Cluster Inter-Spacecraft Communications

NASA Technical Reports Server (NTRS)

Cox, Brian

2008-01-01

A document describes a radio communication system being developed for exchanging data and sharing data-processing capabilities among spacecraft flying in formation. The system would establish a high-speed, low-latency, deterministic loop communication path connecting all the spacecraft in a cluster. The system would be a wireless version of a ring bus that complies with the Institute of Electrical and Electronics Engineers (IEEE) standard 1393 (which pertains to a spaceborne fiber-optic data bus enhancement to the IEEE standard developed at NASA's Jet Propulsion Laboratory). Every spacecraft in the cluster would be equipped with a ring-bus radio transceiver. The identity of a spacecraft would be established upon connection into the ring bus, and the spacecraft could be at any location in the ring communication sequence. In the event of failure of a spacecraft, the ring bus would reconfigure itself, bypassing a failed spacecraft. Similarly, the ring bus would reconfigure itself to accommodate a spacecraft newly added to the cluster or newly enabled or re-enabled. Thus, the ring bus would be scalable and robust. Reliability could be increased by launching, into the cluster, spare spacecraft to be activated in the event of failure of other spacecraft.

Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

PubMed

Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

2009-02-01

Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

Hierarchical Dirichlet process model for gene expression clustering

PubMed Central

2013-01-01

Clustering is an important data processing tool for interpreting microarray data and genomic network inference. In this article, we propose a clustering algorithm based on the hierarchical Dirichlet processes (HDP). The HDP clustering introduces a hierarchical structure in the statistical model which captures the hierarchical features prevalent in biological data such as the gene express data. We develop a Gibbs sampling algorithm based on the Chinese restaurant metaphor for the HDP clustering. We apply the proposed HDP algorithm to both regulatory network segmentation and gene expression clustering. The HDP algorithm is shown to outperform several popular clustering algorithms by revealing the underlying hierarchical structure of the data. For the yeast cell cycle data, we compare the HDP result to the standard result and show that the HDP algorithm provides more information and reduces the unnecessary clustering fragments. PMID:23587447

ClusCo: clustering and comparison of protein models.

PubMed

Jamroz, Michal; Kolinski, Andrzej

2013-02-22

The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of the bottlenecks in the protein modeling pipeline. Clusco is fast and easy-to-use software for high-throughput comparison of protein models with different similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap) and clustering of the comparison results with standard methods: K-means Clustering or Hierarchical Agglomerative Clustering. The application was highly optimized and written in C/C++, including the code for parallel execution on CPU and GPU, which resulted in a significant speedup over similar clustering and scoring computation programs.

DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer.

PubMed

Saha, Abhijoy; Banerjee, Sayantan; Kurtek, Sebastian; Narang, Shivali; Lee, Joonsang; Rao, Ganesh; Martinez, Juan; Bharath, Karthik; Rao, Arvind U K; Baladandayuthapani, Veerabhadran

2016-01-01

Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher-Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.

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.

Photometric Calibrations of Gemini Images of NGC 6253

NASA Astrophysics Data System (ADS)

Pearce, Sean; Jeffery, Elizabeth

2017-01-01

We present preliminary results of our analysis of the metal-rich open cluster NGC 6253 using imaging data from GMOS on the Gemini-South Observatory. These data are part of a larger project to observe the effects of high metallicity on white dwarf cooling processes, especially the white dwarf cooling age, which have important implications on the processes of stellar evolution. To standardize the Gemini photometry, we have also secured imaging data of both the cluster and standard star fields using the 0.6-m SARA Observatory at CTIO. By analyzing and comparing the standard star fields of both the SARA data and the published Gemini zero-points of the standard star fields, we will calibrate the data obtained for the cluster. These calibrations are an important part of the project to obtain a standardized deep color-magnitude diagram to analyze the cluster. We present the process of verifying our standardization process. With a standardized CMD, we also present an analysis of the cluster's main sequence turn off age.

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

Photometry of Standard Stars and Open Star Clusters

NASA Astrophysics Data System (ADS)

Jefferies, Amanda; Frinchaboy, Peter

2010-10-01

Photometric CCD observations of open star clusters and standard stars were carried out at the McDonald Observatory in Fort Davis, Texas. This data was analyzed using aperture photometry algorithms (DAOPHOT II and ALLSTAR) and the IRAF software package. Color-magnitude diagrams of these clusters were produced, showing the evolution of each cluster along the main sequence.

Algorithms of maximum likelihood data clustering with applications

NASA Astrophysics Data System (ADS)

Giada, Lorenzo; Marsili, Matteo

2002-12-01

We address the problem of data clustering by introducing an unsupervised, parameter-free approach based on maximum likelihood principle. Starting from the observation that data sets belonging to the same cluster share a common information, we construct an expression for the likelihood of any possible cluster structure. The likelihood in turn depends only on the Pearson's coefficient of the data. We discuss clustering algorithms that provide a fast and reliable approximation to maximum likelihood configurations. Compared to standard clustering methods, our approach has the advantages that (i) it is parameter free, (ii) the number of clusters need not be fixed in advance and (iii) the interpretation of the results is transparent. In order to test our approach and compare it with standard clustering algorithms, we analyze two very different data sets: time series of financial market returns and gene expression data. We find that different maximization algorithms produce similar cluster structures whereas the outcome of standard algorithms has a much wider variability.

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

Human Resource Consulting Education: Professional Development for the Personnel Consulting Industry.

ERIC Educational Resources Information Center

Bone, John

1996-01-01

Interviews and surveys of 200 personnel consultants revealed an urgent need for basic and ongoing professional development education and for national competence standards and accreditation. Skill needs clustered in three categories: recruitment, selection, and sales/marketing. Professional education should recognize lifelong learning, take…

Non-specific filtering of beta-distributed data.

PubMed

Wang, Xinhui; Laird, Peter W; Hinoue, Toshinori; Groshen, Susan; Siegmund, Kimberly D

2014-06-19

Non-specific feature selection is a dimension reduction procedure performed prior to cluster analysis of high dimensional molecular data. Not all measured features are expected to show biological variation, so only the most varying are selected for analysis. In DNA methylation studies, DNA methylation is measured as a proportion, bounded between 0 and 1, with variance a function of the mean. Filtering on standard deviation biases the selection of probes to those with mean values near 0.5. We explore the effect this has on clustering, and develop alternate filter methods that utilize a variance stabilizing transformation for Beta distributed data and do not share this bias. We compared results for 11 different non-specific filters on eight Infinium HumanMethylation data sets, selected to span a variety of biological conditions. We found that for data sets having a small fraction of samples showing abnormal methylation of a subset of normally unmethylated CpGs, a characteristic of the CpG island methylator phenotype in cancer, a novel filter statistic that utilized a variance-stabilizing transformation for Beta distributed data outperformed the common filter of using standard deviation of the DNA methylation proportion, or its log-transformed M-value, in its ability to detect the cancer subtype in a cluster analysis. However, the standard deviation filter always performed among the best for distinguishing subgroups of normal tissue. The novel filter and standard deviation filter tended to favour features in different genome contexts; for the same data set, the novel filter always selected more features from CpG island promoters and the standard deviation filter always selected more features from non-CpG island intergenic regions. Interestingly, despite selecting largely non-overlapping sets of features, the two filters did find sample subsets that overlapped for some real data sets. We found two different filter statistics that tended to prioritize features with different characteristics, each performed well for identifying clusters of cancer and non-cancer tissue, and identifying a cancer CpG island hypermethylation phenotype. Since cluster analysis is for discovery, we would suggest trying both filters on any new data sets, evaluating the overlap of features selected and clusters discovered.

Know thy eHealth user: Development of biopsychosocial personas from a study of older adults with heart failure.

PubMed

Holden, Richard J; Kulanthaivel, Anand; Purkayastha, Saptarshi; Goggins, Kathryn M; Kripalani, Sunil

2017-12-01

Personas are a canonical user-centered design method increasingly used in health informatics research. Personas-empirically-derived user archetypes-can be used by eHealth designers to gain a robust understanding of their target end users such as patients. To develop biopsychosocial personas of older patients with heart failure using quantitative analysis of survey data. Data were collected using standardized surveys and medical record abstraction from 32 older adults with heart failure recently hospitalized for acute heart failure exacerbation. Hierarchical cluster analysis was performed on a final dataset of n=30. Nonparametric analyses were used to identify differences between clusters on 30 clustering variables and seven outcome variables. Six clusters were produced, ranging in size from two to eight patients per cluster. Clusters differed significantly on these biopsychosocial domains and subdomains: demographics (age, sex); medical status (comorbid diabetes); functional status (exhaustion, household work ability, hygiene care ability, physical ability); psychological status (depression, health literacy, numeracy); technology (Internet availability); healthcare system (visit by home healthcare, trust in providers); social context (informal caregiver support, cohabitation, marital status); and economic context (employment status). Tabular and narrative persona descriptions provide an easy reference guide for informatics designers. Personas development using approaches such as clustering of structured survey data is an important tool for health informatics professionals. We describe insights from our study of patients with heart failure, then recommend a generic ten-step personas development process. Methods strengths and limitations of the study and of personas development generally are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Cluster mass inference via random field theory.

PubMed

Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D

2009-01-01

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.

Southern Clusters for Standardizing CCD Photometry

NASA Astrophysics Data System (ADS)

Moon, T. T.

2017-06-01

Standardizing photometric measurements typically involves undertaking all-sky photometry. This can be laborious and time-consuming and, for CCD photometry, particularly challenging. Transforming photometry to a standard system is, however, a crucial step when routinely measuring variable stars, as it allows photoelectric measurements from different observers to be combined. For observers in the northern hemisphere, standardized UBVRI values of stars in open clusters such as M67 and NGC 7790 have been established, greatly facilitating quick and accurate transformation of CCD measurements. Recently the AAVSO added the cluster NGC 3532 for southern hemisphere observers to similarly standardize their photometry. The availability of NGC 3532 standards was announced on the AAVSO Variable Star Observing, Photometry forum on 27 October 2016. Published photometry, along with some new measurements by the author, provide a means of checking these NGC 3532 standards which were determined through the AAVSO's Bright Star Monitor (BSM) program (see: https://www.aavso.org/aavsonet-epoch-photometry-database). New measurements of selected stars in the open clusters M25 and NGC 6067 are also included.

Assessment of economic status in trauma registries: A new algorithm for generating population-specific clustering-based models of economic status for time-constrained low-resource settings.

PubMed

Eyler, Lauren; Hubbard, Alan; Juillard, Catherine

2016-10-01

Low and middle-income countries (LMICs) and the world's poor bear a disproportionate share of the global burden of injury. Data regarding disparities in injury are vital to inform injury prevention and trauma systems strengthening interventions targeted towards vulnerable populations, but are limited in LMICs. We aim to facilitate injury disparities research by generating a standardized methodology for assessing economic status in resource-limited country trauma registries where complex metrics such as income, expenditures, and wealth index are infeasible to assess. To address this need, we developed a cluster analysis-based algorithm for generating simple population-specific metrics of economic status using nationally representative Demographic and Health Surveys (DHS) household assets data. For a limited number of variables, g, our algorithm performs weighted k-medoids clustering of the population using all combinations of g asset variables and selects the combination of variables and number of clusters that maximize average silhouette width (ASW). In simulated datasets containing both randomly distributed variables and "true" population clusters defined by correlated categorical variables, the algorithm selected the correct variable combination and appropriate cluster numbers unless variable correlation was very weak. When used with 2011 Cameroonian DHS data, our algorithm identified twenty economic clusters with ASW 0.80, indicating well-defined population clusters. This economic model for assessing health disparities will be used in the new Cameroonian six-hospital centralized trauma registry. By describing our standardized methodology and algorithm for generating economic clustering models, we aim to facilitate measurement of health disparities in other trauma registries in resource-limited countries. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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: 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…

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…

X-ray clusters from a high-resolution hydrodynamic PPM simulation of the cold dark matter universe

NASA Technical Reports Server (NTRS)

Bryan, Greg L.; Cen, Renyue; Norman, Michael L.; Ostriker, Jermemiah P.; Stone, James M.

1994-01-01

A new three-dimensional hydrodynamic code based on the piecewise parabolic method (PPM) is utilized to compute the distribution of hot gas in the standard Cosmic Background Explorer (COBE)-normalized cold dark matter (CDM) universe. Utilizing periodic boundary conditions, a box with size 85 h(exp-1) Mpc, having cell size 0.31 h(exp-1) Mpc, is followed in a simulation with 270(exp 3)=10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, Sigma(sub 8)=1.05, Omega(sub b)=0.06, we find the X-ray-emitting clusters, compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. The results, which are compared with those obtained in the preceding paper (Kang et al. 1994a), may be used in conjuction with ROSAT and other observational data sets. Overall, the results of the two computations are qualitatively very similar with regard to the trends of cluster properties, i.e., how the number density, radius, and temeprature depend on luminosity and redshift. The total luminosity from clusters is approximately a factor of 2 higher using the PPM code (as compared to the 'total variation diminishing' (TVD) code used in the previous paper) with the number of bright clusters higher by a similar factor. The primary conclusions of the prior paper, with regard to the power spectrum of the primeval density perturbations, are strengthened: the standard CDM model, normalized to the COBE microwave detection, predicts too many bright X-ray emitting clusters, by a factor probably in excess of 5. The comparison between observations and theoretical predictions for the evolution of cluster properties, luminosity functions, and size and temperature distributions should provide an important discriminator among competing scenarios for the development of structure in the universe.

Illinois Occupational Skill Standards: Information Technology Design/Build Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document contains Illinois Occupational Skill Standards for occupations in the Information Technology Design and Build Cluster (technical writer, programmer, system analyst, network architect, application product architect, network engineer, and database administrator). The skill standards define what an individual should know and the…

Temperament Profiles from Infancy to Middle Childhood: Development and Associations with Behavior Problems

ERIC Educational Resources Information Center

Janson, Harald; Mathiesen, Kristin S.

2008-01-01

The authors applied I-States as Objects Analysis (ISOA), a recently proposed person-oriented analytic approach, to the study of temperament development in 921 Norwegian children from a population-based sample. A 5-profile classification based on cluster analysis of standardized mother reports of activity, sociability, emotionality, and shyness at…

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…

Visualizing statistical significance of disease clusters using cartograms.

PubMed

Kronenfeld, Barry J; Wong, David W S

2017-05-15

Health officials and epidemiological researchers often use maps of disease rates to identify potential disease clusters. Because these maps exaggerate the prominence of low-density districts and hide potential clusters in urban (high-density) areas, many researchers have used density-equalizing maps (cartograms) as a basis for epidemiological mapping. However, we do not have existing guidelines for visual assessment of statistical uncertainty. To address this shortcoming, we develop techniques for visual determination of statistical significance of clusters spanning one or more districts on a cartogram. We developed the techniques within a geovisual analytics framework that does not rely on automated significance testing, and can therefore facilitate visual analysis to detect clusters that automated techniques might miss. On a cartogram of the at-risk population, the statistical significance of a disease cluster is determinate from the rate, area and shape of the cluster under standard hypothesis testing scenarios. We develop formulae to determine, for a given rate, the area required for statistical significance of a priori and a posteriori designated regions under certain test assumptions. Uniquely, our approach enables dynamic inference of aggregate regions formed by combining individual districts. The method is implemented in interactive tools that provide choropleth mapping, automated legend construction and dynamic search tools to facilitate cluster detection and assessment of the validity of tested assumptions. A case study of leukemia incidence analysis in California demonstrates the ability to visually distinguish between statistically significant and insignificant regions. The proposed geovisual analytics approach enables intuitive visual assessment of statistical significance of arbitrarily defined regions on a cartogram. Our research prompts a broader discussion of the role of geovisual exploratory analyses in disease mapping and the appropriate framework for visually assessing the statistical significance of spatial clusters.

Review of Recent Methodological Developments in Group-Randomized Trials: Part 1—Design

PubMed Central

Li, Fan; Gallis, John A.; Prague, Melanie; Murray, David M.

2017-01-01

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have highlighted the developments of the past 13 years in design with a companion article to focus on developments in analysis. As a pair, these articles update the 2004 review. We have discussed developments in the topics of the earlier review (e.g., clustering, matching, and individually randomized group-treatment trials) and in new topics, including constrained randomization and a range of randomized designs that are alternatives to the standard parallel-arm GRT. These include the stepped-wedge GRT, the pseudocluster randomized trial, and the network-randomized GRT, which, like the parallel-arm GRT, require clustering to be accounted for in both their design and analysis. PMID:28426295

Review of Recent Methodological Developments in Group-Randomized Trials: Part 1-Design.

PubMed

Turner, Elizabeth L; Li, Fan; Gallis, John A; Prague, Melanie; Murray, David M

2017-06-01

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have highlighted the developments of the past 13 years in design with a companion article to focus on developments in analysis. As a pair, these articles update the 2004 review. We have discussed developments in the topics of the earlier review (e.g., clustering, matching, and individually randomized group-treatment trials) and in new topics, including constrained randomization and a range of randomized designs that are alternatives to the standard parallel-arm GRT. These include the stepped-wedge GRT, the pseudocluster randomized trial, and the network-randomized GRT, which, like the parallel-arm GRT, require clustering to be accounted for in both their design and analysis.

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…

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: 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: 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…

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

The Effect of Cluster Sampling Design in Survey Research on the Standard Error Statistic.

ERIC Educational Resources Information Center

Wang, Lin; Fan, Xitao

Standard statistical methods are used to analyze data that is assumed to be collected using a simple random sampling scheme. These methods, however, tend to underestimate variance when the data is collected with a cluster design, which is often found in educational survey research. The purposes of this paper are to demonstrate how a cluster design…

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: 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: 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,…

An Empirical Comparison of Variable Standardization Methods in Cluster Analysis.

ERIC Educational Resources Information Center

Schaffer, Catherine M.; Green, Paul E.

1996-01-01

The common marketing research practice of standardizing the columns of a persons-by-variables data matrix prior to clustering the entities corresponding to the rows was evaluated with 10 large-scale data sets. Results indicate that the column standardization practice may be problematic for some kinds of data that marketing researchers used for…

Investigation of dislocation cluster evolution during directional solidification of multicrystalline silicon

NASA Astrophysics Data System (ADS)

Oriwol, Daniel; Trempa, Matthias; Sylla, Lamine; Leipner, Hartmut S.

2017-04-01

Dislocation clusters are the main crystal defects in multicrystalline silicon and are detrimental for solar cell efficiency. They were formed during the silicon ingot casting due to the relaxation of strain energy. The evolution of the dislocation clusters was studied by means of automated analysing tools of the standard wafer and cell production giving information about the cluster development as a function of the ingot height. Due to the observation of the whole wafer surface the point of view is of macroscopic nature. It was found that the dislocations tend to build clusters of high density which usually expand in diameter as a function of ingot height. According to their structure the dislocation clusters can be divided into light and dense clusters. The appearance of both types shows a clear dependence on the orientation of the grain growth direction. Additionally, a process of annihilation of dislocation clusters during the crystallization has been observed. To complement the macroscopic description, the dislocation clusters were also investigates by TEM. It is shown that the dislocations within the subgrain boundaries are closely arranged. Distances of 40-30 nm were found. These results lead to the conclusion that the dislocation density within the cluster structure is impossible to quantify by means of etch pit counting.

Finite temperature properties of clusters by replica exchange metadynamics: the water nonamer.

PubMed

Zhai, Yingteng; Laio, Alessandro; Tosatti, Erio; Gong, Xin-Gao

2011-03-02

We introduce an approach for the accurate calculation of thermal properties of classical nanoclusters. On the basis of a recently developed enhanced sampling technique, replica exchange metadynamics, the method yields the true free energy of each relevant cluster structure, directly sampling its basin and measuring its occupancy in full equilibrium. All entropy sources, whether vibrational, rotational anharmonic, or especially configurational, the latter often forgotten in many cluster studies, are automatically included. For the present demonstration, we choose the water nonamer (H(2)O)(9), an extremely simple cluster, which nonetheless displays a sufficient complexity and interesting physics in its relevant structure spectrum. Within a standard TIP4P potential description of water, we find that the nonamer second relevant structure possesses a higher configurational entropy than the first, so that the two free energies surprisingly cross for increasing temperature.

Finite Temperature Properties of Clusters by Replica Exchange Metadynamics: The Water Nonamer

NASA Astrophysics Data System (ADS)

Zhai, Yingteng; Laio, Alessandro; Tosatti, Erio; Gong, Xingao

2012-02-01

We introduce an approach for the accurate calculation of thermal properties of classical nanoclusters. Based on a recently developed enhanced sampling technique, replica exchange metadynamics, the method yields the true free energy of each relevant cluster structure, directly sampling its basin and measuring its occupancy in full equilibrium. All entropy sources, whether vibrational, rotational anharmonic and especially configurational -- the latter often forgotten in many cluster studies -- are automatically included. For the present demonstration we choose the water nonamer (H2O)9, an extremely simple cluster which nonetheless displays a sufficient complexity and interesting physics in its relevant structure spectrum. Within a standard TIP4P potential description of water, we find that the nonamer second relevant structure possesses a higher configurational entropy than the first, so that the two free energies surprisingly cross for increasing temperature.

Teacher student relationship quality type in elementary grades: Effects on trajectories for achievement and engagement

PubMed Central

Wu, Jiun-yu; Hughes, Jan N.; Kwok, Oi-man

2010-01-01

Teacher, peer, and student reports of the quality of the teacher-student relationship were obtained for an ethnically diverse and academically at-risk sample of 706 second and third grade students. Cluster analysis identified four types of relationships based on the consistency of child reports of support and conflict in the relationship with reports of others: Congruent positive, Congruent Negative, Incongruent Child Negative and Incongruent Child Positive. The cluster solution evidenced good internal consistency and construct validity. Cluster membership predicted growth trajectories for teacher-rated engagement and standardized achievement scores over the following three years, above prior performance. The predictive associations between child reports of teacher support and conflict and outcomes depended on whether child reports were consistent or inconsistent with reports of others. Study findings have implications for theory development, assessment of teacher-student relationships, and teacher professional development. PMID:20728688

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.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

Aflatoxin Regulations in a Network of Global Maize Trade

PubMed Central

Wu, Felicia; Guclu, Hasan

2012-01-01

Worldwide, food supplies often contain unavoidable contaminants, many of which adversely affect health and hence are subject to regulations of maximum tolerable levels in food. These regulations differ from nation to nation, and may affect patterns of food trade. We soughtto determine whether there is an association between nations' food safety regulations and global food trade patterns, with implications for public health and policymaking. We developed a network model of maize trade around the world. From maize import/export data for 217 nations from 2000–2009, we calculated basic statistics on volumes of trade; then examined how regulations of aflatoxin, a common contaminant of maize, are similar or different between pairs of nations engaging in significant amounts of maize trade. Globally, market segregation appears to occur among clusters of nations. The United States is at the center of one cluster; European countries make up another cluster with hardly any maize trade with the US; and Argentina, Brazil, and China export maize all over the world. Pairs of nations trading large amounts of maize have very similar aflatoxin regulations: nations with strict standards tend to trade maize with each other, while nations with more relaxed standards tend to trade maize with each other. Rarely among the top pairs of maize-trading nations do total aflatoxin standards (standards based on the sum of the levels of aflatoxins B1, B2, G1, and G2) differ by more than 5 µg/kg. These results suggest that, globally, separate maize trading communities emerge; and nations tend to trade with other nations that have very similar food safety standards. PMID:23049773

7 CFR 51.913 - Clusters.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Clusters. 51.913 Section 51.913 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 51.913 - Clusters.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Clusters. 51.913 Section 51.913 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 51.913 - Clusters.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Clusters. 51.913 Section 51.913 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 51.913 - Clusters.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Clusters. 51.913 Section 51.913 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 51.913 - Clusters.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Clusters. 51.913 Section 51.913 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

Illinois Occupational Skill Standards: Information Technology Operate Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document contains Illinois Occupational Skill Standards for occupations in the Information Technology Operate Cluster (help desk support, computer maintenance and technical support technician, systems operator, application and computer support specialist, systems administrator, network administrator, and database administrator). The skill…

On-demand intracellular amplification of chemoradiation with cancer-specific plasmonic nanobubbles.

PubMed

Lukianova-Hleb, Ekaterina Y; Ren, Xiaoyang; Sawant, Rupa R; Wu, Xiangwei; Torchilin, Vladimir P; Lapotko, Dmitri O

2014-07-01

Chemoradiation-resistant cancers limit treatment efficacy and safety. We show here the cancer cell-specific, on-demand intracellular amplification of chemotherapy and chemoradiation therapy via gold nanoparticle- and laser pulse-induced mechanical intracellular impact. Cancer aggressiveness promotes the clustering of drug nanocarriers and gold nanoparticles in cancer cells. This cluster, upon exposure to a laser pulse, generates a plasmonic nanobubble, the mechanical explosion that destroys the host cancer cell or ejects the drug into its cytoplasm by disrupting the liposome and endosome. The same cluster locally amplifies external X-rays. Intracellular synergy of the mechanical impact of plasmonic nanobubble, ejected drug and amplified X-rays improves the efficacy of standard chemoradiation in resistant and aggressive head and neck cancer by 100-fold in vitro and 17-fold in vivo, reduces the effective entry doses of drugs and X-rays to 2-6% of their clinical doses and efficiently spares normal cells. The developed quadrapeutics technology combines four clinically validated components and transforms a standard macrotherapy into an intracellular on-demand theranostic microtreatment with radically amplified therapeutic efficacy and specificity.

On-demand intracellular amplification of chemoradiation with cancer-specific plasmonic nanobubbles

PubMed Central

Lukianova-Hleb, Ekaterina Y; Wu, Xiangwei; Torchilin, Vladimir P; Lapotko, Dmitri O

2014-01-01

Chemoradiation-resistant cancers limit treatment efficacy and safety. We show here the cancer cell–specific, on-demand intracellular amplification of chemotherapy and chemoradiation therapy via gold nanoparticle– and laser pulse–induced mechanical intracellular impact. Cancer aggressiveness promotes the clustering of drug nanocarriers and gold nanoparticles in cancer cells. This cluster, upon exposure to a laser pulse, generates a plasmonic nanobubble, the mechanical explosion that destroys the host cancer cell or ejects the drug into its cytoplasm by disrupting the liposome and endosome. The same cluster locally amplifies external X-rays. Intracellular synergy of the mechanical impact of plasmonic nanobubble, ejected drug and amplified X-rays improves the efficacy of standard chemoradiation in resistant and aggressive head and neck cancer by 100-fold in vitro and 17-fold in vivo, reduces the effective entry doses of drugs and X-rays to 2–6% of their clinical doses and efficiently spares normal cells. The developed quadrapeutics technology combines four clinically validated components and transforms a standard macrotherapy into an intracellular on-demand theranostic microtreatment with radically amplified therapeutic efficacy and specificity. PMID:24880615

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

Inherent size effects on XANES of nanometer metal clusters: Size-selected platinum clusters on silica

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

Dai, Yang; Gorey, Timothy J.; Anderson, Scott L.

2016-12-12

X-ray absorption near-edge structure (XANES) is commonly used to probe the oxidation state of metal-containing nanomaterials, however, as the particle size in the material drops below a few nanometers, it becomes important to consider inherent size effects on the electronic structure of the materials. In this paper, we analyze a series of size-selected Pt n/SiO 2 samples, using X-ray photoelectron spectroscopy (XPS), low energy ion scattering, grazing-incidence small angle X-ray scattering, and XANES. The oxidation state and morphology are characterized both as-deposited in UHV, and after air/O 2 exposure and annealing in H 2. Here, the clusters are found tomore » be stable during deposition and upon air exposure, but sinter if heated above ~150 °C. XANES shows shifts in the Pt L 3 edge, relative to bulk Pt, that increase with decreasing cluster size, and the cluster samples show high white line intensity. Reference to bulk standards would suggest that the clusters are oxidized, however, XPS shows that they are not. Instead, the XANES effects are attributable to development of a band gap and localization of empty state wavefunctions in small clusters.« less

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station

NASA Astrophysics Data System (ADS)

Moustris, Konstantinos; Tsiros, Ioannis X.; Tseliou, Areti; Nastos, Panagiotis

2018-04-01

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

PubMed

Moustris, Konstantinos; Tsiros, Ioannis X; Tseliou, Areti; Nastos, Panagiotis

2018-04-11

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

CSW Best Practices

NASA Technical Reports Server (NTRS)

Newman, Doug; Mitchell, Andrew

2016-01-01

During the development of the CMR (Common Metadata Repository) (CMR) for the Earth Observing System Data and Information System (EOSDIS), CSW (Catalog Service for the Web) a number of best practices came to light. Given that the ESIP (Earth Science Information Partners) Discovery Cluster is committed to interoperability and standards in earth data discovery this seemed like a convenient moment to provide Best Practices to the organization in the same way we did for OpenSearch for this widely-used standard.

Exploring the Dynamics of Exoplanetary Systems in a Young Stellar Cluster

NASA Astrophysics Data System (ADS)

Thornton, Jonathan Daniel; Glaser, Joseph Paul; Wall, Joshua Edward

2018-01-01

I describe a dynamical simulation of planetary systems in a young star cluster. One rather arbitrary aspect of cluster simulations is the choice of initial conditions. These are typically chosen from some standard model, such as Plummer or King, or from a “fractal” distribution to try to model young clumpy systems. Here I adopt the approach of realizing an initial cluster model directly from a detailed magnetohydrodynamical model of cluster formation from a 1000-solar-mass interstellar gas cloud, with magnetic fields and radiative and wind feedback from massive stars included self-consistently. The N-body simulation of the stars and planets starts once star formation is largely over and feedback has cleared much of the gas from the region where the newborn stars reside. It continues until the cluster dissolves in the galactic field. Of particular interest is what would happen to the free-floating planets created in the gas cloud simulation. Are they captured by a star or are they ejected from the cluster? This method of building a dynamical cluster simulation directly from the results of a cluster formation model allows us to better understand the evolution of young star clusters and enriches our understanding of extrasolar planet development in them. These simulations were performed within the AMUSE simulation framework, and combine N-body, multiples and background potential code.

Cluster Physics with Merging Galaxy Clusters

NASA Astrophysics Data System (ADS)

Molnar, Sandor

Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard ΛCDM model, where the total density is dominated by the cosmological constant (Λ) and the matter density by cold dark matter (CDM), structure formation is hierarchical, and clusters grow mostly by merging. Mergers of two massive clusters are the most energetic events in the universe after the Big Bang, hence they provide a unique laboratory to study cluster physics. The two main mass components in clusters behave differently during collisions: the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulence are developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thus our review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clusters is to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses. New high spatial and spectral resolution ground and space based telescopes will come online in the near future. Motivated by these new opportunities, we briefly discuss methods which will be feasible in the near future in studying merging clusters.

Effects of Blended Instructional Models on Math Performance

ERIC Educational Resources Information Center

Bottge, Brian A.; Ma, Xin; Gassaway, Linda; Toland, Michael D.; Butler, Mark; Cho, Sun-Joo

2014-01-01

A pretest-posttest cluster-randomized trial involving 31 middle schools and 335 students with disabilities tested the effects of combining explicit and anchored instruction on fraction computation and problem solving. Results of standardized and researcher-developed tests showed that students who were taught with the blended units outscored…

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…

Implementation of the force decomposition machine for molecular dynamics simulations.

PubMed

Borštnik, Urban; Miller, Benjamin T; Brooks, Bernard R; Janežič, Dušanka

2012-09-01

We present the design and implementation of the force decomposition machine (FDM), a cluster of personal computers (PCs) that is tailored to running molecular dynamics (MD) simulations using the distributed diagonal force decomposition (DDFD) parallelization method. The cluster interconnect architecture is optimized for the communication pattern of the DDFD method. Our implementation of the FDM relies on standard commodity components even for networking. Although the cluster is meant for DDFD MD simulations, it remains general enough for other parallel computations. An analysis of several MD simulation runs on both the FDM and a standard PC cluster demonstrates that the FDM's interconnect architecture provides a greater performance compared to a more general cluster interconnect. Copyright © 2012 Elsevier Inc. All rights reserved.

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. 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…

Finding SDSS Galaxy Clusters in 4-dimensional Color Space Using the False Discovery Rate

NASA Astrophysics Data System (ADS)

Nichol, R. C.; Miller, C. J.; Reichart, D.; Wasserman, L.; Genovese, C.; SDSS Collaboration

2000-12-01

We describe a recently developed statistical technique that provides a meaningful cut-off in probability-based decision making. We are concerned with multiple testing, where each test produces a well-defined probability (or p-value). By well-known, we mean that the null hypothesis used to determine the p-value is fully understood and appropriate. The method is entitled False Discovery Rate (FDR) and its largest advantage over other measures is that it allows one to specify a maximal amount of acceptable error. As an example of this tool, we apply FDR to a four-dimensional clustering algorithm using SDSS data. For each galaxy (or test galaxy), we count the number of neighbors that fit within one standard deviation of a four dimensional Gaussian centered on that test galaxy. The mean and standard deviation of that Gaussian are determined from the colors and errors of the test galaxy. We then take that same Gaussian and place it on a random selection of n galaxies and make a similar count. In the limit of large n, we expect the median count around these random galaxies to represent a typical field galaxy. For every test galaxy we determine the probability (or p-value) that it is a field galaxy based on these counts. A low p-value implies that the test galaxy is in a cluster environment. Once we have a p-value for every galaxy, we use FDR to determine at what level we should make our probability cut-off. Once this cut-off is made, we have a final sample of galaxies that are cluster-like galaxies. Using FDR, we also know the maximum amount of field contamination in our cluster galaxy sample. We present our preliminary galaxy clustering results using these methods.

Millisecond radio pulsars in globular clusters

NASA Technical Reports Server (NTRS)

Verbunt, Frank; Lewin, Walter H. G.; Vanparadijs, Jan

1989-01-01

It is shown that the number of millisecond radio pulsars, in globular clusters, should be larger than 100, applying the standard scenario that all the pulsars descend from low-mass X-ray binaries. Moreover, most of the pulsars are located in a small number of clusters. The prediction that Teran 5 and Liller 1 contain at least about a dozen millisecond radio pulsars each is made. The observations of millisecond radio pulsars in globular clusters to date, in particular the discovery of two millisecond radio pulsars in 47 Tuc, are in agreement with the standard scenario, in which the neutron star is spun up during the mass transfer phase.

B, V Photometry for ~19,000 Stars in and around the Magellanic Cloud Globular Clusters NGC 1466, NGC 1841, NGC 2210, NGC 2257, and Reticulum

NASA Astrophysics Data System (ADS)

Jeon, Young-Beom; Nemec, James M.; Walker, Alistair R.; Kunder, Andrea M.

2014-06-01

Homogeneous B, V photometry is presented for 19,324 stars in and around 5 Magellanic Cloud globular clusters: NGC 1466, NGC 1841, NGC 2210, NGC 2257, and Reticulum. The photometry is derived from eight nights of CCD imaging with the Cerro Tololo Inter-American Observatory 0.9 m SMARTS telescope. Instrumental magnitudes were transformed to the Johnson B, V system using accurate calibration relations based on a large sample of Landolt-Stetson equatorial standard stars, which were observed on the same nights as the cluster stars. Residual analysis of the equatorial standards used for the calibration, and validation of the new photometry using Stetson's sample of secondary standards in the vicinities of the five Large Magellanic Cloud clusters, shows excellent agreement with our values in both magnitudes and colors. Color-magnitude diagrams reaching to the main-sequence turnoffs at V ~ 22 mag, sigma-magnitude diagrams, and various other summaries are presented for each cluster to illustrate the range and quality of the new photometry. The photometry should prove useful for future studies of the Magellanic Cloud globular clusters, particularly studies of their variable stars.

Improving Spectral Image Classification through Band-Ratio Optimization and Pixel Clustering

NASA Astrophysics Data System (ADS)

O'Neill, M.; Burt, C.; McKenna, I.; Kimblin, C.

2017-12-01

The Underground Nuclear Explosion Signatures Experiment (UNESE) seeks to characterize non-prompt observables from underground nuclear explosions (UNE). As part of this effort, we evaluated the ability of DigitalGlobe's WorldView-3 (WV3) to detect and map UNE signatures. WV3 is the current state-of-the-art, commercial, multispectral imaging satellite; however, it has relatively limited spectral and spatial resolutions. These limitations impede image classifiers from detecting targets that are spatially small and lack distinct spectral features. In order to improve classification results, we developed custom algorithms to reduce false positive rates while increasing true positive rates via a band-ratio optimization and pixel clustering front-end. The clusters resulting from these algorithms were processed with standard spectral image classifiers such as Mixture-Tuned Matched Filter (MTMF) and Adaptive Coherence Estimator (ACE). WV3 and AVIRIS data of Cuprite, Nevada, were used as a validation data set. These data were processed with a standard classification approach using MTMF and ACE algorithms. They were also processed using the custom front-end prior to the standard approach. A comparison of the results shows that the custom front-end significantly increases the true positive rate and decreases the false positive rate.This work was done by National Security Technologies, LLC, under Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy. DOE/NV/25946-3283.

An imbalance in cluster sizes does not lead to notable loss of power in cross-sectional, stepped-wedge cluster randomised trials with a continuous outcome.

PubMed

Kristunas, Caroline A; Smith, Karen L; Gray, Laura J

2017-03-07

The current methodology for sample size calculations for stepped-wedge cluster randomised trials (SW-CRTs) is based on the assumption of equal cluster sizes. However, as is often the case in cluster randomised trials (CRTs), the clusters in SW-CRTs are likely to vary in size, which in other designs of CRT leads to a reduction in power. The effect of an imbalance in cluster size on the power of SW-CRTs has not previously been reported, nor what an appropriate adjustment to the sample size calculation should be to allow for any imbalance. We aimed to assess the impact of an imbalance in cluster size on the power of a cross-sectional SW-CRT and recommend a method for calculating the sample size of a SW-CRT when there is an imbalance in cluster size. The effect of varying degrees of imbalance in cluster size on the power of SW-CRTs was investigated using simulations. The sample size was calculated using both the standard method and two proposed adjusted design effects (DEs), based on those suggested for CRTs with unequal cluster sizes. The data were analysed using generalised estimating equations with an exchangeable correlation matrix and robust standard errors. An imbalance in cluster size was not found to have a notable effect on the power of SW-CRTs. The two proposed adjusted DEs resulted in trials that were generally considerably over-powered. We recommend that the standard method of sample size calculation for SW-CRTs be used, provided that the assumptions of the method hold. However, it would be beneficial to investigate, through simulation, what effect the maximum likely amount of inequality in cluster sizes would be on the power of the trial and whether any inflation of the sample size would be required.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Migration in the shearing sheet and estimates for young open cluster migration

NASA Astrophysics Data System (ADS)

Quillen, Alice C.; Nolting, Eric; Minchev, Ivan; De Silva, Gayandhi; Chiappini, Cristina

2018-04-01

Using tracer particles embedded in self-gravitating shearing sheet N-body simulations, we investigate the distance in guiding centre radius that stars or star clusters can migrate in a few orbital periods. The standard deviations of guiding centre distributions and maximum migration distances depend on the Toomre or critical wavelength and the contrast in mass surface density caused by spiral structure. Comparison between our simulations and estimated guiding radii for a few young supersolar metallicity open clusters, including NGC 6583, suggests that the contrast in mass surface density in the solar neighbourhood has standard deviation (in the surface density distribution) divided by mean of about 1/4 and larger than measured using COBE data by Drimmel and Spergel. Our estimate is consistent with a standard deviation of ˜0.07 dex in the metallicities measured from high-quality spectroscopic data for 38 young open clusters (<1 Gyr) with mean galactocentric radius 7-9 kpc.

Connecticut Music Trace Map for Grades 10 and 12. Revised.

ERIC Educational Resources Information Center

Connecticut State Board of Education, Hartford.

The Connecticut Curriculum Trace Maps for music are designed to help curriculum developers and teachers translate Connecticut's K-12 performance standards into objectives and classroom practice. The Trace Maps provide specific descriptions of what students should know and be able to do at smaller grade level clusters. The elements in the Trace…

Connecticut Music Trace Map for Grades 6 and 8. Revised.

ERIC Educational Resources Information Center

Connecticut State Board of Education, Hartford.

These Connecticut Curriculum Trace Maps for music are designed to help curriculum developers and teachers translate Connecticut's K-12 performance standards into objectives and classroom practices. Trace Maps provide specific descriptions of what students should know and be able to do at smaller grade level clusters. Elements in the Trace Maps are…

Connecticut Music Trace Map for Grades 2 and 4. Revised.

ERIC Educational Resources Information Center

Connecticut State Board of Education, Hartford.

These Connecticut Curriculum Trace Maps for music are designed to help curriculum developers and teachers translate Connecticut's K-12 performance standards into objectives and classroom practice. The music Trace Maps provide specific descriptions of what students should know and be able to do at smaller grade level clusters. Connecticut's Trace…

Text messaging reminders for influenza vaccine in primary care: a cluster randomised controlled trial (TXT4FLUJAB).

PubMed

Herrett, Emily; Williamson, Elizabeth; van Staa, Tjeerd; Ranopa, Michael; Free, Caroline; Chadborn, Tim; Goldacre, Ben; Smeeth, Liam

2016-02-19

(1) To develop methods for conducting cluster randomised trials of text messaging interventions utilising routine electronic health records at low cost; (2) to assess the effectiveness of text messaging influenza vaccine reminders in increasing vaccine uptake in patients with chronic conditions. Cluster randomised trial with general practices as clusters. English primary care. 156 general practices, who used text messaging software, who had not previously used text message influenza vaccination reminders. Eligible patients were aged 18-64 in 'at-risk' groups. Practices were randomly allocated to either an intervention or standard care arm in the 2013 influenza season (September to December). Practices in the intervention arm were asked to send a text message influenza vaccination reminder to their at-risk patients under 65. Practices in the standard care arm were asked to continue their influenza campaign as planned. Practices were not blinded. Analysis was performed blinded to practice allocation. Practice-level influenza vaccine uptake among at-risk patients aged 18-64 years. 77 practices were randomised to the intervention group (76 analysed, n at-risk patients=51,121), 79 to the standard care group (79 analysed, n at-risk patients=51,136). The text message increased absolute vaccine uptake by 2.62% (95% CI -0.09% to 5.33%), p=0.058, though this could have been due to chance. Within intervention clusters, a median 21.0% (IQR 10.2% to 47.0%) of eligible patients were sent a text message. The number needed to treat was 7.0 (95% CI -0.29 to 14.3). Patient follow-up using routine electronic health records is a low cost method of conducting cluster randomised trials. Text messaging reminders are likely to result in modest improvements in influenza vaccine uptake, but levels of patients being texted need to markedly increase if text messaging reminders are to have much effect. ISRCTN48840025. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The ToxBank Data Warehouse: Supporting the Replacement of In Vivo Repeated Dose Systemic Toxicity Testing.

PubMed

Kohonen, Pekka; Benfenati, Emilio; Bower, David; Ceder, Rebecca; Crump, Michael; Cross, Kevin; Grafström, Roland C; Healy, Lyn; Helma, Christoph; Jeliazkova, Nina; Jeliazkov, Vedrin; Maggioni, Silvia; Miller, Scott; Myatt, Glenn; Rautenberg, Michael; Stacey, Glyn; Willighagen, Egon; Wiseman, Jeff; Hardy, Barry

2013-01-01

The aim of the SEURAT-1 (Safety Evaluation Ultimately Replacing Animal Testing-1) research cluster, comprised of seven EU FP7 Health projects co-financed by Cosmetics Europe, is to generate a proof-of-concept to show how the latest technologies, systems toxicology and toxicogenomics can be combined to deliver a test replacement for repeated dose systemic toxicity testing on animals. The SEURAT-1 strategy is to adopt a mode-of-action framework to describe repeated dose toxicity, combining in vitro and in silico methods to derive predictions of in vivo toxicity responses. ToxBank is the cross-cluster infrastructure project whose activities include the development of a data warehouse to provide a web-accessible shared repository of research data and protocols, a physical compounds repository, reference or "gold compounds" for use across the cluster (available via wiki.toxbank.net), and a reference resource for biomaterials. Core technologies used in the data warehouse include the ISA-Tab universal data exchange format, REpresentational State Transfer (REST) web services, the W3C Resource Description Framework (RDF) and the OpenTox standards. We describe the design of the data warehouse based on cluster requirements, the implementation based on open standards, and finally the underlying concepts and initial results of a data analysis utilizing public data related to the gold compounds. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cluster Stability Estimation Based on a Minimal Spanning Trees Approach

NASA Astrophysics Data System (ADS)

Volkovich, Zeev (Vladimir); Barzily, Zeev; Weber, Gerhard-Wilhelm; Toledano-Kitai, Dvora

2009-08-01

Among the areas of data and text mining which are employed today in science, economy and technology, clustering theory serves as a preprocessing step in the data analyzing. However, there are many open questions still waiting for a theoretical and practical treatment, e.g., the problem of determining the true number of clusters has not been satisfactorily solved. In the current paper, this problem is addressed by the cluster stability approach. For several possible numbers of clusters we estimate the stability of partitions obtained from clustering of samples. Partitions are considered consistent if their clusters are stable. Clusters validity is measured as the total number of edges, in the clusters' minimal spanning trees, connecting points from different samples. Actually, we use the Friedman and Rafsky two sample test statistic. The homogeneity hypothesis, of well mingled samples within the clusters, leads to asymptotic normal distribution of the considered statistic. Resting upon this fact, the standard score of the mentioned edges quantity is set, and the partition quality is represented by the worst cluster corresponding to the minimal standard score value. It is natural to expect that the true number of clusters can be characterized by the empirical distribution having the shortest left tail. The proposed methodology sequentially creates the described value distribution and estimates its left-asymmetry. Numerical experiments, presented in the paper, demonstrate the ability of the approach to detect the true number of clusters.

Direct Standard-Free Quantitation of Tamiflu® and Other Pharmaceutical Tablets using Clustering Agents with Electrospray Ionization Mass Spectrometry

PubMed Central

Flick, Tawnya G.; Leib, Ryan D.; Williams, Evan R.

2010-01-01

Accurate and rapid quantitation is advantageous to identify counterfeit and substandard pharmaceutical drugs. A standard-free electrospray ionization mass spectrometry method is used to directly determine the dosage in the prescription and over-the-counter drugs, Tamiflu®, Sudafed®, and Dramamine®. A tablet of each drug was dissolved in aqueous solution, filtered, and introduced into solutions containing a known concentration of either L-tryptophan, L-phenylalanine or prednisone as clustering agents. The active ingredient(s) incorporates statistically into large clusters of the clustering agent where effects of differential ionization/detection are substantially reduced. From the abundances of large clusters, the dosages of the active ingredients in each of the tablets were determined to typically better than 20% accuracy even when the ionization/detection efficiency of the individual components differed by over 100×. Although this unorthodox method for quantitation is not as accurate as using conventional standards, it has the advantages that it is fast, it can be applied to mixtures where the identities of the analytes are unknown, and it can be used when suitable standards may not be readily available, such as schedule I or II controlled substances or new designer drugs that have not previously been identified. PMID:20092258

Bayesian network meta-analysis for cluster randomized trials with binary outcomes.

PubMed

Uhlmann, Lorenz; Jensen, Katrin; Kieser, Meinhard

2017-06-01

Network meta-analysis is becoming a common approach to combine direct and indirect comparisons of several treatment arms. In recent research, there have been various developments and extensions of the standard methodology. Simultaneously, cluster randomized trials are experiencing an increased popularity, especially in the field of health services research, where, for example, medical practices are the units of randomization but the outcome is measured at the patient level. Combination of the results of cluster randomized trials is challenging. In this tutorial, we examine and compare different approaches for the incorporation of cluster randomized trials in a (network) meta-analysis. Furthermore, we provide practical insight on the implementation of the models. In simulation studies, it is shown that some of the examined approaches lead to unsatisfying results. However, there are alternatives which are suitable to combine cluster randomized trials in a network meta-analysis as they are unbiased and reach accurate coverage rates. In conclusion, the methodology can be extended in such a way that an adequate inclusion of the results obtained in cluster randomized trials becomes feasible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Monte Carlo-based fluorescence molecular tomography reconstruction method accelerated by a cluster of graphic processing units.

PubMed

Quan, Guotao; Gong, Hui; Deng, Yong; Fu, Jianwei; Luo, Qingming

2011-02-01

High-speed fluorescence molecular tomography (FMT) reconstruction for 3-D heterogeneous media is still one of the most challenging problems in diffusive optical fluorescence imaging. In this paper, we propose a fast FMT reconstruction method that is based on Monte Carlo (MC) simulation and accelerated by a cluster of graphics processing units (GPUs). Based on the Message Passing Interface standard, we modified the MC code for fast FMT reconstruction, and different Green's functions representing the flux distribution in media are calculated simultaneously by different GPUs in the cluster. A load-balancing method was also developed to increase the computational efficiency. By applying the Fréchet derivative, a Jacobian matrix is formed to reconstruct the distribution of the fluorochromes using the calculated Green's functions. Phantom experiments have shown that only 10 min are required to get reconstruction results with a cluster of 6 GPUs, rather than 6 h with a cluster of multiple dual opteron CPU nodes. Because of the advantages of high accuracy and suitability for 3-D heterogeneity media with refractive-index-unmatched boundaries from the MC simulation, the GPU cluster-accelerated method provides a reliable approach to high-speed reconstruction for FMT imaging.

MASSCLEANage—Stellar Cluster Ages from Integrated Colors

NASA Astrophysics Data System (ADS)

Popescu, Bogdan; Hanson, M. M.

2010-11-01

We present the recently updated and expanded MASSCLEANcolors, a database of 70 million Monte Carlo models selected to match the properties (metallicity, ages, and masses) of stellar clusters found in the Large Magellanic Cloud (LMC). This database shows the rather extreme and non-Gaussian distribution of integrated colors and magnitudes expected with different cluster age and mass and the enormous age degeneracy of integrated colors when mass is unknown. This degeneracy could lead to catastrophic failures in estimating age with standard simple stellar population models, particularly if most of the clusters are of intermediate or low mass, like in the LMC. Utilizing the MASSCLEANcolors database, we have developed MASSCLEANage, a statistical inference package which assigns the most likely age and mass (solved simultaneously) to a cluster based only on its integrated broadband photometric properties. Finally, we use MASSCLEANage to derive the age and mass of LMC clusters based on integrated photometry alone. First, we compare our cluster ages against those obtained for the same seven clusters using more accurate integrated spectroscopy. We find improved agreement with the integrated spectroscopy ages over the original photometric ages. A close examination of our results demonstrates the necessity of solving simultaneously for mass and age to reduce degeneracies in the cluster ages derived via integrated colors. We then selected an additional subset of 30 photometric clusters with previously well-constrained ages and independently derive their age using the MASSCLEANage with the same photometry with very good agreement. The MASSCLEANage program is freely available under GNU General Public License.

Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies

PubMed Central

Goodpaster, Aaron M.; Kennedy, Michael A.

2015-01-01

Currently, no standard metrics are used to quantify cluster separation in PCA or PLS-DA scores plots for metabonomics studies or to determine if cluster separation is statistically significant. Lack of such measures makes it virtually impossible to compare independent or inter-laboratory studies and can lead to confusion in the metabonomics literature when authors putatively identify metabolites distinguishing classes of samples based on visual and qualitative inspection of scores plots that exhibit marginal separation. While previous papers have addressed quantification of cluster separation in PCA scores plots, none have advocated routine use of a quantitative measure of separation that is supported by a standard and rigorous assessment of whether or not the cluster separation is statistically significant. Here quantification and statistical significance of separation of group centroids in PCA and PLS-DA scores plots are considered. The Mahalanobis distance is used to quantify the distance between group centroids, and the two-sample Hotelling's T2 test is computed for the data, related to an F-statistic, and then an F-test is applied to determine if the cluster separation is statistically significant. We demonstrate the value of this approach using four datasets containing various degrees of separation, ranging from groups that had no apparent visual cluster separation to groups that had no visual cluster overlap. Widespread adoption of such concrete metrics to quantify and evaluate the statistical significance of PCA and PLS-DA cluster separation would help standardize reporting of metabonomics data. PMID:26246647

Ensuring respect for persons in COMPASS: a cluster randomised pragmatic clinical trial.

PubMed

Andrews, Joseph E; Moore, J Brian; Weinberg, Richard B; Sissine, Mysha; Gesell, Sabina; Halladay, Jacquie; Rosamond, Wayne; Bushnell, Cheryl; Jones, Sara; Means, Paula; King, Nancy M P; Omoyeni, Diana; Duncan, Pamela W

2018-05-02

Cluster randomised clinical trials present unique challenges in meeting ethical obligations to those who are treated at a randomised site. Obtaining informed consent for research within the context of clinical care is one such challenge. In order to solve this problem it is important that an informed consent process be effective and efficient, and that it does not impede the research or the healthcare. The innovative approach to informed consent employed in the COMPASS study demonstrates the feasibility of upholding ethical standards without imposing undue burden on clinical workflows, staff members or patients who may participate in the research by virtue of their presence in a cluster randomised facility. The COMPASS study included 40 randomised sites and compared the effectiveness of a postacute stroke intervention with standard care. Each site provided either the comprehensive postacute stroke intervention or standard care according to the randomisation assignment. Working together, the study team, institutional review board and members of the community designed an ethically appropriate and operationally reasonable consent process which was carried out successfully at all randomised sites. This achievement is noteworthy because it demonstrates how to effectively conduct appropriate informed consent in cluster randomised trials, and because it provides a model that can easily be adapted for other pragmatic studies. With this innovative approach to informed consent, patients have access to the information they need about research occurring where they are seeking care, and medical researchers can conduct their studies without ethical concerns or unreasonable logistical impediments. NCT02588664, recruiting. This article covers the development of consent process that is currentlty being employed in the study. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

7 CFR 52.1851 - Sizes of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Sizes of raisins with seeds-layer or cluster. 52.1851 Section 52.1851 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1842 - Product description of Layer or (Cluster) raisins with seeds.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Product description of Layer or (Cluster) raisins with seeds. 52.1842 Section 52.1842 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL...

7 CFR 52.1853 - Grades of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Grades of raisins with seeds-layer or cluster. 52.1853 Section 52.1853 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1853 - Grades of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Grades of raisins with seeds-layer or cluster. 52.1853 Section 52.1853 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1842 - Product description of Layer or (Cluster) raisins with seeds.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Product description of Layer or (Cluster) raisins with seeds. 52.1842 Section 52.1842 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL...

7 CFR 52.1852 - Grades of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Grades of raisins with seeds-except layer or cluster. 52.1852 Section 52.1852 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT O...

7 CFR 52.1851 - Sizes of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Sizes of raisins with seeds-layer or cluster. 52.1851 Section 52.1851 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1853 - Grades of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Grades of raisins with seeds-layer or cluster. 52.1853 Section 52.1853 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1850 - Sizes of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Sizes of raisins with seeds-except layer or cluster. 52.1850 Section 52.1850 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF...

7 CFR 52.1852 - Grades of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Grades of raisins with seeds-except layer or cluster. 52.1852 Section 52.1852 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT O...

7 CFR 52.1850 - Sizes of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Sizes of raisins with seeds-except layer or cluster. 52.1850 Section 52.1850 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF...

7 CFR 52.1851 - Sizes of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Sizes of raisins with seeds-layer or cluster. 52.1851 Section 52.1851 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1842 - Product description of Layer or (Cluster) raisins with seeds.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Product description of Layer or (Cluster) raisins with seeds. 52.1842 Section 52.1842 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL...

7 CFR 52.1842 - Product description of Layer or (Cluster) raisins with seeds.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Product description of Layer or (Cluster) raisins with seeds. 52.1842 Section 52.1842 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL...

7 CFR 52.1852 - Grades of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Grades of raisins with seeds-except layer or cluster. 52.1852 Section 52.1852 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT O...

7 CFR 52.1850 - Sizes of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Sizes of raisins with seeds-except layer or cluster. 52.1850 Section 52.1850 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF...

7 CFR 52.1852 - Grades of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Grades of raisins with seeds-except layer or cluster. 52.1852 Section 52.1852 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT O...

7 CFR 52.1851 - Sizes of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Sizes of raisins with seeds-layer or cluster. 52.1851 Section 52.1851 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1853 - Grades of raisins with seeds-layer or cluster.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Grades of raisins with seeds-layer or cluster. 52.1853 Section 52.1853 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...

7 CFR 52.1850 - Sizes of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Sizes of raisins with seeds-except layer or cluster. 52.1850 Section 52.1850 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF...

Standardized Effect Size Measures for Mediation Analysis in Cluster-Randomized Trials

ERIC Educational Resources Information Center

Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric

2015-01-01

This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…

Measuring galaxy cluster masses with CMB lensing using a Maximum Likelihood estimator: statistical and systematic error budgets for future experiments

NASA Astrophysics Data System (ADS)

Raghunathan, Srinivasan; Patil, Sanjaykumar; Baxter, Eric J.; Bianchini, Federico; Bleem, Lindsey E.; Crawford, Thomas M.; Holder, Gilbert P.; Manzotti, Alessandro; Reichardt, Christian L.

2017-08-01

We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at low noise levels in temperature, this optimal estimator outperforms the standard quadratic estimator by a factor of two. For polarization, we show that the Stokes Q/U maps can be used instead of the traditional E- and B-mode maps without losing information. We test and quantify the bias in the recovered lensing mass for a comprehensive list of potential systematic errors. Using realistic simulations, we examine the cluster mass uncertainties from CMB-cluster lensing as a function of an experiment's beam size and noise level. We predict the cluster mass uncertainties will be 3 - 6% for SPT-3G, AdvACT, and Simons Array experiments with 10,000 clusters and less than 1% for the CMB-S4 experiment with a sample containing 100,000 clusters. The mass constraints from CMB polarization are very sensitive to the experimental beam size and map noise level: for a factor of three reduction in either the beam size or noise level, the lensing signal-to-noise improves by roughly a factor of two.

A Proper Motions Study of the Globular Cluster NGC 3201

NASA Astrophysics Data System (ADS)

Sariya, Devesh P.; Jiang, Ing-Guey; Yadav, R. K. S.

2017-03-01

With a high value of heliocentric radial velocity, a retrograde orbit, and suspected to have an extragalactic origin, NGC 3201 is an interesting globular cluster for kinematical studies. Our purpose is to calculate the relative proper motions (PMs) and membership probability for the stars in the wide region of globular cluster NGC 3201. PM based membership probabilities are used to isolate the cluster sample from the field stars. The membership catalog will help address the question of chemical inhomogeneity in the cluster. Archive CCD data taken with a wide-field imager (WFI) mounted on the ESO 2.2 m telescope are reduced using the high-precision astrometric software developed by Anderson et al. for the WFI images. The epoch gap between the two observational runs is ˜14.3 years. To standardize the BVI photometry, Stetson’s secondary standard stars are used. The CCD data with an epoch gap of ˜14.3 years enables us to decontaminate the cluster stars from field stars efficiently. The median precision of PMs is better than ˜0.8 mas yr-1 for stars having V< 18 mag that increases up to ˜1.5 mas yr-1 for stars with 18< V< 20 mag. Kinematic membership probabilities are calculated using PMs for stars brighter than V˜ 20 mag. An electronic catalog of positions, relative PMs, BVI magnitudes, and membership probabilities in the ˜19.7 × 17 arcmin2 region of NGC 3201 is presented. We use our membership catalog to identify probable cluster members among the known variables and X-ray sources in the direction of NGC 3201. Based on observations with the MPG/ESO 2.2 m and ESO/VLT telescopes, located at La Silla and Paranal Observatory, Chile, under DDT programs 164.O-0561(F), 093.A-9028(A), and the archive material.

Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.

PubMed

Gomes, Manuel; Ng, Edmond S-W; Grieve, Richard; Nixon, Richard; Carpenter, James; Thompson, Simon G

2012-01-01

Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering--seemingly unrelated regression (SUR) without a robust standard error (SE)--and 4 methods that recognized clustering--SUR and generalized estimating equations (GEEs), both with robust SE, a "2-stage" nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92-0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters.

On the Origin of Sub-subgiant Stars. II. Binary Mass Transfer, Envelope Stripping, and Magnetic Activity

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

Leiner, Emily; Mathieu, Robert D.; Geller, Aaron M., E-mail: leiner@astro.wisc.edu

Sub-subgiant stars (SSGs) lie to the red of the main sequence and fainter than the red giant branch in cluster color–magnitude diagrams (CMDs), a region not easily populated by standard stellar evolution pathways. While there has been speculation on what mechanisms may create these unusual stars, no well-developed theory exists to explain their origins. Here we discuss three hypotheses of SSG formation: (1) mass transfer in a binary system, (2) stripping of a subgiant’s envelope, perhaps during a dynamical encounter, and (3) reduced luminosity due to magnetic fields that lower convective efficiency and produce large starspots. Using the stellar evolutionmore » code MESA, we develop evolutionary tracks for each of these hypotheses, and compare the expected stellar and orbital properties of these models with six known SSGs in the two open clusters M67 and NGC 6791. All three of these mechanisms can create stars or binary systems in the SSG CMD domain. We also calculate the frequency with which each of these mechanisms may create SSG systems, and find that the magnetic field hypothesis is expected to create SSGs with the highest frequency in open clusters. Mass transfer and envelope stripping have lower expected formation frequencies, but may nevertheless create occasional SSGs in open clusters. They may also be important mechanisms to create SSGs in higher mass globular clusters.« less

Design guide for low cost standardized payloads, volume 2

NASA Technical Reports Server (NTRS)

1972-01-01

Sixteen engineering approaches to low cost standardized payloads in spacecraft are presented. Standard earth observatory satellite, standard U.S. domestic communication satellite, planetary spacecraft subsystems, standard spacecraft, and cluster spacecraft are reviewed.

Kappa statistic for the clustered dichotomous responses from physicians and patients

PubMed Central

Kang, Chaeryon; Qaqish, Bahjat; Monaco, Jane; Sheridan, Stacey L.; Cai, Jianwen

2013-01-01

The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared to the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. An example of an application to a coronary heart disease prevention study is presented. PMID:23533082

Fingerprint recognition of wavelet-based compressed images by neuro-fuzzy clustering

NASA Astrophysics Data System (ADS)

Liu, Ti C.; Mitra, Sunanda

1996-06-01

Image compression plays a crucial role in many important and diverse applications requiring efficient storage and transmission. This work mainly focuses on a wavelet transform (WT) based compression of fingerprint images and the subsequent classification of the reconstructed images. The algorithm developed involves multiresolution wavelet decomposition, uniform scalar quantization, entropy and run- length encoder/decoder and K-means clustering of the invariant moments as fingerprint features. The performance of the WT-based compression algorithm has been compared with JPEG current image compression standard. Simulation results show that WT outperforms JPEG in high compression ratio region and the reconstructed fingerprint image yields proper classification.

Task Analysis for Health Occupations. Cluster: Nursing. Occupation: Geriatric Aide. Education for Employment Task Lists.

ERIC Educational Resources Information Center

Lake County Area Vocational Center, Grayslake, IL.

This task analysis for nursing education provides performance standards, steps to be followed, knowledge required, attitudes to be developed, safety procedures, and equipment and supplies needed for 13 tasks performed by geriatric aides in the duty area of performing diagnostic measures and for 30 tasks in the duty area of providing therapeutic…

Building Capacity in a Self-Managing Schooling System: The New Zealand Experience

ERIC Educational Resources Information Center

Robinson, Viviane M. J.; McNaughton, Stuart; Timperley, Helen

2011-01-01

Purpose: The purpose of this paper is to evaluate two recent examples of the New Zealand Ministry of Education's approach to reducing the persistent disparities in achievement between students of different social and ethnic groups. The first example is cluster-based school improvement, and the second is the development of national standards for…

Behavioural Development in Chimpanzee (Pan troglodytes) and Human Newborns across the First Month of Life.

ERIC Educational Resources Information Center

Hallock, Martha B.; And Others

1989-01-01

Reports comparisons of behaviors of nine chimpanzee and nine human newborns on a standardized human neonatal assessment scale at the ages of three days and one month. Human infants scored higher than chimpanzee infants on the orientation cluster at both ages, but were lower than chimpanzee infants in motoric maturity. (RJC)

The Impact of Speedometry on Student Knowledge, Interest, and Emotions

ERIC Educational Resources Information Center

Polikoff, Morgan; Le, Q. Tien; Danielson, Robert W.; Sinatra, Gale M.; Marsh, Julie A.

2018-01-01

Given the dearth of high-quality curriculum materials aligned with the new standards (NGSS and CCSS) and low student persistence in STEM fields, we sought to develop and test a STEM curriculum that would improve student knowledge, interest, and emotions. A cluster randomized control trial was conducted to assess the impact of Speedometry, a…

Grade Expectations for Vermont's Framework of Standards and Learning Opportunities, Summer 2004 (Physical Education)

ERIC Educational Resources Information Center

Vermont Department of Education, 2004

2004-01-01

Educators from around the state, with the help of The Vermont Institutes, developed Vermont Physical Education Grade Cluster Expectations (GCEs) as a means to identify the physical education content knowledge and skills expected of all students for local assessment required under Act 68. This work was accomplished using the "Vermont's…

Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Support Distribution Machines

NASA Astrophysics Data System (ADS)

Ntampaka, Michelle; Trac, Hy; Sutherland, Dougal; Fromenteau, Sebastien; Poczos, Barnabas; Schneider, Jeff

2018-01-01

We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership infor- mation and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width E=0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (E=2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement (E=0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncon- taminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

Effect Sizes in Cluster-Randomized Designs

ERIC Educational Resources Information Center

Hedges, Larry V.

2007-01-01

Multisite research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Researchers would like to compute effect size indexes based on the standardized mean difference to compare the results of cluster-randomized studies (and corresponding quasi-experiments) with other studies and to…

MASSCLEANage-STELLAR CLUSTER AGES FROM INTEGRATED COLORS

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

Popescu, Bogdan; Hanson, M. M., E-mail: popescb@mail.uc.ed, E-mail: margaret.hanson@uc.ed

2010-11-20

We present the recently updated and expanded MASSCLEANcolors, a database of 70 million Monte Carlo models selected to match the properties (metallicity, ages, and masses) of stellar clusters found in the Large Magellanic Cloud (LMC). This database shows the rather extreme and non-Gaussian distribution of integrated colors and magnitudes expected with different cluster age and mass and the enormous age degeneracy of integrated colors when mass is unknown. This degeneracy could lead to catastrophic failures in estimating age with standard simple stellar population models, particularly if most of the clusters are of intermediate or low mass, like in the LMC.more » Utilizing the MASSCLEANcolors database, we have developed MASSCLEANage, a statistical inference package which assigns the most likely age and mass (solved simultaneously) to a cluster based only on its integrated broadband photometric properties. Finally, we use MASSCLEANage to derive the age and mass of LMC clusters based on integrated photometry alone. First, we compare our cluster ages against those obtained for the same seven clusters using more accurate integrated spectroscopy. We find improved agreement with the integrated spectroscopy ages over the original photometric ages. A close examination of our results demonstrates the necessity of solving simultaneously for mass and age to reduce degeneracies in the cluster ages derived via integrated colors. We then selected an additional subset of 30 photometric clusters with previously well-constrained ages and independently derive their age using the MASSCLEANage with the same photometry with very good agreement. The MASSCLEANage program is freely available under GNU General Public License.« less

Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference

PubMed Central

Stone, Eric A.; Ayroles, Julien F.

2009-01-01

In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432

Density-cluster NMA: A new protein decomposition technique for coarse-grained normal mode analysis.

PubMed

Demerdash, Omar N A; Mitchell, Julie C

2012-07-01

Normal mode analysis has emerged as a useful technique for investigating protein motions on long time scales. This is largely due to the advent of coarse-graining techniques, particularly Hooke's Law-based potentials and the rotational-translational blocking (RTB) method for reducing the size of the force-constant matrix, the Hessian. Here we present a new method for domain decomposition for use in RTB that is based on hierarchical clustering of atomic density gradients, which we call Density-Cluster RTB (DCRTB). The method reduces the number of degrees of freedom by 85-90% compared with the standard blocking approaches. We compared the normal modes from DCRTB against standard RTB using 1-4 residues in sequence in a single block, with good agreement between the two methods. We also show that Density-Cluster RTB and standard RTB perform well in capturing the experimentally determined direction of conformational change. Significantly, we report superior correlation of DCRTB with B-factors compared with 1-4 residue per block RTB. Finally, we show significant reduction in computational cost for Density-Cluster RTB that is nearly 100-fold for many examples. Copyright © 2012 Wiley Periodicals, Inc.

Effect Sizes in Three-Level Cluster-Randomized Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.

2011-01-01

Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…

The effect of defect cluster size and interpolation on radiographic image quality

NASA Astrophysics Data System (ADS)

Töpfer, Karin; Yip, Kwok L.

2011-03-01

For digital X-ray detectors, the need to control factory yield and cost invariably leads to the presence of some defective pixels. Recently, a standard procedure was developed to identify such pixels for industrial applications. However, no quality standards exist in medical or industrial imaging regarding the maximum allowable number and size of detector defects. While the answer may be application specific, the minimum requirement for any defect specification is that the diagnostic quality of the images be maintained. A more stringent criterion is to keep any changes in the images due to defects below the visual threshold. Two highly sensitive image simulation and evaluation methods were employed to specify the fraction of allowable defects as a function of defect cluster size in general radiography. First, the most critical situation of the defect being located in the center of the disease feature was explored using image simulation tools and a previously verified human observer model, incorporating a channelized Hotelling observer. Detectability index d' was obtained as a function of defect cluster size for three different disease features on clinical lung and extremity backgrounds. Second, four concentrations of defects of four different sizes were added to clinical images with subtle disease features and then interpolated. Twenty observers evaluated the images against the original on a single display using a 2-AFC method, which was highly sensitive to small changes in image detail. Based on a 50% just-noticeable difference, the fraction of allowed defects was specified vs. cluster size.

Clustering gene expression regulators: new approach to disease subtyping.

PubMed

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Clustering Gene Expression Regulators: New Approach to Disease Subtyping

PubMed Central

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient. PMID:24416320

Kappa statistic for clustered dichotomous responses from physicians and patients.

PubMed

Kang, Chaeryon; Qaqish, Bahjat; Monaco, Jane; Sheridan, Stacey L; Cai, Jianwen

2013-09-20

The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared with the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. We present an example of an application to a coronary heart disease prevention study. Copyright © 2013 John Wiley & Sons, Ltd.

Clustered localization of STAT3 during the cell cycle detected by super-resolution fluorescence microscopy

NASA Astrophysics Data System (ADS)

Gao, Jing; Chen, Junling; Cai, Mingjun; Xu, Haijiao; Jiang, Junguang; Tong, Ti; Wang, Hongda

2017-06-01

Signal transducer and activator of transcription 3 (STAT3) plays a key role in various cellular processes such as cell proliferation, differentiation, apoptosis and immune responses. In particular, STAT3 has emerged as a potential molecular target for cancer therapy. The functional role and standard activation mechanism of STAT3 have been well studied, however, the spatial distribution of STAT3 during the cell cycle is poorly known. Therefore, it is indispensable to study STAT3 spatial arrangement and nuclear-cytoplasimic localization at the different phase of cell cycle in cancer cells. By direct stochastic optical reconstruction microscopy imaging, we find that STAT3 forms various number and size of clusters at the different cell-cycle stage, which could not be clearly observed by conventional fluorescent microscopy. STAT3 clusters get more and larger gradually from G1 to G2 phase, during which time transcription and other related activities goes on consistently. The results suggest that there is an intimate relationship between the clustered characteristic of STAT3 and the cell-cycle behavior. Meanwhile, clustering would facilitate STAT3 rapid response to activating signals due to short distances between molecules. Our data might open a new door to develop an antitumor drug for inhibiting STAT3 signaling pathway by destroying its clusters.

Temporal clustering of tropical cyclones and its ecosystem impacts

PubMed Central

Mumby, Peter J.; Vitolo, Renato; Stephenson, David B.

2011-01-01

Tropical cyclones have massive economic, social, and ecological impacts, and models of their occurrence influence many planning activities from setting insurance premiums to conservation planning. Most impact models allow for geographically varying cyclone rates but assume that individual storm events occur randomly with constant rate in time. This study analyzes the statistical properties of Atlantic tropical cyclones and shows that local cyclone counts vary in time, with periods of elevated activity followed by relative quiescence. Such temporal clustering is particularly strong in the Caribbean Sea, along the coasts of Belize, Honduras, Costa Rica, Jamaica, the southwest of Haiti, and in the main hurricane development region in the North Atlantic between Africa and the Caribbean. Failing to recognize this natural nonstationarity in cyclone rates can give inaccurate impact predictions. We demonstrate this by exploring cyclone impacts on coral reefs. For a given cyclone rate, we find that clustered events have a less detrimental impact than independent random events. Predictions using a standard random hurricane model were overly pessimistic, predicting reef degradation more than a decade earlier than that expected under clustered disturbance. The presence of clustering allows coral reefs more time to recover to healthier states, but the impacts of clustering will vary from one ecosystem to another. PMID:22006300

Crystallization of glass-forming liquids: Specific surface energy

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

Schmelzer, Jürn W. P., E-mail: juern-w.schmelzer@uni-rostock.de; Abyzov, Alexander S.

2016-08-14

A generalization of the Stefan-Skapski-Turnbull relation for the melt-crystal specific interfacial energy is developed in terms of the generalized Gibbs approach extending its standard formulation to thermodynamic non-equilibrium states. With respect to crystal nucleation, this relation is required in order to determine the parameters of the critical crystal clusters being a prerequisite for the computation of the work of critical cluster formation. As one of its consequences, a relation for the dependence of the specific surface energy of critical clusters on temperature and pressure is derived applicable for small and moderate deviations from liquid-crystal macroscopic equilibrium states. Employing the Stefan-Skapski-Turnbullmore » relation, general expressions for the size and the work of formation of critical crystal clusters are formulated. The resulting expressions are much more complex as compared to the respective relations obtained via the classical Gibbs theory. Latter relations are retained as limiting cases of these more general expressions for moderate undercoolings. By this reason, the formulated, here, general relations for the specification of the critical cluster size and the work of critical cluster formation give a key for an appropriate interpretation of a variety of crystallization phenomena occurring at large undercoolings which cannot be understood in terms of the Gibbs’ classical treatment.« less

Measuring galaxy cluster masses with CMB lensing using a Maximum Likelihood estimator: statistical and systematic error budgets for future experiments

DOE PAGES

Raghunathan, Srinivasan; Patil, Sanjaykumar; Baxter, Eric J.; ...

2017-08-25

We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at low noise levels in temperature, this optimal estimator outperforms the standard quadratic estimator by a factor of two. For polarization, we show that the Stokes Q/U maps can be used instead of the traditional E- and B-mode maps without losing information. We test and quantify the bias in the recovered lensing mass for a comprehensive list of potential systematic errors. Using realistic simulations, wemore » examine the cluster mass uncertainties from CMB-cluster lensing as a function of an experiment’s beam size and noise level. We predict the cluster mass uncertainties will be 3 - 6% for SPT-3G, AdvACT, and Simons Array experiments with 10,000 clusters and less than 1% for the CMB-S4 experiment with a sample containing 100,000 clusters. The mass constraints from CMB polarization are very sensitive to the experimental beam size and map noise level: for a factor of three reduction in either the beam size or noise level, the lensing signal-to-noise improves by roughly a factor of two.« less

Measuring galaxy cluster masses with CMB lensing using a Maximum Likelihood estimator: statistical and systematic error budgets for future experiments

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

Raghunathan, Srinivasan; Patil, Sanjaykumar; Baxter, Eric J.

We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at low noise levels in temperature, this optimal estimator outperforms the standard quadratic estimator by a factor of two. For polarization, we show that the Stokes Q/U maps can be used instead of the traditional E- and B-mode maps without losing information. We test and quantify the bias in the recovered lensing mass for a comprehensive list of potential systematic errors. Using realistic simulations, wemore » examine the cluster mass uncertainties from CMB-cluster lensing as a function of an experiment’s beam size and noise level. We predict the cluster mass uncertainties will be 3 - 6% for SPT-3G, AdvACT, and Simons Array experiments with 10,000 clusters and less than 1% for the CMB-S4 experiment with a sample containing 100,000 clusters. The mass constraints from CMB polarization are very sensitive to the experimental beam size and map noise level: for a factor of three reduction in either the beam size or noise level, the lensing signal-to-noise improves by roughly a factor of two.« less

Measuring galaxy cluster masses with CMB lensing using a Maximum Likelihood estimator: statistical and systematic error budgets for future experiments

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

Raghunathan, Srinivasan; Patil, Sanjaykumar; Bianchini, Federico

We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at low noise levels in temperature, this optimal estimator outperforms the standard quadratic estimator by a factor of two. For polarization, we show that the Stokes Q/U maps can be used instead of the traditional E- and B-mode maps without losing information. We test and quantify the bias in the recovered lensing mass for a comprehensive list of potential systematic errors. Using realistic simulations, wemore » examine the cluster mass uncertainties from CMB-cluster lensing as a function of an experiment's beam size and noise level. We predict the cluster mass uncertainties will be 3 - 6% for SPT-3G, AdvACT, and Simons Array experiments with 10,000 clusters and less than 1% for the CMB-S4 experiment with a sample containing 100,000 clusters. The mass constraints from CMB polarization are very sensitive to the experimental beam size and map noise level: for a factor of three reduction in either the beam size or noise level, the lensing signal-to-noise improves by roughly a factor of two.« less

Object-Oriented Image Clustering Method Using UAS Photogrammetric Imagery

NASA Astrophysics Data System (ADS)

Lin, Y.; Larson, A.; Schultz-Fellenz, E. S.; Sussman, A. J.; Swanson, E.; Coppersmith, R.

2016-12-01

Unmanned Aerial Systems (UAS) have been used widely as an imaging modality to obtain remotely sensed multi-band surface imagery, and are growing in popularity due to their efficiency, ease of use, and affordability. Los Alamos National Laboratory (LANL) has employed the use of UAS for geologic site characterization and change detection studies at a variety of field sites. The deployed UAS equipped with a standard visible band camera to collect imagery datasets. Based on the imagery collected, we use deep sparse algorithmic processing to detect and discriminate subtle topographic features created or impacted by subsurface activities. In this work, we develop an object-oriented remote sensing imagery clustering method for land cover classification. To improve the clustering and segmentation accuracy, instead of using conventional pixel-based clustering methods, we integrate the spatial information from neighboring regions to create super-pixels to avoid salt-and-pepper noise and subsequent over-segmentation. To further improve robustness of our clustering method, we also incorporate a custom digital elevation model (DEM) dataset generated using a structure-from-motion (SfM) algorithm together with the red, green, and blue (RGB) band data for clustering. In particular, we first employ an agglomerative clustering to create an initial segmentation map, from where every object is treated as a single (new) pixel. Based on the new pixels obtained, we generate new features to implement another level of clustering. We employ our clustering method to the RGB+DEM datasets collected at the field site. Through binary clustering and multi-object clustering tests, we verify that our method can accurately separate vegetation from non-vegetation regions, and are also able to differentiate object features on the surface.

Developing Appropriate Methods for Cost-Effectiveness Analysis of Cluster Randomized Trials

PubMed Central

Gomes, Manuel; Ng, Edmond S.-W.; Nixon, Richard; Carpenter, James; Thompson, Simon G.

2012-01-01

Aim. Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Methods. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering—seemingly unrelated regression (SUR) without a robust standard error (SE)—and 4 methods that recognized clustering—SUR and generalized estimating equations (GEEs), both with robust SE, a “2-stage” nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Results. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92–0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. Conclusions. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters. PMID:22016450

Developing a typology of African Americans with limited literacy based on preventive health practice orientation: implications for colorectal cancer screening strategies.

PubMed

Gordon, Thomas F; Bass, Sarah Bauerle; Ruzek, Sheryl B; Wolak, Caitlin; Rovito, Michael J; Ruggieri, Dominique G; Ward, Stephanie; Paranjape, Anuradha; Greener, Judith

2014-01-01

Preventive health messages are often tailored to reach broad sociodemographic groups. However, within groups, there may be considerable variation in perceptions of preventive health practices, such as colorectal cancer screening. Segmentation analysis provides a tool for crafting messages that are tailored more closely to the mental models of targeted individuals or subgroups. This study used cluster analysis, a psychosocial marketing segmentation technique, to develop a typology of colorectal cancer screening orientation among 102 African American clinic patients between the ages of 50 and 74 years with limited literacy. Patients were from a general internal medicine clinic in a large urban teaching hospital, a subpopulation known to have high rates of colorectal cancer and low rates of screening. Preventive screening orientation variables included the patients' responses to questions involving personal attitudes and preferences toward preventive screening and general prevention practices. A k-means cluster analysis yielded three clusters of patients on the basis of their screening orientation: ready screeners (50.0%), cautious screeners (30.4%), and fearful avoiders (19.6%). The resulting typology clearly defines important subgroups on the basis of their preventive health practice perceptions. The authors propose that the development of a validated typology of patients on the basis of their preventive health perceptions could be applicable to a variety of health concerns. Such a typology would serve to standardize how populations are characterized and would provide a more accurate view of their preventive health-related attitudes, values, concerns, preferences, and behaviors. Used with standardized assessment tools, it would provide an empirical basis for tailoring health messages and improving medical communication.

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.

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.

Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

NASA Astrophysics Data System (ADS)

Ntampaka, M.; Trac, H.; Sutherland, D. J.; Fromenteau, S.; Póczos, B.; Schneider, J.

2016-11-01

We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width of {{Δ }}ε ≈ 0.87. Interlopers introduce additional scatter, significantly widening the error distribution further ({{Δ }}ε ≈ 2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement ({{Δ }}ε ≈ 0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncontaminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

Structural basis for a [4Fe-3S] cluster in the oxygen-tolerant membrane-bound [NiFe]-hydrogenase.

PubMed

Shomura, Yasuhito; Yoon, Ki-Seok; Nishihara, Hirofumi; Higuchi, Yoshiki

2011-10-16

Membrane-bound respiratory [NiFe]-hydrogenase (MBH), a H(2)-uptake enzyme found in the periplasmic space of bacteria, catalyses the oxidation of dihydrogen: H(2) → 2H(+) + 2e(-) (ref. 1). In contrast to the well-studied O(2)-sensitive [NiFe]-hydrogenases (referred to as the standard enzymes), MBH has an O(2)-tolerant H(2) oxidation activity; however, the mechanism of O(2) tolerance is unclear. Here we report the crystal structures of Hydrogenovibrio marinus MBH in three different redox conditions at resolutions between 1.18 and 1.32 Å. We find that the proximal iron-sulphur (Fe-S) cluster of MBH has a [4Fe-3S] structure coordinated by six cysteine residues--in contrast to the [4Fe-4S] cubane structure coordinated by four cysteine residues found in the proximal Fe-S cluster of the standard enzymes--and that an amide nitrogen of the polypeptide backbone is deprotonated and additionally coordinates the cluster when chemically oxidized, thus stabilizing the superoxidized state of the cluster. The structure of MBH is very similar to that of the O(2)-sensitive standard enzymes except for the proximal Fe-S cluster. Our results give a reasonable explanation why the O(2) tolerance of MBH is attributable to the unique proximal Fe-S cluster; we propose that the cluster is not only a component of the electron transfer for the catalytic cycle, but that it also donates two electrons and one proton crucial for the appropriate reduction of O(2) in preventing the formation of an unready, inactive state of the enzyme.

Assessing the feasibility of interrupting the transmission of soil-transmitted helminths through mass drug administration: The DeWorm3 cluster randomized trial protocol.

PubMed

Ásbjörnsdóttir, Kristjana Hrönn; Ajjampur, Sitara S Rao; Anderson, Roy M; Bailey, Robin; Gardiner, Iain; Halliday, Katherine E; Ibikounle, Moudachirou; Kalua, Khumbo; Kang, Gagandeep; Littlewood, D Timothy J; Luty, Adrian J F; Means, Arianna Rubin; Oswald, William; Pullan, Rachel L; Sarkar, Rajiv; Schär, Fabian; Szpiro, Adam; Truscott, James E; Werkman, Marleen; Yard, Elodie; Walson, Judd L

2018-01-01

Current control strategies for soil-transmitted helminths (STH) emphasize morbidity control through mass drug administration (MDA) targeting preschool- and school-age children, women of childbearing age and adults in certain high-risk occupations such as agricultural laborers or miners. This strategy is effective at reducing morbidity in those treated but, without massive economic development, it is unlikely it will interrupt transmission. MDA will therefore need to continue indefinitely to maintain benefit. Mathematical models suggest that transmission interruption may be achievable through MDA alone, provided that all age groups are targeted with high coverage. The DeWorm3 Project will test the feasibility of interrupting STH transmission using biannual MDA targeting all age groups. Study sites (population ≥80,000) have been identified in Benin, Malawi and India. Each site will be divided into 40 clusters, to be randomized 1:1 to three years of twice-annual community-wide MDA or standard-of-care MDA, typically annual school-based deworming. Community-wide MDA will be delivered door-to-door, while standard-of-care MDA will be delivered according to national guidelines. The primary outcome is transmission interruption of the STH species present at each site, defined as weighted cluster-level prevalence ≤2% by quantitative polymerase chain reaction (qPCR), 24 months after the final round of MDA. Secondary outcomes include the endline prevalence of STH, overall and by species, and the endline prevalence of STH among children under five as an indicator of incident infections. Secondary analyses will identify cluster-level factors associated with transmission interruption. Prevalence will be assessed using qPCR of stool samples collected from a random sample of cluster residents at baseline, six months after the final round of MDA and 24 months post-MDA. A smaller number of individuals in each cluster will be followed with annual sampling to monitor trends in prevalence and reinfection throughout the trial. ClinicalTrials.gov NCT03014167.

Bias and inference from misspecified mixed-effect models in stepped wedge trial analysis.

PubMed

Thompson, Jennifer A; Fielding, Katherine L; Davey, Calum; Aiken, Alexander M; Hargreaves, James R; Hayes, Richard J

2017-10-15

Many stepped wedge trials (SWTs) are analysed by using a mixed-effect model with a random intercept and fixed effects for the intervention and time periods (referred to here as the standard model). However, it is not known whether this model is robust to misspecification. We simulated SWTs with three groups of clusters and two time periods; one group received the intervention during the first period and two groups in the second period. We simulated period and intervention effects that were either common-to-all or varied-between clusters. Data were analysed with the standard model or with additional random effects for period effect or intervention effect. In a second simulation study, we explored the weight given to within-cluster comparisons by simulating a larger intervention effect in the group of the trial that experienced both the control and intervention conditions and applying the three analysis models described previously. Across 500 simulations, we computed bias and confidence interval coverage of the estimated intervention effect. We found up to 50% bias in intervention effect estimates when period or intervention effects varied between clusters and were treated as fixed effects in the analysis. All misspecified models showed undercoverage of 95% confidence intervals, particularly the standard model. A large weight was given to within-cluster comparisons in the standard model. In the SWTs simulated here, mixed-effect models were highly sensitive to departures from the model assumptions, which can be explained by the high dependence on within-cluster comparisons. Trialists should consider including a random effect for time period in their SWT analysis model. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Bias and inference from misspecified mixed‐effect models in stepped wedge trial analysis

PubMed Central

Fielding, Katherine L.; Davey, Calum; Aiken, Alexander M.; Hargreaves, James R.; Hayes, Richard J.

2017-01-01

Many stepped wedge trials (SWTs) are analysed by using a mixed‐effect model with a random intercept and fixed effects for the intervention and time periods (referred to here as the standard model). However, it is not known whether this model is robust to misspecification. We simulated SWTs with three groups of clusters and two time periods; one group received the intervention during the first period and two groups in the second period. We simulated period and intervention effects that were either common‐to‐all or varied‐between clusters. Data were analysed with the standard model or with additional random effects for period effect or intervention effect. In a second simulation study, we explored the weight given to within‐cluster comparisons by simulating a larger intervention effect in the group of the trial that experienced both the control and intervention conditions and applying the three analysis models described previously. Across 500 simulations, we computed bias and confidence interval coverage of the estimated intervention effect. We found up to 50% bias in intervention effect estimates when period or intervention effects varied between clusters and were treated as fixed effects in the analysis. All misspecified models showed undercoverage of 95% confidence intervals, particularly the standard model. A large weight was given to within‐cluster comparisons in the standard model. In the SWTs simulated here, mixed‐effect models were highly sensitive to departures from the model assumptions, which can be explained by the high dependence on within‐cluster comparisons. Trialists should consider including a random effect for time period in their SWT analysis model. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28556355

Task shifting of frontline community health workers for cardiovascular risk reduction: design and rationale of a cluster randomised controlled trial (DISHA study) in India.

PubMed

Jeemon, Panniyammakal; Narayanan, Gitanjali; Kondal, Dimple; Kahol, Kashvi; Bharadwaj, Ashok; Purty, Anil; Negi, Prakash; Ladhani, Sulaiman; Sanghvi, Jyoti; Singh, Kuldeep; Kapoor, Deksha; Sobti, Nidhi; Lall, Dorothy; Manimunda, Sathyaprakash; Dwivedi, Supriya; Toteja, Gurudyal; Prabhakaran, Dorairaj

2016-03-15

Effective task-shifting interventions targeted at reducing the global cardiovascular disease (CVD) epidemic in low and middle-income countries (LMICs) are urgently needed. DISHA is a cluster randomised controlled trial conducted across 10 sites (5 in phase 1 and 5 in phase 2) in India in 120 clusters. At each site, 12 clusters were randomly selected from a district. A cluster is defined as a small village with 250-300 households and well defined geographical boundaries. They were then randomly allocated to intervention and control clusters in a 1:1 allocation sequence. If any of the intervention and control clusters were <10 km apart, one was dropped and replaced with another randomly selected cluster from the same district. The study included a representative baseline cross-sectional survey, development of a structured intervention model, delivery of intervention for a minimum period of 18 months by trained frontline health workers (mainly Anganwadi workers and ASHA workers) and a post intervention survey in a representative sample. The study staff had no information on intervention allocation until the completion of the baseline survey. In order to ensure comparability of data across sites, the DISHA study follows a common protocol and manual of operation with standardized measurement techniques. Our study is the largest community based cluster randomised trial in low and middle-income country settings designed to test the effectiveness of 'task shifting' interventions involving frontline health workers for cardiovascular risk reduction. CTRI/2013/10/004049 . Registered 7 October 2013.

Vortex matter stabilized by many-body interactions

NASA Astrophysics Data System (ADS)

Wolf, S.; Vagov, A.; Shanenko, A. A.; Axt, V. M.; Aguiar, J. Albino

2017-10-01

This work investigates interactions of vortices in superconducting materials between standard types I and II, in the domain of the so-called intertype (IT) superconductivity. Contrary to common expectations, the many-body (many-vortex) contribution is not a correction to the pair-vortex interaction here but plays a crucial role in the formation of the IT vortex matter. In particular, the many-body interactions stabilize vortex clusters that otherwise could not exist. Furthermore, clusters with large numbers of vortices become more stable when approaching the boundary between the intertype domain and type I. This indicates that IT superconductors develop a peculiar unconventional type of the vortex matter governed by the many-body interactions of vortices.

Clusters of Monoisotopic Elements for Calibration in (TOF) Mass Spectrometry

NASA Astrophysics Data System (ADS)

Kolářová, Lenka; Prokeš, Lubomír; Kučera, Lukáš; Hampl, Aleš; Peňa-Méndez, Eladia; Vaňhara, Petr; Havel, Josef

2017-03-01

Precise calibration in TOF MS requires suitable and reliable standards, which are not always available for high masses. We evaluated inorganic clusters of the monoisotopic elements gold and phosphorus (Au n +/Au n - and P n +/P n -) as an alternative to peptides or proteins for the external and internal calibration of mass spectra in various experimental and instrumental scenarios. Monoisotopic gold or phosphorus clusters can be easily generated in situ from suitable precursors by laser desorption/ionization (LDI) or matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Their use offers numerous advantages, including simplicity of preparation, biological inertness, and exact mass determination even at lower mass resolution. We used citrate-stabilized gold nanoparticles to generate gold calibration clusters, and red phosphorus powder to generate phosphorus clusters. Both elements can be added to samples to perform internal calibration up to mass-to-charge ( m/z) 10-15,000 without significantly interfering with the analyte. We demonstrated the use of the gold and phosphorous clusters in the MS analysis of complex biological samples, including microbial standards and total extracts of mouse embryonic fibroblasts. We believe that clusters of monoisotopic elements could be used as generally applicable calibrants for complex biological samples.

Towards Accurate Modelling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

2018-04-01

Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter halos. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the "accurate" regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard ΛCDM + halo model against the clustering of SDSS DR7 galaxies. Specifically, we use the projected correlation function, group multiplicity function and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir halos) matches the clustering of low luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the "standard" halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

Percolation Analysis as a Tool to Describe the Topology of the Large Scale Structure of the Universe

NASA Astrophysics Data System (ADS)

Yess, Capp D.

1997-09-01

Percolation analysis is the study of the properties of clusters. In cosmology, it is the statistics of the size and number of clusters. This thesis presents a refinement of percolation analysis and its application to astronomical data. An overview of the standard model of the universe and the development of large scale structure is presented in order to place the study in historical and scientific context. Then using percolation statistics we, for the first time, demonstrate the universal character of a network pattern in the real space, mass distributions resulting from nonlinear gravitational instability of initial Gaussian fluctuations. We also find that the maximum of the number of clusters statistic in the evolved, nonlinear distributions is determined by the effective slope of the power spectrum. Next, we present percolation analyses of Wiener Reconstructions of the IRAS 1.2 Jy Redshift Survey. There are ten reconstructions of galaxy density fields in real space spanning the range β = 0.1 to 1.0, where β=Ω0.6/b,/ Ω is the present dimensionless density and b is the linear bias factor. Our method uses the growth of the largest cluster statistic to characterize the topology of a density field, where Gaussian randomized versions of the reconstructions are used as standards for analysis. For the reconstruction volume of radius, R≈100h-1 Mpc, percolation analysis reveals a slight 'meatball' topology for the real space, galaxy distribution of the IRAS survey. Finally, we employ a percolation technique developed for pointwise distributions to analyze two-dimensional projections of the three northern and three southern slices in the Las Campanas Redshift Survey and then give consideration to further study of the methodology, errors and application of percolation. We track the growth of the largest cluster as a topological indicator to a depth of 400 h-1 Mpc, and report an unambiguous signal, with high signal-to-noise ratio, indicating a network topology which in two dimensions is indicative of a filamentary distribution. It is hoped that one day percolation analysis can characterize the structure of the universe to a degree that will aid theorists in confidently describing the nature of our world.

Tensor Spectral Clustering for Partitioning Higher-order Network Structures.

PubMed

Benson, Austin R; Gleich, David F; Leskovec, Jure

2015-01-01

Spectral graph theory-based methods represent an important class of tools for studying the structure of networks. Spectral methods are based on a first-order Markov chain derived from a random walk on the graph and thus they cannot take advantage of important higher-order network substructures such as triangles, cycles, and feed-forward loops. Here we propose a Tensor Spectral Clustering (TSC) algorithm that allows for modeling higher-order network structures in a graph partitioning framework. Our TSC algorithm allows the user to specify which higher-order network structures (cycles, feed-forward loops, etc.) should be preserved by the network clustering. Higher-order network structures of interest are represented using a tensor, which we then partition by developing a multilinear spectral method. Our framework can be applied to discovering layered flows in networks as well as graph anomaly detection, which we illustrate on synthetic networks. In directed networks, a higher-order structure of particular interest is the directed 3-cycle, which captures feedback loops in networks. We demonstrate that our TSC algorithm produces large partitions that cut fewer directed 3-cycles than standard spectral clustering algorithms.

Tensor Spectral Clustering for Partitioning Higher-order Network Structures

PubMed Central

Benson, Austin R.; Gleich, David F.; Leskovec, Jure

2016-01-01

Spectral graph theory-based methods represent an important class of tools for studying the structure of networks. Spectral methods are based on a first-order Markov chain derived from a random walk on the graph and thus they cannot take advantage of important higher-order network substructures such as triangles, cycles, and feed-forward loops. Here we propose a Tensor Spectral Clustering (TSC) algorithm that allows for modeling higher-order network structures in a graph partitioning framework. Our TSC algorithm allows the user to specify which higher-order network structures (cycles, feed-forward loops, etc.) should be preserved by the network clustering. Higher-order network structures of interest are represented using a tensor, which we then partition by developing a multilinear spectral method. Our framework can be applied to discovering layered flows in networks as well as graph anomaly detection, which we illustrate on synthetic networks. In directed networks, a higher-order structure of particular interest is the directed 3-cycle, which captures feedback loops in networks. We demonstrate that our TSC algorithm produces large partitions that cut fewer directed 3-cycles than standard spectral clustering algorithms. PMID:27812399

Review of methods for handling confounding by cluster and informative cluster size in clustered data

PubMed Central

Seaman, Shaun; Pavlou, Menelaos; Copas, Andrew

2014-01-01

Clustered data are common in medical research. Typically, one is interested in a regression model for the association between an outcome and covariates. Two complications that can arise when analysing clustered data are informative cluster size (ICS) and confounding by cluster (CBC). ICS and CBC mean that the outcome of a member given its covariates is associated with, respectively, the number of members in the cluster and the covariate values of other members in the cluster. Standard generalised linear mixed models for cluster-specific inference and standard generalised estimating equations for population-average inference assume, in general, the absence of ICS and CBC. Modifications of these approaches have been proposed to account for CBC or ICS. This article is a review of these methods. We express their assumptions in a common format, thus providing greater clarity about the assumptions that methods proposed for handling CBC make about ICS and vice versa, and about when different methods can be used in practice. We report relative efficiencies of methods where available, describe how methods are related, identify a previously unreported equivalence between two key methods, and propose some simple additional methods. Unnecessarily using a method that allows for ICS/CBC has an efficiency cost when ICS and CBC are absent. We review tools for identifying ICS/CBC. A strategy for analysis when CBC and ICS are suspected is demonstrated by examining the association between socio-economic deprivation and preterm neonatal death in Scotland. PMID:25087978

Towards a Framework for Developing Semantic Relatedness Reference Standards

PubMed Central

Pakhomov, Serguei V.S.; Pedersen, Ted; McInnes, Bridget; Melton, Genevieve B.; Ruggieri, Alexander; Chute, Christopher G.

2010-01-01

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results. Our proposed framework is based on the experiences of medical informatics and computational linguistics communities and addresses practical and theoretical issues with creating reference standards for semantic relatedness. We demonstrate the use of the framework on a pilot set of 101 medical term pairs rated for semantic relatedness by 13 medical coding experts. While the reliability of this particular reference standard is in the “moderate” range; we show that using clustering and factor analyses offers a data-driven approach to finding systematic differences among raters and identifying groups of potential outliers. We test two ontology-based measures of relatedness and provide both the reference standard containing individual ratings and the R program used to analyze the ratings as open-source. Currently, these resources are intended to be used to reproduce and compare results of studies involving computerized measures of semantic relatedness. Our framework may be extended to the development of reference standards in other research areas in medical informatics including automatic classification, information retrieval from medical records and vocabulary/ontology development. PMID:21044697

Clustering of Emerging Flux

NASA Technical Reports Server (NTRS)

Ruzmaikin, A.

1997-01-01

Observations show that newly emerging flux tends to appear on the Solar surface at sites where there is flux already. This results in clustering of solar activity. Standard dynamo theories do not predict this effect.

Prescribing Oxygen for Cluster Headache: A Guide for the Provider.

PubMed

Tepper, Stewart J; Duplin, Jessica; Nye, Barbara; Tepper, Deborah E

2017-10-01

Oxygen is the standard of care for acute treatment of cluster headache. CMS, the US Centers for Medicaid and Medicare Services, has made the indefensible decision to not cover oxygen for cluster headache for patients with Medicaid and Medicare insurance, despite the evidence and professional guidelines. Commercial insurance generally covers oxygen for cluster headache. This is a "how-to" guide for successfully prescribing oxygen in the US. Prescription information is provided that can be incorporated as dot phrases, smart sets, or other standard templates for prescribing oxygen for cluster patients. In many states, oxygen is affordable and can be prescribed for Medicaid and Medicare patients who wish to pay cash. Welding or nonmedical grade industrial oxygen is almost the same cost as medical oxygen. However, it is less pure, lacks the same inspection of tanks, and is delivered without regulators to provide appropriate flow rates. Patients who pay cash should be strongly encouraged to buy medical oxygen. © 2017 American Headache Society.

Finding new pathway-specific regulators by clustering method using threshold standard deviation based on DNA chip data of Streptomyces coelicolor.

PubMed

Yang, Yung-Hun; Kim, Ji-Nu; Song, Eunjung; Kim, Eunjung; Oh, Min-Kyu; Kim, Byung-Gee

2008-09-01

In order to identify the regulators involved in antibiotic production or time-specific cellular events, the messenger ribonucleic acid (mRNA) expression data of the two gene clusters, actinorhodin (ACT) and undecylprodigiosin (RED) biosynthetic genes, were clustered with known mRNA expression data of regulators from S. coelicolor using a filtering method based on standard deviation and clustering analysis. The result identified five regulators including two well-known regulators namely, SCO3579 (WlbA) and SCO6722 (SsgD). Using overexpression and deletion of the regulator genes, we were able to identify two regulators, i.e., SCO0608 and SCO6808, playing roles as repressors in antibiotics production and sporulation. This approach can be easily applied to mapping out new regulators related to any interesting target gene clusters showing characteristic expression patterns. The result can also be used to provide insightful information on the selection rules among a large number of regulators.

Development of an Identification Procedure for a Large Urban School Corporation: "Identifying Culturally Diverse and Academically Gifted Elementary Students"

ERIC Educational Resources Information Center

Pierce, Rebecca L.; Adams, Cheryll M.; Neumeister, Kristie L. Speirs; Cassady, Jerrell C.; Dixon, Felicia A.; Cross, Tracy L.

2006-01-01

This paper describes the identification process of a Priority One Jacob K. Javits grant, Clustering Learners Unlocks Equity (Project CLUE), a university-school partnership. Project CLUE uses a "sift-down model" to cast the net widely as the talent pool of gifted second-grade students is formed. The model is based on standardized test scores, a…

Examining the Impact of Using the Science Writing Heuristic Approach in Learning Science: A Cluster Randomized Study

ERIC Educational Resources Information Center

Hand, Brian; Therrien, William; Shelley, Mack

2013-01-01

The U.S. began a new national standards movement in the area of K-12 science education curriculum reform in the 1980s known as "Science for All" to develop a population that is literate in economic and democratic agendas for a global market focused on science, technology, engineering, and mathematics (STEM) (Duschl, 2008). The National…

Clusters of Galaxies at High Redshift

NASA Astrophysics Data System (ADS)

Fort, Bernard

For a long time, the small number of clusters at z > 0.3 in the Abell survey catalogue and simulations of the standard CDM formation of large scale structures provided a paradigm where clusters were considered as young merging structures. At earlier times, loose concentrations of galaxy clumps were mostly anticipated. Recent observations broke the taboo. Progressively we became convinced that compact and massive clusters at z = 1 or possibly beyond exist and should be searched for.

Validity of Combining History Elements and Physical Examination Tests to Diagnose Patellofemoral Pain.

PubMed

Décary, Simon; Frémont, Pierre; Pelletier, Bruno; Fallaha, Michel; Belzile, Sylvain; Martel-Pelletier, Johanne; Pelletier, Jean-Pierre; Feldman, Debbie; Sylvestre, Marie-Pierre; Vendittoli, Pascal-André; Desmeules, François

2018-04-01

To assess the validity of diagnostic clusters combining history elements and physical examination tests to diagnose or exclude patellofemoral pain (PFP). Prospective diagnostic study. Orthopedic outpatient clinics, family medicine clinics, and community-dwelling. Consecutive patients (N=279) consulting one of the participating orthopedic surgeons (n=3) or sport medicine physicians (n=2) for any knee complaint. Not applicable. History elements and physical examination tests were obtained by a trained physiotherapist blinded to the reference standard: a composite diagnosis including both physical examination tests and imaging results interpretation performed by an expert physician. Penalized logistic regression (least absolute shrinkage and selection operator) was used to identify history elements and physical examination tests associated with the diagnosis of PFP, and recursive partitioning was used to develop diagnostic clusters. Diagnostic accuracy measures including sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios with associated 95% confidence intervals (CIs) were calculated. Two hundred seventy-nine participants were evaluated, and 75 had a diagnosis of PFP (26.9%). Different combinations of history elements and physical examination tests including the age of participants, knee pain location, difficulty descending stairs, patellar facet palpation, and passive knee extension range of motion were associated with a diagnosis of PFP and used in clusters to accurately discriminate between individuals with PFP and individuals without PFP. Two diagnostic clusters developed to confirm the presence of PFP yielded a positive likelihood ratio of 8.7 (95% CI, 5.2-14.6) and 3 clusters to exclude PFP yielded a negative likelihood ratio of .12 (95% CI, .06-.27). Diagnostic clusters combining common history elements and physical examination tests that can accurately diagnose or exclude PFP compared to various knee disorders were developed. External validation is required before clinical use. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

SU-E-J-272: Auto-Segmentation of Regions with Differentiating CT Numbers for Treatment Response Assessment

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

Yang, C; Noid, G; Dalah, E

2015-06-15

Purpose: It has been reported recently that the change of CT number (CTN) during and after radiation therapy (RT) may be used to assess RT response. The purpose of this work is to develop a tool to automatically segment the regions with differentiating CTN and/or with change of CTN in a series of CTs. Methods: A software tool was developed to identify regions with differentiating CTN using K-mean Cluster of CT numbers and to automatically delineate these regions using convex hull enclosing method. Pre- and Post-RT CT, PET, or MRI images acquired for sample lung and pancreatic cancer cases weremore » used to test the software tool. K-mean cluster of CT numbers within the gross tumor volumes (GTVs) delineated based on PET SUV (standard uptake value of fludeoxyglucose) and/or MRI ADC (apparent diffusion coefficient) map was analyzed. The cluster centers with higher value were considered as active tumor volumes (ATV). The convex hull contours enclosing preset clusters were used to delineate these ATVs with color washed displays. The CTN defined ATVs were compared with the SUV- or ADC-defined ATVs. Results: CTN stability of the CT scanner used to acquire the CTs in this work is less than 1.5 Hounsfield Unit (HU) variation annually. K-mean cluster centers in the GTV have difference of ∼20 HU, much larger than variation due to CTN stability, for the lung cancer cases studied. The dice coefficient between the ATVs delineated based on convex hull enclosure of high CTN centers and the PET defined GTVs based on SUV cutoff value of 2.5 was 90(±5)%. Conclusion: A software tool was developed using K-mean cluster and convex hull contour to automatically segment high CTN regions which may not be identifiable using a simple threshold method. These CTN regions were reasonably overlapped with the PET or MRI defined GTVs.« less

Magnetic Properties of Strongly Correlated Hubbard Model and Quantum Spin-One Ferromagnets with Arbitrary Crystal-Field Potential: Linked Cluster Series Expansion Approach

NASA Astrophysics Data System (ADS)

Pan, Kok-Kwei

We have generalized the linked cluster expansion method to solve more many-body quantum systems, such as quantum spin systems with crystal-field potentials and the Hubbard model. The technique sums up all connected diagrams to a certain order of the perturbative Hamiltonian. The modified multiple-site Wick reduction theorem and the simple tau dependence of the standard basis operators have been used to facilitate the evaluation of the integration procedures in the perturbation expansion. Computational methods are developed to calculate all terms in the series expansion. As a first example, the perturbation series expansion of thermodynamic quantities of the single-band Hubbard model has been obtained using a linked cluster series expansion technique. We have made corrections to all previous results of several papers (up to fourth order). The behaviors of the three dimensional simple cubic and body-centered cubic systems have been discussed from the qualitative analysis of the perturbation series up to fourth order. We have also calculated the sixth-order perturbation series of this model. As a second example, we present the magnetic properties of spin-one Heisenberg model with arbitrary crystal-field potential using a linked cluster series expansion. The calculation of the thermodynamic properties using this method covers the whole range of temperature, in both magnetically ordered and disordered phases. The series for the susceptibility and magnetization have been obtained up to fourth order for this model. The method sums up all perturbation terms to certain order and estimates the result using a well -developed and highly successful extrapolation method (the standard ratio method). The dependence of critical temperature on the crystal-field potential and the magnetization as a function of temperature and crystal-field potential are shown. The critical behaviors at zero temperature are also shown. The range of the crystal-field potential for Ni(2+) compounds is roughly estimated based on this model using known experimental results.

Structural evolution in the crystallization of rapid cooling silver melt

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

Tian, Z.A., E-mail: ze.tian@gmail.com; Laboratory for Simulation and Modelling of Particulate Systems School of Materials Science and Engineering, University of New South Wales, Sydney, NSW 2052; Dong, K.J.

2015-03-15

The structural evolution in a rapid cooling process of silver melt has been investigated at different scales by adopting several analysis methods. The results testify Ostwald’s rule of stages and Frank conjecture upon icosahedron with many specific details. In particular, the cluster-scale analysis by a recent developed method called LSCA (the Largest Standard Cluster Analysis) clarified the complex structural evolution occurred in crystallization: different kinds of local clusters (such as ico-like (ico is the abbreviation of icosahedron), ico-bcc like (bcc, body-centred cubic), bcc, bcc-like structures) in turn have their maximal numbers as temperature decreases. And in a rather wide temperaturemore » range the icosahedral short-range order (ISRO) demonstrates a saturated stage (where the amount of ico-like structures keeps stable) that breeds metastable bcc clusters. As the precursor of crystallization, after reaching the maximal number bcc clusters finally decrease, resulting in the final solid being a mixture mainly composed of fcc/hcp (face-centred cubic and hexagonal-closed packed) clusters and to a less degree, bcc clusters. This detailed geometric picture for crystallization of liquid metal is believed to be useful to improve the fundamental understanding of liquid–solid phase transition. - Highlights: • A comprehensive structural analysis is conducted focusing on crystallization. • The involved atoms in our analysis are more than 90% for all samples concerned. • A series of distinct intermediate states are found in crystallization of silver melt. • A novelty icosahedron-saturated state breeds the metastable bcc state.« less

Infection prevention and control.

PubMed

Pegram, Anne; Bloomfield, Jacqueline

2015-03-18

All newly registered graduate nurses are required to have the appropriate knowledge and understanding to perform the skills required for patient care, specifically the competencies identified in the Nursing and Midwifery Council's essential skills clusters. This article focuses on the third essential skills cluster - infection prevention and control. It provides an overview and discussion of the key skills and behaviours that must be demonstrated to meet the standards set by the Nursing and Midwifery Council. In doing so, it considers the key principles of infection prevention and control, including local and national policies, standard infection control precautions, risk assessment, standard isolation measures and asepsis.

Analysis of Spatial Pattern and Influencing Factors of E-Commerce

NASA Astrophysics Data System (ADS)

Zhang, Y.; Chen, J.; Zhang, S.

2017-09-01

This paper aims to study the relationship between e-commerce development and geographical characteristics using data of e-commerce, economy, Internet, express delivery and population from 2011 to 2015. Moran's I model and GWR model are applied to analyze the spatial pattern of E-commerce and its influencing factors. There is a growth trend of e-commerce from west to east, and it is obvious to see that e-commerce development has a space-time clustering, especially around the Yangtze River delta. The comprehensive factors caculated through PCA are described as fundamental social productivity, resident living standard and population sex structure. The first two factors have positive correlation with e-commerce, and the intensity of effect increases yearly. However, the influence of population sex structure on the E-commerce development is not significant. Our results suggest that the clustering of e-commerce has a downward trend and the impact of driving factors on e-commerce is observably distinct from year to year in space.

uvbyβ photometry of early type open cluster and field stars

NASA Astrophysics Data System (ADS)

Handler, G.

2011-04-01

Context. The β Cephei stars and slowly pulsating B (SPB) stars are massive main sequence variables. The strength of their pulsational driving strongly depends on the opacity of iron-group elements. As many of those stars naturally occur in young open clusters, whose metallicities can be determined in several fundamental ways, it is logical to study the incidence of pulsation in several young open clusters. Aims: To provide the foundation for such an investigation, Strömgren-Crawford uvbyβ photometry of open cluster target stars was carried out to determine effective temperatures, luminosities, and therefore cluster memberships. Methods: In the course of three observing runs, uvbyβ photometry for 168 target stars was acquired and transformed into the standard system by measurements of 117 standard stars. The list of target stars also included some known cluster and field β Cephei stars, as well as β Cephei and SPB candidates that are targets of the asteroseismic part of the Kepler satellite mission. Results: The uvbyβ photometric results are presented. The data are shown to be on the standard system, and the properties of the target stars are discussed: 140 of these are indeed OB stars, a total of 101 targets lie within the β Cephei and/or SPB star instability strips, and each investigated cluster contains such potential pulsators. Conclusions: These measurements will be taken advantage of in a number of subsequent publications. Based on measurements obtained at McDonald Observatory of the University of Texas at Austin.Tables 3-6 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/528/A148

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects

PubMed Central

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called “cluster randomization”). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies. PMID:28584874

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects.

PubMed

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called "cluster randomization"). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies.

Towards accurate modelling of galaxy clustering on small scales: testing the standard ΛCDM + halo model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

2018-07-01

Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter haloes. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the `accurate' regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard Λ cold dark matter (ΛCDM) + halo model against the clustering of Sloan Digital Sky Survey (SDSS) seventh data release (DR7) galaxies. Specifically, we use the projected correlation function, group multiplicity function, and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir haloes) matches the clustering of low-luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the `standard' halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

Comprehensive cluster analysis with Transitivity Clustering.

PubMed

Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

2011-03-01

Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

Cluster lot quality assurance sampling: effect of increasing the number of clusters on classification precision and operational feasibility.

PubMed

Okayasu, Hiromasa; Brown, Alexandra E; Nzioki, Michael M; Gasasira, Alex N; Takane, Marina; Mkanda, Pascal; Wassilak, Steven G F; Sutter, Roland W

2014-11-01

To assess the quality of supplementary immunization activities (SIAs), the Global Polio Eradication Initiative (GPEI) has used cluster lot quality assurance sampling (C-LQAS) methods since 2009. However, since the inception of C-LQAS, questions have been raised about the optimal balance between operational feasibility and precision of classification of lots to identify areas with low SIA quality that require corrective programmatic action. To determine if an increased precision in classification would result in differential programmatic decision making, we conducted a pilot evaluation in 4 local government areas (LGAs) in Nigeria with an expanded LQAS sample size of 16 clusters (instead of the standard 6 clusters) of 10 subjects each. The results showed greater heterogeneity between clusters than the assumed standard deviation of 10%, ranging from 12% to 23%. Comparing the distribution of 4-outcome classifications obtained from all possible combinations of 6-cluster subsamples to the observed classification of the 16-cluster sample, we obtained an exact match in classification in 56% to 85% of instances. We concluded that the 6-cluster C-LQAS provides acceptable classification precision for programmatic action. Considering the greater resources required to implement an expanded C-LQAS, the improvement in precision was deemed insufficient to warrant the effort. Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A detection of wobbling brightest cluster galaxies within massive galaxy clusters

NASA Astrophysics Data System (ADS)

Harvey, David; Courbin, F.; Kneib, J. P.; McCarthy, Ian G.

2017-12-01

A striking signal of dark matter beyond the standard model is the existence of cores in the centre of galaxy clusters. Recent simulations predict that a brightest cluster galaxy (BCG) inside a cored galaxy cluster will exhibit residual wobbling due to previous major mergers, long after the relaxation of the overall cluster. This phenomenon is absent with standard cold dark matter where a cuspy density profile keeps a BCG tightly bound at the centre. We test this hypothesis using cosmological simulations and deep observations of 10 galaxy clusters acting as strong gravitational lenses. Modelling the BCG wobble as a simple harmonic oscillator, we measure the wobble amplitude, Aw, in the BAHAMAS suite of cosmological hydrodynamical simulations, finding an upper limit for the cold dark matter paradigm of Aw < 2 kpc at the 95 per cent confidence limit. We carry out the same test on the data finding a non-zero amplitude of A_w=11.82^{+7.3}_{-3.0} kpc, with the observations dis-favouring Aw = 0 at the 3σ confidence level. This detection of BCG wobbling is evidence for a dark matter core at the heart of galaxy clusters. It also shows that strong lensing models of clusters cannot assume that the BCG is exactly coincident with the large-scale halo. While our small sample of galaxy clusters already indicates a non-zero Aw, with larger surveys, e.g. Euclid, we will be able to not only confirm the effect but also to use it to determine whether or not the wobbling finds its origin in new fundamental physics or astrophysical process.

[Perception of odor quality by Free Image-Association Test].

PubMed

Ueno, Y

1992-10-01

A method was devised for evaluating odor quality. Subjects were requested to freely describe the images elicited by smelling odors. This test was named the "Free Image-Association Test (FIT)". The test was applied for 20 flavors of various foods, five odors from the standards of T&T olfactometer (Japanese standard olfactory test), butter of yak milk, and incense from Lamaism temples. The words for expressing imagery were analyzed by multidimensional scaling and cluster analysis. Seven clusters of odors were obtained. The feature of these clusters were quite similar to that of primary odors which have been suggested by previous studies. However, the clustering of odors can not be explained on the basis of the primary-odor theory, but the information processing theory originally proposed by Miller (1956). These results support the usefulness of the Free Image-Association Test for investigating odor perception based on the images associated with odors.

Statistical analysis of donation--transfusion data with complex correlation.

PubMed

Reilly, Marie; Szulkin, Robert

2007-12-30

Blood-borne transmission of disease is estimated from linked data records from blood donors and transfusion recipients. However, such data are characterized by complex correlation due to donors typically contributing many donations and recipients being transfused with multiple units of blood product. In this paper, we present a method for analysing such data, by using a modification of a nested case-control design. For recipients who develop the disease of interest (cases) and their matched controls, all donors who contributed blood to these individuals define clusters or 'families' of related individuals. Using a Cox regression model for the hazard of the individuals within clusters of donors, we estimate the risk of transmission, and a bootstrap step provides valid standard errors provided the clusters are independent. As an illustration, we apply the method to the analysis of a large database of Swedish donor and recipient records linked to the population cancer register. We investigate whether there is an increased risk of cancer in recipients transfused with blood from donors who develop cancer after donating. Our method provides a powerful alternative to the small 'look-back' studies typical of transfusion medicine and can make an important contribution to haemovigilance efforts. Copyright (c) 2007 John Wiley & Sons, Ltd.

Cross Layered Multi-Meshed Tree Scheme for Cognitive Networks

DTIC Science & Technology

2011-06-01

Meshed Tree Routing protocol wireless ad hoc networks ,” Second IEEE International Workshop on Enabling Technologies and Standards for Wireless Mesh ...and Sensor Networks , 2004 43. Chen G.; Stojmenovic I., “Clustering and routing in mobile wireless networks ,” Technical Report TR-99-05, SITE, June...Cross-layer optimization, intra-cluster routing , packet forwarding, inter-cluster routing , mesh network communications,

QCS : a system for querying, clustering, and summarizing documents.

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

Dunlavy, Daniel M.

2006-08-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test setsmore » from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence ''trimming'', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of the design, and the value of this particular combination of modules.« less

QCS: a system for querying, clustering and summarizing documents.

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

Dunlavy, Daniel M.; Schlesinger, Judith D.; O'Leary, Dianne P.

2006-10-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test setsmore » from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence 'trimming', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of the design, and the value of this particular combination of modules.« less

WIS Implementation Study Report. Volume 2. Resumes.

DTIC Science & Technology

1983-10-01

WIS modernization that major attention be paid to interface definition and design, system integra- tion and test , and configuration management of the...Estimates -- Computer Corporation of America -- 155 Test Processing Systems -- Newburyport Computer Associates, Inc. -- 183 Cluster II Papers-- Standards...enhancements of the SPL/I compiler system, development of test systems for the verification of SDEX/M and the timing and architecture of the AN/U YK-20 and

A cluster randomized pilot trial of a tailored worksite smoking cessation intervention targeting Hispanic/Latino construction workers: Intervention development and research design.

PubMed

Asfar, Taghrid; Caban-Martinez, Alberto J; McClure, Laura A; Ruano-Herreria, Estefania C; Sierra, Danielle; Gilford Clark, G; Samano, Daniel; Dietz, Noella A; Ward, Kenneth D; Arheart, Kristopher L; Lee, David J

2018-04-01

Construction workers have the highest smoking rate among all occupations (39%). Hispanic/Latino workers constitute a large and increasing group in the US construction industry (over 2.6 million; 23% of all workers). These minority workers have lower cessation rates compared to other groups due to their limited access to cessation services, and lack of smoking cessation interventions adapted to their culture and work/life circumstances. Formative research was conducted to create an intervention targeting Hispanic/Latino construction workers. This paper describes the intervention development and the design, methods, and data analysis plans for an ongoing cluster pilot two-arm randomized controlled trial comparing an Enhanced Care worksite cessation program to Standard Care. Fourteen construction sites will be randomized to either Enhanced Care or Standard Care and 126 participants (63/arm) will be recruited. In both arms, recruitment and intervention delivery occur around "food trucks" that regularly visit the construction sites. Participants at Enhanced Care sites will receive the developed intervention consisting of a single face-to-face group counseling session, 2 phone calls, and a fax referral to Florida tobacco quitline (QL). Participants at Standard Care sites will receive a fax referral to the QL. Both groups will receive eight weeks of nicotine replacement treatment and two follow-up assessments at three and six months. Feasibility outcomes are estimated recruitment yield, barriers to delivering the intervention onsite, and rates of adherence/compliance to the intervention, follow-ups, and QL enrollment. Efficacy outcomes are point-prevalence and prolonged abstinence rates at six month follow-up confirmed by saliva cotinine <15 ng/ml. Copyright © 2018. Published by Elsevier Inc.

Time-lapse total internal reflection fluorescence video of acetylcholine receptor cluster formation on myotubes.

PubMed

Wang, M D; Axelrod, D

1994-09-01

To study when and where acetylcholine receptor (AChR) clusters appear on developing rat myotubes in primary culture, we have made time-lapse movies of total internal reflection fluorescence (TIRF) overlaid with schlieren transmitted light images. The receptors, including the ones newly incorporated into the membrane, were labeled with rhodamine alpha-bungarotoxin (R-BT) continuously present in the medium. Since TIRF illuminates only cell-substrate contact regions where almost all of the AChR clusters are located, background fluorescence from fluorophores either in the bulk solution or inside the cells can be suppressed. Also, because TIRF minimizes the exposure of the cell interior to light, the healthy survival of the culture during imaging procedures is much enhanced relative to standard epi- (or trans-) illumination. During the experiment, cells were kept alive on the microscope stage at 37 degrees C in an atmosphere of 10% CO2. Two digital images were recorded by a CCD camera every 20 min: the schlieren image of the cells and the TIRF image of the clusters. After background subtraction, the cluster image was displayed in pseudocolors, overlaid onto the cell images, and recorded as 3 frames on a videotape. The final movies are thus able to summarize a week-long experiment in less than a minute. These movies and images show that clusters form often shortly after the myoblast fusion but sometimes much later, and the formation takes place very rapidly (a few hours). The clusters have an average lifetime of around a day, much shorter than the lifetime of a typical myotube. The brightest and largest clusters tend to be the longest-lived. The cluster formation seems to be associated with the contacts of myotubes at the glass substrate, but not with cell-cell contacts or myoblast fusion into myotubes. New AChR continuously appear in preexisting clusters: after photobleaching, the fluorescence of some clusters recovers within an hour.

Automatic classification of protein structures relying on similarities between alignments

PubMed Central

2012-01-01

Background Identification of protein structural cores requires isolation of sets of proteins all sharing a same subset of structural motifs. In the context of an ever growing number of available 3D protein structures, standard and automatic clustering algorithms require adaptations so as to allow for efficient identification of such sets of proteins. Results When considering a pair of 3D structures, they are stated as similar or not according to the local similarities of their matching substructures in a structural alignment. This binary relation can be represented in a graph of similarities where a node represents a 3D protein structure and an edge states that two 3D protein structures are similar. Therefore, classifying proteins into structural families can be viewed as a graph clustering task. Unfortunately, because such a graph encodes only pairwise similarity information, clustering algorithms may include in the same cluster a subset of 3D structures that do not share a common substructure. In order to overcome this drawback we first define a ternary similarity on a triple of 3D structures as a constraint to be satisfied by the graph of similarities. Such a ternary constraint takes into account similarities between pairwise alignments, so as to ensure that the three involved protein structures do have some common substructure. We propose hereunder a modification algorithm that eliminates edges from the original graph of similarities and gives a reduced graph in which no ternary constraints are violated. Our approach is then first to build a graph of similarities, then to reduce the graph according to the modification algorithm, and finally to apply to the reduced graph a standard graph clustering algorithm. Such method was used for classifying ASTRAL-40 non-redundant protein domains, identifying significant pairwise similarities with Yakusa, a program devised for rapid 3D structure alignments. Conclusions We show that filtering similarities prior to standard graph based clustering process by applying ternary similarity constraints i) improves the separation of proteins of different classes and consequently ii) improves the classification quality of standard graph based clustering algorithms according to the reference classification SCOP. PMID:22974051

A cluster-randomised, controlled trial to assess the impact of a workplace osteoporosis prevention intervention on the dietary and physical activity behaviours of working women: study protocol.

PubMed

Tan, Ai May; Lamontagne, Anthony D; Sarmugam, Rani; Howard, Peter

2013-04-29

Osteoporosis is a debilitating disease and its risk can be reduced through adequate calcium consumption and physical activity. This protocol paper describes a workplace-based intervention targeting behaviour change in premenopausal women working in sedentary occupations. A cluster-randomised design was used, comparing the efficacy of a tailored intervention to standard care. Workplaces were the clusters and units of randomisation and intervention. Sample size calculations incorporated the cluster design. Final number of clusters was determined to be 16, based on a cluster size of 20 and calcium intake parameters (effect size 250 mg, ICC 0.5 and standard deviation 290 mg) as it required the highest number of clusters.Sixteen workplaces were recruited from a pool of 97 workplaces and randomly assigned to intervention and control arms (eight in each). Women meeting specified inclusion criteria were then recruited to participate. Workplaces in the intervention arm received three participatory workshops and organisation wide educational activities. Workplaces in the control/standard care arm received print resources. Intervention workshops were guided by self-efficacy theory and included participatory activities such as goal setting, problem solving, local food sampling, exercise trials, group discussion and behaviour feedback.Outcomes measures were calcium intake (milligrams/day) and physical activity level (duration: minutes/week), measured at baseline, four weeks and six months post intervention. This study addresses the current lack of evidence for behaviour change interventions focussing on osteoporosis prevention. It addresses missed opportunities of using workplaces as a platform to target high-risk individuals with sedentary occupations. The intervention was designed to modify behaviour levels to bring about risk reduction. It is the first to address dietary and physical activity components each with unique intervention strategies in the context of osteoporosis prevention. The intervention used locally relevant behavioural strategies previously shown to support good outcomes in other countries. The combination of these elements have not been incorporated in similar studies in the past, supporting the study hypothesis that the intervention will be more efficacious than standard practice in osteoporosis prevention through improvements in calcium intake and physical activity.

A cluster-randomised, controlled trial to assess the impact of a workplace osteoporosis prevention intervention on the dietary and physical activity behaviours of working women: study protocol

PubMed Central

2013-01-01

Background Osteoporosis is a debilitating disease and its risk can be reduced through adequate calcium consumption and physical activity. This protocol paper describes a workplace-based intervention targeting behaviour change in premenopausal women working in sedentary occupations. Method/Design A cluster-randomised design was used, comparing the efficacy of a tailored intervention to standard care. Workplaces were the clusters and units of randomisation and intervention. Sample size calculations incorporated the cluster design. Final number of clusters was determined to be 16, based on a cluster size of 20 and calcium intake parameters (effect size 250 mg, ICC 0.5 and standard deviation 290 mg) as it required the highest number of clusters. Sixteen workplaces were recruited from a pool of 97 workplaces and randomly assigned to intervention and control arms (eight in each). Women meeting specified inclusion criteria were then recruited to participate. Workplaces in the intervention arm received three participatory workshops and organisation wide educational activities. Workplaces in the control/standard care arm received print resources. Intervention workshops were guided by self-efficacy theory and included participatory activities such as goal setting, problem solving, local food sampling, exercise trials, group discussion and behaviour feedback. Outcomes measures were calcium intake (milligrams/day) and physical activity level (duration: minutes/week), measured at baseline, four weeks and six months post intervention. Discussion This study addresses the current lack of evidence for behaviour change interventions focussing on osteoporosis prevention. It addresses missed opportunities of using workplaces as a platform to target high-risk individuals with sedentary occupations. The intervention was designed to modify behaviour levels to bring about risk reduction. It is the first to address dietary and physical activity components each with unique intervention strategies in the context of osteoporosis prevention. The intervention used locally relevant behavioural strategies previously shown to support good outcomes in other countries. The combination of these elements have not been incorporated in similar studies in the past, supporting the study hypothesis that the intervention will be more efficacious than standard practice in osteoporosis prevention through improvements in calcium intake and physical activity. PMID:23627684

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.

Towards a framework for developing semantic relatedness reference standards.

PubMed

Pakhomov, Serguei V S; Pedersen, Ted; McInnes, Bridget; Melton, Genevieve B; Ruggieri, Alexander; Chute, Christopher G

2011-04-01

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results. Our proposed framework is based on the experiences of medical informatics and computational linguistics communities and addresses practical and theoretical issues with creating reference standards for semantic relatedness. We demonstrate the use of the framework on a pilot set of 101 medical term pairs rated for semantic relatedness by 13 medical coding experts. While the reliability of this particular reference standard is in the "moderate" range; we show that using clustering and factor analyses offers a data-driven approach to finding systematic differences among raters and identifying groups of potential outliers. We test two ontology-based measures of relatedness and provide both the reference standard containing individual ratings and the R program used to analyze the ratings as open-source. Currently, these resources are intended to be used to reproduce and compare results of studies involving computerized measures of semantic relatedness. Our framework may be extended to the development of reference standards in other research areas in medical informatics including automatic classification, information retrieval from medical records and vocabulary/ontology development. Copyright © 2010 Elsevier Inc. All rights reserved.

The Cluster Science Archive: from Time Period to Physics Based Search

NASA Astrophysics Data System (ADS)

Masson, A.; Escoubet, C. P.; Laakso, H. E.; Perry, C. H.

2015-12-01

Since 2000, the Cluster spacecraft relay the most detailed information on how the solar wind affects our geospace in three dimensions. Science output from Cluster is a leap forward in our knowledge of space plasma physics: the science behind space weather. It has been key in improving the modeling of the magnetosphere and understanding its various physical processes. Cluster data have enabled the publication of more than 2000 refereed papers and counting. This substantial scientific return is often attributed to the online availability of the Cluster data archive, now called the Cluster Science Archive (CSA). It is being developed by the ESAC Science Data Center (ESDC) team and maintained alongside other science ESA archives at ESAC (ESA Space Astronomy Center, Madrid, Spain). CSA is a public archive, which contains the entire set of Cluster high-resolution data, and other related products in a standard format and with a complete set of metadata. Since May 2015, it also contains data from the CNSA/ESA Double Star mission (2003-2008), a mission operated in conjunction with Cluster. The total amount of data format now exceeds 100 TB. Accessing CSA requires to be registered to enable user profiles and CSA accounts more than 1,500 users. CSA provides unique tools for visualizing its data including - on-demand particle distribution functions visualization - fast data browsing with more than 15TB of pre-generated plots - inventory plots It also offers command line capabilities (e.g. data access via Matlab or IDL softwares, data streaming). Despite its reliability, users can only request data for a specific time period while scientists often focus on specific regions or data signatures. For these reasons, a data-mining tool is being developed to do just that. It offers an interface to select data based not only on a time period but on various criteria including: key physical parameters, regions of space and spacecraft constellation geometry. The output of this tool is a list of time periods that fits the criteria imposed by the user. Such a list enables to download any bunch of datasets for all these time periods in one go. We propose to present the state of development of this tool and interact with the scientific community to better fit its needs.

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Metabolic Clustering Analysis as a Strategy for Compound Selection in the Drug Discovery Pipeline for Leishmaniasis.

PubMed

Armitage, Emily G; Godzien, Joanna; Peña, Imanol; López-Gonzálvez, Ángeles; Angulo, Santiago; Gradillas, Ana; Alonso-Herranz, Vanesa; Martín, Julio; Fiandor, Jose M; Barrett, Michael P; Gabarro, Raquel; Barbas, Coral

2018-05-18

A lack of viable hits, increasing resistance, and limited knowledge on mode of action is hindering drug discovery for many diseases. To optimize prioritization and accelerate the discovery process, a strategy to cluster compounds based on more than chemical structure is required. We show the power of metabolomics in comparing effects on metabolism of 28 different candidate treatments for Leishmaniasis (25 from the GSK Leishmania box, two analogues of Leishmania box series, and amphotericin B as a gold standard treatment), tested in the axenic amastigote form of Leishmania donovani. Capillary electrophoresis-mass spectrometry was applied to identify the metabolic profile of Leishmania donovani, and principal components analysis was used to cluster compounds on potential mode of action, offering a medium throughput screening approach in drug selection/prioritization. The comprehensive and sensitive nature of the data has also made detailed effects of each compound obtainable, providing a resource to assist in further mechanistic studies and prioritization of these compounds for the development of new antileishmanial drugs.

Using the infrastructure of a conditional cash transfer program to deliver a scalable integrated early child development program in Colombia: cluster randomized controlled trial.

PubMed

Attanasio, Orazio P; Fernández, Camila; Fitzsimons, Emla O A; Grantham-McGregor, Sally M; Meghir, Costas; Rubio-Codina, Marta

2014-09-29

To assess the effectiveness of an integrated early child development intervention, combining stimulation and micronutrient supplementation and delivered on a large scale in Colombia, for children's development, growth, and hemoglobin levels. Cluster randomized controlled trial, using a 2 × 2 factorial design, with municipalities assigned to one of four groups: psychosocial stimulation, micronutrient supplementation, combined intervention, or control. 96 municipalities in Colombia, located across eight of its 32 departments. 1420 children aged 12-24 months and their primary carers. Psychosocial stimulation (weekly home visits with play demonstrations), micronutrient sprinkles given daily, and both combined. All delivered by female community leaders for 18 months. Cognitive, receptive and expressive language, and fine and gross motor scores on the Bayley scales of infant development-III; height, weight, and hemoglobin levels measured at the baseline and end of intervention. Stimulation improved cognitive scores (adjusted for age, sex, testers, and baseline levels of outcomes) by 0.26 of a standard deviation (P=0.002). Stimulation also increased receptive language by 0.22 of a standard deviation (P=0.032). Micronutrient supplementation had no significant effect on any outcome and there was no interaction between the interventions. No intervention affected height, weight, or hemoglobin levels. Using the infrastructure of a national welfare program we implemented the integrated early child development intervention on a large scale and showed its potential for improving children's cognitive development. We found no effect of supplementation on developmental or health outcomes. Moreover, supplementation did not interact with stimulation. The implementation model for delivering stimulation suggests that it may serve as a promising blueprint for future policy on early childhood development.Trial registration Current Controlled trials ISRCTN18991160. © Attanasio et al 2014.

Eight-step method to build the clinical content of an evidence-based care pathway: the case for COPD exacerbation

PubMed Central

2012-01-01

Background Optimization of the clinical care process by integration of evidence-based knowledge is one of the active components in care pathways. When studying the impact of a care pathway by using a cluster-randomized design, standardization of the care pathway intervention is crucial. This methodology paper describes the development of the clinical content of an evidence-based care pathway for in-hospital management of chronic obstructive pulmonary disease (COPD) exacerbation in the context of a cluster-randomized controlled trial (cRCT) on care pathway effectiveness. Methods The clinical content of a care pathway for COPD exacerbation was developed based on recognized process design and guideline development methods. Subsequently, based on the COPD case study, a generalized eight-step method was designed to support the development of the clinical content of an evidence-based care pathway. Results A set of 38 evidence-based key interventions and a set of 24 process and 15 outcome indicators were developed in eight different steps. Nine Belgian multidisciplinary teams piloted both the set of key interventions and indicators. The key intervention set was judged by the teams as being valid and clinically applicable. In addition, the pilot study showed that the indicators were feasible for the involved clinicians and patients. Conclusions The set of 38 key interventions and the set of process and outcome indicators were found to be appropriate for the development and standardization of the clinical content of the COPD care pathway in the context of a cRCT on pathway effectiveness. The developed eight-step method may facilitate multidisciplinary teams caring for other patient populations in designing the clinical content of their future care pathways. PMID:23190552

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

Ben-Naim, Eli; Krapivsky, Paul

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

Improving clustering with metabolic pathway data.

PubMed

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a web-demo at http://fich.unl.edu.ar/sinc/web-demo/bsom-lite/. The source code and the data sets supporting the results of this article are available at http://sourceforge.net/projects/sourcesinc/files/bsom.

Two Suspected Worksite or Occupational Cancer Clusters Investigated Using the Cancer Data Registry and Multiple Primary Standardized Incidence Ratios in SEER *Stat-Idaho, 2013-2014.

PubMed

Rosenthal, Mariana; Johnson, Christopher J; Scoppa, Steve; Carter, Kris

2016-01-01

Investigations of suspected cancer clusters are resource intensive and rarely identify true clusters: among 428 publicly reported US investigations during 1990-2011, only 1 etiologic cluster was identified. In 2013, the Cancer Data Registry of Idaho (CDRI) was contacted regarding a suspected cancer cluster at a worksite (Cluster A) and among an occupational cohort (Cluster B). We investigated to determine whether these were true clusters. We derived investigation cohorts for Cluster A from facility-provided employee records and for Cluster B from professional licensing records. We used Registry PlusTM Link Plus to conduct probabilistic linkage of cohort members to the CDRI registry and completed matching through manual review by using LexisNexis®, Accurint®, and the Social Security Death Index. We calculated standardized incidence ratios (SIR) using the MP-SIR session type in SEER*Stat and Idaho and US referent populations. For Cluster A, we identified 34 cancer cases during 9,689 person-years; compared with Idaho and US rates, 95 percent CIs for SIRs included 1.0 for 24 of 24 primary site categories. For Cluster B, we identified 78 cancer cases during 15,154 person-years; compared with Idaho rates, 95 percent CI for SIRs included 1.0 for 23 of 24 primary site categories and was less than 1.0 for lung and bronchus cancers, and compared with US rates, 95 percent CI for SIRs included 1.0 for 22 of 24 primary site categories and was less than 1.0 for lung and bronchus and colorectal cancers. We identified no statistically significant excess in cancer incidence in either cohort. SEER*Stat's MP-SIR is an efficient tool for performing SIR assessments, a Centers for Disease Control and Prevention/Council of State and Territorial Epidemiologists-recommended step when investigating suspected cancer clusters.

System of HPC content archiving

NASA Astrophysics Data System (ADS)

Bogdanov, A.; Ivashchenko, A.

2017-12-01

This work is aimed to develop a system, that will effectively solve the problem of storing and analyzing files containing text data, by using modern software development tools, techniques and approaches. The main challenge of storing a large number of text documents defined at the problem formulation stage, have to be resolved with such functionality as full text search and document clustering depends on their contents. Main system features could be described with notions of distributed multilevel architecture, flexibility and interchangeability of components, achieved through the standard functionality incapsulation in independent executable modules.

Development of a Two-fluid Drag Law for Clustered Particles using Direct Numerical Simulation and Validation through Experiments

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

Gokaltun, Seckin; Munroe, Norman; Subramaniam, Shankar

2014-12-31

This study presents a new drag model, based on the cohesive inter-particle forces, implemented in the MFIX code. This new drag model combines an existing standard model in MFIX with a particle-based drag model based on a switching principle. Switches between the models in the computational domain occur where strong particle-to-particle cohesion potential is detected. Three versions of the new model were obtained by using one standard drag model in each version. Later, performance of each version was compared against available experimental data for a fluidized bed, published in the literature and used extensively by other researchers for validation purposes.more » In our analysis of the results, we first observed that standard models used in this research were incapable of producing closely matching results. Then, we showed for a simple case that a threshold is needed to be set on the solid volume fraction. This modification was applied to avoid non-physical results for the clustering predictions, when governing equation of the solid granular temperate was solved. Later, we used our hybrid technique and observed the capability of our approach in improving the numerical results significantly; however, improvement of the results depended on the threshold of the cohesive index, which was used in the switching procedure. Our results showed that small values of the threshold for the cohesive index could result in significant reduction of the computational error for all the versions of the proposed drag model. In addition, we redesigned an existing circulating fluidized bed (CFB) test facility in order to create validation cases for clustering regime of Geldart A type particles.« less

Analysis of partially observed clustered data using generalized estimating equations and multiple imputation

PubMed Central

Aloisio, Kathryn M.; Swanson, Sonja A.; Micali, Nadia; Field, Alison; Horton, Nicholas J.

2015-01-01

Clustered data arise in many settings, particularly within the social and biomedical sciences. As an example, multiple–source reports are commonly collected in child and adolescent psychiatric epidemiologic studies where researchers use various informants (e.g. parent and adolescent) to provide a holistic view of a subject’s symptomatology. Fitzmaurice et al. (1995) have described estimation of multiple source models using a standard generalized estimating equation (GEE) framework. However, these studies often have missing data due to additional stages of consent and assent required. The usual GEE is unbiased when missingness is Missing Completely at Random (MCAR) in the sense of Little and Rubin (2002). This is a strong assumption that may not be tenable. Other options such as weighted generalized estimating equations (WEEs) are computationally challenging when missingness is non–monotone. Multiple imputation is an attractive method to fit incomplete data models while only requiring the less restrictive Missing at Random (MAR) assumption. Previously estimation of partially observed clustered data was computationally challenging however recent developments in Stata have facilitated their use in practice. We demonstrate how to utilize multiple imputation in conjunction with a GEE to investigate the prevalence of disordered eating symptoms in adolescents reported by parents and adolescents as well as factors associated with concordance and prevalence. The methods are motivated by the Avon Longitudinal Study of Parents and their Children (ALSPAC), a cohort study that enrolled more than 14,000 pregnant mothers in 1991–92 and has followed the health and development of their children at regular intervals. While point estimates were fairly similar to the GEE under MCAR, the MAR model had smaller standard errors, while requiring less stringent assumptions regarding missingness. PMID:25642154

Just the right age: well-clustered exposure ages from a global glacial 10Be compilation

NASA Astrophysics Data System (ADS)

Heyman, Jakob; Margold, Martin

2017-04-01

Cosmogenic exposure dating has been used extensively for defining glacial chronologies, both in ice sheet and alpine settings, and the global set of published ages today reaches well beyond 10,000 samples. Over the last few years, a number of important developments have improved the measurements (with well-defined AMS standards) and exposure age calculations (with updated data and methods for calculating production rates), in the best case enabling high precision dating of past glacial events. A remaining problem, however, is the fact that a large portion of all dated samples have been affected by prior and/or incomplete exposure, yielding erroneous exposure ages under the standard assumptions. One way to address this issue is to only use exposure ages that can be confidently considered as unaffected by prior/incomplete exposure, such as groups of samples with statistically identical ages. Here we use objective statistical criteria to identify groups of well-clustered exposure ages from the global glacial "expage" 10Be compilation. Out of ˜1700 groups with at least 3 individual samples ˜30% are well-clustered, increasing to ˜45% if allowing outlier rejection of a maximum of 1/3 of the samples (still requiring a minimum of 3 well-clustered ages). The dataset of well-clustered ages is heavily dominated by ages <30 ka, showing that well-defined cosmogenic chronologies primarily exist for the last glaciation. We observe a large-scale global synchronicity in the timing of the last deglaciation from ˜20 to 10 ka. There is also a general correlation between the timing of deglaciation and latitude (or size of the individual ice mass), with earlier deglaciation in lower latitudes and later deglaciation towards the poles. Grouping the data into regions and comparing with available paleoclimate data we can start to untangle regional differences in the last deglaciation and the climate events controlling the ice mass loss. The extensive dataset and the statistical analysis enables an unprecedented global view on the last deglaciation.

Acoustic Disturbances in Galaxy Clusters

NASA Astrophysics Data System (ADS)

Zweibel, Ellen G.; Mirnov, Vladimir V.; Ruszkowski, Mateusz; Reynolds, Christopher S.; Yang, H.-Y. Karen; Fabian, Andrew C.

2018-05-01

Galaxy cluster cores are pervaded by hot gas which radiates at far too high a rate to maintain any semblance of a steady state; this is referred to as the cooling flow problem. Of the many heating mechanisms that have been proposed to balance radiative cooling, one of the most attractive is the dissipation of acoustic waves generated by active galactic nuclei. Fabian et al. showed that if the waves are nearly adiabatic, wave damping due to heat conduction and viscosity must be well below standard Coulomb rates in order to allow the waves to propagate throughout the core. Because of the importance of this result, we have revisited wave dissipation under galaxy cluster conditions in a way that accounts for the self-limiting nature of dissipation by electron thermal conduction, allows the electron and ion temperature perturbations in the waves to evolve separately, and estimates kinetic effects by comparing to a semicollisionless theory. While these effects considerably enlarge the toolkit for analyzing observations of wavelike structures and developing a quantitative theory for wave heating, the drastic reduction of transport coefficients proposed in Fabian et al. remains the most viable path to acoustic wave heating of galaxy cluster cores.

Penalized unsupervised learning with outliers

PubMed Central

Witten, Daniela M.

2013-01-01

We consider the problem of performing unsupervised learning in the presence of outliers – that is, observations that do not come from the same distribution as the rest of the data. It is known that in this setting, standard approaches for unsupervised learning can yield unsatisfactory results. For instance, in the presence of severe outliers, K-means clustering will often assign each outlier to its own cluster, or alternatively may yield distorted clusters in order to accommodate the outliers. In this paper, we take a new approach to extending existing unsupervised learning techniques to accommodate outliers. Our approach is an extension of a recent proposal for outlier detection in the regression setting. We allow each observation to take on an “error” term, and we penalize the errors using a group lasso penalty in order to encourage most of the observations’ errors to exactly equal zero. We show that this approach can be used in order to develop extensions of K-means clustering and principal components analysis that result in accurate outlier detection, as well as improved performance in the presence of outliers. These methods are illustrated in a simulation study and on two gene expression data sets, and connections with M-estimation are explored. PMID:23875057

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.

A pyrosequencing assay for the quantitative methylation analysis of the PCDHB gene cluster, the major factor in neuroblastoma methylator phenotype.

PubMed

Banelli, Barbara; Brigati, Claudio; Di Vinci, Angela; Casciano, Ida; Forlani, Alessandra; Borzì, Luana; Allemanni, Giorgio; Romani, Massimo

2012-03-01

Epigenetic alterations are hallmarks of cancer and powerful biomarkers, whose clinical utilization is made difficult by the absence of standardization and of common methods of data interpretation. The coordinate methylation of many loci in cancer is defined as 'CpG island methylator phenotype' (CIMP) and identifies clinically distinct groups of patients. In neuroblastoma (NB), CIMP is defined by a methylation signature, which includes different loci, but its predictive power on outcome is entirely recapitulated by the PCDHB cluster only. We have developed a robust and cost-effective pyrosequencing-based assay that could facilitate the clinical application of CIMP in NB. This assay permits the unbiased simultaneous amplification and sequencing of 17 out of 19 genes of the PCDHB cluster for quantitative methylation analysis, taking into account all the sequence variations. As some of these variations were at CpG doublets, we bypassed the data interpretation conducted by the methylation analysis software to assign the corrected methylation value at these sites. The final result of the assay is the mean methylation level of 17 gene fragments in the protocadherin B cluster (PCDHB) cluster. We have utilized this assay to compare the methylation levels of the PCDHB cluster between high-risk and very low-risk NB patients, confirming the predictive value of CIMP. Our results demonstrate that the pyrosequencing-based assay herein described is a powerful instrument for the analysis of this gene cluster that may simplify the data comparison between different laboratories and, in perspective, could facilitate its clinical application. Furthermore, our results demonstrate that, in principle, pyrosequencing can be efficiently utilized for the methylation analysis of gene clusters with high internal homologies.

Testing and evaluation of sign support with cluster attachments.

DOT National Transportation Integrated Search

1990-04-01

Two full-scale crash tests were conducted on the Louisiana two-post, inclined, slip-base sign assembly with cluster sign attachment. These two tests were performed and evaluated in accordance with guidelines under NCHRP Report 230 and standards estab...

Cold dark energy constraints from the abundance of galaxy clusters

DOE PAGES

Heneka, Caroline; Rapetti, David; Cataneo, Matteo; ...

2017-10-05

We constrain cold dark energy of negligible sound speed using galaxy cluster abundance observations. In contrast to standard quasi-homogeneous dark energy, negligible sound speed implies clustering of the dark energy fluid at all scales, allowing us to measure the effects of dark energy perturbations at cluster scales. We compare those models and set the stage for using non-linear information from semi-analytical modelling in cluster growth data analyses. For this, we recalibrate the halo mass function with non-linear characteristic quantities, the spherical collapse threshold and virial overdensity, that account for model and redshift-dependent behaviours, as well as an additional mass contributionmore » for cold dark energy. Here in this paper, we present the first constraints from this cold dark matter plus cold dark energy mass function using our cluster abundance likelihood, which self-consistently accounts for selection effects, covariances and systematic uncertainties. We combine cluster growth data with cosmic microwave background, supernovae Ia and baryon acoustic oscillation data, and find a shift between cold versus quasi-homogeneous dark energy of up to 1σ. We make a Fisher matrix forecast of constraints attainable with cluster growth data from the ongoing Dark Energy Survey (DES). For DES, we predict ~ 50 percent tighter constraints on (Ωm, w) for cold dark energy versus wCDM models, with the same free parameters. Overall, we show that cluster abundance analyses are sensitive to cold dark energy, an alternative, viable model that should be routinely investigated alongside the standard dark energy scenario.« less

Cold dark energy constraints from the abundance of galaxy clusters

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

Heneka, Caroline; Rapetti, David; Cataneo, Matteo

We constrain cold dark energy of negligible sound speed using galaxy cluster abundance observations. In contrast to standard quasi-homogeneous dark energy, negligible sound speed implies clustering of the dark energy fluid at all scales, allowing us to measure the effects of dark energy perturbations at cluster scales. We compare those models and set the stage for using non-linear information from semi-analytical modelling in cluster growth data analyses. For this, we recalibrate the halo mass function with non-linear characteristic quantities, the spherical collapse threshold and virial overdensity, that account for model and redshift-dependent behaviours, as well as an additional mass contributionmore » for cold dark energy. Here in this paper, we present the first constraints from this cold dark matter plus cold dark energy mass function using our cluster abundance likelihood, which self-consistently accounts for selection effects, covariances and systematic uncertainties. We combine cluster growth data with cosmic microwave background, supernovae Ia and baryon acoustic oscillation data, and find a shift between cold versus quasi-homogeneous dark energy of up to 1σ. We make a Fisher matrix forecast of constraints attainable with cluster growth data from the ongoing Dark Energy Survey (DES). For DES, we predict ~ 50 percent tighter constraints on (Ωm, w) for cold dark energy versus wCDM models, with the same free parameters. Overall, we show that cluster abundance analyses are sensitive to cold dark energy, an alternative, viable model that should be routinely investigated alongside the standard dark energy scenario.« less

Assessing the feasibility of interrupting the transmission of soil-transmitted helminths through mass drug administration: The DeWorm3 cluster randomized trial protocol

PubMed Central

Ajjampur, Sitara S. Rao; Anderson, Roy M.; Bailey, Robin; Gardiner, Iain; Halliday, Katherine E.; Ibikounle, Moudachirou; Kalua, Khumbo; Kang, Gagandeep; Littlewood, D. Timothy J.; Luty, Adrian J. F.; Means, Arianna Rubin; Oswald, William; Pullan, Rachel L.; Sarkar, Rajiv; Schär, Fabian; Szpiro, Adam; Truscott, James E.; Werkman, Marleen; Yard, Elodie; Walson, Judd L.

2018-01-01

Current control strategies for soil-transmitted helminths (STH) emphasize morbidity control through mass drug administration (MDA) targeting preschool- and school-age children, women of childbearing age and adults in certain high-risk occupations such as agricultural laborers or miners. This strategy is effective at reducing morbidity in those treated but, without massive economic development, it is unlikely it will interrupt transmission. MDA will therefore need to continue indefinitely to maintain benefit. Mathematical models suggest that transmission interruption may be achievable through MDA alone, provided that all age groups are targeted with high coverage. The DeWorm3 Project will test the feasibility of interrupting STH transmission using biannual MDA targeting all age groups. Study sites (population ≥80,000) have been identified in Benin, Malawi and India. Each site will be divided into 40 clusters, to be randomized 1:1 to three years of twice-annual community-wide MDA or standard-of-care MDA, typically annual school-based deworming. Community-wide MDA will be delivered door-to-door, while standard-of-care MDA will be delivered according to national guidelines. The primary outcome is transmission interruption of the STH species present at each site, defined as weighted cluster-level prevalence ≤2% by quantitative polymerase chain reaction (qPCR), 24 months after the final round of MDA. Secondary outcomes include the endline prevalence of STH, overall and by species, and the endline prevalence of STH among children under five as an indicator of incident infections. Secondary analyses will identify cluster-level factors associated with transmission interruption. Prevalence will be assessed using qPCR of stool samples collected from a random sample of cluster residents at baseline, six months after the final round of MDA and 24 months post-MDA. A smaller number of individuals in each cluster will be followed with annual sampling to monitor trends in prevalence and reinfection throughout the trial. Trial registration ClinicalTrials.gov NCT03014167 PMID:29346377

Packing Fraction of a Two-dimensional Eden Model with Random-Sized Particles

NASA Astrophysics Data System (ADS)

Kobayashi, Naoki; Yamazaki, Hiroshi

2018-01-01

We have performed a numerical simulation of a two-dimensional Eden model with random-size particles. In the present model, the particle radii are generated from a Gaussian distribution with mean μ and standard deviation σ. First, we have examined the bulk packing fraction for the Eden cluster and investigated the effects of the standard deviation and the total number of particles NT. We show that the bulk packing fraction depends on the number of particles and the standard deviation. In particular, for the dependence on the standard deviation, we have determined the asymptotic value of the bulk packing fraction in the limit of the dimensionless standard deviation. This value is larger than the packing fraction obtained in a previous study of the Eden model with uniform-size particles. Secondly, we have investigated the packing fraction of the entire Eden cluster including the effect of the interface fluctuation. We find that the entire packing fraction depends on the number of particles while it is independent of the standard deviation, in contrast to the bulk packing fraction. In a similar way to the bulk packing fraction, we have obtained the asymptotic value of the entire packing fraction in the limit NT → ∞. The obtained value of the entire packing fraction is smaller than that of the bulk value. This fact suggests that the interface fluctuation of the Eden cluster influences the packing fraction.

Geospatial data infrastructure: The development of metadata for geo-information in China

NASA Astrophysics Data System (ADS)

Xu, Baiquan; Yan, Shiqiang; Wang, Qianju; Lian, Jian; Wu, Xiaoping; Ding, Keyong

2014-03-01

Stores of geoscience records are in constant flux. These stores are continually added to by new information, ideas and data, which are frequently revised. The geoscience record is in restrained by human thought and technology for handling information. Conventional methods strive, with limited success, to maintain geoscience records which are readily susceptible and renewable. The information system must adapt to the diversity of ideas and data in geoscience and their changes through time. In China, more than 400,000 types of important geological data are collected and produced in geological work during the last two decades, including oil, natural gas and marine data, mine exploration, geophysical, geochemical, remote sensing and important local geological survey and research reports. Numerous geospatial databases are formed and stored in National Geological Archives (NGA) with available formats of MapGIS, ArcGIS, ArcINFO, Metalfile, Raster, SQL Server, Access and JPEG. But there is no effective way to warrant that the quality of information is adequate in theory and practice for decision making. The need for fast, reliable, accurate and up-to-date information by providing the Geographic Information System (GIS) communities are becoming insistent for all geoinformation producers and users in China. Since 2010, a series of geoinformation projects have been carried out under the leadership of the Ministry of Land and Resources (MLR), including (1) Integration, update and maintenance of geoinformation databases; (2) Standards research on clusterization and industrialization of information services; (3) Platform construction of geological data sharing; (4) Construction of key borehole databases; (5) Product development of information services. "Nine-System" of the basic framework has been proposed for the development and improvement of the geospatial data infrastructure, which are focused on the construction of the cluster organization, cluster service, convergence, database, product, policy, technology, standard and infrastructure systems. The development of geoinformation stores and services put forward a need for Geospatial Data Infrastructure (GDI) in China. In this paper, some of the ideas envisaged into the development of metadata in China are discussed.

Sejong Open Cluster Survey (SOS). 0. Target Selection and Data Analysis

NASA Astrophysics Data System (ADS)

Sung, Hwankyung; Lim, Beomdu; Bessell, Michael S.; Kim, Jinyoung S.; Hur, Hyeonoh; Chun, Moo-Young; Park, Byeong-Gon

2013-06-01

Star clusters are superb astrophysical laboratories containing cospatial and coeval samples of stars with similar chemical composition. We initiate the Sejong Open cluster Survey (SOS) - a project dedicated to providing homogeneous photometry of a large number of open clusters in the SAAO Johnson-Cousins' UBVI system. To achieve our main goal, we pay much attention to the observation of standard stars in order to reproduce the SAAO standard system. Many of our targets are relatively small sparse clusters that escaped previous observations. As clusters are considered building blocks of the Galactic disk, their physical properties such as the initial mass function, the pattern of mass segregation, etc. give valuable information on the formation and evolution of the Galactic disk. The spatial distribution of young open clusters will be used to revise the local spiral arm structure of the Galaxy. In addition, the homogeneous data can also be used to test stellar evolutionary theory, especially concerning rare massive stars. In this paper we present the target selection criteria, the observational strategy for accurate photometry, and the adopted calibrations for data analysis such as color-color relations, zero-age main sequence relations, Sp - M_V relations, Sp - T_{eff} relations, Sp - color relations, and T_{eff} - BC relations. Finally we provide some data analysis such as the determination of the reddening law, the membership selection criteria, and distance determination.

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

A search for X-ray bright distant clusters of galaxies

NASA Technical Reports Server (NTRS)

Nichol, R. C.; Ulmer, M. P.; Kron, R. G.; Wirth, G. D.; Koo, D. C.

1994-01-01

We present the results of a search for X-ray luminous distant clusters of galaxies. We found extended X-ray emission characteristic of a cluster toward two of our candidate clusters of galaxies. They both have a luminosity in the ROSAT bandpass of approximately equals 10(exp 44) ergs/s and a redshift greater than 0.5; thus making them two of the most distant X-ray clusters ever observed. Furthermore, we show that both clusters are optically rich and have a known radio source associated with them. We compare our result with other recent searches for distant X-ray luminous clusters and present a lower limit of 1.2 x 10(exp -7)/cu Mpc for the number density of such high-redshift clusters. This limit is consistent with the expected abundance of such clusters in a standard (b = 2) cold dark matter universe. Finally, our clusters provide important high-redshift targets for further study into the origin and evolution of massive clusters of galaxies.

[Helgoland (Germany): hemogenetic study of an island population].

PubMed

Schmidt, H D; Scheil, H G; Winkelbauer, S

2001-03-01

24 haemogenetic markers (5 erythrocyte antigenes, 6 polymorphisms of serum proteins, 12 polymorphisms of red cell enzymes) had been studied in up to 80 individuals from the island of Helgoland (Germany). The cluster analysis separates clearly the Helgoland sample from the neighbouring populations as well as from European standard data. This special position is interpreted partly by genetic peculiarities developed in the course of time, partly as a consequence of genetic drift.

Progress in adapting k-NN methods for forest mapping and estimation using the new annual Forest Inventory and Analysis data

Treesearch

Reija Haapanen; Kimmo Lehtinen; Jukka Miettinen; Marvin E. Bauer; Alan R. Ek

2002-01-01

The k-nearest neighbor (k-NN) method has been undergoing development and testing for applications with USDA Forest Service Forest Inventory and Analysis (FIA) data in Minnesota since 1997. Research began using the 1987-1990 FIA inventory of the state, the then standard 10-point cluster plots, and Landsat TM imagery. In the past year, research has moved to examine...

Gaia Data Release 1. Open cluster astrometry: performance, limitations, and future prospects

NASA Astrophysics Data System (ADS)

Gaia Collaboration; van Leeuwen, F.; Vallenari, A.; Jordi, C.; Lindegren, L.; Bastian, U.; Prusti, T.; de Bruijne, J. H. J.; Brown, A. G. A.; Babusiaux, C.; Bailer-Jones, C. A. L.; Biermann, M.; Evans, D. W.; Eyer, L.; Jansen, F.; Klioner, S. A.; Lammers, U.; Luri, X.; Mignard, F.; Panem, C.; Pourbaix, D.; Randich, S.; Sartoretti, P.; Siddiqui, H. I.; Soubiran, C.; Valette, V.; Walton, N. A.; Aerts, C.; Arenou, F.; Cropper, M.; Drimmel, R.; Høg, E.; Katz, D.; Lattanzi, M. G.; O'Mullane, W.; Grebel, E. K.; Holland, A. D.; Huc, C.; Passot, X.; Perryman, M.; Bramante, L.; Cacciari, C.; Castañeda, J.; Chaoul, L.; Cheek, N.; De Angeli, F.; Fabricius, C.; Guerra, R.; Hernández, J.; Jean-Antoine-Piccolo, A.; Masana, E.; Messineo, R.; Mowlavi, N.; Nienartowicz, K.; Ordóñez-Blanco, D.; Panuzzo, P.; Portell, J.; Richards, P. J.; Riello, M.; Seabroke, G. M.; Tanga, P.; Thévenin, F.; Torra, J.; Els, S. G.; Gracia-Abril, G.; Comoretto, G.; Garcia-Reinaldos, M.; Lock, T.; Mercier, E.; Altmann, M.; Andrae, R.; Astraatmadja, T. L.; Bellas-Velidis, I.; Benson, K.; Berthier, J.; Blomme, R.; Busso, G.; Carry, B.; Cellino, A.; Clementini, G.; Cowell, S.; Creevey, O.; Cuypers, J.; Davidson, M.; De Ridder, J.; de Torres, A.; Delchambre, L.; Dell'Oro, A.; Ducourant, C.; Frémat, Y.; García-Torres, M.; Gosset, E.; Halbwachs, J.-L.; Hambly, N. C.; Harrison, D. L.; Hauser, M.; Hestroffer, D.; Hodgkin, S. T.; Huckle, H. E.; Hutton, A.; Jasniewicz, G.; Jordan, S.; Kontizas, M.; Korn, A. J.; Lanzafame, A. C.; Manteiga, M.; Moitinho, A.; Muinonen, K.; Osinde, J.; Pancino, E.; Pauwels, T.; Petit, J.-M.; Recio-Blanco, A.; Robin, A. C.; Sarro, L. M.; Siopis, C.; Smith, M.; Smith, K. W.; Sozzetti, A.; Thuillot, W.; van Reeven, W.; Viala, Y.; Abbas, U.; Abreu Aramburu, A.; Accart, S.; Aguado, J. J.; Allan, P. M.; Allasia, W.; Altavilla, G.; Álvarez, M. A.; Alves, J.; Anderson, R. I.; Andrei, A. H.; Anglada Varela, E.; Antiche, E.; Antoja, T.; Antón, S.; Arcay, B.; Bach, N.; Baker, S. G.; Balaguer-Núñez, L.; Barache, C.; Barata, C.; Barbier, A.; Barblan, F.; Barrado y Navascués, D.; Barros, M.; Barstow, M. A.; Becciani, U.; Bellazzini, M.; Bello García, A.; Belokurov, V.; Bendjoya, P.; Berihuete, A.; Bianchi, L.; Bienaymé, O.; Billebaud, F.; Blagorodnova, N.; Blanco-Cuaresma, S.; Boch, T.; Bombrun, A.; Borrachero, R.; Bouquillon, S.; Bourda, G.; Bouy, H.; Bragaglia, A.; Breddels, M. A.; Brouillet, N.; Brüsemeister, T.; Bucciarelli, B.; Burgess, P.; Burgon, R.; Burlacu, A.; Busonero, D.; Buzzi, R.; Caffau, E.; Cambras, J.; Campbell, H.; Cancelliere, R.; Cantat-Gaudin, T.; Carlucci, T.; Carrasco, J. M.; Castellani, M.; Charlot, P.; Charnas, J.; Chiavassa, A.; Clotet, M.; Cocozza, G.; Collins, R. S.; Costigan, G.; Crifo, F.; Cross, N. J. G.; Crosta, M.; Crowley, C.; Dafonte, C.; Damerdji, Y.; Dapergolas, A.; David, P.; David, M.; De Cat, P.; de Felice, F.; de Laverny, P.; De Luise, F.; De March, R.; de Martino, D.; de Souza, R.; Debosscher, J.; del Pozo, E.; Delbo, M.; Delgado, A.; Delgado, H. E.; Di Matteo, P.; Diakite, S.; Distefano, E.; Dolding, C.; Dos Anjos, S.; Drazinos, P.; Durán, J.; Dzigan, Y.; Edvardsson, B.; Enke, H.; Evans, N. W.; Eynard Bontemps, G.; Fabre, C.; Fabrizio, M.; Faigler, S.; Falcão, A. J.; Farràs Casas, M.; Federici, L.; Fedorets, G.; Fernández-Hernández, J.; Fernique, P.; Fienga, A.; Figueras, F.; Filippi, F.; Findeisen, K.; Fonti, A.; Fouesneau, M.; Fraile, E.; Fraser, M.; Fuchs, J.; Gai, M.; Galleti, S.; Galluccio, L.; Garabato, D.; García-Sedano, F.; Garofalo, A.; Garralda, N.; Gavras, P.; Gerssen, J.; Geyer, R.; Gilmore, G.; Girona, S.; Giuffrida, G.; Gomes, M.; González-Marcos, A.; González-Núñez, J.; González-Vidal, J. J.; Granvik, M.; Guerrier, A.; Guillout, P.; Guiraud, J.; Gúrpide, A.; Gutiérrez-Sánchez, R.; Guy, L. P.; Haigron, R.; Hatzidimitriou, D.; Haywood, M.; Heiter, U.; Helmi, A.; Hobbs, D.; Hofmann, W.; Holl, B.; Holland, G.; Hunt, J. A. S.; Hypki, A.; Icardi, V.; Irwin, M.; Jevardat de Fombelle, G.; Jofré, P.; Jonker, P. G.; Jorissen, A.; Julbe, F.; Karampelas, A.; Kochoska, A.; Kohley, R.; Kolenberg, K.; Kontizas, E.; Koposov, S. E.; Kordopatis, G.; Koubsky, P.; Krone-Martins, A.; Kudryashova, M.; Kull, I.; Bachchan, R. K.; Lacoste-Seris, F.; Lanza, A. F.; Lavigne, J.-B.; Le Poncin-Lafitte, C.; Lebreton, Y.; Lebzelter, T.; Leccia, S.; Leclerc, N.; Lecoeur-Taibi, I.; Lemaitre, V.; Lenhardt, H.; Leroux, F.; Liao, S.; Licata, E.; Lindstrøm, H. E. P.; Lister, T. A.; Livanou, E.; Lobel, A.; Löffler, W.; López, M.; Lorenz, D.; MacDonald, I.; Magalhães Fernandes, T.; Managau, S.; Mann, R. G.; Mantelet, G.; Marchal, O.; Marchant, J. M.; Marconi, M.; Marinoni, S.; Marrese, P. M.; Marschalkó, G.; Marshall, D. J.; Martín-Fleitas, J. M.; Martino, M.; Mary, N.; Matijevič, G.; Mazeh, T.; McMillan, P. J.; Messina, S.; Michalik, D.; Millar, N. R.; Miranda, B. M. H.; Molina, D.; Molinaro, R.; Molinaro, M.; Molnár, L.; Moniez, M.; Montegriffo, P.; Mor, R.; Mora, A.; Morbidelli, R.; Morel, T.; Morgenthaler, S.; Morris, D.; Mulone, A. F.; Muraveva, T.; Musella, I.; Narbonne, J.; Nelemans, G.; Nicastro, L.; Noval, L.; Ordénovic, C.; Ordieres-Meré, J.; Osborne, P.; Pagani, C.; Pagano, I.; Pailler, F.; Palacin, H.; Palaversa, L.; Parsons, P.; Pecoraro, M.; Pedrosa, R.; Pentikäinen, H.; Pichon, B.; Piersimoni, A. M.; Pineau, F.-X.; Plachy, E.; Plum, G.; Poujoulet, E.; Prša, A.; Pulone, L.; Ragaini, S.; Rago, S.; Rambaux, N.; Ramos-Lerate, M.; Ranalli, P.; Rauw, G.; Read, A.; Regibo, S.; Reylé, C.; Ribeiro, R. A.; Rimoldini, L.; Ripepi, V.; Riva, A.; Rixon, G.; Roelens, M.; Romero-Gómez, M.; Rowell, N.; Royer, F.; Ruiz-Dern, L.; Sadowski, G.; Sagristà Sellés, T.; Sahlmann, J.; Salgado, J.; Salguero, E.; Sarasso, M.; Savietto, H.; Schultheis, M.; Sciacca, E.; Segol, M.; Segovia, J. C.; Segransan, D.; Shih, I.-C.; Smareglia, R.; Smart, R. L.; Solano, E.; Solitro, F.; Sordo, R.; Soria Nieto, S.; Souchay, J.; Spagna, A.; Spoto, F.; Stampa, U.; Steele, I. A.; Steidelmüller, H.; Stephenson, C. A.; Stoev, H.; Suess, F. F.; Süveges, M.; Surdej, J.; Szabados, L.; Szegedi-Elek, E.; Tapiador, D.; Taris, F.; Tauran, G.; Taylor, M. B.; Teixeira, R.; Terrett, D.; Tingley, B.; Trager, S. C.; Turon, C.; Ulla, A.; Utrilla, E.; Valentini, G.; van Elteren, A.; Van Hemelryck, E.; vanLeeuwen, M.; Varadi, M.; Vecchiato, A.; Veljanoski, J.; Via, T.; Vicente, D.; Vogt, S.; Voss, H.; Votruba, V.; Voutsinas, S.; Walmsley, G.; Weiler, M.; Weingrill, K.; Wevers, T.; Wyrzykowski, Ł.; Yoldas, A.; Žerjal, M.; Zucker, S.; Zurbach, C.; Zwitter, T.; Alecu, A.; Allen, M.; Allende Prieto, C.; Amorim, A.; Anglada-Escudé, G.; Arsenijevic, V.; Azaz, S.; Balm, P.; Beck, M.; Bernstein, H.-H.; Bigot, L.; Bijaoui, A.; Blasco, C.; Bonfigli, M.; Bono, G.; Boudreault, S.; Bressan, A.; Brown, S.; Brunet, P.-M.; Bunclark, P.; Buonanno, R.; Butkevich, A. G.; Carret, C.; Carrion, C.; Chemin, L.; Chéreau, F.; Corcione, L.; Darmigny, E.; de Boer, K. S.; de Teodoro, P.; de Zeeuw, P. T.; Delle Luche, C.; Domingues, C. D.; Dubath, P.; Fodor, F.; Frézouls, B.; Fries, A.; Fustes, D.; Fyfe, D.; Gallardo, E.; Gallegos, J.; Gardiol, D.; Gebran, M.; Gomboc, A.; Gómez, A.; Grux, E.; Gueguen, A.; Heyrovsky, A.; Hoar, J.; Iannicola, G.; Isasi Parache, Y.; Janotto, A.-M.; Joliet, E.; Jonckheere, A.; Keil, R.; Kim, D.-W.; Klagyivik, P.; Klar, J.; Knude, J.; Kochukhov, O.; Kolka, I.; Kos, J.; Kutka, A.; Lainey, V.; LeBouquin, D.; Liu, C.; Loreggia, D.; Makarov, V. V.; Marseille, M. G.; Martayan, C.; Martinez-Rubi, O.; Massart, B.; Meynadier, F.; Mignot, S.; Munari, U.; Nguyen, A.-T.; Nordlander, T.; O'Flaherty, K. S.; Ocvirk, P.; Olias Sanz, A.; Ortiz, P.; Osorio, J.; Oszkiewicz, D.; Ouzounis, A.; Palmer, M.; Park, P.; Pasquato, E.; Peltzer, C.; Peralta, J.; Péturaud, F.; Pieniluoma, T.; Pigozzi, E.; Poels, J.; Prat, G.; Prod'homme, T.; Raison, F.; Rebordao, J. M.; Risquez, D.; Rocca-Volmerange, B.; Rosen, S.; Ruiz-Fuertes, M. I.; Russo, F.; Sembay, S.; Serraller Vizcaino, I.; Short, A.; Siebert, A.; Silva, H.; Sinachopoulos, D.; Slezak, E.; Soffel, M.; Sosnowska, D.; Straižys, V.; ter Linden, M.; Terrell, D.; Theil, S.; Tiede, C.; Troisi, L.; Tsalmantza, P.; Tur, D.; Vaccari, M.; Vachier, F.; Valles, P.; Van Hamme, W.; Veltz, L.; Virtanen, J.; Wallut, J.-M.; Wichmann, R.; Wilkinson, M. I.; Ziaeepour, H.; Zschocke, S.

2017-05-01

Context. The first Gaia Data Release contains the Tycho-Gaia Astrometric Solution (TGAS). This is a subset of about 2 million stars for which, besides the position and photometry, the proper motion and parallax are calculated using Hipparcos and Tycho-2 positions in 1991.25 as prior information. Aims: We investigate the scientific potential and limitations of the TGAS component by means of the astrometric data for open clusters. Methods: Mean cluster parallax and proper motion values are derived taking into account the error correlations within the astrometric solutions for individual stars, an estimate of the internal velocity dispersion in the cluster, and, where relevant, the effects of the depth of the cluster along the line of sight. Internal consistency of the TGAS data is assessed. Results: Values given for standard uncertainties are still inaccurate and may lead to unrealistic unit-weight standard deviations of least squares solutions for cluster parameters. Reconstructed mean cluster parallax and proper motion values are generally in very good agreement with earlier Hipparcos-based determination, although the Gaia mean parallax for the Pleiades is a significant exception. We have no current explanation for that discrepancy. Most clusters are observed to extend to nearly 15 pc from the cluster centre, and it will be up to future Gaia releases to establish whether those potential cluster-member stars are still dynamically bound to the clusters. Conclusions: The Gaia DR1 provides the means to examine open clusters far beyond their more easily visible cores, and can provide membership assessments based on proper motions and parallaxes. A combined HR diagram shows the same features as observed before using the Hipparcos data, with clearly increased luminosities for older A and F dwarfs. Tables D.1 to D.19 are also 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/A19

Emergency surgery data and documentation reporting forms for sudden-onset humanitarian crises, natural disasters and the existing burden of surgical disease.

PubMed

Burkle, Frederick M; Nickerson, Jason W; von Schreeb, Johan; Redmond, Anthony D; McQueen, Kelly A; Norton, Ian; Roy, Nobhojit

2012-12-01

Following large-scale disasters and major complex emergencies, especially in resource-poor settings, emergency surgery is practiced by Foreign Medical Teams (FMTs) sent by governmental and non-governmental organizations (NGOs). These surgical experiences have not yielded an appropriate standardized collection of data and reporting to meet standards required by national authorities, the World Health Organization, and the Inter-Agency Standing Committee's Global Health Cluster. Utilizing the 2011 International Data Collection guidelines for surgery initiated by Médecins Sans Frontières, the authors of this paper developed an individual patient-centric form and an International Standard Reporting Template for Surgical Care to record data for victims of a disaster as well as the co-existing burden of surgical disease within the affected community. The data includes surgical patient outcomes and perioperative mortality, along with referrals for rehabilitation, mental health and psychosocial care. The purpose of the standard data format is fourfold: (1) to ensure that all surgical providers, especially from indigenous first responder teams and others performing emergency surgery, from national and international (Foreign) medical teams, contribute relevant and purposeful reporting; (2) to provide universally acceptable forms that meet the minimal needs of both national authorities and the Health Cluster; (3) to increase transparency and accountability, contributing to improved humanitarian coordination; and (4) to facilitate a comprehensive review of services provided to those affected by the crisis.

Clustering of Variables for Mixed Data

NASA Astrophysics Data System (ADS)

Saracco, J.; Chavent, M.

2016-05-01

This chapter presents clustering of variables which aim is to lump together strongly related variables. The proposed approach works on a mixed data set, i.e. on a data set which contains numerical variables and categorical variables. Two algorithms of clustering of variables are described: a hierarchical clustering and a k-means type clustering. A brief description of PCAmix method (that is a principal component analysis for mixed data) is provided, since the calculus of the synthetic variables summarizing the obtained clusters of variables is based on this multivariate method. Finally, the R packages ClustOfVar and PCAmixdata are illustrated on real mixed data. The PCAmix and ClustOfVar approaches are first used for dimension reduction (step 1) before applying in step 2 a standard clustering method to obtain groups of individuals.

Detection of Anomalies in Hydrometric Data Using Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Lauzon, N.; Lence, B. J.

2002-12-01

This work focuses on the detection of anomalies in hydrometric data sequences, such as 1) outliers, which are individual data having statistical properties that differ from those of the overall population; 2) shifts, which are sudden changes over time in the statistical properties of the historical records of data; and 3) trends, which are systematic changes over time in the statistical properties. For the purpose of the design and management of water resources systems, it is important to be aware of these anomalies in hydrometric data, for they can induce a bias in the estimation of water quantity and quality parameters. These anomalies may be viewed as specific patterns affecting the data, and therefore pattern recognition techniques can be used for identifying them. However, the number of possible patterns is very large for each type of anomaly and consequently large computing capacities are required to account for all possibilities using the standard statistical techniques, such as cluster analysis. Artificial intelligence techniques, such as the Kohonen neural network and fuzzy c-means, are clustering techniques commonly used for pattern recognition in several areas of engineering and have recently begun to be used for the analysis of natural systems. They require much less computing capacity than the standard statistical techniques, and therefore are well suited for the identification of outliers, shifts and trends in hydrometric data. This work constitutes a preliminary study, using synthetic data representing hydrometric data that can be found in Canada. The analysis of the results obtained shows that the Kohonen neural network and fuzzy c-means are reasonably successful in identifying anomalies. This work also addresses the problem of uncertainties inherent to the calibration procedures that fit the clusters to the possible patterns for both the Kohonen neural network and fuzzy c-means. Indeed, for the same database, different sets of clusters can be established with these calibration procedures. A simple method for analyzing uncertainties associated with the Kohonen neural network and fuzzy c-means is developed here. The method combines the results from several sets of clusters, either from the Kohonen neural network or fuzzy c-means, so as to provide an overall diagnosis as to the identification of outliers, shifts and trends. The results indicate an improvement in the performance for identifying anomalies when the method of combining cluster sets is used, compared with when only one cluster set is used.

Hot gas in the cold dark matter scenario: X-ray clusters from a high-resolution numerical simulation

NASA Technical Reports Server (NTRS)

Kang, Hyesung; Cen, Renyue; Ostriker, Jeremiah P.; Ryu, Dongsu

1994-01-01

A new, three-dimensional, shock-capturing hydrodynamic code is utilized to determine the distribution of hot gas in a standard cold dark matter (CDM) model of the universe. Periodic boundary conditions are assumed: a box with size 85 h(exp -1) Mpc having cell size 0.31 h(exp -1) Mpc is followed in a simulation with 270(exp 3) = 10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, sigma(sub 8) = 1.05, omega(sub b) = 0.06, and assuming h = 0.5, we find the X-ray-emitting clusters and compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. We find that most of the total X-ray emissivity in our box originates in a relatively small number of identifiable clusters which occupy approximately 10(exp -3) of the box volume. This standard CDM model, normalized to COBE, produces approximately 5 times too much emission from clusters having L(sub x) is greater than 10(exp 43) ergs/s, a not-unexpected result. If all other parameters were unchanged, we would expect adequate agreement for sigma(sub 8) = 0.6. This provides a new and independent argument for lower small-scale power than standard CDM at the 8 h(exp -1) Mpc scale. The background radiation field at 1 keV due to clusters in this model is approximately one-third of the observed background, which, after correction for numerical effects, again indicates approximately 5 times too much emission and the appropriateness of sigma(sub 8) = 0.6. If we have used the observed ratio of gas to total mass in clusters, rather than basing the mean density on light-element nucleosynthesis, then the computed luminosity of each cluster would have increased still further, by a factor of approximately 10. The number density of clusters increases to z approximately 1, but the luminosity per typical cluster decreases, with the result that evolution in the number density of bright clusters is moderate in this redshift range, showing a broad peak near z = 0.7, and then a rapid decline above redshift z = 3. Detailed computations of the luminosity functions in the range L(sub x) = 10(exp 40) - 10(exp 44) ergs/s in various energy bands are presented for both cluster central regions and total luminosities to be used in comparison with ROSAT and other observational data sets. The quantitative results found disagree significantly with those found by other investigators using semianalytic techniques. We find little dependence of core radius on cluster luminosity and a dependence of temperature on luminosity given by log kT(sub x) = A + B log L(sub x), which is slightly steeper (B = 0.38) than is indicated by observations. Computed temperatures are somewhat higher than observed, as expected, in that COBE-normalized CDM has too much power on the relevant scales. A modest average temperature gradient is found, with temperatures dropping to 90% of central values at 0.4 h(exp -1) Mpc and 70% of central values at 0.9 h(exp -1) Mpc. Examining the ratio of gas to total mass in the clusters normalized to Omega(sub B) h(exp 2) = 0.015, and comparing with observations, we conclude, in agreement with White (1991), that the cluster observations argue for an open universe.

Using Cluster Bootstrapping to Analyze Nested Data With a Few Clusters.

PubMed

Huang, Francis L

2018-04-01

Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials are performed with a low number of clusters (~20 groups). Although multilevel models are often used to analyze nested data, researchers may be concerned of potentially biased results due to having only a few groups under study. Cluster bootstrapping has been suggested as an alternative procedure when analyzing clustered data though it has seen very little use in educational and psychological studies. Using a Monte Carlo simulation that varied the number of clusters, average cluster size, and intraclass correlations, we compared standard errors using cluster bootstrapping with those derived using ordinary least squares regression and multilevel models. Results indicate that cluster bootstrapping, though more computationally demanding, can be used as an alternative procedure for the analysis of clustered data when treatment effects at the group level are of primary interest. Supplementary material showing how to perform cluster bootstrapped regressions using R is also provided.

A New Approach for Simulating Galaxy Cluster Properties

NASA Astrophysics Data System (ADS)

Arieli, Y.; Rephaeli, Y.; Norman, M. L.

2008-08-01

We describe a subgrid model for including galaxies into hydrodynamical cosmological simulations of galaxy cluster evolution. Each galaxy construct—or galcon—is modeled as a physically extended object within which star formation, galactic winds, and ram pressure stripping of gas are modeled analytically. Galcons are initialized at high redshift (z ~ 3) after galaxy dark matter halos have formed but before the cluster has virialized. Each galcon moves self-consistently within the evolving cluster potential and injects mass, metals, and energy into intracluster (IC) gas through a well-resolved spherical interface layer. We have implemented galcons into the Enzo adaptive mesh refinement code and carried out a simulation of cluster formation in a ΛCDM universe. With our approach, we are able to economically follow the impact of a large number of galaxies on IC gas. We compare the results of the galcon simulation with a second, more standard simulation where star formation and feedback are treated using a popular heuristic prescription. One advantage of the galcon approach is explicit control over the star formation history of cluster galaxies. Using a galactic SFR derived from the cosmic star formation density, we find the galcon simulation produces a lower stellar fraction, a larger gas core radius, a more isothermal temperature profile, and a flatter metallicity gradient than the standard simulation, in better agreement with observations.

[Optimization of cluster analysis based on drug resistance profiles of MRSA isolates].

PubMed

Tani, Hiroya; Kishi, Takahiko; Gotoh, Minehiro; Yamagishi, Yuka; Mikamo, Hiroshige

2015-12-01

We examined 402 methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from clinical specimens in our hospital between November 19, 2010 and December 27, 2011 to evaluate the similarity between cluster analysis of drug susceptibility tests and pulsed-field gel electrophoresis (PFGE). The results showed that the 402 strains tested were classified into 27 PFGE patterns (151 subtypes of patterns). Cluster analyses of drug susceptibility tests with the cut-off distance yielding a similar classification capability showed favorable results--when the MIC method was used, and minimum inhibitory concentration (MIC) values were used directly in the method, the level of agreement with PFGE was 74.2% when 15 drugs were tested. The Unweighted Pair Group Method with Arithmetic mean (UPGMA) method was effective when the cut-off distance was 16. Using the SIR method in which susceptible (S), intermediate (I), and resistant (R) were coded as 0, 2, and 3, respectively, according to the Clinical and Laboratory Standards Institute (CLSI) criteria, the level of agreement with PFGE was 75.9% when the number of drugs tested was 17, the method used for clustering was the UPGMA, and the cut-off distance was 3.6. In addition, to assess the reproducibility of the results, 10 strains were randomly sampled from the overall test and subjected to cluster analysis. This was repeated 100 times under the same conditions. The results indicated good reproducibility of the results, with the level of agreement with PFGE showing a mean of 82.0%, standard deviation of 12.1%, and mode of 90.0% for the MIC method and a mean of 80.0%, standard deviation of 13.4%, and mode of 90.0% for the SIR method. In summary, cluster analysis for drug susceptibility tests is useful for the epidemiological analysis of MRSA.

The development and validity of the Salford Gait Tool: an observation-based clinical gait assessment tool.

PubMed

Toro, Brigitte; Nester, Christopher J; Farren, Pauline C

2007-03-01

To develop the construct, content, and criterion validity of the Salford Gait Tool (SF-GT) and to evaluate agreement between gait observations using the SF-GT and kinematic gait data. Tool development and comparative evaluation. University in the United Kingdom. For designing construct and content validity, convenience samples of 10 children with hemiplegic, diplegic, and quadriplegic cerebral palsy (CP) and 152 physical therapy students and 4 physical therapists were recruited. For developing criterion validity, kinematic gait data of 13 gait clusters containing 56 children with hemiplegic, diplegic, and quadriplegic CP and 11 neurologically intact children was used. For clinical evaluation, a convenience sample of 23 pediatric physical therapists participated. We developed a sagittal plane observational gait assessment tool through a series of design, test, and redesign iterations. The tool's grading system was calibrated using kinematic gait data of 13 gait clusters and was evaluated by comparing the agreement of gait observations using the SF-GT with kinematic gait data. Criterion standard kinematic gait data. There was 58% mean agreement based on grading categories and 80% mean agreement based on degree estimations evaluated with the least significant difference method. The new SF-GT has good concurrent criterion validity.

New approaches to model and study social networks

NASA Astrophysics Data System (ADS)

Lind, P. G.; Herrmann, H. J.

2007-07-01

We describe and develop three recent novelties in network research which are particularly useful for studying social systems. The first one concerns the discovery of some basic dynamical laws that enable the emergence of the fundamental features observed in social networks, namely the nontrivial clustering properties, the existence of positive degree correlations and the subdivision into communities. To reproduce all these features, we describe a simple model of mobile colliding agents, whose collisions define the connections between the agents which are the nodes in the underlying network, and develop some analytical considerations. The second point addresses the particular feature of clustering and its relationship with global network measures, namely with the distribution of the size of cycles in the network. Since in social bipartite networks it is not possible to measure the clustering from standard procedures, we propose an alternative clustering coefficient that can be used to extract an improved normalized cycle distribution in any network. Finally, the third point addresses dynamical processes occurring on networks, namely when studying the propagation of information in them. In particular, we focus on the particular features of gossip propagation which impose some restrictions in the propagation rules. To this end we introduce a quantity, the spread factor, which measures the average maximal fraction of nearest neighbours which get in contact with the gossip, and find the striking result that there is an optimal non-trivial number of friends for which the spread factor is minimized, decreasing the danger of being gossiped about.

Descriptive Statistics and Cluster Analysis for Extreme Rainfall in Java Island

NASA Astrophysics Data System (ADS)

E Komalasari, K.; Pawitan, H.; Faqih, A.

2017-03-01

This study aims to describe regional pattern of extreme rainfall based on maximum daily rainfall for period 1983 to 2012 in Java Island. Descriptive statistics analysis was performed to obtain centralization, variation and distribution of maximum precipitation data. Mean and median are utilized to measure central tendency data while Inter Quartile Range (IQR) and standard deviation are utilized to measure variation of data. In addition, skewness and kurtosis used to obtain shape the distribution of rainfall data. Cluster analysis using squared euclidean distance and ward method is applied to perform regional grouping. Result of this study show that mean (average) of maximum daily rainfall in Java Region during period 1983-2012 is around 80-181mm with median between 75-160mm and standard deviation between 17 to 82. Cluster analysis produces four clusters and show that western area of Java tent to have a higher annual maxima of daily rainfall than northern area, and have more variety of annual maximum value.

Kinetics of Aggregation with Choice

DOE PAGES

Ben-Naim, Eli; Krapivsky, Paul

2016-12-01

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

Atomic scale simulations of vapor cooled carbon clusters

NASA Astrophysics Data System (ADS)

Bogana, M. P.; Colombo, L.

2007-03-01

By means of atomistic simulations we observed the formation of many topologically non-equivalent carbon clusters formed by the condensation of liquid droplets, including: (i) standard fullerenes and onion-like structures, (ii) clusters showing extremely complex surfaces with both positive and negative curvatures and (iii) complex endohedral structures. In this work we offer a thorough structural characterization of the above systems, as well as an attempt to correlate the resulting structure to the actual protocol of growth. The IR and Raman responses of some exotic linear carbon structures have been further investigated, finding good agreement with experimental evidence of carbinoid structures in cluster-assembled films. Towards the aim of fully understanding the process of cluster-to-cluster coalescence dynamics, we further simulated an aerosol of amorphous carbon clusters at controlled temperatures. Various annealing temperatures and times have been observed, identifying different pathways for cluster ripening, ranging from simple coalescence to extensive reconstruction.

Populating dark matter haloes with galaxies: comparing the 2dFGRS with mock galaxy redshift surveys

NASA Astrophysics Data System (ADS)

Yang, Xiaohu; Mo, H. J.; Jing, Y. P.; van den Bosch, Frank C.; Chu, YaoQuan

2004-06-01

In two recent papers, we developed a powerful technique to link the distribution of galaxies to that of dark matter haloes by considering halo occupation numbers as a function of galaxy luminosity and type. In this paper we use these distribution functions to populate dark matter haloes in high-resolution N-body simulations of the standard ΛCDM cosmology with Ωm= 0.3, ΩΛ= 0.7 and σ8= 0.9. Stacking simulation boxes of 100 h-1 Mpc and 300 h-1 Mpc with 5123 particles each we construct mock galaxy redshift surveys out to a redshift of z= 0.2 with a numerical resolution that guarantees completeness down to 0.01L*. We use these mock surveys to investigate various clustering statistics. The predicted two-dimensional correlation function ξ(rp, π) reveals clear signatures of redshift space distortions. The projected correlation functions for galaxies with different luminosities and types, derived from ξ(rp, π), match the observations well on scales larger than ~3 h-1 Mpc. On smaller scales, however, the model overpredicts the clustering power by about a factor two. Modelling the `finger-of-God' effect on small scales reveals that the standard ΛCDM model predicts pairwise velocity dispersions (PVD) that are ~400 km s-1 too high at projected pair separations of ~1 h-1 Mpc. A strong velocity bias in massive haloes, with bvel≡σgal/σdm~ 0.6 (where σgal and σdm are the velocity dispersions of galaxies and dark matter particles, respectively) can reduce the predicted PVD to the observed level, but does not help to resolve the overprediction of clustering power on small scales. Consistent results can be obtained within the standard ΛCDM model only when the average mass-to-light ratio of clusters is of the order of 1000 (M/L)solar in the B-band. Alternatively, as we show by a simple approximation, a ΛCDM model with σ8~= 0.75 may also reproduce the observational results. We discuss our results in light of the recent WMAP results and the constraints on σ8 obtained independently from other observations.

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

TOSCA-based orchestration of complex clusters at the IaaS level

NASA Astrophysics Data System (ADS)

Caballer, M.; Donvito, G.; Moltó, G.; Rocha, R.; Velten, M.

2017-10-01

This paper describes the adoption and extension of the TOSCA standard by the INDIGO-DataCloud project for the definition and deployment of complex computing clusters together with the required support in both OpenStack and OpenNebula, carried out in close collaboration with industry partners such as IBM. Two examples of these clusters are described in this paper, the definition of an elastic computing cluster to support the Galaxy bioinformatics application where the nodes are dynamically added and removed from the cluster to adapt to the workload, and the definition of an scalable Apache Mesos cluster for the execution of batch jobs and support for long-running services. The coupling of TOSCA with Ansible Roles to perform automated installation has resulted in the definition of high-level, deterministic templates to provision complex computing clusters across different Cloud sites.

Procedural Guide for Designation Surveys of Ocean Dredged Material Disposal Sites. Revision

DTIC Science & Technology

1990-04-01

data standardization." One of the most frequently used clustering strategies is called UPGMA (unweighted pair-group method using arithmetic averages...Sneath and Sokal 1973). Romesburg (1984) 151 evaluated many possible methods and concluded that UPGMA is appropriate for most types of cluster

Feasibility of feature-based indexing, clustering, and search of clinical trials: A case study of breast cancer trials from ClinicalTrials.gov

PubMed Central

Boland, Mary Regina; Miotto, Riccardo; Gao, Junfeng; Weng, Chunhua

2013-01-01

Summary Background When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. Objectives This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. Methods We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. Results We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. Conclusions It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency. PMID:23666475

Using mini-rockwool blocks as growing media for limited-cluster tomato production

NASA Technical Reports Server (NTRS)

Logendra, L. S.; Gianfagna, T. J.; Janes, H. W.

2001-01-01

Rockwool is an excellent growing medium for the hydroponic production of tomato; however, the standard size rockwool blocks [4 x 4 x 2.5 inches (10 x 10 x 6.3 cm) or 3 x 3 x 2.5 inches (7.5 x 7.5 x 6.3 cm)] are expensive. The following experiments were conducted with less expensive minirock wool blocks (MRBs), on rayon polyester material (RPM) as a bench top liner, to reduce the production cost of tomatoes (Lycopersicon esculentum) grown in a limited-cluster, ebb and flood hydroponic cultivation system. Fruit yield for single-cluster plants growing in MRBs [2 x 2 x 1.6 inches (5 x 5 x 4 cm) and 1.6 x 1.6 x 1.6 inches (4 x 4 x 4 cm)] was not significantly different from plants grown in larger sized blocks (3 x 3 x 2.5 inches). When the bench top was lined with RPM, roots penetrated the RPM, and an extensive root mat developed between the RPM and the bench top. The fruit yield from plants on RPM was significantly increased compared to plants without RPM due to increases in fruit size and fruit number. RPM also significantly reduced the incidence of blossom-end rot. In a second experiment, single- and double-cluster plants were grown on RPM. Fruit yield for double-cluster plants was 40% greater than for single-cluster plants due to an increase in fruit number, although the fruit were smaller in size. As in the first experiment, fruit yield for all plants grown in MRBs was not significantly different from plants grown in the larger sized blocks. MRBs and a RPM bench liner are an effective combination in the production of limited-cluster hydroponic tomatoes.

Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov.

PubMed

Boland, M R; Miotto, R; Gao, J; Weng, C

2013-01-01

When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.

Initial derivation of diagnostic clusters combining history elements and physical examination tests for symptomatic knee osteoarthritis.

PubMed

Décary, Simon; Feldman, Debbie; Frémont, Pierre; Pelletier, Jean-Pierre; Martel-Pelletier, Johanne; Fallaha, Michel; Pelletier, Bruno; Belzile, Sylvain; Sylvestre, Marie-Pierre; Vendittoli, Pascal-André; Desmeules, François

2018-05-21

The aim of the present study was to assess the validity of clusters combining history elements and physical examination tests to diagnose symptomatic knee osteoarthritis (SOA) compared with other knee disorders. This was a prospective diagnostic accuracy study, in which 279 consecutive patients consulting for a knee complaint were assessed. History elements and standardized physical examination tests were obtained independently by a physiotherapist and compared with an expert physician's composite diagnosis, including clinical examination and imaging. Recursive partitioning was used to develop diagnostic clusters for SOA. Diagnostic accuracy measures were calculated, including sensitivity, specificity, and positive and negative likelihood ratios (LR+/-), with associated 95% confidence intervals (CIs). A total of 129 patients had a diagnosis of SOA (46.2%). Most cases (76%) had combined tibiofemoral and patellofemoral knee OA and 63% had radiological Kellgren-Lawrence grades of 2 or 3. Different combinations of history elements and physical examination tests were used in clusters accurately to discriminate SOA from other knee disorders. These included age of patients, body mass index, presence of valgus/varus knee misalignment, palpable knee crepitus and limited passive knee extension. Two clusters to rule in SOA reached an LR+ of 13.6 (95% CI 6.5 to 28.4) and three clusters to rule out SOA reached an LR- of 0.11 (95% CI 0.06 to 0.20). Diagnostic clusters combining history elements and physical examination tests were able to support the differential diagnosis of SOA compared with various knee disorders without relying systematically on imaging. This could support primary care clinicians' role in the efficient management of these patients. Copyright © 2018 John Wiley & Sons, Ltd.

Chaos theory perspective for industry clusters development

NASA Astrophysics Data System (ADS)

Yu, Haiying; Jiang, Minghui; Li, Chengzhang

2016-03-01

Industry clusters have outperformed in economic development in most developing countries. The contributions of industrial clusters have been recognized as promotion of regional business and the alleviation of economic and social costs. It is no doubt globalization is rendering clusters in accelerating the competitiveness of economic activities. In accordance, many ideas and concepts involve in illustrating evolution tendency, stimulating the clusters development, meanwhile, avoiding industrial clusters recession. The term chaos theory is introduced to explain inherent relationship of features within industry clusters. A preferred life cycle approach is proposed for industrial cluster recessive theory analysis. Lyapunov exponents and Wolf model are presented for chaotic identification and examination. A case study of Tianjin, China has verified the model effectiveness. The investigations indicate that the approaches outperform in explaining chaos properties in industrial clusters, which demonstrates industrial clusters evolution, solves empirical issues and generates corresponding strategies.

Updated Design Standards and Guidance from the What Works Clearinghouse: Regression Discontinuity Designs and Cluster Designs

ERIC Educational Resources Information Center

Cole, Russell; Deke, John; Seftor, Neil

2016-01-01

The What Works Clearinghouse (WWC) maintains design standards to identify rigorous, internally valid education research. As education researchers advance new methodologies, the WWC must revise its standards to include an assessment of the new designs. Recently, the WWC has revised standards for two emerging study designs: regression discontinuity…

Galaxy clusters and cold dark matter - A low-density unbiased universe?

NASA Technical Reports Server (NTRS)

Bahcall, Neta A.; Cen, Renyue

1992-01-01

Large-scale simulations of a universe dominated by cold dark matter (CDM) are tested against two fundamental properties of clusters of galaxies: the cluster mass function and the cluster correlation function. We find that standard biased CDM models are inconsistent with these observations for any bias parameter b. A low-density, low-bias CDM-type model, with or without a cosmological constant, appears to be consistent with both the cluster mass function and the cluster correlations. The low-density model agrees well with the observed correlation function of the Abell, Automatic Plate Measuring Facility (APM), and Edinburgh-Durham cluster catalogs. The model is in excellent agreement with the observed dependence of the correlation strength on cluster mean separation, reproducing the measured universal dimensionless cluster correlation. The low-density model is also consistent with other large-scale structure observations, including the APM angular galaxy-correlations, and for lambda = 1-Omega with the COBE results of the microwave background radiation fluctuations.

Uncertainties in the cluster-cluster correlation function

NASA Astrophysics Data System (ADS)

Ling, E. N.; Frenk, C. S.; Barrow, J. D.

1986-12-01

The bootstrap resampling technique is applied to estimate sampling errors and significance levels of the two-point correlation functions determined for a subset of the CfA redshift survey of galaxies and a redshift sample of 104 Abell clusters. The angular correlation function for a sample of 1664 Abell clusters is also calculated. The standard errors in xi(r) for the Abell data are found to be considerably larger than quoted 'Poisson errors'. The best estimate for the ratio of the correlation length of Abell clusters (richness class R greater than or equal to 1, distance class D less than or equal to 4) to that of CfA galaxies is 4.2 + 1.4 or - 1.0 (68 percentile error). The enhancement of cluster clustering over galaxy clustering is statistically significant in the presence of resampling errors. The uncertainties found do not include the effects of possible systematic biases in the galaxy and cluster catalogs and could be regarded as lower bounds on the true uncertainty range.

Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006-2011.

PubMed

Faires, Meredith C; Pearl, David L; Ciccotelli, William A; Berke, Olaf; Reid-Smith, Richard J; Weese, J Scott

2014-05-12

In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007-2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital personnel. The identification of time periods with decreased or increased CDI rates may have been a result of specific hospital events. Understanding the clustering of CDIs can aid in the interpretation of surveillance data and lead to the development of better early detection systems.

Competency Index. [Business/Computer Technologies Cluster.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Center on Education and Training for Employment.

This index allows the user to scan the competencies under each title for the 28 subjects appropriate for use in a competency list for the 12 occupations within the business/computer technologies cluster. Titles of the 28 units are as follows: employability skills; professionalism; teamwork; professional and ethical standards; economic and business…

Detection of Galaxy Cluster Motions with the Kinematic Sunyaev-Zel'dovich Effect

NASA Technical Reports Server (NTRS)

Hand, Nick; Addison, Graeme E.; Aubourg, Eric; Battaglia, Nick; Battistelli, Elia S.; Bizyaev, Dmitry; Bond, J. Richard; Brewington, Howard; Brinkmann, Jon; Brown, Benjamin R.;

Synthesis of Nine-atom Deltahedral Zintl Ions of Germanium and their Functionalization with Organic Groups

PubMed Central

Gillett-Kunnath, Miriam M.; Sevov, Slavi C.

2012-01-01

Although the first studies of Zintl ions date between the late 1890's and early 1930's they were not structurally characterized until many years later.1,2 Their redox chemistry is even younger, just about ten years old, but despite this short history these deltahedral clusters ions E9n- (E = Si, Ge, Sn, Pb; n = 2, 3, 4) have already shown interesting and diverse reactivity and have been at the forefront of rapidly developing and exciting new chemistry.3-6 Notable milestones are the oxidative coupling of Ge94- clusters to oligomers and infinite chains,7-19 their metallation,14-16,20-25 capping by transition-metal organometallic fragments,26-34 insertion of a transition-metal atom at the center of the cluster which is sometimes combined with capping and oligomerization,35-47 addition of main-group organometallic fragments as exo-bonded substituents,48-50 and functionalization with various organic residues by reactions with organic halides and alkynes.51-58 This latter development of attaching organic fragments directly to the clusters has opened up a new field, namely organo-Zintl chemistry, that is potentially fertile for further synthetic explorations, and it is the step-by-step procedure for the synthesis of germanium-divinyl clusters described herein. The initial steps outline the synthesis of an intermetallic precursor of K4Ge9 from which the Ge94- clusters are extracted later in solution. This involves fused-silica glass blowing, arc-welding of niobium containers, and handling of highly air-sensitive materials in a glove box. The air-sensitive K4Ge9 is then dissolved in ethylenediamine in the box and then alkenylated by a reaction with Me3SiC≡CSiMe3. The reaction is followed by electrospray mass spectrometry while the resulting solution is used for obtaining single crystals containing the functionalized clusters [H2C=CH-Ge9-CH=CH2]2-. For this purpose the solution is centrifuged, filtered, and carefully layered with a toluene solution of 18-crown-6. Left undisturbed for a few days, the so-layered solutions produced orange crystalline blocks of [K(18-crown-6)]2[Ge9(HCCH2)2]•en which were characterized by single-crystal X-ray diffraction. The process highlights standard reaction techniques, work-up, and analysis towards functionalized deltahedral Zintl clusters. It is hoped that it will help towards further development and understanding of these compounds in the community at large. PMID:22349121

Hebbian self-organizing integrate-and-fire networks for data clustering.

PubMed

Landis, Florian; Ott, Thomas; Stoop, Ruedi

2010-01-01

We propose a Hebbian learning-based data clustering algorithm using spiking neurons. The algorithm is capable of distinguishing between clusters and noisy background data and finds an arbitrary number of clusters of arbitrary shape. These properties render the approach particularly useful for visual scene segmentation into arbitrarily shaped homogeneous regions. We present several application examples, and in order to highlight the advantages and the weaknesses of our method, we systematically compare the results with those from standard methods such as the k-means and Ward's linkage clustering. The analysis demonstrates that not only the clustering ability of the proposed algorithm is more powerful than those of the two concurrent methods, the time complexity of the method is also more modest than that of its generally used strongest competitor.

Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

NASA Astrophysics Data System (ADS)

Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

2014-01-01

We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

Assessing a hydrodynamic description for instabilities in highly dissipative, freely cooling granular gases.

PubMed

Mitrano, Peter P; Garzó, Vicente; Hilger, Andrew M; Ewasko, Christopher J; Hrenya, Christine M

2012-04-01

An intriguing phenomenon displayed by granular flows and predicted by kinetic-theory-based models is the instability known as particle "clustering," which refers to the tendency of dissipative grains to form transient, loose regions of relatively high concentration. In this work, we assess a modified-Sonine approximation recently proposed [Garzó, Santos, and Montanero, Physica A 376, 94 (2007)] for a granular gas via an examination of system stability. In particular, we determine the critical length scale associated with the onset of two types of instabilities--vortices and clusters--via stability analyses of the Navier-Stokes-order hydrodynamic equations by using the expressions of the transport coefficients obtained from both the standard and the modified-Sonine approximations. We examine the impact of both Sonine approximations over a range of solids fraction φ<0.2 for small restitution coefficients e = 0.25-0.4, where the standard and modified theories exhibit discrepancies. The theoretical predictions for the critical length scales are compared to molecular dynamics (MD) simulations, of which a small percentage were not considered due to inelastic collapse. Results show excellent quantitative agreement between MD and the modified-Sonine theory, while the standard theory loses accuracy for this highly dissipative parameter space. The modified theory also remedies a high-dissipation qualitative mismatch between the standard theory and MD for the instability that forms more readily. Furthermore, the evolution of cluster size is briefly examined via MD, indicating that domain-size clusters may remain stable or halve in size, depending on system parameters.

Effectiveness of a long-lasting piperonyl butoxide-treated insecticidal net and indoor residual spray interventions, separately and together, against malaria transmitted by pyrethroid-resistant mosquitoes: a cluster, randomised controlled, two-by-two factorial design trial.

PubMed

Protopopoff, Natacha; Mosha, Jacklin F; Lukole, Eliud; Charlwood, Jacques D; Wright, Alexandra; Mwalimu, Charles D; Manjurano, Alphaxard; Mosha, Franklin W; Kisinza, William; Kleinschmidt, Immo; Rowland, Mark

2018-04-21

Progress in malaria control is under threat by wide-scale insecticide resistance in malaria vectors. Two recent vector control products have been developed: a long-lasting insecticidal net that incorporates a synergist piperonyl butoxide (PBO) and a long-lasting indoor residual spraying formulation of the insecticide pirimiphos-methyl. We evaluated the effectiveness of PBO long-lasting insecticidal nets versus standard long-lasting insecticidal nets as single interventions and in combination with the indoor residual spraying of pirimiphos-methyl. We did a four-group cluster randomised controlled trial using a two-by-two factorial design of 48 clusters derived from 40 villages in Muleba (Kagera, Tanzania). We randomly assigned these clusters using restricted randomisation to four groups: standard long-lasting insecticidal nets, PBO long-lasting insecticidal nets, standard long-lasting insecticidal nets plus indoor residual spraying, or PBO long-lasting insecticidal nets plus indoor residual spraying. Both standard and PBO nets were distributed in 2015. Indoor residual spraying was applied only once in 2015. We masked the inhabitants of each cluster to the type of nets received, as well as field staff who took blood samples. Neither the investigators nor the participants were masked to indoor residual spraying. The primary outcome was the prevalence of malaria infection in children aged 6 months to 14 years assessed by cross-sectional surveys at 4, 9, 16, and 21 months after intervention. The endpoint for assessment of indoor residual spraying was 9 months and PBO long-lasting insecticidal nets was 21 months. This trial is registered with ClinicalTrials.gov, number NCT02288637. 7184 (68·0%) of 10 560 households were selected for post-intervention survey, and 15 469 (89·0%) of 17 377 eligible children from the four surveys were included in the intention-to-treat analysis. Of the 878 households visited in the two indoor residual spraying groups, 827 (94%) had been sprayed. Reported use of long-lasting insecticidal nets, across all groups, was 15 341 (77·3%) of 19 852 residents after 1 year, decreasing to 12 503 (59·2%) of 21 105 in the second year. Malaria infection prevalence after 9 months was lower in the two groups that received PBO long-lasting insecticidal nets than in the two groups that received standard long-lasting insecticidal nets (531 [29%] of 1852 children vs 767 [42%] of 1809; odds ratio [OR] 0·37, 95% CI 0·21-0·65; p=0·0011). At the same timepoint, malaria prevalence in the two groups that received indoor residual spraying was lower than in groups that did not receive indoor residual spraying (508 [28%] of 1846 children vs 790 [44%] of 1815; OR 0·33, 95% CI 0·19-0·55; p<0·0001) and there was evidence of an interaction between PBO long-lasting insecticidal nets and indoor residual spraying (OR 2·43, 95% CI 1·19-4·97; p=0·0158), indicating redundancy when combined. The PBO long-lasting insecticidal net effect was sustained after 21 months with a lower malaria prevalence than the standard long-lasting insecticidal net (865 [45%] of 1930 children vs 1255 [62%] of 2034; OR 0·40, 0·20-0·81; p=0·0122). The PBO long-lasting insecticidal net and non-pyrethroid indoor residual spraying interventions showed improved control of malaria transmission compared with standard long-lasting insecticidal nets where pyrethroid resistance is prevalent and either intervention could be deployed to good effect. As a result, WHO has since recommended to increase coverage of PBO long-lasting insecticidal nets. Combining indoor residual spraying with pirimiphos-methyl and PBO long-lasting insecticidal nets provided no additional benefit compared with PBO long-lasting insecticidal nets alone or standard long-lasting insecticidal nets plus indoor residual spraying. UK Department for International Development, Medical Research Council, and Wellcome Trust. Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Statistical analysis of activation and reaction energies with quasi-variational coupled-cluster theory

NASA Astrophysics Data System (ADS)

Black, Joshua A.; Knowles, Peter J.

2018-06-01

The performance of quasi-variational coupled-cluster (QV) theory applied to the calculation of activation and reaction energies has been investigated. A statistical analysis of results obtained for six different sets of reactions has been carried out, and the results have been compared to those from standard single-reference methods. In general, the QV methods lead to increased activation energies and larger absolute reaction energies compared to those obtained with traditional coupled-cluster theory.

Spatial dynamics of invasion: the geometry of introduced species.

PubMed

Korniss, Gyorgy; Caraco, Thomas

2005-03-07

Many exotic species combine low probability of establishment at each introduction with rapid population growth once introduction does succeed. To analyse this phenomenon, we note that invaders often cluster spatially when rare, and consequently an introduced exotic's population dynamics should depend on locally structured interactions. Ecological theory for spatially structured invasion relies on deterministic approximations, and determinism does not address the observed uncertainty of the exotic-introduction process. We take a new approach to the population dynamics of invasion and, by extension, to the general question of invasibility in any spatial ecology. We apply the physical theory for nucleation of spatial systems to a lattice-based model of competition between plant species, a resident and an invader, and the analysis reaches conclusions that differ qualitatively from the standard ecological theories. Nucleation theory distinguishes between dynamics of single- and multi-cluster invasion. Low introduction rates and small system size produce single-cluster dynamics, where success or failure of introduction is inherently stochastic. Single-cluster invasion occurs only if the cluster reaches a critical size, typically preceded by a number of failed attempts. For this case, we identify the functional form of the probability distribution of time elapsing until invasion succeeds. Although multi-cluster invasion for sufficiently large systems exhibits spatial averaging and almost-deterministic dynamics of the global densities, an analytical approximation from nucleation theory, known as Avrami's law, describes our simulation results far better than standard ecological approximations.

[Principal component analysis and cluster analysis of inorganic elements in sea cucumber Apostichopus japonicus].

PubMed

Liu, Xiao-Fang; Xue, Chang-Hu; Wang, Yu-Ming; Li, Zhao-Jie; Xue, Yong; Xu, Jie

2011-11-01

The present study is to investigate the feasibility of multi-elements analysis in determination of the geographical origin of sea cucumber Apostichopus japonicus, and to make choice of the effective tracers in sea cucumber Apostichopus japonicus geographical origin assessment. The content of the elements such as Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Hg and Pb in sea cucumber Apostichopus japonicus samples from seven places of geographical origin were determined by means of ICP-MS. The results were used for the development of elements database. Cluster analysis(CA) and principal component analysis (PCA) were applied to differentiate the sea cucumber Apostichopus japonicus geographical origin. Three principal components which accounted for over 89% of the total variance were extracted from the standardized data. The results of Q-type cluster analysis showed that the 26 samples could be clustered reasonably into five groups, the classification results were significantly associated with the marine distribution of the sea cucumber Apostichopus japonicus samples. The CA and PCA were the effective methods for elements analysis of sea cucumber Apostichopus japonicus samples. The content of the mineral elements in sea cucumber Apostichopus japonicus samples was good chemical descriptors for differentiating their geographical origins.

Supersonic Bare Metal Cluster Beams. Technical Progress Report, March 16, 1984 - April 1, 1985

DOE R&D Accomplishments Database

Smalley, R. E.

1985-01-01

There have been four major areas of concentration for the study of bare metal cluster beams: neutral cluster, chemical reactivity, cold cluster ion source development (both positive and negative), bare cluster ion ICR (ion cyclotron resonance) development, and photofragmentation studies of bare metal cluster ions.

Broca’s area network in language function: a pooling-data connectivity study

PubMed Central

Bernal, Byron; Ardila, Alfredo; Rosselli, Monica

2015-01-01

Background and Objective: Modern neuroimaging developments have demonstrated that cognitive functions correlate with brain networks rather than specific areas. The purpose of this paper was to analyze the connectivity of Broca’s area based on language tasks. Methods: A connectivity modeling study was performed by pooling data of Broca’s activation in language tasks. Fifty-seven papers that included 883 subjects in 84 experiments were analyzed. Analysis of Likelihood Estimates of pooled data was utilized to generate the map; thresholds at p < 0.01 were corrected for multiple comparisons and false discovery rate. Resulting images were co-registered into MNI standard space. Results: A network consisting of 16 clusters of activation was obtained. Main clusters were located in the frontal operculum, left posterior temporal region, supplementary motor area, and the parietal lobe. Less common clusters were seen in the sub-cortical structures including the left thalamus, left putamen, secondary visual areas, and the right cerebellum. Conclusion: Broca’s area-44-related networks involved in language processing were demonstrated utilizing a pooling-data connectivity study. Significance, interpretation, and limitations of the results are discussed. PMID:26074842

Hospital integrated parallel cluster for fast and cost-efficient image analysis: clinical experience and research evaluation

NASA Astrophysics Data System (ADS)

Erberich, Stephan G.; Hoppe, Martin; Jansen, Christian; Schmidt, Thomas; Thron, Armin; Oberschelp, Walter

2001-08-01

In the last few years more and more University Hospitals as well as private hospitals changed to digital information systems for patient record, diagnostic files and digital images. Not only that patient management becomes easier, it is also very remarkable how clinical research can profit from Picture Archiving and Communication Systems (PACS) and diagnostic databases, especially from image databases. Since images are available on the finger tip, difficulties arise when image data needs to be processed, e.g. segmented, classified or co-registered, which usually demands a lot computational power. Today's clinical environment does support PACS very well, but real image processing is still under-developed. The purpose of this paper is to introduce a parallel cluster of standard distributed systems and its software components and how such a system can be integrated into a hospital environment. To demonstrate the cluster technique we present our clinical experience with the crucial but cost-intensive motion correction of clinical routine and research functional MRI (fMRI) data, as it is processed in our Lab on a daily basis.

Three-dimensional kinematics of the lumbar spine during gait using marker-based systems: a systematic review.

PubMed

Needham, Robert; Stebbins, Julie; Chockalingam, Nachiappan

2016-01-01

To review the current scientific literature on the assessment of three-dimensional movement of the lumbar spine with a focus on the utilisation of a 3D cluster. Electronic databases PubMed, OVID, CINAHL, The Cochrance Library, ScienceDirect, ProQuest and Web of Knowledge were searched between 1966 and March 2015. The reference lists of the articles that met the inclusion criteria were also searched. From the 1530 articles identified through an initial search, 16 articles met the inclusion criteria. All information relating to methodology and kinematic modelling of the lumbar segment along with the outcome measures were extracted from the studies identified for synthesis. Guidelines detailing 3D cluster construction were limited in the identified articles and the lack of information presented makes it difficult to assess the external validity of this technique. Scarce information was presented detailing time-series angle data of the lumbar spine during gait. Further developments of the 3D cluster technique are required and it is essential that the authors provide clear instruction, definitions and standards in their manuscript to improve clarity and reproducibility.

A local framework for calculating coupled cluster singles and doubles excitation energies (LoFEx-CCSD)

DOE PAGES

Baudin, Pablo; Bykov, Dmytro; Liakh, Dmitry I.; ...

2017-02-22

Here, the recently developed Local Framework for calculating Excitation energies (LoFEx) is extended to the coupled cluster singles and doubles (CCSD) model. In the new scheme, a standard CCSD excitation energy calculation is carried out within a reduced excitation orbital space (XOS), which is composed of localised molecular orbitals and natural transition orbitals determined from time-dependent Hartree–Fock theory. The presented algorithm uses a series of reduced second-order approximate coupled cluster singles and doubles (CC2) calculations to optimise the XOS in a black-box manner. This ensures that the requested CCSD excitation energies have been determined to a predefined accuracy compared tomore » a conventional CCSD calculation. We present numerical LoFEx-CCSD results for a set of medium-sized organic molecules, which illustrate the black-box nature of the approach and the computational savings obtained for transitions that are local compared to the size of the molecule. In fact, for such local transitions, the LoFEx-CCSD scheme can be applied to molecular systems where a conventional CCSD implementation is intractable.« less

Organic-inorganic hybrid resists for EUVL

NASA Astrophysics Data System (ADS)

Singh, Vikram; Kalyani, Vishwanath; Satyanarayana, V. S. V.; Pradeep, Chullikkattil P.; Ghosh, Subrata; Sharma, Satinder; Gonsalves, Kenneth E.

2014-03-01

Herein, we describe preliminary results on organic-inorganic hybrid photoresists, capable of showing line patterns up to 16 nm under e-beam exposure studies, prepared by incorporating polyoxometalates (POMs) clusters into organic photoresist materials. Various Mo and W based clusters such as (TBA)2[Mo6O19], (TBA)5(H)[P2V3W15O62] and (TBA)4[P2Mo18O61] (where TBA = tetrabutyl ammonium counter ion) have been incorporated into PMMA matrix by mixing POM solutions and standard PMMA polymer in anisole (MW ~ 95000, MicroChem) in 1:33 w/v ratio. E-beam exposure followed by development with MIBK solutions showed that these new organic-inorganic hybrid photoresists show good line patterns upto 16 nm, which were not observed in the case of control experiments done on pure PMMA polymer resist. The observed enhancement of resist properties in the case of hybrid resists could possibly be due to a combination of features imparted to the resist by the POM clusters such as increased sensitivity, etch resistance and thermal stability.

Spike sorting based upon machine learning algorithms (SOMA).

PubMed

Horton, P M; Nicol, A U; Kendrick, K M; Feng, J F

2007-02-15

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would only identify a known number of clusters. Our extra techniques automatically identify the number of clusters within the dataset, and their sizes, thereby reducing the chance of misclassification. We also discuss a new pre-processing technique, which transforms the data into a higher dimensional feature space revealing separable clusters. Using principal component analysis (PCA) alone may not achieve this. Our new approach appends the features acquired using PCA with features describing the geometric shapes that constitute a spike waveform. To validate our new spike sorting approach, we have applied it to multi-electrode array datasets acquired from the rat olfactory bulb, and from the sheep infero-temporal cortex, and using simulated data. The SOMA sofware is available at http://www.sussex.ac.uk/Users/pmh20/spikes.

Message Passing and Shared Address Space Parallelism on an SMP Cluster

NASA Technical Reports Server (NTRS)

Shan, Hongzhang; Singh, Jaswinder P.; Oliker, Leonid; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2002-01-01

Currently, message passing (MP) and shared address space (SAS) are the two leading parallel programming paradigms. MP has been standardized with MPI, and is the more common and mature approach; however, code development can be extremely difficult, especially for irregularly 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 the programming effort required for six applications under both programming models on a 32-processor PC-SMP cluster, a platform that is becoming increasingly attractive for high-end scientific computing. Our application suite consists of codes that typically do not exhibit scalable performance under shared-memory programming due to their high communication-to-computation ratios and/or complex communication patterns. Results indicate that SAS can achieve about half the parallel efficiency of MPI for most of our applications, while being competitive for the others. A hybrid MPI+SAS strategy shows only a small performance advantage over pure MPI in some cases. Finally, improved implementations of two MPI collective operations on PC-SMP clusters are presented.

Clustering Financial Time Series by Network Community Analysis

NASA Astrophysics Data System (ADS)

Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

Colour segmentation of multi variants tuberculosis sputum images using self organizing map

NASA Astrophysics Data System (ADS)

Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

2017-05-01

Lung tuberculosis detection is still identified from Ziehl-Neelsen sputum smear images in low and middle countries. The clinicians decide the grade of this disease by counting manually the amount of tuberculosis bacilli. It is very tedious for clinicians with a lot number of patient and without standardization for sputum staining. The tuberculosis sputum images have multi variant characterizations in colour, because of no standardization in staining. The sputum has more variants colour and they are difficult to be identified. For helping the clinicians, this research examined the Self Organizing Map method for colouring image segmentation in sputum images based on colour clustering. This method has better performance than k-means clustering which also tried in this research. The Self Organizing Map could segment the sputum images with y good result and cluster the colours adaptively.

Computational methods for evaluation of cell-based data assessment--Bioconductor.

PubMed

Le Meur, Nolwenn

2013-02-01

Recent advances in miniaturization and automation of technologies have enabled cell-based assay high-throughput screening, bringing along new challenges in data analysis. Automation, standardization, reproducibility have become requirements for qualitative research. The Bioconductor community has worked in that direction proposing several R packages to handle high-throughput data including flow cytometry (FCM) experiment. Altogether, these packages cover the main steps of a FCM analysis workflow, that is, data management, quality assessment, normalization, outlier detection, automated gating, cluster labeling, and feature extraction. Additionally, the open-source philosophy of R and Bioconductor, which offers room for new development, continuously drives research and improvement of theses analysis methods, especially in the field of clustering and data mining. This review presents the principal FCM packages currently available in R and Bioconductor, their advantages and their limits. Copyright © 2012 Elsevier Ltd. All rights reserved.

Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

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

Hogan, Emilie A.; Cotilla Sanchez, Jose E.; Halappanavar, Mahantesh

2013-11-30

Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques onmore » two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.« less

The quantitative analysis of silicon carbide surface smoothing by Ar and Xe cluster ions

NASA Astrophysics Data System (ADS)

Ieshkin, A. E.; Kireev, D. S.; Ermakov, Yu. A.; Trifonov, A. S.; Presnov, D. E.; Garshev, A. V.; Anufriev, Yu. V.; Prokhorova, I. G.; Krupenin, V. A.; Chernysh, V. S.

2018-04-01

The gas cluster ion beam technique was used for the silicon carbide crystal surface smoothing. The effect of processing by two inert cluster ions, argon and xenon, was quantitatively compared. While argon is a standard element for GCIB, results for xenon clusters were not reported yet. Scanning probe microscopy and high resolution transmission electron microscopy techniques were used for the analysis of the surface roughness and surface crystal layer quality. The gas cluster ion beam processing results in surface relief smoothing down to average roughness about 1 nm for both elements. It was shown that xenon as the working gas is more effective: sputtering rate for xenon clusters is 2.5 times higher than for argon at the same beam energy. High resolution transmission electron microscopy analysis of the surface defect layer gives values of 7 ± 2 nm and 8 ± 2 nm for treatment with argon and xenon clusters.

XMM-Newton Observations of the Cluster of Galaxies Sersic 159-03

NASA Technical Reports Server (NTRS)

Kaastra, J. S.; Ferrigno, C.; Tamura, T.; Paerels, F. B. S.; Peterson, J. R.; Mittaz, J. P. D.

2000-01-01

The cluster of galaxies Sersic 159-03 was observed with the XMM-Newton X-ray observatory as part of the Guaranteed Time program. X-ray spectra taken with the EPIC and RGS instruments show no evidence for the strong cooling flow derived from previous X-ray observations. There is a significant lack of cool gas below 1.5 keV as compared to standard isobaric cooling flow models. While the oxygen is distributed more or less uniformly over the cluster, iron shows a strong concentration in the center of the cluster, slightly offset from the brightness center but within the central cD galaxy. This points to enhanced type Ia supernova activity in the center of the cluster. There is also an elongated iron-rich structure ex- tending to the east of the cluster, showing the inhomogeneity of the iron distribution. Finally, the temperature drops rapidly beyond 4' from the cluster center.

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

PubMed

Sun, Yanfeng; Gao, Junbin; Hong, Xia; Mishra, Bamdev; Yin, Baocai

2016-03-01

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

NASA Astrophysics Data System (ADS)

Di, Nur Faraidah Muhammad; Satari, Siti Zanariah

2017-05-01

Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically utilizes distance measure to define distance between various data points. Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. It is found that the proposed methods are performed well and applicable for circular regression model.

MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

PubMed Central

Hartler, Jürgen; Thallinger, Gerhard G; Stocker, Gernot; Sturn, Alexander; Burkard, Thomas R; Körner, Erik; Rader, Robert; Schmidt, Andreas; Mechtler, Karl; Trajanoski, Zlatko

2007-01-01

Background The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. Results We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at Conclusion Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community. PMID:17567892

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

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

Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods aremore » applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.« less

A spatial scan statistic for multiple clusters.

PubMed

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2011-10-01

Spatial scan statistics are commonly used for geographical disease surveillance and cluster detection. While there are multiple clusters coexisting in the study area, they become difficult to detect because of clusters' shadowing effect to each other. The recently proposed sequential method showed its better power for detecting the second weaker cluster, but did not improve the ability of detecting the first stronger cluster which is more important than the second one. We propose a new extension of the spatial scan statistic which could be used to detect multiple clusters. Through constructing two or more clusters in the alternative hypothesis, our proposed method accounts for other coexisting clusters in the detecting and evaluating process. The performance of the proposed method is compared to the sequential method through an intensive simulation study, in which our proposed method shows better power in terms of both rejecting the null hypothesis and accurately detecting the coexisting clusters. In the real study of hand-foot-mouth disease data in Pingdu city, a true cluster town is successfully detected by our proposed method, which cannot be evaluated to be statistically significant by the standard method due to another cluster's shadowing effect. Copyright © 2011 Elsevier Inc. All rights reserved.

Electronic structure of the unique [4Fe-3S] cluster in O2-tolerant hydrogenases characterized by 57Fe Mössbauer and EPR spectroscopy

PubMed Central

Pandelia, Maria-Eirini; Bykov, Dmytro; Izsak, Robert; Infossi, Pascale; Giudici-Orticoni, Marie-Thérèse; Bill, Eckhard; Neese, Frank; Lubitz, Wolfgang

2013-01-01

Iron–sulfur clusters are ubiquitous electron transfer cofactors in hydrogenases. Their types and redox properties are important for H2 catalysis, but, recently, their role in a protection mechanism against oxidative inactivation has also been recognized for a [4Fe-3S] cluster in O2-tolerant group 1 [NiFe] hydrogenases. This cluster, which is uniquely coordinated by six cysteines, is situated in the proximity of the catalytic [NiFe] site and exhibits unusual redox versatility. The [4Fe-3S] cluster in hydrogenase (Hase) I from Aquifex aeolicus performs two redox transitions within a very small potential range, forming a superoxidized state above +200 mV vs. standard hydrogen electrode (SHE). Crystallographic data has revealed that this state is stabilized by the coordination of one of the iron atoms to a backbone nitrogen. Thus, the proximal [4Fe-3S] cluster undergoes redox-dependent changes to serve multiple purposes beyond classical electron transfer. In this paper, we present field-dependent 57Fe-Mössbauer and EPR data for Hase I, which, in conjunction with spectroscopically calibrated density functional theory (DFT) calculations, reveal the distribution of Fe valences and spin-coupling schemes for the iron–sulfur clusters. The data demonstrate that the electronic structure of the [4Fe-3S] core in its three oxidation states closely resembles that of corresponding conventional [4Fe-4S] cubanes, albeit with distinct differences for some individual iron sites. The medial and distal iron–sulfur clusters have similar electronic properties as the corresponding cofactors in standard hydrogenases, although their redox potentials are higher. PMID:23267108

Two-year impact of community-based health screening and parenting groups on child development in Zambia: Follow-up to a cluster-randomized controlled trial.

PubMed

Rockers, Peter C; Zanolini, Arianna; Banda, Bowen; Chipili, Mwaba Moono; Hughes, Robert C; Hamer, Davidson H; Fink, Günther

2018-04-01

Early childhood interventions have potential to offset the negative impact of early adversity. We evaluated the impact of a community-based parenting group intervention on child development in Zambia. We conducted a non-masked cluster-randomized controlled trial in Southern Province, Zambia. Thirty clusters of villages were matched based on population density and distance from the nearest health center, and randomly assigned to intervention (15 clusters, 268 caregiver-child dyads) or control (15 clusters, 258 caregiver-child dyads). Caregivers were eligible if they had a child 6 to 12 months old at baseline. In intervention clusters, caregivers were visited twice per month during the first year of the study by child development agents (CDAs) and were invited to attend fortnightly parenting group meetings. Parenting groups selected "head mothers" from their communities who were trained by CDAs to facilitate meetings and deliver a diverse parenting curriculum. The parenting group intervention, originally designed to run for 1 year, was extended, and households were visited for a follow-up assessment at the end of year 2. The control group did not receive any intervention. Intention-to-treat analysis was performed for primary outcomes measured at the year 2 follow-up: stunting and 5 domains of neurocognitive development measured using the Bayley Scales of Infant and Toddler Development-Third Edition (BSID-III). In order to show Cohen's d estimates, BSID-III composite scores were converted to z-scores by standardizing within the study population. In all, 195/268 children (73%) in the intervention group and 182/258 children (71%) in the control group were assessed at endline after 2 years. The intervention significantly reduced stunting (56/195 versus 72/182; adjusted odds ratio 0.45, 95% CI 0.22 to 0.92; p = 0.028) and had a significant positive impact on language (β 0.14, 95% CI 0.01 to 0.27; p = 0.039). The intervention did not significantly impact cognition (β 0.11, 95% CI -0.06 to 0.29; p = 0.196), motor skills (β -0.01, 95% CI -0.25 to 0.24; p = 0.964), adaptive behavior (β 0.21, 95% CI -0.03 to 0.44; p = 0.088), or social-emotional development (β 0.20, 95% CI -0.04 to 0.44; p = 0.098). Observed impacts may have been due in part to home visits by CDAs during the first year of the intervention. The results of this trial suggest that parenting groups hold promise for improving child development, particularly physical growth, in low-resource settings like Zambia. ClinicalTrials.gov NCT02234726.

Singlet-paired coupled cluster theory for open shells

NASA Astrophysics Data System (ADS)

Gomez, John A.; Henderson, Thomas M.; Scuseria, Gustavo E.

2016-06-01

Restricted single-reference coupled cluster theory truncated to single and double excitations accurately describes weakly correlated systems, but often breaks down in the presence of static or strong correlation. Good coupled cluster energies in the presence of degeneracies can be obtained by using a symmetry-broken reference, such as unrestricted Hartree-Fock, but at the cost of good quantum numbers. A large body of work has shown that modifying the coupled cluster ansatz allows for the treatment of strong correlation within a single-reference, symmetry-adapted framework. The recently introduced singlet-paired coupled cluster doubles (CCD0) method is one such model, which recovers correct behavior for strong correlation without requiring symmetry breaking in the reference. Here, we extend singlet-paired coupled cluster for application to open shells via restricted open-shell singlet-paired coupled cluster singles and doubles (ROCCSD0). The ROCCSD0 approach retains the benefits of standard coupled cluster theory and recovers correct behavior for strongly correlated, open-shell systems using a spin-preserving ROHF reference.

Sulfur in Cometary Dust

NASA Technical Reports Server (NTRS)

Fomenkova, M. N.

1997-01-01

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Running climate model on a commercial cloud computing environment: A case study using Community Earth System Model (CESM) on Amazon AWS

NASA Astrophysics Data System (ADS)

Chen, Xiuhong; Huang, Xianglei; Jiao, Chaoyi; Flanner, Mark G.; Raeker, Todd; Palen, Brock

2017-01-01

The suites of numerical models used for simulating climate of our planet are usually run on dedicated high-performance computing (HPC) resources. This study investigates an alternative to the usual approach, i.e. carrying out climate model simulations on commercially available cloud computing environment. We test the performance and reliability of running the CESM (Community Earth System Model), a flagship climate model in the United States developed by the National Center for Atmospheric Research (NCAR), on Amazon Web Service (AWS) EC2, the cloud computing environment by Amazon.com, Inc. StarCluster is used to create virtual computing cluster on the AWS EC2 for the CESM simulations. The wall-clock time for one year of CESM simulation on the AWS EC2 virtual cluster is comparable to the time spent for the same simulation on a local dedicated high-performance computing cluster with InfiniBand connections. The CESM simulation can be efficiently scaled with the number of CPU cores on the AWS EC2 virtual cluster environment up to 64 cores. For the standard configuration of the CESM at a spatial resolution of 1.9° latitude by 2.5° longitude, increasing the number of cores from 16 to 64 reduces the wall-clock running time by more than 50% and the scaling is nearly linear. Beyond 64 cores, the communication latency starts to outweigh the benefit of distributed computing and the parallel speedup becomes nearly unchanged.

Dynamic PROOF clusters with PoD: architecture and user experience

NASA Astrophysics Data System (ADS)

Manafov, Anar

2011-12-01

PROOF on Demand (PoD) is a tool-set, which sets up a PROOF cluster on any resource management system. PoD is a user oriented product with an easy to use GUI and a command-line interface. It is fully automated. No administrative privileges or special knowledge is required to use it. PoD utilizes a plug-in system, to use different job submission front-ends. The current PoD distribution is shipped with LSF, Torque (PBS), Grid Engine, Condor, gLite, and SSH plug-ins. The product is to be extended. We therefore plan to implement a plug-in for AliEn Grid as well. Recently developed algorithms made it possible to efficiently maintain two types of connections: packet-forwarding and native PROOF connections. This helps to properly handle most kinds of workers, with and without firewalls. PoD maintains the PROOF environment automatically and, for example, prevents resource misusage in case when workers idle for too long. As PoD matures as a product and provides more plug-ins, it's used as a standard for setting up dynamic PROOF clusters in many different institutions. The GSI Analysis Facility (GSIAF) is in production since 2007. The static PROOF cluster has been phased out end of 2009. GSIAF is now completely based on PoD. Users create private dynamic PROOF clusters on the general purpose batch farm. This provides an easier resource sharing between interactive local batch and Grid usage. The main user communities are FAIR and ALICE.

RUPRECHT 147: THE OLDEST NEARBY OPEN CLUSTER AS A NEW BENCHMARK FOR STELLAR ASTROPHYSICS

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

Curtis, Jason L.; Wright, Jason T.; Wolfgang, Angie

2013-05-15

Ruprecht 147 is a hitherto unappreciated open cluster that holds great promise as a standard in fundamental stellar astrophysics. We have conducted a radial velocity survey of astrometric candidates with Lick, Palomar, and MMT observatories and have identified over 100 members, including 5 blue stragglers, 11 red giants, and 5 double-lined spectroscopic binaries (SB2s). We estimate the cluster metallicity from spectroscopic analysis, using Spectroscopy Made Easy (SME), and find it to be [M/H] = +0.07 {+-} 0.03. We have obtained deep CFHT/MegaCam g'r'i'z' photometry and fit Padova isochrones to the (g' - i') and Two Micron All Sky Survey (Jmore » - K{sub S} ) color-magnitude diagrams, using the {tau}{sup 2} maximum-likelihood procedure of Naylor, and an alternative method using two-dimensional cross-correlations developed in this work. We find best fits for Padova isochrones at age t = 2.5 {+-} 0.25 Gyr, m - M = 7.35 {+-} 0.1, and A{sub V} = 0.25 {+-} 0.05, with additional uncertainty from the unresolved binary population and possibility of differential extinction across this large cluster. The inferred age is heavily dependent on our choice of stellar evolution model: fitting Dartmouth and PARSEC models yield age parameters of 3 Gyr and 3.25 Gyr, respectively. At {approx}300 pc and {approx}3 Gyr, Ruprecht 147 is by far the oldest nearby star cluster.« less

Related Core Academic Knowledge and Skills. Georgia Core Standards for Occupational Clusters.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Dept. of Occupational Studies.

This document lists the industry-identified core academic knowledge and skills that should be possessed by all Georgia students who are enrolled in occupational cluster programs and are preparing to enter the work force or continue their occupational specialization at the postsecondary level. First, 63 related communications competencies are…

An improved K-means clustering method for cDNA microarray image segmentation.

PubMed

Wang, T N; Li, T J; Shao, G F; Wu, S X

2015-07-14

Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

On the Coupling Time of the Heat-Bath Process for the Fortuin-Kasteleyn Random-Cluster Model

NASA Astrophysics Data System (ADS)

Collevecchio, Andrea; Elçi, Eren Metin; Garoni, Timothy M.; Weigel, Martin

2018-01-01

We consider the coupling from the past implementation of the random-cluster heat-bath process, and study its random running time, or coupling time. We focus on hypercubic lattices embedded on tori, in dimensions one to three, with cluster fugacity at least one. We make a number of conjectures regarding the asymptotic behaviour of the coupling time, motivated by rigorous results in one dimension and Monte Carlo simulations in dimensions two and three. Amongst our findings, we observe that, for generic parameter values, the distribution of the appropriately standardized coupling time converges to a Gumbel distribution, and that the standard deviation of the coupling time is asymptotic to an explicit universal constant multiple of the relaxation time. Perhaps surprisingly, we observe these results to hold both off criticality, where the coupling time closely mimics the coupon collector's problem, and also at the critical point, provided the cluster fugacity is below the value at which the transition becomes discontinuous. Finally, we consider analogous questions for the single-spin Ising heat-bath process.

Testing Gravity and Cosmic Acceleration with Galaxy Clustering

NASA Astrophysics Data System (ADS)

Kazin, Eyal; Tinker, J.; Sanchez, A. G.; Blanton, M.

2012-01-01

The large-scale structure contains vast amounts of cosmological information that can help understand the accelerating nature of the Universe and test gravity on large scales. Ongoing and future sky surveys are designed to test these using various techniques applied on clustering measurements of galaxies. We present redshift distortion measurements of the Sloan Digital Sky Survey II Luminous Red Galaxy sample. We find that when combining the normalized quadrupole Q with the projected correlation function wp(rp) along with cluster counts (Rapetti et al. 2010), results are consistent with General Relativity. The advantage of combining Q and wp is the addition of the bias information, when using the Halo Occupation Distribution framework. We also present improvements to the standard technique of measuring Hubble expansion rates H(z) and angular diameter distances DA(z) when using the baryonic acoustic feature as a standard ruler. We introduce clustering wedges as an alternative basis to the multipole expansion and show that it yields similar constraints. This alternative basis serves as a useful technique to test for systematics, and ultimately improve measurements of the cosmic acceleration.

Role of childhood traumatic experience in personality disorders in China.

PubMed

Zhang, TianHong; Chow, Annabelle; Wang, LanLan; Dai, YunFei; Xiao, ZePing

2012-08-01

There has been no large-scale examination of the association between types of childhood abuse and personality disorders (PDs) in China using standardized assessment tools and the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. Hence, this study aimed to explore the relationship between retrospective reports of various types of childhood maltreatments and current DSM-IV PDs in a clinical population in China, Shanghai. One thousand four hundred two subjects were randomly sampled from the Shanghai Psychological Counselling Centre. PDs were assessed using the Personality Diagnostic Questionnaire, Fourth Edition Plus. Participants were also interviewed using the Structured Clinical Interview for DSM-IV axis II. The Child Trauma Questionnaire (CTQ) was used to assess childhood maltreatment in 5 domains (emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect). According to Pearson correlations, childhood maltreatment had a strong association with most PDs. Subsequently, using partial correlations, significant relationships were also demonstrated between cluster B PDs and all the traumatic factors except physical neglect. A strongest positive correlation was found between cluster B PD and CTQ total scores (r = .312, P < .01). Using the Kruskal-Wallis rank sum test, significant differences in 4 groups of subjects (clusters A, B, and C PD and non-PD) in terms of emotional abuse (χ(2) = 34.864, P < .01), physical abuse (χ(2) = 14.996, P < .05), sex abuse (χ(2) = 9.211, P < .05), and emotional neglect (χ(2) = 17.987, P < .01) were found. Stepwise regression analysis indicated that emotional abuse and emotional neglect were predictive for clusters A and B PD, and sexual abuse was highly predictive for cluster B PD; only emotional neglect was predictive for cluster C PD. Early traumatic experiences are strongly related to the development of PDs. The effects of childhood maltreatment in the 3 clusters of PDs are different. Childhood trauma has the most significant impact on cluster B PD. Copyright © 2012 Elsevier Inc. All rights reserved.

A computational linguistic measure of clustering behavior on semantic verbal fluency task predicts risk of future dementia in the nun study.

PubMed

Pakhomov, Serguei V S; Hemmy, Laura S

2014-06-01

Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer's disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters. We evaluated a novel automated computational linguistic approach for quantifying clustering behavior. Our approach is based on Latent Semantic Analysis (LSA) for computing strength of semantic relatedness between pairs of words produced in response to SVF test. The mean size of semantic clusters (MCS) and semantic chains (MChS) are calculated based on pairwise relatedness values between words. We evaluated the predictive validity of these measures on a set of 239 participants in the Nun Study, a longitudinal study of aging. All were cognitively intact at baseline assessment, measured with the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery, and were followed in 18-month waves for up to 20 years. The onset of either dementia or memory impairment were used as outcomes in Cox proportional hazards models adjusted for age and education and censored at follow-up waves 5 (6.3 years) and 13 (16.96 years). Higher MCS was associated with 38% reduction in dementia risk at wave 5 and 26% reduction at wave 13, but not with the onset of memory impairment. Higher [+1 standard deviation (SD)] MChS was associated with 39% dementia risk reduction at wave 5 but not wave 13, and association with memory impairment was not significant. Higher traditional SVF scores were associated with 22-29% memory impairment and 35-40% dementia risk reduction. SVF scores were not correlated with either MCS or MChS. Our study suggests that an automated approach to measuring clustering behavior can be used to estimate dementia risk in cognitively normal individuals. Copyright © 2013 Elsevier Ltd. All rights reserved.

Clustering of samples and variables with mixed-type data

PubMed Central

Edelmann, Dominic; Kopp-Schneider, Annette

2017-01-01

Analysis of data measured on different scales is a relevant challenge. Biomedical studies often focus on high-throughput datasets of, e.g., quantitative measurements. However, the need for integration of other features possibly measured on different scales, e.g. clinical or cytogenetic factors, becomes increasingly important. The analysis results (e.g. a selection of relevant genes) are then visualized, while adding further information, like clinical factors, on top. However, a more integrative approach is desirable, where all available data are analyzed jointly, and where also in the visualization different data sources are combined in a more natural way. Here we specifically target integrative visualization and present a heatmap-style graphic display. To this end, we develop and explore methods for clustering mixed-type data, with special focus on clustering variables. Clustering of variables does not receive as much attention in the literature as does clustering of samples. We extend the variables clustering methodology by two new approaches, one based on the combination of different association measures and the other on distance correlation. With simulation studies we evaluate and compare different clustering strategies. Applying specific methods for mixed-type data proves to be comparable and in many cases beneficial as compared to standard approaches applied to corresponding quantitative or binarized data. Our two novel approaches for mixed-type variables show similar or better performance than the existing methods ClustOfVar and bias-corrected mutual information. Further, in contrast to ClustOfVar, our methods provide dissimilarity matrices, which is an advantage, especially for the purpose of visualization. Real data examples aim to give an impression of various kinds of potential applications for the integrative heatmap and other graphical displays based on dissimilarity matrices. We demonstrate that the presented integrative heatmap provides more information than common data displays about the relationship among variables and samples. The described clustering and visualization methods are implemented in our R package CluMix available from https://cran.r-project.org/web/packages/CluMix. PMID:29182671

The effect of a patient centred care bundle intervention on pressure ulcer incidence (INTACT): A cluster randomised trial.

PubMed

Chaboyer, Wendy; Bucknall, Tracey; Webster, Joan; McInnes, Elizabeth; Gillespie, Brigid M; Banks, Merrilyn; Whitty, Jennifer A; Thalib, Lukman; Roberts, Shelley; Tallott, Mandy; Cullum, Nicky; Wallis, Marianne

2016-12-01

Hospital-acquired pressure ulcers are a serious patient safety concern, associated with poor patient outcomes and high healthcare costs. They are also viewed as an indicator of nursing care quality. To evaluate the effectiveness of a pressure ulcer prevention care bundle in preventing hospital-acquired pressure ulcers among at risk patients. Pragmatic cluster randomised trial. Eight tertiary referral hospitals with >200 beds each in three Australian states. 1600 patients (200/hospital) were recruited. Patients were eligible if they were: ≥18 years old; at risk of pressure ulcer because of limited mobility; expected to stay in hospital ≥48h and able to read English. Hospitals (clusters) were stratified in two groups by recent pressure ulcer rates and randomised within strata to either a pressure ulcer prevention care bundle or standard care. The care bundle was theoretically and empirically based on patient participation and clinical practice guidelines. It was multi-component, with three messages for patients' participation in pressure ulcer prevention care: keep moving; look after your skin; and eat a healthy diet. Training aids for patients included a DVD, brochure and poster. Nurses in intervention hospitals were trained in partnering with patients in their pressure ulcer prevention care. The statistician, recruiters, and outcome assessors were blinded to group allocation and interventionists blinded to the study hypotheses, tested at both the cluster and patient level. The primary outcome, incidence of hospital-acquired pressure ulcers, which applied to both the cluster and individual participant level, was measured by daily skin inspection. Four clusters were randomised to each group and 799 patients per group analysed. The intraclass correlation coefficient was 0.035. After adjusting for clustering and pre-specified covariates (age, pressure ulcer present at baseline, body mass index, reason for admission, residence and number of comorbidities on admission), the hazard ratio for new pressure ulcers developed (pressure ulcer prevention care bundle relative to standard care) was 0.58 (95% CI: 0.25, 1.33; p=0.198). No adverse events or harms were reported. Although the pressure ulcer prevention care bundle was associated with a large reduction in the hazard of ulceration, there was a high degree of uncertainty around this estimate and the difference was not statistically significant. Possible explanations for this non-significant finding include that the pressure ulcer prevention care bundle was effective but the sample size too small to detect this. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Pragmatic service development and customisation with the CEDA OGC Web Services framework

NASA Astrophysics Data System (ADS)

Pascoe, Stephen; Stephens, Ag; Lowe, Dominic

2010-05-01

The CEDA OGC Web Services framework (COWS) emphasises rapid service development by providing a lightweight layer of OGC web service logic on top of Pylons, a mature web application framework for the Python language. This approach gives developers a flexible web service development environment without compromising access to the full range of web application tools and patterns: Model-View-Controller paradigm, XML templating, Object-Relational-Mapper integration and authentication/authorization. We have found this approach useful for exploring evolving standards and implementing protocol extensions to meet the requirements of operational deployments. This paper outlines how COWS is being used to implement customised WMS, WCS, WFS and WPS services in a variety of web applications from experimental prototypes to load-balanced cluster deployments serving 10-100 simultaneous users. In particular we will cover 1) The use of Climate Science Modeling Language (CSML) in complex-feature aware WMS, WCS and WFS services, 2) Extending WMS to support applications with features specific to earth system science and 3) A cluster-enabled Web Processing Service (WPS) supporting asynchronous data processing. The COWS WPS underpins all backend services in the UK Climate Projections User Interface where users can extract, plot and further process outputs from a multi-dimensional probabilistic climate model dataset. The COWS WPS supports cluster job execution, result caching, execution time estimation and user management. The COWS WMS and WCS components drive the project-specific NCEO and QESDI portals developed by the British Atmospheric Data Centre. These portals use CSML as a backend description format and implement features such as multiple WMS layer dimensions and climatology axes that are beyond the scope of general purpose GIS tools and yet vital for atmospheric science applications.

Using the infrastructure of a conditional cash transfer program to deliver a scalable integrated early child development program in Colombia: cluster randomized controlled trial

PubMed Central

Attanasio, Orazio P; Fernández, Camila; Grantham-McGregor, Sally M; Meghir, Costas; Rubio-Codina, Marta

2014-01-01

Objective To assess the effectiveness of an integrated early child development intervention, combining stimulation and micronutrient supplementation and delivered on a large scale in Colombia, for children’s development, growth, and hemoglobin levels. Design Cluster randomized controlled trial, using a 2×2 factorial design, with municipalities assigned to one of four groups: psychosocial stimulation, micronutrient supplementation, combined intervention, or control. Setting 96 municipalities in Colombia, located across eight of its 32 departments. Participants 1420 children aged 12-24 months and their primary carers. Intervention Psychosocial stimulation (weekly home visits with play demonstrations), micronutrient sprinkles given daily, and both combined. All delivered by female community leaders for 18 months. Main outcome measures Cognitive, receptive and expressive language, and fine and gross motor scores on the Bayley scales of infant development-III; height, weight, and hemoglobin levels measured at the baseline and end of intervention. Results Stimulation improved cognitive scores (adjusted for age, sex, testers, and baseline levels of outcomes) by 0.26 of a standard deviation (P=0.002). Stimulation also increased receptive language by 0.22 of a standard deviation (P=0.032). Micronutrient supplementation had no significant effect on any outcome and there was no interaction between the interventions. No intervention affected height, weight, or hemoglobin levels. Conclusions Using the infrastructure of a national welfare program we implemented the integrated early child development intervention on a large scale and showed its potential for improving children’s cognitive development. We found no effect of supplementation on developmental or health outcomes. Moreover, supplementation did not interact with stimulation. The implementation model for delivering stimulation suggests that it may serve as a promising blueprint for future policy on early childhood development. Trial registration Current Controlled trials ISRCTN18991160. PMID:25266222

ENVRIplus - European collaborative development of environmental infrastructures

NASA Astrophysics Data System (ADS)

Asmi, A.; Brus, M.; Kutsch, W. L.; Laj, P.

2016-12-01

European Research Infrastructures (RI) are built using ESFRI process, which dictates the steps towards a common European RIs. Building each RI separately creates unnessary barriers towards service users (e.g. on differing standards) and is not effiicient in e.g. e-science tool or data system development. To answer these inter-RI issues, the European Commission has funded several large scale cluster projectsto bring these RIs together already in planning and development phases to develop common tools, standards and methodologies, as well as learn from the exisiting systems. ENVRIplus is the cluster project for the environmental RIs in Europe, and provides platform for common development and sharing within the RI community. The project is organized around different themes, each having several workpackages with specific tasks. Major themesof the ENVRIplus are: Technical innovation, including tasks such as RI technology transfer, new observation techniques, autonomous operation, etc.; Data for science, with tasks such as RI reference model development, data discovery and citation, data publication, processing, etc.; Access to RIs, with specific tasks on interdicplinary and transnational access to RI services, and common access governance; Societal relevance and understanding, tackling on ethical issues on RI operations and understanding on human-environmental system and citizen science approaches, among others; Knowledge transfer, particularly between the RIs, and with developing RI organizations, organizing training and staff exchange; and Communication and dissemination, working towards a common environmental RI community (ENVRI community platform), and creating an own advisory RI discussion board (BEERi), and disseminating the ENVRIplus products globally. Importantly, all ENVRIplus results are open to any users from any country. Also, collaboration with international RIs and user communities are crucial to the success of the ENVRI initiatives. Overall goal is to do science globally, to answer global and regional critical challenges. The presentation will not only present the project, its state after nearly 2 years of operation, but will alsop present ideas towards building international and even more interdiciplinary collaboration on research infrastructures and their users.

Multifocal visual evoked potentials for early glaucoma detection.

PubMed

Weizer, Jennifer S; Musch, David C; Niziol, Leslie M; Khan, Naheed W

2012-07-01

To compare multifocal visual evoked potentials (mfVEP) with other detection methods in early open-angle glaucoma. Ten patients with suspected glaucoma and 5 with early open-angle glaucoma underwent mfVEP, standard automated perimetry (SAP), short-wave automated perimetry, frequency-doubling technology perimetry, and nerve fiber layer optical coherence tomography. Nineteen healthy control subjects underwent mfVEP and SAP for comparison. Comparisons between groups involving continuous variables were made using independent t tests; for categorical variables, Fisher's exact test was used. Monocular mfVEP cluster defects were associated with an increased SAP pattern standard deviation (P = .0195). Visual fields that showed interocular mfVEP cluster defects were more likely to also show superior quadrant nerve fiber layer thinning by OCT (P = .0152). Multifocal visual evoked potential cluster defects are associated with a functional and an anatomic measure that both relate to glaucomatous optic neuropathy. Copyright 2012, SLACK Incorporated.

Progeny Clustering: A Method to Identify Biological Phenotypes

PubMed Central

Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

2015-01-01

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

Coarsening of protein clusters on subcellular drops exhibits strong and sudden size selectivity

NASA Astrophysics Data System (ADS)

Brown, Aidan; Rutenberg, Andrew

2015-03-01

Autophagy is an important process for the degradation of cellular components, with receptor proteins targeting substrates to downstream autophagy machinery. An important question is how receptor protein interactions lead to their selective accumulation on autophagy substrates. Receptor proteins have recently been observed in clusters, raising the possibility that clustering could affect autophagy selectivity. We investigate the clustering dynamics of the autophagy receptor protein NBR1. In addition to standard receptor protein domains, NBR1 has a ``J'' domain that anchors it to membranes, and a coiled-coil domain that enhances self-interaction. We model coarsening clusters of NBR1 on the surfaces of a polydisperse collection of drops, representing organelles. Despite the disconnected nature of the drop surfaces, we recover dynamical scaling of cluster sizes. Significantly, we find that at a well-defined time after coarsening begins, clusters evaporate from smaller drops and grow on larger drops. Thus, coarsening-driven size selection will localize protein clusters to larger substrates, leaving smaller substrates without clusters. This provides a possible physical mechanism for autophagy selectivity, and can explain reports of size selection during peroxisome degradation.

Galaxy cluster luminosities and colours, and their dependence on cluster mass and merger state

NASA Astrophysics Data System (ADS)

Mulroy, Sarah L.; McGee, Sean L.; Gillman, Steven; Smith, Graham P.; Haines, Chris P.; Démoclès, Jessica; Okabe, Nobuhiro; Egami, Eiichi

2017-12-01

We study a sample of 19 galaxy clusters in the redshift range 0.15 < z < 0.30 with highly complete spectroscopic membership catalogues (to K < K*(z) + 1.5) from the Arizona Cluster Redshift Survey, individual weak-lensing masses and near-infrared data from the Local Cluster Substructure Survey, and optical photometry from the Sloan Digital Sky Survey. We fit the scaling relations between total cluster luminosity in each of six bandpasses (grizJK) and cluster mass, finding cluster luminosity to be a promising mass proxy with low intrinsic scatter σln L|M of only ∼10-20 per cent for all relations. At fixed overdensity radius, the intercept increases with wavelength, consistent with an old stellar population. The scatter and slope are consistent across all wavelengths, suggesting that cluster colour is not a function of mass. Comparing colour with indicators of the level of disturbance in the cluster, we find a narrower variety in the cluster colours of 'disturbed' clusters than of 'undisturbed' clusters. This trend is more pronounced with indicators sensitive to the initial stages of a cluster merger, e.g. the Dressler Schectman statistic. We interpret this as possible evidence that the total cluster star formation rate is 'standardized' in mergers, perhaps through a process such as a system-wide shock in the intracluster medium.

Innovative Improvement and Intensification of Business Relationships Supported by Cooperative Networks

NASA Astrophysics Data System (ADS)

Vančová, Viera; Čambál, Miloš; Cagáňová, Dagmar

2012-12-01

Nowadays, the opportunity for companies to be involved in cluster initiatives and international business associations is a major factor that contributes to the increase of their innovative potential. Companies organized in technological clusters have greater access to mutual business contacts, faster information transfer and deployment of advanced technologies. These companies cooperate more frequently with universities and research - development institutions on innovative projects. An important benefit of cluster associations is that they create a suitable environment for innovation and the transfer of knowledge by means of international cooperation and networking. This supportive environment is not easy to access for different small and mediumsized companies, who are not members of any clusters or networks. Supplier-customer business channels expand by means of transnational networks and exchanges of experience. Knowledge potential is broadened and joint innovative projects are developed. Reflecting the growing importance of clusters as driving forces of economic and regional development, a number of cluster policies and initiatives have emerged in the last few decades, oriented to encourage the establishment of new clusters, to support existing clusters, or to assist the development of transnational cooperation. To achieve the goals of the Europe 2020 Strategy, European countries should have an interest in building strong clusters and developing cluster cooperation by sharing specialized research infrastructures and testing facilities and facilitating knowledge transfer for crossborder cooperation. This requires developing a long term joint strategy in order to facilitate the development of open global clusters and innovative small and medium entrepreneurs.

Pragmatic setup for bioparticle responses by dielectrophoresis for resource limited environment application

NASA Astrophysics Data System (ADS)

Ali, Mohd Anuar Md; Yeop Majlis, Burhanuddin; Kayani, Aminuddin Ahmad

2017-12-01

Various dielectrophoretic responses of bioparticles, including cell-chain, spinning, rotation and clustering, are of high interest in the field due to their benefit into application for biomedical and clinical implementation potential. Numerous attempts using sophisticated equipment setup have been studied to perform those dielectrophoretic responses, however, for development into resource limited environment application, such as portable, sustainable and environmental friendly diagnostic tools, establishment of pragmatic setup using standard, non-sophisticated and low-cost equipment is of important task. Here we show the advantages in the judicious design optimization of tip microelectrode, also with selection of suspending medium and optimization of electric signal configuration in establishing setup that can promote the aforementioned dielectrophoretic responses within standard equipments, i.e. pragmatic setup.

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

The effect of image processing on the detection of cancers in digital mammography.

PubMed

Warren, Lucy M; Given-Wilson, Rosalind M; Wallis, Matthew G; Cooke, Julie; Halling-Brown, Mark D; Mackenzie, Alistair; Chakraborty, Dev P; Bosmans, Hilde; Dance, David R; Young, Kenneth C

2014-08-01

OBJECTIVE. The objective of our study was to investigate the effect of image processing on the detection of cancers in digital mammography images. MATERIALS AND METHODS. Two hundred seventy pairs of breast images (both breasts, one view) were collected from eight systems using Hologic amorphous selenium detectors: 80 image pairs showed breasts containing subtle malignant masses; 30 image pairs, biopsy-proven benign lesions; 80 image pairs, simulated calcification clusters; and 80 image pairs, no cancer (normal). The 270 image pairs were processed with three types of image processing: standard (full enhancement), low contrast (intermediate enhancement), and pseudo-film-screen (no enhancement). Seven experienced observers inspected the images, locating and rating regions they suspected to be cancer for likelihood of malignancy. The results were analyzed using a jackknife-alternative free-response receiver operating characteristic (JAFROC) analysis. RESULTS. The detection of calcification clusters was significantly affected by the type of image processing: The JAFROC figure of merit (FOM) decreased from 0.65 with standard image processing to 0.63 with low-contrast image processing (p = 0.04) and from 0.65 with standard image processing to 0.61 with film-screen image processing (p = 0.0005). The detection of noncalcification cancers was not significantly different among the image-processing types investigated (p > 0.40). CONCLUSION. These results suggest that image processing has a significant impact on the detection of calcification clusters in digital mammography. For the three image-processing versions and the system investigated, standard image processing was optimal for the detection of calcification clusters. The effect on cancer detection should be considered when selecting the type of image processing in the future.

Impact of a Participatory Intervention with Women’s Groups on Psychological Distress among Mothers in Rural Bangladesh: Secondary Analysis of a Cluster-Randomised Controlled Trial

PubMed Central

Clarke, Kelly; Azad, Kishwar; Kuddus, Abdul; Shaha, Sanjit; Nahar, Tasmin; Aumon, Bedowra Haq; Hossen, Mohammed Munir; Beard, James; Costello, Anthony; Houweling, Tanja A. J.; Prost, Audrey; Fottrell, Edward

2014-01-01

Background Perinatal common mental disorders (PCMDs) are a major cause of disability among women and disproportionately affect lower income countries. Interventions to address PCMDs are urgently needed in these settings, and group-based and peer-led approaches are potential strategies to increase access to mental health interventions. Participatory women’s health groups led by local women previously reduced postpartum psychological distress in eastern India. We assessed the effect of a similar intervention on postpartum psychological distress in rural Bangladesh. Method We conducted a secondary analysis of data from a cluster-randomised controlled trial with 18 clusters and an estimated population of 532,996. Nine clusters received an intervention comprising monthly meetings during which women’s groups worked through a participatory learning and action cycle to develop strategies for improving women’s and children’s health. There was one group for every 309 individuals in the population, 810 groups in total. Mothers in nine control clusters had access to usual perinatal care. Postpartum psychological distress was measured with the 20-item Self Reporting Questionnaire (SRQ-20) between six and 52 weeks after delivery, during the months of January to April, in 2010 and 2011. Results We analysed outcomes for 6275 mothers. Although the cluster mean SRQ-20 score was lower in the intervention arm (mean 5.2, standard deviation 1.8) compared to control (5.3, 1.2), the difference was not significant (β 1.44, 95% CI 0.28, 3.08). Conclusions Despite promising results in India, participatory women’s groups focused on women’s and children’s health had no significant effect on postpartum psychological distress in rural Bangladesh. PMID:25329470

A Web-Based Multidrug-Resistant Organisms Surveillance and Outbreak Detection System with Rule-Based Classification and Clustering

PubMed Central

Tseng, Yi-Ju; Wu, Jung-Hsuan; Ping, Xiao-Ou; Lin, Hui-Chi; Chen, Ying-Yu; Shang, Rung-Ji; Chen, Ming-Yuan; Lai, Feipei

2012-01-01

Background The emergence and spread of multidrug-resistant organisms (MDROs) are causing a global crisis. Combating antimicrobial resistance requires prevention of transmission of resistant organisms and improved use of antimicrobials. Objectives To develop a Web-based information system for automatic integration, analysis, and interpretation of the antimicrobial susceptibility of all clinical isolates that incorporates rule-based classification and cluster analysis of MDROs and implements control chart analysis to facilitate outbreak detection. Methods Electronic microbiological data from a 2200-bed teaching hospital in Taiwan were classified according to predefined criteria of MDROs. The numbers of organisms, patients, and incident patients in each MDRO pattern were presented graphically to describe spatial and time information in a Web-based user interface. Hierarchical clustering with 7 upper control limits (UCL) was used to detect suspicious outbreaks. The system’s performance in outbreak detection was evaluated based on vancomycin-resistant enterococcal outbreaks determined by a hospital-wide prospective active surveillance database compiled by infection control personnel. Results The optimal UCL for MDRO outbreak detection was the upper 90% confidence interval (CI) using germ criterion with clustering (area under ROC curve (AUC) 0.93, 95% CI 0.91 to 0.95), upper 85% CI using patient criterion (AUC 0.87, 95% CI 0.80 to 0.93), and one standard deviation using incident patient criterion (AUC 0.84, 95% CI 0.75 to 0.92). The performance indicators of each UCL were statistically significantly higher with clustering than those without clustering in germ criterion (P < .001), patient criterion (P = .04), and incident patient criterion (P < .001). Conclusion This system automatically identifies MDROs and accurately detects suspicious outbreaks of MDROs based on the antimicrobial susceptibility of all clinical isolates. PMID:23195868

Text messaging reminders for influenza vaccine in primary care: protocol for a cluster randomised controlled trial (TXT4FLUJAB).

PubMed

Herrett, Emily; van Staa, Tjeerd; Free, Caroline; Smeeth, Liam

2014-05-02

The UK government recommends that at least 75% of people aged under 64 with certain conditions receive an annual influenza vaccination. Primary care practices often fall short of this target and strategies to increase vaccine uptake are required. Text messaging reminders are already used in 30% of practices to remind patients about vaccination, but there has been no trial addressing their effectiveness in increasing influenza vaccine uptake in the UK. The aims of the study are (1) to develop the methodology for conducting cluster randomised trials of text messaging interventions utilising routine electronic health records and (2) to assess the effectiveness of using a text messaging influenza vaccine reminder in achieving an increase in influenza vaccine uptake in patients aged 18-64 with chronic conditions, compared with standard care. This cluster randomised trial will recruit general practices across three settings in English primary care (Clinical Practice Research Datalink, ResearchOne and London iPLATO text messaging software users) and randomise them to either standard care or a text messaging campaign to eligible patients. Flu vaccine uptake will be ascertained using routinely collected, anonymised electronic patient records. This protocol outlines the proposed study design and analysis methods. This study will determine the effectiveness of text messaging vaccine reminders in primary care in increasing influenza vaccine uptake, and will strengthen the methodology for using electronic health records in cluster randomised trials of text messaging interventions. This trial was approved by the Surrey Borders Ethics Committee (13/LO/0872). The trial results will be disseminated at national conferences and published in a peer-reviewed medical journal. The results will also be distributed to the Primary Care Research Network and to all participating general practices. This study is registered at controlled-trials.com ISRCTN48840025, July 2013.

The Network Structure of Human Personality According to the NEO-PI-R: Matching Network Community Structure to Factor Structure

PubMed Central

Goekoop, Rutger; Goekoop, Jaap G.; Scholte, H. Steven

2012-01-01

Introduction Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. Aim To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). Methods 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. Results At facet level, NCS showed a best match (96.2%) with a ‘confirmatory’ 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with ‘confirmatory’ 5-FS and ‘exploratory’ 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. Conclusion We present the first optimized network graph of personality traits according to the NEO-PI-R: a ‘Personality Web’. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network. PMID:23284713

The network structure of human personality according to the NEO-PI-R: matching network community structure to factor structure.

PubMed

Goekoop, Rutger; Goekoop, Jaap G; Scholte, H Steven

2012-01-01

Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. At facet level, NCS showed a best match (96.2%) with a 'confirmatory' 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with 'confirmatory' 5-FS and 'exploratory' 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. We present the first optimized network graph of personality traits according to the NEO-PI-R: a 'Personality Web'. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network.

Dealing with Dependence (Part I): Understanding the Effects of Clustered Data

ERIC Educational Resources Information Center

McCoach, D. Betsy; Adelson, Jill L.

2010-01-01

This article provides a conceptual introduction to the issues surrounding the analysis of clustered (nested) data. We define the intraclass correlation coefficient (ICC) and the design effect, and we explain their effect on the standard error. When the ICC is greater than 0, then the design effect is greater than 1. In such a scenario, the…

Task Analysis for Health Occupations. Cluster: Nursing. Occupation: Professional Nurse (Associate Degree). Education for Employment Task Lists.

ERIC Educational Resources Information Center

Lake County Area Vocational Center, Grayslake, IL.

This document contains a task analysis for health occupations (professional nurse) in the nursing cluster. For each task listed, occupation, duty area, performance standard, steps, knowledge, attitudes, safety, equipment/supplies, source of analysis, and Illinois state goals for learning are listed. For the duty area of "providing therapeutic…

Task Analysis for Health Occupations. Cluster: Nursing. Occupation: Home Health Aide. Education for Employment Task Lists.

ERIC Educational Resources Information Center

Lake County Area Vocational Center, Grayslake, IL.

This document contains a task analysis for health occupations (home health aid) in the nursing cluster. For each task listed, occupation, duty area, performance standard, steps, knowledge, attitudes, safety, equipment/supplies, source of analysis, and Illinois state goals for learning are listed. For the duty area of "providing therapeutic…

New Estimates of Design Parameters for Clustered Randomization Studies: Findings from North Carolina and Florida. Working Paper 43

ERIC Educational Resources Information Center

Xu, Zeyu; Nichols, Austin

2010-01-01

The gold standard in making causal inference on program effects is a randomized trial. Most randomization designs in education randomize classrooms or schools rather than individual students. Such "clustered randomization" designs have one principal drawback: They tend to have limited statistical power or precision. This study aims to…

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Clustering algorithm evaluation and the development of a replacement for procedure 1. [for crop inventories

NASA Technical Reports Server (NTRS)

Lennington, R. K.; Johnson, J. K.

1979-01-01

An efficient procedure which clusters data using a completely unsupervised clustering algorithm and then uses labeled pixels to label the resulting clusters or perform a stratified estimate using the clusters as strata is developed. Three clustering algorithms, CLASSY, AMOEBA, and ISOCLS, are compared for efficiency. Three stratified estimation schemes and three labeling schemes are also considered and compared.

A data fusion-based drought index

NASA Astrophysics Data System (ADS)

Azmi, Mohammad; Rüdiger, Christoph; Walker, Jeffrey P.

2016-03-01

Drought and water stress monitoring plays an important role in the management of water resources, especially during periods of extreme climate conditions. Here, a data fusion-based drought index (DFDI) has been developed and analyzed for three different locations of varying land use and climate regimes in Australia. The proposed index comprehensively considers all types of drought through a selection of indices and proxies associated with each drought type. In deriving the proposed index, weekly data from three different data sources (OzFlux Network, Asia-Pacific Water Monitor, and MODIS-Terra satellite) were employed to first derive commonly used individual standardized drought indices (SDIs), which were then grouped using an advanced clustering method. Next, three different multivariate methods (principal component analysis, factor analysis, and independent component analysis) were utilized to aggregate the SDIs located within each group. For the two clusters in which the grouped SDIs best reflected the water availability and vegetation conditions, the variables were aggregated based on an averaging between the standardized first principal components of the different multivariate methods. Then, considering those two aggregated indices as well as the classifications of months (dry/wet months and active/non-active months), the proposed DFDI was developed. Finally, the symbolic regression method was used to derive mathematical equations for the proposed DFDI. The results presented here show that the proposed index has revealed new aspects in water stress monitoring which previous indices were not able to, by simultaneously considering both hydrometeorological and ecological concepts to define the real water stress of the study areas.

Firefighter Hand Anthropometry and Structural Glove Sizing: A New Perspective.

PubMed

Hsiao, Hongwei; Whitestone, Jennifer; Kau, Tsui-Ying; Hildreth, Brooke

2015-12-01

We evaluated the current use and fit of structural firefighting gloves and developed an improved sizing scheme that better accommodates the U.S. firefighter population. Among surveys, 24% to 30% of men and 31% to 62% of women reported experiencing problems with the fit or bulkiness of their structural firefighting gloves. An age-, race/ethnicity-, and gender-stratified sample of 863 male and 88 female firefighters across the United States participated in the study. Fourteen hand dimensions relevant to glove design were measured. A cluster analysis of the hand dimensions was performed to explore options for an improved sizing scheme. The current national standard structural firefighting glove-sizing scheme underrepresents firefighter hand size range and shape variation. In addition, mismatch between existing sizing specifications and hand characteristics, such as hand dimensions, user selection of glove size, and the existing glove sizing specifications, is significant. An improved glove-sizing plan based on clusters of overall hand size and hand/finger breadth-to-length contrast has been developed. This study presents the most up-to-date firefighter hand anthropometry and a new perspective on glove accommodation. The new seven-size system contains narrower variations (standard deviations) for almost all dimensions for each glove size than the current sizing practices. The proposed science-based sizing plan for structural firefighting gloves provides a step-forward perspective (i.e., including two women hand model-based sizes and two wide-palm sizes for men) for glove manufacturers to advance firefighter hand protection. © 2015, Human Factors and Ergonomics Society.

Relation between the Dynamics of Glassy Clusters and Characteristic Features of their Energy Landscape

NASA Astrophysics Data System (ADS)

De, Sandip; Schaefer, Bastian; Sadeghi, Ali; Sicher, Michael; Kanhere, D. G.; Goedecker, Stefan

2014-02-01

Based on a recently introduced metric for measuring distances between configurations, we introduce distance-energy (DE) plots to characterize the potential energy surface of clusters. Producing such plots is computationally feasible on the density functional level since it requires only a few hundred stable low energy configurations including the global minimum. By using standard criteria based on disconnectivity graphs and the dynamics of Lennard-Jones clusters, we show that the DE plots convey the necessary information about the character of the potential energy surface and allow us to distinguish between glassy and nonglassy systems. We then apply this analysis to real clusters at the density functional theory level and show that both glassy and nonglassy clusters can be found in simulations. It turns out that among our investigated clusters only those can be synthesized experimentally which exhibit a nonglassy landscape.

Hybrid approach of selecting hyperparameters of support vector machine for regression.

PubMed

Jeng, Jin-Tsong

2006-06-01

To select the hyperparameters of the support vector machine for regression (SVR), a hybrid approach is proposed to determine the kernel parameter of the Gaussian kernel function and the epsilon value of Vapnik's epsilon-insensitive loss function. The proposed hybrid approach includes a competitive agglomeration (CA) clustering algorithm and a repeated SVR (RSVR) approach. Since the CA clustering algorithm is used to find the nearly "optimal" number of clusters and the centers of clusters in the clustering process, the CA clustering algorithm is applied to select the Gaussian kernel parameter. Additionally, an RSVR approach that relies on the standard deviation of a training error is proposed to obtain an epsilon in the loss function. Finally, two functions, one real data set (i.e., a time series of quarterly unemployment rate for West Germany) and an identification of nonlinear plant are used to verify the usefulness of the hybrid approach.

Dynamic multifactor clustering of financial networks

NASA Astrophysics Data System (ADS)

Ross, Gordon J.

2014-02-01

We investigate the tendency for financial instruments to form clusters when there are multiple factors influencing the correlation structure. Specifically, we consider a stock portfolio which contains companies from different industrial sectors, located in several different countries. Both sector membership and geography combine to create a complex clustering structure where companies seem to first be divided based on sector, with geographical subclusters emerging within each industrial sector. We argue that standard techniques for detecting overlapping clusters and communities are not able to capture this type of structure and show how robust regression techniques can instead be used to remove the influence of both sector and geography from the correlation matrix separately. Our analysis reveals that prior to the 2008 financial crisis, companies did not tend to form clusters based on geography. This changed immediately following the crisis, with geography becoming a more important determinant of clustering structure.

A superior edge preserving filter with a systematic analysis

NASA Technical Reports Server (NTRS)

Holladay, Kenneth W.; Rickman, Doug

1991-01-01

A new, adaptive, edge preserving filter for use in image processing is presented. It had superior performance when compared to other filters. Termed the contiguous K-average, it aggregates pixels by examining all pixels contiguous to an existing cluster and adding the pixel closest to the mean of the existing cluster. The process is iterated until K pixels were accumulated. Rather than simply compare the visual results of processing with this operator to other filters, some approaches were developed which allow quantitative evaluation of how well and filter performs. Particular attention is given to the standard deviation of noise within a feature and the stability of imagery under iterative processing. Demonstrations illustrate the performance of several filters to discriminate against noise and retain edges, the effect of filtering as a preprocessing step, and the utility of the contiguous K-average filter when used with remote sensing data.

Concept mapping and network analysis: an analytic approach to measure ties among constructs.

PubMed

Goldman, Alyssa W; Kane, Mary

2014-12-01

Group concept mapping is a mixed-methods approach that helps a group visually represent its ideas on a topic of interest through a series of related maps. The maps and additional graphics are useful for planning, evaluation and theory development. Group concept maps are typically described, interpreted and utilized through points, clusters and distances, and the implications of these features in understanding how constructs relate to one another. This paper focuses on the application of network analysis to group concept mapping to quantify the strength and directionality of relationships among clusters. The authors outline the steps of this analysis, and illustrate its practical use through an organizational strategic planning example. Additional benefits of this analysis to evaluation projects are also discussed, supporting the overall utility of this supplemental technique to the standard concept mapping methodology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Kinematics of the Normal Knee during Dynamic Activities: A Synthesis of Data from Intracortical Pins and Biplane Imaging

PubMed Central

Gasparutto, Xavier; Moissenet, Florent; Lafon, Yoann

2017-01-01

Few studies have provided in vivo tibiofemoral kinematics of the normal knee during dynamic weight-bearing activities. Indeed, gold standard measurement methods (i.e., intracortical pins and biplane imaging) raise ethical and experimental issues. Moreover, the conventions used for the processing of the kinematics show large inconsistencies. This study aims at synthesising the tibiofemoral kinematics measured with gold standard measurement methods. Published kinematic data were transformed in the standard recommended by the International Society of Biomechanics (ISB), and a clustering method was applied to investigate whether the couplings between the degrees of freedom (DoFs) are consistent among the different activities and measurement methods. The synthesised couplings between the DoFs during knee flexion (from 4° of extension to −61° of flexion) included abduction (up to −10°); internal rotation (up to 15°); and medial (up to 10 mm), anterior (up to 25 mm), and proximal (up to 28 mm) displacements. These synthesised couplings appeared mainly partitioned into two clusters that featured all the dynamic weight-bearing activities and all the measurement methods. Thus, the effect of the dynamic activities on the couplings between the tibiofemoral DoFs appeared to be limited. The synthesised data might be used as a reference of normal in vivo knee kinematics for prosthetic and orthotic design and for knee biomechanical model development and validation. PMID:28487620

A Fast Implementation of the ISODATA Clustering Algorithm

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Mount, David M.; Netanyahu, Nathan S.; LeMoigne, Jacqueline

2005-01-01

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to ISODATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

A Fast Implementation of the Isodata Clustering Algorithm

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Le Moigne, Jacqueline; Mount, David M.; Netanyahu, Nathan S.

2007-01-01

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to IsoDATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

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

Gomez, John A.; Henderson, Thomas M.; Scuseria, Gustavo E.

Restricted single-reference coupled cluster theory truncated to single and double excitations accurately describes weakly correlated systems, but often breaks down in the presence of static or strong correlation. Good coupled cluster energies in the presence of degeneracies can be obtained by using a symmetry-broken reference, such as unrestricted Hartree-Fock, but at the cost of good quantum numbers. A large body of work has shown that modifying the coupled cluster ansatz allows for the treatment of strong correlation within a single-reference, symmetry-adapted framework. The recently introduced singlet-paired coupled cluster doubles (CCD0) method is one such model, which recovers correct behavior formore » strong correlation without requiring symmetry breaking in the reference. Here, we extend singlet-paired coupled cluster for application to open shells via restricted open-shell singlet-paired coupled cluster singles and doubles (ROCCSD0). The ROCCSD0 approach retains the benefits of standard coupled cluster theory and recovers correct behavior for strongly correlated, open-shell systems using a spin-preserving ROHF reference.« less

Defining clusters in APT reconstructions of ODS steels.

PubMed

Williams, Ceri A; Haley, Daniel; Marquis, Emmanuelle A; Smith, George D W; Moody, Michael P

2013-09-01

Oxide nanoclusters in a consolidated Fe-14Cr-2W-0.3Ti-0.3Y₂O₃ ODS steel and in the alloy powder after mechanical alloying (but before consolidation) are investigated by atom probe tomography (APT). The maximum separation method is a standard method to define and characterise clusters from within APT data, but this work shows that the extent of clustering between the two materials is sufficiently different that the nanoclusters in the mechanically alloyed powder and in the consolidated material cannot be compared directly using the same cluster selection parameters. As the cluster selection parameters influence the size and composition of the clusters significantly, a procedure to optimise the input parameters for the maximum separation method is proposed by sweeping the d(max) and N(min) parameter space. By applying this method of cluster parameter selection combined with a 'matrix correction' to account for trajectory aberrations, differences in the oxide nanoclusters can then be reliably quantified. Copyright © 2012 Elsevier B.V. All rights reserved.

Improving the social and emotional climate of classrooms: a clustered randomized controlled trial testing the RULER Approach.

PubMed

Rivers, Susan E; Brackett, Marc A; Reyes, Maria R; Elbertson, Nicole A; Salovey, Peter

2013-02-01

The RULER Approach ("RULER") is a setting-level, social and emotional learning program that is grounded in theory and evidence. RULER is designed to modify the quality of classroom social interactions so that the climate becomes more supportive, empowering, and engaging. This is accomplished by integrating skill-building lessons and tools so that teachers and students develop their emotional literacy. In a clustered randomized control trial, we tested the hypothesis that RULER improves the social and emotional climate of classrooms. Depending upon condition assignment, 62 schools either integrated RULER into fifth- and sixth-grade English language arts (ELA) classrooms or served as comparison schools, using their standard ELA curriculum only. Multi-level modeling analyses showed that compared to classrooms in comparison schools, classrooms in RULER schools were rated as having higher degrees of warmth and connectedness between teachers and students, more autonomy and leadership among students, and teachers who focused more on students' interests and motivations. These findings suggest that RULER enhances classrooms in ways that can promote positive youth development.

Vector dark energy and high-z massive clusters

NASA Astrophysics Data System (ADS)

Carlesi, Edoardo; Knebe, Alexander; Yepes, Gustavo; Gottlöber, Stefan; Jiménez, Jose Beltrán.; Maroto, Antonio L.

2011-12-01

The detection of extremely massive clusters at z > 1 such as SPT-CL J0546-5345, SPT-CL J2106-5844 and XMMU J2235.3-2557 has been considered by some authors as a challenge to the standard Λ cold dark matter cosmology. In fact, assuming Gaussian initial conditions, the theoretical expectation of detecting such objects is as low as ≤1 per cent. In this paper we discuss the probability of the existence of such objects in the light of the vector dark energy paradigm, showing by means of a series of N-body simulations that chances of detection are substantially enhanced in this non-standard framework.

SU-F-BRD-10: Lung IMRT Planning Using Standardized Beam Bouquet Templates

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

Yuan, L; Wu, Q J.; Yin, F

2014-06-15

Purpose: We investigate the feasibility of choosing from a small set of standardized templates of beam bouquets (i.e., entire beam configuration settings) for lung IMRT planning to improve planning efficiency and quality consistency, and also to facilitate automated planning. Methods: A set of beam bouquet templates is determined by learning from the beam angle settings in 60 clinical lung IMRT plans. A k-medoids cluster analysis method is used to classify the beam angle configuration into clusters. The value of the average silhouette width is used to determine the ideal number of clusters. The beam arrangements in each medoid of themore » resulting clusters are taken as the standardized beam bouquet for the cluster, with the corresponding case taken as the reference case. The resulting set of beam bouquet templates was used to re-plan 20 cases randomly selected from the database and the dosimetric quality of the plans was evaluated against the corresponding clinical plans by a paired t-test. The template for each test case was manually selected by a planner based on the match between the test and reference cases. Results: The dosimetric parameters (mean±S.D. in percentage of prescription dose) of the plans using 6 beam bouquet templates and those of the clinical plans, respectively, and the p-values (in parenthesis) are: lung Dmean: 18.8±7.0, 19.2±7.0 (0.28), esophagus Dmean: 32.0±16.3, 34.4±17.9 (0.01), heart Dmean: 19.2±16.5, 19.4±16.6 (0.74), spinal cord D2%: 47.7±18.8, 52.0±20.3 (0.01), PTV dose homogeneity (D2%-D99%): 17.1±15.4, 20.7±12.2 (0.03).The esophagus Dmean, cord D02 and PTV dose homogeneity are statistically better in the plans using the standardized templates, but the improvements (<5%) may not be clinically significant. The other dosimetric parameters are not statistically different. Conclusion: It's feasible to use a small number of standardized beam bouquet templates (e.g. 6) to generate plans with quality comparable to that of clinical plans. Partially supported by NIH/NCI under grant #R21CA161389 and a master research grant by Varian Medical System.« less

A national study of the molecular epidemiology of HIV-1 in Australia 2005-2012.

PubMed

Castley, Alison; Sawleshwarkar, Shailendra; Varma, Rick; Herring, Belinda; Thapa, Kiran; Dwyer, Dominic; Chibo, Doris; Nguyen, Nam; Hawke, Karen; Ratcliff, Rodney; Garsia, Roger; Kelleher, Anthony; Nolan, David

2017-01-01

Rates of new HIV-1 diagnoses are increasing in Australia, with evidence of an increasing proportion of non-B HIV-1 subtypes reflecting a growing impact of migration and travel. The present study aims to define HIV-1 subtype diversity patterns and investigate possible HIV-1 transmission networks within Australia. The Australian Molecular Epidemiology Network (AMEN) HIV collaborating sites in Western Australia, South Australia, Victoria, Queensland and western Sydney (New South Wales), provided baseline HIV-1 partial pol sequence, age and gender information for 4,873 patients who had genotypes performed during 2005-2012. HIV-1 phylogenetic analyses utilised MEGA V6, with a stringent classification of transmission pairs or clusters (bootstrap ≥98%, genetic distance ≤1.5% from at least one other sequence in the cluster). HIV-1 subtype B represented 74.5% of the 4,873 sequences (WA 59%, SA 68.4%, w-Syd 73.8%, Vic 75.6%, Qld 82.1%), with similar proportion of transmission pairs and clusters found in the B and non-B cohorts (23% vs 24.5% of sequences, p = 0.3). Significantly more subtype B clusters were comprised of ≥3 sequences compared with non-B clusters (45.0% vs 24.0%, p = 0.021) and significantly more subtype B pairs and clusters were male-only (88% compared to 53% CRF01_AE and 17% subtype C clusters). Factors associated with being in a cluster of any size included; being sequenced in a more recent time period (p<0.001), being younger (p<0.001), being male (p = 0.023) and having a B subtype (p = 0.02). Being in a larger cluster (>3) was associated with being sequenced in a more recent time period (p = 0.05) and being male (p = 0.008). This nationwide HIV-1 study of 4,873 patient sequences highlights the increased diversity of HIV-1 subtypes within the Australian epidemic, as well as differences in transmission networks associated with these HIV-1 subtypes. These findings provide epidemiological insights not readily available using standard surveillance methods and can inform the development of effective public health strategies in the current paradigm of HIV prevention in Australia.

Clusters of Low (18)F-Fluorodeoxyglucose Uptake Voxels in Combat Veterans with Traumatic Brain Injury and Post-Traumatic Stress Disorder.

PubMed

Buchsbaum, Monte S; Simmons, Alan N; DeCastro, Alex; Farid, Nikdokht; Matthews, Scott C

2015-11-15

Individuals with mild traumatic brain injury (TBI) show diminished metabolic activity when studied with positron emission tomography (PET) with (18)F-fluorodeoxyglucose (FDG). Since blast injury may not be localized in the same specific anatomical areas in every patient or may be diffuse, significance probability mapping may be vulnerable to false-negative detection of abnormalities. To address this problem, we used an anatomically independent measure to assess PET scans: increased numbers of contiguous voxels that are 2 standard deviations below values found in an uninjured control group. We examined this in three age-matched groups of male patients: 16 veterans with a history of mild TBI, 17 veterans with both mild TBI and post-traumatic stress disorder (PTSD), and 15 veterans without either condition. After FDG administration, subjects performed a modified version of the California Verbal Learning Task. Clusters of low uptake voxels were identified by computing the mean and standard deviation for each voxel in the healthy combat veteran group and then determining the voxel-based z-score for the patient groups. Abnormal clusters were defined as those that contained contiguous voxels with a z-score <-2. Patients with mild TBI alone and patients with TBI+PTSD had larger clusters of low uptake voxels, and cluster size significantly differentiated the mild TBI groups from combat controls. Clusters were more irregular in shape in patients, and patients also had a larger number of low-activity voxels throughout the brain. In mild TBI and TBI+PTSD patients, but not healthy subjects, cluster volume was significantly correlated with verbal learning during FDG uptake.

Probability estimates for the unique childhood leukemia cluster in Fallon, Nevada, and risks near other U.S. Military aviation facilities.

PubMed Central

Steinmaus, Craig; Lu, Meng; Todd, Randall L; Smith, Allan H

2004-01-01

A unique cluster of childhood leukemia has recently occurred around the city of Fallon in Churchill County, Nevada. From 1999 to 2001, 11 cases were diagnosed in this county of 23,982 people. Exposures related to a nearby naval air station such as jet fuel or an infectious agent carried by naval aviators have been hypothesized as potential causes. The possibility that the cluster could be attributed to chance was also considered. We used data from the Surveillance, Epidemiology, and End Results Program (SEER) to examine the likelihood that chance could explain this cluster. We also used SEER and California Cancer Registry data to evaluate rates of childhood leukemia in other U.S. counties with military aviation facilities. The age-standardized rate ratio (RR) in Churchill County was 12.0 [95% confidence interval (CI), 6.0-21.4; p = 4.3 times symbol 10(-9)]. A cluster of this magnitude would be expected to occur in the United States by chance about once every 22,000 years. The age-standardized RR for the five cases diagnosed after the cluster was first reported was 11.2 (95% CI, 3.6-26.3). In contrast, the incidence rate was not increased in all other U.S. counties with military aviation bases (RR = 1.04; 95% CI, 0.97-1.12) or in the subset of rural counties with military aviation bases (RR = 0.72; 95% CI, 0.48-1.08). These findings suggest that the Churchill County cluster was unlikely due to chance, but no general increase in childhood leukemia was found in other U.S. counties with military aviation bases. PMID:15121523

Multiple behaviour change intervention for diarrhoea control in Lusaka, Zambia: a cluster randomised trial.

PubMed

Greenland, Katie; Chipungu, Jenala; Curtis, Val; Schmidt, Wolf-Peter; Siwale, Zumbe; Mudenda, Mweetwa; Chilekwa, Joyce; Lewis, James J; Chilengi, Roma

2016-12-01

Effective prevention and control of diarrhoea requires caregivers to comply with a suite of proven measures, including exclusive breastfeeding, handwashing with soap, correct use of oral rehydration salts, and zinc administration. We aimed to assess the effect of a novel behaviour change intervention using emotional drivers on caregiver practice of these behaviours. We did a cluster randomised controlled trial in Lusaka Province, Zambia. A random sample of 16 health centres (clusters) were selected from a sampling frame of 81 health centres in three of four districts in Lusaka Province using a computerised random number generator. Each cluster was randomly assigned 1:1 to either the intervention-clinic events, community events, and radio messaging-or to a standard care control arm, both for 6 months. Primary outcomes were exclusive breastfeeding (self-report), handwashing with soap (observation), oral rehydration salt solution preparation (demonstration), and zinc use in diarrhoea treatment (self-report). We measured outcome behaviours at baseline before start of intervention and 4-6 weeks post-intervention through repeat cross-sectional surveys with mothers of an infant younger than 6 months and primary caregivers of a child younger than 5 years with recent diarrhoea. We compared outcomes on an intention-to-treat population between intervention and control groups adjusted for baseline behaviour. The study was registered with ClinicalTrials.gov, number NCT02081521. Between Jan 20 and Feb 3, 2014, we recruited 306 mothers of an infant aged 0-5 months (156 intervention, 150 standard care) and 343 primary caregiver of a child aged 0-59 months with recent diarrhoea (176 intervention, 167 standard care) at baseline. Between Oct 20 to Nov 7, 2014, we recruited 401 mothers of an infant 0-5 months (234 intervention, 167 standard care) and 410 primary caregivers of a child 0-59 months with recent diarrhoea (257 intervention, 163 standard care) at endline. Intervention was associated with increased prevalence of self-reported exclusive breastfeeding of infants aged 0-5 months (adjusted difference 10·5%, 95% CI 0·9-19·9). Other primary outcomes were not affected by intervention. Cluster intervention exposure ranged from 11-81%, measured by participant self-report with verification questions. Comparison of control and intervention clusters with coverage greater than 35% provided strong evidence of an intervention effect on oral rehydration salt solution preparation and breastfeeding outcomes. The intervention may have improved exclusive breastfeeding (assessed by self-reporting), but intervention effects were diluted in clusters with low exposure. Complex caregiver practices can improve through interventions built around human motives, but these must be implemented more intensely. Absolute Return for Kids (ARK) and Comic Relief. Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

Orbits of Four Very Massive Binaries in the R136 Cluster

NASA Astrophysics Data System (ADS)

Penny, L. R.; Massey, P.; Vukovich, J.

2001-12-01

We present radial velocity and photometry for four early-type, massive double-lined spectroscopic binaries in the R136 cluster. Three of these systems are eclipsing, allowing orbital inclinations to be determined. One of these systems, R136-38 (O3 V + O6 V), has one of the highest masses ever measured, 57 Modot, for the primary. Comparison of our masses with those derived from standard evolutionary tracks shows excellent agreement. We also identify five other light variables in the R136 cluster worthy of follow-up study.

Ion-neutral Clustering of Bile Acids in Electrospray Ionization Across UPLC Flow Regimes

NASA Astrophysics Data System (ADS)

Brophy, Patrick; Broeckling, Corey D.; Murphy, James; Prenni, Jessica E.

2018-02-01

Bile acid authentic standards were used as model compounds to quantitatively evaluate complex in-source phenomenon on a UPLC-ESI-TOF-MS operated in the negative mode. Three different diameter columns and a ceramic-based microfluidic separation device were utilized, allowing for detailed descriptions of bile acid behavior across a wide range of flow regimes and instantaneous concentrations. A custom processing algorithm based on correlation analysis was developed to group together all ion signals arising from a single compound; these grouped signals produce verified compound spectra for each bile acid at each on-column mass loading. Significant adduction was observed for all bile acids investigated under all flow regimes and across a wide range of bile acid concentrations. The distribution of bile acid containing clusters was found to depend on the specific bile acid species, solvent flow rate, and bile acid concentration. Relative abundancies of each cluster changed non-linearly with concentration. It was found that summing all MS level (low collisional energy) ions and ion-neutral adducts arising from a single compound improves linearity across the concentration range (0.125-5 ng on column) and increases the sensitivity of MS level quantification. The behavior of each cluster roughly follows simple equilibrium processes consistent with our understanding of electrospray ionization mechanisms and ion transport processes occurring in atmospheric pressure interfaces. [Figure not available: see fulltext.

Cluster tool solution for fabrication and qualification of advanced photomasks

NASA Astrophysics Data System (ADS)

Schaetz, Thomas; Hartmann, Hans; Peter, Kai; Lalanne, Frederic P.; Maurin, Olivier; Baracchi, Emanuele; Miramond, Corinne; Brueck, Hans-Juergen; Scheuring, Gerd; Engel, Thomas; Eran, Yair; Sommer, Karl

2000-07-01

The reduction of wavelength in optical lithography, phase shift technology and optical proximity correction (OPC), requires a rapid increase in cost effective qualification of photomasks. The knowledge about CD variation, loss of pattern fidelity especially for OPC pattern and mask defects concerning the impact on wafer level is becoming a key issue for mask quality assessment. As part of the European Community supported ESPRIT projection 'Q-CAP', a new cluster concept has been developed, which allows the combination of hardware tools as well as software tools via network communication. It is designed to be open for any tool manufacturer and mask hose. The bi-directional network access allows the exchange of all relevant mask data including grayscale images, measurement results, lithography parameters, defect coordinates, layout data, process data etc. and its storage to a SQL database. The system uses SEMI format descriptions as well as standard network hardware and software components for the client server communication. Each tool is used mainly to perform its specific application without using expensive time to perform optional analysis, but the availability of the database allows each component to share the full data ste gathered by all components. Therefore, the cluster can be considered as one single virtual tool. The paper shows the advantage of the cluster approach, the benefits of the tools linked together already, and a vision of a mask house in the near future.

Is the cluster environment quenching the Seyfert activity in elliptical and spiral galaxies?

NASA Astrophysics Data System (ADS)

de Souza, R. S.; Dantas, M. L. L.; Krone-Martins, A.; Cameron, E.; Coelho, P.; Hattab, M. W.; de Val-Borro, M.; Hilbe, J. M.; Elliott, J.; Hagen, A.; COIN Collaboration

2016-09-01

We developed a hierarchical Bayesian model (HBM) to investigate how the presence of Seyfert activity relates to their environment, herein represented by the galaxy cluster mass, M200, and the normalized cluster centric distance, r/r200. We achieved this by constructing an unbiased sample of galaxies from the Sloan Digital Sky Survey, with morphological classifications provided by the Galaxy Zoo Project. A propensity score matching approach is introduced to control the effects of confounding variables: stellar mass, galaxy colour, and star formation rate. The connection between Seyfert-activity and environmental properties in the de-biased sample is modelled within an HBM framework using the so-called logistic regression technique, suitable for the analysis of binary data (e.g. whether or not a galaxy hosts an AGN). Unlike standard ordinary least square fitting methods, our methodology naturally allows modelling the probability of Seyfert-AGN activity in galaxies on their natural scale, I.e. as a binary variable. Furthermore, we demonstrate how an HBM can incorporate information of each particular galaxy morphological type in an unified framework. In elliptical galaxies our analysis indicates a strong correlation of Seyfert-AGN activity with r/r200, and a weaker correlation with the mass of the host cluster. In spiral galaxies these trends do not appear, suggesting that the link between Seyfert activity and the properties of spiral galaxies are independent of the environment.

Genome-wide identification of physically clustered genes suggests chromatin-level co-regulation in male reproductive development in Arabidopsis thaliana

PubMed Central

Reimegård, Johan; Kundu, Snehangshu; Pendle, Ali; Irish, Vivian F.; Shaw, Peter

2017-01-01

Abstract Co-expression of physically linked genes occurs surprisingly frequently in eukaryotes. Such chromosomal clustering may confer a selective advantage as it enables coordinated gene regulation at the chromatin level. We studied the chromosomal organization of genes involved in male reproductive development in Arabidopsis thaliana. We developed an in-silico tool to identify physical clusters of co-regulated genes from gene expression data. We identified 17 clusters (96 genes) involved in stamen development and acting downstream of the transcriptional activator MS1 (MALE STERILITY 1), which contains a PHD domain associated with chromatin re-organization. The clusters exhibited little gene homology or promoter element similarity, and largely overlapped with reported repressive histone marks. Experiments on a subset of the clusters suggested a link between expression activation and chromatin conformation: qRT-PCR and mRNA in situ hybridization showed that the clustered genes were up-regulated within 48 h after MS1 induction; out of 14 chromatin-remodeling mutants studied, expression of clustered genes was consistently down-regulated only in hta9/hta11, previously associated with metabolic cluster activation; DNA fluorescence in situ hybridization confirmed that transcriptional activation of the clustered genes was correlated with open chromatin conformation. Stamen development thus appears to involve transcriptional activation of physically clustered genes through chromatin de-condensation. PMID:28175342

Functional grouping of similar genes using eigenanalysis on minimum spanning tree based neighborhood graph.

PubMed

Jothi, R; Mohanty, Sraban Kumar; Ojha, Aparajita

2016-04-01

Gene expression data clustering is an important biological process in DNA microarray analysis. Although there have been many clustering algorithms for gene expression analysis, finding a suitable and effective clustering algorithm is always a challenging problem due to the heterogeneous nature of gene profiles. Minimum Spanning Tree (MST) based clustering algorithms have been successfully employed to detect clusters of varying shapes and sizes. This paper proposes a novel clustering algorithm using Eigenanalysis on Minimum Spanning Tree based neighborhood graph (E-MST). As MST of a set of points reflects the similarity of the points with their neighborhood, the proposed algorithm employs a similarity graph obtained from k(') rounds of MST (k(')-MST neighborhood graph). By studying the spectral properties of the similarity matrix obtained from k(')-MST graph, the proposed algorithm achieves improved clustering results. We demonstrate the efficacy of the proposed algorithm on 12 gene expression datasets. Experimental results show that the proposed algorithm performs better than the standard clustering algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

A spatial scan statistic for nonisotropic two-level risk cluster.

PubMed

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2012-01-30

Spatial scan statistic methods are commonly used for geographical disease surveillance and cluster detection. The standard spatial scan statistic does not model any variability in the underlying risks of subregions belonging to a detected cluster. For a multilevel risk cluster, the isotonic spatial scan statistic could model a centralized high-risk kernel in the cluster. Because variations in disease risks are anisotropic owing to different social, economical, or transport factors, the real high-risk kernel will not necessarily take the central place in a whole cluster area. We propose a spatial scan statistic for a nonisotropic two-level risk cluster, which could be used to detect a whole cluster and a noncentralized high-risk kernel within the cluster simultaneously. The performance of the three methods was evaluated through an intensive simulation study. Our proposed nonisotropic two-level method showed better power and geographical precision with two-level risk cluster scenarios, especially for a noncentralized high-risk kernel. Our proposed method is illustrated using the hand-foot-mouth disease data in Pingdu City, Shandong, China in May 2009, compared with two other methods. In this practical study, the nonisotropic two-level method is the only way to precisely detect a high-risk area in a detected whole cluster. Copyright © 2011 John Wiley & Sons, Ltd.

Deep CCD Photometry of the Rich Galaxy Cluster Abel 1656 Characteristics of the Dwarf Elliptical Galaxy Population in the Cluster Core

NASA Astrophysics Data System (ADS)

Secker, Jeffrey Alan

1995-01-01

We have developed a statistically rigorous and automated method to implement the detection, photometry and classification of faint objects on digital images. We use these methods to analyze deep R- and B-band CCD images of the central ~ 700 arcmin ^2 of the Coma cluster core, and an associated control field. We have detected and measured total R magnitudes and (B-R) colors for a sample of 3741 objects on the galaxy cluster fields, and 1164 objects on a remote control field, complete to a limiting magnitude of R = 22.5 mag. The typical uncertainties are +/- 0.06 and +/-0.12 mag in total magnitude and color respectively. The dwarf elliptical (dE) galaxies are confined to a well-defined sequence in the color range given by 0.7<= (B-R)<= 1.9 mag: within this interval there are 2535 dE candidates on our fields in the cluster core, and 694 objects on the control field. With an image scale of 0.53 arcsec/pixel and seeing near 1.2 arcsec, a large fraction of the dE galaxy candidates are resolved. We find a significant metallicity gradient in the radial distribution of the dwarf elliptical galaxies, which goes as Z~ R^{-0.32 } outwards from the cluster center at NGC 4874. As well, there is a strong color-luminosity correlation, in the sense that more luminous dE galaxies are redder in the mean. These effects give rise to a radial variation in the cluster luminosity function. The spatial distribution of the faint dE galaxies is well fit by a standard King model with a central surface density of Sigma _0 = 1.44 dEs arcmin^{ -2}, a core radius R_{ rm c} = 18.7 arcmin (~eq 0.44 Mpc), and a tidal radius of 1.44 deg ( ~eq 2.05 Mpc). This core is significantly larger than R_{rm c} = 12.3 arcmin (~eq 0.29 Mpc) found for the bright cluster galaxies. The composite luminosity function for Coma galaxies is modeled as the sum of a log -normal distribution for the giant galaxies and a Schechter function for the dwarf elliptical galaxies, with a faint -end slope of alpha = -1.41, consistent with known faint-end slopes for the Virgo and Fornax clusters. The early-type dwarf-to-giant ratio for the Coma cluster core is consistent with that of the Virgo cluster, and thus with the rich Coma cluster being formed as the merger of multiple less-rich galaxy clusters.

The bacterial species definition in the genomic era

PubMed Central

Konstantinidis, Konstantinos T; Ramette, Alban; Tiedje, James M

2006-01-01

The bacterial species definition, despite its eminent practical significance for identification, diagnosis, quarantine and diversity surveys, remains a very difficult issue to advance. Genomics now offers novel insights into intra-species diversity and the potential for emergence of a more soundly based system. Although we share the excitement, we argue that it is premature for a universal change to the definition because current knowledge is based on too few phylogenetic groups and too few samples of natural populations. Our analysis of five important bacterial groups suggests, however, that more stringent standards for species may be justifiable when a solid understanding of gene content and ecological distinctiveness becomes available. Our analysis also reveals what is actually encompassed in a species according to the current standards, in terms of whole-genome sequence and gene-content diversity, and shows that this does not correspond to coherent clusters for the environmental Burkholderia and Shewanella genera examined. In contrast, the obligatory pathogens, which have a very restricted ecological niche, do exhibit clusters. Therefore, the idea of biologically meaningful clusters of diversity that applies to most eukaryotes may not be universally applicable in the microbial world, or if such clusters exist, they may be found at different levels of distinction. PMID:17062412

Length-independent structural similarities enrich the antibody CDR canonical class model.

PubMed

Nowak, Jaroslaw; Baker, Terry; Georges, Guy; Kelm, Sebastian; Klostermann, Stefan; Shi, Jiye; Sridharan, Sudharsan; Deane, Charlotte M

2016-01-01

Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variable structural clusters show strong sequence patterns suggesting either that they evolved from the same original structure or result from some form of convergence. We find that our length-independent method not only clusters a larger number of CDRs, but also predicts canonical class from sequence better than the standard length-dependent approach. To demonstrate the usefulness of our findings, we predicted cluster membership of CDR-L3 sequences from 3 next-generation sequencing datasets of the antibody repertoire (over 1,000,000 sequences). Using the length-independent clusters, we can structurally classify an additional 135,000 sequences, which represents a ∼20% improvement over the standard approach. This suggests that our length-independent canonical classes might be a highly prevalent feature of antibody space, and could substantially improve our ability to accurately predict the structure of novel CDRs identified by next-generation sequencing.

Novel multiresolution mammographic density segmentation using pseudo 3D features and adaptive cluster merging

NASA Astrophysics Data System (ADS)

He, Wenda; Juette, Arne; Denton, Erica R. E.; Zwiggelaar, Reyer

2015-03-01

Breast cancer is the most frequently diagnosed cancer in women. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective ways to overcome the disease. Successful mammographic density segmentation is a key aspect in deriving correct tissue composition, ensuring an accurate mammographic risk assessment. However, mammographic densities have not yet been fully incorporated with non-image based risk prediction models, (e.g. the Gail and the Tyrer-Cuzick model), because of unreliable segmentation consistency and accuracy. This paper presents a novel multiresolution mammographic density segmentation, a concept of stack representation is proposed, and 3D texture features were extracted by adapting techniques based on classic 2D first-order statistics. An unsupervised clustering technique was employed to achieve mammographic segmentation, in which two improvements were made; 1) consistent segmentation by incorporating an optimal centroids initialisation step, and 2) significantly reduced the number of missegmentation by using an adaptive cluster merging technique. A set of full field digital mammograms was used in the evaluation. Visual assessment indicated substantial improvement on segmented anatomical structures and tissue specific areas, especially in low mammographic density categories. The developed method demonstrated an ability to improve the quality of mammographic segmentation via clustering, and results indicated an improvement of 26% in segmented image with good quality when compared with the standard clustering approach. This in turn can be found useful in early breast cancer detection, risk-stratified screening, and aiding radiologists in the process of decision making prior to surgery and/or treatment.

A spatio-temporal analysis of suicide in El Salvador.

PubMed

Carcach, Carlos

2017-04-20

In 2012, international statistics showed El Salvador's suicide rate as 40th in the world and the highest in Latin America. Over the last 15 years, national statistics show the suicide death rate declining as opposed to an increasing rate of homicide. Though completed suicide is an important social and health issue, little is known about its prevalence, incidence, etiology and spatio-temporal behavior. The primary objective of this study was to examine completed suicide and homicide using the stream analogy to lethal violence within a spatio-temporal framework. A Bayesian model was applied to examine the spatio-temporal evolution of the tendency of completed suicide over homicide in El Salvador. Data on numbers of suicides and homicides at the municipal level were obtained from the Instituto de Medicina Legal (IML) and population counts, from the Dirección General de Estadística y Censos (DIGESTYC), for the period of 2002 to 2012. Data on migration were derived from the 2007 Population Census, and inequality data were obtained from a study by Damianović, Valenzuela and Vera. The data reveal a stable standardized rate of total lethal violence (completed suicide plus homicide) across municipalities over time; a decline in suicide; and a standardized suicide rate decreasing with income inequality but increasing with social isolation. Municipalities clustered in terms of both total lethal violence and suicide standardized rates. Spatial effects for suicide were stronger among municipalities located in the north-east and center-south sides of the country. New clusters of municipalities with large suicide standardized rates were detected in the north-west, south-west and center-south regions, all of which are part of time-stable clusters of homicide. Prevention efforts to reduce income inequality and mitigate the negative effects of weak relational systems should focus upon municipalities forming time-persistent clusters with a large rate of death by suicide. In municipalities that are part of newly-formed suicide clusters and also are located in areas with a large rate of homicide, interrupting the expansion of spatial concentrations of suicide over time may require the implementation of both public health and public safety interventions.

Industrial Education. Vocational Education Program Courses Standards.

ERIC Educational Resources Information Center

Florida State Dept. of Education, Tallahassee. Div. of Applied Tech., Adult, and Community Education.

This document contains vocational education program course standards for exploratory courses, practical arts courses, and job preparatory programs offered at the secondary and postsecondary level as part of the industrial education component in Florida. Curriculum frameworks are provided for 144 programs/clusters; representative topics are as…

Chronic insomnia cases detection with the help of Athens Insomnia Scale and SF-36 health survey

NASA Astrophysics Data System (ADS)

Wasiewicz, P.; Skalski, M.; Fornal-Pawlowska, Malgorzata

2011-10-01

Standardization of the diagnostic process of insomnia is a highly important task in clinical practice, epidemiological considerations and treatment outcomes assessment. In this paper we describe standard surveys relationships within cluster groups with the same insomnia degrees.

Classification of neocortical interneurons using affinity propagation.

PubMed

Santana, Roberto; McGarry, Laura M; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2013-01-01

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

Automated Comparative Metabolite Profiling of Large LC-ESIMS Data Sets in an ACD/MS Workbook Suite Add-in, and Data Clustering on a New Open-Source Web Platform FreeClust.

PubMed

Božičević, Alen; Dobrzyński, Maciej; De Bie, Hans; Gafner, Frank; Garo, Eliane; Hamburger, Matthias

2017-12-05

The technological development of LC-MS instrumentation has led to significant improvements of performance and sensitivity, enabling high-throughput analysis of complex samples, such as plant extracts. Most software suites allow preprocessing of LC-MS chromatograms to obtain comprehensive information on single constituents. However, more advanced processing needs, such as the systematic and unbiased comparative metabolite profiling of large numbers of complex LC-MS chromatograms remains a challenge. Currently, users have to rely on different tools to perform such data analyses. We developed a two-step protocol comprising a comparative metabolite profiling tool integrated in ACD/MS Workbook Suite, and a web platform developed in R language designed for clustering and visualization of chromatographic data. Initially, all relevant chromatographic and spectroscopic data (retention time, molecular ions with the respective ion abundance, and sample names) are automatically extracted and assembled in an Excel spreadsheet. The file is then loaded into an online web application that includes various statistical algorithms and provides the user with tools to compare and visualize the results in intuitive 2D heatmaps. We applied this workflow to LC-ESIMS profiles obtained from 69 honey samples. Within few hours of calculation with a standard PC, honey samples were preprocessed and organized in clusters based on their metabolite profile similarities, thereby highlighting the common metabolite patterns and distributions among samples. Implementation in the ACD/Laboratories software package enables ulterior integration of other analytical data, and in silico prediction tools for modern drug discovery.

Blue emitting undecaplatinum clusters

NASA Astrophysics Data System (ADS)

Chakraborty, Indranath; Bhuin, Radha Gobinda; Bhat, Shridevi; Pradeep, T.

2014-07-01

A blue luminescent 11-atom platinum cluster showing step-like optical features and the absence of plasmon absorption was synthesized. The cluster was purified using high performance liquid chromatography (HPLC). Electrospray ionization (ESI) and matrix assisted laser desorption ionization (MALDI) mass spectrometry (MS) suggest a composition, Pt11(BBS)8, which was confirmed by a range of other experimental tools. The cluster is highly stable and compatible with many organic solvents.A blue luminescent 11-atom platinum cluster showing step-like optical features and the absence of plasmon absorption was synthesized. The cluster was purified using high performance liquid chromatography (HPLC). Electrospray ionization (ESI) and matrix assisted laser desorption ionization (MALDI) mass spectrometry (MS) suggest a composition, Pt11(BBS)8, which was confirmed by a range of other experimental tools. The cluster is highly stable and compatible with many organic solvents. Electronic supplementary information (ESI) available: Details of experimental procedures, instrumentation, chromatogram of the crude cluster; SEM/EDAX, DLS, PXRD, TEM, FT-IR, and XPS of the isolated Pt11 cluster; UV/Vis, MALDI MS and SEM/EDAX of isolated 2 and 3; and 195Pt NMR of the K2PtCl6 standard. See DOI: 10.1039/c4nr02778g

Mobile telecommunications and health: report of an investigation into an alleged cancer cluster in Sandwell, West Midlands.

PubMed

Stewart, Antony; Rao, Jammi N; Middleton, John D; Pearmain, Philippa; Evans, Tim

2012-11-01

Residents of one street expressed concern about the number of incident cancers, following the installation of a nearby mobile phone base station. The investigation explored whether the base station could be responsible for the cancers. Data were collected from residents' medical records. GPs and oncologists provided further information. Ward-level cancer incidence and mortality data were also obtained, over four three-year time periods. A total of 19 residents had developed cancer. The collection of cancers did not fulfil the criteria for a cancer cluster. Standardized mortality ratios (SMRs) for all malignant neoplasms (excluding non-melanoma skin cancers) in females (1.38 (95% CI, 1.08-1.74)) and all persons (1.27 (CI, 1.06-1.51)) were significantly higher than in the West Midlands during 2001-3. There were no significant differences for colorectal, female breast and prostate cancers, for any time period. Standardized incidence ratios (SIRs) for non-melanoma skin cancers in males and all persons was significantly lower than in the West Midlands during 1999-2001, and significantly lower in males, females and all persons during 2002-4. We cannot conclude that the base station was responsible for the cancers. It is unlikely that information around a single base station can either demonstrate or exclude causality.

A new method for shape and texture classification of orthopedic wear nanoparticles.

PubMed

Zhang, Dongning; Page, Janet R; Kavanaugh, Aaron E; Billi, Fabrizio

2012-09-27

Detailed morphologic analysis of particles produced during wear of orthopedic implants is important in determining a correlation among material, wear, and biological effects. However, the use of simple shape descriptors is insufficient to categorize the data and to compare the nature of wear particles generated by different implants. An approach based on Discrete Fourier Transform (DFT) is presented for describing particle shape and surface texture. Four metal-on-metal bearing couples were tested in an orbital wear simulator under standard and adverse (steep-angled cups) wear simulator conditions. Digitized Scanning Electron Microscope (SEM) images of the wear particles were imported into MATLAB to carry out Fourier descriptor calculations via a specifically developed algorithm. The descriptors were then used for studying particle characteristics (shape and texture) as well as for cluster classification. Analysis of the particles demonstrated the validity of the proposed model by showing that steep-angle Co-Cr wear particles were more asymmetric, compressed, extended, triangular, square, and roughened at 3 Mc than after 0.25 Mc. In contrast, particles from standard angle samples were only more compressed and extended after 3 Mc compared to 0.25 Mc. Cluster analysis revealed that the 0.25 Mc steep-angle particle distribution was a subset of the 3 Mc distribution.

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

Cluster headache: present and future therapy.

PubMed

Leone, Massimo; Giustiniani, Alessandro; Cecchini, Alberto Proietti

2017-05-01

Cluster headache is characterized by severe, unilateral headache attacks of orbital, supraorbital or temporal pain lasting 15-180 min accompanied by ipsilateral lacrimation, rhinorrhea and other cranial autonomic manifestations. Cluster headache attacks need fast-acting abortive agents because the pain peaks very quickly; sumatriptan injection is the gold standard acute treatment. First-line preventative drugs include verapamil and carbolithium. Other drugs demonstrated effective in open trials include topiramate, valproic acid, gabapentin and others. Steroids are very effective; local injection in the occipital area is also effective but its prolonged use needs caution. Monoclonal antibodies against calcitonin gene-related peptide are under investigation as prophylactic agents in both episodic and chronic cluster headache. A number of neurostimulation procedures including occipital nerve stimulation, vagus nerve stimulation, sphenopalatine ganglion stimulation and the more invasive hypothalamic stimulation are employed in chronic intractable cluster headache.

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.

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys

PubMed Central

Hund, Lauren; Bedrick, Edward J.; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis. PMID:26125967

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

PubMed

Hund, Lauren; Bedrick, Edward J; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

X-ray clusters in a cold dark matter + lambda universe: A direct, large-scale, high-resolution, hydrodynamic simulation

NASA Technical Reports Server (NTRS)

Cen, Renyue; Ostriker, Jeremiah P.

1994-01-01

A new, three-dimensional, shock-capturing, hydrodynamic code is utilized to determine the distribution of hot gas in a cold dark matter (CDM) + lambda model universe. Periodic boundary conditions are assumed: a box with size 85/h Mpc, having cell size 0.31/h Mpc, is followed in a simulation with 270(exp 3) = 10(exp 7.3) cells. We adopt omega = 0.45, lambda = 0.55, h identically equal to H/100 km/s/Mpc = 0.6, and then, from the cosmic background explorer (COBE) and light element nucleosynthesis, sigma(sub 8) = 0.77, omega(sub b) = 0.043. We identify the X-ray emitting clusters in the simulation box, compute the luminosity function at several wavelength bands, the temperature function and estimated sizes, as well as the evolution of these quantities with redshift. This open model succeeds in matching local observations of clusters in contrast to the standard omega = 1, CDM model, which fails. It predicts an order of magnitude decline in the number density of bright (h nu = 2-10 keV) clusters from z = 0 to z = 2 in contrast to a slight increase in the number density for standard omega = 1, CDM model. This COBE-normalized CDM + lambda model produces approximately the same number of X-ray clusters having L(sub x) greater than 10(exp 43) erg/s as observed. The background radiation field at 1 keV due to clusters is approximately the observed background which, after correction for numerical effects, again indicates that the model is consistent with observations.

Detection of calcification clusters in digital breast tomosynthesis slices at different dose levels utilizing a SRSAR reconstruction and JAFROC

NASA Astrophysics Data System (ADS)

Timberg, P.; Dustler, M.; Petersson, H.; Tingberg, A.; Zackrisson, S.

2015-03-01

Purpose: To investigate detection performance for calcification clusters in reconstructed digital breast tomosynthesis (DBT) slices at different dose levels using a Super Resolution and Statistical Artifact Reduction (SRSAR) reconstruction method. Method: Simulated calcifications with irregular profile (0.2 mm diameter) where combined to form clusters that were added to projection images (1-3 per abnormal image) acquired on a DBT system (Mammomat Inspiration, Siemens). The projection images were dose reduced by software to form 35 abnormal cases and 25 normal cases as if acquired at 100%, 75% and 50% dose level (AGD of approximately 1.6 mGy for a 53 mm standard breast, measured according to EUREF v0.15). A standard FBP and a SRSAR reconstruction method (utilizing IRIS (iterative reconstruction filters), and outlier detection using Maximum-Intensity Projections and Average-Intensity Projections) were used to reconstruct single central slices to be used in a Free-response task (60 images per observer and dose level). Six observers participated and their task was to detect the clusters and assign confidence rating in randomly presented images from the whole image set (balanced by dose level). Each trial was separated by one weeks to reduce possible memory bias. The outcome was analyzed for statistical differences using Jackknifed Alternative Free-response Receiver Operating Characteristics. Results: The results indicate that it is possible reduce the dose by 50% with SRSAR without jeopardizing cluster detection. Conclusions: The detection performance for clusters can be maintained at a lower dose level by using SRSAR reconstruction.

Word-initial rhotic clusters in Spanish-speaking preschoolers in Chile and Granada, Spain.

PubMed

Perez, Denisse; Vivar, Pilar; Bernhardt, Barbara May; Mendoza, Elvira; Ávila, Carmen; Carballo, Gloria; Fresneda, Dolores; Muñoz, Juana; Vergara, Patricio

2018-01-01

The current paper describes Spanish acquisition of rhotic onset clusters. Data are also provided on related singleton taps/trills and /l/ as a singleton and in clusters. Participants included 9 typically developing (TD) toddlers and 30 TD preschoolers in Chile, and 30 TD preschoolers and 29 with protracted phonological development (PPD) in Granada, Spain. Results showed age and developmental group effects. Preservation of cluster timing units preceded segmental accuracy, especially in stressed syllables. Tap clusters versus singleton trills were variable in order of mastery, some children mastering clusters first, and others, the trill. Rhotics were acquired later than /l/. In early development, mismatches (errors) involved primarily deletion of taps; where substitutions occurred, [j] frequently replaced tap. In later development, [l] more frequently replaced tap; where taps did occur, vowel epenthesis sometimes occurred. The data serve as a criterion reference database for onset cluster acquisition in Chilean and Granada Spanish.

Integrating multisource land use and land cover data

USGS Publications Warehouse

Wright, Bruce E.; Tait, Mike; Lins, K.F.; Crawford, J.S.; Benjamin, S.P.; Brown, Jesslyn F.

1995-01-01

As part of the U.S. Geological Survey's (USGS) land use and land cover (LULC) program, the USGS in cooperation with the Environmental Systems Research Institute (ESRI) is collecting and integrating LULC data for a standard USGS 1:100,000-scale product. The LULC data collection techniques include interpreting spectrally clustered Landsat Thematic Mapper (TM) images; interpreting 1-meter resolution digital panchromatic orthophoto images; and, for comparison, aggregating locally available large-scale digital data of urban areas. The area selected is the Vancouver, WA-OR quadrangle, which has a mix of urban, rural agriculture, and forest land. Anticipated products include an integrated LULC prototype data set in a standard classification scheme referenced to the USGS digital line graph (DLG) data of the area and prototype software to develop digital LULC data sets.This project will evaluate a draft standard LULC classification system developed by the USGS for use with various source material and collection techniques. Federal, State, and local governments, and private sector groups will have an opportunity to evaluate the resulting prototype software and data sets and to provide recommendations. It is anticipated that this joint research endeavor will increase future collaboration among interested organizations, public and private, for LULC data collection using common standards and tools.

Human Services. Georgia Core Standards for Occupational Clusters.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Dept. of Occupational Studies.

This document lists core standards and occupational knowledge and skills that have been identified and validated by industry as necessary to all Georgia students in secondary-level human services occupations programs. First, foundation skills are grouped as follows: basic skills (reading, writing, arithmetic/mathematics, listening, speaking);…

Technical/Engineering. Georgia Core Standards for Occupational Clusters.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Dept. of Occupational Studies.

This document lists core standards and occupational knowledge and skills that have been identified and validated by industry as necessary to all Georgia students in secondary-level technical/engineering programs. First, foundation skills are grouped as follows: basic skills (reading, writing, arithmetic/mathematics, listening, speaking); thinking…

Health Care. Georgia Core Standards for Occupational Clusters.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Dept. of Occupational Studies.

This document lists core standards and occupational knowledge and skills that have been identified/validated by industry as necessary to all Georgia students in secondary-level health care occupations programs. First, foundation skills are grouped as follows: basic skills (reading, writing, arithmetic/mathematics, listening, speaking); thinking…

The Clusters - Collaborative Models of Sustainable Regional Development

NASA Astrophysics Data System (ADS)

Mănescu, Gabriel; Kifor, Claudiu

2014-12-01

The clusters are the subject of actions and of whole series of documents issued by national and international organizations, and, based on experience, many authorities promote the idea that because of the clusters, competitiveness increases, the workforce specializes, regional businesses and economies grow. The present paper is meant to be an insight into the initiatives of forming clusters in Romania. Starting from a comprehensive analysis of the development potential offered by each region of economic development, we present the main types of clusters grouped according to fields of activity and their overall objectives

Poisson Mixture Regression Models for Heart Disease Prediction.

PubMed

Mufudza, Chipo; Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

Poisson Mixture Regression Models for Heart Disease Prediction

PubMed Central

Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

WAIS-III index score profiles in the Canadian standardization sample.

PubMed

Lange, Rael T

2007-01-01

Representative index score profiles were examined in the Canadian standardization sample of the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III). The identification of profile patterns was based on the methodology proposed by Lange, Iverson, Senior, and Chelune (2002) that aims to maximize the influence of profile shape and minimize the influence of profile magnitude on the cluster solution. A two-step cluster analysis procedure was used (i.e., hierarchical and k-means analyses). Cluster analysis of the four index scores (i.e., Verbal Comprehension [VCI], Perceptual Organization [POI], Working Memory [WMI], Processing Speed [PSI]) identified six profiles in this sample. Profiles were differentiated by pattern of performance and were primarily characterized as (a) high VCI/POI, low WMI/PSI, (b) low VCI/POI, high WMI/PSI, (c) high PSI, (d) low PSI, (e) high VCI/WMI, low POI/PSI, and (f) low VCI, high POI. These profiles are potentially useful for determining whether a patient's WAIS-III performance is unusual in a normal population.

New Theoretical Developments in Exploring Electronically Excited States: Including Localized Configuration Interaction Singles and Application to Large Helium Clusters

NASA Astrophysics Data System (ADS)

Closser, Kristina Danielle

This thesis presents new developments in excited state electronic structure theory. Contrasted with the ground state, the electronically excited states of atoms and molecules often are unstable and have short lifetimes, exhibit a greater diversity of character and are generally less well understood. The very unusual excited states of helium clusters motivated much of this work. These clusters consist of large numbers of atoms (experimentally 103--109 atoms) and bands of nearly degenerate excited states. For an isolated atom the lowest energy excitation energies are from 1s → 2s and 1s → 2 p transitions, and in clusters describing the lowest energy band minimally requires four states per atom. In the ground state the clusters are weakly bound by van der Waals interactions, however in the excited state they can form well-defined covalent bonds. The computational cost of quantum chemical calculations rapidly becomes prohibitive as the size of the systems increase. Standard excited-state methods such as configuration interaction singles (CIS) and time-dependent density functional theory (TD-DFT) can be used with ≈100 atoms, and are optimized to treat only a few states. Thus, one of our primary aims is to develop a method which can treat these large systems with large numbers of nearly degenerate excited states. Additionally, excited states are generally formed far from their equilibrium structures. Vertical excitations from the ground state induce dynamics in the excited states. Thus, another focus of this work is to explore the results of these forces and the fate of the excited states. Very little was known about helium cluster excited states when this work began, thus we first investigated the excitations in small helium clusters consisting of 7 or 25 atoms using CIS. The character of these excited states was determined using attachment/detachment density analysis and we found that in the n = 2 manifold the excitations could generally be interpreted as superpositions of atomic states with surface states appearing close to the atomic excitation energies and interior states being blue shifted by up to ≈2 eV. The dynamics resulting from excitation of He_7 were subsequently explored using ab initio molecular dynamics (AIMD). These simulations were performed with classical adiabatic dynamics coupled to a new state-following algorithm on CIS potential energy surfaces. Most clusters were found to completely dissociate and resulted in a single excited atomic state (90%), however, some trajectories formed bound, He*2 (3%), and a few yielded excited trimers (<0.5%). Comparisons were made with available experimental information on much larger clusters. Various applications of this state following algorithm are also presented. In addition to AIMD, these include excited-state geometry optimization and minimal energy path finding via the growing string method. When using state following we demonstrate that more physical results can be obtained with AIMD calculations. Also, the optimized geometries of three excited states of cytosine, two of which were not found without state following, and the minimal energy path between the lowest two singlet excited states of protonated formaldimine are offered as example applications. Finally, to address large clusters, a local variation of CIS was developed. This method exploits the properties of absolutely localized molecular orbitals (ALMOs) to limit the total number of excitations to scaling only linearly with cluster size, which results in formal scaling with the third power of the system size. The derivation of the equations and design of the algorithm are discussed in detail, and computational timings as well as a pilot application to the size dependence of the helium cluster spectrum are presented.

PMLB: a large benchmark suite for machine learning evaluation and comparison.

PubMed

Olson, Randal S; La Cava, William; Orzechowski, Patryk; Urbanowicz, Ryan J; Moore, Jason H

2017-01-01

The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists. The present study introduces an accessible, curated, and developing public benchmark resource to facilitate identification of the strengths and weaknesses of different machine learning methodologies. We compare meta-features among the current set of benchmark datasets in this resource to characterize the diversity of available data. Finally, we apply a number of established machine learning methods to the entire benchmark suite and analyze how datasets and algorithms cluster in terms of performance. From this study, we find that existing benchmarks lack the diversity to properly benchmark machine learning algorithms, and there are several gaps in benchmarking problems that still need to be considered. This work represents another important step towards understanding the limitations of popular benchmarking suites and developing a resource that connects existing benchmarking standards to more diverse and efficient standards in the future.

Improving Glaucoma Detection Using Spatially Correspondent Clusters of Damage and by Combining Standard Automated Perimetry and Optical Coherence Tomography

PubMed Central

Raza, Ali S.; Zhang, Xian; De Moraes, Carlos G. V.; Reisman, Charles A.; Liebmann, Jeffrey M.; Ritch, Robert; Hood, Donald C.

2014-01-01

Purpose. To improve the detection of glaucoma, techniques for assessing local patterns of damage and for combining structure and function were developed. Methods. Standard automated perimetry (SAP) and frequency-domain optical coherence tomography (fdOCT) data, consisting of macular retinal ganglion cell plus inner plexiform layer (mRGCPL) as well as macular and optic disc retinal nerve fiber layer (mRNFL and dRNFL) thicknesses, were collected from 52 eyes of 52 healthy controls and 156 eyes of 96 glaucoma suspects and patients. In addition to generating simple global metrics, SAP and fdOCT data were searched for contiguous clusters of abnormal points and converted to a continuous metric (pcc). The pcc metric, along with simpler methods, was used to combine the information from the SAP and fdOCT. The performance of different methods was assessed using the area under receiver operator characteristic curves (AROC scores). Results. The pcc metric performed better than simple global measures for both the fdOCT and SAP. The best combined structure-function metric (mRGCPL&SAP pcc, AROC = 0.868 ± 0.032) was better (statistically significant) than the best metrics for independent measures of structure and function. When SAP was used as part of the inclusion and exclusion criteria, AROC scores increased for all metrics, including the best combined structure-function metric (AROC = 0.975 ± 0.014). Conclusions. A combined structure-function metric improved the detection of glaucomatous eyes. Overall, the primary sources of value-added for glaucoma detection stem from the continuous cluster search (the pcc), the mRGCPL data, and the combination of structure and function. PMID:24408977

Integration of virtualized worker nodes in standard batch systems

NASA Astrophysics Data System (ADS)

Büge, Volker; Hessling, Hermann; Kemp, Yves; Kunze, Marcel; Oberst, Oliver; Quast, Günter; Scheurer, Armin; Synge, Owen

2010-04-01

Current experiments in HEP only use a limited number of operating system flavours. Their software might only be validated on one single OS platform. Resource providers might have other operating systems of choice for the installation of the batch infrastructure. This is especially the case if a cluster is shared with other communities, or communities that have stricter security requirements. One solution would be to statically divide the cluster into separated sub-clusters. In such a scenario, no opportunistic distribution of the load can be achieved, resulting in a poor overall utilization efficiency. Another approach is to make the batch system aware of virtualization, and to provide each community with its favoured operating system in a virtual machine. Here, the scheduler has full flexibility, resulting in a better overall efficiency of the resources. In our contribution, we present a lightweight concept for the integration of virtual worker nodes into standard batch systems. The virtual machines are started on the worker nodes just before jobs are executed there. No meta-scheduling is introduced. We demonstrate two prototype implementations, one based on the Sun Grid Engine (SGE), the other using Maui/Torque as a batch system. Both solutions support local job as well as Grid job submission. The hypervisors currently used are Xen and KVM, a port to another system is easily envisageable. To better handle different virtual machines on the physical host, the management solution VmImageManager is developed. We will present first experience from running the two prototype implementations. In a last part, we will show the potential future use of this lightweight concept when integrated into high-level (i.e. Grid) work-flows.

Temporal variation of PM10 concentration and properties in Istanbul 2007-2015

NASA Astrophysics Data System (ADS)

Flores, Rosa M.; Kaya, Nefel; Eşer, Övgü; Saltan, Şehnaz

2017-04-01

The study of temporal variation of atmospheric aerosols is essential for a better understanding of sources, transport, and accumulation in the atmosphere. In addition, the study of aerosol properties is important for the understanding of their formation and potential impacts on ecosystems and climate change. Istanbul is a Megacity that often shows exceedance in particulate matter (PM) standard values, especially during the winter season. In this work, temporal variations of hourly ground-level PM10 concentrations, aerosol optical depth (AOD), aerosol index (AI), vertical distribution, and mineral dust loadings were investigated according to air mass trajectory clusters in Istanbul during 2007-2015. Aerosol properties (i.e., AOD, AI, and vertical distribution) and mineral dust loadings were retrieved from satellite observations and the BSC-DREAM8b model, respectively. Air mass backward trajectories and clustering were supplied by NOAA-HYSPLIT model. Mineral dust transport events were characterized according to the exceedance of a dust loading threshold value. The total number of mineral dust transport events ranged from 115 to 183 during the study period. The largest number of mineral dust transport events were observed in 2008 and 2014. However, the highest ground-level PM10 measurements were observed in 2012-2013 with approximately 70% of the daily average concentrations exceeding the air quality standard of 50 µg m-3. Overall, 5-6 air mass trajectory clusters were able to resolve over 85% of the total spatial variance. These trajectories vary in frequency and direction throughout the years, however, the main trajectories favor aerosol transport from N, NE, NNE, and S, and SE. Evaluation of mineral dust loading and PM10 concentrations is helpful for successful development and implementation of air quality management strategies on local levels.

Fuzzy clustering evaluation of the discrimination power of UV-Vis and (±) ESI-MS detection system in individual or coupled RPLC for characterization of Ginkgo Biloba standardized extracts.

PubMed

Medvedovici, Andrei; Albu, Florin; Naşcu-Briciu, Rodica Domnica; Sârbu, Costel

2014-02-01

Discrimination power evaluation of UV-Vis and (±) electrospray ionization/mass spectrometric techniques, (ESI-MS) individually considered or coupled as detectors to reversed phase liquid chromatography (RPLC) in the characterization of Ginkgo Biloba standardized extracts, is used in herbal medicines and/or dietary supplements with the help of Fuzzy hierarchical clustering (FHC). Seventeen batches of Ginkgo Biloba commercially available standardized extracts from seven manufacturers were measured during experiments. All extracts were within the criteria of the official monograph dedicated to dried refined and quantified Ginkgo extracts, in the European Pharmacopoeia. UV-Vis and (±) ESI-MS spectra of the bulk standardized extracts in methanol were acquired. Additionally, an RPLC separation based on a simple gradient elution profile was applied to the standardized extracts. Detection was made through monitoring UV absorption at 220 nm wavelength or the total ion current (TIC) produced through (±) ESI-MS analysis. FHC was applied to raw, centered and scaled data sets, for evaluating the discrimination power of the method with respect to the origins of the extracts and to the batch to batch variability. The discrimination power increases with the increase of the intrinsic selectivity of the spectral technique being used: UV-Vis

Age and Mass for 920 Large Magellanic Cloud Clusters Derived from 100 Million Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

Popescu, Bogdan; Hanson, M. M.; Elmegreen, Bruce G.

2012-06-01

We present new age and mass estimates for 920 stellar clusters in the Large Magellanic Cloud (LMC) based on previously published broadband photometry and the stellar cluster analysis package, MASSCLEANage. Expressed in the generic fitting formula, d 2 N/dMdtvpropM α t β, the distribution of observed clusters is described by α = -1.5 to -1.6 and β = -2.1 to -2.2. For 288 of these clusters, ages have recently been determined based on stellar photometric color-magnitude diagrams, allowing us to gauge the confidence of our ages. The results look very promising, opening up the possibility that this sample of 920 clusters, with reliable and consistent age, mass, and photometric measures, might be used to constrain important characteristics about the stellar cluster population in the LMC. We also investigate a traditional age determination method that uses a χ2 minimization routine to fit observed cluster colors to standard infinite-mass limit simple stellar population models. This reveals serious defects in the derived cluster age distribution using this method. The traditional χ2 minimization method, due to the variation of U, B, V, R colors, will always produce an overdensity of younger and older clusters, with an underdensity of clusters in the log (age/yr) = [7.0, 7.5] range. Finally, we present a unique simulation aimed at illustrating and constraining the fading limit in observed cluster distributions that includes the complex effects of stochastic variations in the observed properties of stellar clusters.

Citywide cluster randomized trial to restore blighted vacant land and its effects on violence, crime, and fear

Treesearch

Charles C. Branas; Eugenia South; Michelle C. Kondo; Bernadette C. Hohl; Philippe Bourgois; Douglas J. Wiebe; John M. MacDonald

2018-01-01

Vacant and blighted urban land is a widespread and potentially risky environmental condition encountered by millions of people on a daily basis. About 15% of the land in US cities is deemed vacant or abandoned, an area roughly the size of Switzerland. In a citywide cluster randomized controlled trial, we investigated the effects of standardized, reproducible...

Accurate calibration of a molecular beam time-of-flight mass spectrometer for on-line analysis of high molecular weight species.

PubMed

Apicella, B; Wang, X; Passaro, M; Ciajolo, A; Russo, C

2016-10-15

Time-of-Flight (TOF) Mass Spectrometry is a powerful analytical technique, provided that an accurate calibration by standard molecules in the same m/z range of the analytes is performed. Calibration in a very large m/z range is a difficult task, particularly in studies focusing on the detection of high molecular weight clusters of different molecules or high molecular weight species. External calibration is the most common procedure used for TOF mass spectrometric analysis in the gas phase and, generally, the only available standards are made up of mixtures of noble gases, covering a small mass range for calibration, up to m/z 136 (higher mass isotope of xenon). In this work, an accurate calibration of a Molecular Beam Time-of Flight Mass Spectrometer (MB-TOFMS) is presented, based on the use of water clusters up to m/z 3000. The advantages of calibrating a MB-TOFMS with water clusters for the detection of analytes with masses above those of the traditional calibrants such as noble gases were quantitatively shown by statistical calculations. A comparison of the water cluster and noble gases calibration procedures in attributing the masses to a test mixture extending up to m/z 800 is also reported. In the case of the analysis of combustion products, another important feature of water cluster calibration was shown, that is the possibility of using them as "internal standard" directly formed from the combustion water, under suitable experimental conditions. The water clusters calibration of a MB-TOFMS gives rise to a ten-fold reduction in error compared to the traditional calibration with noble gases. The consequent improvement in mass accuracy in the calibration of a MB-TOFMS has important implications in various fields where detection of high molecular mass species is required. In combustion products analysis, it is also possible to obtain a new calibration spectrum before the acquisition of each spectrum, only modifying some operative conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Energy Innovation Clusters and their Influence on Manufacturing: A Case Study Perspective

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

Engel-Cox, Jill; Hill, Derek

Innovation clusters have been important for recent development of clean energy technologies and their emergence as mature, globally competitive industries. However, the factors that influence the co-location of manufacturing activities with innovation clusters are less clear. A central question for government agencies seeking to grow manufacturing as part of economic development in their location is how innovation clusters influence manufacturing. Thus, this paper examines case studies of innovation clusters for three different clean energy technologies that have developed in at least two locations: solar PV clusters in California and the province of Jiangsu in China, wind turbine clusters in Germanymore » and the U.S. Great Lakes region, and ethanol clusters in the U.S. Midwest and the state of Sao Paulo in Brazil. These case studies provide initial insight into factors and conditions that contribute to technology manufacturing facility location decisions.« less

Design and simulation study of the immunization Data Quality Audit (DQA).

PubMed

Woodard, Stacy; Archer, Linda; Zell, Elizabeth; Ronveaux, Olivier; Birmingham, Maureen

2007-08-01

The goal of the Data Quality Audit (DQA) is to assess whether the Global Alliance for Vaccines and Immunization-funded countries are adequately reporting the number of diphtheria-tetanus-pertussis immunizations given, on which the "shares" are awarded. Given that this sampling design is a modified two-stage cluster sample (modified because a stratified, rather than a simple, random sample of health facilities is obtained from the selected clusters); the formula for the calculation of the standard error for the estimate is unknown. An approximated standard error has been proposed, and the first goal of this simulation is to assess the accuracy of the standard error. Results from the simulations based on hypothetical populations were found not to be representative of the actual DQAs that were conducted. Additional simulations were then conducted on the actual DQA data to better access the precision of the DQ with both the original and the increased sample sizes.

A novel polyketide biosynthesis gene cluster is involved in fruiting body morphogenesis in the filamentous fungi Sordaria macrospora and Neurospora crassa.

PubMed

Nowrousian, Minou

2009-04-01

During fungal fruiting body development, hyphae aggregate to form multicellular structures that protect and disperse the sexual spores. Analysis of microarray data revealed a gene cluster strongly upregulated during fruiting body development in the ascomycete Sordaria macrospora. Real time PCR analysis showed that the genes from the orthologous cluster in Neurospora crassa are also upregulated during development. The cluster encodes putative polyketide biosynthesis enzymes, including a reducing polyketide synthase. Analysis of knockout strains of a predicted dehydrogenase gene from the cluster showed that mutants in N. crassa and S. macrospora are delayed in fruiting body formation. In addition to the upregulated cluster, the N. crassa genome comprises another cluster containing a polyketide synthase gene, and five additional reducing polyketide synthase (rpks) genes that are not part of clusters. To study the role of these genes in sexual development, expression of the predicted rpks genes in S. macrospora (five genes) and N. crassa (six genes) was analyzed; all but one are upregulated during sexual development. Analysis of knockout strains for the N. crassa rpks genes showed that one of them is essential for fruiting body formation. These data indicate that polyketides produced by RPKSs are involved in sexual development in filamentous ascomycetes.

Effects of physical activity on schoolchildren's academic performance: The Active Smarter Kids (ASK) cluster-randomized controlled trial.

PubMed

Resaland, Geir K; Aadland, Eivind; Moe, Vegard Fusche; Aadland, Katrine N; Skrede, Turid; Stavnsbo, Mette; Suominen, Laura; Steene-Johannessen, Jostein; Glosvik, Øyvind; Andersen, John R; Kvalheim, Olav M; Engelsrud, Gunn; Andersen, Lars B; Holme, Ingar M; Ommundsen, Yngvar; Kriemler, Susi; van Mechelen, Willem; McKay, Heather A; Ekelund, Ulf; Anderssen, Sigmund A

2016-10-01

To investigate the effect of a seven-month, school-based cluster-randomized controlled trial on academic performance in 10-year-old children. In total, 1129 fifth-grade children from 57 elementary schools in Sogn og Fjordane County, Norway, were cluster-randomized by school either to the intervention group or to the control group. The children in the 28 intervention schools participated in a physical activity intervention between November 2014 and June 2015 consisting of three components: 1) 90min/week of physically active educational lessons mainly carried out in the school playground; 2) 5min/day of physical activity breaks during classroom lessons; 3) 10min/day physical activity homework. Academic performance in numeracy, reading and English was measured using standardized Norwegian national tests. Physical activity was measured objectively by accelerometry. We found no effect of the intervention on academic performance in primary analyses (standardized difference 0.01-0.06, p>0.358). Subgroup analyses, however, revealed a favorable intervention effect for those who performed the poorest at baseline (lowest tertile) for numeracy (p=0.005 for the subgroup∗group interaction), compared to controls (standardized difference 0.62, 95% CI 0.19-1.07). This large, rigorously conducted cluster RCT in 10-year-old children supports the notion that there is still inadequate evidence to conclude that increased physical activity in school enhances academic achievement in all children. Still, combining physical activity and learning seems a viable model to stimulate learning in those academically weakest schoolchildren. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Simulation and evaluation on the eco-industrial system of Changchun economic and technological development zone, China.

PubMed

Zhao, Yan; Shang, Jin-cheng; Chen, Chong; Wu, He-nan

2008-04-01

Reasonable structure, adaptive patterns and effective regulation of society, economy and environment subsystems should be taken into account in order to obtain harmonious development of urban eco-industrial system. We simulated and evaluated a redesigned eco-industrial system in Changchun Economic and Technological Development Zone (CCETDZ) in the present work using system dynamics and grey cluster methods. Four typical development strategies were simulated during 2005-2020 via standard system dynamic models. Furthermore, analytic hierarchy process and grey cluster allowed for the eco-industrial system evaluation and scenarios optimizing. Our dynamic simulation and statistical analysis revealed that: (1) CCETDZ would have different development scenarios under different strategies. The total population in scenario 2 grew most rapidly and reached 3.28 x 10(5) in 2020, exceeding its long-term planning expected population. And the GDP differences among these four scenarios would amount to 6.41 x 10(10) RMB. On the other hand, environmental pollution would become serious along with economy increasing. As a restriction factor, positive or negative increment of water resource will occur according to the selected strategy. (2) The fourth strategy would have the best efficiency, which means that the most efficiently development of CCETDZ required to take science, technology, environment progress and economy increase into account at the same time. (3) Positive environment protection measures, such as cleaner production, green manufacture, production life cycle management and environment friendly industries, should be attached great importance the same as economy development during 2005-2020 in CCETDZ.

Patterns and Prevalence of Core Profile Types in the WPPSI Standardization Sample.

ERIC Educational Resources Information Center

Glutting, Joseph J.; McDermott, Paul A.

1990-01-01

Found most representative subtest profiles for 1,200 children comprising standardization sample of Wechsler Preschool and Primary Scale of Intelligence (WPPSI). Grouped scaled scores from WPPSI subtests according to similar level and shape using sequential minimum-variance cluster analysis with independent replications. Obtained final solution of…

7 CFR 52.1850 - Sizes of raisins with seeds-except layer or cluster.

Code of Federal Regulations, 2010 CFR

2010-01-01

... MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946 PROCESSED FRUITS AND VEGETABLES, PROCESSED PRODUCTS... perforations 22/64-inch in diameter. (3) Mixed size raisins means a mixture which does not meet either the...

Illinois Occupational Skill Standards: Occupational Therapy 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 jobs in occupational therapy. Agency partners involved in this project include: the Illinois State board of Education, Illinois Community College…

Illinois Occupational Skill Standards: Agricultural Sales and Marketing 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 jobs in agricultural sales and marketing. Agency partners involved in this project include: the Illinois State Board of Education, Illinois Community…

Environmental and Agricultural Sciences. Georgia Core Standards for Occupational Clusters.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Dept. of Occupational Studies.

This document lists core standards and occupational knowledge amd skills that have been identified/validated by industry as necessary to all Georgia students in secondary-level environmental and agricultural sciences programs. First, foundation skills are grouped as follows: basic skills (reading, writing, arithmetic/mathematics, listening,…

Business, Marketing, and Information Management. Georgia Core Standards for Occupational Clusters.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Dept. of Occupational Studies.

This document lists core standards and occupational knowledge and skills that have been identified and validated by industry as necessary to all Georgia students in business, marketing, and information management programs. First, foundation skills are grouped as follows: basic skills (reading, writing, arithmetic/mathematics, listening, speaking);…

Illinois Occupational Skill Standards: HVAC/R Technician 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 jobs in the heating, ventilation, air conditioning, and refrigeration (HVAC/R) industry. Agency partners involved in this project include: the…

Illinois Occupational Skill Standards: Plastics Molding 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 jobs in the plastics molding industry. Agency partners involved in this project include: the Illinois State Board of Education, Illinois Community…

Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

PubMed

Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

2018-05-01

Cystic fibrosis pulmonary exacerbations accelerate pulmonary decline and increase mortality. Previously, we identified a 10-gene leukocyte panel measured directly from whole blood, which indicates response to exacerbation treatment. We hypothesized that molecular characteristics of exacerbations could also predict future disease severity. We tested whether a 10-gene panel measured from whole blood could identify patient cohorts at increased risk for severe morbidity and mortality, beyond standard clinical measures. Transcript abundance for the 10-gene panel was measured from whole blood at the beginning of exacerbation treatment (n = 57). A hierarchical cluster analysis of subjects based on their gene expression was performed, yielding four molecular clusters. An analysis of cluster membership and outcomes incorporating an independent cohort (n = 21) was completed to evaluate robustness of cluster partitioning of genes to predict severe morbidity and mortality. The four molecular clusters were analyzed for differences in forced expiratory volume in 1 second, C-reactive protein, return to baseline forced expiratory volume in 1 second after treatment, time to next exacerbation, and time to morbidity or mortality events (defined as lung transplant referral, lung transplant, intensive care unit admission for respiratory insufficiency, or death). Clustering based on gene expression discriminated between patient groups with significant differences in forced expiratory volume in 1 second, admission frequency, and overall morbidity and mortality. At 5 years, all subjects in cluster 1 (very low risk) were alive and well, whereas 90% of subjects in cluster 4 (high risk) had suffered a major event (P = 0.0001). In multivariable analysis, the ability of gene expression to predict clinical outcomes remained significant, despite adjustment for forced expiratory volume in 1 second, sex, and admission frequency. The robustness of gene clustering to categorize patients appropriately in terms of clinical characteristics, and short- and long-term clinical outcomes, remained consistent, even when adding in a secondary population with significantly different clinical outcomes. Whole blood gene expression profiling allows molecular classification of acute pulmonary exacerbations, beyond standard clinical measures, providing a predictive tool for identifying subjects at increased risk for mortality and disease progression.

Identifying Two Groups of Entitled Individuals: Cluster Analysis Reveals Emotional Stability and Self-Esteem Distinction.

PubMed

Crowe, Michael L; LoPilato, Alexander C; Campbell, W Keith; Miller, Joshua D

2016-12-01

The present study hypothesized that there exist two distinct groups of entitled individuals: grandiose-entitled, and vulnerable-entitled. Self-report scores of entitlement were collected for 916 individuals using an online platform. Model-based cluster analyses were conducted on the individuals with scores one standard deviation above mean (n = 159) using the five-factor model dimensions as clustering variables. The results support the existence of two groups of entitled individuals categorized as emotionally stable and emotionally vulnerable. The emotionally stable cluster reported emotional stability, high self-esteem, more positive affect, and antisocial behavior. The emotionally vulnerable cluster reported low self-esteem and high levels of neuroticism, disinhibition, conventionality, psychopathy, negative affect, childhood abuse, intrusive parenting, and attachment difficulties. Compared to the control group, both clusters reported being more antagonistic, extraverted, Machiavellian, and narcissistic. These results suggest important differences are missed when simply examining the linear relationships between entitlement and various aspects of its nomological network.

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.

A good mass proxy for galaxy clusters with XMM-Newton

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

Zhao, Hai-Hui; Jia, Shu-Mei; Chen, Yong

2013-12-01

We use a sample of 39 galaxy clusters at redshift z < 0.1 observed by XMM-Newton to investigate the relations between X-ray observables and total mass. Based on central cooling time and central temperature drop, the clusters in this sample are divided into two groups: 25 cool core clusters and 14 non-cool core clusters, respectively. We study the scaling relations of L {sub bol}-M {sub 500}, M {sub 500}-T, M {sub 500}-M {sub g}, and M {sub 500}-Y {sub X}, and also the influences of cool core on these relations. The results show that the M {sub 500}-Y {sub X}more » relation has a slope close to the standard self-similar value, has the smallest scatter and does not vary with the cluster sample. Moreover, the M {sub 500}-Y {sub X} relation is not affected by the cool core. Thus, the parameter of Y{sub X} may be the best mass indicator.« less

Quenching of satellite galaxies at the outskirts of galaxy clusters

NASA Astrophysics Data System (ADS)

Zinger, Elad; Dekel, Avishai; Kravtsov, Andrey V.; Nagai, Daisuke

2018-04-01

We find, using cosmological simulations of galaxy clusters, that the hot X-ray emitting intracluster medium (ICM) enclosed within the outer accretion shock extends out to Rshock ˜ (2-3)Rvir, where Rvir is the standard virial radius of the halo. Using a simple analytic model for satellite galaxies in the cluster, we evaluate the effect of ram-pressure stripping on the gas in the inner discs and in the haloes at different distances from the cluster centre. We find that significant removal of star-forming disc gas occurs only at r ≲ 0.5Rvir, while gas removal from the satellite halo is more effective and can occur when the satellite is found between Rvir and Rshock. Removal of halo gas sets the stage for quenching of the star formation by starvation over 2-3 Gyr, prior to the satellite entry to the inner cluster halo. This scenario explains the presence of quenched galaxies, preferentially discs, at the outskirts of galaxy clusters, and the delayed quenching of satellites compared to central galaxies.

Advanced Electrochemistry of Individual Metal Clusters Electrodeposited Atom by Atom to Nanometer by Nanometer.

PubMed

Kim, Jiyeon; Dick, Jeffrey E; Bard, Allen J

2016-11-15

Metal clusters are very important as building blocks for nanoparticles (NPs) for electrocatalysis and electroanalysis in both fundamental and applied electrochemistry. Attention has been given to understanding of traditional nucleation and growth of metal clusters and to their catalytic activities for various electrochemical applications in energy harvesting as well as analytical sensing. Importantly, understanding the properties of these clusters, primarily the relationship between catalysis and morphology, is required to optimize catalytic function. This has been difficult due to the heterogeneities in the size, shape, and surface properties. Thus, methods that address these issues are necessary to begin understanding the reactivity of individual catalytic centers as opposed to ensemble measurements, where the effect of size and morphology on the catalysis is averaged out in the measurement. This Account introduces our advanced electrochemical approaches to focus on each isolated metal cluster, where we electrochemically fabricated clusters or NPs atom by atom to nanometer by nanometer and explored their electrochemistry for their kinetic and catalytic behavior. Such approaches expand the dimensions of analysis, to include the electrochemistry of (1) a discrete atomic cluster, (2) solely a single NP, or (3) individual NPs in the ensemble sample. Specifically, we studied the electrocatalysis of atomic metal clusters as a nascent electrocatalyst via direct electrodeposition on carbon ultramicroelectrode (C UME) in a femtomolar metal ion precursor. In addition, we developed tunneling ultramicroelectrodes (TUMEs) to study electron transfer (ET) kinetics of a redox probe at a single metal NP electrodeposited on this TUME. Owing to the small dimension of a NP as an active area of a TUME, extremely high mass transfer conditions yielded a remarkably high standard ET rate constant, k 0 , of 36 cm/s for outer-sphere ET reaction. Most recently, we advanced nanoscale scanning electrochemical microscopy (SECM) imaging to resolve the electrocatalytic activity of individual electrodeposited NPs within an ensemble sample yielding consistent high k 0 values of ≥2 cm/s for the hydrogen oxidation reaction (HOR) at different NPs. We envision that our advanced electrochemical approaches will enable us to systematically address structure effects on the catalytic activity, thus providing a quantitative guideline for electrocatalysts in energy-related applications.

How to Select the most Relevant Roughness Parameters of a Surface: Methodology Research Strategy

NASA Astrophysics Data System (ADS)

Bobrovskij, I. N.

2018-01-01

In this paper, the foundations for new methodology creation which provides solving problem of surfaces structure new standards parameters huge amount conflicted with necessary actual floors quantity of surfaces structure parameters which is related to measurement complexity decreasing are considered. At the moment, there is no single assessment of the importance of a parameters. The approval of presented methodology for aerospace cluster components surfaces allows to create necessary foundation, to develop scientific estimation of surfaces texture parameters, to obtain material for investigators of chosen technological procedure. The methods necessary for further work, the creation of a fundamental reserve and development as a scientific direction for assessing the significance of microgeometry parameters are selected.

A cluster-based approach to selecting representative stimuli from the International Affective Picture System (IAPS) database.

PubMed

Constantinescu, Alexandra C; Wolters, Maria; Moore, Adam; MacPherson, Sarah E

2017-06-01

The International Affective Picture System (IAPS; Lang, Bradley, & Cuthbert, 2008) is a stimulus database that is frequently used to investigate various aspects of emotional processing. Despite its extensive use, selecting IAPS stimuli for a research project is not usually done according to an established strategy, but rather is tailored to individual studies. Here we propose a standard, replicable method for stimulus selection based on cluster analysis, which re-creates the group structure that is most likely to have produced the valence arousal, and dominance norms associated with the IAPS images. Our method includes screening the database for outliers, identifying a suitable clustering solution, and then extracting the desired number of stimuli on the basis of their level of certainty of belonging to the cluster they were assigned to. Our method preserves statistical power in studies by maximizing the likelihood that the stimuli belong to the cluster structure fitted to them, and by filtering stimuli according to their certainty of cluster membership. In addition, although our cluster-based method is illustrated using the IAPS, it can be extended to other stimulus databases.

Observing the clustering properties of galaxy clusters in dynamical dark-energy cosmologies

NASA Astrophysics Data System (ADS)

Fedeli, C.; Moscardini, L.; Bartelmann, M.

2009-06-01

We study the clustering properties of galaxy clusters expected to be observed by various forthcoming surveys both in the X-ray and sub-mm regimes by the thermal Sunyaev-Zel'dovich effect. Several different background cosmological models are assumed, including the concordance ΛCDM and various cosmologies with dynamical evolution of the dark energy. Particular attention is paid to models with a significant contribution of dark energy at early times which affects the process of structure formation. Past light cone and selection effects in cluster catalogs are carefully modeled by realistic scaling relations between cluster mass and observables and by properly taking into account the selection functions of the different instruments. The results show that early dark-energy models are expected to produce significantly lower values of effective bias and both spatial and angular correlation amplitudes with respect to the standard ΛCDM model. Among the cluster catalogs studied in this work, it turns out that those based on eRosita, Planck, and South Pole Telescope observations are the most promising for distinguishing between various dark-energy models.

The optimal design of stepped wedge trials with equal allocation to sequences and a comparison to other trial designs.

PubMed

Thompson, Jennifer A; Fielding, Katherine; Hargreaves, James; Copas, Andrew

2017-12-01

Background/Aims We sought to optimise the design of stepped wedge trials with an equal allocation of clusters to sequences and explored sample size comparisons with alternative trial designs. Methods We developed a new expression for the design effect for a stepped wedge trial, assuming that observations are equally correlated within clusters and an equal number of observations in each period between sequences switching to the intervention. We minimised the design effect with respect to (1) the fraction of observations before the first and after the final sequence switches (the periods with all clusters in the control or intervention condition, respectively) and (2) the number of sequences. We compared the design effect of this optimised stepped wedge trial to the design effects of a parallel cluster-randomised trial, a cluster-randomised trial with baseline observations, and a hybrid trial design (a mixture of cluster-randomised trial and stepped wedge trial) with the same total cluster size for all designs. Results We found that a stepped wedge trial with an equal allocation to sequences is optimised by obtaining all observations after the first sequence switches and before the final sequence switches to the intervention; this means that the first sequence remains in the control condition and the last sequence remains in the intervention condition for the duration of the trial. With this design, the optimal number of sequences is [Formula: see text], where [Formula: see text] is the cluster-mean correlation, [Formula: see text] is the intracluster correlation coefficient, and m is the total cluster size. The optimal number of sequences is small when the intracluster correlation coefficient and cluster size are small and large when the intracluster correlation coefficient or cluster size is large. A cluster-randomised trial remains more efficient than the optimised stepped wedge trial when the intracluster correlation coefficient or cluster size is small. A cluster-randomised trial with baseline observations always requires a larger sample size than the optimised stepped wedge trial. The hybrid design can always give an equally or more efficient design, but will be at most 5% more efficient. We provide a strategy for selecting a design if the optimal number of sequences is unfeasible. For a non-optimal number of sequences, the sample size may be reduced by allowing a proportion of observations before the first or after the final sequence has switched. Conclusion The standard stepped wedge trial is inefficient. To reduce sample sizes when a hybrid design is unfeasible, stepped wedge trial designs should have no observations before the first sequence switches or after the final sequence switches.

Microbicides Development Programme: Engaging the community in the standard of care debate in a vaginal microbicide trial in Mwanza, Tanzania

PubMed Central

Vallely, Andrew; Shagi, Charles; Lees, Shelley; Shapiro, Katherine; Masanja, Joseph; Nikolau, Lawi; Kazimoto, Johari; Soteli, Selephina; Moffat, Claire; Changalucha, John; McCormack, Sheena; Hayes, Richard J

2009-01-01

Background HIV prevention research in resource-limited countries is associated with a variety of ethical dilemmas. Key amongst these is the question of what constitutes an appropriate standard of health care (SoC) for participants in HIV prevention trials. This paper describes a community-focused approach to develop a locally-appropriate SoC in the context of a phase III vaginal microbicide trial in Mwanza City, northwest Tanzania. Methods A mobile community-based sexual and reproductive health service for women working as informal food vendors or in traditional and modern bars, restaurants, hotels and guesthouses has been established in 10 city wards. Wards were divided into geographical clusters and community representatives elected at cluster and ward level. A city-level Community Advisory Committee (CAC) with representatives from each ward has been established. Workshops and community meetings at ward and city-level have explored project-related concerns using tools adapted from participatory learning and action techniques e.g. chapati diagrams, pair-wise ranking. Secondary stakeholders representing local public-sector and non-governmental health and social care providers have formed a trial Stakeholders' Advisory Group (SAG), which includes two CAC representatives. Results Key recommendations from participatory community workshops, CAC and SAG meetings conducted in the first year of the trial relate to the quality and range of clinic services provided at study clinics as well as broader standard of care issues. Recommendations have included streamlining clinic services to reduce waiting times, expanding services to include the children and spouses of participants and providing care for common local conditions such as malaria. Participants, community representatives and stakeholders felt there was an ethical obligation to ensure effective access to antiretroviral drugs and to provide supportive community-based care for women identified as HIV positive during the trial. This obligation includes ensuring sustainable, post-trial access to these services. Post-trial access to an effective vaginal microbicide was also felt to be a moral imperative. Conclusion Participatory methodologies enabled effective partnerships between researchers, participant representatives and community stakeholders to be developed and facilitated local dialogue and consensus on what constitutes a locally-appropriate standard of care in the context of a vaginal microbicide trial in this setting. Trial registration Current Controlled Trials ISRCTN64716212 PMID:19814830

Small Project Rapid Integration and Test Environment (SPRITE) An Innovation Space for Small Projects Design, Development, Integration, and Test

NASA Technical Reports Server (NTRS)

Lee, Ashley; Rackoczy, John; Heater, Daniel; Sanders, Devon; Tashakkor, Scott

2013-01-01

Over the past few years interest in the development and use of small satellites has rapidly gained momentum with universities, commercial, and government organizations. In a few years we may see networked clusters of dozens or even hundreds of small, cheap, easily replaceable satellites working together in place of the large, expensive and difficult-to-replace satellites now in orbit. Standards based satellite buses and deployment mechanisms, such as the CubeSat and Poly Pico-satellite Orbital Deployer (P-POD), have stimulated growth in this area. The use of small satellites is also proving to be a cost effective capability in many areas traditionally dominated by large satellites, though many challenges remain. Currently many of these small satellites undergo very little testing prior to flight. As these small satellites move from technology demonstration and student projects toward more complex operational assets, it is expected that the standards for verification and validation will increase.

Use of medicines and adherence to standard treatment guidelines in rural community health centers, Timor-Leste.

PubMed

Higuchi, Michiyo; Okumura, Junko; Aoyama, Atsuko; Suryawati, Sri; Porter, John

2015-03-01

The use of medicines and nurses'/midwives' adherence to standard treatment guidelines (STGs) were examined in Timor-Leste during the early stage of the nation's new health system development. A cross-sectional study was conducted as the quantitative element of mixed methods research. Retrospective samples from patient registration books and prospective observations were obtained in 20 randomly selected rural community health centers. The medicines use indicators, in particular the level of injection use, in Timor-Leste did not suggest overprescription. Prescribers with clinical nurse training prescribed significantly fewer antibiotics than those without such training (P < .01). The adjusted odds ratio of prescribing adherence for clinical nurse training, after accounting for confounders and prescriber clustering, was 6.6 (P < .01). STGs for nonphysician health professionals at the primary health care level have potential value in basic health care delivery, including appropriate use of medicines, in resource-limited communities when strategically developed and introduced. © 2012 APJPH.

Network-based spatial clustering technique for exploring features in regional industry

NASA Astrophysics Data System (ADS)

Chou, Tien-Yin; Huang, Pi-Hui; Yang, Lung-Shih; Lin, Wen-Tzu

2008-10-01

In the past researches, industrial cluster mainly focused on single or particular industry and less on spatial industrial structure and mutual relations. Industrial cluster could generate three kinds of spillover effects, including knowledge, labor market pooling, and input sharing. In addition, industrial cluster indeed benefits industry development. To fully control the status and characteristics of district industrial cluster can facilitate to improve the competitive ascendancy of district industry. The related researches on industrial spatial cluster were of great significance for setting up industrial policies and promoting district economic development. In this study, an improved model, GeoSOM, that combines DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and SOM (Self-Organizing Map) was developed for analyzing industrial cluster. Different from former distance-based algorithm for industrial cluster, the proposed GeoSOM model can calculate spatial characteristics between firms based on DBSCAN algorithm and evaluate the similarity between firms based on SOM clustering analysis. The demonstrative data sets, the manufacturers around Taichung County in Taiwan, were analyzed for verifying the practicability of the proposed model. The analyzed results indicate that GeoSOM is suitable for evaluating spatial industrial cluster.

Constraints on cold dark matter theories from observations of massive x-ray-luminous clusters of galaxies at high redshift

NASA Technical Reports Server (NTRS)

Luppino, G. A.; Gioia, I. M.

1995-01-01

During the course of a gravitational lensing survey of distant, X-ray selected Einstein Observatory Extended Medium Sensitivity Survey (EMSS) clusters of galaxies, we have studied six X-ray-luminous (L(sub x) greater than 5 x 10(exp 44)(h(sub 50)(exp -2))ergs/sec) clusters at redshifts exceeding z = 0.5. All of these clusters are apparently massive. In addition to their high X-ray luminosity, two of the clusters at z approximately 0.6 exhibit gravitationally lensed arcs. Furthermore, the highest redshift cluster in our sample, MS 1054-0321 at z = 0.826, is both extremely X-ray luminous (L(sub 0.3-3.5keV)=9.3 x 10(exp 44)(h(sub 50)(exp -2))ergs/sec) and exceedingly rich with an optical richness comparable to an Abell Richness Class 4 cluster. In this Letter, we discuss the cosmological implications of the very existence of these clusters for hierarchical structure formation theories such as standard Omega = 1 CDM (cold dark matter), hybrid Omega = 1 C + HDM (hot dark matter), and flat, low-density Lambda + CDM models.

Thematic clustering of text documents using an EM-based approach

PubMed Central

2012-01-01

Clustering textual contents is an important step in mining useful information on the web or other text-based resources. The common task in text clustering is to handle text in a multi-dimensional space, and to partition documents into groups, where each group contains documents that are similar to each other. However, this strategy lacks a comprehensive view for humans in general since it cannot explain the main subject of each cluster. Utilizing semantic information can solve this problem, but it needs a well-defined ontology or pre-labeled gold standard set. In this paper, we present a thematic clustering algorithm for text documents. Given text, subject terms are extracted and used for clustering documents in a probabilistic framework. An EM approach is used to ensure documents are assigned to correct subjects, hence it converges to a locally optimal solution. The proposed method is distinctive because its results are sufficiently explanatory for human understanding as well as efficient for clustering performance. The experimental results show that the proposed method provides a competitive performance compared to other state-of-the-art approaches. We also show that the extracted themes from the MEDLINE® dataset represent the subjects of clusters reasonably well. PMID:23046528

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

NASA Astrophysics Data System (ADS)

Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.

2008-03-01

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

A cluster randomised feasibility study of an adolescent incentive intervention to increase uptake of HPV vaccination

PubMed Central

Forster, Alice S; Cornelius, Victoria; Rockliffe, Lauren; Marlow, Laura AV; Bedford, Helen; Waller, Jo

2017-01-01

Background: Uptake of human papillomavirus (HPV) vaccination is suboptimal among some groups. We aimed to determine the feasibility of undertaking a cluster randomised controlled trial (RCT) of incentives to improve HPV vaccination uptake by increasing consent form return. Methods: An equal-allocation, two-arm cluster RCT design was used. We invited 60 London schools to participate. Those agreeing were randomised to either a standard invitation or incentive intervention arm, in which Year 8 girls had the chance to win a £50 shopping voucher if they returned a vaccination consent form, regardless of whether consent was provided. We collected data on school and parent participation rates and questionnaire response rates. Analyses were descriptive. Results: Six schools completed the trial and only 3% of parents opted out. The response rate was 70% for the girls’ questionnaire and 17% for the parents’. In the intervention arm, 87% of girls returned a consent form compared with 67% in the standard invitation arm. The proportion of girls whose parents gave consent for vaccination was higher in the intervention arm (76%) than the standard invitation arm (61%). Conclusions: An RCT of an incentive intervention is feasible. The intervention may improve vaccination uptake but a fully powered RCT is needed. PMID:28829766

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

Cluster analysis of Southeastern U.S. climate stations

NASA Astrophysics Data System (ADS)

Stooksbury, D. E.; Michaels, P. J.

1991-09-01

A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.

New mechanisms of cluster diffusion on metal fcc(100) surfaces

NASA Astrophysics Data System (ADS)

Trushin, Oleg; Salo, Petri; Alatalo, Matti; Ala-Nissila, Tapio

2001-03-01

We have studied atomic mechanisms of the diffusion of small clusters on the fcc(100) metal surfaces using semi-empirical and ab-initio molecular static calculations. Primary goal of these studies was to investigate possible many-body mechanisms of cluster motion which can contribute to low temperature crystal growth. We used embedded atom and Glue potentials in semi-empirical simulations of Cu and Al. Combination of the Nudged Elastic Band and Eigenvector Following methods allowed us to find all the possible transition paths for cluster movements on flat terrace. In case of Cu(001) we have found several new mechanisms for diffusion of clusters, including mechanisms called row-shearing and dimer-rotating in which a whole row inside an island moves according to a concerted jump and a dimer rotates at the periphery of an island, respectively. In some cases these mechanisms yield a lower energy barrier than the standard mechanisms.

Clustering stocks using partial correlation coefficients

NASA Astrophysics Data System (ADS)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

Developing human rights based indicators to support country monitoring of rehabilitation services and programmes for people with disabilities: a study protocol.

PubMed

Skempes, Dimitrios; Bickenbach, Jerome

2015-09-24

Rehabilitation care is fundamental to health and human dignity and a human right enshrined in the United Nations Convention on the Rights of Persons with Disabilities. The provision of rehabilitation is important for reducing the need for formal support and enabling persons with disabilities to lead an independent life. Increasingly scholars and advocacy groups voice concerns over the significant barriers facing people with disabilities in accessing appropriate and quality rehabilitation. A growing body of research highlights a "respond-need" gap in the provision of rehabilitation and assistive technologies and underscore the lack of indicators for assessing performance of rehabilitation systems and monitoring States compliance with human rights standards in rehabilitation service planning and programming. While research on human rights and health monitoring has increased exponentially over the last decade far too little attention has been paid to rehabilitation services. The proposed research aims to reduce this knowledge gap by developing a human rights based monitoring framework with indicators to support human rights accountability and performance assessment in rehabilitation. Concept mapping, a stakeholder-driven approach will be used as the core method to identify rights based indicators and develop the rehabilitation services monitoring framework. Concept mapping requires participants from various stakeholders groups to generate a list of the potential indicators through on line brainstorming, sort the indicators for conceptual similarity into clusters and rate them against predefined criteria. Multidimensional scaling and hierarchical cluster data analysis will be performed to develop the monitoring framework while bridging analysis will provide useful insights about patterns of agreement or disagreement among participants views on indicators. This study has the potential to influence future practices on data collection and measurement of compliance with human rights standards in rehabilitation service delivery and organization. The development of a valid and universally applicable set of indicators will have a profound impact on the design and implementation of evidence informed disability policies and programs as it can support countries in strengthening performance measurement through documentation of comparative information on rehabilitation care systems. Most importantly, the resulting indicators can be used by disabled people's organizations as well as national and international institutions to define a minimal standard for monitoring and reporting progress on the implementation of the Convention on the Rights of Persons with Disabilities in the area of rehabilitation.

Firefighter Hand Anthropometry and Structural Glove Sizing: A New Perspective

PubMed Central

Hsiao, Hongwei; Whitestone, Jennifer; Kau, Tsui-Ying; Hildreth, Brooke

2015-01-01

Objective We evaluated the current use and fit of structural firefighting gloves and developed an improved sizing scheme that better accommodates the U.S. firefighter population. Background Among surveys, 24% to 30% of men and 31% to 62% of women reported experiencing problems with the fit or bulkiness of their structural firefighting gloves. Method An age-, race/ethnicity-, and gender-stratified sample of 863 male and 88 female firefighters across the United States participated in the study. Fourteen hand dimensions relevant to glove design were measured. A cluster analysis of the hand dimensions was performed to explore options for an improved sizing scheme. Results The current national standard structural firefighting glove-sizing scheme underrepresents firefighter hand size range and shape variation. In addition, mismatch between existing sizing specifications and hand characteristics, such as hand dimensions, user selection of glove size, and the existing glove sizing specifications, is significant. An improved glove-sizing plan based on clusters of overall hand size and hand/finger breadth-to-length contrast has been developed. Conclusion This study presents the most up-to-date firefighter hand anthropometry and a new perspective on glove accommodation. The new seven-size system contains narrower variations (standard deviations) for almost all dimensions for each glove size than the current sizing practices. Application The proposed science-based sizing plan for structural firefighting gloves provides a step-forward perspective (i.e., including two women hand model–based sizes and two wide-palm sizes for men) for glove manufacturers to advance firefighter hand protection. PMID:26169309

Breast cancer and symptom clusters during radiotherapy.

PubMed

Matthews, Ellyn E; Schmiege, Sarah J; Cook, Paul F; Sousa, Karen H

2012-01-01

Symptom clusters assessment shifts the clinical focus from a specific symptom to the patient's experience as a whole. Few studies have examined breast cancer symptom clusters during treatment, and fewer studies have addressed symptom clusters during radiation therapy (RT). The theoretical underpinning of this study is the Symptoms Experience Model. Research is needed to identify antecedents and consequences of cancer-related symptom clusters. The present study was intended to determine the clustering of symptoms during RT in women with breast cancer and significant correlations among the symptoms, individual characteristics, and mood. A secondary data analysis from a descriptive correlational study of 93 women at weeks 3 to 7 of RT from centers in the mid-Atlantic region of the United States, Symptom Distress Scale, the subscales of the Positive and Negative Affect Scale, Life Orientation Test, and Self-transcendence Scale were completed. Confirmatory factor analysis revealed symptoms grouped into 3 distinct clusters: pain-insomnia-fatigue, cognitive disturbance-outlook, and gastrointestinal. The pain-insomnia-fatigue and cognitive disturbance-outlook clusters were associated with individual characteristics, optimism, self-transcendence, and positive and negative mood. The gastrointestinal cluster correlated significantly only with positive mood. This study provides insight into symptoms that group together and the relationship of symptom clusters to antecedents and mood. These findings underscore the need to define and standardize the measurement of symptom clusters and understand variability in concurrent symptoms. Attention to symptom clusters shifts the clinical focus from a specific symptom to the patient's experience as a whole and helps identify the most effective interventions.

Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters.

PubMed

Lukashin, A V; Fuchs, R

2001-05-01

Cluster analysis of genome-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and samples. In the present paper, we focus on several important issues related to clustering algorithms that have not yet been fully studied. We describe a simple and robust algorithm for the clustering of temporal gene expression profiles that is based on the simulated annealing procedure. In general, this algorithm guarantees to eventually find the globally optimal distribution of genes over clusters. We introduce an iterative scheme that serves to evaluate quantitatively the optimal number of clusters for each specific data set. The scheme is based on standard approaches used in regular statistical tests. The basic idea is to organize the search of the optimal number of clusters simultaneously with the optimization of the distribution of genes over clusters. The efficiency of the proposed algorithm has been evaluated by means of a reverse engineering experiment, that is, a situation in which the correct distribution of genes over clusters is known a priori. The employment of this statistically rigorous test has shown that our algorithm places greater than 90% genes into correct clusters. Finally, the algorithm has been tested on real gene expression data (expression changes during yeast cell cycle) for which the fundamental patterns of gene expression and the assignment of genes to clusters are well understood from numerous previous studies.

Can standard cosmological models explain the observed Abell cluster bulk flow?

NASA Technical Reports Server (NTRS)

Strauss, Michael A.; Cen, Renyue; Ostriker, Jeremiah P.; Laure, Tod R.; Postman, Marc

1995-01-01

Lauer and Postman (LP) observed that all Abell clusters with redshifts less than 15,000 km/s appear to be participating in a bulk flow of 689 km/s with respect to the cosmic microwave background. We find this result difficult to reconcile with all popular models for large-scale structure formation that assume Gaussian initial conditions. This conclusion is based on Monte Carlo realizations of the LP data, drawn from large particle-mesh N-body simulations for six different models of the initial power spectrum (standard, tilted, and Omega(sub 0) = 0.3 cold dark matter, and two variants of the primordial baryon isocurvature model). We have taken special care to treat properly the longest-wavelength components of the power spectra. The simulations are sampled, 'observed,' and analyzed as identically as possible to the LP cluster sample. Large-scale bulk flows as measured from clusters in the simulations are in excellent agreement with those measured from the grid: the clusters do not exhibit any strong velocity bias on large scales. Bulk flows with amplitude as large as that reported by LP are not uncommon in the Monte Carlo data stes; the distribution of measured bulk flows before error bias subtraction is rougly Maxwellian, with a peak around 400 km/s. However the chi squared of the observed bulk flow, taking into account the anisotropy of the error ellipsoid, is much more difficult to match in the simulations. The models examined are ruled out at confidence levels between 94% and 98%.

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.

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

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.

Observations regarding the Development of Occupational/Skill Clusters.

ERIC Educational Resources Information Center

McCage, Ronald D.

This paper presents an overview and suggestions about the development of occupational and skill clusters by the Vocational-Technical Education Consortium of States (V-TECS), based on the observations of the executive director of the organization. Aspects reviewed include the following: development of occupational and skill clusters; classification…

Coordinate based random effect size meta-analysis of neuroimaging studies.

PubMed

Tench, C R; Tanasescu, Radu; Constantinescu, C S; Auer, D P; Cottam, W J

2017-06-01

Low power in neuroimaging studies can make them difficult to interpret, and Coordinate based meta-analysis (CBMA) may go some way to mitigating this issue. CBMA has been used in many analyses to detect where published functional MRI or voxel-based morphometry studies testing similar hypotheses report significant summary results (coordinates) consistently. Only the reported coordinates and possibly t statistics are analysed, and statistical significance of clusters is determined by coordinate density. Here a method of performing coordinate based random effect size meta-analysis and meta-regression is introduced. The algorithm (ClusterZ) analyses both coordinates and reported t statistic or Z score, standardised by the number of subjects. Statistical significance is determined not by coordinate density, but by a random effects meta-analyses of reported effects performed cluster-wise using standard statistical methods and taking account of censoring inherent in the published summary results. Type 1 error control is achieved using the false cluster discovery rate (FCDR), which is based on the false discovery rate. This controls both the family wise error rate under the null hypothesis that coordinates are randomly drawn from a standard stereotaxic space, and the proportion of significant clusters that are expected under the null. Such control is necessary to avoid propagating and even amplifying the very issues motivating the meta-analysis in the first place. ClusterZ is demonstrated on both numerically simulated data and on real data from reports of grey matter loss in multiple sclerosis (MS) and syndromes suggestive of MS, and of painful stimulus in healthy controls. The software implementation is available to download and use freely. Copyright © 2017 Elsevier Inc. All rights reserved.

A microfluidic device for label-free, physical capture of circulating tumor cell-clusters

PubMed Central

Sarioglu, A. Fatih; Aceto, Nicola; Kojic, Nikola; Donaldson, Maria C.; Zeinali, Mahnaz; Hamza, Bashar; Engstrom, Amanda; Zhu, Huili; Sundaresan, Tilak K.; Miyamoto, David T.; Luo, Xi; Bardia, Aditya; Wittner, Ben S.; Ramaswamy, Sridhar; Shioda, Toshi; Ting, David T.; Stott, Shannon L.; Kapur, Ravi; Maheswaran, Shyamala; Haber, Daniel A.; Toner, Mehmet

2015-01-01

Cancer cells metastasize through the bloodstream either as single migratory circulating tumor cells (CTCs) or as multicellular groupings (CTC-clusters). Existing technologies for CTC enrichment are designed primarily to isolate single CTCs, and while CTC-clusters are detectable in some cases, their true prevalence and significance remain to be determined. Here, we developed a microchip technology (Cluster-Chip) specifically designed to capture CTC-clusters independent of tumor-specific markers from unprocessed blood. CTC-clusters are isolated through specialized bifurcating traps under low shear-stress conditions that preserve their integrity and even two-cell clusters are captured efficiently. Using the Cluster-Chip, we identify CTC-clusters in 30–40% of patients with metastatic cancers of the breast, prostate and melanoma. RNA sequencing of CTC-clusters confirms their tumor origin and identifies leukocytes within the clusters as tissue-derived macrophages. Together, the development of a device for efficient capture of CTC-clusters will enable detailed characterization of their biological properties and role in cancer metastasis. PMID:25984697

Ab initio Bogoliubov coupled cluster theory for open-shell nuclei

DOE PAGES

Signoracci, Angelo J.; Duguet, Thomas; Hagen, Gaute; ...

2015-06-29

Background: Ab initio many-body methods have been developed over the past 10 yr to address closed-shell nuclei up to mass A≈130 on the basis of realistic two- and three-nucleon interactions. A current frontier relates to the extension of those many-body methods to the description of open-shell nuclei. Several routes to address open-shell nuclei are currently under investigation, including ideas that exploit spontaneous symmetry breaking. Purpose: Singly open-shell nuclei can be efficiently described via the sole breaking of U(1) gauge symmetry associated with particle-number conservation as a way to account for their superfluid character. While this route was recently followed withinmore » the framework of self-consistent Green's function theory, the goal of the present work is to formulate a similar extension within the framework of coupled cluster theory. Methods: We formulate and apply Bogoliubov coupled cluster (BCC) theory, which consists of representing the exact ground-state wave function of the system as the exponential of a quasiparticle excitation cluster operator acting on a Bogoliubov reference state. Equations for the ground-state energy and the cluster amplitudes are derived at the singles and doubles level (BCCSD) both algebraically and diagrammatically. The formalism includes three-nucleon forces at the normal-ordered two-body level. The first BCC code is implemented in m scheme, which will permit the treatment of doubly open-shell nuclei via the further breaking of SU(2) symmetry associated with angular momentum conservation. Results: Proof-of-principle calculations in an N max=6 spherical harmonic oscillator basis for 16,18O and 18Ne in the BCCD approximation are in good agreement with standard coupled cluster results with the same chiral two-nucleon interaction, while 20O and 20Mg display underbinding relative to experiment. The breaking of U(1) symmetry, monitored by computing the variance associated with the particle-number operator, is relatively constant for all five nuclei, in both the Hartree-Fock-Bogoliubov and BCCD approximations. Conclusions: The newly developed many-body formalism increases the potential span of ab initio calculations based on single-reference coupled cluster techniques tremendously, i.e., potentially to reach several hundred additional midmass nuclei. The new formalism offers a wealth of potential applications and further extensions dedicated to the description of ground and excited states of open-shell nuclei. Short-term goals include the implementation of three-nucleon forces at the normal-ordered two-body level. Midterm extensions include the approximate treatment of triples corrections and the development of the equation-of-motion methodology to treat both excited states and odd nuclei. Long-term extensions include exact restoration of U(1) and SU(2) symmetries.« less

An Assessment of the Condition of Coral Reefs off the Former Navy Bombing Ranges at Isla De Culebra and Isla De Vieques, Puerto Rico

DTIC Science & Technology

2005-04-01

Bray-Curtis distance measure with an Unweighted Pair Group Method with Arithmetic Averages ( UPGMA ) linkage method to perform a cluster analysis of the...59 35 Comparison of reef condition indicators clustering by UPGMA analysis...Polyvinyl Chloride RBD Red-band Disease SACEX Supporting Arms Coordination Exercise SAV Submerged Aquatic Vegetation SD Standard Deviation UPGMA

Molecular serotyping and antimicrobial resistance profiles of Actinobacillus pleuropneumoniae isolated from pigs in South Korea.

PubMed

Kim, Boram; Hur, Jin; Lee, Ji Yeong; Choi, Yoonyoung; Lee, John Hwa

2016-09-01

Actinobacillus pleuropneumoniae (APP) causes porcine pleuropneumonia (PP). Serotypes and antimicrobial resistance patterns in APP isolates from pigs in Korea were examined. Sixty-five APP isolates were genetically serotyped using standard and multiplex PCR (polymerase chain reaction). Antimicrobial susceptibilities were tested using the standardized disk-agar method. PCR was used to detect β-lactam, gentamicin and tetracycline-resistance genes. The random amplified polymorphic DNA (RAPD) patterns were determined by PCR. Korean pigs predominantly carried APP serotypes 1 and 5. Among 65 isolates, one isolate was sensitive to all 12 antimicrobials tested in this study. Sixty-two isolates was resistant to tetracycline and 53 isolates carried one or five genes including tet(B), tet(A), tet(H), tet(M)/tet(O), tet(C), tet(G) and/or tet(L)-1 markers. Among 64 strains, 9% and 26.6% were resistance to 10 and three or more antimicrobials, respectively. Thirteen different antimicrobial resistance patterns were observed and RAPD analysis revealed a separation of the isolates into two clusters: cluster II (6 strains resistant to 10 antimicrobials) and cluster I (the other 59 strains). Results show that APP serotypes 1 and 5 are the most common in Korea, and multi-drug resistant strains are prevalent. RAPD analysis demonstrated that six isolates resistant to 10 antimicrobials belonged to the same cluster.

SANTA BARBARA CLUSTER COMPARISON TEST WITH DISPH

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

Saitoh, Takayuki R.; Makino, Junichiro, E-mail: saitoh@elsi.jp

2016-06-01

The Santa Barbara cluster comparison project revealed that there is a systematic difference between entropy profiles of clusters of galaxies obtained by Eulerian mesh and Lagrangian smoothed particle hydrodynamics (SPH) codes: mesh codes gave a core with a constant entropy, whereas SPH codes did not. One possible reason for this difference is that mesh codes are not Galilean invariant. Another possible reason is the problem of the SPH method, which might give too much “protection” to cold clumps because of the unphysical surface tension induced at contact discontinuities. In this paper, we apply the density-independent formulation of SPH (DISPH), whichmore » can handle contact discontinuities accurately, to simulations of a cluster of galaxies and compare the results with those with the standard SPH. We obtained the entropy core when we adopt DISPH. The size of the core is, however, significantly smaller than those obtained with mesh simulations and is comparable to those obtained with quasi-Lagrangian schemes such as “moving mesh” and “mesh free” schemes. We conclude that both the standard SPH without artificial conductivity and Eulerian mesh codes have serious problems even with such an idealized simulation, while DISPH, SPH with artificial conductivity, and quasi-Lagrangian schemes have sufficient capability to deal with it.« less

Geographic clustering of emergency department presentations for atrial fibrillation and flutter in Alberta, Canada.

PubMed

Rosychuk, Rhonda J; Mariathas, Hensley H; Graham, Michelle M; Holroyd, Brian R; Rowe, Brian H

2015-08-01

Atrial fibrillation and flutter (AFF) are the most common arrhythmias seen in the outpatient setting, and they affect more than 300,000 adult Canadians. The aims of this study were to examine temporal and geographic trends in emergency department (ED) presentations made by adults (age ≥ 35 years) for AFF in Alberta, Canada, from 1999 to 2011. Statistical disease cluster detection techniques were used to identify geographic areas with higher numbers of individuals presenting with AFF and higher numbers of ED presentations for AFF than expected by chance alone. Geographic clusters of individuals with stroke or heart failure follow-up within 365 days of ED presentations for AFF were also identified. All ED presentations for AFF made by individuals aged ≥35 years were extracted from Alberta's Ambulatory Care Classification System. The Alberta Health Care Insurance Plan provided population counts and demographics for the patients presenting (age, sex, year, geographic unit). The Physician Claims File provided non-ED physician claims data after a patient's ED presentation. Statistical analyses included numerical and graphical summaries, directly standardized rates, and statistical disease cluster detection tests. During 12 years, there were 63,395 ED presentations for AFF made by 32,101 individuals. Standardized rates remained relatively stable over time, at about two per 1,000 for individuals presenting to the ED for AFF and about three per 1,000 for ED presentations for AFF. The northern and southeastern parts of the province were identified as clusters of individuals presenting for AFF, and ED presentations for AFF, and several of the areas demonstrated clusters in multiple years. Further, several of the geographic clusters were also identified as potential clusters for stroke or heart failure within 365 days after the ED presentations for AFF. This population-based study spanned 12 fiscal years and showed variations in the number of people presenting to EDs for AFF and the number of ED presentations for AFF over geography. The potential clusters identified may represent geographic areas with higher disease severity or a lower availability of non-ED health services. The clusters are not all likely to have occurred by chance, and further investigation and intervention could occur to reduce ED presentations for AFF. © 2015 by the Society for Academic Emergency Medicine.

a Snapshot Survey of X-Ray Selected Central Cluster Galaxies

NASA Astrophysics Data System (ADS)

Edge, Alastair

1999-07-01

Central cluster galaxies are the most massive stellar systems known and have been used as standard candles for many decades. Only recently have central cluster galaxies been recognised to exhibit a wide variety of small scale {<100 pc} features that can only be reliably detected with HST resolution. The most intriguing of these are dust lanes which have been detected in many central cluster galaxies. Dust is not expected to survive long in the hostile cluster environment unless shielded by the ISM of a disk galaxy or very dense clouds of cold gas. WFPC2 snapshot images of a representative subset of the central cluster galaxies from an X-ray selected cluster sample would provide important constraints on the formation and evolution of dust in cluster cores that cannot be obtained from ground-based observations. In addition, these images will allow the AGN component, the frequency of multiple nuclei, and the amount of massive-star formation in central cluster galaxies to be ass es sed. The proposed HST observatio ns would also provide high-resolution images of previously unresolved gravitational arcs in the most massive clusters in our sample resulting in constraints on the shape of the gravitational potential of these systems. This project will complement our extensive multi-frequency work on this sample that includes optical spectroscopy and photometry, VLA and X-ray images for the majority of the 210 targets.

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

PubMed

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

2016-04-01

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

Surrogate Reservoir Model

NASA Astrophysics Data System (ADS)

Mohaghegh, Shahab

2010-05-01

Surrogate Reservoir Model (SRM) is new solution for fast track, comprehensive reservoir analysis (solving both direct and inverse problems) using existing reservoir simulation models. SRM is defined as a replica of the full field reservoir simulation model that runs and provides accurate results in real-time (one simulation run takes only a fraction of a second). SRM mimics the capabilities of a full field model with high accuracy. Reservoir simulation is the industry standard for reservoir management. It is used in all phases of field development in the oil and gas industry. The routine of simulation studies calls for integration of static and dynamic measurements into the reservoir model. Full field reservoir simulation models have become the major source of information for analysis, prediction and decision making. Large prolific fields usually go through several versions (updates) of their model. Each new version usually is a major improvement over the previous version. The updated model includes the latest available information incorporated along with adjustments that usually are the result of single-well or multi-well history matching. As the number of reservoir layers (thickness of the formations) increases, the number of cells representing the model approaches several millions. As the reservoir models grow in size, so does the time that is required for each run. Schemes such as grid computing and parallel processing helps to a certain degree but do not provide the required speed for tasks such as: field development strategies using comprehensive reservoir analysis, solving the inverse problem for injection/production optimization, quantifying uncertainties associated with the geological model and real-time optimization and decision making. These types of analyses require hundreds or thousands of runs. Furthermore, with the new push for smart fields in the oil/gas industry that is a natural growth of smart completion and smart wells, the need for real time reservoir modeling becomes more pronounced. SRM is developed using the state of the art in neural computing and fuzzy pattern recognition to address the ever growing need in the oil and gas industry to perform accurate, but high speed simulation and modeling. Unlike conventional geo-statistical approaches (response surfaces, proxy models …) that require hundreds of simulation runs for development, SRM is developed only with a few (from 10 to 30 runs) simulation runs. SRM can be developed regularly (as new versions of the full field model become available) off-line and can be put online for real-time processing to guide important decisions. SRM has proven its value in the field. An SRM was developed for a giant oil field in the Middle East. The model included about one million grid blocks with more than 165 horizontal wells and took ten hours for a single run on 12 parallel CPUs. Using only 10 simulation runs, an SRM was developed that was able to accurately mimic the behavior of the reservoir simulation model. Performing a comprehensive reservoir analysis that included making millions of SRM runs, wells in the field were divided into five clusters. It was predicted that wells in cluster one & two are best candidates for rate relaxation with minimal, long term water production while wells in clusters four and five are susceptive to high water cuts. Two and a half years and 20 wells later, rate relaxation results from the field proved that all the predictions made by the SRM analysis were correct. While incremental oil production increased in all wells (wells in clusters 1 produced the most followed by wells in cluster 2, 3 …) the percent change in average monthly water cut for wells in each cluster clearly demonstrated the analytic power of SRM. As it was correctly predicted, wells in clusters 1 and 2 actually experience a reduction in water cut while a substantial increase in water cut was observed in wells classified into clusters 4 and 5. Performing these analyses would have been impossible using the original full field simulation model.

Word-initial /r/-clusters in Swedish speaking children with typical versus protracted phonological development.

PubMed

Lundeborg Hammarström, Inger

2018-01-01

The present study investigated word-initial (WI) /r/-clusters in Central Swedish-speaking children with and without protracted phonological development (PPD). Data for WI singleton /r/ and singleton and cluster /l/ served as comparisons. Participants were twelve 4-year-olds with PPD and twelve age- and gender-matched typically developing (TD) controls. Native speakers audio-recorded and transcribed 109 target single words using a Swedish phonology test with 12 WI C+/r/-clusters and three WI CC+/r/-clusters. The results showed significantly higher match scores for the TD children, a lower match proportion for the /r/ targets and for singletons compared with clusters, and differences in mismatch patterns between the groups. There were no matches for /r/-cluster targets in the PPD group, with all children except two in that group showing deletions for both /r/-cluster types. The differences in mismatch proportions and types between the PPD group and controls suggests new directions for future clinical practice.

Anthocyanins in the bracts of Curcuma species and relationship of the species based on anthocyanin composition.

PubMed

Koshioka, Masaji; Umegaki, Naoko; Boontiang, Kriangsuk; Pornchuti, Witayaporn; Thammasiri, Kanchit; Yamaguchi, Satoshi; Tatsuzawa, Fumi; Nakayama, Masayoshi; Tateishi, Akira; Kubota, Satoshi

2015-03-01

Five anthocyanins, delphinidin 3-O-rutinoside, cyanidin 3-O-rutinoside, petunidin 3-O-rutinoside, malvidin 3-O-glucoside and malvidin 3-O-rutinoside, were identified. Three anthocyanins, delphinidin 3-O-glucoside, cyanidin 3-O-glucoside and pelargonidin 3-O-rutinoside, were putatively identified based on C18 HPLC retention time, absorption spectrum, including λmax, and comparisons with those of corresponding standard anthocyanins, as the compounds responsible for the pink to purple-red pigmentation of the bracts of Curcuma alismatifolia and five related species. Cluster analysis based on four major anthocyanins formed two clusters. One consisted of only one species, C. alismatifolia, and the other consisted of five. Each cluster further formed sub-clusters depending on either species or habitats.

Toward a DNA Taxonomy of Alpine Rhithrogena (Ephemeroptera: Heptageniidae) Using a Mixed Yule-Coalescent Analysis of Mitochondrial and Nuclear DNA

PubMed Central

Vuataz, Laurent; Sartori, Michel; Wagner, André; Monaghan, Michael T.

2011-01-01

Aquatic larvae of many Rhithrogena mayflies (Ephemeroptera) inhabit sensitive Alpine environments. A number of species are on the IUCN Red List and many recognized species have restricted distributions and are of conservation interest. Despite their ecological and conservation importance, ambiguous morphological differences among closely related species suggest that the current taxonomy may not accurately reflect the evolutionary diversity of the group. Here we examined the species status of nearly 50% of European Rhithrogena diversity using a widespread sampling scheme of Alpine species that included 22 type localities, general mixed Yule-coalescent (GMYC) model analysis of one standard mtDNA marker and one newly developed nDNA marker, and morphological identification where possible. Using sequences from 533 individuals from 144 sampling localities, we observed significant clustering of the mitochondrial (cox1) marker into 31 GMYC species. Twenty-one of these could be identified based on the presence of topotypes (expertly identified specimens from the species' type locality) or unambiguous morphology. These results strongly suggest the presence of both cryptic diversity and taxonomic oversplitting in Rhithrogena. Significant clustering was not detected with protein-coding nuclear PEPCK, although nine GMYC species were congruent with well supported terminal clusters of nDNA. Lack of greater congruence in the two data sets may be the result of incomplete sorting of ancestral polymorphism. Bayesian phylogenetic analyses of both gene regions recovered four of the six recognized Rhithrogena species groups in our samples as monophyletic. Future development of more nuclear markers would facilitate multi-locus analysis of unresolved, closely related species pairs. The DNA taxonomy developed here lays the groundwork for a future revision of the important but cryptic Rhithrogena genus in Europe. PMID:21611178

Eliminating Social Inequality by Reinforcing Standard Language Ideology? Language Policy for Dutch in Flemish Schools

ERIC Educational Resources Information Center

Delarue, Steven; De Caluwe, Johan

2015-01-01

Flanders, the northern, Dutch-speaking part of Belgium, is experiencing growing intra- and interlingual diversity. On the intralingual level, Tussentaal ("in-between-language") has emerged as a cluster of intermediate varieties between the Flemish dialects and Standard Dutch, gradually becoming "the" colloquial language. At the…

7 CFR 989.702 - Minimum grade standards for packed raisins.

Code of Federal Regulations, 2010 CFR

2010-01-01

... RAISINS PRODUCED FROM GRAPES GROWN IN CALIFORNIA Quality Control § 989.702 Minimum grade standards for... washed with water to assure a wholesome product. (2) Grades. (i) Marketing Order Grade A is a quality of... paragraph. (ii) Marketing Order Grade B is the quality of the Cluster Seedless raisins that have similar...

An oral health intervention for people with serious mental illness (Three Shires Early Intervention Dental Trial): study protocol for a randomised controlled trial.

PubMed

Jones, Hannah F; Adams, Clive E; Clifton, Andrew; Simpson, Jayne; Tosh, Graeme; Liddle, Peter F; Callaghan, Patrick; Yang, Min; Guo, Boliang; Furtado, Vivek

2013-05-29

Oral health is an important part of general physical health and is essential for self-esteem, self-confidence and overall quality of life. There is a well-established link between mental illness and poor oral health. Oral health problems are not generally well recognized by mental health professionals and many patients experience barriers to treatment. This is the protocol for a pragmatic cluster randomised trial that has been designed to fit within standard care. Dental awareness training for care co-ordinators plus a dental checklist for service users in addition to standard care will be compared with standard care alone for people with mental illness. The checklist consists of questions about service users' current oral health routine and condition. Ten Early Intervention in Psychosis (EIP) teams in Nottinghamshire, Derbyshire and Lincolnshire will be cluster randomised (five to intervention and five to standard care) in blocks accounting for location and size of caseload. The oral health of the service users will be monitored for one year after randomisation. Current Controlled Trials ISRCTN63382258.

A national study of the molecular epidemiology of HIV-1 in Australia 2005–2012

PubMed Central

Castley, Alison; Sawleshwarkar, Shailendra; Varma, Rick; Herring, Belinda; Thapa, Kiran; Dwyer, Dominic; Chibo, Doris; Nguyen, Nam; Hawke, Karen; Ratcliff, Rodney; Garsia, Roger; Kelleher, Anthony; Nolan, David

2017-01-01

Introduction Rates of new HIV-1 diagnoses are increasing in Australia, with evidence of an increasing proportion of non-B HIV-1 subtypes reflecting a growing impact of migration and travel. The present study aims to define HIV-1 subtype diversity patterns and investigate possible HIV-1 transmission networks within Australia. Methods The Australian Molecular Epidemiology Network (AMEN) HIV collaborating sites in Western Australia, South Australia, Victoria, Queensland and western Sydney (New South Wales), provided baseline HIV-1 partial pol sequence, age and gender information for 4,873 patients who had genotypes performed during 2005–2012. HIV-1 phylogenetic analyses utilised MEGA V6, with a stringent classification of transmission pairs or clusters (bootstrap ≥98%, genetic distance ≤1.5% from at least one other sequence in the cluster). Results HIV-1 subtype B represented 74.5% of the 4,873 sequences (WA 59%, SA 68.4%, w-Syd 73.8%, Vic 75.6%, Qld 82.1%), with similar proportion of transmission pairs and clusters found in the B and non-B cohorts (23% vs 24.5% of sequences, p = 0.3). Significantly more subtype B clusters were comprised of ≥3 sequences compared with non-B clusters (45.0% vs 24.0%, p = 0.021) and significantly more subtype B pairs and clusters were male-only (88% compared to 53% CRF01_AE and 17% subtype C clusters). Factors associated with being in a cluster of any size included; being sequenced in a more recent time period (p<0.001), being younger (p<0.001), being male (p = 0.023) and having a B subtype (p = 0.02). Being in a larger cluster (>3) was associated with being sequenced in a more recent time period (p = 0.05) and being male (p = 0.008). Conclusion This nationwide HIV-1 study of 4,873 patient sequences highlights the increased diversity of HIV-1 subtypes within the Australian epidemic, as well as differences in transmission networks associated with these HIV-1 subtypes. These findings provide epidemiological insights not readily available using standard surveillance methods and can inform the development of effective public health strategies in the current paradigm of HIV prevention in Australia. PMID:28489920

Absolute Magnitude Calibration for Dwarfs Based on the Colour-Magnitude Diagrams of Galactic Clusters

NASA Astrophysics Data System (ADS)

Karaali, S.; Gökçe, E. Yaz; Bilir, S.; Güçtekin, S. Tunçel

2014-07-01

We present two absolute magnitude calibrations for dwarfs based on colour-magnitude diagrams of Galactic clusters. The combination of the Mg absolute magnitudes of the dwarf fiducial sequences of the clusters M92, M13, M5, NGC 2420, M67, and NGC 6791 with the corresponding metallicities provides absolute magnitude calibration for a given (g - r)0 colour. The calibration is defined in the colour interval 0.25 ≤ (g - r)0 ≤ 1.25 mag and it covers the metallicity interval - 2.15 ≤ [Fe/H] ≤ +0.37 dex. The absolute magnitude residuals obtained by the application of the procedure to another set of Galactic clusters lie in the interval - 0.15 ≤ ΔMg ≤ +0.12 mag. The mean and standard deviation of the residuals are < ΔMg > = - 0.002 and σ = 0.065 mag, respectively. The calibration of the MJ absolute magnitude in terms of metallicity is carried out by using the fiducial sequences of the clusters M92, M13, 47 Tuc, NGC 2158, and NGC 6791. It is defined in the colour interval 0.90 ≤ (V - J)0 ≤ 1.75 mag and it covers the same metallicity interval of the Mg calibration. The absolute magnitude residuals obtained by the application of the procedure to the cluster M5 ([Fe/H] = -1.40 dex) and 46 solar metallicity, - 0.45 ≤ [Fe/H] ≤ +0.35 dex, field stars lie in the interval - 0.29 and + 0.35 mag. However, the range of 87% of them is rather shorter, - 0.20 ≤ ΔMJ ≤ +0.20 mag. The mean and standard deviation of all residuals are < ΔMJ > =0.05 and σ = 0.13 mag, respectively. The derived relations are applicable to stars older than 4 Gyr for the Mg calibration, and older than 2 Gyr for the MJ calibration. The cited limits are the ages of the youngest calibration clusters in the two systems.

A clinical carepath for obese pregnant women: A pragmatic pilot cluster randomized controlled trial.

PubMed

McDonald, Sarah D; Viaje, Kristen A; Rooney, Rebecca A; Jarde, Alexander; Giglia, Lucia; Maxwell, Cynthia V; Small, David; Kelly, Tracy Pearce; Midwifery, B H Sc; Sabatino, Lisa; Thabane, Lehana

2018-05-17

Obese women are at increased risks for complications during pregnancy, birth and in their infants. Although guidelines have been established for the clinical care of obese pregnant women, management is sometimes suboptimal. Our goal was to determine the feasibility of implementing and testing a clinical carepath for obese pregnant women compared to standard care, in a pilot cluster randomized controlled trial (RCT). A pragmatic pilot cluster RCT was conducted, randomly allocating eight clinics to the carepath or standard care for obese pregnant women. Women were eligible if they had a prepregnancy body mass index of ≥ 30 kg/m 2 and a viable singleton < 21 weeks. The primary outcomes were the feasibility of conducting a full-scale cluster RCT (defined as > 80%: randomization of clinics, use in eligible women, and completeness of follow-up) and of the intervention (defined as > 80%: compliance with each step in the carepath, and recommendation of the carepath by clinicians to a colleague). All eight approached clinics agreed to participate and were randomized. Half of the intervention clinics used the carepath, resulting in < 80% uptake of eligible women. High follow-up (99.5%) was achieved, in 188 of 189 women. The carepath was feasible for numerous guideline-directed recommendations for screening, but less so for counselling topics. When the carepath was used in the majority of women, all clinicians, most of whom were midwives, reported they would recommend it to a colleague. The intervention group had significantly higher overall adherence to the guideline recommendations compared to control (relative risk 1.71, 95% confidence interval 1.57-1.87). In this pragmatic pilot cluster RCT, a guideline-directed clinical carepath improved some aspects of care of obese pregnant women and was recommended by clinicians, particularly midwives. A cluster RCT may not be feasible in a mix of obstetric and midwifery clinics, but may be feasible in midwifery clinics. This pragmatic pilot cluster RCT was registered on clinicaltrials.gov (identifier: NCT02534051 ).

The effects of baryon physics, black holes and active galactic nucleus feedback on the mass distribution in clusters of galaxies

NASA Astrophysics Data System (ADS)

Martizzi, Davide; Teyssier, Romain; Moore, Ben; Wentz, Tina

2012-06-01

The spatial distribution of matter in clusters of galaxies is mainly determined by the dominant dark matter component; however, physical processes involving baryonic matter are able to modify it significantly. We analyse a set of 500 pc resolution cosmological simulations of a cluster of galaxies with mass comparable to Virgo, performed with the AMR code RAMSES. We compare the mass density profiles of the dark, stellar and gaseous matter components of the cluster that result from different assumptions for the subgrid baryonic physics and galaxy formation processes. First, the prediction of a gravity-only N-body simulation is compared to that of a hydrodynamical simulation with standard galaxy formation recipes, and then all results are compared to a hydrodynamical simulation which includes thermal active galactic nucleus (AGN) feedback from supermassive black holes (SMBHs). We find the usual effects of overcooling and adiabatic contraction in the run with standard galaxy formation physics, but very different results are found when implementing SMBHs and AGN feedback. Star formation is strongly quenched, producing lower stellar densities throughout the cluster, and much less cold gas is available for star formation at low redshifts. At redshift z= 0 we find a flat density core of radius 10 kpc in both the dark and stellar matter density profiles. We speculate on the possible formation mechanisms able to produce such cores and we conclude that they can be produced through the coupling of different processes: (I) dynamical friction from the decay of black hole orbits during galaxy mergers; (II) AGN-driven gas outflows producing fluctuations of the gravitational potential causing the removal of collisionless matter from the central region of the cluster; (III) adiabatic expansion in response to the slow expulsion of gas from the central region of the cluster during the quiescent mode of AGN activity.

Volunteer Clouds and Citizen Cyberscience for LHC Physics

NASA Astrophysics Data System (ADS)

Aguado Sanchez, Carlos; Blomer, Jakob; Buncic, Predrag; Chen, Gang; Ellis, John; Garcia Quintas, David; Harutyunyan, Artem; Grey, Francois; Lombrana Gonzalez, Daniel; Marquina, Miguel; Mato, Pere; Rantala, Jarno; Schulz, Holger; Segal, Ben; Sharma, Archana; Skands, Peter; Weir, David; Wu, Jie; Wu, Wenjing; Yadav, Rohit

2011-12-01

Computing for the LHC, and for HEP more generally, is traditionally viewed as requiring specialized infrastructure and software environments, and therefore not compatible with the recent trend in "volunteer computing", where volunteers supply free processing time on ordinary PCs and laptops via standard Internet connections. In this paper, we demonstrate that with the use of virtual machine technology, at least some standard LHC computing tasks can be tackled with volunteer computing resources. Specifically, by presenting volunteer computing resources to HEP scientists as a "volunteer cloud", essentially identical to a Grid or dedicated cluster from a job submission perspective, LHC simulations can be processed effectively. This article outlines both the technical steps required for such a solution and the implications for LHC computing as well as for LHC public outreach and for participation by scientists from developing regions in LHC research.

Apex predator and the cyclic competition in a rock-paper-scissors game of three species

NASA Astrophysics Data System (ADS)

Souza-Filho, C. A.; Bazeia, D.; Ramos, J. G. G. S.

2017-06-01

This work deals with the effects of an apex predator on the cyclic competition among three distinct species that follow the rules of the rock-paper-scissors game. The investigation develops standard stochastic simulations but is motivated by a procedure which is explained in the work. We add the apex predator as the fourth species in a system that contains three species that evolve following the standard rules of migration, reproduction, and predation, and study how the system evolves in this new environment, in comparison with the case in the absence of the apex predator. The results show that the apex predator engenders the tendency to spread uniformly in the lattice, contributing to destroy the spiral patterns, keeping biodiversity but diminishing the average size of the clusters of the species that compete cyclically.

Pilot Study of an Open-source Image Analysis Software for Automated Screening of Conventional Cervical Smears.

PubMed

Sanyal, Parikshit; Ganguli, Prosenjit; Barui, Sanghita; Deb, Prabal

2018-01-01

The Pap stained cervical smear is a screening tool for cervical cancer. Commercial systems are used for automated screening of liquid based cervical smears. However, there is no image analysis software used for conventional cervical smears. The aim of this study was to develop and test the diagnostic accuracy of a software for analysis of conventional smears. The software was developed using Python programming language and open source libraries. It was standardized with images from Bethesda Interobserver Reproducibility Project. One hundred and thirty images from smears which were reported Negative for Intraepithelial Lesion or Malignancy (NILM), and 45 images where some abnormality has been reported, were collected from the archives of the hospital. The software was then tested on the images. The software was able to segregate images based on overall nuclear: cytoplasmic ratio, coefficient of variation (CV) in nuclear size, nuclear membrane irregularity, and clustering. 68.88% of abnormal images were flagged by the software, as well as 19.23% of NILM images. The major difficulties faced were segmentation of overlapping cell clusters and separation of neutrophils. The software shows potential as a screening tool for conventional cervical smears; however, further refinement in technique is required.

Evaluation of Eight Methods for Aligning Orientation of Two Coordinate Systems.

PubMed

Mecheri, Hakim; Robert-Lachaine, Xavier; Larue, Christian; Plamondon, André

2016-08-01

The aim of this study was to evaluate eight methods for aligning the orientation of two different local coordinate systems. Alignment is very important when combining two different systems of motion analysis. Two of the methods were developed specifically for biomechanical studies, and because there have been at least three decades of algorithm development in robotics, it was decided to include six methods from this field. To compare these methods, an Xsens sensor and two Optotrak clusters were attached to a Plexiglas plate. The first optical marker cluster was fixed on the sensor and 20 trials were recorded. The error of alignment was calculated for each trial, and the mean, the standard deviation, and the maximum values of this error over all trials were reported. One-way repeated measures analysis of variance revealed that the alignment error differed significantly across the eight methods. Post-hoc tests showed that the alignment error from the methods based on angular velocities was significantly lower than for the other methods. The method using angular velocities performed the best, with an average error of 0.17 ± 0.08 deg. We therefore recommend this method, which is easy to perform and provides accurate alignment.

Cost/Performance Ratio Achieved by Using a Commodity-Based Cluster

NASA Technical Reports Server (NTRS)

Lopez, Isaac

2001-01-01

Researchers at the NASA Glenn Research Center acquired a commodity cluster based on Intel Corporation processors to compare its performance with a traditional UNIX cluster in the execution of aeropropulsion applications. Since the cost differential of the clusters was significant, a cost/performance ratio was calculated. After executing a propulsion application on both clusters, the researchers demonstrated a 9.4 cost/performance ratio in favor of the Intel-based cluster. These researchers utilize the Aeroshark cluster as one of the primary testbeds for developing NPSS parallel application codes and system software. The Aero-shark cluster provides 64 Intel Pentium II 400-MHz processors, housed in 32 nodes. Recently, APNASA - a code developed by a Government/industry team for the design and analysis of turbomachinery systems was used for a simulation on Glenn's Aeroshark cluster.

Profiling Local Optima in K-Means Clustering: Developing a Diagnostic Technique

ERIC Educational Resources Information Center

Steinley, Douglas

2006-01-01

Using the cluster generation procedure proposed by D. Steinley and R. Henson (2005), the author investigated the performance of K-means clustering under the following scenarios: (a) different probabilities of cluster overlap; (b) different types of cluster overlap; (c) varying samples sizes, clusters, and dimensions; (d) different multivariate…

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

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.

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.

Automated Epileptiform Spike Detection via Affinity Propagation-Based Template Matching

PubMed Central

Thomas, John; Jin, Jing; Dauwels, Justin; Cash, Sydney S.; Westover, M. Brandon

2018-01-01

Interictal epileptiform spikes are the key diagnostic biomarkers for epilepsy. The clinical gold standard of spike detection is visual inspection performed by neurologists. This is a tedious, time-consuming, and expert-centered process. The development of automated spike detection systems is necessary in order to provide a faster and more reliable diagnosis of epilepsy. In this paper, we propose an efficient template matching spike detector based on a combination of spike and background waveform templates. We generate a template library by clustering a collection of spikes and background waveforms extracted from a database of 50 patients with epilepsy. We benchmark the performance of five clustering techniques based on the receiver operating characteristic (ROC) curves. In addition, background templates are integrated with existing spike templates to improve the overall performance. The affinity propagation-based template matching system with a combination of spike and background templates is shown to outperform the other four conventional methods with the highest area-under-curve (AUC) of 0.953. PMID:29060543

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

PubMed

Sauzet, Odile; Peacock, Janet L

2017-07-20

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

An Overview of the History of Cluster Conferences

NASA Astrophysics Data System (ADS)

Horiuchi, H.

2017-06-01

An overview is given on the historical development of the cluster conference series which started at Bohum in 1969. I start with the discussion of the philosophy of Karl Wildermuth and then I make a review on the main subjects and topics in cluster conferences. Since the cluster dynamics is a main nuclear dynamics together with the mean-field dynamics, we see that development of the cluster conference has been along with the rises of many new subjects in nuclear physics itself. Examples of them include superheavy nuclei, nuclear astrophysics, neutron-rich nuclei, cluster-gas states and ab initio calculations. Finally I discuss that more activities in and attention to cluster physics are seen in recent days.

GestationaL Obesity Weight management: Implementation of National Guidelines (GLOWING): a pilot cluster randomised controlled trial of a guideline implementation intervention for the management of maternal obesity by midwives.

PubMed

Heslehurst, Nicola; Rankin, Judith; McParlin, Catherine; Sniehotta, Falko F; Howel, Denise; Rice, Stephen; McColl, Elaine

2018-01-01

Weight management in pregnancy guidelines exist, although dissemination alone is an ineffective means of implementation. Midwives identify the need for support to overcome complex barriers to practice. An evaluation of an intervention to support midwives' guideline implementation would require a large-scale cluster randomised controlled trial. A pilot study is necessary to explore the feasibility of delivery and evaluation prior to a definitive trial. The GestationaL Obesity Weight management: Implementation of National Guidelines (GLOWING) trial aims to test whether it is feasible and acceptable to deliver a behaviour change intervention to support midwives' implementation of weight management guidelines. GLOWING is a multi-centre parallel group pilot cluster randomised controlled trial comparing the delivery of a behaviour change intervention for midwives versus usual practice. Four NHS Trusts (clusters) will be randomised to intervention and control arms, stratified by size of maternity services. The intervention uses social cognitive theory and consists of face-to-face midwifery training plus information resources for routine practice. The main outcomes are whether the intervention and trial procedures are feasible and acceptable to participants and the feasibility of recruitment and data collection for a definitive trial. Target recruitment involves all eligible midwives in the intervention arm recruited to receive the intervention, 30 midwives and pregnant women per arm for baseline and outcome questionnaire data collection and 20 midwives and women to provide qualitative data. All quantitative and qualitative analyses will be descriptive with the purpose of informing the development of the definitive trial. This pilot study has been developed to support community midwives' implementation of guidelines. Community midwives have been selected as they usually carry out the booking appointment which includes measuring and discussing maternal body mass index. A cluster design is the gold standard in implementation research as there would be a high risk of contamination if randomisation was at individual midwife level: community midwives usually work in locality-based teams, interact on a daily basis, and share care of pregnant women. The results of the pilot trial will be used to further develop and refine GLOWING prior to a definitive trial to evaluate effectiveness and cost-effectiveness. ISRCTN46869894; retrospectively registered 25th May 2016.

Precision cosmology from X-ray AGN clustering

NASA Astrophysics Data System (ADS)

Basilakos, Spyros; Plionis, Manolis

2009-11-01

We place tight constraints on the main cosmological parameters of spatially flat cosmological models by using the recent angular clustering results of XMM-Newton soft (0.5-2keV) X-ray sources, which have a redshift distribution with a median of z ~ 1. Performing a standard likelihood procedure, assuming a constant in comoving coordinates active galactic nuclei (AGN) clustering evolution, the AGN bias evolution model of Basilakos, Plionis & Ragone-Figueroa and the Wilkinson Microwave Anisotropy Probe5 value of σ8, we find stringent simultaneous constraints in the (Ωm, w) plane, with Ωm = 0.26 +/- 0.05, w = -0.93+0.11-0.19.

Selection of representative embankments based on rough set - fuzzy clustering method

NASA Astrophysics Data System (ADS)

Bin, Ou; Lin, Zhi-xiang; Fu, Shu-yan; Gao, Sheng-song

2018-02-01

The premise condition of comprehensive evaluation of embankment safety is selection of representative unit embankment, on the basis of dividing the unit levee the influencing factors and classification of the unit embankment are drafted.Based on the rough set-fuzzy clustering, the influence factors of the unit embankment are measured by quantitative and qualitative indexes.Construct to fuzzy similarity matrix of standard embankment then calculate fuzzy equivalent matrix of fuzzy similarity matrix by square method. By setting the threshold of the fuzzy equivalence matrix, the unit embankment is clustered, and the representative unit embankment is selected from the classification of the embankment.

A nonperturbative light-front coupled-cluster method

NASA Astrophysics Data System (ADS)

Hiller, J. R.

2012-10-01

The nonperturbative Hamiltonian eigenvalue problem for bound states of a quantum field theory is formulated in terms of Dirac's light-front coordinates and then approximated by the exponential-operator technique of the many-body coupled-cluster method. This approximation eliminates any need for the usual approximation of Fock-space truncation. Instead, the exponentiated operator is truncated, and the terms retained are determined by a set of nonlinear integral equations. These equations are solved simultaneously with an effective eigenvalue problem in the valence sector, where the number of constituents is small. Matrix elements can be calculated, with extensions of techniques from standard coupled-cluster theory, to obtain form factors and other observables.

Molecular dynamics simulations of the structure evolutions of Cu-Zr metallic glasses under irradiation

NASA Astrophysics Data System (ADS)

Lang, Lin; Tian, Zean; Xiao, Shifang; Deng, Huiqiu; Ao, Bingyun; Chen, Piheng; Hu, Wangyu

2017-02-01

Molecular dynamics simulations have been performed to investigate the structural evolution of Cu64.5Zr35.5 metallic glasses under irradiation. The largest standard cluster analysis (LSCA) method was used to quantify the microstructure within the collision cascade regions. It is found that the majority of clusters within the collision cascade regions are full and defective icosahedrons. Not only the smaller structures (common neighbor subcluster) but also primary clusters greatly changed during the collision cascades; while most of these radiation damages self-recover quickly in the following quench states. These findings indicate the Cu-Zr metallic glasses have excellent irradiation-resistance properties.

Investing in innovation: trade-offs in the costs and cost-efficiency of school feeding using community-based kitchens in Bangladesh.

PubMed

Gelli, Aulo; Suwa, Yuko

2014-09-01

School feeding programs have been a key response to the recent food and economic crises and function to some degree in nearly every country in the world. However, school feeding programs are complex and exhibit different, context-specific models or configurations. To examine the trade-offs, including the costs and cost-efficiency, of an innovative cluster kitchen implementation model in Bangladesh using a standardized framework. A supply chain framework based on international standards was used to provide benchmarks for meaningful comparisons across models. Implementation processes specific to the program in Bangladesh were mapped against this reference to provide a basis for standardized performance measures. Qualitative and quantitative data on key metrics were collected retrospectively using semistructured questionnaires following an ingredients approach, including both financial and economic costs. Costs were standardized to a 200-feeding-day year and 700 kcal daily. The cluster kitchen model had similarities with the semidecentralized model and outsourced models in the literature, the main differences involving implementation scale, scale of purchasing volumes, and frequency of purchasing. Two important features stand out in terms of implementation: the nutritional quality of meals and the level of community involvement. The standardized full cost per child per year was US$110. Despite the nutritious content of the meals, the overall cost-efficiency in cost per nutrient output was lower than the benchmark for centralized programs, due mainly to support and start-up costs. Cluster kitchens provide an example of an innovative implementation model, combining an emphasis on quality meal delivery with strong community engagement. However, the standardized costs-per child were above the average benchmarks for both low-and middle-income countries. In contrast to the existing benchmark data from mature, centralized models, the main cost drivers of the program were associated with support and start-up activities. Further research is required to better understand changes in cost drivers as programs mature.

Cluster headache - clinical pattern and a new severity scale in a Swedish cohort.

PubMed

Steinberg, Anna; Fourier, Carmen; Ran, Caroline; Waldenlind, Elisabet; Sjöstrand, Christina; Belin, Andrea Carmine

2018-06-01

Background The aim of this study was to investigate clinical features of a cluster headache cohort in Sweden and to construct and test a new scale for grading severity. Methods Subjects were identified by screening medical records for the ICD 10 code G44.0, that is, cluster headache. Five hundred participating research subjects filled in a questionnaire including personal, demographic and medical aspects. We constructed a novel scale for grading cluster headache in this cohort: The Cluster Headache Severity Scale, which included number of attacks per day, attack and period duration. The lowest total score was three and the highest 12, and we used the Cluster Headache Severity Scale to grade subjects suffering from cluster headache. We further implemented the scale by defining a cluster headache maximum severity subgroup with a high Cluster Headache Severity Scale score ≥ 9. Results A majority (66.7%) of the patients reported that attacks appear at certain time intervals. In addition, cluster headache patients who were current tobacco users or had a history of tobacco consumption had a later age of disease onset (31.7 years) compared to non-tobacco users (28.5 years). The Cluster Headache Severity Scale score was higher in the patient group reporting sporadic or no alcohol intake than in the groups reporting an alcohol consumption of three to four standard units per week or more. Maximum severity cluster headache patients were characterised by higher age at disease onset, greater use of prophylactic medication, reduced hours of sleep, and lower alcohol consumption compared to the non-cluster headache maximum severity group. Conclusion There was a wide variation of severity grade among cluster headache patients, with a very marked impact on daily living for the most profoundly affected.

Fingerprint analysis of Hibiscus mutabilis L. leaves based on ultra performance liquid chromatography with photodiode array detector combined with similarity analysis and hierarchical clustering analysis methods

PubMed Central

Liang, Xianrui; Ma, Meiling; Su, Weike

2013-01-01

Background: A method for chemical fingerprint analysis of Hibiscus mutabilis L. leaves was developed based on ultra performance liquid chromatography with photodiode array detector (UPLC-PAD) combined with similarity analysis (SA) and hierarchical clustering analysis (HCA). Materials and Methods: 10 batches of Hibiscus mutabilis L. leaves samples were collected from different regions of China. UPLC-PAD was employed to collect chemical fingerprints of Hibiscus mutabilis L. leaves. Results: The relative standard deviations (RSDs) of the relative retention times (RRT) and relative peak areas (RPA) of 10 characteristic peaks (one of them was identified as rutin) in precision, repeatability and stability test were less than 3%, and the method of fingerprint analysis was validated to be suitable for the Hibiscus mutabilis L. leaves. Conclusions: The chromatographic fingerprints showed abundant diversity of chemical constituents qualitatively in the 10 batches of Hibiscus mutabilis L. leaves samples from different locations by similarity analysis on basis of calculating the correlation coefficients between each two fingerprints. Moreover, the HCA method clustered the samples into four classes, and the HCA dendrogram showed the close or distant relations among the 10 samples, which was consistent to the SA result to some extent. PMID:23930008

VariantSpark: population scale clustering of genotype information.

PubMed

O'Brien, Aidan R; Saunders, Neil F W; Guo, Yi; Buske, Fabian A; Scott, Rodney J; Bauer, Denis C

2015-12-10

Genomic information is increasingly used in medical practice giving rise to the need for efficient analysis methodology able to cope with thousands of individuals and millions of variants. The widely used Hadoop MapReduce architecture and associated machine learning library, Mahout, provide the means for tackling computationally challenging tasks. However, many genomic analyses do not fit the Map-Reduce paradigm. We therefore utilise the recently developed SPARK engine, along with its associated machine learning library, MLlib, which offers more flexibility in the parallelisation of population-scale bioinformatics tasks. The resulting tool, VARIANTSPARK provides an interface from MLlib to the standard variant format (VCF), offers seamless genome-wide sampling of variants and provides a pipeline for visualising results. To demonstrate the capabilities of VARIANTSPARK, we clustered more than 3,000 individuals with 80 Million variants each to determine the population structure in the dataset. VARIANTSPARK is 80 % faster than the SPARK-based genome clustering approach, ADAM, the comparable implementation using Hadoop/Mahout, as well as ADMIXTURE, a commonly used tool for determining individual ancestries. It is over 90 % faster than traditional implementations using R and Python. The benefits of speed, resource consumption and scalability enables VARIANTSPARK to open up the usage of advanced, efficient machine learning algorithms to genomic data.

Relationship of some upland rice genotype after gamma irradiation

NASA Astrophysics Data System (ADS)

Suliartini, N. W. S.; Wijayanto, T.; Madiki, A.; Boer, D.; Muhidin; Juniawan

2018-02-01

The objective of the research was to group local upland rice genotypes after being treated with gamma irradiation. The research materials were upland rice genotypes resulted from mutation of the second generation and two parents: Pae Loilo (K3D0) and Pae Pongasi (K2D0) Cultivars. The research was conducted at the Indonesian Sweetener and Fiber Crops Research Institute, Malang Regency, and used the augmented design method. Research data were analyzed with R Program. Eight hundred and seventy one genotypes were selected with the selection criteria were based on yields on the average parents added 1.5 standard deviation. Based on the selection, eighty genotypes were analyzed with cluster analyses. Nine observation variables were used to develop cluster dendrogram using average linked method. Genetic distance was measured by euclidean distance. The results of cluster dendrogram showed that tested genotypes were divided into eight groups. Group 1, 2, 7, and 8 each had one genotype, group 3 and 6 each had two genotypes, group 4 had 25 genotypes, and group 5 had 51 genotypes. Check genotypes formed a separate group. Group 6 had the highest yield per plant of 126.11 gram, followed by groups 5 and 4 of 97.63 and 94.08 gram, respectively.

Self-organizing map analysis using multivariate data from theophylline powders predicted by a thin-plate spline interpolation.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Kikuchi, Shingo; Takayama, Kozo

2010-11-01

The quality by design concept in pharmaceutical formulation development requires establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline powders were prepared based on the standard formulation. The angle of repose, compressibility, cohesion, and dispersibility were measured as the response variables. These responses were predicted quantitatively on the basis of a nonlinear TPS. A large amount of data on these powders was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the powders could be classified into several distinctive clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and powder characteristics. For instance, the quantities of microcrystalline cellulose (MCC) and magnesium stearate (Mg-St) were classified distinctly into each cluster, indicating that the quantities of MCC and Mg-St were crucial for determining the powder characteristics. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline powder formulations. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Current trends in molecular diagnostics of chronic myeloid leukemia.

PubMed

Vinhas, Raquel; Cordeiro, Milton; Pedrosa, Pedro; Fernandes, Alexandra R; Baptista, Pedro V

2017-08-01

Nearly 1.5 million people worldwide suffer from chronic myeloid leukemia (CML), characterized by the genetic translocation t(9;22)(q34;q11.2), involving the fusion of the Abelson oncogene (ABL1) with the breakpoint cluster region (BCR) gene. Early onset diagnosis coupled to current therapeutics allow for a treatment success rate of 90, which has focused research on the development of novel diagnostics approaches. In this review, we present a critical perspective on current strategies for CML diagnostics, comparing to gold standard methodologies and with an eye on the future trends on nanotheranostics.

Working Around Cosmic Variance: Remote Quadrupole Measurements of the CMB

NASA Astrophysics Data System (ADS)

Adil, Arsalan; Bunn, Emory

2018-01-01

Anisotropies in the CMB maps continue to revolutionize our understanding of the Cosmos. However, the statistical interpretation of these anisotropies is tainted with a posteriori statistics. The problem is particularly emphasized for lower order multipoles, i.e. in the cosmic variance regime of the power spectrum. Naturally, the solution lies in acquiring a new data set – a rather difficult task given the sample size of the Universe.The CMB temperature, in theory, depends on: the direction of photon propagation, the time at which the photons are observed, and the observer’s location in space. In existing CMB data, only the first parameter varies. However, as first pointed out by Kamionkowski and Loeb, a solution lies in making the so-called “Remote Quadrupole Measurements” by analyzing the secondary polarization produced by incoming CMB photons via the Sunyaev-Zel’dovich (SZ) effect. These observations allow us to measure the projected CMB quadrupole at the location and look-back time of a galaxy cluster.At low redshifts, the remote quadrupole is strongly correlated to the CMB anisotropy from our last scattering surface. We provide here a formalism for computing the covariance and relation matrices for both the two-point correlation function on the last scattering surface of a galaxy cluster and the cross correlation of the remote quadrupole with the local CMB. We then calculate these matrices based on a fiducial model and a non-standard model that suppresses power at large angles for ~104 clusters up to z=2. We anticipate to make a priori predictions of the differences between our expectations for the standard and non-standard models. Such an analysis is timely in the wake of the CMB S4 era which will provide us with an extensive SZ cluster catalogue.

Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study.

PubMed

Wu, Jia; Gensheimer, Michael F; Dong, Xinzhe; Rubin, Daniel L; Napel, Sandy; Diehn, Maximilian; Loo, Billy W; Li, Ruijiang

2016-08-01

To develop an intratumor partitioning framework for identifying high-risk subregions from (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. In this institutional review board-approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). We propose a robust intratumor partitioning method to identify clinically relevant, high-risk subregions in lung cancer. We envision that this approach will be applicable to identifying useful imaging biomarkers in many cancer types. Copyright © 2016 Elsevier Inc. All rights reserved.

Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study

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

Wu, Jia; Gensheimer, Michael F.; Dong, Xinzhe

2016-08-01

Purpose: To develop an intratumor partitioning framework for identifying high-risk subregions from {sup 18}F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods and Materials: In this institutional review board–approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET andmore » CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). Conclusion: We propose a robust intratumor partitioning method to identify clinically relevant, high-risk subregions in lung cancer. We envision that this approach will be applicable to identifying useful imaging biomarkers in many cancer types.« less

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2016-12-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Appraising the self-assessed support needs of Turkish women with breast cancer.

PubMed

Erci, B; Karabulut, N

2007-03-01

The purposes of this study were to establish the range of needs of women with breast cancer and to examine how women's needs might form clusters that could provide the basis for developing a standardized scale of needs for use by local breast care nurses in the evaluation of care. The sample consisted of 143 women with breast cancer who were admitted to the outpatient and inpatient oncology clinics in a university hospital in Erzurum, Turkey. The data were collected by questionnaire, and included demographic characteristics and the self-assessed support needs of women with breast cancer. Statistical analyses have shown that the standardized scale of needs has statistically acceptable levels of reliability and validity. The women's support needs mostly clustered in Family and Friends (79%) and After Care (78.3%). The most frequently required support category was Family and Friend; however, the women were in need of support of all categories. In terms of age ranges, there are statistically significant differences in relation to Femininity and Body Image, and Family and Friends of the seven categories. Women experienced a high level of needs associated with a diagnosis of breast cancer. The results in this study should increase awareness among cancer care professionals about a range of psychosocial needs and may help them target particular patient groups for particular support interventions.

Reducing diarrhoea in Guatemalan children: randomized controlled trial of flocculant-disinfectant for drinking-water.

PubMed

Chiller, Tom M; Mendoza, Carlos E; Lopez, M Beatriz; Alvarez, Maricruz; Hoekstra, Robert M; Keswick, Bruce H; Luby, Stephen P

2006-01-01

To examine the effect of a new point-of-use treatment for drinking-water, a commercially developed flocculant-disinfectant, on the prevalence of diarrhoea in children. We conducted a randomized controlled trial among 514 rural Guatemalan households, divided into 42 neighbourhood clusters, for 13 weeks, from 4 November 2002 through 31 January 2003. Clusters assigned to water treatment with the flocculant-disinfectant were compared with those using their usual water-handling practices. The longitudinal prevalence of diarrhoea was calculated as the proportion of total days with diarrhoea divided by the total number of days of observation. The prevalence of diarrhoea was compared using the Wilcoxon rank-sum test. The 1702 people in households receiving the disinfectant had a prevalence of diarrhoea that was 40% lower than that among the 1699 people using standard water-handling practices (0.9% versus 1.5%; P = 0.001). In households using the flocculant-disinfectant, children < 1 year of age had a 39% lower prevalence of diarrhoea than those in households using their standard practices (3.7% versus 6.0%; P = 0.005). In settings where families rarely treat drinking-water, we introduced a novel flocculant-disinfectant that reduced the longitudinal prevalence of diarrhoea, especially among children aged < 1 year, among whom diarrhoea has been strongly associated with mortality. Successful introduction and use of this product could contribute to preventing diarrhoeal disease globally.

Combining satellite photographs and raster lidar data for channel connectivity in tidal marshes.

NASA Astrophysics Data System (ADS)

Li, Zhi; Hodges, Ben

2017-04-01

High resolution airborne lidar is capable of providing topographic detail down to the 1 x 1 m scale or finer over large tidal marshes of a river delta. Such data sets can be challenging to develop and ground-truth due to the inherent complexities of the environment, the relatively small changes in elevation throughout a marsh, and practical difficulties in accessing the variety of flooded, dry, and muddy regions. Standard lidar point-cloud processing techniques (as typically applied in large lidar data collection program) have a tendency to mis-identify narrow channels and water connectivity in a marsh, which makes it difficult to directly use such data for modeling marsh flows. Unfortunately, it is not always practical, or even possible, to access the point cloud and re-analyze the raw lidar data when discrepancies have been found in a raster work product. Faced with this problem in preparing a model of the Trinity River delta (Texas, USA), we developed an approach to integrating analysis of a lidar-based raster with satellite images. Our primary goal was to identify the clear land/water boundaries needed to identify channelization in the available rasterized lidar data. The channel extraction method uses pixelized satellite photographs that are stretched/distorted with image-processing techniques to match identifiable control features in both lidar and photographic data sets. A kmeans clustering algorithm was applied cluster pixels based on their colors, which is effective in separating land and water in a satellite photograph. The clustered image was matched to the lidar data such that the combination shows the channel network. In effect, we are able to use the fact that the satellite photograph is higher resolution than the lidar data, and thus provides connectivity in the clustering at a finer scale. The principal limitation of the method is the where the satellite image and lidar suffer from similar problems For example, vegetation overhanging a narrow channel might show up as higher-elevation land in the lidar data an also as a non-water cluster color in the satellite photo.

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

Kira, M., E-mail: mackillo.kira@physik.uni-marburg.de

Atomic Bose–Einstein condensates (BECs) can be viewed as macroscopic objects where atoms form correlated atom clusters to all orders. Therefore, the presence of a BEC makes the direct use of the cluster-expansion approach–lucrative e.g. in semiconductor quantum optics–inefficient when solving the many-body kinetics of a strongly interacting Bose. An excitation picture is introduced with a nonunitary transformation that describes the system in terms of atom clusters within the normal component alone. The nontrivial properties of this transformation are systematically studied, which yields a cluster-expansion friendly formalism for a strongly interacting Bose gas. Its connections and corrections to the standard Hartree–Fock–Bogoliubov approachmore » are discussed and the role of the order parameter and the Bogoliubov excitations are identified. The resulting interaction effects are shown to visibly modify number fluctuations of the BEC. Even when the BEC has a nearly perfect second-order coherence, the BEC number fluctuations can still resolve interaction-generated non-Poissonian fluctuations. - Highlights: • Excitation picture expresses interacting Bose gas with few atom clusters. • Semiconductor and BEC many-body investigations are connected with cluster expansion. • Quantum statistics of BEC is identified in terms of atom clusters. • BEC number fluctuations show extreme sensitivity to many-body correlations. • Cluster-expansion friendly framework is established for an interacting Bose gas.« less

Characterization of micron-size hydrogen clusters using Mie scattering.

PubMed

Jinno, S; Tanaka, H; Matsui, R; Kanasaki, M; Sakaki, H; Kando, M; Kondo, K; Sugiyama, A; Uesaka, M; Kishimoto, Y; Fukuda, Y

2017-08-07

Hydrogen clusters with diameters of a few micrometer range, composed of 10 8-10 hydrogen molecules, have been produced for the first time in an expansion of supercooled, high-pressure hydrogen gas into a vacuum through a conical nozzle connected to a cryogenic pulsed solenoid valve. The size distribution of the clusters has been evaluated by measuring the angular distribution of laser light scattered from the clusters. The data were analyzed based on the Mie scattering theory combined with the Tikhonov regularization method including the instrumental functions, the validity of which was assessed by performing a calibration study using a reference target consisting of standard micro-particles with two different sizes. The size distribution of the clusters was found discrete peaked at 0.33 ± 0.03, 0.65 ± 0.05, 0.81 ± 0.06, 1.40 ± 0.06 and 2.00 ± 0.13 µm in diameter. The highly reproducible and impurity-free nature of the micron-size hydrogen clusters can be a promising target for laser-driven multi-MeV proton sources with the currently available high power lasers.

Neutron stars and millisecond pulsars from accretion-induced collapse in globular clusters

NASA Technical Reports Server (NTRS)

Bailyn, Charles D.; Grindlay, Jonathan E.

1990-01-01

This paper examines the limits on the number of millisecond pulsars which could be formed in globular clusters by the generally accepted scenario (in which a neutron star is created by the supernova of an initially massive star and subsequently captures a companion to form a low-mass X-ray binary which eventually becomes a millisecond pulsar). It is found that, while the number of observed low-mass X-ray binaries can be adequately explained in this way, the reasonable assumption that the pulsar luminosity function in clusters extends below the current observational limits down to the luminosity of the faintest millisecond pulsars in the field suggests a cluster population of millisecond pulsars which is substantially larger than the standard model can produce. Alleviating this problem by postulating much shorter lifetimes for the X-ray binaries requires massive star populations sufficiently large that the mass loss resulting from their evolution would be likely to unbind the cluster. It is argued that neutron star formation in globular clusters by accretion-induced collapse of white dwarfs may resolve the discrepancy in birthrates.

Cluster Randomized Test-Negative Design (CR-TND) Trials: A Novel and Efficient Method to Assess the Efficacy of Community Level Dengue Interventions.

PubMed

Anders, Katherine L; Cutcher, Zoe; Kleinschmidt, Immo; Donnelly, Christl A; Ferguson, Neil M; Indriani, Citra; O'Neill, Scott L; Jewell, Nicholas P; Simmons, Cameron P

2018-05-07

Cluster randomized trials are the gold standard for assessing efficacy of community-level interventions, such as vector control strategies against dengue. We describe a novel cluster randomized trial methodology with a test-negative design, which offers advantages over traditional approaches. It utilizes outcome-based sampling of patients presenting with a syndrome consistent with the disease of interest, who are subsequently classified as test-positive cases or test-negative controls on the basis of diagnostic testing. We use simulations of a cluster trial to demonstrate validity of efficacy estimates under the test-negative approach. This demonstrates that, provided study arms are balanced for both test-negative and test-positive illness at baseline and that other test-negative design assumptions are met, the efficacy estimates closely match true efficacy. We also briefly discuss analytical considerations for an odds ratio-based effect estimate arising from clustered data, and outline potential approaches to analysis. We conclude that application of the test-negative design to certain cluster randomized trials could increase their efficiency and ease of implementation.

Chemical composition of the stellar cluster Gaia1: no surprise behind Sirius

NASA Astrophysics Data System (ADS)

Mucciarelli, A.; Monaco, L.; Bonifacio, P.; Saviane, I.

2017-07-01

We observed six He-clump stars of the intermediate-age stellar cluster Gaia1 with the MIKE/Magellan spectrograph. A possible extra-galactic origin of this cluster, recently discovered thanks to the first data release of the ESA Gaia mission, has been suggested, based on its orbital parameters. Abundances for Fe, α, proton- and neutron-capture elements have been obtained. We find no evidence of intrinsic abundance spreads. The iron abundance is solar ([FeI/H] = + 0.00 ± 0.01; σ = 0.03 dex). All the other abundance ratios are generally solar-scaled, similar to the Galactic thin disk and open cluster stars of similar metallicity. The chemical composition of Gaia1 does not support an extra-galactic origin for this stellar cluster, which can be considered as a standard Galactic open cluster. The full Table A.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/603/L7

Cluster stability in the analysis of mass cytometry data.

PubMed

Melchiotti, Rossella; Gracio, Filipe; Kordasti, Shahram; Todd, Alan K; de Rinaldis, Emanuele

2017-01-01

Manual gating has been traditionally applied to cytometry data sets to identify cells based on protein expression. The advent of mass cytometry allows for a higher number of proteins to be simultaneously measured on cells, therefore providing a means to define cell clusters in a high dimensional expression space. This enhancement, whilst opening unprecedented opportunities for single cell-level analyses, makes the incremental replacement of manual gating with automated clustering a compelling need. To this aim many methods have been implemented and their successful applications demonstrated in different settings. However, the reproducibility of automatically generated clusters is proving challenging and an analytical framework to distinguish spurious clusters from more stable entities, and presumably more biologically relevant ones, is still missing. One way to estimate cell clusters' stability is the evaluation of their consistent re-occurrence within- and between-algorithms, a metric that is commonly used to evaluate results from gene expression. Herein we report the usage and importance of cluster stability evaluations, when applied to results generated from three popular clustering algorithms - SPADE, FLOCK and PhenoGraph - run on four different data sets. These algorithms were shown to generate clusters with various degrees of statistical stability, many of them being unstable. By comparing the results of automated clustering with manually gated populations, we illustrate how information on cluster stability can assist towards a more rigorous and informed interpretation of clustering results. We also explore the relationships between statistical stability and other properties such as clusters' compactness and isolation, demonstrating that whilst cluster stability is linked to other properties it cannot be reliably predicted by any of them. Our study proposes the introduction of cluster stability as a necessary checkpoint for cluster interpretation and contributes to the construction of a more systematic and standardized analytical framework for the assessment of cytometry clustering results. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Targeting Clusters, Achieving Excellence.

ERIC Educational Resources Information Center

Rosenfeld, Stuart; Jacobs, Jim; Liston, Cynthia

2003-01-01

Suggests that groups, or clusters, of industries form partnerships with community colleges in order to positively impact economic development. Asserts that a cluster-oriented community college system requires innovation, specialized resources and expertise, knowledge of trends, and links to industry. Offers suggestions for developing such a…

Interlaced coarse-graining for the dynamical cluster approximation

NASA Astrophysics Data System (ADS)

Haehner, Urs; Staar, Peter; Jiang, Mi; Maier, Thomas; Schulthess, Thomas

The negative sign problem remains a challenging limiting factor in quantum Monte Carlo simulations of strongly correlated fermionic many-body systems. The dynamical cluster approximation (DCA) makes this problem less severe by coarse-graining the momentum space to map the bulk lattice to a cluster embedded in a dynamical mean-field host. Here, we introduce a new form of an interlaced coarse-graining and compare it with the traditional coarse-graining. We show that it leads to more controlled results with weaker cluster shape and smoother cluster size dependence, which with increasing cluster size converge to the results obtained using the standard coarse-graining. In addition, the new coarse-graining reduces the severity of the fermionic sign problem. Therefore, it enables calculations on much larger clusters and can allow the evaluation of the exact infinite cluster size result via finite size scaling. To demonstrate this, we study the hole-doped two-dimensional Hubbard model and show that the interlaced coarse-graining in combination with the DCA+ algorithm permits the determination of the superconducting Tc on cluster sizes, for which the results can be fitted with the Kosterlitz-Thouless scaling law. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) awarded by the INCITE program, and of the Swiss National Supercomputing Center. OLCF is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

End of Course Grades and Standardized Test Scores: Are Grades Predictive of Student Achievement?

ERIC Educational Resources Information Center

Ricketts, Christine R.

2010-01-01

This study examined the extent to which end-of-course grades are predictive of Virginia Standards of Learning test scores in nine high school content areas. It also analyzed the impact of the variables school cluster attended, gender, ethnicity, disability status, Limited English Proficiency status, and socioeconomic status on the relationship…

Transitioning to the Common Core State Standards for Mathematics: A Mixed Methods Study of Elementary Teachers' Experiences and Perspectives

ERIC Educational Resources Information Center

Swars, Susan Lee; Chestnutt, Cliff

2016-01-01

This mixed methods study explored elementary teachers' (n = 73) experiences with and perspectives on the recently implemented Common Core State Standards for Mathematics (CCSS-Mathematics) at a high-needs, urban school. Analysis of the survey, questionnaire, and interview data reveals the findings cluster around: familiarity with and preparation…

A transversal approach to predict gene product networks from ontology-based similarity

PubMed Central

Chabalier, Julie; Mosser, Jean; Burgun, Anita

2007-01-01

Background Interpretation of transcriptomic data is usually made through a "standard" approach which consists in clustering the genes according to their expression patterns and exploiting Gene Ontology (GO) annotations within each expression cluster. This approach makes it difficult to underline functional relationships between gene products that belong to different expression clusters. To address this issue, we propose a transversal analysis that aims to predict functional networks based on a combination of GO processes and data expression. Results The transversal approach presented in this paper consists in computing the semantic similarity between gene products in a Vector Space Model. Through a weighting scheme over the annotations, we take into account the representativity of the terms that annotate a gene product. Comparing annotation vectors results in a matrix of gene product similarities. Combined with expression data, the matrix is displayed as a set of functional gene networks. The transversal approach was applied to 186 genes related to the enterocyte differentiation stages. This approach resulted in 18 functional networks proved to be biologically relevant. These results were compared with those obtained through a standard approach and with an approach based on information content similarity. Conclusion Complementary to the standard approach, the transversal approach offers new insight into the cellular mechanisms and reveals new research hypotheses by combining gene product networks based on semantic similarity, and data expression. PMID:17605807