The Equivalence of Three Statistical Packages for Performing Hierarchical Cluster Analysis

ERIC Educational Resources Information Center

Blashfield, Roger

1977-01-01

Three different software programs which contain hierarchical agglomerative cluster analysis procedures were shown to generate different solutions on the same data set using apparently the same options. The basis for the differences in the solutions was the formulae used to calculate Euclidean distance. (Author/JKS)

Exploring root symbiotic programs in the model legume Medicago truncatula using EST analysis.

PubMed

Journet, Etienne-Pascal; van Tuinen, Diederik; Gouzy, Jérome; Crespeau, Hervé; Carreau, Véronique; Farmer, Mary-Jo; Niebel, Andreas; Schiex, Thomas; Jaillon, Olivier; Chatagnier, Odile; Godiard, Laurence; Micheli, Fabienne; Kahn, Daniel; Gianinazzi-Pearson, Vivienne; Gamas, Pascal

2002-12-15

We report on a large-scale expressed sequence tag (EST) sequencing and analysis program aimed at characterizing the sets of genes expressed in roots of the model legume Medicago truncatula during interactions with either of two microsymbionts, the nitrogen-fixing bacterium Sinorhizobium meliloti or the arbuscular mycorrhizal fungus Glomus intraradices. We have designed specific tools for in silico analysis of EST data, in relation to chimeric cDNA detection, EST clustering, encoded protein prediction, and detection of differential expression. Our 21 473 5'- and 3'-ESTs could be grouped into 6359 EST clusters, corresponding to distinct virtual genes, along with 52 498 other M.truncatula ESTs available in the dbEST (NCBI) database that were recruited in the process. These clusters were manually annotated, using a specifically developed annotation interface. Analysis of EST cluster distribution in various M.truncatula cDNA libraries, supported by a refined R test to evaluate statistical significance and by 'electronic northern' representation, enabled us to identify a large number of novel genes predicted to be up- or down-regulated during either symbiotic root interaction. These in silico analyses provide a first global view of the genetic programs for root symbioses in M.truncatula. A searchable database has been built and can be accessed through a public interface.

Potential of SNP markers for the characterization of Brazilian cassava germplasm.

PubMed

de Oliveira, Eder Jorge; Ferreira, Cláudia Fortes; da Silva Santos, Vanderlei; de Jesus, Onildo Nunes; Oliveira, Gilmara Alvarenga Fachardo; da Silva, Maiane Suzarte

2014-06-01

High-throughput markers, such as SNPs, along with different methodologies were used to evaluate the applicability of the Bayesian approach and the multivariate analysis in structuring the genetic diversity in cassavas. The objective of the present work was to evaluate the diversity and genetic structure of the largest cassava germplasm bank in Brazil. Complementary methodological approaches such as discriminant analysis of principal components (DAPC), Bayesian analysis and molecular analysis of variance (AMOVA) were used to understand the structure and diversity of 1,280 accessions genotyped using 402 single nucleotide polymorphism markers. The genetic diversity (0.327) and the average observed heterozygosity (0.322) were high considering the bi-allelic markers. In terms of population, the presence of a complex genetic structure was observed indicating the formation of 30 clusters by DAPC and 34 clusters by Bayesian analysis. Both methodologies presented difficulties and controversies in terms of the allocation of some accessions to specific clusters. However, the clusters suggested by the DAPC analysis seemed to be more consistent for presenting higher probability of allocation of the accessions within the clusters. Prior information related to breeding patterns and geographic origins of the accessions were not sufficient for providing clear differentiation between the clusters according to the AMOVA analysis. In contrast, the F ST was maximized when considering the clusters suggested by the Bayesian and DAPC analyses. The high frequency of germplasm exchange between producers and the subsequent alteration of the name of the same material may be one of the causes of the low association between genetic diversity and geographic origin. The results of this study may benefit cassava germplasm conservation programs, and contribute to the maximization of genetic gains in breeding programs.

An algol program for dissimilarity analysis: a divisive-omnithetic clustering technique

USGS Publications Warehouse

Tipper, J.C.

1979-01-01

Clustering techniques are used properly to generate hypotheses about patterns in data. Of the hierarchical techniques, those which are divisive and omnithetic possess many theoretically optimal properties. One such method, dissimilarity analysis, is implemented here in ALGOL 60, and determined to be competitive computationally with most other methods. ?? 1979.

Profiles of behavioral problems in children who witness domestic violence.

PubMed

Spilsbury, James C; Kahana, Shoshana; Drotar, Dennis; Creeden, Rosemary; Flannery, Daniel J; Friedman, Steve

2008-01-01

Unlike previous investigations of shelter-based samples, our study examined whether profiles of adjustment problems occurred in a community-program-based sample of 175 school-aged children exposed to domestic violence. Cluster analysis revealed three stable profiles/clusters. The largest cluster (69%) consisted of children below clinical thresholds for any internalizing or externalizing problem. Children in the next largest cluster (18%) were characterized as having externalizing problems with or without internalizing problems. The smallest cluster (13%) consisted of children with internalizing problems only. Comparison across demographic and violence characteristics revealed that the profiles differed by child gender, mother's education, child's lifetime exposure to violence, and aspects of the event precipitating contact with the community program. Clinical and future research implications of study findings are discussed.

A cluster analysis method for identification of subpopulations of cells in flow cytometric list-mode arrays

NASA Technical Reports Server (NTRS)

Li, Z. K.

1985-01-01

A specialized program was developed for flow cytometric list-mode data using an heirarchical tree method for identifying and enumerating individual subpopulations, the method of principal components for a two-dimensional display of 6-parameter data array, and a standard sorting algorithm for characterizing subpopulations. The program was tested against a published data set subjected to cluster analysis and experimental data sets from controlled flow cytometry experiments using a Coulter Electronics EPICS V Cell Sorter. A version of the program in compiled BASIC is usable on a 16-bit microcomputer with the MS-DOS operating system. It is specialized for 6 parameters and up to 20,000 cells. Its two-dimensional display of Euclidean distances reveals clusters clearly, as does its 1-dimensional display. The identified subpopulations can, in suitable experiments, be related to functional subpopulations of cells.

Application of clustering methods: Regularized Markov clustering (R-MCL) for analyzing dengue virus similarity

NASA Astrophysics Data System (ADS)

Lestari, D.; Raharjo, D.; Bustamam, A.; Abdillah, B.; Widhianto, W.

2017-07-01

Dengue virus consists of 10 different constituent proteins and are classified into 4 major serotypes (DEN 1 - DEN 4). This study was designed to perform clustering against 30 protein sequences of dengue virus taken from Virus Pathogen Database and Analysis Resource (VIPR) using Regularized Markov Clustering (R-MCL) algorithm and then we analyze the result. By using Python program 3.4, R-MCL algorithm produces 8 clusters with more than one centroid in several clusters. The number of centroid shows the density level of interaction. Protein interactions that are connected in a tissue, form a complex protein that serves as a specific biological process unit. The analysis of result shows the R-MCL clustering produces clusters of dengue virus family based on the similarity role of their constituent protein, regardless of serotypes.

Cluster analysis of phytoplankton data collected from the National Stream Quality Accounting Network in the Tennessee River basin, 1974-81

USGS Publications Warehouse

Stephens, D.W.; Wangsgard, J.B.

1988-01-01

A computer program, Numerical Taxonomy System of Multivariate Statistical Programs (NTSYS), was used with interfacing software to perform cluster analyses of phytoplankton data stored in the biological files of the U.S. Geological Survey. The NTSYS software performs various types of statistical analyses and is capable of handling a large matrix of data. Cluster analyses were done on phytoplankton data collected from 1974 to 1981 at four national Stream Quality Accounting Network stations in the Tennessee River basin. Analysis of the changes in clusters of phytoplankton genera indicated possible changes in the water quality of the French Broad River near Knoxville, Tennessee. At this station, the most common diatom groups indicated a shift in dominant forms with some of the less common diatoms being replaced by green and blue-green algae. There was a reduction in genera variability between 1974-77 and 1979-81 sampling periods. Statistical analysis of chloride and dissolved solids confirmed that concentrations of these substances were smaller in 1974-77 than in 1979-81. At Pickwick Landing Dam, the furthest downstream station used in the study, there was an increase in the number of genera of ' rare ' organisms with time. The appearance of two groups of green and blue-green algae indicated that an increase in temperature or nutrient concentrations occurred from 1974 to 1981, but this could not be confirmed using available water quality data. Associations of genera forming the phytoplankton communities at three stations on the Tennessee River were found to be seasonal. Nodal analysis of combined data from all four stations used in the study did not identify any seasonal or temporal patterns during 1974-81. Cluster analysis using the NYSYS programs was effective in reducing the large phytoplankton data set to a manageable size and provided considerable insight into the structure of phytoplankton communities in the Tennessee River basin. Problems encountered using cluster analysis were the subjectivity introduced in the definition of meaningful clusters, and the lack of taxonomic identification to the species level. (Author 's abstract)

Cluster Analysis of Assessment in Anatomy and Physiology for Health Science Undergraduates

ERIC Educational Resources Information Center

Brown, Stephen; White, Sue; Power, Nicola

2016-01-01

Academic content common to health science programs is often taught to a mixed group of students; however, content assessment may be consistent for each discipline. This study used a retrospective cluster analysis on such a group, first to identify high and low achieving students, and second, to determine the distribution of students within…

Corrections for Cluster-Plot Slop

Treesearch

Harry T. Valentine; Mark J. Ducey; Jeffery H. Gove; Adrian Lanz; David L.R. Affleck

2006-01-01

Cluster-plot designs, including the design used by the Forest Inventory and Analysis program of the USDA Forest Service (FIA), are attended by a complicated boundary slopover problem. Slopover occurs where inclusion zones of objects of interest cross the boundary of the area of interest. The dispersed nature of inclusion zones that arise from the use of cluster plots...

Integrating Multiple Data Views for Improved Malware Analysis

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

Anderson, Blake H.

2014-01-31

Exploiting multiple views of a program makes obfuscating the intended behavior of a program more difficult allowing for better performance in classification, clustering, and phylogenetic reconstruction.

The CNO Bi-cycle in the Open Cluster NGC 752

NASA Astrophysics Data System (ADS)

Hawkins, Keith; Schuler, S.; King, J.; The, L.

2011-01-01

The CNO bi-cycle is the primary energy source for main sequence stars more massive than the sun. To test our understanding of stellar evolution models using the CNO bi-cycle, we have undertaken light-element (CNO) abundance analysis of three main sequence dwarf stars and three red giant stars in the open cluster NGC 752 utilizing high resolution (R 50,000) spectroscopy from the Keck Observatory. Preliminary results indicate, as expected, there is a depletion of carbon in the giants relative to the dwarfs. Additional analysis is needed to determine if the amount of depletion is in line with model predictions, as seen in the Hyades open cluster. Oxygen abundances are derived from the high-excitation O I triplet, and there is a 0.19 dex offset in the [O/H] abundances between the giants and dwarfs which may be explained by non-local thermodynamic equilibrium (NLTE), although further analysis is needed to verify this. The standard procedure for spectroscopically determining stellar parameters used here allows for a measurement of the cluster metallicity, [Fe/H] = 0.04 ± 0.02. In addition to the Fe abundances we have determined Na, Mg, and Al abundances to determine the status of other nucleosynthesis processes. The Na, Mg and Al abundances of the giants are enhanced relative to the dwarfs, which is consistent with similar findings in giants of other open clusters. Support for K. Hawkins was provided by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF.

a Morphometric Analysis of HYLARANA SIGNATA Group (previously Known as RANA SIGNATA and RANA PICTURATA) of Malaysia

NASA Astrophysics Data System (ADS)

Zainudin, Ramlah; Sazali, Siti Nurlydia

A study on morphometrical variations of Malaysian Hylarana signata group was conducted to reveal the morphological relationships within the species group. Twenty-seven morphological characters from 18 individuals of H. signata and H. picturata were measured and recorded. The numerical data were analysed using Discriminant Function Analysis in SPSS program version 16.0 and UPGMA Cluster Analysis in Minitab program version 14.0. The results show the complexity clustering between the examined species that might be due to ancient polymorphism of the lineages or cryptic species within the group. Hence, further study should include more representatives in order to fully elucidate the morphological relationships of H. signata group.

About the Clusters Program

EPA Pesticide Factsheets

The Environmental Technology Innovation Clusters Program advises cluster organizations, encourages collaboration between clusters, tracks U.S. environmental technology clusters, and connects EPA programs to cluster needs.

Applications of Combinatorial Programming to Data Analysis: The Traveling Salesman and Related Problems

ERIC Educational Resources Information Center

Hubert, Lawrence J.; Baker, Frank B.

1978-01-01

The "Traveling Salesman" and similar combinatorial programming tasks encountered in operations research are discussed as possible data analysis models in psychology, for example, in developmental scaling, Guttman scaling, profile smoothing, and data array clustering. A short overview of various computational approaches from this area of…

Obstructive Sleep Apnea: A Cluster Analysis at Time of Diagnosis

PubMed Central

Grillet, Yves; Richard, Philippe; Stach, Bruno; Vivodtzev, Isabelle; Timsit, Jean-Francois; Lévy, Patrick; Tamisier, Renaud; Pépin, Jean-Louis

2016-01-01

Background The classification of obstructive sleep apnea is on the basis of sleep study criteria that may not adequately capture disease heterogeneity. Improved phenotyping may improve prognosis prediction and help select therapeutic strategies. Objectives: This study used cluster analysis to investigate the clinical clusters of obstructive sleep apnea. Methods An ascending hierarchical cluster analysis was performed on baseline symptoms, physical examination, risk factor exposure and co-morbidities from 18,263 participants in the OSFP (French national registry of sleep apnea). The probability for criteria to be associated with a given cluster was assessed using odds ratios, determined by univariate logistic regression. Results: Six clusters were identified, in which patients varied considerably in age, sex, symptoms, obesity, co-morbidities and environmental risk factors. The main significant differences between clusters were minimally symptomatic versus sleepy obstructive sleep apnea patients, lean versus obese, and among obese patients different combinations of co-morbidities and environmental risk factors. Conclusions Our cluster analysis identified six distinct clusters of obstructive sleep apnea. Our findings underscore the high degree of heterogeneity that exists within obstructive sleep apnea patients regarding clinical presentation, risk factors and consequences. This may help in both research and clinical practice for validating new prevention programs, in diagnosis and in decisions regarding therapeutic strategies. PMID:27314230

Calibrating the Planck cluster mass scale with CLASH

NASA Astrophysics Data System (ADS)

Penna-Lima, M.; Bartlett, J. G.; Rozo, E.; Melin, J.-B.; Merten, J.; Evrard, A. E.; Postman, M.; Rykoff, E.

2017-08-01

We determine the mass scale of Planck galaxy clusters using gravitational lensing mass measurements from the Cluster Lensing And Supernova survey with Hubble (CLASH). We have compared the lensing masses to the Planck Sunyaev-Zeldovich (SZ) mass proxy for 21 clusters in common, employing a Bayesian analysis to simultaneously fit an idealized CLASH selection function and the distribution between the measured observables and true cluster mass. We used a tiered analysis strategy to explicitly demonstrate the importance of priors on weak lensing mass accuracy. In the case of an assumed constant bias, bSZ, between true cluster mass, M500, and the Planck mass proxy, MPL, our analysis constrains 1-bSZ = 0.73 ± 0.10 when moderate priors on weak lensing accuracy are used, including a zero-mean Gaussian with standard deviation of 8% to account for possible bias in lensing mass estimations. Our analysis explicitly accounts for possible selection bias effects in this calibration sourced by the CLASH selection function. Our constraint on the cluster mass scale is consistent with recent results from the Weighing the Giants program and the Canadian Cluster Comparison Project. It is also consistent, at 1.34σ, with the value needed to reconcile the Planck SZ cluster counts with Planck's base ΛCDM model fit to the primary cosmic microwave background anisotropies.

Business and Marketing Cluster. Task Analyses.

ERIC Educational Resources Information Center

Henrico County Public Schools, Glen Allen, VA. Virginia Vocational Curriculum and Resource Center.

Developed in Virginia, this publication contains task analysis guides to support selected tech prep programs that prepare students for careers in the business and marketing cluster. Guides are included for accounting systems, legal systems administration, office systems technology, and retail marketing. Each task analyses guide has the following…

Tobacco, Marijuana, and Alcohol Use in University Students: A Cluster Analysis

PubMed Central

Primack, Brian A.; Kim, Kevin H.; Shensa, Ariel; Sidani, Jaime E.; Barnett, Tracey E.; Switzer, Galen E.

2012-01-01

Objective Segmentation of populations may facilitate development of targeted substance abuse prevention programs. We aimed to partition a national sample of university students according to profiles based on substance use. Participants We used 2008–2009 data from the National College Health Assessment from the American College Health Association. Our sample consisted of 111,245 individuals from 158 institutions. Method We partitioned the sample using cluster analysis according to current substance use behaviors. We examined the association of cluster membership with individual and institutional characteristics. Results Cluster analysis yielded six distinct clusters. Three individual factors—gender, year in school, and fraternity/sorority membership—were the most strongly associated with cluster membership. Conclusions In a large sample of university students, we were able to identify six distinct patterns of substance abuse. It may be valuable to target specific populations of college-aged substance users based on individual factors. However, comprehensive intervention will require a multifaceted approach. PMID:22686360

Planning a mentorship initiative for foster parents: Does gender matter?

PubMed

Jay Miller, J; Benner, Kalea; Thrasher, Shawndaya; Pope, Natalie; Dumas, Tamikia; Damron, Larry J; Segress, Melissa; Niu, Chunling

2017-10-01

Despite the use of mentoring programs in fields such as business, career training, and youth development, little is known about how mentoring can be used to train and support new foster parents. This paper describes how Concept Mapping was used with current foster parents to develop a conceptual framework suitable to plan a foster parent mentor program. A secondary aim of this study was to explore priority differences in the conceptualization by self-reported gender (foster mothers vs. foster fathers). Participant data was collected via three qualitative brainstorming sessions, and analyzed using non-metric multidimensional scaling and hierarchical cluster analysis. Findings indicate that foster parents participating in this study conceptualized effective mentor programs via a seven cluster solution. Study results also showed no significant differences in cluster ratings by gender. Implications for practice and program planning are identified, as well as areas for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Testing the Archivas Cluster (Arc) for Ozone Monitoring Instrument (OMI) Scientific Data Storage

NASA Technical Reports Server (NTRS)

Tilmes, Curt

2005-01-01

The Ozone Monitoring Instrument (OMI) launched on NASA's Aura Spacecraft, the third of the major platforms of the EOS program on July 15,2004. In addition to the long term archive and distribution of the data from OM1 through the Goddard Earth Science Distributed Active Archive Center (GESDAAC), we are evaluating other archive mechanisms that can archive the data in a more immediately available method where it can be used for futher data production and analysis. In 2004, Archivas, Inc. was selected by NASA s Small Business Innovative Research (SBIR) program for the development of their Archivas Cluster (ArC) product. Arc is an online disk based system utilizing self-management and automation on a Linux cluster. Its goal is to produce a low cost solution coupled with the ease of management. The OM1 project is an application partner of the SBIR program, and has deployed a small cluster (5TB) based on the beta Archwas software. We performed extensive testing of the unit using production OM1 data since launch. In 2005, Archivas, Inc. was funded in SBIR Phase II for further development, which will include testing scalability with the deployment of a larger (35TB) cluster at Goddard. We plan to include Arc in the OM1 Team Leader Computing Facility (TLCF) hosting OM1 data for direct access and analysis by the OMI Science Team. This presentation will include a brief technical description of the Archivas Cluster, a summary of the SBIR Phase I beta testing results, and an overview of the OMI ground data processing architecture including its interaction with the Phase II Archivas Cluster and hosting of OMI data for the scientists.

The Evolution of Stellar Dynamos; Survey for Low Mass Members of NGC2232; An X-Ray Survey of the Open Cluster CR140; Towards a Better Understanding of the Rotation-Activity Relation for Solar-Type Members of the Pleiades

NASA Technical Reports Server (NTRS)

Stauffer, John R.; Petre, Robert (Technical Monitor)

2000-01-01

This grant was originally awarded to Dr. Charles Prosser, who died tragically in a car accident in Tucson in 1998. We had hoped to finish the work Charles had started, which involved analysis of ROSAT data for three programs (observations of the clusters NGC2232, Crl4O and the Pleiades) and also analysis of optical data for each cluster in order to allow interpretation of the ROSAT observations. The Pleiades portion of the program was completed during the past year, and a paper published. We have obtained optical imaging of the other two clusters, and those data are being analyzed. Dr. Brian Patten intends to complete analysis of the ROSAT observations and to combine those data with the optical photometry, but progress on those efforts has been slow due to the press of other work (Dr. Patten is responsible for the pipeline processing of data from SWAS). We intend to publish those results as soon as we can, but it will now be completed without further support from this grant.

Long-term analysis of health status and preventive behavior in music students across an entire university program.

PubMed

Spahn, Claudia; Nusseck, Manfred; Zander, Mark

2014-03-01

The aim of this investigation was to analyze longitudinal data concerning physical and psychological health, playing-related problems, and preventive behavior among music students across their complete 4- to 5-year study period. In a longitudinal, observational study, we followed students during their university training and measured their psychological and physical health status and preventive behavior using standardized questionnaires at four different times. The data were in accordance with previous findings. They demonstrated three groups of health characteristics observed in beginners of music study: healthy students (cluster 1), students with preclinical symptoms (cluster 2), and students who are clinically symptomatic (cluster 3). In total, 64% of all students remained in the same cluster group during their whole university training. About 10% of the students showed considerable health problems and belonged to the third cluster group. The three clusters of health characteristics found in this longitudinal study with music students necessitate that prevention programs for musicians must be adapted to the target audience.

Spatio-Temporal Analysis of Smear-Positive Tuberculosis in the Sidama Zone, Southern Ethiopia

PubMed Central

Dangisso, Mesay Hailu; Datiko, Daniel Gemechu; Lindtjørn, Bernt

2015-01-01

Background Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs). However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia. Methods A retrospective space–time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district) to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB). Scan statistics, Global Moran’s I, and Getis and Ordi (Gi*) statistics were all used to help analyze the spatial distribution and clusters of the disease across settings. Results A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001), with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001), with 7,584 observed and 4,738 expected cases in 2003-2012. Conclusion The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas characterized by the highest CNRs. Further studies are required to understand the factors associated with clustering based on individual level locations and investigation of cases. PMID:26030162

A New Approach to Identify High Burnout Medical Staffs by Kernel K-Means Cluster Analysis in a Regional Teaching Hospital in Taiwan

PubMed Central

Lee, Yii-Ching; Huang, Shian-Chang; Huang, Chih-Hsuan; Wu, Hsin-Hung

2016-01-01

This study uses kernel k-means cluster analysis to identify medical staffs with high burnout. The data collected in October to November 2014 are from the emotional exhaustion dimension of the Chinese version of Safety Attitudes Questionnaire in a regional teaching hospital in Taiwan. The number of effective questionnaires including the entire staffs such as physicians, nurses, technicians, pharmacists, medical administrators, and respiratory therapists is 680. The results show that 8 clusters are generated by kernel k-means method. Employees in clusters 1, 4, and 5 are relatively in good conditions, whereas employees in clusters 2, 3, 6, 7, and 8 need to be closely monitored from time to time because they have relatively higher degree of burnout. When employees with higher degree of burnout are identified, the hospital management can take actions to improve the resilience, reduce the potential medical errors, and, eventually, enhance the patient safety. This study also suggests that the hospital management needs to keep track of medical staffs’ fatigue conditions and provide timely assistance for burnout recovery through employee assistance programs, mindfulness-based stress reduction programs, positivity currency buildup, and forming appreciative inquiry groups. PMID:27895218

Space station ECLSS integration analysis: Simplified General Cluster Systems Model, ECLS System Assessment Program enhancements

NASA Technical Reports Server (NTRS)

Ferguson, R. E.

1985-01-01

The data base verification of the ECLS Systems Assessment Program (ESAP) was documented and changes made to enhance the flexibility of the water recovery subsystem simulations are given. All changes which were made to the data base values are described and the software enhancements performed. The refined model documented herein constitutes the submittal of the General Cluster Systems Model. A source listing of the current version of ESAP is provided in Appendix A.

A large sample of shear-selected clusters from the Hyper Suprime-Cam Subaru Strategic Program S16A Wide field mass maps

NASA Astrophysics Data System (ADS)

Miyazaki, Satoshi; Oguri, Masamune; Hamana, Takashi; Shirasaki, Masato; Koike, Michitaro; Komiyama, Yutaka; Umetsu, Keiichi; Utsumi, Yousuke; Okabe, Nobuhiro; More, Surhud; Medezinski, Elinor; Lin, Yen-Ting; Miyatake, Hironao; Murayama, Hitoshi; Ota, Naomi; Mitsuishi, Ikuyuki

2018-01-01

We present the result of searching for clusters of galaxies based on weak gravitational lensing analysis of the ˜160 deg2 area surveyed by Hyper Suprime-Cam (HSC) as a Subaru Strategic Program. HSC is a new prime focus optical imager with a 1.5°-diameter field of view on the 8.2 m Subaru telescope. The superb median seeing on the HSC i-band images of 0.56" allows the reconstruction of high angular resolution mass maps via weak lensing, which is crucial for the weak lensing cluster search. We identify 65 mass map peaks with a signal-to-noise (S/N) ratio larger than 4.7, and carefully examine their properties by cross-matching the clusters with optical and X-ray cluster catalogs. We find that all the 39 peaks with S/N > 5.1 have counterparts in the optical cluster catalogs, and only 2 out of the 65 peaks are probably false positives. The upper limits of X-ray luminosities from the ROSAT All Sky Survey (RASS) imply the existence of an X-ray underluminous cluster population. We show that the X-rays from the shear-selected clusters can be statistically detected by stacking the RASS images. The inferred average X-ray luminosity is about half that of the X-ray-selected clusters of the same mass. The radial profile of the dark matter distribution derived from the stacking analysis is well modeled by the Navarro-Frenk-White profile with a small concentration parameter value of c500 ˜ 2.5, which suggests that the selection bias on the orientation or the internal structure for our shear-selected cluster sample is not strong.

Use of DAVID algorithms for gene functional classification in a non-model organism, rainbow trout

USDA-ARS?s Scientific Manuscript database

Gene functional clustering is essential in transcriptome data analysis but software programs are not always suitable for use with non-model species. The DAVID Gene Functional Classification Tool has been widely used for soft clustering in model species, but requires adaptations for use in non-model ...

Order-Constrained Solutions in K-Means Clustering: Even Better than Being Globally Optimal

ERIC Educational Resources Information Center

Steinley, Douglas; Hubert, Lawrence

2008-01-01

This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that…

ICAP: An Interactive Cluster Analysis Procedure for analyzing remotely sensed data. [to classify the radiance data to produce a thematic map

NASA Technical Reports Server (NTRS)

Wharton, S. W.

1980-01-01

An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. The algorithm interfaces the rapid numerical processing capacity of a computer with the human ability to integrate qualitative information. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters and the analyst, who evaluate and elect to modify the cluster structure. Clusters can be deleted or lumped pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The ICAP was implemented in APL (A Programming Language), an interactive computer language. The flexibility of the algorithm was evaluated using data from different LANDSAT scenes to simulate two situations: one in which the analyst is assumed to have no prior knowledge about the data and wishes to have the clusters formed more or less automatically; and the other in which the analyst is assumed to have some knowledge about the data structure and wishes to use that information to closely supervise the clustering process. For comparison, an existing clustering method was also applied to the two data sets.

Software system for data management and distributed processing of multichannel biomedical signals.

PubMed

Franaszczuk, P J; Jouny, C C

2004-01-01

The presented software is designed for efficient utilization of cluster of PC computers for signal analysis of multichannel physiological data. The system consists of three main components: 1) a library of input and output procedures, 2) a database storing additional information about location in a storage system, 3) a user interface for selecting data for analysis, choosing programs for analysis, and distributing computing and output data on cluster nodes. The system allows for processing multichannel time series data in multiple binary formats. The description of data format, channels and time of recording are included in separate text files. Definition and selection of multiple channel montages is possible. Epochs for analysis can be selected both manually and automatically. Implementation of a new signal processing procedures is possible with a minimal programming overhead for the input/output processing and user interface. The number of nodes in cluster used for computations and amount of storage can be changed with no major modification to software. Current implementations include the time-frequency analysis of multiday, multichannel recordings of intracranial EEG of epileptic patients as well as evoked response analyses of repeated cognitive tasks.

A Bayesian cluster analysis method for single-molecule localization microscopy data.

PubMed

Griffié, Juliette; Shannon, Michael; Bromley, Claire L; Boelen, Lies; Burn, Garth L; Williamson, David J; Heard, Nicholas A; Cope, Andrew P; Owen, Dylan M; Rubin-Delanchy, Patrick

2016-12-01

Cell function is regulated by the spatiotemporal organization of the signaling machinery, and a key facet of this is molecular clustering. Here, we present a protocol for the analysis of clustering in data generated by 2D single-molecule localization microscopy (SMLM)-for example, photoactivated localization microscopy (PALM) or stochastic optical reconstruction microscopy (STORM). Three features of such data can cause standard cluster analysis approaches to be ineffective: (i) the data take the form of a list of points rather than a pixel array; (ii) there is a non-negligible unclustered background density of points that must be accounted for; and (iii) each localization has an associated uncertainty in regard to its position. These issues are overcome using a Bayesian, model-based approach. Many possible cluster configurations are proposed and scored against a generative model, which assumes Gaussian clusters overlaid on a completely spatially random (CSR) background, before every point is scrambled by its localization precision. We present the process of generating simulated and experimental data that are suitable to our algorithm, the analysis itself, and the extraction and interpretation of key cluster descriptors such as the number of clusters, cluster radii and the number of localizations per cluster. Variations in these descriptors can be interpreted as arising from changes in the organization of the cellular nanoarchitecture. The protocol requires no specific programming ability, and the processing time for one data set, typically containing 30 regions of interest, is ∼18 h; user input takes ∼1 h.

Sputum neutrophil counts are associated with more severe asthma phenotypes using cluster analysis.

PubMed

Moore, Wendy C; Hastie, Annette T; Li, Xingnan; Li, Huashi; Busse, William W; Jarjour, Nizar N; Wenzel, Sally E; Peters, Stephen P; Meyers, Deborah A; Bleecker, Eugene R

2014-06-01

Clinical cluster analysis from the Severe Asthma Research Program (SARP) identified 5 asthma subphenotypes that represent the severity spectrum of early-onset allergic asthma, late-onset severe asthma, and severe asthma with chronic obstructive pulmonary disease characteristics. Analysis of induced sputum from a subset of SARP subjects showed 4 sputum inflammatory cellular patterns. Subjects with concurrent increases in eosinophil (≥2%) and neutrophil (≥40%) percentages had characteristics of very severe asthma. To better understand interactions between inflammation and clinical subphenotypes, we integrated inflammatory cellular measures and clinical variables in a new cluster analysis. Participants in SARP who underwent sputum induction at 3 clinical sites were included in this analysis (n = 423). Fifteen variables, including clinical characteristics and blood and sputum inflammatory cell assessments, were selected using factor analysis for unsupervised cluster analysis. Four phenotypic clusters were identified. Cluster A (n = 132) and B (n = 127) subjects had mild-to-moderate early-onset allergic asthma with paucigranulocytic or eosinophilic sputum inflammatory cell patterns. In contrast, these inflammatory patterns were present in only 7% of cluster C (n = 117) and D (n = 47) subjects who had moderate-to-severe asthma with frequent health care use despite treatment with high doses of inhaled or oral corticosteroids and, in cluster D, reduced lung function. The majority of these subjects (>83%) had sputum neutrophilia either alone or with concurrent sputum eosinophilia. Baseline lung function and sputum neutrophil percentages were the most important variables determining cluster assignment. This multivariate approach identified 4 asthma subphenotypes representing the severity spectrum from mild-to-moderate allergic asthma with minimal or eosinophil-predominant sputum inflammation to moderate-to-severe asthma with neutrophil-predominant or mixed granulocytic inflammation. Published by Mosby, Inc.

Sputum neutrophils are associated with more severe asthma phenotypes using cluster analysis

PubMed Central

Moore, Wendy C.; Hastie, Annette T.; Li, Xingnan; Li, Huashi; Busse, William W.; Jarjour, Nizar N.; Wenzel, Sally E.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

2013-01-01

Background Clinical cluster analysis from the Severe Asthma Research Program (SARP) identified five asthma subphenotypes that represent the severity spectrum of early onset allergic asthma, late onset severe asthma and severe asthma with COPD characteristics. Analysis of induced sputum from a subset of SARP subjects showed four sputum inflammatory cellular patterns. Subjects with concurrent increases in eosinophils (≥2%) and neutrophils (≥40%) had characteristics of very severe asthma. Objective To better understand interactions between inflammation and clinical subphenotypes we integrated inflammatory cellular measures and clinical variables in a new cluster analysis. Methods Participants in SARP at three clinical sites who underwent sputum induction were included in this analysis (n=423). Fifteen variables including clinical characteristics and blood and sputum inflammatory cell assessments were selected by factor analysis for unsupervised cluster analysis. Results Four phenotypic clusters were identified. Cluster A (n=132) and B (n=127) subjects had mild-moderate early onset allergic asthma with paucigranulocytic or eosinophilic sputum inflammatory cell patterns. In contrast, these inflammatory patterns were present in only 7% of Cluster C (n=117) and D (n=47) subjects who had moderate-severe asthma with frequent health care utilization despite treatment with high doses of inhaled or oral corticosteroids, and in Cluster D, reduced lung function. The majority these subjects (>83%) had sputum neutrophilia either alone or with concurrent sputum eosinophilia. Baseline lung function and sputum neutrophils were the most important variables determining cluster assignment. Conclusion This multivariate approach identified four asthma subphenotypes representing the severity spectrum from mild-moderate allergic asthma with minimal or eosinophilic predominant sputum inflammation to moderate-severe asthma with neutrophilic predominant or mixed granulocytic inflammation. PMID:24332216

Analyzing Patients' Values by Applying Cluster Analysis and LRFM Model in a Pediatric Dental Clinic in Taiwan

PubMed Central

Lin, Shih-Yen; Liu, Chih-Wei

2014-01-01

This study combines cluster analysis and LRFM (length, recency, frequency, and monetary) model in a pediatric dental clinic in Taiwan to analyze patients' values. A two-stage approach by self-organizing maps and K-means method is applied to segment 1,462 patients into twelve clusters. The average values of L, R, and F excluding monetary covered by national health insurance program are computed for each cluster. In addition, customer value matrix is used to analyze customer values of twelve clusters in terms of frequency and monetary. Customer relationship matrix considering length and recency is also applied to classify different types of customers from these twelve clusters. The results show that three clusters can be classified into loyal patients with L, R, and F values greater than the respective average L, R, and F values, while three clusters can be viewed as lost patients without any variable above the average values of L, R, and F. When different types of patients are identified, marketing strategies can be designed to meet different patients' needs. PMID:25045741

Analyzing patients' values by applying cluster analysis and LRFM model in a pediatric dental clinic in Taiwan.

PubMed

Wu, Hsin-Hung; Lin, Shih-Yen; Liu, Chih-Wei

2014-01-01

This study combines cluster analysis and LRFM (length, recency, frequency, and monetary) model in a pediatric dental clinic in Taiwan to analyze patients' values. A two-stage approach by self-organizing maps and K-means method is applied to segment 1,462 patients into twelve clusters. The average values of L, R, and F excluding monetary covered by national health insurance program are computed for each cluster. In addition, customer value matrix is used to analyze customer values of twelve clusters in terms of frequency and monetary. Customer relationship matrix considering length and recency is also applied to classify different types of customers from these twelve clusters. The results show that three clusters can be classified into loyal patients with L, R, and F values greater than the respective average L, R, and F values, while three clusters can be viewed as lost patients without any variable above the average values of L, R, and F. When different types of patients are identified, marketing strategies can be designed to meet different patients' needs.

The effectiveness of an aged care specific leadership and management program on workforce, work environment, and care quality outcomes: design of a cluster randomised controlled trial.

PubMed

Jeon, Yun-Hee; Simpson, Judy M; Chenoweth, Lynn; Cunich, Michelle; Kendig, Hal

2013-10-25

A plethora of observational evidence exists concerning the impact of management and leadership on workforce, work environment, and care quality. Yet, no randomised controlled trial has been conducted to test the effectiveness of leadership and management interventions in aged care. An innovative aged care clinical leadership program (Clinical Leadership in Aged Care--CLiAC) was developed to improve managers' leadership capacities to support the delivery of quality care in Australia. This paper describes the study design of the cluster randomised controlled trial testing the effectiveness of the program. Twenty-four residential and community aged care sites were recruited as managers at each site agreed in writing to participate in the study and ensure that leaders allocated to the control arm would not be offered the intervention program. Sites undergoing major managerial or structural changes were excluded. The 24 sites were randomly allocated to receive the CLiAC program (intervention) or usual care (control), stratified by type (residential vs. community, six each for each arm). Treatment allocation was masked to assessors and staff of all participating sites. The objective is to establish the effectiveness of the CLiAC program in improving work environment, workforce retention, as well as care safety and quality, when compared to usual care. The primary outcomes are measures of work environment, care quality and safety, and staff turnover rates. Secondary outcomes include manager leadership capacity, staff absenteeism, intention to leave, stress levels, and job satisfaction. Differences between intervention and control groups will be analysed by researchers blinded to treatment allocation using linear regression of individual results adjusted for stratification and clustering by site (primary analysis), and additionally for baseline values and potential confounders (secondary analysis). Outcomes measured at the site level will be compared by cluster-level analysis. The overall costs and benefits of the program will also be assessed. The outcomes of the trial have the potential to inform actions to enhance leadership and management capabilities of the aged care workforce, address pressing issues about workforce shortages, and increase the quality of aged care services. Australian New Zealand Clinical Trials Registry (ACTRN12611001070921).

Typology of adults diagnosed with mental disorders based on socio-demographics and clinical and service use characteristics

PubMed Central

2011-01-01

Background Mental disorder is a leading cause of morbidity worldwide. Its cost and negative impact on productivity are substantial. Consequently, improving mental health-care system efficiency - especially service utilisation - is a priority. Few studies have explored the use of services by specific subgroups of persons with mental disorder; a better understanding of these individuals is key to improving service planning. This study develops a typology of individuals, diagnosed with mental disorder in a 12-month period, based on their individual characteristics and use of services within a Canadian urban catchment area of 258,000 persons served by a psychiatric hospital. Methods From among the 2,443 people who took part in the survey, 406 (17%) experienced at least one episode of mental disorder (as per the Composite International Diagnostic Interview (CIDI)) in the 12 months pre-interview. These individuals were selected for cluster analysis. Results Analysis yielded four user clusters: people who experienced mainly anxiety disorder; depressive disorder; alcohol and/or drug disorder; and multiple mental and dependence disorder. Two clusters were more closely associated with females and anxiety or depressive disorders. In the two other clusters, males were over-represented compared with the sample as a whole, namely, substance abuses with or without concomitant mental disorder. Clusters with the greatest number of mental disorders per subject used a greater number of mental health-care services. Conversely, clusters associated exclusively with dependence disorders used few services. Conclusion The study found considerable heterogeneity among socio-demographic characteristics, number of disorders, and number of health-care services used by individuals with mental or dependence disorders. Cluster analysis revealed important differences in service use with regard to gender and age. It reinforces the relevance of developing targeted programs for subgroups of individuals with mental and/or dependence disorders. Strategies aimed at changing low service users' attitude (youths and males) or instituting specialised programs for that particular clientele should be promoted. Finally, as concomitant disorders are frequent among individuals with mental disorder, psychological services and/or addiction programs must be prioritised as components of integrated services when planning treatment. PMID:21507251

Clusters and Factors Associated with Complementary Basic Education in Tanzania Mainland

ERIC Educational Resources Information Center

Edwin, Paul; Amina, Msengwa S.; Godwin, Naimani M.

2017-01-01

Complimentary Basic Education in Tanzania (COBET) is a community-based programme initiated in 1999 to provide formal education system opportunity to over aged children or children above school age. The COBET program was analyzed using secondary data collected from 21 regions from 2008 to 2012. Cluster analysis was applied to classify the 21…

A New Approach to Identify High Burnout Medical Staffs by Kernel K-Means Cluster Analysis in a Regional Teaching Hospital in Taiwan.

PubMed

Lee, Yii-Ching; Huang, Shian-Chang; Huang, Chih-Hsuan; Wu, Hsin-Hung

2016-01-01

This study uses kernel k-means cluster analysis to identify medical staffs with high burnout. The data collected in October to November 2014 are from the emotional exhaustion dimension of the Chinese version of Safety Attitudes Questionnaire in a regional teaching hospital in Taiwan. The number of effective questionnaires including the entire staffs such as physicians, nurses, technicians, pharmacists, medical administrators, and respiratory therapists is 680. The results show that 8 clusters are generated by kernel k-means method. Employees in clusters 1, 4, and 5 are relatively in good conditions, whereas employees in clusters 2, 3, 6, 7, and 8 need to be closely monitored from time to time because they have relatively higher degree of burnout. When employees with higher degree of burnout are identified, the hospital management can take actions to improve the resilience, reduce the potential medical errors, and, eventually, enhance the patient safety. This study also suggests that the hospital management needs to keep track of medical staffs' fatigue conditions and provide timely assistance for burnout recovery through employee assistance programs, mindfulness-based stress reduction programs, positivity currency buildup, and forming appreciative inquiry groups. © The Author(s) 2016.

TCW: Transcriptome Computational Workbench

PubMed Central

Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R.

2013-01-01

Background The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. Methodology The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. Conclusion It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw. PMID:23874959

TCW: transcriptome computational workbench.

PubMed

Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R

2013-01-01

The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw.

MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.

PubMed

Hedeker, D; Gibbons, R D

1996-05-01

MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.

fluff: exploratory analysis and visualization of high-throughput sequencing data

PubMed Central

Georgiou, Georgios

2016-01-01

Summary. In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at http://fluff.readthedocs.org. Availability. fluff is implemented in Python and runs on Linux. The source code is freely available for download at https://github.com/simonvh/fluff. PMID:27547532

See Change: Cosmology Analysis Update for the Supernova Cosmology Project High-z Cluster Supernova Survey

NASA Astrophysics Data System (ADS)

Hayden, Brian; Aldering, Gregory; Amanullah, Rahman; Barbary, Kyle; Bohringer, Hans; Boone, Kyle Robert; Brodwin, Mark; Cunha, Carlos; Currie, Miles; Deustua, Susana; Dixon, Samantha; Eisenhardt, Peter; Fassbender, Rene; Fruchter, Andrew; Gladders, Michael; Gonzalez, Anthony; Goobar, Ariel; Hildebrandt, Hendrik; Hilton, Matt; Hoekstra, Henk; Hook, Isobel; Huang, Xiaosheng; Huterer, Dragan; Jee, Myungkook James; Kim, Alex; Kowalski, Marek; Lidman, Chris; Linder, Eric; Luther, Kyle; Meyers, Joshua; Muzzin, Adam; Nordin, Jakob; Pain, Reynald; Perlmutter, Saul; Richard, Johan; Rosati, Piero; Rozo, Eduardo; Rubin, David; Ruiz-Lapuente, Pilar; Rykoff, Eli; Santos, Joana; Myers Saunders, Clare; Sofiatti, Caroline; Spadafora, Anthony L.; Stanford, Spencer; Stern, Daniel; Suzuki, Nao; Webb, Tracy; Wechsler, Risa; Williams, Steven; Willis, Jon; Wilson, Gillian; Yen, Mike

2018-01-01

The Supernova Cosmology Project has finished executing a large (174 orbits, cycles 22-23) Hubble Space Telescope program, which has measured ~30 type Ia Supernovae above z~1 in the highest-redshift, most massive galaxy clusters known to date. We present the status of the ongoing blinded cosmology analysis, demonstrating substantial improvement to the uncertainty on the Dark Energy density above z~1. Our extensive HST and ground-based campaign has already produced unique results; we have confirmed several of the highest redshift cluster members known to date, confirmed the redshift of one of the most massive galaxy clusters expected across the entire sky, and characterized one of the most extreme starburst environments yet known in a z~1.7 cluster. We have also discovered a lensed SN Ia at z=2.22 magnified by a factor of ~2.8, which is the highest spectroscopic redshift SN Ia currently known.

VizieR Online Data Catalog: Slug analysis of star clusters in NGC 628 & 7793 (Krumholz+, 2015)

NASA Astrophysics Data System (ADS)

Krumholz, M. R.; Adamo, A.; Fumagalli, M.; Wofford, A.; Calzetti, D.; Lee, J. C.; Whitmore, B. C.; Bright, S. N.; Grasha, K.; Gouliermis, D. A.; Kim, H.; Nair, P.; Ryon, J. E.; Smith, L. J.; Thilker, D.; Ubeda, L.; Zackrisson, E.

2016-02-01

In this paper we use slug, the Stochastically Lighting Up Galaxies code (da Silva et al. 2012ApJ...745..145D, 2014MNRAS.444.3275D; Krumholz et al. 2015MNRAS.452.1447K), and its post-processing tool for analysis of star cluster properties, cluster_slug, to analyze an initial sample of clusters from the LEGUS (Calzetti et al. 2015AJ....149...51C). A description of the steps required to produce final cluster catalogs of the Legacy Extragalactic UV Survey (LEGUS) targets can be found in Calzetti et al. (2015AJ....149...51C), and in A. Adamo et al. (2015, in preparation). LEGUS is an HST Cycle 21 Treasury program that is imaging 50 nearby galaxies in five broadbands with the WFC3/UVIS, from the NUV to the I band. (1 data file).

Coastal Benthic Boundary Layer Special Research Program. Program Direction and Workshop Recommendations

DTIC Science & Technology

1992-08-01

Faas, " Analysis of the relationship between acoustic reflectivity and sediment porosity," Geophysics 3 4, 546-553 (1969). M. A. Foda , J. Y.-H. Chang...properties, together with in situ measured mechanical, acoustic and electrical properties, should be subjected to factor analysis . Natural clusters could...properties. The mechanical 1 properties and remotely sensed properties are a matrix of information that can be subjected to factor analysis . One can

Cluster headache and the hypocretin receptor 2 reconsidered: a genetic association study and meta-analysis.

PubMed

Weller, Claudia M; Wilbrink, Leopoldine A; Houwing-Duistermaat, Jeanine J; Koelewijn, Stephany C; Vijfhuizen, Lisanne S; Haan, Joost; Ferrari, Michel D; Terwindt, Gisela M; van den Maagdenberg, Arn M J M; de Vries, Boukje

2015-08-01

Cluster headache is a severe neurological disorder with a complex genetic background. A missense single nucleotide polymorphism (rs2653349; p.Ile308Val) in the HCRTR2 gene that encodes the hypocretin receptor 2 is the only genetic factor that is reported to be associated with cluster headache in different studies. However, as there are conflicting results between studies, we re-evaluated its role in cluster headache. We performed a genetic association analysis for rs2653349 in our large Leiden University Cluster headache Analysis (LUCA) program study population. Systematic selection of the literature yielded three additional studies comprising five study populations, which were included in our meta-analysis. Data were extracted according to predefined criteria. A total of 575 cluster headache patients from our LUCA study and 874 controls were genotyped for HCRTR2 SNP rs2653349 but no significant association with cluster headache was found (odds ratio 0.91 (95% confidence intervals 0.75-1.10), p = 0.319). In contrast, the meta-analysis that included in total 1167 cluster headache cases and 1618 controls from the six study populations, which were part of four different studies, showed association of the single nucleotide polymorphism with cluster headache (random effect odds ratio 0.69 (95% confidence intervals 0.53-0.90), p = 0.006). The association became weaker, as the odds ratio increased to 0.80, when the meta-analysis was repeated without the initial single South European study with the largest effect size. Although we did not find evidence for association of rs2653349 in our LUCA study, which is the largest investigated study population thus far, our meta-analysis provides genetic evidence for a role of HCRTR2 in cluster headache. Regardless, we feel that the association should be interpreted with caution as meta-analyses with individual populations that have limited power have diminished validity. © International Headache Society 2014.

Clumpak: a program for identifying clustering modes and packaging population structure inferences across K.

PubMed

Kopelman, Naama M; Mayzel, Jonathan; Jakobsson, Mattias; Rosenberg, Noah A; Mayrose, Itay

2015-09-01

The identification of the genetic structure of populations from multilocus genotype data has become a central component of modern population-genetic data analysis. Application of model-based clustering programs often entails a number of steps, in which the user considers different modelling assumptions, compares results across different predetermined values of the number of assumed clusters (a parameter typically denoted K), examines multiple independent runs for each fixed value of K, and distinguishes among runs belonging to substantially distinct clustering solutions. Here, we present Clumpak (Cluster Markov Packager Across K), a method that automates the postprocessing of results of model-based population structure analyses. For analysing multiple independent runs at a single K value, Clumpak identifies sets of highly similar runs, separating distinct groups of runs that represent distinct modes in the space of possible solutions. This procedure, which generates a consensus solution for each distinct mode, is performed by the use of a Markov clustering algorithm that relies on a similarity matrix between replicate runs, as computed by the software Clumpp. Next, Clumpak identifies an optimal alignment of inferred clusters across different values of K, extending a similar approach implemented for a fixed K in Clumpp and simplifying the comparison of clustering results across different K values. Clumpak incorporates additional features, such as implementations of methods for choosing K and comparing solutions obtained by different programs, models, or data subsets. Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model-based analyses of population structure in population genetics and molecular ecology. © 2015 John Wiley & Sons Ltd.

The peculiar velocities of rich clusters in the hot and cold dark matter scenarios

NASA Technical Reports Server (NTRS)

Rhee, George F.; West, Michael J.; Villumsen, Jens V.

1993-01-01

We present the results of a study of the peculiar velocities of rich clusters of galaxies. The peculiar motion of rich clusters in various cosmological scenarios is of interest for a number of reasons. Observationally, one can measure the peculiar motion of clusters to greater distances than galaxies because cluster peculiar motions can be determined to greater accuracy. One can also test the slope of distance indicator relations using clusters to see if galaxy properties vary with environment. We have used N-body simulations to measure the amplitude and rms cluster peculiar velocity as a function of bias parameter in the hot and cold dark matter scenarios. In addition to measuring the mean and rms peculiar velocity of clusters in the two models, we determined whether the peculiar velocity vector of a given cluster is well aligned with the gravity vector due to all the particles in the simulation and the gravity vector due to the particles present only in the clusters. We have investigated the peculiar velocities of rich clusters of galaxies in the cold dark matter and hot dark matter galaxy formation scenarios. We have derived peculiar velocities and associated errors for the scenarios using four values of the bias parameter ranging from b = 1 to b = 2.5. The growth of the mean peculiar velocity with scale factor has been determined and compared to that predicted by linear theory. In addition, we have compared the orientation of force and velocity in these simulations to see if a program such as that proposed by Bertschinger and Dekel (1989) for elliptical galaxy peculiar motions can be applied to clusters. The method they describe enables one to recover the density field from large scale redshift distance samples. The method makes it possible to do this when only radial velocities are known by assuming that the velocity field is curl free. Our analysis suggests that this program if applied to clusters is only realizable for models with a low value of the bias parameter, i.e., models in which the peculiar velocities of clusters are large enough that the errors do not render the analysis impracticable.

Mindfulness-Based Stress Reduction in Post-treatment Breast Cancer Patients: Immediate and Sustained Effects Across Multiple Symptom Clusters.

PubMed

Reich, Richard R; Lengacher, Cecile A; Alinat, Carissa B; Kip, Kevin E; Paterson, Carly; Ramesar, Sophia; Han, Heather S; Ismail-Khan, Roohi; Johnson-Mallard, Versie; Moscoso, Manolete; Budhrani-Shani, Pinky; Shivers, Steve; Cox, Charles E; Goodman, Matthew; Park, Jong

2017-01-01

Breast cancer survivors (BCS) face adverse physical and psychological symptoms, often co-occurring. Biologic and psychological factors may link symptoms within clusters, distinguishable by prevalence and/or severity. Few studies have examined the effects of behavioral interventions or treatment of symptom clusters. The aim of this study was to identify symptom clusters among post-treatment BCS and determine symptom cluster improvement following the Mindfulness-Based Stress Reduction for Breast Cancer (MBSR(BC)) program. Three hundred twenty-two Stage 0-III post-treatment BCS were randomly assigned to either a six-week MBSR(BC) program or usual care. Psychological (depression, anxiety, stress, and fear of recurrence), physical (fatigue, pain, sleep, and drowsiness), and cognitive symptoms and quality of life were assessed at baseline, six, and 12 weeks, along with demographic and clinical history data at baseline. A three-step analytic process included the error-accounting models of factor analysis and structural equation modeling. Four symptom clusters emerged at baseline: pain, psychological, fatigue, and cognitive. From baseline to six weeks, the model demonstrated evidence of MBSR(BC) effectiveness in both the psychological (anxiety, depression, perceived stress and QOL, emotional well-being) (P = 0.007) and fatigue (fatigue, sleep, and drowsiness) (P < 0.001) clusters. Results between six and 12 weeks showed sustained effects, but further improvement was not observed. Our results provide clinical effectiveness evidence that MBSR(BC) works to improve symptom clusters, particularly for psychological and fatigue symptom clusters, with the greatest improvement occurring during the six-week program with sustained effects for several weeks after MBSR(BC) training. Name and URL of Registry: ClinicalTrials.gov. Registration number: NCT01177124. Copyright © 2016. Published by Elsevier Inc.

Health and Human Services Cluster. Task Analyses. Physical Therapist Aide and Physical Therapist Assistant. A Competency-Based Curriculum Guide.

ERIC Educational Resources Information Center

Henrico County Public Schools, Glen Allen, VA. Virginia Vocational Curriculum and Resource Center.

Developed in Virginia, this publication contains task analysis guides to support selected tech prep programs that prepare students for careers in the health and human services cluster. Occupations profiled are physical therapist aide and physical therapist assistant. Each guide contains the following elements: (1) an occupational task list derived…

Opportunity for collaboration: a conceptual model of success in tobacco control and cancer prevention.

PubMed

Stillman, Frances A; Schmitt, Carol L; Rosas, Scott R

2012-01-01

Collaborations between cancer prevention and tobacco control programs can leverage scarce resources to address noncommunicable diseases globally, but barriers to cooperation and actual collaboration are substantial. To foster collaboration between cancer prevention and tobacco control programs, the Global Health Partnership conducted research to identify similarities and differences in how the 2 programs viewed program success. Using concept mapping, cancer prevention and tobacco control experts generated statements describing the components of a successful cancer prevention or tobacco control program and 33 participants sorted and rated the final 99 statements. Multidimensional scaling analysis with a 2-dimensional solution was used to identify an 8-cluster conceptual map of program success. We calculated Pearson correlation coefficients for all 99 statements to compare the item-level ratings of both groups and used t tests to compare the mean importance of ratings assigned to each cluster. Eight major clusters of success were identified: 1) advocacy and persuasion, 2) building sustainability, 3) partnerships, 4) readiness and support, 5) program management fundamentals, 6) monitoring and evaluation, 7) utilization of evidence, and 8) implementation. We found no significant difference between the maps created by the 2 groups and only 1 mean difference for the importance ratings for 1 of the clusters: cancer prevention experts rated partnerships as more important to program success than did tobacco control experts. Our findings are consistent with those of research documenting the necessary components of successful programs and the similarities between cancer prevention and tobacco control. Both programs value the same strategies to address a common risk factor: tobacco use. Identifying common ground between these 2 research and practice communities can benefit future collaborations at the local, state, tribal, national, and international levels, and inform the broader discussion on resource sharing among other organizations whose mission focuses on noncommunicable diseases.

Computer program documentation: ISOCLS iterative self-organizing clustering program, program C094

NASA Technical Reports Server (NTRS)

Minter, R. T. (Principal Investigator)

1972-01-01

The author has identified the following significant results. This program implements an algorithm which, ideally, sorts a given set of multivariate data points into similar groups or clusters. The program is intended for use in the evaluation of multispectral scanner data; however, the algorithm could be used for other data types as well. The user may specify a set of initial estimated cluster means to begin the procedure, or he may begin with the assumption that all the data belongs to one cluster. The procedure is initiatized by assigning each data point to the nearest (in absolute distance) cluster mean. If no initial cluster means were input, all of the data is assigned to cluster 1. The means and standard deviations are calculated for each cluster.

42 CFR 431.992 - Corrective action plan.

Code of Federal Regulations, 2010 CFR

2010-10-01

... CMS, designed to reduce improper payments in each program based on its analysis of the error causes in... State must take the following actions: (1) Data analysis. States must conduct data analysis such as reviewing clusters of errors, general error causes, characteristics, and frequency of errors that are...

42 CFR 431.992 - Corrective action plan.

Code of Federal Regulations, 2011 CFR

2011-10-01

... CMS, designed to reduce improper payments in each program based on its analysis of the error causes in... State must take the following actions: (1) Data analysis. States must conduct data analysis such as reviewing clusters of errors, general error causes, characteristics, and frequency of errors that are...

Use of Spatial Epidemiology and Hot Spot Analysis to Target Women Eligible for Prenatal Women, Infants, and Children Services

PubMed Central

Krawczyk, Christopher; Gradziel, Pat; Geraghty, Estella M.

2014-01-01

Objectives. We used a geographic information system and cluster analyses to determine locations in need of enhanced Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) Program services. Methods. We linked documented births in the 2010 California Birth Statistical Master File with the 2010 data from the WIC Integrated Statewide Information System. Analyses focused on the density of pregnant women who were eligible for but not receiving WIC services in California’s 7049 census tracts. We used incremental spatial autocorrelation and hot spot analyses to identify clusters of WIC-eligible nonparticipants. Results. We detected clusters of census tracts with higher-than-expected densities, compared with the state mean density of WIC-eligible nonparticipants, in 21 of 58 (36.2%) California counties (P < .05). In subsequent county-level analyses, we located neighborhood-level clusters of higher-than-expected densities of eligible nonparticipants in Sacramento, San Francisco, Fresno, and Los Angeles Counties (P < .05). Conclusions. Hot spot analyses provided a rigorous and objective approach to determine the locations of statistically significant clusters of WIC-eligible nonparticipants. Results helped inform WIC program and funding decisions, including the opening of new WIC centers, and offered a novel approach for targeting public health services. PMID:24354821

Elements concentration analysis in groundwater from the North Serra Geral aquifer in Santa Helena-Brazil using SR-TXRF spectrometer.

PubMed

Justen, Gisele C; Espinoza-Quiñones, Fernando R; Módenes, Aparecido Nivaldo; Bergamasco, Rosangela

2012-01-01

In this work the analysis of elements concentration in groundwater was performed using the synchrotron radiation total-reflection X-ray fluorescence (SR-TXRF) technique. A set of nine tube-wells with serious risk of contamination was chosen to monitor the mean concentration of elements in groundwater from the North Serra Geral aquifer in Santa Helena, Brazil, during 1 year. Element concentrations were determined applying a SR-TXRF methodology. The accuracy of SR-TXRF technique was validated by analysis of a certified reference material. As the groundwater composition in the North Serra Geral aquifer showed heterogeneity in the spatial distribution of eight major elements, a hierarchical clustering to the data was performed. By a similarity in their compositions, two of the nine wells were grouped in a first cluster, while the other seven were grouped in a second cluster. Calcium was the major element in all wells, with higher Ca concentration in the second cluster than in the first cluster. However, concentrations of Ti, V, Cr in the first cluster are slightly higher than those in the second cluster. The findings of this study within a monitoring program of tube-wells could provide a useful assessment of controls over groundwater composition and support management at regional level.

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

PubMed Central

Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

2015-01-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

Convex clustering: an attractive alternative to hierarchical clustering.

PubMed

Chen, Gary K; Chi, Eric C; Ranola, John Michael O; Lange, Kenneth

2015-05-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/.

Cluster analysis of the national weight control registry to identify distinct subgroups maintaining successful weight loss.

PubMed

Ogden, Lorraine G; Stroebele, Nanette; Wyatt, Holly R; Catenacci, Victoria A; Peters, John C; Stuht, Jennifer; Wing, Rena R; Hill, James O

2012-10-01

The National Weight Control Registry (NWCR) is the largest ongoing study of individuals successful at maintaining weight loss; the registry enrolls individuals maintaining a weight loss of at least 13.6 kg (30 lb) for a minimum of 1 year. The current report uses multivariate latent class cluster analysis to identify unique clusters of individuals within the NWCR that have distinct experiences, strategies, and attitudes with respect to weight loss and weight loss maintenance. The cluster analysis considers weight and health history, weight control behaviors and strategies, effort and satisfaction with maintaining weight, and psychological and demographic characteristics. The analysis includes 2,228 participants enrolled between 1998 and 2002. Cluster 1 (50.5%) represents a weight-stable, healthy, exercise conscious group who are very satisfied with their current weight. Cluster 2 (26.9%) has continuously struggled with weight since childhood; they rely on the greatest number of resources and strategies to lose and maintain weight, and report higher levels of stress and depression. Cluster 3 (12.7%) represents a group successful at weight reduction on the first attempt; they were least likely to be overweight as children, are maintaining the longest duration of weight loss, and report the least difficulty maintaining weight. Cluster 4 (9.9%) represents a group less likely to use exercise to control weight; they tend to be older, eat fewer meals, and report more health problems. Further exploration of the unique characteristics of these clusters could be useful for tailoring future weight loss and weight maintenance programs to the specific characteristics of an individual.

Associations Among Health Care Workplace Safety, Resident Satisfaction, and Quality of Care in Long-Term Care Facilities.

PubMed

Boakye-Dankwa, Ernest; Teeple, Erin; Gore, Rebecca; Punnett, Laura

2017-11-01

We performed an integrated cross-sectional analysis of relationships between long-term care work environments, employee and resident satisfaction, and quality of patient care. Facility-level data came from a network of 203 skilled nursing facilities in 13 states in the eastern United States owned or managed by one company. K-means cluster analysis was applied to investigate clustered associations between safe resident handling program (SRHP) performance, resident care outcomes, employee satisfaction, rates of workers' compensation claims, and resident satisfaction. Facilities in the better-performing cluster were found to have better patient care outcomes and resident satisfaction; lower rates of workers compensation claims; better SRHP performance; higher employee retention; and greater worker job satisfaction and engagement. The observed clustered relationships support the utility of integrated performance assessment in long-term care facilities.

Description and typology of intensive Chios dairy sheep farms in Greece.

PubMed

Gelasakis, A I; Valergakis, G E; Arsenos, G; Banos, G

2012-06-01

The aim was to assess the intensified dairy sheep farming systems of the Chios breed in Greece, establishing a typology that may properly describe and characterize them. The study included the total of the 66 farms of the Chios sheep breeders' cooperative Macedonia. Data were collected using a structured direct questionnaire for in-depth interviews, including questions properly selected to obtain a general description of farm characteristics and overall management practices. A multivariate statistical analysis was used on the data to obtain the most appropriate typology. Initially, principal component analysis was used to produce uncorrelated variables (principal components), which would be used for the consecutive cluster analysis. The number of clusters was decided using hierarchical cluster analysis, whereas, the farms were allocated in 4 clusters using k-means cluster analysis. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main differences were evident on land availability and use, facility and equipment availability and type, expansion rates, and application of preventive flock health programs. In general, cluster 1 included newly established, intensive, well-equipped, specialized farms and cluster 2 included well-established farms with balanced sheep and feed/crop production. In cluster 3 were assigned small flock farms focusing more on arable crops than on sheep farming with a tendency to evolve toward cluster 2, whereas cluster 4 included farms representing a rather conservative form of Chios sheep breeding with low/intermediate inputs and choosing not to focus on feed/crop production. In the studied set of farms, 4 different farmer attitudes were evident: 1) farming disrupts sheep breeding; feed should be purchased and economies of scale will decrease costs (mainly cluster 1), 2) only exercise/pasture land is necessary; at least part of the feed (pasture) must be home-grown to decrease costs (clusters 1 and 4), 3) providing pasture to sheep is essential; on-farm feed production decreases costs (mainly cluster 3), and 4) large-scale farming (feed production and cash crops) does not disrupt sheep breeding; all feed must be produced on-farm to decrease costs (mainly cluster 3). Conducting a profitability analysis among different clusters, exploring and discovering the most beneficial levels of intensified management and capital investment should now be considered. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Financial-Ratio Analysis and Medical School Management.

ERIC Educational Resources Information Center

Eastaugh, Steven R.

1980-01-01

The value of a uniform program of financial assistance to medical education and research is questioned. Medical schools have an uneven ability to compensate for declining federal capitation and research grants. Financial-ratio analysis and cluster analysis are utilized to suggest four adaptive responses to future financial pressures. (Author/MLW)

A Search for Ram-pressure Stripping in the Hydra I Cluster

NASA Technical Reports Server (NTRS)

Brown, B.

2005-01-01

Ram-pressure stripping is a method by which hot interstellar gas can be removed from a galaxy moving through a group or cluster of galaxies. Indirect evidence of ram-pressure stripping includes lowered X-ray brightness in a galaxy due to less X-ray emitting gas remaining in the galaxy. Here we present the initial results of our program to determine whether cluster elliptical galaxies have lower hot gas masses than their counterparts in less rich environments. This test requires the use of the high-resolution imaging of the Chandra Observatory and we present our analysis of the galaxies in the nearby cluster Hydra I.

A Search for Ram-pressure Stripping in the Hydra I Cluster

NASA Technical Reports Server (NTRS)

Brown, B. A.

2005-01-01

Ram-pressure stripping is a method by which hot interstellar gas can be removed from a galaxy moving through a group or cluster of galaxies. Indirect evidence of ram-pressure stripping includes lowered X- ray brightness in a galaxy due to less X-ray emitting gas remaining in the galaxy. Here we present the initial results of our program to determine whether cluster elliptical galaxies have lower hot gas masses than their counterparts in less rich environments. This test requires the use of the high-resolution imaging of the Chundru Observatory and we present our analysis of the galaxies in the nearby cluster Hydra I.

The Most Distant X-Ray Clusters

NASA Technical Reports Server (NTRS)

Dickinson, Mark

1999-01-01

In this program we have used ROSAT (Roentgen Satellite Mission) to observe X-ray emission around several high redshift radio galaxies in a search for extended, hot plasma which may indicate the presence of a rich galaxy cluster. When this program was begun, massive, X-ray emitting galaxy clusters were known to exist out to to z=0.8, but no more distant examples had been identified. However, we had identified several apparently rich clusters around 3CR radio galaxies at z greater than 0.8, and hoped to use ROSAT to confirm the nature of these structures as massive, virialized clusters. We have written up our results and submitted them as a paper to the Astrophysical Journal. This paper has been refereed and requires some significant revisions to accommodate the referees comments. We are in the process of doing this, adding some additional analysis as well. We will resubmit the paper early in 2000, and hopefully will meet with the referee's approval. We are including three copies of the submitted paper here, although it has not yet been accepted for publication.

On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

PubMed

Haneuse, Sebastien; Rivera-Rodriguez, Claudia

2018-01-01

In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

Evaluating elevated levels of crown dieback among northern white-cedar (Thuja occidentalis L.) trees in Maine and Michigan: a summary of evaluation monitoring

Treesearch

KaDonna Randolph; William A. Bechtold; Randall S. Morin; Stanley J. Zarnoch

2012-01-01

Analysis of crown condition data for the 2006 national technical report of the Forest Health Monitoring (FHM) Program of the Forest Service, U.S. Department of Agriculture, exposed clusters of phase 3 plots (by the Forest Inventory and Analysis [FIA] Program of the Forest Service) with northern white-cedar (Thuja occidentalis L.) crown dieback...

VizieR Online Data Catalog: IN-SYNC. III. Radial velocities of IC348 stars (Cottaar+, 2015)

NASA Astrophysics Data System (ADS)

Cottaar, M.; Covey, K. R.; Foster, J. B.; Meyer, M. R.; Tan, J. C.; Nidever, D. L.; Drew Chojnowski, S.; da Rio, N.; Flaherty, K. M.; Frinchaboy, P. M.; Majewski, S.; Skrutskie, M. F.; Wilson, J. C.; Zasowski, G.

2015-11-01

Cottaar et al. (Paper I, 2014, J/ApJ/794/125) describes the analysis of the high-resolution near-infrared spectra obtained by the APOGEE multi-object spectrograph from stars in IC 348, NGC 1333, NGC 2264, and Orion A as part of the INfrared Spectroscopy of Young Nebulous Clusters (IN-SYNC) ancillary program. Using radial velocities determined from APOGEE spectra of 380 likely cluster members, we have measured the radial velocity distribution of the young (2-6Myr) cluster IC 348. (2 data files).

Patterning C. elegans: homeotic cluster genes, cell fates and cell migrations.

PubMed

Salser, S J; Kenyon, C

1994-05-01

Despite its simple body form, the nematode C. elegans expresses homeotic cluster genes similar to those of insects and vertebrates in the patterning of many cell types and tissues along the anteroposterior axis. In the ventral nerve cord, these genes program spatial patterns of cell death, fusion, division and neurotransmitter production; in migrating cells they regulate the direction and extent of movement. Nematode development permits an analysis at the cellular level of how homeotic cluster genes interact to specify cell fates, and how cell behavior can be regulated to assemble an organism.

Genetic diversity analysis of Capparis spinosa L. populations by using ISSR markers.

PubMed

Liu, C; Xue, G P; Cheng, B; Wang, X; He, J; Liu, G H; Yang, W J

2015-12-09

Capparis spinosa L. is an important medicinal species in the Xinjiang Province of China. Ten natural populations of C. spinosa from 3 locations in North, Central, and South Xinjiang were studied using morphological trait inter simple sequence repeat (ISSR) molecular markers to assess the genetic diversity and population structure. In this study, the 10 ISSR primers produced 313 amplified DNA fragments, with 52% of fragments being polymorphic. Unweighted pair-group method with arithmetic average (UPGMA) cluster analysis indicated that 10 C. spinosa populations were clustered into 3 geographically distinct groups. The Nei gene of C. spinosa populations in different regions had Diversity and Shannon's information index ranges of 0.1312-0.2001 and 0.1004-0.1875, respectively. The 362 markers were used to construct the dendrogram based on the UPGMA cluster analysis. The dendrogram indicated that 10 populations of C. spinosa were clustered into 3 geographically distinct groups. The results showed these genotypes have high genetic diversity, and can be used for an alternative breeding program.

Galactic Astronomy in the Ultraviolet

NASA Astrophysics Data System (ADS)

Rastorguev, A. S.; Sachkov, M. E.; Zabolotskikh, M. V.

2017-12-01

We propose a number of prospective observational programs for the ultraviolet space observatory WSO-UV, which seem to be of great importance to modern galactic astronomy. The programs include the search for binary Cepheids; the search and detailed photometric study and the analysis of radial distribution of UV-bright stars in globular clusters ("blue stragglers", blue horizontal-branch stars, RR Lyrae variables, white dwarfs, and stars with UV excesses); the investigation of stellar content and kinematics of young open clusters and associations; the study of spectral energy distribution in hot stars, including calculation of the extinction curves in the UV, optical and NIR; and accurate definition of the relations between the UV-colors and effective temperature. The high angular resolution of the observatory allows accurate astrometric measurements of stellar proper motions and their kinematic analysis.

West Virginia US Department of Energy experimental program to stimulate competitive research. Section 2: Human resource development; Section 3: Carbon-based structural materials research cluster; Section 3: Data parallel algorithms for scientific computing

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

Not Available

1994-02-02

This report consists of three separate but related reports. They are (1) Human Resource Development, (2) Carbon-based Structural Materials Research Cluster, and (3) Data Parallel Algorithms for Scientific Computing. To meet the objectives of the Human Resource Development plan, the plan includes K--12 enrichment activities, undergraduate research opportunities for students at the state`s two Historically Black Colleges and Universities, graduate research through cluster assistantships and through a traineeship program targeted specifically to minorities, women and the disabled, and faculty development through participation in research clusters. One research cluster is the chemistry and physics of carbon-based materials. The objective of thismore » cluster is to develop a self-sustaining group of researchers in carbon-based materials research within the institutions of higher education in the state of West Virginia. The projects will involve analysis of cokes, graphites and other carbons in order to understand the properties that provide desirable structural characteristics including resistance to oxidation, levels of anisotropy and structural characteristics of the carbons themselves. In the proposed cluster on parallel algorithms, research by four WVU faculty and three state liberal arts college faculty are: (1) modeling of self-organized critical systems by cellular automata; (2) multiprefix algorithms and fat-free embeddings; (3) offline and online partitioning of data computation; and (4) manipulating and rendering three dimensional objects. This cluster furthers the state Experimental Program to Stimulate Competitive Research plan by building on existing strengths at WVU in parallel algorithms.« less

The effectiveness of an aged care specific leadership and management program on workforce, work environment, and care quality outcomes: design of a cluster randomised controlled trial

PubMed Central

2013-01-01

Background A plethora of observational evidence exists concerning the impact of management and leadership on workforce, work environment, and care quality. Yet, no randomised controlled trial has been conducted to test the effectiveness of leadership and management interventions in aged care. An innovative aged care clinical leadership program (Clinical Leadership in Aged Care − CLiAC) was developed to improve managers’ leadership capacities to support the delivery of quality care in Australia. This paper describes the study design of the cluster randomised controlled trial testing the effectiveness of the program. Methods Twenty-four residential and community aged care sites were recruited as managers at each site agreed in writing to participate in the study and ensure that leaders allocated to the control arm would not be offered the intervention program. Sites undergoing major managerial or structural changes were excluded. The 24 sites were randomly allocated to receive the CLiAC program (intervention) or usual care (control), stratified by type (residential vs. community, six each for each arm). Treatment allocation was masked to assessors and staff of all participating sites. The objective is to establish the effectiveness of the CLiAC program in improving work environment, workforce retention, as well as care safety and quality, when compared to usual care. The primary outcomes are measures of work environment, care quality and safety, and staff turnover rates. Secondary outcomes include manager leadership capacity, staff absenteeism, intention to leave, stress levels, and job satisfaction. Differences between intervention and control groups will be analysed by researchers blinded to treatment allocation using linear regression of individual results adjusted for stratification and clustering by site (primary analysis), and additionally for baseline values and potential confounders (secondary analysis). Outcomes measured at the site level will be compared by cluster-level analysis. The overall costs and benefits of the program will also be assessed. Discussion The outcomes of the trial have the potential to inform actions to enhance leadership and management capabilities of the aged care workforce, address pressing issues about workforce shortages, and increase the quality of aged care services. Trial registration Australian New Zealand Clinical Trials Registry (ACTRN12611001070921) PMID:24160714

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data

PubMed Central

Tian, Ting; McLachlan, Geoffrey J.; Dieters, Mark J.; Basford, Kaye E.

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances. PMID:26689369

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

PubMed

Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.

Development of a Computing Cluster At the University of Richmond

NASA Astrophysics Data System (ADS)

Carbonneau, J.; Gilfoyle, G. P.; Bunn, E. F.

2010-11-01

The University of Richmond has developed a computing cluster to support the massive simulation and data analysis requirements for programs in intermediate-energy nuclear physics, and cosmology. It is a 20-node, 240-core system running Red Hat Enterprise Linux 5. We have built and installed the physics software packages (Geant4, gemc, MADmap...) and developed shell and Perl scripts for running those programs on the remote nodes. The system has a theoretical processing peak of about 2500 GFLOPS. Testing with the High Performance Linpack (HPL) benchmarking program (one of the standard benchmarks used by the TOP500 list of fastest supercomputers) resulted in speeds of over 900 GFLOPS. The difference between the maximum and measured speeds is due to limitations in the communication speed among the nodes; creating a bottleneck for large memory problems. As HPL sends data between nodes, the gigabit Ethernet connection cannot keep up with the processing power. We will show how both the theoretical and actual performance of the cluster compares with other current and past clusters, as well as the cost per GFLOP. We will also examine the scaling of the performance when distributed to increasing numbers of nodes.

Spatial cluster detection using dynamic programming.

PubMed

Sverchkov, Yuriy; Jiang, Xia; Cooper, Gregory F

2012-03-25

The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm.

Spatial cluster detection using dynamic programming

PubMed Central

2012-01-01

Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm. PMID:22443103

A method for topological analysis of high nuclearity coordination clusters and its application to Mn coordination compounds.

PubMed

Kostakis, George E; Blatov, Vladislav A; Proserpio, Davide M

2012-04-21

A novel method for the topological description of high nuclearity coordination clusters (CCs) was improved and applied to all compounds containing only manganese as a metal center, the data on which are collected in the CCDC (CCDC 5.33 Nov. 2011). Using the TOPOS program package that supports this method, we identified 539 CCs with five or more Mn centers adopting 159 topologically different graphs. In the present database all the Mn CCs are collected and illustrated in such a way that can be searched by cluster topological symbol and nuclearity, compound name and Refcode. The main principles for such an analysis are described herein as well as useful applications of this method.

Multiwavelength study of X-ray luminous clusters in the Hyper Suprime-Cam Subaru Strategic Program S16A field

NASA Astrophysics Data System (ADS)

Miyaoka, Keita; Okabe, Nobuhiro; Kitaguchi, Takao; Oguri, Masamune; Fukazawa, Yasushi; Mandelbaum, Rachel; Medezinski, Elinor; Babazaki, Yasunori; Nishizawa, Atsushi J.; Hamana, Takashi; Lin, Yen-Ting; Akamatsu, Hiroki; Chiu, I.-Non; Fujita, Yutaka; Ichinohe, Yuto; Komiyama, Yutaka; Sasaki, Toru; Takizawa, Motokazu; Ueda, Shutaro; Umetsu, Keiichi; Coupon, Jean; Hikage, Chiaki; Hoshino, Akio; Leauthaud, Alexie; Matsushita, Kyoko; Mitsuishi, Ikuyuki; Miyatake, Hironao; Miyazaki, Satoshi; More, Surhud; Nakazawa, Kazuhiro; Ota, Naomi; Sato, Kousuke; Spergel, David; Tamura, Takayuki; Tanaka, Masayuki; Tanaka, Manobu M.; Utsumi, Yousuke

2018-01-01

We present a joint X-ray, optical, and weak-lensing analysis for X-ray luminous galaxy clusters selected from the MCXC (Meta-Catalog of X-Ray Detected Clusters of Galaxies) cluster catalog in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey field with S16A data. As a pilot study for a series of papers, we measure hydrostatic equilibrium (HE) masses using XMM-Newton data for four clusters in the current coverage area out of a sample of 22 MCXC clusters. We additionally analyze a non-MCXC cluster associated with one MCXC cluster. We show that HE masses for the MCXC clusters are correlated with cluster richness from the CAMIRA catalog, while that for the non-MCXC cluster deviates from the scaling relation. The mass normalization of the relationship between cluster richness and HE mass is compatible with one inferred by matching CAMIRA cluster abundance with a theoretical halo mass function. The mean gas mass fraction based on HE masses for the MCXC clusters is = 0.125 ± 0.012 at spherical overdensity Δ = 500, which is ˜80%-90% of the cosmic mean baryon fraction, Ωb/Ωm, measured by cosmic microwave background experiments. We find that the mean baryon fraction estimated from X-ray and HSC-SSP optical data is comparable to Ωb/Ωm. A weak-lensing shear catalog of background galaxies, combined with photometric redshifts, is currently available only for three clusters in our sample. Hydrostatic equilibrium masses roughly agree with weak-lensing masses, albeit with large uncertainty. This study demonstrates that further multiwavelength study for a large sample of clusters using X-ray, HSC-SSP optical, and weak-lensing data will enable us to understand cluster physics and utilize cluster-based cosmology.

MIXOR: a computer program for mixed-effects ordinal regression analysis.

PubMed

Hedeker, D; Gibbons, R D

1996-03-01

MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

PubMed

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

Analyzing human errors in flight mission operations

NASA Technical Reports Server (NTRS)

Bruno, Kristin J.; Welz, Linda L.; Barnes, G. Michael; Sherif, Josef

1993-01-01

A long-term program is in progress at JPL to reduce cost and risk of flight mission operations through a defect prevention/error management program. The main thrust of this program is to create an environment in which the performance of the total system, both the human operator and the computer system, is optimized. To this end, 1580 Incident Surprise Anomaly reports (ISA's) from 1977-1991 were analyzed from the Voyager and Magellan projects. A Pareto analysis revealed that 38 percent of the errors were classified as human errors. A preliminary cluster analysis based on the Magellan human errors (204 ISA's) is presented here. The resulting clusters described the underlying relationships among the ISA's. Initial models of human error in flight mission operations are presented. Next, the Voyager ISA's will be scored and included in the analysis. Eventually, these relationships will be used to derive a theoretically motivated and empirically validated model of human error in flight mission operations. Ultimately, this analysis will be used to make continuous process improvements continuous process improvements to end-user applications and training requirements. This Total Quality Management approach will enable the management and prevention of errors in the future.

Optimization Techniques for Analysis of Biological and Social Networks

DTIC Science & Technology

2012-03-28

analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms , test and fine...alternative mathematical programming formulations, their theoretical analysis, the development of exact algorithms , and heuristics. Originally, clusters...systematic fashion under a unifying theoretical and algorithmic framework. Optimization, Complex Networks, Social Network Analysis, Computational

Exploring the nature and synchronicity of early cluster formation in the Large Magellanic Cloud - III. Horizontal branch morphology

NASA Astrophysics Data System (ADS)

Wagner-Kaiser, R.; Mackey, Dougal; Sarajedini, Ata; Cohen, Roger E.; Geisler, Doug; Yang, Soung-Chul; Grocholski, Aaron J.; Cummings, Jeffrey D.

2018-03-01

We leverage new high-quality data from Hubble Space Telescope program GO-14164 to explore the variation in horizontal branch morphology among globular clusters in the Large Magellanic Cloud (LMC). Our new observations lead to photometry with a precision commensurate with that available for the Galactic globular cluster population. Our analysis indicates that, once metallicity is accounted for, clusters in the LMC largely share similar horizontal branch morphologies regardless of their location within the system. Furthermore, the LMC clusters possess, on average, slightly redder morphologies than most of the inner halo Galactic population; we find, instead, that their characteristics tend to be more similar to those exhibited by clusters in the outer Galactic halo. Our results are consistent with previous studies, showing a correlation between horizontal branch morphology and age.

Implementation of hybrid clustering based on partitioning around medoids algorithm and divisive analysis on human Papillomavirus DNA

NASA Astrophysics Data System (ADS)

Arimbi, Mentari Dian; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Data clustering can be executed through partition or hierarchical method for many types of data including DNA sequences. Both clustering methods can be combined by processing partition algorithm in the first level and hierarchical in the second level, called hybrid clustering. In the partition phase some popular methods such as PAM, K-means, or Fuzzy c-means methods could be applied. In this study we selected partitioning around medoids (PAM) in our partition stage. Furthermore, following the partition algorithm, in hierarchical stage we applied divisive analysis algorithm (DIANA) in order to have more specific clusters and sub clusters structures. The number of main clusters is determined using Davies Bouldin Index (DBI) value. We choose the optimal number of clusters if the results minimize the DBI value. In this work, we conduct the clustering on 1252 HPV DNA sequences data from GenBank. The characteristic extraction is initially performed, followed by normalizing and genetic distance calculation using Euclidean distance. In our implementation, we used the hybrid PAM and DIANA using the R open source programming tool. In our results, we obtained 3 main clusters with average DBI value is 0.979, using PAM in the first stage. After executing DIANA in the second stage, we obtained 4 sub clusters for Cluster-1, 9 sub clusters for Cluster-2 and 2 sub clusters in Cluster-3, with the BDI value 0.972, 0.771, and 0.768 for each main cluster respectively. Since the second stage produce lower DBI value compare to the DBI value in the first stage, we conclude that this hybrid approach can improve the accuracy of our clustering results.

CLASSIFY: A Group Teaching Exercise in Microbial Identification and Numerical Taxonomy Using a Commodore 64 Microcomputer.

ERIC Educational Resources Information Center

Soddell, J. A.; Seviour, R. J.

1985-01-01

Describes an exercise which uses a computer program (written for Commodore 64 microcomputers) that accepts data obtained from identifying bacteria, calculates similarity coefficients, and performs single linkage cluster analysis. Includes a program for simulating bacterial cultures for students who should not handle pathogenic microorganisms. (JN)

UFVA, A Combined Linear and Nonlinear Factor Analysis Program Package for Chemical Data Evaluation.

DTIC Science & Technology

1980-11-01

that one cluster consists of the monoterpenes and Isoprene; the second is of the sesquiterpenes. Compound 8 (Caryophyllene) should therefore belong to...two clusters very clearly (Fig. 6). Figure 6 The very similar fragmentation pattern of Isoprene and the monoterpenes is reflected by their close...13 of another set of 13 terpene components. These are Isoprene, four monoterpenes (Myrcene, Menthol, Camphene, Umbellulone), four sesquiterpenes

RAPTOR-scan: Identifying and Tracking Objects Through Thousands of Sky Images

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

Davidoff, Sherri; Wozniak, Przemyslaw

2004-09-28

The RAPTOR-scan system mines data for optical transients associated with gamma-ray bursts and is used to create a catalog for the RAPTOR telescope system. RAPTOR-scan can detect and track individual astronomical objects across data sets containing millions of observed points.Accurately identifying a real object over many optical images (clustering the individual appearances) is necessary in order to analyze object light curves. To achieve this, RAPTOR telescope observations are sent in real time to a database. Each morning, a program based on the DBSCAN algorithm clusters the observations and labels each one with an object identifier. Once clustering is complete, themore » analysis program may be used to query the database and produce light curves, maps of the sky field, or other informative displays.Although RAPTOR-scan was designed for the RAPTOR optical telescope system, it is a general tool designed to identify objects in a collection of astronomical data and facilitate quick data analysis. RAPTOR-scan will be released as free software under the GNU General Public License.« less

Spatial distribution of HIV, HCV, and co-infections among drug users in the southwestern border areas of China (2004-2014): a cohort study of a national methadone maintenance treatment program.

PubMed

Li, Mingli; Li, Rongjian; Shen, Zhiyong; Li, Chunying; Liang, Nengxiu; Peng, Zhenren; Huang, Wenbo; He, Chongwei; Zhong, Feng; Tang, Xianyan; Lan, Guanghua

2017-09-30

A methadone maintenance treatment (MMT) program to curb the dual epidemics of HIV/AIDS and drug use has been administered by China since 2004. Little is known regarding the geographic heterogeneity of HIV and hepatitis C virus (HCV) infections among MMT clients in the resource-constrained context of Chinese provinces, such as Guangxi. This study aimed to characterize the geographic distribution patterns and co-clustered epidemic factors of HIV, HCV and co-infections at the county level among drug users receiving MMT in Guangxi Zhuang Autonomous Region, located in the southwestern border area of China. Baseline data on drug users' demographic, behavioral and biological characteristics in the MMT clinics of Guangxi Zhuang Autonomous Region during the period of March 2004 to December 2014 were obtained from national HIV databases. Residential addresses were entered into a geographical information system (GIS) program and analyzed for spatial clustering of HIV, HCV and co-infections among MMT clients at the county level using geographic autocorrelation analysis and geographic scan statistics. A total of 31,015 MMT clients were analyzed, and the prevalence of HIV, HCV and co-infections were 13.05%, 72.51% and 11.96% respectively. Both the geographic autocorrelation analysis and geographic scan statistics showed that HIV, HCV and co-infections in Guangxi Zhuang Autonomous Region exhibited significant geographic clustering at the county level, and the Moran's I values were 0.33, 0.41 and 0.30, respectively (P < 0.05). The most significant high-risk overlapping clusters for these infections were restricted to within a 10.95 km 2 radius of each of the 13 locations where P county was the cluster center. These infections also co-clustered with certain characteristics, such as being unmarried, having a primary level of education or below, having used drugs for more than 10 years, and receptive sharing of syringes with others. The high-risk clusters for these characteristics were more likely to reside in the areas surrounding P county. HIV, HCV and co-infections among MMT clients in Guangxi Zhuang Autonomous Region all presented substantial geographic heterogeneity at the county level with a number of overlapping significant clusters. The areas surrounding P county were effective in enrolling high-risk clients in their MMT programs which, in turn, might enable people who inject drugs to inject less, share fewer syringes, and receive referrals for HIV or HCV treatment in a timely manner.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

PubMed

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of Landsat digital data. [mapping of hydrothermally altered volcanic rocks

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB.

PubMed

Kent, Peter; Jensen, Rikke K; Kongsted, Alice

2014-10-02

There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets indicated that all three clustering methods showed a near-perfect ability to detect known subgroups and correctly classify individuals into those subgroups. Our subjective judgement was that Latent Gold offered the best balance of sensitivity to subgroups, ease of use and presentation of results with these datasets but we recognise that different clustering methods may suit other types of data and clinical research questions.

Incentives, Program Configuration, and Employee Uptake of Workplace Wellness Programs.

PubMed

Huang, Haijing; Mattke, Soeren; Batorsky, Benajmin; Miles, Jeremy; Liu, Hangsheng; Taylor, Erin

2016-01-01

The aim of this study was to determine the effect of wellness program configurations and financial incentives on employee participation rate. We analyze a nationally representative survey on workplace wellness programs from 407 employers using cluster analysis and multivariable regression analysis. Employers who offer incentives and provide a comprehensive set of program offerings have higher participation rates. The effect of incentives differs by program configuration, with the strongest effect found for comprehensive and prevention-focused programs. Among intervention-focused programs, incentives are not associated with higher participation. Wellness programs can be grouped into distinct configurations, which have different workplace health focuses. Although monetary incentives can be effective in improving employee participation, the magnitude and significance of the effect is greater for some program configurations than others.

Optimizing disinfection by-product monitoring points in a distribution system using cluster analysis.

PubMed

Delpla, Ianis; Florea, Mihai; Pelletier, Geneviève; Rodriguez, Manuel J

2018-06-04

Trihalomethanes (THMs) and Haloacetic Acids (HAAs) are the main groups detected in drinking water and are consequently strictly regulated. However, the increasing quantity of data for disinfection byproducts (DBPs) produced from research projects and regulatory programs remains largely unexploited, despite a great potential for its use in optimizing drinking water quality monitoring to meet specific objectives. In this work, we developed a procedure to optimize locations and periods for DBPs monitoring based on a set of monitoring scenarios using the cluster analysis technique. The optimization procedure used a robust set of spatio-temporal monitoring results on DBPs (THMs and HAAs) generated from intensive sampling campaigns conducted in a residential sector of a water distribution system. Results shows that cluster analysis allows for the classification of water quality in different groups of THMs and HAAs according to their similarities, and the identification of locations presenting water quality concerns. By using cluster analysis with different monitoring objectives, this work provides a set of monitoring solutions and a comparison between various monitoring scenarios for decision-making purposes. Finally, it was demonstrated that the data from intensive monitoring of free chlorine residual and water temperature as DBP proxy parameters, when processed using cluster analysis, could also help identify the optimal sampling points and periods for regulatory THMs and HAAs monitoring. Copyright © 2018 Elsevier Ltd. All rights reserved.

WISC-R Types of Learning Disabilities: A Profile Analysis with Cross-Validation.

ERIC Educational Resources Information Center

Holcomb, William R.; And Others

1987-01-01

Profiles (Wechsler Intelligence Scale for Children - Revised) of 119 children in five learning disability programs were placed in six homogeneous groups using cluster analysis. One group showed superior intelligence quotient (IQ) with motor coordination deficits and severe emotional problems, while three groups represented children with low IQs…

Diversity, Knowledge Clusters, and Job Placement: Graduate Economics Teaching of Core Microeconomics

ERIC Educational Resources Information Center

Campbell, Arthur; Feinstein, Jonathan S.; Hong, Soonwook; Qian, Sharon; Williams, Trevor C.

2017-01-01

The authors present an empirical analysis of what is taught in core micro-economics at a set of top U.S. doctoral economics programs. Their aim is to evaluate the diversity across programs and assess whether there are distinct "schools of thought" in graduate economics education. Their empirical findings reveal substantial, in fact,…

Construction and Utilization of a Beowulf Computing Cluster: A User's Perspective

NASA Technical Reports Server (NTRS)

Woods, Judy L.; West, Jeff S.; Sulyma, Peter R.

2000-01-01

Lockheed Martin Space Operations - Stennis Programs (LMSO) at the John C Stennis Space Center (NASA/SSC) has designed and built a Beowulf computer cluster which is owned by NASA/SSC and operated by LMSO. The design and construction of the cluster are detailed in this paper. The cluster is currently used for Computational Fluid Dynamics (CFD) simulations. The CFD codes in use and their applications are discussed. Examples of some of the work are also presented. Performance benchmark studies have been conducted for the CFD codes being run on the cluster. The results of two of the studies are presented and discussed. The cluster is not currently being utilized to its full potential; therefore, plans are underway to add more capabilities. These include the addition of structural, thermal, fluid, and acoustic Finite Element Analysis codes as well as real-time data acquisition and processing during test operations at NASA/SSC. These plans are discussed as well.

Comparison of Salmonella enteritidis phage types isolated from layers and humans in Belgium in 2005.

PubMed

Welby, Sarah; Imberechts, Hein; Riocreux, Flavien; Bertrand, Sophie; Dierick, Katelijne; Wildemauwe, Christa; Hooyberghs, Jozef; Van der Stede, Yves

2011-08-01

The aim of this study was to investigate the available results for Belgium of the European Union coordinated monitoring program (2004/665 EC) on Salmonella in layers in 2005, as well as the results of the monthly outbreak reports of Salmonella Enteritidis in humans in 2005 to identify a possible statistical significant trend in both populations. Separate descriptive statistics and univariate analysis were carried out and the parametric and/or non-parametric hypothesis tests were conducted. A time cluster analysis was performed for all Salmonella Enteritidis phage types (PTs) isolated. The proportions of each Salmonella Enteritidis PT in layers and in humans were compared and the monthly distribution of the most common PT, isolated in both populations, was evaluated. The time cluster analysis revealed significant clusters during the months May and June for layers and May, July, August, and September for humans. PT21, the most frequently isolated PT in both populations in 2005, seemed to be responsible of these significant clusters. PT4 was the second most frequently isolated PT. No significant difference was found for the monthly trend evolution of both PT in both populations based on parametric and non-parametric methods. A similar monthly trend of PT distribution in humans and layers during the year 2005 was observed. The time cluster analysis and the statistical significance testing confirmed these results. Moreover, the time cluster analysis showed significant clusters during the summer time and slightly delayed in time (humans after layers). These results suggest a common link between the prevalence of Salmonella Enteritidis in layers and the occurrence of the pathogen in humans. Phage typing was confirmed to be a useful tool for identifying temporal trends.

Scalability of an Evidence-Based Adolescent Pregnancy Prevention Program: New Evidence From 5 Cluster-Randomized Evaluations of the Teen Outreach Program.

PubMed

Francis, Kimberly; Philliber, Susan; Walsh-Buhi, Eric R; Philliber, Ashley; Seshadri, Roopa; Daley, Ellen

2016-09-01

To determine if the Teen Outreach Program (TOP), a youth development and service learning program, can reduce sexual risk-taking behaviors compared with a business as usual or benign counterfactual. We synthesized results of 5 independent studies conducted in 5 geographically and ethnically diverse locations between 2011 and 2015 with 17 194 middle and high school students. Each study cluster-randomized classes, teachers, or schools to treatment or control groups and included the students enrolled in those clusters at baseline in an intent-to-treat analysis. Multilevel models tested impacts on recent sexual activity, recent unprotected sexual activity, and sexual initiation among the sexually inexperienced at baseline at approximately 1 and 2 years after baseline. Precision-weighted average effect sizes showed nonsignificant reductions of 1 percentage point or less in recent sexual activity (5 studies: -0.6; P = .32), recent unprotected sex (5 studies: -0.2; P = .76), and sexual initiation (4 studies: -1.1; P = .10) after 1 year. There was little evidence of the effectiveness of TOP in reducing sexual risk-taking behaviors. Results underscored the importance of continually evaluating evidence-based programs that have previously been shown to be effective.

On the clustering of multidimensional pictorial data

NASA Technical Reports Server (NTRS)

Bryant, J. D. (Principal Investigator)

1979-01-01

Obvious approaches to reducing the cost (in computer resources) of applying current clustering techniques to the problem of remote sensing are discussed. The use of spatial information in finding fields and in classifying mixture pixels is examined, and the AMOEBA clustering program is described. Internally, a pattern recognition program, from without, AMOEBA appears to be an unsupervised clustering program. It is fast and automatic. No choices (such as arbitrary thresholds to set split/combine sequences) need be made. The problem of finding the number of clusters is solved automatically. At the conclusion of the program, all points in the scene are classified; however, a provision is included for a reject classification of some points which, within the theoretical framework, cannot rationally be assigned to any cluster.

Perceived Effects of Scholarships on STEM Majors' Commitment to Teaching in High Need Schools

NASA Astrophysics Data System (ADS)

Liou, Pey-Yan; Kirchhoff, Allison; Lawrenz, Frances

2010-06-01

This study examines the Noyce Program, which provides scholarships for STEM majors in return for teaching in high need schools. The perceptions of 555 scholarship recipients were investigated using hierarchical cluster analysis, confirmatory factor analysis, and Rasch analysis to determine how the scholarship influenced their commitments to teaching in high need schools. The analyses indicated that recipients perceived the scholarship in two ways: it influenced their commitment to complete their certification program and to teach in high need schools. Implications for teacher education programs include that recruitment strategies should identify candidates who are committed to teaching in high need schools and programs should provide experiences to encourage this commitment not just to become certified.

Plug cluster module demonstration

NASA Technical Reports Server (NTRS)

Rousar, D. C.

1978-01-01

The low pressure, film cooled rocket engine design concept developed during two previous ALRC programs was re-evaluated for application as a module for a plug cluster engine capable of performing space shuttle OTV missions. The nominal engine mixture ratio was 5.5 and the engine life requirements were 1200 thermal cycles and 10 hours total operating life. The program consisted of pretest analysis; engine tests, performed using residual components; and posttest analysis. The pretest analysis indicated that operation of the operation of the film cooled engine at O/F = 5.5 was feasible. During the engine tests, steady state wall temperature and performance measurement were obtained over a range of film cooling flow rates, and the durability of the engine was demonstrated by firing the test engine 1220 times at a nominal performance ranging from 430 - 432 seconds. The performance of the test engine was limited by film coolant sleeve damage which had occurred during previous testing. The post-test analyses indicated that the nominal performance level can be increased to 436 seconds.

Spatial cluster analysis of human cases of Crimean Congo hemorrhagic fever reported in Pakistan.

PubMed

Abbas, Tariq; Younus, Muhammad; Muhammad, Sayyad Aun

2015-01-01

Crimean Congo hemorrhagic fever (CCHF) is a tick-borne viral zoonotic disease that has been reported in almost all geographic regions in Pakistan. The aim of this study was to identify spatial clusters of human cases of CCHF reported in country. Kulldorff's spatial scan statisitc, Anselin's Local Moran's I and Getis Ord Gi* tests were applied on data (i.e. number of laboratory confirmed cases reported from each district during year 2013). The analyses revealed a large multi-district cluster of high CCHF incidence in the uplands of Balochistan province near it border with Afghanistan. The cluster comprised the following districts: Qilla Abdullah; Qilla Saifullah; Loralai, Quetta, Sibi, Chagai, and Mastung. Another cluster was detected in Punjab and included Rawalpindi district and a part of Islamabad. We provide empirical evidence of spatial clustering of human CCHF cases in the country. The districts in the clusters should be given priority in surveillance, control programs, and further research.

76 FR 18573 - Notice of Proposed Information Collection; Comment Request; National Resource Bank

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-04

... December 16, 2009) funds technical assistance for HUD programs under the Transformation Initiative (TI... business cluster and job market analysis, to name a few. Agency form numbers, if applicable: SF-424, SF...

Dynamics of cD Clusters of Galaxies. 4; Conclusion of a Survey of 25 Abell Clusters

NASA Technical Reports Server (NTRS)

Oegerle, William R.; Hill, John M.; Fisher, Richard R. (Technical Monitor)

2001-01-01

We present the final results of a spectroscopic study of a sample of cD galaxy clusters. The goal of this program has been to study the dynamics of the clusters, with emphasis on determining the nature and frequency of cD galaxies with peculiar velocities. Redshifts measured with the MX Spectrometer have been combined with those obtained from the literature to obtain typically 50 - 150 observed velocities in each of 25 galaxy clusters containing a central cD galaxy. We present a dynamical analysis of the final 11 clusters to be observed in this sample. All 25 clusters are analyzed in a uniform manner to test for the presence of substructure, and to determine peculiar velocities and their statistical significance for the central cD galaxy. These peculiar velocities were used to determine whether or not the central cD galaxy is at rest in the cluster potential well. We find that 30 - 50% of the clusters in our sample possess significant subclustering (depending on the cluster radius used in the analysis), which is in agreement with other studies of non-cD clusters. Hence, the dynamical state of cD clusters is not different than other present-day clusters. After careful study, four of the clusters appear to have a cD galaxy with a significant peculiar velocity. Dressler-Shectman tests indicate that three of these four clusters have statistically significant substructure within 1.5/h(sub 75) Mpc of the cluster center. The dispersion 75 of the cD peculiar velocities is 164 +41/-34 km/s around the mean cluster velocity. This represents a significant detection of peculiar cD velocities, but at a level which is far below the mean velocity dispersion for this sample of clusters. The picture that emerges is one in which cD galaxies are nearly at rest with respect to the cluster potential well, but have small residual velocities due to subcluster mergers.

Effectiveness of a self-management program for dual sensory impaired seniors in aged care settings: study protocol for a cluster randomized controlled trial.

PubMed

Roets-Merken, Lieve M; Graff, Maud J L; Zuidema, Sytse U; Hermsen, Pieter G J M; Teerenstra, Steven; Kempen, Gertrudis I J M; Vernooij-Dassen, Myrra J F J

2013-10-07

Five to 25 percent of residents in aged care settings have a combined hearing and visual sensory impairment. Usual care is generally restricted to single sensory impairment, neglecting the consequences of dual sensory impairment on social participation and autonomy. The aim of this study is to evaluate the effectiveness of a self-management program for seniors who acquired dual sensory impairment at old age. In a cluster randomized, single-blind controlled trial, with aged care settings as the unit of randomization, the effectiveness of a self-management program will be compared to usual care. A minimum of 14 and maximum of 20 settings will be randomized to either the intervention cluster or the control cluster, aiming to include a total of 132 seniors with dual sensory impairment. Each senior will be linked to a licensed practical nurse working at the setting. During a five to six month intervention period, nurses at the intervention clusters will be trained in a self-management program to support and empower seniors to use self-management strategies. In two separate diaries, nurses keep track of the interviews with the seniors and their reflections on their own learning process. Nurses of the control clusters offer care as usual. At senior level, the primary outcome is the social participation of the seniors measured using the Hearing Handicap Questionnaire and the Activity Card Sort, and secondary outcomes are mood, autonomy and quality of life. At nurse level, the outcome is job satisfaction. Effectiveness will be evaluated using linear mixed model analysis. The results of this study will provide evidence for the effectiveness of the Self-Management Program for seniors with dual sensory impairment living in aged care settings. The findings are expected to contribute to the knowledge on the program's potential to enhance social participation and autonomy of the seniors, as well as increasing the job satisfaction of the licensed practical nurses. Furthermore, an extensive process evaluation will take place which will offer insight in the quality and feasibility of the sampling and intervention process. If it is shown to be effective and feasible, this Self-Management Program could be widely disseminated. ClinicalTrials.gov, NCT01217502.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Web Program for Development of GUIs for Cluster Computers

NASA Technical Reports Server (NTRS)

Czikmantory, Akos; Cwik, Thomas; Klimeck, Gerhard; Hua, Hook; Oyafuso, Fabiano; Vinyard, Edward

2003-01-01

WIGLAF (a Web Interface Generator and Legacy Application Facade) is a computer program that provides a Web-based, distributed, graphical-user-interface (GUI) framework that can be adapted to any of a broad range of application programs, written in any programming language, that are executed remotely on any cluster computer system. WIGLAF enables the rapid development of a GUI for controlling and monitoring a specific application program running on the cluster and for transferring data to and from the application program. The only prerequisite for the execution of WIGLAF is a Web-browser program on a user's personal computer connected with the cluster via the Internet. WIGLAF has a client/server architecture: The server component is executed on the cluster system, where it controls the application program and serves data to the client component. The client component is an applet that runs in the Web browser. WIGLAF utilizes the Extensible Markup Language to hold all data associated with the application software, Java to enable platform-independent execution on the cluster system and the display of a GUI generator through the browser, and the Java Remote Method Invocation software package to provide simple, effective client/server networking.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

PubMed

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

PubMed Central

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

Analysis of genetic diversity in banana cultivars (Musa cvs.) from the South of Oman using AFLP markers and classification by phylogenetic, hierarchical clustering and principal component analyses*

PubMed Central

Opara, Umezuruike Linus; Jacobson, Dan; Al-Saady, Nadiya Abubakar

2010-01-01

Banana is an important crop grown in Oman and there is a dearth of information on its genetic diversity to assist in crop breeding and improvement programs. This study employed amplified fragment length polymorphism (AFLP) to investigate the genetic variation in local banana cultivars from the southern region of Oman. Using 12 primer combinations, a total of 1094 bands were scored, of which 1012 were polymorphic. Eighty-two unique markers were identified, which revealed the distinct separation of the seven cultivars. The results obtained show that AFLP can be used to differentiate the banana cultivars. Further classification by phylogenetic, hierarchical clustering and principal component analyses showed significant differences between the clusters found with molecular markers and those clusters created by previous studies using morphological analysis. Based on the analytical results, a consensus dendrogram of the banana cultivars is presented. PMID:20443211

Report to the administrator by the NASA Aerospace Safety Advisory Panel on the Skylab program. Volume 2: Program implementation and maturity. [systems management evaluation and design analysis

NASA Technical Reports Server (NTRS)

1973-01-01

Results of the design and manufacturing reviews on the maturity of the Skylab modules are presented along with results of investigations on the scope of the cluster risk assessment efforts. The technical management system and its capability to assess and resolve problems are studied.

Exploring relationships between Dairy Herd Improvement monitors of performance and the Transition Cow Index in Wisconsin dairy herds.

PubMed

Schultz, K K; Bennett, T B; Nordlund, K V; Döpfer, D; Cook, N B

2016-09-01

Transition cow management has been tracked via the Transition Cow Index (TCI; AgSource Cooperative Services, Verona, WI) since 2006. Transition Cow Index was developed to measure the difference between actual and predicted milk yield at first test day to evaluate the relative success of the transition period program. This project aimed to assess TCI in relation to all commonly used Dairy Herd Improvement (DHI) metrics available through AgSource Cooperative Services. Regression analysis was used to isolate variables that were relevant to TCI, and then principal components analysis and network analysis were used to determine the relative strength and relatedness among variables. Finally, cluster analysis was used to segregate herds based on similarity of relevant variables. The DHI data were obtained from 2,131 Wisconsin dairy herds with test-day mean ≥30 cows, which were tested ≥10 times throughout the 2014 calendar year. The original list of 940 DHI variables was reduced through expert-driven selection and regression analysis to 23 variables. The K-means cluster analysis produced 5 distinct clusters. Descriptive statistics were calculated for the 23 variables per cluster grouping. Using principal components analysis, cluster analysis, and network analysis, 4 parameters were isolated as most relevant to TCI; these were energy-corrected milk, 3 measures of intramammary infection (dry cow cure rate, linear somatic cell count score in primiparous cows, and new infection rate), peak ratio, and days in milk at peak milk production. These variables together with cow and newborn calf survival measures form a group of metrics that can be used to assist in the evaluation of overall transition period performance. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Open source clustering software.

PubMed

de Hoon, M J L; Imoto, S; Nolan, J; Miyano, S

2004-06-12

We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C. The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

High-throughput analysis of the satellitome illuminates satellite DNA evolution

NASA Astrophysics Data System (ADS)

Ruiz-Ruano, Francisco J.; López-León, María Dolores; Cabrero, Josefa; Camacho, Juan Pedro M.

2016-07-01

Satellite DNA (satDNA) is a major component yet the great unknown of eukaryote genomes and clearly underrepresented in genome sequencing projects. Here we show the high-throughput analysis of satellite DNA content in the migratory locust by means of the bioinformatic analysis of Illumina reads with the RepeatExplorer and RepeatMasker programs. This unveiled 62 satDNA families and we propose the term “satellitome” for the whole collection of different satDNA families in a genome. The finding that satDNAs were present in many contigs of the migratory locust draft genome indicates that they show many genomic locations invisible by fluorescent in situ hybridization (FISH). The cytological pattern of five satellites showing common descent (belonging to the SF3 superfamily) suggests that non-clustered satDNAs can become into clustered through local amplification at any of the many genomic loci resulting from previous dissemination of short satDNA arrays. The fact that all kinds of satDNA (micro- mini- and satellites) can show the non-clustered and clustered states suggests that all these elements are mostly similar, except for repeat length. Finally, the presence of VNTRs in bacteria, showing similar properties to non-clustered satDNAs in eukaryotes, suggests that this kind of tandem repeats show common properties in all living beings.

Parallel Wavefront Analysis for a 4D Interferometer

NASA Technical Reports Server (NTRS)

Rao, Shanti R.

2011-01-01

This software provides a programming interface for automating data collection with a PhaseCam interferometer from 4D Technology, and distributing the image-processing algorithm across a cluster of general-purpose computers. Multiple instances of 4Sight (4D Technology s proprietary software) run on a networked cluster of computers. Each connects to a single server (the controller) and waits for instructions. The controller directs the interferometer to several images, then assigns each image to a different computer for processing. When the image processing is finished, the server directs one of the computers to collate and combine the processed images, saving the resulting measurement in a file on a disk. The available software captures approximately 100 images and analyzes them immediately. This software separates the capture and analysis processes, so that analysis can be done at a different time and faster by running the algorithm in parallel across several processors. The PhaseCam family of interferometers can measure an optical system in milliseconds, but it takes many seconds to process the data so that it is usable. In characterizing an adaptive optics system, like the next generation of astronomical observatories, thousands of measurements are required, and the processing time quickly becomes excessive. A programming interface distributes data processing for a PhaseCam interferometer across a Windows computing cluster. A scriptable controller program coordinates data acquisition from the interferometer, storage on networked hard disks, and parallel processing. Idle time of the interferometer is minimized. This architecture is implemented in Python and JavaScript, and may be altered to fit a customer s needs.

Accident patterns for construction-related workers: a cluster analysis

NASA Astrophysics Data System (ADS)

Liao, Chia-Wen; Tyan, Yaw-Yauan

2012-01-01

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Accident patterns for construction-related workers: a cluster analysis

NASA Astrophysics Data System (ADS)

Liao, Chia-Wen; Tyan, Yaw-Yauan

2011-12-01

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Color-magnitude diagrams for six metal-rich, low-latitude globular clusters

NASA Technical Reports Server (NTRS)

Armandroff, Taft E.

1988-01-01

Colors and magnitudes for stars on CCD frames for six metal-rich, low-latitude, previously unstudied globular clusters and one well-studied, metal-rich cluster (47 Tuc) have been derived and color-magnitude diagrams have been constructed. The photometry for stars in 47 Tuc are in good agreement with previous studies, while the V magnitudes of the horizontal-branch stars in the six program clusters do not agree with estimates based on secondary methods. The distances to these clusters are different from prior estimates. Redding values are derived for each program cluster. The horizontal branches of the program clusters all appear to lie entirely redwards of the red edge of the instability strip, as is normal for their metallicities.

Block clustering based on difference of convex functions (DC) programming and DC algorithms.

PubMed

Le, Hoai Minh; Le Thi, Hoai An; Dinh, Tao Pham; Huynh, Van Ngai

2013-10-01

We investigate difference of convex functions (DC) programming and the DC algorithm (DCA) to solve the block clustering problem in the continuous framework, which traditionally requires solving a hard combinatorial optimization problem. DC reformulation techniques and exact penalty in DC programming are developed to build an appropriate equivalent DC program of the block clustering problem. They lead to an elegant and explicit DCA scheme for the resulting DC program. Computational experiments show the robustness and efficiency of the proposed algorithm and its superiority over standard algorithms such as two-mode K-means, two-mode fuzzy clustering, and block classification EM.

Final Report of the Evaluation of the 1969-1970 Benjamin Franklin Cluster Program: Programs and Patterns for Disadvantaged High School Students. ESEA Title I.

ERIC Educational Resources Information Center

Hoffman, Louis J.

The Cluster Program at Benjamin Franklin High School, funded under Title I of the 1965 Elementary Secondary Education Act, is designed to be a school within a school in which 249 ninth grade students attend classes in two separate clusters. Each cluster is formulated such that all students receive instruction from five teachers in classes whose…

Room-temperature isolation of V(benzene)2 sandwich clusters via soft-landing into n-alkanethiol self-assembled monolayers.

PubMed

Nagaoka, Shuhei; Matsumoto, Takeshi; Okada, Eiji; Mitsui, Masaaki; Nakajima, Atsushi

2006-08-17

The adsorption state and thermal stability of V(benzene)2 sandwich clusters soft-landed onto a self-assembled monolayer of different chain-length n-alkanethiols (Cn-SAM, n = 8, 12, 16, 18, and 22) were studied by means of infrared reflection absorption spectroscopy (IRAS) and temperature-programmed desorption (TPD). The IRAS measurement confirmed that V(benzene)2 clusters are molecularly adsorbed and maintain a sandwich structure on all of the SAM substrates. In addition, the clusters supported on the SAM substrates are oriented with their molecular axes tilted 70-80 degrees off the surface normal. An Arrhenius analysis of the TPD spectra reveals that the activation energy for the desorption of the supported clusters increases linearly with the chain length of the SAMs. For the longest chain C22-SAM, the activation energy reaches approximately 150 kJ/mol, and the thermal desorption of the supported clusters can be considerably suppressed near room temperature. The clear chain-length-dependent thermal stability of the supported clusters observed here can be explained well in terms of the cluster penetration into the SAM matrixes.

Mapping of terrain by computer clustering techniques using multispectral scanner data and using color aerial film

NASA Technical Reports Server (NTRS)

Smedes, H. W.; Linnerud, H. J.; Woolaver, L. B.; Su, M. Y.; Jayroe, R. R.

1972-01-01

Two clustering techniques were used for terrain mapping by computer of test sites in Yellowstone National Park. One test was made with multispectral scanner data using a composite technique which consists of (1) a strictly sequential statistical clustering which is a sequential variance analysis, and (2) a generalized K-means clustering. In this composite technique, the output of (1) is a first approximation of the cluster centers. This is the input to (2) which consists of steps to improve the determination of cluster centers by iterative procedures. Another test was made using the three emulsion layers of color-infrared aerial film as a three-band spectrometer. Relative film densities were analyzed using a simple clustering technique in three-color space. Important advantages of the clustering technique over conventional supervised computer programs are (1) human intervention, preparation time, and manipulation of data are reduced, (2) the computer map, gives unbiased indication of where best to select the reference ground control data, (3) use of easy to obtain inexpensive film, and (4) the geometric distortions can be easily rectified by simple standard photogrammetric techniques.

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

NASA Astrophysics Data System (ADS)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and Diamantaras, K.: 'Programming and architecture of parallel processing systems', 1st Edition, Eds. Kleidarithmos, 2011 [4] NVIDIA.: 'NVidia CUDA C Programming Guide', version 5.0, NVidia (reference book) [5] Konstantaras, A.: 'Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc', IEEE Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6 (4), pp. 1857-1863, 2013 [6] Konstantaras, A. Varley, M.R.,. Valianatos, F., Collins, G. and Holifield, P.: 'Recognition of electric earthquake precursors using neuro-fuzzy models: methodology and simulation results', Proc. IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 2002, pp 303-308, 2002 [7] Konstantaras, A., Katsifarakis, E., Maravelakis, E., Skounakis, E., Kokkinos, E. and Karapidakis, E.: 'Intelligent Spatial-Clustering of Seismicity in the Vicinity of the Hellenic Seismic Arc', Earth Science Research, vol. 1 (2), pp. 1-10, 2012 [8] Georgoulas, G., Konstantaras, A., Katsifarakis, E., Stylios, C.D., Maravelakis, E. and Vachtsevanos, G.: '"Seismic-Mass" Density-based Algorithm for Spatio-Temporal Clustering', Expert Systems with Applications, vol. 40 (10), pp. 4183-4189, 2013 [9] Konstantaras, A. J.: 'Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters', Earth Science Informatics, 2015 (In Press, see: www.scopus.com) [10] Drakatos, G. and Latoussakis, J.: 'A catalog of aftershock sequences in Greece (1971-1997): Their spatial and temporal characteristics', Journal of Seismology, vol. 5, pp. 137-145, 2001

THE CLUSTER LENSING AND SUPERNOVA SURVEY WITH HUBBLE (CLASH): STRONG-LENSING ANALYSIS OF A383 FROM 16-BAND HST/WFC3/ACS IMAGING

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

Zitrin, A.; Broadhurst, T.; Coe, D.

2011-12-01

We examine the inner mass distribution of the relaxed galaxy cluster A383 (z = 0.189), in deep 16 band Hubble Space Telescope/ACS+WFC3 imaging taken as part of the Cluster Lensing And Supernova survey with Hubble (CLASH) multi-cycle treasury program. Our program is designed to study the dark matter distribution in 25 massive clusters, and balances depth with a wide wavelength coverage, 2000-16000 A, to better identify lensed systems and generate precise photometric redshifts. This photometric information together with the predictive strength of our strong-lensing analysis method identifies 13 new multiply lensed images and candidates, so that a total of 27more » multiple images of nine systems are used to tightly constrain the inner mass profile gradient, dlog {Sigma}/dlog r {approx_equal} -0.6 {+-} 0.1 (r < 160 kpc). We find consistency with the standard distance-redshift relation for the full range spanned by the lensed images, 1.01 < z < 6.03, with the higher-redshift sources deflected through larger angles as expected. The inner mass profile derived here is consistent with the results of our independent weak-lensing analysis of wide-field Subaru images, with good agreement in the region of overlap ({approx}0.7-1 arcmin). Combining weak and strong lensing, the overall mass profile is well fitted by a Navarro-Frenk-White profile with M{sub vir} = (5.37{sup +0.70}{sub -0.63} {+-} 0.26) Multiplication-Sign 10{sup 14} M{sub Sun} h{sup -1} and a relatively high concentration, c{sub vir} = 8.77{sup +0.44}{sub -0.42} {+-} 0.23, which lies above the standard c-M relation similar to other well-studied clusters. The critical radius of A383 is modest by the standards of other lensing clusters, r{sub E} {approx_equal} 16 {+-} 2'' (for z{sub s} = 2.55), so the relatively large number of lensed images uncovered here with precise photometric redshifts validates our imaging strategy for the CLASH survey. In total we aim to provide similarly high-quality lensing data for 25 clusters, 20 of which are X-ray-selected relaxed clusters, enabling a precise determination of the representative mass profile free from lensing bias.« less

Untangling Magmatic Processes and Hydrothermal Alteration of in situ Superfast Spreading Ocean Crust at ODP/IODP Site 1256 with Fuzzy c-means Cluster Analysis of Rock Magnetic Properties

NASA Astrophysics Data System (ADS)

Dekkers, M. J.; Heslop, D.; Herrero-Bervera, E.; Acton, G.; Krasa, D.

2014-12-01

Ocean Drilling Program (ODP)/Integrated ODP (IODP) Hole 1256D (6.44.1' N, 91.56.1' W) on the Cocos Plate occurs in 15.2 Ma oceanic crust generated by superfast seafloor spreading. Presently, it is the only drill hole that has sampled all three oceanic crust layers in a tectonically undisturbed setting. Here we interpret down-hole trends in several rock-magnetic parameters with fuzzy c-means cluster analysis, a multivariate statistical technique. The parameters include the magnetization ratio, the coercivity ratio, the coercive force, the low-field susceptibility, and the Curie temperature. By their combined, multivariate, analysis the effects of magmatic and hydrothermal processes can be evaluated. The optimal number of clusters - a key point in the analysis because there is no a priori information on this - was determined through a combination of approaches: by calculation of several cluster validity indices, by testing for coherent cluster distributions on non-linear-map plots, and importantly by testing for stability of the cluster solution from all possible starting points. Here, we consider a solution robust if the cluster allocation is independent of the starting configuration. The five-cluster solution appeared to be robust. Three clusters are distinguished in the extrusive segment of the Hole that express increasing hydrothermal alteration of the lavas. The sheeted dike and gabbro portions are characterized by two clusters, both with higher coercivities than in lava samples. Extensive alteration, however, can obliterate magnetic property differences between lavas, dikes, and gabbros. The imprint of thermochemical alteration on the iron-titanium oxides is only partially related to the porosity of the rocks. All clusters display rock magnetic characteristics in line with a stable NRM. This implies that the entire sampled sequence of ocean crust can contribute to marine magnetic anomalies. Determination of the absolute paleointensity with thermal techniques is not straightforward because of the propensity of oxyexsolution during laboratory heating and/or the presence of intergrowths. The upper part of the extrusive sequence, the granoblastic portion of the dikes, and moderately altered gabbros may contain a comparatively uncontaminated thermoremanent magnetization.

The Outer Limits of Galaxy Clusters: Observations to the Virial Radius with Suzaku, XMM,and Chandra

NASA Technical Reports Server (NTRS)

Miller, Eric D.; Bautz, Marshall; George, Jithin; Mushotzky, Richard; Davis, David; Henry, J. Patrick

2012-01-01

The outskirts of galaxy clusters, near the virial radius, remain relatively unexplored territory and yet are vital to our understanding of cluster growth, structure, and mass. In this presentation, we show the first results from a program to constrain the sate of the outer intra-cluster medium (ICM) in a large sample of galaxy clusters, exploiting the strengths of three complementary X-ray observatories: Suzaku (low, stable background), XMM-Newton (high sensitivity),and Chandra (good spatial resolution). By carefully combining observations from the cluster core to beyond r200, we are able to identify and reduce systematic uncertainties that would impede our spatial and spectral analysis using a single telescope. Our sample comprises nine clusters at z is approximately 0.1-0.2 fully covered in azimuth to beyond r200, and our analysis indicates that the ICM is not in hydrostatic equilibrium in the cluster outskirts, where we see clear azimuthal variations in temperature and surface brightness. In one of the clusters, we are able to measure the diffuse X-ray emission well beyond r200, and we find that the entropy profile and the gas fraction are consistent with expectations from theory and numerical simulations. These results stand in contrast to recent studies which point to gas clumping in the outskirts; the extent to which differences of cluster environment or instrumental effects factor in this difference remains unclear. From a broader perspective, this project will produce a sizeable fiducial data set for detailed comparison with high-resolution numerical simulations.

GibbsCluster: unsupervised clustering and alignment of peptide sequences.

PubMed

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-07-03

Receptor interactions with short linear peptide fragments (ligands) are at the base of many biological signaling processes. Conserved and information-rich amino acid patterns, commonly called sequence motifs, shape and regulate these interactions. Because of the properties of a receptor-ligand system or of the assay used to interrogate it, experimental data often contain multiple sequence motifs. GibbsCluster is a powerful tool for unsupervised motif discovery because it can simultaneously cluster and align peptide data. The GibbsCluster 2.0 presented here is an improved version incorporating insertion and deletions accounting for variations in motif length in the peptide input. In basic terms, the program takes as input a set of peptide sequences and clusters them into meaningful groups. It returns the optimal number of clusters it identified, together with the sequence alignment and sequence motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Farmers' Market Use Patterns Among Supplemental Nutrition Assistance Program Recipients With High Access to Farmers' Markets.

PubMed

Freedman, Darcy A; Flocke, Susan; Shon, En-Jung; Matlack, Kristen; Trapl, Erika; Ohri-Vachaspati, Punam; Osborne, Amanda; Borawski, Elaine

2017-05-01

Evaluate farmers' market (FM) use patterns among Supplemental Nutrition Assistance Program (SNAP) recipients. Cross-sectional survey administered June to August, 2015. Cleveland and East Cleveland, OH. A total of 304 SNAP recipients with children. Participants lived within 1 mile of 1 of 17 FMs. Most were African American (82.6%) and female (88.1%), and had received SNAP for ≥5 years (65.8%). Patterns of FM shopping, awareness of FM near home and of healthy food incentive program, use of SNAP to buy fruits and vegetables and to buy other foods at FMs, receipt of healthy food incentive program. Two-stage cluster analysis to identify segments with similar FM use patterns. Bivariate statistics including chi-square and ANOVA to evaluate main outcomes, with significance at P ≤ .05. A total of 42% reported FM use in the past year. Current FM shoppers (n = 129) were segmented into 4 clusters: single market, public market, multiple market, and high frequency. Clusters differed significantly in awareness of FM near home and the incentive program, use of SNAP to buy fruit and vegetables at FMs, and receipt of incentive. Findings highlight distinct types of FM use and had implications for tailoring outreach to maximize first time and repeat use of FMs among SNAP recipients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Cellular fatty acid analysis as a potential tool for predicting mosquitocidal activity of Bacillus sphaericus strains.

PubMed Central

Frachon, E; Hamon, S; Nicolas, L; de Barjac, H

1991-01-01

Gas-liquid chromatography of fatty acid methyl esters and numerical analysis were carried out with 114 Bacillus sphaericus strains. Since only two clusters harbored mosquitocidal strains, this technique could be developed in screening programs to limit bioassays on mosquito larvae. It also allows differentiation of highly homologous strains. PMID:1781697

A Massive Galaxy Cluster At z=1.45 From The XMM Cluster Survey: Discovery, Confirmation And Implications For The L-T Relation And Cosmology

NASA Astrophysics Data System (ADS)

Sabirli, Kivanc; Romer, A. K.; Davidson, M.; Stanford, S. A.; Viana, P. T.; Hilton, M.; Collins, C. A.; Kay, S. T.; Liddle, A. R.; Mann, R. G.; Miller, C. J.; Nichol, R. C.; West, M. J.; Conselice, C. J.; Spinrad, H.; Stern, D.; XCS Collaboration

2006-06-01

We report the discovery of the hottest cluster known at z > 1. It was identified as an extended X-ray source in the XMM Cluster Survey (XCS, Romer et al., 2001) and optical spectroscopy shows that 6 galaxies within a 60 arcsec diameter region lie at z = 1.45 ± 0.01. Hence its redshift is the highest currently known for a spectroscopically-confirmed cluster. Analysis of the X-ray spectra yields kT = 7.9+2.8-1.8 keV (90% confidence) and suggests that it is relatively massive for such a high redshift cluster.We acknowledge financial support from NASA grant NAG-11634 (AKR, RCN, KS, MD, PTPV), The Royal Astronomical Society's Hosie Request (MD, KS), PPARC (ARL, STK, RGM), the NASA XMM program (KS), the Institute of Astronomy at the University of Edinburgh (MD), Liverpool John Moores University (MH), Carnegie Mellon University (KS, AKR), and NSF grant AST-0205960 (MJW).

Evaluation of a self-management patient education program for patients with fibromyalgia syndrome: study protocol of a cluster randomized controlled trial.

PubMed

Musekamp, Gunda; Gerlich, Christian; Ehlebracht-König, Inge; Faller, Hermann; Reusch, Andrea

2016-02-03

Fibromyalgia syndrome (FMS) is a complex chronic condition that makes high demands on patients' self-management skills. Thus, patient education is considered an important component of multimodal therapy, although evidence regarding its effectiveness is scarce. The main objective of this study is to assess the effectiveness of an advanced self-management patient education program for patients with FMS as compared to usual care in the context of inpatient rehabilitation. We conducted a multicenter cluster randomized controlled trial in 3 rehabilitation clinics. Clusters are groups of patients with FMS consecutively recruited within one week after admission. Patients of the intervention group receive the advanced multidisciplinary self-management patient education program (considering new knowledge on FMS, with a focus on transfer into everyday life), whereas patients in the control group receive standard patient education programs including information on FMS and coping with pain. A total of 566 patients are assessed at admission, at discharge and after 6 and 12 months, using patient reported questionnaires. Primary outcomes are patients' disease- and treatment-specific knowledge at discharge and self-management skills after 6 months. Secondary outcomes include satisfaction, attitudes and coping competences, health-promoting behavior, psychological distress, health impairment and participation. Treatment effects between groups are evaluated using multilevel regression analysis adjusting for baseline values. The study evaluates the effectiveness of a self-management patient education program for patients with FMS in the context of inpatient rehabilitation in a cluster randomized trial. Study results will show whether self-management patient education is beneficial for this group of patients. German Clinical Trials Register, DRKS00008782 , Registered 8 July 2015.

Patient Stratification Using Electronic Health Records from a Chronic Disease Management Program.

PubMed

Chen, Robert; Sun, Jimeng; Dittus, Robert S; Fabbri, Daniel; Kirby, Jacqueline; Laffer, Cheryl L; McNaughton, Candace D; Malin, Bradley

2016-01-04

The goal of this study is to devise a machine learning framework to assist care coordination programs in prognostic stratification to design and deliver personalized care plans and to allocate financial and medical resources effectively. This study is based on a de-identified cohort of 2,521 hypertension patients from a chronic care coordination program at the Vanderbilt University Medical Center. Patients were modeled as vectors of features derived from electronic health records (EHRs) over a six-year period. We applied a stepwise regression to identify risk factors associated with a decrease in mean arterial pressure of at least 2 mmHg after program enrollment. The resulting features were subsequently validated via a logistic regression classifier. Finally, risk factors were applied to group the patients through model-based clustering. We identified a set of predictive features that consisted of a mix of demographic, medication, and diagnostic concepts. Logistic regression over these features yielded an area under the ROC curve (AUC) of 0.71 (95% CI: [0.67, 0.76]). Based on these features, four clinically meaningful groups are identified through clustering - two of which represented patients with more severe disease profiles, while the remaining represented patients with mild disease profiles. Patients with hypertension can exhibit significant variation in their blood pressure control status and responsiveness to therapy. Yet this work shows that a clustering analysis can generate more homogeneous patient groups, which may aid clinicians in designing and implementing customized care programs. The study shows that predictive modeling and clustering using EHR data can be beneficial for providing a systematic, generalized approach for care providers to tailor their management approach based upon patient-level factors.

Motivational Interviewing for Workers with Disabling Musculoskeletal Disorders: Results of a Cluster Randomized Control Trial.

PubMed

Park, Joanne; Esmail, Shaniff; Rayani, Fahreen; Norris, Colleen M; Gross, Douglas P

2018-06-01

Purpose Although functional restoration programs appear effective in assisting injured workers to return-to-work (RTW) after a work related musculoskeletal (MSK) disorder, the addition of Motivational Interviewing (MI) to these programs may result in higher RTW. Methods We conducted a cluster randomized controlled trial with claimants attending an occupational rehabilitation facility from November 17, 2014 to June 30, 2015. Six clinicians provided MI in addition to the standard functional restoration program and formed an intervention group. Six clinicians continued to provide the standard functional restoration program based on graded activity, therapeutic exercise, and workplace accommodations. Independent t tests and chi square analysis were used to compare groups. Multivariable logistic regression was used to obtain the odds ratio of claimants' confirmed RTW status at time of program discharge. Results 728 workers' compensation claimants with MSK disorders were entered into 1 of 12 therapist clusters (MI group = 367, control group = 361). Claimants were predominantly employed (72.7%), males (63.2%), with moderate levels of pain and disability (mean pain VAS = 5.0/10 and mean Pain Disability Index = 48/70). Claimants were stratified based on job attachment status. The proportion of successful RTW at program discharge was 12.1% higher for unemployed workers in the intervention group (intervention group 21.6 vs. 9.5% in control, p = 0.03) and 3.0% higher for job attached workers compared to the control group (intervention group 97.1 vs. 94.1% in control, p = 0.10). Adherence to MI was mixed, but RTW was significantly higher among MI-adherent clinicians. The odds ratio for unemployed claimants was 2.64 (0.69-10.14) and 2.50 (0.68-9.14) for employed claimants after adjusting for age, sex, pain intensity, perceived disability, and therapist cluster. Conclusion MI in addition to routine functional restoration is more effective than routine functional restoration program alone in improving RTW among workers with disabling MSK disorders.

Effectiveness of a self-management program for dual sensory impaired seniors in aged care settings: study protocol for a cluster randomized controlled trial

PubMed Central

2013-01-01

Background Five to 25 percent of residents in aged care settings have a combined hearing and visual sensory impairment. Usual care is generally restricted to single sensory impairment, neglecting the consequences of dual sensory impairment on social participation and autonomy. The aim of this study is to evaluate the effectiveness of a self-management program for seniors who acquired dual sensory impairment at old age. Methods/Design In a cluster randomized, single-blind controlled trial, with aged care settings as the unit of randomization, the effectiveness of a self-management program will be compared to usual care. A minimum of 14 and maximum of 20 settings will be randomized to either the intervention cluster or the control cluster, aiming to include a total of 132 seniors with dual sensory impairment. Each senior will be linked to a licensed practical nurse working at the setting. During a five to six month intervention period, nurses at the intervention clusters will be trained in a self-management program to support and empower seniors to use self-management strategies. In two separate diaries, nurses keep track of the interviews with the seniors and their reflections on their own learning process. Nurses of the control clusters offer care as usual. At senior level, the primary outcome is the social participation of the seniors measured using the Hearing Handicap Questionnaire and the Activity Card Sort, and secondary outcomes are mood, autonomy and quality of life. At nurse level, the outcome is job satisfaction. Effectiveness will be evaluated using linear mixed model analysis. Discussion The results of this study will provide evidence for the effectiveness of the Self-Management Program for seniors with dual sensory impairment living in aged care settings. The findings are expected to contribute to the knowledge on the program’s potential to enhance social participation and autonomy of the seniors, as well as increasing the job satisfaction of the licensed practical nurses. Furthermore, an extensive process evaluation will take place which will offer insight in the quality and feasibility of the sampling and intervention process. If it is shown to be effective and feasible, this Self-Management Program could be widely disseminated. Clinical trials registration ClinicalTrials.gov, NCT01217502. PMID:24099315

Systematic Identification of LAEs for Visible Exploration and Reionization Research Using Subaru HSC (SILVERRUSH). I. Program strategy and clustering properties of ˜2000 Lyα emitters at z = 6-7 over the 0.3-0.5 Gpc2 survey area

NASA Astrophysics Data System (ADS)

Ouchi, Masami; Harikane, Yuichi; Shibuya, Takatoshi; Shimasaku, Kazuhiro; Taniguchi, Yoshiaki; Konno, Akira; Kobayashi, Masakazu; Kajisawa, Masaru; Nagao, Tohru; Ono, Yoshiaki; Inoue, Akio K.; Umemura, Masayuki; Mori, Masao; Hasegawa, Kenji; Higuchi, Ryo; Komiyama, Yutaka; Matsuda, Yuichi; Nakajima, Kimihiko; Saito, Tomoki; Wang, Shiang-Yu

2018-01-01

We present the SILVERRUSH program strategy and clustering properties investigated with ˜2000 Lyα emitters (LAEs) at z = 5.7 and 6.6 found in the early data of the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey exploiting the carefully designed narrow-band filters. We derive angular correlation functions with the unprecedentedly large samples of LAEs at z = 6-7 over the large total area of 14-21 deg2 corresponding to 0.3-0.5 comoving Gpc2. We obtain the average large-scale bias values of bavg = 4.1 ± 0.2 (4.5 ± 0.6) at z = 5.7 (z = 6.6) for ≳ L* LAEs, indicating a weak evolution of LAE clustering from z = 5.7 to 6.6. We compare the LAE clustering results with two independent theoretical models that suggest an increase of an LAE clustering signal by the patchy ionized bubbles at the epoch of reionization (EoR), and estimate the neutral hydrogen fraction to be x_{H I}=0.15^{+0.15}_{-0.15} at z = 6.6. Based on the halo occupation distribution models, we find that the ≳ L* LAEs are hosted by dark-matter halos with an average mass of log (< M_h > /M_⊙ ) =11.1^{+0.2}_{-0.4} (10.8^{+0.3}_{-0.5}) at z = 5.7 (6.6) with a Lyα duty cycle of 1% or less, where the results of z = 6.6 LAEs may be slightly biased, due to the increase of the clustering signal at the EoR. Our clustering analysis reveals the low-mass nature of ≳ L* LAEs at z = 6-7, and that these LAEs probably evolve into massive super-L* galaxies in the present-day universe.

Clustering of health-related behaviors, health outcomes and demographics in Dutch adolescents: a cross-sectional study.

PubMed

Busch, Vincent; Van Stel, Henk F; Schrijvers, Augustinus J P; de Leeuw, Johannes R J

2013-12-04

Recent studies show several health-related behaviors to cluster in adolescents. This has important implications for public health. Interrelated behaviors have been shown to be most effectively targeted by multimodal interventions addressing wider-ranging improvements in lifestyle instead of via separate interventions targeting individual behaviors. However, few previous studies have taken into account a broad, multi-disciplinary range of health-related behaviors and connected these behavioral patterns to health-related outcomes. This paper presents an analysis of the clustering of a broad range of health-related behaviors with relevant demographic factors and several health-related outcomes in adolescents. Self-report questionnaire data were collected from a sample of 2,690 Dutch high school adolescents. Behavioral patterns were deducted via Principal Components Analysis. Subsequently a Two-Step Cluster Analysis was used to identify groups of adolescents with similar behavioral patterns and health-related outcomes. Four distinct behavioral patterns describe the analyzed individual behaviors: 1- risk-prone behavior, 2- bully behavior, 3- problematic screen time use, and 4- sedentary behavior. Subsequent cluster analysis identified four clusters of adolescents. Multi-problem behavior was associated with problematic physical and psychosocial health outcomes, as opposed to those exerting relatively few unhealthy behaviors. These associations were relatively independent of demographics such as ethnicity, gender and socio-economic status. The results show that health-related behaviors tend to cluster, indicating that specific behavioral patterns underlie individual health behaviors. In addition, specific patterns of health-related behaviors were associated with specific health outcomes and demographic factors. In general, unhealthy behavior on account of multiple health-related behaviors was associated with both poor psychosocial and physical health. These findings have significant meaning for future public health programs, which should be more tailored with use of such knowledge on behavioral clustering via e.g. Transfer Learning.

Clustering of health-related behaviors, health outcomes and demographics in Dutch adolescents: a cross-sectional study

PubMed Central

2013-01-01

Background Recent studies show several health-related behaviors to cluster in adolescents. This has important implications for public health. Interrelated behaviors have been shown to be most effectively targeted by multimodal interventions addressing wider-ranging improvements in lifestyle instead of via separate interventions targeting individual behaviors. However, few previous studies have taken into account a broad, multi-disciplinary range of health-related behaviors and connected these behavioral patterns to health-related outcomes. This paper presents an analysis of the clustering of a broad range of health-related behaviors with relevant demographic factors and several health-related outcomes in adolescents. Methods Self-report questionnaire data were collected from a sample of 2,690 Dutch high school adolescents. Behavioral patterns were deducted via Principal Components Analysis. Subsequently a Two-Step Cluster Analysis was used to identify groups of adolescents with similar behavioral patterns and health-related outcomes. Results Four distinct behavioral patterns describe the analyzed individual behaviors: 1- risk-prone behavior, 2- bully behavior, 3- problematic screen time use, and 4- sedentary behavior. Subsequent cluster analysis identified four clusters of adolescents. Multi-problem behavior was associated with problematic physical and psychosocial health outcomes, as opposed to those exerting relatively few unhealthy behaviors. These associations were relatively independent of demographics such as ethnicity, gender and socio-economic status. Conclusions The results show that health-related behaviors tend to cluster, indicating that specific behavioral patterns underlie individual health behaviors. In addition, specific patterns of health-related behaviors were associated with specific health outcomes and demographic factors. In general, unhealthy behavior on account of multiple health-related behaviors was associated with both poor psychosocial and physical health. These findings have significant meaning for future public health programs, which should be more tailored with use of such knowledge on behavioral clustering via e.g. Transfer Learning. PMID:24305509

Development of a gene expression database and related analysis programs for evaluation of anticancer compounds.

PubMed

Ushijima, Masaru; Mashima, Tetsuo; Tomida, Akihiro; Dan, Shingo; Saito, Sakae; Furuno, Aki; Tsukahara, Satomi; Seimiya, Hiroyuki; Yamori, Takao; Matsuura, Masaaki

2013-03-01

Genome-wide transcriptional expression analysis is a powerful strategy for characterizing the biological activity of anticancer compounds. It is often instructive to identify gene sets involved in the activity of a given drug compound for comparison with different compounds. Currently, however, there is no comprehensive gene expression database and related application system that is; (i) specialized in anticancer agents; (ii) easy to use; and (iii) open to the public. To develop a public gene expression database of antitumor agents, we first examined gene expression profiles in human cancer cells after exposure to 35 compounds including 25 clinically used anticancer agents. Gene signatures were extracted that were classified as upregulated or downregulated after exposure to the drug. Hierarchical clustering showed that drugs with similar mechanisms of action, such as genotoxic drugs, were clustered. Connectivity map analysis further revealed that our gene signature data reflected modes of action of the respective agents. Together with the database, we developed analysis programs that calculate scores for ranking changes in gene expression and for searching statistically significant pathways from the Kyoto Encyclopedia of Genes and Genomes database in order to analyze the datasets more easily. Our database and the analysis programs are available online at our website (http://scads.jfcr.or.jp/db/cs/). Using these systems, we successfully showed that proteasome inhibitors are selectively classified as endoplasmic reticulum stress inducers and induce atypical endoplasmic reticulum stress. Thus, our public access database and related analysis programs constitute a set of efficient tools to evaluate the mode of action of novel compounds and identify promising anticancer lead compounds. © 2012 Japanese Cancer Association.

Differential segmentation responses to an alcohol social marketing program.

PubMed

Dietrich, Timo; Rundle-Thiele, Sharyn; Schuster, Lisa; Drennan, Judy; Russell-Bennett, Rebekah; Leo, Cheryl; Gullo, Matthew J; Connor, Jason P

2015-10-01

This study seeks to establish whether meaningful subgroups exist within a 14-16 year old adolescent population and if these segments respond differently to the Game On: Know Alcohol (GOKA) intervention, a school-based alcohol social marketing program. This study is part of a larger cluster randomized controlled evaluation of the GOKA program implemented in 14 schools in 2013/2014. TwoStep cluster analysis was conducted to segment 2,114 high school adolescents (14-16 years old) on the basis of 22 demographic, behavioral, and psychographic variables. Program effects on knowledge, attitudes, behavioral intentions, social norms, alcohol expectancies, and drinking refusal self-efficacy of identified segments were subsequently examined. Three segments were identified: (1) Abstainers, (2) Bingers, and (3) Moderate Drinkers. Program effects varied significantly across segments. The strongest positive change effects post-participation were observed for Bingers, while mixed effects were evident for Moderate Drinkers and Abstainers. These findings provide preliminary empirical evidence supporting the application of social marketing segmentation in alcohol education programs. Development of targeted programs that meet the unique needs of each of the three identified segments will extend the social marketing footprint in alcohol education. Copyright © 2015 Elsevier Ltd. All rights reserved.

Population Structure With Localized Haplotype Clusters

PubMed Central

Browning, Sharon R.; Weir, Bruce S.

2010-01-01

We propose a multilocus version of FST and a measure of haplotype diversity using localized haplotype clusters. Specifically, we use haplotype clusters identified with BEAGLE, which is a program implementing a hidden Markov model for localized haplotype clustering and performing several functions including inference of haplotype phase. We apply this methodology to HapMap phase 3 data. With this haplotype-cluster approach, African populations have highest diversity and lowest divergence from the ancestral population, East Asian populations have lowest diversity and highest divergence, and other populations (European, Indian, and Mexican) have intermediate levels of diversity and divergence. These relationships accord with expectation based on other studies and accepted models of human history. In contrast, the population-specific FST estimates obtained directly from single-nucleotide polymorphisms (SNPs) do not reflect such expected relationships. We show that ascertainment bias of SNPs has less impact on the proposed haplotype-cluster-based FST than on the SNP-based version, which provides a potential explanation for these results. Thus, these new measures of FST and haplotype-cluster diversity provide an important new tool for population genetic analysis of high-density SNP data. PMID:20457877

Template growth of Au, Ni and Ni–Au nanoclusters on hexagonal boron nitride/Rh(111): a combined STM, TPD and AES study

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

Wu, Fanglue; Huang, Dali; Yue, Yuan

In this study, the template growth of Au, Ni, and Ni–Au bimetallic nanoclusters on hexagonal boron nitride/Rh(111), i.e. h-BN/Rh(111), was investigated via scanning tunneling microscopy (STM), temperature programmed-desorption (TPD), and Auger electron spectroscopy (AES). STM study shows that template growth of Au clusters on h-BN/Rh(111) forms mainly well-dispersed monolayer clusters. In contrast, Ni forms large multilayer clusters showing a relatively high diffusivity on h-BN/Rh(111) substrate. Ni–Au bimetallic clusters are effectively formed first by Au deposition followed by Ni deposition, with the Au clusters functioning as nucleation sites for the subsequently deposited Ni. Further structural analysis was carried out via TPDmore » and AES. The resulting TPD and AES data show the surface composition and charge transfer between Au and Ni of the bimetallic clusters. These results suggest that the h-BN/Rh(111) substrate represents a unique candidate for supporting Ni–Au bimetallic clusters in further catalytic reactions.« less

Template growth of Au, Ni and Ni–Au nanoclusters on hexagonal boron nitride/Rh(111): a combined STM, TPD and AES study

DOE PAGES

Wu, Fanglue; Huang, Dali; Yue, Yuan; ...

2017-09-12

In this study, the template growth of Au, Ni, and Ni–Au bimetallic nanoclusters on hexagonal boron nitride/Rh(111), i.e. h-BN/Rh(111), was investigated via scanning tunneling microscopy (STM), temperature programmed-desorption (TPD), and Auger electron spectroscopy (AES). STM study shows that template growth of Au clusters on h-BN/Rh(111) forms mainly well-dispersed monolayer clusters. In contrast, Ni forms large multilayer clusters showing a relatively high diffusivity on h-BN/Rh(111) substrate. Ni–Au bimetallic clusters are effectively formed first by Au deposition followed by Ni deposition, with the Au clusters functioning as nucleation sites for the subsequently deposited Ni. Further structural analysis was carried out via TPDmore » and AES. The resulting TPD and AES data show the surface composition and charge transfer between Au and Ni of the bimetallic clusters. These results suggest that the h-BN/Rh(111) substrate represents a unique candidate for supporting Ni–Au bimetallic clusters in further catalytic reactions.« less

Stellar and Binary Evolution in Star Clusters

NASA Technical Reports Server (NTRS)

McMillan, Stephen L. W.

2001-01-01

This paper presents a final report on research activities covered on Stellar and Binary Evolution in Star Clusters. Substantial progress was made in the development and dissemination of the "Starlab" software environment. Significant improvements were made to "kira," an N-body simulation program tailored to the study of dense stellar systems such as star clusters and galactic nuclei. Key advances include (1) the inclusion of stellar and binary evolution in a self-consistent manner, (2) proper treatment of the anisotropic Galactic tidal field, (3) numerous technical enhancements in the treatment of binary dynamics and interactions, and (4) full support for the special-purpose GRAPE-4 hardware, boosting the program's performance by a factor of 10-100 over the accelerated version. The data-reduction and analysis tools in Starlab were also substantially expanded. A Starlab Web site (http://www.sns.ias.edu/-starlab) was created and developed. The site contains detailed information on the structure and function of the various tools that comprise the package, as well as download information, "how to" tips and examples of common operations, demonstration programs, animations, etc. All versions of the software are freely distributed to all interested users, along with detailed installation instructions.

Using Opinions and Knowledge to Identify Natural Groups of Gambling Employees.

PubMed

Gray, Heather M; Tom, Matthew A; LaPlante, Debi A; Shaffer, Howard J

2015-12-01

Gaming industry employees are at higher risk than the general population for health conditions including gambling disorder. Responsible gambling training programs, which train employees about gambling and gambling-related problems, might be a point of intervention. However, such programs tend to use a "one-size-fits-all" approach rather than multiple tiers of instruction. We surveyed employees of one Las Vegas casino (n = 217) and one online gambling operator (n = 178) regarding their gambling-related knowledge and opinions prior to responsible gambling training, to examine the presence of natural knowledge groups among recently hired employees. Using k-means cluster analysis, we observed four natural groups within the Las Vegas casino sample and two natural groups within the online operator sample. We describe these natural groups in terms of opinion/knowledge differences as well as distributions of demographic/occupational characteristics. Gender and language spoken at home were correlates of cluster group membership among the sample of Las Vegas casino employees, but we did not identify demographic or occupational correlates of cluster group membership among the online gambling operator employees. Gambling operators should develop more sophisticated training programs that include instruction that targets different natural knowledge groups.

Ultraviolet properties of individual hot stars in globular cluster cores. 1: NGC 1904 (M 79)

NASA Technical Reports Server (NTRS)

Altner, Bruce; Matilsky, Terry A.

1992-01-01

As part of an observing program using the International Ultraviolet Explorer (IUE) satellite to investigate the ultraviolet properties of stars found within the cores of galactic globular clusters with blue horizontal branches (HBs), we obtained three spectra of the cluster NGC 1904 (M 79). All three were long integration-time, short-wavelength (SWP) spectra obtained at the so called 'center of light' and all three showed evidence of sources within the IUE large aperture (21.4 in. by 10 in.). In this paper we shall describe the analysis of these spectra and present evidence that the UV sources represent individual hot stars in the post-HB stage of evolution.

Data Handling and Communication

NASA Astrophysics Data System (ADS)

Hemmer, FréDéRic Giorgio Innocenti, Pier

The following sections are included: * Introduction * Computing Clusters and Data Storage: The New Factory and Warehouse * Local Area Networks: Organizing Interconnection * High-Speed Worldwide Networking: Accelerating Protocols * Detector Simulation: Events Before the Event * Data Analysis and Programming Environment: Distilling Information * World Wide Web: Global Networking * References

Tools for Material Design and Selection

NASA Astrophysics Data System (ADS)

Wehage, Kristopher

The present thesis focuses on applications of numerical methods to create tools for material characterization, design and selection. The tools generated in this work incorporate a variety of programming concepts, from digital image analysis, geometry, optimization, and parallel programming to data-mining, databases and web design. The first portion of the thesis focuses on methods for characterizing clustering in bimodal 5083 Aluminum alloys created by cryomilling and powder metallurgy. The bimodal samples analyzed in the present work contain a mixture of a coarse grain phase, with a grain size on the order of several microns, and an ultra-fine grain phase, with a grain size on the order of 200 nm. The mixing of the two phases is not homogeneous and clustering is observed. To investigate clustering in these bimodal materials, various microstructures were created experimentally by conventional cryomilling, Hot Isostatic Pressing (HIP), Extrusion, Dual-Mode Dynamic Forging (DMDF) and a new 'Gradient' cryomilling process. Two techniques for quantitative clustering analysis are presented, formulated and implemented. The first technique, the Area Disorder function, provides a metric of the quality of coarse grain dispersion in an ultra-fine grain matrix and the second technique, the Two-Point Correlation function, provides a metric of long and short range spatial arrangements of the two phases, as well as an indication of the mean feature size in any direction. The two techniques are implemented on digital images created by Scanning Electron Microscopy (SEM) and Electron Backscatter Detection (EBSD) of the microstructures. To investigate structure--property relationships through modeling and simulation, strategies for generating synthetic microstructures are discussed and a computer program that generates randomized microstructures with desired configurations of clustering described by the Area Disorder Function is formulated and presented. In the computer program, two-dimensional microstructures are generated by Random Sequential Adsorption (RSA) of voxelized ellipses representing the coarse grain phase. A simulated annealing algorithm is used to geometrically optimize the placement of the ellipses in the model to achieve varying user-defined configurations of spatial arrangement of the coarse grains. During the simulated annealing process, the ellipses are allowed to overlap up to a specified threshold, allowing triple junctions to form in the model. Once the simulated annealing process is complete, the remaining space is populated by smaller ellipses representing the ultra-fine grain phase. Uniform random orientations are assigned to the grains. The program generates text files that can be imported in to Crystal Plasticity Finite Element Analysis Software for stress analysis. Finally, numerical methods and programming are applied to current issues in green engineering and hazard assessment. To understand hazards associated with materials and select safer alternatives, engineers and designers need access to up-to-date hazard information. However, hazard information comes from many disparate sources and aggregating, interpreting and taking action on the wealth of data is not trivial. In light of these challenges, a Framework for Automated Hazard Assessment based on the GreenScreen list translator is presented. The framework consists of a computer program that automatically extracts data from the GHS-Japan hazard database, loads the data into a machine-readable JSON format, transforms the JSON document in to a GreenScreen JSON document using the GreenScreen List Translator v1.2 and performs GreenScreen Benchmark scoring on the material. The GreenScreen JSON documents are then uploaded to a document storage system to allow human operators to search for, modify or add additional hazard information via a web interface.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

A long-term space astrophysics research program: An x-ray perspective of the components and structure of galaxies

NASA Technical Reports Server (NTRS)

Fabbiano, G.

1995-01-01

X-ray studies of galaxies by the Smithsonian Astrophysical Observatory (SAO) and MIT are described. Activities at SAO include ROSAT PSPC x-ray data reduction and analysis pipeline; x-ray sources in nearby Sc galaxies; optical, x-ray, and radio study of ongoing galactic merger; a radio, far infrared, optical, and x-ray study of the Sc galaxy NGC247; and a multiparametric analysis of the Einstein sample of early-type galaxies. Activities at MIT included continued analysis of observations with ROSAT and ASCA, and continued development of new approaches to spectral analysis with ASCA and AXAF. Also, a new method for characterizing structure in galactic clusters was developed and applied to ROSAT images of a large sample of clusters. An appendix contains preprints generated by the research.

A segmentation/clustering model for the analysis of array CGH data.

PubMed

Picard, F; Robin, S; Lebarbier, E; Daudin, J-J

2007-09-01

Microarray-CGH (comparative genomic hybridization) experiments are used to detect and map chromosomal imbalances. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose representative sequences share the same relative copy number on average. Segmentation methods constitute a natural framework for the analysis, but they do not provide a biological status for the detected segments. We propose a new model for this segmentation/clustering problem, combining a segmentation model with a mixture model. We present a new hybrid algorithm called dynamic programming-expectation maximization (DP-EM) to estimate the parameters of the model by maximum likelihood. This algorithm combines DP and the EM algorithm. We also propose a model selection heuristic to select the number of clusters and the number of segments. An example of our procedure is presented, based on publicly available data sets. We compare our method to segmentation methods and to hidden Markov models, and we show that the new segmentation/clustering model is a promising alternative that can be applied in the more general context of signal processing.

Insights into magmatic processes and hydrothermal alteration of in situ superfast spreading ocean crust at ODP/IODP site 1256 from a cluster analysis of rock magnetic properties

NASA Astrophysics Data System (ADS)

Dekkers, Mark J.; Heslop, David; Herrero-Bervera, Emilio; Acton, Gary; Krasa, David

2014-08-01

We analyze magnetic properties from Ocean Drilling Program (ODP)/Integrated ODP (IODP) Hole 1256D (6°44.1' N, 91°56.1' W) on the Cocos Plate in ˜15.2 Ma oceanic crust generated by superfast seafloor spreading, the only drill hole that has sampled all three oceanic crust layers in a tectonically undisturbed setting. Fuzzy c-means cluster analysis and nonlinear mapping are utilized to study down-hole trends in the ratio of the saturation remanent magnetization and the saturation magnetization, the coercive force, the ratio of the remanent coercive force and coercive force, the low-field magnetic susceptibility, and the Curie temperature, to evaluate the effects of magmatic and hydrothermal processes on magnetic properties. A statistically robust five cluster solution separates the data predominantly into three clusters that express increasing hydrothermal alteration of the lavas, which differ from two distinct clusters mainly representing the dikes and gabbros. Extensive alteration can obliterate magnetic property differences between lavas, dikes, and gabbros. The imprint of thermochemical alteration on the iron-titanium oxides is only partially related to the porosity of the rocks. Thus, the analysis complements interpretation based on electrofacies analysis. All clusters display rock magnetic characteristics compatible with an ability to retain a stable natural remanent magnetization suggesting that the entire sampled sequence of ocean crust can contribute to marine magnetic anomalies. Paleointensity determination is difficult because of the propensity of oxyexsolution during laboratory heating and/or the presence of intergrowths. The upper part of the extrusive sequence, the granoblastic dikes, and moderately altered gabbros may contain a comparatively uncontaminated thermoremanent magnetization.

Graph configuration model based evaluation of the education-occupation match

PubMed Central

2018-01-01

To study education—occupation matchings we developed a bipartite network model of education to work transition and a graph configuration model based metric. We studied the career paths of 15 thousand Hungarian students based on the integrated database of the National Tax Administration, the National Health Insurance Fund, and the higher education information system of the Hungarian Government. A brief analysis of gender pay gap and the spatial distribution of over-education is presented to demonstrate the background of the research and the resulted open dataset. We highlighted the hierarchical and clustered structure of the career paths based on the multi-resolution analysis of the graph modularity. The results of the cluster analysis can support policymakers to fine-tune the fragmented program structure of higher education. PMID:29509783

Graph configuration model based evaluation of the education-occupation match.

PubMed

Gadar, Laszlo; Abonyi, Janos

2018-01-01

To study education-occupation matchings we developed a bipartite network model of education to work transition and a graph configuration model based metric. We studied the career paths of 15 thousand Hungarian students based on the integrated database of the National Tax Administration, the National Health Insurance Fund, and the higher education information system of the Hungarian Government. A brief analysis of gender pay gap and the spatial distribution of over-education is presented to demonstrate the background of the research and the resulted open dataset. We highlighted the hierarchical and clustered structure of the career paths based on the multi-resolution analysis of the graph modularity. The results of the cluster analysis can support policymakers to fine-tune the fragmented program structure of higher education.

AMMI adjustment for statistical analysis of an international wheat yield trial.

PubMed

Crossa, J; Fox, P N; Pfeiffer, W H; Rajaram, S; Gauch, H G

1991-01-01

Multilocation trials are important for the CIMMYT Bread Wheat Program in producing high-yielding, adapted lines for a wide range of environments. This study investigated procedures for improving predictive success of a yield trial, grouping environments and genotypes into homogeneous subsets, and determining the yield stability of 18 CIMMYT bread wheats evaluated at 25 locations. Additive Main effects and Multiplicative Interaction (AMMI) analysis gave more precise estimates of genotypic yields within locations than means across replicates. This precision facilitated formation by cluster analysis of more cohesive groups of genotypes and locations for biological interpretation of interactions than occurred with unadjusted means. Locations were clustered into two subsets for which genotypes with positive interactions manifested in high, stable yields were identified. The analyses highlighted superior selections with both broad and specific adaptation.

SpatialEpiApp: A Shiny web application for the analysis of spatial and spatio-temporal disease data.

PubMed

Moraga, Paula

2017-11-01

During last years, public health surveillance has been facilitated by the existence of several packages implementing statistical methods for the analysis of spatial and spatio-temporal disease data. However, these methods are still inaccesible for many researchers lacking the adequate programming skills to effectively use the required software. In this paper we present SpatialEpiApp, a Shiny web application that integrate two of the most common approaches in health surveillance: disease mapping and detection of clusters. SpatialEpiApp is easy to use and does not require any programming knowledge. Given information about the cases, population and optionally covariates for each of the areas and dates of study, the application allows to fit Bayesian models to obtain disease risk estimates and their uncertainty by using R-INLA, and to detect disease clusters by using SaTScan. The application allows user interaction and the creation of interactive data visualizations and reports showing the analyses performed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Agriculture Cluster Brief. Vocational Education in Oregon.

ERIC Educational Resources Information Center

Galbraith, Gordon

This guide sets forth minimum approval criteria for vocational agriculture cluster programs in Oregon. The agriculture cluster program includes instruction in six areas: animal science, soil science, plant science, agricultural economics, agriculture mechanics, and leadership development. The information in the guide is intended for use by…

Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Hao-Qiang; anMey, Dieter; Hatay, Ferhat F.

2003-01-01

Clusters of SMP (Symmetric Multi-Processors) nodes provide support for a wide range of parallel programming paradigms. The shared address space within each node is suitable for OpenMP parallelization. Message passing can be employed within and across the nodes of a cluster. Multiple levels of parallelism can be achieved by combining message passing and OpenMP parallelization. Which programming paradigm is the best will depend on the nature of the given problem, the hardware components of the cluster, the network, and the available software. In this study we compare the performance of different implementations of the same CFD benchmark application, using the same numerical algorithm but employing different programming paradigms.

A new physical performance classification system for elite handball players: cluster analysis

PubMed Central

Chirosa, Ignacio J.; Robinson, Joseph E.; van der Tillaar, Roland; Chirosa, Luis J.; Martín, Isidoro Martínez

2016-01-01

Abstract The aim of the present study was to identify different cluster groups of handball players according to their physical performance level assessed in a series of physical assessments, which could then be used to design a training program based on individual strengths and weaknesses, and to determine which of these variables best identified elite performance in a group of under-19 [U19] national level handball players. Players of the U19 National Handball team (n=16) performed a set of tests to determine: 10 m (ST10) and 20 m (ST20) sprint time, ball release velocity (BRv), countermovement jump (CMJ) height and squat jump (SJ) height. All players also performed an incremental-load bench press test to determine the 1 repetition maximum (1RMest), the load corresponding to maximum mean power (LoadMP), the mean propulsive phase power at LoadMP (PMPPMP) and the peak power at LoadMP (PPEAKMP). Cluster analyses of the test results generated four groupings of players. The variables best able to discriminate physical performance were BRv, ST20, 1RMest, PPEAKMP and PMPPMP. These variables could help coaches identify talent or monitor the physical performance of athletes in their team. Each cluster of players has a particular weakness related to physical performance and therefore, the cluster results can be applied to a specific training programmed based on individual needs. PMID:28149376

PyPele Rewritten To Use MPI

NASA Technical Reports Server (NTRS)

Hockney, George; Lee, Seungwon

2008-01-01

A computer program known as PyPele, originally written as a Pythonlanguage extension module of a C++ language program, has been rewritten in pure Python language. The original version of PyPele dispatches and coordinates parallel-processing tasks on cluster computers and provides a conceptual framework for spacecraft-mission- design and -analysis software tools to run in an embarrassingly parallel mode. The original version of PyPele uses SSH (Secure Shell a set of standards and an associated network protocol for establishing a secure channel between a local and a remote computer) to coordinate parallel processing. Instead of SSH, the present Python version of PyPele uses Message Passing Interface (MPI) [an unofficial de-facto standard language-independent application programming interface for message- passing on a parallel computer] while keeping the same user interface. The use of MPI instead of SSH and the preservation of the original PyPele user interface make it possible for parallel application programs written previously for the original version of PyPele to run on MPI-based cluster computers. As a result, engineers using the previously written application programs can take advantage of embarrassing parallelism without need to rewrite those programs.

Five task clusters that enable efficient and effective digitization of biological collections

PubMed Central

Nelson, Gil; Paul, Deborah; Riccardi, Gregory; Mast, Austin R.

2012-01-01

Abstract This paper describes and illustrates five major clusters of related tasks (herein referred to as task clusters) that are common to efficient and effective practices in the digitization of biological specimen data and media. Examples of these clusters come from the observation of diverse digitization processes. The staff of iDigBio (The U.S. National Science Foundation’s National Resource for Advancing Digitization of Biological Collections) visited active biological and paleontological collections digitization programs for the purpose of documenting and assessing current digitization practices and tools. These observations identified five task clusters that comprise the digitization process leading up to data publication: (1) pre-digitization curation and staging, (2) specimen image capture, (3) specimen image processing, (4) electronic data capture, and (5) georeferencing locality descriptions. While not all institutions are completing each of these task clusters for each specimen, these clusters describe a composite picture of digitization of biological and paleontological specimens across the programs that were observed. We describe these clusters, three workflow patterns that dominate the implemention of these clusters, and offer a set of workflow recommendations for digitization programs. PMID:22859876

Interactive Parallel Data Analysis within Data-Centric Cluster Facilities using the IPython Notebook

NASA Astrophysics Data System (ADS)

Pascoe, S.; Lansdowne, J.; Iwi, A.; Stephens, A.; Kershaw, P.

2012-12-01

The data deluge is making traditional analysis workflows for many researchers obsolete. Support for parallelism within popular tools such as matlab, IDL and NCO is not well developed and rarely used. However parallelism is necessary for processing modern data volumes on a timescale conducive to curiosity-driven analysis. Furthermore, for peta-scale datasets such as the CMIP5 archive, it is no longer practical to bring an entire dataset to a researcher's workstation for analysis, or even to their institutional cluster. Therefore, there is an increasing need to develop new analysis platforms which both enable processing at the point of data storage and which provides parallelism. Such an environment should, where possible, maintain the convenience and familiarity of our current analysis environments to encourage curiosity-driven research. We describe how we are combining the interactive python shell (IPython) with our JASMIN data-cluster infrastructure. IPython has been specifically designed to bridge the gap between the HPC-style parallel workflows and the opportunistic curiosity-driven analysis usually carried out using domain specific languages and scriptable tools. IPython offers a web-based interactive environment, the IPython notebook, and a cluster engine for parallelism all underpinned by the well-respected Python/Scipy scientific programming stack. JASMIN is designed to support the data analysis requirements of the UK and European climate and earth system modeling community. JASMIN, with its sister facility CEMS focusing the earth observation community, has 4.5 PB of fast parallel disk storage alongside over 370 computing cores provide local computation. Through the IPython interface to JASMIN, users can make efficient use of JASMIN's multi-core virtual machines to perform interactive analysis on all cores simultaneously or can configure IPython clusters across multiple VMs. Larger-scale clusters can be provisioned through JASMIN's batch scheduling system. Outputs can be summarised and visualised using the full power of Python's many scientific tools, including Scipy, Matplotlib, Pandas and CDAT. This rich user experience is delivered through the user's web browser; maintaining the interactive feel of a workstation-based environment with the parallel power of a remote data-centric processing facility.

Cluster Guide. Accounting Occupations.

ERIC Educational Resources Information Center

Beaverton School District 48, OR.

Based on a recent task inventory of key occupations in the accounting cluster taken in the Portland, Oregon, area, this curriculum guide is intended to assist administrators and teachers in the design and implementation of high school accounting cluster programs. The guide is divided into four major sections: program organization and…

AN INVESTIGATION AND DEVELOPMENT OF THE CLUSTER CONCEPT AS A PROGRAM IN VOCATIONAL EDUCATION AT THE SECONDARY SCHOOL LEVEL--FINAL REPORT, PHASE 1.

ERIC Educational Resources Information Center

MALEY, DONALD

THE INVESTIGATION AND DEVELOPMENT OF THE CLUSTER CONCEPT AS A PROGRAM IN VOCATIONAL EDUCATION AT THE SECONDARY SCHOOL LEVEL WERE REPORTED. THE "CLUSTER CONCEPT" PROGRAM IS AIMED AT THE DEVELOPMENT OF SKILLS AND UNDERSTANDINGS RELATED TO A NUMBER OF ALLIED FIELDS, AND WOULD PREPARE THE PERSON TO ENTER INTO A FAMILY OF OCCUPATIONS RATHER…

Outcome-Driven Cluster Analysis with Application to Microarray Data.

PubMed

Hsu, Jessie J; Finkelstein, Dianne M; Schoenfeld, David A

2015-01-01

One goal of cluster analysis is to sort characteristics into groups (clusters) so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes) into groups of highly correlated genes that have the same effect on the outcome (recovery). We propose a random effects model where the genes within each group (cluster) equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.

A mathematical programming approach for sequential clustering of dynamic networks

NASA Astrophysics Data System (ADS)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics

PubMed Central

2010-01-01

Background Bioinformatics researchers are now confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. Description An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date. Conclusions Hadoop and the MapReduce programming paradigm already have a substantial base in the bioinformatics community, especially in the field of next-generation sequencing analysis, and such use is increasing. This is due to the cost-effectiveness of Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms. PMID:21210976

An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics.

PubMed

Taylor, Ronald C

2010-12-21

Bioinformatics researchers are now confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date. Hadoop and the MapReduce programming paradigm already have a substantial base in the bioinformatics community, especially in the field of next-generation sequencing analysis, and such use is increasing. This is due to the cost-effectiveness of Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms.

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs.

PubMed

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-05-28

Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4-15.9 times faster, while Unphased jobs performed 1.1-18.6 times faster compared to the accumulated computation duration. Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance.

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs

PubMed Central

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-01-01

Background Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Results Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4–15.9 times faster, while Unphased jobs performed 1.1–18.6 times faster compared to the accumulated computation duration. Conclusion Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance. PMID:18541045

Clustering and Network Analysis of Reverse Phase Protein Array Data.

PubMed

Byron, Adam

2017-01-01

Molecular profiling of proteins and phosphoproteins using a reverse phase protein array (RPPA) platform, with a panel of target-specific antibodies, enables the parallel, quantitative proteomic analysis of many biological samples in a microarray format. Hence, RPPA analysis can generate a high volume of multidimensional data that must be effectively interrogated and interpreted. A range of computational techniques for data mining can be applied to detect and explore data structure and to form functional predictions from large datasets. Here, two approaches for the computational analysis of RPPA data are detailed: the identification of similar patterns of protein expression by hierarchical cluster analysis and the modeling of protein interactions and signaling relationships by network analysis. The protocols use freely available, cross-platform software, are easy to implement, and do not require any programming expertise. Serving as data-driven starting points for further in-depth analysis, validation, and biological experimentation, these and related bioinformatic approaches can accelerate the functional interpretation of RPPA data.

A Cluster Analytic Approach to Identifying Predictors and Moderators of Psychosocial Treatment for Bipolar Depression: Results from STEP-BD

PubMed Central

Deckersbach, Thilo; Peters, Amy T.; Sylvia, Louisa G.; Gold, Alexandra K.; da Silva Magalhaes, Pedro Vieira; Henry, David B.; Frank, Ellen; Otto, Michael W.; Berk, Michael; Dougherty, Darin D.; Nierenberg, Andrew A.; Miklowitz, David J.

2016-01-01

Background We sought to address how predictors and moderators of psychotherapy for bipolar depression – identified individually in prior analyses – can inform the development of a metric for prospectively classifying treatment outcome in intensive psychotherapy (IP) versus collaborative care (CC) adjunctive to pharmacotherapy in the Systematic Treatment Enhancement Program (STEP-BD) study. Methods We conducted post-hoc analyses on 135 STEP-BD participants using cluster analysis to identify subsets of participants with similar clinical profiles and investigated this combined metric as a moderator and predictor of response to IP. We used agglomerative hierarchical cluster analyses and k-means clustering to determine the content of the clinical profiles. Logistic regression and Cox proportional hazard models were used to evaluate whether the resulting clusters predicted or moderated likelihood of recovery or time until recovery. Results The cluster analysis yielded a two-cluster solution: 1) “less-recurrent/severe” and 2) “chronic/recurrent.” Rates of recovery in IP were similar for less-recurrent/severe and chronic/recurrent participants. Less-recurrent/severe patients were more likely than chronic/recurrent patients to achieve recovery in CC (p = .040, OR = 4.56). IP yielded a faster recovery for chronic/recurrent participants, whereas CC led to recovery sooner in the less-recurrent/severe cluster (p = .034, OR = 2.62). Limitations Cluster analyses require list-wise deletion of cases with missing data so we were unable to conduct analyses on all STEP-BD participants. Conclusions A well-powered, parametric approach can distinguish patients based on illness history and provide clinicians with symptom profiles of patients that confer differential prognosis in CC vs. IP. PMID:27289316

A Cluster Analysis of the 1985-1989 Credit Student Body: Implementing Geo-Demographic Marketing at P.G.C.C. Market Analysis MA91-4.

ERIC Educational Resources Information Center

Boughan, Karl

In an effort to better market the college's credit programs and services, Prince George's Community College (PGCC), Mayland, has employed its own tracking system which utilizes a socioeconomic segmentation of their serviceable target population. This approach utilizes U.S. Census data grouping neighborhoods into 24 natural socioeconomic, cultural…

A Cluster Analysis of the 1985-1989 Non-Credit Student Body: Implementing Geo-Demographic Marketing at P.G.C.C., Part II. Market Analysis MA91-5.

ERIC Educational Resources Information Center

Boughan, Karl

In an effort to better market the college's programs and services, Prince George's Community College (PGCC), Maryland, has employed its own tracking system which utilizes a socioeconomic segmentation of their serviceable target population. This approach utilizes U.S. Census data grouping neighborhoods into natural socioeconomic, cultural, and…

Imaging Electron Spectrometer (IES) Electron Preprocessor (EPP) Design

NASA Technical Reports Server (NTRS)

Fennell, J. F.; Osborn, J. V.; Christensen, John L. (Technical Monitor)

2001-01-01

The Aerospace Corporation developed the Electron PreProcessor (EPP) to support the Imaging Electron Spectrometer (IES) that is part of the RAPID experiment on the ESA/NASA CLUSTER mission. The purpose of the EPP is to collect raw data from the IES and perform processing and data compression on it before transferring it to the RAPID microprocessor system for formatting and transmission to the CLUSTER satellite data system. The report provides a short history of the RAPID and CLUSTER programs and describes the EPP design. Four EPP units were fabricated, tested, and delivered for the original CLUSTER program. These were destroyed during a launch failure. Four more EPP units were delivered for the CLUSTER II program. These were successfully launched and are operating nominally on orbit.

DENBRAN: A basic program for a significance test for multivariate normality of clusters from branching patterns in dendrograms

NASA Astrophysics Data System (ADS)

Sneath, P. H. A.

A BASIC program is presented for significance tests to determine whether a dendrogram is derived from clustering of points that belong to a single multivariate normal distribution. The significance tests are based on statistics of the Kolmogorov—Smirnov type, obtained by comparing the observed cumulative graph of branch levels with a graph for the hypothesis of multivariate normality. The program also permits testing whether the dendrogram could be from a cluster of lower dimensionality due to character correlations. The program makes provision for three similarity coefficients, (1) Euclidean distances, (2) squared Euclidean distances, and (3) Simple Matching Coefficients, and for five cluster methods (1) WPGMA, (2) UPGMA, (3) Single Linkage (or Minimum Spanning Trees), (4) Complete Linkage, and (5) Ward's Increase in Sums of Squares. The program is entitled DENBRAN.

Networking between community health programs: a case study outlining the effectiveness, barriers and enablers

PubMed Central

2012-01-01

Background In India, since the 1990s, there has been a burgeoning of NGOs involved in providing primary health care. This has resulted in a complex NGO-Government interface which is difficult for lone NGOs to navigate. The Uttarakhand Cluster, India, links such small community health programs together to build NGO capacity, increase visibility and better link to the government schemes and the formal healthcare system. This research, undertaken between 1998 and 2011, aims to examine barriers and facilitators to such linking, or clustering, and the effectiveness of this clustering approach. Methods Interviews, indicator surveys and participant observation were used to document the process and explore the enablers, the barriers and the effectiveness of networks improving community health. Results The analysis revealed that when activating, framing, mobilising and synthesizing the Uttarakhand Cluster, key brokers and network players were important in bridging between organisations. The ties (or relationships) that held the cluster together included homophily around common faith, common friendships and geographical location and common mission. Self interest whereby members sought funds, visibility, credibility, increased capacity and access to trainings was also a commonly identified motivating factor for networking. Barriers to network synthesizing included lack of funding, poor communication, limited time and lack of human resources. Risk aversion and mistrust remained significant barriers to overcome for such a network. Conclusions In conclusion, specific enabling factors allowed the clustering approach to be effective at increasing access to resources, creating collaborative opportunities and increasing visibility, credibility and confidence of the cluster members. These findings add to knowledge regarding social network formation and collaboration, and such knowledge will assist in the conceptualisation, formation and success of potential health networks in India and other developing world countries. PMID:22812627

Networking between community health programs: a case study outlining the effectiveness, barriers and enablers.

PubMed

Grills, Nathan J; Robinson, Priscilla; Phillip, Maneesh

2012-07-19

In India, since the 1990s, there has been a burgeoning of NGOs involved in providing primary health care. This has resulted in a complex NGO-Government interface which is difficult for lone NGOs to navigate. The Uttarakhand Cluster, India, links such small community health programs together to build NGO capacity, increase visibility and better link to the government schemes and the formal healthcare system. This research, undertaken between 1998 and 2011, aims to examine barriers and facilitators to such linking, or clustering, and the effectiveness of this clustering approach. Interviews, indicator surveys and participant observation were used to document the process and explore the enablers, the barriers and the effectiveness of networks improving community health. The analysis revealed that when activating, framing, mobilising and synthesizing the Uttarakhand Cluster, key brokers and network players were important in bridging between organisations. The ties (or relationships) that held the cluster together included homophily around common faith, common friendships and geographical location and common mission. Self interest whereby members sought funds, visibility, credibility, increased capacity and access to trainings was also a commonly identified motivating factor for networking. Barriers to network synthesizing included lack of funding, poor communication, limited time and lack of human resources. Risk aversion and mistrust remained significant barriers to overcome for such a network. In conclusion, specific enabling factors allowed the clustering approach to be effective at increasing access to resources, creating collaborative opportunities and increasing visibility, credibility and confidence of the cluster members. These findings add to knowledge regarding social network formation and collaboration, and such knowledge will assist in the conceptualisation, formation and success of potential health networks in India and other developing world countries.

Two-year population-based molecular epidemiological study of tuberculosis transmission in the metropolitan area of Milan, Italy.

PubMed

Moro, M L; Salamina, G; Gori, A; Penati, V; Sacchetti, R; Mezzetti, F; Infuso, A; Sodano, L

2002-02-01

A 2-year, population-based, molecular epidemiological study was conducted in Milan, Italy, to determine the proportion of tuberculosis (TB) cases attributable to recent transmission. All strains were typed by restriction fragment length polymorphism (RFLP) analysis; clustering was considered indicative of recent transmission. Of the 581 cases, 239 (41.1%) belonged to clusters that consisted of 2 to 11 patients; 28.1% were attributable to recent transmission (number of clustered patients minus 1). Clustering was associated with multidrug-resistant Mycobacterium tuberculosis strains (74.2% of cases), AIDS (60.2%), and a history of incarceration (67.4%). The frequency of multidrug-resistant Mycobacterium tuberculosis was 5.3% overall (15.4% among AIDS patients). Among AIDS patients, infection with a resistant strain was independently associated with clustering (odds ratio, 1.32; 95% confidence interval, 1.07-1.163), while among non-AIDS patients, three factors were associated with clustering: history of incarceration (odds ratio, 2.03; 95% confidence interval, 1.41-2.92), age <30 years (odds ratio, 1.43; 95% confidence interval, 1.05-1.94), and native-born Italian nationality (odds ratio, 1.44; 95% confidence interval, 1.08-1.92). Of the 118 patients who belonged to either the smallest or the largest cluster, 19 (16.1%) reported an epidemiological link with another study patient. The results of this study highlight the need for control programs that focus on selected high-risk groups consisting primarily of HIV-infected individuals and persons with social and lifestyle risks for TB. These programs should be aimed at reducing the probability of transmission of drug-resistant TB through early identification of cases and provision of effective treatment until the individual is cured.

Classification of cassava genotypes based on qualitative and quantitative data.

PubMed

Oliveira, E J; Oliveira Filho, O S; Santos, V S

2015-02-02

We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

Mississippi Curriculum Framework for Horticulture Technology Cluster (Program CIP: 01.0601--Horticulture Serv. Op. & Mgmt., Gen.) (Program CIP: 01.0605--Landscaping Op. & Mgmt.). Postsecondary Programs.

ERIC Educational Resources Information Center

Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for the course sequences in the horticulture technology programs cluster. Presented in the introductory section are a framework of programs and courses, description of the programs, and suggested course sequences for…

Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

PubMed

Yokoyama, Eiji; Uchimura, Masako

2007-11-01

Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

Cognitive Mapping Tobacco Control Advice for Dentistry: A Dental PBRN Study

ERIC Educational Resources Information Center

Qu, Haiyan; Houston, Thomas K.; Williams, Jessica H.; Gilbert, Gregg H.; Shewchuk, Richard M.

2011-01-01

Objective: To identify facilitative strategies that could be used in developing a tobacco cessation program for community dental practices. Methods: Nominal group technique (NGT) meetings and a card-sort task were used to obtain formative data. A cognitive mapping approach involving multidimensional scaling and hierarchical cluster analysis was…

Use of intermediaries in DWI deterrence. Volume 2, Phase 1 report : analysis of potential target clusters for DWI intermediary programs

DOT National Transportation Integrated Search

1983-04-01

This report summarizes the results of Phase I of the project, "Use of Intermediaries in DWI Deterrence." Data from secondary sources along with National Accident Samplimg System (NASS), Fatal Accident Reporting System (FARS) and National Institute on...

Tobacco, Marijuana, and Alcohol Use in University Students: A Cluster Analysis

ERIC Educational Resources Information Center

Primack, Brian A.; Kim, Kevin H.; Shensa, Ariel; Sidani, Jaime E.; Barnett, Tracey E.; Switzer, Galen E.

2012-01-01

Objective: Segmentation of populations may facilitate development of targeted substance abuse prevention programs. The authors aimed to partition a national sample of university students according to profiles based on substance use. Participants: The authors used 2008-2009 data from the National College Health Assessment from the American College…

Exploring the Association between Campus Co-Curricular Involvement and Academic Achievement

ERIC Educational Resources Information Center

Bergen-Cico, Dessa; Viscomi, Joe

2013-01-01

This research examines the relationship between college student attendance at co-curricular programs and GPA. Researchers tracked attendance of two cohorts totaling 3,000+ students through electromagnetic scanning at university-sponsored events. Analysis of GPA by attendance rate clusters revealed that students attending 5-14 events over the…

Health Lifestyles: Audience Segmentation Analysis for Public Health Interventions.

ERIC Educational Resources Information Center

Slater, Michael D.; Flora, June A.

This paper is concerned with the application of market research techniques to segment large populations into homogeneous units in order to improve the reach, utilization, and effectiveness of health programs. The paper identifies seven distinctive patterns of health attitudes, social influences, and behaviors using cluster analytic techniques in a…

Cluster galaxy population evolution from the Subaru Hyper Suprime-Cam survey: brightest cluster galaxies, stellar mass distribution, and active galaxies

NASA Astrophysics Data System (ADS)

Lin, Yen-Ting; Hsieh, Bau-Ching; Lin, Sheng-Chieh; Oguri, Masamune; Chen, Kai-Feng; Tanaka, Masayuki; Chiu, I.-non; Huang, Song; Kodama, Tadayuki; Leauthaud, Alexie; More, Surhud; Nishizawa, Atsushi J.; Bundy, Kevin; Lin, Lihwai; Miyazaki, Satoshi; HSC Collaboration

2018-01-01

The unprecedented depth and area surveyed by the Subaru Strategic Program with the Hyper Suprime-Cam (HSC-SSP) have enabled us to construct and publish the largest distant cluster sample out to z~1 to date. In this exploratory study of cluster galaxy evolution from z=1 to z=0.3, we investigate the stellar mass assembly history of brightest cluster galaxies (BCGs), and evolution of stellar mass and luminosity distributions, stellar mass surface density profile, as well as the population of radio galaxies. Our analysis is the first high redshift application of the top N richest cluster selection, which is shown to allow us to trace the cluster galaxy evolution faithfully. Our stellar mass is derived from a machine-learning algorithm, which we show to be unbiased and accurate with respect to the COSMOS data. We find very mild stellar mass growth in BCGs, and no evidence for evolution in both the total stellar mass-cluster mass correlation and the shape of the stellar mass surface density profile. The clusters are found to contain more red galaxies compared to the expectations from the field, even after the differences in density between the two environments have been taken into account. We also present the first measurement of the radio luminosity distribution in clusters out to z~1.

The Cluster Concept Program Developed by the University of Maryland, Industrial Education Department.

ERIC Educational Resources Information Center

Kratochvil, Daniel W.; Thompson, Lorna J.

This report, one of 21 case studies, describes the history of a recent educational product. The Cluster Concept Program, developed at the University of Maryland, is directed toward the preparation of individuals for entrance into a spectrum of occupations. Three clusters of occupations are included: (1) Construction, (2) Electro-Mechanical…

Review of Instructional Approaches in Ethics Education.

PubMed

Mulhearn, Tyler J; Steele, Logan M; Watts, Logan L; Medeiros, Kelsey E; Mumford, Michael D; Connelly, Shane

2017-06-01

Increased investment in ethics education has prompted a variety of instructional objectives and frameworks. Yet, no systematic procedure to classify these varying instructional approaches has been attempted. In the present study, a quantitative clustering procedure was conducted to derive a typology of instruction in ethics education. In total, 330 ethics training programs were included in the cluster analysis. The training programs were appraised with respect to four instructional categories including instructional content, processes, delivery methods, and activities. Eight instructional approaches were identified through this clustering procedure, and these instructional approaches showed different levels of effectiveness. Instructional effectiveness was assessed based on one of nine commonly used ethics criteria. With respect to specific training types, Professional Decision Processes Training (d = 0.50) and Field-Specific Compliance Training (d = 0.46) appear to be viable approaches to ethics training based on Cohen's d effect size estimates. By contrast, two commonly used approaches, General Discussion Training (d = 0.31) and Norm Adherence Training (d = 0.37), were found to be considerably less effective. The implications for instruction in ethics training are discussed.

Off-road truck-related accidents in U.S. mines

PubMed Central

Dindarloo, Saeid R.; Pollard, Jonisha P.; Siami-Irdemoosa, Elnaz

2016-01-01

Introduction Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. Methods A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Results Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. Conclusions The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Practical application Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. PMID:27620937

Off-road truck-related accidents in U.S. mines.

PubMed

Dindarloo, Saeid R; Pollard, Jonisha P; Siami-Irdemoosa, Elnaz

2016-09-01

Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity

PubMed Central

Pope, Welkin H; Bowman, Charles A; Russell, Daniel A; Jacobs-Sera, Deborah; Asai, David J; Cresawn, Steven G; Jacobs, William R; Hendrix, Roger W; Lawrence, Jeffrey G; Hatfull, Graham F; Abbazia, Patrick; Ababio, Amma; Adam, Naazneen

2015-01-01

The bacteriophage population is large, dynamic, ancient, and genetically diverse. Limited genomic information shows that phage genomes are mosaic, and the genetic architecture of phage populations remains ill-defined. To understand the population structure of phages infecting a single host strain, we isolated, sequenced, and compared 627 phages of Mycobacterium smegmatis. Their genetic diversity is considerable, and there are 28 distinct genomic types (clusters) with related nucleotide sequences. However, amino acid sequence comparisons show pervasive genomic mosaicism, and quantification of inter-cluster and intra-cluster relatedness reveals a continuum of genetic diversity, albeit with uneven representation of different phages. Furthermore, rarefaction analysis shows that the mycobacteriophage population is not closed, and there is a constant influx of genes from other sources. Phage isolation and analysis was performed by a large consortium of academic institutions, illustrating the substantial benefits of a disseminated, structured program involving large numbers of freshman undergraduates in scientific discovery. DOI: http://dx.doi.org/10.7554/eLife.06416.001 PMID:25919952

Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity.

PubMed

Pope, Welkin H; Bowman, Charles A; Russell, Daniel A; Jacobs-Sera, Deborah; Asai, David J; Cresawn, Steven G; Jacobs, William R; Hendrix, Roger W; Lawrence, Jeffrey G; Hatfull, Graham F

2015-04-28

The bacteriophage population is large, dynamic, ancient, and genetically diverse. Limited genomic information shows that phage genomes are mosaic, and the genetic architecture of phage populations remains ill-defined. To understand the population structure of phages infecting a single host strain, we isolated, sequenced, and compared 627 phages of Mycobacterium smegmatis. Their genetic diversity is considerable, and there are 28 distinct genomic types (clusters) with related nucleotide sequences. However, amino acid sequence comparisons show pervasive genomic mosaicism, and quantification of inter-cluster and intra-cluster relatedness reveals a continuum of genetic diversity, albeit with uneven representation of different phages. Furthermore, rarefaction analysis shows that the mycobacteriophage population is not closed, and there is a constant influx of genes from other sources. Phage isolation and analysis was performed by a large consortium of academic institutions, illustrating the substantial benefits of a disseminated, structured program involving large numbers of freshman undergraduates in scientific discovery.

Study protocol for a self-controlled cluster randomised trial of the Alert Program to improve self-regulation and executive function in Australian Aboriginal children with fetal alcohol spectrum disorder

PubMed Central

Fitzpatrick, James P; Mazzucchelli, Trevor G; Symons, Martyn; Carmichael Olson, Heather; Jirikowic, Tracy; Cross, Donna; Wright, Edie; Adams, Emma; Carter, Maureen; Bruce, Kaashifah; Latimer, Jane

2018-01-01

Introduction While research highlights the benefits of early diagnosis and intervention for children with fetal alcohol spectrum disorders (FASD), there are limited data documenting effective interventions for Australian children living in remote communities. Methods and analysis This self-controlled cluster randomised trial is evaluating the effectiveness of an 8-week Alert Program school curriculum for improving self-regulation and executive function in children living in remote Australian Aboriginal communities. Children in grades 1–6 attending any of the eight participating schools across the Fitzroy Valley in remote North-West Australia (N ≈ 363) were invited to participate. Each school was assigned to one of four clusters with clusters randomly assigned to receive the intervention at one of four time points. Clusters two, three and four had extended control conditions where students received regular schooling before later receiving the intervention. Trained classroom teachers delivered the Alert Program to students in discrete, weekly, 1-hour lessons. Student outcomes were assessed at three time points. For the intervention condition, data collection occurred 2 weeks immediately before and after the intervention, with a follow-up 8 weeks later. For control conditions in clusters two to four, the control data collection matched that of the data collection for the intervention condition in the preceding cluster. The primary outcome is change in self-regulation. FASD diagnoses will be determined via medical record review after the completion of data collection. The results will be analysed using generalised linear mixed modelling and reported in accordance with Consolidated Standards of Reporting Trials (CONSORT) guidelines. Ethics and dissemination Ethical approval was obtained from the University of Western Australia (WA) (RA/4/1/7234), WA Aboriginal Health Ethics Committee (601) and WA Country Health Service (2015:04). The Kimberley Aboriginal Health Planning Forum Research Sub-Committee and WA Department of Education also provided approval. The results will be disseminated through peer-reviewed journals, conference presentations, the media and at forums. Trial registration number ACTRN12615000733572; Pre-results. PMID:29581212

Hard x ray imaging graphics development and literature search

NASA Technical Reports Server (NTRS)

Emslie, A. Gordon

1991-01-01

This report presents work performed between June 1990 and June 1991 and has the following objectives: (1) a comprehensive literature search of imaging technology and coded aperture imaging as well as relevant topics relating to solar flares; (2) an analysis of random number generators; and (3) programming simulation models of hard x ray telescopes. All programs are compatible with NASA/MSFC Space Science LAboratory VAX Cluster and are written in VAX FORTRAN and VAX IDL (Interactive Data Language).

Student profiling on university co-curricular activities using cluster analysis

NASA Astrophysics Data System (ADS)

Rajenthran, Hemabegai A./P.; Shaharanee, Izwan Nizal Mohd; Jamil, Jastini Mohd.

2017-11-01

In higher learning institutions, the co-curricular programs are needed for the graduation besides the standard academic programs. By actively participating in co-curricular, students can attain many of soft skills and proficiencies besides learning and adopting campus environment, community and traditions. Co-curricular activities are implemented by universities mainly for the refinement of the academic achievement along with the social development. This studies aimed to analyse the academic profile of the co-curricular students among uniform units. The main objective of study is to develop a profile of student co-curricular activities in uniform units. Additionally, several variables has been selected to serve as the characteristics for student co-curricular profile. The findings of this study demonstrate the practicality of clustering technique to investigate student's profiles and allow for a better understanding of student's behavior and co-curriculum activities.

Scholarly Research Program in Fuel Analysis and Combustion Research

DTIC Science & Technology

1993-02-01

Public reporting burden for this collection of information is es•tmated to average I hour per response, ilnduding the time fo," reviwing ...Thermal Oxidative Flask Test 45 9. Advanced Fuel System Configuration Descent Condition 57 10. TGPGC for n-Alkane Mixture 63 11. Hierarchical Cluster ...will include all analytical data, data analysis conclusions, recommendations and rationale. 16 a& k : 05 Titl: Development of Test Cell Assemblies for

Social Networks and High Healthcare Utilization: Building Resilience Through Analysis

DTIC Science & Technology

2016-09-01

of Social Network Analysis Patients Developing targeted intervention programs based on the individual’s needs may potentially help improve the...network structure is found in the patterns of interconnection that develop between nodes. It is this linking through common nodes, “the AB link shares...transitivity is responsible for the clustering of nodes that form “communities” of people based on geography, common interests, or other group

FRONTIER FIELDS: HIGH-REDSHIFT PREDICTIONS AND EARLY RESULTS

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

Coe, Dan; Bradley, Larry; Zitrin, Adi, E-mail: DCoe@STScI.edu

2015-02-20

The Frontier Fields program is obtaining deep Hubble and Spitzer Space Telescope images of new ''blank'' fields and nearby fields gravitationally lensed by massive galaxy clusters. The Hubble images of the lensed fields are revealing nJy sources (AB mag > 31), the faintest galaxies yet observed. The full program will transform our understanding of galaxy evolution in the first 600 million years (z > 9). Previous programs have yielded a dozen or so z > 9 candidates, including perhaps fewer than expected in the Ultra Deep Field and more than expected in shallower Hubble images. In this paper, we present high-redshift (z >more » 6) number count predictions for the Frontier Fields and candidates in three of the first Hubble images. We show the full Frontier Fields program may yield up to ∼70 z > 9 candidates (∼6 per field). We base this estimate on an extrapolation of luminosity functions observed between 4 < z < 8 and gravitational lensing models submitted by the community. However, in the first two deep infrared Hubble images obtained to date, we find z ∼ 8 candidates but no strong candidates at z > 9. We defer quantitative analysis of the z > 9 deficit (including detection completeness estimates) to future work including additional data. At these redshifts, cosmic variance (field-to-field variation) is expected to be significant (greater than ±50%) and include clustering of early galaxies formed in overdensities. The full Frontier Fields program will significantly mitigate this uncertainty by observing six independent sightlines each with a lensing cluster and nearby blank field.« less

Exploration of a leadership competency model for medical school faculties in Korea.

PubMed

Lee, Yong Seok; Oh, Dong Keun; Kim, Myungun; Lee, Yoon Seong; Shin, Jwa Seop

2010-12-01

To adapt to rapid and turbulent changes in the field of medicine, education, and society, medical school faculties need appropriate leadership. To develop leadership competencies through education, coaching, and mentoring, we need a leadership competency model. The purpose of this study was to develop a new leadership competency model that is suitable for medical school faculties in Korea. To collect behavioral episodes with regard to leadership, we interviewed 54 subjects (faculties, residents, nurses) and surveyed 41 faculties with open-ended questionnaires. We classified the behavioral episodes based on Quinn and Cameron's leadership competency model and developed a Likert scale questionnaire to perform a confirmatory factor analysis. Two hundred seven medical school faculties responded to the questionnaire. The competency clusters that were identified by factor analysis were professionalism, citizenship, leadership, and membership to an organization. Accordingly, each cluster was linked with a dimension: self, society, team (that he/she is leading), and organization (to which he/she belongs). The clusters of competencies were: professional ability, ethics/morality, self-management, self-development, and passion; public interest, networking, social participation, and active service; motivating, caring, promoting teamwork, nurturing, conflict management, directing, performance management, and systems thinking; organizational orientation, collaboration, voluntary participation, and cost-benefit orientation. This competency model that fits medical school faculties in Korea can be used to design and develop selection plans, education programs, feedback tools, diagnostic evaluation tools, and career plan support programs.

The role of poverty rate and racial distribution in the geographic clustering of breast cancer survival among older women: a geographic and multilevel analysis.

PubMed

Schootman, Mario; Jeffe, Donna B; Lian, Min; Gillanders, William E; Aft, Rebecca

2009-03-01

The authors examined disparities in survival among women aged 66 years or older in association with census-tract-level poverty rate, racial distribution, and individual-level factors, including patient-, treatment-, and tumor-related factors, utilization of medical care, and mammography use. They used linked data from the 1992-1999 Surveillance, Epidemiology, and End Results (SEER) programs, 1991-1999 Medicare claims, and the 1990 US Census. A geographic information system and advanced statistics identified areas of increased or reduced breast cancer survival and possible reasons for geographic variation in survival in 2 of the 5 SEER areas studied. In the Detroit, Michigan, area, one geographic cluster of shorter-than-expected breast cancer survival was identified (hazard ratio (HR) = 1.60). An additional area where survival was longer than expected approached statistical significance (HR = 0.4; P = 0.056). In the Atlanta, Georgia, area, one cluster of shorter- (HR = 1.81) and one cluster of longer-than-expected (HR = 0.72) breast cancer survival were identified. Stage at diagnosis and census-tract poverty (and patient's race in Atlanta) explained the geographic variation in breast cancer survival. No geographic clusters were identified in the 3 other SEER programs. Interventions to reduce late-stage breast cancer, focusing on areas of high poverty and targeting African Americans, may reduce disparities in breast cancer survival in the Detroit and Atlanta areas.

Accounting Cluster Brief. Vocational Education in Oregon.

ERIC Educational Resources Information Center

Stamps, Margaret McDonnall

This guide sets forth minimum approval criteria for accounting occupations cluster training programs in Oregon. The information in the guide is intended for use by district-level curriculum planners, teachers, regional coordinators, or state education department staff involved with new program development or revisions of existing programs. The…

A Clustering-Based Approach to Enriching Code Foraging Environment.

PubMed

Niu, Nan; Jin, Xiaoyu; Niu, Zhendong; Cheng, Jing-Ru C; Li, Ling; Kataev, Mikhail Yu

2016-09-01

Developers often spend valuable time navigating and seeking relevant code in software maintenance. Currently, there is a lack of theoretical foundations to guide tool design and evaluation to best shape the code base to developers. This paper contributes a unified code navigation theory in light of the optimal food-foraging principles. We further develop a novel framework for automatically assessing the foraging mechanisms in the context of program investigation. We use the framework to examine to what extent the clustering of software entities affects code foraging. Our quantitative analysis of long-lived open-source projects suggests that clustering enriches the software environment and improves foraging efficiency. Our qualitative inquiry reveals concrete insights into real developer's behavior. Our research opens the avenue toward building a new set of ecologically valid code navigation tools.

SHIPS: Spectral Hierarchical Clustering for the Inference of Population Structure in Genetic Studies

PubMed Central

Bouaziz, Matthieu; Paccard, Caroline; Guedj, Mickael; Ambroise, Christophe

2012-01-01

Inferring the structure of populations has many applications for genetic research. In addition to providing information for evolutionary studies, it can be used to account for the bias induced by population stratification in association studies. To this end, many algorithms have been proposed to cluster individuals into genetically homogeneous sub-populations. The parametric algorithms, such as Structure, are very popular but their underlying complexity and their high computational cost led to the development of faster parametric alternatives such as Admixture. Alternatives to these methods are the non-parametric approaches. Among this category, AWclust has proven efficient but fails to properly identify population structure for complex datasets. We present in this article a new clustering algorithm called Spectral Hierarchical clustering for the Inference of Population Structure (SHIPS), based on a divisive hierarchical clustering strategy, allowing a progressive investigation of population structure. This method takes genetic data as input to cluster individuals into homogeneous sub-populations and with the use of the gap statistic estimates the optimal number of such sub-populations. SHIPS was applied to a set of simulated discrete and admixed datasets and to real SNP datasets, that are data from the HapMap and Pan-Asian SNP consortium. The programs Structure, Admixture, AWclust and PCAclust were also investigated in a comparison study. SHIPS and the parametric approach Structure were the most accurate when applied to simulated datasets both in terms of individual assignments and estimation of the correct number of clusters. The analysis of the results on the real datasets highlighted that the clusterings of SHIPS were the more consistent with the population labels or those produced by the Admixture program. The performances of SHIPS when applied to SNP data, along with its relatively low computational cost and its ease of use make this method a promising solution to infer fine-scale genetic patterns. PMID:23077494

BESIU Physical Analysis on Hadoop Platform

NASA Astrophysics Data System (ADS)

Huo, Jing; Zang, Dongsong; Lei, Xiaofeng; Li, Qiang; Sun, Gongxing

2014-06-01

In the past 20 years, computing cluster has been widely used for High Energy Physics data processing. The jobs running on the traditional cluster with a Data-to-Computing structure, have to read large volumes of data via the network to the computing nodes for analysis, thereby making the I/O latency become a bottleneck of the whole system. The new distributed computing technology based on the MapReduce programming model has many advantages, such as high concurrency, high scalability and high fault tolerance, and it can benefit us in dealing with Big Data. This paper brings the idea of using MapReduce model to do BESIII physical analysis, and presents a new data analysis system structure based on Hadoop platform, which not only greatly improve the efficiency of data analysis, but also reduces the cost of system building. Moreover, this paper establishes an event pre-selection system based on the event level metadata(TAGs) database to optimize the data analyzing procedure.

Multi-cluster processor operating only select number of clusters during each phase based on program statistic monitored at predetermined intervals

DOEpatents

Balasubramonian, Rajeev [Sandy, UT; Dwarkadas, Sandhya [Rochester, NY; Albonesi, David [Ithaca, NY

2009-02-10

In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied dynamically. At the start of each program phase, the configuration option for an interval is run to determine the optimal configuration, which is used until the next phase change is detected. The optimum instruction interval is determined by starting with a minimum interval and doubling it until a low stability factor is reached.

XMM-Subaru:Complete High Precision Study of Galaxy Clusters for Modern Cosmology

NASA Astrophysics Data System (ADS)

Zhang, Yu-Ying

2011-10-01

We request 382 ks data for 12 clusters to complete our survey of a volume-limited sample of 55 clusters. We investigated the existing data, which hints a mass dependent bias in the X-ray to weak lensing mass ratios for disturbed ones. X-ray mass proxies, e.g., Yx, show low scatter, but the best fits, particularly the slopes, of the mass-observable relations may be biased due to this mass dependence. Our program will quantify any mass/radial dependent bias based on three independent probes (X-ray/lensing/velocity dispersion) for such a volume-limited sample, and deliver definitive constraints on systematics for upcoming cluster cosmology surveys. The dataset will be a major asset for programs aiming to measure dark energy and programs adding a multi-wavelength focus to studies of cluster physics.

Cluster analysis of lowland and upland rice cultivars based on grain quality attributes

USDA-ARS?s Scientific Manuscript database

Rice is cropped in many countries all over the world and plays an important role in human nutrition as well as in agricultural economics, besides its social importance. Embrapa Rice and Beans is responsible for national rice enhancement programs and is conducting breeding projects to increase yield ...

Research Visibility. Vocational Education for Girls and Women.

ERIC Educational Resources Information Center

Law, Gordon F.

1968-01-01

Reviews of 17 studies relating to female vocational education are organized by topics: (1) "New Directions in Business Education" reports a program for scientific secretaries, the effects of interval pacing on typing skills, a task analysis of an office occupation cluster, and a 4-week preservice institute for office education teachers, (2) "Home…

Anomalous dismeter distribution shifts estimated from FIA inventories through time

Treesearch

Francis A. Roesch; Paul C. Van Deusen

2010-01-01

In the past decade, the United States Department of Agriculture Forest Service’s Forest Inventory and Analysis Program (FIA) has replaced regionally autonomous, periodic, state-wide forest inventories using various probability proportional to tree size sampling designs with a nationally consistent annual forest inventory design utilizing systematically spaced clusters...

Reading Profiles for Adults with Low-Literacy: Cluster Analysis with Power and Speeded Measures

ERIC Educational Resources Information Center

Mellard, Daryl F.; Fall, Emily; Mark, Caroline

2009-01-01

The United States' National Institute for Literacy's (NIFL) review of adult literacy instruction research recommended adult education (AE) programs assess underlying reading abilities in order to plan appropriate instruction for low-literacy learners. This study developed adult reading ability groups using measures from power tests and speeded…

7 CFR 3052.105 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... programs that share common compliance requirements. The types of clusters of programs are research and... action. Federal agency has the same meaning as the term agency in Section 551(1) of title 5, United.... The types of clusters of programs are: (i) Research and development (R&D); (ii) Student financial aid...

7 CFR 3052.105 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... programs that share common compliance requirements. The types of clusters of programs are research and... action. Federal agency has the same meaning as the term agency in Section 551(1) of title 5, United.... The types of clusters of programs are: (i) Research and development (R&D); (ii) Student financial aid...

7 CFR 3052.105 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... programs that share common compliance requirements. The types of clusters of programs are research and... action. Federal agency has the same meaning as the term agency in Section 551(1) of title 5, United.... The types of clusters of programs are: (i) Research and development (R&D); (ii) Student financial aid...

7 CFR 3052.105 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... programs that share common compliance requirements. The types of clusters of programs are research and... action. Federal agency has the same meaning as the term agency in Section 551(1) of title 5, United.... The types of clusters of programs are: (i) Research and development (R&D); (ii) Student financial aid...

7 CFR 3052.105 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... programs that share common compliance requirements. The types of clusters of programs are research and... action. Federal agency has the same meaning as the term agency in Section 551(1) of title 5, United.... The types of clusters of programs are: (i) Research and development (R&D); (ii) Student financial aid...

Service Occupations Cluster Brief. [Vocational Education in Oregon.

ERIC Educational Resources Information Center

Brock, Howard

This guide sets forth minimum approval criteria for service occupations cluster programs in Oregon. The information in the guide is intended for use by district-level curriculum planners, teachers, regional coordinators, or state education department staff involved with new program development or revisions of existing programs. The guide outlines…

Cluster-impact fusion, or beam-contaminant fusion? (abstract)a),b)

NASA Astrophysics Data System (ADS)

Lo, Daniel H.; Petrasso, Richard D.; Wenzel, Kevin W.

1992-10-01

Beuhler, Friedlander, and Friedman (BFF) reported anomalously huge D-D fusion rates while bombarding deuterated targets with (D2O)N+ clusters (N˜25-1000) accelerated to ≊325 keV [R. J. Beuhler et al., Phys. Rev. Lett. 63, 1292 (1989); R. J. Beuhler et al., J. Phys. Chem. 94, 7665 (1990)] [i.e., ≊0.3 keV lab energy for D in (D2O)100+]. However, from our analysis of BFF's fusion product spectra, we conclude that their D lab energy was ˜50 keV. Therefore, no gross anomalies exist. Also, from our analysis of the BFF beam-ranging experiments through 500 μg/cm2 of Au, we conclude that light-ion-beam contaminants (e.g., D+ of order 100 keV) have not been ruled out, and are the probable cause of their fusion reactions. This work was supported by LLNL Subcontract B116798, Department of Energy (DOE) Grant No. DE-FG02-91ER54109, DOE Magnetic Fusion Energy Technology Fellowship Program (D. H. Lo), and DOE Fusion Energy Postdoctoral Research Program (Kevin W. Wenzel).

[The attitude of German veterinarians towards farm animal welfare: results of a cluster analysis].

PubMed

Heise, Heinke; Kemper, Nicole; Theuvsen, Ludwig

2016-01-01

In recent years the issue of animal welfare in intensive livestock production systems has been subjected to increasing criticism from the broad public. Some groups in society ask for higher animal welfare standards and there is an increas- ing number of consumers who prefer meat from more animal friendly husbandry systems. An intense social debate on animal welfare has flared up in the recent past. Veterinarians are considered as experts for the assessment of animal welfare. Nevertheless they are rarely consulted in the current debate. Therefore, only little is known about their attitude towards animal welfare in livestock farming. Even for Germany, there is so far no comprehensive analysis about their atti- tudes towards animal welfare and animal welfare programs. In the present study, 433 veterinarians were questioned via an online survey. The results show that veterinarians have a very differentiated perception of the issue animal welfare. Four groups (clusters) which have different attitudes towards livestock farming, voluntary animal welfare programs, farm size and the effects of national animal welfare standards were identified.

Yellow supergiants in open clusters

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

Sowell, J.R.

1986-01-01

Superluminous giant stars (SLGs) have been reported in young globular clusters in the Large Magellanic Cloud (LMC). These stars appear to be in the post-asymptotic-giant-branch phase of evolution. This program was an investigation of galactic SLG candidates in open clusters, which are more like the LMC young globular clusters. These were chosen because luminosity, mass, and age determinations can be made for members since cluster distances and interstellar reddenings are known. Color magnitude diagrams were searched for candidates, using the same selection criteria as for SLGs in the LMC. Classification spectra were obtained of 115 program stars from McGraw-Hill Observatorymore » and of 68 stars from Cerro Tololo Inter-American Observatory Chile. These stars were visually classified on the MK system using spectral scans of standard stars taken at the respective observations. Published information was combined with this program's data for 83 stars in 30 clusters. Membership probabilities were assigned to these stars, and the clusters were analyzed according to age. It was seen that the intrinsically brightest supergiants are found in the youngest clusters. With increasing cluster age, the absolute luminosities attained by the supergiants decline. Also, it appears that the evolutionary tracks of luminosity class II stars are more similar to those of class I than of class III.« less

ETE: a python Environment for Tree Exploration.

PubMed

Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni

2010-01-13

Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org.

Genetic identification of Theobroma cacao L. trees with high Criollo ancestry in Soconusco, Chiapas, Mexico.

PubMed

Vázquez-Ovando, J A; Molina-Freaner, F; Nuñez-Farfán, J; Ovando-Medina, I; Salvador-Figueroa, M

2014-12-12

Criollo-type cacao trees are an important pool of genes with potential to be used in cacao breeding and selection programs. For that reason, we assessed the diversity and population structure of Criollo-type trees (108 cultivars with Criollo phenotypic characteristics and 10 Criollo references) using 12 simple sequence repeat (SSR) markers. Cultivars were selected from 7 demes in the Soconusco region of southern Mexico. SSRs amplified 74 alleles with an average of 3.6 alleles per population. The overall populations showed an average observed heterozygosity of 0.28, indicating heterozygote deficiency (average fixation index F = 0.50). However, moderate allelic diversity was found within populations (Shannon index for all populations I = 0.97). Bayesian method analysis determined 2 genetic clusters (K = 2) within individuals. In concordance, an assignment test grouped 37 multilocus genotypes (including 10 references) into a first cluster (Criollo), 54 into a second (presumably Amelonado), and 27 admixed individuals unassigned at the 90% threshold likely corresponding to the Trinitario genotype. This classification was supported by the principal coordinate analysis and analysis of molecular variance, which showed 12% of variation among populations (FST = 0.123, P < 0.0001). Sampled demes sites (1- 7) in the Soconusco region did not show any evidence of clustering by geographic location, and this was supported by the Mantel test (Rxy = 0.54, P = 0.120). Individuals with high Criollo lineage planted in Soconusco farms could be an important reservoir of genes for future breeding programs searching for fine, taste, flavor, and aroma cocoa.

ETE: a python Environment for Tree Exploration

PubMed Central

2010-01-01

Background Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Results Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. Conclusions ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org. PMID:20070885

County Clustering for the California 4-H Youth Development Program: Impacts and Lessons Learned

ERIC Educational Resources Information Center

Subramaniam, Aarti; Dasher, Harry Steve; Young, Jane Chin

2012-01-01

In response to budgetary constraints, a new staffing structure, the Pilot Leadership Plan, was proposed for California's 4-H Youth Development Program. County clusters were formed, each led by a coordinator. The plan was piloted for 2 years to provide insight into how county clustering could support Extension staff to increase and enhance program…

Evaluation of genetic diversity in jackfruit (Artocarpus heterophyllus Lam.) based on amplified fragment length polymorphism markers.

PubMed

Shyamalamma, S; Chandra, S B C; Hegde, M; Naryanswamy, P

2008-07-22

Artocarpus heterophyllus Lam., commonly called jackfruit, is a medium-sized evergreen tree that bears high yields of the largest known edible fruit. Yet, it has been little explored commercially due to wide variation in fruit quality. The genetic diversity and genetic relatedness of 50 jackfruit accessions were studied using amplified fragment length polymorphism markers. Of 16 primer pairs evaluated, eight were selected for screening of genotypes based on the number and quality of polymorphic fragments produced. These primer combinations produced 5976 bands, 1267 (22%) of which were polymorphic. Among the jackfruit accessions, the similarity coefficient ranged from 0.137 to 0.978; the accessions also shared a large number of monomorphic fragments (78%). Cluster analysis and principal component analysis grouped all jackfruit genotypes into three major clusters. Cluster I included the genotypes grown in a jackfruit region of Karnataka, called Tamaka, with very dry conditions; cluster II contained the genotypes collected from locations having medium to heavy rainfall in Karnataka; cluster III grouped the genotypes in distant locations with different environmental conditions. Strong coincidence of these amplified fragment length polymorphism-based groupings with geographical localities as well as morphological characters was observed. We found moderate genetic diversity in these jackfruit accessions. This information should be useful for tree breeding programs, as part of our effort to popularize jackfruit as a commercial crop.

NASA Space Science and a Search for Ram-Pressure Stripping in the Hydra I Cluster

NASA Technical Reports Server (NTRS)

Brown, Beth

2005-01-01

The NASA Goddard Space Flight Center's Sciences and Exploration Directorate seeks to expand scientific knowledge through observational and theoretical research in the study of the Earth-Sun system, the solar system and the origins of life, and the birth and evolution of the universe. This talk will discuss some of the cutting-edge space science research being conducted at Goddard. In addition, I will discuss my research on ram-pressure stripping in cluster elliptical galaxies. Ram-pressure stripping is a method by which hot interstellar gas can be removed from a galaxy moving through a group or cluster of galaxies. Indirect evidence of ram-pressure stripping includes lowered X-ray brightness in a galaxy due to less X-ray emitting gas remaining in the galaxy. Here we present the initial results of our program to determine whether cluster elliptical galaxies have lower hot gas masses than their counterparts in less rich environments. This test requires the use of the high-resolution imaging of the Chandra Observatory and we present our analysis of the galaxies in the nearby cluster Hydra I.

The Africa Yoga Project: A Participant-Driven Concept Map of Kenyan Teachers' Reported Experiences.

PubMed

Klein, Jessalyn E; Cook-Cottone, Catherine; Giambrone, Carla

2015-01-01

The Africa Yoga Project (AYP) trains and funds Kenyans to teach community yoga classes. Preliminary research with a small sample of AYP teachers suggested the program had a positive impact. This study used concept mapping to explore the experiences of a larger sample. Participants brainstormed statements about how practicing and/or teaching yoga changed them. They sorted statements into self-defined piles and rated them in terms of perceived importance. Multidimensional scaling (MDS) of sort data calculated statement coordinates wherein each statement is placed in proximity to other statements as a function of how frequently statements are sorted together by participants. These results are then and mapped in a two-dimensional space. Hierarchical cluster analysis (HCA) of these data identified clusters (i.e., concepts) among statements. Cluster average importance ratings gave the concept map depth and indicated concept importance. Bridging analysis and researchers' conceptual understanding of yoga literature facilitated HCA interpretive decisions. Of 72 AYP teachers, 52 and 48 teachers participated in brainstorming and sorting/rating activities, respectively. Teachers brainstormed 93 statements about how they had changed. The resultant MDS statement map had adequate validity (stress value = .29). HCA created a 12-cluster solution with the following concepts of perceived change: Identity as a Yoga Teacher; Prosocial Development; Existential Possibility; Genuine Positive Regard; Value and Respect for Others (highest importance); Presence, Acceptance, and Competence; Service and Trust; Non-judgment and Emotion Regulation (lowest importance); Engagement and Connection; Interpersonal Effectiveness; Psychosocial Functioning; and Physical Competence and Security. Teachers perceived the AYP as facilitating change across physical, mental, and spiritual domains. Additional research is needed to quantify and compare this change to other health promotion program outcomes.

AFLP-Based Analysis of Genetic Diversity, Population Structure, and Relationships with Agronomic Traits in Rice Germplasm from North Region of Iran and World Core Germplasm Set.

PubMed

Sorkheh, Karim; Masaeli, Mohammad; Chaleshtori, Maryam Hosseini; Adugna, Asfaw; Ercisli, Sezai

2016-04-01

Analysis of the genetic diversity and population structure of crops is very important for use in breeding programs and for genetic resources conservation. We analyzed the genetic diversity and population structure of 47 rice genotypes from diverse origins using amplified fragment length polymorphism (AFLP) markers and morphological characters. The 47 genotypes, which were composed of four populations: Iranian native varieties, Iranian improved varieties, International Rice Research Institute (IRRI) rice varieties, and world rice collections, were analyzed using ten primer combinations. A total of 221 scorable bands were produced with an average of 22.1 alleles per pair of primers, of which 120 (54.30%) were polymorphic. The polymorphism information content (PIC) values varied from 0.32 to 0.41 with an average of 0.35. The high percentage of polymorphic bands (%PB) was found to be 64.71 and the resolving power (R p) collections were 63.36. UPGMA clustering based on numerical data from AFLP patterns clustered all 47 genotypes into three large groups. The genetic similarity between individuals ranged from 0.54 to 0.94 with an average of 0.74. Population genetic tree showed that Iranian native cultivars formed far distant cluster from the other populations, which may indicate that these varieties had minimal genetic change over time. Analysis of molecular variance (AMOVA) revealed that the largest proportion of the variation (84%) to be within populations showing the inbreeding nature of rice. Therefore, Iranian native varieties (landraces) may have unique genes, which can be used for future breeding programs and there is a need to conserve this unique diversity. Furthermore, crossing of Iranian genotypes with the genetically distant genotypes in the other three populations may result in useful combinations, which can be used as varieties and/or lines for future rice breeding programs.

Time-Series Monitoring of Open Star Clusters

NASA Astrophysics Data System (ADS)

Hojaev, A. S.; Semakov, D. G.

2006-08-01

Star clusters especially a compact ones (with diameter of few to ten arcmin) are suitable targets to search of light variability for orchestera of stars by means of ordinary Casegrain telescope plus CCD system. A special patroling with short time-fixed exposures and mmag accuracy could be used also to study of stellar oscillation for group of stars simultaneously. The last can be carried out both separately from one site and within international campaigns. Detection and study of optical variability of X-ray sources including X-ray binaries with compact objects might be as a result of a long-term monitoring of such clusters as well. We present the program of open star clusters monitoring with Zeiss 1 meter RCC telescope of Maidanak observatory has been recently automated. In combination with quite good seeing at this observatory (see, e.g., Sarazin, M. 1999, URL http://www.eso.org/gen-fac/pubs/astclim/) the automatic telescope equipped with large-format (2KX2K) CCD camera AP-10 available will allow to collect homogenious time-series for analysis. We already started this program in 2001 and had a set of patrol observations with Zeiss 0.6 meter telescope and AP-10 camera in 2003. 7 compact open clusters in the Milky Way (NGC 7801, King1, King 13, King18, King20, Berkeley 55, IC 4996) have been monitored for stellar variability and some results of photometry will be presented. A few interesting variables were discovered and dozens were suspected for variability to the moment in these clusters for the first time. We have made steps to join the Whole-Earth Telescope effort in its future campaigns.

Cognitive profiles in euthymic patients with bipolar disorders: results from the FACE-BD cohort.

PubMed

Roux, Paul; Raust, Aurélie; Cannavo, Anne Sophie; Aubin, Valérie; Aouizerate, Bruno; Azorin, Jean-Michel; Bellivier, Frank; Belzeaux, Raoul; Bougerol, Thierry; Cussac, Iréna; Courtet, Philippe; Etain, Bruno; Gard, Sébastien; Job, Sophie; Kahn, Jean-Pierre; Leboyer, Marion; Olié, Emilie; Henry, Chantal; Passerieux, Christine

2017-03-01

Although cognitive deficits are a well-established feature of bipolar disorders (BD), even during periods of euthymia, little is known about cognitive phenotype heterogeneity among patients with BD. We investigated neuropsychological performance in 258 euthymic patients with BD recruited via the French network of expert centers for BD. We used a test battery assessing six domains of cognition. Hierarchical cluster analysis of the cross-sectional data was used to determine the optimal number of subgroups and to assign each patient to a specific cognitive cluster. Subsequently, subjects from each cluster were compared on demographic, clinical functioning, and pharmacological variables. A four-cluster solution was identified. The global cognitive performance was above normal in one cluster and below normal in another. The other two clusters had a near-normal cognitive performance, with above and below average verbal memory, respectively. Among the four clusters, significant differences were observed in estimated intelligence quotient and social functioning, which were lower for the low cognitive performers compared to the high cognitive performers. These results confirm the existence of several distinct cognitive profiles in BD. Identification of these profiles may help to develop profile-specific cognitive remediation programs, which might improve functioning in BD. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Career Exploration Program: A Cluster Approach. Publication No. 0057.

ERIC Educational Resources Information Center

Ansbro, William; And Others

Based on the occupational clusters designated by the Department of Health, Education and Welfare, this curriculum guide presents a career exploration program for junior high and middle school students. The program, presented in eighty-minute weekly sessions, is designed as an alternative activity in which students can elect to explore a wide…

Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Haoqiang; anMey, Dieter; Hatay, Ferhat F.

2003-01-01

With the advent of parallel hardware and software technologies users are faced with the challenge to choose a programming paradigm best suited for the underlying computer architecture. With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors (SMP), parallel programming techniques have evolved to support parallelism beyond a single level. Which programming paradigm is the best will depend on the nature of the given problem, the hardware architecture, and the available software. In this study we will compare different programming paradigms for the parallelization of a selected benchmark application on a cluster of SMP nodes. We compare the timings of different implementations of the same CFD benchmark application employing the same numerical algorithm on a cluster of Sun Fire SMP nodes. The rest of the paper is structured as follows: In section 2 we briefly discuss the programming models under consideration. We describe our compute platform in section 3. The different implementations of our benchmark code are described in section 4 and the performance results are presented in section 5. We conclude our study in section 6.

Analysis of indoor air pollutants checklist using environmetric technique for health risk assessment of sick building complaint in nonindustrial workplace

PubMed Central

Syazwan, AI; Rafee, B Mohd; Juahir, Hafizan; Azman, AZF; Nizar, AM; Izwyn, Z; Syahidatussyakirah, K; Muhaimin, AA; Yunos, MA Syafiq; Anita, AR; Hanafiah, J Muhamad; Shaharuddin, MS; Ibthisham, A Mohd; Hasmadi, I Mohd; Azhar, MN Mohamad; Azizan, HS; Zulfadhli, I; Othman, J; Rozalini, M; Kamarul, FT

2012-01-01

Purpose To analyze and characterize a multidisciplinary, integrated indoor air quality checklist for evaluating the health risk of building occupants in a nonindustrial workplace setting. Design A cross-sectional study based on a participatory occupational health program conducted by the National Institute of Occupational Safety and Health (Malaysia) and Universiti Putra Malaysia. Method A modified version of the indoor environmental checklist published by the Department of Occupational Health and Safety, based on the literature and discussion with occupational health and safety professionals, was used in the evaluation process. Summated scores were given according to the cluster analysis and principal component analysis in the characterization of risk. Environmetric techniques was used to classify the risk of variables in the checklist. Identification of the possible source of item pollutants was also evaluated from a semiquantitative approach. Result Hierarchical agglomerative cluster analysis resulted in the grouping of factorial components into three clusters (high complaint, moderate-high complaint, moderate complaint), which were further analyzed by discriminant analysis. From this, 15 major variables that influence indoor air quality were determined. Principal component analysis of each cluster revealed that the main factors influencing the high complaint group were fungal-related problems, chemical indoor dispersion, detergent, renovation, thermal comfort, and location of fresh air intake. The moderate-high complaint group showed significant high loading on ventilation, air filters, and smoking-related activities. The moderate complaint group showed high loading on dampness, odor, and thermal comfort. Conclusion This semiquantitative assessment, which graded risk from low to high based on the intensity of the problem, shows promising and reliable results. It should be used as an important tool in the preliminary assessment of indoor air quality and as a categorizing method for further IAQ investigations and complaints procedures. PMID:23055779

Analysis of indoor air pollutants checklist using environmetric technique for health risk assessment of sick building complaint in nonindustrial workplace.

PubMed

Syazwan, Ai; Rafee, B Mohd; Juahir, Hafizan; Azman, Azf; Nizar, Am; Izwyn, Z; Syahidatussyakirah, K; Muhaimin, Aa; Yunos, Ma Syafiq; Anita, Ar; Hanafiah, J Muhamad; Shaharuddin, Ms; Ibthisham, A Mohd; Hasmadi, I Mohd; Azhar, Mn Mohamad; Azizan, Hs; Zulfadhli, I; Othman, J; Rozalini, M; Kamarul, Ft

2012-01-01

To analyze and characterize a multidisciplinary, integrated indoor air quality checklist for evaluating the health risk of building occupants in a nonindustrial workplace setting. A cross-sectional study based on a participatory occupational health program conducted by the National Institute of Occupational Safety and Health (Malaysia) and Universiti Putra Malaysia. A modified version of the indoor environmental checklist published by the Department of Occupational Health and Safety, based on the literature and discussion with occupational health and safety professionals, was used in the evaluation process. Summated scores were given according to the cluster analysis and principal component analysis in the characterization of risk. Environmetric techniques was used to classify the risk of variables in the checklist. Identification of the possible source of item pollutants was also evaluated from a semiquantitative approach. Hierarchical agglomerative cluster analysis resulted in the grouping of factorial components into three clusters (high complaint, moderate-high complaint, moderate complaint), which were further analyzed by discriminant analysis. From this, 15 major variables that influence indoor air quality were determined. Principal component analysis of each cluster revealed that the main factors influencing the high complaint group were fungal-related problems, chemical indoor dispersion, detergent, renovation, thermal comfort, and location of fresh air intake. The moderate-high complaint group showed significant high loading on ventilation, air filters, and smoking-related activities. The moderate complaint group showed high loading on dampness, odor, and thermal comfort. This semiquantitative assessment, which graded risk from low to high based on the intensity of the problem, shows promising and reliable results. It should be used as an important tool in the preliminary assessment of indoor air quality and as a categorizing method for further IAQ investigations and complaints procedures.

Creating a Parallel Version of VisIt for Microsoft Windows

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

Whitlock, B J; Biagas, K S; Rawson, P L

2011-12-07

VisIt is a popular, free interactive parallel visualization and analysis tool for scientific data. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images or movies for presentations. VisIt was designed from the ground up to work on many scales of computers from modest desktops up to massively parallel clusters. VisIt is comprised of a set of cooperating programs. All programs can be run locally or in client/server mode in which some run locally and some run remotely on compute clusters. The VisIt program most able to harness today's computing powermore » is the VisIt compute engine. The compute engine is responsible for reading simulation data from disk, processing it, and sending results or images back to the VisIt viewer program. In a parallel environment, the compute engine runs several processes, coordinating using the Message Passing Interface (MPI) library. Each MPI process reads some subset of the scientific data and filters the data in various ways to create useful visualizations. By using MPI, VisIt has been able to scale well into the thousands of processors on large computers such as dawn and graph at LLNL. The advent of multicore CPU's has made parallelism the 'new' way to achieve increasing performance. With today's computers having at least 2 cores and in many cases up to 8 and beyond, it is more important than ever to deploy parallel software that can use that computing power not only on clusters but also on the desktop. We have created a parallel version of VisIt for Windows that uses Microsoft's MPI implementation (MSMPI) to process data in parallel on the Windows desktop as well as on a Windows HPC cluster running Microsoft Windows Server 2008. Initial desktop parallel support for Windows was deployed in VisIt 2.4.0. Windows HPC cluster support has been completed and will appear in the VisIt 2.5.0 release. We plan to continue supporting parallel VisIt on Windows so our users will be able to take full advantage of their multicore resources.« less

A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis

DOE PAGES

Pimentel, Harold; Parra, Marilyn; Gee, Sherry L.; ...

2015-11-03

Differentiating erythroblasts execute a dynamic alternative splicing program shown here to include extensive and diverse intron retention (IR) events. Cluster analysis revealed hundreds of developmentallydynamic introns that exhibit increased IR in mature erythroblasts, and are enriched in functions related to RNA processing such as SF3B1 spliceosomal factor. Distinct, developmentally-stable IR clusters are enriched in metal-ion binding functions and include mitoferrin genes SLC25A37 and SLC25A28 that are critical for iron homeostasis. Some IR transcripts are abundant, e.g. comprising ~50% of highly-expressed SLC25A37 and SF3B1 transcripts in late erythroblasts, and thereby limiting functional mRNA levels. IR transcripts tested were predominantly nuclearlocalized. Splicemore » site strength correlated with IR among stable but not dynamic intron clusters, indicating distinct regulation of dynamically-increased IR in late erythroblasts. Retained introns were preferentially associated with alternative exons with premature termination codons (PTCs). High IR was observed in disease-causing genes including SF3B1 and the RNA binding protein FUS. Comparative studies demonstrated that the intron retention program in erythroblasts shares features with other tissues but ultimately is unique to erythropoiesis. Finally, we conclude that IR is a multi-dimensional set of processes that post-transcriptionally regulate diverse gene groups during normal erythropoiesis, misregulation of which could be responsible for human disease.« less

Diversity and genetic stability in banana genotypes in a breeding program using inter simple sequence repeats (ISSR) markers.

PubMed

Silva, A V C; Nascimento, A L S; Vitória, M F; Rabbani, A R C; Soares, A N R; Lédo, A S

2017-02-23

Banana (Musa spp) is a fruit species frequently cultivated and consumed worldwide. Molecular markers are important for estimating genetic diversity in germplasm and between genotypes in breeding programs. The objective of this study was to analyze the genetic diversity of 21 banana genotypes (FHIA 23, PA42-44, Maçã, Pacovan Ken, Bucaneiro, YB42-47, Grand Naine, Tropical, FHIA 18, PA94-01, YB42-17, Enxerto, Japira, Pacovã, Prata-Anã, Maravilha, PV79-34, Caipira, Princesa, Garantida, and Thap Maeo), by using inter-simple sequence repeat (ISSR) markers. Material was generated from the banana breeding program of Embrapa Cassava & Fruits and evaluated at Embrapa Coastal Tablelands. The 12 primers used in this study generated 97.5% polymorphism. Four clusters were identified among the different genotypes studied, and the sum of the first two principal components was 48.91%. From the Unweighted Pair Group Method using Arithmetic averages (UPGMA) dendrogram, it was possible to identify two main clusters and subclusters. Two genotypes (Garantida and Thap Maeo) remained isolated from the others, both in the UPGMA clustering and in the principal cordinate analysis (PCoA). Using ISSR markers, we could analyze the genetic diversity of the studied material and state that these markers were efficient at detecting sufficient polymorphism to estimate the genetic variability in banana genotypes.

A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis

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

Pimentel, Harold; Parra, Marilyn; Gee, Sherry L.

Differentiating erythroblasts execute a dynamic alternative splicing program shown here to include extensive and diverse intron retention (IR) events. Cluster analysis revealed hundreds of developmentallydynamic introns that exhibit increased IR in mature erythroblasts, and are enriched in functions related to RNA processing such as SF3B1 spliceosomal factor. Distinct, developmentally-stable IR clusters are enriched in metal-ion binding functions and include mitoferrin genes SLC25A37 and SLC25A28 that are critical for iron homeostasis. Some IR transcripts are abundant, e.g. comprising ~50% of highly-expressed SLC25A37 and SF3B1 transcripts in late erythroblasts, and thereby limiting functional mRNA levels. IR transcripts tested were predominantly nuclearlocalized. Splicemore » site strength correlated with IR among stable but not dynamic intron clusters, indicating distinct regulation of dynamically-increased IR in late erythroblasts. Retained introns were preferentially associated with alternative exons with premature termination codons (PTCs). High IR was observed in disease-causing genes including SF3B1 and the RNA binding protein FUS. Comparative studies demonstrated that the intron retention program in erythroblasts shares features with other tissues but ultimately is unique to erythropoiesis. Finally, we conclude that IR is a multi-dimensional set of processes that post-transcriptionally regulate diverse gene groups during normal erythropoiesis, misregulation of which could be responsible for human disease.« less

US Household Food Shopping Patterns: Dynamic Shifts since 2000 and Socioeconomic Predictors

PubMed Central

Stern, Dalia; Robinson, Whitney R; Ng, Shu Wen; Gordon-Larsen, Penny; Popkin, Barry M

2016-01-01

Under the assumption that differential food access might underlie nutritional disparities, programs and policies have focused on the need to build supermarkets in underserved areas, in an effort to improve dietary quality. However, there is limited evidence about which types of stores different income and race-ethnic households use. We used cross-sectional cluster analysis to derive shopping patterns from US households’ volume food purchases (Nielsen Homescan) by store from 2000–2012. Multinomial logistic regression identified household SES characteristics that were associated with shopping patterns in 2012. We found three shopping patterns: primary-grocery, primary-mass-merchandise, and combination cluster. In 2012, we found no income/race-ethnic differences for grocery cluster membership. However, low-income non-Hispanic blacks (vs. non-Hispanic whites) had a significantly lower probability of belonging to the mass-merchandise cluster. These varied shopping patterns must be considered in future policy initiatives. Further, it is important to continue studying the complex rationale for people’s food shopping patterns. PMID:26526241

Multi-fault clustering and diagnosis of gear system mined by spectrum entropy clustering based on higher order cumulants

NASA Astrophysics Data System (ADS)

Shao, Renping; Li, Jing; Hu, Wentao; Dong, Feifei

2013-02-01

Higher order cumulants (HOC) is a new kind of modern signal analysis of theory and technology. Spectrum entropy clustering (SEC) is a data mining method of statistics, extracting useful characteristics from a mass of nonlinear and non-stationary data. Following a discussion on the characteristics of HOC theory and SEC method in this paper, the study of signal processing techniques and the unique merits of nonlinear coupling characteristic analysis in processing random and non-stationary signals are introduced. Also, a new clustering analysis and diagnosis method is proposed for detecting multi-damage on gear by introducing the combination of HOC and SEC into the damage-detection and diagnosis of the gear system. The noise is restrained by HOC and by extracting coupling features and separating the characteristic signal at different speeds and frequency bands. Under such circumstances, the weak signal characteristics in the system are emphasized and the characteristic of multi-fault is extracted. Adopting a data-mining method of SEC conducts an analysis and diagnosis at various running states, such as the speed of 300 r/min, 900 r/min, 1200 r/min, and 1500 r/min of the following six signals: no-fault, short crack-fault in tooth root, long crack-fault in tooth root, short crack-fault in pitch circle, long crack-fault in pitch circle, and wear-fault on tooth. Research shows that this combined method of detection and diagnosis can also identify the degree of damage of some faults. On this basis, the virtual instrument of the gear system which detects damage and diagnoses faults is developed by combining with advantages of MATLAB and VC++, employing component object module technology, adopting mixed programming methods, and calling the program transformed from an *.m file under VC++. This software system possesses functions of collecting and introducing vibration signals of gear, analyzing and processing signals, extracting features, visualizing graphics, detecting and diagnosing faults, detecting and monitoring, etc. Finally, the results of testing and verifying show that the developed system can effectively be used to detect and diagnose faults in an actual operating gear transmission system.

Multi-fault clustering and diagnosis of gear system mined by spectrum entropy clustering based on higher order cumulants.

PubMed

Shao, Renping; Li, Jing; Hu, Wentao; Dong, Feifei

2013-02-01

Higher order cumulants (HOC) is a new kind of modern signal analysis of theory and technology. Spectrum entropy clustering (SEC) is a data mining method of statistics, extracting useful characteristics from a mass of nonlinear and non-stationary data. Following a discussion on the characteristics of HOC theory and SEC method in this paper, the study of signal processing techniques and the unique merits of nonlinear coupling characteristic analysis in processing random and non-stationary signals are introduced. Also, a new clustering analysis and diagnosis method is proposed for detecting multi-damage on gear by introducing the combination of HOC and SEC into the damage-detection and diagnosis of the gear system. The noise is restrained by HOC and by extracting coupling features and separating the characteristic signal at different speeds and frequency bands. Under such circumstances, the weak signal characteristics in the system are emphasized and the characteristic of multi-fault is extracted. Adopting a data-mining method of SEC conducts an analysis and diagnosis at various running states, such as the speed of 300 r/min, 900 r/min, 1200 r/min, and 1500 r/min of the following six signals: no-fault, short crack-fault in tooth root, long crack-fault in tooth root, short crack-fault in pitch circle, long crack-fault in pitch circle, and wear-fault on tooth. Research shows that this combined method of detection and diagnosis can also identify the degree of damage of some faults. On this basis, the virtual instrument of the gear system which detects damage and diagnoses faults is developed by combining with advantages of MATLAB and VC++, employing component object module technology, adopting mixed programming methods, and calling the program transformed from an *.m file under VC++. This software system possesses functions of collecting and introducing vibration signals of gear, analyzing and processing signals, extracting features, visualizing graphics, detecting and diagnosing faults, detecting and monitoring, etc. Finally, the results of testing and verifying show that the developed system can effectively be used to detect and diagnose faults in an actual operating gear transmission system.

Low Cost, Scalable Proteomics Data Analysis Using Amazon's Cloud Computing Services and Open Source Search Algorithms

PubMed Central

Halligan, Brian D.; Geiger, Joey F.; Vallejos, Andrew K.; Greene, Andrew S.; Twigger, Simon N.

2009-01-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step by step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center website (http://proteomics.mcw.edu/vipdac). PMID:19358578

Analysis of human tissues by total reflection X-ray fluorescence. Application of chemometrics for diagnostic cancer recognition

NASA Astrophysics Data System (ADS)

Benninghoff, L.; von Czarnowski, D.; Denkhaus, E.; Lemke, K.

1997-07-01

For the determination of trace element distributions of more than 20 elements in malignant and normal tissues of the human colon, tissue samples (approx. 400 mg wet weight) were digested with 3 ml of nitric acid (sub-boiled quality) by use of an autoclave system. The accuracy of measurements has been investigated by using certified materials. The analytical results were evaluated by using a spreadsheet program to give an overview of the element distribution in cancerous samples and in normal colon tissues. A further application, cluster analysis of the analytical results, was introduced to demonstrate the possibility of classification for cancer diagnosis. To confirm the results of cluster analysis, multivariate three-way principal component analysis was performed. Additionally, microtome frozen sections (10 μm) were prepared from the same tissue samples to compare the analytical results, i.e. the mass fractions of elements, according to the preparation method and to exclude systematic errors depending on the inhomogeneity of the tissues.

Polyphasic characterization of Gluconacetobacter diazotrophicus isolates obtained from different sugarcane varieties

PubMed Central

Guedes, Helma V.; dos Santos, Samuel T.; Perin, Liamara; Teixeira, Kátia R. dos S.; Reis, Veronica M.; Baldani, José I.

2008-01-01

A polyphasic approach was applied to characterize 35 G. diazotrophicus isolates obtained from sugarcane varieties cultivated in Brazil. The isolates were analyzed by phenotypic (use of different carbon sources) and genotypic tests (ARDRA and RISA–RFLP techniques). Variability among the isolates was observed in relation to the carbon source use preference. Glucose and sucrose were used by all isolates in contrast to myo-inositol, galactose and ribose that were not metabolized. The results of the analysis showed the presence of two groups clustered at 68% of similarity. The genetic distance was higher when RISA-RFLP analysis was used. Analysis of 16S rDNA sequences from isolates showed that all of them belonged to the G. diazotrophicus species. Neither effect of the plant part nor sugarcane variety was observed during the cluster analysis. The observed metabolic and genetic variability will be helpful during the strain selection studies for sugarcane inoculation in association with sugarcane breeding programs. PMID:24031296

Low cost, scalable proteomics data analysis using Amazon's cloud computing services and open source search algorithms.

PubMed

Halligan, Brian D; Geiger, Joey F; Vallejos, Andrew K; Greene, Andrew S; Twigger, Simon N

2009-06-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).

Characterizing the spatial distribution of brown marmorated stink bug, Halyomorpha halys Stål (Hemiptera: Pentatomidae), populations in peach orchards

PubMed Central

Hahn, Noel G.

2017-01-01

Geospatial analyses were used to investigate the spatial distribution of populations of Halyomorpha halys, an important invasive agricultural pest in mid-Atlantic peach orchards. This spatial analysis will improve efficiency by allowing growers and farm managers to predict insect arrangement and target management strategies. Data on the presence of H. halys were collected from five peach orchards at four farms in New Jersey from 2012–2014 located in different land-use contexts. A point pattern analysis, using Ripley’s K function, was used to describe clustering of H. halys. In addition, the clustering of damage indicative of H. halys feeding was described. With low populations early in the growing season, H. halys did not exhibit signs of clustering in the orchards at most distances. At sites with low populations throughout the season, clustering was not apparent. However, later in the season, high infestation levels led to more evident clustering of H. halys. Damage, although present throughout the entire orchard, was found at low levels. When looking at trees with greater than 10% fruit damage, damage was shown to cluster in orchards. The Moran’s I statistic showed that spatial autocorrelation of H. halys was present within the orchards on the August sample dates, in relation to both populations density and levels of damage. Kriging the abundance of H. halys and the severity of damage to peaches revealed that the estimations of these are generally found in the same region of the orchards. This information on the clustering of H. halys populations will be useful to help predict presence of insects for use in management or scouting programs. PMID:28362797

Mississippi Curriculum Framework for Machine Tool Operation/Machine Shop and Tool and Die Making Technology Cluster (Program CIP: 48.0507--Tool and Die Maker/Technologist) (Program CIP: 48.0503--Machine Shop Assistant). Postsecondary Programs.

ERIC Educational Resources Information Center

Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for the course sequences in the machine tool operation/machine tool and tool and die making technology programs cluster. Presented in the introductory section are a framework of courses and programs, description of the…

Satisfaction Clustering Analysis of Distance Education Computer Programming Students: A Sample of Karadeniz Technical University

ERIC Educational Resources Information Center

Ozyurt, Hacer

2014-01-01

In line with recently developing technology, distant education systems based on information technologies are started to be commonly used within higher education. Students' satisfaction is one of the vital aspects in order to maintain distant education efficiently and achieving its goal. As a matter of the fact, previous studies proved that student…

Drug Prevention by Increasing Self-Esteem: Influence of Teaching Approaches and Gender on Different Consumption Groups

ERIC Educational Resources Information Center

Heyne, Thomas; Bogner, Franz X.

2013-01-01

Our study focused on an educational intervention designed to increase the self-esteem of low-achieving eighth graders. The intervention was a substance-specific life skills program built upon teacher-centered versus student-centered teaching methods. A cluster analysis identified four consumption groups prior to the intervention: A potentially…

An Evaluation of Second Step: What Are the Benefits for Youth With and Without Disabilities?

ERIC Educational Resources Information Center

Sullivan, Terri N.; Sutherland, Kevin S.; Farrell, Albert D.; Taylor, Katherine A.

2015-01-01

The impact of a school-based violence prevention program, Second Step, on peer victimization and aggression, and emotion regulation was evaluated among 457 sixth graders. A cluster-randomized trial was conducted with classrooms randomly assigned to intervention (n = 14) or control (n = 14) conditions. A repeated measures analysis of covariance on…

Citrullinemia type I, classical variant. Identification of ASS-p~G390R (c.1168G>A) mutation in families of a limited geographic area of Argentina: a possible population cluster.

PubMed

Laróvere, Laura E; Angaroni, Celia J; Antonozzi, Sandra L; Bezard, Miriam B; Shimohama, Mariko; de Kremer, Raquel Dodelson

2009-07-01

Citrullinemia type I (CTLN1) is an urea cycle defect caused by mutations in the argininosuccinate synthetase gene. We report the first identification in Argentina of patients with CTLN1 in a limited geographic area. Molecular analysis in patient/relatives included PCR, sequencing and restriction enzyme assay. The studied families showed the same mutation: ASS~p.G390R, associated with the early-onset/severe phenotype. We postulate a possible population cluster. A program to know the carrier frequency in that population is in progress.

[Poverty profile regarding households participating in a food assistance program].

PubMed

Álvarez-Uribe, Martha C; Aguirre-Acevedo, Daniel C

2012-06-01

This study was aimed at establishing subgroups having specific socioeconomic characteristics by using latent class analysis as a method for segmenting target population members of the MANA-ICBF supplementary food program in the Antioquia department of Colombia and determine their differences regarding poverty and health conditions in efficiently addressing pertinent resources, programs and policies. The target population consisted of 200,000 children and their households involved in the MANA food assistance program; a representative sample by region was used. Latent class analysis was used, as were the expectation-maximization and Newton Raphson algorithms for identifying the appropriate number of classes. The final model classified the households into four clusters or classes, differing according to well-defined socio-demographic conditions affecting children's health. Some homes had a greater depth of poverty, therefore lowering the families' quality of life and affecting the health of the children in this age group.

Attributes of quality programs in universities in developing countries: Case studies of two private universities in Ecuador and beyond

NASA Astrophysics Data System (ADS)

Uriguen, Monica I.

This study sought to identify the key attributes of high-quality programs with an eye toward helping developing countries such as Ecuador advance program quality. The dissertation is divided into five chapters: (1) introduction to high-quality programs; (2) literature review of attributes of high-quality programs; (3) grounded theory method (including interviews with 60 individuals) used to identify program attributes that enhance student learning; (4) findings; and (5) conclusions and recommendations. Following are the five clusters and thirteen attributes of high-quality programs that I identified: Cluster One: Highly Qualified Participants: (1) Highly Qualified Faculty, and (2) Highly Qualified Students; Cluster Two: Learning-Centered Cultures: (3) Shared Program Direction Focused on Learning, (4) Real-World Learning Experiences, (5) Reading-Centered Culture, and (6) Supportive and Risk-Taking Environment; Cluster Three: Interactive Teaching and Learning: (7) Integrative learning: Theory with Practice, Self with Subject, and (8) Exclusive Tutoring and Mentoring; Cluster Four: Connected Program Requirements: (9) Planned Breadth and Depth Course Work, and (10) Tangible Products; and Cluster Five: Adequate Resources: (11) Support for Students, (12) Support for Faculty, and (13) Support for Campus Infrastructure. The study was guided by Haworth and Conrad's (1997) "Engagement Theory of High-Quality Programs." Eleven of the attributes of high-quality programs are closely connected to Haworth and Conrad's theory and the other two attributes---real-world learning experiences and a reading-centered culture---make the signature theoretical contributions of the study. Real-world learning experiences encourage the active involvement of stakeholders in designing curricula with real-world learning experiences. The second attribute---a reading-centered culture---has never before been identified in the literature. There are four key differences between Haworth and Conrad's theory and the theory developed in this study. This study identified four attributes that are highly important in Ecuador and, possibly, other developing countries: highly-qualified faculty, highly-qualified students, reading-centered cultures, and real-world learning experiences. If Latin American universities implement the recommendations proposed in the study, particularly Ecuadorian universities, there is a foundation for envisioning a better future for Ecuadorian universities.

Dropping Out or Keeping Up? Early-Dropouts, Late-Dropouts, and Maintainers Differ in Their Automatic Evaluations of Exercise Already before a 14-Week Exercise Course.

PubMed

Antoniewicz, Franziska; Brand, Ralf

2016-01-01

The aim of this study was to examine how automatic evaluations of exercising (AEE) varied according to adherence to an exercise program. Eighty-eight participants (24.98 years ± 6.88; 51.1% female) completed a Brief-Implicit Association Task assessing their AEE, positive and negative associations to exercising at the beginning of a 3-month exercise program. Attendance data were collected for all participants and used in a cluster analysis of adherence patterns. Three different adherence patterns (52 maintainers, 16 early dropouts, 20 late dropouts; 40.91% overall dropouts) were detected using cluster analyses. Participants from these three clusters differed significantly with regard to their positive and negative associations to exercising before the first course meeting ([Formula: see text] = 0.07). Discriminant function analyses revealed that positive associations to exercising was a particularly good discriminating factor. This is the first study to provide evidence of the differential impact of positive and negative associations on exercise behavior over the medium term. The findings contribute to theoretical understanding of evaluative processes from a dual-process perspective and may provide a basis for targeted interventions.

Environmental, health and economic conditions perceived by 50 rural communities in Bangladesh.

PubMed

Ohtsuka, Ryutaro; Inaoka, Tsukasa; Moji, Kazuhiko; Karim, Enamul; Yoshinaga, Mari

2002-12-01

For randomly selected 50 villages in Bangladesh, an interview survey with a structured questionnaire was conducted to reveal their perception on the environmental, health and economic conditions at present and for the past 10-year change. The eight following items were analyzed in this paper: air pollution and water pollution, which represent environmental conditions with close relation to health conditions, soil degradation and deforestation, which represent environmental conditions with close relation to economic conditions, epidemic diseases and malnutrition, which represent health conditions, and poverty and jobless, which represent economic conditions. Among the 50 villages, deforestation was most frequently perceived serious at present and worsened in the past 10 years. Of the remaining seven items, those related to economic conditions were more seriously perceived than those related to health and environmental conditions. As revealed by the cluster analysis for the inter-item relations, epidemic diseases, which formed the same cluster with the environmental items, were recognized less serious whereas malnutrition, which formed the same cluster with the economic items, was recognized more serious. These findings are useful not only for rural development programs but also for mitigation programs toward health and environmental hazards in Bangladesh.

Dropping Out or Keeping Up? Early-Dropouts, Late-Dropouts, and Maintainers Differ in Their Automatic Evaluations of Exercise Already before a 14-Week Exercise Course

PubMed Central

Antoniewicz, Franziska; Brand, Ralf

2016-01-01

The aim of this study was to examine how automatic evaluations of exercising (AEE) varied according to adherence to an exercise program. Eighty-eight participants (24.98 years ± 6.88; 51.1% female) completed a Brief-Implicit Association Task assessing their AEE, positive and negative associations to exercising at the beginning of a 3-month exercise program. Attendance data were collected for all participants and used in a cluster analysis of adherence patterns. Three different adherence patterns (52 maintainers, 16 early dropouts, 20 late dropouts; 40.91% overall dropouts) were detected using cluster analyses. Participants from these three clusters differed significantly with regard to their positive and negative associations to exercising before the first course meeting (ηp2 = 0.07). Discriminant function analyses revealed that positive associations to exercising was a particularly good discriminating factor. This is the first study to provide evidence of the differential impact of positive and negative associations on exercise behavior over the medium term. The findings contribute to theoretical understanding of evaluative processes from a dual-process perspective and may provide a basis for targeted interventions. PMID:27313559

Electrician Cluster, STEP Training Plan. Skills Training and Education Program.

ERIC Educational Resources Information Center

Alabama State Dept. of Postsecondary Education, Montgomery.

This guide is a training plan for the electrical skills cluster of the Skills Training and Education Program (STEP), an open-entry, open-exit program funded by the Job Training Partnership Act (JTPA). In the STEP training plan, each task has its own lesson plan guide. This manual contains the following information: definitions, instructions for…

Clerical Cluster, STEP Training Plan. Skills Training and Education Program.

ERIC Educational Resources Information Center

Alabama State Dept. of Postsecondary Education, Montgomery.

This guide is a training plan for the clerical skills cluster of the Skills Training and Education Program (STEP), an open-entry, open-exit program funded by the Job Training Partnership Act (JTPA). In the STEP training plan, each task has its own lesson plan guide. This manual contains the following information: definitions, instructions for…

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale.

PubMed

Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto

2010-03-09

An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps.

ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

PubMed Central

Metsalu, Tauno; Vilo, Jaak

2015-01-01

The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/. PMID:25969447

RELICS: Reionization Lensing Cluster Survey - Discovering Brightly Lensed Distant Galaxies for JWST

NASA Astrophysics Data System (ADS)

Coe, Dan; Bradley, Larry; Salmon, Brett; Avila, Roberto J.; Ogaz, Sara; Bradac, Marusa; Huang, Kuang-Han; Strait, Victoria; Hoag, Austin; Sharon, Keren q.; Cerny, Catherine; Paterno-Mahler, Rachel; Johnson, Traci Lin; Mahler, Guillaume; Zitrin, Adi; Sendra Server, Irene; Acebron, Ana; Cibirka, Nathália; Rodney, Steven; Strolger, Louis; Riess, Adam; Dawson, William; Jones, Christine; Andrade-Santos, Felipe; Lovisari, Lorenzo; Czakon, Nicole; Umetsu, Keiichi; Trenti, Michele; Vulcani, Benedetta; Carrasco, Daniela; Livermore, Rachael; Stark, Daniel P.; Mainali, Ramesh; Frye, Brenda; Oesch, Pascal; Lam, Daniel; Toft, Sune; Ryan, Russell; Peterson, Avery; Past, Matthew; Kikuchihara, Shotaro; Ouchi, Masami; Oguri, Masamune

2018-01-01

The Reionization Lensing Cluster Survey (RELICS) Hubble Treasury Program has completed observations of 41 massive galaxy clusters with 188 orbits of HST ACS and WFC3/IR imaging and 390 hours of Spitzer IRAC imaging. This poster presents an overview of the program and data releases. Reduced images, catalogs, and lens models for all clusters are now available on MAST. RELICS is studying the clusters, supernovae, and lensed high-redshift galaxies. A companion poster presents our high-redshift results: over 300 lensed z ~ 6 - 10 candidates, including some of the brightest known at these redshifts (Salmon et al. 2018). These will be excellent targets for detailed follow-up study in JWST Cycle 1 GO proposals.

Effects of a Stretching Development and Maintenance Program on Hamstring Extensibility in Schoolchildren: A Cluster-Randomized Controlled Trial

PubMed Central

Mayorga-Vega, Daniel; Merino-Marban, Rafael; Manzano-Lagunas, Jorge; Blanco, Humberto; Viciana, Jesús

2016-01-01

The main purpose of the present study was to examine the effects of a physical education-based stretching development and maintenance program on hamstring extensibility in schoolchildren. A sample of 150 schoolchildren aged 7-10 years old from a primary school participated in the present study (140 participants were finally included). The six classes balanced by grade were cluster randomly assigned to the experimental group 1 (n = 51), experimental group 2 (n = 51) or control group (n = 49) (i.e., a cluster randomized controlled trial design was used). During the physical education classes, the students from the experimental groups 1 and 2 performed a four-minute stretching program twice a week for nine weeks (first semester). Then, after a five-week period of detraining coinciding with the Christmas holidays, the students from the experimental groups 1 and 2 completed another stretching program twice a week for eleven weeks (second semester). The students from the experimental group 1 continued performing the stretching program for four minutes while those from the experimental group 2 completed a flexibility maintenance program for only one minute. The results of the two-way analysis of variance showed that the physical education-based stretching development program significantly improved the students’ hamstring extensibility (p < 0.001), as well as that these gains obtained remained after the stretching maintenance program (p < 0.001). Additionally, statistically significant differences between the two experimental groups were not found (p > 0.05). After a short-term stretching development program, a physical education-based stretching maintenance program of only one-minute sessions twice a week is effective in maintaining hamstring extensibility among schoolchildren. This knowledge could help and guide teachers to design programs that allow a feasible and effective development and maintenance of students’ flexibility in the physical education setting. Key points A physical education-based stretching maintenance program of only one-minute sessions twice a week is effective in maintaining hamstring extensibility among schoolchildren. A four-minute maintenance program shows similar effects that the one-minute maintenance program on hamstring extensibility among schoolchildren. Physical education teachers and other practitioners could carry out one-minute programs for a feasible and effective maintenance of students’ flexibility. PMID:26957928

BioMake: a GNU make-compatible utility for declarative workflow management.

PubMed

Holmes, Ian H; Mungall, Christopher J

2017-11-01

The Unix 'make' program is widely used in bioinformatics pipelines, but suffers from problems that limit its application to large analysis datasets. These include reliance on file modification times to determine whether a target is stale, lack of support for parallel execution on clusters, and restricted flexibility to extend the underlying logic program. We present BioMake, a make-like utility that is compatible with most features of GNU Make and adds support for popular cluster-based job-queue engines, MD5 signatures as an alternative to timestamps, and logic programming extensions in Prolog. BioMake is available for MacOSX and Linux systems from https://github.com/evoldoers/biomake under the BSD3 license. The only dependency is SWI-Prolog (version 7), available from http://www.swi-prolog.org/. ihholmes + biomake@gmail.com or cmungall + biomake@gmail.com. Feature table comparing BioMake to similar tools. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Spike detection, characterization, and discrimination using feature analysis software written in LabVIEW.

PubMed

Stewart, C M; Newlands, S D; Perachio, A A

2004-12-01

Rapid and accurate discrimination of single units from extracellular recordings is a fundamental process for the analysis and interpretation of electrophysiological recordings. We present an algorithm that performs detection, characterization, discrimination, and analysis of action potentials from extracellular recording sessions. The program was entirely written in LabVIEW (National Instruments), and requires no external hardware devices or a priori information about action potential shapes. Waveform events are detected by scanning the digital record for voltages that exceed a user-adjustable trigger. Detected events are characterized to determine nine different time and voltage levels for each event. Various algebraic combinations of these waveform features are used as axis choices for 2-D Cartesian plots of events. The user selects axis choices that generate distinct clusters. Multiple clusters may be defined as action potentials by manually generating boundaries of arbitrary shape. Events defined as action potentials are validated by visual inspection of overlain waveforms. Stimulus-response relationships may be identified by selecting any recorded channel for comparison to continuous and average cycle histograms of binned unit data. The algorithm includes novel aspects of feature analysis and acquisition, including higher acquisition rates for electrophysiological data compared to other channels. The program confirms that electrophysiological data may be discriminated with high-speed and efficiency using algebraic combinations of waveform features derived from high-speed digital records.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Demographic characterization and spatial cluster analysis of human Salmonella 1,4,[5],12:i:- infections in Portugal: A 10year study.

PubMed

Seixas, R; Nunes, T; Machado, J; Tavares, L; Owen, S P; Bernardo, F; Oliveira, M

Salmonella 1,4,[5],12:i:- is presently considered one of the major serovars responsible for human salmonellosis worldwide. Due to its recent emergence, studies assessing the demographic characterization and spatial epidemiology of salmonellosis 1,4,[5],12:i:- at local- or country-level are lacking. In this study, a analysis was conducted over a 10year period, from 2000 to the first quarter of 2011 at the Portuguese National Laboratory in Portugal mainland, with a total of 215 Salmonella 1,4,[5],12:i:- serotyped isolates obtained from human infections by a passive surveillance system. Data regarding source, year and month of sampling, gender, age, district and municipality of the patients were registered. Descriptive statistical analysis and a spatial scan statistic combined with a geographic information system were employed to characterize the epidemiology and identify spatial clusters. Results showed that most districts have reports of Salmonella 1,4,[5],12:i:-, with a higher number of cases at the Portuguese coastland, including districts like Porto (n=60, 27.9%), Lisboa (n=29, 13.5%) and Aveiro (n=28, 13.0%). An increased incidence was observed in the period from 2004 to 2011 and most infections occurred during May and October. Spatial analysis revealed 4 clusters of higher than expected infection rates. Three were located in the north of Portugal, including two at the coastland (Cluster 1 [RR=3.58, p≤0.001] and 4 [RR=10.42 p≤0.230]), and one at the countryside (Cluster 3 [RR=17.76, p≤0.001]). A larger cluster was detected involving the center and south of Portugal (Cluster 2 [RR=4.85, p≤0.001]). The present study was elaborated with data provided by a passive surveillance system, which may originate an underestimation of disease burden. However, this is the first report describing the incidence and the distribution of areas with higher risk of infection in Portugal, revealing that Salmonella 1,4,[5],12:i:- displayed a significant geographic clustering and these areas should be further evaluated to identify risk factors in order to establish prevention programs. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Discovery and Characterization of Gravitationally Lensed X-ray Sources in the CLASH Sample

NASA Astrophysics Data System (ADS)

Pasha, Imad; Van Weeren, Reinout J.; Santos, Felipe A.

2017-01-01

We present the discovery of ~20 gravitationally lensed X-ray sources in the Cluster Lensing And Supernova survey with Hubble (CLASH) survey, a sample of massive clusters of galaxies between z ~ 0.2-0.9 observed with the Hubble Space Telescope (HST). By combining CLASH imaging with Chandra X-ray Observatory observations of the same clusters, we select those sources in the HST images which are gravitationally lensed X-ray sources behind the clusters. Of those discovered sources, we determine various properties including source redshifts and magnifications, as well as performing X-ray spectral fits to determine source fluxes and luminosities. Prior to this study, only four lensed X-ray sources behind clusters have been found, thus to the best of our knowledge, our program is the first to systematically categorize lensed X-ray sources behind galaxy clusters.This work was supported by the SAO REU program, which is funded in part by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant no. 1262851, and by the Smithsonian Institution.

First Results on the Cluster Galaxy Population from the Subaru Hyper Suprime-Cam Survey. III. Brightest Cluster Galaxies, Stellar Mass Distribution, and Active Galaxies

NASA Astrophysics Data System (ADS)

Lin, Yen-Ting; Hsieh, Bau-Ching; Lin, Sheng-Chieh; Oguri, Masamune; Chen, Kai-Feng; Tanaka, Masayuki; Chiu, I.-Non; Huang, Song; Kodama, Tadayuki; Leauthaud, Alexie; More, Surhud; Nishizawa, Atsushi J.; Bundy, Kevin; Lin, Lihwai; Miyazaki, Satoshi

2017-12-01

The unprecedented depth and area surveyed by the Subaru Strategic Program with the Hyper Suprime-Cam (HSC-SSP) have enabled us to construct and publish the largest distant cluster sample out to z∼ 1 to date. In this exploratory study of cluster galaxy evolution from z = 1 to z = 0.3, we investigate the stellar mass assembly history of brightest cluster galaxies (BCGs), the evolution of stellar mass and luminosity distributions, the stellar mass surface density profile, as well as the population of radio galaxies. Our analysis is the first high-redshift application of the top N richest cluster selection, which is shown to allow us to trace the cluster galaxy evolution faithfully. Over the 230 deg2 area of the current HSC-SSP footprint, selecting the top 100 clusters in each of the four redshift bins allows us to observe the buildup of galaxy population in descendants of clusters whose z≈ 1 mass is about 2× {10}14 {M}ȯ . Our stellar mass is derived from a machine-learning algorithm, which is found to be unbiased and accurate with respect to the COSMOS data. We find very mild stellar mass growth in BCGs (about 35% between z = 1 and 0.3), and no evidence for evolution in both the total stellar mass–cluster mass correlation and the shape of the stellar mass surface density profile. We also present the first measurement of the radio luminosity distribution in clusters out to z∼ 1, and show hints of changes in the dominant accretion mode powering the cluster radio galaxies at z∼ 0.8.

Microbial community analysis using MEGAN.

PubMed

Huson, Daniel H; Weber, Nico

2013-01-01

Metagenomics, the study of microbes in the environment using DNA sequencing, depends upon dedicated software tools for processing and analyzing very large sequencing datasets. One such tool is MEGAN (MEtaGenome ANalyzer), which can be used to interactively analyze and compare metagenomic and metatranscriptomic data, both taxonomically and functionally. To perform a taxonomic analysis, the program places the reads onto the NCBI taxonomy, while functional analysis is performed by mapping reads to the SEED, COG, and KEGG classifications. Samples can be compared taxonomically and functionally, using a wide range of different charting and visualization techniques. PCoA analysis and clustering methods allow high-level comparison of large numbers of samples. Different attributes of the samples can be captured and used within analysis. The program supports various input formats for loading data and can export analysis results in different text-based and graphical formats. The program is designed to work with very large samples containing many millions of reads. It is written in Java and installers for the three major computer operating systems are available from http://www-ab.informatik.uni-tuebingen.de. © 2013 Elsevier Inc. All rights reserved.

Measuring User Compliance and Cost Effectiveness of Safe Drinking Water Programs: A Cluster-Randomized Study of Household Ultraviolet Disinfection in Rural Mexico.

PubMed

Reygadas, Fermín; Gruber, Joshua S; Dreizler, Lindsay; Nelson, Kara L; Ray, Isha

2018-03-01

Low adoption and compliance levels for household water treatment and safe storage (HWTS) technologies have made it challenging for these systems to achieve measurable health benefits in the developing world. User compliance remains an inconsistently defined and poorly understood feature of HWTS programs. In this article, we develop a comprehensive approach to understanding HWTS compliance. First, our Safe Drinking Water Compliance Framework disaggregates and measures the components of compliance from initial adoption of the HWTS to exclusive consumption of treated water. We apply this framework to an ultraviolet (UV)-based safe water system in a cluster-randomized controlled trial in rural Mexico. Second, we evaluate a no-frills (or "Basic") variant of the program as well as an improved (or "Enhanced") variant, to test if subtle changes in the user interface of HWTS programs could improve compliance. Finally, we perform a full-cost analysis of both variants to assess their cost effectiveness (CE) in achieving compliance. We define "compliance" strictly as the habit of consuming safe water. We find that compliance was significantly higher in the groups where the UV program variants were rolled out than in the control groups. The Enhanced variant performed better immediately postintervention than the Basic, but compliance (and thus CE) degraded with time such that no effective difference remained between the two versions of the program.

Massive and Distant Clusters of WISE Survey (MaDCoWS)

NASA Astrophysics Data System (ADS)

Brodwin, Mark; MaDCoWS Collaboration

2018-06-01

The Massive and Distant Clusters of WISE Survey (MaDCoWS) is a comprehensive program to detect and characterize the most massive galaxy clusters in the Universe at z ~ 1, and is the only all-sky survey sensitive to galaxy clusters at this epoch. The foundation for this program is data from the NASA Wide-field Infrared Survey Explorer (WISE). The primary goal is to study the evolution of massive galaxies in the most overdense environments at z > 1 when star formation and AGN activity may be peaking in these structures. Spitzer follow-up imaging of 2000 MaDCoWS clusters has allowed us to select the richest and/or most distant clusters for detailed study. To date we have spectroscopically confirmed over 35 MaDCoWS clusters, spanning a wide range of masses (2-11 x 10^14 Msun), out to z = 1.5. This includes the discovery of the most massive z > 1.15 cluster found to date, as well as a cluster at z = 1.23 that is lensing a z = 2.22 supernova Ia. Multiwavelength follow-up observations of these distant clusters, currently underway, will permit several novel studies of galaxy evolution in rich cluster environments at z > 1.

Alcohol-Specific Parenting within a Cluster-Randomized Effectiveness Trial of a Swedish Primary Prevention Program

ERIC Educational Resources Information Center

Strandberg, Anna K.; Bodin, Maria C.

2011-01-01

Purpose: Within the framework of an ongoing cluster-randomized effectiveness trial of a parental prevention program, the aim of the present study is to investigate attitudes towards under-age drinking and use of program components, i.e. alcohol-specific parenting behaviors, in parents who did and did not take part in the programme.…

A Microswitch-Cluster Program to Foster Adaptive Responses and Head Control in Students with Multiple Disabilities: Replication and Validation Assessment

ERIC Educational Resources Information Center

Lancioni, Giulio E.; Singh, Nirbhay N.; O'Reilly, Mark F.; Sigafoos, Jeff; Oliva, Doretta; Gatti, Michela; Manfredi, Francesco; Megna, Gianfranco; La Martire, Maria L.; Tota, Alessia; Smaldone, Angela; Groeneweg, Jop

2008-01-01

A program relying on microswitch clusters (i.e., combinations of microswitches) and preferred stimuli was recently developed to foster adaptive responses and head control in persons with multiple disabilities. In the last version of this program, preferred stimuli (a) are scheduled for adaptive responses occurring in combination with head control…

Message Passing vs. Shared Address Space on a Cluster of SMPs

NASA Technical Reports Server (NTRS)

Shan, Hongzhang; Singh, Jaswinder Pal; Oliker, Leonid; Biswas, Rupak

2000-01-01

The convergence of scalable computer architectures using clusters of PCs (or PC-SMPs) with commodity networking has become an attractive platform for high end scientific computing. Currently, message-passing and shared address space (SAS) are the two leading programming paradigms for these systems. Message-passing has been standardized with MPI, and is the most common and mature programming approach. However message-passing code development can be extremely difficult, especially for irregular structured computations. SAS offers substantial ease of programming, but may suffer from performance limitations due to poor spatial locality, and high protocol overhead. In this paper, we compare the performance of and programming effort, required for six applications under both programming models on a 32 CPU PC-SMP cluster. Our application suite consists of codes that typically do not exhibit high efficiency under shared memory programming. due to their high communication to computation ratios and complex communication patterns. Results indicate that SAS can achieve about half the parallel efficiency of MPI for most of our applications: however, on certain classes of problems SAS performance is competitive with MPI. We also present new algorithms for improving the PC cluster performance of MPI collective operations.

Using Cluster Analysis to Examine Husband-Wife Decision Making

ERIC Educational Resources Information Center

Bonds-Raacke, Jennifer M.

2006-01-01

Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

Observations and analysis of the contact binary H 235 in the open cluster NGC 752

NASA Astrophysics Data System (ADS)

Milone, E. F.; Stagg, C. R.; Sugars, B. A.; McVean, J. R.; Schiller, S. J.; Kallrath, J.; Bradstreet, D. H.

1995-01-01

The short-period variable star Heinemann 235 in the open cluster NGC 752 has been identified as a contact binary with a variable period of about 0 d 4118. BVRI light curves and radial velocity curves have been obtained and analyzed with enhanced versions of the Wilson-Devinney light curve program. We find that the system is best modeled as an A-type W UMa system, with a contact parameter of 0.21 +/- 0.11. The masses of the components are found to be 1.18 +/- 0.17 and 0.24 +/- 0.04 solar mass, with bolometric magnitudes of 3.60 +/- 0.10 and 5.21 +/- 0.13, for the hotter (6500 K, assumed) and cooler (6421 K) components, respectively, with Delta T=79 +/- 25 K. The distance to the binary is established at 381 +/- 17 pc. H235 becomes one of a relatively small number of open-cluster contact systems with detailed light curve analysis for which an age may be estimated. If it is coeval with the cluster, and with the detached eclipsing and double-lined spectroscopic binary H219 (DS And), H235 is approximately 1.8 Gyr old, and may provide a fiducial point for the evolution of contact systems. There is, however, evidence for dynamical evolution of the cluster and the likelihood of weak interactions over the age of the binary precludes the determination of its initial state with certainty.

NASA System-Level Design, Analysis and Simulation Tools Research on NextGen

NASA Technical Reports Server (NTRS)

Bardina, Jorge

2011-01-01

A review of the research accomplished in 2009 in the System-Level Design, Analysis and Simulation Tools (SLDAST) of the NASA's Airspace Systems Program is presented. This research thrust focuses on the integrated system-level assessment of component level innovations, concepts and technologies of the Next Generation Air Traffic System (NextGen) under research in the ASP program to enable the development of revolutionary improvements and modernization of the National Airspace System. The review includes the accomplishments on baseline research and the advancements on design studies and system-level assessment, including the cluster analysis as an annualization standard of the air traffic in the U.S. National Airspace, and the ACES-Air MIDAS integration for human-in-the-loop analyzes within the NAS air traffic simulation.

A Study on Regional Frequency Analysis using Artificial Neural Network - the Sumjin River Basin

NASA Astrophysics Data System (ADS)

Jeong, C.; Ahn, J.; Ahn, H.; Heo, J. H.

2017-12-01

Regional frequency analysis means to make up for shortcomings in the at-site frequency analysis which is about a lack of sample size through the regional concept. Regional rainfall quantile depends on the identification of hydrologically homogeneous regions, hence the regional classification based on hydrological homogeneous assumption is very important. For regional clustering about rainfall, multidimensional variables and factors related geographical features and meteorological figure are considered such as mean annual precipitation, number of days with precipitation in a year and average maximum daily precipitation in a month. Self-Organizing Feature Map method which is one of the artificial neural network algorithm in the unsupervised learning techniques solves N-dimensional and nonlinear problems and be shown results simply as a data visualization technique. In this study, for the Sumjin river basin in South Korea, cluster analysis was performed based on SOM method using high-dimensional geographical features and meteorological factor as input data. then, for the results, in order to evaluate the homogeneity of regions, the L-moment based discordancy and heterogeneity measures were used. Rainfall quantiles were estimated as the index flood method which is one of regional rainfall frequency analysis. Clustering analysis using SOM method and the consequential variation in rainfall quantile were analyzed. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

ICM: a web server for integrated clustering of multi-dimensional biomedical data.

PubMed

He, Song; He, Haochen; Xu, Wenjian; Huang, Xin; Jiang, Shuai; Li, Fei; He, Fuchu; Bo, Xiaochen

2016-07-08

Large-scale efforts for parallel acquisition of multi-omics profiling continue to generate extensive amounts of multi-dimensional biomedical data. Thus, integrated clustering of multiple types of omics data is essential for developing individual-based treatments and precision medicine. However, while rapid progress has been made, methods for integrated clustering are lacking an intuitive web interface that facilitates the biomedical researchers without sufficient programming skills. Here, we present a web tool, named Integrated Clustering of Multi-dimensional biomedical data (ICM), that provides an interface from which to fuse, cluster and visualize multi-dimensional biomedical data and knowledge. With ICM, users can explore the heterogeneity of a disease or a biological process by identifying subgroups of patients. The results obtained can then be interactively modified by using an intuitive user interface. Researchers can also exchange the results from ICM with collaborators via a web link containing a Project ID number that will directly pull up the analysis results being shared. ICM also support incremental clustering that allows users to add new sample data into the data of a previous study to obtain a clustering result. Currently, the ICM web server is available with no login requirement and at no cost at http://biotech.bmi.ac.cn/icm/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Tri-Laboratory Linux Capacity Cluster 2007 SOW

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

Seager, M

2007-03-22

The Advanced Simulation and Computing (ASC) Program (formerly know as Accelerated Strategic Computing Initiative, ASCI) has led the world in capability computing for the last ten years. Capability computing is defined as a world-class platform (in the Top10 of the Top500.org list) with scientific simulations running at scale on the platform. Example systems are ASCI Red, Blue-Pacific, Blue-Mountain, White, Q, RedStorm, and Purple. ASC applications have scaled to multiple thousands of CPUs and accomplished a long list of mission milestones on these ASC capability platforms. However, the computing demands of the ASC and Stockpile Stewardship programs also include a vastmore » number of smaller scale runs for day-to-day simulations. Indeed, every 'hero' capability run requires many hundreds to thousands of much smaller runs in preparation and post processing activities. In addition, there are many aspects of the Stockpile Stewardship Program (SSP) that can be directly accomplished with these so-called 'capacity' calculations. The need for capacity is now so great within the program that it is increasingly difficult to allocate the computer resources required by the larger capability runs. To rectify the current 'capacity' computing resource shortfall, the ASC program has allocated a large portion of the overall ASC platforms budget to 'capacity' systems. In addition, within the next five to ten years the Life Extension Programs (LEPs) for major nuclear weapons systems must be accomplished. These LEPs and other SSP programmatic elements will further drive the need for capacity calculations and hence 'capacity' systems as well as future ASC capability calculations on 'capability' systems. To respond to this new workload analysis, the ASC program will be making a large sustained strategic investment in these capacity systems over the next ten years, starting with the United States Government Fiscal Year 2007 (GFY07). However, given the growing need for 'capability' systems as well, the budget demands are extreme and new, more cost effective ways of fielding these systems must be developed. This Tri-Laboratory Linux Capacity Cluster (TLCC) procurement represents the ASC first investment vehicle in these capacity systems. It also represents a new strategy for quickly building, fielding and integrating many Linux clusters of various sizes into classified and unclassified production service through a concept of Scalable Units (SU). The programmatic objective is to dramatically reduce the overall Total Cost of Ownership (TCO) of these 'capacity' systems relative to the best practices in Linux Cluster deployments today. This objective only makes sense in the context of these systems quickly becoming very robust and useful production clusters under the crushing load that will be inflicted on them by the ASC and SSP scientific simulation capacity workload.« less

Illinois Occupational Skill Standards: Telecommunications Technician Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for workforce preparation program providers, details the Illinois Occupational Skill Standards for programs preparing students for employment in the telecommunications technician occupational cluster. The document begins with a brief overview of the Illinois perspective on occupational skills standards…

VEGF-Induced Expression of miR-17–92 Cluster in Endothelial Cells Is Mediated by ERK/ELK1 Activation and Regulates Angiogenesis

PubMed Central

Chamorro-Jorganes, Aránzazu; Lee, Monica Y.; Araldi, Elisa; Landskroner-Eiger, Shira; Fernández-Fuertes, Marta; Sahraei, Mahnaz; Quiles del Rey, Maria; van Solingen, Coen; Yu, Jun; Fernández-Hernando, Carlos; Sessa, William C.

2016-01-01

Rationale: Several lines of evidence indicate that the regulation of microRNA (miRNA) levels by different stimuli may contribute to the modulation of stimulus-induced responses. The miR-17–92 cluster has been linked to tumor development and angiogenesis, but its role in vascular endothelial growth factor–induced endothelial cell (EC) functions is unclear and its regulation is unknown. Objective: The purpose of this study was to elucidate the mechanism by which VEGF regulates the expression of miR-17–92 cluster in ECs and determine its contribution to the regulation of endothelial angiogenic functions, both in vitro and in vivo. This was done by analyzing the effect of postnatal inactivation of miR-17–92 cluster in the endothelium (miR-17–92 iEC-KO mice) on developmental retinal angiogenesis, VEGF-induced ear angiogenesis, and tumor angiogenesis. Methods and Results: Here, we show that Erk/Elk1 activation on VEGF stimulation of ECs is responsible for Elk-1-mediated transcription activation (chromatin immunoprecipitation analysis) of the miR-17–92 cluster. Furthermore, we demonstrate that VEGF-mediated upregulation of the miR-17–92 cluster in vitro is necessary for EC proliferation and angiogenic sprouting. Finally, we provide genetic evidence that miR-17–92 iEC-KO mice have blunted physiological retinal angiogenesis during development and diminished VEGF-induced ear angiogenesis and tumor angiogenesis. Computational analysis and rescue experiments show that PTEN (phosphatase and tensin homolog) is a target of the miR-17–92 cluster and is a crucial mediator of miR-17-92–induced EC proliferation. However, the angiogenic transcriptional program is reduced when miR-17–92 is inhibited. Conclusions: Taken together, our results indicate that VEGF-induced miR-17–92 cluster expression contributes to the angiogenic switch of ECs and participates in the regulation of angiogenesis. PMID:26472816

VizieR Online Data Catalog: Hogg 16 peculiar stars (Cariddi+, 2018)

NASA Astrophysics Data System (ADS)

Cariddi, S.; Azatyan, N. M.; Kurfurst, P.; Stofanova, L.; Netopil, M.; Paunzen, E.; Pintado, O. I.; Aidelman, Y. J.

2017-07-01

The photometric observations of Hogg 16 were performed on 2004 June 15, with the EFOSC2 instrument, installed on the 3.6m telescope at ESO - La Silla within the program 073.C-0144(A), and the target field was centred on the main concentration of stars in the cluster area (J2000 RA=13:29:18, DE=-61:12:00). The field-of-view is about 5.2'x5.2', and the 2x2 binning mode results in a resolution of 0.31"/pixel. Thus, we cover almost the complete cluster area if adopting a diameter of 6' as listed in the updated open cluster catalogue by Dias et al. (2002, version 3.5, Cat. B/ocl). We used a Δa filter set with the following characteristics: g1 (λc=5007Å, FWHM=126Å, TP=78%), g2 (5199, 95, 68), and y (5466, 108, 70). We have investigated 150 stars in the area of the young open cluster Hogg 16 using the Delta-a photometric system. We have performed a membership analysis and identified several chemically peculiar cluster stars. (1 data file).

VizieR Online Data Catalog: GLASS. IV. Lensing cluster Abell 2744 (Wang+, 2015)

NASA Astrophysics Data System (ADS)

Wang, X.; Hoag, A.; Huang, K.-H.; Treu, T.; Bradac, M.; Schmidt, K. B.; Brammer, G. B.; Vulcani, B.; Jones, T. A.; Ryan, R. E. Jr; Amorin, R.; Castellano, M.; Fontana, A.; Merlin, E.; Trenti, M.

2016-02-01

The two position angles (P.A.s) of Grism Lens-Amplified Survey from Space (GLASS) data analyzed in this study were taken on 2014 August 22 and 23 (P.A.=135) and 2014 October 24 and 25 (P.A.=233), respectively. The Hubble Frontier Fields initiative (HFF, P.I. Lotz) is a Director's Discretionary Time legacy program with HST devoting 840 orbits of HST time to acquire optical ACS and NIR WFC3 imaging of six of the strongest lensing galaxy clusters on the sky. All six HFF clusters are included in the GLASS sample. The Spitzer Frontier Fields program (P.I. Soifer) is a Director's Discretionary Time program that images all six strong lensing galaxy clusters targeted by the HFF in both warm IRAC channels (3.6 and 4.5um). (2 data files).

Telescope Scientist on the Advanced X-ray Astrophysics Observatory

NASA Technical Reports Server (NTRS)

Smith, Carl M. (Technical Monitor); VanSpeybroeck, Leon; Tananbaum, Harvey D.

2004-01-01

In this period, the Chandra X-ray Observatory continued to perform exceptionally well, with many scientific observations and spectacular results. The HRMA performance continues to be essentially identical to that predicted from ground calibration data. The Telescope Scientist Team has improved the mirror model to provide a more accurate description to the Chandra observers, enabling them to reduce the systematic errors and uncertainties in their data reduction. There also has been good progress in the scientific program. Using the Telescope Scientist GTO time, we carried out an extensive Chandra program to observe distant clusters of galaxies. The goals of this program were to use clusters to derive cosmological constraints and to investigate the physics and evolution of clusters. A total of 71 clusters were observed with ACIS-I; the last observations were completed in December 2003.

Cluster Matrices for Health Occupations. Education for Employment Task Lists.

ERIC Educational Resources Information Center

Lathrop, Janice

These cluster matrices provide duties and tasks that form the basis of instructional content for secondary, postsecondary, and adult training programs for health occupations. The eight clusters (and the job titles included in each cluster) are as follows: (1) dental assisting (dental assistant); (2) dental laboratory technology (dental laboratory…

Cluster Matarices for Industrial Occupations. Education for Employment Task Lists.

ERIC Educational Resources Information Center

Dimmlich, David

These cluster matrices provide duties and tasks that form the basis of instructional content for secondary, postsecondary, and adult training programs industrial health occupations. The 14 clusters (and the job titles included in each cluster) are as follows: (1) construction (bricklayer, carpenter, building maintenance worker, electrician,…

Investigating the usefulness of a cluster-based trend analysis to detect visual field progression in patients with open-angle glaucoma.

PubMed

Aoki, Shuichiro; Murata, Hiroshi; Fujino, Yuri; Matsuura, Masato; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Hirasawa, Kazunori; Shoji, Nobuyuki; Asaoka, Ryo

2017-12-01

To investigate the usefulness of the Octopus (Haag-Streit) EyeSuite's cluster trend analysis in glaucoma. Ten visual fields (VFs) with the Humphrey Field Analyzer (Carl Zeiss Meditec), spanning 7.7 years on average were obtained from 728 eyes of 475 primary open angle glaucoma patients. Mean total deviation (mTD) trend analysis and EyeSuite's cluster trend analysis were performed on various series of VFs (from 1st to 10th: VF1-10 to 6th to 10th: VF6-10). The results of the cluster-based trend analysis, based on different lengths of VF series, were compared against mTD trend analysis. Cluster-based trend analysis and mTD trend analysis results were significantly associated in all clusters and with all lengths of VF series. Between 21.2% and 45.9% (depending on VF series length and location) of clusters were deemed to progress when the mTD trend analysis suggested no progression. On the other hand, 4.8% of eyes were observed to progress using the mTD trend analysis when cluster trend analysis suggested no progression in any two (or more) clusters. Whole field trend analysis can miss local VF progression. Cluster trend analysis appears as robust as mTD trend analysis and useful to assess both sectorial and whole field progression. Cluster-based trend analyses, in particular the definition of two or more progressing cluster, may help clinicians to detect glaucomatous progression in a timelier manner than using a whole field trend analysis, without significantly compromising specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Genome-wide SNP discovery and population structure analysis in pepper (Capsicum annuum) using genotyping by sequencing.

PubMed

Taranto, F; D'Agostino, N; Greco, B; Cardi, T; Tripodi, P

2016-11-21

Knowledge on population structure and genetic diversity in vegetable crops is essential for association mapping studies and genomic selection. Genotyping by sequencing (GBS) represents an innovative method for large scale SNP detection and genotyping of genetic resources. Herein we used the GBS approach for the genome-wide identification of SNPs in a collection of Capsicum spp. accessions and for the assessment of the level of genetic diversity in a subset of 222 cultivated pepper (Capsicum annum) genotypes. GBS analysis generated a total of 7,568,894 master tags, of which 43.4% uniquely aligned to the reference genome CM334. A total of 108,591 SNP markers were identified, of which 105,184 were in C. annuum accessions. In order to explore the genetic diversity of C. annuum and to select a minimal core set representing most of the total genetic variation with minimum redundancy, a subset of 222 C. annuum accessions were analysed using 32,950 high quality SNPs. Based on Bayesian and Hierarchical clustering it was possible to divide the collection into three clusters. Cluster I had the majority of varieties and landraces mainly from Southern and Northern Italy, and from Eastern Europe, whereas clusters II and III comprised accessions of different geographical origins. Considering the genome-wide genetic variation among the accessions included in cluster I, a second round of Bayesian (K = 3) and Hierarchical (K = 2) clustering was performed. These analysis showed that genotypes were grouped not only based on geographical origin, but also on fruit-related features. GBS data has proven useful to assess the genetic diversity in a collection of C. annuum accessions. The high number of SNP markers, uniformly distributed on the 12 chromosomes, allowed the accessions to be distinguished according to geographical origin and fruit-related features. SNP markers and information on population structure developed in this study will undoubtedly support genome-wide association mapping studies and marker-assisted selection programs.

Illinois Occupational Skill Standards: Automotive Technician Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the automotive technician cluster. The document begins with overviews of the Illinois perspective on occupational skill standards and…

Illinois Occupational Skill Standards. Meeting Professional Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for workforce preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in the meeting professional occupational cluster. It begins with a brief overview of the Illinois perspective on occupational skill standards and credentialing,…

Illinois Occupational Skill Standards. Beef Production Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for workforce preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the beef production cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards and…

Impact of intensive horticulture practices on groundwater content of nitrates, sodium, potassium, and pesticides.

PubMed

Melo, Armindo; Pinto, Edgar; Aguiar, Ana; Mansilha, Catarina; Pinho, Olívia; Ferreira, Isabel M P L V O

2012-07-01

A monitoring program of nitrate, nitrite, potassium, sodium, and pesticides was carried out in water samples from an intensive horticulture area in a vulnerable zone from north of Portugal. Eight collecting points were selected and water-analyzed in five sampling campaigns, during 1 year. Chemometric techniques, such as cluster analysis, principal component analysis (PCA), and discriminant analysis, were used in order to understand the impact of intensive horticulture practices on dug and drilled wells groundwater and to study variations in the hydrochemistry of groundwater. PCA performed on pesticide data matrix yielded seven significant PCs explaining 77.67% of the data variance. Although PCA rendered considerable data reduction, it could not clearly group and distinguish the sample types. However, a visible differentiation between the water samples was obtained. Cluster and discriminant analysis grouped the eight collecting points into three clusters of similar characteristics pertaining to water contamination, indicating that it is necessary to improve the use of water, fertilizers, and pesticides. Inorganic fertilizers such as potassium nitrate were suspected to be the most important factors for nitrate contamination since highly significant Pearson correlation (r = 0.691, P < 0.01) was obtained between groundwater nitrate and potassium contents. Water from dug wells is especially prone to contamination from the grower and their closer neighbor's practices. Water from drilled wells is also contaminated from distant practices.

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

Using concept mapping to design an indicator framework for addiction treatment centres.

PubMed

Nabitz, Udo; van Den Brink, Wim; Jansen, Paul

2005-06-01

The objective of this study is to determine an indicator framework for addiction treatment centres based on the demands of stakeholders and in alignment with the European Foundation for Quality Management (EFQM) Excellence Model. The setting is the Jellinek Centre based in Amsterdam, the Netherlands, which serves as a prototype for an addiction treatment centre. Concept mapping was used in the construction of the indicator framework. During the 1-day workshop, 16 stakeholders generated, prioritized and sorted 73 items concerning quality and performance. Multidimensional scaling and cluster analysis was applied in constructing a framework consisting of two dimensions and eight clusters. The horizontal axis of the indicator framework is named 'Organization' and has two poles, namely, 'Processes' and 'Results'. The vertical axis is named ' Task' and the poles are named 'Efficient treatment' and 'Prevention programs'. The eight clusters in the two-dimensional framework are arranged in the following, prioritized sequence: 'Efficient treatment network', 'Effective service', ' Target group', 'Quality of life', 'Efficient service', 'Knowledge transfer', 'Reducing addiction related problems', and 'Prevention programs'. The most important items in the framework are: 'patients are satisfied with their treatment', 'early interventions', and 'efficient treatment chain'. The indicator framework aligns with three clusters of the results criteria of the EFQM Excellence Model. It is based on the stakeholders' perspectives and is believed to be specific for addiction treatment centres. The study demonstrates that concept mapping is a suitable strategy for generating indicator frameworks.

Local Spatial and Temporal Processes of Influenza in Pennsylvania, USA: 2003–2009

PubMed Central

Stark, James H.; Sharma, Ravi; Ostroff, Stephen; Cummings, Derek A. T.; Ermentrout, Bard; Stebbins, Samuel; Burke, Donald S.; Wisniewski, Stephen R.

2012-01-01

Background Influenza is a contagious respiratory disease responsible for annual seasonal epidemics in temperate climates. An understanding of how influenza spreads geographically and temporally within regions could result in improved public health prevention programs. The purpose of this study was to summarize the spatial and temporal spread of influenza using data obtained from the Pennsylvania Department of Health's influenza surveillance system. Methodology and Findings We evaluated the spatial and temporal patterns of laboratory-confirmed influenza cases in Pennsylvania, United States from six influenza seasons (2003–2009). Using a test of spatial autocorrelation, local clusters of elevated risk were identified in the South Central region of the state. Multivariable logistic regression indicated that lower monthly precipitation levels during the influenza season (OR = 0.52, 95% CI: 0.28, 0.94), fewer residents over age 64 (OR = 0.27, 95% CI: 0.10, 0.73) and fewer residents with more than a high school education (OR = 0.76, 95% CI: 0.61, 0.95) were significantly associated with membership in this cluster. In addition, time series analysis revealed a temporal lag in the peak timing of the influenza B epidemic compared to the influenza A epidemic. Conclusions These findings illustrate a distinct spatial cluster of cases in the South Central region of Pennsylvania. Further examination of the regional transmission dynamics within these clusters may be useful in planning public health influenza prevention programs. PMID:22470544

Founded: Genetic Reconstruction of Lineage Diversity and Kinship Informs Ex situ Conservation of Cuban Amazon Parrots (Amazona leucocephala).

PubMed

Milián-García, Yoamel; Jensen, Evelyn L; Madsen, Jeanette; Álvarez Alonso, Suleiky; Serrano Rodríguez, Aryamne; Espinosa López, Georgina; Russello, Michael A

2015-01-01

Captive breeding is a widespread conservation strategy, yet such programs rarely include empirical genetic data for assessing management assumptions and meeting conservation goals. Cuban Amazon parrots (Amazona leucocephala) are considered vulnerable, and multiple on-island captive populations have been established from wild-caught and confiscated individuals of unknown ancestry. Here, we used mitochondrial haplotypic and nuclear genotypic data at 9 microsatellite loci to quantify the extent and distribution of genetic variation within and among captive populations in Zapata Swamp and Managua, Cuba, and to estimate kinship among breeders (n = 88). Using Bayesian clustering analysis, we detected 2 distinct clusters within the Zapata population, one of which was shared with Managua. Individuals from the cluster unique to Zapata possessed mitochondrial haplotypes with affinities to Cuban subspecies (A. l. leucocephala, A. l. palmarum); the shared cluster was similar, but also included haplotypes closely related to the subspecies restricted to Cayman Brac (A. l. hesterna). Overall mean kinship was low within each captive population (-0.026 to -0.012), with 19 and 11 recommended breeding pairs in Zapata and Managua, respectively, ranked according to mean kinship and informed by molecular sexing. Our results highlight the importance of understanding population history within ex situ management programs, while providing genetic information to directly inform Cuban parrot conservation. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

STAR CLUSTERS IN M31. II. OLD CLUSTER METALLICITIES AND AGES FROM HECTOSPEC DATA

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

Caldwell, Nelson; Schiavon, Ricardo; Morrison, Heather

2011-02-15

We present new high signal-to-noise spectroscopic data on the M31 globular cluster (GC) system, obtained with the Hectospec multifiber spectrograph on the 6.5 m MMT. More than 300 clusters have been observed at a resolution of 5 A and with a median S/N of 75 per A, providing velocities with a median uncertainty of 6 km s{sup -1}. The primary focus of this paper is the determination of mean cluster metallicities, ages, and reddenings. Metallicities were estimated using a calibration of Lick indices with [Fe/H] provided by Galactic GCs. These match well the metallicities of 24 M31 clusters determined frommore » Hubble Space Telescope color-magnitude diagrams, the differences having an rms of 0.2 dex. The metallicity distribution is not generally bimodal, in strong distinction with the bimodal Galactic globular distribution. Rather, the M31 distribution shows a broad peak, centered at [Fe/H] = -1, possibly with minor peaks at [Fe/H] = -1.4, -0.7, and -0.2, suggesting that the cluster systems of M31 and the Milky Way had different formation histories. Ages for clusters with [Fe/H] > - 1 were determined using the automatic stellar population analysis program EZ{sub A}ges. We find no evidence for massive clusters in M31 with intermediate ages, those between 2 and 6 Gyr. Moreover, we find that the mean ages of the old GCs are remarkably constant over about a decade in metallicity (-0.95{approx}< [Fe/H] {approx}<0.0).« less

Clustering Genes of Common Evolutionary History

PubMed Central

Gori, Kevin; Suchan, Tomasz; Alvarez, Nadir; Goldman, Nick; Dessimoz, Christophe

2016-01-01

Phylogenetic inference can potentially result in a more accurate tree using data from multiple loci. However, if the loci are incongruent—due to events such as incomplete lineage sorting or horizontal gene transfer—it can be misleading to infer a single tree. To address this, many previous contributions have taken a mechanistic approach, by modeling specific processes. Alternatively, one can cluster loci without assuming how these incongruencies might arise. Such “process-agnostic” approaches typically infer a tree for each locus and cluster these. There are, however, many possible combinations of tree distance and clustering methods; their comparative performance in the context of tree incongruence is largely unknown. Furthermore, because standard model selection criteria such as AIC cannot be applied to problems with a variable number of topologies, the issue of inferring the optimal number of clusters is poorly understood. Here, we perform a large-scale simulation study of phylogenetic distances and clustering methods to infer loci of common evolutionary history. We observe that the best-performing combinations are distances accounting for branch lengths followed by spectral clustering or Ward’s method. We also introduce two statistical tests to infer the optimal number of clusters and show that they strongly outperform the silhouette criterion, a general-purpose heuristic. We illustrate the usefulness of the approach by 1) identifying errors in a previous phylogenetic analysis of yeast species and 2) identifying topological incongruence among newly sequenced loci of the globeflower fly genus Chiastocheta. We release treeCl, a new program to cluster genes of common evolutionary history (http://git.io/treeCl). PMID:26893301

Globular clusters and environmental effects in galaxy clusters

NASA Astrophysics Data System (ADS)

Sales, Laura

2016-10-01

Globular clusters are old compact stellar systems orbiting around galaxies of all types. Tens of thousands of them can also be found populating the intra-cluster regions of nearby galaxy clusters like Virgo and Coma. Thanks to the HST Frontier Fields program, GCs are starting now to be detected also in intermediate redshift clusters. Yet, despite their ubiquity, a theoretical model for the formation and evolution of GCs is still missing, especially within the cosmological context.Here we propose to use cosmological hydrodynamical simulations of 18 galaxy clusters coupled to a post-processing GC formation model to explore the assembly of galaxies in clusters together with their expected GC population. The method, which has already been implemented and tested, will allow us to characterize for the first time the number, radial distribution and kinematics of GCs in clusters, with products directly comparable to observational maps. We will explore cluster-to-cluster variations and also characterize the build up of the intra-cluster component of GCs with time.As the method relies on a detailed study of the star-formation history of galaxies, we will jointly constrain the predicted quenching time-scales for satellites and the occurrence of starburst events associated to infall and orbital pericenters of galaxies in massive clusters. This will inform further studies on the distribution, velocity and properties of post-starburst galaxies in past, ongoing and future HST programs.

On evaluating clustering procedures for use in classification

NASA Technical Reports Server (NTRS)

Pore, M. D.; Moritz, T. E.; Register, D. T.; Yao, S. S.; Eppler, W. G. (Principal Investigator)

1979-01-01

The problem of evaluating clustering algorithms and their respective computer programs for use in a preprocessing step for classification is addressed. In clustering for classification the probability of correct classification is suggested as the ultimate measure of accuracy on training data. A means of implementing this criterion and a measure of cluster purity are discussed. Examples are given. A procedure for cluster labeling that is based on cluster purity and sample size is presented.

Mapping the spatial distribution of star formation in cluster galaxies at z ~0.5 with the Grism Lens-Amplified Survey from Space (GLASS)

NASA Astrophysics Data System (ADS)

Vulcani, Benedetta

2015-08-01

What physical processes regulate star formation in dense environments? Understanding why galaxy evolution is environment dependent is one of the key questions of current astrophysics. I will present the first characterization of the spatial distribution of star formation in cluster galaxies at z~0.5, in order to quantify the role of different physical processes that are believed to be responsible for shutting down star formation. The analysis makes use of data from the Grism Lens-Amplified Survey from Space (GLASS), a large HST cycle-21 program targeting 10 massive galaxy clusters with extensive HST imaging from CLASH and the Frontier Field Initiative. The program consists of 140 primary and 140 parallel orbits of near-infrared WCF3 and optical ACS slitless grism observations, which result in 3D spectroscopy of hundreds of galaxies. The grism data are used to produce spatially resolved maps of the star formation density, while the stellar mass density and optical surface brightness are obtained from multiband imaging. I will describe quantitative measures of the spatial location and extend of the star formation rate, showing that about half of the cluster members with significant Halpha detection have diffused star formation, larger than the optical counterpart. This suggests that star formation occurs out to larger radii than the rest frame continuum. For some systems, nuclear star forming regions are found. I will also present a comparison between the Halpha distribution observed in cluster and field galaxies. The characterization of the spatial distribution of Halpha provides a new window, yet poorly exploited, on the mechanisms that regulate star formation and morphological transformation in dense environments.

Subtypes of female juvenile offenders: a cluster analysis of the Millon Adolescent Clinical Inventory.

PubMed

Stefurak, Tres; Calhoun, Georgia B

2007-01-01

The current study sought to explore subtypes of adolescents within a sample of female juvenile offenders. Using the Millon Adolescent Clinical Inventory with 101 female juvenile offenders, a two-step cluster analysis was performed beginning with a Ward's method hierarchical cluster analysis followed by a K-Means iterative partitioning cluster analysis. The results suggest an optimal three-cluster solution, with cluster profiles leading to the following group labels: Externalizing Problems, Depressed/Interpersonally Ambivalent, and Anxious Prosocial. Analysis along the factors of age, race, offense typology and offense chronicity were conducted to further understand the nature of found clusters. Only the effect for race was significant with the Anxious Prosocial and Depressed Intepersonally Ambivalent clusters appearing disproportionately comprised of African American girls. To establish external validity, clusters were compared across scales of the Behavioral Assessment System for Children - Self Report of Personality, and corroborative distinctions between clusters were found here.

Swarm v2: highly-scalable and high-resolution amplicon clustering.

PubMed

Mahé, Frédéric; Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

2015-01-01

Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks.

[Cluster analysis in biomedical researches].

PubMed

Akopov, A S; Moskovtsev, A A; Dolenko, S A; Savina, G D

2013-01-01

Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research.

OpenCluster: A Flexible Distributed Computing Framework for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Wei, Shoulin; Wang, Feng; Deng, Hui; Liu, Cuiyin; Dai, Wei; Liang, Bo; Mei, Ying; Shi, Congming; Liu, Yingbo; Wu, Jingping

2017-02-01

The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their limitations and programming difficulties. In this paper, we therefore present OpenCluster, an open-source distributed computing framework to support rapidly developing high-performance processing pipelines of astronomical big data. We first detail the OpenCluster design principles and implementations and present the APIs facilitated by the framework. We then demonstrate a case in which OpenCluster is used to resolve complex data processing problems for developing a pipeline for the Mingantu Ultrawide Spectral Radioheliograph. Finally, we present our OpenCluster performance evaluation. Overall, OpenCluster provides not only high fault tolerance and simple programming interfaces, but also a flexible means of scaling up the number of interacting entities. OpenCluster thereby provides an easily integrated distributed computing framework for quickly developing a high-performance data processing system of astronomical telescopes and for significantly reducing software development expenses.

Wrapping up BLAST and other applications for use on Unix clusters.

PubMed

Hokamp, Karsten; Shields, Denis C; Wolfe, Kenneth H; Caffrey, Daniel R

2003-02-12

We have developed two programs that speed up common bioinformatic applications by spreading them across a UNIX cluster.(1) BLAST.pm, a new module for the 'MOLLUSC' package. (2) WRAPID, a simple tool for parallelizing large numbers of small instances of programs such as BLAST, FASTA and CLUSTALW. The packages were developed in Perl on a 20-node Linux cluster and are provided together with a configuration script and documentation. They can be freely downloaded from http://wolfe.gen.tcd.ie/wrapper.

Illinois Occupational Skill Standards: Information Technology End User Applications Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

These skill standards for the information technology end user applications cluster are intended to be a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. An introduction provides the Illinois perspective; Illinois…

Illinois Occupational Skill Standards: Mechanical Drafting Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the mechanical drafting cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards and…

Saturn Apollo Program

NASA Image and Video Library

1960-01-01

Pictured is one of the earliest testing of the Saturn I S-I (first) stage, with a cluster of eight H-1 engines, at the Marshall Space Flight Center (MSFC). It was a part of the test program to prove out the clustered-booster concept. MSFC was responsible for designing and development the Saturn launch vehicles.

Illinois Occupational Skill Standards: Architectural Drafting Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the architectural drafting cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards and…

Illinois Occupational Skill Standards: In-Store Retailing Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended to serve as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the in-store retailing cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards…

Illinois Occupational Skill Standards: Industrial Maintenance General Maintenance Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

These skill standards for the industrial maintenance general maintenance cluster are intended to be a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. An introduction provides the Illinois perspective; Illinois Occupational…

Illinois Occupational Skill Standards. Collision Repair Technician Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for workforce preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the (vehicle) collision repair technician cluster. It begins with a brief overview of the Illinois perspective on occupational skill standards…

Illinois Occupational Skill Standards: Finishing and Distribution Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the finishing and distribution cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards…

Illinois Occupational Skill Standards: Imaging/Pre-Press Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document, which is intended as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the imaging/pre-press cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards and…

Curriculum Designs for Tech Prep Clusters. PACE '94.

ERIC Educational Resources Information Center

Schoon, Kenneth J., Ed.; Wiles, Clyde A., Ed.

This booklet contains descriptions of various Tech Prep programs developed by PACE (Promoting Academic Excellence In Mathematics, Science & Technology for Workers of the 21st Century). Each entry includes general program descriptions, curriculum outlines, and course descriptions. The clusters and their specialty areas described in the booklet are:…

Office Occupations Cluster Brief. Clerical Cluster. [Vocational Education in Oregon.

ERIC Educational Resources Information Center

Stamps, Margaret McDonnall

This guide sets forth minimum approval criteria for clerical training in office occupations education programs in Oregon. The information in the guide is intended for use by district-level curriculum planners, teachers, regional coordinators, or state education department staff involved with new program development or revisions of existing…

Office Occupations Cluster Brief. Secretarial Cluster. [Vocational Education in Oregon.

ERIC Educational Resources Information Center

Stamps, Margaret McDonnall

This guide sets forth minimum approval criteria for secretarial training in office occupations education programs in Oregon. The information in the guide is intended for use by district-level curriculum planners, teachers, regional coordinators, or state education department staff involved with new program development or revisions of existing…

Accounting Cluster Demonstration Program at Aloha High School. Final Report.

ERIC Educational Resources Information Center

Beaverton School District 48, OR.

A model high school accounting cluster program was planned, developed, implemented, and evaluated in the Beaverton, Oregon, school district. The curriculum was developed with the help of representatives from the accounting occupations in the Portland metropolitan area. Through management interviews, identification of on-the job requirements, and…

Industrial Mechanics Occupational Cluster Guide.

ERIC Educational Resources Information Center

Bishop, Frank

This guide, developed by the Oregon Department of Education, is intended to assist the vocational teacher in designing and implementing a cluster program in industrial mechanics. It suggests teaching ideas and is aimed at high school students, as well as those wishing to enter community college, university, or apprenticeship programs. The guide is…

Power Calculations for Moderators in Multi-Site Cluster Randomized Trials

ERIC Educational Resources Information Center

Spybrook, Jessaca; Kelcey, Ben; Dong, Nianbo

2016-01-01

Cluster randomized trials (CRTs), or studies in which intact groups of individuals are randomly assigned to a condition, are becoming more common in evaluation studies of educational programs. A specific type of CRT in which clusters are randomly assigned to treatment within blocks or sites, known as multisite cluster randomized trials (MSCRTs),…

A Typology of Social Workers in Long-Term Care Facilities in Israel.

PubMed

Lev, Sagit; Ayalon, Liat

2018-04-01

This article explores moral distress among long-term care facility (LTCF) social workers by examining the relationships between moral distress and environmental and personal features. Based on these features, authors identified a typology of LTCF social workers and how they handle moral distress. Such a typology can assist in the identification of social workers who are in a particular need for assistance. Overall, 216 LTCF social workers took part in the study. A two-step cluster analysis was conducted to identify a typology of LTCF social workers based on features such as ethical environment, support in workplace, mastery, and resilience. The variance of the identified clusters and their associations with moral distress were examined, and four clusters of LTCF social workers were identified. The clusters varied from each other in relation to their personal and environmental features and in relation to their experience of moral distress. The article concludes with a discussion of the importance of developing programs for LTCF social workers that provide support and enhancement of personal resources and an adequate and ethical environment for practice.

The Formation and Early Evolution of Embedded Massive Star Clusters

NASA Astrophysics Data System (ADS)

Barnes, Peter

We propose to combine Spitzer, WISE, Herschel, and other archival spacecraft data with an existing ground- and space-based mm-wave to near-IR survey of molecular clouds over a large portion of the Milky Way, in order to systematically study the formation and early evolution of massive stars and star clusters, and provide new observational calibrations for a theoretical paradigm of this key astrophysical problem. Central Objectives: The Galactic Census of High- and Medium-mass Protostars (CHaMP) is a large, unbiased, uniform, and panchromatic survey of massive star and cluster formation and early evolution, covering 20°x6° of the Galactic Plane. Its uniqueness lies in the comprehensive molecular spectroscopy of 303 massive dense clumps, which have also been included in several archival spacecraft surveys. Our objective is a systematic demographic analysis of massive star and cluster formation, one which has not been possible without knowledge of our CHaMP cloud sample, including all clouds with embedded clusters as well as those that have not yet formed massive stars. For proto-clusters deeply embedded within dense molecular clouds, analysis of these space-based data will: 1. Yield a complete census of Young Stellar Objects in each cluster. 2. Allow systematic measurements of embedded cluster properties: spectral energy distributions, luminosity functions, protostellar and disk fractions, and how these vary with cluster mass, age, and density. Combined with other, similarly complete and unbiased infrared and mm data, CHaMP's goals include: 3. A detailed comparison of the embedded stellar populations with their natal dense gas to derive extinction maps, star formation efficiencies and feedback effects, and the kinematics, physics, and chemistry of the gas in and around the clusters. 4. Tying the demographics, age spreads, and timescales of the clusters, based on pre-Main Sequence evolution, to that of the dense gas clumps and Giant Molecular Clouds. 5. A measurement of the local star formation rate per gas mass surface density in the Milky Way, as well as examining arm versus interarm dependencies. Methods and Techniques: We will primarily use archival cryogenic-Spitzer, WISE, and Herschel data, and support this with existing data from ground- and space-based facilities, to conduct a comprehensive assay of critical metrics (as above) and provide observational calibration of theoretical models over the entire massive star formation process. The mm-wave molecular maps of 303 dense gas clumps in multiple species, comprising all the gas above a column density limit of 100 Msun/pc^2, are already inhand. We have also surveyed the embedded stellar content of these clumps, down to subsolar masses, in the near-infrared J, H, and K bands and with deep Warm Spitzer data. Relevance to NASA programs: Analysis to date of the space- and ground-based data has yielded several new insights into evolutionary timescales and the chemical & energy evolution of clumps during the cluster formation process. Investigations as described in this proposal will yield new demographic insights on how the properties and evolution of molecular clouds relate to the properties of massive stars and clusters that form within them, and significantly enhance the science return from these spacecraft missions. The large number of resulting data products are already being made publicly available to the astronomical community, providing crucial information for future NASA science targets. This research will be performed within the framework of a broad international collaboration spanning four continents. This ambitious but practical program will therefore maximise the science payoff from these archival data sets, provide enhanced legacy data for more advanced studies with the next generation of ground- and space-based instruments such as JWST, and open up several new windows into the discovery space of Galactic star formation & interstellar medium studies.

FY17 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models.

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

Appel, Gordon John; Hadgu, Teklu; Appel, Gordon John

Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014), Hadgu et al. (2015) and Hadgu and Appel (2016). The TSPA computing hardware (CL2014) and storage system described in Hadgu et al. (2015) weremore » used for the current analysis. One floating license of GoldSim with Versions 9.60.300, 10.5, 11.1 and 12.0 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA- type analysis on the server cluster. The current tasks included preliminary upgrade of the TSPA-LA from Version 9.60.300 to the latest version 12.0 and address DLL-related issues observed in the FY16 work. The model upgrade task successfully converted the Nominal Modeling case to GoldSim Versions 11.1/12. Conversions of the rest of the TSPA models were also attempted but program and operational difficulties precluded this. Upgrade of the remaining of the modeling cases and distributed processing tasks is expected to continue. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.« less

Experimental analysis of control mechanisms in somite segmentation in avian embryos. II. Reduction of material in the gastrula stages of the chick.

PubMed

Bellairs, R; Veini, M

1984-02-01

A new theory of control of somite segmentation in chick embryos is proposed. This supposses that tiny clusters of already programmed cells are present throughout the presumptive somite area at stage 4, but that in order to fulfill their destiny they probably depend on the addition of further cells from the primitive streak. Evidence is based on the two groups of experiments: a) Experiments involving transection across the primitive streak at various stages, (which results in a 'tail' which possesses mesodermal derivatives) and across the segmental plate (which results in a 'tail' lacking mesodermal derivatives). b) Experiments in which parts of embryos have been explanted with or without their primitive streak. It is suggested that the initial clusters of pre-programmed cells move further and further posteriorly, developing into somitomeres (the precursors of true somites) only as they receive re-inforcements from the primitive streak or, ultimately, from the tail bud.

StrAuto: automation and parallelization of STRUCTURE analysis.

PubMed

Chhatre, Vikram E; Emerson, Kevin J

2017-03-24

Population structure inference using the software STRUCTURE has become an integral part of population genetic studies covering a broad spectrum of taxa including humans. The ever-expanding size of genetic data sets poses computational challenges for this analysis. Although at least one tool currently implements parallel computing to reduce computational overload of this analysis, it does not fully automate the use of replicate STRUCTURE analysis runs required for downstream inference of optimal K. There is pressing need for a tool that can deploy population structure analysis on high performance computing clusters. We present an updated version of the popular Python program StrAuto, to streamline population structure analysis using parallel computing. StrAuto implements a pipeline that combines STRUCTURE analysis with the Evanno Δ K analysis and visualization of results using STRUCTURE HARVESTER. Using benchmarking tests, we demonstrate that StrAuto significantly reduces the computational time needed to perform iterative STRUCTURE analysis by distributing runs over two or more processors. StrAuto is the first tool to integrate STRUCTURE analysis with post-processing using a pipeline approach in addition to implementing parallel computation - a set up ideal for deployment on computing clusters. StrAuto is distributed under the GNU GPL (General Public License) and available to download from http://strauto.popgen.org .

Genetic divergence of physiological-quality traits of seeds in a population of peppers.

PubMed

Pessoa, A M S; Barroso, P A; do Rêgo, E R; Medeiros, G D A; Bruno, R L A; do Rêgo, M M

2015-10-16

Brazil has a great diversity of Capsicum peppers that can be used in breeding programs. The objective of this study was to evaluate genetic variation in traits related to the physiological quality of seeds of Capsicum annuum L. in a segregating F2 population and its parents. A total of 250 seeds produced by selfing in the F1 generation resulting from crosses between UFPB 77.3 and UFPB 76 were used, with 100 seeds of both parents used as additional controls, totaling 252 genotypes. The seeds were germinated in gerboxes containing substrate blotting paper moistened with distilled water. Germination and the following vigor tests were evaluated: first count, germination velocity index, and root and shoot lengths. Data were subjected to analysis of variance, and means were compared by Scott and Knott's method at 1% probability. Tocher's clustering based on Mahalanobis distance and canonical variable analysis with graphic dispersion of genotypes were performed, and genetic parameters were estimated. All variables were found to be significant by the F test (P ≤ 0.01) and showed high heritability and a CVg/CVe ratio higher than 1.0, indicating genetic differences among genotypes. Parents (genotypes 1 and 2) formed distinct groups in all clustering methods. Genotypes 3, 104, 153, and 232 were found to be the most divergent according to Tocher's clustering method, and this was mainly due to early germination, which was observed on day 14, and would therefore be selected. Understanding the phenotypic variability among these 252 genotypes will serve as a basis for continuing the breeding program within this family.

Relatedness of Indian flax genotypes (Linum usitatissimum L.): an inter-simple sequence repeat (ISSR) primer assay.

PubMed

Rajwade, Ashwini V; Arora, Ritu S; Kadoo, Narendra Y; Harsulkar, Abhay M; Ghorpade, Prakash B; Gupta, Vidya S

2010-06-01

The objective of this study was to analyze the genetic relationships, using PCR-based ISSR markers, among 70 Indian flax (Linum usitatissimum L.) genotypes actively utilized in flax breeding programs. Twelve ISSR primers were used for the analysis yielding 136 loci, of which 87 were polymorphic. The average number of amplified loci and the average number of polymorphic loci per primer were 11.3 and 7.25, respectively, while the percent loci polymorphism ranged from 11.1 to 81.8 with an average of 63.9 across all the genotypes. The range of polymorphism information content scores was 0.03-0.49, with an average of 0.18. A dendrogram was generated based on the similarity matrix by the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), wherein the flax genotypes were grouped in five clusters. The Jaccard's similarity coefficient among the genotypes ranged from 0.60 to 0.97. When the omega-3 alpha linolenic acid (ALA) contents of the individual genotypes were correlated with the clusters in the dendrogram, the high ALA containing genotypes were grouped in two clusters. This study identified SLS 50, Ayogi, and Sheetal to be the most diverse genotypes and suggested their use in breeding programs and for developing mapping populations.

Geospatial characteristics of measles transmission in China during 2005−2014

PubMed Central

Wen, Liang; Li, Shen-Long; Chen, Kai; Zhang, Wen-Yi

2017-01-01

Measles is a highly contagious and severe disease. Despite mass vaccination, it remains a leading cause of death in children in developing regions, killing 114,900 globally in 2014. In 2006, China committed to eliminating measles by 2012; to this end, the country enhanced its mandatory vaccination programs and achieved vaccination rates reported above 95% by 2008. However, in spite of these efforts, during the last 3 years (2013–2015) China documented 27,695, 52,656, and 42,874 confirmed measles cases. How measles manages to spread in China—the world’s largest population—in the mass vaccination era remains poorly understood. To address this conundrum and provide insights for future public health efforts, we analyze the geospatial pattern of measles transmission across China during 2005–2014. We map measles incidence and incidence rates for each of the 344 cities in mainland China, identify the key socioeconomic and demographic features associated with high disease burden, and identify transmission clusters based on the synchrony of outbreak cycles. Using hierarchical cluster analysis, we identify 21 epidemic clusters, of which 12 were cross-regional. The cross-regional clusters included more underdeveloped cities with large numbers of emigrants than would be expected by chance (p = 0.011; bootstrap sampling), indicating that cities in these clusters were likely linked by internal worker migration in response to uneven economic development. In contrast, cities in regional clusters were more likely to have high rates of minorities and high natural growth rates than would be expected by chance (p = 0.074; bootstrap sampling). Our findings suggest that multiple highly connected foci of measles transmission coexist in China and that migrant workers likely facilitate the transmission of measles across regions. This complex connection renders eradication of measles challenging in China despite its high overall vaccination coverage. Future immunization programs should therefore target these transmission foci simultaneously. PMID:28376097

Geospatial characteristics of measles transmission in China during 2005-2014.

PubMed

Yang, Wan; Wen, Liang; Li, Shen-Long; Chen, Kai; Zhang, Wen-Yi; Shaman, Jeffrey

2017-04-01

Measles is a highly contagious and severe disease. Despite mass vaccination, it remains a leading cause of death in children in developing regions, killing 114,900 globally in 2014. In 2006, China committed to eliminating measles by 2012; to this end, the country enhanced its mandatory vaccination programs and achieved vaccination rates reported above 95% by 2008. However, in spite of these efforts, during the last 3 years (2013-2015) China documented 27,695, 52,656, and 42,874 confirmed measles cases. How measles manages to spread in China-the world's largest population-in the mass vaccination era remains poorly understood. To address this conundrum and provide insights for future public health efforts, we analyze the geospatial pattern of measles transmission across China during 2005-2014. We map measles incidence and incidence rates for each of the 344 cities in mainland China, identify the key socioeconomic and demographic features associated with high disease burden, and identify transmission clusters based on the synchrony of outbreak cycles. Using hierarchical cluster analysis, we identify 21 epidemic clusters, of which 12 were cross-regional. The cross-regional clusters included more underdeveloped cities with large numbers of emigrants than would be expected by chance (p = 0.011; bootstrap sampling), indicating that cities in these clusters were likely linked by internal worker migration in response to uneven economic development. In contrast, cities in regional clusters were more likely to have high rates of minorities and high natural growth rates than would be expected by chance (p = 0.074; bootstrap sampling). Our findings suggest that multiple highly connected foci of measles transmission coexist in China and that migrant workers likely facilitate the transmission of measles across regions. This complex connection renders eradication of measles challenging in China despite its high overall vaccination coverage. Future immunization programs should therefore target these transmission foci simultaneously.

Hybrid cloud and cluster computing paradigms for life science applications

PubMed Central

2010-01-01

Background Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. Results Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. Conclusions The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. Methods We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments. PMID:21210982

Hybrid cloud and cluster computing paradigms for life science applications.

PubMed

Qiu, Judy; Ekanayake, Jaliya; Gunarathne, Thilina; Choi, Jong Youl; Bae, Seung-Hee; Li, Hui; Zhang, Bingjing; Wu, Tak-Lon; Ruan, Yang; Ekanayake, Saliya; Hughes, Adam; Fox, Geoffrey

2010-12-21

Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments.

[Development of Staphylococcus Haemolyticus multilocus sequencing scheme and its use for molecular-epidemiologic analysis of strains isolated in hospitals in Russian federation in 2009-2010].

PubMed

Voronina, O L; Kunda, M S; Dmitrenko, O A; Lunin, V G; Gintsburg, A L

2011-01-01

Development of Staphylococcus haemolyticus strain typing method based on multilocus sequencing for resolving problems of molecular epidemiology. 102 strains of coagulase negative staphylococci (CNS) isolated in hospitals of various specialization in N. Novgorod and Moscow were studied. Species identification of strain was performed by using tuf gene fragment sequencing, S. haemolyticus strain differentiation--by MLST results. eBURST approach was used for cluster analysis of MLST data; structural changes in tagatose-6-phosphate kinase were studied by using InterProScan platform and SWISS-MODEL site programs; MLST scheme gene allele variability analysis was performed by using MEGA4.0 program package. In the 102 strains sampled CNS was detected in 28 strains of the S. haemolyticus species. The MLST scheme developed for the first time for S. haemolyticus including mvaK, rphE, tphK, gtr, arcC, triA, aroE genes allowed the differentiation of the sampled strains by 11 genotypes. Strains with ST 3, 8, 6, 1, 4, 5 and 11 differed by highest epidemiologic significance. Cluster and phylogenetic analysis of the data obtained showed a high adaptive ability of the nosocomial S. haemolyticus strains. Multiresistance to antibacterial preparations was detected in the analyzed strains. The MLST method developed was effective in the differentiation of S. haemolyticus strains that circulate in hospitals and threaten both neonates and hospitalized adult patients.

MBGD update 2015: microbial genome database for flexible ortholog analysis utilizing a diverse set of genomic data.

PubMed

Uchiyama, Ikuo; Mihara, Motohiro; Nishide, Hiroyo; Chiba, Hirokazu

2015-01-01

The microbial genome database for comparative analysis (MBGD) (available at http://mbgd.genome.ad.jp/) is a comprehensive ortholog database for flexible comparative analysis of microbial genomes, where the users are allowed to create an ortholog table among any specified set of organisms. Because of the rapid increase in microbial genome data owing to the next-generation sequencing technology, it becomes increasingly challenging to maintain high-quality orthology relationships while allowing the users to incorporate the latest genomic data available into an analysis. Because many of the recently accumulating genomic data are draft genome sequences for which some complete genome sequences of the same or closely related species are available, MBGD now stores draft genome data and allows the users to incorporate them into a user-specific ortholog database using the MyMBGD functionality. In this function, draft genome data are incorporated into an existing ortholog table created only from the complete genome data in an incremental manner to prevent low-quality draft data from affecting clustering results. In addition, to provide high-quality orthology relationships, the standard ortholog table containing all the representative genomes, which is first created by the rapid classification program DomClust, is now refined using DomRefine, a recently developed program for improving domain-level clustering using multiple sequence alignment information. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genomewide Analysis of Aryl Hydrocarbon Receptor Binding Targets Reveals an Extensive Array of Gene Clusters that Control Morphogenetic and Developmental Programs

PubMed Central

Sartor, Maureen A.; Schnekenburger, Michael; Marlowe, Jennifer L.; Reichard, John F.; Wang, Ying; Fan, Yunxia; Ma, Ci; Karyala, Saikumar; Halbleib, Danielle; Liu, Xiangdong; Medvedovic, Mario; Puga, Alvaro

2009-01-01

Background The vertebrate aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that regulates cellular responses to environmental polycyclic and halogenated compounds. The naive receptor is believed to reside in an inactive cytosolic complex that translocates to the nucleus and induces transcription of xenobiotic detoxification genes after activation by ligand. Objectives We conducted an integrative genomewide analysis of AHR gene targets in mouse hepatoma cells and determined whether AHR regulatory functions may take place in the absence of an exogenous ligand. Methods The network of AHR-binding targets in the mouse genome was mapped through a multipronged approach involving chromatin immunoprecipitation/chip and global gene expression signatures. The findings were integrated into a prior functional knowledge base from Gene Ontology, interaction networks, Kyoto Encyclopedia of Genes and Genomes pathways, sequence motif analysis, and literature molecular concepts. Results We found the naive receptor in unstimulated cells bound to an extensive array of gene clusters with functions in regulation of gene expression, differentiation, and pattern specification, connecting multiple morphogenetic and developmental programs. Activation by the ligand displaced the receptor from some of these targets toward sites in the promoters of xenobiotic metabolism genes. Conclusions The vertebrate AHR appears to possess unsuspected regulatory functions that may be potential targets of environmental injury. PMID:19654925

Hera - The HEASARC's New Data Analysis Service

NASA Technical Reports Server (NTRS)

Pence, William

2006-01-01

Hera is the new computer service provided by the HEASARC at the NASA Goddard Space Flight Center that enables qualified student and professional astronomical researchers to immediately begin analyzing scientific data from high-energy astrophysics missions. All the necessary resources needed to do the data analysis are freely provided by Hera, including: * the latest version of the hundreds of scientific analysis programs in the HEASARC's HEASOFT package, as well as most of the programs in the Chandra CIAO package and the XMM-Newton SAS package. * high speed access to the terabytes of data in the HEASARC's high energy astrophysics Browse data archive. * a cluster of fast Linw workstations to run the software * ample local disk space to temporarily store the data and results. Some of the many features and different modes of using Hera are illustrated in this poster presentation.

EXPLORING FUNCTIONAL CONNECTIVITY IN FMRI VIA CLUSTERING.

PubMed

Venkataraman, Archana; Van Dijk, Koene R A; Buckner, Randy L; Golland, Polina

2009-04-01

In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering algorithms as alternatives to the commonly used Seed-Based Analysis. To enable clustering of the entire brain volume, we use the Nyström Method to approximate the necessary spectral decompositions. We apply K-Means, Spectral Clustering and Seed-Based Analysis to resting-state fMRI data collected from 45 healthy young adults. Without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via Seed-Based Analysis. Our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.

Extending cluster Lot Quality Assurance Sampling designs for surveillance programs

PubMed Central

Hund, Lauren; Pagano, Marcello

2014-01-01

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance based on the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible non-parametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. PMID:24633656

Extending cluster lot quality assurance sampling designs for surveillance programs.

PubMed

Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

Exploring the galaxy cluster-group transition regime at high redshifts. Physical properties of two newly detected z > 1 systems

NASA Astrophysics Data System (ADS)

Šuhada, R.; Fassbender, R.; Nastasi, A.; Böhringer, H.; de Hoon, A.; Pierini, D.; Santos, J. S.; Rosati, P.; Mühlegger, M.; Quintana, H.; Schwope, A. D.; Lamer, G.; Kohnert, J.; Pratt, G. W.

2011-06-01

Context. Multi-wavelength surveys for clusters of galaxies are opening a window on the elusive high-redshift (z > 1) cluster population. Well controlled statistical samples of distant clusters will enable us to answer questions about their cosmological context, early assembly phases and the thermodynamical evolution of the intracluster medium. Aims: We report on the detection of two z > 1 systems, XMMU J0302.2-0001 and XMMU J1532.2-0836, as part of the XMM-Newton Distant Cluster Project (XDCP) sample. We investigate the nature of the sources, measure their spectroscopic redshift and determine their basic physical parameters. Methods: The results of the present paper are based on the analysis of XMM-Newton archival data, optical/near-infrared imaging and deep optical follow-up spectroscopy of the clusters. Results: We confirm the X-ray source XMMU J0302.2-0001 as a gravitationally bound, bona fide cluster of galaxies at spectroscopic redshift z = 1.185. We estimate its M500 mass to (1.6 ± 0.3) × 1014 M⊙ from its measured X-ray luminosity. This ranks the cluster among intermediate mass system. In the case of XMMU J1532.2-0836 we find the X-ray detection to be coincident with a dynamically bound system of galaxies at z = 1.358. Optical spectroscopy reveals the presence of a central active galactic nucleus, which can be a dominant source of the detected X-ray emission from this system. We provide upper limits of X-ray parameters for the system and discuss cluster identification challenges in the high-redshift low-mass cluster regime. A third, intermediate redshift (z = 0.647) cluster, XMMU J0302.1-0000, is serendipitously detected in the same field as XMMU J0302.2-0001. We provide its analysis as well. Based on observations obtained with ESO Telescopes at the Paranal Observatory under program ID 080.A-0659 and 081.A-0312, observations collected at the Centro Astrnómico Hispano Alemán (CAHA) at Calar Alto, Spain operated jointly by the Max-Planck Institut für Astronomie and the Instituto de Astrofísica de Andalucía (CSIC). X-ray observations were obtained by XMM-Newton.

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network.

PubMed

Wang, Jianxin; Zhong, Jiancheng; Chen, Gang; Li, Min; Wu, Fang-xiang; Pan, Yi

2015-01-01

Cluster analysis of biological networks is one of the most important approaches for identifying functional modules and predicting protein functions. Furthermore, visualization of clustering results is crucial to uncover the structure of biological networks. In this paper, ClusterViz, an APP of Cytoscape 3 for cluster analysis and visualization, has been developed. In order to reduce complexity and enable extendibility for ClusterViz, we designed the architecture of ClusterViz based on the framework of Open Services Gateway Initiative. According to the architecture, the implementation of ClusterViz is partitioned into three modules including interface of ClusterViz, clustering algorithms and visualization and export. ClusterViz fascinates the comparison of the results of different algorithms to do further related analysis. Three commonly used clustering algorithms, FAG-EC, EAGLE and MCODE, are included in the current version. Due to adopting the abstract interface of algorithms in module of the clustering algorithms, more clustering algorithms can be included for the future use. To illustrate usability of ClusterViz, we provided three examples with detailed steps from the important scientific articles, which show that our tool has helped several research teams do their research work on the mechanism of the biological networks.

Illinois Occupational Skill Standards: Agricultural Laboratory and Field Technician Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

These Illinois skill standards for the agricultural laboratory and field technician cluster are intended to serve as a guide to workforce preparation program providers as they define content for their programs and to employers as they establish the skills and standards necessary for job acquisition. They could also serve as a mechanism for…

Illinois Occupational Skill Standards: Lodging Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document of skill standards for the lodging cluster serves as a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. These 28 occupational skill standards describe what people should know and be able to do in an…

Illinois Occupational Skill Standards: Greenhouse/Nursery Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document of skill standards for the greenhouse/nursery cluster serves as a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. These 23 occupational skill standards describe what people should know and be able to do in an…

Illinois Occupational Skill Standards: Accounting Services Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

These Illinois skill standards for the accounting services cluster are intended to serve as a guide to workforce preparation program providers as they define content for their programs and to employers as they establish the skills and standards necessary for job acquisition. They could also serve as a mechanism for communication among education,…

Illinois Occupational Skill Standards: Machining Skills Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document of skill standards for the machining skills cluster serves as a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. These 67 occupational skill standards describe what people should know and be able to do in an…

The Effectiveness of Healthy Start Home Visit Program: Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Leung, Cynthia; Tsang, Sandra; Heung, Kitty

2015-01-01

Purpose: The study reported the effectiveness of a home visit program for disadvantaged Chinese parents with preschool children, using cluster randomized controlled trial design. Method: Participants included 191 parents and their children from 24 preschools, with 84 dyads (12 preschools) in the intervention group and 107 dyads (12 preschools) in…

Illinois Occupational Skill Standards: Landscape Technician Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document of skill standards for the landscape technician cluster serves as a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. These 19 occupational skill standards describe what people should know and be able to do in…

Career and Technical Education as Pathways: Factors Influencing Postcollege Earnings of Selected Career Clusters

ERIC Educational Resources Information Center

Compton, Jonathan I.; Laanan, Frankie Santos; Starobin, Soko S.

2010-01-01

This study investigated the relationship between student characteristics such as gender, race/ethnicity, program of study, degree completion, and earnings outcomes for students enrolled in career and technical education (CTE) programs within the business, information technology (IT), and marketing career clusters in community colleges to determine…

Illinois Occupational Skill Standards: Welding Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

These Illinois skill standards for the welding cluster are intended to serve as a guide to workforce preparation program providers as they define content for their programs and to employers as they establish the skills and standards necessary for job acquisition. They could also serve as a mechanism for communication among education, business,…

Fit 5 Kids TV reduction program for Latino preschoolers: A cluster randomized controlled trial

USDA-ARS?s Scientific Manuscript database

Reducing Latino preschoolers' TV viewing is needed to reduce their risk of obesity and other chronic diseases. This study's objective was to evaluate the Fit 5 Kids (F5K) TV reduction program's impact on Latino preschooler's TV viewing. The study design was a cluster randomized controlled trial (RCT...

A program to compute the soft Robinson-Foulds distance between phylogenetic networks.

PubMed

Lu, Bingxin; Zhang, Louxin; Leong, Hon Wai

2017-03-14

Over the past two decades, phylogenetic networks have been studied to model reticulate evolutionary events. The relationships among phylogenetic networks, phylogenetic trees and clusters serve as the basis for reconstruction and comparison of phylogenetic networks. To understand these relationships, two problems are raised: the tree containment problem, which asks whether a phylogenetic tree is displayed in a phylogenetic network, and the cluster containment problem, which asks whether a cluster is represented at a node in a phylogenetic network. Both the problems are NP-complete. A fast exponential-time algorithm for the cluster containment problem on arbitrary networks is developed and implemented in C. The resulting program is further extended into a computer program for fast computation of the Soft Robinson-Foulds distance between phylogenetic networks. Two computer programs are developed for facilitating reconstruction and validation of phylogenetic network models in evolutionary and comparative genomics. Our simulation tests indicated that they are fast enough for use in practice. Additionally, the distribution of the Soft Robinson-Foulds distance between phylogenetic networks is demonstrated to be unlikely normal by our simulation data.

Effect of a Nutrition Supplement and Physical Activity Program on Pneumonia and Walking Capacity in Chilean Older People: A Factorial Cluster Randomized Trial

PubMed Central

Dangour, Alan D.; Albala, Cecilia; Allen, Elizabeth; Grundy, Emily; Walker, Damian G.; Aedo, Cristian; Sanchez, Hugo; Fletcher, Olivia; Elbourne, Diana; Uauy, Ricardo

2011-01-01

Background Ageing is associated with increased risk of poor health and functional decline. Uncertainties about the health-related benefits of nutrition and physical activity for older people have precluded their widespread implementation. We investigated the effectiveness and cost-effectiveness of a national nutritional supplementation program and/or a physical activity intervention among older people in Chile. Methods and Findings We conducted a cluster randomized factorial trial among low to middle socioeconomic status adults aged 65–67.9 years living in Santiago, Chile. We randomized 28 clusters (health centers) into the study and recruited 2,799 individuals in 2005 (∼100 per cluster). The interventions were a daily micronutrient-rich nutritional supplement, or two 1-hour physical activity classes per week, or both interventions, or neither, for 24 months. The primary outcomes, assessed blind to allocation, were incidence of pneumonia over 24 months, and physical function assessed by walking capacity 24 months after enrolment. Adherence was good for the nutritional supplement (∼75%), and moderate for the physical activity intervention (∼43%). Over 24 months the incidence rate of pneumonia did not differ between intervention and control clusters (32.5 versus 32.6 per 1,000 person years respectively; risk ratio = 1.00; 95% confidence interval 0.61–1.63; p = 0.99). In intention-to-treat analysis, after 24 months there was a significant difference in walking capacity between the intervention and control clusters (mean difference 33.8 meters; 95% confidence interval 13.9–53.8; p = 0.001). The overall cost of the physical activity intervention over 24 months was US$164/participant; equivalent to US$4.84/extra meter walked. The number of falls and fractures was balanced across physical activity intervention arms and no serious adverse events were reported for either intervention. Conclusions Chile's nutritional supplementation program for older people is not effective in reducing the incidence of pneumonia. This trial suggests that the provision of locally accessible physical activity classes in a transition economy population can be a cost-effective means of enhancing physical function in later life. Trial registration Current Controlled Trials ISRCTN 48153354 Please see later in the article for the Editors' Summary PMID:21526229

Membership and Coronal Activity in the NGC 2232 and Cr 140 Open Clusters

NASA Technical Reports Server (NTRS)

Patten, Brian M.; Oliversen, Ronald J. (Technical Monitor)

2001-01-01

This is the second annual performance report for our grant "Membership and Coronal Activity in the NGC 2232 and Cr 140 Open Clusters." We propose to identify X-ray sources and extract net source counts in 8 archival ROSAT HRI images in the regions of the NGC 2232 and Cr 140 open clusters. These X-ray data will be combined with ground-based photometry and spectroscopy in order to identify G, K, and early-M type cluster members. At present, no members later than approximately F5 are currently known for either cluster. With ages of approximately 25 Myr and at a distance of just 320 - 360 pc, the combined late-type membership of the NGC 2232 and Cr 140 clusters will yield an almost unique sample of solar-type stars in the post-T Tauri/pre-main sequence phase of evolution. These stars will be used to assess the level and dispersion in coronal activity levels, as part of a probe of the importance of magnetic braking and the level of magnetic dynamo activity, for solar-type stars just before they reach the ZAMS. Over the past year we have successfully acquired all of the ground-based data necessary to support the analysis of the archival ROSAT X-ray data in the regions around both of these clusters. By the end of 2001 we expect to have completed the reduction and analysis of the ground-based photometry and spectroscopy and will begin the integration of these data with the ROSAT X-ray data. A certain amount of pressure to complete the work on NGC 2232 is coming from the SIRTF project, as this cluster may be a key component to a circumstellar disk evolution GTO program. We are only too happy to try to help and have worked to speed the analysis as much as possible. The primary activity to be undertaken in the next few months is the integration of the groundbased photometry and spectroscopy with the archival ROSAT X-ray data and then writing the paper summarizing our results. The most time consuming portion of this next phase is, of course, seeing the paper through publication in a peer-reviewed journal. Therefore, we have requested a no-cost extension to the grant to allow us to bring this project to a conclusion.

Variability among Capsicum baccatum accessions from Goiás, Brazil, assessed by morphological traits and molecular markers.

PubMed

Martinez, A L A; Araújo, J S P; Ragassi, C F; Buso, G S C; Reifschneider, F J B

2017-07-06

Capsicum peppers are native to the Americas, with Brazil being a significant diversity center. Capsicum baccatum accessions at Instituto Federal (IF) Goiano represent a portion of the species genetic resources from central Brazil. We aimed to characterize a C. baccatum working collection comprising 27 accessions and 3 commercial cultivars using morphological traits and molecular markers to describe its genetic and morphological variability and verify the occurrence of duplicates. This set included 1 C. baccatum var. praetermissum and 29 C. baccatum var. pendulum with potential for use in breeding programs. Twenty-two morphological descriptors, 57 inter-simple sequence repeat, and 34 random amplified polymorphic DNA markers were used. Genetic distance was calculated through the Jaccard similarity index and genetic variability through cluster analysis using the unweighted pair group method with arithmetic mean, resulting in dendrograms for both morphological analysis and molecular analysis. Genetic variability was found among C. baccatum var. pendulum accessions, and the distinction between the two C. baccatum varieties was evident in both the morphological and molecular analyses. The 29 C. baccatum var. pendulum genotypes clustered in four groups according to fruit type in the morphological analysis. They formed seven groups in the molecular analysis, without a clear correspondence with morphology. No duplicates were found. The results describe the genetic and morphological variability, provide a detailed characterization of genotypes, and discard the possibility of duplicates within the IF Goiano C. baccatum L. collection. This study will foment the use of this germplasm collection in C. baccatum breeding programs.

Geographical Analysis of the Distribution and Spread of Human Rabies in China from 2005 to 2011

PubMed Central

Yin, Wenwu; Yu, Hongjie; Si, Yali; Li, Jianhui; Zhou, Yuanchun; Zhou, Xiaoyan; Magalhães, Ricardo J. Soares.

2013-01-01

Background Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China. Methods We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread. Findings Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease. Conclusion Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program. PMID:23991098

Using Fuzzy Clustering for Real-time Space Flight Safety

NASA Technical Reports Server (NTRS)

Lee, Charles; Haskell, Richard E.; Hanna, Darrin; Alena, Richard L.

2004-01-01

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Ground-Based Calibration Support for Two Approved HST Programs

NASA Technical Reports Server (NTRS)

Stauffer, John R.

1998-01-01

This final report is a summary of the study on ground-based calibration support for two approved HST programs. A large set of new rotational periods for low mass stars in the Pleiades open cluster have been published and used to help interpret chromospheric and coronal activity indicators for low mass stars in the cluster. The Caltech/TJC/NASA Keck telescope in Hawaii has also been used to obtain spectra of brown dwarf candidates in the Pleiades. Those spectra help to derive an accurate and precise new age for that fiducial open cluster.

Mississippi Curriculum Framework for Business and Office and Related Technology Cluster. Office Systems Technology (CIP: 52.0401--Administrative Assistant/Secretarial). Accounting Technology (CIP: 52.0302). Medical Office Technology (CIP: 52.0404--Medical Admin. Asst./Secretarial). Microcomputer Technology (CIP: 52.0490). Court Reporting Technology (CIP: 52.0405). Paralegal Technology (CIP: Paralegal/Legal Assistant).

ERIC Educational Resources Information Center

Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for four programs in the postsecondary-level business and office cluster (office systems, accounting, medical office, and microcomputer technologies) and two programs in the legal cluster (court reporting and paralegal…

Cluster Analysis in Nursing Research: An Introduction, Historical Perspective, and Future Directions.

PubMed

Dunn, Heather; Quinn, Laurie; Corbridge, Susan J; Eldeirawi, Kamal; Kapella, Mary; Collins, Eileen G

2017-05-01

The use of cluster analysis in the nursing literature is limited to the creation of classifications of homogeneous groups and the discovery of new relationships. As such, it is important to provide clarity regarding its use and potential. The purpose of this article is to provide an introduction to distance-based, partitioning-based, and model-based cluster analysis methods commonly utilized in the nursing literature, provide a brief historical overview on the use of cluster analysis in nursing literature, and provide suggestions for future research. An electronic search included three bibliographic databases, PubMed, CINAHL and Web of Science. Key terms were cluster analysis and nursing. The use of cluster analysis in the nursing literature is increasing and expanding. The increased use of cluster analysis in the nursing literature is positioning this statistical method to result in insights that have the potential to change clinical practice.

ICAP - An Interactive Cluster Analysis Procedure for analyzing remotely sensed data

NASA Technical Reports Server (NTRS)

Wharton, S. W.; Turner, B. J.

1981-01-01

An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. ICAP differs from conventional clustering algorithms by allowing the analyst to optimize the cluster configuration by inspection, rather than by manipulating process parameters. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters, and the analyst, who can evaluate and elect to modify the cluster structure. Clusters can be deleted, or lumped together pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The principal advantage of this approach is that it allows prior information (when available) to be used directly in the analysis, since the analyst interacts with ICAP in a straightforward manner, using basic terms with which he is more likely to be familiar. Results from testing ICAP showed that an informed use of ICAP can improve classification, as compared to an existing cluster analysis procedure.

Spots and the Activity of Stars in the Hyades Cluster from Observations with the Kepler Space Telescope (K2)

NASA Astrophysics Data System (ADS)

Savanov, I. S.; Dmitrienko, E. S.

2018-03-01

Observations of the K2 mission (continuing the program of the Kepler Space Telescope) are used to estimate the spot coverage S (the fractional area of spots on the surface of an active star) for stars of the Hyades cluster. The analysis is based on data on the photometric variations of 47 confirmed single cluster members, together with their atmospheric parameters, masses, and rotation periods. The resulting values of S for these Hyades objects are lower than those stars of the Pleiades cluster (on average, by Δ S 0.05-0.06). A comparison of the results of studies of cool, low-mass dwarfs in the Hyades and Pleiades clusters, as well as the results of a study of 1570 M stars from the main field observed in the Kepler SpaceMission, indicates that the Hyades stars are more evolved than the Pleiades stars, and demonstrate lower activity. The activity of seven solar-type Hyades stars ( S = 0.013 ± 0.006) almost approaches the activity level of the present-day Sun, and is lower than the activity of solar-mass stars in the Pleiades ( S = 0.031 ± 0.003). Solar-type stars in the Hyades rotate faster than the Sun (< P> = 8.6 d ), but slower than similar Pleiades stars.

Spatial Analysis of HIV Positive Injection Drug Users in San Francisco, 1987 to 2005

PubMed Central

Martinez, Alexis N.; Mobley, Lee R.; Lorvick, Jennifer; Novak, Scott P.; Lopez, Andrea M.; Kral, Alex H.

2014-01-01

Spatial analyses of HIV/AIDS related outcomes are growing in popularity as a tool to understand geographic changes in the epidemic and inform the effectiveness of community-based prevention and treatment programs. The Urban Health Study was a serial, cross-sectional epidemiological study of injection drug users (IDUs) in San Francisco between 1987 and 2005 (N = 29,914). HIV testing was conducted for every participant. Participant residence was geocoded to the level of the United States Census tract for every observation in dataset. Local indicator of spatial autocorrelation (LISA) tests were used to identify univariate and bivariate Census tract clusters of HIV positive IDUs in two time periods. We further compared three tract level characteristics (% poverty, % African Americans, and % unemployment) across areas of clustered and non-clustered tracts. We identified significant spatial clustering of high numbers of HIV positive IDUs in the early period (1987–1995) and late period (1996–2005). We found significant bivariate clusters of Census tracts where HIV positive IDUs and tract level poverty were above average compared to the surrounding areas. Our data suggest that poverty, rather than race, was an important neighborhood characteristic associated with the spatial distribution of HIV in SF and its spatial diffusion over time. PMID:24722543

US Household Food Shopping Patterns: Dynamic Shifts Since 2000 And Socioeconomic Predictors.

PubMed

Stern, Dalia; Robinson, Whitney R; Ng, Shu Wen; Gordon-Larsen, Penny; Popkin, Barry M

2015-11-01

Under the assumption that differential food access might underlie nutritional disparities, programs and policies have focused on the need to build supermarkets in underserved areas, in an effort to improve dietary quality. However, there is limited evidence about which types of stores are used by households of different income levels and differing races/ethnicities. We used cross-sectional cluster analysis to derive shopping patterns from US households' volume food purchases by store from 2000 to 2012. Multinomial logistic regression identified household socioeconomic characteristics that were associated with shopping patterns in 2012. We found three food shopping patterns or clusters: households that primarily shopped at grocery stores, households that primarily shopped at mass merchandisers, and a combination cluster in which households split their purchases among multiple store types. In 2012 we found no income or race/ethnicity differences for the cluster of households that primarily shopped at grocery stores. However, low-income non-Hispanic blacks (versus non-Hispanic whites) had a significantly lower probability of belonging to the mass merchandise cluster. These varied shopping patterns must be considered in future policy initiatives. Furthermore, it is important to continue studying the complex rationales for people's food shopping patterns. Project HOPE—The People-to-People Health Foundation, Inc.

Approximate kernel competitive learning.

PubMed

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Mathematical description and program documentation for CLASSY, an adaptive maximum likelihood clustering method

NASA Technical Reports Server (NTRS)

Lennington, R. K.; Rassbach, M. E.

1979-01-01

Discussed in this report is the clustering algorithm CLASSY, including detailed descriptions of its general structure and mathematical background and of the various major subroutines. The report provides a development of the logic and equations used with specific reference to program variables. Some comments on timing and proposed optimization techniques are included.

Efficacy of a Universal Parent Training Program (HOPE-20): Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Leung, Cynthia; Tsang, Sandra; Kwan, H. W.

2017-01-01

Objective: This study examined the efficacy of Hands-On Parent Empowerment-20 (HOPE-20) program. Methods: Eligible participants were parents residing in Hong Kong with target children aged 2 years attending nursery schools. Cluster randomized control trial was adopted, with 10 schools (110 participants) assigned to intervention group and 8 schools…

Special features of the CLUSTER antenna and radial booms design, development and verification

NASA Technical Reports Server (NTRS)

Gianfiglio, G.; Yorck, M.; Luhmann, H. J.

1995-01-01

CLUSTER is a scientific space mission to in-situ investigate the Earth's plasma environment by means of four identical spin-stabilized spacecraft. Each spacecraft is provided with a set of four rigid booms: two Antenna Booms and two Radial Booms. This paper presents a summary of the boom development and verification phases addressing the key aspects of the Radial Boom design. In particular, it concentrates on the difficulties encountered in fulfilling simultaneously the requirements of minimum torque ratio and maximum allowed shock loads at boom latching for this two degree of freedom boom. The paper also provides an overview of the analysis campaign and testing program performed to achieve sufficient confidence in the boom performance and operation.

Business Clusters: Building on Local Strengths.

ERIC Educational Resources Information Center

Baldwin, Fred D.

2001-01-01

The Northwest Pennsylvania Industrial Resource Center's "wood cluster initiative" illustrates the benefits of rural business clusters. The initiative is turning a loose grouping of timber and forest-product firms into a competitive system by providing technical assistance, helping businesses plan and conduct job training programs,…

Industrial Occupations. Education for Employment Task Lists.

ERIC Educational Resources Information Center

Lake County Area Vocational Center, Grayslake, IL.

The duties and tasks found in these task lists form the basis of instructional content for secondary, postsecondary, and adult occupational training programs for industrial occupations. The industrial occupations are divided into eight clusters. The clusters and occupations are: construction cluster (bricklayer, carpenter, building maintenance…

Swarm v2: highly-scalable and high-resolution amplicon clustering

PubMed Central

Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

2015-01-01

Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks. PMID:26713226

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

Adding a post-training FIFA 11+ exercise program to the pre-training FIFA 11+ injury prevention program reduces injury rates among male amateur soccer players: a cluster-randomised trial.

PubMed

Al Attar, Wesam Saleh A; Soomro, Najeebullah; Pappas, Evangelos; Sinclair, Peter J; Sanders, Ross H

2017-10-01

Does adding a post-training Fédération Internationale de Football Association (FIFA) 11+ exercise program to the pre-training FIFA 11+ injury prevention program reduce injury rates among male amateur soccer players? Cluster-randomised, controlled trial with concealed allocation. Twenty-one teams of male amateur soccer players aged 14 to 35 years were randomly assigned to the experimental group (n=10 teams, 160 players) or the control group (n=11 teams, 184 players). Both groups performed pre-training FIFA 11+ exercises for 20minutes. The experimental group also performed post-training FIFA 11+ exercises for 10minutes. The primary outcomes measures were incidence of overall injury, incidence of initial and recurrent injury, and injury severity. The secondary outcome measure was compliance to the experimental intervention (pre and post FIFA 11+ program) and the control intervention (pre FIFA 11+ program). During one season, 26 injuries (team mean=0.081 injuries/1000 exposure hours, SD=0.064) were reported in the experimental group, and 82 injuries were reported in the control group (team mean=0.324 injuries/1000hours, SD=0.084). Generalised Estimating Equations were applied with an intention-to-treat analysis. The pre and post FIFA 11+ program reduced the total number of injuries (χ 2 (1)=11.549, p=0.001) and the incidence of initial injury (χ 2 (2)=8.987, p=0.003) significantly more than the pre FIFA 11+ program alone. However, the odds of suffering a recurrent injury were not different between the two groups (χ 2 (1)=2.350, p=0.125). Moreover, the severity level of injuries was not dependent upon whether or not the pre and post FIFA 11+ program was implemented (χ 2 (1)=0.016, p=0.898). Implementation of the FIFA 11+ program pre-training and post-training reduced overall injury rates in male amateur soccer players more than the pre FIFA 11+ program alone. ACTRN12615001206516. [Al Attar WSA, Soomro N, Pappas E, Sinclair PJ, Sanders RH (2017) Adding a post-training FIFA 11+ exercise program to the pre-training FIFA 11+ injury prevention program reduces injury rates among male amateur soccer players: a cluster-randomised trial. Journal of Physiotherapy 63: 235-242]. Copyright © 2017 Australian Physiotherapy Association. Published by Elsevier B.V. All rights reserved.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome.

PubMed

Lalonde, Michel; Wells, R Glenn; Birnie, David; Ruddy, Terrence D; Wassenaar, Richard

2014-07-01

Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

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

Lalonde, Michel, E-mail: mlalonde15@rogers.com; Wassenaar, Richard; Wells, R. Glenn

2014-07-15

Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: Aboutmore » 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). Conclusions: A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.« less

Precise and Efficient Static Array Bound Checking for Large Embedded C Programs

NASA Technical Reports Server (NTRS)

Venet, Arnaud

2004-01-01

In this paper we describe the design and implementation of a static array-bound checker for a family of embedded programs: the flight control software of recent Mars missions. These codes are large (up to 250 KLOC), pointer intensive, heavily multithreaded and written in an object-oriented style, which makes their analysis very challenging. We designed a tool called C Global Surveyor (CGS) that can analyze the largest code in a couple of hours with a precision of 80%. The scalability and precision of the analyzer are achieved by using an incremental framework in which a pointer analysis and a numerical analysis of array indices mutually refine each other. CGS has been designed so that it can distribute the analysis over several processors in a cluster of machines. To the best of our knowledge this is the first distributed implementation of static analysis algorithms. Throughout the paper we will discuss the scalability setbacks that we encountered during the construction of the tool and their impact on the initial design decisions.

Street Ball, Swim Team and the Sour Cream Machine: A Cluster Analysis of out of School Time Participation Portfolios

ERIC Educational Resources Information Center

Nelson, Ingrid Ann; Gastic, Billie

2009-01-01

Adolescents spend only a fraction of their waking hours in school and what they do with the rest of their time varies dramatically. Despite this, research on out-of-school time has largely focused on structured programming. The authors analyzed data from the Educational Longitudinal Study of 2002 (ELS:2002) to examine the out-of-school time…

Genetic diversity analysis of Varronia curassavica Jacq. accessions using ISSR markers.

PubMed

Brito, F A; Nizio, D A C; Silva, A V C; Diniz, L E C; Rabbani, A R C; Arrigoni-Blank, M F; Alvares-Carvalho, S V; Figueira, G M; Montanari Júnior, I; Blank, A F

2016-09-02

Varronia curassavica Jacq. is a medicinal and aromatic plant from Brazil with significant economic importance. Studies on genetic diversity in active germplasm banks (AGB) are essential for conservation and breeding programs. The aim of this study was to analyze the genetic diversity of V. curassavica accessions of the AGB of Medicinal and Aromatic Plants of the Federal University of Sergipe (UFS), using inter-simple sequence repeat molecular markers. Twenty-four primers were tested, and 14 were polymorphic and informative, resulting in 149 bands with 97.98% polymorphism. The UPGMA dendrogram divided the accessions into Clusters I and II. Jaccard similarity coefficients for pair-wise comparisons of accessions ranged between 0.24 and 0.78. The pairs of accessions VCUR-001/VCUR-503, VCUR-001/VCUR-504, and VCUR-104/VCUR-501 showed relatively low similarity (0.24), and the pair of accessions VCUR-402/VCUR- 403 showed medium similarity (0.78). Twenty-eight accessions were divided into three distinct clusters, according to the STRUCTURE analysis. The genetic diversity of V. curassavica in the AGB of UFS is low to medium, and it requires expansion. Accession VCUR-802 is the most suitable for selection in breeding program of this species, since it clearly represents all of the diversity present in the AGB.

Analysis of RXTE data on Clusters of Galaxies

NASA Technical Reports Server (NTRS)

Petrosian, Vahe

2004-01-01

This grant provided support for the reduction, analysis and interpretation of of hard X-ray (HXR, for short) observations of the cluster of galaxies RXJO658--5557 scheduled for the week of August 23, 2002 under the RXTE Cycle 7 program (PI Vahe Petrosian, Obs. ID 70165). The goal of the observation was to search for and characterize the shape of the HXR component beyond the well established thermal soft X-ray (SXR) component. Such hard components have been detected in several nearby clusters. distant cluster would provide information on the characteristics of this radiation at a different epoch in the evolution of the imiverse and shed light on its origin. We (Petrosian, 2001) have argued that thermal bremsstrahlung, as proposed earlier, cannot be the mechanism for the production of the HXRs and that the most likely mechanism is Compton upscattering of the cosmic microwave radiation by relativistic electrons which are known to be present in the clusters and be responsible for the observed radio emission. Based on this picture we estimated that this cluster, in spite of its relatively large distance, will have HXR signal comparable to the other nearby ones. The planned observation of a relatively The proposed RXTE observations were carried out and the data have been analyzed. We detect a hard X-ray tail in the spectrum of this cluster with a flux very nearly equal to our predicted value. This has strengthen the case for the Compton scattering model. We intend the data obtained via this observation to be a part of a larger data set. We have identified other clusters of galaxies (in archival RXTE and other instrument data sets) with sufficiently high quality data where we can search for and measure (or at least put meaningful limits) on the strength of the hard component. With these studies we expect to clarify the mechanism for acceleration of particles in the intercluster medium and provide guidance for future observations of this intriguing phenomenon by instrument on GLAST. The details of the nonthermal particle population has important implications for the theories of cluster formation, mergers and evolution. The results of this work were first presented at the High Energy Division meeting of the American astronomical Society at Mt. Tremblene, Canada (Petrosian et al. 2003). and in an invited review talk at the General Assembly of the International Astronomical Union at Sydney, Australia (Petrosian, 2003). A paper describe the observations, the data analysis and its implication is being prepared for publication in the Astrophysical Journal.

Near real-time space-time cluster analysis for detection of enteric disease outbreaks in a community setting.

PubMed

Glatman-Freedman, Aharona; Kaufman, Zalman; Kopel, Eran; Bassal, Ravit; Taran, Diana; Valinsky, Lea; Agmon, Vered; Shpriz, Manor; Cohen, Daniel; Anis, Emilia; Shohat, Tamy

2016-08-01

To enhance timely surveillance of bacterial enteric pathogens, space-time cluster analysis was introduced in Israel in May 2013. Stool isolation data of Salmonella, Shigella, and Campylobacter from patients of a large Health Maintenance Organization were analyzed weekly by ArcGIS and SaTScan, and cluster results were sent promptly to local departments of health (LDOHs). During eighteen months, we identified 52 Shigella sonnei clusters, two Salmonella clusters, and no Campylobacter clusters. S. sonnei clusters lasted from one to 33 days and included three to 30 individuals. Thirty-one (60%) of the S. sonnei clusters were known to LDOHs prior to cluster analysis. Clusters not previously known by the LDOHs prompted epidemiologic investigations. In 31 of the 37 (84%) confirmed clusters, educational institutes (nursery schools, kindergartens, and a primary school) were involved. Cluster analysis demonstrated capability to complement enteric disease surveillance. Scaling up the system can further enhance timely detection and control of outbreaks. Copyright © 2016 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

An effective fuzzy kernel clustering analysis approach for gene expression data.

PubMed

Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

2015-01-01

Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

PubMed

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

2015-05-01

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2015-01-01

Abstract To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice. PMID:25560745

Identifying environmental risk factors for human neural tube defects before and after folic acid supplementation

PubMed Central

Liao, Yilan; Wang, Jinfeng; Li, Xinhu; Guo, Yaoqin; Zheng, Xiaoying

2009-01-01

Background Birth defects are a major cause of infant mortality and disability in many parts of the world. Neural tube defects (NTDs) are one of the most common types of birth defects. In 2001, the Chinese population and family planning commission initiated a national intervention program for the prevention of birth defects. A key step in the program was the introduction of folic acid supplementation. Of interest in the present study was to determine whether folic acid supplementation has the same protective effect on NTDs under various geographical and socioeconomic conditions within the Chinese population and the nature in which the influence of environmental factors varied after folic acid supplementation. Methods In this study, Heshun was selected as the region of interest as a surrogate for helping to answer some of the questions raised in this study on the impact of the intervention program. Spatial filtering in combination with GIS software was used to detect annual potential clusters from 1998 to 2005 in Heshun, and Kruskal-wallis test and multivariate regression were applied to identify the environmental risk factors for NTDs among various regions. Results In 1998, a significant (p < 0.100) NTDs cluster was detected in the west of Heshun. After folic acid supplementation, the significant clusters gradually moved from west to east. However, during the study period, most of the clusters appeared in the middle region of Heshun where more than 95 percent of the coal mines of Heshun are located. For the analysis, buffer regions of the coal mine zone were built in a GIS environment. It was found that the correlations between environmental risk factors and NTDs vary among the buffer regions. Conclusion This suggests that the government needs to adapt the intervention measures according to local conditions. More attention needs to be paid to the poor and to people living in areas near coal mines. PMID:19835574

The Gaia-ESO Survey: the present-day radial metallicity distribution of the Galactic disc probed by pre-main-sequence clusters

NASA Astrophysics Data System (ADS)

Spina, L.; Randich, S.; Magrini, L.; Jeffries, R. D.; Friel, E. D.; Sacco, G. G.; Pancino, E.; Bonito, R.; Bravi, L.; Franciosini, E.; Klutsch, A.; Montes, D.; Gilmore, G.; Vallenari, A.; Bensby, T.; Bragaglia, A.; Flaccomio, E.; Koposov, S. E.; Korn, A. J.; Lanzafame, A. C.; Smiljanic, R.; Bayo, A.; Carraro, G.; Casey, A. R.; Costado, M. T.; Damiani, F.; Donati, P.; Frasca, A.; Hourihane, A.; Jofré, P.; Lewis, J.; Lind, K.; Monaco, L.; Morbidelli, L.; Prisinzano, L.; Sousa, S. G.; Worley, C. C.; Zaggia, S.

2017-05-01

Context. The radial metallicity distribution in the Galactic thin disc represents a crucial constraint for modelling disc formation and evolution. Open star clusters allow us to derive both the radial metallicity distribution and its evolution over time. Aims: In this paper we perform the first investigation of the present-day radial metallicity distribution based on [Fe/H] determinations in late type members of pre-main-sequence clusters. Because of their youth, these clusters are therefore essential for tracing the current interstellar medium metallicity. Methods: We used the products of the Gaia-ESO Survey analysis of 12 young regions (age < 100 Myr), covering Galactocentric distances from 6.67 to 8.70 kpc. For the first time, we derived the metal content of star forming regions farther than 500 pc from the Sun. Median metallicities were determined through samples of reliable cluster members. For ten clusters the membership analysis is discussed in the present paper, while for other two clusters (I.e. Chamaeleon I and Gamma Velorum) we adopted the members identified in our previous works. Results: All the pre-main-sequence clusters considered in this paper have close-to-solar or slightly sub-solar metallicities. The radial metallicity distribution traced by these clusters is almost flat, with the innermost star forming regions having [Fe/H] values that are 0.10-0.15 dex lower than the majority of the older clusters located at similar Galactocentric radii. Conclusions: This homogeneous study of the present-day radial metallicity distribution in the Galactic thin disc favours models that predict a flattening of the radial gradient over time. On the other hand, the decrease of the average [Fe/H] at young ages is not easily explained by the models. Our results reveal a complex interplay of several processes (e.g. star formation activity, initial mass function, supernova yields, gas flows) that controlled the recent evolution of the Milky Way. Based on observations made with the ESO/VLT, at Paranal Observatory, under program 188.B-3002 (The Gaia-ESO Public Spectroscopic Survey).Full Table 1 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/601/A70

Bulk tank milk prevalence and production losses, spatial analysis, and predictive risk mapping of Ostertagia ostertagi infections in Mexican cattle herds.

PubMed

Villa-Mancera, Abel; Pastelín-Rojas, César; Olivares-Pérez, Jaime; Córdova-Izquierdo, Alejandro; Reynoso-Palomar, Alejandro

2018-05-01

This study investigated the prevalence, production losses, spatial clustering, and predictive risk mapping in different climate zones in five states of Mexico. The bulk tank milk samples obtained between January and April 2015 were analyzed for antibodies against Ostertagia ostertagi using the Svanovir ELISA. A total of 1204 farm owners or managers answered the questionnaire. The overall herd prevalence and mean optical density ratio (ODR) of parasite were 61.96% and 0.55, respectively. Overall, the production loss was approximately 0.542 kg of milk per parasited cow per day (mean ODR = 0.92, 142 farms, 11.79%). The spatial disease cluster analysis using SatScan software indicated that two high-risk clusters were observed. In the multivariable analysis, three models were tested for potential association with the ELISA results supported by climatic, environmental, and management factors. The final logistic regression model based on both climatic/environmental and management variables included the factors rainfall, elevation, land surface temperature (LST) day, and parasite control program that were significantly associated with an increased risk of infection. Geostatistical kriging was applied to generate a risk map for the presence of parasite in dairy cattle herds in Mexico. The results indicate that climatic and meteorological factors had a higher potential impact on the spatial distribution of O. ostertagi than the management factors.

RSAT 2018: regulatory sequence analysis tools 20th anniversary.

PubMed

Nguyen, Nga Thi Thuy; Contreras-Moreira, Bruno; Castro-Mondragon, Jaime A; Santana-Garcia, Walter; Ossio, Raul; Robles-Espinoza, Carla Daniela; Bahin, Mathieu; Collombet, Samuel; Vincens, Pierre; Thieffry, Denis; van Helden, Jacques; Medina-Rivera, Alejandra; Thomas-Chollier, Morgane

2018-05-02

RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATAC-seq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or refactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variation-scan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seq-bed), to select motifs from motif collections (retrieve-matrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20-year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

Management and Analysis of Radiation Portal Monitor Data

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

Rowe, Nathan C; Alcala, Scott; Crye, Jason Michael

2014-01-01

Oak Ridge National Laboratory (ORNL) receives, archives, and analyzes data from radiation portal monitors (RPMs). Over time the amount of data submitted for analysis has grown significantly, and in fiscal year 2013, ORNL received 545 gigabytes of data representing more than 230,000 RPM operating days. This data comes from more than 900 RPMs. ORNL extracts this data into a relational database, which is accessed through a custom software solution called the Desktop Analysis and Reporting Tool (DART). DART is used by data analysts to complete a monthly lane-by-lane review of RPM status. Recently ORNL has begun to extend its datamore » analysis based on program-wide data processing in addition to the lane-by-lane review. Program-wide data processing includes the use of classification algorithms designed to identify RPMs with specific known issues and clustering algorithms intended to identify as-yet-unknown issues or new methods and measures for use in future classification algorithms. This paper provides an overview of the architecture used in the management of this data, performance aspects of the system, and additional requirements and methods used in moving toward an increased program-wide analysis paradigm.« less

Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-Means Cluster Analysis

ERIC Educational Resources Information Center

de Craen, Saskia; Commandeur, Jacques J. F.; Frank, Laurence E.; Heiser, Willem J.

2006-01-01

K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these…

Changing cluster composition in cluster randomised controlled trials: design and analysis considerations

PubMed Central

2014-01-01

Background There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. To illustrate this, we focus on the issue of cluster merging, considering the impact on the design, analysis and interpretation of trial outcomes. Methods We explored the effects of merging clusters on study power using standard methods of power calculation. We assessed the potential impacts on study findings of both homogeneous cluster merges (involving clusters randomised to the same arm of a trial) and heterogeneous merges (involving clusters randomised to different arms of a trial) by simulation. To determine the impact on bias and precision of treatment effect estimates, we applied standard methods of analysis to different populations under analysis. Results Cluster merging produced a systematic reduction in study power. This effect depended on the number of merges and was most pronounced when variability in cluster size was at its greatest. Simulations demonstrate that the impact on analysis was minimal when cluster merges were homogeneous, with impact on study power being balanced by a change in observed intracluster correlation coefficient (ICC). We found a decrease in study power when cluster merges were heterogeneous, and the estimate of treatment effect was attenuated. Conclusions Examples of cluster merges found in previously published reports of cluster randomised trials were typically homogeneous rather than heterogeneous. Simulations demonstrated that trial findings in such cases would be unbiased. However, simulations also showed that any heterogeneous cluster merges would introduce bias that would be hard to quantify, as well as having negative impacts on the precision of estimates obtained. Further methodological development is warranted to better determine how to analyse such trials appropriately. Interim recommendations include avoidance of cluster merges where possible, discontinuation of clusters following heterogeneous merges, allowance for potential loss of clusters and additional variability in cluster size in the original sample size calculation, and use of appropriate ICC estimates that reflect cluster size. PMID:24884591

A generalized analysis of hydrophobic and loop clusters within globular protein sequences

PubMed Central

Eudes, Richard; Le Tuan, Khanh; Delettré, Jean; Mornon, Jean-Paul; Callebaut, Isabelle

2007-01-01

Background Hydrophobic Cluster Analysis (HCA) is an efficient way to compare highly divergent sequences through the implicit secondary structure information directly derived from hydrophobic clusters. However, its efficiency and application are currently limited by the need of user expertise. In order to help the analysis of HCA plots, we report here the structural preferences of hydrophobic cluster species, which are frequently encountered in globular domains of proteins. These species are characterized only by their hydrophobic/non-hydrophobic dichotomy. This analysis has been extended to loop-forming clusters, using an appropriate loop alphabet. Results The structural behavior of hydrophobic cluster species, which are typical of protein globular domains, was investigated within banks of experimental structures, considered at different levels of sequence redundancy. The 294 more frequent hydrophobic cluster species were analyzed with regard to their association with the different secondary structures (frequencies of association with secondary structures and secondary structure propensities). Hydrophobic cluster species are predominantly associated with regular secondary structures, and a large part (60 %) reveals preferences for α-helices or β-strands. Moreover, the analysis of the hydrophobic cluster amino acid composition generally allows for finer prediction of the regular secondary structure associated with the considered cluster within a cluster species. We also investigated the behavior of loop forming clusters, using a "PGDNS" alphabet. These loop clusters do not overlap with hydrophobic clusters and are highly associated with coils. Finally, the structural information contained in the hydrophobic structural words, as deduced from experimental structures, was compared to the PSI-PRED predictions, revealing that β-strands and especially α-helices are generally over-predicted within the limits of typical β and α hydrophobic clusters. Conclusion The dictionary of hydrophobic clusters described here can help the HCA user to interpret and compare the HCA plots of globular protein sequences, as well as provides an original fundamental insight into the structural bricks of protein folds. Moreover, the novel loop cluster analysis brings additional information for secondary structure prediction on the whole sequence through a generalized cluster analysis (GCA), and not only on regular secondary structures. Such information lays the foundations for developing a new and original tool for secondary structure prediction. PMID:17210072

Understanding the many-body expansion for large systems. I. Precision considerations

NASA Astrophysics Data System (ADS)

Richard, Ryan M.; Lao, Ka Un; Herbert, John M.

2014-07-01

Electronic structure methods based on low-order "n-body" expansions are an increasingly popular means to defeat the highly nonlinear scaling of ab initio quantum chemistry calculations, taking advantage of the inherently distributable nature of the numerous subsystem calculations. Here, we examine how the finite precision of these subsystem calculations manifests in applications to large systems, in this case, a sequence of water clusters ranging in size up to (H_2O)_{47}. Using two different computer implementations of the n-body expansion, one fully integrated into a quantum chemistry program and the other written as a separate driver routine for the same program, we examine the reproducibility of total binding energies as a function of cluster size. The combinatorial nature of the n-body expansion amplifies subtle differences between the two implementations, especially for n ⩾ 4, leading to total energies that differ by as much as several kcal/mol between two implementations of what is ostensibly the same method. This behavior can be understood based on a propagation-of-errors analysis applied to a closed-form expression for the n-body expansion, which is derived here for the first time. Discrepancies between the two implementations arise primarily from the Coulomb self-energy correction that is required when electrostatic embedding charges are implemented by means of an external driver program. For reliable results in large systems, our analysis suggests that script- or driver-based implementations should read binary output files from an electronic structure program, in full double precision, or better yet be fully integrated in a way that avoids the need to compute the aforementioned self-energy. Moreover, four-body and higher-order expansions may be too sensitive to numerical thresholds to be of practical use in large systems.

Understanding the many-body expansion for large systems. I. Precision considerations

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

Richard, Ryan M.; Lao, Ka Un; Herbert, John M., E-mail: herbert@chemistry.ohio-state.edu

2014-07-07

Electronic structure methods based on low-order “n-body” expansions are an increasingly popular means to defeat the highly nonlinear scaling of ab initio quantum chemistry calculations, taking advantage of the inherently distributable nature of the numerous subsystem calculations. Here, we examine how the finite precision of these subsystem calculations manifests in applications to large systems, in this case, a sequence of water clusters ranging in size up to (H{sub 2}O){sub 47}. Using two different computer implementations of the n-body expansion, one fully integrated into a quantum chemistry program and the other written as a separate driver routine for the same program,more » we examine the reproducibility of total binding energies as a function of cluster size. The combinatorial nature of the n-body expansion amplifies subtle differences between the two implementations, especially for n ⩾ 4, leading to total energies that differ by as much as several kcal/mol between two implementations of what is ostensibly the same method. This behavior can be understood based on a propagation-of-errors analysis applied to a closed-form expression for the n-body expansion, which is derived here for the first time. Discrepancies between the two implementations arise primarily from the Coulomb self-energy correction that is required when electrostatic embedding charges are implemented by means of an external driver program. For reliable results in large systems, our analysis suggests that script- or driver-based implementations should read binary output files from an electronic structure program, in full double precision, or better yet be fully integrated in a way that avoids the need to compute the aforementioned self-energy. Moreover, four-body and higher-order expansions may be too sensitive to numerical thresholds to be of practical use in large systems.« less

A school-based sleep education program for adolescents: a cluster randomized trial.

PubMed

Wing, Yun Kwok; Chan, Ngan Yin; Man Yu, Mandy Wai; Lam, Siu Ping; Zhang, Jihui; Li, Shirley Xin; Kong, Alice Pik Shan; Li, Albert Martin

2015-03-01

To evaluate the effectiveness of a multilevel and multimodal school-based education program. A cluster randomized controlled trial with 14 secondary schools in Hong Kong and a total of 3713 students (intervention: 1545 vs control: 2168; 40.2% boys; mean age ± SD: 14.72 ± 1.53 years) were included in the final analysis. The intervention included a town hall seminar, small class workshops, a slogan competition, a brochure, and an educational Web site. Their parents and teachers were offered sleep education seminars. The control schools did not receive any sleep program. Data were collected before and 5 weeks after the intervention. The students in the intervention group had significantly improved sleep knowledge compared with the control group (mean difference: 3.64 [95% confidence interval (CI): 3.21 to 4.07]; Cohen's d = 0.51) as measured by using a sleep knowledge questionnaire. Weekday sleep duration was reduced in both groups, and the significant difference in weekday sleep duration was lost in the intention-to-treat analysis (mean difference: 0:01 [95% CI: -0:00 to 0:04]). In addition, the intervention group had a lower incidence of consuming caffeine-containing energy drinks (adjusted odds ratio: 0.46 [95% CI: 0.22 to 0.99]) and had better behavioral (mean difference: -0.56 [95% CI: -1.02 to -0.10]; Cohen's d = 0.13) and mental health (mean difference: -0.30 [95% CI: -0.15 to -0.46]; Cohen's d = 0.11) outcomes. A school-based sleep education program was effective in enhancing sleep knowledge and improving behavioral and mental health, but it had no significant impact on sleep duration or pattern among adolescents. Copyright © 2015 by the American Academy of Pediatrics.

Does classification of persons with fibromyalgia into Multidimensional Pain Inventory subgroups detect differences in outcome after a standard chronic pain management program?

PubMed Central

Verra, Martin L; Angst, Felix; Brioschi, Roberto; Lehmann, Susanne; Keefe, Francis J; Staal, J Bart; de Bie, Rob A; Aeschlimann, André

2009-01-01

INTRODUCTION: The present study aimed to replicate and validate the empirically derived subgroup classification based on the Multidimensional Pain Inventory (MPI) in a sample of highly disabled fibromyalgia (FM) patients. Second, it examined how the identified subgroups differed in their response to an intensive, interdisciplinary inpatient pain management program. METHODS: Participants were 118 persons with FM who experienced persistent pain and were disabled. Subgroup classification was conducted by cluster analysis using MPI subscale scores at entry to the program. At program entry and discharge, participants completed the MPI, Medical Outcomes Study Short Form-36, Hospital Anxiety and Depression Scale and Coping Strategies Questionnaire. RESULTS: Cluster analysis identified three subgroups in the highly disabled sample that were similar to those described by other studies using less disabled samples of FM. The dysfunctional subgroup (DYS; 36% of the sample) showed the highest level of depression, the interpersonally distressed subgroup (ID; 24%) showed a modest level of depression and the adaptive copers subgroup (AC; 38%) showed the lowest depression scores in the MPI (negative mood), Medical Outcomes Study Short Form-36 (mental health), Hospital Anxiety and Depression Scale (depression) and Coping Strategies Questionnaire (catastrophizing). Significant differences in treatment outcome were observed among the three subgroups in terms of reduction of pain severity (as assessed using the MPI). The effect sizes were 1.42 for DYS, 1.32 for AC and 0.62 for ID (P=0.004 for pairwise comparison of ID-AC and P=0.018 for ID-DYS). DISCUSSION: These findings underscore the importance of assessing individuals’ differences in how they adjust to FM. PMID:20011715

Whole genome sequencing analysis of Salmonella enterica serovar Weltevreden isolated from human stool and contaminated food samples collected from the Southern coastal area of China.

PubMed

Li, Baisheng; Yang, Xingfen; Tan, Hailing; Ke, Bixia; He, Dongmei; Wang, Haiyan; Chen, Qiuxia; Ke, Changwen; Zhang, Yonghui

2018-02-02

Salmonella enterica serovar Weltevreden is the most common non-typhoid Salmonella found in South and Southeast Asia. It causes zoonoses worldwide through the consumption of contaminated foods and seafood, and is considered as an important food-borne pathogen in China, especially in the Southern coastal area. We compared the whole genomes of 44 S. Weltevreden strains isolated from human stool and contaminated food samples from Southern Coastal China, in order to investigate their phylogenetic relationships and establish their genetic relatedness to known international strains. ResFinder analysis of the draft genomes of isolated strains detected antimicrobial resistance (AMR) genes in only eight isolates, equivalent to minimum inhibitory concentration assay, and only a few isolates showed resistance to tetracycline, ciprofloxacin or ampicillin. In silico MLST analysis revealed that 43 out of 44 S. Weltevreden strains belonged to sequence type 365 (CC205), the most common sequence type of the serovars. Phylogenetic analysis of the 44 domestic and 26 international isolates suggested that the population of S. Weltevreden could be segregated into six phylogenetic clusters. Cluster I included two strains from food and strains of the "Island Cluster", indicating potential inter-transmission between different countries and regions through foods. The predominant S. Weltevreden isolates obtained from the samples from Southern coastal China were found to be phylogenetically related to strains from Southern East Asia, and formed clusters II-VI. The study has demonstrated that WGS-based analysis may be used to improve our understanding of the epidemiology of this bacterium as part of a food-borne disease surveillance program. The methods used are also more widely applicable to other geographical regions and areas and could therefore be useful for improving our understanding of the international spread of S. Weltevreden on a global scale. Copyright © 2017. Published by Elsevier B.V.

Topology and Control of the Cell-Cycle-Regulated Transcriptional Circuitry

PubMed Central

Haase, Steven B.; Wittenberg, Curt

2014-01-01

Nearly 20% of the budding yeast genome is transcribed periodically during the cell division cycle. The precise temporal execution of this large transcriptional program is controlled by a large interacting network of transcriptional regulators, kinases, and ubiquitin ligases. Historically, this network has been viewed as a collection of four coregulated gene clusters that are associated with each phase of the cell cycle. Although the broad outlines of these gene clusters were described nearly 20 years ago, new technologies have enabled major advances in our understanding of the genes comprising those clusters, their regulation, and the complex regulatory interplay between clusters. More recently, advances are being made in understanding the roles of chromatin in the control of the transcriptional program. We are also beginning to discover important regulatory interactions between the cell-cycle transcriptional program and other cell-cycle regulatory mechanisms such as checkpoints and metabolic networks. Here we review recent advances and contemporary models of the transcriptional network and consider these models in the context of eukaryotic cell-cycle controls. PMID:24395825

Merging history of three bimodal clusters

NASA Astrophysics Data System (ADS)

Maurogordato, S.; Sauvageot, J. L.; Bourdin, H.; Cappi, A.; Benoist, C.; Ferrari, C.; Mars, G.; Houairi, K.

2011-01-01

We present a combined X-ray and optical analysis of three bimodal galaxy clusters selected as merging candidates at z ~ 0.1. These targets are part of MUSIC (MUlti-Wavelength Sample of Interacting Clusters), which is a general project designed to study the physics of merging clusters by means of multi-wavelength observations. Observations include spectro-imaging with XMM-Newton EPIC camera, multi-object spectroscopy (260 new redshifts), and wide-field imaging at the ESO 3.6 m and 2.2 m telescopes. We build a global picture of these clusters using X-ray luminosity and temperature maps together with galaxy density and velocity distributions. Idealized numerical simulations were used to constrain the merging scenario for each system. We show that A2933 is very likely an equal-mass advanced pre-merger ~200 Myr before the core collapse, while A2440 and A2384 are post-merger systems (~450 Myr and ~1.5 Gyr after core collapse, respectively). In the case of A2384, we detect a spectacular filament of galaxies and gas spreading over more than 1 h-1 Mpc, which we infer to have been stripped during the previous collision. The analysis of the MUSIC sample allows us to outline some general properties of merging clusters: a strong luminosity segregation of galaxies in recent post-mergers; the existence of preferential axes - corresponding to the merging directions - along which the BCGs and structures on various scales are aligned; the concomitance, in most major merger cases, of secondary merging or accretion events, with groups infalling onto the main cluster, and in some cases the evidence of previous merging episodes in one of the main components. These results are in good agreement with the hierarchical scenario of structure formation, in which clusters are expected to form by successive merging events, and matter is accreted along large-scale filaments. Based on data obtained with the European Southern Observatory, Chile (programs 072.A-0595, 075.A-0264, and 079.A-0425).Tables 5-7 are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/525/A79

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

NASA Astrophysics Data System (ADS)

Rostrup, Scott; De Sterck, Hans

2010-12-01

Increasingly, high-performance computing is looking towards data-parallel computational devices to enhance computational performance. Two technologies that have received significant attention are IBM's Cell Processor and NVIDIA's CUDA programming model for graphics processing unit (GPU) computing. In this paper we investigate the acceleration of parallel hyperbolic partial differential equation simulation on structured grids with explicit time integration on clusters with Cell and GPU backends. The message passing interface (MPI) is used for communication between nodes at the coarsest level of parallelism. Optimizations of the simulation code at the several finer levels of parallelism that the data-parallel devices provide are described in terms of data layout, data flow and data-parallel instructions. Optimized Cell and GPU performance are compared with reference code performance on a single x86 central processing unit (CPU) core in single and double precision. We further compare the CPU, Cell and GPU platforms on a chip-to-chip basis, and compare performance on single cluster nodes with two CPUs, two Cell processors or two GPUs in a shared memory configuration (without MPI). We finally compare performance on clusters with 32 CPUs, 32 Cell processors, and 32 GPUs using MPI. Our GPU cluster results use NVIDIA Tesla GPUs with GT200 architecture, but some preliminary results on recently introduced NVIDIA GPUs with the next-generation Fermi architecture are also included. This paper provides computational scientists and engineers who are considering porting their codes to accelerator environments with insight into how structured grid based explicit algorithms can be optimized for clusters with Cell and GPU accelerators. It also provides insight into the speed-up that may be gained on current and future accelerator architectures for this class of applications. Program summaryProgram title: SWsolver Catalogue identifier: AEGY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGY_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL v3 No. of lines in distributed program, including test data, etc.: 59 168 No. of bytes in distributed program, including test data, etc.: 453 409 Distribution format: tar.gz Programming language: C, CUDA Computer: Parallel Computing Clusters. Individual compute nodes may consist of x86 CPU, Cell processor, or x86 CPU with attached NVIDIA GPU accelerator. Operating system: Linux Has the code been vectorised or parallelized?: Yes. Tested on 1-128 x86 CPU cores, 1-32 Cell Processors, and 1-32 NVIDIA GPUs. RAM: Tested on Problems requiring up to 4 GB per compute node. Classification: 12 External routines: MPI, CUDA, IBM Cell SDK Nature of problem: MPI-parallel simulation of Shallow Water equations using high-resolution 2D hyperbolic equation solver on regular Cartesian grids for x86 CPU, Cell Processor, and NVIDIA GPU using CUDA. Solution method: SWsolver provides 3 implementations of a high-resolution 2D Shallow Water equation solver on regular Cartesian grids, for CPU, Cell Processor, and NVIDIA GPU. Each implementation uses MPI to divide work across a parallel computing cluster. Additional comments: Sub-program numdiff is used for the test run.

Monte Carlo Shower Counter Studies

NASA Technical Reports Server (NTRS)

Snyder, H. David

1991-01-01

Activities and accomplishments related to the Monte Carlo shower counter studies are summarized. A tape of the VMS version of the GEANT software was obtained and installed on the central computer at Gallaudet University. Due to difficulties encountered in updating this VMS version, a decision was made to switch to the UNIX version of the package. This version was installed and used to generate the set of data files currently accessed by various analysis programs. The GEANT software was used to write files of data for positron and proton showers. Showers were simulated for a detector consisting of 50 alternating layers of lead and scintillator. Each file consisted of 1000 events at each of the following energies: 0.1, 0.5, 2.0, 10, 44, and 200 GeV. Data analysis activities related to clustering, chi square, and likelihood analyses are summarized. Source code for the GEANT user subprograms and data analysis programs are provided along with example data plots.

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…

Clusters of Behaviors and Beliefs Predicting Adolescent Depression: Implications for Prevention

PubMed Central

Paunesku, David; Ellis, Justin; Fogel, Joshua; Kuwabara, Sachiko A; Gollan, Jackie; Gladstone, Tracy; Reinecke, Mark; Van Voorhees, Benjamin W.

2009-01-01

OBJECTIVE Risk factors for various disorders are known to cluster. However, the factor structure for behaviors and beliefs predicting depressive disorder in adolescents is not known. Knowledge of this structure can facilitate prevention planning. METHODS We used the National Longitudinal Study of Adolescent Health (AddHealth) data set to conduct an exploratory factor analysis to identify clusters of behaviors/experiences predicting the onset of major depressive disorder (MDD) at 1-year follow-up (N=4,791). RESULTS Four factors were identified: family/interpersonal relations, self-emancipation, avoidant problem solving/low self-worth, and religious activity. Strong family/interpersonal relations were the most significantly protective against depression at one year follow-up. Avoidant problem solving/low self-worth was not predictive of MDD on its own, but significantly amplified the risks associated with delinquency. CONCLUSION Depression prevention interventions should consider giving family relationships a more central role in their efforts. Programs teaching problem solving skills may be most appropriate for reducing MDD risk in delinquent youth. PMID:20502621

What drives the formation of massive stars and clusters?

NASA Astrophysics Data System (ADS)

Ochsendorf, Bram; Meixner, Margaret; Roman-Duval, Julia; Evans, Neal J., II; Rahman, Mubdi; Zinnecker, Hans; Nayak, Omnarayani; Bally, John; Jones, Olivia C.; Indebetouw, Remy

2018-01-01

Galaxy-wide surveys allow to study star formation in unprecedented ways. In this talk, I will discuss our analysis of the Large Magellanic Cloud (LMC) and the Milky Way, and illustrate how studying both the large and small scale structure of galaxies are critical in addressing the question: what drives the formation of massive stars and clusters?I will show that ‘turbulence-regulated’ star formation models do not reproduce massive star formation properties of GMCs in the LMC and Milky Way: this suggests that theory currently does not capture the full complexity of star formation on small scales. I will also report on the discovery of a massive star forming complex in the LMC, which in many ways manifests itself as an embedded twin of 30 Doradus: this may shed light on the formation of R136 and 'Super Star Clusters' in general. Finally, I will highlight what we can expect in the next years in the field of star formation with large-scale sky surveys, ALMA, and our JWST-GTO program.

Investigating Subtypes of Child Development: A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

ERIC Educational Resources Information Center

DiStefano, Christine; Kamphaus, R. W.

2006-01-01

Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures…

Establishment of a Hall Thruster Cluster

DTIC Science & Technology

2004-02-01

DURIP funds were used to develop a Hall thruster cluster test facility centered around the University of Michigan Large Vacuum Test Facility and a 2x2 cluster of BUSEK 600 W BHT-600 Hall thrusters. This capability will facilitate our three-year program to address the issue of high-power CDT operation and to provide insight on how chamber effects influence CDT engine/cluster characteristics.

SBA Innovation Clusters

DTIC Science & Technology

2012-03-02

Programs and services to help you start, grow and succeed www.sba.gov U.S. Small Business Administration Your Small Business Resource 1Approved for...Public Release SBA Innovation Clusters RADM Steven G. Smith USN (Ret) Advanced Defense Technology Cluster Coordinator U.S. Small Business ...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Small Business Administration ,Advanced Defense Technology Cluster,409 3rd St, SW

Cluster analysis in phenotyping a Portuguese population.

PubMed

Loureiro, C C; Sa-Couto, P; Todo-Bom, A; Bousquet, J

2015-09-03

Unbiased cluster analysis using clinical parameters has identified asthma phenotypes. Adding inflammatory biomarkers to this analysis provided a better insight into the disease mechanisms. This approach has not yet been applied to asthmatic Portuguese patients. To identify phenotypes of asthma using cluster analysis in a Portuguese asthmatic population treated in secondary medical care. Consecutive patients with asthma were recruited from the outpatient clinic. Patients were optimally treated according to GINA guidelines and enrolled in the study. Procedures were performed according to a standard evaluation of asthma. Phenotypes were identified by cluster analysis using Ward's clustering method. Of the 72 patients enrolled, 57 had full data and were included for cluster analysis. Distribution was set in 5 clusters described as follows: cluster (C) 1, early onset mild allergic asthma; C2, moderate allergic asthma, with long evolution, female prevalence and mixed inflammation; C3, allergic brittle asthma in young females with early disease onset and no evidence of inflammation; C4, severe asthma in obese females with late disease onset, highly symptomatic despite low Th2 inflammation; C5, severe asthma with chronic airflow obstruction, late disease onset and eosinophilic inflammation. In our study population, the identified clusters were mainly coincident with other larger-scale cluster analysis. Variables such as age at disease onset, obesity, lung function, FeNO (Th2 biomarker) and disease severity were important for cluster distinction. Copyright © 2015. Published by Elsevier España, S.L.U.

Beyond MACS: A Snapshot Survey of the Most Massive Clusters of Galaxies at z>0.5

NASA Astrophysics Data System (ADS)

Ebeling, Harald

2017-08-01

Truly massive galaxy clusters play a pivotal role for a wealth of extragalactic and cosmological research topics, and SNAPshot observations of these systems are ideally suited to identify the most promising cluster targets for further, in-depth study. The power of this approach was demonstrated by ACS/WFC3 SNAPshots of X-ray selected MACS and eMACS clusters at z>0.3 obtained by us in previous Cycles (44 of them in all of F606W, F814W, F110W, and F140W). Based on these data, the CLASH MCT program selected 16 out of 25 of their targets to be MACS clusters. Similarly, all but one of the six most powerful cluster lenses selected for in-depth study by the HST Frontier Fields initiative are MACS detections, and so are 16 of the 29 z>0.3 clusters targeted by the RELICS legacy program.We propose to extend our spectacularly successful SNAPshot survey of the most X-ray luminous distant clusters to a redshift-mass regime that is poorly sampled by any other project. Targeting only extremely massive clusters at z>0.5 from the X-ray selected eMACS sample (median velocity dispersion: 1180 km/s), the proposed program will (a) identify the most powerful gravitational telescopes at yet higher redshift for the next generation of in-depth studies of the distant Universe with HST and JWST, (b) provide constraints on the mass distribution within these extreme systems, (c) help improve our understanding of the physical nature of galaxy-galaxy and galaxy-gas interactions in cluster cores, and (d) unveil Balmer Break Galaxies at z 2 and Lyman-break galaxies at z>6 as F814W dropouts.Acknowledging the broad community interest in our sample we waive our data rights for these observations.

Microsatellites Reveal a High Population Structure in Triatoma infestans from Chuquisaca, Bolivia

PubMed Central

Pizarro, Juan Carlos; Gilligan, Lauren M.; Stevens, Lori

2008-01-01

Background For Chagas disease, the most serious infectious disease in the Americas, effective disease control depends on elimination of vectors through spraying with insecticides. Molecular genetic research can help vector control programs by identifying and characterizing vector populations and then developing effective intervention strategies. Methods and Findings The population genetic structure of Triatoma infestans (Hemiptera: Reduviidae), the main vector of Chagas disease in Bolivia, was investigated using a hierarchical sampling strategy. A total of 230 adults and nymphs from 23 localities throughout the department of Chuquisaca in Southern Bolivia were analyzed at ten microsatellite loci. Population structure, estimated using analysis of molecular variance (AMOVA) to estimate FST (infinite alleles model) and RST (stepwise mutation model), was significant between western and eastern regions within Chuquisaca and between insects collected in domestic and peri-domestic habitats. Genetic differentiation at three different hierarchical geographic levels was significant, even in the case of adjacent households within a single locality (R ST = 0.14, F ST = 0.07). On the largest geographic scale, among five communities up to 100 km apart, R ST = 0.12 and F ST = 0.06. Cluster analysis combined with assignment tests identified five clusters within the five communities. Conclusions Some houses are colonized by insects from several genetic clusters after spraying, whereas other households are colonized predominately by insects from a single cluster. Significant population structure, measured by both R ST and F ST, supports the hypothesis of poor dispersal ability and/or reduced migration of T. infestans. The high degree of genetic structure at small geographic scales, inferences from cluster analysis and assignment tests, and demographic data suggest reinfesting vectors are coming from nearby and from recrudescence (hatching of eggs that were laid before insecticide spraying). Suggestions for using these results in vector control strategies are made. PMID:18365033

Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

PubMed

Youroukova, Vania M; Dimitrova, Denitsa G; Valerieva, Anna D; Lesichkova, Spaska S; Velikova, Tsvetelina V; Ivanova-Todorova, Ekaterina I; Tumangelova-Yuzeir, Kalina D

2017-06-01

Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.

The YouthMood Project: A Cluster Randomized Controlled Trial of an Online Cognitive Behavioral Program with Adolescents

ERIC Educational Resources Information Center

Calear, Alison L.; Christensen, Helen; Mackinnon, Andrew; Griffiths, Kathleen M.; O'Kearney, Richard

2009-01-01

The aim in the current study was to investigate the effectiveness of an online, self-directed cognitive-behavioral therapy program (MoodGYM) in preventing and reducing the symptoms of anxiety and depression in an adolescent school-based population. A cluster randomized controlled trial was conducted with 30 schools (N = 1,477) from across…

Agricultural Business and Management Materials for Agricultural Education Programs. Core Agricultural Education Curriculum, Central Cluster.

ERIC Educational Resources Information Center

Illinois Univ., Urbana. Office of Agricultural Communications and Education.

This curriculum guide contains 5 teaching units for 44 agricultural business and management cluster problem areas. These problem areas have been selected as suggested areas of study to be included in a core curriculum for secondary students enrolled in an agricultural education program. The five units are as follows: (1) agribusiness operation and…

Toward the 21st Century: Preparing Proactive Visionary Transformational Leaders for Building Learning Communities. Human Resource Development. Tampa Cluster. Winter 1994.

ERIC Educational Resources Information Center

Groff, Warren H.

This document describes the Tampa Cluster human resources development (HRD) seminar that was conducted as part of Nova University's distance education program in higher education (PHE). Discussed first are HRD in the agricultural and business industrial eras and changing HRD practices/needs, Nova University's PHE and HRD program, the proceedings…

A Clustered Randomized Controlled Trial to Determine Impacts of the Harvest of the Month Program

ERIC Educational Resources Information Center

LaChausse, Robert G.

2017-01-01

The study purpose was to examine the impact of the Harvest of the Month (HOTM) program on fruit and vegetable (FV) consumption, FV preferences, other eating behaviors, physical activity and other variables related to healthy eating. A clustered randomized controlled trial was employed in 28 elementary schools. After parental consent was obtained,…

Impact of a Social-Emotional and Character Development Program on School-Level Indicators of Academic Achievement, Absenteeism, and Disciplinary Outcomes: A Matched-Pair, Cluster-Randomized, Controlled Trial

ERIC Educational Resources Information Center

Snyder, Frank; Flay, Brian; Vuchinich, Samuel; Acock, Alan; Washburn, Isaac; Beets, Michael; Li, Kin-Kit

2010-01-01

This article reports the effects of a comprehensive elementary school-based social-emotional and character education program on school-level achievement, absenteeism, and disciplinary outcomes utilizing a matched-pair, cluster-randomized, controlled design. The "Positive Action" Hawai'i trial included 20 racially/ethnically diverse…

Biochemistry in an Undergraduate Writing-Intensive First-Year Program: Seminar Courses in Drugs and Bioethics

ERIC Educational Resources Information Center

Mills, Kenneth V.

2015-01-01

The College of the Holy Cross offers a universal first-year program called Montserrat, in which first-year students participate in a living-learning experience anchored by a yearlong seminar course. The seminar courses are part of a thematic cluster of four to eight courses; students in the cluster live together in a common dormitory and…

Risk Evaluation for Cyclic Aliphatic Bromide Cluster (HBCD Cluster)

EPA Pesticide Factsheets

EPA's existing chemicals programs address pollution prevention, risk assessment, hazard and exposure assessment and/or characterization, and risk management for chemicals substances in commercial use.

Cross-scale analysis of cluster correspondence using different operational neighborhoods

NASA Astrophysics Data System (ADS)

Lu, Yongmei; Thill, Jean-Claude

2008-09-01

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.

CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart.

PubMed

Gomez-Velazquez, Melisa; Badia-Careaga, Claudio; Lechuga-Vieco, Ana Victoria; Nieto-Arellano, Rocio; Tena, Juan J; Rollan, Isabel; Alvarez, Alba; Torroja, Carlos; Caceres, Eva F; Roy, Anna R; Galjart, Niels; Delgado-Olguin, Paul; Sanchez-Cabo, Fatima; Enriquez, Jose Antonio; Gomez-Skarmeta, Jose Luis; Manzanares, Miguel

2017-08-01

Cardiac progenitors are specified early in development and progressively differentiate and mature into fully functional cardiomyocytes. This process is controlled by an extensively studied transcriptional program. However, the regulatory events coordinating the progression of such program from development to maturation are largely unknown. Here, we show that the genome organizer CTCF is essential for cardiogenesis and that it mediates genomic interactions to coordinate cardiomyocyte differentiation and maturation in the developing heart. Inactivation of Ctcf in cardiac progenitor cells and their derivatives in vivo during development caused severe cardiac defects and death at embryonic day 12.5. Genome wide expression analysis in Ctcf mutant hearts revealed that genes controlling mitochondrial function and protein production, required for cardiomyocyte maturation, were upregulated. However, mitochondria from mutant cardiomyocytes do not mature properly. In contrast, multiple development regulatory genes near predicted heart enhancers, including genes in the IrxA cluster, were downregulated in Ctcf mutants, suggesting that CTCF promotes cardiomyocyte differentiation by facilitating enhancer-promoter interactions. Accordingly, loss of CTCF disrupts gene expression and chromatin interactions as shown by chromatin conformation capture followed by deep sequencing. Furthermore, CRISPR-mediated deletion of an intergenic CTCF site within the IrxA cluster alters gene expression in the developing heart. Thus, CTCF mediates local regulatory interactions to coordinate transcriptional programs controlling transitions in morphology and function during heart development.

CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart

PubMed Central

Gomez-Velazquez, Melisa; Badia-Careaga, Claudio; Lechuga-Vieco, Ana Victoria; Nieto-Arellano, Rocio; Rollan, Isabel; Alvarez, Alba; Torroja, Carlos; Caceres, Eva F.; Roy, Anna R.; Galjart, Niels; Sanchez-Cabo, Fatima; Enriquez, Jose Antonio; Gomez-Skarmeta, Jose Luis

2017-01-01

Cardiac progenitors are specified early in development and progressively differentiate and mature into fully functional cardiomyocytes. This process is controlled by an extensively studied transcriptional program. However, the regulatory events coordinating the progression of such program from development to maturation are largely unknown. Here, we show that the genome organizer CTCF is essential for cardiogenesis and that it mediates genomic interactions to coordinate cardiomyocyte differentiation and maturation in the developing heart. Inactivation of Ctcf in cardiac progenitor cells and their derivatives in vivo during development caused severe cardiac defects and death at embryonic day 12.5. Genome wide expression analysis in Ctcf mutant hearts revealed that genes controlling mitochondrial function and protein production, required for cardiomyocyte maturation, were upregulated. However, mitochondria from mutant cardiomyocytes do not mature properly. In contrast, multiple development regulatory genes near predicted heart enhancers, including genes in the IrxA cluster, were downregulated in Ctcf mutants, suggesting that CTCF promotes cardiomyocyte differentiation by facilitating enhancer-promoter interactions. Accordingly, loss of CTCF disrupts gene expression and chromatin interactions as shown by chromatin conformation capture followed by deep sequencing. Furthermore, CRISPR-mediated deletion of an intergenic CTCF site within the IrxA cluster alters gene expression in the developing heart. Thus, CTCF mediates local regulatory interactions to coordinate transcriptional programs controlling transitions in morphology and function during heart development. PMID:28846746

Does poverty alleviation decrease depression symptoms in post-conflict settings? A cluster-randomized trial of microenterprise assistance in Northern Uganda.

PubMed

Green, E P; Blattman, C; Jamison, J; Annan, J

2016-01-01

By 2009, two decades of war and widespread displacement left the majority of the population of Northern Uganda impoverished. This study used a cluster-randomized design to test the hypothesis that a poverty alleviation program would improve economic security and reduce symptoms of depression in a sample of mostly young women. Roughly 120 villages in Northern Uganda were invited to participate. Community committees were asked to identify the most vulnerable women (and some men) to participate. The implementing agency screened all proposed participants, and a total of 1800 were enrolled. Following a baseline survey, villages were randomized to a treatment or wait-list control group. Participants in treatment villages received training, start-up capital, and follow-up support. Participants, implementers, and data collectors were not blinded to treatment status. Villages were randomized to the treatment group (60 villages with 896 participants) or the wait-list control group (60 villages with 904 participants) with an allocation ration of 1:1. All clusters participated in the intervention and were included in the analysis. The intent-to-treat analysis included 860 treatment participants and 866 control participants (4.1% attrition). Sixteen months after the program, monthly cash earnings doubled from UGX 22 523 to 51 124, non-household and non-farm businesses doubled, and cash savings roughly quadrupled. There was no measurable effect on a locally derived measure of symptoms of depression. Despite finding large increases in business, income, and savings among the treatment group, we do not find support for an indirect effect of poverty alleviation on symptoms of depression.

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

PubMed Central

2010-01-01

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data. PMID:20937082

Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis.

PubMed

Lee, Seohyun; Cho, Yoon-Min; Kim, Sun-Young

2017-08-22

Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran's I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the northern area shows extensive low-low association. This study aimed to shed some light on the potential for strategic regional collaboration for scale-up of mHealth and mobile penetration. Firstly, countries in the eastern area with much experience can take the lead role in pursuing regional collaboration for mHealth programs in sub-Saharan Africa. Secondly, collective effort in improving mobile penetration rates for the northern area is recommended.

Modest validity and fair reproducibility of dietary patterns derived by cluster analysis.

PubMed

Funtikova, Anna N; Benítez-Arciniega, Alejandra A; Fitó, Montserrat; Schröder, Helmut

2015-03-01

Cluster analysis is widely used to analyze dietary patterns. We aimed to analyze the validity and reproducibility of the dietary patterns defined by cluster analysis derived from a food frequency questionnaire (FFQ). We hypothesized that the dietary patterns derived by cluster analysis have fair to modest reproducibility and validity. Dietary data were collected from 107 individuals from population-based survey, by an FFQ at baseline (FFQ1) and after 1 year (FFQ2), and by twelve 24-hour dietary recalls (24-HDR). Repeatability and validity were measured by comparing clusters obtained by the FFQ1 and FFQ2 and by the FFQ2 and 24-HDR (reference method), respectively. Cluster analysis identified a "fruits & vegetables" and a "meat" pattern in each dietary data source. Cluster membership was concordant for 66.7% of participants in FFQ1 and FFQ2 (reproducibility), and for 67.0% in FFQ2 and 24-HDR (validity). Spearman correlation analysis showed reasonable reproducibility, especially in the "fruits & vegetables" pattern, and lower validity also especially in the "fruits & vegetables" pattern. κ statistic revealed a fair validity and reproducibility of clusters. Our findings indicate a reasonable reproducibility and fair to modest validity of dietary patterns derived by cluster analysis. Copyright © 2015 Elsevier Inc. All rights reserved.

Cluster analysis of medical service resources at district hospitals in Taiwan, 2007-2011.

PubMed

Tseng, Shu-Fang; Lee, Tian-Shyug; Deng, Chung-Yeh

2015-12-01

A vast amount of the annual/national budget has been spent on the National Health Insurance program in Taiwan. However, the market for district hospitals has become increasingly competitive, and district hospitals are under pressure to optimize the use of health service resources. Therefore, we employed a clustering method to explore variations in input and output service volumes, and investigate resource allocation and health care service efficiency in district hospitals. Descriptive and cluster analyses were conducted to examine the district hospitals included in the Ministry of Health and Welfare database during 2007-2011. The results, according to the types of hospital ownership, suggested that the number of public hospitals has decreased and that of private hospitals increased; the largest increase in the number of district hospitals occurred when Taichung City was merged into Taichung County. The descriptive statistics from 2007 to 2011 indicated that 43% and 36.4% of the hospitals had 501-800 occupied beds and 101-200 physicians, respectively, and > 401 medical staff members. However, the number of outpatients and discharged patients exceeded 6001 and 90,001, respectively. In addition, the highest percentage of hospitals (43.9%) had 30,001-60,000 emergency department patients. In 2010, the number of patients varied widely, and the analysis of variance cluster results were nonsignificant (p > 0.05). District hospitals belonging to low-throughput and low-performance groups were encouraged to improve resource utilization for enhancing health care service efficiency. Copyright © 2015. Published by Elsevier Taiwan.

Cluster Analysis to Identify Possible Subgroups in Tinnitus Patients.

PubMed

van den Berge, Minke J C; Free, Rolien H; Arnold, Rosemarie; de Kleine, Emile; Hofman, Rutger; van Dijk, J Marc C; van Dijk, Pim

2017-01-01

In tinnitus treatment, there is a tendency to shift from a "one size fits all" to a more individual, patient-tailored approach. Insight in the heterogeneity of the tinnitus spectrum might improve the management of tinnitus patients in terms of choice of treatment and identification of patients with severe mental distress. The goal of this study was to identify subgroups in a large group of tinnitus patients. Data were collected from patients with severe tinnitus complaints visiting our tertiary referral tinnitus care group at the University Medical Center Groningen. Patient-reported and physician-reported variables were collected during their visit to our clinic. Cluster analyses were used to characterize subgroups. For the selection of the right variables to enter in the cluster analysis, two approaches were used: (1) variable reduction with principle component analysis and (2) variable selection based on expert opinion. Various variables of 1,783 tinnitus patients were included in the analyses. Cluster analysis (1) included 976 patients and resulted in a four-cluster solution. The effect of external influences was the most discriminative between the groups, or clusters, of patients. The "silhouette measure" of the cluster outcome was low (0.2), indicating a "no substantial" cluster structure. Cluster analysis (2) included 761 patients and resulted in a three-cluster solution, comparable to the first analysis. Again, a "no substantial" cluster structure was found (0.2). Two cluster analyses on a large database of tinnitus patients revealed that clusters of patients are mostly formed by a different response of external influences on their disease. However, both cluster outcomes based on this dataset showed a poor stability, suggesting that our tinnitus population comprises a continuum rather than a number of clearly defined subgroups.

Ecological tolerances of Miocene larger benthic foraminifera from Indonesia

NASA Astrophysics Data System (ADS)

Novak, Vibor; Renema, Willem

2018-01-01

To provide a comprehensive palaeoenvironmental reconstruction based on larger benthic foraminifera (LBF), a quantitative analysis of their assemblage composition is needed. Besides microfacies analysis which includes environmental preferences of foraminiferal taxa, statistical analyses should also be employed. Therefore, detrended correspondence analysis and cluster analysis were performed on relative abundance data of identified LBF assemblages deposited in mixed carbonate-siliciclastic (MCS) systems and blue-water (BW) settings. Studied MCS system localities include ten sections from the central part of the Kutai Basin in East Kalimantan, ranging from late Burdigalian to Serravallian age. The BW samples were collected from eleven sections of the Bulu Formation on Central Java, dated as Serravallian. Results from detrended correspondence analysis reveal significant differences between these two environmental settings. Cluster analysis produced five clusters of samples; clusters 1 and 2 comprise dominantly MCS samples, clusters 3 and 4 with dominance of BW samples, and cluster 5 showing a mixed composition with both MCS and BW samples. The results of cluster analysis were afterwards subjected to indicator species analysis resulting in the interpretation that generated three groups among LBF taxa: typical assemblage indicators, regularly occurring taxa and rare taxa. By interpreting the results of detrended correspondence analysis, cluster analysis and indicator species analysis, along with environmental preferences of identified LBF taxa, a palaeoenvironmental model is proposed for the distribution of LBF in Miocene MCS systems and adjacent BW settings of Indonesia.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

How molecular epidemiology studies can support the National Malaria Control Program in Papua New Guinea.

PubMed

Koepfli, Cristian; Barry, Alyssa; Javati, Sarah; Timinao, Lincoln; Nate, Elma; Mueller, Ivo; Barnadas, Celine

2014-01-01

Papua New Guinea (PNG) is undertaking intensified efforts to control malaria. The National Malaria Control Program aims to reduce the burden of disease by large-scale distribution of insecticide-treated bednets, improved diagnosis and implementation of new treatments. A scientific program monitoring the effect of these interventions, including molecular epidemiology studies, closely accompanies the program. Laboratory assays have been developed in (or transferred to) PNG to measure prevalence of infection and intensity of transmission as well as potential resistance to currently used drugs. These assays help to assess the impact of the National Malaria Control Program, and they reveal a much clearer picture of malaria epidemiology in PNG. In addition, analysis of the geographical clustering of parasites aids in selecting areas where intensified control will be most successful. This paper gives an overview of current research and recently completed studies in the molecular epidemiology of malaria conducted in Papua New Guinea.

Vegetation spatial variability and its effect on vegetation indices

NASA Technical Reports Server (NTRS)

Ormsby, J. P.; Choudhury, B. J.; Owe, M.

1987-01-01

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification program. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12.7 per cent in determining these areas. NDVI values less than 0.3 represented fractional vegetated areas of 5 per cent or less, while a value of 0.7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0.89 and 0.95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.

[Simultaneous determination of 4 diterpenoids in Rabdosia japonica var.glaucocalyx by HPLC-ESI-MS/MS and cluster analysis].

PubMed

Tian, Ting-Ting; Ma, Ying-Hua; Xie, Wei-Wei; Jin, Yi-Ran; Xu, Hui-Jun; Zhang, Lan-Tong; Du, Ying-Feng

2016-01-01

A quick HPLC-ESI-MS/MS method was established for simultaneous determination of four major diterpenoids in Rabdosia japonica var.glaucocalyx, including glaucocalyxin A, oridonin, hebeirubesensin and enmenol. Analysis was performed on an Agilent ZORBAX SB-C18(4.6 mm×250 mm, 5 μm ) column eluted in a gradient program with methanol and water. The flow rate was 0.8 mL•min⁻¹. Multiple reaction monitoring (MRM) scanning mode was performed in negative ion switching mode to apply for the quantitative determination. The calibration curves for the above four compounds were linear in corresponding injection amount. The average recoveries of the compounds ranged from 92.40% to 105.9%, with RSDs of 1.7%-6.5%. The method is simple, rapid, accurate with good repeatability, which can provide a reference for overcalling evaluation the quality of R. japonica var.glaucocalyx. The result of cluster analysis- showed that the quality of R. japonica glaucocalyx var. greatly varied between areas and parts. Copyright© by the Chinese Pharmaceutical Association.

On the analysis of large data sets

NASA Astrophysics Data System (ADS)

Ruch, Gerald T., Jr.

We present a set of tools and techniques for performing detailed comparisons between computational models with high dimensional parameter spaces and large sets of archival data. By combining a principal component analysis of a large grid of samples from the model with an artificial neural network, we create a powerful data visualization tool as well as a way to robustly recover physical parameters from a large set of experimental data. Our techniques are applied in the context of circumstellar disks, the likely sites of planetary formation. An analysis is performed applying the two layer approximation of Chiang et al. (2001) and Dullemond et al. (2001) to the archive created by the Spitzer Space Telescope Cores to Disks Legacy program. We find two populations of disk sources. The first population is characterized by the lack of a puffed up inner rim while the second population appears to contain an inner rim which casts a shadow across the disk. The first population also exhibits a trend of increasing spectral index while the second population exhibits a decreasing trend in the strength of the 20 mm silicate emission feature. We also present images of the giant molecular cloud W3 obtained with the Infrared Array Camera (IRAC) and the Multiband Imaging Photometer (MIPS) on board the Spitzer Space Telescope. The images encompass the star forming regions W3 Main, W3(OH), and a region that we refer to as the Central Cluster which encloses the emission nebula IC 1795. We present a star count analysis of the point sources detected in W3. The star count analysis shows that the stellar population of the Central Cluster, when compared to that in the background, contains an over density of sources. The Central Cluster also contains an excess of sources with colors consistent with Class II Young Stellar Objects (YSOs). A analysis of the color-color diagrams also reveals a large number of Class II YSOs in the Central Cluster. Our results suggest that an earlier epoch of star formation created the Central Cluster, created a cavity, and triggered the active star formation in the W3 Main and W3(OH) regions. We also detect a new outflow and its candidate exciting star.

The genetic structure of a relict population of wood frogs

USGS Publications Warehouse

Scherer, Rick; Muths, Erin; Noon, Barry; Oyler-McCance, Sara

2012-01-01

Habitat fragmentation and the associated reduction in connectivity between habitat patches are commonly cited causes of genetic differentiation and reduced genetic variation in animal populations. We used eight microsatellite markers to investigate genetic structure and levels of genetic diversity in a relict population of wood frogs (Lithobates sylvatica) in Rocky Mountain National Park, Colorado, where recent disturbances have altered hydrologic processes and fragmented amphibian habitat. We also estimated migration rates among subpopulations, tested for a pattern of isolation-by-distance, and looked for evidence of a recent population bottleneck. The results from the clustering algorithm in Program STRUCTURE indicated the population is partitioned into two genetic clusters (subpopulations), and this result was further supported by factorial component analysis. In addition, an estimate of FST (FST = 0.0675, P value \\0.0001) supported the genetic differentiation of the two clusters. Estimates of migration rates among the two subpopulations were low, as were estimates of genetic variability. Conservation of the population of wood frogs may be improved by increasing the spatial distribution of the population and improving gene flow between the subpopulations. Construction or restoration of wetlands in the landscape between the clusters has the potential to address each of these objectives.

The Oxidation Products of Aluminum Hydride and Boron Aluminum Hydride Clusters

DTIC Science & Technology

2016-01-04

AFRL-AFOSR-VA-TR-2016-0075 The Oxidation Products of Aluminum Hydride and Boron Aluminum Hydride Clusters KIT BOWEN JOHNS HOPKINS UNIV BALTIMORE MD...Hydride and Boron Aluminum Hydride Clusters 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-14-1-0324 5c.  PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) KIT...of both Aluminum Hydride Cluster Anions and Boron Aluminum Hydride Cluster Anions with Oxygen: Anionic Products The anionic products of reactions

Interactive visual exploration and refinement of cluster assignments.

PubMed

Kern, Michael; Lex, Alexander; Gehlenborg, Nils; Johnson, Chris R

2017-09-12

With ever-increasing amounts of data produced in biology research, scientists are in need of efficient data analysis methods. Cluster analysis, combined with visualization of the results, is one such method that can be used to make sense of large data volumes. At the same time, cluster analysis is known to be imperfect and depends on the choice of algorithms, parameters, and distance measures. Most clustering algorithms don't properly account for ambiguity in the source data, as records are often assigned to discrete clusters, even if an assignment is unclear. While there are metrics and visualization techniques that allow analysts to compare clusterings or to judge cluster quality, there is no comprehensive method that allows analysts to evaluate, compare, and refine cluster assignments based on the source data, derived scores, and contextual data. In this paper, we introduce a method that explicitly visualizes the quality of cluster assignments, allows comparisons of clustering results and enables analysts to manually curate and refine cluster assignments. Our methods are applicable to matrix data clustered with partitional, hierarchical, and fuzzy clustering algorithms. Furthermore, we enable analysts to explore clustering results in context of other data, for example, to observe whether a clustering of genomic data results in a meaningful differentiation in phenotypes. Our methods are integrated into Caleydo StratomeX, a popular, web-based, disease subtype analysis tool. We show in a usage scenario that our approach can reveal ambiguities in cluster assignments and produce improved clusterings that better differentiate genotypes and phenotypes.

Somatotyping using 3D anthropometry: a cluster analysis.

PubMed

Olds, Tim; Daniell, Nathan; Petkov, John; David Stewart, Arthur

2013-01-01

Somatotyping is the quantification of human body shape, independent of body size. Hitherto, somatotyping (including the most popular method, the Heath-Carter system) has been based on subjective visual ratings, sometimes supported by surface anthropometry. This study used data derived from three-dimensional (3D) whole-body scans as inputs for cluster analysis to objectively derive clusters of similar body shapes. Twenty-nine dimensions normalised for body size were measured on a purposive sample of 301 adults aged 17-56 years who had been scanned using a Vitus Smart laser scanner. K-means Cluster Analysis with v-fold cross-validation was used to determine shape clusters. Three male and three female clusters emerged, and were visualised using those scans closest to the cluster centroid and a caricature defined by doubling the difference between the average scan and the cluster centroid. The male clusters were decidedly endomorphic (high fatness), ectomorphic (high linearity), and endo-mesomorphic (a mixture of fatness and muscularity). The female clusters were clearly endomorphic, ectomorphic, and the ecto-mesomorphic (a mixture of linearity and muscularity). An objective shape quantification procedure combining 3D scanning and cluster analysis yielded shape clusters strikingly similar to traditional somatotyping.

Clusters of Occupations Based on Systematically Derived Work Dimensions: An Exploratory Study.

ERIC Educational Resources Information Center

Cunningham, J. W.; And Others

The study explored the feasibility of deriving an educationally relevant occupational cluster structure based on Occupational Analysis Inventory (OAI) work dimensions. A hierarchical cluster analysis was applied to the factor score profiles of 814 occupations on 22 higher-order OAI work dimensions. From that analysis, 73 occupational clusters were…

Using cluster analysis to identify phenotypes and validation of mortality in men with COPD.

PubMed

Chen, Chiung-Zuei; Wang, Liang-Yi; Ou, Chih-Ying; Lee, Cheng-Hung; Lin, Chien-Chung; Hsiue, Tzuen-Ren

2014-12-01

Cluster analysis has been proposed to examine phenotypic heterogeneity in chronic obstructive pulmonary disease (COPD). The aim of this study was to use cluster analysis to define COPD phenotypes and validate them by assessing their relationship with mortality. Male subjects with COPD were recruited to identify and validate COPD phenotypes. Seven variables were assessed for their relevance to COPD, age, FEV(1) % predicted, BMI, history of severe exacerbations, mMRC, SpO(2), and Charlson index. COPD groups were identified by cluster analysis and validated prospectively against mortality during a 4-year follow-up. Analysis of 332 COPD subjects identified five clusters from cluster A to cluster E. Assessment of the predictive validity of these clusters of COPD showed that cluster E patients had higher all cause mortality (HR 18.3, p < 0.0001), and respiratory cause mortality (HR 21.5, p < 0.0001) than those in the other four groups. Cluster E patients also had higher all cause mortality (HR 14.3, p = 0.0002) and respiratory cause mortality (HR 10.1, p = 0.0013) than patients in cluster D alone. COPD patient with severe airflow limitation, many symptoms, and a history of frequent severe exacerbations was a novel and distinct clinical phenotype predicting mortality in men with COPD.

Wheat EST resources for functional genomics of abiotic stress

PubMed Central

Houde, Mario; Belcaid, Mahdi; Ouellet, François; Danyluk, Jean; Monroy, Antonio F; Dryanova, Ani; Gulick, Patrick; Bergeron, Anne; Laroche, André; Links, Matthew G; MacCarthy, Luke; Crosby, William L; Sarhan, Fathey

2006-01-01

Background Wheat is an excellent species to study freezing tolerance and other abiotic stresses. However, the sequence of the wheat genome has not been completely characterized due to its complexity and large size. To circumvent this obstacle and identify genes involved in cold acclimation and associated stresses, a large scale EST sequencing approach was undertaken by the Functional Genomics of Abiotic Stress (FGAS) project. Results We generated 73,521 quality-filtered ESTs from eleven cDNA libraries constructed from wheat plants exposed to various abiotic stresses and at different developmental stages. In addition, 196,041 ESTs for which tracefiles were available from the National Science Foundation wheat EST sequencing program and DuPont were also quality-filtered and used in the analysis. Clustering of the combined ESTs with d2_cluster and TGICL yielded a few large clusters containing several thousand ESTs that were refractory to routine clustering techniques. To resolve this problem, the sequence proximity and "bridges" were identified by an e-value distance graph to manually break clusters into smaller groups. Assembly of the resolved ESTs generated a 75,488 unique sequence set (31,580 contigs and 43,908 singletons/singlets). Digital expression analyses indicated that the FGAS dataset is enriched in stress-regulated genes compared to the other public datasets. Over 43% of the unique sequence set was annotated and classified into functional categories according to Gene Ontology. Conclusion We have annotated 29,556 different sequences, an almost 5-fold increase in annotated sequences compared to the available wheat public databases. Digital expression analysis combined with gene annotation helped in the identification of several pathways associated with abiotic stress. The genomic resources and knowledge developed by this project will contribute to a better understanding of the different mechanisms that govern stress tolerance in wheat and other cereals. PMID:16772040

DMRT gene cluster analysis in the platypus: new insights into genomic organization and regulatory regions.

PubMed

El-Mogharbel, Nisrine; Wakefield, Matthew; Deakin, Janine E; Tsend-Ayush, Enkhjargal; Grützner, Frank; Alsop, Amber; Ezaz, Tariq; Marshall Graves, Jennifer A

2007-01-01

We isolated and characterized a cluster of platypus DMRT genes and compared their arrangement, location, and sequence across vertebrates. The DMRT gene cluster on human 9p24.3 harbors, in order, DMRT1, DMRT3, and DMRT2, which share a DM domain. DMRT1 is highly conserved and involved in sexual development in vertebrates, and deletions in this region cause sex reversal in humans. Sequence comparisons of DMRT genes between species have been valuable in identifying exons, control regions, and conserved nongenic regions (CNGs). The addition of platypus sequences is expected to be particularly valuable, since monotremes fill a gap in the vertebrate genome coverage. We therefore isolated and fully sequenced platypus BAC clones containing DMRT3 and DMRT2 as well as DMRT1 and then generated multispecies alignments and ran prediction programs followed by experimental verification to annotate this gene cluster. We found that the three genes have 58-66% identity to their human orthologues, lie in the same order as in other vertebrates, and colocate on 1 of the 10 platypus sex chromosomes, X5. We also predict that optimal annotation of the newly sequenced platypus genome will be challenging. The analysis of platypus sequence revealed differences in structure and sequence of the DMRT gene cluster. Multispecies comparison was particularly effective for detecting CNGs, revealing several novel potential regulatory regions within DMRT3 and DMRT2 as well as DMRT1. RT-PCR indicated that platypus DMRT1 and DMRT3 are expressed specifically in the adult testis (and not ovary), but DMRT2 has a wider expression profile, as it does for other mammals. The platypus DMRT1 expression pattern, and its location on an X chromosome, suggests an involvement in monotreme sexual development.

Epidemiology of bovine brucellosis in Costa Rica: Lessons learned from failures in the control of the disease

PubMed Central

Hernández-Mora, Gabriela; Ruiz-Villalobos, Nazareth; Bonilla-Montoya, Roberto; Romero-Zúniga, Juan-José; Jiménez-Arias, Julio; González-Barrientos, Rocío; Barquero-Calvo, Elías; Chacón-Díaz, Carlos; Rojas, Norman; Chaves-Olarte, Esteban; Guzmán-Verri, Caterina

2017-01-01

Brucellosis, caused by Brucella abortus is a major disease of cattle and a zoonosis. In order to estimate the bovine brucellosis prevalence in Costa Rica (CR), a total 765 herds (13078 bovines) from six regions of CR were randomly sampled during 2012–2013. A non-random sample of 7907 herds (532199 bovines) of the six regions, arriving for diagnoses during 2014–2016 to the Costa Rican Animal Health Service was also studied. The prevalence estimated by Rose Bengal test (RBT) ranged from 10.5%-11.4%; alternatively, the prevalence estimated by testing the RBT positives in iELISA, ranged from 4.1%-6.0%, respectively. However, cattle in CR are not vaccinated with B. abortus S19 but with RB51 (vaccination coverage close to 11%), and under these conditions the RBT displays 99% specificity and 99% sensitivity. Therefore, the RBT herd depicted in the random analysis stands as a feasible assessment and then, the recommended value in case of planning an eradication program in CR. Studies of three decades reveled that bovine brucellosis prevalence has increased in CR. B. abortus was identified by biochemical and molecular studies as the etiological agent of bovine brucellosis. Multiple locus variable-number tandem repeat analysis-16 revealed four B. abortus clusters. Cluster one and three are intertwined with isolates from other countries, while clusters two and four have only representatives from CR. Cluster one is widely distributed in all regions of the country and may be the primary B. abortus source. The other clusters seem to be restricted to specific areas in CR. The implications of our findings, in relation to the control of the disease in CR, are critically discussed. PMID:28797045

Epidemiology of bovine brucellosis in Costa Rica: Lessons learned from failures in the control of the disease.

PubMed

Hernández-Mora, Gabriela; Ruiz-Villalobos, Nazareth; Bonilla-Montoya, Roberto; Romero-Zúniga, Juan-José; Jiménez-Arias, Julio; González-Barrientos, Rocío; Barquero-Calvo, Elías; Chacón-Díaz, Carlos; Rojas, Norman; Chaves-Olarte, Esteban; Guzmán-Verri, Caterina; Moreno, Edgardo

2017-01-01

Brucellosis, caused by Brucella abortus is a major disease of cattle and a zoonosis. In order to estimate the bovine brucellosis prevalence in Costa Rica (CR), a total 765 herds (13078 bovines) from six regions of CR were randomly sampled during 2012-2013. A non-random sample of 7907 herds (532199 bovines) of the six regions, arriving for diagnoses during 2014-2016 to the Costa Rican Animal Health Service was also studied. The prevalence estimated by Rose Bengal test (RBT) ranged from 10.5%-11.4%; alternatively, the prevalence estimated by testing the RBT positives in iELISA, ranged from 4.1%-6.0%, respectively. However, cattle in CR are not vaccinated with B. abortus S19 but with RB51 (vaccination coverage close to 11%), and under these conditions the RBT displays 99% specificity and 99% sensitivity. Therefore, the RBT herd depicted in the random analysis stands as a feasible assessment and then, the recommended value in case of planning an eradication program in CR. Studies of three decades reveled that bovine brucellosis prevalence has increased in CR. B. abortus was identified by biochemical and molecular studies as the etiological agent of bovine brucellosis. Multiple locus variable-number tandem repeat analysis-16 revealed four B. abortus clusters. Cluster one and three are intertwined with isolates from other countries, while clusters two and four have only representatives from CR. Cluster one is widely distributed in all regions of the country and may be the primary B. abortus source. The other clusters seem to be restricted to specific areas in CR. The implications of our findings, in relation to the control of the disease in CR, are critically discussed.

Cluster self-organization of TR-containing germanate systems: Suprapolyhedral precursors and self-assembly of the crystal structures of the LiNdGeO{sub 4} and CeGeO{sub 4} compounds

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

Ilyushin, G. D., E-mail: ilyushin@nc.cryst.ras.ru; Dem'yanets, L. N.

2007-07-15

A combinatorial-topological analysis of the orthogermanates LiNdGeO{sub 4} (space group Pbcn) and CeGeO{sub 4} (space group I 4{sub 1}/a, the scheelite structure type), which have MT frameworks composed of polyhedral structural units in the form of M dodecahedra (NdO{sub 8} and CeO{sub 8}) and T tetrahedra (GeO{sub 4}), is performed using the method of coordination sequences with the TOPOS program package. It is established that the structures of both orthogermanates are characterized by equivalent crystal-forming nets 4444. The cluster precursors of the M{sub 2}T{sub 2} cyclic type are identified by the method of two-color decomposition. The local symmetry of four-polyhedralmore » clusters corresponds to the point group 2. In the precursor of the LiNdGeO{sub 4} orthogermanate, the Li atom is located above the M{sub 2}T{sub 2} ring. The number of Li-O bonds in this precursor is 4. The cluster precursors M{sub 2}T{sub 2} and LiM{sub 2}T{sub 2} are responsible for the formation of crystal-forming clusters of a higher level according to the mechanism of matrix self-assembly. The coordination numbers of the cluster precursors in two-dimensional nets for these structures are found to be equal to 4. The equivalent bilayer TR,Ge stacks that consist of eight cluster precursors are revealed in the structures under investigation. It is demonstrated that there exist three types of translational interlayer arrangements of cluster precursors upon the formation of macrostructures of the orthogermanates.« less

Conserved water molecules in bacterial serine hydroxymethyltransferases.

PubMed

Milano, Teresa; Di Salvo, Martino Luigi; Angelaccio, Sebastiana; Pascarella, Stefano

2015-10-01

Water molecules occurring in the interior of protein structures often are endowed with key structural and functional roles. We report the results of a systematic analysis of conserved water molecules in bacterial serine hydroxymethyltransferases (SHMTs). SHMTs are an important group of pyridoxal-5'-phosphate-dependent enzymes that catalyze the reversible conversion of l-serine and tetrahydropteroylglutamate to glycine and 5,10-methylenetetrahydropteroylglutamate. The approach utilized in this study relies on two programs, ProACT2 and WatCH. The first software is able to categorize water molecules in a protein crystallographic structure as buried, positioned in clefts or at the surface. The other program finds, in a set of superposed homologous proteins, water molecules that occur approximately in equivalent position in each of the considered structures. These groups of molecules are referred to as 'clusters' and represent structurally conserved water molecules. Several conserved clusters of buried or cleft water molecules were found in the set of 11 bacterial SHMTs we took into account for this work. The majority of these clusters were not described previously. Possible structural and functional roles for the conserved water molecules are envisaged. This work provides a map of the conserved water molecules helpful for deciphering SHMT mechanism and for rational design of molecular engineering experiments. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

Unraveling the efficiency of RAPD and SSR markers in diversity analysis and population structure estimation in common bean.

PubMed

Zargar, Sajad Majeed; Farhat, Sufia; Mahajan, Reetika; Bhakhri, Ayushi; Sharma, Arjun

2016-01-01

Increase in food production viz-a-viz quality of food is important to feed the growing human population to attain food as well as nutritional security. The availability of diverse germplasm of any crop is an important genetic resource to mine the genes that may assist in attaining food as well as nutritional security. Here we used 15 RAPD and 23 SSR markers to elucidate diversity among 51 common bean genotypes mostly landraces collected from the Himalayan region of Jammu and Kashmir, India. We observed that both the markers are highly polymorphic. The discriminatory power of these markers was determined using various parameters like; percent polymorphism, PIC, resolving power and marker index. 15 RAPDs produced 171 polymorphic bands, while 23 SSRs produced 268 polymorphic bands. SSRs showed a higher PIC value (0.300) compared to RAPDs (0.243). Further the resolving power of SSRs was 5.241 compared to 3.86 for RAPDs. However, RAPDs showed a higher marker index (2.69) compared to SSRs (1.279) that may be attributed to their higher multiplex ratio. The dendrograms generated with hierarchical UPGMA cluster analysis grouped genotypes into two main clusters with various degrees of sub clustering within the cluster. Here we observed that both the marker systems showed comparable accuracy in grouping genotypes of common bean according to their area of cultivation. The model based STRUCTURE analysis using 15 RAPD and 23 SSR markers identified a population with 3 sub-populations which corresponds to distance based groupings. High level of genetic diversity was observed within the population. These findings have further implications in common bean breeding as well as conservation programs.

Assessment of genetic diversity and phylogenetic relationships of Korean native chicken breeds using microsatellite markers

PubMed Central

Seo, Joo Hee; Lee, Jun Heon; Kong, Hong Sik

2017-01-01

Objective This study was conducted to investigate the basic information on genetic structure and characteristics of Korean Native chickens (NC) and foreign breeds through the analysis of the pure chicken populations and commercial chicken lines of the Hanhyup Company which are popular in the NC market, using the 20 microsatellite markers. Methods In this study, the genetic diversity and phylogenetic relationships of 445 NC from five different breeds (NC, Leghorn [LH], Cornish [CS], Rhode Island Red [RIR], and Hanhyup [HH] commercial line) were investigated by performing genotyping using 20 microsatellite markers. Results The highest genetic distance was observed between RIR and LH (18.9%), whereas the lowest genetic distance was observed between HH and NC (2.7%). In the principal coordinates analysis (PCoA) illustrated by the first component, LH was clearly separated from the other groups. The correspondence analysis showed close relationship among individuals belonging to the NC, CS, and HH lines. From the STRUCTURE program, the presence of 5 clusters was detected and it was found that the proportion of membership in the different clusters was almost comparable among the breeds with the exception of one breed (HH), although it was highest in LH (0.987) and lowest in CS (0.578). For the cluster 1 it was high in HH (0.582) and in CS (0.368), while for the cluster 4 it was relatively higher in HH (0.392) than other breeds. Conclusion Our study showed useful genetic diversity and phylogenetic relationship data that can be utilized for NC breeding and development by the commercial chicken industry to meet consumer demands. PMID:28335091

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

clusterProfiler: an R package for comparing biological themes among gene clusters.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Han, Yanyan; He, Qing-Yu

2012-05-01

Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

Effectiveness of a School-based Academic Asthma Health Education and Counseling Program on Fostering Acceptance of Asthma in Older School-age Students with Asthma

PubMed Central

Kintner, Eileen K.; Cook, Gwendolyn; Marti, C. Nathan; Gomes, Melissa; Meeder, Linda; Van Egeren, Laurie A.

2014-01-01

Purpose The purpose was to evaluate the effectiveness of the academic asthma education and counseling SHARP program on fostering psychosocial acceptance of asthma. Design and Methods This was a phase III, two-group, cluster randomized, single-blinded, longitudinal study. Students from grades 4 and 5 (N = 205) with asthma and their caregivers completed surveys at pre-intervention and at 1, 12, and 24 months post-intervention. Analysis involved multilevel modeling. Results All students demonstrated significant improvement in aspects of acceptance; students in SHARP demonstrated significant improvement in openness to sharing and connectedness with teachers over students in the control condition. Practice Implications The SHARP program offers a well-tested, effective program for psychosocial acceptance of asthma, which is welcomed by schools. PMID:25443593

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends

PubMed Central

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called “big data” challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. The MapReduce programming framework uses two tasks common in functional programming: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields. PMID:25383096

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends.

PubMed

Mohammed, Emad A; Far, Behrouz H; Naugler, Christopher

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called "big data" challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. THE MAPREDUCE PROGRAMMING FRAMEWORK USES TWO TASKS COMMON IN FUNCTIONAL PROGRAMMING: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields.

Clinical Characteristics of Exacerbation-Prone Adult Asthmatics Identified by Cluster Analysis.

PubMed

Kim, Mi Ae; Shin, Seung Woo; Park, Jong Sook; Uh, Soo Taek; Chang, Hun Soo; Bae, Da Jeong; Cho, You Sook; Park, Hae Sim; Yoon, Ho Joo; Choi, Byoung Whui; Kim, Yong Hoon; Park, Choon Sik

2017-11-01

Asthma is a heterogeneous disease characterized by various types of airway inflammation and obstruction. Therefore, it is classified into several subphenotypes, such as early-onset atopic, obese non-eosinophilic, benign, and eosinophilic asthma, using cluster analysis. A number of asthmatics frequently experience exacerbation over a long-term follow-up period, but the exacerbation-prone subphenotype has rarely been evaluated by cluster analysis. This prompted us to identify clusters reflecting asthma exacerbation. A uniform cluster analysis method was applied to 259 adult asthmatics who were regularly followed-up for over 1 year using 12 variables, selected on the basis of their contribution to asthma phenotypes. After clustering, clinical profiles and exacerbation rates during follow-up were compared among the clusters. Four subphenotypes were identified: cluster 1 was comprised of patients with early-onset atopic asthma with preserved lung function, cluster 2 late-onset non-atopic asthma with impaired lung function, cluster 3 early-onset atopic asthma with severely impaired lung function, and cluster 4 late-onset non-atopic asthma with well-preserved lung function. The patients in clusters 2 and 3 were identified as exacerbation-prone asthmatics, showing a higher risk of asthma exacerbation. Two different phenotypes of exacerbation-prone asthma were identified among Korean asthmatics using cluster analysis; both were characterized by impaired lung function, but the age at asthma onset and atopic status were different between the two. Copyright © 2017 The Korean Academy of Asthma, Allergy and Clinical Immunology · The Korean Academy of Pediatric Allergy and Respiratory Disease

An efficient matrix-matrix multiplication based antisymmetric tensor contraction engine for general order coupled cluster.

PubMed

Hanrath, Michael; Engels-Putzka, Anna

2010-08-14

In this paper, we present an efficient implementation of general tensor contractions, which is part of a new coupled-cluster program. The tensor contractions, used to evaluate the residuals in each coupled-cluster iteration are particularly important for the performance of the program. We developed a generic procedure, which carries out contractions of two tensors irrespective of their explicit structure. It can handle coupled-cluster-type expressions of arbitrary excitation level. To make the contraction efficient without loosing flexibility, we use a three-step procedure. First, the data contained in the tensors are rearranged into matrices, then a matrix-matrix multiplication is performed, and finally the result is backtransformed to a tensor. The current implementation is significantly more efficient than previous ones capable of treating arbitrary high excitations.

ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster.

PubMed

Stocker, Gernot; Rieder, Dietmar; Trajanoski, Zlatko

2004-03-22

ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions. http://genome.tugraz.at/Software/ClusterControl

Associations between Functional Milestones and Psychiatric Admissions in an Urban Area: Utility of a Cluster-Analytical Approach.

PubMed

Montemagni, Cristiana; Frieri, Tiziana; Villari, Vincenzo; Rocca, Paola

2018-06-01

The purpose of the study was to identify homogenous subgroups, based upon achievement of two functional milestones (marriage and employment) and Global Assessment of Functioning (GAF) score in a sample of 848 acute patients admitted to the Psychiatric Emergency Service (PES) of the Città della Salute e della Scienza di Torino, during a 24-months period. A two-step cluster-analysis, using GAF total score and the achievements in the two milestones as input data was performed. In order to examine whether the identified subgroups differed in external variables that were not included in the clustering process, and consequently to validate the found functional profiles, chi-square tests for categorical variables and analyses of variance (ANOVA) for continuous variables were performed. Five clusters were found. Employed patients (Clusters 4 and 5) had more years of education, less illness chronicity (shorter duration of illness and lower proportion of previous voluntary hospitalizations), lower use of mental health resources in the last year yet higher treatment adherence, larger network size, and higher ordinary discharge. Married inpatients (Clusters 3 and 5) had lower frequencies of substance abuse. The remarkably high rate of unemployment in this inpatients' sample, and the evidence of associations between unemployment and poorer functioning, argue for further research and development of evidence-based supported employment programs, that put forth diligent effort in helping people obtain work quickly and sustain; they may also help to reduce health care service use among that clientele.

Deep Chandra Observations of Abell 586: A Remarkably Relaxed Non-Cool-Core Cluster

NASA Astrophysics Data System (ADS)

Richstein, Hannah; Su, Yuanyuan

2018-01-01

The dichotomy between cool-core and non-cool-core clusters has been a lasting perplexity in extragalactic astronomy. Nascent cores in non-cool-core clusters may have been disrupted by major mergers, yet the dichotomy cannot be reproduced in cosmology simulations. We present deep Chandra observations of the massive galaxy cluster Abell 586, which resides at z=0.17, thus allowing its gas properties to be measured out to its virial radius. Abell 586 appears remarkably relaxed with a nearly spherical X-ray surface brightness distribution and without any offset between its X-ray and optical centroids. We measure that its temperature profile does not decrease towards the cluster center and its central entropy stays above 100 keV cm2. A non-cool-core emerges in Abell 586 in the absence of any disruptions on the large scale. Our study demonstrates that non-cool-core clusters can be formed without major mergers. The origins of some non-cool-core clusters may be related to conduction, AGN feedback, or preheating.The SAO REU program is funded by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant AST-1659473, and by the Smithsonian Institution.

Cluster analysis of autoantibodies in 852 patients with systemic lupus erythematosus from a single center.

PubMed

Artim-Esen, Bahar; Çene, Erhan; Şahinkaya, Yasemin; Ertan, Semra; Pehlivan, Özlem; Kamali, Sevil; Gül, Ahmet; Öcal, Lale; Aral, Orhan; Inanç, Murat

2014-07-01

Associations between autoantibodies and clinical features have been described in systemic lupus erythematosus (SLE). Herein, we aimed to define autoantibody clusters and their clinical correlations in a large cohort of patients with SLE. We analyzed 852 patients with SLE who attended our clinic. Seven autoantibodies were selected for cluster analysis: anti-DNA, anti-Sm, anti-RNP, anticardiolipin (aCL) immunoglobulin (Ig)G or IgM, lupus anticoagulant (LAC), anti-Ro, and anti-La. Two-step clustering and Kaplan-Meier survival analyses were used. Five clusters were identified. A cluster consisted of patients with only anti-dsDNA antibodies, a cluster of anti-Sm and anti-RNP, a cluster of aCL IgG/M and LAC, and a cluster of anti-Ro and anti-La antibodies. Analysis revealed 1 more cluster that consisted of patients who did not belong to any of the clusters formed by antibodies chosen for cluster analysis. Sm/RNP cluster had significantly higher incidence of pulmonary hypertension and Raynaud phenomenon. DsDNA cluster had the highest incidence of renal involvement. In the aCL/LAC cluster, there were significantly more patients with neuropsychiatric involvement, antiphospholipid syndrome, autoimmune hemolytic anemia, and thrombocytopenia. According to the Systemic Lupus International Collaborating Clinics damage index, the highest frequency of damage was in the aCL/LAC cluster. Comparison of 10 and 20 years survival showed reduced survival in the aCL/LAC cluster. This study supports the existence of autoantibody clusters with distinct clinical features in SLE and shows that forming clinical subsets according to autoantibody clusters may be useful in predicting the outcome of the disease. Autoantibody clusters in SLE may exhibit differences according to the clinical setting or population.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

The KMOS Cluster Survey (KCS). II. The Effect of Environment on the Structural Properties of Massive Cluster Galaxies at Redshift 1.39 < z < 1.61

NASA Astrophysics Data System (ADS)

Chan, Jeffrey C. C.; Beifiori, Alessandra; Saglia, Roberto P.; Mendel, J. Trevor; Stott, John P.; Bender, Ralf; Galametz, Audrey; Wilman, David J.; Cappellari, Michele; Davies, Roger L.; Houghton, Ryan C. W.; Prichard, Laura J.; Lewis, Ian J.; Sharples, Ray; Wegner, Michael

2018-03-01

We present results on the structural properties of massive passive galaxies in three clusters at 1.39 < z < 1.61 from the KMOS Cluster Survey. We measure light-weighted and mass-weighted sizes from optical and near-infrared Hubble Space Telescope imaging and spatially resolved stellar mass maps. The rest-frame R-band sizes of these galaxies are a factor of ∼2–3 smaller than their local counterparts. The slopes of the relation between the stellar mass and the light-weighted size are consistent with recent studies in clusters and the field. Their mass-weighted sizes are smaller than the rest-frame R-band sizes, with an average mass-weighted to light-weighted size ratio that varies between ∼0.45 and 0.8 among the clusters. We find that the median light-weighted size of the passive galaxies in the two more evolved clusters is ∼24% larger than that for field galaxies, independent of the use of circularized effective radii or semimajor axes. These two clusters also show a smaller size ratio than the less evolved cluster, which we investigate using color gradients to probe the underlying {M}* /{L}{{{H}}160} gradients. The median color gradients are ∇z ‑ H ∼ ‑0.4 mag dex‑1, twice the local value. Using stellar populations models, these gradients are best reproduced by a combination of age and metallicity gradients. Our results favor the minor merger scenario as the dominant process responsible for the observed galaxy properties and the environmental differences at this redshift. The environmental differences support that clusters experience accelerated structural evolution compared to the field, likely via an epoch of enhanced minor merger activity during cluster assembly. Based on observations obtained at the Very Large Telescope (VLT) of the European Southern Observatory (ESO; program IDs: 092.A-0210; 093.A-0051; 094.A-0578; 095.A-0137(A); 096.A-0189(A); 097.A-0332(A)). This work is based on observations made with the NASA/ESA HST, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with program GO 13687, as well as with the CANDELS Multi-Cycle Treasury Program and the 3D-HST Treasury Program (GO 12177 and 12328).

Properties of the Open Cluster Tombaugh 1 from High-resolution Spectroscopy and uvbyCaHβ Photometry

NASA Astrophysics Data System (ADS)

Sales Silva, João V.; Carraro, Giovanni; Anthony-Twarog, Barbara J.; Moni Bidin, Christian; Costa, Edgardo; Twarog, Bruce A.

2016-01-01

Open clusters can be the key to deepening our knowledge on various issues involving the structure and evolution of the Galactic disk and details of stellar evolution because a cluster’s properties are applicable to all its members. However, the number of open clusters with detailed analysis from high-resolution spectroscopy or precision photometry imposes severe limitations on studies of these objects. To expand the number of open clusters with well-defined chemical abundances and fundamental parameters, we investigate the poorly studied, anticenter open cluster Tombaugh 1. Using precision uvbyCaHβ photometry and high-resolution spectroscopy, we derive the cluster’s reddening, obtain photometric metallicity estimates, and, for the first time, present a detailed abundance analysis of 10 potential cluster stars (nine clump stars and one Cepheid). Using the radial position from the cluster center and multiple color indices, we have isolated a sample of unevolved, probable single-star members of Tombaugh 1. From 51 stars, the cluster reddening is found to be E(b-y) = 0.221 ± 0.006 or E(B-V) = 0.303 ± 0.008, where the errors refer to the internal standard errors of the mean. The weighted photometric metallicity from m1 and hk is [Fe/H] = -0.10 ± 0.02, while a match to the Victoria-Regina Strömgren isochrones leads to an age of 0.95 ± 0.10 Gyr and an apparent modulus of (m-M) = 13.10 ± 0.10. Radial velocities identify six giants as probable cluster members, and the elemental abundances of Fe, Na, Mg, Al, Si, Ca, Ti, Cr, Ni, Y, Ba, Ce, and Nd have been derived for both the cluster and the field stars. Tombaugh 1 appears to be a typical inner thin disk, intermediate-age open cluster of slightly subsolar metallicity, located just beyond the solar circle, with solar elemental abundance ratios except for the heavy s-process elements, which are a factor of two above solar. Its metallicity is consistent with a steep metallicity gradient in the galactocentric region between 9.5 and 12 kpc. Our study also shows that Cepheid XZ CMa is not a member of Tombaugh 1 and reveals that this Cepheid presents signs of barium enrichment, making it a probable binary star. Based on observations carried out at Las Campanas Observatory (program ID: CN2009B-042) and Cerro Tololo Inter-American Observatory.

A cross-species bi-clustering approach to identifying conserved co-regulated genes.

PubMed

Sun, Jiangwen; Jiang, Zongliang; Tian, Xiuchun; Bi, Jinbo

2016-06-15

A growing number of studies have explored the process of pre-implantation embryonic development of multiple mammalian species. However, the conservation and variation among different species in their developmental programming are poorly defined due to the lack of effective computational methods for detecting co-regularized genes that are conserved across species. The most sophisticated method to date for identifying conserved co-regulated genes is a two-step approach. This approach first identifies gene clusters for each species by a cluster analysis of gene expression data, and subsequently computes the overlaps of clusters identified from different species to reveal common subgroups. This approach is ineffective to deal with the noise in the expression data introduced by the complicated procedures in quantifying gene expression. Furthermore, due to the sequential nature of the approach, the gene clusters identified in the first step may have little overlap among different species in the second step, thus difficult to detect conserved co-regulated genes. We propose a cross-species bi-clustering approach which first denoises the gene expression data of each species into a data matrix. The rows of the data matrices of different species represent the same set of genes that are characterized by their expression patterns over the developmental stages of each species as columns. A novel bi-clustering method is then developed to cluster genes into subgroups by a joint sparse rank-one factorization of all the data matrices. This method decomposes a data matrix into a product of a column vector and a row vector where the column vector is a consistent indicator across the matrices (species) to identify the same gene cluster and the row vector specifies for each species the developmental stages that the clustered genes co-regulate. Efficient optimization algorithm has been developed with convergence analysis. This approach was first validated on synthetic data and compared to the two-step method and several recent joint clustering methods. We then applied this approach to two real world datasets of gene expression during the pre-implantation embryonic development of the human and mouse. Co-regulated genes consistent between the human and mouse were identified, offering insights into conserved functions, as well as similarities and differences in genome activation timing between the human and mouse embryos. The R package containing the implementation of the proposed method in C ++ is available at: https://github.com/JavonSun/mvbc.git and also at the R platform https://www.r-project.org/ jinbo@engr.uconn.edu. © The Author 2016. Published by Oxford University Press.

Is It Feasible to Identify Natural Clusters of TSC-Associated Neuropsychiatric Disorders (TAND)?

PubMed

Leclezio, Loren; Gardner-Lubbe, Sugnet; de Vries, Petrus J

2018-04-01

Tuberous sclerosis complex (TSC) is a genetic disorder with multisystem involvement. The lifetime prevalence of TSC-Associated Neuropsychiatric Disorders (TAND) is in the region of 90% in an apparently unique, individual pattern. This "uniqueness" poses significant challenges for diagnosis, psycho-education, and intervention planning. To date, no studies have explored whether there may be natural clusters of TAND. The purpose of this feasibility study was (1) to investigate the practicability of identifying natural TAND clusters, and (2) to identify appropriate multivariate data analysis techniques for larger-scale studies. TAND Checklist data were collected from 56 individuals with a clinical diagnosis of TSC (n = 20 from South Africa; n = 36 from Australia). Using R, the open-source statistical platform, mean squared contingency coefficients were calculated to produce a correlation matrix, and various cluster analyses and exploratory factor analysis were examined. Ward's method rendered six TAND clusters with good face validity and significant convergence with a six-factor exploratory factor analysis solution. The "bottom-up" data-driven strategies identified a "scholastic" cluster of TAND manifestations, an "autism spectrum disorder-like" cluster, a "dysregulated behavior" cluster, a "neuropsychological" cluster, a "hyperactive/impulsive" cluster, and a "mixed/mood" cluster. These feasibility results suggest that a combination of cluster analysis and exploratory factor analysis methods may be able to identify clinically meaningful natural TAND clusters. Findings require replication and expansion in larger dataset, and could include quantification of cluster or factor scores at an individual level. Copyright © 2018 Elsevier Inc. All rights reserved.

A Proposal to Investigate Outstanding Problems in Astronomy

NASA Technical Reports Server (NTRS)

Ford, Holland

2003-01-01

During the past year the ACS science team has concentrated on analyzing ACS observations, writing papers, and disseminating our results to the astronomy community at conferences and workshops around the world. We also have put considerable effort in getting our results to the public via public lectures and through press releases. Taking a very broad view of our program, we are investigating the evolution of galaxies and clusters of galaxies from their birth, approximately one billion years after the beginning of the Universe, to the present. We have found and characterized a population of galaxies that are no more than 1.4 billion years old. These may well be the Universe s first generation of infant galaxies. Looking at the Universe 500,000 years later, we see what appears to be a cluster of galaxies just beginning to form (a proto-cluster) around a luminous radio galaxy. Moving forward in time and closer to the present, we are studying clusters of galaxies that are less than half the age of the Universe. Our observations and analysis lead us to the important conclusion that the elliptical galaxies in these clusters must have had their last significant star formation some three billion years earlier, which is about the time when the proto-cluster was forming. Coming still closer to home, we are observing nearby massive clusters of galaxies that are approximately 12 billion years old. The gravity from these large aggregates of dark and luminous matter is so strong it warps space-time itself, and makes the cluster act as a cosmic telescope that magnifies the distant galaxies behind the cluster. We used the magnified (or lensed) galaxies to map the distribution of the dominant matter within the clusters, which is the so-called dark matter (the matter is invisible, and its nature is unknown). We also are using these cosmic telescopes to study the distant lensed galaxies that would otherwise be too small and too faint to be seen even by Hubble and the ACS.

Design of a Cluster-Randomized Controlled Trial of a Diabetes Prevention Program within African-American Churches: The Fit Body and Soul Study

PubMed Central

Williams, Lovoria B.; Sattin, Richard W.; Dias, James; Garvin, Jane T.; Marion, Lucy; Joshua, Thomas; Kriska, Andrea; Kramer, M. Kaye; Echouffo-Tcheugui, Justin B.; Freeman, Arin; Narayan, K.M. Venkat

2013-01-01

Evidence from varied community settings has shown that the Group Lifestyle Balance (GLB) Program and other adaptations of the Diabetes Prevention Program (DPP) intervention are effective in lowering diabetes risk. Most DPP data originated from studies of pre-diabetic whites, with only sparse evidence of the effect of DPP in African Americans (AAs) in community settings. This paper describes the design, methods, baseline characteristics and cost effective measures, of a single-blinded, cluster- randomized trial of a faith-based adaptation of the GLB program, Fit Body and Soul (FBAS). The major aims are to test efficacy and cost utility of FBAS in twenty AA churches. Randomization occurred at the church level and 604 AA overweight/obese (BMI≥25 kg/m2) adults with fasting plasma glucose range from normal to pre-diabetic received either FBAS or a health-education comparison program. FBAS is a group-based, multi-level intervention delivered by trained church health advisors (health professionals from within the church), with the goal of ≥7% weight loss, achieved through increasing physical activity, healthy eating and behavior modification. The primary outcome is weight change at 12-weeks post intervention. Secondary outcomes include hemoglobin A1C, fasting plasma glucose, waist circumference, blood pressure, physical activity level, quality of life measures, and cost-effectiveness. FBAS is the largest known cohort of AAs enrolled in a faith-based DPP translation. Reliance on health professionals from within the church for program implementation and the cost analysis are unique aspects of this trial. The design provides a model for faith-based DPPs and holds promise for program sustainability and widespread dissemination. PMID:23354313

Spatial analysis of county-based gonorrhoea incidence in mainland China, from 2004 to 2009.

PubMed

Yin, Fei; Feng, Zijian; Li, Xiaosong

2012-07-01

Gonorrhoea is one of the most common sexually transmissible infections in mainland China. Effective spatial monitoring of gonorrhoea incidence is important for successful implementation of control and prevention programs. The county-level gonorrhoea incidence rates for all of mainland China was monitored through examining spatial patterns. County-level data on gonorrhoea cases between 2004 and 2009 were obtained from the China Information System for Disease Control and Prevention. Bayesian smoothing and exploratory spatial data analysis (ESDA) methods were used to characterise the spatial distribution pattern of gonorrhoea cases. During the 6-year study period, the average annual gonorrhoea incidence was 12.41 cases per 100000 people. Using empirical Bayes smoothed rates, the local Moran test identified one significant single-centre cluster and two significant multi-centre clusters of high gonorrhoea risk (all P-values <0.01). Bayesian smoothing and ESDA methods can assist public health officials in using gonorrhoea surveillance data to identify high risk areas. Allocating more resources to such areas could effectively reduce gonorrhoea incidence.

Video Analysis of Granular Gases in a Low-Gravity Environment

NASA Astrophysics Data System (ADS)

Lewallen, Erin

2004-10-01

Granular Agglomeration in Non-Gravitating Systems is a research project undertaken by the University of Tulsa Granular Dynamics Group. The project investigates the effects of weightlessness on granular systems by studying the dynamics of a "gas" of 1-mm diameter brass ball bearings driven at various amplitudes and frequencies in low-gravity. Models predict that particles in systems subjected to these conditions should exhibit clustering behavior due to energy loss through multiple inelastic collisions. Observation and study of clustering in our experiment could shed light on this phenomenon as a possible mechanism by which particles in space coalesce to form stable objects such as planetesimals and planetary ring systems. Our experiment has flown on NASA's KC-135 low gravity aircraft. Data analysis techniques for video data collected during these flights include modification of images using Adobe Photoshop and development of ball identification and tracking programs written in Interactive Data Language. By tracking individual balls, we aim to establish speed distributions for granular gases and thereby obtain values for granular temperature.

A cluster analysis of service utilization and incarceration among homeless youth

PubMed Central

Kort-Butler, Lisa A.; Tyler, Kimberly A.

2012-01-01

Our paper examines service usage (e.g., shelter) as well as a typology of individuals who are most likely to use groupings of services among 249 homeless youth. Our results revealed that the majority of homeless young people have used food programs (66%) and street outreach (65%) on at least one occasion within the past year. Cluster analysis of services revealed four distinct groups: (1) basic survival service use, characterized by above average shelter, food, and outreach service use, but below average on counseling, substance abuse/ mental health services, and incarceration; (2) multiple service use, which included above average use of all six services; (3) incarceration experience, characterized by above average incarceration experience, but below average use of all other five services; and (4) minimal service use, which included slightly above average use of counseling, but below average use of all other services. These findings have the potential to provide important information that may assist with targeting services to homeless youth. PMID:23017796

Development of a Pilot Career Cluster Curriculum for all Students in a College Preparatory Oriented High School. Final Report. Part I: Curriculum Development.

ERIC Educational Resources Information Center

Montgomery County Public Schools, Rockville, MD.

In developing a program to assist the individual student to plan a goal-oriented program and increase his opportunities both to select courses moving him toward his personal goals and to use the community resources as supplemental educational experiences, the Winston Churchill High School designed a Career Cluster Curriculum Project, the first…

The Long-Term Effectiveness of a Selective, Personality-Targeted Prevention Program in Reducing Alcohol Use and Related Harms: A Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Newton, Nicola C.; Conrod, Patricia J.; Slade, Tim; Carragher, Natacha; Champion, Katrina E.; Barrett, Emma L.; Kelly, Erin V.; Nair, Natasha K.; Stapinski, Lexine; Teesson, Maree

2016-01-01

Background: This study investigated the long-term effectiveness of Preventure, a selective personality-targeted prevention program, in reducing the uptake of alcohol, harmful use of alcohol, and alcohol-related harms over a 3-year period. Methods: A cluster randomized controlled trial was conducted to assess the effectiveness of Preventure.…

Using Social-Emotional and Character Development to Improve Academic Outcomes: A Matched-Pair, Cluster-Randomized Controlled Trial in Low-Income, Urban Schools

ERIC Educational Resources Information Center

Bavarian, Niloofar; Lewis, Kendra M.; DuBois, David L.; Acock, Alan; Vuchinich, Samuel; Silverthorn, Naida; Snyder, Frank J.; Day, Joseph; Ji, Peter; Flay, Brian R.

2013-01-01

Background: School-based social-emotional and character development (SECD) programs can influence not only SECD but also academic-related outcomes. This study evaluated the impact of one SECD program, Positive Action (PA), on educational outcomes among low-income, urban youth. Methods: The longitudinal study used a matched-pair, cluster-randomized…