; Boehmer, Felix Valentin; Boldizsar, Laszlo; Bombara, Marek; Book, Julian Heinz; Borel, Herve; Borissov, Alexander; Bossu, Francesco; Botje, Michiel; Botta, Elena; Boettger, Stefan; Braun-Munzinger, Peter; Bregant, Marco; Breitner, Timo Gunther; Broker, Theo Alexander; Browning, Tyler Allen; Broz, Michal; Bruna, Elena; Bruno, Giuseppe Eugenio; Budnikov, Dmitry; Buesching, Henner; Bufalino, Stefania; Buncic, Predrag; Busch, Oliver; Buthelezi, Edith Zinhle; Caffarri, Davide; Cai, Xu; Caines, Helen Louise; Calero Diaz, Liliet; Caliva, Alberto; Calvo Villar, Ernesto; Camerini, Paolo; Carena, Francesco; Carena, Wisla; Castillo Castellanos, Javier Ernesto; Casula, Ester Anna Rita; Catanescu, Vasile Ioan; Cavicchioli, Costanza; Ceballos Sanchez, Cesar; Cepila, Jan; Cerello, Piergiorgio; Chang, Beomsu; Chapeland, Sylvain; Charvet, Jean-Luc Fernand; Chattopadhyay, Subhasis; Chattopadhyay, Sukalyan; Chelnokov, Volodymyr; Cherney, Michael Gerard; Cheshkov, Cvetan Valeriev; Cheynis, Brigitte; Chibante Barroso, Vasco Miguel; Dobrigkeit Chinellato, David; Chochula, Peter; Chojnacki, Marek; Choudhury, Subikash; Christakoglou, Panagiotis; Christensen, Christian Holm; Christiansen, Peter; Chujo, Tatsuya; Chung, Suh-Urk; Cicalo, Corrado; Cifarelli, Luisa; Cindolo, Federico; Cleymans, Jean Willy Andre; Colamaria, Fabio Filippo; Colella, Domenico; Collu, Alberto; Colocci, Manuel; Conesa Balbastre, Gustavo; Conesa Del Valle, Zaida; Connors, Megan Elizabeth; Contreras Nuno, Jesus Guillermo; Cormier, Thomas Michael; Corrales Morales, Yasser; Cortese, Pietro; Cortes Maldonado, Ismael; Cosentino, Mauro Rogerio; Costa, Filippo; Crochet, Philippe; Cruz Albino, Rigoberto; Cuautle Flores, Eleazar; Cunqueiro Mendez, Leticia; Dainese, Andrea; Dang, Ruina; Danu, Andrea; Das, Debasish; Das, Indranil; Das, Kushal; Das, Supriya; Dash, Ajay Kumar; Dash, Sadhana; De, Sudipan; Delagrange, Hugues; Deloff, Andrzej; Denes, Ervin Sandor; D'Erasmo, Ginevra; De Caro, Annalisa; De Cataldo, Giacinto; De Cuveland, Jan; De Falco, Alessandro; De Gruttola, Daniele; De Marco, Nora; De Pasquale, Salvatore; De Rooij, Raoul Stefan; Diaz Corchero, Miguel Angel; Dietel, Thomas; Dillenseger, Pascal; Divia, Roberto; Di Bari, Domenico; Di Liberto, Sergio; Di Mauro, Antonio; Di Nezza, Pasquale; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Dobrowolski, Tadeusz Antoni; Domenicis Gimenez, Diogenes; Donigus, Benjamin; Dordic, Olja; Dorheim, Sverre; Dubey, Anand Kumar; Dubla, Andrea; Ducroux, Laurent; Dupieux, Pascal; Dutt Mazumder, Abhee Kanti; Hilden, Timo Eero; Ehlers Iii, Raymond James; Elia, Domenico; Engel, Heiko; Erazmus, Barbara Ewa; Erdal, Hege Austrheim; Eschweiler, Dominic; Espagnon, Bruno; Esposito, Marco; Estienne, Magali Danielle; Esumi, Shinichi; Evans, David; Evdokimov, Sergey; Fabris, Daniela; Faivre, Julien; Falchieri, Davide; Fantoni, Alessandra; Fasel, Markus; Fehlker, Dominik; Feldkamp, Linus; Felea, Daniel; Feliciello, Alessandro; Feofilov, Grigory; Ferencei, Jozef; Fernandez Tellez, Arturo; Gonzalez Ferreiro, Elena; Ferretti, Alessandro; Festanti, Andrea; Figiel, Jan; Araujo Silva Figueredo, Marcel; Filchagin, Sergey; Finogeev, Dmitry; Fionda, Fiorella; Fiore, Enrichetta Maria; Floratos, Emmanouil; Floris, Michele; Foertsch, Siegfried Valentin; Foka, Panagiota; Fokin, Sergey; Fragiacomo, Enrico; Francescon, Andrea; Frankenfeld, Ulrich Michael; Fuchs, Ulrich; Furget, Christophe; Fusco Girard, Mario; Gaardhoeje, Jens Joergen; Gagliardi, Martino; Gago Medina, Alberto Martin; Gallio, Mauro; Gangadharan, Dhevan Raja; Ganoti, Paraskevi; Garabatos Cuadrado, Jose; Garcia-Solis, Edmundo Javier; Gargiulo, Corrado; Garishvili, Irakli; Gerhard, Jochen; Germain, Marie; Gheata, Andrei George; Gheata, Mihaela; Ghidini, Bruno; Ghosh, Premomoy; Ghosh, Sanjay Kumar; Gianotti, Paola; Giubellino, Paolo; Gladysz-Dziadus, Ewa; Glassel, Peter; Gomez Ramirez, Andres; Gonzalez Zamora, Pedro; Gorbunov, Sergey; Gorlich, Lidia Maria; Gotovac, Sven; Graczykowski, Lukasz Kamil; Grelli, Alessandro; Grigoras, Alina Gabriela; Grigoras, Costin; Grigoryev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grynyov, Borys; Grion, Nevio; Grosse-Oetringhaus, Jan Fiete; Grossiord, Jean-Yves; Grosso, Raffaele; Guber, Fedor; Guernane, Rachid; Guerzoni, Barbara; Guilbaud, Maxime Rene Joseph; Gulbrandsen, Kristjan Herlache; Gulkanyan, Hrant; Gumbo, Mervyn; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Khan, Kamal; Haake, Rudiger; Haaland, Oystein Senneset; Hadjidakis, Cynthia Marie; Haiduc, Maria; Hamagaki, Hideki; Hamar, Gergoe; Hanratty, Luke David; Hansen, Alexander; Harris, John William; Hartmann, Helvi; Harton, Austin Vincent; Hatzifotiadou, Despina; Hayashi, Shinichi; Heckel, Stefan Thomas; Heide, Markus Ansgar; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Hess, Benjamin Andreas; Hetland, Kristin Fanebust; Hippolyte, Boris; Hladky, Jan; Hristov, Peter Zahariev; Huang, Meidana; Humanic, Thomas; Hussain, Nur; Hutter, Dirk; Hwang, Dae Sung; Ilkaev, Radiy; Ilkiv, Iryna; Inaba, Motoi; Innocenti, Gian Michele; Ionita, Costin; Ippolitov, Mikhail; Irfan, Muhammad; Ivanov, Marian; Ivanov, Vladimir; Jacholkowski, Adam Wlodzimierz; Jacobs, Peter Martin; Jahnke, Cristiane; Jang, Haeng Jin; Janik, Malgorzata Anna; Pahula Hewage, Sandun; Jena, Chitrasen; Jena, Satyajit; Jimenez Bustamante, Raul Tonatiuh; Jones, Peter Graham; Jung, Hyungtaik; Jusko, Anton; Kadyshevskiy, Vladimir; Kalcher, Sebastian; Kalinak, Peter; Kalweit, Alexander Philipp; Kamin, Jason Adrian; Kang, Ju Hwan; Kaplin, Vladimir; Kar, Somnath; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karpechev, Evgeny; Kebschull, Udo Wolfgang; Keidel, Ralf; Keijdener, Darius Laurens; Khan, Mohammed Mohisin; Khan, Palash; Khan, Shuaib Ahmad; Khanzadeev, Alexei; Kharlov, Yury; Kileng, Bjarte; Kim, Beomkyu; Kim, Do Won; Kim, Dong Jo; Kim, Jinsook; Kim, Mimae; Kim, Minwoo; Kim, Se Yong; Kim, Taesoo; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Kiss, Gabor; Klay, Jennifer Lynn; Klein, Jochen; Klein-Boesing, Christian; Kluge, Alexander; Knichel, Michael Linus; Knospe, Anders Garritt; Kobdaj, Chinorat; Kofarago, Monika; Kohler, Markus Konrad; Kollegger, Thorsten; Kolozhvari, Anatoly; Kondratev, Valerii; Kondratyeva, Natalia; Konevskikh, Artem; Kovalenko, Vladimir; Kowalski, Marek; Kox, Serge; Koyithatta Meethaleveedu, Greeshma; Kral, Jiri; Kralik, Ivan; Kramer, Frederick; Kravcakova, Adela; Krelina, Michal; Kretz, Matthias; Krivda, Marian; Krizek, Filip; Kryshen, Evgeny; Krzewicki, Mikolaj; Kucera, Vit; Kucheryaev, Yury; Kugathasan, Thanushan; Kuhn, Christian Claude; Kuijer, Paulus Gerardus; Kulakov, Igor; Kumar, Jitendra; Kurashvili, Podist; Kurepin, Alexander; Kurepin, Alexey; Kuryakin, Alexey; Kushpil, Svetlana; Kweon, Min Jung; Kwon, Youngil; Ladron De Guevara, Pedro; Lagana Fernandes, Caio; Lakomov, Igor; Langoy, Rune; Lara Martinez, Camilo Ernesto; Lardeux, Antoine Xavier; Lattuca, Alessandra; La Pointe, Sarah Louise; La Rocca, Paola; Lea, Ramona; Leardini, Lucia; Lee, Graham Richard; Legrand, Iosif; Lehnert, Joerg Walter; Lemmon, Roy Crawford; Lenti, Vito; Leogrande, Emilia; Leoncino, Marco; Leon Monzon, Ildefonso; Levai, Peter; Li, Shuang; Lien, Jorgen Andre; Lietava, Roman; Lindal, Svein; Lindenstruth, Volker; Lippmann, Christian; Lisa, Michael Annan; Ljunggren, Hans Martin; Lodato, Davide Francesco; Lonne, Per-Ivar; Loggins, Vera Renee; Loginov, Vitaly; Lohner, Daniel; Loizides, Constantinos; Lopez, Xavier Bernard; Lopez Torres, Ernesto; Lu, Xianguo; Luettig, Philipp Johannes; Lunardon, Marcello; Luparello, Grazia; Ma, Rongrong; Maevskaya, Alla; Mager, Magnus; Mahapatra, Durga Prasad; Mahmood, Sohail Musa; Maire, Antonin; Majka, Richard Daniel; Malaev, Mikhail; Maldonado Cervantes, Ivonne Alicia; Malinina, Liudmila; Mal'Kevich, Dmitry; Malzacher, Peter; Mamonov, Alexander; Manceau, Loic Henri Antoine; Manko, Vladislav; Manso, Franck; Manzari, Vito; Marchisone, Massimiliano; Mares, Jiri; Margagliotti, Giacomo Vito; Margotti, Anselmo; Marin, Ana Maria; Markert, Christina; Marquard, Marco; Martashvili, Irakli; Martin, Nicole Alice; Martinengo, Paolo; Martinez Hernandez, Mario Ivan; Martinez-Garcia, Gines; Martin Blanco, Javier; Martynov, Yevgen; Mas, Alexis Jean-Michel; Masciocchi, Silvia; Masera, Massimo; Masoni, Alberto; Massacrier, Laure Marie; Mastroserio, Annalisa; Matyja, Adam Tomasz; Mayer, Christoph; Mazer, Joel Anthony; Mazzoni, Alessandra Maria; Meddi, Franco; Menchaca-Rocha, Arturo Alejandro; Mercado-Perez, Jorge; Meres, Michal; Miake, Yasuo; Mikhaylov, Konstantin; Milano, Leonardo; Milosevic, Jovan; Mischke, Andre; Mishra, Aditya Nath; Miskowiec, Dariusz Czeslaw; Mitra, Jubin; Mitu, Ciprian Mihai; Mlynarz, Jocelyn; Mohammadi, Naghmeh; Mohanty, Bedangadas; Molnar, Levente; Montano Zetina, Luis Manuel; Montes Prado, Esther; Morando, Maurizio; Moreira De Godoy, Denise Aparecida; Moretto, Sandra; Morsch, Andreas; Muccifora, Valeria; Mudnic, Eugen; Muhlheim, Daniel Michael; Muhuri, Sanjib; Mukherjee, Maitreyee; Muller, Hans; Gameiro Munhoz, Marcelo; Murray, Sean; Musa, Luciano; Musinsky, Jan; Nandi, Basanta Kumar; Nania, Rosario; Nappi, Eugenio; Nattrass, Christine; Nayak, Kishora; Nayak, Tapan Kumar; Nazarenko, Sergey; Nedosekin, Alexander; Nicassio, Maria; Niculescu, Mihai; Nielsen, Borge Svane; Nikolaev, Sergey; Nikulin, Sergey; Nikulin, Vladimir; Nilsen, Bjorn Steven; Noferini, Francesco; Nomokonov, Petr; Nooren, Gerardus; Norman, Jaime; Nyanin, Alexander; Nystrand, Joakim Ingemar; Oeschler, Helmut Oskar; Oh, Saehanseul; Oh, Sun Kun; Okatan, Ali; Olah, Laszlo; Oleniacz, Janusz; Oliveira Da Silva, Antonio Carlos; Onderwaater, Jacobus; Oppedisano, Chiara; Ortiz Velasquez, Antonio; Oskarsson, Anders Nils Erik; Otwinowski, Jacek Tomasz; Oyama, Ken; Sahoo, Pragati; Pachmayer, Yvonne Chiara; Pachr, Milos; Pagano, Paola; Paic, Guy; Painke, Florian; Pajares Vales, Carlos; Pal, Susanta Kumar; Palmeri, Armando; Pant, Divyash; Papikyan, Vardanush; Pappalardo, Giuseppe; Pareek, Pooja; Park, Woojin; Parmar, Sonia; Passfeld, Annika; Patalakha, Dmitry; Paticchio, Vincenzo; Paul, Biswarup; Pawlak, Tomasz Jan; Peitzmann, Thomas; Pereira Da Costa, Hugo Denis Antonio; Pereira De Oliveira Filho, Elienos; Peresunko, Dmitry Yurevich; Perez Lara, Carlos Eugenio; Pesci, Alessandro; Peskov, Vladimir; Pestov, Yury; Petracek, Vojtech; Petran, Michal; Petris, Mariana; Petrovici, Mihai; Petta, Catia; Piano, Stefano; Pikna, Miroslav; Pillot, Philippe; Pinazza, Ombretta; Pinsky, Lawrence; Piyarathna, Danthasinghe; Ploskon, Mateusz Andrzej; Planinic, Mirko; Pluta, Jan Marian; Pochybova, Sona; Podesta Lerma, Pedro Luis Manuel; Poghosyan, Martin; Pohjoisaho, Esko Heikki Oskari; Polishchuk, Boris; Poljak, Nikola; Pop, Amalia; Porteboeuf, Sarah Julie; Porter, R Jefferson; Potukuchi, Baba; Prasad, Sidharth Kumar; Preghenella, Roberto; Prino, Francesco; Pruneau, Claude Andre; Pshenichnov, Igor; Puddu, Giovanna; Pujahari, Prabhat Ranjan; Punin, Valery; Putschke, Jorn Henning; Qvigstad, Henrik; Rachevski, Alexandre; Raha, Sibaji; Rak, Jan; Rakotozafindrabe, Andry Malala; Ramello, Luciano; Raniwala, Rashmi; Raniwala, Sudhir; Rasanen, Sami Sakari; Rascanu, Bogdan Theodor; Rathee, Deepika; Rauf, Aamer Wali; Razazi, Vahedeh; Read, Kenneth Francis; Real, Jean-Sebastien; Redlich, Krzysztof; Reed, Rosi Jan; Rehman, Attiq Ur; Reichelt, Patrick Simon; Reicher, Martijn; Reidt, Felix; Renfordt, Rainer Arno Ernst; Reolon, Anna Rita; Reshetin, Andrey; Rettig, Felix Vincenz; Revol, Jean-Pierre; Reygers, Klaus Johannes; Riabov, Viktor; Ricci, Renato Angelo; Richert, Tuva Ora Herenui; Richter, Matthias Rudolph; Riedler, Petra; Riegler, Werner; Riggi, Francesco; Rivetti, Angelo; Rocco, Elena; Rodriguez Cahuantzi, Mario; Rodriguez Manso, Alis; Roeed, Ketil; Rogochaya, Elena; Sharma, Rohni; Rohr, David Michael; Roehrich, Dieter; Romita, Rosa; Ronchetti, Federico; Ronflette, Lucile; Rosnet, Philippe; Rossi, Andrea; Roukoutakis, Filimon; Roy, Ankhi; Roy, Christelle Sophie; Roy, Pradip Kumar; Rubio Montero, Antonio Juan; Rui, Rinaldo; Russo, Riccardo; Ryabinkin, Evgeny; Ryabov, Yury; Rybicki, Andrzej; Sadovskiy, Sergey; Safarik, Karel; Sahlmuller, Baldo; Sahoo, Raghunath; Sahu, Pradip Kumar; Saini, Jogender; Sakai, Shingo; Salgado Lopez, Carlos Alberto; Salzwedel, Jai Samuel Nielsen; Sambyal, Sanjeev Singh; Samsonov, Vladimir; Sanchez Castro, Xitzel; Sanchez Rodriguez, Fernando Javier; Sandor, Ladislav; Sandoval, Andres; Sano, Masato; Santagati, Gianluca; Sarkar, Debojit; Scapparone, Eugenio; Scarlassara, Fernando; Scharenberg, Rolf Paul; Schiaua, Claudiu Cornel; Schicker, Rainer Martin; Schmidt, Christian Joachim; Schmidt, Hans Rudolf; Schuchmann, Simone; Schukraft, Jurgen; Schulc, Martin; Schuster, Tim Robin; Schutz, Yves Roland; Schwarz, Kilian Eberhard; Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Rebecca Michelle; Segato, Gianfranco; Seger, Janet Elizabeth; Sekiguchi, Yuko; Selyuzhenkov, Ilya; Seo, Jeewon; Serradilla Rodriguez, Eulogio; Sevcenco, Adrian; Shabetai, Alexandre; Shabratova, Galina; Shahoyan, Ruben; Shangaraev, Artem; Sharma, Natasha; Sharma, Satish; Shigaki, Kenta; Shtejer Diaz, Katherin; Sibiryak, Yury; Sicking, Eva; Siddhanta, Sabyasachi; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Silvestre, Catherine Micaela; Simatovic, Goran; Singaraju, Rama Narayana; Singh, Ranbir; Singha, Subhash; Singhal, Vikas; Sinha, Bikash; Sarkar - Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Skjerdal, Kyrre; Slupecki, Maciej; Smirnov, Nikolai; Snellings, Raimond; Soegaard, Carsten; Soltz, Ron Ariel; Song, Jihye; Song, Myunggeun; Soramel, Francesca; Sorensen, Soren Pontoppidan; Spacek, Michal; Spiriti, Eleuterio; Sputowska, Iwona Anna; Spyropoulou-Stassinaki, Martha; Srivastava, Brijesh Kumar; Stachel, Johanna; Stan, Ionel; Stefanek, Grzegorz; Steinpreis, Matthew Donald; Stenlund, Evert Anders; Steyn, Gideon Francois; Stiller, Johannes Hendrik; Stocco, Diego; Stolpovskiy, Mikhail; Strmen, Peter; Alarcon Do Passo Suaide, Alexandre; Sugitate, Toru; Suire, Christophe Pierre; Suleymanov, Mais Kazim Oglu; Sultanov, Rishat; Sumbera, Michal; Susa, Tatjana; Symons, Timothy; Szabo, Alexander; Szanto De Toledo, Alejandro; Szarka, Imrich; Szczepankiewicz, Adam; Szymanski, Maciej Pawel; Takahashi, Jun; Tangaro, Marco-Antonio; Tapia Takaki, Daniel Jesus; Tarantola Peloni, Attilio; Tarazona Martinez, Alfonso; Tarzila, Madalina-Gabriela; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terrevoli, Cristina; Thaeder, Jochen Mathias; Thomas, Deepa; Tieulent, Raphael Noel; Timmins, Anthony Robert; Toia, Alberica; Trubnikov, Victor; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ullaland, Kjetil; Uras, Antonio; Usai, Gianluca; Vajzer, Michal; Vala, Martin; Valencia Palomo, Lizardo; Vallero, Sara; Vande Vyvre, Pierre; Van Der Maarel, Jasper; Van Hoorne, Jacobus Willem; Van Leeuwen, Marco; Diozcora Vargas Trevino, Aurora; Vargyas, Marton; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vechernin, Vladimir; Veldhoen, Misha; Velure, Arild; Venaruzzo, Massimo; Vercellin, Ermanno; Vergara Limon, Sergio; Vernet, Renaud; Verweij, Marta; Vickovic, Linda; Viesti, Giuseppe; Viinikainen, Jussi Samuli; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Vinogradov, Alexander; Vinogradov, Leonid; Vinogradov, Yury; Virgili, Tiziano; Viyogi, Yogendra; Vodopyanov, Alexander; Volkl, Martin Andreas; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; Von Haller, Barthelemy; Vorobyev, Ivan; Vranic, Danilo; Vrlakova, Janka; Vulpescu, Bogdan; Vyushin, Alexey; Wagner, Boris; Wagner, Jan; Wagner, Vladimir; Wang, Mengliang; Wang, Yifei; Watanabe, Daisuke; Weber, Michael; Wessels, Johannes Peter; Westerhoff, Uwe; Wiechula, Jens; Wikne, Jon; Wilde, Martin Rudolf; Wilk, Grzegorz Andrzej; Wilkinson, Jeremy John; Williams, Crispin; Windelband, Bernd Stefan; Winn, Michael Andreas; Yaldo, Chris G; Yamaguchi, Yorito; Yang, Hongyan; Yang, Ping; Yang, Shiming; Yano, Satoshi; Yasnopolskiy, Stanislav; Yi, Jungyu; Yin, Zhongbao; Yoo, In-Kwon; Yushmanov, Igor; Zaccolo, Valentina; Zach, Cenek; Zaman, Ali; Zampolli, Chiara; Zaporozhets, Sergey; Zarochentsev, Andrey; Zavada, Petr; Zavyalov, Nikolay; Zbroszczyk, Hanna Paulina; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhang, Yonghong; Zhao, Chengxin; Zhigareva, Natalia; Zhou, Daicui; Zhou, Fengchu; Zhou, You; Zhou, Zhuo; Zhu, Hongsheng; Zhu, Jianhui; Zhu, Xiangrong; Zichichi, Antonino; Zimmermann, Alice; Zimmermann, Markus Bernhard; Zinovjev, Gennady; Zoccarato, Yannick Denis; Zyzak, Maksym

    2015-02-04

    Two-particle angular correlations between unidentified charged trigger and associated particles are measured by the ALICE detector in p–Pb collisions at a nucleon–nucleon centre-of-mass energy of 5.02 TeV. The transverse-momentum range 0.7 < $p_{T,assoc} < p_{T,trig}$ < 5.0 GeV/c is examined, to include correlations induced by jets originating from low momentum-transfer scatterings (minijets). The correlations expressed as associated yield per trigger particle are obtained in the pseudorapidity range |η| < 0.9. The near-side long-range pseudorapidity correlations observed in high-multiplicity p–Pb collisions are subtracted from both near-side short-range and away-side correlations in order to remove the non- jet-like components. The yields in the jet-like peaks are found to be invariant with event multiplicity with the exception of events with low multiplicity. This invariance is consistent with the particles being produced via the incoherent fragmentation of multiple parton–parton scatte...

  1. Mridangam stroke dataset

    OpenAIRE

    CompMusic

    2014-01-01

    The audio examples were recorded from a professional Carnatic percussionist in a semi-anechoic studio conditions by Akshay Anantapadmanabhan using SM-58 microphones and an H4n ZOOM recorder. The audio was sampled at 44.1 kHz and stored as 16 bit wav files. The dataset can be used for training models for each Mridangam stroke. /n/nA detailed description of the Mridangam and its strokes can be found in the paper below. A part of the dataset was used in the following paper. /nAkshay Anantapadman...

  2. Development of a SPARK Training Dataset

    International Nuclear Information System (INIS)

    Sayre, Amanda M.; Olson, Jarrod R.

    2015-01-01

    In its first five years, the National Nuclear Security Administration's (NNSA) Next Generation Safeguards Initiative (NGSI) sponsored more than 400 undergraduate, graduate, and post-doctoral students in internships and research positions (Wyse 2012). In the past seven years, the NGSI program has, and continues to produce a large body of scientific, technical, and policy work in targeted core safeguards capabilities and human capital development activities. Not only does the NGSI program carry out activities across multiple disciplines, but also across all U.S. Department of Energy (DOE)/NNSA locations in the United States. However, products are not readily shared among disciplines and across locations, nor are they archived in a comprehensive library. Rather, knowledge of NGSI-produced literature is localized to the researchers, clients, and internal laboratory/facility publication systems such as the Electronic Records and Information Capture Architecture (ERICA) at the Pacific Northwest National Laboratory (PNNL). There is also no incorporated way of analyzing existing NGSI literature to determine whether the larger NGSI program is achieving its core safeguards capabilities and activities. A complete library of NGSI literature could prove beneficial to a cohesive, sustainable, and more economical NGSI program. The Safeguards Platform for Automated Retrieval of Knowledge (SPARK) has been developed to be a knowledge storage, retrieval, and analysis capability to capture safeguards knowledge to exist beyond the lifespan of NGSI. During the development process, it was necessary to build a SPARK training dataset (a corpus of documents) for initial entry into the system and for demonstration purposes. We manipulated these data to gain new information about the breadth of NGSI publications, and they evaluated the science-policy interface at PNNL as a practical demonstration of SPARK's intended analysis capability. The analysis demonstration sought to answer

  3. A first dataset toward a standardized community-driven global mapping of the human immunopeptidome

    Directory of Open Access Journals (Sweden)

    Pouya Faridi

    2016-06-01

    Full Text Available We present the first standardized HLA peptidomics dataset generated by the immunopeptidomics community. The dataset is composed of native HLA class I peptides as well as synthetic HLA class II peptides that were acquired in data-dependent acquisition mode using multiple types of mass spectrometers. All laboratories used the spiked-in landmark iRT peptides for retention time normalization and data analysis. The mass spectrometric data were deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier http://www.ebi.ac.uk/pride/archive/projects/PXD001872. The generated data were used to build HLA allele-specific peptide spectral and assay libraries, which were stored in the SWATHAtlas database. Data presented here are described in more detail in the original eLife article entitled ‘An open-source computational and data resource to analyze digital maps of immunopeptidomes’.

  4. Modelling and analysis of turbulent datasets using Auto Regressive Moving Average processes

    International Nuclear Information System (INIS)

    Faranda, Davide; Dubrulle, Bérengère; Daviaud, François; Pons, Flavio Maria Emanuele; Saint-Michel, Brice; Herbert, Éric; Cortet, Pierre-Philippe

    2014-01-01

    We introduce a novel way to extract information from turbulent datasets by applying an Auto Regressive Moving Average (ARMA) statistical analysis. Such analysis goes well beyond the analysis of the mean flow and of the fluctuations and links the behavior of the recorded time series to a discrete version of a stochastic differential equation which is able to describe the correlation structure in the dataset. We introduce a new index Υ that measures the difference between the resulting analysis and the Obukhov model of turbulence, the simplest stochastic model reproducing both Richardson law and the Kolmogorov spectrum. We test the method on datasets measured in a von Kármán swirling flow experiment. We found that the ARMA analysis is well correlated with spatial structures of the flow, and can discriminate between two different flows with comparable mean velocities, obtained by changing the forcing. Moreover, we show that the Υ is highest in regions where shear layer vortices are present, thereby establishing a link between deviations from the Kolmogorov model and coherent structures. These deviations are consistent with the ones observed by computing the Hurst exponents for the same time series. We show that some salient features of the analysis are preserved when considering global instead of local observables. Finally, we analyze flow configurations with multistability features where the ARMA technique is efficient in discriminating different stability branches of the system

  5. Thermal effects in the hadronic and photonic multiplicity distributions and correlations: a thermo-field dynamic approach

    International Nuclear Information System (INIS)

    Bambah, Bindu A.; Mogurampally, Naveen Kumar

    2016-01-01

    The existence of the Quark Gluon Plasma (QGP) requires that in the collision of heavy ions an initial fireball is formed which has a lifetime larger than typical hadronic time scale of 10"−"2"3 sec and that the temperature and volume of the fireball is sufficient to ensure that the Quark Hadron phase transition predicted by statistical QCD is achieved. Then the pions and photons emitted from this hot fire ball may carry information of the temperature and life time of the emitting region, and this may manifest itself in the correlation functions and multiplicities which can be modified by finite temperature. Thus it is important to find ways of incorporating finite temperature effects in multiplicity distributions and correlations. The Thermo field formalism is particularly useful in the description of parametric dynamical systems in which squeezing of quantum fluctuations is important

  6. 2008 TIGER/Line Nationwide Dataset

    Data.gov (United States)

    California Natural Resource Agency — This dataset contains a nationwide build of the 2008 TIGER/Line datasets from the US Census Bureau downloaded in April 2009. The TIGER/Line Shapefiles are an extract...

  7. Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

    Science.gov (United States)

    Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

    2017-04-01

    Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall

  8. Correlated Noise: How it Breaks NMF, and What to Do About It.

    Science.gov (United States)

    Plis, Sergey M; Potluru, Vamsi K; Lane, Terran; Calhoun, Vince D

    2011-01-12

    Non-negative matrix factorization (NMF) is a problem of decomposing multivariate data into a set of features and their corresponding activations. When applied to experimental data, NMF has to cope with noise, which is often highly correlated. We show that correlated noise can break the Donoho and Stodden separability conditions of a dataset and a regular NMF algorithm will fail to decompose it, even when given freedom to be able to represent the noise as a separate feature. To cope with this issue, we present an algorithm for NMF with a generalized least squares objective function (glsNMF) and derive multiplicative updates for the method together with proving their convergence. The new algorithm successfully recovers the true representation from the noisy data. Robust performance can make glsNMF a valuable tool for analyzing empirical data.

  9. Multiple Speech Source Separation Using Inter-Channel Correlation and Relaxed Sparsity

    Directory of Open Access Journals (Sweden)

    Maoshen Jia

    2018-01-01

    Full Text Available In this work, a multiple speech source separation method using inter-channel correlation and relaxed sparsity is proposed. A B-format microphone with four spatially located channels is adopted due to the size of the microphone array to preserve the spatial parameter integrity of the original signal. Specifically, we firstly measure the proportion of overlapped components among multiple sources and find that there exist many overlapped time-frequency (TF components with increasing source number. Then, considering the relaxed sparsity of speech sources, we propose a dynamic threshold-based separation approach of sparse components where the threshold is determined by the inter-channel correlation among the recording signals. After conducting a statistical analysis of the number of active sources at each TF instant, a form of relaxed sparsity called the half-K assumption is proposed so that the active source number in a certain TF bin does not exceed half the total number of simultaneously occurring sources. By applying the half-K assumption, the non-sparse components are recovered by regarding the extracted sparse components as a guide, combined with vector decomposition and matrix factorization. Eventually, the final TF coefficients of each source are recovered by the synthesis of sparse and non-sparse components. The proposed method has been evaluated using up to six simultaneous speech sources under both anechoic and reverberant conditions. Both objective and subjective evaluations validated that the perceptual quality of the separated speech by the proposed approach outperforms existing blind source separation (BSS approaches. Besides, it is robust to different speeches whilst confirming all the separated speeches with similar perceptual quality.

  10. Background qualitative analysis of the European reference life cycle database (ELCD) energy datasets - part II: electricity datasets.

    Science.gov (United States)

    Garraín, Daniel; Fazio, Simone; de la Rúa, Cristina; Recchioni, Marco; Lechón, Yolanda; Mathieux, Fabrice

    2015-01-01

    The aim of this paper is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) electricity datasets. The revision is based on the data quality indicators described by the International Life Cycle Data system (ILCD) Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. Results show that ELCD electricity datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the electricity-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD electricity datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall Data Quality Requirements of databases.

  11. Designs of Optoelectronic Trinary Signed-Digit Multiplication by use of Joint Spatial Encodings and Optical Correlation

    Science.gov (United States)

    Cherri, Abdallah K.

    1999-02-01

    Trinary signed-digit (TSD) symbolic-substitution-based (SS-based) optical adders, which were recently proposed, are used as the basic modules for designing highly parallel optical multiplications by use of cascaded optical correlators. The proposed multiplications perform carry-free generation of the multiplication partial products of two words in constant time. Also, three different multiplication designs are presented, and new joint spatial encodings for the TSD numbers are introduced. The proposed joint spatial encodings allow one to reduce the SS computation rules involved in optical multiplication. In addition, the proposed joint spatial encodings increase the space bandwidth product of the spatial light modulators of the optical system. This increase is achieved by reduction of the numbers of pixels in the joint spatial encodings for the input TSD operands as well as reduction of the number of pixels used in the proposed matched spatial filters for the optical multipliers.

  12. Robust computational analysis of rRNA hypervariable tag datasets.

    Directory of Open Access Journals (Sweden)

    Maksim Sipos

    Full Text Available Next-generation DNA sequencing is increasingly being utilized to probe microbial communities, such as gastrointestinal microbiomes, where it is important to be able to quantify measures of abundance and diversity. The fragmented nature of the 16S rRNA datasets obtained, coupled with their unprecedented size, has led to the recognition that the results of such analyses are potentially contaminated by a variety of artifacts, both experimental and computational. Here we quantify how multiple alignment and clustering errors contribute to overestimates of abundance and diversity, reflected by incorrect OTU assignment, corrupted phylogenies, inaccurate species diversity estimators, and rank abundance distribution functions. We show that straightforward procedural optimizations, combining preexisting tools, are effective in handling large (10(5-10(6 16S rRNA datasets, and we describe metrics to measure the effectiveness and quality of the estimators obtained. We introduce two metrics to ascertain the quality of clustering of pyrosequenced rRNA data, and show that complete linkage clustering greatly outperforms other widely used methods.

  13. Modeling Rabbit Responses to Single and Multiple Aerosol ...

    Science.gov (United States)

    Journal Article Survival models are developed here to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple dose dataset to predict the probability of death through specifying dose-response functions and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) has an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed employ different underlying dose-response functions and use the assumption that, in a multiple dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this paper. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit datasets. More accurate survival models depend upon future development of dose-response datasets specifically designed to assess potential multiple dose effects on response and time-to-response. The process used in this paper to dev

  14. On correlation between multiplicities of different fragments and deuterons in 16Op-collisions at 3.25 A GeV/C

    International Nuclear Information System (INIS)

    Olimov, K.; Usarov, A.; Bazarov, E.; Karshiev, D.; Fazylov, M.I.; Yuldashev, B.S.

    2004-01-01

    Full text: Production of light fragments is characteristical for nucleus fragmentation phenomenon. Therefore, it is impossible to understand this phenomenon without identifying a production mechanism of these particles. One can have useful information on deuterons formation dynamics by studying correlations between different fragments multiplicities. Thus, this work is dedicated to study of correlations between multiplicities of different fragments in 16 Op-events with deuteron and without. The experimental material was obtained from 1-meter hydrogen bubble chamber in HEL JINR irradiated by 16 O nuclei beam at momentum of 3,25 GeV/C. Methodological questions related to stereo graphs processing, particle and nuclei identification are described in works [1,2]. The results presented below are obtained based on an analysis of 11098 measured 16 Op events. Experimental results on correlations between multiplicities of different fragments and presence (absence) of deuterons in 16 Op-events are compared with data calculated by cascade-fragmentation evaporation model (CFEM) [3]. In frames of CFEM [3] the main mechanism of fragments production is Fermi break-up. Contribution of 'evaporative mechanism' to light fragments production can be neglected for fragmentation of such light nucleus as 16 O. Experimental values for average multiplicities of light fragments ( 1 H 1 , 3 H 1 , 3 He 2 and 4 He 2 ) in events with deuteron and without demonstrate their dependence on presence of deuteron. Appearance of 1 H 1 and 4 He 2 in events with deuterons is ∼1,75 times higher that that without deuteron; whereas for mirror nuclei 3 H 1 and 3 He 2 this difference is more than ∼2,7 times higher. Notice, average multiplicities of these mirror nuclei within statistical errors are in coincidence with each other independently of presence or absence of deuteron in this event. In CFEM, correlations between average multiplicities of fragments and presence of deuteron in the event are observed

  15. The GTZAN dataset

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    The GTZAN dataset appears in at least 100 published works, and is the most-used public dataset for evaluation in machine listening research for music genre recognition (MGR). Our recent work, however, shows GTZAN has several faults (repetitions, mislabelings, and distortions), which challenge...... of GTZAN, and provide a catalog of its faults. We review how GTZAN has been used in MGR research, and find few indications that its faults have been known and considered. Finally, we rigorously study the effects of its faults on evaluating five different MGR systems. The lesson is not to banish GTZAN...

  16. Stochastic resonance and MFPT in an asymmetric bistable system driven by correlated multiplicative colored noise and additive white noise

    Science.gov (United States)

    Shi, Pei-Ming; Li, Qun; Han, Dong-Ying

    2017-06-01

    This paper investigates a new asymmetric bistable model driven by correlated multiplicative colored noise and additive white noise. The mean first-passage time (MFPT) and the signal-to-noise ratio (SNR) as the indexes of evaluating the model are researched. Based on the two-state theory and the adiabatic approximation theory, the expressions of MFPT and SNR have been obtained for the asymmetric bistable system driven by a periodic signal, correlated multiplicative colored noise and additive noise. Simulation results show that it is easier to generate stochastic resonance (SR) to adjust the intensity of correlation strength λ. Meanwhile, the decrease of asymmetric coefficient r2 and the increase of noise intensity are beneficial to realize the transition between the two steady states in the system. At the same time, the twice SR phenomena can be observed by adjusting additive white noise and correlation strength. The influence of asymmetry of potential function on the MFPTs in two different directions is different.

  17. Using neural networks to describe tracer correlations

    Directory of Open Access Journals (Sweden)

    D. J. Lary

    2004-01-01

    Full Text Available Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and methane volume mixing ratio (v.m.r.. In this study a neural network using Quickprop learning and one hidden layer with eight nodes was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9995. Such an accurate representation of tracer-tracer correlations allows more use to be made of long-term datasets to constrain chemical models. Such as the dataset from the Halogen Occultation Experiment (HALOE which has continuously observed CH4  (but not N2O from 1991 till the present. The neural network Fortran code used is available for download.

  18. Sparse multivariate measures of similarity between intra-modal neuroimaging datasets

    Directory of Open Access Journals (Sweden)

    Maria J. Rosa

    2015-10-01

    Full Text Available An increasing number of neuroimaging studies are now based on either combining more than one data modality (inter-modal or combining more than one measurement from the same modality (intra-modal. To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA. However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA, overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labelling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow.

  19. Common pitfalls in statistical analysis: The perils of multiple testing

    Science.gov (United States)

    Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc

    2016-01-01

    Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple subgroups or for multiple end-points. This amplifies the probability of a false-positive finding. In this article, we look at the consequences of multiple testing and explore various methods to deal with this issue. PMID:27141478

  20. Correlated long-range mixed-harmonic fluctuations in $pp$, $p$+Pb and low-multiplicity Pb+Pb collisions with the ATLAS detector

    CERN Document Server

    The ATLAS collaboration

    2018-01-01

    Correlations of two flow harmonics $v_n$ and $v_m$ via three- and four-particle cumulants are measured in 13 TeV $pp$, 5.02 TeV $p$+Pb, and 2.76 TeV peripheral Pb+Pb collisions with the ATLAS detector at the LHC. The goal is to understand the multi-particle nature of the long-range collective phenomenon in these collision systems. The large non-flow background from dijet production present in the standard cumulant method is suppressed using a method of subevent cumulants involving two, three and four pseudorapidity-separated subevents. The results show an anti-correlation between $v_2$ and $v_3$ and a positive correlation between $v_2$ and $v_4$ for all collision systems and over the full multiplicity range. However, the magnitudes of the correlations are found to depend strongly on the event multiplicity, transverse momentum and the collision systems. The relative correlation strength, obtained by normalization of the cumulants with the $\\langle v_n^2\\rangle$ from a two-particle correlation analysis, is simi...

  1. A global gridded dataset of daily precipitation going back to 1950, ideal for analysing precipitation extremes

    Science.gov (United States)

    Contractor, S.; Donat, M.; Alexander, L. V.

    2017-12-01

    Reliable observations of precipitation are necessary to determine past changes in precipitation and validate models, allowing for reliable future projections. Existing gauge based gridded datasets of daily precipitation and satellite based observations contain artefacts and have a short length of record, making them unsuitable to analyse precipitation extremes. The largest limiting factor for the gauge based datasets is a dense and reliable station network. Currently, there are two major data archives of global in situ daily rainfall data, first is Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and the other by Global Precipitation Climatology Centre (GPCC) part of the Deutsche Wetterdienst (DWD). We combine the two data archives and use automated quality control techniques to create a reliable long term network of raw station data, which we then interpolate using block kriging to create a global gridded dataset of daily precipitation going back to 1950. We compare our interpolated dataset with existing global gridded data of daily precipitation: NOAA Climate Prediction Centre (CPC) Global V1.0 and GPCC Full Data Daily Version 1.0, as well as various regional datasets. We find that our raw station density is much higher than other datasets. To avoid artefacts due to station network variability, we provide multiple versions of our dataset based on various completeness criteria, as well as provide the standard deviation, kriging error and number of stations for each grid cell and timestep to encourage responsible use of our dataset. Despite our efforts to increase the raw data density, the in situ station network remains sparse in India after the 1960s and in Africa throughout the timespan of the dataset. Our dataset would allow for more reliable global analyses of rainfall including its extremes and pave the way for better global precipitation observations with lower and more transparent uncertainties.

  2. Resolution testing and limitations of geodetic and tsunami datasets for finite fault inversions along subduction zones

    Science.gov (United States)

    Williamson, A.; Newman, A. V.

    2017-12-01

    Finite fault inversions utilizing multiple datasets have become commonplace for large earthquakes pending data availability. The mixture of geodetic datasets such as Global Navigational Satellite Systems (GNSS) and InSAR, seismic waveforms, and when applicable, tsunami waveforms from Deep-Ocean Assessment and Reporting of Tsunami (DART) gauges, provide slightly different observations that when incorporated together lead to a more robust model of fault slip distribution. The merging of different datasets is of particular importance along subduction zones where direct observations of seafloor deformation over the rupture area are extremely limited. Instead, instrumentation measures related ground motion from tens to hundreds of kilometers away. The distance from the event and dataset type can lead to a variable degree of resolution, affecting the ability to accurately model the spatial distribution of slip. This study analyzes the spatial resolution attained individually from geodetic and tsunami datasets as well as in a combined dataset. We constrain the importance of distance between estimated parameters and observed data and how that varies between land-based and open ocean datasets. Analysis focuses on accurately scaled subduction zone synthetic models as well as analysis of the relationship between slip and data in recent large subduction zone earthquakes. This study shows that seafloor deformation sensitive datasets, like open-ocean tsunami waveforms or seafloor geodetic instrumentation, can provide unique offshore resolution for understanding most large and particularly tsunamigenic megathrust earthquake activity. In most environments, we simply lack the capability to resolve static displacements using land-based geodetic observations.

  3. Correlates of sexual function in male and female patients with multiple sclerosis.

    Science.gov (United States)

    Lew-Starowicz, Michal; Rola, Rafal

    2014-09-01

    Many factors have been suggested to contribute to sexual dysfunction (SD) in multiple sclerosis (MS) patients, but the research on their impact on sexual functioning (SF) and sexual quality of life (SQoL) remains scant. The aim of this study was to investigate correlates of SF and SQoL in MS patients, as well as possible gender differences. 204 MS patients were interviewed, completed the questionnaires, and underwent neurological assessment. Primary outcome measures included the International Index of Erectile Function, the Female Sexual Function Questionnaire, the Sexual Quality of Life Questionnaire, the Beck Depression Inventory, and the Expanded Disability Status Scale. The course and duration of the disease did not predict patients' SF. Negative correlations were found for brainstem symptoms with orgasmic function and overall satisfaction in men and between cognitive functioning and the partner domain in women. Interestingly, brainstem symptoms correlated positively with the arousal domain in women. More than half (52.1%) of patients fulfilled Beck Depression Inventory criteria for depression, and these patients showed more SD than nondepressive individuals. The strongest negative correlations with depressive symptoms were found for desire, erectile function, and overall satisfaction with sexual life in men and for orgasm and sexual enjoyment in women. Deterioration in particular domains of SF was clearly related with diminished SQoL. The main gender difference was a strong influence of decreased desire on SQoL in women and no such correlation in men. Negative assessment of the relationship with partner significantly affected all domains of SF and SQoL in MS women and the desire domain in MS men. Several correlates of SF in MS patients were found. The role of brainstem symptoms needs further investigation. Clinicians should pay close attention to depressive symptoms and relationship factors in MS patients who suffer from SD. © 2014 International Society for

  4. Structural health monitoring and damage assessment using measured FRFs from multiple sensors. Part I. The indicator of correlation criteria

    Energy Technology Data Exchange (ETDEWEB)

    Zang, C.; Friswell, M.I. [Dept. of Aerospace Engineering, Univ. of Bristol, Bristol (United Kingdom); Imregun, M. [Dept. of Mechanical Engineering, Imperial Coll., London (United Kingdom)

    2003-07-01

    This paper presents two criteria for correlating measured frequency responses from multiple sensors and proposes to use them as indicators for structural damage detection. The first criterion is a global shape correlation (GSC) function that is sensitive to mode shape differences but not to relative scales. The second criterion, a global amplitude correlation (GAC) function, is based on actual response amplitudes. Both correlation criteria are a function of frequency and uniquely map a set of complex responses to a real scalar between zero and unity. The averaged integrations of GSC and GAC functions along the frequency points over the measurement range, also called damage indicators, are used to describe the correlation between two sets of vibration data. When a structure state remains unchanged, both correlation criteria are as close to unity simultaneously. Otherwise, the correlation with the reference data will be decreased with changes of structure states. Using GSC and GAC functions has the advantage of being able to deal with incomplete measurements. Also, all available response data are used and hence there is no critical selection of frequency points for damage detection. The above correlation criteria were applied to a bookshelf structure and various cases such as undamaged states, damage locations (single and multiple), damage levels, as well as environmental variability are discussed. As expected, it was found that indicators of correlation criteria were able to identify all various cases correctly. (orig.)

  5. Velocity landscape correlation resolves multiple flowing protein populations from fluorescence image time series.

    Science.gov (United States)

    Pandžić, Elvis; Abu-Arish, Asmahan; Whan, Renee M; Hanrahan, John W; Wiseman, Paul W

    2018-02-16

    Molecular, vesicular and organellar flows are of fundamental importance for the delivery of nutrients and essential components used in cellular functions such as motility and division. With recent advances in fluorescence/super-resolution microscopy modalities we can resolve the movements of these objects at higher spatio-temporal resolutions and with better sensitivity. Previously, spatio-temporal image correlation spectroscopy has been applied to map molecular flows by correlation analysis of fluorescence fluctuations in image series. However, an underlying assumption of this approach is that the sampled time windows contain one dominant flowing component. Although this was true for most of the cases analyzed earlier, in some situations two or more different flowing populations can be present in the same spatio-temporal window. We introduce an approach, termed velocity landscape correlation (VLC), which detects and extracts multiple flow components present in a sampled image region via an extension of the correlation analysis of fluorescence intensity fluctuations. First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics. Finally we apply VLC to study variable fluxing of STIM1 proteins on microtubules connected to the plasma membrane of Cystic Fibrosis Bronchial Epithelial (CFBE) cells. Copyright © 2018 Elsevier Inc. All rights reserved.

  6. SERUM YKL-40 CORRELATES WITH SERUM INTERLEUKIN-6 IN MULTIPLE MYELOMA

    DEFF Research Database (Denmark)

    Mylin, Anne Kjærsgaard; Andersen, Niels Frost; Johansen, Julia S.

    2007-01-01

    Introduction. The secreted glycoprotein YKL-40 (CHI3L1, HC gp-39) is a potential player in the tumor-host interactions affecting several aspects of multiple myeloma (MM) including angiogenesis. YKL-40 expression is seeen in vascular smooth muscle cells, and the protein is suggested to function......, but S-YKL-40 show a strong positive correlation with S-IL-6 consistent with a possible IL-6 mediated regulation of YKL-40 secretion demonstrated in previous studies. Table 1     Normal S-YKL-40 N   Median (range)     Elevated S-YKL-40 N   Median (range)     p-value   S-IL-6, ng/L             PB 23 3 (1...

  7. QSAR study of HCV NS5B polymerase inhibitors using the genetic algorithm-multiple linear regression (GA-MLR).

    Science.gov (United States)

    Rafiei, Hamid; Khanzadeh, Marziyeh; Mozaffari, Shahla; Bostanifar, Mohammad Hassan; Avval, Zhila Mohajeri; Aalizadeh, Reza; Pourbasheer, Eslam

    2016-01-01

    Quantitative structure-activity relationship (QSAR) study has been employed for predicting the inhibitory activities of the Hepatitis C virus (HCV) NS5B polymerase inhibitors . A data set consisted of 72 compounds was selected, and then different types of molecular descriptors were calculated. The whole data set was split into a training set (80 % of the dataset) and a test set (20 % of the dataset) using principle component analysis. The stepwise (SW) and the genetic algorithm (GA) techniques were used as variable selection tools. Multiple linear regression method was then used to linearly correlate the selected descriptors with inhibitory activities. Several validation technique including leave-one-out and leave-group-out cross-validation, Y-randomization method were used to evaluate the internal capability of the derived models. The external prediction ability of the derived models was further analyzed using modified r(2), concordance correlation coefficient values and Golbraikh and Tropsha acceptable model criteria's. Based on the derived results (GA-MLR), some new insights toward molecular structural requirements for obtaining better inhibitory activity were obtained.

  8. Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

    Directory of Open Access Journals (Sweden)

    H. E. Beck

    2017-12-01

    Full Text Available We undertook a comprehensive evaluation of 22 gridded (quasi-global (sub-daily precipitation (P datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized ( <  50 000 km2 catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR and the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7 or near-surface soil moisture (SM2RAIN-ASCAT, and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS. Two of the three reanalyses (ERA-Interim and JRA-55 unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified, and MSWEP V1.2 and V2.0 generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU, which in turn outperformed the one indirectly incorporating gauge data through another multi-source dataset (PERSIANN-CDR V1R1. Our results highlight large differences in estimation accuracy

  9. TU-AB-BRA-11: Evaluation of Fully Automatic Volumetric GBM Segmentation in the TCGA-GBM Dataset: Prognosis and Correlation with VASARI Features

    International Nuclear Information System (INIS)

    Rios Velazquez, E; Meier, R; Dunn, W; Gutman, D; Alexander, B; Wiest, R; Reyes, M; Bauer, S; Aerts, H

    2015-01-01

    Purpose: Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. Methods: MRI sets of 67 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA), including necrosis, edema, contrast enhancing and non-enhancing tumor. Spearman’s correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Results: Auto-segmented sub-volumes showed high agreement with manually delineated volumes (range (r): 0.65 – 0.91). Also showed higher correlation with VASARI features (auto r = 0.35, 0.60 and 0.59; manual r = 0.29, 0.50, 0.43, for contrast-enhancing, necrosis and edema, respectively). The contrast-enhancing volume and post-contrast abnormal volume showed the highest C-index (0.73 and 0.72), comparable to manually defined volumes (p = 0.22 and p = 0.07, respectively). The non-enhancing region defined by BraTumIA showed a significantly higher prognostic value (CI = 0.71) than the edema (CI = 0.60), both of which could not be distinguished by manual delineation. Conclusion: BraTumIA tumor sub-compartments showed higher correlation with VASARI data, and equivalent performance in terms of prognosis compared to manual sub-volumes. This method can enable more reproducible definition and quantification of imaging based biomarkers and has a large potential in high-throughput medical imaging research

  10. TU-AB-BRA-11: Evaluation of Fully Automatic Volumetric GBM Segmentation in the TCGA-GBM Dataset: Prognosis and Correlation with VASARI Features

    Energy Technology Data Exchange (ETDEWEB)

    Rios Velazquez, E [Dana-Farber Cancer Institute | Harvard Medical School, Boston, MA (United States); Meier, R [Institute for Surgical Technology and Biomechanics, Bern, NA (Switzerland); Dunn, W; Gutman, D [Emory University School of Medicine, Atlanta, GA (United States); Alexander, B [Dana- Farber Cancer Institute, Brigham and Womens Hospital, Harvard Medic, Boston, MA (United States); Wiest, R; Reyes, M [Institute for Surgical Technology and Biomechanics, University of Bern, Bern, NA (Switzerland); Bauer, S [Institute for Surgical Technology and Biomechanics, Support Center for Adva, Bern, NA (Switzerland); Aerts, H [Dana-Farber/Brigham Womens Cancer Center, Boston, MA (United States)

    2015-06-15

    Purpose: Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. Methods: MRI sets of 67 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA), including necrosis, edema, contrast enhancing and non-enhancing tumor. Spearman’s correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Results: Auto-segmented sub-volumes showed high agreement with manually delineated volumes (range (r): 0.65 – 0.91). Also showed higher correlation with VASARI features (auto r = 0.35, 0.60 and 0.59; manual r = 0.29, 0.50, 0.43, for contrast-enhancing, necrosis and edema, respectively). The contrast-enhancing volume and post-contrast abnormal volume showed the highest C-index (0.73 and 0.72), comparable to manually defined volumes (p = 0.22 and p = 0.07, respectively). The non-enhancing region defined by BraTumIA showed a significantly higher prognostic value (CI = 0.71) than the edema (CI = 0.60), both of which could not be distinguished by manual delineation. Conclusion: BraTumIA tumor sub-compartments showed higher correlation with VASARI data, and equivalent performance in terms of prognosis compared to manual sub-volumes. This method can enable more reproducible definition and quantification of imaging based biomarkers and has a large potential in high-throughput medical imaging research.

  11. Editorial: Datasets for Learning Analytics

    NARCIS (Netherlands)

    Dietze, Stefan; George, Siemens; Davide, Taibi; Drachsler, Hendrik

    2018-01-01

    The European LinkedUp and LACE (Learning Analytics Community Exchange) project have been responsible for setting up a series of data challenges at the LAK conferences 2013 and 2014 around the LAK dataset. The LAK datasets consists of a rich collection of full text publications in the domain of

  12. Superior temporal gyrus thickness correlates with cognitive performance in multiple sclerosis.

    Science.gov (United States)

    Achiron, Asaf; Chapman, Joab; Tal, Sigal; Bercovich, Eran; Gil, Hararai; Achiron, Anat

    2013-07-01

    Decreased cortical thickness that signifies gray matter pathology and its impact on cognitive performance is a research field with growing interest in relapsing-remitting multiple sclerosis (RRMS) and needs to be further elucidated. Using high-field 3.0 T MRI, three-dimensional T1-FSPGR (voxel size 1 × 1 × 1 mm) cortical thickness was measured in 82 regions in the left hemisphere (LH) and right hemisphere (RH) in 20 RRMS patients with low disease activity and in 20 age-matched healthy subjects that in parallel underwent comprehensive cognitive evaluation. The correlation between local cortical atrophy and cognitive performance was examined. We identified seven regions with cortical tissue loss that differed between RRMS and age-matched healthy controls. These regions were mainly located in the frontal and temporal lobes, specifically within the gyrus rectus, inferior frontal sulcus, orbital gyrus, parahippocampal gyrus, and superior temporal gyrus, with preferential left asymmetry. Increased cortical thickness was identified in two visual sensory regions, the LH inferior occipital gyrus, and the RH cuneus, implicating adaptive plasticity. Correlation analysis demonstrated that only the LH superior temporal gyrus thickness was associated with cognitive performance and its thickness correlated with motor skills (r = 0.65, p = 0.003), attention (r = 0.45, p = 0.042), and information processing speed (r = 0.50, p = 0.025). Our findings show that restricted cortical thinning occurs in RRMS patients with mild disease and that LH superior temporal gyrus atrophy is associated with cognitive dysfunction.

  13. The Geometry of Finite Equilibrium Datasets

    DEFF Research Database (Denmark)

    Balasko, Yves; Tvede, Mich

    We investigate the geometry of finite datasets defined by equilibrium prices, income distributions, and total resources. We show that the equilibrium condition imposes no restrictions if total resources are collinear, a property that is robust to small perturbations. We also show that the set...... of equilibrium datasets is pathconnected when the equilibrium condition does impose restrictions on datasets, as for example when total resources are widely non collinear....

  14. Handling limited datasets with neural networks in medical applications: A small-data approach.

    Science.gov (United States)

    Shaikhina, Torgyn; Khovanova, Natalia A

    2017-01-01

    Single-centre studies in medical domain are often characterised by limited samples due to the complexity and high costs of patient data collection. Machine learning methods for regression modelling of small datasets (less than 10 observations per predictor variable) remain scarce. Our work bridges this gap by developing a novel framework for application of artificial neural networks (NNs) for regression tasks involving small medical datasets. In order to address the sporadic fluctuations and validation issues that appear in regression NNs trained on small datasets, the method of multiple runs and surrogate data analysis were proposed in this work. The approach was compared to the state-of-the-art ensemble NNs; the effect of dataset size on NN performance was also investigated. The proposed framework was applied for the prediction of compressive strength (CS) of femoral trabecular bone in patients suffering from severe osteoarthritis. The NN model was able to estimate the CS of osteoarthritic trabecular bone from its structural and biological properties with a standard error of 0.85MPa. When evaluated on independent test samples, the NN achieved accuracy of 98.3%, outperforming an ensemble NN model by 11%. We reproduce this result on CS data of another porous solid (concrete) and demonstrate that the proposed framework allows for an NN modelled with as few as 56 samples to generalise on 300 independent test samples with 86.5% accuracy, which is comparable to the performance of an NN developed with 18 times larger dataset (1030 samples). The significance of this work is two-fold: the practical application allows for non-destructive prediction of bone fracture risk, while the novel methodology extends beyond the task considered in this study and provides a general framework for application of regression NNs to medical problems characterised by limited dataset sizes. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  15. Column-Parallel Single Slope ADC with Digital Correlated Multiple Sampling for Low Noise CMOS Image Sensors

    NARCIS (Netherlands)

    Chen, Y.; Theuwissen, A.J.P.; Chae, Y.

    2011-01-01

    This paper presents a low noise CMOS image sensor (CIS) using 10/12 bit configurable column-parallel single slope ADCs (SS-ADCs) and digital correlated multiple sampling (CMS). The sensor used is a conventional 4T active pixel with a pinned-photodiode as photon detector. The test sensor was

  16. ­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome [version 1; referees: 1 approved, 2 approved with reservations

    Directory of Open Access Journals (Sweden)

    Rafah Mackeh

    2017-02-01

    Full Text Available The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of interest. Here we made available a collection of transcriptome datasets related to human follicular cells from normal individuals or patients with polycystic ovary syndrome, in the process of their development, during in vitro fertilization. After RNA-seq dataset exclusion and careful selection based on study description and sample information, 12 datasets, encompassing a total of 85 unique transcriptome profiles, were identified in NCBI Gene Expression Omnibus and uploaded to the Gene Expression Browser (GXB, a web application specifically designed for interactive query and visualization of integrated large-scale data. Once annotated in GXB, multiple sample grouping has been made in order to create rank lists to allow easy data interpretation and comparison. The GXB tool also allows the users to browse a single gene across multiple projects to evaluate its expression profiles in multiple biological systems/conditions in a web-based customized graphical views. The curated dataset is accessible at the following link: http://ivf.gxbsidra.org/dm3/landing.gsp.

  17. Subscales correlations between MSSS-88 and PRISM scales in evaluation of spasticity for patients with multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Knežević Tatjana

    2017-01-01

    Full Text Available Introduction/Objective. Patient-reported outcomes have been recognized as an important way of assessing health and well-being of patients with multiple sclerosis (MS. The aim of the study is to determine the correlation between different subscales of Patient-Reported Impact of Spasticity Measure (PRISM and Multiple Sclerosis Spasticity Scale (MSSS-88 scales in the estimation of spasticity influence on different domains Methods. The study is a cross-sectional observational study. MSSS-88 and PRISM scales were analyzed in five domains (body-function domain, activity domain, participation domain, personal factors/wellbeing domain, and hypothesis. For statistical interpretation of the correlation we performed the Spearman’s ρ-test, concurrent validity, divergent validity, and the linear regression model. Results. We found a significant correlation between subscales of evaluated MSSS-88 and PRISM scales for body domains; the highest correlation was between the need for assistance/positioning (NA/P and walking (W. Spasticity has the weakest correlation with the need for intervention (NI. The presence of pain has a negative impact and significant positive correlation between pain discomfort and NI. In the domain of body function for males, there was a non-significant correlation between muscle spasms and NI. The same applies for social functioning and social embarrassment domains, as well as for emotional health and psychological agitation for personal factors / wellbeing domain. The differences between genders of MS patients persist in different domains; muscle spasms are strong predictors for NI, and body movement is a strong predictor versus W for NA/P. Conclusion. MSSS-88 and PRISM scales can be considered reliable in measuring different domains of disability for MS patients with spasticity. Because it is shorter, quicker, and simple to use, it is concluded that the PRISM scale can successfully compete with and replace the MSSS-88 scale in

  18. Time-delay-induced dynamical behaviors for an ecological vegetation growth system driven by cross-correlated multiplicative and additive noises.

    Science.gov (United States)

    Wang, Kang-Kang; Ye, Hui; Wang, Ya-Jun; Li, Sheng-Hong

    2018-05-14

    In this paper, the modified potential function, the stationary probability distribution function (SPDF), the mean growth time and the mean degeneration time for a vegetation growth system with time delay are investigated, where the vegetation system is assumed to be disturbed by cross-correlated multiplicative and additive noises. The results reveal some fact that the multiplicative and additive noises can both reduce the stability and speed up the decline of the vegetation system, while the strength of the noise correlation and time delay can both enhance the stability of the vegetation and slow down the depression process of the ecological system. On the other hand, with regard to the impacts of noises and time delay on the mean development and degeneration processes of the ecological system, it is discovered that 1) in the development process of the vegetation population, the increase of the noise correlation strength and time delay will restrain the regime shift from the barren state to the boom one, while the increase of the additive noise can lead to the fast regime shift from the barren state to the boom one. 2) Conversely, in the depression process of the ecological system, the increase of the strength of the correlation noise and time delay will prevent the regime shift from the boom state to the barren one. Comparatively, the increase of the additive and multiplicative noises can accelerate the regime shift from the boom state to the barren state.

  19. Matrix correlations for high-dimensional data: The modified RV-coefficient

    NARCIS (Netherlands)

    Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; Erk, M.J. van

    2009-01-01

    Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they

  20. Merged SAGE II, Ozone_cci and OMPS ozone profile dataset and evaluation of ozone trends in the stratosphere

    Directory of Open Access Journals (Sweden)

    V. F. Sofieva

    2017-10-01

    Full Text Available In this paper, we present a merged dataset of ozone profiles from several satellite instruments: SAGE II on ERBS, GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, ACE-FTS on SCISAT, and OMPS on Suomi-NPP. The merged dataset is created in the framework of the European Space Agency Climate Change Initiative (Ozone_cci with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The datasets from the individual instruments have been extensively validated and intercompared; only those datasets which are in good agreement, and do not exhibit significant drifts with respect to collocated ground-based observations and with respect to each other, are used for merging. The long-term SAGE–CCI–OMPS dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The merged SAGE–CCI–OMPS dataset consists of deseasonalized anomalies of ozone in 10° latitude bands from 90° S to 90° N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to July 2016. This newly created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at midlatitudes and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s and stratospheric cooling.

  1. Scientific Datasets: Discovery and Aggregation for Semantic Interpretation.

    Science.gov (United States)

    Lopez, L. A.; Scott, S.; Khalsa, S. J. S.; Duerr, R.

    2015-12-01

    One of the biggest challenges that interdisciplinary researchers face is finding suitable datasets in order to advance their science; this problem remains consistent across multiple disciplines. A surprising number of scientists, when asked what tool they use for data discovery, reply "Google", which is an acceptable solution in some cases but not even Google can find -or cares to compile- all the data that's relevant for science and particularly geo sciences. If a dataset is not discoverable through a well known search provider it will remain dark data to the scientific world.For the past year, BCube, an EarthCube Building Block project, has been developing, testing and deploying a technology stack capable of data discovery at web-scale using the ultimate dataset: The Internet. This stack has 2 principal components, a web-scale crawling infrastructure and a semantic aggregator. The web-crawler is a modified version of Apache Nutch (the originator of Hadoop and other big data technologies) that has been improved and tailored for data and data service discovery. The second component is semantic aggregation, carried out by a python-based workflow that extracts valuable metadata and stores it in the form of triples through the use semantic technologies.While implementing the BCube stack we have run into several challenges such as a) scaling the project to cover big portions of the Internet at a reasonable cost, b) making sense of very diverse and non-homogeneous data, and lastly, c) extracting facts about these datasets using semantic technologies in order to make them usable for the geosciences community. Despite all these challenges we have proven that we can discover and characterize data that otherwise would have remained in the dark corners of the Internet. Having all this data indexed and 'triplelized' will enable scientists to access a trove of information relevant to their work in a more natural way. An important characteristic of the BCube stack is that all

  2. An Annotated Dataset of 14 Meat Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2002-01-01

    This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given.......This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

  3. Illness perception, treatment beliefs, self-esteem, and self-efficacy as correlates of self-management in multiple sclerosis.

    Science.gov (United States)

    Wilski, M; Tasiemski, T

    2016-05-01

    Self-management of a disease is considered one of the most important factors affecting the treatment outcome. The research on the correlates of self-management in multiple sclerosis (MS) is limited. The aim of this study was to determine if personal factors, such as illness perception, treatment beliefs, self-esteem and self-efficacy, are correlates of self-management in MS. This cross-sectional study included 210 patients with MS who completed Multiple Sclerosis Self-Management Scale - Revised, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Rosenberg Self-Esteem Scale, and Generalized Self-Efficacy Scale. The patients were recruited from a MS rehabilitation clinic. Demographic data and illness-related problems of the study participants were collected with a self-report survey. Correlation and regression analyses were performed to determine associations between variables. Four factors: age at the time of the study (β = 0.14, P = 0.032), timeline (β = 0.16, P = 0.018), treatment control (β = 0.17, P = 0.022), and general self-efficacy (β = 0.19, P = 0.014) turned out to be the significant correlates of self-management in MS. The model including these variables explained 25% of variance in self-management in MS. Personal factors, such as general self-efficacy, perception of treatment control and realistic MS timeline perspective, are more salient correlates of self-management in MS than the objective clinical variables, such as the severity, type, and duration of MS. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

    KAUST Repository

    Xu, Ganggang

    2015-01-01

    When spatio-temporal datasets are large, the computational burden can lead to failures in the implementation of traditional geostatistical tools. In this paper, we propose a computationally efficient Bayesian hierarchical spatio-temporal model in which the spatial dependence is approximated by a Gaussian Markov random field (GMRF) while the temporal correlation is described using a vector autoregressive model. By introducing an auxiliary lattice on the spatial region of interest, the proposed method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo algorithm is of the order O(n) with n the total number of observations in space and time, our method can be used to handle very large spatio-temporal datasets with reasonable CPU times. The performance of the proposed model is illustrated using simulation studies and a dataset of precipitation data from the coterminous United States.

  5. Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

    Science.gov (United States)

    Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

    2016-12-01

    Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

  6. Comparison of recent SnIa datasets

    International Nuclear Information System (INIS)

    Sanchez, J.C. Bueno; Perivolaropoulos, L.; Nesseris, S.

    2009-01-01

    We rank the six latest Type Ia supernova (SnIa) datasets (Constitution (C), Union (U), ESSENCE (Davis) (E), Gold06 (G), SNLS 1yr (S) and SDSS-II (D)) in the context of the Chevalier-Polarski-Linder (CPL) parametrization w(a) = w 0 +w 1 (1−a), according to their Figure of Merit (FoM), their consistency with the cosmological constant (ΛCDM), their consistency with standard rulers (Cosmic Microwave Background (CMB) and Baryon Acoustic Oscillations (BAO)) and their mutual consistency. We find a significant improvement of the FoM (defined as the inverse area of the 95.4% parameter contour) with the number of SnIa of these datasets ((C) highest FoM, (U), (G), (D), (E), (S) lowest FoM). Standard rulers (CMB+BAO) have a better FoM by about a factor of 3, compared to the highest FoM SnIa dataset (C). We also find that the ranking sequence based on consistency with ΛCDM is identical with the corresponding ranking based on consistency with standard rulers ((S) most consistent, (D), (C), (E), (U), (G) least consistent). The ranking sequence of the datasets however changes when we consider the consistency with an expansion history corresponding to evolving dark energy (w 0 ,w 1 ) = (−1.4,2) crossing the phantom divide line w = −1 (it is practically reversed to (G), (U), (E), (S), (D), (C)). The SALT2 and MLCS2k2 fitters are also compared and some peculiar features of the SDSS-II dataset when standardized with the MLCS2k2 fitter are pointed out. Finally, we construct a statistic to estimate the internal consistency of a collection of SnIa datasets. We find that even though there is good consistency among most samples taken from the above datasets, this consistency decreases significantly when the Gold06 (G) dataset is included in the sample

  7. SIMADL: Simulated Activities of Daily Living Dataset

    Directory of Open Access Journals (Sweden)

    Talal Alshammari

    2018-04-01

    Full Text Available With the realisation of the Internet of Things (IoT paradigm, the analysis of the Activities of Daily Living (ADLs, in a smart home environment, is becoming an active research domain. The existence of representative datasets is a key requirement to advance the research in smart home design. Such datasets are an integral part of the visualisation of new smart home concepts as well as the validation and evaluation of emerging machine learning models. Machine learning techniques that can learn ADLs from sensor readings are used to classify, predict and detect anomalous patterns. Such techniques require data that represent relevant smart home scenarios, for training, testing and validation. However, the development of such machine learning techniques is limited by the lack of real smart home datasets, due to the excessive cost of building real smart homes. This paper provides two datasets for classification and anomaly detection. The datasets are generated using OpenSHS, (Open Smart Home Simulator, which is a simulation software for dataset generation. OpenSHS records the daily activities of a participant within a virtual environment. Seven participants simulated their ADLs for different contexts, e.g., weekdays, weekends, mornings and evenings. Eighty-four files in total were generated, representing approximately 63 days worth of activities. Forty-two files of classification of ADLs were simulated in the classification dataset and the other forty-two files are for anomaly detection problems in which anomalous patterns were simulated and injected into the anomaly detection dataset.

  8. The NOAA Dataset Identifier Project

    Science.gov (United States)

    de la Beaujardiere, J.; Mccullough, H.; Casey, K. S.

    2013-12-01

    The US National Oceanic and Atmospheric Administration (NOAA) initiated a project in 2013 to assign persistent identifiers to datasets archived at NOAA and to create informational landing pages about those datasets. The goals of this project are to enable the citation of datasets used in products and results in order to help provide credit to data producers, to support traceability and reproducibility, and to enable tracking of data usage and impact. A secondary goal is to encourage the submission of datasets for long-term preservation, because only archived datasets will be eligible for a NOAA-issued identifier. A team was formed with representatives from the National Geophysical, Oceanographic, and Climatic Data Centers (NGDC, NODC, NCDC) to resolve questions including which identifier scheme to use (answer: Digital Object Identifier - DOI), whether or not to embed semantics in identifiers (no), the level of granularity at which to assign identifiers (as coarsely as reasonable), how to handle ongoing time-series data (do not break into chunks), creation mechanism for the landing page (stylesheet from formal metadata record preferred), and others. Decisions made and implementation experience gained will inform the writing of a Data Citation Procedural Directive to be issued by the Environmental Data Management Committee in 2014. Several identifiers have been issued as of July 2013, with more on the way. NOAA is now reporting the number as a metric to federal Open Government initiatives. This paper will provide further details and status of the project.

  9. Control Measure Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EPA Control Measure Dataset is a collection of documents describing air pollution control available to regulated facilities for the control and abatement of air...

  10. Multiple comparative metagenomics using multiset k-mer counting

    Directory of Open Access Journals (Sweden)

    Gaëtan Benoit

    2016-11-01

    Full Text Available Background Large scale metagenomic projects aim to extract biodiversity knowledge between different environmental conditions. Current methods for comparing microbial communities face important limitations. Those based on taxonomical or functional assignation rely on a small subset of the sequences that can be associated to known organisms. On the other hand, de novo methods, that compare the whole sets of sequences, either do not scale up on ambitious metagenomic projects or do not provide precise and exhaustive results. Methods These limitations motivated the development of a new de novo metagenomic comparative method, called Simka. This method computes a large collection of standard ecological distances by replacing species counts by k-mer counts. Simka scales-up today’s metagenomic projects thanks to a new parallel k-mer counting strategy on multiple datasets. Results Experiments on public Human Microbiome Project datasets demonstrate that Simka captures the essential underlying biological structure. Simka was able to compute in a few hours both qualitative and quantitative ecological distances on hundreds of metagenomic samples (690 samples, 32 billions of reads. We also demonstrate that analyzing metagenomes at the k-mer level is highly correlated with extremely precise de novo comparison techniques which rely on all-versus-all sequences alignment strategy or which are based on taxonomic profiling.

  11. Validating a continental-scale groundwater diffuse pollution model using regional datasets.

    Science.gov (United States)

    Ouedraogo, Issoufou; Defourny, Pierre; Vanclooster, Marnik

    2017-12-11

    In this study, we assess the validity of an African-scale groundwater pollution model for nitrates. In a previous study, we identified a statistical continental-scale groundwater pollution model for nitrate. The model was identified using a pan-African meta-analysis of available nitrate groundwater pollution studies. The model was implemented in both Random Forest (RF) and multiple regression formats. For both approaches, we collected as predictors a comprehensive GIS database of 13 spatial attributes, related to land use, soil type, hydrogeology, topography, climatology, region typology, nitrogen fertiliser application rate, and population density. In this paper, we validate the continental-scale model of groundwater contamination by using a nitrate measurement dataset from three African countries. We discuss the issue of data availability, and quality and scale issues, as challenges in validation. Notwithstanding that the modelling procedure exhibited very good success using a continental-scale dataset (e.g. R 2  = 0.97 in the RF format using a cross-validation approach), the continental-scale model could not be used without recalibration to predict nitrate pollution at the country scale using regional data. In addition, when recalibrating the model using country-scale datasets, the order of model exploratory factors changes. This suggests that the structure and the parameters of a statistical spatially distributed groundwater degradation model for the African continent are strongly scale dependent.

  12. QCD prediction of jet structure in 2D trigger-associated momentum correlations and implications for multiple parton interactions

    Directory of Open Access Journals (Sweden)

    Trainor Thomas A.

    2015-01-01

    Full Text Available The expression “multiple parton interactions” (MPI denotes a conjectured QCD mechanism representing contributions from secondary (semihard parton scattering to the transverse azimuth region (TR of jet-triggered p-p collisions. MPI is an object of underlying-event (UE studies that consider variation of TR nch or pt yields relative to a trigger condition (leading hadron or jet pt. An alternative approach is 2D trigger-associated (TA correlations on hadron transverse momentum pt or rapidity yt in which all hadrons from all p-p events are included. Based on a two-component (soft+hard model (TCM of TA correlations a jet-related TA hard component is isolated. Contributions to the hard component from the triggered dijet and from secondary dijets (MPI can be distinguished, including their azimuth dependence relative to the trigger direction. Measured e+-e− and p-p̄ fragmentation functions and a minimum-bias jet spectrum from 200 GeV p-p̄ collisions are convoluted to predict the 2D hard component of TA correlations as a function of p-p collision multiplicity. The agreement between QCD predictions and TA correlation data is quantitative, confirming a dijet interpretation for the TCM hard component. The TA azimuth dependence is inconsistent with conventional UE assumptions.

  13. Predictive geochemical mapping using environmental correlation

    International Nuclear Information System (INIS)

    Wilford, John; Caritat, Patrice de; Bui, Elisabeth

    2016-01-01

    The distribution of chemical elements at and near the Earth's surface, the so-called critical zone, is complex and reflects the geochemistry and mineralogy of the original substrate modified by environmental factors that include physical, chemical and biological processes over time. Geochemical data typically is illustrated in the form of plan view maps or vertical cross-sections, where the composition of regolith, soil, bedrock or any other material is represented. These are primarily point observations that frequently are interpolated to produce rasters of element distributions. Here we propose the application of environmental or covariate regression modelling to predict and better understand the controls on major and trace element geochemistry within the regolith. Available environmental covariate datasets (raster or vector) representing factors influencing regolith or soil composition are intersected with the geochemical point data in a spatial statistical correlation model to develop a system of multiple linear correlations. The spatial resolution of the environmental covariates, which typically is much finer (e.g. ∼90 m pixel) than that of geochemical surveys (e.g. 1 sample per 10-10,000 km 2 ), carries over to the predictions. Therefore the derived predictive models of element concentrations take the form of continuous geochemical landscape representations that are potentially much more informative than geostatistical interpolations. Environmental correlation is applied to the Sir Samuel 1:250,000 scale map sheet in Western Australia to produce distribution models of individual elements describing the geochemical composition of the regolith and exposed bedrock. As an example we model the distribution of two elements – chromium and sodium. We show that the environmental correlation approach generates high resolution predictive maps that are statistically more accurate and effective than ordinary kriging and inverse distance weighting interpolation

  14. The Kinetics Human Action Video Dataset

    OpenAIRE

    Kay, Will; Carreira, Joao; Simonyan, Karen; Zhang, Brian; Hillier, Chloe; Vijayanarasimhan, Sudheendra; Viola, Fabio; Green, Tim; Back, Trevor; Natsev, Paul; Suleyman, Mustafa; Zisserman, Andrew

    2017-01-01

    We describe the DeepMind Kinetics human action video dataset. The dataset contains 400 human action classes, with at least 400 video clips for each action. Each clip lasts around 10s and is taken from a different YouTube video. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands. We describe the statistics of the dataset, how it was collected, and give some ...

  15. Updated heat transfer correlations for supercritical water-cooled reactor applications

    International Nuclear Information System (INIS)

    Mokry, S.J.; Pioro, I.L.; Farah, A.; King, K.

    2011-01-01

    In support of the development of SuperCritical Water-cooled Reactors (SCWRs), research is currently being conducted for heat-transfer at supercritical conditions. Currently, there are no experimental datasets for heat transfer from power reactor fuel bundles to the fuel coolant (Water) available in open literature. Therefore, for preliminary calculations, heat-transfer correlations obtained with bare tube data can be used as a conservative approach. A large set of experimental data, for supercritical water was analyzed and an updated heat-transfer correlation for forced-convective heat-transfer, in the normal heat transfer regime, was developed. This experimental dataset was obtained within conditions similar to those for proposed SCWR concepts. Thus, this new correlation can be used for preliminary heat-transfer calculations in SCWR fuel channels. It has demonstrated a good fit for the analyzed dataset. Experiments with SuperCritical Water (SCW) are very expensive. Therefore, a number of experiments are performed in modeling fluids, such as carbon dioxide and refrigerants. However, there is no common opinion if SC modeling fluids' correlations can be applied to SCW and vice versa. Therefore, a correlation for supercritical carbon dioxide heat transfer was developed as a less expensive alternative to using supercritical water. The conducted analysis also meets the objective of improving our fundamental knowledge of the transport processes and handling of supercritical fluids. These correlations can be used for supercritical water heat exchangers linked to indirect-cycle concepts and the cogeneration of hydrogen, for future comparisons with other independent datasets, with bundle data, for the verification of computer codes for SCWR core thermalhydraulics and for the verification of scaling parameters between water and modeling fluids. (author)

  16. Using multiple-accumulator CMACs to improve efficiency of the X part of an input-buffered FX correlator

    Science.gov (United States)

    Lapshev, Stepan; Hasan, S. M. Rezaul

    2017-04-01

    This paper presents the approach of using complex multiplier-accumulators (CMACs) with multiple accumulators to reduce the total number of memory operations in an input-buffered architecture for the X part of an FX correlator. A processing unit of this architecture uses an array of CMACs that are reused for different groups of baselines. The disadvantage of processing correlations in this way is that each input data sample has to be read multiple times from the memory because each input signal is used in many of these baseline groups. While a one-accumulator CMAC cannot switch to a different baseline until it is finished integrating the current one, a multiple-accumulator CMAC can. Thus, the array of multiple-accumulator CMACs can switch between processing different baselines that share some input signals at any moment to reuse the current data in the processing buffers. In this way significant reductions in the number of memory read operations are achieved with only a few accumulators per CMAC. For example, for a large number of input signals three-accumulator CMACs reduce the total number of memory operations by more than a third. Simulated energy measurements of four VLSI designs in a high-performance 28 nm CMOS technology are presented in this paper to demonstrate that using multiple accumulators can also lead to reduced power dissipation of the processing array. Using three accumulators as opposed to one has been found to reduce the overall energy of 8-bit CMACs by 1.4% through the reduction of the switching activity within their circuits, which is in addition to a more than 30% reduction in the memory.

  17. Software ion scan functions in analysis of glycomic and lipidomic MS/MS datasets.

    Science.gov (United States)

    Haramija, Marko

    2018-03-01

    Hardware ion scan functions unique to tandem mass spectrometry (MS/MS) mode of data acquisition, such as precursor ion scan (PIS) and neutral loss scan (NLS), are important for selective extraction of key structural data from complex MS/MS spectra. However, their software counterparts, software ion scan (SIS) functions, are still not regularly available. Software ion scan functions can be easily coded for additional functionalities, such as software multiple precursor ion scan, software no ion scan, and software variable ion scan functions. These are often necessary, since they allow more efficient analysis of complex MS/MS datasets, often encountered in glycomics and lipidomics. Software ion scan functions can be easily coded by using modern script languages and can be independent of instrument manufacturer. Here we demonstrate the utility of SIS functions on a medium-size glycomic MS/MS dataset. Knowledge of sample properties, as well as of diagnostic and conditional diagnostic ions crucial for data analysis, was needed. Based on the tables constructed with the output data from the SIS functions performed, a detailed analysis of a complex MS/MS glycomic dataset could be carried out in a quick, accurate, and efficient manner. Glycomic research is progressing slowly, and with respect to the MS experiments, one of the key obstacles for moving forward is the lack of appropriate bioinformatic tools necessary for fast analysis of glycomic MS/MS datasets. Adding novel SIS functionalities to the glycomic MS/MS toolbox has a potential to significantly speed up the glycomic data analysis process. Similar tools are useful for analysis of lipidomic MS/MS datasets as well, as will be discussed briefly. Copyright © 2017 John Wiley & Sons, Ltd.

  18. The impact of the resolution of meteorological datasets on catchment-scale drought studies

    Science.gov (United States)

    Hellwig, Jost; Stahl, Kerstin

    2017-04-01

    Gridded meteorological datasets provide the basis to study drought at a range of scales, including catchment scale drought studies in hydrology. They are readily available to study past weather conditions and often serve real time monitoring as well. As these datasets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a tradeoff between these features. Our investigation examines whether biases occur when studying drought on catchment scale with low resolution input data. For that, a comparison among the datasets HYRAS (covering Central Europe, 1x1 km grid, daily data, 1951 - 2005), E-OBS (Europe, 0.25° grid, daily data, 1950-2015) and GPCC (whole world, 0.5° grid, monthly data, 1901 - 2013) is carried out. Generally, biases in precipitation increase with decreasing resolution. Most important variations are found during summer. In low mountain range of Central Europe the datasets of sparse resolution (E-OBS, GPCC) overestimate dry days and underestimate total precipitation since they are not able to describe high spatial variability. However, relative measures like the correlation coefficient reveal good consistencies of dry and wet periods, both for absolute precipitation values and standardized indices like the Standardized Precipitation Index (SPI) or Standardized Precipitation Evaporation Index (SPEI). Particularly the most severe droughts derived from the different datasets match very well. These results indicate that absolute values of sparse resolution datasets applied to catchment scale might be critical to use for an assessment of the hydrological drought at catchment scale, whereas relative measures for determining periods of drought are more trustworthy. Therefore, studies on drought, that downscale meteorological data, should carefully consider their data needs and focus on relative measures for dry periods if sufficient for the task.

  19. Comparison of CORA and EN4 in-situ datasets validation methods, toward a better quality merged dataset.

    Science.gov (United States)

    Szekely, Tanguy; Killick, Rachel; Gourrion, Jerome; Reverdin, Gilles

    2017-04-01

    CORA and EN4 are both global delayed time mode validated in-situ ocean temperature and salinity datasets distributed by the Met Office (http://www.metoffice.gov.uk/) and Copernicus (www.marine.copernicus.eu). A large part of the profiles distributed by CORA and EN4 in recent years are Argo profiles from the ARGO DAC, but profiles are also extracted from the World Ocean Database and TESAC profiles from GTSPP. In the case of CORA, data coming from the EUROGOOS Regional operationnal oserving system( ROOS) operated by European institutes no managed by National Data Centres and other datasets of profiles povided by scientific sources can also be found (Sea mammals profiles from MEOP, XBT datasets from cruises ...). (EN4 also takes data from the ASBO dataset to supplement observations in the Arctic). First advantage of this new merge product is to enhance the space and time coverage at global and european scales for the period covering 1950 till a year before the current year. This product is updated once a year and T&S gridded fields are alos generated for the period 1990-year n-1. The enhancement compared to the revious CORA product will be presented Despite the fact that the profiles distributed by both datasets are mostly the same, the quality control procedures developed by the Met Office and Copernicus teams differ, sometimes leading to different quality control flags for the same profile. Started in 2016 a new study started that aims to compare both validation procedures to move towards a Copernicus Marine Service dataset with the best features of CORA and EN4 validation.A reference data set composed of the full set of in-situ temperature and salinity measurements collected by Coriolis during 2015 is used. These measurements have been made thanks to wide range of instruments (XBTs, CTDs, Argo floats, Instrumented sea mammals,...), covering the global ocean. The reference dataset has been validated simultaneously by both teams.An exhaustive comparison of the

  20. The Role of Datasets on Scientific Influence within Conflict Research.

    Science.gov (United States)

    Van Holt, Tracy; Johnson, Jeffery C; Moates, Shiloh; Carley, Kathleen M

    2016-01-01

    We inductively tested if a coherent field of inquiry in human conflict research emerged in an analysis of published research involving "conflict" in the Web of Science (WoS) over a 66-year period (1945-2011). We created a citation network that linked the 62,504 WoS records and their cited literature. We performed a critical path analysis (CPA), a specialized social network analysis on this citation network (~1.5 million works), to highlight the main contributions in conflict research and to test if research on conflict has in fact evolved to represent a coherent field of inquiry. Out of this vast dataset, 49 academic works were highlighted by the CPA suggesting a coherent field of inquiry; which means that researchers in the field acknowledge seminal contributions and share a common knowledge base. Other conflict concepts that were also analyzed-such as interpersonal conflict or conflict among pharmaceuticals, for example, did not form their own CP. A single path formed, meaning that there was a cohesive set of ideas that built upon previous research. This is in contrast to a main path analysis of conflict from 1957-1971 where ideas didn't persist in that multiple paths existed and died or emerged reflecting lack of scientific coherence (Carley, Hummon, and Harty, 1993). The critical path consisted of a number of key features: 1) Concepts that built throughout include the notion that resource availability drives conflict, which emerged in the 1960s-1990s and continued on until 2011. More recent intrastate studies that focused on inequalities emerged from interstate studies on the democracy of peace earlier on the path. 2) Recent research on the path focused on forecasting conflict, which depends on well-developed metrics and theories to model. 3) We used keyword analysis to independently show how the CP was topically linked (i.e., through democracy, modeling, resources, and geography). Publically available conflict datasets developed early on helped shape the

  1. Self-Regulatory Strategies as Correlates of Physical Activity Behavior in Persons With Multiple Sclerosis.

    Science.gov (United States)

    Cederberg, Katie L; Balto, Julia M; Motl, Robert W

    2018-05-01

    To examine self-regulation strategies as correlates of physical activity in persons with multiple sclerosis (MS). Cross-sectional, or survey, study. University-based research laboratory. Convenience sample of persons with MS (N=68). Not applicable. Exercise Self-Efficacy Scale (EXSE), 12-item Physical Activity Self-Regulation Scale (PASR-12), and Godin Leisure-Time Exercise Questionnaire (GLTEQ). Correlation analyses indicated that GLTEQ scores were positively and significantly associated with overall self-regulation (r=.43), self-monitoring (r=.45), goal-setting (r=.27), reinforcement (r=.30), time management (r=.41), and relapse prevention (r=.53) PASR-12 scores. Regression analyses indicated that relapse prevention (B=5.01; SE B=1.74; β=.51) and self-monitoring (B=3.65; SE B=1.71; β=.33) were unique predictors of physical activity behavior, and relapse prevention demonstrated a significant association with physical activity behavior that was accounted for by EXSE. Our results indicate that self-regulatory strategies, particularly relapse prevention, may be important correlates of physical activity behavior that can inform the design of future behavioral interventions in MS. Published by Elsevier Inc.

  2. A comprehensive dataset of genes with a loss-of-function mutant phenotype in Arabidopsis.

    Science.gov (United States)

    Lloyd, Johnny; Meinke, David

    2012-03-01

    Despite the widespread use of Arabidopsis (Arabidopsis thaliana) as a model plant, a curated dataset of Arabidopsis genes with mutant phenotypes remains to be established. A preliminary list published nine years ago in Plant Physiology is outdated, and genome-wide phenotype information remains difficult to obtain. We describe here a comprehensive dataset of 2,400 genes with a loss-of-function mutant phenotype in Arabidopsis. Phenotype descriptions were gathered primarily from manual curation of the scientific literature. Genes were placed into prioritized groups (essential, morphological, cellular-biochemical, and conditional) based on the documented phenotypes of putative knockout alleles. Phenotype classes (e.g. vegetative, reproductive, and timing, for the morphological group) and subsets (e.g. flowering time, senescence, circadian rhythms, and miscellaneous, for the timing class) were also established. Gene identities were classified as confirmed (through molecular complementation or multiple alleles) or not confirmed. Relationships between mutant phenotype and protein function, genetic redundancy, protein connectivity, and subcellular protein localization were explored. A complementary dataset of 401 genes that exhibit a mutant phenotype only when disrupted in combination with a putative paralog was also compiled. The importance of these genes in confirming functional redundancy and enhancing the value of single gene datasets is discussed. With further input and curation from the Arabidopsis community, these datasets should help to address a variety of important biological questions, provide a foundation for exploring the relationship between genotype and phenotype in angiosperms, enhance the utility of Arabidopsis as a reference plant, and facilitate comparative studies with model genetic organisms.

  3. Correlation between mean transverse momentum and charged particle multiplicity based on geometrical superposition of p-Pb collisions

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Jerome [Institut fuer Kernphysik, Goethe-Universitaet Frankfurt (Germany); Collaboration: ALICE-Collaboration

    2015-07-01

    The mean transverse momentum left angle p{sub T} right angle as a function of the charged-particle multiplicity N{sub ch} in pp, p-Pb and Pb-Pb collisions was recently published by ALICE. While in pp and in p-Pb collisions a strong increase of left angle p{sub T} right angle with N{sub ch} is observed, Pb-Pb collisions show a saturation at a much lower left angle p{sub T} right angle. Efforts of reproducing this behaviour in Pb-Pb with a superpositon of nucleon-nucleon interactions do not succeed. A superposition of p-Pb collisions seems to be more promising, since the p-Pb data shows characteristics of both pp and Pb-Pb collisions. The geometric distribution of the p-Pb impact parameters is based on the Woods-Saxon density distribution. Using the correlation of the impact parameter and the multiplicity N{sub ch} in p-Pb collisions a multiplicity-spectrum was generated. Combining this spectrum with experimental p-Pb data we present left angle p{sub T} right angle as a function of N{sub ch} in simulated Pb-Pb collisions and compare it to the correlation measured in Pb-Pb by ALICE.

  4. Multiple plots in R

    DEFF Research Database (Denmark)

    Edwards, Stefan McKinnon

    2012-01-01

    In this chapter I will investigate how to combine multiple plots into a single. The scenario is a dataset of a series of measurements, on three samples in three situations. There are many ways we can display this, e.g. 3d graphs or faceting. 3d graphs are not good for displaying static data so we...

  5. Correlation between olfactory dysfunction and various clinical parameters in patients with multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Kostić Jelena

    2009-01-01

    Full Text Available Background/Aim. Multiple sclerosis (MS is a chronic inflammatory disease of the central nervous system (CNS characterized by myelin destruction and axon loss. Among various clinical manifestations of MS cognitive disorders are frequent. Olfactory disorders are also noticed but they are rarely considered in clinical practice. The aim of the present study was to examine frequency of olfactory dysfunction in patients with MS and its relationship to clinical parameters. Methods. Our study comprised 61 consecutive patients with definite MS who were hospitalized at the Department for Multiple Sclerosis and Other Immune- Mediated Disorders of CNS, Institute of Neurology, Clinical Center of Serbia, Belgrade, and 45 gender-, age- and education-matched healthy voluntaries. The Pocket Smell Test (PST was used for examination of olfactory function. Cognitive functions were analyzed using the tests from the Brief Battery of Neuropsychological Tests: Paced Auditory Serial Addition Test 3-minute Version (PASAT 3', Word List Generation (WLG and Symbol Digit Modalities Test (SDMT. Results. Olfactory dysfunction was found in 26 (43% MS patients and 5 (11% controls (p = 0.001. Statistically significant positive correlation was found only between PST score and WLG scores (r = 0.297, p = 0.030. In comparison with the previously published normative values, our subjects with MS had decrease in the mean indices of the PASAT 3' in 28%, SDMT in 51% and WLG in 90% of the subjects. Conclusion. Olfactory dysfunction is frequent in our population of patients with MS. This disturbance correlates with the impairment of cognitive functions in these patients.

  6. Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets

    Science.gov (United States)

    Liu, Wenbin; Sun, Fubao; Li, Yanzhong; Zhang, Guoqing; Sang, Yan-Fang; Lim, Wee Ho; Liu, Jiahong; Wang, Hong; Bai, Peng

    2018-01-01

    The dynamics of basin-scale water budgets over the Tibetan Plateau (TP) are not well understood nowadays due to the lack of in situ hydro-climatic observations. In this study, we investigate the seasonal cycles and trends of water budget components (e.g. precipitation P, evapotranspiration ET and runoff Q) in 18 TP river basins during the period 1982-2011 through the use of multi-source datasets (e.g. in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations). A water balance-based two-step procedure, which considers the changes in basin-scale water storage on the annual scale, is also adopted to calculate actual ET. The results indicated that precipitation (mainly snowfall from mid-autumn to next spring), which are mainly concentrated during June-October (varied among different monsoons-impacted basins), was the major contributor to the runoff in TP basins. The P, ET and Q were found to marginally increase in most TP basins during the past 30 years except for the upper Yellow River basin and some sub-basins of Yalong River, which were mainly affected by the weakening east Asian monsoon. Moreover, the aridity index (PET/P) and runoff coefficient (Q/P) decreased slightly in most basins, which were in agreement with the warming and moistening climate in the Tibetan Plateau. The results obtained demonstrated the usefulness of integrating multi-source datasets to hydrological applications in the data-sparse regions. More generally, such an approach might offer helpful insights into understanding the water and energy budgets and sustainability of water resource management practices of data-sparse regions in a changing environment.

  7. Challenges and Experiences of Building Multidisciplinary Datasets across Cultures

    Science.gov (United States)

    Jamiyansharav, K.; Laituri, M.; Fernandez-Gimenez, M.; Fassnacht, S. R.; Venable, N. B. H.; Allegretti, A. M.; Reid, R.; Baival, B.; Jamsranjav, C.; Ulambayar, T.; Linn, S.; Angerer, J.

    2017-12-01

    Efficient data sharing and management are key challenges to multidisciplinary scientific research. These challenges are further complicated by adding a multicultural component. We address the construction of a complex database for social-ecological analysis in Mongolia. Funded by the National Science Foundation (NSF) Dynamics of Coupled Natural and Human (CNH) Systems, the Mongolian Rangelands and Resilience (MOR2) project focuses on the vulnerability of Mongolian pastoral systems to climate change and adaptive capacity. The MOR2 study spans over three years of fieldwork in 36 paired districts (Soum) from 18 provinces (Aimag) of Mongolia that covers steppe, mountain forest steppe, desert steppe and eastern steppe ecological zones. Our project team is composed of hydrologists, social scientists, geographers, and ecologists. The MOR2 database includes multiple ecological, social, meteorological, geospatial and hydrological datasets, as well as archives of original data and survey in multiple formats. Managing this complex database requires significant organizational skills, attention to detail and ability to communicate within collective team members from diverse disciplines and across multiple institutions in the US and Mongolia. We describe the database's rich content, organization, structure and complexity. We discuss lessons learned, best practices and recommendations for complex database management, sharing, and archiving in creating a cross-cultural and multi-disciplinary database.

  8. Patterns and correlates of co-occurrence among multiple types of child maltreatment

    Science.gov (United States)

    Kim, Kihyun; Mennen, Ferol E.; Trickett, Penelope K.

    2017-01-01

    This study examined the patterns and correlates of the types of maltreatment experienced by adolescents aged 9–12, participating in an ongoing longitudinal study on the impact of neglect on children’s development. Using case record abstraction, the study compared the child protection classification and findings from the case record abstraction with regard to the rates of four types of maltreatment (i.e. physical, sexual, emotional abuse and neglect) as well as co-occurrence across multiple types of maltreatment. Next, the study examined the frequently observed patterns of child maltreatment. Finally, the study investigated whether aspects of caretaker functioning and the detailed incident characteristics in the cases of neglect differed by the number of different types of maltreatment the children experienced. Results showed significant discrepancies between the Child Protective Service classification and case record abstraction. Child Protective Service classification considerably underestimated the rate of co-occurrence across multiple types of maltreatment. Neglect accompanied by physical and emotional abuse was the most common form. Some of the caretaker functioning variables distinguished the number of types of maltreatment. Based on the findings, future-research directions and practice implication were discussed. PMID:29225485

  9. A dataset mapping the potential biophysical effects of vegetation cover change

    Science.gov (United States)

    Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

    2018-02-01

    Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

  10. Fluxnet Synthesis Dataset Collaboration Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Deborah A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Humphrey, Marty [Univ. of Virginia, Charlottesville, VA (United States); van Ingen, Catharine [Microsoft. San Francisco, CA (United States); Beekwilder, Norm [Univ. of Virginia, Charlottesville, VA (United States); Goode, Monte [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jackson, Keith [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rodriguez, Matt [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Weber, Robin [Univ. of California, Berkeley, CA (United States)

    2008-02-06

    The Fluxnet synthesis dataset originally compiled for the La Thuile workshop contained approximately 600 site years. Since the workshop, several additional site years have been added and the dataset now contains over 920 site years from over 240 sites. A data refresh update is expected to increase those numbers in the next few months. The ancillary data describing the sites continues to evolve as well. There are on the order of 120 site contacts and 60proposals have been approved to use thedata. These proposals involve around 120 researchers. The size and complexity of the dataset and collaboration has led to a new approach to providing access to the data and collaboration support and the support team attended the workshop and worked closely with the attendees and the Fluxnet project office to define the requirements for the support infrastructure. As a result of this effort, a new website (http://www.fluxdata.org) has been created to provide access to the Fluxnet synthesis dataset. This new web site is based on a scientific data server which enables browsing of the data on-line, data download, and version tracking. We leverage database and data analysis tools such as OLAP data cubes and web reports to enable browser and Excel pivot table access to the data.

  11. Projection of Anthropometric Correlation for Virtual Population Modelling

    DEFF Research Database (Denmark)

    Rasmussen, John; Waagepetersen, Rasmus Plenge; Rasmussen, Kasper Pihl

    2018-01-01

    , and therefore the correlations between parameters, are not accessible. This problem is solved by projecting correlation from a data set for which raw data are provided. The method is tested and validated by generation of pseudo females from males in the ANSUR anthropometric dataset. Results show...

  12. Simulation of Smart Home Activity Datasets

    Directory of Open Access Journals (Sweden)

    Jonathan Synnott

    2015-06-01

    Full Text Available A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

  13. Simulation of Smart Home Activity Datasets.

    Science.gov (United States)

    Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

    2015-06-16

    A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

  14. Publishing datasets with eSciDoc and panMetaDocs

    Science.gov (United States)

    Ulbricht, D.; Klump, J.; Bertelmann, R.

    2012-04-01

    Currently serveral research institutions worldwide undertake considerable efforts to have their scientific datasets published and to syndicate them to data portals as extensively described objects identified by a persistent identifier. This is done to foster the reuse of data, to make scientific work more transparent, and to create a citable entity that can be referenced unambigously in written publications. GFZ Potsdam established a publishing workflow for file based research datasets. Key software components are an eSciDoc infrastructure [1] and multiple instances of the data curation tool panMetaDocs [2]. The eSciDoc repository holds data objects and their associated metadata in container objects, called eSciDoc items. A key metadata element in this context is the publication status of the referenced data set. PanMetaDocs, which is based on PanMetaWorks [3], is a PHP based web application that allows to describe data with any XML-based metadata schema. The metadata fields can be filled with static or dynamic content to reduce the number of fields that require manual entries to a minimum and make use of contextual information in a project setting. Access rights can be applied to set visibility of datasets to other project members and allow collaboration on and notifying about datasets (RSS) and interaction with the internal messaging system, that was inherited from panMetaWorks. When a dataset is to be published, panMetaDocs allows to change the publication status of the eSciDoc item from status "private" to "submitted" and prepare the dataset for verification by an external reviewer. After quality checks, the item publication status can be changed to "published". This makes the data and metadata available through the internet worldwide. PanMetaDocs is developed as an eSciDoc application. It is an easy to use graphical user interface to eSciDoc items, their data and metadata. It is also an application supporting a DOI publication agent during the process of

  15. Solar Integration National Dataset Toolkit | Grid Modernization | NREL

    Science.gov (United States)

    Solar Integration National Dataset Toolkit Solar Integration National Dataset Toolkit NREL is working on a Solar Integration National Dataset (SIND) Toolkit to enable researchers to perform U.S . regional solar generation integration studies. It will provide modeled, coherent subhourly solar power data

  16. A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets

    Directory of Open Access Journals (Sweden)

    Min Deng

    2016-02-01

    Full Text Available Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly developed for space-time processes that exhibit stationarity in space and time. It is still challenging to model heterogeneity of space-time data in the interpolation model. To overcome this limitation, in this study, a novel space-time interpolation method considering both spatial and temporal heterogeneity is developed for estimating missing data in space-time datasets. The interpolation operation is first implemented in spatial and temporal dimensions. Heterogeneous covariance functions are constructed to obtain the best linear unbiased estimates in spatial and temporal dimensions. Spatial and temporal correlations are then considered to combine the interpolation results in spatial and temporal dimensions to estimate the missing data. The proposed method is tested on annual average temperature and precipitation data in China (1984–2009. Experimental results show that, for these datasets, the proposed method outperforms three state-of-the-art methods—e.g., spatio-temporal kriging, spatio-temporal inverse distance weighting, and point estimation model of biased hospitals-based area disease estimation methods.

  17. PROVIDING GEOGRAPHIC DATASETS AS LINKED DATA IN SDI

    Directory of Open Access Journals (Sweden)

    E. Hietanen

    2016-06-01

    Full Text Available In this study, a prototype service to provide data from Web Feature Service (WFS as linked data is implemented. At first, persistent and unique Uniform Resource Identifiers (URI are created to all spatial objects in the dataset. The objects are available from those URIs in Resource Description Framework (RDF data format. Next, a Web Ontology Language (OWL ontology is created to describe the dataset information content using the Open Geospatial Consortium’s (OGC GeoSPARQL vocabulary. The existing data model is modified in order to take into account the linked data principles. The implemented service produces an HTTP response dynamically. The data for the response is first fetched from existing WFS. Then the Geographic Markup Language (GML format output of the WFS is transformed on-the-fly to the RDF format. Content Negotiation is used to serve the data in different RDF serialization formats. This solution facilitates the use of a dataset in different applications without replicating the whole dataset. In addition, individual spatial objects in the dataset can be referred with URIs. Furthermore, the needed information content of the objects can be easily extracted from the RDF serializations available from those URIs. A solution for linking data objects to the dataset URI is also introduced by using the Vocabulary of Interlinked Datasets (VoID. The dataset is divided to the subsets and each subset is given its persistent and unique URI. This enables the whole dataset to be explored with a web browser and all individual objects to be indexed by search engines.

  18. Wind Integration National Dataset Toolkit | Grid Modernization | NREL

    Science.gov (United States)

    Integration National Dataset Toolkit Wind Integration National Dataset Toolkit The Wind Integration National Dataset (WIND) Toolkit is an update and expansion of the Eastern Wind Integration Data Set and Western Wind Integration Data Set. It supports the next generation of wind integration studies. WIND

  19. Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies.

    Science.gov (United States)

    Wang, Haohan; Aragam, Bryon; Xing, Eric P

    2018-04-26

    A fundamental and important challenge in modern datasets of ever increasing dimensionality is variable selection, which has taken on renewed interest recently due to the growth of biological and medical datasets with complex, non-i.i.d. structures. Naïvely applying classical variable selection methods such as the Lasso to such datasets may lead to a large number of false discoveries. Motivated by genome-wide association studies in genetics, we study the problem of variable selection for datasets arising from multiple subpopulations, when this underlying population structure is unknown to the researcher. We propose a unified framework for sparse variable selection that adaptively corrects for population structure via a low-rank linear mixed model. Most importantly, the proposed method does not require prior knowledge of sample structure in the data and adaptively selects a covariance structure of the correct complexity. Through extensive experiments, we illustrate the effectiveness of this framework over existing methods. Further, we test our method on three different genomic datasets from plants, mice, and human, and discuss the knowledge we discover with our method. Copyright © 2018. Published by Elsevier Inc.

  20. Superadditive correlation

    International Nuclear Information System (INIS)

    Giraud, B.G.; Heumann, J.M.; Lapedes, A.S.

    1999-01-01

    The fact that correlation does not imply causation is well known. Correlation between variables at two sites does not imply that the two sites directly interact, because, e.g., correlation between distant sites may be induced by chaining of correlation between a set of intervening, directly interacting sites. Such 'noncausal correlation' is well understood in statistical physics: an example is long-range order in spin systems, where spins which have only short-range direct interactions, e.g., the Ising model, display correlation at a distance. It is less well recognized that such long-range 'noncausal' correlations can in fact be stronger than the magnitude of any causal correlation induced by direct interactions. We call this phenomenon superadditive correlation (SAC). We demonstrate this counterintuitive phenomenon by explicit examples in (i) a model spin system and (ii) a model continuous variable system, where both models are such that two variables have multiple intervening pathways of indirect interaction. We apply the technique known as decimation to explain SAC as an additive, constructive interference phenomenon between the multiple pathways of indirect interaction. We also explain the effect using a definition of the collective mode describing the intervening spin variables. Finally, we show that the SAC effect is mirrored in information theory, and is true for mutual information measures in addition to correlation measures. Generic complex systems typically exhibit multiple pathways of indirect interaction, making SAC a potentially widespread phenomenon. This affects, e.g., attempts to deduce interactions by examination of correlations, as well as, e.g., hierarchical approximation methods for multivariate probability distributions, which introduce parameters based on successive orders of correlation. copyright 1999 The American Physical Society

  1. Automatic plankton image classification combining multiple view features via multiple kernel learning.

    Science.gov (United States)

    Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

    2017-12-28

    Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

  2. Application of multiple correlation analysis method to the prognosis and evaluation of uranium metallogenisys in Jiangzha region

    International Nuclear Information System (INIS)

    Zhu Hongxun; Pan Hongping; Jian Xingxiang

    2008-01-01

    Prognosis and evaluation of uranium resources in Jiangzha region, Sichuan province are carried out through the multiple correlation analysis method. Through combining the characteristics of the methods and geology circumstance of areas to be predict, the uranium source, rock types, structure, terrain, hot springs and red basin are selected as estimation variable (factor). The original data of reference and predict unit are listed first, then correlation degree is calculated and uranium mineralization prospect areas are discriminated finally. The result shows that the method is credible, and should be applied to the whole Ruoergai uranium metallogenic area. (authors)

  3. A framework for automatic creation of gold-standard rigid 3D-2D registration datasets.

    Science.gov (United States)

    Madan, Hennadii; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

    2017-02-01

    Advanced image-guided medical procedures incorporate 2D intra-interventional information into pre-interventional 3D image and plan of the procedure through 3D/2D image registration (32R). To enter clinical use, and even for publication purposes, novel and existing 32R methods have to be rigorously validated. The performance of a 32R method can be estimated by comparing it to an accurate reference or gold standard method (usually based on fiducial markers) on the same set of images (gold standard dataset). Objective validation and comparison of methods are possible only if evaluation methodology is standardized, and the gold standard  dataset is made publicly available. Currently, very few such datasets exist and only one contains images of multiple patients acquired during a procedure. To encourage the creation of gold standard 32R datasets, we propose an automatic framework. The framework is based on rigid registration of fiducial markers. The main novelty is spatial grouping of fiducial markers on the carrier device, which enables automatic marker localization and identification across the 3D and 2D images. The proposed framework was demonstrated on clinical angiograms of 20 patients. Rigid 32R computed by the framework was more accurate than that obtained manually, with the respective target registration error below 0.027 mm compared to 0.040 mm. The framework is applicable for gold standard setup on any rigid anatomy, provided that the acquired images contain spatially grouped fiducial markers. The gold standard datasets and software will be made publicly available.

  4. A New Outlier Detection Method for Multidimensional Datasets

    KAUST Repository

    Abdel Messih, Mario A.

    2012-07-01

    This study develops a novel hybrid method for outlier detection (HMOD) that combines the idea of distance based and density based methods. The proposed method has two main advantages over most of the other outlier detection methods. The first advantage is that it works well on both dense and sparse datasets. The second advantage is that, unlike most other outlier detection methods that require careful parameter setting and prior knowledge of the data, HMOD is not very sensitive to small changes in parameter values within certain parameter ranges. The only required parameter to set is the number of nearest neighbors. In addition, we made a fully parallelized implementation of HMOD that made it very efficient in applications. Moreover, we proposed a new way of using the outlier detection for redundancy reduction in datasets where the confidence level that evaluates how accurate the less redundant dataset can be used to represent the original dataset can be specified by users. HMOD is evaluated on synthetic datasets (dense and mixed “dense and sparse”) and a bioinformatics problem of redundancy reduction of dataset of position weight matrices (PWMs) of transcription factor binding sites. In addition, in the process of assessing the performance of our redundancy reduction method, we developed a simple tool that can be used to evaluate the confidence level of reduced dataset representing the original dataset. The evaluation of the results shows that our method can be used in a wide range of problems.

  5. The Role of Datasets on Scientific Influence within Conflict Research.

    Directory of Open Access Journals (Sweden)

    Tracy Van Holt

    Full Text Available We inductively tested if a coherent field of inquiry in human conflict research emerged in an analysis of published research involving "conflict" in the Web of Science (WoS over a 66-year period (1945-2011. We created a citation network that linked the 62,504 WoS records and their cited literature. We performed a critical path analysis (CPA, a specialized social network analysis on this citation network (~1.5 million works, to highlight the main contributions in conflict research and to test if research on conflict has in fact evolved to represent a coherent field of inquiry. Out of this vast dataset, 49 academic works were highlighted by the CPA suggesting a coherent field of inquiry; which means that researchers in the field acknowledge seminal contributions and share a common knowledge base. Other conflict concepts that were also analyzed-such as interpersonal conflict or conflict among pharmaceuticals, for example, did not form their own CP. A single path formed, meaning that there was a cohesive set of ideas that built upon previous research. This is in contrast to a main path analysis of conflict from 1957-1971 where ideas didn't persist in that multiple paths existed and died or emerged reflecting lack of scientific coherence (Carley, Hummon, and Harty, 1993. The critical path consisted of a number of key features: 1 Concepts that built throughout include the notion that resource availability drives conflict, which emerged in the 1960s-1990s and continued on until 2011. More recent intrastate studies that focused on inequalities emerged from interstate studies on the democracy of peace earlier on the path. 2 Recent research on the path focused on forecasting conflict, which depends on well-developed metrics and theories to model. 3 We used keyword analysis to independently show how the CP was topically linked (i.e., through democracy, modeling, resources, and geography. Publically available conflict datasets developed early on helped

  6. The Role of Datasets on Scientific Influence within Conflict Research

    Science.gov (United States)

    Van Holt, Tracy; Johnson, Jeffery C.; Moates, Shiloh; Carley, Kathleen M.

    2016-01-01

    We inductively tested if a coherent field of inquiry in human conflict research emerged in an analysis of published research involving “conflict” in the Web of Science (WoS) over a 66-year period (1945–2011). We created a citation network that linked the 62,504 WoS records and their cited literature. We performed a critical path analysis (CPA), a specialized social network analysis on this citation network (~1.5 million works), to highlight the main contributions in conflict research and to test if research on conflict has in fact evolved to represent a coherent field of inquiry. Out of this vast dataset, 49 academic works were highlighted by the CPA suggesting a coherent field of inquiry; which means that researchers in the field acknowledge seminal contributions and share a common knowledge base. Other conflict concepts that were also analyzed—such as interpersonal conflict or conflict among pharmaceuticals, for example, did not form their own CP. A single path formed, meaning that there was a cohesive set of ideas that built upon previous research. This is in contrast to a main path analysis of conflict from 1957–1971 where ideas didn’t persist in that multiple paths existed and died or emerged reflecting lack of scientific coherence (Carley, Hummon, and Harty, 1993). The critical path consisted of a number of key features: 1) Concepts that built throughout include the notion that resource availability drives conflict, which emerged in the 1960s-1990s and continued on until 2011. More recent intrastate studies that focused on inequalities emerged from interstate studies on the democracy of peace earlier on the path. 2) Recent research on the path focused on forecasting conflict, which depends on well-developed metrics and theories to model. 3) We used keyword analysis to independently show how the CP was topically linked (i.e., through democracy, modeling, resources, and geography). Publically available conflict datasets developed early on helped

  7. PRIVACY PRESERVING DATA MINING USING MULTIPLE OBJECTIVE OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    V. Shyamala Susan

    2016-10-01

    Full Text Available Privacy preservation is that the most targeted issue in information publication, because the sensitive data shouldn't be leaked. For this sake, several privacy preservation data mining algorithms are proposed. In this work, feature selection using evolutionary algorithm and data masking coupled with slicing is treated as a multiple objective optimisation to preserve privacy. To start with, Genetic Algorithm (GA is carried out over the datasets to perceive the sensitive attributes and prioritise the attributes for treatment as per their determined sensitive level. In the next phase, to distort the data, noise is added to the higher level sensitive value using Hybrid Data Transformation (HDT method. In the following phase slicing algorithm groups the correlated attributes organized and by this means reduces the dimensionality by retaining the Advanced Clustering Algorithm (ACA. With the aim of getting the optimal dimensions of buckets, tuple segregating is accomplished by Metaheuristic Firefly Algorithm (MFA. The investigational consequences imply that the anticipated technique can reserve confidentiality and therefore the information utility is additionally high. Slicing algorithm allows the protection of association and usefulness in which effects in decreasing the information dimensionality and information loss. Performance analysis is created over OCC 7 and OCC 15 and our optimization method proves its effectiveness over two totally different datasets by showing 92.98% and 96.92% respectively.

  8. NP-PAH Interaction Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

  9. A dataset on tail risk of commodities markets.

    Science.gov (United States)

    Powell, Robert J; Vo, Duc H; Pham, Thach N; Singh, Abhay K

    2017-12-01

    This article contains the datasets related to the research article "The long and short of commodity tails and their relationship to Asian equity markets"(Powell et al., 2017) [1]. The datasets contain the daily prices (and price movements) of 24 different commodities decomposed from the S&P GSCI index and the daily prices (and price movements) of three share market indices including World, Asia, and South East Asia for the period 2004-2015. Then, the dataset is divided into annual periods, showing the worst 5% of price movements for each year. The datasets are convenient to examine the tail risk of different commodities as measured by Conditional Value at Risk (CVaR) as well as their changes over periods. The datasets can also be used to investigate the association between commodity markets and share markets.

  10. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    patients (Morgan et al., 2012; Abraham and Medzhitov, 2011; Bennike, 2014) [8–10. Therefore, we characterized the proteome of colon mucosa biopsies from 10 inflammatory bowel disease ulcerative colitis (UC) patients, 11 gastrointestinal healthy rheumatoid arthritis (RA) patients, and 10 controls. We...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  11. Use of country of birth as an indicator of refugee background in health datasets

    Science.gov (United States)

    2014-01-01

    Background Routine public health databases contain a wealth of data useful for research among vulnerable or isolated groups, who may be under-represented in traditional medical research. Identifying specific vulnerable populations, such as resettled refugees, can be particularly challenging; often country of birth is the sole indicator of whether an individual has a refugee background. The objective of this article was to review strengths and weaknesses of different methodological approaches to identifying resettled refugees and comparison groups from routine health datasets and to propose the application of additional methodological rigour in future research. Discussion Methodological approaches to selecting refugee and comparison groups from existing routine health datasets vary widely and are often explained in insufficient detail. Linked data systems or datasets from specialized refugee health services can accurately select resettled refugee and asylum seeker groups but have limited availability and can be selective. In contrast, country of birth is commonly collected in routine health datasets but a robust method for selecting humanitarian source countries based solely on this information is required. The authors recommend use of national immigration data to objectively identify countries of birth with high proportions of humanitarian entrants, matched by time period to the study dataset. When available, additional migration indicators may help to better understand migration as a health determinant. Methodologically, if multiple countries of birth are combined, the proportion of the sample represented by each country of birth should be included, with sub-analysis of individual countries of birth potentially providing further insights, if population size allows. United Nations-defined world regions provide an objective framework for combining countries of birth when necessary. A comparison group of economic migrants from the same world region may be appropriate

  12. Bose-Einstein correlations

    International Nuclear Information System (INIS)

    Zalewski, Kacper

    2000-01-01

    The effect of Bose-Einstein correlations on multiplicity distributions of identical pions is discussed. It is found that these correlations affect significantly the observed multiplicity distributions, but Einstein's condensation is unlikely to be achieved, unless 'cold spots', i.e. regions, where groups of pions with very small relative momenta are produced, occur in high energy heavy-ion collisions

  13. Multiplicity and transverse momentum evolution of charge-dependent correlations in pp, p-Pb, and Pb-Pb collisions at the LHC.

    Science.gov (United States)

    Adam, J; Adamová, D; Aggarwal, M M; Aglieri Rinella, G; Agnello, M; Agrawal, N; Ahammed, Z; Ahn, S U; Aiola, S; Akindinov, A; Alam, S N; Aleksandrov, D; Alessandro, B; Alexandre, D; Alfaro Molina, R; Alici, A; Alkin, A; Almaraz, J R M; Alme, J; Alt, T; Altinpinar, S; Altsybeev, I; Alves Garcia Prado, C; Andrei, C; Andronic, A; Anguelov, V; Anielski, J; Antičić, T; Antinori, F; Antonioli, P; Aphecetche, L; Appelshäuser, H; Arcelli, S; Arnaldi, R; Arnold, O W; Arsene, I C; Arslandok, M; Audurier, B; Augustinus, A; Averbeck, R; Azmi, M D; Badalà, A; Baek, Y W; Bagnasco, S; Bailhache, R; Bala, R; Baldisseri, A; Baral, R C; Barbano, A M; Barbera, R; Barile, F; Barnaföldi, G G; Barnby, L S; Barret, V; Bartalini, P; Barth, K; Bartke, J; Bartsch, E; Basile, M; Bastid, N; Basu, S; Bathen, B; Batigne, G; Batista Camejo, A; Batyunya, B; Batzing, P C; Bearden, I G; Beck, H; Bedda, C; Behera, N K; Belikov, I; Bellini, F; Bello Martinez, H; Bellwied, R; Belmont, R; Belmont-Moreno, E; Belyaev, V; Bencedi, G; Beole, S; Berceanu, I; Bercuci, A; Berdnikov, Y; Berenyi, D; Bertens, R A; Berzano, D; Betev, L; Bhasin, A; Bhat, I R; Bhati, A K; Bhattacharjee, B; Bhom, J; Bianchi, L; Bianchi, N; Bianchin, C; Bielčík, J; Bielčíková, J; Bilandzic, A; Biswas, R; Biswas, S; Bjelogrlic, S; Blair, J T; Blau, D; Blume, C; Bock, F; Bogdanov, A; Bøggild, H; Boldizsár, L; Bombara, M; Book, J; Borel, H; Borissov, A; Borri, M; Bossú, F; Botta, E; Böttger, S; Bourjau, C; Braun-Munzinger, P; Bregant, M; Breitner, T; Broker, T A; Browning, T A; Broz, M; Brucken, E J; Bruna, E; Bruno, G E; Budnikov, D; Buesching, H; Bufalino, S; Buncic, P; Busch, O; Buthelezi, Z; Butt, J B; Buxton, J T; Caffarri, D; Cai, X; Caines, H; Calero Diaz, L; Caliva, A; Calvo Villar, E; Camerini, P; Carena, F; Carena, W; Carnesecchi, F; Castillo Castellanos, J; Castro, A J; Casula, E A R; Ceballos Sanchez, C; Cepila, J; Cerello, P; Cerkala, J; Chang, B; Chapeland, S; Chartier, M; Charvet, J L; Chattopadhyay, S; Chattopadhyay, S; Chelnokov, V; Cherney, M; Cheshkov, C; Cheynis, B; Chibante Barroso, V; Chinellato, D D; Cho, S; Chochula, P; Choi, K; Chojnacki, M; Choudhury, S; Christakoglou, P; Christensen, C H; Christiansen, P; Chujo, T; Chung, S U; Cicalo, C; Cifarelli, L; Cindolo, F; Cleymans, J; Colamaria, F; Colella, D; Collu, A; Colocci, M; Conesa Balbastre, G; Conesa Del Valle, Z; Connors, M E; Contreras, J G; Cormier, T M; Corrales Morales, Y; Cortés Maldonado, I; Cortese, P; Cosentino, M R; Costa, F; Crochet, P; Cruz Albino, R; Cuautle, E; Cunqueiro, L; Dahms, T; Dainese, A; Danu, A; Das, D; Das, I; Das, S; Dash, A; Dash, S; De, S; De Caro, A; de Cataldo, G; de Conti, C; de Cuveland, J; De Falco, A; De Gruttola, D; De Marco, N; De Pasquale, S; Deisting, A; Deloff, A; Dénes, E; Deplano, C; Dhankher, P; Di Bari, D; Di Mauro, A; Di Nezza, P; Diaz Corchero, M A; Dietel, T; Dillenseger, P; Divià, R; Djuvsland, Ø; Dobrin, A; Domenicis Gimenez, D; Dönigus, B; Dordic, O; Drozhzhova, T; Dubey, A K; Dubla, A; Ducroux, L; Dupieux, P; Ehlers, R J; Elia, D; Engel, H; Epple, E; Erazmus, B; Erdemir, I; Erhardt, F; Espagnon, B; Estienne, M; Esumi, S; Eum, J; Evans, D; Evdokimov, S; Eyyubova, G; Fabbietti, L; Fabris, D; Faivre, J; Fantoni, A; Fasel, M; Feldkamp, L; Feliciello, A; Feofilov, G; Ferencei, J; Fernández Téllez, A; Ferreiro, E G; Ferretti, A; Festanti, A; Feuillard, V J G; Figiel, J; Figueredo, M A S; Filchagin, S; Finogeev, D; Fionda, F M; Fiore, E M; Fleck, M G; Floris, M; Foertsch, S; Foka, P; Fokin, S; Fragiacomo, E; Francescon, A; Frankenfeld, U; Fuchs, U; Furget, C; Furs, A; Fusco Girard, M; Gaardhøje, J J; Gagliardi, M; Gago, A M; Gallio, M; Gangadharan, D R; Ganoti, P; Gao, C; Garabatos, C; Garcia-Solis, E; Gargiulo, C; Gasik, P; Gauger, E F; Germain, M; Gheata, A; Gheata, M; Ghosh, P; Ghosh, S K; Gianotti, P; Giubellino, P; Giubilato, P; Gladysz-Dziadus, E; Glässel, P; Goméz Coral, D M; Gomez Ramirez, A; Gonzalez, V; González-Zamora, P; Gorbunov, S; Görlich, L; Gotovac, S; Grabski, V; Grachov, O A; Graczykowski, L K; Graham, K L; Grelli, A; Grigoras, A; Grigoras, C; Grigoriev, V; Grigoryan, A; Grigoryan, S; Grinyov, B; Grion, N; Gronefeld, J M; Grosse-Oetringhaus, J F; Grossiord, J-Y; Grosso, R; Guber, F; Guernane, R; Guerzoni, B; Gulbrandsen, K; Gunji, T; Gupta, A; Gupta, R; Haake, R; Haaland, Ø; Hadjidakis, C; Haiduc, M; Hamagaki, H; Hamar, G; Harris, J W; Harton, A; Hatzifotiadou, D; Hayashi, S; Heckel, S T; Heide, M; Helstrup, H; Herghelegiu, A; Herrera Corral, G; Hess, B A; Hetland, K F; Hillemanns, H; Hippolyte, B; Hosokawa, R; Hristov, P; Huang, M; Humanic, T J; Hussain, N; Hussain, T; Hutter, D; Hwang, D S; Ilkaev, R; Inaba, M; Ippolitov, M; Irfan, M; Ivanov, M; Ivanov, V; Izucheev, V; Jacobs, P M; Jadhav, M B; Jadlovska, S; Jadlovsky, J; Jahnke, C; Jakubowska, M J; Jang, H J; Janik, M A; Jayarathna, P H S Y; Jena, C; Jena, S; Jimenez Bustamante, R T; Jones, P G; Jung, H; Jusko, A; Kalinak, P; Kalweit, A; Kamin, J; Kang, J H; Kaplin, V; Kar, S; Karasu Uysal, A; Karavichev, O; Karavicheva, T; Karayan, L; Karpechev, E; Kebschull, U; Keidel, R; Keijdener, D L D; Keil, M; Mohisin Khan, M; Khan, P; Khan, S A; Khanzadeev, A; Kharlov, Y; Kileng, B; Kim, D W; Kim, D J; Kim, D; Kim, H; Kim, J S; Kim, M; Kim, M; Kim, S; Kim, T; Kirsch, S; Kisel, I; Kiselev, S; Kisiel, A; Kiss, G; Klay, J L; Klein, C; Klein, J; Klein-Bösing, C; Klewin, S; Kluge, A; Knichel, M L; Knospe, A G; Kobayashi, T; Kobdaj, C; Kofarago, M; Kollegger, T; Kolojvari, A; Kondratiev, V; Kondratyeva, N; Kondratyuk, E; Konevskikh, A; Kopcik, M; Kour, M; Kouzinopoulos, C; Kovalenko, O; Kovalenko, V; Kowalski, M; Koyithatta Meethaleveedu, G; Králik, I; Kravčáková, A; Kretz, M; Krivda, M; Krizek, F; Kryshen, E; Krzewicki, M; Kubera, A M; Kučera, V; Kuhn, C; Kuijer, P G; Kumar, A; Kumar, J; Kumar, L; Kumar, S; Kurashvili, P; Kurepin, A; Kurepin, A B; Kuryakin, A; Kweon, M J; Kwon, Y; La Pointe, S L; La Rocca, P; Ladron de Guevara, P; Lagana Fernandes, C; Lakomov, I; Langoy, R; Lara, C; Lardeux, A; Lattuca, A; Laudi, E; Lea, R; Leardini, L; Lee, G R; Lee, S; Lehas, F; Lemmon, R C; Lenti, V; Leogrande, E; León Monzón, I; León Vargas, H; Leoncino, M; Lévai, P; Li, S; Li, X; Lien, J; Lietava, R; Lindal, S; Lindenstruth, V; Lippmann, C; Lisa, M A; Ljunggren, H M; Lodato, D F; Loenne, P I; Loginov, V; Loizides, C; Lopez, X; López Torres, E; Lowe, A; Luettig, P; Lunardon, M; Luparello, G; Maevskaya, A; Mager, M; Mahajan, S; Mahmood, S M; Maire, A; Majka, R D; Malaev, M; Maldonado Cervantes, I; Malinina, L; Mal'Kevich, D; Malzacher, P; Mamonov, A; Manko, V; Manso, F; Manzari, V; Marchisone, M; Mareš, J; Margagliotti, G V; Margotti, A; Margutti, J; Marín, A; Markert, C; Marquard, M; Martin, N A; Martin Blanco, J; Martinengo, P; Martínez, M I; Martínez García, G; Martinez Pedreira, M; Mas, A; Masciocchi, S; Masera, M; Masoni, A; Massacrier, L; Mastroserio, A; Matyja, A; Mayer, C; Mazer, J; Mazzoni, M A; Mcdonald, D; Meddi, F; Melikyan, Y; Menchaca-Rocha, A; Meninno, E; Mercado Pérez, J; Meres, M; Miake, Y; Mieskolainen, M M; Mikhaylov, K; Milano, L; Milosevic, J; Minervini, L M; Mischke, A; Mishra, A N; Miśkowiec, D; Mitra, J; Mitu, C M; Mohammadi, N; Mohanty, B; Molnar, L; Montaño Zetina, L; Montes, E; Moreira De Godoy, D A; Moreno, L A P; Moretto, S; Morreale, A; Morsch, A; Muccifora, V; Mudnic, E; Mühlheim, D; Muhuri, S; Mukherjee, M; Mulligan, J D; Munhoz, M G; Munzer, R H; Murray, S; Musa, L; Musinsky, J; Naik, B; Nair, R; Nandi, B K; Nania, R; Nappi, E; Naru, M U; Natal da Luz, H; Nattrass, C; Nayak, K; Nayak, T K; Nazarenko, S; Nedosekin, A; Nellen, L; Ng, F; Nicassio, M; Niculescu, M; Niedziela, J; Nielsen, B S; Nikolaev, S; Nikulin, S; Nikulin, V; Noferini, F; Nomokonov, P; Nooren, G; Noris, J C C; Norman, J; Nyanin, A; Nystrand, J; Oeschler, H; Oh, S; Oh, S K; Ohlson, A; Okatan, A; Okubo, T; Olah, L; Oleniacz, J; Oliveira Da Silva, A C; Oliver, M H; Onderwaater, J; Oppedisano, C; Orava, R; Ortiz Velasquez, A; Oskarsson, A; Otwinowski, J; Oyama, K; Ozdemir, M; Pachmayer, Y; Pagano, P; Paić, G; Pal, S K; Pan, J; Pandey, A K; Papcun, P; Papikyan, V; Pappalardo, G S; Pareek, P; Park, W J; Parmar, S; Passfeld, A; Paticchio, V; Patra, R N; Paul, B; Peitzmann, T; Pereira Da Costa, H; Pereira De Oliveira Filho, E; Peresunko, D; Pérez Lara, C E; Perez Lezama, E; Peskov, V; Pestov, Y; Petráček, V; Petrov, V; Petrovici, M; Petta, C; Piano, S; Pikna, M; Pillot, P; Pinazza, O; Pinsky, L; Piyarathna, D B; Płoskoń, M; Planinic, M; Pluta, J; Pochybova, S; Podesta-Lerma, P L M; Poghosyan, M G; Polichtchouk, B; Poljak, N; Poonsawat, W; Pop, A; Porteboeuf-Houssais, S; Porter, J; Pospisil, J; Prasad, S K; Preghenella, R; Prino, F; Pruneau, C A; Pshenichnov, I; Puccio, M; Puddu, G; Pujahari, P; Punin, V; Putschke, J; Qvigstad, H; Rachevski, A; Raha, S; Rajput, S; Rak, J; Rakotozafindrabe, A; Ramello, L; Rami, F; Raniwala, R; Raniwala, S; Räsänen, S S; Rascanu, B T; Rathee, D; Read, K F; Redlich, K; Reed, R J; Rehman, A; Reichelt, P; Reidt, F; Ren, X; Renfordt, R; Reolon, A R; Reshetin, A; Revol, J-P; Reygers, K; Riabov, V; Ricci, R A; Richert, T; Richter, M; Riedler, P; Riegler, W; Riggi, F; Ristea, C; Rocco, E; Rodríguez Cahuantzi, M; Rodriguez Manso, A; Røed, K; Rogochaya, E; Rohr, D; Röhrich, D; Romita, R; Ronchetti, F; Ronflette, L; Rosnet, P; Rossi, A; Roukoutakis, F; Roy, A; Roy, C; Roy, P; Rubio Montero, A J; Rui, R; Russo, R; Ryabinkin, E; Ryabov, Y; Rybicki, A; Sadovsky, S; Šafařík, K; Sahlmuller, B; Sahoo, P; Sahoo, R; Sahoo, S; Sahu, P K; Saini, J; Sakai, S; Saleh, M A; Salzwedel, J; Sambyal, S; Samsonov, V; Šándor, L; Sandoval, A; Sano, M; Sarkar, D; Scapparone, E; Scarlassara, F; Schiaua, C; Schicker, R; Schmidt, C; Schmidt, H R; Schuchmann, S; Schukraft, J; Schulc, M; Schuster, T; Schutz, Y; Schwarz, K; Schweda, K; Scioli, G; Scomparin, E; Scott, R; Šefčík, M; Seger, J E; Sekiguchi, Y; Sekihata, D; Selyuzhenkov, I; Senosi, K; Senyukov, S; Serradilla, E; Sevcenco, A; Shabanov, A; Shabetai, A; Shadura, O; Shahoyan, R; Shangaraev, A; Sharma, A; Sharma, M; Sharma, M; Sharma, N; Shigaki, K; Shtejer, K; Sibiriak, Y; Siddhanta, S; Sielewicz, K M; Siemiarczuk, T; Silvermyr, D; Silvestre, C; Simatovic, G; Simonetti, G; Singaraju, R; Singh, R; Singha, S; Singhal, V; Sinha, B C; Sinha, T; Sitar, B; Sitta, M; Skaali, T B; Slupecki, M; Smirnov, N; Snellings, R J M; Snellman, T W; Søgaard, C; Song, J; Song, M; Song, Z; Soramel, F; Sorensen, S; Sozzi, F; Spacek, M; Spiriti, E; Sputowska, I; Spyropoulou-Stassinaki, M; Stachel, J; Stan, I; Stefanek, G; Stenlund, E; Steyn, G; Stiller, J H; Stocco, D; Strmen, P; Suaide, A A P; Sugitate, T; Suire, C; Suleymanov, M; Suljic, M; Sultanov, R; Šumbera, M; Szabo, A; Szanto de Toledo, A; Szarka, I; Szczepankiewicz, A; Szymanski, M; Tabassam, U; Takahashi, J; Tambave, G J; Tanaka, N; Tangaro, M A; Tarhini, M; Tariq, M; Tarzila, M G; Tauro, A; Tejeda Muñoz, G; Telesca, A; Terasaki, K; Terrevoli, C; Teyssier, B; Thäder, J; Thomas, D; Tieulent, R; Timmins, A R; Toia, A; Trogolo, S; Trombetta, G; Trubnikov, V; Trzaska, W H; Tsuji, T; Tumkin, A; Turrisi, R; Tveter, T S; Ullaland, K; Uras, A; Usai, G L; Utrobicic, A; Vajzer, M; Vala, M; Valencia Palomo, L; Vallero, S; Van Der Maarel, J; Van Hoorne, J W; van Leeuwen, M; Vanat, T; Vande Vyvre, P; Varga, D; Vargas, A; Vargyas, M; Varma, R; Vasileiou, M; Vasiliev, A; Vauthier, A; Vechernin, V; Veen, A M; Veldhoen, M; Velure, A; Venaruzzo, M; Vercellin, E; Vergara Limón, S; Vernet, R; Verweij, M; Vickovic, L; Viesti, G; Viinikainen, J; Vilakazi, Z; Villalobos Baillie, O; Villatoro Tello, A; Vinogradov, A; Vinogradov, L; Vinogradov, Y; Virgili, T; Vislavicius, V; Viyogi, Y P; Vodopyanov, A; Völkl, M A; Voloshin, K; Voloshin, S A; Volpe, G; von Haller, B; Vorobyev, I; Vranic, D; Vrláková, J; Vulpescu, B; Vyushin, A; Wagner, B; Wagner, J; Wang, H; Wang, M; Watanabe, D; Watanabe, Y; Weber, M; Weber, S G; Weiser, D F; Wessels, J P; Westerhoff, U; Whitehead, A M; Wiechula, J; Wikne, J; Wilde, M; Wilk, G; Wilkinson, J; Williams, M C S; Windelband, B; Winn, M; Yaldo, C G; Yang, H; Yang, P; Yano, S; Yasar, C; Yin, Z; Yokoyama, H; Yoo, I-K; Yoon, J H; Yurchenko, V; Yushmanov, I; Zaborowska, A; Zaccolo, V; Zaman, A; Zampolli, C; Zanoli, H J C; Zaporozhets, S; Zardoshti, N; Zarochentsev, A; Závada, P; Zaviyalov, N; Zbroszczyk, H; Zgura, I S; Zhalov, M; Zhang, H; Zhang, X; Zhang, Y; Zhang, C; Zhang, Z; Zhao, C; Zhigareva, N; Zhou, D; Zhou, Y; Zhou, Z; Zhu, H; Zhu, J; Zichichi, A; Zimmermann, A; Zimmermann, M B; Zinovjev, G; Zyzak, M

    We report on two-particle charge-dependent correlations in pp, p-Pb, and Pb-Pb collisions as a function of the pseudorapidity and azimuthal angle difference, [Formula: see text] and [Formula: see text] respectively. These correlations are studied using the balance function that probes the charge creation time and the development of collectivity in the produced system. The dependence of the balance function on the event multiplicity as well as on the trigger and associated particle transverse momentum ([Formula: see text]) in pp, p-Pb, and Pb-Pb collisions at [Formula: see text] 7, 5.02, and 2.76 TeV, respectively, are presented. In the low transverse momentum region, for [Formula: see text] GeV/ c , the balance function becomes narrower in both [Formula: see text] and [Formula: see text] directions in all three systems for events with higher multiplicity. The experimental findings favor models that either incorporate some collective behavior (e.g. AMPT) or different mechanisms that lead to effects that resemble collective behavior (e.g. PYTHIA8 with color reconnection). For higher values of transverse momenta the balance function becomes even narrower but exhibits no multiplicity dependence, indicating that the observed narrowing with increasing multiplicity at low [Formula: see text] is a feature of bulk particle production.

  14. Comparison of Shallow Survey 2012 Multibeam Datasets

    Science.gov (United States)

    Ramirez, T. M.

    2012-12-01

    The purpose of the Shallow Survey common dataset is a comparison of the different technologies utilized for data acquisition in the shallow survey marine environment. The common dataset consists of a series of surveys conducted over a common area of seabed using a variety of systems. It provides equipment manufacturers the opportunity to showcase their latest systems while giving hydrographic researchers and scientists a chance to test their latest algorithms on the dataset so that rigorous comparisons can be made. Five companies collected data for the Common Dataset in the Wellington Harbor area in New Zealand between May 2010 and May 2011; including Kongsberg, Reson, R2Sonic, GeoAcoustics, and Applied Acoustics. The Wellington harbor and surrounding coastal area was selected since it has a number of well-defined features, including the HMNZS South Seas and HMNZS Wellington wrecks, an armored seawall constructed of Tetrapods and Akmons, aquifers, wharves and marinas. The seabed inside the harbor basin is largely fine-grained sediment, with gravel and reefs around the coast. The area outside the harbor on the southern coast is an active environment, with moving sand and exposed reefs. A marine reserve is also in this area. For consistency between datasets, the coastal research vessel R/V Ikatere and crew were used for all surveys conducted for the common dataset. Using Triton's Perspective processing software multibeam datasets collected for the Shallow Survey were processed for detail analysis. Datasets from each sonar manufacturer were processed using the CUBE algorithm developed by the Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC). Each dataset was gridded at 0.5 and 1.0 meter resolutions for cross comparison and compliance with International Hydrographic Organization (IHO) requirements. Detailed comparisons were made of equipment specifications (transmit frequency, number of beams, beam width), data density, total uncertainty, and

  15. National Hydrography Dataset (NHD)

    Data.gov (United States)

    Kansas Data Access and Support Center — The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the...

  16. Detrended fluctuation analysis of short datasets: An application to fetal cardiac data

    Science.gov (United States)

    Govindan, R. B.; Wilson, J. D.; Preißl, H.; Eswaran, H.; Campbell, J. Q.; Lowery, C. L.

    2007-02-01

    Using detrended fluctuation analysis (DFA) we perform scaling analysis of short datasets of length 500-1500 data points. We quantify the long range correlation (exponent α) by computing the mean value of the local exponents αL (in the asymptotic regime). The local exponents are obtained as the (numerical) derivative of the logarithm of the fluctuation function F(s) with respect to the logarithm of the scale factor s:αL=dlog10F(s)/dlog10s. These local exponents display huge variations and complicate the correct quantification of the underlying correlations. We propose the use of the phase randomized surrogate (PRS), which preserves the long range correlations of the original data, to minimize the variations in the local exponents. Using the numerically generated uncorrelated and long range correlated data, we show that performing DFA on several realizations of PRS and estimating αL from the averaged fluctuation functions (of all realizations) can minimize the variations in αL. The application of this approach to the fetal cardiac data (RR intervals) is discussed and we show that there is a statistically significant correlation between α and the gestation age.

  17. A new bed elevation dataset for Greenland

    Directory of Open Access Journals (Sweden)

    J. L. Bamber

    2013-03-01

    Full Text Available We present a new bed elevation dataset for Greenland derived from a combination of multiple airborne ice thickness surveys undertaken between the 1970s and 2012. Around 420 000 line kilometres of airborne data were used, with roughly 70% of this having been collected since the year 2000, when the last comprehensive compilation was undertaken. The airborne data were combined with satellite-derived elevations for non-glaciated terrain to produce a consistent bed digital elevation model (DEM over the entire island including across the glaciated–ice free boundary. The DEM was extended to the continental margin with the aid of bathymetric data, primarily from a compilation for the Arctic. Ice thickness was determined where an ice shelf exists from a combination of surface elevation and radar soundings. The across-track spacing between flight lines warranted interpolation at 1 km postings for significant sectors of the ice sheet. Grids of ice surface elevation, error estimates for the DEM, ice thickness and data sampling density were also produced alongside a mask of land/ocean/grounded ice/floating ice. Errors in bed elevation range from a minimum of ±10 m to about ±300 m, as a function of distance from an observation and local topographic variability. A comparison with the compilation published in 2001 highlights the improvement in resolution afforded by the new datasets, particularly along the ice sheet margin, where ice velocity is highest and changes in ice dynamics most marked. We estimate that the volume of ice included in our land-ice mask would raise mean sea level by 7.36 m, excluding any solid earth effects that would take place during ice sheet decay.

  18. The Harvard organic photovoltaic dataset.

    Science.gov (United States)

    Lopez, Steven A; Pyzer-Knapp, Edward O; Simm, Gregor N; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-09-27

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications.

  19. Analysis of pairwise correlations in multi-parametric PET/MR data for biological tumor characterization and treatment individualization strategies

    Energy Technology Data Exchange (ETDEWEB)

    Leibfarth, Sara; Moennich, David; Thorwarth, Daniela [University Hospital Tuebingen, Section for Biomedical Physics, Department of Radiation Oncology, Tuebingen (Germany); Simoncic, Urban [University Hospital Tuebingen, Section for Biomedical Physics, Department of Radiation Oncology, Tuebingen (Germany); University of Ljubljana, Faculty of Mathematics and Physics, Ljubljana (Slovenia); Jozef Stefan Institute, Ljubljana (Slovenia); Welz, Stefan; Zips, Daniel [University Hospital Tuebingen, Department of Radiation Oncology, Tuebingen (Germany); Schmidt, Holger; Schwenzer, Nina [University Hospital Tuebingen, Department of Diagnostic and Interventional Radiology, Tuebingen (Germany)

    2016-07-15

    The aim of this pilot study was to explore simultaneous functional PET/MR for biological characterization of tumors and potential future treatment adaptations. To investigate the extent of complementarity between different PET/MR-based functional datasets, a pairwise correlation analysis was performed. Functional datasets of N=15 head and neck (HN) cancer patients were evaluated. For patients of group A (N=7), combined PET/MR datasets including FDG-PET and ADC maps were available. Patients of group B (N=8) had FMISO-PET, DCE-MRI and ADC maps from combined PET/MRI, an additional dynamic FMISO-PET/CT acquired directly after FMISO tracer injection as well as an FDG-PET/CT acquired a few days earlier. From DCE-MR, parameter maps K{sup trans}, v{sub e} and v{sub p} were obtained with the extended Tofts model. Moreover, parameter maps of mean DCE enhancement, ΔS{sub DCE}, and mean FMISO signal 0-4 min p.i., anti A{sub FMISO}, were derived. Pairwise correlations were quantified using the Spearman correlation coefficient (r) on both a voxel and a regional level within the gross tumor volume. Between some pairs of functional imaging modalities moderate correlations were observed with respect to the median over all patient datasets, whereas distinct correlations were only present on an individual basis. Highest inter-modality median correlations on the voxel level were obtained for FDG/FMISO (r = 0.56), FDG/ anti A{sub FMISO} (r = 0.55), anti A{sub FMISO}/ΔS{sub DCE} (r = 0.46), and FDG/ADC (r = -0.39). Correlations on the regional level showed comparable results. The results of this study suggest that the examined functional datasets provide complementary information. However, only pairwise correlations were examined, and correlations could still exist between combinations of three or more datasets. These results might contribute to the future design of individually adapted treatment approaches based on multiparametric functional imaging.

  20. Tables and figure datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — Soil and air concentrations of asbestos in Sumas study. This dataset is associated with the following publication: Wroble, J., T. Frederick, A. Frame, and D....

  1. A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Jessica Roelands

    2018-02-01

    Full Text Available The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB. In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.

  2. Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm

    DEFF Research Database (Denmark)

    Grotkjær, Thomas; Winther, Ole; Regenberg, Birgitte

    2006-01-01

    Motivation: Hierarchical and relocation clustering (e.g. K-means and self-organizing maps) have been successful tools in the display and analysis of whole genome DNA microarray expression data. However, the results of hierarchical clustering are sensitive to outliers, and most relocation methods...... analysis by collecting re-occurring clustering patterns in a co-occurrence matrix. The results show that consensus clustering obtained from clustering multiple times with Variational Bayes Mixtures of Gaussians or K-means significantly reduces the classification error rate for a simulated dataset...

  3. Information security using multiple reference-based optical joint transform correlation and orthogonal code

    Science.gov (United States)

    Nazrul Islam, Mohammed; Karim, Mohammad A.; Vijayan Asari, K.

    2013-09-01

    Protecting and processing of confidential information, such as personal identification, biometrics, remains a challenging task for further research and development. A new methodology to ensure enhanced security of information in images through the use of encryption and multiplexing is proposed in this paper. We use orthogonal encoding scheme to encode multiple information independently and then combine them together to save storage space and transmission bandwidth. The encoded and multiplexed image is encrypted employing multiple reference-based joint transform correlation. The encryption key is fed into four channels which are relatively phase shifted by different amounts. The input image is introduced to all the channels and then Fourier transformed to obtain joint power spectra (JPS) signals. The resultant JPS signals are again phase-shifted and then combined to form a modified JPS signal which yields the encrypted image after having performed an inverse Fourier transformation. The proposed cryptographic system makes the confidential information absolutely inaccessible to any unauthorized intruder, while allows for the retrieval of the information to the respective authorized recipient without any distortion. The proposed technique is investigated through computer simulations under different practical conditions in order to verify its overall robustness.

  4. Forward-backward multiplicity correlations in pp collisions at root s=0.9, 2.76 and 7 TeV

    NARCIS (Netherlands)

    Adam, J.; Adamova, D.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmed, I.; Ahn, S. U.; Aimo, I.; Aiola, S.; Ajaz, M.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anielski, J.; Anticic, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshaeuser, H.; Arcelli, S.; Armesto, N.; Arnaldi, R.; Aronsson, T.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Bach, M.; Badala, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Pedrosa, F. Baltasar Dos Santos; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnafoeldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Camejo, A. Batista; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Martinez, H. Bello; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielcik, J.; Bielcikova, J.; Bilandzic, A.; Biswas, S.; Bjelogrlic, S.; Blanco, F.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Boggild, H.; Boldizsar, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossu, F.; Botje, M.; Botta, E.; Boettger, S.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Diaz, L. Calero; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Cavicchioli, C.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Balbastre, G. Conesa; del Valle, Z. Conesa; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Cortes Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deloff, A.; Denes, E.; D'Erasmo, G.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Corchero, M. A. Diaz; Dietel, T.; Dillenseger, P.; Divia, R.; Djuvsland, O.; Dobrin, A.; Dobrowolski, T.; Domenicis Gimenez, D.; Doenigus, B.; Dordic, O.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Erazmus, B.; Erdal, H. A.; Eschweiler, D.; Espagnon, B.; Esposito, M.; Estienne, M.; Esumi, S.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Felea, D.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernandez Tellez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fuchs, U.; Furget, C.; Furs, A.; Girard, M. Fusco; Gaardhoje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Germain, M.; Gheata, A.; Gheata, M.; Ghidini, B.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glaessel, P.; Ramirez, A. Gomez; Gonzalez-Zamora, P.; Gorbunov, S.; Goerlich, L.; Gotovac, S.; Grabski, V.; Graczykowski, L. K.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Grosse-Oetringhaus, J. F.; Grossiord, J. -Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gulkanyan, H.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, O.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hanratty, L. D.; Hansen, A.; Harris, J. W.; Hartmann, H.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Heide, M.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hilden, T. E.; Hillemanns, H.; Hippolyte, B.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Ilkiv, I.; Inaba, M.; Ionita, C.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Jacholkowski, A.; Jacobs, P. M.; Jahnke, C.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jung, H.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Uysal, A. Karasu; Karavichev, O.; Karavicheva, T.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Khan, K. H.; Khan, M. M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, B.; Kim, D. W.; Kim, D. J.; Kim, H.; Kim, J. S.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Boesing, C.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobayashi, T.; Kobdaj, C.; Kofarago, M.; Koehler, M. K.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kovalenko, V.; Kowalski, M.; Kox, S.; Meethaleveedu, G. Koyithatta; Kral, J.; Kralik, I.; Kravcakova, A.; Krelina, M.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kucera, V.; Kucheriaev, Y.; Kugathasan, T.; Kuhn, C.; Kuijer, P. G.; Kulakov, I.; Kumar, J.; Kumar, L.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Legrand, I.; Lehnert, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; Leon Monzon, I.; Leoncino, M.; Levai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loggins, V. R.; Loginov, V.; Loizides, C.; Lopez, X.; Lopez Torres, E.; Lowe, A.; Lu, X. -G.; Luettig, P.; Lunardon, M.; Luparello, G.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manceau, L.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mares, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marin, A.; Markert, C.; Marquard, M.; Martashvili, I.; Martin, N. A.; Blanco, J. Martin; Martinengo, P.; Martinez, M. I.; Garcia, G. Martinez; Martynov, Y.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Menchaca-Rocha, A.; Meninno, E.; Perez, J. Mercado; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montano Zetina, L.; Montes, E.; Morando, M.; De Godoy, D. A. Moreira; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Muehlheim, D.; Muhuri, S.; Mukherjee, M.; Mueller, H.; Mulligan, J. D.; Munhoz, M. G.; Murray, S.; Musa, L.; Musinsky, J.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Nilsen, B. S.; Noferini, F.; Nomokonov, P.; Nooren, G.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Onderwaater, J.; Oppedisano, C.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paic, G.; Pajares, C.; Pal, S. K.; Pan, J.; Pandey, A. K.; Pant, D.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Patalakha, D. I.; Paticchio, V.; Paul, B.; Pawlak, T.; Peitzmann, T.; Da Costa, H. Pereira; De Oliveira Filho, E. Pereira; Peresunko, D.; Lara, C. E. Perez; Peskov, V.; Pestov, Y.; Petracek, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Raniwala, R.; Raniwala, S.; Rasanen, S. S.; Rascanu, B. T.; Rathee, D.; Rauf, A. W.; Razazi, V.; Read, K. F.; Real, J. S.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reicher, M.; Reidt, F.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Rettig, F.; Revol, J. -P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rivetti, A.; Rocco, E.; Rodriguez Cahuantzi, M.; Manso, A. Rodriguez; Roed, K.; Rogochaya, E.; Rohr, D.; Rohrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Safarik, K. .; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salgado, C. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Castro, X. Sanchez; Sandor, L.; Sandoval, A.; Sano, M.; Santagati, G.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Seeder, K. S.; Segato, G.; Seger, J. E.; Sekiguchi, Y.; Selyuzhenkov, I.; Senosi, K.; Seo, J.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Skjerdal, K.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Sogaard, C.; Soltz, R.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stefanek, G.; Steinpreis, M.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Sultanov, R.; Sumbera, M.; Symons, T. J. M.; Szabo, A.; de Toledo, A. Szanto; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Takahashi, J.; Tanaka, N.; Tangaro, M. A.; Takaki, J. D. Tapia; Peloni, A. Tarantola; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Munoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thaeder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Palomo, L. Valencia; Vallero, S.; Van der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vyvre, P. Vande; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limon, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Baillie, O. Villalobos; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Voelkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrlakova, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Wang, Y.; Watanabe, D.; Weber, M.; Weber, S. G.; Wessels, J. P.; Westerhoff, U.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yamaguchi, Y.; Yang, H.; Yang, P.; Yano, S.; Yasnopolskiy, S.; Yin, Z.; Yokoyama, H.; Yoo, I. -K.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zarochentsev, A.; Zavada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zhu, X.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.

    2015-01-01

    The strength of forward-backward (FB) multiplicity correlations is measured by the ALICE detector in proton-proton (pp) collisions at = 0.9, 2.76 and 7 TeV. The measurement is performed in the central pseudorapidity region (|eta| <0.8) for the transverse momentum p (T) > 0.3 GeV/c. Two separate

  5. Bayesian Correlation Analysis for Sequence Count Data.

    Directory of Open Access Journals (Sweden)

    Daniel Sánchez-Taltavull

    Full Text Available Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low-especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities' signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset.

  6. Swallowing abnormalities in multiple sclerosis: correlation between videofluoroscopy and subjective symptoms

    Energy Technology Data Exchange (ETDEWEB)

    Wiesner, W.; Steinbrich, W. [Institute of Diagnostic Radiology, University Hospital of Basel (Switzerland); Wetzel, S.G.; Radue, E.W. [Institute of Neuroradiology, University Hospital Basel (Switzerland); Kappos, L.; Hoshi, M.M. [Department of Neurology, University Hospital of Basel (Switzerland); Witte, U. [Section of Logopedia, University Hospital of Basel (Switzerland)

    2002-04-01

    The purpose of this study was to evaluate if subjective symptoms indicating an impaired deglutition correlate with videofluoroscopic findings in patients with multiple sclerosis (MS). Videofluoroscopic examinations of 18 MS patients were analyzed by a radiologist and a logopedist and compared with the symptoms of these patients. Four patients complained about permanent dysphagia. Six patients reported mild and intermittent difficulties in swallowing, but were asymptomatic at the time of videofluoroscopy. Eight patients had no symptoms regarding their deglutition. All patients (n=4) who complained of permanent dysphagia showed aspiration. All patients (n=6) with mild and intermittent difficulties in swallowing showed undercoating of the epiglottis and/or laryngeal penetration. Of those 8 patients without any swallowing symptoms, only 2 had a normal videofluoroscopy. Swallowing abnormalities seem to be much more frequent in patients with MS than generally believed and they may easily be missed clinically as long as the patients do not aspirate. (orig.)

  7. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2013-01-01

    The first part of the Long Shutdown period has been dedicated to the preparation of the samples for the analysis targeting the summer conferences. In particular, the 8 TeV data acquired in 2012, including most of the “parked datasets”, have been reconstructed profiting from improved alignment and calibration conditions for all the sub-detectors. A careful planning of the resources was essential in order to deliver the datasets well in time to the analysts, and to schedule the update of all the conditions and calibrations needed at the analysis level. The newly reprocessed data have undergone detailed scrutiny by the Dataset Certification team allowing to recover some of the data for analysis usage and further improving the certification efficiency, which is now at 91% of the recorded luminosity. With the aim of delivering a consistent dataset for 2011 and 2012, both in terms of conditions and release (53X), the PPD team is now working to set up a data re-reconstruction and a new MC pro...

  8. Analyzing the Impacts of Alternated Number of Iterations in Multiple Imputation Method on Explanatory Factor Analysis

    Directory of Open Access Journals (Sweden)

    Duygu KOÇAK

    2017-11-01

    Full Text Available The study aims to identify the effects of iteration numbers used in multiple iteration method, one of the methods used to cope with missing values, on the results of factor analysis. With this aim, artificial datasets of different sample sizes were created. Missing values at random and missing values at complete random were created in various ratios by deleting data. For the data in random missing values, a second variable was iterated at ordinal scale level and datasets with different ratios of missing values were obtained based on the levels of this variable. The data were generated using “psych” program in R software, while “dplyr” program was used to create codes that would delete values according to predetermined conditions of missing value mechanism. Different datasets were generated by applying different iteration numbers. Explanatory factor analysis was conducted on the datasets completed and the factors and total explained variances are presented. These values were first evaluated based on the number of factors and total variance explained of the complete datasets. The results indicate that multiple iteration method yields a better performance in cases of missing values at random compared to datasets with missing values at complete random. Also, it was found that increasing the number of iterations in both missing value datasets decreases the difference in the results obtained from complete datasets.

  9. Dataset of statements on policy integration of selected intergovernmental organizations

    Directory of Open Access Journals (Sweden)

    Jale Tosun

    2018-04-01

    Full Text Available This article describes data for 78 intergovernmental organizations (IGOs working on topics related to energy governance, environmental protection, and the economy. The number of IGOs covered also includes organizations active in other sectors. The point of departure for data construction was the Correlates of War dataset, from which we selected this sample of IGOs. We updated and expanded the empirical information on the IGOs selected by manual coding. Most importantly, we collected the primary law texts of the individual IGOs in order to code whether they commit themselves to environmental policy integration (EPI, climate policy integration (CPI and/or energy policy integration (EnPI.

  10. Integrated Surface Dataset (Global)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Integrated Surface (ISD) Dataset (ISD) is composed of worldwide surface weather observations from over 35,000 stations, though the best spatial coverage is...

  11. Aaron Journal article datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — All figures used in the journal article are in netCDF format. This dataset is associated with the following publication: Sims, A., K. Alapaty , and S. Raman....

  12. Market Squid Ecology Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains ecological information collected on the major adult spawning and juvenile habitats of market squid off California and the US Pacific Northwest....

  13. MRI EVALUATION OF PAINFUL KNEE JOINT- THE CORRELATION OF MULTIPLE COEXISTING PATHOLOGIES, AGE AND SEX

    Directory of Open Access Journals (Sweden)

    Mukheswar Pame

    2017-03-01

    Full Text Available BACKGROUND 1. To evaluate the incidence and coexistence of multiple knee joint pathologies causing painful knee and their correlation to age and sex. 2. To evaluate the Magnetic Resonance Imaging (MRI features in various knee pathologies and to identify the common lesions. MATERIALS AND METHODS A retrospective study was performed using the clinical data of patients presenting with painful knee joint which were evaluated with MRI. Data from 200 patients examined between September 2015 and August 2016 were included into this study. The data was analysed statistically to evaluate the correlation between the MR pathological findings to age and sex of the patients. RESULTS The patient’s age ranged between 8 and 75 years (mean: 36 years. Anterior cruciate ligament (ACL tear was the commonest finding (60% followed by bursitis (55%, meniscal degeneration (54.6% and meniscal tear (52%. Primary signs of ACL tear were hyperintensity, discontinuity and nonvisualisation. Secondary signs like Posterior cruciate ligament (PCL buckling, PCL index of greater than 0.5, uncovered Lateral meniscus (LM and bone contusion assisted in diagnosis in indeterminate cases. Mid substance was the commonest site of ACL tear (64%. PCL tear accounted for only a small percentage (7%. Medial Meniscus (MM tear (35% was commoner than LM tear (17%. The posterior horn of meniscus was the commonest site of injury (86.5%. Age was significantly correlated with meniscal degeneration and tear, Medial collateral ligament (MCL degeneration, parameniscal cyst, and chondromalacia patellae. A significant correlation between male gender and ACL injury was noted. Meniscal injury was significantly correlated with bursitis, as well with MCL injury. Bone bruise was significantly correlated with ACL injury, MCL injury and Lateral collateral ligament (LCL injury. CONCLUSIONS MRI findings of certain pathologies in a painful knee can coexist and significantly correlate with each other, age and sex of

  14. T2 relaxation time analysis in patients with multiple sclerosis: correlation with magnetization transfer ratio

    International Nuclear Information System (INIS)

    Papanikolaou, Nickolas; Papadaki, Eufrosini; Karampekios, Spyros; Maris, Thomas; Prassopoulos, Panos; Gourtsoyiannis, Nicholas; Spilioti, Martha

    2004-01-01

    The aim of the current study was to perform T2 relaxation time measurements in multiple sclerosis (MS) patients and correlate them with magnetization transfer ratio (MTR) measurements, in order to investigate in more detail the various histopathological changes that occur in lesions and normal-appearing white matter (NAWM). A total number of 291 measurements of MTR and T2 relaxation times were performed in 13 MS patients and 10 age-matched healthy volunteers. Measurements concerned MS plaques (105), NAWM (80), and ''dirty'' white matter (DWM; 30), evenly divided between the MS patients, and normal white matter (NWM; 76) in the healthy volunteers. Biexponential T2 relaxation-time analysis was performed, and also possible linearity between MTR and mean T2 relaxation times was evaluated using linear regression analysis in all subgroups. Biexponential relaxation was more pronounced in ''black-hole'' lesions (16.6%) and homogeneous enhancing plaques (10%), whereas DWM, NAWM, and mildly hypointense lesions presented biexponential behavior with a lower frequency(6.6, 5, and 3.1%, respectively). Non-enhancing isointense lesions and normal white matter did not reveal any biexponentional behavior. Linear regression analysis between monoexponential T2 relaxation time and MTR measurements demonstrated excellent correlation for DWM(r=-0.78, p<0.0001), very good correlation for black-hole lesions(r=-0.71, p=0.002), good correlation for isointense lesions(r=-0.60, p=0.005), moderate correlation for mildly hypointense lesions(r=-0.34, p=0.007), and non-significant correlation for homogeneous enhancing plaques, NAWM, and NWM. Biexponential T2 relaxation-time behavior is seen in only very few lesions (mainly on plaques with high degree of demyelination and axonal loss). A strong correlation between MTR and monoexponential T2 values was found in regions where either inflammation or demyelination predominates; however, when both pathological conditions coexist, this linear

  15. Inferring Ice Thickness from a Glacier Dynamics Model and Multiple Surface Datasets.

    Science.gov (United States)

    Guan, Y.; Haran, M.; Pollard, D.

    2017-12-01

    The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major impact on future climate. For instance, ice sheet melt may contribute significantly to global sea level rise. Understanding the current state of WAIS is therefore of great interest. WAIS is drained by fast-flowing glaciers which are major contributors to ice loss. Hence, understanding the stability and dynamics of glaciers is critical for predicting the future of the ice sheet. Glacier dynamics are driven by the interplay between the topography, temperature and basal conditions beneath the ice. A glacier dynamics model describes the interactions between these processes. We develop a hierarchical Bayesian model that integrates multiple ice sheet surface data sets with a glacier dynamics model. Our approach allows us to (1) infer important parameters describing the glacier dynamics, (2) learn about ice sheet thickness, and (3) account for errors in the observations and the model. Because we have relatively dense and accurate ice thickness data from the Thwaites Glacier in West Antarctica, we use these data to validate the proposed approach. The long-term goal of this work is to have a general model that may be used to study multiple glaciers in the Antarctic.

  16. Norwegian Hydrological Reference Dataset for Climate Change Studies

    Energy Technology Data Exchange (ETDEWEB)

    Magnussen, Inger Helene; Killingland, Magnus; Spilde, Dag

    2012-07-01

    Based on the Norwegian hydrological measurement network, NVE has selected a Hydrological Reference Dataset for studies of hydrological change. The dataset meets international standards with high data quality. It is suitable for monitoring and studying the effects of climate change on the hydrosphere and cryosphere in Norway. The dataset includes streamflow, groundwater, snow, glacier mass balance and length change, lake ice and water temperature in rivers and lakes.(Author)

  17. CT abnormality in multiple sclerosis analysis based on 28 probable cases and correlation with clinical manifestations

    International Nuclear Information System (INIS)

    Kakigi, Ryusuke; Shibasaki, Hiroshi; Tabira, Takeshi; Kuroiwa, Yoshigoro; Numaguchi, Yuji.

    1981-01-01

    In order to investigate the occurrence and nature of CT abnormality and its correlation with clinical manifestations in multiple sclerosis, 34 CT records obtained from 28 consecutive patients with probable multiple sclerosis were reviewed. Forty-six percent of all cases showed abnormal CT. Dilatation of cortical sulci was found in 39%; dilatation of the lateral ventricle in 36%; dilatation of prepontine or cerebello-pontine cistern and the fourth ventricle, suggesting brainstem atrophy, in 18%; dilatation of cerebellar sulci, superior cerebellar cistern and cisterna magna, suggesting cerebellar atrophy, in 11%. Low density area was found in the cerebral hemisphere in 11% of cases. Contrast enhancement, performed on 25 CT records, did not show any change. There was no correlation between CT abnormality and duration of the illness. Although abnormal CT tended to occur more frequently during exacerbations and chronic stable state than during remissions, the difference was not statistically significant. CT abnormalities suggesting brainstem atrophy, cerebellar atrophy or plaques were found exclusively during exacerbations and chronic stable state. The occurrence of CT abnormalities was not significantly different among various clinical forms which were classified based on clinically estimated sites of lesion, except that abnormal CT tended to occur less frequently in cases classified as the optic-spinal form. It is noteworthy that cerebral cortical atrophy and/or dilatation of the lateral ventricle were found in 31% of cases who did not show any clinical sign of cerebral involvement. There was a statistically significant correlation between CT abnormalities and levels of clinical disability. Eighty percent of the bedridden or severely disabled patients showed abnormal CT, in contrast with only 29% of those with moderate, slight or no disability. (author)

  18. CT abnormality in multiple sclerosis analysis based on 28 probable cases and correlation with clinical manifestations

    Energy Technology Data Exchange (ETDEWEB)

    Kakigi, R.; Shibasaki, H.; Tabira, T.; Kuroiwa, Y. (Kyushu Univ., Fukuoka (Japan). Faculty of Medicine); Numaguchi, Y.

    1981-10-01

    In order to investigate the occurrence and nature of CT abnormality and its correlation with clinical manifestations in multiple sclerosis, 34 CT records obtained from 28 consecutive patients with probable multiple sclerosis were reviewed. Forty-six percent of all cases showed abnormal CT. Dilatation of cortical sulci was found in 39%; dilatation of the lateral ventricle in 36%; dilatation of prepontine or cerebello-pontine cistern and the fourth ventricle, suggesting brainstem atrophy, in 18%; dilatation of cerebellar sulci, superior cerebellar cistern and cisterna magna, suggesting cerebellar atrophy, in 11%. Low density area was found in the cerebral hemisphere in 11% of cases. Contrast enhancement, performed on 25 CT records, did not show any change. There was no correlation between CT abnormality and duration of the illness. Although abnormal CT tended to occur more frequently during exacerbations and chronic stable state than during remissions, the difference was not statistically significant. CT abnormalities suggesting brainstem atrophy, cerebellar atrophy or plaques were found exclusively during exacerbations and chronic stable state. The occurrence of CT abnormalities was not significantly different among various clinical forms which were classified based on clinically estimated sites of lesion, except that abnormal CT tended to occur less frequently in cases classified as the optic-spinal form. It is noteworthy that cerebral cortical atrophy and/or dilatation of the lateral ventricle were found in 31% of cases who did not show any clinical sign of cerebral involvement. There was a statistically significant correlation between CT abnormalities and levels of clinical disability. Eighty percent of the bedridden or severely disabled patients showed abnormal CT, in contrast with only 29% of those with moderate, slight or no disability.

  19. The Harvard organic photovoltaic dataset

    Science.gov (United States)

    Lopez, Steven A.; Pyzer-Knapp, Edward O.; Simm, Gregor N.; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R.; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-01-01

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications. PMID:27676312

  20. Measurement of long-range angular correlations and azimuthal anisotropies in high-multiplicity p +Au collisions at √{sNN}=200 GeV

    Science.gov (United States)

    Aidala, C.; Akiba, Y.; Alfred, M.; Andrieux, V.; Aoki, K.; Apadula, N.; Asano, H.; Ayuso, C.; Azmoun, B.; Babintsev, V.; Bandara, N. S.; Barish, K. N.; Bathe, S.; Bazilevsky, A.; Beaumier, M.; Belmont, R.; Berdnikov, A.; Berdnikov, Y.; Blau, D. S.; Boer, M.; Bok, J. S.; Brooks, M. L.; Bryslawskyj, J.; Bumazhnov, V.; Butler, C.; Campbell, S.; Canoa Roman, V.; Cervantes, R.; Chi, C. Y.; Chiu, M.; Choi, I. J.; Choi, J. B.; Citron, Z.; Connors, M.; Cronin, N.; Csanád, M.; Csörgő, T.; Danley, T. W.; Daugherity, M. S.; David, G.; Deblasio, K.; Dehmelt, K.; Denisov, A.; Deshpande, A.; Desmond, E. J.; Dion, A.; Dixit, D.; Do, J. H.; Drees, A.; Drees, K. A.; Dumancic, M.; Durham, J. M.; Durum, A.; Elder, T.; Enokizono, A.; En'yo, H.; Esumi, S.; Fadem, B.; Fan, W.; Feege, N.; Fields, D. E.; Finger, M.; Finger, M.; Fokin, S. L.; Frantz, J. E.; Franz, A.; Frawley, A. D.; Fukuda, Y.; Gal, C.; Gallus, P.; Garg, P.; Ge, H.; Giordano, F.; Goto, Y.; Grau, N.; Greene, S. V.; Grosse Perdekamp, M.; Gunji, T.; Guragain, H.; Hachiya, T.; Haggerty, J. S.; Hahn, K. I.; Hamagaki, H.; Hamilton, H. F.; Han, S. Y.; Hanks, J.; Hasegawa, S.; Haseler, T. O. S.; He, X.; Hemmick, T. K.; Hill, J. C.; Hill, K.; Hollis, R. S.; Homma, K.; Hong, B.; Hoshino, T.; Hotvedt, N.; Huang, J.; Huang, S.; Imai, K.; Imrek, J.; Inaba, M.; Iordanova, A.; Isenhower, D.; Ito, Y.; Ivanishchev, D.; Jacak, B. V.; Jezghani, M.; Ji, Z.; Jiang, X.; Johnson, B. M.; Jorjadze, V.; Jouan, D.; Jumper, D. S.; Kang, J. H.; Kapukchyan, D.; Karthas, S.; Kawall, D.; Kazantsev, A. V.; Khachatryan, V.; Khanzadeev, A.; Kim, C.; Kim, D. J.; Kim, E.-J.; Kim, M. H.; Kim, M.; Kincses, D.; Kistenev, E.; Klatsky, J.; Kline, P.; Koblesky, T.; Kotov, D.; Kudo, S.; Kurita, K.; Kwon, Y.; Lajoie, J. G.; Lallow, E. O.; Lebedev, A.; Lee, S.; Leitch, M. J.; Leung, Y. H.; Lewis, N. A.; Li, X.; Lim, S. H.; Liu, L. D.; Liu, M. X.; Loggins, V.-R.; Loggins, V.-R.; Lovasz, K.; Lynch, D.; Majoros, T.; Makdisi, Y. I.; Makek, M.; Malaev, M.; Manko, V. I.; Mannel, E.; Masuda, H.; McCumber, M.; McGaughey, P. L.; McGlinchey, D.; McKinney, C.; Mendoza, M.; Mignerey, A. C.; Mihalik, D. E.; Milov, A.; Mishra, D. K.; Mitchell, J. T.; Mitsuka, G.; Miyasaka, S.; Mizuno, S.; Montuenga, P.; Moon, T.; Morrison, D. P.; Morrow, S. I. M.; Murakami, T.; Murata, J.; Nagai, K.; Nagashima, K.; Nagashima, T.; Nagle, J. L.; Nagy, M. I.; Nakagawa, I.; Nakagomi, H.; Nakano, K.; Nattrass, C.; Niida, T.; Nouicer, R.; Novák, T.; Novitzky, N.; Novotny, R.; Nyanin, A. S.; O'Brien, E.; Ogilvie, C. A.; Orjuela Koop, J. D.; Osborn, J. D.; Oskarsson, A.; Ottino, G. J.; Ozawa, K.; Pantuev, V.; Papavassiliou, V.; Park, J. S.; Park, S.; Pate, S. F.; Patel, M.; Peng, W.; Perepelitsa, D. V.; Perera, G. D. N.; Peressounko, D. Yu.; Perezlara, C. E.; Perry, J.; Petti, R.; Phipps, M.; Pinkenburg, C.; Pisani, R. P.; Pun, A.; Purschke, M. L.; Read, K. F.; Reynolds, D.; Riabov, V.; Riabov, Y.; Richford, D.; Rinn, T.; Rolnick, S. D.; Rosati, M.; Rowan, Z.; Runchey, J.; Safonov, A. S.; Sakaguchi, T.; Sako, H.; Samsonov, V.; Sarsour, M.; Sato, K.; Sato, S.; Schaefer, B.; Schmoll, B. K.; Sedgwick, K.; Seidl, R.; Sen, A.; Seto, R.; Sexton, A.; Sharma, D.; Shein, I.; Shibata, T.-A.; Shigaki, K.; Shimomura, M.; Shioya, T.; Shukla, P.; Sickles, A.; Silva, C. L.; Silvermyr, D.; Singh, B. K.; Singh, C. P.; Singh, V.; Slunečka, M.; Smith, K. L.; Snowball, M.; Soltz, R. A.; Sondheim, W. E.; Sorensen, S. P.; Sourikova, I. V.; Stankus, P. W.; Stoll, S. P.; Sugitate, T.; Sukhanov, A.; Sumita, T.; Sun, J.; Syed, S.; Sziklai, J.; Takeda, A.; Tanida, K.; Tannenbaum, M. J.; Tarafdar, S.; Tarnai, G.; Tieulent, R.; Timilsina, A.; Todoroki, T.; Tomášek, M.; Towell, C. L.; Towell, R. S.; Tserruya, I.; Ueda, Y.; Ujvari, B.; van Hecke, H. W.; Vazquez-Carson, S.; Velkovska, J.; Virius, M.; Vrba, V.; Vukman, N.; Wang, X. R.; Wang, Z.; Watanabe, Y.; Watanabe, Y. S.; Wong, C. P.; Woody, C. L.; Xu, C.; Xu, Q.; Xue, L.; Yalcin, S.; Yamaguchi, Y. L.; Yamamoto, H.; Yanovich, A.; Yin, P.; Yoo, J. H.; Yoon, I.; Yu, H.; Yushmanov, I. E.; Zajc, W. A.; Zelenski, A.; Zharko, S.; Zou, L.; Phenix Collaboration

    2017-03-01

    We present measurements of long-range angular correlations and the transverse momentum dependence of elliptic flow v2 in high-multiplicity p +Au collisions at √{s NN}=200 GeV. A comparison of these results to previous measurements in high-multiplicity d +Au and 3He+Au collisions demonstrates a relation between v2 and the initial collision eccentricity ɛ2, suggesting that the observed momentum-space azimuthal anisotropies in these small systems have a collective origin and reflect the initial geometry. Good agreement is observed between the measured v2 and hydrodynamic calculations for all systems, and an argument disfavoring theoretical explanations based on initial momentum-space domain correlations is presented. The set of measurements presented here allows us to leverage the distinct intrinsic geometry of each of these systems to distinguish between different theoretical descriptions of the long-range correlations observed in small collision systems.

  1. Synthetic and Empirical Capsicum Annuum Image Dataset

    NARCIS (Netherlands)

    Barth, R.

    2016-01-01

    This dataset consists of per-pixel annotated synthetic (10500) and empirical images (50) of Capsicum annuum, also known as sweet or bell pepper, situated in a commercial greenhouse. Furthermore, the source models to generate the synthetic images are included. The aim of the datasets are to

  2. Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.

    2013-10-01

    Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

  3. Multiplicity and transverse momentum dependence of two- and four-particle correlations in pPb and PbPb collisions

    CERN Document Server

    Chatrchyan, Serguei; Sirunyan, Albert M; Tumasyan, Armen; Adam, Wolfgang; Bergauer, Thomas; Dragicevic, Marko; Erö, Janos; Fabjan, Christian; Friedl, Markus; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Hörmann, Natascha; Hrubec, Josef; Jeitler, Manfred; Kiesenhofer, Wolfgang; Knünz, Valentin; Krammer, Manfred; Krätschmer, Ilse; Liko, Dietrich; Mikulec, Ivan; Rabady, Dinyar; Rahbaran, Babak; Rohringer, Christine; Rohringer, Herbert; Schöfbeck, Robert; Strauss, Josef; Taurok, Anton; Treberer-Treberspurg, Wolfgang; Waltenberger, Wolfgang; Wulz, Claudia-Elisabeth; Mossolov, Vladimir; Shumeiko, Nikolai; Suarez Gonzalez, Juan; Alderweireldt, Sara; Bansal, Monika; Bansal, Sunil; Cornelis, Tom; De Wolf, Eddi A; Janssen, Xavier; Knutsson, Albert; Luyckx, Sten; Mucibello, Luca; Ochesanu, Silvia; Roland, Benoit; Rougny, Romain; Staykova, Zlatka; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Van Spilbeeck, Alex; Blekman, Freya; Blyweert, Stijn; D'Hondt, Jorgen; Kalogeropoulos, Alexis; Keaveney, James; Maes, Michael; Olbrechts, Annik; Tavernier, Stefaan; Van Doninck, Walter; Van Mulders, Petra; Van Onsem, Gerrit Patrick; Villella, Ilaria; Clerbaux, Barbara; De Lentdecker, Gilles; Favart, Laurent; Gay, Arnaud; Hreus, Tomas; Léonard, Alexandre; Marage, Pierre Edouard; Mohammadi, Abdollah; Perniè, Luca; Reis, Thomas; Seva, Tomislav; Thomas, Laurent; Vander Velde, Catherine; Vanlaer, Pascal; Wang, Jian; Adler, Volker; Beernaert, Kelly; Benucci, Leonardo; Cimmino, Anna; Costantini, Silvia; Dildick, Sven; Garcia, Guillaume; Klein, Benjamin; Lellouch, Jérémie; Marinov, Andrey; Mccartin, Joseph; Ocampo Rios, Alberto Andres; Ryckbosch, Dirk; Sigamani, Michael; Strobbe, Nadja; Thyssen, Filip; Tytgat, Michael; Walsh, Sinead; Yazgan, Efe; Zaganidis, Nicolas; Basegmez, Suzan; Beluffi, Camille; Bruno, Giacomo; Castello, Roberto; Caudron, Adrien; Ceard, Ludivine; Delaere, Christophe; Du Pree, Tristan; Favart, Denis; Forthomme, Laurent; Giammanco, Andrea; Hollar, Jonathan; Jez, Pavel; Lemaitre, Vincent; Liao, Junhui; Militaru, Otilia; Nuttens, Claude; Pagano, Davide; Pin, Arnaud; Piotrzkowski, Krzysztof; Popov, Andrey; Selvaggi, Michele; Vizan Garcia, Jesus Manuel; Beliy, Nikita; Caebergs, Thierry; Daubie, Evelyne; Hammad, Gregory Habib; Alves, Gilvan; Correa Martins Junior, Marcos; Martins, Thiago; Pol, Maria Elena; Henrique Gomes E Souza, Moacyr; Aldá Júnior, Walter Luiz; Carvalho, Wagner; Chinellato, Jose; Custódio, Analu; Melo Da Costa, Eliza; De Jesus Damiao, Dilson; De Oliveira Martins, Carley; Fonseca De Souza, Sandro; Malbouisson, Helena; Malek, Magdalena; Matos Figueiredo, Diego; Mundim, Luiz; Nogima, Helio; Prado Da Silva, Wanda Lucia; Santoro, Alberto; Sznajder, Andre; Tonelli Manganote, Edmilson José; Vilela Pereira, Antonio; Bernardes, Cesar Augusto; De Almeida Dias, Flavia; Tomei, Thiago; De Moraes Gregores, Eduardo; Lagana, Caio; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Genchev, Vladimir; Iaydjiev, Plamen; Piperov, Stefan; Rodozov, Mircho; Sultanov, Georgi; Vutova, Mariana; Dimitrov, Anton; Hadjiiska, Roumyana; Kozhuharov, Venelin; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Bian, Jian-Guo; Chen, Guo-Ming; Chen, He-Sheng; Jiang, Chun-Hua; Liang, Dong; Liang, Song; Meng, Xiangwei; Tao, Junquan; Wang, Jian; Wang, Xianyou; Wang, Zheng; Xiao, Hong; Xu, Ming; Asawatangtrakuldee, Chayanit; Ban, Yong; Guo, Yifei; Li, Wenbo; Liu, Shuai; Mao, Yajun; Qian, Si-Jin; Teng, Haiyun; Wang, Dayong; Zhang, Linlin; Zou, Wei; Avila, Carlos; Carrillo Montoya, Camilo Andres; Chaparro Sierra, Luisa Fernanda; Gomez, Juan Pablo; Gomez Moreno, Bernardo; Sanabria, Juan Carlos; Godinovic, Nikola; Lelas, Damir; Plestina, Roko; Polic, Dunja; Puljak, Ivica; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Duric, Senka; Kadija, Kreso; Luetic, Jelena; Mekterovic, Darko; Morovic, Srecko; Tikvica, Lucija; Attikis, Alexandros; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Finger, Miroslav; Finger Jr, Michael; Assran, Yasser; Elgammal, Sherif; Ellithi Kamel, Ali; Mahmoud, Mohammed; Mahrous, Ayman; Radi, Amr; Kadastik, Mario; Müntel, Mait; Murumaa, Marion; Raidal, Martti; Rebane, Liis; Tiko, Andres; Eerola, Paula; Fedi, Giacomo; Voutilainen, Mikko; Härkönen, Jaakko; Karimäki, Veikko; Kinnunen, Ritva; Kortelainen, Matti J; Lampén, Tapio; Lassila-Perini, Kati; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Mäenpää, Teppo; Peltola, Timo; Tuominen, Eija; Tuominiemi, Jorma; Tuovinen, Esa; Wendland, Lauri; Tuuva, Tuure; Besancon, Marc; Couderc, Fabrice; Dejardin, Marc; Denegri, Daniel; Fabbro, Bernard; Faure, Jean-Louis; Ferri, Federico; Ganjour, Serguei; Givernaud, Alain; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Locci, Elizabeth; Malcles, Julie; Millischer, Laurent; Nayak, Aruna; Rander, John; Rosowsky, André; Titov, Maksym; Baffioni, Stephanie; Beaudette, Florian; Benhabib, Lamia; Bluj, Michal; Busson, Philippe; Charlot, Claude; Daci, Nadir; Dahms, Torsten; Dalchenko, Mykhailo; Dobrzynski, Ludwik; Florent, Alice; Granier de Cassagnac, Raphael; Haguenauer, Maurice; Miné, Philippe; Mironov, Camelia; Naranjo, Ivo Nicolas; Nguyen, Matthew; Ochando, Christophe; Paganini, Pascal; Sabes, David; Salerno, Roberto; Sirois, Yves; Veelken, Christian; Zabi, Alexandre; Agram, Jean-Laurent; Andrea, Jeremy; Bloch, Daniel; Bodin, David; Brom, Jean-Marie; Chabert, Eric Christian; Collard, Caroline; Conte, Eric; Drouhin, Frédéric; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Goetzmann, Christophe; Juillot, Pierre; Le Bihan, Anne-Catherine; Van Hove, Pierre; Gadrat, Sébastien; Beauceron, Stephanie; Beaupere, Nicolas; Boudoul, Gaelle; Brochet, Sébastien; Chasserat, Julien; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fay, Jean; Gascon, Susan; Gouzevitch, Maxime; Ille, Bernard; Kurca, Tibor; Lethuillier, Morgan; Mirabito, Laurent; Perries, Stephane; Sgandurra, Louis; Sordini, Viola; Tschudi, Yohann; Vander Donckt, Muriel; Verdier, Patrice; Viret, Sébastien; Tsamalaidze, Zviad; Autermann, Christian; Beranek, Sarah; Calpas, Betty; Edelhoff, Matthias; Feld, Lutz; Heracleous, Natalie; Hindrichs, Otto; Klein, Katja; Ostapchuk, Andrey; Perieanu, Adrian; Raupach, Frank; Sammet, Jan; Schael, Stefan; Sprenger, Daniel; Weber, Hendrik; Wittmer, Bruno; Zhukov, Valery; Ata, Metin; Caudron, Julien; Dietz-Laursonn, Erik; Duchardt, Deborah; Erdmann, Martin; Fischer, Robert; Güth, Andreas; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Klingebiel, Dennis; Kreuzer, Peter; Merschmeyer, Markus; Meyer, Arnd; Olschewski, Mark; Padeken, Klaas; Papacz, Paul; Pieta, Holger; Reithler, Hans; Schmitz, Stefan Antonius; Sonnenschein, Lars; Steggemann, Jan; Teyssier, Daniel; Thüer, Sebastian; Weber, Martin; Cherepanov, Vladimir; Erdogan, Yusuf; Flügge, Günter; Geenen, Heiko; Geisler, Matthias; Haj Ahmad, Wael; Hoehle, Felix; Kargoll, Bastian; Kress, Thomas; Kuessel, Yvonne; Lingemann, Joschka; Nowack, Andreas; Nugent, Ian Michael; Perchalla, Lars; Pooth, Oliver; Stahl, Achim; Aldaya Martin, Maria; Asin, Ivan; Bartosik, Nazar; Behr, Joerg; Behrenhoff, Wolf; Behrens, Ulf; Bergholz, Matthias; Bethani, Agni; Borras, Kerstin; Burgmeier, Armin; Cakir, Altan; Calligaris, Luigi; Campbell, Alan; Choudhury, Somnath; Costanza, Francesco; Diez Pardos, Carmen; Dooling, Samantha; Dorland, Tyler; Eckerlin, Guenter; Eckstein, Doris; Flucke, Gero; Geiser, Achim; Glushkov, Ivan; Gunnellini, Paolo; Habib, Shiraz; Hauk, Johannes; Hellwig, Gregor; Horton, Dean; Jung, Hannes; Kasemann, Matthias; Katsas, Panagiotis; Kleinwort, Claus; Kluge, Hannelies; Krämer, Mira; Krücker, Dirk; Kuznetsova, Ekaterina; Lange, Wolfgang; Leonard, Jessica; Lipka, Katerina; Lohmann, Wolfgang; Lutz, Benjamin; Mankel, Rainer; Marfin, Ihar; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Mnich, Joachim; Mussgiller, Andreas; Naumann-Emme, Sebastian; Novgorodova, Olga; Nowak, Friederike; Olzem, Jan; Perrey, Hanno; Petrukhin, Alexey; Pitzl, Daniel; Placakyte, Ringaile; Raspereza, Alexei; Ribeiro Cipriano, Pedro M; Riedl, Caroline; Ron, Elias; Sahin, Mehmet Özgür; Salfeld-Nebgen, Jakob; Schmidt, Ringo; Schoerner-Sadenius, Thomas; Sen, Niladri; Stein, Matthias; Walsh, Roberval; Wissing, Christoph; Blobel, Volker; Enderle, Holger; Erfle, Joachim; Garutti, Erika; Gebbert, Ulla; Görner, Martin; Gosselink, Martijn; Haller, Johannes; Heine, Kristin; Höing, Rebekka Sophie; Kaussen, Gordon; Kirschenmann, Henning; Klanner, Robert; Kogler, Roman; Lange, Jörn; Marchesini, Ivan; Peiffer, Thomas; Pietsch, Niklas; Rathjens, Denis; Sander, Christian; Schettler, Hannes; Schleper, Peter; Schlieckau, Eike; Schmidt, Alexander; Schröder, Matthias; Schum, Torben; Seidel, Markus; Sibille, Jennifer; Sola, Valentina; Stadie, Hartmut; Steinbrück, Georg; Thomsen, Jan; Troendle, Daniel; Usai, Emanuele; Vanelderen, Lukas; Barth, Christian; Baus, Colin; Berger, Joram; Böser, Christian; Butz, Erik; Chwalek, Thorsten; De Boer, Wim; Descroix, Alexis; Dierlamm, Alexander; Feindt, Michael; Guthoff, Moritz; Hartmann, Frank; Hauth, Thomas; Held, Hauke; Hoffmann, Karl-Heinz; Husemann, Ulrich; Katkov, Igor; Komaragiri, Jyothsna Rani; Kornmayer, Andreas; Lobelle Pardo, Patricia; Martschei, Daniel; Müller, Thomas; Niegel, Martin; Nürnberg, Andreas; Oberst, Oliver; Ott, Jochen; Quast, Gunter; Rabbertz, Klaus; Ratnikov, Fedor; Röcker, Steffen; Schilling, Frank-Peter; Schott, Gregory; Simonis, Hans-Jürgen; Stober, Fred-Markus Helmut; Ulrich, Ralf; Wagner-Kuhr, Jeannine; Wayand, Stefan; Weiler, Thomas; Zeise, Manuel; Anagnostou, Georgios; Daskalakis, Georgios; Geralis, Theodoros; Kesisoglou, Stilianos; Kyriakis, Aristotelis; Loukas, Demetrios; Markou, Athanasios; Markou, Christos; Ntomari, Eleni; Gouskos, Loukas; Mertzimekis, Theodoros; Panagiotou, Apostolos; Saoulidou, Niki; Stiliaris, Efstathios; Aslanoglou, Xenofon; Evangelou, Ioannis; Flouris, Giannis; Foudas, Costas; Kokkas, Panagiotis; Manthos, Nikolaos; Papadopoulos, Ioannis; Paradas, Evangelos; Bencze, Gyorgy; Hajdu, Csaba; Hidas, Pàl; Horvath, Dezso; Radics, Balint; Sikler, Ferenc; Veszpremi, Viktor; Vesztergombi, Gyorgy; Zsigmond, Anna Julia; Beni, Noemi; Czellar, Sandor; Molnar, Jozsef; Palinkas, Jozsef; Szillasi, Zoltan; Karancsi, János; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Beri, Suman Bala; Bhatnagar, Vipin; Dhingra, Nitish; Gupta, Ruchi; Kaur, Manjit; Mehta, Manuk Zubin; Mittal, Monika; Nishu, Nishu; Saini, Lovedeep Kaur; Sharma, Archana; Singh, Jasbir; Kumar, Ashok; Kumar, Arun; Ahuja, Sudha; Bhardwaj, Ashutosh; Choudhary, Brajesh C; Malhotra, Shivali; Naimuddin, Md; Ranjan, Kirti; Saxena, Pooja; Sharma, Varun; Shivpuri, Ram Krishen; Banerjee, Sunanda; Bhattacharya, Satyaki; Chatterjee, Kalyanmoy; Dutta, Suchandra; Gomber, Bhawna; Jain, Sandhya; Jain, Shilpi; Khurana, Raman; Modak, Atanu; Mukherjee, Swagata; Roy, Debarati; Sarkar, Subir; Sharan, Manoj; Abdulsalam, Abdulla; Dutta, Dipanwita; Kailas, Swaminathan; Kumar, Vineet; Mohanty, Ajit Kumar; Pant, Lalit Mohan; Shukla, Prashant; Topkar, Anita; Aziz, Tariq; Chatterjee, Rajdeep Mohan; Ganguly, Sanmay; Ghosh, Saranya; Guchait, Monoranjan; Gurtu, Atul; Kole, Gouranga; Kumar, Sanjeev; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Mohanty, Gagan Bihari; Parida, Bibhuti; Sudhakar, Katta; Wickramage, Nadeesha; Banerjee, Sudeshna; Dugad, Shashikant; Arfaei, Hessamaddin; Bakhshiansohi, Hamed; Etesami, Seyed Mohsen; Fahim, Ali; Hesari, Hoda; Jafari, Abideh; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Paktinat Mehdiabadi, Saeid; Safarzadeh, Batool; Zeinali, Maryam; Grunewald, Martin; Abbrescia, Marcello; Barbone, Lucia; Calabria, Cesare; Chhibra, Simranjit Singh; Colaleo, Anna; Creanza, Donato; De Filippis, Nicola; De Palma, Mauro; Fiore, Luigi; Iaselli, Giuseppe; Maggi, Giorgio; Maggi, Marcello; Marangelli, Bartolomeo; My, Salvatore; Nuzzo, Salvatore; Pacifico, Nicola; Pompili, Alexis; Pugliese, Gabriella; Selvaggi, Giovanna; Silvestris, Lucia; Singh, Gurpreet; Venditti, Rosamaria; Verwilligen, Piet; Zito, Giuseppe; Abbiendi, Giovanni; Benvenuti, Alberto; Bonacorsi, Daniele; Braibant-Giacomelli, Sylvie; Brigliadori, Luca; Campanini, Renato; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Fasanella, Daniele; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Meneghelli, Marco; Montanari, Alessandro; Navarria, Francesco; Odorici, Fabrizio; Perrotta, Andrea; Primavera, Federica; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Tosi, Nicolò; Travaglini, Riccardo; Albergo, Sebastiano; Chiorboli, Massimiliano; Costa, Salvatore; Giordano, Ferdinando; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Frosali, Simone; Gallo, Elisabetta; Gonzi, Sandro; Gori, Valentina; Lenzi, Piergiulio; Meschini, Marco; Paoletti, Simone; Sguazzoni, Giacomo; Tropiano, Antonio; Benussi, Luigi; Bianco, Stefano; Fabbri, Franco; Piccolo, Davide; Fabbricatore, Pasquale; Musenich, Riccardo; Tosi, Silvano; Benaglia, Andrea; De Guio, Federico; Dinardo, Mauro Emanuele; Fiorendi, Sara; Gennai, Simone; Ghezzi, Alessio; Govoni, Pietro; Lucchini, Marco Toliman; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Martelli, Arabella; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pedrini, Daniele; Ragazzi, Stefano; Redaelli, Nicola; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Cavallo, Nicola; De Cosa, Annapaola; Fabozzi, Francesco; Iorio, Alberto Orso Maria; Lista, Luca; Meola, Sabino; Merola, Mario; Paolucci, Pierluigi; Azzi, Patrizia; Bacchetta, Nicola; Bisello, Dario; Branca, Antonio; Carlin, Roberto; Checchia, Paolo; Dorigo, Tommaso; Dosselli, Umberto; Galanti, Mario; Gasparini, Fabrizio; Gasparini, Ugo; Giubilato, Piero; Gonella, Franco; Gozzelino, Andrea; Kanishchev, Konstantin; Lacaprara, Stefano; Lazzizzera, Ignazio; Margoni, Martino; Meneguzzo, Anna Teresa; Montecassiano, Fabio; Pazzini, Jacopo; Pozzobon, Nicola; Ronchese, Paolo; Sgaravatto, Massimo; Simonetto, Franco; Torassa, Ezio; Tosi, Mia; Zotto, Pierluigi; Zucchetta, Alberto; Zumerle, Gianni; Gabusi, Michele; Ratti, Sergio P; Riccardi, Cristina; Vitulo, Paolo; Biasini, Maurizio; Bilei, Gian Mario; Fanò, Livio; Lariccia, Paolo; Mantovani, Giancarlo; Menichelli, Mauro; Nappi, Aniello; Romeo, Francesco; Saha, Anirban; Santocchia, Attilio; Spiezia, Aniello; Androsov, Konstantin; Azzurri, Paolo; Bagliesi, Giuseppe; Bernardini, Jacopo; Boccali, Tommaso; Broccolo, Giuseppe; Castaldi, Rino; D'Agnolo, Raffaele Tito; Dell'Orso, Roberto; Fiori, Francesco; Foà, Lorenzo; Giassi, Alessandro; Grippo, Maria Teresa; Kraan, Aafke; Ligabue, Franco; Lomtadze, Teimuraz; Martini, Luca; Messineo, Alberto; Palla, Fabrizio; Rizzi, Andrea; Savoy-navarro, Aurore; Serban, Alin Titus; Spagnolo, Paolo; Squillacioti, Paola; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Vernieri, Caterina; Barone, Luciano; Cavallari, Francesca; Del Re, Daniele; Diemoz, Marcella; Grassi, Marco; Longo, Egidio; Margaroli, Fabrizio; Meridiani, Paolo; Micheli, Francesco; Nourbakhsh, Shervin; Organtini, Giovanni; Paramatti, Riccardo; Rahatlou, Shahram; Rovelli, Chiara; Soffi, Livia; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Biino, Cristina; Cartiglia, Nicolo; Casasso, Stefano; Costa, Marco; De Remigis, Paolo; Demaria, Natale; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Musich, Marco; Obertino, Maria Margherita; Pastrone, Nadia; Pelliccioni, Mario; Potenza, Alberto; Romero, Alessandra; Ruspa, Marta; Sacchi, Roberto; Solano, Ada; Staiano, Amedeo; Tamponi, Umberto; Belforte, Stefano; Candelise, Vieri; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Gobbo, Benigno; La Licata, Chiara; Marone, Matteo; Montanino, Damiana; Penzo, Aldo; Schizzi, Andrea; Zanetti, Anna; Chang, Sunghyun; Kim, Tae Yeon; Nam, Soon-Kwon; Kim, Dong Hee; Kim, Gui Nyun; Kim, Ji Eun; Kong, Dae Jung; Oh, Young Do; Park, Hyangkyu; Son, Dong-Chul; Kim, Jae Yool; Kim, Zero Jaeho; Song, Sanghyeon; Choi, Suyong; Gyun, Dooyeon; Hong, Byung-Sik; Jo, Mihee; Kim, Hyunchul; Kim, Tae Jeong; Lee, Kyong Sei; Park, Sung Keun; Roh, Youn; Choi, Minkyoo; Kim, Ji Hyun; Park, Chawon; Park, Inkyu; Park, Sangnam; Ryu, Geonmo; Choi, Young-Il; Choi, Young Kyu; Goh, Junghwan; Kim, Min Suk; Kwon, Eunhyang; Lee, Byounghoon; Lee, Jongseok; Lee, Sungeun; Seo, Hyunkwan; Yu, Intae; Grigelionis, Ignas; Juodagalvis, Andrius; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Heredia-de La Cruz, Ivan; Lopez-Fernandez, Ricardo; Martínez-Ortega, Jorge; Sánchez Hernández, Alberto; Villasenor-Cendejas, Luis Manuel; Carrillo Moreno, Salvador; Vazquez Valencia, Fabiola; Salazar Ibarguen, Humberto Antonio; Casimiro Linares, Edgar; Morelos Pineda, Antonio; Reyes-Santos, Marco A; Krofcheck, David; Bell, Alan James; Butler, Philip H; Doesburg, Robert; Reucroft, Steve; Silverwood, Hamish; Ahmad, Muhammad; Asghar, Muhammad Irfan; Butt, Jamila; Hoorani, Hafeez R; Khalid, Shoaib; Khan, Wajid Ali; Khurshid, Taimoor; Qazi, Shamona; Shah, Mehar Ali; Shoaib, Muhammad; Bialkowska, Helena; Boimska, Bożena; Frueboes, Tomasz; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Romanowska-Rybinska, Katarzyna; Szleper, Michal; Wrochna, Grzegorz; Zalewski, Piotr; Brona, Grzegorz; Bunkowski, Karol; Cwiok, Mikolaj; Dominik, Wojciech; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Misiura, Maciej; Wolszczak, Weronika; Almeida, Nuno; Bargassa, Pedrame; Beirão Da Cruz E Silva, Cristóvão; Faccioli, Pietro; Ferreira Parracho, Pedro Guilherme; Gallinaro, Michele; Rodrigues Antunes, Joao; Seixas, Joao; Varela, Joao; Vischia, Pietro; Afanasiev, Serguei; Bunin, Pavel; Golutvin, Igor; Gorbunov, Ilya; Kamenev, Alexey; Karjavin, Vladimir; Konoplyanikov, Viktor; Kozlov, Guennady; Lanev, Alexander; Malakhov, Alexander; Matveev, Viktor; Moisenz, Petr; Palichik, Vladimir; Perelygin, Victor; Shmatov, Sergey; Skatchkov, Nikolai; Smirnov, Vitaly; Zarubin, Anatoli; Evstyukhin, Sergey; Golovtsov, Victor; Ivanov, Yury; Kim, Victor; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Vorobyev, Andrey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Kirsanov, Mikhail; Krasnikov, Nikolai; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Erofeeva, Maria; Gavrilov, Vladimir; Lychkovskaya, Natalia; Popov, Vladimir; Safronov, Grigory; Semenov, Sergey; Spiridonov, Alexander; Stolin, Viatcheslav; Vlasov, Evgueni; Zhokin, Alexander; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Leonidov, Andrey; Mesyats, Gennady; Rusakov, Sergey V; Vinogradov, Alexey; Belyaev, Andrey; Boos, Edouard; Demiyanov, Andrey; Ershov, Alexander; Gribushin, Andrey; Kodolova, Olga; Korotkikh, Vladimir; Lokhtin, Igor; Markina, Anastasia; Obraztsov, Stepan; Petrushanko, Sergey; Savrin, Viktor; Snigirev, Alexander; Vardanyan, Irina; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Kachanov, Vassili; Kalinin, Alexey; Konstantinov, Dmitri; Krychkine, Victor; Petrov, Vladimir; Ryutin, Roman; Sobol, Andrei; Tourtchanovitch, Leonid; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Adzic, Petar; Ekmedzic, Marko; Krpic, Dragomir; Milosevic, Jovan; Aguilar-Benitez, Manuel; Alcaraz Maestre, Juan; Battilana, Carlo; Calvo, Enrique; Cerrada, Marcos; Chamizo Llatas, Maria; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Domínguez Vázquez, Daniel; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Ferrando, Antonio; Flix, Jose; Fouz, Maria Cruz; Garcia-Abia, Pablo; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Merino, Gonzalo; Navarro De Martino, Eduardo; Puerta Pelayo, Jesus; Quintario Olmeda, Adrián; Redondo, Ignacio; Romero, Luciano; Santaolalla, Javier; Senghi Soares, Mara; Willmott, Carlos; Albajar, Carmen; de Trocóniz, Jorge F; Brun, Hugues; Cuevas, Javier; Fernandez Menendez, Javier; Folgueras, Santiago; Gonzalez Caballero, Isidro; Lloret Iglesias, Lara; Piedra Gomez, Jonatan; Brochero Cifuentes, Javier Andres; Cabrillo, Iban Jose; Calderon, Alicia; Chuang, Shan-Huei; Duarte Campderros, Jordi; Fernandez, Marcos; Gomez, Gervasio; Gonzalez Sanchez, Javier; Graziano, Alberto; Jorda, Clara; Lopez Virto, Amparo; Marco, Jesus; Marco, Rafael; Martinez Rivero, Celso; Matorras, Francisco; Munoz Sanchez, Francisca Javiela; Rodrigo, Teresa; Rodríguez-Marrero, Ana Yaiza; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Auffray, Etiennette; Auzinger, Georg; Bachtis, Michail; Baillon, Paul; Ball, Austin; Barney, David; Bendavid, Joshua; Benitez, Jose F; Bernet, Colin; Bianchi, Giovanni; Bloch, Philippe; Bocci, Andrea; Bonato, Alessio; Bondu, Olivier; Botta, Cristina; Breuker, Horst; Camporesi, Tiziano; Cerminara, Gianluca; Christiansen, Tim; Coarasa Perez, Jose Antonio; Colafranceschi, Stefano; D'Enterria, David; Dabrowski, Anne; David Tinoco Mendes, Andre; De Roeck, Albert; De Visscher, Simon; Di Guida, Salvatore; Dobson, Marc; Dupont-Sagorin, Niels; Elliott-Peisert, Anna; Eugster, Jürg; Funk, Wolfgang; Georgiou, Georgios; Giffels, Manuel; Gigi, Dominique; Gill, Karl; Giordano, Domenico; Girone, Maria; Giunta, Marina; Glege, Frank; Gomez-Reino Garrido, Robert; Gowdy, Stephen; Guida, Roberto; Hammer, Josef; Hansen, Magnus; Harris, Philip; Hartl, Christian; Hinzmann, Andreas; Innocente, Vincenzo; Janot, Patrick; Karavakis, Edward; Kousouris, Konstantinos; Krajczar, Krisztian; Lecoq, Paul; Lee, Yen-Jie; Lourenco, Carlos; Magini, Nicolo; Malberti, Martina; Malgeri, Luca; Mannelli, Marcello; Masetti, Lorenzo; Meijers, Frans; Mersi, Stefano; Meschi, Emilio; Moser, Roland; Mulders, Martijn; Musella, Pasquale; Nesvold, Erik; Orsini, Luciano; Palencia Cortezon, Enrique; Perez, Emmanuelle; Perrozzi, Luca; Petrilli, Achille; Pfeiffer, Andreas; Pierini, Maurizio; Pimiä, Martti; Piparo, Danilo; Plagge, Michael; Quertenmont, Loic; Racz, Attila; Reece, William; Rolandi, Gigi; Rovere, Marco; Sakulin, Hannes; Santanastasio, Francesco; Schäfer, Christoph; Schwick, Christoph; Segoni, Ilaria; Sekmen, Sezen; Sharma, Archana; Siegrist, Patrice; Silva, Pedro; Simon, Michal; Sphicas, Paraskevas; Spiga, Daniele; Stoye, Markus; Tsirou, Andromachi; Veres, Gabor Istvan; Vlimant, Jean-Roch; Wöhri, Hermine Katharina; Worm, Steven; Zeuner, Wolfram Dietrich; Bertl, Willi; Deiters, Konrad; Erdmann, Wolfram; Gabathuler, Kurt; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; König, Stefan; Kotlinski, Danek; Langenegger, Urs; Renker, Dieter; Rohe, Tilman; Bachmair, Felix; Bäni, Lukas; Bianchini, Lorenzo; Bortignon, Pierluigi; Buchmann, Marco-Andrea; Casal, Bruno; Chanon, Nicolas; Deisher, Amanda; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dünser, Marc; Eller, Philipp; Freudenreich, Klaus; Grab, Christoph; Hits, Dmitry; Lecomte, Pierre; Lustermann, Werner; Mangano, Boris; Marini, Andrea Carlo; Martinez Ruiz del Arbol, Pablo; Mohr, Niklas; Moortgat, Filip; Nägeli, Christoph; Nef, Pascal; Nessi-Tedaldi, Francesca; Pandolfi, Francesco; Pape, Luc; Pauss, Felicitas; Peruzzi, Marco; Ronga, Frederic Jean; Rossini, Marco; Sala, Leonardo; Sanchez, Ann - Karin; Starodumov, Andrei; Stieger, Benjamin; Takahashi, Maiko; Tauscher, Ludwig; Thea, Alessandro; Theofilatos, Konstantinos; Treille, Daniel; Urscheler, Christina; Wallny, Rainer; Weber, Hannsjoerg Artur; Amsler, Claude; Chiochia, Vincenzo; Favaro, Carlotta; Ivova Rikova, Mirena; Kilminster, Benjamin; Millan Mejias, Barbara; Otiougova, Polina; Robmann, Peter; Snoek, Hella; Taroni, Silvia; Tupputi, Salvatore; Verzetti, Mauro; Cardaci, Marco; Chen, Kuan-Hsin; Ferro, Cristina; Kuo, Chia-Ming; Li, Syue-Wei; Lin, Willis; Lu, Yun-Ju; Volpe, Roberta; Yu, Shin-Shan; Bartalini, Paolo; Chang, Paoti; Chang, You-Hao; Chang, Yu-Wei; Chao, Yuan; Chen, Kai-Feng; Dietz, Charles; Grundler, Ulysses; Hou, George Wei-Shu; Hsiung, Yee; Kao, Kai-Yi; Lei, Yeong-Jyi; Lu, Rong-Shyang; Majumder, Devdatta; Petrakou, Eleni; Shi, Xin; Shiu, Jing-Ge; Tzeng, Yeng-Ming; Wang, Minzu; Asavapibhop, Burin; Suwonjandee, Narumon; Adiguzel, Aytul; Bakirci, Mustafa Numan; Cerci, Salim; Dozen, Candan; Dumanoglu, Isa; Eskut, Eda; Girgis, Semiray; Gokbulut, Gul; Gurpinar, Emine; Hos, Ilknur; Kangal, Evrim Ersin; Kayis Topaksu, Aysel; Onengut, Gulsen; Ozdemir, Kadri; Ozturk, Sertac; Polatoz, Ayse; Sogut, Kenan; Sunar Cerci, Deniz; Tali, Bayram; Topakli, Huseyin; Vergili, Mehmet; Akin, Ilina Vasileva; Aliev, Takhmasib; Bilin, Bugra; Bilmis, Selcuk; Deniz, Muhammed; Gamsizkan, Halil; Guler, Ali Murat; Karapinar, Guler; Ocalan, Kadir; Ozpineci, Altug; Serin, Meltem; Sever, Ramazan; Surat, Ugur Emrah; Yalvac, Metin; Zeyrek, Mehmet; Gülmez, Erhan; Isildak, Bora; Kaya, Mithat; Kaya, Ozlem; Ozkorucuklu, Suat; Sonmez, Nasuf; Bahtiyar, Hüseyin; Barlas, Esra; Cankocak, Kerem; Günaydin, Yusuf Oguzhan; Vardarli, Fuat Ilkehan; Yücel, Mete; Levchuk, Leonid; Sorokin, Pavel; Brooke, James John; Clement, Emyr; Cussans, David; Flacher, Henning; Frazier, Robert; Goldstein, Joel; Grimes, Mark; Heath, Greg P; Heath, Helen F; Kreczko, Lukasz; Metson, Simon; Newbold, Dave M; Nirunpong, Kachanon; Poll, Anthony; Senkin, Sergey; Smith, Vincent J; Williams, Thomas; Basso, Lorenzo; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Jackson, James; Olaiya, Emmanuel; Petyt, David; Radburn-Smith, Benjamin Charles; Shepherd-Themistocleous, Claire; Tomalin, Ian R; Womersley, William John; Bainbridge, Robert; Buchmuller, Oliver; Burton, Darren; Colling, David; Cripps, Nicholas; Cutajar, Michael; Dauncey, Paul; Davies, Gavin; Della Negra, Michel; Ferguson, William; Fulcher, Jonathan; Futyan, David; Gilbert, Andrew; Guneratne Bryer, Arlo; Hall, Geoffrey; Hatherell, Zoe; Hays, Jonathan; Iles, Gregory; Jarvis, Martyn; Karapostoli, Georgia; Kenzie, Matthew; Lane, Rebecca; Lucas, Robyn; Lyons, Louis; Magnan, Anne-Marie; Marrouche, Jad; Mathias, Bryn; Nandi, Robin; Nash, Jordan; Nikitenko, Alexander; Pela, Joao; Pesaresi, Mark; Petridis, Konstantinos; Pioppi, Michele; Raymond, David Mark; Rogerson, Samuel; Rose, Andrew; Seez, Christopher; Sharp, Peter; Sparrow, Alex; Tapper, Alexander; Vazquez Acosta, Monica; Virdee, Tejinder; Wakefield, Stuart; Wardle, Nicholas; Whyntie, Tom; Chadwick, Matthew; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Leggat, Duncan; Leslie, Dawn; Martin, William; Reid, Ivan; Symonds, Philip; Teodorescu, Liliana; Turner, Mark; Dittmann, Jay; Hatakeyama, Kenichi; Kasmi, Azeddine; Liu, Hongxuan; Scarborough, Tara; Charaf, Otman; Cooper, Seth; Henderson, Conor; Rumerio, Paolo; Avetisyan, Aram; Bose, Tulika; Fantasia, Cory; Heister, Arno; Lawson, Philip; Lazic, Dragoslav; Rohlf, James; Sperka, David; St John, Jason; Sulak, Lawrence; Alimena, Juliette; Bhattacharya, Saptaparna; Christopher, Grant; Cutts, David; Demiragli, Zeynep; Ferapontov, Alexey; Garabedian, Alex; Heintz, Ulrich; Kukartsev, Gennadiy; Laird, Edward; Landsberg, Greg; Luk, Michael; Narain, Meenakshi; Segala, Michael; Sinthuprasith, Tutanon; Speer, Thomas; Breedon, Richard; Breto, Guillermo; Calderon De La Barca Sanchez, Manuel; Chauhan, Sushil; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Erbacher, Robin; Gardner, Michael; Houtz, Rachel; Ko, Winston; Kopecky, Alexandra; Lander, Richard; Mall, Orpheus; Miceli, Tia; Nelson, Randy; Pellett, Dave; Ricci-Tam, Francesca; Rutherford, Britney; Searle, Matthew; Smith, John; Squires, Michael; Tripathi, Mani; Wilbur, Scott; Yohay, Rachel; Andreev, Valeri; Cline, David; Cousins, Robert; Erhan, Samim; Everaerts, Pieter; Farrell, Chris; Felcini, Marta; Hauser, Jay; Ignatenko, Mikhail; Jarvis, Chad; Rakness, Gregory; Schlein, Peter; Takasugi, Eric; Traczyk, Piotr; Valuev, Vyacheslav; Weber, Matthias; Babb, John; Clare, Robert; Ellison, John Anthony; Gary, J William; Hanson, Gail; Liu, Hongliang; Long, Owen Rosser; Luthra, Arun; Nguyen, Harold; Paramesvaran, Sudarshan; Sturdy, Jared; Sumowidagdo, Suharyo; Wilken, Rachel; Wimpenny, Stephen; Andrews, Warren; Branson, James G; Cerati, Giuseppe Benedetto; Cittolin, Sergio; Evans, David; Holzner, André; Kelley, Ryan; Lebourgeois, Matthew; Letts, James; Macneill, Ian; Padhi, Sanjay; Palmer, Christopher; Petrucciani, Giovanni; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Simon, Sean; Sudano, Elizabeth; Tadel, Matevz; Tu, Yanjun; Vartak, Adish; Wasserbaech, Steven; Würthwein, Frank; Yagil, Avraham; Yoo, Jaehyeok; Barge, Derek; Bellan, Riccardo; Campagnari, Claudio; D'Alfonso, Mariarosaria; Danielson, Thomas; Flowers, Kristen; Geffert, Paul; George, Christopher; Golf, Frank; Incandela, Joe; Justus, Christopher; Kalavase, Puneeth; Kovalskyi, Dmytro; Krutelyov, Vyacheslav; Lowette, Steven; Magaña Villalba, Ricardo; Mccoll, Nickolas; Pavlunin, Viktor; Ribnik, Jacob; Richman, Jeffrey; Rossin, Roberto; Stuart, David; To, Wing; West, Christopher; Apresyan, Artur; Bornheim, Adolf; Bunn, Julian; Chen, Yi; Di Marco, Emanuele; Duarte, Javier; Kcira, Dorian; Ma, Yousi; Mott, Alexander; Newman, Harvey B; Rogan, Christopher; Spiropulu, Maria; Timciuc, Vladlen; Veverka, Jan; Wilkinson, Richard; Xie, Si; Yang, Yong; Zhu, Ren-Yuan; Azzolini, Virginia; Calamba, Aristotle; Carroll, Ryan; Ferguson, Thomas; Iiyama, Yutaro; Jang, Dong Wook; Liu, Yueh-Feng; Paulini, Manfred; Russ, James; Vogel, Helmut; Vorobiev, Igor; Cumalat, John Perry; Drell, Brian Robert; Ford, William T; Gaz, Alessandro; Luiggi Lopez, Eduardo; Nauenberg, Uriel; Smith, James; Stenson, Kevin; Ulmer, Keith; Wagner, Stephen Robert; Alexander, James; Chatterjee, Avishek; Eggert, Nicholas; Gibbons, Lawrence Kent; Hopkins, Walter; Khukhunaishvili, Aleko; Kreis, Benjamin; Mirman, Nathan; Nicolas Kaufman, Gala; Patterson, Juliet Ritchie; Ryd, Anders; Salvati, Emmanuele; Sun, Werner; Teo, Wee Don; Thom, Julia; Thompson, Joshua; Tucker, Jordan; Weng, Yao; Winstrom, Lucas; Wittich, Peter; Winn, Dave; Abdullin, Salavat; Albrow, Michael; Anderson, Jacob; Apollinari, Giorgio; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Burkett, Kevin; Butler, Joel Nathan; Chetluru, Vasundhara; Cheung, Harry; Chlebana, Frank; Cihangir, Selcuk; Elvira, Victor Daniel; Fisk, Ian; Freeman, Jim; Gao, Yanyan; Gottschalk, Erik; Gray, Lindsey; Green, Dan; Gutsche, Oliver; Hare, Daryl; Harris, Robert M; Hirschauer, James; Hooberman, Benjamin; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Klima, Boaz; Kunori, Shuichi; Kwan, Simon; Linacre, Jacob; Lincoln, Don; Lipton, Ron; Lykken, Joseph; Maeshima, Kaori; Marraffino, John Michael; Martinez Outschoorn, Verena Ingrid; Maruyama, Sho; Mason, David; McBride, Patricia; Mishra, Kalanand; Mrenna, Stephen; Musienko, Yuri; Newman-Holmes, Catherine; O'Dell, Vivian; Prokofyev, Oleg; Ratnikova, Natalia; Sexton-Kennedy, Elizabeth; Sharma, Seema; Spalding, William J; Spiegel, Leonard; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vidal, Richard; Whitmore, Juliana; Wu, Weimin; Yang, Fan; Yun, Jae Chul; Acosta, Darin; Avery, Paul; Bourilkov, Dimitri; Chen, Mingshui; Cheng, Tongguang; Das, Souvik; De Gruttola, Michele; Di Giovanni, Gian Piero; Dobur, Didar; Drozdetskiy, Alexey; Field, Richard D; Fisher, Matthew; Fu, Yu; Furic, Ivan-Kresimir; Hugon, Justin; Kim, Bockjoo; Konigsberg, Jacobo; Korytov, Andrey; Kropivnitskaya, Anna; Kypreos, Theodore; Low, Jia Fu; Matchev, Konstantin; Milenovic, Predrag; Mitselmakher, Guenakh; Muniz, Lana; Remington, Ronald; Rinkevicius, Aurelijus; Skhirtladze, Nikoloz; Snowball, Matthew; Yelton, John; Zakaria, Mohammed; Gaultney, Vanessa; Hewamanage, Samantha; Lebolo, Luis Miguel; Linn, Stephan; Markowitz, Pete; Martinez, German; Rodriguez, Jorge Luis; Adams, Todd; Askew, Andrew; Bochenek, Joseph; Chen, Jie; Diamond, Brendan; Gleyzer, Sergei V; Haas, Jeff; Hagopian, Sharon; Hagopian, Vasken; Johnson, Kurtis F; Prosper, Harrison; Veeraraghavan, Venkatesh; Weinberg, Marc; Baarmand, Marc M; Dorney, Brian; Hohlmann, Marcus; Kalakhety, Himali; Yumiceva, Francisco; Adams, Mark Raymond; Apanasevich, Leonard; Bazterra, Victor Eduardo; Betts, Russell Richard; Bucinskaite, Inga; Callner, Jeremy; Cavanaugh, Richard; Evdokimov, Olga; Gauthier, Lucie; Gerber, Cecilia Elena; Hofman, David Jonathan; Khalatyan, Samvel; Kurt, Pelin; Lacroix, Florent; Moon, Dong Ho; O'Brien, Christine; Silkworth, Christopher; Strom, Derek; Turner, Paul; Varelas, Nikos; Akgun, Ugur; Albayrak, Elif Asli; Bilki, Burak; Clarida, Warren; Dilsiz, Kamuran; Duru, Firdevs; Griffiths, Scott; Merlo, Jean-Pierre; Mermerkaya, Hamit; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Newsom, Charles Ray; Ogul, Hasan; Onel, Yasar; Ozok, Ferhat; Sen, Sercan; Tan, Ping; Tiras, Emrah; Wetzel, James; Yetkin, Taylan; Yi, Kai; Barnett, Bruce Arnold; Blumenfeld, Barry; Bolognesi, Sara; Fehling, David; Giurgiu, Gavril; Gritsan, Andrei; Hu, Guofan; Maksimovic, Petar; Swartz, Morris; Whitbeck, Andrew; Baringer, Philip; Bean, Alice; Benelli, Gabriele; Kenny III, Raymond Patrick; Murray, Michael; Noonan, Daniel; Sanders, Stephen; Stringer, Robert; Wang, Quan; Wood, Jeffrey Scott; Barfuss, Anne-Fleur; Chakaberia, Irakli; Ivanov, Andrew; Khalil, Sadia; Makouski, Mikhail; Maravin, Yurii; Shrestha, Shruti; Svintradze, Irakli; Gronberg, Jeffrey; Lange, David; Rebassoo, Finn; Wright, Douglas; Baden, Drew; Calvert, Brian; Eno, Sarah Catherine; Gomez, Jaime; Hadley, Nicholas John; Kellogg, Richard G; Kolberg, Ted; Lu, Ying; Marionneau, Matthieu; Mignerey, Alice; Pedro, Kevin; Peterman, Alison; Skuja, Andris; Temple, Jeffrey; Tonjes, Marguerite; Tonwar, Suresh C; Apyan, Aram; Bauer, Gerry; Busza, Wit; Cali, Ivan Amos; Chan, Matthew; Di Matteo, Leonardo; Dutta, Valentina; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Kim, Yongsun; Klute, Markus; Lai, Yue Shi; Levin, Andrew; Luckey, Paul David; Ma, Teng; Nahn, Steve; Paus, Christoph; Ralph, Duncan; Roland, Christof; Roland, Gunther; Stephans, George; Stöckli, Fabian; Sumorok, Konstanty; Velicanu, Dragos; Wolf, Roger; Wyslouch, Bolek; Yang, Mingming; Yilmaz, Yetkin; Yoon, Sungho; Zanetti, Marco; Zhukova, Victoria; Dahmes, Bryan; De Benedetti, Abraham; Franzoni, Giovanni; Gude, Alexander; Haupt, Jason; Kao, Shih-Chuan; Klapoetke, Kevin; Kubota, Yuichi; Mans, Jeremy; Pastika, Nathaniel; Rusack, Roger; Sasseville, Michael; Singovsky, Alexander; Tambe, Norbert; Turkewitz, Jared; Cremaldi, Lucien Marcus; Kroeger, Rob; Perera, Lalith; Rahmat, Rahmat; Sanders, David A; Summers, Don; Avdeeva, Ekaterina; Bloom, Kenneth; Bose, Suvadeep; Claes, Daniel R; Dominguez, Aaron; Eads, Michael; Gonzalez Suarez, Rebeca; Keller, Jason; Kravchenko, Ilya; Lazo-Flores, Jose; Malik, Sudhir; Meier, Frank; Snow, Gregory R; Dolen, James; Godshalk, Andrew; Iashvili, Ia; Jain, Supriya; Kharchilava, Avto; Kumar, Ashish; Rappoccio, Salvatore; Wan, Zongru; Alverson, George; Barberis, Emanuela; Baumgartel, Darin; Chasco, Matthew; Haley, Joseph; Massironi, Andrea; Nash, David; Orimoto, Toyoko; Trocino, Daniele; Wood, Darien; Zhang, Jinzhong; Anastassov, Anton; Hahn, Kristan Allan; Kubik, Andrew; Lusito, Letizia; Mucia, Nicholas; Odell, Nathaniel; Pollack, Brian; Pozdnyakov, Andrey; Schmitt, Michael Henry; Stoynev, Stoyan; Sung, Kevin; Velasco, Mayda; Won, Steven; Berry, Douglas; Brinkerhoff, Andrew; Chan, Kwok Ming; Hildreth, Michael; Jessop, Colin; Karmgard, Daniel John; Kolb, Jeff; Lannon, Kevin; Luo, Wuming; Lynch, Sean; Marinelli, Nancy; Morse, David Michael; Pearson, Tessa; Planer, Michael; Ruchti, Randy; Slaunwhite, Jason; Valls, Nil; Wayne, Mitchell; Wolf, Matthias; Antonelli, Louis; Bylsma, Ben; Durkin, Lloyd Stanley; Hill, Christopher; Hughes, Richard; Kotov, Khristian; Ling, Ta-Yung; Puigh, Darren; Rodenburg, Marissa; Smith, Geoffrey; Vuosalo, Carl; Williams, Grayson; Winer, Brian L; Wolfe, Homer; Berry, Edmund; Elmer, Peter; Halyo, Valerie; Hebda, Philip; Hegeman, Jeroen; Hunt, Adam; Jindal, Pratima; Koay, Sue Ann; Lopes Pegna, David; Lujan, Paul; Marlow, Daniel; Medvedeva, Tatiana; Mooney, Michael; Olsen, James; Piroué, Pierre; Quan, Xiaohang; Raval, Amita; Saka, Halil; Stickland, David; Tully, Christopher; Werner, Jeremy Scott; Zenz, Seth Conrad; Zuranski, Andrzej; Brownson, Eric; Lopez, Angel; Mendez, Hector; Ramirez Vargas, Juan Eduardo; Alagoz, Enver; Benedetti, Daniele; Bolla, Gino; Bortoletto, Daniela; De Mattia, Marco; Everett, Adam; Hu, Zhen; Jones, Matthew; Jung, Kurt; Koybasi, Ozhan; Kress, Matthew; Leonardo, Nuno; Maroussov, Vassili; Merkel, Petra; Miller, David Harry; Neumeister, Norbert; Shipsey, Ian; Silvers, David; Svyatkovskiy, Alexey; Vidal Marono, Miguel; Wang, Fuqiang; Xu, Lingshan; Yoo, Hwi Dong; Zablocki, Jakub; Zheng, Yu; Guragain, Samir; Parashar, Neeti; Adair, Antony; Akgun, Bora; Ecklund, Karl Matthew; Geurts, Frank JM; Li, Wei; Padley, Brian Paul; Redjimi, Radia; Roberts, Jay; Zabel, James; Betchart, Burton; Bodek, Arie; Covarelli, Roberto; de Barbaro, Pawel; Demina, Regina; Eshaq, Yossof; Ferbel, Thomas; Garcia-Bellido, Aran; Goldenzweig, Pablo; Han, Jiyeon; Harel, Amnon; Miner, Daniel Carl; Petrillo, Gianluca; Vishnevskiy, Dmitry; Zielinski, Marek; Bhatti, Anwar; Ciesielski, Robert; Demortier, Luc; Goulianos, Konstantin; Lungu, Gheorghe; Malik, Sarah; Mesropian, Christina; Arora, Sanjay; Barker, Anthony; Chou, John Paul; Contreras-Campana, Christian; Contreras-Campana, Emmanuel; Duggan, Daniel; Ferencek, Dinko; Gershtein, Yuri; Gray, Richard; Halkiadakis, Eva; Hidas, Dean; Lath, Amitabh; Panwalkar, Shruti; Park, Michael; Patel, Rishi; Rekovic, Vladimir; Robles, Jorge; Salur, Sevil; Schnetzer, Steve; Seitz, Claudia; Somalwar, Sunil; Stone, Robert; Thomas, Scott; Walker, Matthew; Cerizza, Giordano; Hollingsworth, Matthew; Rose, Keith; Spanier, Stefan; Yang, Zong-Chang; York, Andrew; Eusebi, Ricardo; Flanagan, Will; Gilmore, Jason; Kamon, Teruki; Khotilovich, Vadim; Montalvo, Roy; Osipenkov, Ilya; Pakhotin, Yuriy; Perloff, Alexx; Roe, Jeffrey; Safonov, Alexei; Sakuma, Tai; Suarez, Indara; Tatarinov, Aysen; Toback, David; Akchurin, Nural; Damgov, Jordan; Dragoiu, Cosmin; Dudero, Phillip Russell; Jeong, Chiyoung; Kovitanggoon, Kittikul; Lee, Sung Won; Libeiro, Terence; Volobouev, Igor; Appelt, Eric; Delannoy, Andrés G; Greene, Senta; Gurrola, Alfredo; Johns, Willard; Maguire, Charles; Mao, Yaxian; Melo, Andrew; Sharma, Monika; Sheldon, Paul; Snook, Benjamin; Tuo, Shengquan; Velkovska, Julia; Arenton, Michael Wayne; Boutle, Sarah; Cox, Bradley; Francis, Brian; Goodell, Joseph; Hirosky, Robert; Ledovskoy, Alexander; Lin, Chuanzhe; Neu, Christopher; Wood, John; Gollapinni, Sowjanya; Harr, Robert; Karchin, Paul Edmund; Kottachchi Kankanamge Don, Chamath; Lamichhane, Pramod; Sakharov, Alexandre; Belknap, Donald; Borrello, Laura; Carlsmith, Duncan; Cepeda, Maria; Dasu, Sridhara; Friis, Evan; Grothe, Monika; Hall-Wilton, Richard; Herndon, Matthew; Hervé, Alain; Kaadze, Ketino; Klabbers, Pamela; Klukas, Jeffrey; Lanaro, Armando; Loveless, Richard; Mohapatra, Ajit; Mozer, Matthias Ulrich; Ojalvo, Isabel; Pierro, Giuseppe Antonio; Polese, Giovanni; Ross, Ian; Savin, Alexander; Smith, Wesley H; Swanson, Joshua

    2013-07-23

    Measurements of two- and four-particle angular correlations for charged particles emitted in pPb collisions are presented over a wide range in pseudorapidity and full azimuth. The data, corresponding to an integrated luminosity of approximately 31 inverse nanobarns, were collected during the 2013 LHC pPb run at a nucleon-nucleon center-of-mass energy of 5.02 TeV by the CMS experiment. The results are compared to 2.76 TeV semi-peripheral PbPb collision data, collected during the 2011 PbPb run, covering a similar range of particle multiplicities. The observed correlations are characterized by the near-side (abs(Delta(phi)~0) associated pair yields and the azimuthal anisotropy Fourier harmonics (v[n]). The second-order (v[2]) and third-order (v[3]) anisotropy harmonics are extracted using the two-particle azimuthal correlation technique. A four-particle correlation method is also applied to obtain the value of v[2] and further explore the multi-particle nature of the correlations. Both associated pair yields and...

  4. Correlation of Diffusion and Metabolic Alterations in Different Clinical Forms of Multiple Sclerosis

    Science.gov (United States)

    Hannoun, Salem; Bagory, Matthieu; Durand-Dubief, Francoise; Ibarrola, Danielle; Comte, Jean-Christophe; Confavreux, Christian; Cotton, Francois; Sappey-Marinier, Dominique

    2012-01-01

    Diffusion tensor imaging (DTI) and MR spectroscopic imaging (MRSI) provide greater sensitivity than conventional MRI to detect diffuse alterations in normal appearing white matter (NAWM) of Multiple Sclerosis (MS) patients with different clinical forms. Therefore, the goal of this study is to combine DTI and MRSI measurements to analyze the relation between diffusion and metabolic markers, T2-weighted lesion load (T2-LL) and the patients clinical status. The sensitivity and specificity of both methods were then compared in terms of MS clinical forms differentiation. MR examination was performed on 71 MS patients (27 relapsing remitting (RR), 26 secondary progressive (SP) and 18 primary progressive (PP)) and 24 control subjects. DTI and MRSI measurements were obtained from two identical regions of interest selected in left and right centrum semioval (CSO) WM. DTI metrics and metabolic contents were significantly altered in MS patients with the exception of N-acetyl-aspartate (NAA) and NAA/Choline (Cho) ratio in RR patients. Significant correlations were observed between diffusion and metabolic measures to various degrees in every MS patients group. Most DTI metrics were significantly correlated with the T2-LL while only NAA/Cr ratio was correlated in RR patients. A comparison analysis of MR methods efficiency demonstrated a better sensitivity/specificity of DTI over MRSI. Nevertheless, NAA/Cr ratio could distinguish all MS and SP patients groups from controls, while NAA/Cho ratio differentiated PP patients from controls. This study demonstrated that diffusivity changes related to microstructural alterations were correlated with metabolic changes and provided a better sensitivity to detect early changes, particularly in RR patients who are more subject to inflammatory processes. In contrast, the better specificity of metabolic ratios to detect axonal damage and demyelination may provide a better index for identification of PP patients. PMID:22479330

  5. EEG datasets for motor imagery brain-computer interface.

    Science.gov (United States)

    Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan

    2017-07-01

    Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.

  6. A high-resolution European dataset for hydrologic modeling

    Science.gov (United States)

    Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

    2013-04-01

    There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as

  7. A Multi-Resolution Spatial Model for Large Datasets Based on the Skew-t Distribution

    KAUST Repository

    Tagle, Felipe

    2017-12-06

    Large, non-Gaussian spatial datasets pose a considerable modeling challenge as the dependence structure implied by the model needs to be captured at different scales, while retaining feasible inference. Skew-normal and skew-t distributions have only recently begun to appear in the spatial statistics literature, without much consideration, however, for the ability to capture dependence at multiple resolutions, and simultaneously achieve feasible inference for increasingly large data sets. This article presents the first multi-resolution spatial model inspired by the skew-t distribution, where a large-scale effect follows a multivariate normal distribution and the fine-scale effects follow a multivariate skew-normal distributions. The resulting marginal distribution for each region is skew-t, thereby allowing for greater flexibility in capturing skewness and heavy tails characterizing many environmental datasets. Likelihood-based inference is performed using a Monte Carlo EM algorithm. The model is applied as a stochastic generator of daily wind speeds over Saudi Arabia.

  8. Being an honest broker of hydrology: Uncovering, communicating and addressing model error in a climate change streamflow dataset

    Science.gov (United States)

    Chegwidden, O.; Nijssen, B.; Pytlak, E.

    2017-12-01

    Any model simulation has errors, including errors in meteorological data, process understanding, model structure, and model parameters. These errors may express themselves as bias, timing lags, and differences in sensitivity between the model and the physical world. The evaluation and handling of these errors can greatly affect the legitimacy, validity and usefulness of the resulting scientific product. In this presentation we will discuss a case study of handling and communicating model errors during the development of a hydrologic climate change dataset for the Pacific Northwestern United States. The dataset was the result of a four-year collaboration between the University of Washington, Oregon State University, the Bonneville Power Administration, the United States Army Corps of Engineers and the Bureau of Reclamation. Along the way, the partnership facilitated the discovery of multiple systematic errors in the streamflow dataset. Through an iterative review process, some of those errors could be resolved. For the errors that remained, honest communication of the shortcomings promoted the dataset's legitimacy. Thoroughly explaining errors also improved ways in which the dataset would be used in follow-on impact studies. Finally, we will discuss the development of the "streamflow bias-correction" step often applied to climate change datasets that will be used in impact modeling contexts. We will describe the development of a series of bias-correction techniques through close collaboration among universities and stakeholders. Through that process, both universities and stakeholders learned about the others' expectations and workflows. This mutual learning process allowed for the development of methods that accommodated the stakeholders' specific engineering requirements. The iterative revision process also produced a functional and actionable dataset while preserving its scientific merit. We will describe how encountering earlier techniques' pitfalls allowed us

  9. CSF inflammation and axonal damage are increased and correlate in progressive multiple sclerosis

    DEFF Research Database (Denmark)

    Romme Christensen, Jeppe; Börnsen, Lars; Khademi, Mohsen

    2013-01-01

    BACKGROUND: The mechanism underlying disease progression in progressive multiple sclerosis (MS) is uncertain. Pathological studies found widespread inflammation in progressive MS brains correlating with disease progression and axonal damage. OBJECTIVES: To study cerebrospinal fluid (CSF) biomarkers...... and clarify whether inflammation and axonal damage are associated in progressive MS. METHODS: Using enzyme-linked immunosorbent assay (ELISA), we analysed CSF from 40 secondary progressive (SPMS), 21 primary progressive (PPMS), and 36 relapsing-remitting (RRMS) and 20 non-inflammatory neurological disease...... (NIND) patients. Twenty-two of the SPMS patients participated in an MBP8298 peptide clinical trial and had CSF follow-up after one year. RESULTS: Compared to NIND patients, inflammatory biomarkers osteopontin and matrix metalloproteinase-9 (MMP9) were increased in all MS patients while CXCL13...

  10. Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China

    International Nuclear Information System (INIS)

    Sun, Qiaohong; Miao, Chiyuan; Duan, Qingyun; Kong, Dongxian; Ye, Aizhong; Di, Zhenhua; Gong, Wei

    2014-01-01

    This research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the University of Delaware (UDEL) product, Precipitation Reconstruction over Land (PREC/L), the Asian Precipitation Highly Resolved Observational (APHRO) product, the Institute of Atmospheric Physics (IAP) dataset from the Chinese Academy of Sciences, and the National Meteorological Information Center dataset from the China Meteorological Administration (CN05). The meteorological variables focus on surface air temperature (SAT) or precipitation (PR) in China. All datasets presented general agreement on the whole spatio-temporal scale, but some differences appeared for specific periods and regions. On a temporal scale, EA shows the highest amount of PR, while APHRO shows the lowest. CRU and UDEL show higher SAT than IAP or CN05. On a spatial scale, the most significant differences occur in western China for PR and SAT. For PR, the difference between EA and CRU is the largest. When compared with CN05, CRU shows higher SAT in the central and southern Northwest river drainage basin, UDEL exhibits higher SAT over the Southwest river drainage system, and IAP has lower SAT in the Tibetan Plateau. The differences in annual mean PR and SAT primarily come from summer and winter, respectively. Finally, potential factors impacting agreement among gridded climate datasets are discussed, including raw data sources, quality control (QC) schemes, orographic correction, and interpolation techniques. The implications and challenges of these results for climate research are also briefly addressed. (paper)

  11. Estimating parameters for probabilistic linkage of privacy-preserved datasets.

    Science.gov (United States)

    Brown, Adrian P; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Boyd, James H

    2017-07-10

    Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. The linkage strategy and associated match probabilities are often estimated through investigations into data quality and manual inspection. However, as privacy-preserved datasets comprise encrypted data, such methods are not possible. In this paper, we present a method for estimating the probabilities and threshold values for probabilistic privacy-preserved record linkage using Bloom filters. Our method was tested through a simulation study using synthetic data, followed by an application using real-world administrative data. Synthetic datasets were generated with error rates from zero to 20% error. Our method was used to estimate parameters (probabilities and thresholds) for de-duplication linkages. Linkage quality was determined by F-measure. Each dataset was privacy-preserved using separate Bloom filters for each field. Match probabilities were estimated using the expectation-maximisation (EM) algorithm on the privacy-preserved data. Threshold cut-off values were determined by an extension to the EM algorithm allowing linkage quality to be estimated for each possible threshold. De-duplication linkages of each privacy-preserved dataset were performed using both estimated and calculated probabilities. Linkage quality using the F-measure at the estimated threshold values was also compared to the highest F-measure. Three large administrative datasets were used to demonstrate the applicability of the probability and threshold estimation technique on real-world data. Linkage of the synthetic datasets using the estimated probabilities produced an F-measure that was comparable to the F-measure using calculated probabilities, even with up to 20% error. Linkage of the administrative datasets using estimated probabilities produced an F-measure that was higher

  12. An application of Random Forests to a genome-wide association dataset: Methodological considerations & new findings

    Directory of Open Access Journals (Sweden)

    Hubbard Alan E

    2010-06-01

    Full Text Available Abstract Background As computational power improves, the application of more advanced machine learning techniques to the analysis of large genome-wide association (GWA datasets becomes possible. While most traditional statistical methods can only elucidate main effects of genetic variants on risk for disease, certain machine learning approaches are particularly suited to discover higher order and non-linear effects. One such approach is the Random Forests (RF algorithm. The use of RF for SNP discovery related to human disease has grown in recent years; however, most work has focused on small datasets or simulation studies which are limited. Results Using a multiple sclerosis (MS case-control dataset comprised of 300 K SNP genotypes across the genome, we outline an approach and some considerations for optimally tuning the RF algorithm based on the empirical dataset. Importantly, results show that typical default parameter values are not appropriate for large GWA datasets. Furthermore, gains can be made by sub-sampling the data, pruning based on linkage disequilibrium (LD, and removing strong effects from RF analyses. The new RF results are compared to findings from the original MS GWA study and demonstrate overlap. In addition, four new interesting candidate MS genes are identified, MPHOSPH9, CTNNA3, PHACTR2 and IL7, by RF analysis and warrant further follow-up in independent studies. Conclusions This study presents one of the first illustrations of successfully analyzing GWA data with a machine learning algorithm. It is shown that RF is computationally feasible for GWA data and the results obtained make biologic sense based on previous studies. More importantly, new genes were identified as potentially being associated with MS, suggesting new avenues of investigation for this complex disease.

  13. Do fish growth rates correlate with PCB body burdens?

    Science.gov (United States)

    Andrew L. Rypel; David R.. Bayne

    2010-01-01

    We evaluated whether growth rates of six fish species correlated with PCB concentrations in a moderately-to-heavily polluted freshwater ecosystem. Using a large dataset (n ¼ 984 individuals), and after accounting for growth effects related to fish age, habitat, sex, and lipids, growth correlated significantly, but positively with lipid-corrected PCB concentrations for...

  14. Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Directory of Open Access Journals (Sweden)

    R. Zubieta

    2017-07-01

    Full Text Available In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG (product/final run as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015 when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively. In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %. Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin. GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins, probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  15. A wind loading correlation for an isolated square heliostat, part 1: lift and drag forces

    CSIR Research Space (South Africa)

    Roos, TH

    2012-05-01

    Full Text Available dataset to high accuracy. Correlations for the lift and drag forces are presented. A companion paper presents correlations for the side forces and correlations for moments about the three principal axes, and discusses the behavior of the correlations....

  16. Advanced quantitative methods in correlating sarcopenic muscle degeneration with lower extremity function biometrics and comorbidities.

    Science.gov (United States)

    Edmunds, Kyle; Gíslason, Magnús; Sigurðsson, Sigurður; Guðnason, Vilmundur; Harris, Tamara; Carraro, Ugo; Gargiulo, Paolo

    2018-01-01

    Sarcopenic muscular degeneration has been consistently identified as an independent risk factor for mortality in aging populations. Recent investigations have realized the quantitative potential of computed tomography (CT) image analysis to describe skeletal muscle volume and composition; however, the optimum approach to assessing these data remains debated. Current literature reports average Hounsfield unit (HU) values and/or segmented soft tissue cross-sectional areas to investigate muscle quality. However, standardized methods for CT analyses and their utility as a comorbidity index remain undefined, and no existing studies compare these methods to the assessment of entire radiodensitometric distributions. The primary aim of this study was to present a comparison of nonlinear trimodal regression analysis (NTRA) parameters of entire radiodensitometric muscle distributions against extant CT metrics and their correlation with lower extremity function (LEF) biometrics (normal/fast gait speed, timed up-and-go, and isometric leg strength) and biochemical and nutritional parameters, such as total solubilized cholesterol (SCHOL) and body mass index (BMI). Data were obtained from 3,162 subjects, aged 66-96 years, from the population-based AGES-Reykjavik Study. 1-D k-means clustering was employed to discretize each biometric and comorbidity dataset into twelve subpopulations, in accordance with Sturges' Formula for Class Selection. Dataset linear regressions were performed against eleven NTRA distribution parameters and standard CT analyses (fat/muscle cross-sectional area and average HU value). Parameters from NTRA and CT standards were analogously assembled by age and sex. Analysis of specific NTRA parameters with standard CT results showed linear correlation coefficients greater than 0.85, but multiple regression analysis of correlative NTRA parameters yielded a correlation coefficient of 0.99 (Pbiometrics, SCHOL, and BMI, and particularly highlight the value of the

  17. Tag cloud generation for results of multiple keywords queries

    DEFF Research Database (Denmark)

    Leginus, Martin; Dolog, Peter; Lage, Ricardo Gomes

    2013-01-01

    In this paper we study tag cloud generation for retrieved results of multiple keyword queries. It is motivated by many real world scenarios such as personalization tasks, surveillance systems and information retrieval tasks defined with multiple keywords. We adjust the state-of-the-art tag cloud...... generation techniques for multiple keywords query results. Consequently, we conduct the extensive evaluation on top of three distinct collaborative tagging systems. The graph-based methods perform significantly better for the Movielens and Bibsonomy datasets. Tag cloud generation based on maximal coverage...

  18. Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

    Science.gov (United States)

    Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

    2017-11-01

    Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

  19. MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets.

    Science.gov (United States)

    Lemieux, Sebastien; Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J; Mader, Sylvie; Sauvageau, Guy

    2017-07-27

    Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  20. Homogenised Australian climate datasets used for climate change monitoring

    International Nuclear Information System (INIS)

    Trewin, Blair; Jones, David; Collins; Dean; Jovanovic, Branislava; Braganza, Karl

    2007-01-01

    Full text: The Australian Bureau of Meteorology has developed a number of datasets for use in climate change monitoring. These datasets typically cover 50-200 stations distributed as evenly as possible over the Australian continent, and have been subject to detailed quality control and homogenisation.The time period over which data are available for each element is largely determined by the availability of data in digital form. Whilst nearly all Australian monthly and daily precipitation data have been digitised, a significant quantity of pre-1957 data (for temperature and evaporation) or pre-1987 data (for some other elements) remains to be digitised, and is not currently available for use in the climate change monitoring datasets. In the case of temperature and evaporation, the start date of the datasets is also determined by major changes in instruments or observing practices for which no adjustment is feasible at the present time. The datasets currently available cover: Monthly and daily precipitation (most stations commence 1915 or earlier, with many extending back to the late 19th century, and a few to the mid-19th century); Annual temperature (commences 1910); Daily temperature (commences 1910, with limited station coverage pre-1957); Twice-daily dewpoint/relative humidity (commences 1957); Monthly pan evaporation (commences 1970); Cloud amount (commences 1957) (Jovanovic etal. 2007). As well as the station-based datasets listed above, an additional dataset being developed for use in climate change monitoring (and other applications) covers tropical cyclones in the Australian region. This is described in more detail in Trewin (2007). The datasets already developed are used in analyses of observed climate change, which are available through the Australian Bureau of Meteorology website (http://www.bom.gov.au/silo/products/cli_chg/). They are also used as a basis for routine climate monitoring, and in the datasets used for the development of seasonal

  1. A Comprehensive Dataset of Genes with a Loss-of-Function Mutant Phenotype in Arabidopsis1[W][OA

    Science.gov (United States)

    Lloyd, Johnny; Meinke, David

    2012-01-01

    Despite the widespread use of Arabidopsis (Arabidopsis thaliana) as a model plant, a curated dataset of Arabidopsis genes with mutant phenotypes remains to be established. A preliminary list published nine years ago in Plant Physiology is outdated, and genome-wide phenotype information remains difficult to obtain. We describe here a comprehensive dataset of 2,400 genes with a loss-of-function mutant phenotype in Arabidopsis. Phenotype descriptions were gathered primarily from manual curation of the scientific literature. Genes were placed into prioritized groups (essential, morphological, cellular-biochemical, and conditional) based on the documented phenotypes of putative knockout alleles. Phenotype classes (e.g. vegetative, reproductive, and timing, for the morphological group) and subsets (e.g. flowering time, senescence, circadian rhythms, and miscellaneous, for the timing class) were also established. Gene identities were classified as confirmed (through molecular complementation or multiple alleles) or not confirmed. Relationships between mutant phenotype and protein function, genetic redundancy, protein connectivity, and subcellular protein localization were explored. A complementary dataset of 401 genes that exhibit a mutant phenotype only when disrupted in combination with a putative paralog was also compiled. The importance of these genes in confirming functional redundancy and enhancing the value of single gene datasets is discussed. With further input and curation from the Arabidopsis community, these datasets should help to address a variety of important biological questions, provide a foundation for exploring the relationship between genotype and phenotype in angiosperms, enhance the utility of Arabidopsis as a reference plant, and facilitate comparative studies with model genetic organisms. PMID:22247268

  2. Introduction of a simple-model-based land surface dataset for Europe

    Science.gov (United States)

    Orth, Rene; Seneviratne, Sonia I.

    2015-04-01

    Land surface hydrology can play a crucial role during extreme events such as droughts, floods and even heat waves. We introduce in this study a new hydrological dataset for Europe that consists of soil moisture, runoff and evapotranspiration (ET). It is derived with a simple water balance model (SWBM) forced with precipitation, temperature and net radiation. The SWBM dataset extends over the period 1984-2013 with a daily time step and 0.5° × 0.5° resolution. We employ a novel calibration approach, in which we consider 300 random parameter sets chosen from an observation-based range. Using several independent validation datasets representing soil moisture (or terrestrial water content), ET and streamflow, we identify the best performing parameter set and hence the new dataset. To illustrate its usefulness, the SWBM dataset is compared against several state-of-the-art datasets (ERA-Interim/Land, MERRA-Land, GLDAS-2-Noah, simulations of the Community Land Model Version 4), using all validation datasets as reference. For soil moisture dynamics it outperforms the benchmarks. Therefore the SWBM soil moisture dataset constitutes a reasonable alternative to sparse measurements, little validated model results, or proxy data such as precipitation indices. Also in terms of runoff the SWBM dataset performs well, whereas the evaluation of the SWBM ET dataset is overall satisfactory, but the dynamics are less well captured for this variable. This highlights the limitations of the dataset, as it is based on a simple model that uses uniform parameter values. Hence some processes impacting ET dynamics may not be captured, and quality issues may occur in regions with complex terrain. Even though the SWBM is well calibrated, it cannot replace more sophisticated models; but as their calibration is a complex task the present dataset may serve as a benchmark in future. In addition we investigate the sources of skill of the SWBM dataset and find that the parameter set has a similar

  3. Data Mining for Imbalanced Datasets: An Overview

    Science.gov (United States)

    Chawla, Nitesh V.

    A dataset is imbalanced if the classification categories are not approximately equally represented. Recent years brought increased interest in applying machine learning techniques to difficult "real-world" problems, many of which are characterized by imbalanced data. Additionally the distribution of the testing data may differ from that of the training data, and the true misclassification costs may be unknown at learning time. Predictive accuracy, a popular choice for evaluating performance of a classifier, might not be appropriate when the data is imbalanced and/or the costs of different errors vary markedly. In this Chapter, we discuss some of the sampling techniques used for balancing the datasets, and the performance measures more appropriate for mining imbalanced datasets.

  4. Multiple Response Regression for Gaussian Mixture Models with Known Labels.

    Science.gov (United States)

    Lee, Wonyul; Du, Ying; Sun, Wei; Hayes, D Neil; Liu, Yufeng

    2012-12-01

    Multiple response regression is a useful regression technique to model multiple response variables using the same set of predictor variables. Most existing methods for multiple response regression are designed for modeling homogeneous data. In many applications, however, one may have heterogeneous data where the samples are divided into multiple groups. Our motivating example is a cancer dataset where the samples belong to multiple cancer subtypes. In this paper, we consider modeling the data coming from a mixture of several Gaussian distributions with known group labels. A naive approach is to split the data into several groups according to the labels and model each group separately. Although it is simple, this approach ignores potential common structures across different groups. We propose new penalized methods to model all groups jointly in which the common and unique structures can be identified. The proposed methods estimate the regression coefficient matrix, as well as the conditional inverse covariance matrix of response variables. Asymptotic properties of the proposed methods are explored. Through numerical examples, we demonstrate that both estimation and prediction can be improved by modeling all groups jointly using the proposed methods. An application to a glioblastoma cancer dataset reveals some interesting common and unique gene relationships across different cancer subtypes.

  5. Relating Out-of-Time-Order Correlations to Entanglement via Multiple-Quantum Coherences.

    Science.gov (United States)

    Gärttner, Martin; Hauke, Philipp; Rey, Ana Maria

    2018-01-26

    Out-of-time-order correlations (OTOCs) characterize the scrambling, or delocalization, of quantum information over all the degrees of freedom of a system and thus have been proposed as a proxy for chaos in quantum systems. Recent experimental progress in measuring OTOCs calls for a more thorough understanding of how these quantities characterize complex quantum systems, most importantly in terms of the buildup of entanglement. Although a connection between OTOCs and entanglement entropy has been derived, the latter only quantifies entanglement in pure systems and is hard to access experimentally. In this work, we formally demonstrate that the multiple-quantum coherence spectra, a specific family of OTOCs well known in NMR, can be used as an entanglement witness and as a direct probe of multiparticle entanglement. Our results open a path to experimentally testing the fascinating idea that entanglement is the underlying glue that links thermodynamics, statistical mechanics, and quantum gravity.

  6. Relating Out-of-Time-Order Correlations to Entanglement via Multiple-Quantum Coherences

    Science.gov (United States)

    Gärttner, Martin; Hauke, Philipp; Rey, Ana Maria

    2018-01-01

    Out-of-time-order correlations (OTOCs) characterize the scrambling, or delocalization, of quantum information over all the degrees of freedom of a system and thus have been proposed as a proxy for chaos in quantum systems. Recent experimental progress in measuring OTOCs calls for a more thorough understanding of how these quantities characterize complex quantum systems, most importantly in terms of the buildup of entanglement. Although a connection between OTOCs and entanglement entropy has been derived, the latter only quantifies entanglement in pure systems and is hard to access experimentally. In this work, we formally demonstrate that the multiple-quantum coherence spectra, a specific family of OTOCs well known in NMR, can be used as an entanglement witness and as a direct probe of multiparticle entanglement. Our results open a path to experimentally testing the fascinating idea that entanglement is the underlying glue that links thermodynamics, statistical mechanics, and quantum gravity.

  7. A curated transcriptome dataset collection to investigate the functional programming of human hematopoietic cells in early life.

    Science.gov (United States)

    Rahman, Mahbuba; Boughorbel, Sabri; Presnell, Scott; Quinn, Charlie; Cugno, Chiara; Chaussabel, Damien; Marr, Nico

    2016-01-01

    Compendia of large-scale datasets made available in public repositories provide an opportunity to identify and fill gaps in biomedical knowledge. But first, these data need to be made readily accessible to research investigators for interpretation. Here we make available a collection of transcriptome datasets to investigate the functional programming of human hematopoietic cells in early life. Thirty two datasets were retrieved from the NCBI Gene Expression Omnibus (GEO) and loaded in a custom web application called the Gene Expression Browser (GXB), which was designed for interactive query and visualization of integrated large-scale data. Quality control checks were performed. Multiple sample groupings and gene rank lists were created allowing users to reveal age-related differences in transcriptome profiles, changes in the gene expression of neonatal hematopoietic cells to a variety of immune stimulators and modulators, as well as during cell differentiation. Available demographic, clinical, and cell phenotypic information can be overlaid with the gene expression data and used to sort samples. Web links to customized graphical views can be generated and subsequently inserted in manuscripts to report novel findings. GXB also enables browsing of a single gene across projects, thereby providing new perspectives on age- and developmental stage-specific expression of a given gene across the human hematopoietic system. This dataset collection is available at: http://developmentalimmunology.gxbsidra.org/dm3/geneBrowser/list.

  8. The largest human cognitive performance dataset reveals insights into the effects of lifestyle factors and aging

    Directory of Open Access Journals (Sweden)

    Daniel A Sternberg

    2013-06-01

    Full Text Available Making new breakthroughs in understanding the processes underlying human cognition may depend on the availability of very large datasets that have not historically existed in psychology and neuroscience. Lumosity is a web-based cognitive training platform that has grown to include over 600 million cognitive training task results from over 35 million individuals, comprising the largest existing dataset of human cognitive performance. As part of the Human Cognition Project, Lumosity’s collaborative research program to understand the human mind, Lumos Labs researchers and external research collaborators have begun to explore this dataset in order uncover novel insights about the correlates of cognitive performance. This paper presents two preliminary demonstrations of some of the kinds of questions that can be examined with the dataset. The first example focuses on replicating known findings relating lifestyle factors to baseline cognitive performance in a demographically diverse, healthy population at a much larger scale than has previously been available. The second example examines a question that would likely be very difficult to study in laboratory-based and existing online experimental research approaches: specifically, how learning ability for different types of cognitive tasks changes with age. We hope that these examples will provoke the imagination of researchers who are interested in collaborating to answer fundamental questions about human cognitive performance.

  9. A hybrid organic-inorganic perovskite dataset

    Science.gov (United States)

    Kim, Chiho; Huan, Tran Doan; Krishnan, Sridevi; Ramprasad, Rampi

    2017-05-01

    Hybrid organic-inorganic perovskites (HOIPs) have been attracting a great deal of attention due to their versatility of electronic properties and fabrication methods. We prepare a dataset of 1,346 HOIPs, which features 16 organic cations, 3 group-IV cations and 4 halide anions. Using a combination of an atomic structure search method and density functional theory calculations, the optimized structures, the bandgap, the dielectric constant, and the relative energies of the HOIPs are uniformly prepared and validated by comparing with relevant experimental and/or theoretical data. We make the dataset available at Dryad Digital Repository, NoMaD Repository, and Khazana Repository (http://khazana.uconn.edu/), hoping that it could be useful for future data-mining efforts that can explore possible structure-property relationships and phenomenological models. Progressive extension of the dataset is expected as new organic cations become appropriate within the HOIP framework, and as additional properties are calculated for the new compounds found.

  10. Genomics dataset of unidentified disclosed isolates

    Directory of Open Access Journals (Sweden)

    Bhagwan N. Rekadwad

    2016-09-01

    Full Text Available Analysis of DNA sequences is necessary for higher hierarchical classification of the organisms. It gives clues about the characteristics of organisms and their taxonomic position. This dataset is chosen to find complexities in the unidentified DNA in the disclosed patents. A total of 17 unidentified DNA sequences were thoroughly analyzed. The quick response codes were generated. AT/GC content of the DNA sequences analysis was carried out. The QR is helpful for quick identification of isolates. AT/GC content is helpful for studying their stability at different temperatures. Additionally, a dataset on cleavage code and enzyme code studied under the restriction digestion study, which helpful for performing studies using short DNA sequences was reported. The dataset disclosed here is the new revelatory data for exploration of unique DNA sequences for evaluation, identification, comparison and analysis. Keywords: BioLABs, Blunt ends, Genomics, NEB cutter, Restriction digestion, Short DNA sequences, Sticky ends

  11. Effects of Perfectly Correlated and Anti-Correlated Noise in a Logistic Growth Model

    International Nuclear Information System (INIS)

    Zhang Li; Cao Li

    2011-01-01

    The logistic growth model with correlated additive and multiplicative Gaussian white noise is used to analyze tumor cell population. The effects of perfectly correlated and anti-correlated noise on the stationary properties of tumor cell population are studied. As in both cases the diffusion coefficient has zero point in real number field, some special features of the system are arisen. It is found that in both cases, the increase of the multiplicative noise intensity cause tumor cell extinction. In the perfectly anti-correlated case, the stationary probability distribution as a function of tumor cell population exhibit two extrema. (general)

  12. A comparison of daily evaporation downscaled using WRFDA model and GLEAM dataset over the Iberian Peninsula.

    Science.gov (United States)

    José González-Rojí, Santos; Sáenz, Jon; Ibarra-Berastegi, Gabriel

    2017-04-01

    GLEAM dataset was presented a few years ago and since that moment, it has just been used for validation of evaporation in a few places of the world (Australia and Africa). The Iberian Peninsula is composed of different soil types and it is affected by different weather regimes, with different climate regions. It is this feature which makes it a very interesting zone for the study of the meteorological cycle, including evaporation. For that purpose, a numerical downscaling exercise over the Iberian Peninsula was run nesting the WRF model inside ERA Interim. Two model configurations were tested in two experiments spanning the period 2010-2014 after a one-year spin-up (2009). In the first experiment (N), boundary conditions drive the model. The second experiment (D) is configured the same way as the N case, but 3DVAR data assimilation is run every six hours (00Z, 06Z, 12Z and 18Z) using observations obtained from the PREPBUFR dataset. For both N and D runs and ERA Interim, the evaporation of the model runs was compared to GLEAM v3.0b and v3.0c datasets over the Iberian Peninsula, both at the daily and monthly time scales. GLEAM v3.0a was not used for validation as it uses for forcing radiation and air temperature data from ERA Interim. Results show that the experiment with data assimilation (D) improve the results obtained for N experiment. Moreover, correlations values are comparable to the ones obtained with ERA Interim. However, some negative correlation values are observed at Portuguese and Mediterranean coasts for both WRF runs. All of these problematic points are considered as urban sites by the NOAH land surface model. Because of that, the model is not able to simulate a correct evaporation value. Even with these discrepancies, better results than for ERA Interim are observed for seasonal Biases and daily RMSEs over Iberian Peninsula, obtaining the best values inland. Minimal differences are observed for the two GLEAM datasets selected.

  13. IPCC Socio-Economic Baseline Dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land...

  14. QSAR studies of the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by multiple linear regression (MLR) and support vector machine (SVM).

    Science.gov (United States)

    Qin, Zijian; Wang, Maolin; Yan, Aixia

    2017-07-01

    In this study, quantitative structure-activity relationship (QSAR) models using various descriptor sets and training/test set selection methods were explored to predict the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by using a multiple linear regression (MLR) and a support vector machine (SVM) method. 512 HCV NS3/4A protease inhibitors and their IC 50 values which were determined by the same FRET assay were collected from the reported literature to build a dataset. All the inhibitors were represented with selected nine global and 12 2D property-weighted autocorrelation descriptors calculated from the program CORINA Symphony. The dataset was divided into a training set and a test set by a random and a Kohonen's self-organizing map (SOM) method. The correlation coefficients (r 2 ) of training sets and test sets were 0.75 and 0.72 for the best MLR model, 0.87 and 0.85 for the best SVM model, respectively. In addition, a series of sub-dataset models were also developed. The performances of all the best sub-dataset models were better than those of the whole dataset models. We believe that the combination of the best sub- and whole dataset SVM models can be used as reliable lead designing tools for new NS3/4A protease inhibitors scaffolds in a drug discovery pipeline. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. The LANDFIRE Refresh strategy: updating the national dataset

    Science.gov (United States)

    Nelson, Kurtis J.; Connot, Joel A.; Peterson, Birgit E.; Martin, Charley

    2013-01-01

    The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth, and natural succession. The LANDFIRE Refresh effort was the first attempt to consistently update these products nationwide. It incorporated a combination of specific systematic improvements to the original LANDFIRE National data, remote sensing based disturbance detection methods, field collected disturbance information, vegetation growth and succession modeling, and vegetation transition processes. This resulted in the creation of two complete datasets for all 50 states: LANDFIRE Refresh 2001, which includes the systematic improvements, and LANDFIRE Refresh 2008, which includes the disturbance and succession updates to the vegetation and fuel data. The new datasets are comparable for studying landscape changes in vegetation type and structure over a decadal period, and provide the most recent characterization of fuel conditions across the country. The applicability of the new layers is discussed and the effects of using the new fuel datasets are demonstrated through a fire behavior modeling exercise using the 2011 Wallow Fire in eastern Arizona as an example.

  16. Identification of dust storm source areas in West Asia using multiple environmental datasets.

    Science.gov (United States)

    Cao, Hui; Amiraslani, Farshad; Liu, Jian; Zhou, Na

    2015-01-01

    Sand and Dust storms are common phenomena in arid and semi-arid areas. West Asia Region, especially Tigris-Euphrates alluvial plain, has been recognized as one of the most important dust source areas in the world. In this paper, a method is applied to extract SDS (Sand and Dust Storms) sources in West Asia region using thematic maps, climate and geography, HYSPLIT model and satellite images. Out of 50 dust storms happened during 2000-2013 and collected in form of MODIS images, 27 events were incorporated as demonstrations of the simulated trajectories by HYSPLIT model. Besides, a dataset of the newly released Landsat images was used as base-map for the interpretation of SDS source regions. As a result, six main clusters were recognized as dust source areas. Of which, 3 clusters situated in Tigris-Euphrates plain were identified as severe SDS sources (including 70% dust storms in this research). Another cluster in Sistan plain is also a potential source area. This approach also confirmed six main paths causing dust storms. These paths are driven by the climate system including Siberian and Polar anticyclones, monsoon from Indian Subcontinent and depression from north of Africa. The identification of SDS source areas and paths will improve our understandings on the mechanisms and impacts of dust storms on socio-economy and environment of the region. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Total ozone trends from 1979 to 2016 derived from five merged observational datasets - the emergence into ozone recovery

    Science.gov (United States)

    Weber, Mark; Coldewey-Egbers, Melanie; Fioletov, Vitali E.; Frith, Stacey M.; Wild, Jeannette D.; Burrows, John P.; Long, Craig S.; Loyola, Diego

    2018-02-01

    We report on updated trends using different merged datasets from satellite and ground-based observations for the period from 1979 to 2016. Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. Merged datasets used here include NASA MOD v8.6 and National Oceanic and Atmospheric Administration (NOAA) merge v8.6, both based on data from the series of Solar Backscatter UltraViolet (SBUV) and SBUV-2 satellite instruments (1978-present) as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone (GTO) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (1995-present), mainly comprising satellite data from GOME, the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and GOME-2A. The fifth dataset consists of the monthly mean zonal mean data from ground-based measurements collected at World Ozone and UV Data Center (WOUDC). The addition of four more years of data since the last World Meteorological Organization (WMO) ozone assessment (2013-2016) shows that for most datasets and regions the trends since the stratospheric halogen reached its maximum (˜ 1996 globally and ˜ 2000 in polar regions) are mostly not significantly different from zero. However, for some latitudes, in particular the Southern Hemisphere extratropics and Northern Hemisphere subtropics, several datasets show small positive trends of slightly below +1 % decade-1 that are barely statistically significant at the 2σ uncertainty level. In the tropics, only two datasets show significant trends of +0.5 to +0.8 % decade-1, while the others show near-zero trends. Positive trends since 2000 have been observed over Antarctica in September, but near-zero trends are found in October as well as in March over the Arctic. Uncertainties due to possible drifts between the datasets, from the merging procedure used to combine satellite datasets and related to the low sampling of ground-based data, are not accounted for in the trend

  18. A correlation comparison between Altmetric Attention Scores and citations for six PLOS journals.

    Science.gov (United States)

    Huang, Wenya; Wang, Peiling; Wu, Qiang

    2018-01-01

    This study considered all articles published in six Public Library of Science (PLOS) journals in 2012 and Web of Science citations for these articles as of May 2015. A total of 2,406 articles were analyzed to examine the relationships between Altmetric Attention Scores (AAS) and Web of Science citations. The AAS for an article, provided by Altmetric aggregates activities surrounding research outputs in social media (news outlet mentions, tweets, blogs, Wikipedia, etc.). Spearman correlation testing was done on all articles and articles with AAS. Further analysis compared the stratified datasets based on percentile ranks of AAS: top 50%, top 25%, top 10%, and top 1%. Comparisons across the six journals provided additional insights. The results show significant positive correlations between AAS and citations with varied strength for all articles and articles with AAS (or social media mentions), as well as for normalized AAS in the top 50%, top 25%, top 10%, and top 1% datasets. Four of the six PLOS journals, Genetics, Pathogens, Computational Biology, and Neglected Tropical Diseases, show significant positive correlations across all datasets. However, for the two journals with high impact factors, PLOS Biology and Medicine, the results are unexpected: the Medicine articles showed no significant correlations but the Biology articles tested positive for correlations with the whole dataset and the set with AAS. Both journals published substantially fewer articles than the other four journals. Further research to validate the AAS algorithm, adjust the weighting scheme, and include appropriate social media sources is needed to understand the potential uses and meaning of AAS in different contexts and its relationship to other metrics.

  19. A Method to Correlate mRNA Expression Datasets Obtained from Fresh Frozen and Formalin-Fixed, Paraffin-Embedded Tissue Samples: A Matter of Thresholds.

    Directory of Open Access Journals (Sweden)

    Dana A M Mustafa

    Full Text Available Gene expression profiling of tumors is a successful tool for the discovery of new cancer biomarkers and potential targets for the development of new therapeutic strategies. Reliable profiling is preferably performed on fresh frozen (FF tissues in which the quality of nucleic acids is better preserved than in formalin-fixed paraffin-embedded (FFPE material. However, since snap-freezing of biopsy materials is often not part of daily routine in pathology laboratories, one may have to rely on archival FFPE material. Procedures to retrieve the RNAs from FFPE materials have been developed and therefore, datasets obtained from FFPE and FF materials need to be made compatible to ensure reliable comparisons are possible.To develop an efficient method to compare gene expression profiles obtained from FFPE and FF samples using the same platform.Twenty-six FFPE-FF sample pairs of the same tumors representing various cancer types, and two FFPE-FF sample pairs of breast cancer cell lines, were included. Total RNA was extracted and gene expression profiling was carried out using Illumina's Whole-Genome cDNA-mediated Annealing, Selection, extension and Ligation (WG-DASL V3 arrays, enabling the simultaneous detection of 24,526 mRNA transcripts. A sample exclusion criterion was created based on the expression of 11 stably expressed reference genes. Pearson correlation at the probe level was calculated for paired FFPE-FF, and three cut-off values were chosen. Spearman correlation coefficients between the matched FFPE and FF samples were calculated for three probe lists with varying levels of significance and compared to the correlation based on all measured probes. Unsupervised hierarchical cluster analysis was performed to verify performance of the included probe lists to compare matched FPPE-FF samples.Twenty-seven FFPE-FF pairs passed the sample exclusion criterion. From the profiles of 27 FFPE and FF matched samples, the best correlating probes were identified

  20. Omicseq: a web-based search engine for exploring omics datasets

    Science.gov (United States)

    Sun, Xiaobo; Pittard, William S.; Xu, Tianlei; Chen, Li; Zwick, Michael E.; Jiang, Xiaoqian; Wang, Fusheng

    2017-01-01

    Abstract The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve ‘findability’ of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. PMID:28402462

  1. Correlation of isotopic cisternographic patterns in multiple sclerosis with CSF IgG values

    International Nuclear Information System (INIS)

    Bartolini, S.; Inzitari, D.; Castagnoli, A.; Amaducci, L.

    1982-01-01

    Thirty-eight patients with multiple sclerosis (MS) were examined with isotopic cisternography (IC) in order to study cerebrospinal fluid (CSF) dynamics. Cisternography was also performed in 15 patients with amyotrophic lateral sclerosis and in 14 with senile dementia of the Alzheimer type as controls. IC pattern of ''mixed'' type was found in 18 MS patients and all those with Alzheimer senile dementia examined, while the IC examination did not show abnormality in any of 15 patients with amyotrophic lateral sclerosis. In MS patients, the abnormal IC picture proved to be significantly correlated with the CSF IgG values as calculated by Link's and Tourtelotte's formulas. The abnormal IC in MS may be due to altered CSF reabsorption or increased transependymal flow, or it may be related to the abnormal concentration of IgG

  2. Nanoparticle-organic pollutant interaction dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

  3. Assessing the correlation between grey and white matter damage with motor and cognitive impairment in multiple sclerosis patients.

    Directory of Open Access Journals (Sweden)

    Emilia Sbardella

    Full Text Available BACKGROUND: Multiple sclerosis (MS is characterized by demyelinating and degenerative processes within the central nervous system. Unlike conventional MRI,new advanced imaging techniques improve pathological specificity and better highlight the relationship between anatomical damage and clinical impairment. OBJECTIVE: To investigate the relationship between clinical disability and both grey (GM and white matter (WM regional damage in MS patients. METHODS: Thirty-six relapsing remitting-MS patients and 25 sex- and age-matched controls were enrolled. All patients were clinically evaluated by the Expanded Disability Status Scale and the Multiple Sclerosis Functional Composite (MSFC scale, which includes the 9-hole peg test (9HPT, the timed 25-feet walking test (T25FW and the paced auditory serial addition test (PASAT. All subjects were imaged by a 3.0 T scanner: dual-echo fast spin-echo, 3DT1-weighted and diffusion-tensor imaging (DTI sequences were acquired. Voxel-based morphometry (VBM and tract-based spatial statistics (TBSS analyses were run for regional GM and WM assessment, respectively. T2 lesion volumes were also calculated, by using a semi-automated technique. RESULTS: Brain volumetric assessment of GM and DTI measures revealed significant differences between patients and controls. In patients, different measures of WM damage correlated each-other (p<0.0001, whereas none of them correlated with GM volume. In patients, focal GM atrophy and widespread WM damage significantly correlated with clinical measures. In particular, VBM analysis revealed a significant correlation (p<0.05 between GM volume and 9HPT in cerebellum and between GM volume and PASAT in orbito-frontal cortex. TBSS showed significant correlations between DTI metrics with 9HPT and PASAT scores in many WM bundles (p<0.05, including corpus callosum, internal capsule, posterior thalamic radiations, cerebral peduncles. CONCLUSIONS: Selective GM atrophy and widespread WM tracts

  4. Multiplicity and transverse momentum evolution of charge-dependent correlations in pp, p-Pb, and Pb-Pb collisions at the LHC

    CERN Document Server

    Adam, Jaroslav; Aggarwal, Madan Mohan; Aglieri Rinella, Gianluca; Agnello, Michelangelo; Agrawal, Neelima; Ahammed, Zubayer; Ahn, Sang Un; Aiola, Salvatore; Akindinov, Alexander; Alam, Sk Noor; Aleksandrov, Dmitry; Alessandro, Bruno; Alexandre, Didier; Alfaro Molina, Jose Ruben; Alici, Andrea; Alkin, Anton; Millan Almaraz, Jesus Roberto; Alme, Johan; Alt, Torsten; Altinpinar, Sedat; Altsybeev, Igor; Alves Garcia Prado, Caio; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anielski, Jonas; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshaeuser, Harald; Arcelli, Silvia; Arnaldi, Roberta; Arnold, Oliver Werner; Arsene, Ionut Cristian; Arslandok, Mesut; Audurier, Benjamin; Augustinus, Andre; Averbeck, Ralf Peter; Azmi, Mohd Danish; Badala, Angela; Baek, Yong Wook; Bagnasco, Stefano; Bailhache, Raphaelle Marie; Bala, Renu; Baldisseri, Alberto; Baral, Rama Chandra; Barbano, Anastasia Maria; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Ramillien Barret, Valerie; Bartalini, Paolo; Barth, Klaus; Bartke, Jerzy Gustaw; Bartsch, Esther; Basile, Maurizio; Bastid, Nicole; Basu, Sumit; Bathen, Bastian; Batigne, Guillaume; Batista Camejo, Arianna; Batyunya, Boris; Batzing, Paul Christoph; Bearden, Ian Gardner; Beck, Hans; Bedda, Cristina; Behera, Nirbhay Kumar; Belikov, Iouri; Bellini, Francesca; Bello Martinez, Hector; Bellwied, Rene; Belmont Iii, Ronald John; Belmont Moreno, Ernesto; Belyaev, Vladimir; Bencedi, Gyula; Beole, Stefania; Berceanu, Ionela; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Bertens, Redmer Alexander; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhat, Inayat Rasool; Bhati, Ashok Kumar; Bhattacharjee, Buddhadeb; Bhom, Jihyun; Bianchi, Livio; Bianchi, Nicola; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Biswas, Rathijit; Biswas, Saikat; Bjelogrlic, Sandro; Blair, Justin Thomas; Blau, Dmitry; Blume, Christoph; Bock, Friederike; Bogdanov, Alexey; Boggild, Hans; Boldizsar, Laszlo; Bombara, Marek; Book, Julian Heinz; Borel, Herve; Borissov, Alexander; Borri, Marcello; Bossu, Francesco; Botta, Elena; Boettger, Stefan; Bourjau, Christian; Braun-Munzinger, Peter; Bregant, Marco; Breitner, Timo Gunther; Broker, Theo Alexander; Browning, Tyler Allen; Broz, Michal; Brucken, Erik Jens; Bruna, Elena; Bruno, Giuseppe Eugenio; Budnikov, Dmitry; Buesching, Henner; Bufalino, Stefania; Buncic, Predrag; Busch, Oliver; Buthelezi, Edith Zinhle; Bashir Butt, Jamila; Buxton, Jesse Thomas; Caffarri, Davide; Cai, Xu; Caines, Helen Louise; Calero Diaz, Liliet; Caliva, Alberto; Calvo Villar, Ernesto; Camerini, Paolo; Carena, Francesco; Carena, Wisla; Carnesecchi, Francesca; Castillo Castellanos, Javier Ernesto; Castro, Andrew John; Casula, Ester Anna Rita; Ceballos Sanchez, Cesar; Cepila, Jan; Cerello, Piergiorgio; Cerkala, Jakub; Chang, Beomsu; Chapeland, Sylvain; Chartier, Marielle; Charvet, Jean-Luc Fernand; Chattopadhyay, Subhasis; Chattopadhyay, Sukalyan; Chelnokov, Volodymyr; Cherney, Michael Gerard; Cheshkov, Cvetan Valeriev; Cheynis, Brigitte; Chibante Barroso, Vasco Miguel; Dobrigkeit Chinellato, David; Cho, Soyeon; Chochula, Peter; Choi, Kyungeon; Chojnacki, Marek; Choudhury, Subikash; Christakoglou, Panagiotis; Christensen, Christian Holm; Christiansen, Peter; Chujo, Tatsuya; Chung, Suh-Urk; Cicalo, Corrado; Cifarelli, Luisa; Cindolo, Federico; Cleymans, Jean Willy Andre; Colamaria, Fabio Filippo; Colella, Domenico; Collu, Alberto; Colocci, Manuel; Conesa Balbastre, Gustavo; Conesa Del Valle, Zaida; Connors, Megan Elizabeth; Contreras Nuno, Jesus Guillermo; Cormier, Thomas Michael; Corrales Morales, Yasser; Cortes Maldonado, Ismael; Cortese, Pietro; Cosentino, Mauro Rogerio; Costa, Filippo; Crochet, Philippe; Cruz Albino, Rigoberto; Cuautle Flores, Eleazar; Cunqueiro Mendez, Leticia; Dahms, Torsten; Dainese, Andrea; Danu, Andrea; Das, Debasish; Das, Indranil; Das, Supriya; Dash, Ajay Kumar; Dash, Sadhana; De, Sudipan; De Caro, Annalisa; De Cataldo, Giacinto; De Conti, Camila; De Cuveland, Jan; De Falco, Alessandro; De Gruttola, Daniele; De Marco, Nora; De Pasquale, Salvatore; Deisting, Alexander; Deloff, Andrzej; Denes, Ervin Sandor; Deplano, Caterina; Dhankher, Preeti; Di Bari, Domenico; Di Mauro, Antonio; Di Nezza, Pasquale; Diaz Corchero, Miguel Angel; Dietel, Thomas; Dillenseger, Pascal; Divia, Roberto; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Domenicis Gimenez, Diogenes; Donigus, Benjamin; Dordic, Olja; Drozhzhova, Tatiana; Dubey, Anand Kumar; Dubla, Andrea; Ducroux, Laurent; Dupieux, Pascal; Ehlers Iii, Raymond James; Elia, Domenico; Engel, Heiko; Epple, Eliane; Erazmus, Barbara Ewa; Erdemir, Irem; Erhardt, Filip; Espagnon, Bruno; Estienne, Magali Danielle; Esumi, Shinichi; Eum, Jongsik; Evans, David; Evdokimov, Sergey; Eyyubova, Gyulnara; Fabbietti, Laura; Fabris, Daniela; Faivre, Julien; Fantoni, Alessandra; Fasel, Markus; Feldkamp, Linus; Feliciello, Alessandro; Feofilov, Grigorii; Ferencei, Jozef; Fernandez Tellez, Arturo; Gonzalez Ferreiro, Elena; Ferretti, Alessandro; Festanti, Andrea; Feuillard, Victor Jose Gaston; Figiel, Jan; Araujo Silva Figueredo, Marcel; Filchagin, Sergey; Finogeev, Dmitry; Fionda, Fiorella; Fiore, Enrichetta Maria; Fleck, Martin Gabriel; Floris, Michele; Foertsch, Siegfried Valentin; Foka, Panagiota; Fokin, Sergey; Fragiacomo, Enrico; Francescon, Andrea; Frankenfeld, Ulrich Michael; Fuchs, Ulrich; Furget, Christophe; Furs, Artur; Fusco Girard, Mario; Gaardhoeje, Jens Joergen; Gagliardi, Martino; Gago Medina, Alberto Martin; Gallio, Mauro; Gangadharan, Dhevan Raja; Ganoti, Paraskevi; Gao, Chaosong; Garabatos Cuadrado, Jose; Garcia-Solis, Edmundo Javier; Gargiulo, Corrado; Gasik, Piotr Jan; Gauger, Erin Frances; Germain, Marie; Gheata, Andrei George; Gheata, Mihaela; Ghosh, Premomoy; Ghosh, Sanjay Kumar; Gianotti, Paola; Giubellino, Paolo; Giubilato, Piero; Gladysz-Dziadus, Ewa; Glassel, Peter; Gomez Coral, Diego Mauricio; Gomez Ramirez, Andres; Gonzalez, Victor; Gonzalez Zamora, Pedro; Gorbunov, Sergey; Gorlich, Lidia Maria; Gotovac, Sven; Grabski, Varlen; Grachov, Oleg Anatolievich; Graczykowski, Lukasz Kamil; Graham, Katie Leanne; Grelli, Alessandro; Grigoras, Alina Gabriela; Grigoras, Costin; Grigoryev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grynyov, Borys; Grion, Nevio; Gronefeld, Julius Maximilian; Grosse-Oetringhaus, Jan Fiete; Grossiord, Jean-Yves; Grosso, Raffaele; Guber, Fedor; Guernane, Rachid; Guerzoni, Barbara; Gulbrandsen, Kristjan Herlache; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Haake, Rudiger; Haaland, Oystein Senneset; Hadjidakis, Cynthia Marie; Haiduc, Maria; Hamagaki, Hideki; Hamar, Gergoe; Harris, John William; Harton, Austin Vincent; Hatzifotiadou, Despina; Hayashi, Shinichi; Heckel, Stefan Thomas; Heide, Markus Ansgar; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Hess, Benjamin Andreas; Hetland, Kristin Fanebust; Hillemanns, Hartmut; Hippolyte, Boris; Hosokawa, Ritsuya; Hristov, Peter Zahariev; Huang, Meidana; Humanic, Thomas; Hussain, Nur; Hussain, Tahir; Hutter, Dirk; Hwang, Dae Sung; Ilkaev, Radiy; Inaba, Motoi; Ippolitov, Mikhail; Irfan, Muhammad; Ivanov, Marian; Ivanov, Vladimir; Izucheev, Vladimir; Jacobs, Peter Martin; Jadhav, Manoj Bhanudas; Jadlovska, Slavka; Jadlovsky, Jan; Jahnke, Cristiane; Jakubowska, Monika Joanna; Jang, Haeng Jin; Janik, Malgorzata Anna; Pahula Hewage, Sandun; Jena, Chitrasen; Jena, Satyajit; Jimenez Bustamante, Raul Tonatiuh; Jones, Peter Graham; Jung, Hyungtaik; Jusko, Anton; Kalinak, Peter; Kalweit, Alexander Philipp; Kamin, Jason Adrian; Kang, Ju Hwan; Kaplin, Vladimir; Kar, Somnath; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karayan, Lilit; Karpechev, Evgeny; Kebschull, Udo Wolfgang; Keidel, Ralf; Keijdener, Darius Laurens; Keil, Markus; Khan, Mohammed Mohisin; Khan, Palash; Khan, Shuaib Ahmad; Khanzadeev, Alexei; Kharlov, Yury; Kileng, Bjarte; Kim, Do Won; Kim, Dong Jo; Kim, Daehyeok; Kim, Hyeonjoong; Kim, Jinsook; Kim, Mimae; Kim, Minwoo; Kim, Se Yong; Kim, Taesoo; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Kiss, Gabor; Klay, Jennifer Lynn; Klein, Carsten; Klein, Jochen; Klein-Boesing, Christian; Klewin, Sebastian; Kluge, Alexander; Knichel, Michael Linus; Knospe, Anders Garritt; Kobayashi, Taiyo; Kobdaj, Chinorat; Kofarago, Monika; Kollegger, Thorsten; Kolozhvari, Anatoly; Kondratev, Valerii; Kondratyeva, Natalia; Kondratyuk, Evgeny; Konevskikh, Artem; Kopcik, Michal; Kour, Mandeep; Kouzinopoulos, Charalampos; Kovalenko, Oleksandr; Kovalenko, Vladimir; Kowalski, Marek; Koyithatta Meethaleveedu, Greeshma; Kralik, Ivan; Kravcakova, Adela; Kretz, Matthias; Krivda, Marian; Krizek, Filip; Kryshen, Evgeny; Krzewicki, Mikolaj; Kubera, Andrew Michael; Kucera, Vit; Kuhn, Christian Claude; Kuijer, Paulus Gerardus; Kumar, Ajay; Kumar, Jitendra; Lokesh, Kumar; Kumar, Shyam; Kurashvili, Podist; Kurepin, Alexander; Kurepin, Alexey; Kuryakin, Alexey; Kweon, Min Jung; Kwon, Youngil; La Pointe, Sarah Louise; La Rocca, Paola; Ladron De Guevara, Pedro; Lagana Fernandes, Caio; Lakomov, Igor; Langoy, Rune; Lara Martinez, Camilo Ernesto; Lardeux, Antoine Xavier; Lattuca, Alessandra; Laudi, Elisa; Lea, Ramona; Leardini, Lucia; Lee, Graham Richard; Lee, Seongjoo; Lehas, Fatiha; Lemmon, Roy Crawford; Lenti, Vito; Leogrande, Emilia; Leon Monzon, Ildefonso; Leon Vargas, Hermes; Leoncino, Marco; Levai, Peter; Li, Shuang; Li, Xiaomei; Lien, Jorgen Andre; Lietava, Roman; Lindal, Svein; Lindenstruth, Volker; Lippmann, Christian; Lisa, Michael Annan; Ljunggren, Hans Martin; Lodato, Davide Francesco; Lonne, Per-Ivar; Loginov, Vitaly; Loizides, Constantinos; Lopez, Xavier Bernard; Lopez Torres, Ernesto; Lowe, Andrew John; Luettig, Philipp Johannes; Lunardon, Marcello; Luparello, Grazia; Maevskaya, Alla; Mager, Magnus; Mahajan, Sanjay; Mahmood, Sohail Musa; Maire, Antonin; Majka, Richard Daniel; Malaev, Mikhail; Maldonado Cervantes, Ivonne Alicia; Malinina, Liudmila; Mal'Kevich, Dmitry; Malzacher, Peter; Mamonov, Alexander; Manko, Vladislav; Manso, Franck; Manzari, Vito; Marchisone, Massimiliano; Mares, Jiri; Margagliotti, Giacomo Vito; Margotti, Anselmo; Margutti, Jacopo; Marin, Ana Maria; Markert, Christina; Marquard, Marco; Martin, Nicole Alice; Martin Blanco, Javier; Martinengo, Paolo; Martinez Hernandez, Mario Ivan; Martinez-Garcia, Gines; Martinez Pedreira, Miguel; Mas, Alexis Jean-Michel; Masciocchi, Silvia; Masera, Massimo; Masoni, Alberto; Massacrier, Laure Marie; Mastroserio, Annalisa; Matyja, Adam Tomasz; Mayer, Christoph; Mazer, Joel Anthony; Mazzoni, Alessandra Maria; Mcdonald, Daniel; Meddi, Franco; Melikyan, Yuri; Menchaca-Rocha, Arturo Alejandro; Meninno, Elisa; Mercado-Perez, Jorge; Meres, Michal; Miake, Yasuo; Mieskolainen, Matti Mikael; Mikhaylov, Konstantin; Milano, Leonardo; Milosevic, Jovan; Minervini, Lazzaro Manlio; Mischke, Andre; Mishra, Aditya Nath; Miskowiec, Dariusz Czeslaw; Mitra, Jubin; Mitu, Ciprian Mihai; Mohammadi, Naghmeh; Mohanty, Bedangadas; Molnar, Levente; Montano Zetina, Luis Manuel; Montes Prado, Esther; Moreira De Godoy, Denise Aparecida; Perez Moreno, Luis Alberto; Moretto, Sandra; Morreale, Astrid; Morsch, Andreas; Muccifora, Valeria; Mudnic, Eugen; Muhlheim, Daniel Michael; Muhuri, Sanjib; Mukherjee, Maitreyee; Mulligan, James Declan; Gameiro Munhoz, Marcelo; Munzer, Robert Helmut; Murray, Sean; Musa, Luciano; Musinsky, Jan; Naik, Bharati; Nair, Rahul; Nandi, Basanta Kumar; Nania, Rosario; Nappi, Eugenio; Naru, Muhammad Umair; Ferreira Natal Da Luz, Pedro Hugo; Nattrass, Christine; Nayak, Kishora; Nayak, Tapan Kumar; Nazarenko, Sergey; Nedosekin, Alexander; Nellen, Lukas; Ng, Fabian; Nicassio, Maria; Niculescu, Mihai; Niedziela, Jeremi; Nielsen, Borge Svane; Nikolaev, Sergey; Nikulin, Sergey; Nikulin, Vladimir; Noferini, Francesco; Nomokonov, Petr; Nooren, Gerardus; Cabanillas Noris, Juan Carlos; Norman, Jaime; Nyanin, Alexander; Nystrand, Joakim Ingemar; Oeschler, Helmut Oskar; Oh, Saehanseul; Oh, Sun Kun; Ohlson, Alice Elisabeth; Okatan, Ali; Okubo, Tsubasa; Olah, Laszlo; Oleniacz, Janusz; Oliveira Da Silva, Antonio Carlos; Oliver, Michael Henry; Onderwaater, Jacobus; Oppedisano, Chiara; Orava, Risto; Ortiz Velasquez, Antonio; Oskarsson, Anders Nils Erik; Otwinowski, Jacek Tomasz; Oyama, Ken; Ozdemir, Mahmut; Pachmayer, Yvonne Chiara; Pagano, Paola; Paic, Guy; Pal, Susanta Kumar; Pan, Jinjin; Pandey, Ashutosh Kumar; Papcun, Peter; Papikyan, Vardanush; Pappalardo, Giuseppe; Pareek, Pooja; Park, Woojin; Parmar, Sonia; Passfeld, Annika; Paticchio, Vincenzo; Patra, Rajendra Nath; Paul, Biswarup; Peitzmann, Thomas; Pereira Da Costa, Hugo Denis Antonio; Pereira De Oliveira Filho, Elienos; Peresunko, Dmitry Yurevich; Perez Lara, Carlos Eugenio; Perez Lezama, Edgar; Peskov, Vladimir; Pestov, Yury; Petracek, Vojtech; Petrov, Viacheslav; Petrovici, Mihai; Petta, Catia; Piano, Stefano; Pikna, Miroslav; Pillot, Philippe; Pinazza, Ombretta; Pinsky, Lawrence; Piyarathna, Danthasinghe; Ploskon, Mateusz Andrzej; Planinic, Mirko; Pluta, Jan Marian; Pochybova, Sona; Podesta Lerma, Pedro Luis Manuel; Poghosyan, Martin; Polishchuk, Boris; Poljak, Nikola; Poonsawat, Wanchaloem; Pop, Amalia; Porteboeuf, Sarah Julie; Porter, R Jefferson; Pospisil, Jan; Prasad, Sidharth Kumar; Preghenella, Roberto; Prino, Francesco; Pruneau, Claude Andre; Pshenichnov, Igor; Puccio, Maximiliano; Puddu, Giovanna; Pujahari, Prabhat Ranjan; Punin, Valery; Putschke, Jorn Henning; Qvigstad, Henrik; Rachevski, Alexandre; Raha, Sibaji; Rajput, Sonia; Rak, Jan; Rakotozafindrabe, Andry Malala; Ramello, Luciano; Rami, Fouad; Raniwala, Rashmi; Raniwala, Sudhir; Rasanen, Sami Sakari; Rascanu, Bogdan Theodor; Rathee, Deepika; Read, Kenneth Francis; Redlich, Krzysztof; Reed, Rosi Jan; Rehman, Attiq Ur; Reichelt, Patrick Simon; Reidt, Felix; Ren, Xiaowen; Renfordt, Rainer Arno Ernst; Reolon, Anna Rita; Reshetin, Andrey; Revol, Jean-Pierre; Reygers, Klaus Johannes; Riabov, Viktor; Ricci, Renato Angelo; Richert, Tuva Ora Herenui; Richter, Matthias Rudolph; Riedler, Petra; Riegler, Werner; Riggi, Francesco; Ristea, Catalin-Lucian; Rocco, Elena; Rodriguez Cahuantzi, Mario; Rodriguez Manso, Alis; Roeed, Ketil; Rogochaya, Elena; Rohr, David Michael; Roehrich, Dieter; Romita, Rosa; Ronchetti, Federico; Ronflette, Lucile; Rosnet, Philippe; Rossi, Andrea; Roukoutakis, Filimon; Roy, Ankhi; Roy, Christelle Sophie; Roy, Pradip Kumar; Rubio Montero, Antonio Juan; Rui, Rinaldo; Russo, Riccardo; Ryabinkin, Evgeny; Ryabov, Yury; Rybicki, Andrzej; Sadovskiy, Sergey; Safarik, Karel; Sahlmuller, Baldo; Sahoo, Pragati; Sahoo, Raghunath; Sahoo, Sarita; Sahu, Pradip Kumar; Saini, Jogender; Sakai, Shingo; Saleh, Mohammad Ahmad; Salzwedel, Jai Samuel Nielsen; Sambyal, Sanjeev Singh; Samsonov, Vladimir; Sandor, Ladislav; Sandoval, Andres; Sano, Masato; Sarkar, Debojit; Scapparone, Eugenio; Scarlassara, Fernando; Schiaua, Claudiu Cornel; Schicker, Rainer Martin; Schmidt, Christian Joachim; Schmidt, Hans Rudolf; Schuchmann, Simone; Schukraft, Jurgen; Schulc, Martin; Schuster, Tim Robin; Schutz, Yves Roland; Schwarz, Kilian Eberhard; Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Rebecca Michelle; Sefcik, Michal; Seger, Janet Elizabeth; Sekiguchi, Yuko; Sekihata, Daiki; Selyuzhenkov, Ilya; Senosi, Kgotlaesele; Senyukov, Serhiy; Serradilla Rodriguez, Eulogio; Sevcenco, Adrian; Shabanov, Arseniy; Shabetai, Alexandre; Shadura, Oksana; Shahoyan, Ruben; Shangaraev, Artem; Sharma, Ankita; Sharma, Mona; Sharma, Monika; Sharma, Natasha; Shigaki, Kenta; Shtejer Diaz, Katherin; Sibiryak, Yury; Siddhanta, Sabyasachi; Sielewicz, Krzysztof Marek; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Silvestre, Catherine Micaela; Simatovic, Goran; Simonetti, Giuseppe; Singaraju, Rama Narayana; Singh, Ranbir; Singha, Subhash; Singhal, Vikas; Sinha, Bikash; Sarkar - Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Slupecki, Maciej; Smirnov, Nikolai; Snellings, Raimond; Snellman, Tomas Wilhelm; Soegaard, Carsten; Song, Jihye; Song, Myunggeun; Song, Zixuan; Soramel, Francesca; Sorensen, Soren Pontoppidan; Sozzi, Federica; Spacek, Michal; Spiriti, Eleuterio; Sputowska, Iwona Anna; Spyropoulou-Stassinaki, Martha; Stachel, Johanna; Stan, Ionel; Stefanek, Grzegorz; Stenlund, Evert Anders; Steyn, Gideon Francois; Stiller, Johannes Hendrik; Stocco, Diego; Strmen, Peter; Alarcon Do Passo Suaide, Alexandre; Sugitate, Toru; Suire, Christophe Pierre; Suleymanov, Mais Kazim Oglu; Suljic, Miljenko; Sultanov, Rishat; Sumbera, Michal; Szabo, Alexander; Szanto De Toledo, Alejandro; Szarka, Imrich; Szczepankiewicz, Adam; Szymanski, Maciej Pawel; Tabassam, Uzma; Takahashi, Jun; Tambave, Ganesh Jagannath; Tanaka, Naoto; Tangaro, Marco-Antonio; Tarhini, Mohamad; Tariq, Mohammad; Tarzila, Madalina-Gabriela; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terasaki, Kohei; Terrevoli, Cristina; Teyssier, Boris; Thaeder, Jochen Mathias; Thomas, Deepa; Tieulent, Raphael Noel; Timmins, Anthony Robert; Toia, Alberica; Trogolo, Stefano; Trombetta, Giuseppe; Trubnikov, Victor; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ullaland, Kjetil; Uras, Antonio; Usai, Gianluca; Utrobicic, Antonija; Vajzer, Michal; Vala, Martin; Valencia Palomo, Lizardo; Vallero, Sara; Van Der Maarel, Jasper; Van Hoorne, Jacobus Willem; Van Leeuwen, Marco; Vanat, Tomas; Vande Vyvre, Pierre; Varga, Dezso; Diozcora Vargas Trevino, Aurora; Vargyas, Marton; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vauthier, Astrid; Vechernin, Vladimir; Veen, Annelies Marianne; Veldhoen, Misha; Velure, Arild; Venaruzzo, Massimo; Vercellin, Ermanno; Vergara Limon, Sergio; Vernet, Renaud; Verweij, Marta; Vickovic, Linda; Viesti, Giuseppe; Viinikainen, Jussi Samuli; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Villatoro Tello, Abraham; Vinogradov, Alexander; Vinogradov, Leonid; Vinogradov, Yury; Virgili, Tiziano; Vislavicius, Vytautas; Viyogi, Yogendra; Vodopyanov, Alexander; Volkl, Martin Andreas; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; Von Haller, Barthelemy; Vorobyev, Ivan; Vranic, Danilo; Vrlakova, Janka; Vulpescu, Bogdan; Vyushin, Alexey; Wagner, Boris; Wagner, Jan; Wang, Hongkai; Wang, Mengliang; Watanabe, Daisuke; Watanabe, Yosuke; Weber, Michael; Weber, Steffen Georg; Weiser, Dennis Franz; Wessels, Johannes Peter; Westerhoff, Uwe; Whitehead, Andile Mothegi; Wiechula, Jens; Wikne, Jon; Wilde, Martin Rudolf; Wilk, Grzegorz Andrzej; Wilkinson, Jeremy John; Williams, Crispin; Windelband, Bernd Stefan; Winn, Michael Andreas; Yaldo, Chris G; Yang, Hongyan; Yang, Ping; Yano, Satoshi; Yasar, Cigdem; Yin, Zhongbao; Yokoyama, Hiroki; Yoo, In-Kwon; Yoon, Jin Hee; Yurchenko, Volodymyr; Yushmanov, Igor; Zaborowska, Anna; Zaccolo, Valentina; Zaman, Ali; Zampolli, Chiara; Correia Zanoli, Henrique Jose; Zaporozhets, Sergey; Zardoshti, Nima; Zarochentsev, Andrey; Zavada, Petr; Zavyalov, Nikolay; Zbroszczyk, Hanna Paulina; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhang, Yonghong; Chunhui, Zhang; Zhang, Zuman; Zhao, Chengxin; Zhigareva, Natalia; Zhou, Daicui; Zhou, You; Zhou, Zhuo; Zhu, Hongsheng; Zhu, Jianhui; Zichichi, Antonino; Zimmermann, Alice; Zimmermann, Markus Bernhard; Zinovjev, Gennady; Zyzak, Maksym

    2016-02-19

    We report on two-particle charge-dependent correlations in pp, p-Pb, and Pb-Pb collisions as a function of the pseudorapidity and azimuthal angle difference, $\\mathrm{\\Delta}\\eta$ and $\\mathrm{\\Delta}\\varphi$ respectively. These correlations are studied using the balance function that probes the charge creation time and the development of collectivity in the produced system. The dependence of the balance function on the event multiplicity as well as on the trigger and associated particle transverse momentum ($p_{\\mathrm{T}}$) in pp, p-Pb, and Pb-Pb collisions at $\\sqrt{s_{\\mathrm{NN}}} = 7$, 5.02, and 2.76 TeV, respectively, are presented. In the low transverse momentum region, for $0.2 < p_{\\mathrm{T}} < 2.0$ GeV/$c$, the balance function becomes narrower in both $\\mathrm{\\Delta}\\eta$ and $\\mathrm{\\Delta}\\varphi$ directions in all three systems for events with higher multiplicity. The experimental findings favor models that either incorporate some collective behavior (e.g. AMPT) or different mechanisms...

  5. Data-driven analysis of collections of big datasets by the Bi-CoPaM method yields field-specific novel insights

    DEFF Research Database (Denmark)

    Abu-Jamous, Basel; Liu, Chao; Roberts, David, J.

    2017-01-01

    not commonly considered. To bridge this gap between the fast pace of data generation and the slower pace of data analysis, and to exploit the massive amounts of existing data, we suggest employing data-driven explorations to analyse collections of related big datasets. This approach aims at extracting field......Massive amounts of data have recently been, and are increasingly being, generated from various fields, such as bioinformatics, neuroscience and social networks. Many of these big datasets were generated to answer specific research questions, and were analysed accordingly. However, the scope...... clusters of consistently correlated objects. We demonstrate the power of data-driven explorations by applying the Bi-CoPaM to two collections of big datasets from two distinct fields, namely bioinformatics and neuroscience. In the first application, the collective analysis of forty yeast gene expression...

  6. Framework for Interactive Parallel Dataset Analysis on the Grid

    Energy Technology Data Exchange (ETDEWEB)

    Alexander, David A.; Ananthan, Balamurali; /Tech-X Corp.; Johnson, Tony; Serbo, Victor; /SLAC

    2007-01-10

    We present a framework for use at a typical Grid site to facilitate custom interactive parallel dataset analysis targeting terabyte-scale datasets of the type typically produced by large multi-institutional science experiments. We summarize the needs for interactive analysis and show a prototype solution that satisfies those needs. The solution consists of desktop client tool and a set of Web Services that allow scientists to sign onto a Grid site, compose analysis script code to carry out physics analysis on datasets, distribute the code and datasets to worker nodes, collect the results back to the client, and to construct professional-quality visualizations of the results.

  7. Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks.

    Directory of Open Access Journals (Sweden)

    Xiaoke Ma

    2015-06-01

    Full Text Available Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules. We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression.

  8. Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

    Science.gov (United States)

    Maskey, M.; Ramachandran, R.; Miller, J.

    2017-12-01

    Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

  9. An Affinity Propagation Clustering Algorithm for Mixed Numeric and Categorical Datasets

    Directory of Open Access Journals (Sweden)

    Kang Zhang

    2014-01-01

    Full Text Available Clustering has been widely used in different fields of science, technology, social science, and so forth. In real world, numeric as well as categorical features are usually used to describe the data objects. Accordingly, many clustering methods can process datasets that are either numeric or categorical. Recently, algorithms that can handle the mixed data clustering problems have been developed. Affinity propagation (AP algorithm is an exemplar-based clustering method which has demonstrated good performance on a wide variety of datasets. However, it has limitations on processing mixed datasets. In this paper, we propose a novel similarity measure for mixed type datasets and an adaptive AP clustering algorithm is proposed to cluster the mixed datasets. Several real world datasets are studied to evaluate the performance of the proposed algorithm. Comparisons with other clustering algorithms demonstrate that the proposed method works well not only on mixed datasets but also on pure numeric and categorical datasets.

  10. Chemical product and function dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Merged product weight fraction and chemical function data. This dataset is associated with the following publication: Isaacs , K., M. Goldsmith, P. Egeghy , K....

  11. PARENT'S AND FRIEND’S AS FACTORS OF CHILD’S BEHAVIOR AT SCHOOL: A COMPARISON OF MULTIPLE CORRELATIONS

    Directory of Open Access Journals (Sweden)

    Orhideja Shurbanovska

    2013-06-01

    Full Text Available Why are some children lonely, aggressive or they behaving prosocially at school? This study tends to answer the research question: how are family and peer relations associated with the social behavior of the pupils in mid childhood and early adolescence (3rd grade and 7th grade pupils, respectively. The hypotheses refer to the differences in the connections of the family and peer relations with the student’s social behavior at school. The data gathered from 194 examinees were elaborated in the research, as follows: 3rd grade pupils (85 and 7th grade pupils (109.            The data from third grade pupils shows that multiple correlation between family variables in regards to loneliness is more significant (R=0.639, p<0. 01 than multiple correlation of peer variables (R=0.352, p>0. 05 which is not significant. For aggressive behavior both correlations: family (R=0.494, p<0. 05 and peer variable ( R=0.489, p<0.05 are significant. For prosocially behavior both family (R=0.434, p<0.05 and peer correlations (R=0.423, p<0.05 are almost equally significant. Shyness is not significantly associated neither with family nor with peer variables. Satisfaction from school is significantly associated with peer variables (R=0.440, p<0. 05  and with family variables (R=0.482, p<0.05 too.For the seventh grade students loneliness is significantly more influenced by family variables (R=0.617, p<0.01 than by peer variables (R=0.422, p<0.01. Aggressive behavior is more significantly related to family variables (R=0.577, p<0, 01 than peer variables. From that data the conclusion is that family variables in more cases are connected with child’s social behavior at school than peer variables, in middle childhood but and in early adolescence, too. 

  12. Geostatistical exploration of dataset assessing the heavy metal contamination in Ewekoro limestone, Southwestern Nigeria

    Directory of Open Access Journals (Sweden)

    Kehinde D. Oyeyemi

    2017-10-01

    Full Text Available The dataset for this article contains geostatistical analysis of heavy metals contamination from limestone samples collected from Ewekoro Formation in the eastern Dahomey basin, Ogun State Nigeria. The samples were manually collected and analysed using Microwave Plasma Atomic Absorption Spectrometer (MPAS. Analysis of the twenty different samples showed different levels of heavy metals concentration. The analysed nine elements are Arsenic, Mercury, Cadmium, Cobalt, Chromium, Nickel, Lead, Vanadium and Zinc. Descriptive statistics was used to explore the heavy metal concentrations individually. Pearson, Kendall tau and Spearman rho correlation coefficients was used to establish the relationships among the elements and the analysis of variance showed that there is a significant difference in the mean distribution of the heavy metals concentration within and between the groups of the 20 samples analysed. The dataset can provide insights into the health implications of the contaminants especially when the mean concentration levels of the heavy metals are compared with recommended regulatory limit concentration.

  13. Redundant correlation effect on personalized recommendation

    Science.gov (United States)

    Qiu, Tian; Han, Teng-Yue; Zhong, Li-Xin; Zhang, Zi-Ke; Chen, Guang

    2014-02-01

    The high-order redundant correlation effect is investigated for a hybrid algorithm of heat conduction and mass diffusion (HHM), through both heat conduction biased (HCB) and mass diffusion biased (MDB) correlation redundancy elimination processes. The HCB and MDB algorithms do not introduce any additional tunable parameters, but keep the simple character of the original HHM. Based on two empirical datasets, the Netflix and MovieLens, the HCB and MDB are found to show better recommendation accuracy for both the overall objects and the cold objects than the HHM algorithm. Our work suggests that properly eliminating the high-order redundant correlations can provide a simple and effective approach to accurate recommendation.

  14. General Purpose Multimedia Dataset - GarageBand 2008

    DEFF Research Database (Denmark)

    Meng, Anders

    This document describes a general purpose multimedia data-set to be used in cross-media machine learning problems. In more detail we describe the genre taxonomy applied at http://www.garageband.com, from where the data-set was collected, and how the taxonomy have been fused into a more human...... understandable taxonomy. Finally, a description of various features extracted from both the audio and text are presented....

  15. Assessing regional groundwater stress for nations using multiple data sources with the groundwater footprint

    International Nuclear Information System (INIS)

    Gleeson, Tom; Wada, Yoshihide

    2013-01-01

    Groundwater is a critical resource for agricultural production, ecosystems, drinking water and industry, yet groundwater depletion is accelerating, especially in a number of agriculturally important regions. Assessing the stress of groundwater resources is crucial for science-based policy and management, yet water stress assessments have often neglected groundwater and used single data sources, which may underestimate the uncertainty of the assessment. We consistently analyze and interpret groundwater stress across whole nations using multiple data sources for the first time. We focus on two nations with the highest national groundwater abstraction rates in the world, the United States and India, and use the recently developed groundwater footprint and multiple datasets of groundwater recharge and withdrawal derived from hydrologic models and data synthesis. A minority of aquifers, mostly with known groundwater depletion, show groundwater stress regardless of the input dataset. The majority of aquifers are not stressed with any input data while less than a third are stressed for some input data. In both countries groundwater stress affects agriculturally important regions. In the United States, groundwater stress impacts a lower proportion of the national area and population, and is focused in regions with lower population and water well density compared to India. Importantly, the results indicate that the uncertainty is generally greater between datasets than within datasets and that much of the uncertainty is due to recharge estimates. Assessment of groundwater stress consistently across a nation and assessment of uncertainty using multiple datasets are critical for the development of a science-based rationale for policy and management, especially with regard to where and to what extent to focus limited research and management resources. (letter)

  16. Omicseq: a web-based search engine for exploring omics datasets.

    Science.gov (United States)

    Sun, Xiaobo; Pittard, William S; Xu, Tianlei; Chen, Li; Zwick, Michael E; Jiang, Xiaoqian; Wang, Fusheng; Qin, Zhaohui S

    2017-07-03

    The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve 'findability' of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  17. Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

    Science.gov (United States)

    Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

    2011-01-01

    In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R, the correlation matrix of associated t-statistics is also studied. In general R depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

  18. New hybrid multivariate analysis approach to optimize multiple response surfaces considering correlations in both inputs and outputs

    OpenAIRE

    Hejazi, Taha Hossein; Amirkabir University of Technology - Iran; Seyyed-Esfahani, Mirmehdi; Amirkabir University of Technology - Iran; Ramezani, Majid; Amirkabir University of Technology - Iran

    2014-01-01

    Quality control in industrial and service systems requires the correct setting of input factors by which the outputs result at minimum cost with desirable characteristics. There are often more than one input and output in such systems. Response surface methodology in its multiple variable forms is one of the most applied methods to estimate and improve the quality characteristics of products with respect to control factors. When there is some degree of correlation among the variables, the exi...

  19. Quantifying uncertainty in observational rainfall datasets

    Science.gov (United States)

    Lennard, Chris; Dosio, Alessandro; Nikulin, Grigory; Pinto, Izidine; Seid, Hussen

    2015-04-01

    The CO-ordinated Regional Downscaling Experiment (CORDEX) has to date seen the publication of at least ten journal papers that examine the African domain during 2012 and 2013. Five of these papers consider Africa generally (Nikulin et al. 2012, Kim et al. 2013, Hernandes-Dias et al. 2013, Laprise et al. 2013, Panitz et al. 2013) and five have regional foci: Tramblay et al. (2013) on Northern Africa, Mariotti et al. (2014) and Gbobaniyi el al. (2013) on West Africa, Endris et al. (2013) on East Africa and Kalagnoumou et al. (2013) on southern Africa. There also are a further three papers that the authors know about under review. These papers all use an observed rainfall and/or temperature data to evaluate/validate the regional model output and often proceed to assess projected changes in these variables due to climate change in the context of these observations. The most popular reference rainfall data used are the CRU, GPCP, GPCC, TRMM and UDEL datasets. However, as Kalagnoumou et al. (2013) point out there are many other rainfall datasets available for consideration, for example, CMORPH, FEWS, TAMSAT & RIANNAA, TAMORA and the WATCH & WATCH-DEI data. They, with others (Nikulin et al. 2012, Sylla et al. 2012) show that the observed datasets can have a very wide spread at a particular space-time coordinate. As more ground, space and reanalysis-based rainfall products become available, all which use different methods to produce precipitation data, the selection of reference data is becoming an important factor in model evaluation. A number of factors can contribute to a uncertainty in terms of the reliability and validity of the datasets such as radiance conversion algorithims, the quantity and quality of available station data, interpolation techniques and blending methods used to combine satellite and guage based products. However, to date no comprehensive study has been performed to evaluate the uncertainty in these observational datasets. We assess 18 gridded

  20. Using correlation functions as free decays

    DEFF Research Database (Denmark)

    Brincker, Rune; Amador, Sandro; Juul, Martin

    It is a general assumption in OMA that correlation functions are free decays. In multiple input OMA this assumption also implies that any column in the correlation function matrix is to be considered as multiple output free decays. This assumption is discussed in this paper together with issues...... concerning estimation and application of correlations functions in OMA....

  1. Analysis of Public Datasets for Wearable Fall Detection Systems.

    Science.gov (United States)

    Casilari, Eduardo; Santoyo-Ramón, José-Antonio; Cano-García, José-Manuel

    2017-06-27

    Due to the boom of wireless handheld devices such as smartwatches and smartphones, wearable Fall Detection Systems (FDSs) have become a major focus of attention among the research community during the last years. The effectiveness of a wearable FDS must be contrasted against a wide variety of measurements obtained from inertial sensors during the occurrence of falls and Activities of Daily Living (ADLs). In this regard, the access to public databases constitutes the basis for an open and systematic assessment of fall detection techniques. This paper reviews and appraises twelve existing available data repositories containing measurements of ADLs and emulated falls envisaged for the evaluation of fall detection algorithms in wearable FDSs. The analysis of the found datasets is performed in a comprehensive way, taking into account the multiple factors involved in the definition of the testbeds deployed for the generation of the mobility samples. The study of the traces brings to light the lack of a common experimental benchmarking procedure and, consequently, the large heterogeneity of the datasets from a number of perspectives (length and number of samples, typology of the emulated falls and ADLs, characteristics of the test subjects, features and positions of the sensors, etc.). Concerning this, the statistical analysis of the samples reveals the impact of the sensor range on the reliability of the traces. In addition, the study evidences the importance of the selection of the ADLs and the need of categorizing the ADLs depending on the intensity of the movements in order to evaluate the capability of a certain detection algorithm to discriminate falls from ADLs.

  2. Turkey Run Landfill Emissions Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — landfill emissions measurements for the Turkey run landfill in Georgia. This dataset is associated with the following publication: De la Cruz, F., R. Green, G....

  3. Measurement of multi-particle azimuthal correlations in pp, p + Pb and low-multiplicity Pb + Pb collisions with the ATLAS detector

    Energy Technology Data Exchange (ETDEWEB)

    Aaboud, M. [Univ. Mohamed Premier et LPTPM, Oujda (Morocco). Faculte des Sciences; Aad, G. [CPPM, Aix-Marseille Univ. et CNRS/IN2P3, Marseille (France); Abbott, B. [Oklahoma Univ., Norman, OK (United States). Homer L. Dodge Dept. of Physics and Astronomy; Collaboration: ATLAS Collaboration; and others

    2017-06-15

    Multi-particle cumulants and corresponding Fourier harmonics are measured for azimuthal angle distributions of charged particles in pp collisions at √(s) = 5.02 and 13 TeV and in p + Pb collisions at √(s{sub NN}) = 5.02 TeV, and compared to the results obtained for low-multiplicity Pb + Pb collisions at √(s{sub NN}) = 2.76 TeV. These measurements aim to assess the collective nature of particle production. The measurements of multi-particle cumulants confirm the evidence for collective phenomena in p + Pb and low-multiplicity Pb + Pb collisions. On the other hand, the pp results for four-particle cumulants do not demonstrate collective behaviour, indicating that they may be biased by contributions from non-flow correlations. A comparison of multi-particle cumulants and derived Fourier harmonics across different collision systems is presented as a function of the charged-particle multiplicity. For a given multiplicity, the measured Fourier harmonics are largest in Pb + Pb, smaller in p + Pb and smallest in pp results show no dependence on the collision energy, nor on the multiplicity. (orig.)

  4. Recent ice cap snowmelt in Russian High Arctic and anti-correlation with late summer sea ice extent

    International Nuclear Information System (INIS)

    Zhao, Meng; Ramage, Joan; Semmens, Kathryn; Obleitner, Friedrich

    2014-01-01

    Glacier surface melt dynamics throughout Novaya Zemlya (NovZ) and Severnaya Zemlya (SevZ) serve as a good indicator of ice mass ablation and regional climate change in the Russian High Arctic. Here we report trends of surface melt onset date (MOD) and total melt days (TMD) by combining multiple resolution-enhanced active and passive microwave satellite datasets and analyze the TMD correlations with local temperature and regional sea ice extent. The glacier surface snowpack on SevZ melted significantly earlier (−7.3 days/decade) from 1992 to 2012 and significantly longer (7.7 days/decade) from 1995 to 2011. NovZ experienced large interannual variability in MOD, but its annual mean TMD increased. The snowpack melt on NovZ is more sensitive to temperature fluctuations than SevZ in recent decades. After ruling out the regional temperature influence using partial correlation analysis, the TMD on both archipelagoes is statistically anti-correlated with regional late summer sea ice extent, linking land ice snowmelt dynamics to regional sea ice extent variations. (letter)

  5. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

  6. Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations

    Directory of Open Access Journals (Sweden)

    Miller Crispin J

    2006-06-01

    Full Text Available Abstract Background Microarrays measure the binding of nucleotide sequences to a set of sequence specific probes. This information is combined with annotation specifying the relationship between probes and targets and used to make inferences about transcript- and, ultimately, gene expression. In some situations, a probe is capable of hybridizing to more than one transcript, in others, multiple probes can target a single sequence. These 'multiply targeted' probes can result in non-independence between measured expression levels. Results An analysis of these relationships for Affymetrix arrays considered both the extent and influence of exact matches between probe and transcript sequences. For the popular HGU133A array, approximately half of the probesets were found to interact in this way. Both real and simulated expression datasets were used to examine how these effects influenced the expression signal. It was found not only to lead to increased signal strength for the affected probesets, but the major effect is to significantly increase their correlation, even in situations when only a single probe from a probeset was involved. By building a network of probe-probeset-transcript relationships, it is possible to identify families of interacting probesets. More than 10% of the families contain members annotated to different genes or even different Unigene clusters. Within a family, a mixture of genuine biological and artefactual correlations can occur. Conclusion Multiple targeting is not only prevalent, but also significant. The ability of probesets to hybridize to more than one gene product can lead to false positives when analysing gene expression. Comprehensive annotation describing multiple targeting is required when interpreting array data.

  7. An Analysis of the GTZAN Music Genre Dataset

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2012-01-01

    Most research in automatic music genre recognition has used the dataset assembled by Tzanetakis et al. in 2001. The composition and integrity of this dataset, however, has never been formally analyzed. For the first time, we provide an analysis of its composition, and create a machine...

  8. Dataset definition for CMS operations and physics analyses

    Science.gov (United States)

    Franzoni, Giovanni; Compact Muon Solenoid Collaboration

    2016-04-01

    Data recorded at the CMS experiment are funnelled into streams, integrated in the HLT menu, and further organised in a hierarchical structure of primary datasets and secondary datasets/dedicated skims. Datasets are defined according to the final-state particles reconstructed by the high level trigger, the data format and the use case (physics analysis, alignment and calibration, performance studies). During the first LHC run, new workflows have been added to this canonical scheme, to exploit at best the flexibility of the CMS trigger and data acquisition systems. The concepts of data parking and data scouting have been introduced to extend the physics reach of CMS, offering the opportunity of defining physics triggers with extremely loose selections (e.g. dijet resonance trigger collecting data at a 1 kHz). In this presentation, we review the evolution of the dataset definition during the LHC run I, and we discuss the plans for the run II.

  9. Dataset definition for CMS operations and physics analyses

    CERN Document Server

    AUTHOR|(CDS)2051291

    2016-01-01

    Data recorded at the CMS experiment are funnelled into streams, integrated in the HLT menu, and further organised in a hierarchical structure of primary datasets, secondary datasets, and dedicated skims. Datasets are defined according to the final-state particles reconstructed by the high level trigger, the data format and the use case (physics analysis, alignment and calibration, performance studies). During the first LHC run, new workflows have been added to this canonical scheme, to exploit at best the flexibility of the CMS trigger and data acquisition systems. The concept of data parking and data scouting have been introduced to extend the physics reach of CMS, offering the opportunity of defining physics triggers with extremely loose selections (e.g. dijet resonance trigger collecting data at a 1 kHz). In this presentation, we review the evolution of the dataset definition during the first run, and we discuss the plans for the second LHC run.

  10. Dataset of NRDA emission data

    Data.gov (United States)

    U.S. Environmental Protection Agency — Emissions data from open air oil burns. This dataset is associated with the following publication: Gullett, B., J. Aurell, A. Holder, B. Mitchell, D. Greenwell, M....

  11. Discovery and Reuse of Open Datasets: An Exploratory Study

    Directory of Open Access Journals (Sweden)

    Sara

    2016-07-01

    Full Text Available Objective: This article analyzes twenty cited or downloaded datasets and the repositories that house them, in order to produce insights that can be used by academic libraries to encourage discovery and reuse of research data in institutional repositories. Methods: Using Thomson Reuters’ Data Citation Index and repository download statistics, we identified twenty cited/downloaded datasets. We documented the characteristics of the cited/downloaded datasets and their corresponding repositories in a self-designed rubric. The rubric includes six major categories: basic information; funding agency and journal information; linking and sharing; factors to encourage reuse; repository characteristics; and data description. Results: Our small-scale study suggests that cited/downloaded datasets generally comply with basic recommendations for facilitating reuse: data are documented well; formatted for use with a variety of software; and shared in established, open access repositories. Three significant factors also appear to contribute to dataset discovery: publishing in discipline-specific repositories; indexing in more than one location on the web; and using persistent identifiers. The cited/downloaded datasets in our analysis came from a few specific disciplines, and tended to be funded by agencies with data publication mandates. Conclusions: The results of this exploratory research provide insights that can inform academic librarians as they work to encourage discovery and reuse of institutional datasets. Our analysis also suggests areas in which academic librarians can target open data advocacy in their communities in order to begin to build open data success stories that will fuel future advocacy efforts.

  12. Computer code MLCOSP for multiple-correlation and spectrum analysis with a hybrid computer

    International Nuclear Information System (INIS)

    Oguma, Ritsuo; Fujii, Yoshio; Usui, Hozumi; Watanabe, Koichi

    1975-10-01

    Usage of the computer code MLCOSP(Multiple Correlation and Spectrum) developed is described for a hybrid computer installed in JAERI Functions of the hybrid computer and its terminal devices are utilized ingeniously in the code to reduce complexity of the data handling which occurrs in analysis of the multivariable experimental data and to perform the analysis in perspective. Features of the code are as follows; Experimental data can be fed to the digital computer through the analog part of the hybrid computer by connecting with a data recorder. The computed results are displayed in figures, and hardcopies are taken when necessary. Series-messages to the code are shown on the terminal, so man-machine communication is possible. And further the data can be put in through a keyboard, so case study according to the results of analysis is possible. (auth.)

  13. An Annotated Dataset of 14 Cardiac MR Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2002-01-01

    This note describes a dataset consisting of 14 annotated cardiac MR images. Points of correspondence are placed on each image at the left ventricle (LV). As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

  14. Measurement of multi-particle azimuthal correlations in $pp$, $p$+Pb and low-multiplicity Pb+Pb collisions with the ATLAS detector

    CERN Document Server

    Aaboud, Morad; ATLAS Collaboration; Abbott, Brad; Abdallah, Jalal; Abdinov, Ovsat; Abeloos, Baptiste; Abidi, Syed Haider; AbouZeid, Ossama; Abraham, Nicola; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Adachi, Shunsuke; Adamczyk, Leszek; Adelman, Jahred; Adersberger, Michael; Adye, Tim; Affolder, Tony; Agatonovic-Jovin, Tatjana; Agheorghiesei, Catalin; Aguilar-Saavedra, Juan Antonio; Ahlen, Steven; Ahmadov, Faig; Aielli, Giulio; Akatsuka, Shunichi; Akerstedt, Henrik; Åkesson, Torsten Paul Ake; Akimov, Andrei; Alberghi, Gian Luigi; Albert, Justin; Albicocco, Pietro; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexopoulos, Theodoros; Alhroob, Muhammad; Ali, Babar; Aliev, Malik; Alimonti, Gianluca; Alison, John; Alkire, Steven Patrick; Allbrooke, Benedict; Allen, Benjamin William; Allport, Phillip; Aloisio, Alberto; Alonso, Alejandro; Alonso, Francisco; Alpigiani, Cristiano; Alshehri, Azzah Aziz; Alstaty, Mahmoud; Alvarez Gonzalez, Barbara; Άlvarez Piqueras, Damián; Alviggi, Mariagrazia; Amadio, Brian Thomas; Amaral Coutinho, Yara; Amelung, Christoph; Amidei, Dante; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, John Kenneth; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Angelidakis, Stylianos; Angelozzi, Ivan; Angerami, Aaron; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antel, Claire; Antonelli, Mario; Antonov, Alexey; Antrim, Daniel Joseph; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Arabidze, Giorgi; Arai, Yasuo; Araque, Juan Pedro; Araujo Ferraz, Victor; Arce, Ayana; Ardell, Rose Elisabeth; Arduh, Francisco Anuar; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Armitage, Lewis James; Arnaez, Olivier; Arnold, Hannah; Arratia, Miguel; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Artz, Sebastian; Asai, Shoji; Asbah, Nedaa; Ashkenazi, Adi; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Augsten, Kamil; Avolio, Giuseppe; Axen, Bradley; Ayoub, Mohamad Kassem; Azuelos, Georges; Baas, Alessandra; Baca, Matthew John; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Bagnaia, Paolo; Bahrasemani, Sina; Baines, John; Bajic, Milena; Baker, Oliver Keith; Baldin, Evgenii; Balek, Petr; Balli, Fabrice; Balunas, William Keaton; Banas, Elzbieta; Banerjee, Swagato; Bannoura, Arwa A E; Barak, Liron; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisits, Martin-Stefan; Barklow, Timothy; Barlow, Nick; Barnes, Sarah Louise; Barnett, Bruce; Barnett, Michael; Barnovska-Blenessy, Zuzana; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barranco Navarro, Laura; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Basalaev, Artem; Bassalat, Ahmed; Bates, Richard; Batista, Santiago Juan; Batley, Richard; Battaglia, Marco; Bauce, Matteo; Bauer, Florian; Bawa, Harinder Singh; Beacham, James; Beattie, Michael David; Beau, Tristan; Beauchemin, Pierre-Hugues; Bechtle, Philip; Beck, Hans~Peter; Becker, Kathrin; Becker, Maurice; Beckingham, Matthew; Becot, Cyril; Beddall, Andrew; Beddall, Ayda; Bednyakov, Vadim; Bedognetti, Matteo; Bee, Christopher; Beermann, Thomas; Begalli, Marcia; Begel, Michael; Behr, Janna Katharina; Bell, Andrew Stuart; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belotskiy, Konstantin; Beltramello, Olga; Belyaev, Nikita; Benary, Odette; Benchekroun, Driss; Bender, Michael; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez, Jose; Benjamin, Douglas; Benoit, Mathieu; Bensinger, James; Bentvelsen, Stan; Beresford, Lydia; Beretta, Matteo; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Beringer, Jürg; Berlendis, Simon; Bernard, Nathan Rogers; Bernardi, Gregorio; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertoli, Gabriele; Bertolucci, Federico; Bertram, Iain Alexander; Bertsche, Carolyn; Bertsche, David; Besjes, Geert-Jan; Bessidskaia Bylund, Olga; Bessner, Martin Florian; Besson, Nathalie; Betancourt, Christopher; Bethani, Agni; Bethke, Siegfried; Bevan, Adrian John; Bianchi, Riccardo-Maria; Biebel, Otmar; Biedermann, Dustin; Bielski, Rafal; Biesuz, Nicolo Vladi; Biglietti, Michela; Bilbao De Mendizabal, Javier; Billoud, Thomas Remy Victor; Bilokon, Halina; Bindi, Marcello; Bingul, Ahmet; Bini, Cesare; Biondi, Silvia; Bisanz, Tobias; Bittrich, Carsten; Bjergaard, David Martin; Black, Curtis; Black, James; Black, Kevin; Blackburn, Daniel; Blair, Robert; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blue, Andrew; Blum, Walter; Blumenschein, Ulrike; Blunier, Sylvain; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Bock, Christopher; Boehler, Michael; Boerner, Daniela; Bogavac, Danijela; Bogdanchikov, Alexander; Bohm, Christian; Boisvert, Veronique; Bokan, Petar; Bold, Tomasz; Boldyrev, Alexey; Bolz, Arthur Eugen; Bomben, Marco; Bona, Marcella; Boonekamp, Maarten; Borisov, Anatoly; Borissov, Guennadi; Bortfeldt, Jonathan; Bortoletto, Daniela; Bortolotto, Valerio; Boscherini, Davide; Bosman, Martine; Bossio Sola, Jonathan David; Boudreau, Joseph; Bouffard, Julian; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Boutle, Sarah Kate; Boveia, Antonio; Boyd, James; Boyko, Igor; Bracinik, Juraj; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Breaden Madden, William Dmitri; Brendlinger, Kurt; Brennan, Amelia Jean; Brenner, Lydia; Brenner, Richard; Bressler, Shikma; Briglin, Daniel Lawrence; Bristow, Timothy Michael; Britton, Dave; Britzger, Daniel; Brochu, Frederic; Brock, Ian; Brock, Raymond; Brooijmans, Gustaaf; Brooks, Timothy; Brooks, William; Brosamer, Jacquelyn; Brost, Elizabeth; Broughton, James; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruni, Alessia; Bruni, Graziano; Bruni, Lucrezia Stella; Brunt, Benjamin; Bruschi, Marco; Bruscino, Nello; Bryant, Patrick; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Buchholz, Peter; Buckley, Andrew; Budagov, Ioulian; Buehrer, Felix; Bugge, Magnar Kopangen; Bulekov, Oleg; Bullock, Daniel; Burch, Tyler James; Burckhart, Helfried; Burdin, Sergey; Burgard, Carsten Daniel; Burger, Angela Maria; Burghgrave, Blake; Burka, Klaudia; Burke, Stephen; Burmeister, Ingo; Burr, Jonathan Thomas Peter; Busato, Emmanuel; Büscher, Daniel; Büscher, Volker; Bussey, Peter; Butler, John; Buttar, Craig; Butterworth, Jonathan; Butti, Pierfrancesco; Buttinger, William; Buzatu, Adrian; Buzykaev, Aleksey; Cabrera Urbán, Susana; Caforio, Davide; Cairo, Valentina; Cakir, Orhan; Calace, Noemi; Calafiura, Paolo; Calandri, Alessandro; Calderini, Giovanni; Calfayan, Philippe; Callea, Giuseppe; Caloba, Luiz; Calvente Lopez, Sergio; Calvet, David; Calvet, Samuel; Calvet, Thomas Philippe; Camacho Toro, Reina; Camarda, Stefano; Camarri, Paolo; Cameron, David; Caminal Armadans, Roger; Camincher, Clement; Campana, Simone; Campanelli, Mario; Camplani, Alessandra; Campoverde, Angel; Canale, Vincenzo; Cano Bret, Marc; Cantero, Josu; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capua, Marcella; Carbone, Ryne Michael; Cardarelli, Roberto; Cardillo, Fabio; Carli, Ina; Carli, Tancredi; Carlino, Gianpaolo; Carlson, Benjamin Taylor; Carminati, Leonardo; Carney, Rebecca; Caron, Sascha; Carquin, Edson; Carrá, Sonia; Carrillo-Montoya, German D; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Casolino, Mirkoantonio; Casper, David William; Castelijn, Remco; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Caudron, Julien; Cavaliere, Viviana; Cavallaro, Emanuele; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Celebi, Emre; Ceradini, Filippo; Cerda Alberich, Leonor; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chan, Stephen Kam-wah; Chan, Wing Sheung; Chan, Yat Long; Chang, Philip; Chapman, John Derek; Charlton, Dave; Chau, Chav Chhiv; Chavez Barajas, Carlos Alberto; Che, Siinn; Cheatham, Susan; Chegwidden, Andrew; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Shenjian; Chen, Shion; Chen, Xin; Chen, Ye; Cheng, Hok Chuen; Cheng, Huajie; Cheplakov, Alexander; Cheremushkina, Evgenia; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Chevalier, Laurent; Chiarella, Vitaliano; Chiarelli, Giorgio; Chiodini, Gabriele; Chisholm, Andrew; Chitan, Adrian; Chiu, Yu Him Justin; Chizhov, Mihail; Choi, Kyungeon; Chomont, Arthur Rene; Chouridou, Sofia; Christodoulou, Valentinos; Chromek-Burckhart, Doris; Chu, Ming Chung; Chudoba, Jiri; Chuinard, Annabelle Julia; Chwastowski, Janusz; Chytka, Ladislav; Ciftci, Abbas Kenan; Cinca, Diane; Cindro, Vladimir; Cioara, Irina Antonela; Ciocca, Claudia; Ciocio, Alessandra; Cirotto, Francesco; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Brian Lee; Clark, Michael; Clark, Philip James; Clarke, Robert; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Colasurdo, Luca; Cole, Brian; Colijn, Auke-Pieter; Collot, Johann; Colombo, Tommaso; Conde Muiño, Patricia; Coniavitis, Elias; Connell, Simon Henry; Connelly, Ian; Constantinescu, Serban; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper-Sarkar, Amanda; Cormier, Felix; Cormier, Kyle James Read; Corradi, Massimo; Corriveau, Francois; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Cottin, Giovanna; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Crawley, Samuel Joseph; Creager, Rachael; Cree, Graham; Crépé-Renaudin, Sabine; Crescioli, Francesco; Cribbs, Wayne Allen; Cristinziani, Markus; Croft, Vince; Crosetti, Giovanni; Cueto, Ana; Cuhadar Donszelmann, Tulay; Cukierman, Aviv Ruben; Cummings, Jane; Curatolo, Maria; Cúth, Jakub; Czirr, Hendrik; Czodrowski, Patrick; D'amen, Gabriele; D'Auria, Saverio; D'Onofrio, Monica; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dado, Tomas; Dai, Tiesheng; Dale, Orjan; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Dandoy, Jeffrey; Dang, Nguyen Phuong; Daniells, Andrew Christopher; Dann, Nicholas Stuart; Danninger, Matthias; Dano Hoffmann, Maria; Dao, Valerio; Darbo, Giovanni; Darmora, Smita; Dassoulas, James; Dattagupta, Aparajita; Daubney, Thomas; Davey, Will; David, Claire; Davidek, Tomas; Davies, Merlin; Davison, Peter; Dawe, Edmund; Dawson, Ian; De, Kaushik; de Asmundis, Riccardo; De Benedetti, Abraham; De Castro, Stefano; De Cecco, Sandro; De Groot, Nicolo; de Jong, Paul; De la Torre, Hector; De Lorenzi, Francesco; De Maria, Antonio; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vasconcelos Corga, Kevin; De Vivie De Regie, Jean-Baptiste; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dedovich, Dmitri; Dehghanian, Nooshin; Deigaard, Ingrid; Del Gaudio, Michela; Del Peso, Jose; Del Prete, Tarcisio; Delgove, David; Deliot, Frederic; Delitzsch, Chris Malena; Dell'Acqua, Andrea; Dell'Asta, Lidia; Dell'Orso, Mauro; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delporte, Charles; Delsart, Pierre-Antoine; DeMarco, David; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Denisov, Sergey; Denysiuk, Denys; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deterre, Cecile; Dette, Karola; Devesa, Maria Roberta; Deviveiros, Pier-Olivier; Dewhurst, Alastair; Dhaliwal, Saminder; Di Bello, Francesco Armando; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Clemente, William Kennedy; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Micco, Biagio; Di Nardo, Roberto; Di Petrillo, Karri Folan; Di Simone, Andrea; Di Sipio, Riccardo; Di Valentino, David; Diaconu, Cristinel; Diamond, Miriam; Dias, Flavia; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Díez Cornell, Sergio; Dimitrievska, Aleksandra; Dingfelder, Jochen; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Djuvsland, Julia Isabell; Barros do Vale, Maria Aline; Dobos, Daniel; Dobre, Monica; Doglioni, Caterina; Dolejsi, Jiri; Dolezal, Zdenek; Donadelli, Marisilvia; Donati, Simone; Dondero, Paolo; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dova, Maria-Teresa; Doyle, Tony; Drechsler, Eric; Dris, Manolis; Du, Yanyan; Duarte-Campderros, Jorge; Dubreuil, Arnaud; Duchovni, Ehud; Duckeck, Guenter; Ducourthial, Audrey; Ducu, Otilia Anamaria; Duda, Dominik; Dudarev, Alexey; Dudder, Andreas Christian; Duffield, Emily Marie; Duflot, Laurent; Dührssen, Michael; Dumancic, Mirta; Dumitriu, Ana Elena; Duncan, Anna Kathryn; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Durglishvili, Archil; Duschinger, Dirk; Dutta, Baishali; Dyndal, Mateusz; Eckardt, Christoph; Ecker, Katharina Maria; Edgar, Ryan Christopher; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Ekelof, Tord; El Kacimi, Mohamed; El Kosseifi, Rima; Ellajosyula, Venugopal; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Elliot, Alison; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Ennis, Joseph Stanford; Erdmann, Johannes; Ereditato, Antonio; Ernis, Gunar; Ernst, Michael; Errede, Steven; Ertel, Eugen; Escalier, Marc; Escobar, Carlos; Esposito, Bellisario; Estrada Pastor, Oscar; Etienvre, Anne-Isabelle; Etzion, Erez; Evans, Hal; Ezhilov, Alexey; Ezzi, Mohammed; Fabbri, Federica; Fabbri, Laura; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Falla, Rebecca Jane; Faltova, Jana; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farina, Christian; Farina, Edoardo Maria; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Faucci Giannelli, Michele; Favareto, Andrea; Fawcett, William James; Fayard, Louis; Fedin, Oleg; Fedorko, Wojciech; Feigl, Simon; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenton, Michael James; Fenyuk, Alexander; Feremenga, Last; Fernandez Martinez, Patricia; Fernandez Perez, Sonia; Ferrando, James; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrere, Didier; Ferretti, Claudio; Fiedler, Frank; Filipčič, Andrej; Filipuzzi, Marco; Filthaut, Frank; Fincke-Keeler, Margret; Finelli, Kevin Daniel; Fiolhais, Miguel; Fiorini, Luca; Fischer, Adam; Fischer, Cora; Fischer, Julia; Fisher, Wade Cameron; Flaschel, Nils; Fleck, Ivor; Fleischmann, Philipp; Fletcher, Rob Roy MacGregor; Flick, Tobias; Flierl, Bernhard Matthias; Flores Castillo, Luis; Flowerdew, Michael; Forcolin, Giulio Tiziano; Formica, Andrea; Förster, Fabian Alexander; Forti, Alessandra; Foster, Andrew Geoffrey; Fournier, Daniel; Fox, Harald; Fracchia, Silvia; Francavilla, Paolo; Franchini, Matteo; Franchino, Silvia; Francis, David; Franconi, Laura; Franklin, Melissa; Frate, Meghan; Fraternali, Marco; Freeborn, David; Fressard-Batraneanu, Silvia; Freund, Benjamin; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fusayasu, Takahiro; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gach, Grzegorz; Gadatsch, Stefan; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Louis Guillaume; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallop, Bruce; Gallus, Petr; Galster, Gorm Aske Gram Krohn; Gan, KK; Ganguly, Sanmay; Gao, Jun; Gao, Yanyan; Gao, Yongsheng; Garay Walls, Francisca; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gascon Bravo, Alberto; Gasnikova, Ksenia; Gatti, Claudio; Gaudiello, Andrea; Gaudio, Gabriella; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Gee, Norman; Geisen, Jannik; Geisen, Marc; Geisler, Manuel Patrice; Gellerstedt, Karl; Gemme, Claudia; Genest, Marie-Hélène; Geng, Cong; Gentile, Simonetta; Gentsos, Christos; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghasemi, Sara; Ghneimat, Mazuza; Giacobbe, Benedetto; Giagu, Stefano; Giannetti, Paola; Gibson, Stephen; Gignac, Matthew; Gilchriese, Murdock; Gillberg, Dag; Gilles, Geoffrey; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giorgi, Filippo Maria; Giraud, Pierre-Francois; Giromini, Paolo; Giugni, Danilo; Giuli, Francesco; Giuliani, Claudia; Giulini, Maddalena; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gkougkousis, Evangelos Leonidas; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glaysher, Paul; Glazov, Alexandre; Goblirsch-Kolb, Maximilian; Godlewski, Jan; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gonçalo, Ricardo; Goncalves Gama, Rafael; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Giulia; Gonella, Laura; Gongadze, Alexi; González de la Hoz, Santiago; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Goudet, Christophe Raymond; Goujdami, Driss; Goussiou, Anna; Govender, Nicolin; Gozani, Eitan; Graber, Lars; Grabowska-Bold, Iwona; Gradin, Per Olov Joakim; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Gratchev, Vadim; Gravila, Paul Mircea; Gray, Chloe; Gray, Heather; Greenwood, Zeno Dixon; Grefe, Christian; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Grevtsov, Kirill; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grivaz, Jean-Francois; Groh, Sabrina; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Grout, Zara Jane; Grummer, Aidan; Guan, Liang; Guan, Wen; Guenther, Jaroslav; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Gui, Bin; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Guo, Jun; Guo, Wen; Guo, Yicheng; Gupta, Ruchi; Gupta, Shaun; Gustavino, Giuliano; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guyot, Claude; Guzik, Marcin Pawel; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haber, Carl; Hadavand, Haleh Khani; Haddad, Nacim; Hadef, Asma; Hageböck, Stephan; Hagihara, Mutsuto; Hakobyan, Hrachya; Haleem, Mahsana; Haley, Joseph; Halladjian, Garabed; Hallewell, Gregory David; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamilton, Andrew; Hamity, Guillermo Nicolas; Hamnett, Phillip George; Han, Liang; Han, Shuo; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Haney, Bijan; Hanke, Paul; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Maike Christina; Hansen, Peter Henrik; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Hariri, Faten; Harkusha, Siarhei; Harrington, Robert; Harrison, Paul Fraser; Hartmann, Nikolai Marcel; Hasegawa, Makoto; Hasegawa, Yoji; Hasib, Ahmed; Hassani, Samira; Haug, Sigve; Hauser, Reiner; Hauswald, Lorenz; Havener, Laura Brittany; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hayakawa, Daiki; Hayden, Daniel; Hays, Chris; Hays, Jonathan Michael; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heidegger, Kim Katrin; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Jochen Jens; Heinrich, Lukas; Heinz, Christian; Hejbal, Jiri; Helary, Louis; Held, Alexander; Hellman, Sten; Helsens, Clement; Henderson, Robert; Heng, Yang; Henkelmann, Steffen; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Herbert, Geoffrey Henry; Herde, Hannah; Herget, Verena; Hernández Jiménez, Yesenia; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Herwig, Theodor Christian; Hesketh, Gavin Grant; Hessey, Nigel; Hetherly, Jeffrey Wayne; Higashino, Satoshi; Higón-Rodriguez, Emilio; Hill, Ewan; Hill, John; Hiller, Karl Heinz; Hillier, Stephen; Hinchliffe, Ian; Hirose, Minoru; Hirschbuehl, Dominic; Hiti, Bojan; Hladik, Ondrej; Hoad, Xanthe; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoenig, Friedrich; Hohn, David; Holmes, Tova Ray; Homann, Michael; Honda, Shunsuke; Honda, Takuya; Hong, Tae Min; Hooberman, Benjamin Henry; Hopkins, Walter; Horii, Yasuyuki; Horton, Arthur James; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howarth, James; Hoya, Joaquin; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hrynevich, Aliaksei; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Qipeng; Hu, Shuyang; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Huo, Peng; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Idrissi, Zineb; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikeno, Masahiro; Ilchenko, Yuriy; Iliadis, Dimitrios; Ilic, Nikolina; Introzzi, Gianluca; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Isacson, Max Fredrik; Ishijima, Naoki; Ishino, Masaya; Ishitsuka, Masaki; Issever, Cigdem; Istin, Serhat; Ito, Fumiaki; Iturbe Ponce, Julia Mariana; Iuppa, Roberto; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jabbar, Samina; Jackson, Paul; Jacobs, Ruth Magdalena; Jain, Vivek; Jakobi, Katharina Bianca; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jamin, David Olivier; Jana, Dilip; Jansky, Roland; Janssen, Jens; Janus, Michel; Janus, Piotr Andrzej; Jarlskog, Göran; Javadov, Namig; Javůrek, Tomáš; Javurkova, Martina; Jeanneau, Fabien; Jeanty, Laura; Jejelava, Juansher; Jelinskas, Adomas; Jenni, Peter; Jeske, Carl; Jézéquel, Stéphane; Ji, Haoshuang; Jia, Jiangyong; Jiang, Hai; Jiang, Yi; Jiang, Zihao; Jiggins, Stephen; Jimenez Pena, Javier; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Jivan, Harshna; Johansson, Per; Johns, Kenneth; Johnson, Christian; Johnson, William Joseph; Jon-And, Kerstin; Jones, Roger; Jones, Samuel David; Jones, Sarah; Jones, Tim; Jongmanns, Jan; Jorge, Pedro; Jovicevic, Jelena; Ju, Xiangyang; Juste Rozas, Aurelio; Köhler, Markus Konrad; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kahn, Sebastien Jonathan; Kaji, Toshiaki; Kajomovitz, Enrique; Kalderon, Charles William; Kaluza, Adam; Kama, Sami; Kamenshchikov, Andrey; Kanaya, Naoko; Kanjir, Luka; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kaplan, Laser Seymour; Kar, Deepak; Karakostas, Konstantinos; Karastathis, Nikolaos; Kareem, Mohammad Jawad; Karentzos, Efstathios; Karpov, Sergey; Karpova, Zoya; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kasahara, Kota; Kashif, Lashkar; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Kato, Chikuma; Katre, Akshay; Katzy, Judith; Kawade, Kentaro; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kay, Ellis; Kazanin, Vassili; Keeler, Richard; Kehoe, Robert; Keller, John; Kempster, Jacob Julian; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Keyes, Robert; Khader, Mazin; Khalil-zada, Farkhad; Khanov, Alexander; Kharlamov, Alexey; Kharlamova, Tatyana; Khodinov, Alexander; Khoo, Teng Jian; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kido, Shogo; Kilby, Callum; Kim, Hee Yeun; Kim, Shinhong; Kim, Young-Kee; Kimura, Naoki; Kind, Oliver Maria; King, Barry; Kirchmeier, David; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kiuchi, Kenji; Kivernyk, Oleh; Kladiva, Eduard; Klapdor-Kleingrothaus, Thorwald; Klein, Matthew Henry; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klingl, Tobias; Klioutchnikova, Tatiana; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Knapik, Joanna; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Aine; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koffas, Thomas; Koffeman, Els; Köhler, Nicolas Maximilian; Koi, Tatsumi; Kolb, Mathis; Koletsou, Iro; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kondrashova, Nataliia; Köneke, Karsten; König, Adriaan; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Kortner, Oliver; Kortner, Sandra; Kosek, Tomas; Kostyukhin, Vadim; Kotwal, Ashutosh; Koulouris, Aimilianos; Kourkoumeli-Charalampidi, Athina; Kourkoumelis, Christine; Kourlitis, Evangelos; Kouskoura, Vasiliki; Kowalewska, Anna Bozena; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozakai, Chihiro; Kozanecki, Witold; Kozhin, Anatoly; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitrii; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Krauss, Dominik; Kremer, Jakub Andrzej; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Peter; Krizka, Karol; Kroeninger, Kevin; Kroha, Hubert; Kroll, Jiri; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Krumnack, Nils; Kruse, Mark; Kubota, Takashi; Kucuk, Hilal; Kuday, Sinan; Kuechler, Jan Thomas; Kuehn, Susanne; Kugel, Andreas; Kuger, Fabian; Kuhl, Thorsten; Kukhtin, Victor; Kukla, Romain; Kulchitsky, Yuri; Kuleshov, Sergey; Kulinich, Yakov Petrovich; Kuna, Marine; Kunigo, Takuto; Kupco, Alexander; Kuprash, Oleg; Kurashige, Hisaya; Kurchaninov, Leonid; Kurochkin, Yurii; Kurth, Matthew Glenn; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; Kwan, Tony; Kyriazopoulos, Dimitrios; La Rosa, Alessandro; La Rosa Navarro, Jose Luis; La Rotonda, Laura; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Lammers, Sabine; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lanfermann, Marie Christine; Lang, Valerie Susanne; Lange, J örn Christian; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Lanza, Agostino; Lapertosa, Alessandro; Laplace, Sandrine; Laporte, Jean-Francois; Lari, Tommaso; Lasagni Manghi, Federico; Lassnig, Mario; Laurelli, Paolo; Lavrijsen, Wim; Law, Alexander; Laycock, Paul; Lazovich, Tomo; Lazzaroni, Massimo; Le, Brian; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Quilleuc, Eloi; LeBlanc, Matthew Edgar; LeCompte, Thomas; Ledroit-Guillon, Fabienne; Lee, Claire Alexandra; Lee, Graham Richard; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Benoit; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leight, William Axel; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzi, Bruno; Leone, Robert; Leone, Sandra; Leonidopoulos, Christos; Lerner, Giuseppe; Leroy, Claude; Lesage, Arthur; Lester, Christopher; Levchenko, Mikhail; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levy, Mark; Lewis, Dave; Li, Bing; Li, Changqiao; Li, Haifeng; Li, Liang; Li, Qi; Li, Shu; Li, Xingguo; Li, Yichen; Liang, Zhijun; Liberti, Barbara; Liblong, Aaron; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limosani, Antonio; Lin, Simon; Lin, Tai-Hua; Lindquist, Brian Edward; Lionti, Anthony Eric; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Hao; Liu, Hongbin; Liu, Jesse Kar Kee; Liu, Jian; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Minghui; Liu, Yanlin; Liu, Yanwen; Livan, Michele; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo, Cheuk Yee; Lo Sterzo, Francesco; Lobodzinska, Ewelina Maria; Loch, Peter; Loebinger, Fred; Loew, Kevin Michael; Loginov, Andrey; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Long, Brian Alexander; Long, Jonathan David; Long, Robin Eamonn; Longo, Luigi; Looper, Kristina Anne; Lopez, Jorge; Lopez Mateos, David; Lopez Paz, Ivan; Lopez Solis, Alvaro; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Lösel, Philipp Jonathan; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lu, Haonan; Lu, Nan; Lu, Yun-Ju; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Luedtke, Christian; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Olof; Lund-Jensen, Bengt; Luzi, Pierre Marc; Lynn, David; Lysak, Roman; Lytken, Else; Lyubushkin, Vladimir; Ma, Hong; Ma, Lian Liang; Ma, Yanhui; Maccarrone, Giovanni; Macchiolo, Anna; Macdonald, Calum Michael; Maček, Boštjan; Machado Miguens, Joana; Madaffari, Daniele; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeda, Junpei; Maeland, Steffen; Maeno, Tadashi; Maevskiy, Artem; Magradze, Erekle; Mahlstedt, Joern; Maiani, Camilla; Maidantchik, Carmen; Maier, Andreas Alexander; Maier, Thomas; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Malaescu, Bogdan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Claire; Maltezos, Stavros; Malyukov, Sergei; Mamuzic, Judita; Mancini, Giada; Mandelli, Luciano; Mandić, Igor; Maneira, José; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany; Mann, Alexander; Manousos, Athanasios; Mansoulie, Bruno; Mansour, Jason Dhia; Mantifel, Rodger; Mantoani, Matteo; Manzoni, Stefano; Mapelli, Livio; Marceca, Gino; March, Luis; Marchese, Luigi; Marchiori, Giovanni; Marcisovsky, Michal; Marjanovic, Marija; Marley, Daniel; Marroquim, Fernando; Marsden, Stephen Philip; Marshall, Zach; Martensson, Mikael; Marti-Garcia, Salvador; Martin, Christopher Blake; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Mario; Martinez Outschoorn, Verena; Martin-Haugh, Stewart; Martoiu, Victor Sorin; Martyniuk, Alex; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Lorenzo; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mättig, Peter; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Maznas, Ioannis; Mazza, Simone Michele; Mc Fadden, Neil Christopher; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McClymont, Laurie; McDonald, Emily; Mcfayden, Josh; Mchedlidze, Gvantsa; McMahon, Steve; McNamara, Peter Charles; McPherson, Robert; Meehan, Samuel; Megy, Theo Jean; Mehlhase, Sascha; Mehta, Andrew; Meideck, Thomas; Meier, Karlheinz; Meirose, Bernhard; Melini, Davide; Mellado Garcia, Bruce Rafael; Mellenthin, Johannes Donatus; Melo, Matej; Meloni, Federico; Menary, Stephen Burns; Meng, Lingxin; Meng, Xiangting; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mergelmeyer, Sebastian; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Meyer Zu Theenhausen, Hanno; Miano, Fabrizio; Middleton, Robin; Miglioranzi, Silvia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Milesi, Marco; Milic, Adriana; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Minaenko, Andrey; Minami, Yuto; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Minegishi, Yuji; Ming, Yao; Mir, Lluisa-Maria; Mistry, Khilesh; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Miucci, Antonio; Miyagawa, Paul; Mizukami, Atsushi; Mjörnmark, Jan-Ulf; Mkrtchyan, Tigran; Mlynarikova, Michaela; Moa, Torbjoern; Mochizuki, Kazuya; Mogg, Philipp; Mohapatra, Soumya; Molander, Simon; Moles-Valls, Regina; Monden, Ryutaro; Mondragon, Matthew Craig; Mönig, Klaus; Monk, James; Monnier, Emmanuel; Montalbano, Alyssa; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Morange, Nicolas; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Stefanie; Mori, Daniel; Mori, Tatsuya; Morii, Masahiro; Morinaga, Masahiro; Morisbak, Vanja; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Moschovakos, Paris; Mosidze, Maia; Moss, Harry James; Moss, Josh; Motohashi, Kazuki; Mount, Richard; Mountricha, Eleni; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Ralph Soeren Peter; Muenstermann, Daniel; Mullen, Paul; Mullier, Geoffrey; Munoz Sanchez, Francisca Javiela; Murray, Bill; Musheghyan, Haykuhi; Muškinja, Miha; Myagkov, Alexey; Myska, Miroslav; Nachman, Benjamin Philip; Nackenhorst, Olaf; Nagai, Koichi; Nagai, Ryo; Nagano, Kunihiro; Nagasaka, Yasushi; Nagata, Kazuki; Nagel, Martin; Nagy, Elemer; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Naranjo Garcia, Roger Felipe; Narayan, Rohin; Narrias Villar, Daniel Isaac; Naryshkin, Iouri; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Negri, Andrea; Negrini, Matteo; Nektarijevic, Snezana; Nellist, Clara; Nelson, Andrew; Nelson, Michael Edward; Nemecek, Stanislav; Nemethy, Peter; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Newman, Paul; Ng, Tsz Yu; Nguyen Manh, Tuan; Nickerson, Richard; Nicolaidou, Rosy; Nielsen, Jason; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolopoulos, Konstantinos; Nilsen, Jon Kerr; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nishu, Nishu; Nisius, Richard; Nobe, Takuya; Noguchi, Yohei; Nomachi, Masaharu; Nomidis, Ioannis; Nomura, Marcelo Ayumu; Nooney, Tamsin; Nordberg, Markus; Norjoharuddeen, Nurfikri; Novgorodova, Olga; Nowak, Sebastian; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nurse, Emily; Nuti, Francesco; O'connor, Kelsey; O'Neil, Dugan; O'Rourke, Abigail Alexandra; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Obermann, Theresa; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Ochoa-Ricoux, Juan Pedro; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohman, Henrik; Oide, Hideyuki; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Oleiro Seabra, Luis Filipe; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onogi, Kouta; Onyisi, Peter; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Owen, Mark; Owen, Rhys Edward; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; Pacheco Pages, Andres; Pacheco Rodriguez, Laura; Padilla Aranda, Cristobal; Pagan Griso, Simone; Paganini, Michela; Paige, Frank; Palacino, Gabriel; Palazzo, Serena; Palestini, Sandro; Palka, Marek; Pallin, Dominique; Panagiotopoulou, Evgenia; Panagoulias, Ilias; Pandini, Carlo Enrico; Panduro Vazquez, William; Pani, Priscilla; Panitkin, Sergey; Pantea, Dan; Paolozzi, Lorenzo; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Parker, Adam Jackson; Parker, Michael Andrew; Parker, Kerry Ann; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pascuzzi, Vincent; Pasner, Jacob Martin; Pasqualucci, Enrico; Passaggio, Stefano; Pastore, Francesca; Pataraia, Sophio; Pater, Joleen; Pauly, Thilo; Pearson, Benjamin; Pedraza Lopez, Sebastian; Pedro, Rute; Peleganchuk, Sergey; Penc, Ondrej; Peng, Cong; Peng, Haiping; Penwell, John; Peralva, Bernardo; Perego, Marta Maria; Perepelitsa, Dennis; Perini, Laura; Pernegger, Heinz; Perrella, Sabrina; Peschke, Richard; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petroff, Pierre; Petrolo, Emilio; Petrov, Mariyan; Petrucci, Fabrizio; Pettersson, Nora Emilia; Peyaud, Alan; Pezoa, Raquel; Phillips, Forrest Hays; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Pickering, Mark Andrew; Piegaia, Ricardo; Pilcher, James; Pilkington, Andrew; Pin, Arnaud Willy J; Pinamonti, Michele; Pinfold, James; Pirumov, Hayk; Pitt, Michael; Plazak, Lukas; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Pluth, Daniel; Podberezko, Pavel; Poettgen, Ruth; Poggi, Riccardo; Poggioli, Luc; Pohl, David-leon; Polesello, Giacomo; Poley, Anne-luise; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Pollard, Christopher Samuel; Polychronakos, Venetios; Pommès, Kathy; Ponomarenko, Daniil; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Poppleton, Alan; Pospisil, Stanislav; Potamianos, Karolos; Potrap, Igor; Potter, Christina; Poulard, Gilbert; Poulsen, Trine; Poveda, Joaquin; Pozo Astigarraga, Mikel Eukeni; Pralavorio, Pascal; Pranko, Aliaksandr; Prell, Soeren; Price, Darren; Price, Lawrence; Primavera, Margherita; Prince, Sebastien; Proklova, Nadezda; Prokofiev, Kirill; Prokoshin, Fedor; Protopopescu, Serban; Proudfoot, James; Przybycien, Mariusz; Puri, Akshat; Puzo, Patrick; Qian, Jianming; Qin, Gang; Qin, Yang; Quadt, Arnulf; Queitsch-Maitland, Michaela; Quilty, Donnchadha; Raddum, Silje; Radeka, Veljko; Radescu, Voica; Radhakrishnan, Sooraj Krishnan; Radloff, Peter; Rados, Pere; Ragusa, Francesco; Rahal, Ghita; Raine, John Andrew; Rajagopalan, Srinivasan; Rangel-Smith, Camila; Rashid, Tasneem; Ratti, Maria Giulia; Rauch, Daniel; Rauscher, Felix; Rave, Stefan; Ravinovich, Ilia; Rawling, Jacob Henry; Raymond, Michel; Read, Alexander Lincoln; Readioff, Nathan Peter; Reale, Marilea; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reed, Robert; Reeves, Kendall; Rehnisch, Laura; Reichert, Joseph; Reiss, Andreas; Rembser, Christoph; Ren, Huan; Rescigno, Marco; Resconi, Silvia; Resseguie, Elodie Deborah; Rettie, Sebastien; Reynolds, Elliot; Rezanova, Olga; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Richter, Stefan; Richter-Was, Elzbieta; Ricken, Oliver; Ridel, Melissa; Rieck, Patrick; Riegel, Christian Johann; Rieger, Julia; Rifki, Othmane; Rijssenbeek, Michael; Rimoldi, Adele; Rimoldi, Marco; Rinaldi, Lorenzo; Ristić, Branislav; Ritsch, Elmar; Riu, Imma; Rizatdinova, Flera; Rizvi, Eram; Rizzi, Chiara; Roberts, Rhys Thomas; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Rocco, Elena; Roda, Chiara; Rodina, Yulia; Rodriguez Bosca, Sergi; Rodriguez Perez, Andrea; Rodriguez Rodriguez, Daniel; Roe, Shaun; Rogan, Christopher Sean; Røhne, Ole; Roloff, Jennifer; Romaniouk, Anatoli; Romano, Marino; Romano Saez, Silvestre Marino; Romero Adam, Elena; Rompotis, Nikolaos; Ronzani, Manfredi; Roos, Lydia; Rosati, Stefano; Rosbach, Kilian; Rose, Peyton; Rosien, Nils-Arne; Rossi, Elvira; Rossi, Leonardo Paolo; Rosten, Jonatan; Rosten, Rachel; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Rozanov, Alexandre; Rozen, Yoram; Ruan, Xifeng; Rubbo, Francesco; Rühr, Frederik; Ruiz-Martinez, Aranzazu; Rurikova, Zuzana; Rusakovich, Nikolai; Russell, Heather; Rutherfoord, John; Ruthmann, Nils; Ryabov, Yury; Rybar, Martin; Rybkin, Grigori; Ryu, Soo; Ryzhov, Andrey; Rzehorz, Gerhard Ferdinand; Saavedra, Aldo; Sabato, Gabriele; Sacerdoti, Sabrina; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Saha, Puja; Sahinsoy, Merve; Saimpert, Matthias; Saito, Masahiko; Saito, Tomoyuki; Sakamoto, Hiroshi; Sakurai, Yuki; Salamanna, Giuseppe; Salazar Loyola, Javier Esteban; Salek, David; Sales De Bruin, Pedro Henrique; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sammel, Dirk; Sampsonidis, Dimitrios; Sampsonidou, Despoina; Sánchez, Javier; Sanchez Martinez, Victoria; Sanchez Pineda, Arturo Rodolfo; Sandaker, Heidi; Sandbach, Ruth Laura; Sander, Christian Oliver; Sandhoff, Marisa; Sandoval, Carlos; Sankey, Dave; Sannino, Mario; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapronov, Andrey; Saraiva, João; Sarrazin, Bjorn; Sasaki, Osamu; Sato, Koji; Sauvan, Emmanuel; Savage, Graham; Savard, Pierre; Savic, Natascha; Sawyer, Craig; Sawyer, Lee; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scanlon, Tim; Scannicchio, Diana; Scarcella, Mark; Scarfone, Valerio; Schaarschmidt, Jana; Schacht, Peter; Schachtner, Balthasar Maria; Schaefer, Douglas; Schaefer, Leigh; Schaefer, Ralph; Schaeffer, Jan; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R Dean; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Schiavi, Carlo; Schier, Sheena; Schildgen, Lara Katharina; Schillo, Christian; Schioppa, Marco; Schlenker, Stefan; Schmidt-Sommerfeld, Korbinian Ralf; Schmieden, Kristof; Schmitt, Christian; Schmitt, Stefan; Schmitz, Simon; Schnoor, Ulrike; Schoeffel, Laurent; Schoening, Andre; Schoenrock, Bradley Daniel; Schopf, Elisabeth; Schott, Matthias; Schouwenberg, Jeroen; Schovancova, Jaroslava; Schramm, Steven; Schuh, Natascha; Schulte, Alexandra; Schultens, Martin Johannes; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwartzman, Ariel; Schwarz, Thomas Andrew; Schweiger, Hansdieter; Schwemling, Philippe; Schwienhorst, Reinhard; Schwindling, Jerome; Sciandra, Andrea; Sciolla, Gabriella; Scuri, Fabrizio; Scutti, Federico; Searcy, Jacob; Seema, Pienpen; Seidel, Sally; Seiden, Abraham; Seixas, José; Sekhniaidze, Givi; Sekhon, Karishma; Sekula, Stephen; Semprini-Cesari, Nicola; Senkin, Sergey; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Sessa, Marco; Seuster, Rolf; Severini, Horst; Sfiligoj, Tina; Sforza, Federico; Sfyrla, Anna; Shabalina, Elizaveta; Shaikh, Nabila Wahab; Shan, Lianyou; Shang, Ruo-yu; Shank, James; Shapiro, Marjorie; Shatalov, Pavel; Shaw, Kate; Shaw, Savanna Marie; Shcherbakova, Anna; Shehu, Ciwake Yusufu; Shen, Yu-Ting; Sherwood, Peter; Shi, Liaoshan; Shimizu, Shima; Shimmin, Chase Owen; Shimojima, Makoto; Shipsey, Ian Peter Joseph; Shirabe, Shohei; Shiyakova, Mariya; Shlomi, Jonathan; Shmeleva, Alevtina; Shoaleh Saadi, Diane; Shochet, Mel; Shojaii, Seyed Ruhollah; Shope, David Richard; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Sicho, Petr; Sickles, Anne Marie; Sidebo, Per Edvin; Sideras Haddad, Elias; Sidiropoulou, Ourania; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silva, José; Silverstein, Samuel; Simak, Vladislav; Simic, Ljiljana; Simion, Stefan; Simioni, Eduard; Simmons, Brinick; Simon, Manuel; Sinervo, Pekka; Sinev, Nikolai; Sioli, Maximiliano; Siragusa, Giovanni; Siral, Ismet; Sivoklokov, Serguei; Sjölin, Jörgen; Skinner, Malcolm Bruce; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Slawinska, Magdalena; Sliwa, Krzysztof; Slovak, Radim; Smakhtin, Vladimir; Smart, Ben; Smiesko, Juraj; Smirnov, Nikita; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Joshua Wyatt; Smith, Matthew; Smith, Russell; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snyder, Ian Michael; Snyder, Scott; Sobie, Randall; Socher, Felix; Soffer, Abner; Soh, Dart-yin; Sokhrannyi, Grygorii; Solans Sanchez, Carlos; Solar, Michael; Soldatov, Evgeny; Soldevila, Urmila; Solodkov, Alexander; Soloshenko, Alexei; Solovyanov, Oleg; Solovyev, Victor; Sommer, Philip; Son, Hyungsuk; Song, Hong Ye; Sopczak, Andre; Sosa, David; Sotiropoulou, Calliope Louisa; Soualah, Rachik; Soukharev, Andrey; South, David; Sowden, Benjamin; Spagnolo, Stefania; Spalla, Margherita; Spangenberg, Martin; Spanò, Francesco; Sperlich, Dennis; Spettel, Fabian; Spieker, Thomas Malte; Spighi, Roberto; Spigo, Giancarlo; Spiller, Laurence Anthony; Spousta, Martin; St Denis, Richard Dante; Stabile, Alberto; Stamen, Rainer; Stamm, Soren; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Giordon; Stark, Jan; Stark, Simon Holm; Staroba, Pavel; Starovoitov, Pavel; Stärz, Steffen; Staszewski, Rafal; Steinberg, Peter; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stewart, Graeme; Stockton, Mark; Stoebe, Michael; Stoicea, Gabriel; Stolte, Philipp; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Stramaglia, Maria Elena; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Stroynowski, Ryszard; Strubig, Antonia; Stucci, Stefania Antonia; Stugu, Bjarne; Styles, Nicholas Adam; Su, Dong; Su, Jun; Suchek, Stanislav; Sugaya, Yorihito; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Siyuan; Sun, Xiaohu; Suruliz, Kerim; Suster, Carl; Sutton, Mark; Suzuki, Shota; Svatos, Michal; Swiatlowski, Maximilian; Swift, Stewart Patrick; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Tackmann, Kerstin; Taenzer, Joe; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takai, Helio; Takashima, Ryuichi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tanaka, Junichi; Tanaka, Masahiro; Tanaka, Reisaburo; Tanaka, Shuji; Tanioka, Ryo; Tannenwald, Benjamin Bordy; Tapia Araya, Sebastian; Tapprogge, Stefan; Tarem, Shlomit; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tavares Delgado, Ademar; Tayalati, Yahya; Taylor, Aaron; Taylor, Geoffrey; Taylor, Pierre Thor Elliot; Taylor, Wendy; Teixeira-Dias, Pedro; Temple, Darren; Ten Kate, Herman; Teng, Ping-Kun; Teoh, Jia Jian; Tepel, Fabian-Phillipp; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Theveneaux-Pelzer, Timothée; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Paul; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Tibbetts, Mark James; Ticse Torres, Royer Edson; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tipton, Paul; Tisserant, Sylvain; Todome, Kazuki; Todorova-Nova, Sharka; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tolley, Emma; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Tong, Baojia(Tony); Tornambe, Peter; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Treado, Colleen Jennifer; Trefzger, Thomas; Tresoldi, Fabio; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Tripiana, Martin; Trischuk, William; Trocmé, Benjamin; Trofymov, Artur; Troncon, Clara; Trottier-McDonald, Michel; Trovatelli, Monica; Truong, Loan; Trzebinski, Maciej; Trzupek, Adam; Tsang, Ka Wa; Tseng, Jeffrey; Tsiareshka, Pavel; Tsipolitis, Georgios; Tsirintanis, Nikolaos; Tsiskaridze, Shota; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsui, Ka Ming; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsuno, Soshi; Tsybychev, Dmitri; Tu, Yanjun; Tudorache, Alexandra; Tudorache, Valentina; Tulbure, Traian Tiberiu; Tuna, Alexander Naip; Tupputi, Salvatore; Turchikhin, Semen; Turgeman, Daniel; Turk Cakir, Ilkay; Turra, Ruggero; Tuts, Michael; Ucchielli, Giulia; Ueda, Ikuo; Ughetto, Michael; Ukegawa, Fumihiko; Unal, Guillaume; Undrus, Alexander; Unel, Gokhan; Ungaro, Francesca; Unno, Yoshinobu; Unverdorben, Christopher; Urban, Jozef; Urquijo, Phillip; Urrejola, Pedro; Usai, Giulio; Usui, Junya; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Valderanis, Chrysostomos; Valdes Santurio, Eduardo; Valentinetti, Sara; Valero, Alberto; Valéry, Lo\\"ic; Valkar, Stefan; Vallier, Alexis; Valls Ferrer, Juan Antonio; Van Den Wollenberg, Wouter; van der Graaf, Harry; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; van Woerden, Marius Cornelis; Vanadia, Marco; Vandelli, Wainer; Vaniachine, Alexandre; Vankov, Peter; Vardanyan, Gagik; Vari, Riccardo; Varnes, Erich; Varni, Carlo; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vasquez, Jared Gregory; Vasquez, Gerardo; Vazeille, Francois; Vazquez Schroeder, Tamara; Veatch, Jason; Veeraraghavan, Venkatesh; Veloce, Laurelle Maria; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Venturi, Manuela; Venturi, Nicola; Venturini, Alessio; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vetterli, Michel; Viaux Maira, Nicolas; Viazlo, Oleksandr; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Vigani, Luigi; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinogradov, Vladimir; Vishwakarma, Akanksha; Vittori, Camilla; Vivarelli, Iacopo; Vlachos, Sotirios; Vlasak, Michal; Vogel, Marcelo; Vokac, Petr; Volpi, Guido; von der Schmitt, Hans; von Toerne, Eckhard; Vorobel, Vit; Vorobev, Konstantin; Vos, Marcel; Voss, Rudiger; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vuillermet, Raphael; Vukotic, Ilija; Wagner, Peter; Wagner, Wolfgang; Wagner-Kuhr, Jeannine; Wahlberg, Hernan; Wahrmund, Sebastian; Wakabayashi, Jun; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wallangen, Veronica; Wang, Chao; Wang, Chao; Wang, Fuquan; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Qing; Wang, Rui; Wang, Song-Ming; Wang, Tingting; Wang, Wei; Wang, Wenxiao; Wang, Zirui; Wanotayaroj, Chaowaroj; Warburton, Andreas; Ward, Patricia; Wardrope, David Robert; Washbrook, Andrew; Watkins, Peter; Watson, Alan; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Ben; Webb, Aaron Foley; Webb, Samuel; Weber, Michele; Weber, Stefan Wolf; Weber, Stephen; Webster, Jordan S; Weidberg, Anthony; Weinert, Benjamin; Weingarten, Jens; Weirich, Marcel; Weiser, Christian; Weits, Hartger; Wells, Phillippa; Wenaus, Torre; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Michael David; Werner, Per; Wessels, Martin; Whalen, Kathleen; Whallon, Nikola Lazar; Wharton, Andrew Mark; White, Aaron; White, Andrew; White, Martin; White, Ryan; Whiteson, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wiglesworth, Craig; Wiik-Fuchs, Liv Antje Mari; Wildauer, Andreas; Wilk, Fabian; Wilkens, Henric George; Williams, Hugh; Williams, Sarah; Willis, Christopher; Willocq, Stephane; Wilson, John; Wingerter-Seez, Isabelle; Winkels, Emma; Winklmeier, Frank; Winston, Oliver James; Winter, Benedict Tobias; Wittgen, Matthias; Wobisch, Markus; Wolf, Tim Michael Heinz; Wolff, Robert; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wong, Vincent Wai Sum; Worm, Steven; Wosiek, Barbara; Wotschack, Jorg; Wozniak, Krzysztof; Wu, Miles; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wyatt, Terry Richard; Wynne, Benjamin; Xella, Stefania; Xi, Zhaoxu; Xia, Ligang; Xu, Da; Xu, Lailin; Yabsley, Bruce; Yacoob, Sahal; Yamaguchi, Daiki; Yamaguchi, Yohei; Yamamoto, Akira; Yamamoto, Shimpei; Yamanaka, Takashi; Yamauchi, Katsuya; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Hongtao; Yang, Yi; Yang, Zongchang; Yao, Weiming; Yap, Yee Chinn; Yasu, Yoshiji; Yatsenko, Elena; Yau Wong, Kaven Henry; Ye, Jingbo; Ye, Shuwei; Yeletskikh, Ivan; Yigitbasi, Efe; Yildirim, Eda; Yorita, Kohei; Yoshihara, Keisuke; Young, Charles; Young, Christopher John; Yu, David Ren-Hwa; Yu, Jaehoon; Yu, Jie; Yuen, Stephanie P; Yusuff, Imran; Zabinski, Bartlomiej; Zacharis, Georgios; Zaidan, Remi; Zaitsev, Alexander; Zakharchuk, Nataliia; Zalieckas, Justas; Zaman, Aungshuman; Zambito, Stefano; Zanzi, Daniele; Zeitnitz, Christian; Zemla, Andrzej; Zeng, Jian Cong; Zeng, Qi; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zhang, Dongliang; Zhang, Fangzhou; Zhang, Guangyi; Zhang, Huijun; Zhang, Jinlong; Zhang, Lei; Zhang, Liqing; Zhang, Matt; Zhang, Peng; Zhang, Rui; Zhang, Ruiqi; Zhang, Xueyao; Zhang, Yu; Zhang, Zhiqing; Zhao, Xiandong; Zhao, Yongke; Zhao, Zhengguo; Zhemchugov, Alexey; Zhou, Bing; Zhou, Chen; Zhou, Li; Zhou, Maosen; Zhou, Mingliang; Zhou, Ning; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhukov, Konstantin; Zibell, Andre; Zieminska, Daria; Zimine, Nikolai; Zimmermann, Christoph; Zimmermann, Stephanie; Zinonos, Zinonas; Zinser, Markus; Ziolkowski, Michael; Živković, Lidija; Zobernig, Georg; Zoccoli, Antonio; Zou, Rui; zur Nedden, Martin; Zwalinski, Lukasz

    2017-06-26

    Multi-particle cumulants and corresponding Fourier harmonics are measured for azimuthal angle distributions of charged particles in $pp$ collisions at $\\sqrt{s}$ = 5.02 and 13 TeV and in $p$+Pb collisions at $\\sqrt{s_{NN}}$ = 5.02 TeV, and compared to the results obtained for low-multiplicity Pb+Pb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV. These measurements aim to assess the collective nature of particle production. The measurements of multi-particle cumulants confirm the evidence for collective phenomena in $p$+Pb and low-multiplicity Pb+Pb collisions. On the other hand, the $pp$ results for four-particle cumulants do not demonstrate collective behaviour, indicating that they may be biased by contributions from non-flow correlations. A comparison of multi-particle cumulants and derived Fourier harmonics across different collision systems is presented as a function of the charged-particle multiplicity. For a given multiplicity, the measured Fourier harmonics are largest in Pb+Pb, smaller in $p$+Pb and smal...

  15. Adhesion molecules levels in blood correlate with MRI activity and clinical activity in multiple sclerosis

    International Nuclear Information System (INIS)

    Millers, A.; Enina, G.; Platkajis, A.; Metra, M.; Kukaine, R.

    2002-01-01

    Research into pathogenesis of multiple sclerosis (MS) has prompted efforts to identify immunological markers associated with disease activity. Adhesion molecules ICAM-1 and VCAM-1 are associated with inflammatory mediated blood-brain barrier (BBB) dysfunction. In this study investigates the correlation between blood level of circulating ICAM-1 and VCAM-1 and magnetic resonance imaging (MRI) activity in different clinical phases of patients with MS. We show that RRMS and SPMS patients in clinically active phase with Gd-enhancing lesions in CNS had higher blood levels of cICAM-1 and cVCAM-1 compared these parameters levers of RRMS patients in remission stage. These results suggest that cICAM-1 and cVCAM-1 is a sensitive indicator of disease activity associated with BBB inflammatory dysfunction. Elevated blood level of cICAM-1 more strongly correlated with clinical activity and BBB damage, than cVCAM-1 and that could be used as biological marker of disease activity. Circulating VCAM-1 as an early indicator of BBB disturbance, may also serve as marker of beneficial activity in relapses phase of MS course. (authors)

  16. Dataset - Adviesregel PPL 2010

    NARCIS (Netherlands)

    Evert, van F.K.; Schans, van der D.A.; Geel, van W.C.A.; Slabbekoorn, J.J.; Booij, R.; Jukema, J.N.; Meurs, E.J.J.; Uenk, D.

    2011-01-01

    This dataset contains experimental data from a number of field experiments with potato in The Netherlands (Van Evert et al., 2011). The data are presented as an SQL dump of a PostgreSQL database (version 8.4.4). An outline of the entity-relationship diagram of the database is given in an

  17. Tension in the recent Type Ia supernovae datasets

    International Nuclear Information System (INIS)

    Wei, Hao

    2010-01-01

    In the present work, we investigate the tension in the recent Type Ia supernovae (SNIa) datasets Constitution and Union. We show that they are in tension not only with the observations of the cosmic microwave background (CMB) anisotropy and the baryon acoustic oscillations (BAO), but also with other SNIa datasets such as Davis and SNLS. Then, we find the main sources responsible for the tension. Further, we make this more robust by employing the method of random truncation. Based on the results of this work, we suggest two truncated versions of the Union and Constitution datasets, namely the UnionT and ConstitutionT SNIa samples, whose behaviors are more regular.

  18. Viability of Controlling Prosthetic Hand Utilizing Electroencephalograph (EEG) Dataset Signal

    Science.gov (United States)

    Miskon, Azizi; A/L Thanakodi, Suresh; Raihan Mazlan, Mohd; Mohd Haziq Azhar, Satria; Nooraya Mohd Tawil, Siti

    2016-11-01

    This project presents the development of an artificial hand controlled by Electroencephalograph (EEG) signal datasets for the prosthetic application. The EEG signal datasets were used as to improvise the way to control the prosthetic hand compared to the Electromyograph (EMG). The EMG has disadvantages to a person, who has not used the muscle for a long time and also to person with degenerative issues due to age factor. Thus, the EEG datasets found to be an alternative for EMG. The datasets used in this work were taken from Brain Computer Interface (BCI) Project. The datasets were already classified for open, close and combined movement operations. It served the purpose as an input to control the prosthetic hand by using an Interface system between Microsoft Visual Studio and Arduino. The obtained results reveal the prosthetic hand to be more efficient and faster in response to the EEG datasets with an additional LiPo (Lithium Polymer) battery attached to the prosthetic. Some limitations were also identified in terms of the hand movements, weight of the prosthetic, and the suggestions to improve were concluded in this paper. Overall, the objective of this paper were achieved when the prosthetic hand found to be feasible in operation utilizing the EEG datasets.

  19. Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

    Science.gov (United States)

    Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

    2012-01-01

    The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

  20. Technical note: An inorganic water chemistry dataset (1972–2011 ...

    African Journals Online (AJOL)

    A national dataset of inorganic chemical data of surface waters (rivers, lakes, and dams) in South Africa is presented and made freely available. The dataset comprises more than 500 000 complete water analyses from 1972 up to 2011, collected from more than 2 000 sample monitoring stations in South Africa. The dataset ...

  1. A multi-dataset time-reversal approach to clinical trial placebo response and the relationship to natural variability in epilepsy.

    Science.gov (United States)

    Goldenholz, Daniel M; Strashny, Alex; Cook, Mark; Moss, Robert; Theodore, William H

    2017-12-01

    Clinical epilepsy drug trials have been measuring increasingly high placebo response rates, up to 40%. This study was designed to examine the relationship between the natural variability in epilepsy, and the placebo response seen in trials. We tested the hypothesis that 'reversing' trial direction, with the baseline period as the treatment observation phase, would reveal effects of natural variability. Clinical trial simulations were run with time running forward and in reverse. Data sources were: SeizureTracker.com (patient reported diaries), a randomized sham-controlled TMS trial, and chronically implanted intracranial EEG electrodes. Outcomes were 50%-responder rates (RR50) and median percentage change (MPC). The RR50 results showed evidence that temporal reversal does not prevent large responder rates across datasets. The MPC results negative in the TMS dataset, and positive in the other two. Typical RR50s of clinical trials can be reproduced using the natural variability of epilepsy as a substrate across multiple datasets. Therefore, the placebo response in epilepsy clinical trials may be attributable almost entirely to this variability, rather than the "placebo effect". Published by Elsevier Ltd.

  2. Ontology-aided feature correlation for multi-modal urban sensing

    Science.gov (United States)

    Misra, Archan; Lantra, Zaman; Jayarajah, Kasthuri

    2016-05-01

    The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

  3. Multiple soft limits of cosmological correlation functions

    International Nuclear Information System (INIS)

    Joyce, Austin; Khoury, Justin; Simonović, Marko

    2015-01-01

    We derive novel identities satisfied by inflationary correlation functions in the limit where two external momenta are taken to be small. We derive these statements in two ways: using background-wave arguments and as Ward identities following from the fixed-time path integral. Interestingly, these identities allow us to constrain some of the O(q 2 ) components of the soft limit, in contrast to their single-soft analogues. We provide several nontrivial checks of our identities both in the context of resonant non-Gaussianities and in small sound speed models. Additionally, we extend the relation at lowest order in external momenta to arbitrarily many soft legs, and comment on the many-soft extension at higher orders in the soft momentum. Finally, we consider how higher soft limits lead to identities satisfied by correlation functions in large-scale structure

  4. Wind and wave dataset for Matara, Sri Lanka

    Science.gov (United States)

    Luo, Yao; Wang, Dongxiao; Priyadarshana Gamage, Tilak; Zhou, Fenghua; Madusanka Widanage, Charith; Liu, Taiwei

    2018-01-01

    We present a continuous in situ hydro-meteorology observational dataset from a set of instruments first deployed in December 2012 in the south of Sri Lanka, facing toward the north Indian Ocean. In these waters, simultaneous records of wind and wave data are sparse due to difficulties in deploying measurement instruments, although the area hosts one of the busiest shipping lanes in the world. This study describes the survey, deployment, and measurements of wind and waves, with the aim of offering future users of the dataset the most comprehensive and as much information as possible. This dataset advances our understanding of the nearshore hydrodynamic processes and wave climate, including sea waves and swells, in the north Indian Ocean. Moreover, it is a valuable resource for ocean model parameterization and validation. The archived dataset (Table 1) is examined in detail, including wave data at two locations with water depths of 20 and 10 m comprising synchronous time series of wind, ocean astronomical tide, air pressure, etc. In addition, we use these wave observations to evaluate the ERA-Interim reanalysis product. Based on Buoy 2 data, the swells are the main component of waves year-round, although monsoons can markedly alter the proportion between swell and wind sea. The dataset (Luo et al., 2017) is publicly available from Science Data Bank (https://doi.org/10.11922/sciencedb.447).

  5. Wind and wave dataset for Matara, Sri Lanka

    Directory of Open Access Journals (Sweden)

    Y. Luo

    2018-01-01

    Full Text Available We present a continuous in situ hydro-meteorology observational dataset from a set of instruments first deployed in December 2012 in the south of Sri Lanka, facing toward the north Indian Ocean. In these waters, simultaneous records of wind and wave data are sparse due to difficulties in deploying measurement instruments, although the area hosts one of the busiest shipping lanes in the world. This study describes the survey, deployment, and measurements of wind and waves, with the aim of offering future users of the dataset the most comprehensive and as much information as possible. This dataset advances our understanding of the nearshore hydrodynamic processes and wave climate, including sea waves and swells, in the north Indian Ocean. Moreover, it is a valuable resource for ocean model parameterization and validation. The archived dataset (Table 1 is examined in detail, including wave data at two locations with water depths of 20 and 10 m comprising synchronous time series of wind, ocean astronomical tide, air pressure, etc. In addition, we use these wave observations to evaluate the ERA-Interim reanalysis product. Based on Buoy 2 data, the swells are the main component of waves year-round, although monsoons can markedly alter the proportion between swell and wind sea. The dataset (Luo et al., 2017 is publicly available from Science Data Bank (https://doi.org/10.11922/sciencedb.447.

  6. Heuristics for Relevancy Ranking of Earth Dataset Search Results

    Science.gov (United States)

    Lynnes, Christopher; Quinn, Patrick; Norton, James

    2016-01-01

    As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

  7. QSAR ligand dataset for modelling mutagenicity, genotoxicity, and rodent carcinogenicity

    Directory of Open Access Journals (Sweden)

    Davy Guan

    2018-04-01

    Full Text Available Five datasets were constructed from ligand and bioassay result data from the literature. These datasets include bioassay results from the Ames mutagenicity assay, Greenscreen GADD-45a-GFP assay, Syrian Hamster Embryo (SHE assay, and 2 year rat carcinogenicity assay results. These datasets provide information about chemical mutagenicity, genotoxicity and carcinogenicity.

  8. The Dataset of Countries at Risk of Electoral Violence

    OpenAIRE

    Birch, Sarah; Muchlinski, David

    2017-01-01

    Electoral violence is increasingly affecting elections around the world, yet researchers have been limited by a paucity of granular data on this phenomenon. This paper introduces and describes a new dataset of electoral violence – the Dataset of Countries at Risk of Electoral Violence (CREV) – that provides measures of 10 different types of electoral violence across 642 elections held around the globe between 1995 and 2013. The paper provides a detailed account of how and why the dataset was ...

  9. Toward computational cumulative biology by combining models of biological datasets.

    Science.gov (United States)

    Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

    2014-01-01

    A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations-for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database.

  10. A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits.

    Science.gov (United States)

    Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

    2017-01-01

    Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.

  11. Using kittens to unlock photo-sharing website datasets for environmental applications

    Science.gov (United States)

    Gascoin, Simon

    2016-04-01

    Mining photo-sharing websites is a promising approach to complement in situ and satellite observations of the environment, however a challenge is to deal with the large degree of noise inherent to online social datasets. Here I explored the value of the Flickr image hosting website database to monitor the snow cover in the Pyrenees. Using the Flickr application programming interface (API) I queried all the public images metadata tagged at least with one of the following words: "snow", "neige", "nieve", "neu" (snow in French, Spanish and Catalan languages). The search was limited to the geo-tagged pictures taken in the Pyrenees area. However, the number of public pictures available in the Flickr database for a given time interval depends on several factors, including the Flickr website popularity and the development of digital photography. Thus, I also searched for all Flickr images tagged with "chat", "gat" or "gato" (cat in French, Spanish and Catalan languages). The tag "cat" was not considered in order to exclude the results from North America where Flickr got popular earlier than in Europe. The number of "cat" images per month was used to fit a model of the number of images uploaded in Flickr with time. This model was used to remove this trend in the numbers of snow-tagged photographs. The resulting time series was compared to a time series of the snow cover area derived from the MODIS satellite over the same region. Both datasets are well correlated; in particular they exhibit the same seasonal evolution, although the inter-annual variabilities are less similar. I will also discuss which other factors may explain the main discrepancies in order to further decrease the noise in the Flickr dataset.

  12. Reconstructing missing information on precipitation datasets: impact of tails on adopted statistical distributions.

    Science.gov (United States)

    Pedretti, Daniele; Beckie, Roger Daniel

    2014-05-01

    Missing data in hydrological time-series databases are ubiquitous in practical applications, yet it is of fundamental importance to make educated decisions in problems involving exhaustive time-series knowledge. This includes precipitation datasets, since recording or human failures can produce gaps in these time series. For some applications, directly involving the ratio between precipitation and some other quantity, lack of complete information can result in poor understanding of basic physical and chemical dynamics involving precipitated water. For instance, the ratio between precipitation (recharge) and outflow rates at a discharge point of an aquifer (e.g. rivers, pumping wells, lysimeters) can be used to obtain aquifer parameters and thus to constrain model-based predictions. We tested a suite of methodologies to reconstruct missing information in rainfall datasets. The goal was to obtain a suitable and versatile method to reduce the errors given by the lack of data in specific time windows. Our analyses included both a classical chronologically-pairing approach between rainfall stations and a probability-based approached, which accounted for the probability of exceedence of rain depths measured at two or multiple stations. Our analyses proved that it is not clear a priori which method delivers the best methodology. Rather, this selection should be based considering the specific statistical properties of the rainfall dataset. In this presentation, our emphasis is to discuss the effects of a few typical parametric distributions used to model the behavior of rainfall. Specifically, we analyzed the role of distributional "tails", which have an important control on the occurrence of extreme rainfall events. The latter strongly affect several hydrological applications, including recharge-discharge relationships. The heavy-tailed distributions we considered were parametric Log-Normal, Generalized Pareto, Generalized Extreme and Gamma distributions. The methods were

  13. Variability of interconnected wind plants: correlation length and its dependence on variability time scale

    Science.gov (United States)

    St. Martin, Clara M.; Lundquist, Julie K.; Handschy, Mark A.

    2015-04-01

    The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. But how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer ‘how far is far enough,’ we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25-2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high

  14. 3DSEM: A 3D microscopy dataset

    Directory of Open Access Journals (Sweden)

    Ahmad P. Tafti

    2016-03-01

    Full Text Available The Scanning Electron Microscope (SEM as a 2D imaging instrument has been widely used in many scientific disciplines including biological, mechanical, and materials sciences to determine the surface attributes of microscopic objects. However the SEM micrographs still remain 2D images. To effectively measure and visualize the surface properties, we need to truly restore the 3D shape model from 2D SEM images. Having 3D surfaces would provide anatomic shape of micro-samples which allows for quantitative measurements and informative visualization of the specimens being investigated. The 3DSEM is a dataset for 3D microscopy vision which is freely available at [1] for any academic, educational, and research purposes. The dataset includes both 2D images and 3D reconstructed surfaces of several real microscopic samples. Keywords: 3D microscopy dataset, 3D microscopy vision, 3D SEM surface reconstruction, Scanning Electron Microscope (SEM

  15. Active Semisupervised Clustering Algorithm with Label Propagation for Imbalanced and Multidensity Datasets

    Directory of Open Access Journals (Sweden)

    Mingwei Leng

    2013-01-01

    Full Text Available The accuracy of most of the existing semisupervised clustering algorithms based on small size of labeled dataset is low when dealing with multidensity and imbalanced datasets, and labeling data is quite expensive and time consuming in many real-world applications. This paper focuses on active data selection and semisupervised clustering algorithm in multidensity and imbalanced datasets and proposes an active semisupervised clustering algorithm. The proposed algorithm uses an active mechanism for data selection to minimize the amount of labeled data, and it utilizes multithreshold to expand labeled datasets on multidensity and imbalanced datasets. Three standard datasets and one synthetic dataset are used to demonstrate the proposed algorithm, and the experimental results show that the proposed semisupervised clustering algorithm has a higher accuracy and a more stable performance in comparison to other clustering and semisupervised clustering algorithms, especially when the datasets are multidensity and imbalanced.

  16. A reanalysis dataset of the South China Sea

    Science.gov (United States)

    Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

    2014-01-01

    Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992–2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability. PMID:25977803

  17. A dataset of forest biomass structure for Eurasia.

    Science.gov (United States)

    Schepaschenko, Dmitry; Shvidenko, Anatoly; Usoltsev, Vladimir; Lakyda, Petro; Luo, Yunjian; Vasylyshyn, Roman; Lakyda, Ivan; Myklush, Yuriy; See, Linda; McCallum, Ian; Fritz, Steffen; Kraxner, Florian; Obersteiner, Michael

    2017-05-16

    The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

  18. A Dataset for Visual Navigation with Neuromorphic Methods

    Directory of Open Access Journals (Sweden)

    Francisco eBarranco

    2016-02-01

    Full Text Available Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we want to enhance the visibility of event-driven vision and increase its impact, we will need benchmarks that allow comparison among different neuromorphic methods as well as comparison to Computer Vision conventional approaches. We present datasets to evaluate the accuracy of frame-free and frame-based approaches for tasks of visual navigation. Similar to conventional Computer Vision datasets, we provide synthetic and real scenes, with the synthetic data created with graphics packages, and the real data recorded using a mobile robotic platform carrying a dynamic and active pixel vision sensor (DAVIS and an RGB+Depth sensor. For both datasets the cameras move with a rigid motion in a static scene, and the data includes the images, events, optic flow, 3D camera motion, and the depth of the scene, along with calibration procedures. Finally, we also provide simulated event data generated synthetically from well-known frame-based optical flow datasets.

  19. Correlations of Fecal Metabonomic and Microbiomic Changes Induced by High-fat Diet in the Pre-Obesity State

    Science.gov (United States)

    Lin, Hong; An, Yanpeng; Hao, Fuhua; Wang, Yulan; Tang, Huiru

    2016-02-01

    Obesity resulting from interactions of genetic and environmental factors becomes a serious public health problem worldwide with alterations of the metabolic phenotypes in multiple biological matrices involving multiple metabolic pathways. To understand the contributions of gut microbiota to obesity development, we analyzed dynamic alterations in fecal metabonomic phenotype using NMR and fecal microorganism composition in rats using pyrosequencing technology during the high-fat diet (HFD) feeding for 81 days (pre-obesity state). Integrated analysis of these two phenotypic datasets was further conducted to establish correlations between the altered rat fecal metabonome and gut microbiome. We found that one-week HFD feeding already caused significant changes in rat fecal metabonome and such changes sustained throughout 81-days feeding with the host and gut microbiota co-metabolites clearly featured. We also found that HFD caused outstanding decreases in most fecal metabolites implying enhancement of gut absorptions. We further established comprehensive correlations between the HFD-induced changes in fecal metabonome and fecal microbial composition indicating contributions of gut microbiota in pathogenesis and progression of the HFD-induced obesity. These findings provided essential information about the functions of gut microbiota in pathogenesis of metabolic disorders which could be potentially important for developing obesity prevention and treatment therapies.

  20. Exponential smoothing weighted correlations

    Science.gov (United States)

    Pozzi, F.; Di Matteo, T.; Aste, T.

    2012-06-01

    In many practical applications, correlation matrices might be affected by the "curse of dimensionality" and by an excessive sensitiveness to outliers and remote observations. These shortcomings can cause problems of statistical robustness especially accentuated when a system of dynamic correlations over a running window is concerned. These drawbacks can be partially mitigated by assigning a structure of weights to observational events. In this paper, we discuss Pearson's ρ and Kendall's τ correlation matrices, weighted with an exponential smoothing, computed on moving windows using a data-set of daily returns for 300 NYSE highly capitalized companies in the period between 2001 and 2003. Criteria for jointly determining optimal weights together with the optimal length of the running window are proposed. We find that the exponential smoothing can provide more robust and reliable dynamic measures and we discuss that a careful choice of the parameters can reduce the autocorrelation of dynamic correlations whilst keeping significance and robustness of the measure. Weighted correlations are found to be smoother and recovering faster from market turbulence than their unweighted counterparts, helping also to discriminate more effectively genuine from spurious correlations.

  1. Search for MH370: New Geologic Insights Gained from Integrating Multiple Geophysical Datasets

    Science.gov (United States)

    McBee, J.; Gharib, J. J.; Ingle, S.

    2017-12-01

    During the search for the missing flight MH370, Fugro acquired the largest extent of high resolution bathymetry in the southern Indian Ocean to date. These recently released multibeam echosounder (MBES) backscatter, bathymetry, water column, and sub-bottom profiler data reveal additional insights into the characteristics of the Indian Ocean seafloor and the geologic and oceanographic processes that shaped it. The mapping is at a sufficient resolution to examine relict spreading texture such as fracture zones, pseudofaults, failed propogating rifts, devals (deviations from axial linearity), etc. In this presentation, we will highlight several prominent regional seafloor features, and illustrate insights gained by integrating MBES backscatter and water column data with bathymetric analyses. Backscatter data to the north of the southern flank of Broken Ridge illustrate the complexity to which sediment has been reworked downslope where intricate patterns of low backscatter intensities are observed. Here, exposed rocks form prominent high backscatter reflectors amid the surrounding low backscatter sediments. The lateral extent of high backscatter intensity reflectors south of the Diamantina reveals the expansiveness of exposed igneous rocks that resulted from seafloor spreading. Volcanic features, including off-axis volcanoes and leaky transforms are also interpreted as high backscatter anomalies in the tectonic speading fabric to the north of the Geelvinck fracture zone, towards the southern extent of the dataset. These and other examples show that by integrating the entire suite of data collected by MBES systems, more detailed interpretations of the geologic processes that shaped the seafloor may be gained than by examination of bathymetry alone.

  2. Colocalization analysis in fluorescence micrographs: verification of a more accurate calculation of pearson's correlation coefficient.

    Science.gov (United States)

    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.

  3. Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers.

    Science.gov (United States)

    Church, Philip C; Goscinski, Andrzej; Holt, Kathryn; Inouye, Michael; Ghoting, Amol; Makarychev, Konstantin; Reumann, Matthias

    2011-01-01

    The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.

  4. Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices.

    Science.gov (United States)

    Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H Eugene

    2011-04-01

    We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

  5. Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices

    Science.gov (United States)

    Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H. Eugene

    2011-04-01

    We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes “bad news” for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

  6. Correlations between contouring similarity metrics and simulated treatment outcome for prostate radiotherapy

    Science.gov (United States)

    Roach, D.; Jameson, M. G.; Dowling, J. A.; Ebert, M. A.; Greer, P. B.; Kennedy, A. M.; Watt, S.; Holloway, L. C.

    2018-02-01

    Many similarity metrics exist for inter-observer contouring variation studies, however no correlation between metric choice and prostate cancer radiotherapy dosimetry has been explored. These correlations were investigated in this study. Two separate trials were undertaken, the first a thirty-five patient cohort with three observers, the second a five patient dataset with ten observers. Clinical and planning target volumes (CTV and PTV), rectum, and bladder were independently contoured by all observers in each trial. Structures were contoured on T2-weighted MRI and transferred onto CT following rigid registration for treatment planning in the first trial. Structures were contoured directly on CT in the second trial. STAPLE and majority voting volumes were generated as reference gold standard volumes for each structure for the two trials respectively. VMAT treatment plans (78 Gy to PTV) were simulated for observer and gold standard volumes, and dosimetry assessed using multiple radiobiological metrics. Correlations between contouring similarity metrics and dosimetry were calculated using Spearman’s rank correlation coefficient. No correlations were observed between contouring similarity metrics and dosimetry for CTV within either trial. Volume similarity correlated most strongly with radiobiological metrics for PTV in both trials, including TCPPoisson (ρ  =  0.57, 0.65), TCPLogit (ρ  =  0.39, 0.62), and EUD (ρ  =  0.43, 0.61) for each respective trial. Rectum and bladder metric correlations displayed no consistency for the two trials. PTV volume similarity was found to significantly correlate with rectum normal tissue complication probability (ρ  =  0.33, 0.48). Minimal to no correlations with dosimetry were observed for overlap or boundary contouring metrics. Future inter-observer contouring variation studies for prostate cancer should incorporate volume similarity to provide additional insights into dosimetry during analysis.

  7. Improved nonparametric inference for multiple correlated periodic sequences

    KAUST Repository

    Sun, Ying; Hart, Jeffrey D.; Genton, Marc G.

    2013-01-01

    cross-validation method to the temperature data obtained from multiple ice cores, investigating the periodicity of the El Niño effect. Our methodology is also illustrated by estimating patients' cardiac cycle from different physiological signals

  8. Reduced α-stable dynamics for multiple time scale systems forced with correlated additive and multiplicative Gaussian white noise

    Science.gov (United States)

    Thompson, William F.; Kuske, Rachel A.; Monahan, Adam H.

    2017-11-01

    Stochastic averaging problems with Gaussian forcing have been the subject of numerous studies, but far less attention has been paid to problems with infinite-variance stochastic forcing, such as an α-stable noise process. It has been shown that simple linear systems driven by correlated additive and multiplicative (CAM) Gaussian noise, which emerge in the context of reduced atmosphere and ocean dynamics, have infinite variance in certain parameter regimes. In this study, we consider the stochastic averaging of systems where a linear CAM noise process in the infinite variance parameter regime drives a comparatively slow process. We use (semi)-analytical approximations combined with numerical illustrations to compare the averaged process to one that is forced by a white α-stable process, demonstrating consistent properties in the case of large time-scale separation. We identify the conditions required for the fast linear CAM process to have such an influence in driving a slower process and then derive an (effectively) equivalent fast, infinite-variance process for which an existing stochastic averaging approximation is readily applied. The results are illustrated using numerical simulations of a set of example systems.

  9. Genetic algorithm as a variable selection procedure for the simulation of 13C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression.

    Science.gov (United States)

    Ghavami, Raoof; Najafi, Amir; Sajadi, Mohammad; Djannaty, Farhad

    2008-09-01

    In order to accurately simulate (13)C NMR spectra of hydroxy, polyhydroxy and methoxy substituted flavonoid a quantitative structure-property relationship (QSPR) model, relating atom-based calculated descriptors to (13)C NMR chemical shifts (ppm, TMS=0), is developed. A dataset consisting of 50 flavonoid derivatives was employed for the present analysis. A set of 417 topological, geometrical, and electronic descriptors representing various structural characteristics was calculated and separate multilinear QSPR models were developed between each carbon atom of flavonoid and the calculated descriptors. Genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used to select the descriptors and to generate the correlation models. Analysis of the results revealed a correlation coefficient and root mean square error (RMSE) of 0.994 and 2.53ppm, respectively, for the prediction set.

  10. Analysis of neutron multiplicity measurements with allowance for dead-time losses between time-correlated detections

    International Nuclear Information System (INIS)

    Vincent, C.H.

    1992-01-01

    An exact solution is found for dead-time losses between detections occurring within a gate interval, with constant dead time and with allowance for time correlation between detections from the same spontaneous initial event. This is used to obtain a close approximation to the losses with a multi-channel detection system, with allowance for dead times briding the gate opening. This is applied, inversely, to calculate the true detection multiplicity rates from the distribution of the recorded counts within that interval. A suggestion is made for a circuit change to give a major reduction in dead-time effects. The unavoidable statistical errors that would remain are calculated. Their minimization and the limits of such minimization are discussed. (orig.)

  11. Analysis of Public Datasets for Wearable Fall Detection Systems

    Directory of Open Access Journals (Sweden)

    Eduardo Casilari

    2017-06-01

    Full Text Available Due to the boom of wireless handheld devices such as smartwatches and smartphones, wearable Fall Detection Systems (FDSs have become a major focus of attention among the research community during the last years. The effectiveness of a wearable FDS must be contrasted against a wide variety of measurements obtained from inertial sensors during the occurrence of falls and Activities of Daily Living (ADLs. In this regard, the access to public databases constitutes the basis for an open and systematic assessment of fall detection techniques. This paper reviews and appraises twelve existing available data repositories containing measurements of ADLs and emulated falls envisaged for the evaluation of fall detection algorithms in wearable FDSs. The analysis of the found datasets is performed in a comprehensive way, taking into account the multiple factors involved in the definition of the testbeds deployed for the generation of the mobility samples. The study of the traces brings to light the lack of a common experimental benchmarking procedure and, consequently, the large heterogeneity of the datasets from a number of perspectives (length and number of samples, typology of the emulated falls and ADLs, characteristics of the test subjects, features and positions of the sensors, etc.. Concerning this, the statistical analysis of the samples reveals the impact of the sensor range on the reliability of the traces. In addition, the study evidences the importance of the selection of the ADLs and the need of categorizing the ADLs depending on the intensity of the movements in order to evaluate the capability of a certain detection algorithm to discriminate falls from ADLs.

  12. A canonical correlation analysis-based dynamic bayesian network prior to infer gene regulatory networks from multiple types of biological data.

    Science.gov (United States)

    Baur, Brittany; Bozdag, Serdar

    2015-04-01

    One of the challenging and important computational problems in systems biology is to infer gene regulatory networks (GRNs) of biological systems. Several methods that exploit gene expression data have been developed to tackle this problem. In this study, we propose the use of copy number and DNA methylation data to infer GRNs. We developed an algorithm that scores regulatory interactions between genes based on canonical correlation analysis. In this algorithm, copy number or DNA methylation variables are treated as potential regulator variables, and expression variables are treated as potential target variables. We first validated that the canonical correlation analysis method is able to infer true interactions in high accuracy. We showed that the use of DNA methylation or copy number datasets leads to improved inference over steady-state expression. Our results also showed that epigenetic and structural information could be used to infer directionality of regulatory interactions. Additional improvements in GRN inference can be gleaned from incorporating the result in an informative prior in a dynamic Bayesian algorithm. This is the first study that incorporates copy number and DNA methylation into an informative prior in dynamic Bayesian framework. By closely examining top-scoring interactions with different sources of epigenetic or structural information, we also identified potential novel regulatory interactions.

  13. Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

    Science.gov (United States)

    Kim, Yoonsang; Emery, Sherry

    2013-01-01

    Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

  14. Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

    Science.gov (United States)

    Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

    2013-08-01

    Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

  15. Characteristics and correlates of coping with multiple sclerosis: a systematic review.

    Science.gov (United States)

    Keramat Kar, Maryam; Whitehead, Lisa; Smith, Catherine M

    2017-10-10

    The purpose of this systematic review was to examine coping strategies that people with multiple sclerosis use, and to identify factors that influence their coping pattern. This systematic review followed the Joanna Briggs Institute guidelines for synthesizing descriptive quantitative research. The following databases were searched from the inception of databases until December 2016: Ovid (Medline, Embase, CINAHL, and PsycINFO), Science Direct, Web of Science, and Scopus. Manual search was also conducted from the reference lists of retrieved articles. Findings related to the patterns of coping with multiple sclerosis and factors influencing coping with multiple sclerosis were extracted and synthesized. The search of the database yielded 455 articles. After excluding duplicates (n = 341) and studies that did not meet the inclusion criteria (n = 27), 71 studies were included in the full-text review. Following the full-text, a further 21 studies were excluded. Quality appraisal of 50 studies was completed, and 38 studies were included in the review. Synthesis of findings indicated that people with multiple sclerosis use emotional and avoidance coping strategies more than other types of coping, particularly in the early stages of the disease. In comparison to the general population, people with multiple sclerosis were less likely to use active coping strategies and used more avoidance and emotional coping strategies. The pattern of coping with multiple sclerosis was associated with individual, clinical and psychological factors including gender, educational level, clinical course, mood and mental status, attitude, personality traits, and religious beliefs. The findings of this review suggest that considering individual or disease-related factors could help healthcare professionals in identifying those less likely to adapt to multiple sclerosis. This information could also be used to provide client-centered rehabilitation for people living with multiple

  16. Exploiting Multiple Detections for Person Re-Identification

    Directory of Open Access Journals (Sweden)

    Amran Bhuiyan

    2018-01-01

    Full Text Available Re-identification systems aim at recognizing the same individuals in multiple cameras, and one of the most relevant problems is that the appearance of same individual varies across cameras due to illumination and viewpoint changes. This paper proposes the use of cumulative weighted brightness transfer functions (CWBTFs to model these appearance variations. Different from recently proposed methods which only consider pairs of images to learn a brightness transfer function, we exploit such a multiple-frame-based learning approach that leverages consecutive detections of each individual to transfer the appearance. We first present a CWBTF framework for the task of transforming appearance from one camera to another. We then present a re-identification framework where we segment the pedestrian images into meaningful parts and extract features from such parts, as well as from the whole body. Jointly, both of these frameworks contribute to model the appearance variations more robustly. We tested our approach on standard multi-camera surveillance datasets, showing consistent and significant improvements over existing methods on three different datasets without any other additional cost. Our approach is general and can be applied to any appearance-based method.

  17. An Analysis on Better Testing than Training Performances on the Iris Dataset

    NARCIS (Netherlands)

    Schutten, Marten; Wiering, Marco

    2016-01-01

    The Iris dataset is a well known dataset containing information on three different types of Iris flowers. A typical and popular method for solving classification problems on datasets such as the Iris set is the support vector machine (SVM). In order to do so the dataset is separated in a set used

  18. Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection

    Directory of Open Access Journals (Sweden)

    Gavin C. Bowick

    2011-05-01

    Full Text Available The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.

  19. Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES

    Directory of Open Access Journals (Sweden)

    M. Kopacz

    2010-02-01

    Full Text Available We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005 global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD, and aircraft (MOZAIC are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a−1. This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

  20. A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery.

    Science.gov (United States)

    Ahmidi, Narges; Tao, Lingling; Sefati, Shahin; Gao, Yixin; Lea, Colin; Haro, Benjamin Bejar; Zappella, Luca; Khudanpur, Sanjeev; Vidal, Rene; Hager, Gregory D

    2017-09-01

    State-of-the-art techniques for surgical data analysis report promising results for automated skill assessment and action recognition. The contributions of many of these techniques, however, are limited to study-specific data and validation metrics, making assessment of progress across the field extremely challenging. In this paper, we address two major problems for surgical data analysis: First, lack of uniform-shared datasets and benchmarks, and second, lack of consistent validation processes. We address the former by presenting the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS), a public dataset that we have created to support comparative research benchmarking. JIGSAWS contains synchronized video and kinematic data from multiple performances of robotic surgical tasks by operators of varying skill. We address the latter by presenting a well-documented evaluation methodology and reporting results for six techniques for automated segmentation and classification of time-series data on JIGSAWS. These techniques comprise four temporal approaches for joint segmentation and classification: hidden Markov model, sparse hidden Markov model (HMM), Markov semi-Markov conditional random field, and skip-chain conditional random field; and two feature-based ones that aim to classify fixed segments: bag of spatiotemporal features and linear dynamical systems. Most methods recognize gesture activities with approximately 80% overall accuracy under both leave-one-super-trial-out and leave-one-user-out cross-validation settings. Current methods show promising results on this shared dataset, but room for significant progress remains, particularly for consistent prediction of gesture activities across different surgeons. The results reported in this paper provide the first systematic and uniform evaluation of surgical activity recognition techniques on the benchmark database.

  1. Something From Nothing (There): Collecting Global IPv6 Datasets from DNS

    NARCIS (Netherlands)

    Fiebig, T.; Borgolte, Kevin; Hao, Shuang; Kruegel, Christopher; Vigna, Giovanny; Spring, Neil; Riley, George F.

    2017-01-01

    Current large-scale IPv6 studies mostly rely on non-public datasets, asmost public datasets are domain specific. For instance, traceroute-based datasetsare biased toward network equipment. In this paper, we present a new methodologyto collect IPv6 address datasets that does not require access to

  2. Automatic processing of multimodal tomography datasets.

    Science.gov (United States)

    Parsons, Aaron D; Price, Stephen W T; Wadeson, Nicola; Basham, Mark; Beale, Andrew M; Ashton, Alun W; Mosselmans, J Frederick W; Quinn, Paul D

    2017-01-01

    With the development of fourth-generation high-brightness synchrotrons on the horizon, the already large volume of data that will be collected on imaging and mapping beamlines is set to increase by orders of magnitude. As such, an easy and accessible way of dealing with such large datasets as quickly as possible is required in order to be able to address the core scientific problems during the experimental data collection. Savu is an accessible and flexible big data processing framework that is able to deal with both the variety and the volume of data of multimodal and multidimensional scientific datasets output such as those from chemical tomography experiments on the I18 microfocus scanning beamline at Diamond Light Source.

  3. Interannual Variability of Northern Hemisphere Storm Tracks in Coarse-Gridded Datasets

    Directory of Open Access Journals (Sweden)

    Timothy Paul Eichler

    2013-01-01

    Full Text Available Extratropical cyclones exert a large socioeconomic impact. It is therefore important to assess their interannual variability. We generate cyclone tracks from the National Center for Environmental Prediction’s Reanalysis I and the European Centre for Medium Range Prediction ERA-40 reanalysis datasets. To investigate the interannual variability of cyclone tracks, we compare the effects of El Niño, the North Atlantic Oscillation (NAO, the Indian Ocean Dipole (IOD, and the Pacific North American Pattern (PNA on cyclone tracks. Composite analysis shows similar results for the impacts of El Niño, NAO, and the PNA on NH storm tracks. Although it is encouraging, we also found regional differences when comparing reanalysis datasets. The results for the IOD suggested a wave-like alteration of cyclone frequency across the northern US/Canada possibly related to Rossby wave propagation. Partial correlation demonstrates that although El Niño affects cyclone frequency in the North Pacific and along the US east coast, its impact on the North Pacific is accomplished via the PNA. Similarly, the PNA’s impact on US east coast storms is modulated via El Niño. In contrast, the impacts of the NAO extend as far west as the North Pacific and are not influenced by either the PNA or El Niño.

  4. Process mining in oncology using the MIMIC-III dataset

    Science.gov (United States)

    Prima Kurniati, Angelina; Hall, Geoff; Hogg, David; Johnson, Owen

    2018-03-01

    Process mining is a data analytics approach to discover and analyse process models based on the real activities captured in information systems. There is a growing body of literature on process mining in healthcare, including oncology, the study of cancer. In earlier work we found 37 peer-reviewed papers describing process mining research in oncology with a regular complaint being the limited availability and accessibility of datasets with suitable information for process mining. Publicly available datasets are one option and this paper describes the potential to use MIMIC-III, for process mining in oncology. MIMIC-III is a large open access dataset of de-identified patient records. There are 134 publications listed as using the MIMIC dataset, but none of them have used process mining. The MIMIC-III dataset has 16 event tables which are potentially useful for process mining and this paper demonstrates the opportunities to use MIMIC-III for process mining in oncology. Our research applied the L* lifecycle method to provide a worked example showing how process mining can be used to analyse cancer pathways. The results and data quality limitations are discussed along with opportunities for further work and reflection on the value of MIMIC-III for reproducible process mining research.

  5. A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits

    Directory of Open Access Journals (Sweden)

    Shigeyuki Ikeda

    2017-06-01

    Full Text Available Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz of resting-state functional magnetic resonance imaging (fMRI activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI, and the fractional amplitude of low-frequency fluctuation (fALFF at four distinct frequency bands (slow-5 (0.01–0.027 Hz, slow-4 (0.027–0.073 Hz, slow-3 (0.073–0.198 Hz and slow-2 (0.198–0.25 Hz. We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.

  6. Orthology detection combining clustering and synteny for very large datasets.

    Science.gov (United States)

    Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K; Prohaska, Sonja J; Stadler, Peter F

    2014-01-01

    The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.

  7. Veterans Affairs Suicide Prevention Synthetic Dataset

    Data.gov (United States)

    Department of Veterans Affairs — The VA's Veteran Health Administration, in support of the Open Data Initiative, is providing the Veterans Affairs Suicide Prevention Synthetic Dataset (VASPSD). The...

  8. SAR image classification based on CNN in real and simulation datasets

    Science.gov (United States)

    Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

    2018-04-01

    Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

  9. On sample size and different interpretations of snow stability datasets

    Science.gov (United States)

    Schirmer, M.; Mitterer, C.; Schweizer, J.

    2009-04-01

    Interpretations of snow stability variations need an assessment of the stability itself, independent of the scale investigated in the study. Studies on stability variations at a regional scale have often chosen stability tests such as the Rutschblock test or combinations of various tests in order to detect differences in aspect and elevation. The question arose: ‘how capable are such stability interpretations in drawing conclusions'. There are at least three possible errors sources: (i) the variance of the stability test itself; (ii) the stability variance at an underlying slope scale, and (iii) that the stability interpretation might not be directly related to the probability of skier triggering. Various stability interpretations have been proposed in the past that provide partly different results. We compared a subjective one based on expert knowledge with a more objective one based on a measure derived from comparing skier-triggered slopes vs. slopes that have been skied but not triggered. In this study, the uncertainties are discussed and their effects on regional scale stability variations will be quantified in a pragmatic way. An existing dataset with very large sample sizes was revisited. This dataset contained the variance of stability at a regional scale for several situations. The stability in this dataset was determined using the subjective interpretation scheme based on expert knowledge. The question to be answered was how many measurements were needed to obtain similar results (mainly stability differences in aspect or elevation) as with the complete dataset. The optimal sample size was obtained in several ways: (i) assuming a nominal data scale the sample size was determined with a given test, significance level and power, and by calculating the mean and standard deviation of the complete dataset. With this method it can also be determined if the complete dataset consists of an appropriate sample size. (ii) Smaller subsets were created with similar

  10. Really big data: Processing and analysis of large datasets

    Science.gov (United States)

    Modern animal breeding datasets are large and getting larger, due in part to the recent availability of DNA data for many animals. Computational methods for efficiently storing and analyzing those data are under development. The amount of storage space required for such datasets is increasing rapidl...

  11. A robust dataset-agnostic heart disease classifier from Phonocardiogram.

    Science.gov (United States)

    Banerjee, Rohan; Dutta Choudhury, Anirban; Deshpande, Parijat; Bhattacharya, Sakyajit; Pal, Arpan; Mandana, K M

    2017-07-01

    Automatic classification of normal and abnormal heart sounds is a popular area of research. However, building a robust algorithm unaffected by signal quality and patient demography is a challenge. In this paper we have analysed a wide list of Phonocardiogram (PCG) features in time and frequency domain along with morphological and statistical features to construct a robust and discriminative feature set for dataset-agnostic classification of normal and cardiac patients. The large and open access database, made available in Physionet 2016 challenge was used for feature selection, internal validation and creation of training models. A second dataset of 41 PCG segments, collected using our in-house smart phone based digital stethoscope from an Indian hospital was used for performance evaluation. Our proposed methodology yielded sensitivity and specificity scores of 0.76 and 0.75 respectively on the test dataset in classifying cardiovascular diseases. The methodology also outperformed three popular prior art approaches, when applied on the same dataset.

  12. A Comparative Analysis of Classification Algorithms on Diverse Datasets

    Directory of Open Access Journals (Sweden)

    M. Alghobiri

    2018-04-01

    Full Text Available Data mining involves the computational process to find patterns from large data sets. Classification, one of the main domains of data mining, involves known structure generalizing to apply to a new dataset and predict its class. There are various classification algorithms being used to classify various data sets. They are based on different methods such as probability, decision tree, neural network, nearest neighbor, boolean and fuzzy logic, kernel-based etc. In this paper, we apply three diverse classification algorithms on ten datasets. The datasets have been selected based on their size and/or number and nature of attributes. Results have been discussed using some performance evaluation measures like precision, accuracy, F-measure, Kappa statistics, mean absolute error, relative absolute error, ROC Area etc. Comparative analysis has been carried out using the performance evaluation measures of accuracy, precision, and F-measure. We specify features and limitations of the classification algorithms for the diverse nature datasets.

  13. What invariant one-particle multiplicity distributions and two-particle correlations are telling us about relativistic heavy-ion collisions

    International Nuclear Information System (INIS)

    Nix, J.R.; Strottman, D.; Hecke, H.W. van; Schlei, B.R.; Sullivan, J.P.; Murray, M.J.

    1998-02-01

    The authors have used a nine-parameter expanding source model that includes special relativity, quantum statistics, resonance decays, and freeze-out on a realistic hypersurface in spacetime to analyze in detail invariant π + , K + , and K - one-particle multiplicity distributions and π + and π - two-particle correlations in nearly central collisions of Pb + Pb at p lab /A = 158 GeV/c. These studies confirm an earlier conclusion for nearly central collisions of Si + Au at p lab /A = 14.6 GeV/c that the freeze-out temperature is less than 100 meV and that both the longitudinal and transverse collective velocities -- which are anti-correlated with the temperature -- are substantial. The authors also reconciled their current results with those of previous analyses that yielded a much higher freeze-out temperature of approximately 140 meV for both Pb + Pb collisions at p lab /A = 158 GeV/c and other reactions. One type of analysis was based upon the use of a heuristic equation that neglects relativity to extrapolate slope parameters to zero particle mass. Another type of analysis utilized a thermal model in which there was an accumulation of effects from several approximations. The future should witness the arrival of much new data on invariant one-particle multiplicity distributions and two-particle correlations as functions of bombarding energy and/or size of the colliding nuclei. The proper analysis of these data in terms of a realistic model could yield accurate values for the density, temperature, collective velocity, size, and other properties of the expanding matter as it freezes out into a collection of noninteracting hadrons. A sharp discontinuity in the value of one or more of these properties could conceivably be the long-awaited signal for the formation of a quark-gluon plasma or other new physics

  14. CADDIS Volume 4. Data Analysis: Exploratory Data Analysis

    Science.gov (United States)

    Intro to exploratory data analysis. Overview of variable distributions, scatter plots, correlation analysis, GIS datasets. Use of conditional probability to examine stressor levels and impairment. Exploring correlations among multiple stressors.

  15. Differences between charge-charge forward-backward multiplicity correlations in multiparticle production

    International Nuclear Information System (INIS)

    Barshay, S.

    1987-01-01

    We analyze new data from hadron-hadron collisions on forward-backward correlations. The difference between these correlations for unlike and like charges implies different dynamical correlations at fixed impact parameter. These different correlations should be observable in e + e - annihilations. (orig.)

  16. Does the Visibility of Greenery Increase Perceived Safety in Urban Areas? Evidence from the Place Pulse 1.0 Dataset

    Directory of Open Access Journals (Sweden)

    Xiaojiang Li

    2015-07-01

    Full Text Available Urban green space provides a series of esthetic, environmental and psychological benefits to urban residents. However, the relationship between the visibility of green vegetation and perceived safety is still in debate. This research investigated whether green vegetation could help to increase the perceived safety based on a crowdsourced dataset: the Place Pulse 1.0 dataset. Place Pulse 1.0 dataset, which was generated from a large number of votes by online participants, includes geo-tagged Google Street View images and the corresponding perceived safety score for each image. In this study, we conducted statistical analyses to analyze the relationship between perceived safety and green vegetation characteristics, which were extracted from Google Street View images. Results show that the visibility of green vegetation plays an important role in increasing perceived safety in urban areas. For different land use types, the relationship between vegetation structures and perceived safety varies. In residential, urban public/institutional, commercial and open land areas, the visibility of vegetation higher than 2.5 m has significant positive correlations with perceived safety, but there exists no significant correlation between perceived safety and the percentage of green vegetation in transportation and industrial areas. The visibility of vegetation below 2.5 m has no significant relationship with the perceived safety in almost all land use types, except for multifamily residential land and urban public/institutional land. In general, this study provided insight for the relationship between green vegetation characteristics and the perception of environment, as well as valuable reference data for developing urban greening programs.

  17. Event recognition in personal photo collections via multiple instance learning-based classification of multiple images

    Science.gov (United States)

    Ahmad, Kashif; Conci, Nicola; Boato, Giulia; De Natale, Francesco G. B.

    2017-11-01

    Over the last few years, a rapid growth has been witnessed in the number of digital photos produced per year. This rapid process poses challenges in the organization and management of multimedia collections, and one viable solution consists of arranging the media on the basis of the underlying events. However, album-level annotation and the presence of irrelevant pictures in photo collections make event-based organization of personal photo albums a more challenging task. To tackle these challenges, in contrast to conventional approaches relying on supervised learning, we propose a pipeline for event recognition in personal photo collections relying on a multiple instance-learning (MIL) strategy. MIL is a modified form of supervised learning and fits well for such applications with weakly labeled data. The experimental evaluation of the proposed approach is carried out on two large-scale datasets including a self-collected and a benchmark dataset. On both, our approach significantly outperforms the existing state-of-the-art.

  18. An assessment of differences in gridded precipitation datasets in complex terrain

    Science.gov (United States)

    Henn, Brian; Newman, Andrew J.; Livneh, Ben; Daly, Christopher; Lundquist, Jessica D.

    2018-01-01

    Hydrologic modeling and other geophysical applications are sensitive to precipitation forcing data quality, and there are known challenges in spatially distributing gauge-based precipitation over complex terrain. We conduct a comparison of six high-resolution, daily and monthly gridded precipitation datasets over the Western United States. We compare the long-term average spatial patterns, and interannual variability of water-year total precipitation, as well as multi-year trends in precipitation across the datasets. We find that the greatest absolute differences among datasets occur in high-elevation areas and in the maritime mountain ranges of the Western United States, while the greatest percent differences among datasets relative to annual total precipitation occur in arid and rain-shadowed areas. Differences between datasets in some high-elevation areas exceed 200 mm yr-1 on average, and relative differences range from 5 to 60% across the Western United States. In areas of high topographic relief, true uncertainties and biases are likely higher than the differences among the datasets; we present evidence of this based on streamflow observations. Precipitation trends in the datasets differ in magnitude and sign at smaller scales, and are sensitive to how temporal inhomogeneities in the underlying precipitation gauge data are handled.

  19. Strontium removal jar test dataset for all figures and tables.

    Data.gov (United States)

    U.S. Environmental Protection Agency — The datasets where used to generate data to demonstrate strontium removal under various water quality and treatment conditions. This dataset is associated with the...

  20. Benchmarking of Typical Meteorological Year datasets dedicated to Concentrated-PV systems

    Science.gov (United States)

    Realpe, Ana Maria; Vernay, Christophe; Pitaval, Sébastien; Blanc, Philippe; Wald, Lucien; Lenoir, Camille

    2016-04-01

    Accurate analysis of meteorological and pyranometric data for long-term analysis is the basis of decision-making for banks and investors, regarding solar energy conversion systems. This has led to the development of methodologies for the generation of Typical Meteorological Years (TMY) datasets. The most used method for solar energy conversion systems was proposed in 1978 by the Sandia Laboratory (Hall et al., 1978) considering a specific weighted combination of different meteorological variables with notably global, diffuse horizontal and direct normal irradiances, air temperature, wind speed, relative humidity. In 2012, a new approach was proposed in the framework of the European project FP7 ENDORSE. It introduced the concept of "driver" that is defined by the user as an explicit function of the pyranometric and meteorological relevant variables to improve the representativeness of the TMY datasets with respect the specific solar energy conversion system of interest. The present study aims at comparing and benchmarking different TMY datasets considering a specific Concentrated-PV (CPV) system as the solar energy conversion system of interest. Using long-term (15+ years) time-series of high quality meteorological and pyranometric ground measurements, three types of TMY datasets generated by the following methods: the Sandia method, a simplified driver with DNI as the only representative variable and a more sophisticated driver. The latter takes into account the sensitivities of the CPV system with respect to the spectral distribution of the solar irradiance and wind speed. Different TMY datasets from the three methods have been generated considering different numbers of years in the historical dataset, ranging from 5 to 15 years. The comparisons and benchmarking of these TMY datasets are conducted considering the long-term time series of simulated CPV electric production as a reference. The results of this benchmarking clearly show that the Sandia method is not

  1. Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.

    Science.gov (United States)

    Gangnon, Ronald E

    2012-03-01

    The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.

  2. SIAM 2007 Text Mining Competition dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — Subject Area: Text Mining Description: This is the dataset used for the SIAM 2007 Text Mining competition. This competition focused on developing text mining...

  3. Environmental Dataset Gateway (EDG) REST Interface

    Data.gov (United States)

    U.S. Environmental Protection Agency — Use the Environmental Dataset Gateway (EDG) to find and access EPA's environmental resources. Many options are available for easily reusing EDG content in other...

  4. SATCHMO-JS: a webserver for simultaneous protein multiple sequence alignment and phylogenetic tree construction.

    Science.gov (United States)

    Hagopian, Raffi; Davidson, John R; Datta, Ruchira S; Samad, Bushra; Jarvis, Glen R; Sjölander, Kimmen

    2010-07-01

    We present the jump-start simultaneous alignment and tree construction using hidden Markov models (SATCHMO-JS) web server for simultaneous estimation of protein multiple sequence alignments (MSAs) and phylogenetic trees. The server takes as input a set of sequences in FASTA format, and outputs a phylogenetic tree and MSA; these can be viewed online or downloaded from the website. SATCHMO-JS is an extension of the SATCHMO algorithm, and employs a divide-and-conquer strategy to jump-start SATCHMO at a higher point in the phylogenetic tree, reducing the computational complexity of the progressive all-versus-all HMM-HMM scoring and alignment. Results on a benchmark dataset of 983 structurally aligned pairs from the PREFAB benchmark dataset show that SATCHMO-JS provides a statistically significant improvement in alignment accuracy over MUSCLE, Multiple Alignment using Fast Fourier Transform (MAFFT), ClustalW and the original SATCHMO algorithm. The SATCHMO-JS webserver is available at http://phylogenomics.berkeley.edu/satchmo-js. The datasets used in these experiments are available for download at http://phylogenomics.berkeley.edu/satchmo-js/supplementary/.

  5. Geoseq: a tool for dissecting deep-sequencing datasets

    Directory of Open Access Journals (Sweden)

    Homann Robert

    2010-10-01

    Full Text Available Abstract Background Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO, Sequence Read Archive (SRA hosted by the NCBI, or the DNA Data Bank of Japan (ddbj. Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Results Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Conclusions Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a identify differential isoform expression in mRNA-seq datasets, b identify miRNAs (microRNAs in libraries, and identify mature and star sequences in miRNAS and c to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool.

  6. The Geomagnetic Field and Correlations with Multiple Sclerosis: A Possible Etiology of Disease

    Science.gov (United States)

    Wade, Brett

    Multiple sclerosis (MS) is a complex autoimmune disease that results in a demyelinating process of the central nervous system. It is the most common, progressive, neurological disease affecting young adults, and there is no cure. A curious feature of MS is its distinct global prevalence with high rates of occurrence between 40 and 60 degrees latitude. While genetics may partially explain this phenomenon, studies have shown that the influence of genetics is modest. Many non-genetic variables, such as viruses, vitamin D, smoking, diet, hormones, etc., have been shown to be related to the expression of MS but none of these variables have been determined to be necessarily strong enough to exclude other factors. The geomagnetic field, which is a non-uniform, three dimensional entity which protects all living things from ionizing radiation, is suggested in this research to be related to global MS prevalence. This study hypothesized that either the total field, the vertical field, or the horizontal field strength of the geomagnetic field will be correlated with MS. Using secondary sources of prevalence studies (N=131) and geomagnetic data, the results supported all three hypotheses with the strongest correlation being an inverse relationship between the horizontal field and MS (r = -.607). The explanation for the inverse relationship being most strongly correlated with MS prevalence is explained by the fact that the horizontal aspect of the geomagnetic field has a protective effect from incoming cosmic radiation. Chronic exposure to high levels of background radiation can have deleterious health effects. This research suggests that living in areas of a weak horizontal field increases a person's exposure to ionizing radiation and therefore increases the risk for developing MS. While it was not the intention of this research, it became clear that an explanation which explained the results of this research and also attempted to unify the mechanisms of all non

  7. Chord Recognition Based on Temporal Correlation Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhongyang Rao

    2016-05-01

    Full Text Available In this paper, we propose a method called temporal correlation support vector machine (TCSVM for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and the sparse component to contain the vocal signals. Then, we extract a new logarithmic pitch class profile (LPCP feature called enhanced LPCP from the low-rank part. To exploit the temporal correlation among the LPCP features of chords, we propose an improved support vector machine algorithm called TCSVM. We perform this study using the MIREX’09 (Music Information Retrieval Evaluation eXchange Audio Chord Estimation dataset. Furthermore, we conduct comprehensive experiments using different pitch class profile feature vectors to examine the performance of TCSVM. The results of our method are comparable to the state-of-the-art methods that entered the MIREX in 2013 and 2014 for the MIREX’09 Audio Chord Estimation task dataset.

  8. An SPSS Macro to Compute Confidence Intervals for Pearson’s Correlation

    Directory of Open Access Journals (Sweden)

    Bruce Weaver

    2014-04-01

    Full Text Available In many disciplines, including psychology, medical research, epidemiology and public health, authors are required, or at least encouraged to report confidence intervals (CIs along with effect size estimates. Many students and researchers in these areas use IBM-SPSS for statistical analysis. Unfortunately, the CORRELATIONS procedure in SPSS does not provide CIs in the output. Various work-around solutions have been suggested for obtaining CIs for rhowith SPSS, but most of them have been sub-optimal. Since release 18, it has been possible to compute bootstrap CIs, but only if users have the optional bootstrap module. The !rhoCI macro described in this article is accessible to all SPSS users with release 14 or later. It directs output from the CORRELATIONS procedure to another dataset, restructures that dataset to have one row per correlation, computes a CI for each correlation, and displays the results in a single table. Because the macro uses the CORRELATIONS procedure, it allows users to specify a list of two or more variables to include in the correlation matrix, to choose a confidence level, and to select either listwise or pairwise deletion. Thus, it offers substantial improvements over previous solutions to theproblem of how to compute CIs for rho with SPSS.

  9. Structural dataset for the PPARγ V290M mutant

    Directory of Open Access Journals (Sweden)

    Ana C. Puhl

    2016-06-01

    Full Text Available Loss-of-function mutation V290M in the ligand-binding domain of the peroxisome proliferator activated receptor γ (PPARγ is associated with a ligand resistance syndrome (PLRS, characterized by partial lipodystrophy and severe insulin resistance. In this data article we discuss an X-ray diffraction dataset that yielded the structure of PPARγ LBD V290M mutant refined at 2.3 Å resolution, that allowed building of 3D model of the receptor mutant with high confidence and revealed continuous well-defined electron density for the partial agonist diclofenac bound to hydrophobic pocket of the PPARγ. These structural data provide significant insights into molecular basis of PLRS caused by V290M mutation and are correlated with the receptor disability of rosiglitazone binding and increased affinity for corepressors. Furthermore, our structural evidence helps to explain clinical observations which point out to a failure to restore receptor function by the treatment with a full agonist of PPARγ, rosiglitazone.

  10. Robust estimation of the correlation matrix of longitudinal data

    KAUST Repository

    Maadooliat, Mehdi

    2011-09-23

    We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky decomposition of the form Σ=DLL⊤D where D is a diagonal matrix proportional to the square roots of the diagonal entries of Σ and L is a unit lower-triangular matrix determining solely the correlation matrix. The first robustness is with respect to model misspecification for the innovation variances in D, and the second is robustness to outliers in the data. The latter is handled using heavy-tailed multivariate t-distributions with unknown degrees of freedom. We develop a Fisher scoring algorithm for computing the maximum likelihood estimator of the parameters when the nonredundant and unconstrained entries of (L,D) are modeled parsimoniously using covariates. We compare our results with those based on the modified Cholesky decomposition of the form LD2L⊤ using simulations and a real dataset. © 2011 Springer Science+Business Media, LLC.

  11. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  12. Harvard Aging Brain Study: Dataset and accessibility.

    Science.gov (United States)

    Dagley, Alexander; LaPoint, Molly; Huijbers, Willem; Hedden, Trey; McLaren, Donald G; Chatwal, Jasmeer P; Papp, Kathryn V; Amariglio, Rebecca E; Blacker, Deborah; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Schultz, Aaron P

    2017-01-01

    The Harvard Aging Brain Study is sharing its data with the global research community. The longitudinal dataset consists of a 284-subject cohort with the following modalities acquired: demographics, clinical assessment, comprehensive neuropsychological testing, clinical biomarkers, and neuroimaging. To promote more extensive analyses, imaging data was designed to be compatible with other publicly available datasets. A cloud-based system enables access to interested researchers with blinded data available contingent upon completion of a data usage agreement and administrative approval. Data collection is ongoing and currently in its fifth year. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Cerebrospinal fluid B cells correlate with early brain inflammation in multiple sclerosis.

    Directory of Open Access Journals (Sweden)

    Bettina Kuenz

    Full Text Available BACKGROUND: There is accumulating evidence from immunological, pathological and therapeutic studies that B cells are key components in the pathophysiology of multiple sclerosis (MS. METHODOLOGY/PRINCIPAL FINDINGS: In this prospective study we have for the first time investigated the differences in the inflammatory response between relapsing and progressive MS by comparing cerebrospinal fluid (CSF cell profiles from patients at the onset of the disease (clinically isolated syndrome, CIS, relapsing-remitting (RR and chronic progressive (CP MS by flow cytometry. As controls we have used patients with other neurological diseases. We have found a statistically significant accumulation of CSF mature B cells (CD19+CD138- and plasma blasts (CD19+CD138+ in CIS and RRMS. Both B cell populations were, however, not significantly increased in CPMS. Further, this accumulation of B cells correlated with acute brain inflammation measured by magnetic resonance imaging and with inflammatory CSF parameters such as the number of CSF leukocytes, intrathecal immunoglobulin M and G synthesis and intrathecal production of matrix metalloproteinase (MMP-9 and the B cell chemokine CxCL-13. CONCLUSIONS: Our data support an important role of CSF B cells in acute brain inflammation in CIS and RRMS.

  14. Querying Large Biological Network Datasets

    Science.gov (United States)

    Gulsoy, Gunhan

    2013-01-01

    New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.…

  15. Asymmetric correlation matrices: an analysis of financial data

    Science.gov (United States)

    Livan, G.; Rebecchi, L.

    2012-06-01

    We analyse the spectral properties of correlation matrices between distinct statistical systems. Such matrices are intrinsically non-symmetric, and lend themselves to extend the spectral analyses usually performed on standard Pearson correlation matrices to the realm of complex eigenvalues. We employ some recent random matrix theory results on the average eigenvalue density of this type of matrix to distinguish between noise and non-trivial correlation structures, and we focus on financial data as a case study. Namely, we employ daily prices of stocks belonging to the American and British stock exchanges, and look for the emergence of correlations between two such markets in the eigenvalue spectrum of their non-symmetric correlation matrix. We find several non trivial results when considering time-lagged correlations over short lags, and we corroborate our findings by additionally studying the asymmetric correlation matrix of the principal components of our datasets.

  16. BanglaLekha-Isolated: A multi-purpose comprehensive dataset of Handwritten Bangla Isolated characters

    Directory of Open Access Journals (Sweden)

    Mithun Biswas

    2017-06-01

    Full Text Available BanglaLekha-Isolated, a Bangla handwritten isolated character dataset is presented in this article. This dataset contains 84 different characters comprising of 50 Bangla basic characters, 10 Bangla numerals and 24 selected compound characters. 2000 handwriting samples for each of the 84 characters were collected, digitized and pre-processed. After discarding mistakes and scribbles, 1,66,105 handwritten character images were included in the final dataset. The dataset also includes labels indicating the age and the gender of the subjects from whom the samples were collected. This dataset could be used not only for optical handwriting recognition research but also to explore the influence of gender and age on handwriting. The dataset is publicly available at https://data.mendeley.com/datasets/hf6sf8zrkc/2.

  17. A dataset of human decision-making in teamwork management

    Science.gov (United States)

    Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

    2017-01-01

    Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

  18. Correlation of proliferative and clonogenic tumor cells in multiple myeloma

    International Nuclear Information System (INIS)

    Karp, J.E.; Burke, P.J.; Saylor, P.L.; Humphrey, R.L.

    1984-01-01

    To expand on the findings from previous clinical trials that the growth of residual tumor is increased at a predictable time following initial drug administration, malignant plasma cells from bone marrows of patients with multiple myeloma (MM) were examined for changes in proliferation and clonogenicity induced in vivo by cyclophosphamide and in vitro by drug-induced humoral stimulatory activity. Peak plasma cell [ 3 H]thymidine labeling index (LI) occurred predictably following drug and paralleled changes in agar colony formation by marrow cells obtained during therapy. Colony-forming capacity of pretreatment MM marrow populations was enhanced when those cells were cultured with humoral stimulatory activity, similar to the increased colony formation detected in Day 9 postcyclophosphamide marrows at the time of peak plasma cell LI. To further define a relationship between proliferative plasma cells and colony-forming tumor cells, MM marrows were fractionated by sedimentation on an isokinetic gradient. Enrichment of a proliferative tumor cell cohort was achieved, evidenced by [ 3 H]thymidine LI. Colony-forming cells were also enriched by isokinetic gradient sedimentation, and agar colony formation by MM marrow cell fractions correlated with the kinetic characteristics of the isolated subpopulations. These studies of whole and fractionated human MM marrow cell populations suggest that the kinetically active cells which are induced to proliferate in vivo and in vitro are closely related to the clonogenic tumor cells which produce colonies in agar and which, like those cells measured by [ 3 H]thymidine LI, respond to growth stimulation by drug-induced humoral stimulatory activity

  19. A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits

    Directory of Open Access Journals (Sweden)

    Hayashi Takeshi

    2013-01-01

    Full Text Available Abstract Background Genomic selection is an effective tool for animal and plant breeding, allowing effective individual selection without phenotypic records through the prediction of genomic breeding value (GBV. To date, genomic selection has focused on a single trait. However, actual breeding often targets multiple correlated traits, and, therefore, joint analysis taking into consideration the correlation between traits, which might result in more accurate GBV prediction than analyzing each trait separately, is suitable for multi-trait genomic selection. This would require an extension of the prediction model for single-trait GBV to multi-trait case. As the computational burden of multi-trait analysis is even higher than that of single-trait analysis, an effective computational method for constructing a multi-trait prediction model is also needed. Results We described a Bayesian regression model incorporating variable selection for jointly predicting GBVs of multiple traits and devised both an MCMC iteration and variational approximation for Bayesian estimation of parameters in this multi-trait model. The proposed Bayesian procedures with MCMC iteration and variational approximation were referred to as MCBayes and varBayes, respectively. Using simulated datasets of SNP genotypes and phenotypes for three traits with high and low heritabilities, we compared the accuracy in predicting GBVs between multi-trait and single-trait analyses as well as between MCBayes and varBayes. The results showed that, compared to single-trait analysis, multi-trait analysis enabled much more accurate GBV prediction for low-heritability traits correlated with high-heritability traits, by utilizing the correlation structure between traits, while the prediction accuracy for uncorrelated low-heritability traits was comparable or less with multi-trait analysis in comparison with single-trait analysis depending on the setting for prior probability that a SNP has zero

  20. Sharing Video Datasets in Design Research

    DEFF Research Database (Denmark)

    Christensen, Bo; Abildgaard, Sille Julie Jøhnk

    2017-01-01

    This paper examines how design researchers, design practitioners and design education can benefit from sharing a dataset. We present the Design Thinking Research Symposium 11 (DTRS11) as an exemplary project that implied sharing video data of design processes and design activity in natural settings...... with a large group of fellow academics from the international community of Design Thinking Research, for the purpose of facilitating research collaboration and communication within the field of Design and Design Thinking. This approach emphasizes the social and collaborative aspects of design research, where...... a multitude of appropriate perspectives and methods may be utilized in analyzing and discussing the singular dataset. The shared data is, from this perspective, understood as a design object in itself, which facilitates new ways of working, collaborating, studying, learning and educating within the expanding...

  1. Interpolation of diffusion weighted imaging datasets

    DEFF Research Database (Denmark)

    Dyrby, Tim B; Lundell, Henrik; Burke, Mark W

    2014-01-01

    anatomical details and signal-to-noise-ratio for reliable fibre reconstruction. We assessed the potential benefits of interpolating DWI datasets to a higher image resolution before fibre reconstruction using a diffusion tensor model. Simulations of straight and curved crossing tracts smaller than or equal......Diffusion weighted imaging (DWI) is used to study white-matter fibre organisation, orientation and structural connectivity by means of fibre reconstruction algorithms and tractography. For clinical settings, limited scan time compromises the possibilities to achieve high image resolution for finer...... interpolation methods fail to disentangle fine anatomical details if PVE is too pronounced in the original data. As for validation we used ex-vivo DWI datasets acquired at various image resolutions as well as Nissl-stained sections. Increasing the image resolution by a factor of eight yielded finer geometrical...

  2. The Statistical Differences Between the Gridded Temperature Datasets, and its Implications for Stochastic Modelling

    Science.gov (United States)

    Fredriksen, H. B.; Løvsletten, O.; Rypdal, M.; Rypdal, K.

    2014-12-01

    Several research groups around the world collect instrumental temperature data and combine them in different ways to obtain global gridded temperature fields. The three most well known datasets are HadCRUT4 produced by the Climatic Research Unit and the Met Office Hadley Centre in UK, one produced by NASA GISS, and one produced by NOAA. Recently Berkeley Earth has also developed a gridded dataset. All these four will be compared in our analysis. The statistical properties we will focus on are the standard deviation and the Hurst exponent. These two parameters are sufficient to describe the temperatures as long-range memory stochastic processes; the standard deviation describes the general fluctuation level, while the Hurst exponent relates the strength of the long-term variability to the strength of the short-term variability. A higher Hurst exponent means that the slow variations are stronger compared to the fast, and that the autocovariance function will have a stronger tail. Hence the Hurst exponent gives us information about the persistence or memory of the process. We make use of these data to show that data averaged over a larger area exhibit higher Hurst exponents and lower variance than data averaged over a smaller area, which provides information about the relationship between temporal and spatial correlations of the temperature fluctuations. Interpolation in space has some similarities with averaging over space, although interpolation is more weighted towards the measurement locations. We demonstrate that the degree of spatial interpolation used can explain some differences observed between the variances and memory exponents computed from the various datasets.

  3. The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

    Science.gov (United States)

    Özgür, Arzucan; Hur, Junguk; He, Yongqun

    2016-01-01

    The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A

  4. Orthology detection combining clustering and synteny for very large datasets.

    Directory of Open Access Journals (Sweden)

    Marcus Lechner

    Full Text Available The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.

  5. Resampling Methods Improve the Predictive Power of Modeling in Class-Imbalanced Datasets

    Directory of Open Access Journals (Sweden)

    Paul H. Lee

    2014-09-01

    Full Text Available In the medical field, many outcome variables are dichotomized, and the two possible values of a dichotomized variable are referred to as classes. A dichotomized dataset is class-imbalanced if it consists mostly of one class, and performance of common classification models on this type of dataset tends to be suboptimal. To tackle such a problem, resampling methods, including oversampling and undersampling can be used. This paper aims at illustrating the effect of resampling methods using the National Health and Nutrition Examination Survey (NHANES wave 2009–2010 dataset. A total of 4677 participants aged ≥20 without self-reported diabetes and with valid blood test results were analyzed. The Classification and Regression Tree (CART procedure was used to build a classification model on undiagnosed diabetes. A participant demonstrated evidence of diabetes according to WHO diabetes criteria. Exposure variables included demographics and socio-economic status. CART models were fitted using a randomly selected 70% of the data (training dataset, and area under the receiver operating characteristic curve (AUC was computed using the remaining 30% of the sample for evaluation (testing dataset. CART models were fitted using the training dataset, the oversampled training dataset, the weighted training dataset, and the undersampled training dataset. In addition, resampling case-to-control ratio of 1:1, 1:2, and 1:4 were examined. Resampling methods on the performance of other extensions of CART (random forests and generalized boosted trees were also examined. CARTs fitted on the oversampled (AUC = 0.70 and undersampled training data (AUC = 0.74 yielded a better classification power than that on the training data (AUC = 0.65. Resampling could also improve the classification power of random forests and generalized boosted trees. To conclude, applying resampling methods in a class-imbalanced dataset improved the classification power of CART, random forests

  6. Exploring the QSAR's predictive truthfulness of the novel N-tuple discrete derivative indices on benchmark datasets.

    Science.gov (United States)

    Martínez-Santiago, O; Marrero-Ponce, Y; Vivas-Reyes, R; Rivera-Borroto, O M; Hurtado, E; Treto-Suarez, M A; Ramos, Y; Vergara-Murillo, F; Orozco-Ugarriza, M E; Martínez-López, Y

    2017-05-01

    Graph derivative indices (GDIs) have recently been defined over N-atoms (N = 2, 3 and 4) simultaneously, which are based on the concept of derivatives in discrete mathematics (finite difference), metaphorical to the derivative concept in classical mathematical analysis. These molecular descriptors (MDs) codify topo-chemical and topo-structural information based on the concept of the derivative of a molecular graph with respect to a given event (S) over duplex, triplex and quadruplex relations of atoms (vertices). These GDIs have been successfully applied in the description of physicochemical properties like reactivity, solubility and chemical shift, among others, and in several comparative quantitative structure activity/property relationship (QSAR/QSPR) studies. Although satisfactory results have been obtained in previous modelling studies with the aforementioned indices, it is necessary to develop new, more rigorous analysis to assess the true predictive performance of the novel structure codification. So, in the present paper, an assessment and statistical validation of the performance of these novel approaches in QSAR studies are executed, as well as a comparison with those of other QSAR procedures reported in the literature. To achieve the main aim of this research, QSARs were developed on eight chemical datasets widely used as benchmarks in the evaluation/validation of several QSAR methods and/or many different MDs (fundamentally 3D MDs). Three to seven variable QSAR models were built for each chemical dataset, according to the original dissection into training/test sets. The models were developed by using multiple linear regression (MLR) coupled with a genetic algorithm as the feature wrapper selection technique in the MobyDigs software. Each family of GDIs (for duplex, triplex and quadruplex) behaves similarly in all modelling, although there were some exceptions. However, when all families were used in combination, the results achieved were quantitatively

  7. BASE MAP DATASET, INYO COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  8. BASE MAP DATASET, JACKSON COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  9. BASE MAP DATASET, KINGFISHER COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  10. [Correlation between feeding index and growth development of 6-36 month-old infants in two counties of western China by applying multiple correspondence analysis].

    Science.gov (United States)

    Chen, Hong-da; Hao, Bo; Kang, Xiao-ping; Zhao, Geng-li; Zhou, Min

    2012-06-18

    To explore the correlation between feeding index and growth development status of infants from two counties of western China by applying the method of multiple correspondence analysis. Two sample counties were randomly selected from the ones that satisfied the research conditions in Shaanxi province and Chongqing in western China. In the study, 472 premature/low birth weight infants (PLBW) and 461 normal term infants (NT) of 6-36 months from the two counties were investigated from September 2010 to November 2010. The SPSS 19.0 software was applied to analyze the data using general statistical analysis and multiple correspondence analysis. In the two counties of western China, the proportion of infants with feeding index at the medium level was the highest, which was between 50% and 60%. In the PLBW group and the NT group, the proportion of low level of feeding index among 6-9 month-old infants was the highest, and the proportion was 33.3% for the PLBW group and 29.4% for the NT group. For both the PLBW group and the NT group, the distribution of feeding index among the different age groups showed significant difference (Pgrowth development of the PLBW lay behind that of the NT. We could see a catching-up trend of the PLBW with medium or good level of feeding index, but their growth development index was still at a lower level than that of the NT with the same level of feeding condition. Through multiple correspondence analyses, the outcomes of PLBW corresponded and strongly correlated with low level of feeding index, low level of growth development index, mother's low education degree and low annual family income. And the outcomes of NT corresponded and strongly correlated with medium/good level of feeding index, medium level of growth development status, mother's medium/high education degree and medium/high level of annual family income. There are good correspondence correlations at different hierarchical levels of the infants' group, feeding index, growth

  11. Correlation Dimension Estimates of Global and Local Temperature Data.

    Science.gov (United States)

    Wang, Qiang

    1995-11-01

    The author has attempted to detect the presence of low-dimensional deterministic chaos in temperature data by estimating the correlation dimension with the Hill estimate that has been recently developed by Mikosch and Wang. There is no convincing evidence of low dimensionality with either global dataset (Southern Hemisphere monthly average temperatures from 1858 to 1984) or local temperature dataset (daily minimums at Auckland, New Zealand). Any apparent reduction in the dimension estimates appears to be due large1y, if not entirely, to effects of statistical bias, but neither is it a purely random stochastic process. The dimension of the climatic attractor may be significantly larger than 10.

  12. Interobserver variability of patient positioning using four different CT datasets for image registration in lung stereotactic body radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Oechsner, Markus [Technical University of Munich, Department of Radiation Oncology, Klinikum rechts der Isar, Muenchen (Germany); Technical University of Munich, Zentrum fuer Stereotaxie und personalisierte Hochpraezisionsstrahlentherapie (StereotakTUM), Munich (Germany); Chizzali, Barbara; Devecka, Michal; Muench, Stefan [Technical University of Munich, Department of Radiation Oncology, Klinikum rechts der Isar, Muenchen (Germany); Combs, Stephanie Elisabeth; Wilkens, Jan Jakob; Duma, Marciana Nona [Technical University of Munich, Department of Radiation Oncology, Klinikum rechts der Isar, Muenchen (Germany); Technical University of Munich, Zentrum fuer Stereotaxie und personalisierte Hochpraezisionsstrahlentherapie (StereotakTUM), Munich (Germany); Helmholtz Zentrum Muenchen, Institute of Innovative Radiotherapy (iRT), Munich (Germany)

    2017-10-15

    To assess the impact of different reference CT datasets on manual image registration with free-breathing three-dimensional (3D) cone beam CTs (FB-CBCT) for patient positioning by several observers. For 48 patients with lung lesions, manual image registration with FB-CBCTs was performed by four observers. A slow planning CT (PCT), average intensity projection (AIP), maximum intensity projection (MIP), and midventilation CT (MidV) were used as reference images. Couch shift differences between the four reference CT datasets for each observer as well as shift differences between the observers for the same reference CT dataset were determined. Statistical analyses were performed and correlations between the registration differences and the 3D tumor motion and the CBCT score were calculated. The mean 3D shift difference between different reference CT datasets was the smallest for AIPvsMIP (range 1.1-2.2 mm) and the largest for MidVvsPCT (2.8-3.5 mm) with differences >10 mm. The 3D shifts showed partially significant correlations to 3D tumor motion and CBCT score. The interobserver comparison for the same reference CTs resulted in the smallest ∇3D mean differences and mean ∇3D standard deviation for ∇AIP (1.5 ± 0.7 mm, 0.7 ± 0.4 mm). The maximal 3D shift difference between observers was 10.4 mm (∇MidV). Both 3D tumor motion and mean CBCT score correlated with the shift differences (R{sub s} = 0.336-0.740). The applied reference CT dataset impacts image registration and causes interobserver variabilities. The 3D tumor motion and CBCT quality affect shift differences. The smallest differences were found for AIP which might be the most appropriate CT dataset for image registration with FB-CBCT. (orig.) [German] Untersuchung des Einflusses verschiedener Referenz-CT-Datensaetze auf die manuelle Bildregistrierung mit dreidimensionaler (3D) ConeBeam-Computertomographie in freier Atmung (FB-CBCT) zur Patientenpositionierung durch verschiedene Observer. Bei 48 Patienten

  13. Glyco-centric lectin magnetic bead array (LeMBA − proteomics dataset of human serum samples from healthy, Barrett׳s esophagus and esophageal adenocarcinoma individuals

    Directory of Open Access Journals (Sweden)

    Alok K. Shah

    2016-06-01

    Full Text Available This data article describes serum glycoprotein biomarker discovery and qualification datasets generated using lectin magnetic bead array (LeMBA – mass spectrometry techniques, “Serum glycoprotein biomarker discovery and qualification pipeline reveals novel diagnostic biomarker candidates for esophageal adenocarcinoma” [1]. Serum samples collected from healthy, metaplastic Barrett׳s esophagus (BE and esophageal adenocarcinoma (EAC individuals were profiled for glycoprotein subsets via differential lectin binding. The biomarker discovery proteomics dataset consisting of 20 individual lectin pull-downs for 29 serum samples with a spiked-in internal standard chicken ovalbumin protein has been deposited in the PRIDE partner repository of the ProteomeXchange Consortium with the data set identifier PRIDE: http://www.ebi.ac.uk/pride/archive/projects/PXD002442. Annotated MS/MS spectra for the peptide identifications can be viewed using MS-Viewer (〈http://prospector2.ucsf.edu/prospector/cgi-bin/msform.cgi?form=msviewer〉 using search key “jn7qafftux”. The qualification dataset contained 6-lectin pulldown-coupled multiple reaction monitoring-mass spectrometry (MRM-MS data for 41 protein candidates, from 60 serum samples. This dataset is available as a supplemental files with the original publication [1].

  14. Multiplicity correlations in the forward and backward hemispheres in the center of mass in bar pp and pp interactions at 32 GeV/c

    International Nuclear Information System (INIS)

    Bravina, L.V.; Amelin, N.S.; Bogolyubskii, M.Y.; Bumazhnov, V.A.; Vinitskii, A.A.; Ermolov, P.F.; Zhautykov, B.O.; Zabrodin, E.E.; Kiryunin, A.E.; Klochkov, M.A.; Kotova, A.I.; Kruglov, N.A.; Levitskii, M.S.; Lukina, O.Y.; Minaenko, A.A.; Moiseev, A.M.; Murzin, V.S.; Proskuryakov, A.S.; Rizatdinova, F.K.; Sarycheva, L.I.; Smirnova, L.N.; Starchenko, E.A.; Ukhanov, M.N.; Chekulaev, S.V.

    1989-01-01

    A rise in the average multiplicity of particles in one hemisphere in the c.m.s. of bar pp and pp interactions with energy (s) 1/2 =7.86 GeV is observed with increase of the number of particles in the other hemisphere. The correlation parameter reaches b=0.19±0.01 and 0.10±0.02 in inelastic bar pp and pp interactions respectively. The observed correlations are reproduced in the quark-gluon string model

  15. Neural correlates of alerting and orienting impairment in multiple sclerosis patients.

    Science.gov (United States)

    Vázquez-Marrufo, Manuel; Galvao-Carmona, Alejandro; González-Rosa, Javier J; Hidalgo-Muñoz, Antonio R; Borges, Mónica; Ruiz-Peña, Juan Luis; Izquierdo, Guillermo

    2014-01-01

    A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (pmultiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients.

  16. Image segmentation evaluation for very-large datasets

    Science.gov (United States)

    Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

    2016-03-01

    With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

  17. A New Dataset Size Reduction Approach for PCA-Based Classification in OCR Application

    Directory of Open Access Journals (Sweden)

    Mohammad Amin Shayegan

    2014-01-01

    Full Text Available A major problem of pattern recognition systems is due to the large volume of training datasets including duplicate and similar training samples. In order to overcome this problem, some dataset size reduction and also dimensionality reduction techniques have been introduced. The algorithms presently used for dataset size reduction usually remove samples near to the centers of classes or support vector samples between different classes. However, the samples near to a class center include valuable information about the class characteristics and the support vector is important for evaluating system efficiency. This paper reports on the use of Modified Frequency Diagram technique for dataset size reduction. In this new proposed technique, a training dataset is rearranged and then sieved. The sieved training dataset along with automatic feature extraction/selection operation using Principal Component Analysis is used in an OCR application. The experimental results obtained when using the proposed system on one of the biggest handwritten Farsi/Arabic numeral standard OCR datasets, Hoda, show about 97% accuracy in the recognition rate. The recognition speed increased by 2.28 times, while the accuracy decreased only by 0.7%, when a sieved version of the dataset, which is only as half as the size of the initial training dataset, was used.

  18. Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix.

    Science.gov (United States)

    Zhang, Haicang; Gao, Yujuan; Deng, Minghua; Wang, Chao; Zhu, Jianwei; Li, Shuai Cheng; Zheng, Wei-Mou; Bu, Dongbo

    2016-03-25

    Strategies for correlation analysis in protein contact prediction often encounter two challenges, namely, the indirect coupling among residues, and the background correlations mainly caused by phylogenetic biases. While various studies have been conducted on how to disentangle indirect coupling, the removal of background correlations still remains unresolved. Here, we present an approach for removing background correlations via low-rank and sparse decomposition (LRS) of a residue correlation matrix. The correlation matrix can be constructed using either local inference strategies (e.g., mutual information, or MI) or global inference strategies (e.g., direct coupling analysis, or DCA). In our approach, a correlation matrix was decomposed into two components, i.e., a low-rank component representing background correlations, and a sparse component representing true correlations. Finally the residue contacts were inferred from the sparse component of correlation matrix. We trained our LRS-based method on the PSICOV dataset, and tested it on both GREMLIN and CASP11 datasets. Our experimental results suggested that LRS significantly improves the contact prediction precision. For example, when equipped with the LRS technique, the prediction precision of MI and mfDCA increased from 0.25 to 0.67 and from 0.58 to 0.70, respectively (Top L/10 predicted contacts, sequence separation: 5 AA, dataset: GREMLIN). In addition, our LRS technique also consistently outperforms the popular denoising technique APC (average product correction), on both local (MI_LRS: 0.67 vs MI_APC: 0.34) and global measures (mfDCA_LRS: 0.70 vs mfDCA_APC: 0.67). Interestingly, we found out that when equipped with our LRS technique, local inference strategies performed in a comparable manner to that of global inference strategies, implying that the application of LRS technique narrowed down the performance gap between local and global inference strategies. Overall, our LRS technique greatly facilitates

  19. The CMS dataset bookkeeping service

    Science.gov (United States)

    Afaq, A.; Dolgert, A.; Guo, Y.; Jones, C.; Kosyakov, S.; Kuznetsov, V.; Lueking, L.; Riley, D.; Sekhri, V.

    2008-07-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems.

  20. The CMS dataset bookkeeping service

    Energy Technology Data Exchange (ETDEWEB)

    Afaq, A; Guo, Y; Kosyakov, S; Lueking, L; Sekhri, V [Fermilab, Batavia, Illinois 60510 (United States); Dolgert, A; Jones, C; Kuznetsov, V; Riley, D [Cornell University, Ithaca, New York 14850 (United States)

    2008-07-15

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems.

  1. The CMS dataset bookkeeping service

    International Nuclear Information System (INIS)

    Afaq, A; Guo, Y; Kosyakov, S; Lueking, L; Sekhri, V; Dolgert, A; Jones, C; Kuznetsov, V; Riley, D

    2008-01-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems

  2. The CMS dataset bookkeeping service

    International Nuclear Information System (INIS)

    Afaq, Anzar; Dolgert, Andrew; Guo, Yuyi; Jones, Chris; Kosyakov, Sergey; Kuznetsov, Valentin; Lueking, Lee; Riley, Dan; Sekhri, Vijay

    2007-01-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems

  3. Results of the Collaborative Energy and Water Cycle Information Services (CEWIS) Workshop on Heterogeneous Dataset Analysis Preparation

    Science.gov (United States)

    Kempler, Steven; Teng, William; Acker, James; Belvedere, Deborah; Liu, Zhong; Leptoukh, Gregory

    2010-01-01

    In support of the NASA Energy and Water Cycle Study (NEWS), the Collaborative Energy and Water Cycle Information Services (CEWIS), sponsored by NEWS Program Manager Jared Entin, was initiated to develop an evolving set of community-based data and information services that would facilitate users to locate, access, and bring together multiple distributed heterogeneous energy and water cycle datasets. The CEWIS workshop, June 15-16, 2010, at NASA/GSFC, was the initial step of the process, starting with identifying and scoping the issues, as defined by the community.

  4. Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

    Science.gov (United States)

    Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

    2013-03-21

    Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group

  5. A cross-country Exchange Market Pressure (EMP dataset

    Directory of Open Access Journals (Sweden)

    Mohit Desai

    2017-06-01

    Full Text Available The data presented in this article are related to the research article titled - “An exchange market pressure measure for cross country analysis” (Patnaik et al. [1]. In this article, we present the dataset for Exchange Market Pressure values (EMP for 139 countries along with their conversion factors, ρ (rho. Exchange Market Pressure, expressed in percentage change in exchange rate, measures the change in exchange rate that would have taken place had the central bank not intervened. The conversion factor ρ can interpreted as the change in exchange rate associated with $1 billion of intervention. Estimates of conversion factor ρ allow us to calculate a monthly time series of EMP for 139 countries. Additionally, the dataset contains the 68% confidence interval (high and low values for the point estimates of ρ’s. Using the standard errors of estimates of ρ’s, we obtain one sigma intervals around mean estimates of EMP values. These values are also reported in the dataset.

  6. A cross-country Exchange Market Pressure (EMP) dataset.

    Science.gov (United States)

    Desai, Mohit; Patnaik, Ila; Felman, Joshua; Shah, Ajay

    2017-06-01

    The data presented in this article are related to the research article titled - "An exchange market pressure measure for cross country analysis" (Patnaik et al. [1]). In this article, we present the dataset for Exchange Market Pressure values (EMP) for 139 countries along with their conversion factors, ρ (rho). Exchange Market Pressure, expressed in percentage change in exchange rate, measures the change in exchange rate that would have taken place had the central bank not intervened. The conversion factor ρ can interpreted as the change in exchange rate associated with $1 billion of intervention. Estimates of conversion factor ρ allow us to calculate a monthly time series of EMP for 139 countries. Additionally, the dataset contains the 68% confidence interval (high and low values) for the point estimates of ρ 's. Using the standard errors of estimates of ρ 's, we obtain one sigma intervals around mean estimates of EMP values. These values are also reported in the dataset.

  7. The new Planetary Science Archive: A tool for exploration and discovery of scientific datasets from ESA's planetary missions

    Science.gov (United States)

    Heather, David

    2016-07-01

    Introduction: The Planetary Science Archive (PSA) is the European Space Agency's (ESA) repository of science data from all planetary science and exploration missions. The PSA provides access to scientific datasets through various interfaces (e.g. FTP browser, Map based, Advanced search, and Machine interface): http://archives.esac.esa.int/psa All datasets are scientifically peer-reviewed by independent scientists, and are compliant with the Planetary Data System (PDS) standards. Updating the PSA: The PSA is currently implementing a number of significant changes, both to its web-based interface to the scientific community, and to its database structure. The new PSA will be up-to-date with versions 3 and 4 of the PDS standards, as PDS4 will be used for ESA's upcoming ExoMars and BepiColombo missions. The newly designed PSA homepage will provide direct access to scientific datasets via a text search for targets or missions. This will significantly reduce the complexity for users to find their data and will promote one-click access to the datasets. Additionally, the homepage will provide direct access to advanced views and searches of the datasets. Users will have direct access to documentation, information and tools that are relevant to the scientific use of the dataset, including ancillary datasets, Software Interface Specification (SIS) documents, and any tools/help that the PSA team can provide. A login mechanism will provide additional functionalities to the users to aid / ease their searches (e.g. saving queries, managing default views). Queries to the PSA database will be possible either via the homepage (for simple searches of missions or targets), or through a filter menu for more tailored queries. The filter menu will offer multiple options to search for a particular dataset or product, and will manage queries for both in-situ and remote sensing instruments. Parameters such as start-time, phase angle, and heliocentric distance will be emphasized. A further

  8. Multi-contrast, isotropic, single-slab 3D MR imaging in multiple sclerosis

    NARCIS (Netherlands)

    Moraal, B.; Roosendaal, S.D.; Pouwels, P.J.W.; Vrenken, H.; van Schijndel, R.A.; Meier, D.S.; Guttmann, C.R.G.; Geurts, J.J.G.; Barkhof, F.

    2008-01-01

    To describe signal and contrast properties of an isotropic, single-slab 3D dataset [double inversion-recovery (DIR), fluid-attenuated inversion recovery (FLAIR), T2, and T1-weighted magnetization prepared rapid acquisition gradient-echo (MPRAGE)] and to evaluate its performance in detecting multiple

  9. "Bunched Black Swans" in Complex Geosystems: Cross-Disciplinary Approaches to the Additive and Multiplicative Modelling of Correlated Extreme Bursts

    Science.gov (United States)

    Watkins, N. W.; Rypdal, M.; Lovsletten, O.

    2012-12-01

    For all natural hazards, the question of when the next "extreme event" (c.f. Taleb's "black swans") is expected is of obvious importance. In the environmental sciences users often frame such questions in terms of average "return periods", e.g. "is an X meter rise in the Thames water level a 1-in-Y year event ?". Frequently, however, we also care about the emergence of correlation, and whether the probability of several big events occurring in close succession is truly independent, i.e. are the black swans "bunched". A "big event", or a "burst", defined by its integrated signal above a threshold, might be a single, very large, event, or, instead, could in fact be a correlated series of "smaller" (i.e. less wildly fluctuating) events. Several available stochastic approaches provide quantitative information about such bursts, including Extreme Value Theory (EVT); the theory of records; level sets; sojourn times; and models of space-time "avalanches" of activity in non-equilibrium systems. Some focus more on the probability of single large events. Others are more concerned with extended dwell times above a given spatiotemporal threshold: However, the state of the art is not yet fully integrated, and the above-mentioned approaches differ in fundamental aspects. EVT is perhaps the best known in the geosciences. It is concerned with the distribution obeyed by the extremes of datasets, e.g. the 100 values obtained by considering the largest daily temperature recorded in each of the years of a century. However, the pioneering work from the 1920s on which EVT originally built was based on independent identically distributed samples, and took no account of memory and correlation that characterise many natural hazard time series. Ignoring this would fundamentally limit our ability to forecast; so much subsequent activity has been devoted to extending EVT to encompass dependence. A second group of approaches, by contrast, has notions of time and thus possible non

  10. Effects of correlations and fees in random multiplicative environments: Implications for portfolio management

    Science.gov (United States)

    Alper, Ofer; Somekh-Baruch, Anelia; Pirvandy, Oz; Schaps, Malka; Yaari, Gur

    2017-08-01

    Geometric Brownian motion (GBM) is frequently used to model price dynamics of financial assets, and a weighted average of multiple GBMs is commonly used to model a financial portfolio. Diversified portfolios can lead to an increased exponential growth compared to a single asset by effectively reducing the effective noise. The sum of GBM processes is no longer a log-normal process and has a complex statistical properties. The nonergodicity of the weighted average process results in constant degradation of the exponential growth from the ensemble average toward the time average. One way to stay closer to the ensemble average is to maintain a balanced portfolio: keep the relative weights of the different assets constant over time. To keep these proportions constant, whenever assets values change, it is necessary to rebalance their relative weights, exposing this strategy to fees (transaction costs). Two strategies that were suggested in the past for cases that involve fees are rebalance the portfolio periodically and rebalance it in a partial way. In this paper, we study these two strategies in the presence of correlations and fees. We show that using periodic and partial rebalance strategies, it is possible to maintain a steady exponential growth while minimizing the losses due to fees. We also demonstrate how these redistribution strategies perform in a phenomenal way on real-world market data, despite the fact that not all assumptions of the model hold in these real-world systems. Our results have important implications for stochastic dynamics in general and to portfolio management in particular, as we show that there is a superior alternative to the common buy-and-hold strategy, even in the presence of correlations and fees.

  11. Effects of correlations and fees in random multiplicative environments: Implications for portfolio management.

    Science.gov (United States)

    Alper, Ofer; Somekh-Baruch, Anelia; Pirvandy, Oz; Schaps, Malka; Yaari, Gur

    2017-08-01

    Geometric Brownian motion (GBM) is frequently used to model price dynamics of financial assets, and a weighted average of multiple GBMs is commonly used to model a financial portfolio. Diversified portfolios can lead to an increased exponential growth compared to a single asset by effectively reducing the effective noise. The sum of GBM processes is no longer a log-normal process and has a complex statistical properties. The nonergodicity of the weighted average process results in constant degradation of the exponential growth from the ensemble average toward the time average. One way to stay closer to the ensemble average is to maintain a balanced portfolio: keep the relative weights of the different assets constant over time. To keep these proportions constant, whenever assets values change, it is necessary to rebalance their relative weights, exposing this strategy to fees (transaction costs). Two strategies that were suggested in the past for cases that involve fees are rebalance the portfolio periodically and rebalance it in a partial way. In this paper, we study these two strategies in the presence of correlations and fees. We show that using periodic and partial rebalance strategies, it is possible to maintain a steady exponential growth while minimizing the losses due to fees. We also demonstrate how these redistribution strategies perform in a phenomenal way on real-world market data, despite the fact that not all assumptions of the model hold in these real-world systems. Our results have important implications for stochastic dynamics in general and to portfolio management in particular, as we show that there is a superior alternative to the common buy-and-hold strategy, even in the presence of correlations and fees.

  12. Correlations of pseudo-random numbers of multiplicative sequence

    International Nuclear Information System (INIS)

    Bukin, A.D.

    1989-01-01

    An algorithm is suggested for searching with a computer in unit n-dimensional cube the sets of planes where all the points fall whose coordinates are composed of n successive pseudo-random numbers of multiplicative sequence. This effect should be taken into account in Monte-Carlo calculations with definite constructive dimension. The parameters of these planes are obtained for three random number generators. 2 refs.; 2 tabs

  13. Knowledge Mining from Clinical Datasets Using Rough Sets and Backpropagation Neural Network

    Directory of Open Access Journals (Sweden)

    Kindie Biredagn Nahato

    2015-01-01

    Full Text Available The availability of clinical datasets and knowledge mining methodologies encourages the researchers to pursue research in extracting knowledge from clinical datasets. Different data mining techniques have been used for mining rules, and mathematical models have been developed to assist the clinician in decision making. The objective of this research is to build a classifier that will predict the presence or absence of a disease by learning from the minimal set of attributes that has been extracted from the clinical dataset. In this work rough set indiscernibility relation method with backpropagation neural network (RS-BPNN is used. This work has two stages. The first stage is handling of missing values to obtain a smooth data set and selection of appropriate attributes from the clinical dataset by indiscernibility relation method. The second stage is classification using backpropagation neural network on the selected reducts of the dataset. The classifier has been tested with hepatitis, Wisconsin breast cancer, and Statlog heart disease datasets obtained from the University of California at Irvine (UCI machine learning repository. The accuracy obtained from the proposed method is 97.3%, 98.6%, and 90.4% for hepatitis, breast cancer, and heart disease, respectively. The proposed system provides an effective classification model for clinical datasets.

  14. Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

    Science.gov (United States)

    Bansal, Ravi; Peterson, Bradley S

    2018-06-01

    Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal

  15. Multiplicity distribution and multiplicity moment of black and grey particles in high energy nucleus–nucleus interactions

    International Nuclear Information System (INIS)

    Ghosh, Dipak; Deb, Argha; Datta, Utpal; Bhattacharyya, S.

    2011-01-01

    In this paper we have studied the multiplicity distribution of black and grey particles emitted from 16 O–AgBr interactions at 2.1 AGeV and 60 AGeV. We have also calculated the multiplicity moment up to the fifth order for both the interactions and for both kinds of emitted particles. The variation of multiplicity moment with the order number has been investigated. It is seen that in the case of black particles multiplicity moment up to fourth order remains almost constant as energy increases from 2.1 AGeV to 60 AGeV. Fifth order multiplicity moment increases insignificantly with energy. However in the case of grey particles no such constancy of multiplicity moment with energy of the projectile beam is obtained. Later we have extended our study on the basis of Regge–Mueller approach to find the existence of second order correlation during the emission of black as well as the grey particles. The second Mueller moment is found to be positive and it increases as energy increases in the case of black particles. On the contrary in the case of grey particles the second Mueller moment decreases with energy. It can be concluded that as energy increases correlation among the black particles increases. On the other hand with the increase of energy correlation among the grey particles is found to diminish. (author)

  16. Multiple sclerosis

    International Nuclear Information System (INIS)

    Sadashima, Hiromichi; Kusaka, Hirofumi; Imai, Terukuni; Takahashi, Ryosuke; Matsumoto, Sadayuki; Yamamoto, Toru; Yamasaki, Masahiro; Maya, Kiyomi

    1986-01-01

    Eleven patients with a definite diagnosis of multiple sclerosis were examined in terms of correlations between the clinical features and the results of cranial computed tomography (CT), and magnetic resonance imaging (MRI). Results: In 5 of the 11 patients, both CT and MRI demonstrated lesions consistent with a finding of multiple sclerosis. In 3 patients, only MRI demonstrated lesions. In the remaining 3 patients, neither CT nor MRI revealed any lesion in the brain. All 5 patients who showed abnormal findings on both CT and MRI had clinical signs either of cerebral or brainstem - cerebellar lesions. On the other hand, two of the 3 patients with normal CT and MRI findings had optic-nerve and spinal-cord signs. Therefore, our results suggested relatively good correlations between the clinical features, CT, and MRI. MRI revealed cerebral lesions in two of the four patients with clinical signs of only optic-nerve and spinal-cord lesions. MRI demonstrated sclerotic lesions in 3 of the 6 patients whose plaques were not detected by CT. In conclusion, MRI proved to be more helpful in the demonstration of lesions attributable to chronic multiple sclerosis. (author)

  17. Geographical and seasonal correlation of multiple sclerosis to sporadic schizophrenia

    Directory of Open Access Journals (Sweden)

    Fritzsche Markus

    2002-12-01

    Full Text Available Abstract Background Clusters by season and locality reveal a striking epidemiological overlap between sporadic schizophrenia and multiple sclerosis (MS. As the birth excesses of those individuals who later in life develop schizophrenia mirror the seasonal distribution of Ixodid ticks, a meta analysis has been performed between all neuropsychiatric birth excesses including MS and the epidemiology of spirochaetal infectious diseases. Results The prevalence of MS and schizophrenic birth excesses entirely spares the tropical belt where human treponematoses are endemic, whereas in more temperate climates infection rates of Borrelia garinii in ticks collected from seabirds match the global geographic distribution of MS. If the seasonal fluctuations of Lyme borreliosis in Europe are taken into account, the birth excesses of MS and those of schizophrenia are nine months apart, reflecting the activity of Ixodes ricinus at the time of embryonic implantation and birth. In America, this nine months' shift between MS and schizophrenic births is also reflected by the periodicity of Borrelia burgdorferi transmitting Ixodes pacificus ticks along the West Coast and the periodicity of Ixodes scapularis along the East Coast. With respect to Ixodid tick activity, amongst the neuropsychiatric birth excesses only amyotrophic lateral sclerosis (ALS shows a similar seasonal trend. Conclusion It cannot be excluded at present that maternal infection by Borrelia burgdorferi poses a risk to the unborn. The seasonal and geographical overlap between schizophrenia, MS and neuroborreliosis rather emphasises a causal relation that derives from exposure to a flagellar virulence factor at conception and delivery. It is hoped that the pathogenic correlation of spirochaetal virulence to temperature and heat shock proteins (HSP might encourage a new direction of research in molecular epidemiology.

  18. A study on land surface phenology in eastern China based on SPOT/VGT datasets

    International Nuclear Information System (INIS)

    Han, Guifeng; Xie, Hongxia

    2014-01-01

    Vegetation phenology provides a relevant indicator of the response of terrestrial ecosystems to climate change. In this study, vegetation phenology measurements were extracted and the spatial distributions were investigated using time series SPOT/VGT NDVI datasets for eastern China. Four phenology measurements were analyzed: the start of the growing season (SOS), the end of the growing season (EOS), the length of the growing season (GSL) and the time of the peak NDVI. The SOS in the northern part of the study area occurred earlier than in the rest of the study area due to larger amounts of cropland. The EOS showed a strong latitudinal pattern, especially in the southern portion of the study area. The GSL also showed a clear spatial pattern along the latitudinal gradient from north to south. The time of peak NDVI did not show a spatial pattern along the latitudinal gradient, which is likely due to the influence of vegetation types and the types of farming systems. In addition, there were no significant correlations between longitude and the four phenology measurements. SOS does not correlate with latitude, longitude or altitude, but EOS, GSL and the time of peak NDVI all correlated with latitude and altitude

  19. Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

    Science.gov (United States)

    Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

    2014-01-01

    Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution

  20. Characterizing Organic Aerosol Processes and Climatically Relevant Properties via Advanced and Integrated Analyses of Aerosol Mass Spectrometry Datasets from DOE Campaigns and ACRF Measurements. Final report for DE-SC0007178

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qi [Univ. of California, Davis, CA (United States)

    2017-05-21

    Organic aerosols (OA) are an important but poorly characterized component of the earth’s climate system. Enormous complexities commonly associated with OA composition and life cycle processes have significantly complicated the simulation and quantification of aerosol effects. To unravel these complexities and improve understanding of the properties, sources, formation, evolution processes, and radiative properties of atmospheric OA, we propose to perform advanced and integrated analyses of multiple DOE aerosol mass spectrometry datasets, including two high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) datasets from intensive field campaigns on the aerosol life cycle and the Aerosol Chemical Speciation Monitor (ACSM) datasets from long-term routine measurement programs at ACRF sites. In this project, we will focus on 1) characterizing the chemical (i.e., composition, organic elemental ratios), physical (i.e., size distribution and volatility), and radiative (i.e., sub- and super-saturated growth) properties of organic aerosols, 2) examining the correlations of these properties with different source and process regimes (e.g., primary, secondary, urban, biogenic, biomass burning, marine, or mixtures), 3) quantifying the evolutions of these properties as a function of photochemical processing, 4) identifying and characterizing special cases for important processes such as SOA formation and new particle formation and growth, and 5) correlating size-resolved aerosol chemistry with measurements of radiative properties of aerosols to determine the climatically relevant properties of OA and characterize the relationship between these properties and processes of atmospheric aerosol organics. Our primary goal is to improve a process-level understanding of the life cycle of organic aerosols in the Earth’s atmosphere. We will also aim at bridging between observations and models via synthesizing and translating the results and insights generated from this