WorldWideScience

Sample records for hiflugcs cluster sample

  1. Galaxy clusters from eeHIFLUGCS, to eROSITA, to Athena

    Science.gov (United States)

    Reiprich, T.

    2017-10-01

    The latest results from detailed X-ray follow-up observations of large X-ray selected galaxy cluster samples are discussed, in particular from eeHIFLUGCS. An outlook is given to expected cosmological constraints from eROSITA, in particular on dark energy and neutrino masses. The possible significant role of XMM-Newton to improve on these constraints is highlighted. Finally, the expectations for Athena to discover and characterize the first galaxy groups, massive and evolved enough to contain ≫10 million Kelvin gas, around redshift 2.5 are quantified.

  2. HICOSMO: cosmology with a complete sample of galaxy clusters - II. Cosmological results

    Science.gov (United States)

    Schellenberger, G.; Reiprich, T. H.

    2017-10-01

    The X-ray bright, hot gas in the potential well of a galaxy cluster enables systematic X-ray studies of samples of galaxy clusters to constrain cosmological parameters. HIFLUGCS consists of the 64 X-ray brightest galaxy clusters in the Universe, building up a local sample. Here, we utilize this sample to determine, for the first time, individual hydrostatic mass estimates for all the clusters of the sample and, by making use of the completeness of the sample, we quantify constraints on the two interesting cosmological parameters, Ωm and σ8. We apply our total hydrostatic and gas mass estimates from the X-ray analysis to a Bayesian cosmological likelihood analysis and leave several parameters free to be constrained. We find Ωm = 0.30 ± 0.01 and σ8 = 0.79 ± 0.03 (statistical uncertainties, 68 per cent credibility level) using our default analysis strategy combining both a mass function analysis and the gas mass fraction results. The main sources of biases that we correct here are (1) the influence of galaxy groups (incompleteness in parent samples and differing behaviour of the Lx-M relation), (2) the hydrostatic mass bias, (3) the extrapolation of the total mass (comparing various methods), (4) the theoretical halo mass function and (5) other physical effects (non-negligible neutrino mass). We find that galaxy groups introduce a strong bias, since their number density seems to be over predicted by the halo mass function. On the other hand, incorporating baryonic effects does not result in a significant change in the constraints. The total (uncorrected) systematic uncertainties (∼20 per cent) clearly dominate the statistical uncertainties on cosmological parameters for our sample.

  3. A parallel sampling based clustering

    OpenAIRE

    Sastry, Aditya AV; Netti, Kalyan

    2014-01-01

    The problem of automatically clustering data is an age old problem. People have created numerous algorithms to tackle this problem. The execution time of any of this algorithm grows with the number of input points and the number of cluster centers required. To reduce the number of input points we could average the points locally and use the means or the local centers as the input for clustering. However since the required number of local centers is very high, running the clustering algorithm ...

  4. The XXL survey XV: evidence for dry merger driven BCG growth in XXL-100-GC X-ray clusters

    Science.gov (United States)

    Lavoie, S.; Willis, J. P.; Démoclès, J.; Eckert, D.; Gastaldello, F.; Smith, G. P.; Lidman, C.; Adami, C.; Pacaud, F.; Pierre, M.; Clerc, N.; Giles, P.; Lieu, M.; Chiappetti, L.; Altieri, B.; Ardila, F.; Baldry, I.; Bongiorno, A.; Desai, S.; Elyiv, A.; Faccioli, L.; Gardner, B.; Garilli, B.; Groote, M. W.; Guennou, L.; Guzzo, L.; Hopkins, A. M.; Liske, J.; McGee, S.; Melnyk, O.; Owers, M. S.; Poggianti, B.; Ponman, T. J.; Scodeggio, M.; Spitler, L.; Tuffs, R. J.

    2016-11-01

    The growth of brightest cluster galaxies (BCGs) is closely related to the properties of their host cluster. We present evidence for dry mergers as the dominant source of BCG mass growth at z ≲ 1 in the XXL 100 brightest cluster sample. We use the global red sequence, Hα emission and mean star formation history to show that BCGs in the sample possess star formation levels comparable to field ellipticals of similar stellar mass and redshift. XXL 100 brightest clusters are less massive on average than those in other X-ray selected samples such as LoCuSS or HIFLUGCS. Few clusters in the sample display high central gas concentration, rendering inefficient the growth of BCGs via star formation resulting from the accretion of cool gas. Using measures of the relaxation state of their host clusters, we show that BCGs grow as relaxation proceeds. We find that the BCG stellar mass corresponds to a relatively constant fraction 1 per cent of the total cluster mass in relaxed systems. We also show that, following a cluster scale merger event, the BCG stellar mass lags behind the expected value from the Mcluster-MBCG relation but subsequently accretes stellar mass via dry mergers as the BCG and cluster evolve towards a relaxed state.

  5. The design effect and cluster samples: optimising tuberculosis prevalence surveys

    NARCIS (Netherlands)

    Williams, B.; Gopi, P. G.; Borgdorff, M. W.; Yamada, N.; Dye, C.

    2008-01-01

    Cross-sectional surveys of disease prevalence, including for tuberculosis (TB), often use a two (or more) stage sampling procedure. By choosing clusters of people randomly from all possible clusters, the logistic costs of doing the survey can be reduced. However, this increases the statistical

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

    Science.gov (United States)

    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.

  7. Methods for sample size determination in cluster randomized trials.

    Science.gov (United States)

    Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

    2015-06-01

    The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster. The assumptions of a simple design effect may not always be met; alternative or more complicated approaches are required. We summarise a wide range of sample size methods available for cluster randomized trials. For those familiar with sample size calculations for individually randomized trials but with less experience in the clustered case, this manuscript provides formulae for a wide range of scenarios with associated explanation and recommendations. For those with more experience, comprehensive summaries are provided that allow quick identification of methods for a given design, outcome and analysis method. We present first those methods applicable to the simplest two-arm, parallel group, completely randomized design followed by methods that incorporate deviations from this design such as: variability in cluster sizes; attrition; non-compliance; or the inclusion of baseline covariates or repeated measures. The paper concludes with methods for alternative designs. There is a large amount of methodology available for sample size calculations in CRTs. This paper gives the most comprehensive description of published methodology for sample size calculation and provides an important resource for those designing these trials. © The Author 2015. Published by Oxford University Press on behalf of the International Epidemiological Association.

  8. Extending cluster lot quality assurance sampling designs for surveillance programs.

    Science.gov (United States)

    Hund, Lauren; Pagano, Marcello

    2014-07-20

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

  9. Cosmology and astrophysics from relaxed galaxy clusters - I. Sample selection

    Science.gov (United States)

    Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn; Schmidt, Robert W.; von der Linden, Anja; Urban, Ondrej

    2015-05-01

    This is the first in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Here we present a new, automated method for identifying relaxed clusters based on their morphologies in X-ray imaging data. While broadly similar to others in the literature, the morphological quantities that we measure are specifically designed to provide a fair basis for comparison across a range of data quality and cluster redshifts, to be robust against missing data due to point source masks and gaps between detectors, and to avoid strong assumptions about the cosmological background and cluster masses. Based on three morphological indicators - symmetry, peakiness, and alignment - we develop the symmetry-peakiness-alignment (SPA) criterion for relaxation. This analysis was applied to a large sample of cluster observations from the Chandra and ROSAT archives. Of the 361 clusters which received the SPA treatment, 57 (16 per cent) were subsequently found to be relaxed according to our criterion. We compare our measurements to similar estimators in the literature, as well as projected ellipticity and other image measures, and comment on trends in the relaxed cluster fraction with redshift, temperature, and survey selection method. Code implementing our morphological analysis will be made available on the web (http://www.slac.stanford.edu/amantz/work/morph14/).

  10. The ATLASGAL survey: The sample of young massive cluster progenitors

    Science.gov (United States)

    Csengeri, T.; Bontemps, S.; Wyrowski, F.; Megeath, S. T.; Motte, F.; Sanna, A.; Wienen, M.; Menten, K. M.

    2017-05-01

    Context. The progenitors of high-mass stars and clusters are still challenging to recognise. Only unbiased surveys, sensitive to compact regions of high dust column density, can unambiguously reveal such a small population of particularly massive and cold clumps. Aims: Here we use the ATLASGAL survey to identify a sample of candidate progenitors of massive clusters in the inner Galaxy. Methods: We characterise a flux limited sample of compact sources selected from the ATLASGAL survey. Sensitive mid-infrared data at 21-24μm from the WISE and MIPSGAL surveys were explored to search for embedded objects, and complementary spectroscopic data were used to investigate their stability and their star formation activity. Results: We identify an unbiased sample of infrared-quiet massive clumps in the Galaxy that potentially represent the earliest stages of massive cluster formation. An important fraction of this sample consists of sources that have not been studied in detail before. We first find that clumps hosting more evolved embedded objects and infrared-quiet clumps exhibit similar physical properties in terms of mass and size, suggesting that the sources are not only capable of forming high-mass stars, but likely also follow a single evolutionary track leading to the formation of massive clusters. The majority of the clumps are likely not in virial-equilibrium, suggesting collapse on the clump scale. Conclusions: We identify the precursors of the most massive clusters in the Galaxy within our completeness limit, and argue that these objects are undergoing large-scale collapse. This is in line with the low number of infrared-quiet massive clumps and earlier findings that star formation, in particular for high-mass objects is a fast, dynamic process. We propose a scenario in which massive clumps start to fragment and collapse before their final mass is accumulated indicating that strong self-gravity and global collapse is needed to build up rich clusters and the most

  11. Calculating sample sizes for cluster randomized trials: we can keep it simple and efficient !

    NARCIS (Netherlands)

    van Breukelen, Gerard J.P.; Candel, Math J.J.M.

    2012-01-01

    Objective: Simple guidelines for efficient sample sizes in cluster randomized trials with unknown intraclass correlation and varying cluster sizes. Methods: A simple equation is given for the optimal number of clusters and sample size per cluster. Here, optimal means maximizing power for a given

  12. Merging and Clustering of the Swift BAT AGN Sample

    Science.gov (United States)

    Koss, Michael; Mushotzky, Richard; Veilleux, Sylvain; Winter, Lisa

    2010-06-01

    We discuss the merger rate, close galaxy environment, and clustering on scales up to an Mpc of the Swift BAT hard X-ray sample of nearby (zincidence of galaxies with signs of disruption compared to a matched control sample (18% versus 1%) and of close pairs within 30 kpc (24% versus 1%). We also find a larger fraction with companions compared to normal galaxies and optical emission line selected AGNs at scales up to 250 kpc. We hypothesize that these merging AGNs may not be identified using optical emission line diagnostics because of optical extinction and dilution by star formation. In support of this hypothesis, in merging systems we find a higher hard X-ray to [O III] flux ratio, as well as emission line diagnostics characteristic of composite or star-forming galaxies, and a larger IRAS 60 μm to stellar mass ratio.

  13. [Selection of sentinel sites for death surveillance, using cluster or unequal probability sampling].

    Science.gov (United States)

    Lian, Heng-li; Xu, Yong-yong; Guo, Ling-xia; Tan, Zhi-jun; Liu, Dan-hong; Rao, Ke-qin

    2010-04-01

    To compare the sampling errors from cluster or unequal probability sampling designs and to adopt the unequal probability sampling method to be used for death surveillance. Taking 107 areas from the county level in Shaanxi province as the sampling frame, a set of samples are drawn by equal probability cluster sampling and unequal probability designs methodologies. Sampling error and effect of each design are estimated according to their complex sample plans. Both the sampling errors depend on the sampling plan and the errors of equal probability in stratified cluster sampling appears to be less than simple cluster sampling. The design effects of unequal probability stratified cluster sampling, such as piPS design, are slightly lower than those of equal probability stratified cluster sampling, but the unequal probability stratified cluster sampling can cover a wider scope of monitoring population. Results from the analysis of sampling data can not be conducted without consideration of the sampling plan when the sampling frame is finite and a given sampling plan and parameters, such as sampling proportion and population weights, are assigned in advance. Unequal probability cluster sampling designs seems to be more appropriate in selecting the national death surveillance sites since more available monitoring data can be obtained and having more weight in estimating the mortality for the whole province or the municipality to be selected.

  14. Stratified sampling using cluster analysis: a sample selection strategy for improved generalizations from experiments.

    Science.gov (United States)

    Tipton, Elizabeth

    2013-04-01

    An important question in the design of experiments is how to ensure that the findings from the experiment are generalizable to a larger population. This concern with generalizability is particularly important when treatment effects are heterogeneous and when selecting units into the experiment using random sampling is not possible-two conditions commonly met in large-scale educational experiments. This article introduces a model-based balanced-sampling framework for improving generalizations, with a focus on developing methods that are robust to model misspecification. Additionally, the article provides a new method for sample selection within this framework: First units in an inference population are divided into relatively homogenous strata using cluster analysis, and then the sample is selected using distance rankings. In order to demonstrate and evaluate the method, a reanalysis of a completed experiment is conducted. This example compares samples selected using the new method with the actual sample used in the experiment. Results indicate that even under high nonresponse, balance is better on most covariates and that fewer coverage errors result. The article concludes with a discussion of additional benefits and limitations of the method.

  15. Tigers on trails: occupancy modeling for cluster sampling.

    Science.gov (United States)

    Hines, J E; Nichols, J D; Royle, J A; MacKenzie, D I; Gopalaswamy, A M; Kumar, N Samba; Karanth, K U

    2010-07-01

    estimation in conservation monitoring. More generally, this work represents a contribution to the topic of cluster sampling for situations in which there is a need for specific modeling (e.g., reflecting dependence) for the distribution of the variable(s) of interest among subunits.

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

    Science.gov (United States)

    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.

  17. Sample size calculations for 3-level cluster randomized trials

    NARCIS (Netherlands)

    Teerenstra, S.; Moerbeek, M.; Achterberg, T. van; Pelzer, B.J.; Borm, G.F.

    2008-01-01

    BACKGROUND: The first applications of cluster randomized trials with three instead of two levels are beginning to appear in health research, for instance, in trials where different strategies to implement best-practice guidelines are compared. In such trials, the strategy is implemented in health

  18. Sample size calculations for 3-level cluster randomized trials

    NARCIS (Netherlands)

    Teerenstra, S.; Moerbeek, M.; Achterberg, T. van; Pelzer, B.J.; Borm, G.F.

    2008-01-01

    Background The first applications of cluster randomized trials with three instead of two levels are beginning to appear in health research, for instance, in trials where different strategies to implement best-practice guidelines are compared. In such trials, the strategy is implemented in health

  19. Variation in rank abundance replicate samples and impact of clustering

    NARCIS (Netherlands)

    Neuteboom, J.H.; Struik, P.C.

    2005-01-01

    Calculating a single-sample rank abundance curve by using the negative-binomial distribution provides a way to investigate the variability within rank abundance replicate samples and yields a measure of the degree of heterogeneity of the sampled community. The calculation of the single-sample rank

  20. XMM-Newton/Sloan Digital Sky Survey: Star Formation Efficiency in Galaxy Clusters and Constraints on the Matter-density Parameter

    Science.gov (United States)

    Laganá, Tatiana F.; Zhang, Yu-Ying; Reiprich, Thomas H.; Schneider, Peter

    2011-12-01

    It is believed that the global baryon content of clusters of galaxies is representative of the matter distribution of the universe, and can, therefore, be used to reliably determine the matter-density parameter Ωm. This assumption is challenged by the growing evidence from optical and X-ray observations that the total baryon mass fraction increases toward rich clusters. In this context, we investigate the dependence of stellar and total baryon mass fractions as a function of mass. To do so, we used a subsample of 19 clusters extracted from the X-ray flux-limited sample HIFLUGCS that have available Sloan Digital Sky Survey Data Release 7 data. From the optical analysis we derived the stellar masses. Using XMM-Newton we derived the gas masses. Then, adopting a scaling relation we estimate the total masses. Adding the gas and the stellar mass fractions we obtain the total baryonic content that we find to increase with cluster mass, reaching seven-year Wilkinson Microwave Anisotropy Probe (WMAP7) prediction for clusters with M 500 = 1.6 × 1015 M ⊙. We observe a decrease of the stellar mass fraction (from 4.5% to ~1.0%) with increasing total mass where our findings for the stellar mass fraction agree with previous studies. This result suggests a difference in the number of stars formed per unit of halo mass, though with a large scatter for low-mass systems. That is, the efficiency of star formation varies on a cluster scale that lower mass systems are likely to have higher star formation efficiencies. It follows immediately that the dependence of the stellar mass fraction on total mass results in an increase of the mass-to-light ratio from lower to higher mass systems. We also discuss the consequences of these results in the context of determining the cosmic matter-density parameter Ωm.

  1. XMM-NEWTON/SLOAN DIGITAL SKY SURVEY: STAR FORMATION EFFICIENCY IN GALAXY CLUSTERS AND CONSTRAINTS ON THE MATTER-DENSITY PARAMETER

    Energy Technology Data Exchange (ETDEWEB)

    Lagana, Tatiana F. [Universidade de Sao Paulo, Instituto de Astronomia, Geofisica e Ciencias Atmosfericas, Departamento de Astronomia, Cidade Universitaria, CEP:05508-090, Sao Paulo, SP (Brazil); Zhang Yuying; Reiprich, Thomas H.; Schneider, Peter [Argelander-Institut fuer Astronomie, Universitaet Bonn, 53121 Bonn (Germany)

    2011-12-10

    It is believed that the global baryon content of clusters of galaxies is representative of the matter distribution of the universe, and can, therefore, be used to reliably determine the matter-density parameter {Omega}{sub m}. This assumption is challenged by the growing evidence from optical and X-ray observations that the total baryon mass fraction increases toward rich clusters. In this context, we investigate the dependence of stellar and total baryon mass fractions as a function of mass. To do so, we used a subsample of 19 clusters extracted from the X-ray flux-limited sample HIFLUGCS that have available Sloan Digital Sky Survey Data Release 7 data. From the optical analysis we derived the stellar masses. Using XMM-Newton we derived the gas masses. Then, adopting a scaling relation we estimate the total masses. Adding the gas and the stellar mass fractions we obtain the total baryonic content that we find to increase with cluster mass, reaching seven-year Wilkinson Microwave Anisotropy Probe (WMAP7) prediction for clusters with M{sub 500} = 1.6 Multiplication-Sign 10{sup 15} M{sub Sun }. We observe a decrease of the stellar mass fraction (from 4.5% to {approx}1.0%) with increasing total mass where our findings for the stellar mass fraction agree with previous studies. This result suggests a difference in the number of stars formed per unit of halo mass, though with a large scatter for low-mass systems. That is, the efficiency of star formation varies on a cluster scale that lower mass systems are likely to have higher star formation efficiencies. It follows immediately that the dependence of the stellar mass fraction on total mass results in an increase of the mass-to-light ratio from lower to higher mass systems. We also discuss the consequences of these results in the context of determining the cosmic matter-density parameter {Omega}{sub m}.

  2. Occurrence of Radio Minihalos in a Mass-limited Sample of Galaxy Clusters

    Science.gov (United States)

    Giacintucci, Simona; Markevitch, Maxim; Cassano, Rossella; Venturi, Tiziana; Clarke, Tracy E.; Brunetti, Gianfranco

    2017-06-01

    We investigate the occurrence of radio minihalos—diffuse radio sources of unknown origin observed in the cores of some galaxy clusters—in a statistical sample of 58 clusters drawn from the Planck Sunyaev-Zel’dovich cluster catalog using a mass cut (M 500 > 6 × 1014 M ⊙). We supplement our statistical sample with a similarly sized nonstatistical sample mostly consisting of clusters in the ACCEPT X-ray catalog with suitable X-ray and radio data, which includes lower-mass clusters. Where necessary (for nine clusters), we reanalyzed the Very Large Array archival radio data to determine whether a minihalo is present. Our total sample includes all 28 currently known and recently discovered radio minihalos, including six candidates. We classify clusters as cool-core or non-cool-core according to the value of the specific entropy floor in the cluster center, rederived or newly derived from the Chandra X-ray density and temperature profiles where necessary (for 27 clusters). Contrary to the common wisdom that minihalos are rare, we find that almost all cool cores—at least 12 out of 15 (80%)—in our complete sample of massive clusters exhibit minihalos. The supplementary sample shows that the occurrence of minihalos may be lower in lower-mass cool-core clusters. No minihalos are found in non-cool cores or “warm cores.” These findings will help test theories of the origin of minihalos and provide information on the physical processes and energetics of the cluster cores.

  3. Adaptive cluster sampling: An efficient method for assessing inconspicuous species

    Science.gov (United States)

    Andrea M. Silletti; Joan Walker

    2003-01-01

    Restorationistis typically evaluate the success of a project by estimating the population sizes of species that have been planted or seeded. Because total census is raely feasible, they must rely on sampling methods for population estimates. However, traditional random sampling designs may be inefficient for species that, for one reason or another, are challenging to...

  4. Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

    2016-01-01

    Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

  5. Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

    2015-10-01

    Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

  6. The Hubble Space Telescope Medium Deep Survey Cluster Sample: Methodology and Data

    Science.gov (United States)

    Ostrander, E. J.; Nichol, R. C.; Ratnatunga, K. U.; Griffiths, R. E.

    1998-12-01

    We present a new, objectively selected, sample of galaxy overdensities detected in the Hubble Space Telescope Medium Deep Survey (MDS). These clusters/groups were found using an automated procedure that involved searching for statistically significant galaxy overdensities. The contrast of the clusters against the field galaxy population is increased when morphological data are used to search around bulge-dominated galaxies. In total, we present 92 overdensities above a probability threshold of 99.5%. We show, via extensive Monte Carlo simulations, that at least 60% of these overdensities are likely to be real clusters and groups and not random line-of-sight superpositions of galaxies. For each overdensity in the MDS cluster sample, we provide a richness and the average of the bulge-to-total ratio of galaxies within each system. This MDS cluster sample potentially contains some of the most distant clusters/groups ever detected, with about 25% of the overdensities having estimated redshifts z > ~0.9. We have made this sample publicly available to facilitate spectroscopic confirmation of these clusters and help more detailed studies of cluster and galaxy evolution. We also report the serendipitous discovery of a new cluster close on the sky to the rich optical cluster Cl l0016+16 at z = 0.546. This new overdensity, HST 001831+16208, may be coincident with both an X-ray source and a radio source. HST 001831+16208 is the third cluster/group discovered near to Cl 0016+16 and appears to strengthen the claims of Connolly et al. of superclustering at high redshift.

  7. Interval estimation of the mass fractal dimension for anisotropic sampling percolation clusters

    OpenAIRE

    Moskalev, P. V.; Grebennikov, K. V.; Shitov, V. V.

    2011-01-01

    This report focuses on the dependencies for the center and radius of the confidence interval that arise when estimating the mass fractal dimensions of anisotropic sampling clusters in the site percolation model.

  8. Interval estimation of the mass fractal dimension for isotropic sampling percolation clusters

    OpenAIRE

    Moskalev, P. V.; Grebennikov, K. V.; Shitov, V. V.

    2011-01-01

    This report focuses on the dependencies for the center and radius of the confidence interval that arise when estimating the mass fractal dimensions of isotropic sampling clusters in the site percolation model.

  9. Cored Cottonwood Tree Sample Cluster Polygons at Sand Creek Massacre National Historic Site, Colorado

    Data.gov (United States)

    National Park Service, Department of the Interior — A vector polygon dataset representing the location of sample clusters of cored trees at Sand Creek Massacre NHS as part of a University of Colorado research study.

  10. Disturbed galaxy clusters are more abundant in an X-ray volume-limited sample

    Science.gov (United States)

    Chon, Gayoung; Böhringer, Hans

    2017-10-01

    X-ray observations of clusters of galaxies have been used to study the large-scale structure of our Universe and to test cosmological models. In such studies it is critical to understand the unique survey selection function correctly. In comparison to the cluster detection by the Sunyaev-Zel'dovich effect (SZE), it has been shown that X-ray observations preferentially detect clusters that have cool cores or are more relaxed as opposed to more disturbed or non-cool-core clusters found in SZE surveys. In this Letter we show that it is not the means of detection, X-rays or SZE, but the sampling strategy, flux-limited or volume-limited surveying, that makes the difference. XMM-Newton observations of the REFLEX clusters in our Volume-Limited Sample (ReVols) show that the fraction of disturbed clusters, determined by the third moment of the power ratios and by centre shifts, is larger by about a factor of two than that of relaxed clusters. In contrast, two flux-limited cluster samples that can be constructed out of ReVols contain more comparable fractions of disturbed and relaxed clusters, which differ by only ten per cent. We use the ratio of the luminosity measured within r500 to that measured in the same aperture without the core region as an indicator for a cool core and find that the number of non-cool-core clusters is comparable to or larger than that of the cool-core clusters in ReVols. In addition, we show that the X-ray luminosity distributions of the disturbed and relaxed clusters are distinctly different, and on average, a displacement of 60% in luminosity is required to match two distributions. Therefore the larger fraction of relaxed and cool-core clusters reported in previous X-ray surveys does not result from the X-ray detection per se, but from the fact that these samples were constructed from flux-limited surveys. Our findings also suggest that the Malmquist bias correction used in cosmological studies with X-ray galaxy clusters could be improved by

  11. Hot Zone Identification: Analyzing Effects of Data Sampling on Spam Clustering

    Directory of Open Access Journals (Sweden)

    Rasib Khan

    2014-03-01

    Full Text Available Email is the most common and comparatively the most efficient means of exchanging information in today's world. However, given the widespread use of emails in all sectors, they have been the target of spammers since the beginning. Filtering spam emails has now led to critical actions such as forensic activities based on mining spam email. The data mine for spam emails at the University of Alabama at Birmingham is considered to be one of the most prominent resources for mining and identifying spam sources. It is a widely researched repository used by researchers from different global organizations. The usual process of mining the spam data involves going through every email in the data mine and clustering them based on their different attributes. However, given the size of the data mine, it takes an exceptionally long time to execute the clustering mechanism each time. In this paper, we have illustrated sampling as an efficient tool for data reduction, while preserving the information within the clusters, which would thus allow the spam forensic experts to quickly and effectively identify the ‘hot zone’ from the spam campaigns. We have provided detailed comparative analysis of the quality of the clusters after sampling, the overall distribution of clusters on the spam data, and timing measurements for our sampling approach. Additionally, we present different strategies which allowed us to optimize the sampling process using data-preprocessing and using the database engine's computational resources, and thus improving the performance of the clustering process.

  12. Planck early results. VIII. The all-sky early Sunyaev-Zeldovich cluster sample

    DEFF Research Database (Denmark)

    Poutanen, T.; Natoli, P.; Polenta, G.

    2011-01-01

    We present the first all-sky sample of galaxy clusters detected blindly by the Planck satellite through the Sunyaev-Zeldovich (SZ) effect from its six highest frequencies. This early SZ (ESZ) sample is comprised of 189 candidates, which have a high signal-to-noise ratio ranging from 6 to 29. Its ...

  13. Parameter Estimation in Stratified Cluster Sampling under Randomized Response Models for Sensitive Question Survey.

    Science.gov (United States)

    Pu, Xiangke; Gao, Ge; Fan, Yubo; Wang, Mian

    2016-01-01

    Randomized response is a research method to get accurate answers to sensitive questions in structured sample survey. Simple random sampling is widely used in surveys of sensitive questions but hard to apply on large targeted populations. On the other side, more sophisticated sampling regimes and corresponding formulas are seldom employed to sensitive question surveys. In this work, we developed a series of formulas for parameter estimation in cluster sampling and stratified cluster sampling under two kinds of randomized response models by using classic sampling theories and total probability formulas. The performances of the sampling methods and formulas in the survey of premarital sex and cheating on exams at Soochow University were also provided. The reliability of the survey methods and formulas for sensitive question survey was found to be high.

  14. Parameter Estimation in Stratified Cluster Sampling under Randomized Response Models for Sensitive Question Survey.

    Directory of Open Access Journals (Sweden)

    Xiangke Pu

    Full Text Available Randomized response is a research method to get accurate answers to sensitive questions in structured sample survey. Simple random sampling is widely used in surveys of sensitive questions but hard to apply on large targeted populations. On the other side, more sophisticated sampling regimes and corresponding formulas are seldom employed to sensitive question surveys. In this work, we developed a series of formulas for parameter estimation in cluster sampling and stratified cluster sampling under two kinds of randomized response models by using classic sampling theories and total probability formulas. The performances of the sampling methods and formulas in the survey of premarital sex and cheating on exams at Soochow University were also provided. The reliability of the survey methods and formulas for sensitive question survey was found to be high.

  15. Spatially explicit population estimates for black bears based on cluster sampling

    Science.gov (United States)

    Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

    2017-01-01

    We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

  16. Cluster analysis in kinetic modelling of the brain: A noninvasive alternative to arterial sampling

    DEFF Research Database (Denmark)

    Liptrot, Matthew George; Adams, K.H.; Martiny, L.

    2004-01-01

    In emission tomography, quantification of brain tracer uptake, metabolism or binding requires knowledge of the cerebral input function. Traditionally, this is achieved with arterial blood sampling. We propose a noninvasive alternative via the use of a blood vessel time-activity curve (TAC......) extracted directly from dynamic positron emission tomography (PET) scans by cluster analysis. Five healthy subjects were injected with the 5HT2A- receptor ligand [18F]-altanserin and blood samples were subsequently taken from the radial artery and cubital vein. Eight regions-of-interest (ROI) TACs were...... by the 'within-variance' measure and by 3D visual inspection of the homogeneity of the determined clusters. The cluster-determined input curve was then used in Logan plot analysis and compared with the arterial and venous blood samples, and additionally with one of the currently used alternatives to arterial...

  17. Posttraumatic Stress Disorder Symptom Clusters and the Interpersonal Theory of Suicide in a Large Military Sample.

    Science.gov (United States)

    Pennings, Stephanie M; Finn, Joseph; Houtsma, Claire; Green, Bradley A; Anestis, Michael D

    2017-10-01

    Prior studies examining posttraumatic stress disorder (PTSD) symptom clusters and the components of the interpersonal theory of suicide (ITS) have yielded mixed results, likely stemming in part from the use of divergent samples and measurement techniques. This study aimed to expand on these findings by utilizing a large military sample, gold standard ITS measures, and multiple PTSD factor structures. Utilizing a sample of 935 military personnel, hierarchical multiple regression analyses were used to test the association between PTSD symptom clusters and the ITS variables. Additionally, we tested for indirect effects of PTSD symptom clusters on suicidal ideation through thwarted belongingness, conditional on levels of perceived burdensomeness. Results indicated that numbing symptoms are positively associated with both perceived burdensomeness and thwarted belongingness and hyperarousal symptoms (dysphoric arousal in the 5-factor model) are positively associated with thwarted belongingness. Results also indicated that hyperarousal symptoms (anxious arousal in the 5-factor model) were positively associated with fearlessness about death. The positive association between PTSD symptom clusters and suicidal ideation was inconsistent and modest, with mixed support for the ITS model. Overall, these results provide further clarity regarding the association between specific PTSD symptom clusters and suicide risk factors. © 2016 The American Association of Suicidology.

  18. Precision of systematic and random sampling in clustered populations: habitat patches and aggregating organisms.

    Science.gov (United States)

    McGarvey, Richard; Burch, Paul; Matthews, Janet M

    2016-01-01

    Natural populations of plants and animals spatially cluster because (1) suitable habitat is patchy, and (2) within suitable habitat, individuals aggregate further into clusters of higher density. We compare the precision of random and systematic field sampling survey designs under these two processes of species clustering. Second, we evaluate the performance of 13 estimators for the variance of the sample mean from a systematic survey. Replicated simulated surveys, as counts from 100 transects, allocated either randomly or systematically within the study region, were used to estimate population density in six spatial point populations including habitat patches and Matérn circular clustered aggregations of organisms, together and in combination. The standard one-start aligned systematic survey design, a uniform 10 x 10 grid of transects, was much more precise. Variances of the 10 000 replicated systematic survey mean densities were one-third to one-fifth of those from randomly allocated transects, implying transect sample sizes giving equivalent precision by random survey would need to be three to five times larger. Organisms being restricted to patches of habitat was alone sufficient to yield this precision advantage for the systematic design. But this improved precision for systematic sampling in clustered populations is underestimated by standard variance estimators used to compute confidence intervals. True variance for the survey sample mean was computed from the variance of 10 000 simulated survey mean estimates. Testing 10 published and three newly proposed variance estimators, the two variance estimators (v) that corrected for inter-transect correlation (ν₈ and ν(W)) were the most accurate and also the most precise in clustered populations. These greatly outperformed the two "post-stratification" variance estimators (ν₂ and ν₃) that are now more commonly applied in systematic surveys. Similar variance estimator performance rankings were found with

  19. A framework for space-efficient read clustering in metagenomic samples.

    Science.gov (United States)

    Alanko, Jarno; Cunial, Fabio; Belazzougui, Djamal; Mäkinen, Veli

    2017-03-14

    A metagenomic sample is a set of DNA fragments, randomly extracted from multiple cells in an environment, belonging to distinct, often unknown species. Unsupervised metagenomic clustering aims at partitioning a metagenomic sample into sets that approximate taxonomic units, without using reference genomes. Since samples are large and steadily growing, space-efficient clustering algorithms are strongly needed. We design and implement a space-efficient algorithmic framework that solves a number of core primitives in unsupervised metagenomic clustering using just the bidirectional Burrows-Wheeler index and a union-find data structure on the set of reads. When run on a sample of total length n, with m reads of maximum length ℓ each, on an alphabet of total size σ, our algorithms take O(n(t+logσ)) time and just 2n+o(n)+O(max{ℓ σlogn,K logm}) bits of space in addition to the index and to the union-find data structure, where K is a measure of the redundancy of the sample and t is the query time of the union-find data structure. Our experimental results show that our algorithms are practical, they can exploit multiple cores by a parallel traversal of the suffix-link tree, and they are competitive both in space and in time with the state of the art.

  20. Clustered lot quality assurance sampling: a pragmatic tool for timely assessment of vaccination coverage.

    Science.gov (United States)

    Greenland, K; Rondy, M; Chevez, A; Sadozai, N; Gasasira, A; Abanida, E A; Pate, M A; Ronveaux, O; Okayasu, H; Pedalino, B; Pezzoli, L

    2011-07-01

    To evaluate oral poliovirus vaccine (OPV) coverage of the November 2009 round in five Northern Nigeria states with ongoing wild poliovirus transmission using clustered lot quality assurance sampling (CLQAS). We selected four local government areas in each pre-selected state and sampled six clusters of 10 children in each Local Government Area, defined as the lot area. We used three decision thresholds to classify OPV coverage: 75-90%, 55-70% and 35-50%. A full lot was completed, but we also assessed in retrospect the potential time-saving benefits of stopping sampling when a lot had been classified. We accepted two local government areas (LGAs) with vaccination coverage above 75%. Of the remaining 18 rejected LGAs, 11 also failed to reach 70% coverage, of which four also failed to reach 50%. The average time taken to complete a lot was 10 h. By stopping sampling when a decision was reached, we could have classified lots in 5.3, 7.7 and 7.3 h on average at the 90%, 70% and 50% coverage targets, respectively. Clustered lot quality assurance sampling was feasible and useful to estimate OPV coverage in Northern Nigeria. The multi-threshold approach provided useful information on the variation of IPD vaccination coverage. CLQAS is a very timely tool, allowing corrective actions to be directly taken in insufficiently covered areas. © 2011 Blackwell Publishing Ltd.

  1. Using Dynamic Quantum Clustering to Analyze Hierarchically Heterogeneous Samples on the Nanoscale

    Energy Technology Data Exchange (ETDEWEB)

    Hume, Allison; /Princeton U. /SLAC

    2012-09-07

    Dynamic Quantum Clustering (DQC) is an unsupervised, high visual data mining technique. DQC was tested as an analysis method for X-ray Absorption Near Edge Structure (XANES) data from the Transmission X-ray Microscopy (TXM) group. The TXM group images hierarchically heterogeneous materials with nanoscale resolution and large field of view. XANES data consists of energy spectra for each pixel of an image. It was determined that DQC successfully identifies structure in data of this type without prior knowledge of the components in the sample. Clusters and sub-clusters clearly reflected features of the spectra that identified chemical component, chemical environment, and density in the image. DQC can also be used in conjunction with the established data analysis technique, which does require knowledge of components present.

  2. Identification of Clusters of Foot Pain Location in a Community Sample.

    Science.gov (United States)

    Gill, Tiffany K; Menz, Hylton B; Landorf, Karl B; Arnold, John B; Taylor, Anne W; Hill, Catherine L

    2017-12-01

    To identify foot pain clusters according to pain location in a community-based sample of the general population. This study analyzed data from the North West Adelaide Health Study. Data were obtained between 2004 and 2006, using computer-assisted telephone interviewing, clinical assessment, and self-completed questionnaire. The location of foot pain was assessed using a diagram during the clinical assessment. Hierarchical cluster analysis was undertaken to identify foot pain location clusters, which were then compared in relation to demographics, comorbidities, and podiatry services utilization. There were 558 participants with foot pain (mean age 54.4 years, 57.5% female). Five clusters were identified: 1 with predominantly arch and ball pain (26.8%), 1 with rearfoot pain (20.9%), 1 with heel pain (13.3%), and 2 with predominantly forefoot, toe, and nail pain (28.3% and 10.7%). Each cluster was distinct in age, sex, and comorbidity profile. Of the two clusters with predominantly forefoot, toe, and nail pain, one of them had a higher proportion of men and those classified as obese, had diabetes mellitus, and used podiatry services (30%), while the other was comprised of a higher proportion of women who were overweight and reported less use of podiatry services (17.5%). Five clusters of foot pain according to pain location were identified, all with distinct age, sex, and comorbidity profiles. These findings may assist in the identification of individuals at risk for developing foot pain and in the development of targeted preventive strategies and treatments. © 2017, American College of Rheumatology.

  3. Cluster analysis of passive air sampling data based on the relative composition of persistent organic pollutants.

    Science.gov (United States)

    Liu, Xiande; Wania, Frank

    2014-03-01

    The development of passive air samplers has allowed the measurement of time-integrated concentrations of persistent organic pollutants (POPs) within spatial networks on a variety of scales. Cluster analysis of POP composition may enhance the interpretation of such spatial data. Several methodological aspects of the application of cluster analysis are discussed, including the influence of a dominant pollutant, the role of PAS duplication, and comparison of regional studies. Relying on data from six regional studies in North and South America, Africa, and Asia, we illustrate here how cluster analysis can be used to extract information and gain insights into POP sources and atmospheric transport contributions. Cluster analysis allows classification of PAS samples into those with significant local source contributions and those that represent regional fingerprints. Local emissions, atmospheric transport, and seasonal cycles are identified as being among the major factors determining the variation in POP composition at many sites. By complementing cluster analysis with meteorological data such as air mass back-trajectories, terrain, as well as geographical and socio-economic aspects, a comprehensive picture of the atmospheric contamination of a region by POPs emerges.

  4. A simple method to generate equal-sized homogenous strata or clusters for population-based sampling.

    Science.gov (United States)

    Elliott, Michael R

    2011-04-01

    Statistical efficiency and cost efficiency can be achieved in population-based samples through stratification and/or clustering. Strata typically combine subgroups of the population that are similar with respect to an outcome. Clusters are often taken from preexisting units, but may be formed to minimize between-cluster variance, or to equalize exposure to a treatment or risk factor. Area probability sample design procedures for the National Children's Study required contiguous strata and clusters that maximized within-stratum and within-cluster homogeneity while maintaining approximately equal size of the strata or clusters. However, there were few methods that allowed such strata or clusters to be constructed under these contiguity and equal size constraints. A search algorithm generates equal-size cluster sets that approximately span the space of all possible clusters of equal size. An optimal cluster set is chosen based on analysis of variance and convexity criteria. The proposed algorithm is used to construct 10 strata based on demographics and air pollution measures in Kent County, MI, following census tract boundaries. A brief simulation study is also conducted. The proposed algorithm is effective at uncovering underlying clusters from noisy data. It can be used in multi-stage sampling where equal-size strata or clusters are desired. Copyright © 2011 Elsevier Inc. All rights reserved.

  5. The XXL Survey. XIII. Baryon content of the bright cluster sample

    Science.gov (United States)

    Eckert, D.; Ettori, S.; Coupon, J.; Gastaldello, F.; Pierre, M.; Melin, J.-B.; Le Brun, A. M. C.; McCarthy, I. G.; Adami, C.; Chiappetti, L.; Faccioli, L.; Giles, P.; Lavoie, S.; Lefèvre, J. P.; Lieu, M.; Mantz, A.; Maughan, B.; McGee, S.; Pacaud, F.; Paltani, S.; Sadibekova, T.; Smith, G. P.; Ziparo, F.

    2016-06-01

    Traditionally, galaxy clusters have been expected to retain all the material accreted since their formation epoch. For this reason, their matter content should be representative of the Universe as a whole, and thus their baryon fraction should be close to the Universal baryon fraction Ωb/ Ωm. We make use of the sample of the 100 brightest galaxy clusters discovered in the XXL Survey to investigate the fraction of baryons in the form of hot gas and stars in the cluster population. Since it spans a wide range of mass (1013-1015 M⊙) and redshift (0.05-1.1) and benefits from a large set of multiwavelength data, the XXL-100-GC sample is ideal for measuring the global baryon budget of massive halos. We measure the gas masses of the detected halos and use a mass-temperature relation directly calibrated using weak-lensing measurements for a subset of XXL clusters to estimate the halo mass. We find that the weak-lensing calibrated gas fraction of XXL-100-GC clusters is substantially lower than was found in previous studies using hydrostatic masses. Our best-fit relation between gas fraction and mass reads fgas,500 = 0.055-0.006+0.007(M500/1014 M⊙)0.21-0.10+0.11. The baryon budget of galaxy clusters therefore falls short of the Universal baryon fraction by about a factor of two at r500,MT. Our measurements require a hydrostatic bias 1-b = MX/MWL = 0.72-0.07+0.08 to match the gas fraction obtained using lensing and hydrostatic equilibrium, which holds independently of the instrument considered. Comparing our gas fraction measurements with the expectations from numerical simulations, we find that our results favour an extreme feedback scheme in which a significant fraction of the baryons are expelled from the cores of halos. This model is, however, in contrast with the thermodynamical properties of observed halos, which might suggest that weak-lensing masses are overestimated. In light of these results, we note that a mass bias 1-b = 0.58 as required to reconcile Planck

  6. SATISFACTION CLUSTERING ANALYSIS OF DISTANCE EDUCATION COMPUTER PROGRAMMING STUDENTS: A Sample of Karadeniz Technical University

    Directory of Open Access Journals (Sweden)

    Hacer OZYURT

    2014-04-01

    Full Text Available In line with recently developing technology, distant education systems based on information technologies are started to be commonly used within higher education. Students’ satisfaction is one of the vital aspects in order to maintain distant education efficiently and achieving its goal. As a matter of the fact, previous studies proved that student satisfaction is one of the most important factors in deciding the success of a system in terms of application. Therefore, this paper analyzes satisfaction variables of distant education computer programming students regarding this program as well as their clustering tendencies. 96 students who were having their majors in distant education computer programming at Karadeniz Technical University during 2012-2013 academic term constitute the sample of the study. The study employed Satisfaction Scale for Students of Distant education Based on Information Technologies as data collection tool which comprised of 42 items. Data obtained from the scale was analyzed via Ward method, one of the hierarchical clustering methods, in order to reveal their clustering tendencies. Accordingly, satisfaction variables were divided into three main clusters which were A, B and C. Of these main clusters, it was seen that A and B has two sub-clusters each which were A1, A2 and B1, B2 respectively. These divisions were named after the variables they include; A1: “Interest of the instructors and the implementation of program content”, A2: “Support and rapport of the university”, B1: “Scope of the program”, B2: “Individuality and the opportunity for interaction” and C: “The defects in application by both the program and the university”. From an overall perspective, it is seen that Cluster A covers variables positively affecting the satisfaction which are “the quality of service provided by the university for this program”, “application of program content fitting to the purpose” and

  7. Sample size estimation to substantiate freedom from disease for clustered binary data with a specific risk profile

    DEFF Research Database (Denmark)

    Kostoulas, P.; Nielsen, Søren Saxmose; Browne, W. J.

    2013-01-01

    SUMMARY Disease cases are often clustered within herds or generally groups that share common characteristics. Sample size formulae must adjust for the within-cluster correlation of the primary sampling units. Traditionally, the intra-cluster correlation coefficient (ICC), which is an average meas...... subsp. paratuberculosis infection, in Danish dairy cattle and a study on critical control points for Salmonella cross-contamination of pork, in Greek slaughterhouses....

  8. Molecular dynamics computer simulations of sputtering of benzene sample by large mixed Lennard-Jones clusters

    Energy Technology Data Exchange (ETDEWEB)

    Rzeznik, L., E-mail: rzeznik@lippmann.lu [University of Information Technology and Management, Sucharskiego 2, 35-225 Rzeszów (Poland); Postawa, Z. [Institute of Physics, Jagiellonian University, Reymonta 4, 30-059 Kraków (Poland)

    2014-05-01

    Molecular dynamics computer simulations have been used to probe the role of the projectile composition on the emission efficiency and the sample damage. A benzene crystal was bombarded by 15 keV large heterogeneous noble gas clusters containing 2953 atoms. The projectiles used in this study are two-component clusters composed of Ne, Ar, and Kr atoms directed at 0° and 60° relative to the surface normal. It has been found that for normal incidence the total sputtering yield decreases with the projectile mass, whereas for 60° impact angle the yield increases with this quantity. For both 0° and 60° impact angles the observed sputtering yield for heterogeneous clusters cannot be calculated as a sum of sputtering yields obtained for homogeneous projectiles multiplied by the concentration of each component in the multi-component cluster. The difference in deposition scenarios of the primary kinetic energy is shown to be responsible for the observed behavior of the total sputtering yield.

  9. Fuzzy C-Means Clustering Model Data Mining For Recognizing Stock Data Sampling Pattern

    Directory of Open Access Journals (Sweden)

    Sylvia Jane Annatje Sumarauw

    2007-06-01

    Full Text Available Abstract Capital market has been beneficial to companies and investor. For investors, the capital market provides two economical advantages, namely deviden and capital gain, and a non-economical one that is a voting .} hare in Shareholders General Meeting. But, it can also penalize the share owners. In order to prevent them from the risk, the investors should predict the prospect of their companies. As a consequence of having an abstract commodity, the share quality will be determined by the validity of their company profile information. Any information of stock value fluctuation from Jakarta Stock Exchange can be a useful consideration and a good measurement for data analysis. In the context of preventing the shareholders from the risk, this research focuses on stock data sample category or stock data sample pattern by using Fuzzy c-Me, MS Clustering Model which providing any useful information jar the investors. lite research analyses stock data such as Individual Index, Volume and Amount on Property and Real Estate Emitter Group at Jakarta Stock Exchange from January 1 till December 31 of 204. 'he mining process follows Cross Industry Standard Process model for Data Mining (CRISP,. DM in the form of circle with these steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. At this modelling process, the Fuzzy c-Means Clustering Model will be applied. Data Mining Fuzzy c-Means Clustering Model can analyze stock data in a big database with many complex variables especially for finding the data sample pattern, and then building Fuzzy Inference System for stimulating inputs to be outputs that based on Fuzzy Logic by recognising the pattern. Keywords: Data Mining, AUz..:y c-Means Clustering Model, Pattern Recognition

  10. The Nature of Optically-Luminous Stellar Clusters in a Large Sample of Luminous Infrared Galaxies

    Science.gov (United States)

    Vavilkin, Tatjana

    2011-08-01

    Luminous Star Clusters (SCs) are fundamental building blocks of galaxies, and they provide basic information regarding the mechanisms of star formation and the process of galaxy formation and evolution. In my PhD thesis project I investigated properties of young SCs in a sample of 87 nearby Luminous Infrared Galaxies (LIRGs: LIR>10^11 L_sun) imaged with the Hubble Space Telescope's Advanced Camera for Surveys at 0.4μm (F435W) and 0.9μm (F814W). Many LIRGs are observed to be ongoing mergers of gas-rich disk galaxies. They contain extreme starbursts and hence are expected to host particularly rich and luminous populations of SCs. This project represents the largest sample of galaxies with uniformly characterized properties of their SC population. The size of the sample allows an identification of trends in SC properties with merger stage and star formation rate. A large fraction (∼17%) of the cluster population is younger than 10 Myr. There is uncertainty in the determination of the ages of the bulk of the SCs due to an age-extinction degeneracy--the majority of the detected cluster population may have ages of up to a few hundred Myr. The median SC luminosity function index of the LIRG sample is alpha=-1.8, which is in a good agreement with previously published studies in various galaxy types. This sample contains some of the most luminous clusters observed so far, with Mmax (F435W) exceeding -17 mag. LIRGs follow the "brightest cluster--star formation rate" correlation observed for lower luminosity star-forming galaxies quite closely, although a large degree of scatter possibly due to extinction and over-estimation of Star Formation Rates (SFRs) in galaxies containing an Active Galactic Nucleus (AGN) is present. Thus, the size-of-sample effect and the observed high SFRs are responsible for high luminosity of SCs found in LIRGs. The specific luminosity TL(F435W)--SFR(far-IR + far-UV) relation observed for nearby non-interacting spiral galaxies is not applicable

  11. New Survey Questions and Estimators for Network Clustering with Respondent-Driven Sampling Data

    CERN Document Server

    Verdery, Ashton M; Siripong, Nalyn; Abdesselam, Kahina; Bauldry, Shawn

    2016-01-01

    Respondent-driven sampling (RDS) is a popular method for sampling hard-to-survey populations that leverages social network connections through peer recruitment. While RDS is most frequently applied to estimate the prevalence of infections and risk behaviors of interest to public health, like HIV/AIDS or condom use, it is rarely used to draw inferences about the structural properties of social networks among such populations because it does not typically collect the necessary data. Drawing on recent advances in computer science, we introduce a set of data collection instruments and RDS estimators for network clustering, an important topological property that has been linked to a network's potential for diffusion of information, disease, and health behaviors. We use simulations to explore how these estimators, originally developed for random walk samples of computer networks, perform when applied to RDS samples with characteristics encountered in realistic field settings that depart from random walks. In partic...

  12. Use of a modified cluster sampling method to perform rapid needs assessment after Hurricane Andrew.

    Science.gov (United States)

    Hlady, W G; Quenemoen, L E; Armenia-Cope, R R; Hurt, K J; Malilay, J; Noji, E K; Wurm, G

    1994-04-01

    To rapidly obtain population-based estimates of needs in the early aftermath of Hurricane Andrew in South Florida. We used a modified cluster-sampling method (the Expanded Programme on Immunization [EPI] method) for three surveys. We selected a systematic sample of 30 quarter-mile square clusters for each survey and, beginning from a random start, interviewed members of seven consecutive occupied households in each cluster. Two surveys were of the most affected area (1990 population, 32,672) at three and ten days after the hurricane struck; one survey was of a less affected area (1990 population, 15,576) seven days after the hurricane struck. Results were available within 24 hours of beginning each survey. Initial findings emphasized the need for restoring utilities and sanitation and helped to focus medical relief on primary care and preventive services. The second survey of the most affected area showed improvement in the availability of food, water, electricity, and sanitation (P < or = .05). There was no evidence of disease outbreaks. For the first time, the EPI method provided population-based information to guide and evaluate relief operations after a sudden-impact natural disaster. An improvement over previous approaches, the EPI method warrants further evaluation as a needs assessment tool in acute disasters.

  13. Evaluation of Primary Immunization Coverage of Infants Under Universal Immunization Programme in an Urban Area of Bangalore City Using Cluster Sampling and Lot Quality Assurance Sampling Techniques

    Science.gov (United States)

    K, Punith; K, Lalitha; G, Suman; BS, Pradeep; Kumar K, Jayanth

    2008-01-01

    Research Question: Is LQAS technique better than cluster sampling technique in terms of resources to evaluate the immunization coverage in an urban area? Objective: To assess and compare the lot quality assurance sampling against cluster sampling in the evaluation of primary immunization coverage. Study Design: Population-based cross-sectional study. Study Setting: Areas under Mathikere Urban Health Center. Study Subjects: Children aged 12 months to 23 months. Sample Size: 220 in cluster sampling, 76 in lot quality assurance sampling. Statistical Analysis: Percentages and Proportions, Chi square Test. Results: (1) Using cluster sampling, the percentage of completely immunized, partially immunized and unimmunized children were 84.09%, 14.09% and 1.82%, respectively. With lot quality assurance sampling, it was 92.11%, 6.58% and 1.31%, respectively. (2) Immunization coverage levels as evaluated by cluster sampling technique were not statistically different from the coverage value as obtained by lot quality assurance sampling techniques. Considering the time and resources required, it was found that lot quality assurance sampling is a better technique in evaluating the primary immunization coverage in urban area. PMID:19876474

  14. Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.

    Science.gov (United States)

    Wang, Huiya; Feng, Jun; Wang, Hongyu

    2017-07-20

    Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.

  15. A Unified Framework for Representation-Based Subspace Clustering of Out-of-Sample and Large-Scale Data.

    Science.gov (United States)

    Peng, Xi; Tang, Huajin; Zhang, Lei; Yi, Zhang; Xiao, Shijie

    2016-12-01

    Under the framework of spectral clustering, the key of subspace clustering is building a similarity graph, which describes the neighborhood relations among data points. Some recent works build the graph using sparse, low-rank, and l2 -norm-based representation, and have achieved the state-of-the-art performance. However, these methods have suffered from the following two limitations. First, the time complexities of these methods are at least proportional to the cube of the data size, which make those methods inefficient for solving the large-scale problems. Second, they cannot cope with the out-of-sample data that are not used to construct the similarity graph. To cluster each out-of-sample datum, the methods have to recalculate the similarity graph and the cluster membership of the whole data set. In this paper, we propose a unified framework that makes the representation-based subspace clustering algorithms feasible to cluster both the out-of-sample and the large-scale data. Under our framework, the large-scale problem is tackled by converting it as the out-of-sample problem in the manner of sampling, clustering, coding, and classifying. Furthermore, we give an estimation for the error bounds by treating each subspace as a point in a hyperspace. Extensive experimental results on various benchmark data sets show that our methods outperform several recently proposed scalable methods in clustering a large-scale data set.

  16. Impact of non-uniform correlation structure on sample size and power in multiple-period cluster randomised trials.

    Science.gov (United States)

    Kasza, J; Hemming, K; Hooper, R; Matthews, Jns; Forbes, A B

    2017-01-01

    Stepped wedge and cluster randomised crossover trials are examples of cluster randomised designs conducted over multiple time periods that are being used with increasing frequency in health research. Recent systematic reviews of both of these designs indicate that the within-cluster correlation is typically taken account of in the analysis of data using a random intercept mixed model, implying a constant correlation between any two individuals in the same cluster no matter how far apart in time they are measured: within-period and between-period intra-cluster correlations are assumed to be identical. Recently proposed extensions allow the within- and between-period intra-cluster correlations to differ, although these methods require that all between-period intra-cluster correlations are identical, which may not be appropriate in all situations. Motivated by a proposed intensive care cluster randomised trial, we propose an alternative correlation structure for repeated cross-sectional multiple-period cluster randomised trials in which the between-period intra-cluster correlation is allowed to decay depending on the distance between measurements. We present results for the variance of treatment effect estimators for varying amounts of decay, investigating the consequences of the variation in decay on sample size planning for stepped wedge, cluster crossover and multiple-period parallel-arm cluster randomised trials. We also investigate the impact of assuming constant between-period intra-cluster correlations instead of decaying between-period intra-cluster correlations. Our results indicate that in certain design configurations, including the one corresponding to the proposed trial, a correlation decay can have an important impact on variances of treatment effect estimators, and hence on sample size and power. An R Shiny app allows readers to interactively explore the impact of correlation decay.

  17. Searching for Be Stars in the Open Clusters with PTF/iPTF. I. Cluster Sample and Be Star Candidates

    Science.gov (United States)

    Yu, Po-Chieh; Yu, Chang-Hsien; Lee, Chien-De; Lin, Chien-Cheng; Hsia, Chih-Hao; Chang, Chang-Kao; Chen, I.-Chenn; Ngeow, Chow-Choong; Ip, Wing-Huen; Chen, Wen-Ping; Laher, Russ; Surace, Jason; Kulkarni, Shrinivas R.

    2018-02-01

    We conducted a search for Be star candidates in open clusters using Hα imaging photometry of the Palomar Transient Factory Survey to investigate some connections among Be star phenomena, cluster environments, and ages. Stellar members of clusters were identified by spatial distributions, near-infrared magnitudes and colors, and by proper motions. Among 104 open clusters, we identified 96 Be star candidates in 32 clusters; 11 of our candidates have been reported in previous studies. We found that the clusters with age 7.5 < log(t(year)) ≤slant 8.5 tend to have more Be star candidates; there is about a 40% occurrence rate within this age bin. The clusters in this age bin also tend to have a higher Be fraction N(Be)/N(Be+B-type). These results suggest that the environments of young and intermediate clusters are favorable to the formation of Be phenomena. Spatial distribution of Be star candidates with different ages implies that they do not form preferentially in the central regions. Furthermore, we showed that the mid-infrared (MIR) colors of the Be star candidates are similar to known Be stars, which could be caused by free–free emission or bound-free emission. Some Be star candidates might have no circumstellar dust according to their MIR colors. Finally, among 96 Be candidates, we discovered that one Be star candidate FSR 0904-1 exhibits long-term variability on the timescale of ∼2000 days with an amplitude of 0.2–0.3 mag, indicating a long timescale of disk evolution.

  18. CA II TRIPLET SPECTROSCOPY OF SMALL MAGELLANIC CLOUD RED GIANTS. III. ABUNDANCES AND VELOCITIES FOR A SAMPLE OF 14 CLUSTERS

    Energy Technology Data Exchange (ETDEWEB)

    Parisi, M. C.; Clariá, J. J.; Marcionni, N. [Observatorio Astronómico, Universidad Nacional de Córdoba, Laprida 854, Córdoba, CP 5000 (Argentina); Geisler, D.; Villanova, S. [Departamento de Astronomía, Universidad de Concepción Casilla 160-C, Concepción (Chile); Sarajedini, A. [Department of Astronomy, University of Florida P.O. Box 112055, Gainesville, FL 32611 (United States); Grocholski, A. J., E-mail: celeste@oac.uncor.edu, E-mail: claria@oac.uncor.edu, E-mail: nmarcionni@oac.uncor.edu, E-mail: dgeisler@astro-udec.cl, E-mail: svillanova@astro-udec.cl, E-mail: ata@astro.ufl.edu, E-mail: grocholski@phys.lsu.edu [Department of Physics and Astronomy, Louisiana State University 202 Nicholson Hall, Tower Drive, Baton Rouge, LA 70803-4001 (United States)

    2015-05-15

    We obtained spectra of red giants in 15 Small Magellanic Cloud (SMC) clusters in the region of the Ca ii lines with FORS2 on the Very Large Telescope. We determined the mean metallicity and radial velocity with mean errors of 0.05 dex and 2.6 km s{sup −1}, respectively, from a mean of 6.5 members per cluster. One cluster (B113) was too young for a reliable metallicity determination and was excluded from the sample. We combined the sample studied here with 15 clusters previously studied by us using the same technique, and with 7 clusters whose metallicities determined by other authors are on a scale similar to ours. This compilation of 36 clusters is the largest SMC cluster sample currently available with accurate and homogeneously determined metallicities. We found a high probability that the metallicity distribution is bimodal, with potential peaks at −1.1 and −0.8 dex. Our data show no strong evidence of a metallicity gradient in the SMC clusters, somewhat at odds with recent evidence from Ca ii triplet spectra of a large sample of field stars. This may be revealing possible differences in the chemical history of clusters and field stars. Our clusters show a significant dispersion of metallicities, whatever age is considered, which could be reflecting the lack of a unique age–metallicity relation in this galaxy. None of the chemical evolution models currently available in the literature satisfactorily represents the global chemical enrichment processes of SMC clusters.

  19. Cairn detection in southern Arabia using a supervised automatic detection algorithm and multiple sample data spectroscopic clustering

    Science.gov (United States)

    Schuetter, Jared Michael

    Excavating cairns in southern Arabia is a way for anthropologists to understand which factors led ancient settlers to transition from a pastoral lifestyle and tribal narrative to the formation of states that exist today. Locating these monuments has traditionally been done in the field, relying on eyewitness reports and costly searches through the arid landscape. In this thesis, an algorithm for automatically detecting cairns in satellite imagery is presented. The algorithm uses a set of filters in a window based approach to eliminate background pixels and other objects that do not look like cairns. The resulting set of detected objects constitutes fewer than 0.001% of the pixels in the satellite image, and contains the objects that look the most like cairns in imagery. When a training set of cairns is available, a further reduction of this set of objects can take place, along with a likelihood-based ranking system. To aid in cairn detection, the satellite image is also clustered to determine land-form classes that tend to be consistent with the presence of cairns. Due to the large number of pixels in the image, a subsample spectral clustering algorithm called "Multiple Sample Data Spectroscopic clustering" is used. This multiple sample clustering procedure is motivated by perturbation studies on single sample spectral algorithms. The studies, presented in this thesis, show that sampling variability in the single sample approach can cause an unsatisfactory level of instability in clustering results. The multiple sample data spectroscopic clustering algorithm is intended to stabilize this perturbation by combining information from different samples. While sampling variability is still present, the use of multiple samples mitigates its effect on cluster results. Finally, a step-through of the cairn detection algorithm and satellite image clustering are given for an image in the Hadramawt region of Yemen. The top ranked detected objects are presented, and a discussion

  20. Clustering Information of Non-Sampled Area in Small Area Estimation of Poverty Indicators

    Science.gov (United States)

    Sundara, V. Y.; Kurnia, A.; Sadik, K.

    2017-03-01

    Empirical Bayes (EB) is one of indirect estimates methods which used to estimate parameters in small area. Molina and Rao has been used this method for estimates nonlinear small area parameter based on a nested error model. Problems occur when this method is used to estimate parameter of non-sampled area which is solely based on synthetic model which ignore the area effects. This paper proposed an approach to clustering area effects of auxiliary variable by assuming that there are similarities among particular area. A simulation study was presented to demonstrate the proposed approach. All estimations were evaluated based on the relative bias and relative root mean squares error. The result of simulation showed that proposed approach can improve the ability of model to estimate non-sampled area. The proposed model was applied to estimate poverty indicators at sub-districts level in regency and city of Bogor, West Java, Indonesia. The result of case study, relative root mean squares error prediction of empirical Bayes with information cluster is smaller than synthetic model.

  1. A study of high-redshift AGN feedback in SZ cluster samples

    Science.gov (United States)

    Bîrzan, L.; Rafferty, D. A.; Brüggen, M.; Intema, H. T.

    2017-10-01

    We present a study of active galactic nucleus (AGN) feedback at higher redshifts (0.3 HERGs) in massive clusters at z > 0.6, implying a transition from HERG-mode accretion to lower power low-excitation radio galaxy (LERG)-mode accretion at intermediate redshifts. Additionally, we use local radio-to-jet power scaling relations to estimate feedback power and find that half of the CF systems in our sample probably have enough heating to balance cooling. However, we postulate that the local relations are likely not well suited to predict feedback power in high-luminosity HERGs, as they are derived from samples composed mainly of lower luminosity LERGs.

  2. cluster

    Indian Academy of Sciences (India)

    electron transfer chains involved in a number of biologi- cal systems including respiration and photosynthesis.1. The most common iron–sulphur clusters found as active centres in iron–sulphur proteins are [Fe2S2], [Fe3S4] and [Fe4S4], in which Fe(III) ions are coordinated to cysteines from the peptide and are linked to each ...

  3. ANALYZING STAR CLUSTER POPULATIONS WITH STOCHASTIC MODELS: THE HUBBLE SPACE TELESCOPE/WIDE FIELD CAMERA 3 SAMPLE OF CLUSTERS IN M83

    Energy Technology Data Exchange (ETDEWEB)

    Fouesneau, Morgan; Lancon, Ariane [Observatoire astronomique and CNRS UMR 7550, Universite de Strasbourg, Strasbourg (France); Chandar, Rupali [Department of Physics and Astronomy, University of Toledo, Toledo, OH (United States); Whitmore, Bradley C., E-mail: morgan.fouesneau@astro.u-strasbg.fr [Space Telescope Science Institute, Baltimore, MD (United States)

    2012-05-01

    The majority of clusters in the universe have masses well below 10{sup 5} M{sub Sun }. Hence, their integrated fluxes and colors can be affected by the presence or absence of a few bright stars introduced by stochastic sampling of the stellar mass function. Specific methods are being developed to extend the analysis of cluster energy distributions into the low-mass regime. In this paper, we apply such a method to real observations of star clusters, in the nearby spiral galaxy M83. We reassess the ages and masses of a sample of 1242 clusters for which UBVIH{alpha} fluxes were obtained from observations with the Wide Field Camera 3 instrument on board the Hubble Space Telescope. Synthetic clusters with known properties are used to characterize the limitations of the method (valid range and resolution in age and mass, method artifacts). The ensemble of color predictions of the discrete cluster models are in good agreement with the distribution of observed colors. We emphasize the important role of the H{alpha} data in the assessment of the fraction of young objects, particularly in breaking the age-extinction degeneracy that hampers an analysis based on UBVI data only. We find the mass distribution of the cluster sample to follow a power law of index -2.1 {+-} 0.2, and the distribution of ages a power law of index -1.0 {+-} 0.2 for log (M/ M{sub Sun }) > 3.5, and ages between 10{sup 7} and 10{sup 9} yr. An extension of our main method, which makes full use of the probability distributions of age and mass obtained for the individual clusters of the sample, is explored. It produces similar power-law slopes and will deserve further investigation. Although the properties derived for individual clusters significantly differ from those obtained with traditional, non-stochastic models in about 30% of the objects, the first-order aspect of the age and mass distributions is similar to those obtained previously for this M83 sample in the range of overlap of the studies. We

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

    Science.gov (United States)

    NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

    2017-08-01

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

  5. Clustering of temperamental and cognitive risk factors for anxiety in a college sample of late adolescents.

    Science.gov (United States)

    Viana, Andres G; Gratz, Kim L; Bierman, Karen L

    2013-01-01

    Temperamental vulnerabilities (e.g., behavioral inhibition, anxiety sensitivity) and cognitive biases (e.g., interpretive and judgment biases) may exacerbate feelings of stress and anxiety, particularly among late adolescents during the early years of college. The goal of the present study was to apply person-centered analyses to explore possible heterogeneity in the patterns of these four risk factors in late adolescence, and to examine associations with several anxiety outcomes (i.e., worry, anxiety symptoms, and trait anxiety). Cluster analyses in a college sample of 855 late adolescents revealed a Low-Risk group, along with four reliable clusters with distinct profiles of risk factors and anxiety outcomes (Inhibited, Sensitive, Cognitively-Biased, and Multi-Risk). Of the risk profiles, Multi-Risk youth experienced the highest levels of anxiety outcomes, whereas Inhibited youth experienced the lowest levels of anxiety outcomes. Sensitive and Cognitively-Biased youth experienced comparable levels of anxiety-related outcomes, despite different constellations of risk factors. Implications for interventions and future research are discussed.

  6. Chandra Cluster Cosmology Project. II. Samples and X-Ray Data Reduction

    DEFF Research Database (Denmark)

    Vikhlinin, A.; Burenin, R. A.; Ebeling, H.

    2009-01-01

    We discuss the measurements of the galaxy cluster mass functions at z ≈ 0.05 and z ≈ 0.5 using high-quality Chandra observations of samples derived from the ROSAT PSPC All-Sky and 400 deg2 surveys. We provide a full reference for the data analysis procedures, present updated calibration of relati...... at a fixed mass threshold, e.g., by a factor of 5.0 ± 1.2 at M 500 = 2.5 × 1014 h –1 M sun between z = 0 and 0.5. This evolution reflects the growth of density perturbations, and can be used for the cosmological constraints complementing those from the distance-redshift relation....

  7. On the errors on Omega(0): Monte Carlo simulations of the EMSS cluster sample

    DEFF Research Database (Denmark)

    Oukbir, J.; Arnaud, M.

    2001-01-01

    and normalization of the power spectrum of matter fluctuations imply relatively large uncertainties on this estimate of Omega (0), of the order of Delta (stat)Omega (0) = 0.1 at the 1 sigma level. On the other hand, the statistical uncertainties due to the finite size of the high-redshift sample are twice as small...... the scatter around the relation between cluster X-ray luminosity and temperature to be a source of systematic error, of the order of Delta (syst)Omega (0) = 0.09, if not properly taken into account in the modelling. After correcting for this bias, our best Omega (0) is 0.66. The uncertainties on the shape...

  8. Influence of sampling on clustering and associations with risk factors in the molecular epidemiology of tuberculosis

    NARCIS (Netherlands)

    Borgdorff, Martien W.; van den Hof, Susan; Kalisvaart, Nico; Kremer, Kristin; van Soolingen, Dick

    2011-01-01

    Molecular epidemiologic studies may use genotypic clustering of isolates as an indicator of recent transmission. It has been shown that missing cases lead to underestimating clustering, and modelling studies suggested that they may also lead to underestimating odds ratios for clustering. Using a

  9. Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease

    Directory of Open Access Journals (Sweden)

    Carolina Pinto Souza

    Full Text Available ABSTRACT Background: Cognitive impairment is a common feature of Parkinson's disease (PD. The diagnoses of mild cognitive impairment (MCI in patients with PD implies an increased risk for later development of dementia, however, it is unclear whether a specific type of cognitive loss confers increased risk for faster cognitive decline. Objective: Determine whether it was possible to identify distinct cognitive phenotypes in a sample of patients with PD. Methods: A cross-sectional evaluation of 100 patients with PD recruited from a movement disorders clinic was conducted. The patients were evaluated using the simplified motor score of the UPDRS, the Hoehn and Yahr, Schwab and England, Geriatric Depression Scale, Pfeffer Functional Activities Questionnaire, Clinical Dementia Rating Scale, Mini-Mental State Examination, clock drawing test, digit span, word list battery of CERAD, Frontal Assessment Battery and verbal fluency test. We classified the patients as having normal cognition (PDNC, MCI (PDMCI or dementia (PDD. Data were analyzed using the chi-square test, non-parametric statistics and cluster analysis. Results: There were 40 patients with PDD, 39 with PDMCI and 21 with PDNC. Patients with PDD were older, had longer disease duration, lower education and lower MMSE scores. Cluster analysis showed 3 general distinct cognitive profiles that represented a continuum from mild to severe impairment of cognition, without distinguishing specific cognitive profiles. Conclusion: Cognitive impairment in PD occurs progressively and heterogeneously in most patients. It is unclear whether the definition of the initial phenotype of cognitive loss can be used to establish the cognitive prognosis of patients.

  10. Cluster Sampling Bias in Government-Sponsored Evaluations: A Correlational Study of Employment and Welfare Pilots in England.

    Science.gov (United States)

    Vaganay, Arnaud

    2016-01-01

    For pilot or experimental employment programme results to apply beyond their test bed, researchers must select 'clusters' (i.e. the job centres delivering the new intervention) that are reasonably representative of the whole territory. More specifically, this requirement must account for conditions that could artificially inflate the effect of a programme, such as the fluidity of the local labour market or the performance of the local job centre. Failure to achieve representativeness results in Cluster Sampling Bias (CSB). This paper makes three contributions to the literature. Theoretically, it approaches the notion of CSB as a human behaviour. It offers a comprehensive theory, whereby researchers with limited resources and conflicting priorities tend to oversample 'effect-enhancing' clusters when piloting a new intervention. Methodologically, it advocates for a 'narrow and deep' scope, as opposed to the 'wide and shallow' scope, which has prevailed so far. The PILOT-2 dataset was developed to test this idea. Empirically, it provides evidence on the prevalence of CSB. In conditions similar to the PILOT-2 case study, investigators (1) do not sample clusters with a view to maximise generalisability; (2) do not oversample 'effect-enhancing' clusters; (3) consistently oversample some clusters, including those with higher-than-average client caseloads; and (4) report their sampling decisions in an inconsistent and generally poor manner. In conclusion, although CSB is prevalent, it is still unclear whether it is intentional and meant to mislead stakeholders about the expected effect of the intervention or due to higher-level constraints or other considerations.

  11. Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials.

    Science.gov (United States)

    Scott, JoAnna M; deCamp, Allan; Juraska, Michal; Fay, Michael P; Gilbert, Peter B

    2017-04-01

    Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.

  12. Cluster information of non-sampled area in small area estimation of poverty indicators using Empirical Bayes

    Science.gov (United States)

    Sundara, Vinny Yuliani; Sadik, Kusman; Kurnia, Anang

    2017-03-01

    Survey is one of data collection method which sampling of individual units from a population. However, national survey only provides limited information which impacts on low precision in small area level. In fact, when the area is not selected as sample unit, estimation cannot be made. Therefore, small area estimation method is required to solve this problem. One of model-based estimation methods is empirical Bayes which has been widely used to estimate parameter in small area, even in non-sampled area. Yet, problems occur when this method is used to estimate parameter of non-sampled area which is solely based on synthetic model which ignore the area effects. This paper proposed an approach to cluster area effects of auxiliary variable by assuming that there are similar among particular area. Direct estimates in several sub-districts in regency and city of Bogor are zero because no household which are under poverty in the sample that selected from these sub-districts. Empirical Bayes method is used to get the estimates are not zero. Empirical Bayes method on FGT poverty measures both Molina & Rao and information clusters have the same estimates in the sub-districts selected as samples, but have different estimates on non-sampled sub-districts. Empirical Bayes methods with information cluster has smaller coefficient of variation. Empirical Bayes method with cluster information is better than empirical Bayes methods without cluster information on non-sampled sub-districts in regency and city of Bogor in terms of coefficient of variation.

  13. Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.

    Science.gov (United States)

    Johnson, Jacqueline L; Kreidler, Sarah M; Catellier, Diane J; Murray, David M; Muller, Keith E; Glueck, Deborah H

    2015-11-30

    We used theoretical and simulation-based approaches to study Type I error rates for one-stage and two-stage analytic methods for cluster-randomized designs. The one-stage approach uses the observed data as outcomes and accounts for within-cluster correlation using a general linear mixed model. The two-stage model uses the cluster specific means as the outcomes in a general linear univariate model. We demonstrate analytically that both one-stage and two-stage models achieve exact Type I error rates when cluster sizes are equal. With unbalanced data, an exact size α test does not exist, and Type I error inflation may occur. Via simulation, we compare the Type I error rates for four one-stage and six two-stage hypothesis testing approaches for unbalanced data. With unbalanced data, the two-stage model, weighted by the inverse of the estimated theoretical variance of the cluster means, and with variance constrained to be positive, provided the best Type I error control for studies having at least six clusters per arm. The one-stage model with Kenward-Roger degrees of freedom and unconstrained variance performed well for studies having at least 14 clusters per arm. The popular analytic method of using a one-stage model with denominator degrees of freedom appropriate for balanced data performed poorly for small sample sizes and low intracluster correlation. Because small sample sizes and low intracluster correlation are common features of cluster-randomized trials, the Kenward-Roger method is the preferred one-stage approach. Copyright © 2015 John Wiley & Sons, Ltd.

  14. A Unique Sample of Extreme-BCG Clusters at 0.2 < z < 0.5

    Science.gov (United States)

    Garmire, Gordon

    2017-09-01

    The recently-discovered Phoenix cluster harbors the most extreme BCG in the known universe. Despite the cluster's high mass and X-ray luminosity, it was consistently identified by surveys as an isolated AGN, due to the bright central point source and the compact cool core. Armed with hindsight, we have undertaken an all-sky survey based on archival X-ray, OIR, and radio data to identify other similarly-extreme systems that were likewise missed. A pilot study demonstrated that this strategy works, leading to the discovery of a new, massive cluster at z 0.2 which was missed by previous X-ray surveys due to the presence of a bright central QSO. We propose here to observe 6 new clusters from our complete northern-sky survey, which harbor some of the most extreme central galaxies known.

  15. C II 158 ??bservations of a Sample of Late-type Galaxies from the Virgo Cluster

    Science.gov (United States)

    Leech, K.; Volk, H.; Heinrichsen, I.; Hippelein, H.; Metcalfe, L.; Pierini, D.; Popescu, C.; Tuffs, R.; Xu, C.

    1999-01-01

    We have observed 19 Virgo cluster spiral galaxies with the Long Wavelength Spectrometer (LWS) onboard ESAs Infrared Space Observatory (ISO) obtaining spectra around the [CII] 157.741 ??ine structure line.

  16. The XMM-LSS survey: the Class 1 cluster sample over the initial 5 deg2 and its cosmological modelling

    Science.gov (United States)

    Pacaud, F.; Pierre, M.; Adami, C.; Altieri, B.; Andreon, S.; Chiappetti, L.; Detal, A.; Duc, P.-A.; Galaz, G.; Gueguen, A.; Le Fèvre, J.-P.; Hertling, G.; Libbrecht, C.; Melin, J.-B.; Ponman, T. J.; Quintana, H.; Refregier, A.; Sprimont, P.-G.; Surdej, J.; Valtchanov, I.; Willis, J. P.; Alloin, D.; Birkinshaw, M.; Bremer, M. N.; Garcet, O.; Jean, C.; Jones, L. R.; Le Fèvre, O.; Maccagni, D.; Mazure, A.; Proust, D.; Röttgering, H. J. A.; Trinchieri, G.

    2007-12-01

    We present a sample of 29 galaxy clusters from the XMM-LSS survey over an area of some 5 deg2 out to a redshift of z = 1.05. The sample clusters, which represent about half of the X-ray clusters identified in the region, follow well-defined X-ray selection criteria and are all spectroscopically confirmed. For all clusters, we provide X-ray luminosities and temperatures as well as masses, obtained from dedicated spatial and spectral fitting. The cluster distribution peaks around z = 0.3 and T = 1.5 keV, half of the objects being groups with a temperature below 2 keV. Our LX-T(z) relation points towards self-similar evolution, but does not exclude other physically plausible models. Assuming that cluster scaling laws follow self-similar evolution, our number density estimates up to z = 1 are compatible with the predictions of the concordance cosmology and with the findings of previous ROSAT surveys. Our well-monitored selection function allowed us to demonstrate that the inclusion of selection effects is essential for the correct determination of the evolution of the LX-T relation, which may explain the contradictory results from previous studies. Extensive simulations show that extending the survey area to 10 deg2 has the potential to exclude the non-evolution hypothesis, but those constraints on more refined intracluster medium models will probably be limited by the large intrinsic dispersion of the LX-T relation, whatever be the sample size. We further demonstrate that increasing the dispersion in the scaling laws increases the number of detectable clusters, hence generating further degeneracy [in addition to σ8,Ωm, LX-T(z)] in the cosmological interpretation of the cluster number counts. We provide useful empirical formulae for the cluster mass-flux and mass-count rate relations as well as a comparison between the XMM-LSS mass sensitivity and that of forthcoming Sunyaev-Zel'dovich surveys. Based on data collected with XMM, Very Large Telescope, Magellan, NTT and

  17. Elemental Abundance Ratios in Stars of the Outer Galactic Disk. IV. A New Sample of Open Clusters

    Science.gov (United States)

    Yong, David; Carney, Bruce W.; Friel, Eileen D.

    2012-10-01

    We present radial velocities and chemical abundances for nine stars in the old, distant open clusters Be18, Be21, Be22, Be32, and PWM4. For Be18 and PWM4, these are the first chemical abundance measurements. Combining our data with literature results produces a compilation of some 68 chemical abundance measurements in 49 unique clusters. For this combined sample, we study the chemical abundances of open clusters as a function of distance, age, and metallicity. We confirm that the metallicity gradient in the outer disk is flatter than the gradient in the vicinity of the solar neighborhood. We also confirm that the open clusters in the outer disk are metal-poor with enhancements in the ratios [α/Fe] and perhaps [Eu/Fe]. All elements show negligible or small trends between [X/Fe] and distance ( 13 kpc) samples may have different trends with distance. There is no evidence for significant abundance trends versus age (history different from that of the solar neighborhood, we echo the sentiments expressed by Friel et al. that definitive conclusions await homogeneous analyses of larger samples of stars in larger numbers of clusters. Arguably, our understanding of the evolution of the outer disk from open clusters is currently limited by systematic abundance differences between various studies. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

  18. The X-ray luminosity-temperature relation of a complete sample of low-mass galaxy clusters

    DEFF Research Database (Denmark)

    Zou, S.; Maughan, B. J.; Giles, P. A.

    2016-01-01

    We present Chandra observations of 23 galaxy groups and low-mass galaxy clusters at 0.03 sample is a statistically complete flux-limited subset of the 400 deg2 survey. We investigated the scaling relation between X-ray luminosity (L) and temperatur...... (T), taking selection biases fully into account. The logarithmic slope of the bolometric L-T relation was found to be 3.29 ± 0.33, consistent with values typically found for samples of more massive clusters. In combination with other recent studies of the L-T relation, we show...... that there is no evidence for the slope, normalization, or scatter of the L-T relation of galaxy groups being different than that of massive clusters. The exception to this is that in the special case of the most relaxed systems, the slope of the core-excised L-T relation appears to steepen from the self-similar value...... found for massive clusters to a steeper slope for the lower mass sample studied here. Thanks to our rigorous treatment of selection biases, these measurements provide a robust reference against which to compare predictions of models of the impact of feedback on the X-ray properties of galaxy groups....

  19. Diversity in the stellar velocity dispersion profiles of a large sample of Brightest Cluster Galaxies z ≤ 0.3

    Science.gov (United States)

    Loubser, S. I.; Hoekstra, H.; Babul, A.; O'Sullivan, E.

    2018-02-01

    We analyse spatially-resolved deep optical spectroscopy of Brightest Cluster Galaxies (BCGs) located in 32 massive clusters with redshifts of 0.05 ≤z ≤ 0.30, to investigate their velocity dispersion profiles. We compare these measurements to those of other massive early-type galaxies, as well as central group galaxies, where relevant. This unique, large sample extends to the most extreme of massive galaxies, spanning MK between -25.7 to -27.8 mag, and host cluster halo mass M500 up to 1.7 × 1015 M⊙. To compare the kinematic properties between brightest group and cluster members, we analyse similar spatially-resolved long-slit spectroscopy for 23 nearby Brightest Group Galaxies (BGGs) from the Complete Local-Volume Groups Sample (CLoGS). We find a surprisingly large variety in velocity dispersion slopes for BCGs, with a significantly larger fraction of positive slopes, unique compared to other (non-central) early-type galaxies as well as the majority of the brightest members of the groups. We find that the velocity dispersion slopes of the BCGs and BGGs correlate with the luminosity of the galaxies, and we quantify this correlation. It is not clear whether the full diversity in velocity dispersion slopes that we see is reproduced in simulations.

  20. Cluster analysis of intradiurnal holm oak pollen cycles at peri-urban and rural sampling sites in southwestern Spain

    Science.gov (United States)

    Hernández-Ceballos, M. A.; García-Mozo, H.; Galán, C.

    2015-08-01

    The impact of regional and local weather and of local topography on intradiurnal variations in airborne pollen levels was assessed by analysing bi-hourly holm oak ( Quercus ilex subsp. ballota (Desf.) Samp.) pollen counts at two sampling stations located 40 km apart, in southwestern Spain (Cordoba city and El Cabril nature reserve) over the period 2010-2011. Pollen grains were captured using Hirst-type volumetric spore traps. Analysis of regional weather conditions was based on the computation of backward trajectories using the HYSPLIT model. Sampling days were selected on the basis of phenological data; rainy days were eliminated, as were days lying outside a given range of percentiles (P95-P5). Analysis of cycles for the study period, as a whole, revealed differences between sampling sites, with peak bi-hourly pollen counts at night in Cordoba and at midday in El Cabril. Differences were also noted in the influence of surface weather conditions (temperature, relative humidity and wind). Cluster analysis of diurnal holm oak pollen cycles revealed the existence of five clusters at each sampling site. Analysis of backward trajectories highlighted specific regional air-flow patterns associated with each site. Findings indicated the contribution of both nearby and distant pollen sources to diurnal cycles. The combined use of cluster analysis and meteorological analysis proved highly suitable for charting the impact of local weather conditions on airborne pollen-count patterns. This method, and the specific tools used here, could be used not only to study diurnal variations in counts for other pollen types and in other biogeographical settings, but also in a number of other research fields involving airborne particle transport modelling, e.g. radionuclide transport in emergency preparedness exercises.

  1. The Australian longitudinal study on male health sampling design and survey weighting: implications for analysis and interpretation of clustered data.

    Science.gov (United States)

    Spittal, Matthew J; Carlin, John B; Currier, Dianne; Downes, Marnie; English, Dallas R; Gordon, Ian; Pirkis, Jane; Gurrin, Lyle

    2016-10-31

    The Australian Longitudinal Study on Male Health (Ten to Men) used a complex sampling scheme to identify potential participants for the baseline survey. This raises important questions about when and how to adjust for the sampling design when analyzing data from the baseline survey. We describe the sampling scheme used in Ten to Men focusing on four important elements: stratification, multi-stage sampling, clustering and sample weights. We discuss how these elements fit together when using baseline data to estimate a population parameter (e.g., population mean or prevalence) or to estimate the association between an exposure and an outcome (e.g., an odds ratio). We illustrate this with examples using a continuous outcome (weight in kilograms) and a binary outcome (smoking status). Estimates of a population mean or disease prevalence using Ten to Men baseline data are influenced by the extent to which the sampling design is addressed in an analysis. Estimates of mean weight and smoking prevalence are larger in unweighted analyses than weighted analyses (e.g., mean = 83.9 kg vs. 81.4 kg; prevalence = 18.0 % vs. 16.7 %, for unweighted and weighted analyses respectively) and the standard error of the mean is 1.03 times larger in an analysis that acknowledges the hierarchical (clustered) structure of the data compared with one that does not. For smoking prevalence, the corresponding standard error is 1.07 times larger. Measures of association (mean group differences, odds ratios) are generally similar in unweighted or weighted analyses and whether or not adjustment is made for clustering. The extent to which the Ten to Men sampling design is accounted for in any analysis of the baseline data will depend on the research question. When the goals of the analysis are to estimate the prevalence of a disease or risk factor in the population or the magnitude of a population-level exposure-outcome association, our advice is to adopt an analysis that respects the

  2. The Australian longitudinal study on male health sampling design and survey weighting: implications for analysis and interpretation of clustered data

    Directory of Open Access Journals (Sweden)

    Matthew J. Spittal

    2016-10-01

    Full Text Available Abstract Background The Australian Longitudinal Study on Male Health (Ten to Men used a complex sampling scheme to identify potential participants for the baseline survey. This raises important questions about when and how to adjust for the sampling design when analyzing data from the baseline survey. Methods We describe the sampling scheme used in Ten to Men focusing on four important elements: stratification, multi-stage sampling, clustering and sample weights. We discuss how these elements fit together when using baseline data to estimate a population parameter (e.g., population mean or prevalence or to estimate the association between an exposure and an outcome (e.g., an odds ratio. We illustrate this with examples using a continuous outcome (weight in kilograms and a binary outcome (smoking status. Results Estimates of a population mean or disease prevalence using Ten to Men baseline data are influenced by the extent to which the sampling design is addressed in an analysis. Estimates of mean weight and smoking prevalence are larger in unweighted analyses than weighted analyses (e.g., mean = 83.9 kg vs. 81.4 kg; prevalence = 18.0 % vs. 16.7 %, for unweighted and weighted analyses respectively and the standard error of the mean is 1.03 times larger in an analysis that acknowledges the hierarchical (clustered structure of the data compared with one that does not. For smoking prevalence, the corresponding standard error is 1.07 times larger. Measures of association (mean group differences, odds ratios are generally similar in unweighted or weighted analyses and whether or not adjustment is made for clustering. Conclusions The extent to which the Ten to Men sampling design is accounted for in any analysis of the baseline data will depend on the research question. When the goals of the analysis are to estimate the prevalence of a disease or risk factor in the population or the magnitude of a population-level exposure

  3. Evaluation of protein spectra cluster analysis for Streptococcus spp. identification from various swine clinical samples.

    Science.gov (United States)

    Matajira, Carlos E C; Moreno, Luisa Z; Gomes, Vasco T M; Silva, Ana Paula S; Mesquita, Renan E; Doto, Daniela S; Calderaro, Franco F; de Souza, Fernando N; Christ, Ana Paula G; Sato, Maria Inês Z; Moreno, Andrea M

    2017-03-01

    Traditional microbiological methods enable genus-level identification of Streptococcus spp. isolates. However, as the species of this genus show broad phenotypic variation, species-level identification or even differentiation within the genus is difficult. Herein we report the evaluation of protein spectra cluster analysis for the identification of Streptococcus species associated with disease in swine by means of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). A total of 250 S. suis-like isolates obtained from pigs with clinical signs of encephalitis, arthritis, pneumonia, metritis, and urinary or septicemic infection were studied. The isolates came from pigs in different Brazilian states from 2001 to 2014. The MALDI-TOF MS analysis identified 86% (215 of 250) as S. suis and 14% (35 of 250) as S. alactolyticus, S. dysgalactiae, S. gallinaceus, S. gallolyticus, S. gordonii, S. henryi, S. hyointestinalis, S. hyovaginalis, S. mitis, S. oralis, S. pluranimalium, and S. sanguinis. The MALDI-TOF MS identification was confirmed in 99.2% of the isolates by 16S rDNA sequencing, with MALDI-TOF MS misidentifying 2 S. pluranimalium as S. hyovaginalis. Isolates were also tested by a biochemical automated system that correctly identified all isolates of 8 of the 10 species in the database. Neither the isolates of the 3 species not in the database ( S. gallinaceus, S. henryi, and S. hyovaginalis) nor the isolates of 2 species that were in the database ( S. oralis and S. pluranimalium) could be identified. The topology of the protein spectra cluster analysis appears to sustain the species phylogenetic similarities, further supporting identification by MALDI-TOF MS examination as a rapid and accurate alternative to 16S rDNA sequencing.

  4. REDSHIFTS, SAMPLE PURITY, AND BCG POSITIONS FOR THE GALAXY CLUSTER CATALOG FROM THE FIRST 720 SQUARE DEGREES OF THE SOUTH POLE TELESCOPE SURVEY

    Energy Technology Data Exchange (ETDEWEB)

    Song, J. [Department of Physics, University of Michigan, 450 Church Street, Ann Arbor, MI 48109 (United States); Zenteno, A.; Desai, S.; Bazin, G. [Department of Physics, Ludwig-Maximilians-Universitaet, Scheinerstr. 1, D-81679 Muenchen (Germany); Stalder, B.; Ashby, M. L. N.; Bayliss, M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Bleem, L. E.; Benson, B. A.; Carlstrom, J. E.; Chang, C. L.; Crawford, T. M.; Crites, A. T. [Kavli Institute for Cosmological Physics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); Aird, K. A. [Department of Physics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); Armstrong, R. [Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104 (United States); Bertin, E. [Institut d' Astrophysique de Paris, UMR 7095 CNRS, Universite Pierre et Marie Curie, 98 bis boulevard Arago, F-75014 Paris (France); Brodwin, M. [Department of Physics and Astronomy, University of Missouri, 5110 Rockhill Road, Kansas City, MO 64110 (United States); Cho, H. M. [NIST Quantum Devices Group, 325 Broadway Mailcode 817.03, Boulder, CO 80305 (United States); Clocchiatti, A. [Departamento de Astronomia y Astrosifica, Pontificia Universidad Catolica, Santiago (Chile); De Haan, T. [Department of Physics, McGill University, 3600 Rue University, Montreal, Quebec H3A 2T8 (Canada); and others

    2012-12-10

    We present the results of the ground- and space-based optical and near-infrared (NIR) follow-up of 224 galaxy cluster candidates detected with the Sunyaev-Zel'dovich (SZ) effect in the 720 deg{sup 2} of the South Pole Telescope (SPT) survey completed in the 2008 and 2009 observing seasons. We use the optical/NIR data to establish whether each candidate is associated with an overdensity of galaxies and to estimate the cluster redshift. Most photometric redshifts are derived through a combination of three different cluster redshift estimators using red-sequence galaxies, resulting in an accuracy of {Delta}z/(1 + z) = 0.017, determined through comparison with a subsample of 57 clusters for which we have spectroscopic redshifts. We successfully measure redshifts for 158 systems and present redshift lower limits for the remaining candidates. The redshift distribution of the confirmed clusters extends to z = 1.35 with a median of z{sub med} = 0.57. Approximately 18% of the sample with measured redshifts lies at z > 0.8. We estimate a lower limit to the purity of this SPT SZ-selected sample by assuming that all unconfirmed clusters are noise fluctuations in the SPT data. We show that the cumulative purity at detection significance {xi} > 5({xi} > 4.5) is {>=}95% ({>=}70%). We present the red brightest cluster galaxy (rBCG) positions for the sample and examine the offsets between the SPT candidate position and the rBCG. The radial distribution of offsets is similar to that seen in X-ray-selected cluster samples, providing no evidence that SZ-selected cluster samples include a different fraction of recent mergers from X-ray-selected cluster samples.

  5. Time clustered sampling can inflate the inferred substitution rate in foot-and-mouth disease virus analyses

    DEFF Research Database (Denmark)

    Pedersen, Casper-Emil Tingskov; Frandsen, Peter; Wekesa, Sabenzia N.

    2015-01-01

    through a study of the foot-and-mouth (FMD) disease virus serotypes SAT 1 and SAT 2. Our study shows that clustered temporal sampling in phylogenetic analyses of FMD viruses will strongly bias the inferences of substitution rates and tMRCA because the inferred rates in such data sets reflect a rate closer......With the emergence of analytical software for the inference of viral evolution, a number of studies have focused on estimating important parameters such as the substitution rate and the time to the most recent common ancestor (tMRCA) for rapidly evolving viruses. Coupled with an increasing...... to the mutation rate rather than the substitution rate. Estimating evolutionary parameters from viral sequences should be performed with due consideration of the differences in short-term and longer-term evolutionary processes occurring within sets of temporally sampled viruses, and studies should carefully...

  6. The Atacama Cosmology Telescope: Physical Properties and Purity of a Galaxy Cluster Sample Selected Via the Sunyaev-Zel'Dovich Effect

    Science.gov (United States)

    Menanteau, Felipe; Gonzalez, Jorge; Juin, Jean-Baptiste; Marriage, Tobias; Reese, Erik D.; Acquaviva, Viviana; Aguirre, Paula; Appel, John Willam; Baker, Andrew J.; Barrientos, L. Felipe; hide

    2010-01-01

    We present optical and X-ray properties for the first confirmed galaxy cluster sample selected by the Sunyaev-Zel'dovich Effect from 148 GHz maps over 455 square degrees of sky made with the Atacama Cosmology Telescope. These maps. coupled with multi-band imaging on 4-meter-class optical telescopes, have yielded a sample of 23 galaxy clusters with redshifts between 0.118 and 1.066. Of these 23 clusters, 10 are newly discovered. The selection of this sample is approximately mass limited and essentially independent of redshift. We provide optical positions, images, redshifts and X-ray fluxes and luminosities for the full sample, and X-ray temperatures of an important subset. The mass limit of the full sample is around 8.0 x 10(exp 14) Stellar Mass. with a number distribution that peaks around a redshift of 0.4. For the 10 highest significance SZE-selected cluster candidates, all of which are optically confirmed, the mass threshold is 1 x 10(exp 15) Stellar Mass and the redshift range is 0.167 to 1.066. Archival observations from Chandra, XMM-Newton. and ROSAT provide X-ray luminosities and temperatures that are broadly consistent with this mass threshold. Our optical follow-up procedure also allowed us to assess the purity of the ACT cluster sample. Eighty (one hundred) percent of the 148 GHz candidates with signal-to-noise ratios greater than 5.1 (5.7) are confirmed as massive clusters. The reported sample represents one of the largest SZE-selected sample of massive clusters over all redshifts within a cosmologically-significant survey volume, which will enable cosmological studies as well as future studies on the evolution, morphology, and stellar populations in the most massive clusters in the Universe.

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

    OpenAIRE

    NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

    2016-01-01

    Cluster-level dynamic treatment regimens can be used to guide sequential, intervention or treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level DTR, the intervention or treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including based on aggregate measures of the individuals or patients that comprise it. Cluster-randomized sequentia...

  8. A Large Sample of Proto-Clusters and Proto-Groups from the VIMOS Ultra-Deep Survey

    Science.gov (United States)

    Lemaux, Brian C.

    2017-07-01

    Using observations from the VIMOS Ultra-Deep Survey (VUDS), a massive spectroscopic campaign targeting 10,000 typical star-forming galaxies at 2 groups forming in the early universe. Though ostensibly a field survey, a number of factors relating to the survey itself and intrinsic to proto-structures have allowed VUDS to sample a large range of local and global densities at these redshifts. In this talk, I will discuss the development of the methods for finding, confirming, and characterizing proto-clusters and proto-groups in the context of VUDS including new techniques and tools developed specifically for these purposes. Several case studies of spectroscopically confirmed massive proto-clusters will be presented, focused both on the diversity of their global properties and that of their member populations. I will also discuss preliminary work on the full ensemble of VUDS proto-structures as well as measurements of the star formation rate-density and color-density relations at these redshifts.

  9. Near-infrared photometry and stellar populations of first-ranked galaxies in a complete sample of nearby Abell clusters

    Science.gov (United States)

    Thuan, Trinx X.; Puschell, Jeffery J.

    1989-01-01

    Eighty-four brightest cluster members (BCMs) in the complete sample of high Galactic latitude nearby Abell clusters of Hoessel, Gunn, and Thuan (HGT) are investigated. The stellar populations in BCMs using near-infrared and optical-near-infrared colors are studied. Brighter BCMs have redder (J-K) and (V-K) colors, suggesting a metallicity increase in brighter galaxies. The larger dispersion of their colors implies that BCMs possess more heterogeneous stellar populations than their lower luminosity counterparts, the normal elliptical galaxies. Special attention is paid to BCMs associated with cooling flows. BCMs with larger accretion rates have bluer (V-K) colors due to ultraviolet excesses and are brighter in the visual wavelength region, but not in the infrared. It is suggested that part of the X-ray emitting cooling gas is converted into high- and intermediate-mass stars emitting in the blue and visible, but not in the infrared. The properties of BCMs as standard candles in the near-infrared are examined and compared with those in the optical.

  10. Employing post-DEA cross-evaluation and cluster analysis in a sample of Greek NHS hospitals.

    Science.gov (United States)

    Flokou, Angeliki; Kontodimopoulos, Nick; Niakas, Dimitris

    2011-10-01

    To increase Data Envelopment Analysis (DEA) discrimination of efficient Decision Making Units (DMUs), by complementing "self-evaluated" efficiencies with "peer-evaluated" cross-efficiencies and, based on these results, to classify the DMUs using cluster analysis. Healthcare, which is deprived of such studies, was chosen as the study area. The sample consisted of 27 small- to medium-sized (70-500 beds) NHS general hospitals distributed throughout Greece, in areas where they are the sole NHS representatives. DEA was performed on 2005 data collected from the Ministry of Health and the General Secretariat of the National Statistical Service. Three inputs -hospital beds, physicians and other health professionals- and three outputs -case-mix adjusted hospitalized cases, surgeries and outpatient visits- were included in input-oriented, constant-returns-to-scale (CRS) and variable-returns-to-scale (VRS) models. In a second stage (post-DEA), aggressive and benevolent cross-efficiency formulations and clustering were employed, to validate (or not) the initial DEA scores. The "maverick index" was used to sort the peer-appraised hospitals. All analyses were performed using custom-made software. Ten benchmark hospitals were identified by DEA, but using the aggressive and benevolent formulations showed that two and four of them respectively were at the lower end of the maverick index list. On the other hand, only one 100% efficient (self-appraised) hospital was at the higher end of the list, using either formulation. Cluster analysis produced a hierarchical "tree" structure which dichotomized the hospitals in accordance to the cross-evaluation results, and provided insight on the two-dimensional path to improving efficiency. This is, to our awareness, the first study in the healthcare domain to employ both of these post-DEA techniques (cross efficiency and clustering) at the hospital (i.e. micro) level. The potential benefit for decision-makers is the capability to examine high

  11. Low vaccination coverage of Greek Roma children amid economic crisis: national survey using stratified cluster sampling.

    Science.gov (United States)

    Papamichail, Dimitris; Petraki, Ioanna; Arkoudis, Chrisoula; Terzidis, Agis; Smyrnakis, Emmanouil; Benos, Alexis; Panagiotopoulos, Takis

    2017-04-01

    Research on Roma health is fragmentary as major methodological obstacles often exist. Reliable estimates on vaccination coverage of Roma children at a national level and identification of risk factors for low coverage could play an instrumental role in developing evidence-based policies to promote vaccination in this marginalized population group. We carried out a national vaccination coverage survey of Roma children. Thirty Roma settlements, stratified by geographical region and settlement type, were included; 7-10 children aged 24-77 months were selected from each settlement using systematic sampling. Information on children's vaccination coverage was collected from multiple sources. In the analysis we applied weights for each stratum, identified through a consensus process. A total of 251 Roma children participated in the study. A vaccination document was presented for the large majority (86%). We found very low vaccination coverage for all vaccines. In 35-39% of children 'minimum vaccination' (DTP3 and IPV2 and MMR1) was administered, while 34-38% had received HepB3 and 31-35% Hib3; no child was vaccinated against tuberculosis in the first year of life. Better living conditions and primary care services close to Roma settlements were associated with higher vaccination indices. Our study showed inadequate vaccination coverage of Roma children in Greece, much lower than that of the non-minority child population. This serious public health challenge should be systematically addressed, or, amid continuing economic recession, the gap may widen. Valid national estimates on important characteristics of the Roma population can contribute to planning inclusion policies.

  12. X-Ray Temperatures, Luminosities, and Masses from XMM-Newton Follow-upof the First Shear-selected Galaxy Cluster Sample

    Science.gov (United States)

    Deshpande, Amruta J.; Hughes, John P.; Wittman, David

    2017-04-01

    We continue the study of the first sample of shear-selected clusters from the initial 8.6 square degrees of the Deep Lens Survey (DLS); a sample with well-defined selection criteria corresponding to the highest ranked shear peaks in the survey area. We aim to characterize the weak lensing selection by examining the sample’s X-ray properties. There are multiple X-ray clusters associated with nearly all the shear peaks: 14 X-ray clusters corresponding to seven DLS shear peaks. An additional three X-ray clusters cannot be definitively associated with shear peaks, mainly due to large positional offsets between the X-ray centroid and the shear peak. Here we report on the XMM-Newton properties of the 17 X-ray clusters. The X-ray clusters display a wide range of luminosities and temperatures; the L X -T X relation we determine for the shear-associated X-ray clusters is consistent with X-ray cluster samples selected without regard to dynamical state, while it is inconsistent with self-similarity. For a subset of the sample, we measure X-ray masses using temperature as a proxy, and compare to weak lensing masses determined by the DLS team. The resulting mass comparison is consistent with equality. The X-ray and weak lensing masses show considerable intrinsic scatter (˜48%), which is consistent with X-ray selected samples when their X-ray and weak lensing masses are independently determined. Some of the data presented herein were obtained at the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

  13. Cluster sampling with referral to improve the efficiency of estimating unmet needs among pregnant and postpartum women after disasters.

    Science.gov (United States)

    Horney, Jennifer; Zotti, Marianne E; Williams, Amy; Hsia, Jason

    2012-01-01

    Women of reproductive age, in particular women who are pregnant or fewer than 6 months postpartum, are uniquely vulnerable to the effects of natural disasters, which may create stressors for caregivers, limit access to prenatal/postpartum care, or interrupt contraception. Traditional approaches (e.g., newborn records, community surveys) to survey women of reproductive age about unmet needs may not be practical after disasters. Finding pregnant or postpartum women is especially challenging because fewer than 5% of women of reproductive age are pregnant or postpartum at any time. From 2009 to 2011, we conducted three pilots of a sampling strategy that aimed to increase the proportion of pregnant and postpartum women of reproductive age who were included in postdisaster reproductive health assessments in Johnston County, North Carolina, after tornadoes, Cobb/Douglas Counties, Georgia, after flooding, and Bertie County, North Carolina, after hurricane-related flooding. Using this method, the percentage of pregnant and postpartum women interviewed in each pilot increased from 0.06% to 21%, 8% to 19%, and 9% to 17%, respectively. Two-stage cluster sampling with referral can be used to increase the proportion of pregnant and postpartum women included in a postdisaster assessment. This strategy may be a promising way to assess unmet needs of pregnant and postpartum women in disaster-affected communities. Published by Elsevier Inc.

  14. A national baseline prevalence survey of schistosomiasis in the Philippines using stratified two-step systematic cluster sampling design.

    Science.gov (United States)

    Leonardo, Lydia; Rivera, Pilarita; Saniel, Ofelia; Villacorte, Elena; Lebanan, May Antonnette; Crisostomo, Bobby; Hernandez, Leda; Baquilod, Mario; Erce, Edgardo; Martinez, Ruth; Velayudhan, Raman

    2012-01-01

    For the first time in the country, a national baseline prevalence survey using a well-defined sampling design such as a stratified two-step systematic cluster sampling was conducted in 2005 to 2008. The purpose of the survey was to stratify the provinces according to prevalence of schistosomiasis such as high, moderate, and low prevalence which in turn would be used as basis for the intervention program to be implemented. The national survey was divided into four phases. Results of the first two phases conducted in Mindanao and the Visayas were published in 2008. Data from the last two phases showed three provinces with prevalence rates higher than endemic provinces surveyed in the first two phases thus changing the overall ranking of endemic provinces at the national level. Age and sex distribution of schistosomiasis remained the same in Luzon and Maguindanao. Soil-transmitted and food-borne helminthes were also recorded in these surveys. This paper deals with the results of the last 2 phases done in Luzon and Maguindanao and integrates all four phases in the discussion.

  15. A National Baseline Prevalence Survey of Schistosomiasis in the Philippines Using Stratified Two-Step Systematic Cluster Sampling Design

    Directory of Open Access Journals (Sweden)

    Lydia Leonardo

    2012-01-01

    Full Text Available For the first time in the country, a national baseline prevalence survey using a well-defined sampling design such as a stratified two-step systematic cluster sampling was conducted in 2005 to 2008. The purpose of the survey was to stratify the provinces according to prevalence of schistosomiasis such as high, moderate, and low prevalence which in turn would be used as basis for the intervention program to be implemented. The national survey was divided into four phases. Results of the first two phases conducted in Mindanao and the Visayas were published in 2008. Data from the last two phases showed three provinces with prevalence rates higher than endemic provinces surveyed in the first two phases thus changing the overall ranking of endemic provinces at the national level. Age and sex distribution of schistosomiasis remained the same in Luzon and Maguindanao. Soil-transmitted and food-borne helminthes were also recorded in these surveys. This paper deals with the results of the last 2 phases done in Luzon and Maguindanao and integrates all four phases in the discussion.

  16. Detailed abundances for a large sample of giant stars in the globular cluster 47 Tucanae (NGC 104)

    Energy Technology Data Exchange (ETDEWEB)

    Cordero, M. J.; Pilachowski, C. A. [Astronomy Department, Indiana University Bloomington, Swain West 319, 727 East 3rd Street, Bloomington, IN 47405-7105 (United States); Johnson, C. I. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, MS-15, Cambridge, MA 02138 (United States); McDonald, I.; Zijlstra, A. A. [Jodrell Bank Centre for Astrophysics, Alan Turing Building, Manchester M13 9PL (United Kingdom); Simmerer, J., E-mail: majocord@indiana.edu, E-mail: catyp@astro.indiana.edu, E-mail: cjohnson@cfa.harvard.edu, E-mail: mcdonald@jb.man.ac.uk, E-mail: albert.zijlstra@manchester.ac.uk, E-mail: jennifer@physics.utah.edu [University of Utah, Physics and Astronomy, 115 South 1400 East #201, Salt Lake City, UT 84112-0830 (United States)

    2014-01-01

    47 Tuc is an ideal target to study chemical evolution and globular cluster (GC) formation in massive more metal-rich GCs, as it is the closest massive GC. We present chemical abundances for O, Na, Al, Si, Ca, Ti, Fe, Ni, La, and Eu in 164 red giant branch stars in the massive GC 47 Tuc using spectra obtained with both the Hydra multifiber spectrograph at the Blanco 4 m telescope and the FLAMES multiobject spectrograph at the Very Large Telescope. We find an average [Fe/H] = –0.79 ± 0.09 dex, consistent with literature values, as well as overabundances of alpha-elements ([α/Fe] ∼ 0.3 dex). The n-capture process elements indicate that 47 Tuc is r process-dominated ([Eu/La] = +0.24), and the light elements O, Na, and Al exhibit star-to-star variations. The Na-O anticorrelation, a signature typically seen in Galactic GCs, is present in 47 Tuc, and extends to include a small number of stars with [O/Fe] ∼ –0.5. Additionally, the [O/Na] ratios of our sample reveal that the cluster stars can be separated into three distinct populations. A Kolmogorov-Smirnov test demonstrates that the O-poor/Na-rich stars are more centrally concentrated than the O-rich/Na-poor stars. The observed number and radial distribution of 47 Tuc's stellar populations, as distinguished by their light element composition, agrees closely with the results obtained from photometric data. We do not find evidence supporting a strong Na-Al correlation in 47 Tuc, which is consistent with current models of asymptotic giant branch nucleosynthesis yields.

  17. Probing BL Lac and Cluster Evolution via a Wide-angle, Deep X-ray Selected Sample

    Science.gov (United States)

    Perlman, E.; Jones, L.; White, N.; Angelini, L.; Giommi, P.; McHardy, I.; Wegner, G.

    1994-12-01

    The WARPS survey (Wide-Angle ROSAT Pointed Survey) has been constructed from the archive of all public ROSAT PSPC observations, and is a subset of the WGACAT catalog. WARPS will include a complete sample of >= 100 BL Lacs at F_x >= 10(-13) erg s(-1) cm(-2) . A second selection technique will identify ~ 100 clusters at 0.15 = 0.304 +/- 0.062 for XBLs but = 0.60 +/- 0.05 for RBLs. Models of the X-ray luminosity function (XLF) are also poorly constrained. WARPS will allow us to compute an accurate XLF, decreasing the error bars above by over a factor of two. We will also test for low-luminosity BL Lacs, whose non-thermal nuclear sources are dim compared to the host galaxy. Browne and Marcha (1993) claim the EMSS missed most of these objects and is incomplete. If their predictions are correct, 20-40% of the BL Lacs we find will fall in this category, enabling us to probe the evolution and internal workings of BL Lacs at lower luminosities than ever before. By removing likely QSOs before optical spectroscopy, WARPS requires only modest amounts of telescope time. It will extend measurement of the cluster XLF both to higher redshifts (z>0.5) and lower luminosities (LX<1x10(44) erg s(-1) ) than previous measurements, confirming or rejecting the 3sigma detection of negative evolution found in the EMSS, and constraining Cold Dark Matter cosmologies. Faint NELGs are a recently discovered major contributor to the X-ray background. They are a mixture of Sy2s, starbursts and galaxies of unknown type. Detailed classification and evolution of their XLF will be determined for the first time.

  18. THE ATACAMA COSMOLOGY TELESCOPE: DYNAMICAL MASSES AND SCALING RELATIONS FOR A SAMPLE OF MASSIVE SUNYAEV-ZEL'DOVICH EFFECT SELECTED GALAXY CLUSTERS {sup ,}

    Energy Technology Data Exchange (ETDEWEB)

    Sifon, Cristobal; Barrientos, L. Felipe; Gonzalez, Jorge; Infante, Leopoldo; Duenner, Rolando [Departamento de Astronomia y Astrofisica, Facultad de Fisica, Pontificia Universidad Catolica de Chile, Casilla 306, Santiago 22 (Chile); Menanteau, Felipe; Hughes, John P.; Baker, Andrew J. [Department of Physics and Astronomy, Rutgers University, 136 Frelinghuysen Road, Piscataway, NJ 08854 (United States); Hasselfield, Matthew [Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T 1Z4 (Canada); Marriage, Tobias A.; Crichton, Devin; Gralla, Megan B. [Department of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD 21218-2686 (United States); Addison, Graeme E.; Dunkley, Joanna [Sub-department of Astrophysics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH (United Kingdom); Battaglia, Nick; Bond, J. Richard; Hajian, Amir [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada); Das, Sudeep [Berkeley Center for Cosmological Physics, LBL and Department of Physics, University of California, Berkeley, CA 94720 (United States); Devlin, Mark J. [Department of Physics and Astronomy, University of Pennsylvania, 209 South 33rd Street, Philadelphia, PA 19104 (United States); Hilton, Matt [School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom); and others

    2013-07-20

    We present the first dynamical mass estimates and scaling relations for a sample of Sunyaev-Zel'dovich effect (SZE) selected galaxy clusters. The sample consists of 16 massive clusters detected with the Atacama Cosmology Telescope (ACT) over a 455 deg{sup 2} area of the southern sky. Deep multi-object spectroscopic observations were taken to secure intermediate-resolution (R {approx} 700-800) spectra and redshifts for Almost-Equal-To 60 member galaxies on average per cluster. The dynamical masses M{sub 200c} of the clusters have been calculated using simulation-based scaling relations between velocity dispersion and mass. The sample has a median redshift z = 0.50 and a median mass M{sub 200c}{approx_equal}12 Multiplication-Sign 10{sup 14} h{sub 70}{sup -1} M{sub sun} with a lower limit M{sub 200c}{approx_equal}6 Multiplication-Sign 10{sup 14} h{sub 70}{sup -1} M{sub sun}, consistent with the expectations for the ACT southern sky survey. These masses are compared to the ACT SZE properties of the sample, specifically, the match-filtered central SZE amplitude y{sub 0}-tilde, the central Compton parameter y{sub 0}, and the integrated Compton signal Y{sub 200c}, which we use to derive SZE-mass scaling relations. All SZE estimators correlate with dynamical mass with low intrinsic scatter ({approx}< 20%), in agreement with numerical simulations. We explore the effects of various systematic effects on these scaling relations, including the correlation between observables and the influence of dynamically disturbed clusters. Using the three-dimensional information available, we divide the sample into relaxed and disturbed clusters and find that {approx}50% of the clusters are disturbed. There are hints that disturbed systems might bias the scaling relations, but given the current sample sizes, these differences are not significant; further studies including more clusters are required to assess the impact of these clusters on the scaling relations.

  19. Evaluation of immunization coverage in the rural area of Pune, Maharashtra, using the 30 cluster sampling technique

    Directory of Open Access Journals (Sweden)

    Pankaj Kumar Gupta

    2013-01-01

    Full Text Available Background: Infectious diseases are a major cause of morbidity and mortality in children. One of the most cost-effective and easy methods for child survival is immunization. Despite all the efforts put in by governmental and nongovernmental institutes for 100% immunization coverage, there are still pockets of low-coverage areas. In India, immunization services are offered free in public health facilities, but, despite rapid increases, the immunization rate remains low in some areas. The Millennium Development Goals (MDG indicators also give importance to immunization. Objective: To assess the immunization coverage in the rural area of Pune. Materials and Methods: A cross-sectional study was conducted in the field practice area of the Rural Health Training Center (RHTC using the WHO′s 30 cluster sampling method for evaluation of immunization coverage. Results: A total of 1913 houses were surveyed. A total of 210 children aged 12-23 months were included in the study. It was found that 86.67% of the children were fully immunized against all the six vaccine-preventable diseases. The proportion of fully immunized children was marginally higher in males (87.61% than in females (85.57%, and the immunization card was available with 60.95% of the subjects. The most common cause for partial immunization was that the time of immunization was inconvenient (36%. Conclusion: Sustained efforts are required to achieve universal coverage of immunization in the rural area of Pune district.

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

    Science.gov (United States)

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

    2017-12-01

    We present the result of searching for clusters of galaxies based on weak gravitational lensing analysis of the ˜160 deg2 area surveyed by Hyper Suprime-Cam (HSC) as a Subaru Strategic Program. HSC is a new prime focus optical imager with a 1.5°-diameter field of view on the 8.2 m Subaru telescope. The superb median seeing on the HSC i-band images of 0{^''.}56 allows the reconstruction of high angular resolution mass maps via weak lensing, which is crucial for the weak lensing cluster search. We identify 65 mass map peaks with a signal-to-noise (S/N) ratio larger than 4.7, and carefully examine their properties by cross-matching the clusters with optical and X-ray cluster catalogs. We find that all the 39 peaks with S/N > 5.1 have counterparts in the optical cluster catalogs, and only 2 out of the 65 peaks are probably false positives. The upper limits of X-ray luminosities from the ROSAT All Sky Survey (RASS) imply the existence of an X-ray underluminous cluster population. We show that the X-rays from the shear-selected clusters can be statistically detected by stacking the RASS images. The inferred average X-ray luminosity is about half that of the X-ray-selected clusters of the same mass. The radial profile of the dark matter distribution derived from the stacking analysis is well modeled by the Navarro-Frenk-White profile with a small concentration parameter value of c500 ˜ 2.5, which suggests that the selection bias on the orientation or the internal structure for our shear-selected cluster sample is not strong.

  1. Xray cavities in a sample of 83 SPT-selected clusters galaxies. Tracing the evolution of AGN feedback in clusters of galaxies out to z=1.2

    Energy Technology Data Exchange (ETDEWEB)

    Hlavacek-Larrondo, J.; McDonald, M.; Benson, B. A.; Forman, W. R.; Allen, S. W.; Bleem, L. E.; Ashby, M. L. N.; Bocquet, S.; Brodwin, M.; Dietrich, J. P.; Jones, C.; Liu, J.; Reichardt, C. L.; Saliwanchik, B. R.; Saro, A.; Schrabback, T.; Song, J.; Stalder, B.; Vikhlinin, A.; Zenteno, A.

    2015-05-18

    X-ray cavities are key tracers of mechanical (or radio mode) heating arising from the active galactic nuclei (AGNs) in brightest cluster galaxies (BCGs). We report on a survey for X-ray cavities in 83 massive, high-redshift ($0.4\\lt z\\lt 1.2$) clusters of galaxies selected by their Sunyaev-Zel’dovich signature in the South Pole Telescope data. Based on Chandra X-ray images, we find a total of six clusters having symmetric pairs of surface brightness depressions consistent with the picture of radio jets inflating X-ray cavities in the intracluster medium (ICM). The majority of these detections are of relatively low significance and require deeper follow-up data in order to be confirmed. Further, this search will miss small (<10 kpc) X-ray cavities that are unresolved by Chandra at high ($z\\gtrsim 0.5$) redshift. Despite these limitations, our results suggest that the power generated by AGN feedback in BCGs has remained unchanged for over half of the age of the universe ($\\gt 7$ Gyr at $z\\sim 0.8$). On average, the detected X-ray cavities have powers of $(0.8-5)\\times {{10}^{45}}\\ {\\rm erg}\\ {{{\\rm s}}^{-1}}$, enthalpies of $(3-6)\\times {{10}^{59}}\\ {\\rm erg}$, and radii of ~17 kpc. Integrating over 7 Gyr, we find that the supermassive black holes in BCGs may have accreted 10(8) to several ${{10}^{9}}\\,{{M}_{\\odot }}$ of material to power these outflows. This level of accretion indicates that significant supermassive black hole growth may occur not only at early times, in the quasar era, but at late times as well. We also find that X-ray cavities at high redshift may inject an excess heat of 0.1–1.0 keV per particle into the hot ICM above and beyond the energy needed to offset cooling. Although this result needs to be confirmed, we note that the magnitude of excess heating is similar to the energy needed to preheat clusters, break self-similarity, and explain the excess entropy in hot atmospheres.

  2. In silico sampling reveals the effect of clustering and shows that the log-normal rank abundance curve is an artefact

    NARCIS (Netherlands)

    Neuteboom, J.H.; Struik, P.C.

    2005-01-01

    The impact of clustering on rank abundance, species-individual (S-N)and species-area curves was investigated using a computer programme for in silico sampling. In a rank abundance curve the abundances of species are plotted on log-scale against species sequence. In an S-N curve the number of species

  3. THE NATURE OF E AND S0 GALAXIES - A STUDY OF A MAGNITUDE-LIMITED SAMPLE OF GALAXIES IN THE COMA CLUSTER

    NARCIS (Netherlands)

    JORGENSEN, [No Value; FRANX, M

    1994-01-01

    Differences and similarities of E and SO galaxies have been investigated on basis of new CCD surface photometry in Gunn r for 171 galaxies within the central square degree of the Coma Cluster; 146 of the galaxies are classified as E or SO. The galaxies form a magnitude-limited sample with Gunn r

  4. Weak-Lensing Mass Calibration of the Atacama Cosmology Telescope Equatorial Sunyaev-Zeldovich Cluster Sample with the Canada-France-Hawaii Telescope Stripe 82 Survey

    Science.gov (United States)

    Battaglia, N.; Leauthaud, A.; Miyatake, H.; Hasseleld, M.; Gralla, M. B.; Allison, R.; Bond, J. R.; Calabrese, E.; Crichton, D.; Devlin, M. J.; hide

    2016-01-01

    Mass calibration uncertainty is the largest systematic effect for using clustersof galaxies to constrain cosmological parameters. We present weak lensing mass measurements from the Canada-France-Hawaii Telescope Stripe 82 Survey for galaxy clusters selected through their high signal-to-noise thermal Sunyaev-Zeldovich (tSZ) signal measured with the Atacama Cosmology Telescope (ACT). For a sample of 9 ACT clusters with a tSZ signal-to-noise greater than five, the average weak lensing mass is (4.8 plus or minus 0.8) times 10 (sup 14) solar mass, consistent with the tSZ mass estimate of (4.7 plus or minus 1.0) times 10 (sup 14) solar mass, which assumes a universal pressure profile for the cluster gas. Our results are consistent with previous weak-lensing measurements of tSZ-detected clusters from the Planck satellite. When comparing our results, we estimate the Eddington bias correction for the sample intersection of Planck and weak-lensing clusters which was previously excluded.

  5. Health and human rights in Chin State, Western Burma: a population-based assessment using multistaged household cluster sampling.

    Directory of Open Access Journals (Sweden)

    Richard Sollom

    Full Text Available BACKGROUND: The Chin State of Burma (also known as Myanmar is an isolated ethnic minority area with poor health outcomes and reports of food insecurity and human rights violations. We report on a population-based assessment of health and human rights in Chin State. We sought to quantify reported human rights violations in Chin State and associations between these reported violations and health status at the household level. METHODS AND FINDINGS: Multistaged household cluster sampling was done. Heads of household were interviewed on demographics, access to health care, health status, food insecurity, forced displacement, forced labor, and other human rights violations during the preceding 12 months. Ratios of the prevalence of household hunger comparing exposed and unexposed to each reported violation were estimated using binomial regression, and 95% confidence intervals (CIs were constructed. Multivariate models were done to adjust for possible confounders. Overall, 91.9% of households (95% CI 89.7%-94.1% reported forced labor in the past 12 months. Forty-three percent of households met FANTA-2 (Food and Nutrition Technical Assistance II project definitions for moderate to severe household hunger. Common violations reported were food theft, livestock theft or killing, forced displacement, beatings and torture, detentions, disappearances, and religious and ethnic persecution. Self reporting of multiple rights abuses was independently associated with household hunger. CONCLUSIONS: Our findings indicate widespread self-reports of human rights violations. The nature and extent of these violations may warrant investigation by the United Nations or International Criminal Court. Please see later in the article for the Editors' Summary.

  6. Health and Human Rights in Chin State, Western Burma: A Population-Based Assessment Using Multistaged Household Cluster Sampling

    Science.gov (United States)

    Sollom, Richard; Richards, Adam K.; Parmar, Parveen; Mullany, Luke C.; Lian, Salai Bawi; Iacopino, Vincent; Beyrer, Chris

    2011-01-01

    Background The Chin State of Burma (also known as Myanmar) is an isolated ethnic minority area with poor health outcomes and reports of food insecurity and human rights violations. We report on a population-based assessment of health and human rights in Chin State. We sought to quantify reported human rights violations in Chin State and associations between these reported violations and health status at the household level. Methods and Findings Multistaged household cluster sampling was done. Heads of household were interviewed on demographics, access to health care, health status, food insecurity, forced displacement, forced labor, and other human rights violations during the preceding 12 months. Ratios of the prevalence of household hunger comparing exposed and unexposed to each reported violation were estimated using binomial regression, and 95% confidence intervals (CIs) were constructed. Multivariate models were done to adjust for possible confounders. Overall, 91.9% of households (95% CI 89.7%–94.1%) reported forced labor in the past 12 months. Forty-three percent of households met FANTA-2 (Food and Nutrition Technical Assistance II project) definitions for moderate to severe household hunger. Common violations reported were food theft, livestock theft or killing, forced displacement, beatings and torture, detentions, disappearances, and religious and ethnic persecution. Self reporting of multiple rights abuses was independently associated with household hunger. Conclusions Our findings indicate widespread self-reports of human rights violations. The nature and extent of these violations may warrant investigation by the United Nations or International Criminal Court. Please see later in the article for the Editors' Summary PMID:21346799

  7. [C II] 158-micrometer Observations of a Sample of Late-type Galaxies from the Virgo Cluster

    Science.gov (United States)

    Leech, K. J.; Volk, H. J.; Heinrichsen, I.; Hippelein, H.; Metcalfe, L.; Pierini, D.; Popescu, C. C.; Tuffs, R. J.; Xu, C.

    1998-01-01

    We have observed 19 Virgo cluster spiral galaxies with the Long Wavelength Spectrometer (LWS) onboard ESAs Infrared Space Observatory (ISO) obtaining spectral around the (C II) 157.741-micrometer fine structure line.

  8. A two-stage cluster sampling method using gridded population data, a GIS, and Google EarthTM imagery in a population-based mortality survey in Iraq

    Directory of Open Access Journals (Sweden)

    Galway LP

    2012-04-01

    Full Text Available Abstract Background Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. Results We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Conclusion Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings.

  9. Sampling

    CERN Document Server

    Thompson, Steven K

    2012-01-01

    Praise for the Second Edition "This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book." —Technometrics "Well-written . . . an excellent book on an important subject. Highly recommended." —Choice "An ideal reference for scientific researchers and other professionals who use sampling." —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treat

  10. Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

    Science.gov (United States)

    Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

    2016-01-01

    Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

  11. The SEGUE Stellar Parameter Pipeline. IV. Validation with an Extended Sample of Galactic Globular and Open Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Smolinski, Jason P.; Beers, Timothy C.; Lee, Young Sun; /Michigan State U. /Michigan State U., JINA; An, Deokkeun; /Ewha Women' s U., Seoul; Bickerton, Steven J.; /Princeton U., Astrophys. Sci. Dept.; Johnson, Jennifer A.; /Ohio State U., Dept. Astron.; Loomis, Craig P.; /Princeton U., Astrophys. Sci. Dept.; Rockosi, Constance M.; /Lick Observ.; Sivarani, Thirupathi; /Bangalore, Indian Inst. Astrophys.; Yanny, Brian; /Fermilab

    2010-08-01

    Spectroscopic and photometric data for likely member stars of five Galactic globular clusters (M 3, M 53, M 71, M 92, and NGC 5053) and three open clusters (M 35, NGC 2158, and NGC 6791) are processed by the current version of the SEGUE Stellar Parameter Pipeline (SSPP), in order to determine estimates of metallicities and radial velocities for the clusters. These results are then compared to values from the literature. We find that the mean metallicity (<[Fe/H]>) and mean radial velocity (hRVi) estimates for each cluster are almost all within 2{sigma} of the adopted literature values; most are within 1{sigma}. We also demonstrate that the new version of the SSPP achieves small, but noteworthy, improvements in <[Fe/H]> estimates at the extrema of the cluster metallicity range, as compared to a previous version of the pipeline software. These results provide additional confidence in the application of the SSPP for studies of the abundances and kinematics of stellar populations in the Galaxy.

  12. Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

    Energy Technology Data Exchange (ETDEWEB)

    Chiu, I.; et al.

    2017-11-02

    We estimate total mass ($M_{500}$), intracluster medium (ICM) mass ($M_{\\mathrm{ICM}}$) and stellar mass ($M_{\\star}$) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses $M_{500}\\gtrsim2.5\\times10^{14}M_{\\odot}$ and redshift $0.2 < z < 1.25$ from the 2500 deg$^2$ South Pole Telescope SPT-SZ survey. The total masses $M_{500}$ are estimated from the SZE observable, the ICM masses $M_{\\mathrm{ICM}}$ are obtained from the analysis of $Chandra$ X-ray observations, and the stellar masses $M_{\\star}$ are derived by fitting spectral energy distribution templates to Dark Energy Survey (DES) $griz$ optical photometry and $WISE$ or $Spitzer$ near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass and the cold baryonic fraction with cluster mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past $\\approx9$ Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the strong mass and weak redshift trends in the stellar mass scaling relation suggest a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called 'missing baryons' outside cluster virial regions.

  13. Whole-genome sequencing of Campylobacter jejuni isolated from Danish routine human stool samples reveals surprising degree of clustering

    DEFF Research Database (Denmark)

    Joensen, K G; Kuhn, K G; Müller, L

    2018-01-01

    OBJECTIVES: Outbreaks of Campylobacter are traditionally considered to be rare, however rather than being the true nature of the disease, this may reflect our present inability to detect them. The aim of this study was to determine the genetic and epidemiological degree of clustering among...

  14. Study of atomic clusters in neutron irradiated reactor pressure vessel surveillance samples by extended X-ray absorption fine structure spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Cammelli, S. [LWV, NES, Paul Scherrer Institute, 5232 Villigen PSI (Switzerland); Fachbereich C - Physik, Bergische Universitaet Wuppertal, Gauss-Str. 20, 42097 Wuppertal (Germany)], E-mail: Sebastiano.cammelli@psi.ch; Degueldre, C.; Kuri, G.; Bertsch, J. [LWV, NES, Paul Scherrer Institute, 5232 Villigen PSI (Switzerland); Luetzenkirchen-Hecht, D.; Frahm, R. [Fachbereich C - Physik, Bergische Universitaet Wuppertal, Gauss-Str. 20, 42097 Wuppertal (Germany)

    2009-03-31

    Copper and nickel impurities in nuclear reactor pressure vessel (RPV) steel can form nano-clusters, which have a strong impact on the ductile-brittle transition temperature of the material. Thus, for control purposes and simulation of long irradiation times, surveillance samples are submitted to enhanced neutron irradiation. In this work, surveillance samples from a Swiss nuclear power plant were investigated by extended X-ray absorption fine structure spectroscopy (EXAFS). The density of Cu and Ni atoms determined in the first and second shells around the absorber is affected by the irradiation and temperature. The comparison of the EXAFS data at Cu and Ni K-edges shows that these elements reside in arrangements similar to bcc Fe. However, the EXAFS analysis reveals local irradiation damage in the form of vacancy fractions, which can be determined with a precision of {approx}5%. There are indications that the formation of Cu and Ni clusters differs significantly.

  15. X-Ray Temperatures for the Extended Medium-Sensitivity Survey High-Redshift Cluster Sample: Constraints on Cosmology and the Dark Energy Equation of State

    Science.gov (United States)

    Henry, J. Patrick

    2004-07-01

    We measure the X-ray temperature (and luminosity) with ASCA of all but one cluster in the Einstein Extended Medium-Sensitivity Survey (EMSS) high-redshift (z>=0.3) sample. We compare these data to a complete sample of low-redshift clusters that also has temperature measurements, thereby providing cosmological constraints. Improvements over our previous work include (1) an enlarged high-redshift sample; (2) temperatures for the low-redshift comparison sample that come from the same instrument as the high-redshift sample; (3) the elimination of three EMSS clusters with the same redshift as the target (i.e., not truly serendipitous) and a fourth with an ASCA flux well below the completeness limit; (4) using a theoretical cluster mass function that more closely matches N-body simulations (the Sheth-Torman function); (5) using a cold dark matter power spectrum instead of a power law; (6) using a general cosmology with arbitrary matter density and cosmological constant; (7) using a cosmology that generalizes the cosmological constant to quintessence; (8) including the effects of temperature measurement errors and scatter in the cluster luminosity-temperature relation; and (9) marginalizing over the poorly known normalization of the mass-temperature relation. We find an allowed band in the Ωm0-ΩΛ0 plane of different orientation to the band of constraints provided by the supernovae Ia Hubble diagram and the cosmic microwave background fluctuations. All three bands intersect at the same place: Ωm0~0.3, ΩΛ0~0.7. We measure the quintessence equation-of-state parameter to be w=-(0.42+/-0.21) (68% confidence for one interesting parameter), consistent with previously determined upper limits. We measure the normalization of the mass fluctuation power spectrum to be σ8=0.66+/-0.16 (68% confidence for three interesting parameters). Systematic errors are larger than the statistical errors only for σ8 with our sample; thus the errors for it depend on the details of the

  16. Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

    Directory of Open Access Journals (Sweden)

    Sakellariou Argiris

    2012-10-01

    Full Text Available Abstract Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. Results We propose a hybrid FS method (mAP-KL, which combines multiple hypothesis testing and affinity propagation (AP-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. Conclusions mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.

  17. Rutaceae sampled from Germany, Malta, and Mallorca (Spain) are associated with AMF clustering with Glomus hoi Berch & Trappe.

    Science.gov (United States)

    Appelhans, M; Weber, H Chr; Imhof, S

    2008-07-01

    Six Rutaceae species collected from natural habitats (Malta, Mallorca (Spain), and Tenerife (Spain)) and the Botanical Garden in Marburg were examined with respect to mycorrhizal structures and fungal identity. All species have the same gross colonization pattern of arbuscular mycorrhiza (AM) with distinct intracellular and intercellular phases but show remarkable differences in details, especially in terms of the extent of the intracellular phase. The associated AM fungi, identified using molecular methods, cluster together with Glomus hoi Berch & Trappe, although the plants were collected from very distant locations.

  18. X-ray studies of coeval star samples. II - The Pleiades cluster as observed with the Einstein Observatory

    Science.gov (United States)

    Micela, G.; Sciortino, S.; Vaiana, G. S.; Harnden, F. R., Jr.; Rosner, R.

    1990-01-01

    Coronal X-ray emission of the Pleiades stars is investigated, and maximum likelihood, integral X-ray luminosity functions are computed for Pleiades members in selected color-index ranges. A detailed search is conducted for long-term variability in the X-ray emission of those stars observed more than once. An overall comparison of the survey results with those of previous surveys confirms the ubiquity of X-ray emission in the Pleiades cluster stars and its higher rate of emission with respect to older stars. It is found that the X-ray emission from dA and early dF stars cannot be proven to be dissimilar to that of Hyades and field stars of the same spectral type. The Pleiades cluster members show a real rise of the X-ray luminosity from dA stars to early dF stars. X-ray emission for the young, solarlike Pleiades stars is about two orders of magnitude more intense than for the nearby solarlike stars.

  19. A cluster-randomized trial of a middle school gender violence prevention program: Design, rationale, and sample characteristics.

    Science.gov (United States)

    Abebe, Kaleab Z; Jones, Kelley A; Ciaravino, Samantha; Ripper, Lisa; Paglisotti, Taylor; Morrow, Sarah Elizabeth; Grafals, Melanie; Van Dusen, Courtney; Miller, Elizabeth

    2017-11-01

    High rates of adolescent relationship abuse (ARA) and sexual violence (SV) reported among adolescents point to the need for prevention among middle school-age youth. This is a cluster randomized controlled trial to test an athletic coach-delivered ARA/SV prevention program in 41 middle schools (38 clusters). Trained coaches talk to their male athletes about 1) what constitutes harmful vs. respectful relationship behaviors, 2) dispelling myths that glorify male sexual aggression and promoting more gender-equitable attitudes, and 3) positive bystander intervention when aggressive male behaviors toward females are witnessed. A total of 973 male athletes (ages 11-14, grades 6-8) are participating. Athletes complete surveys at the beginning and end of sports season (Time 2), and one year later (Time 3). The primary outcome is an increase in positive bystander behaviors (i.e., intervening in peers' disrespectful or harmful behaviors); secondary outcomes are changes in recognition of what constitutes abusive behavior, intentions to intervene, and gender equitable attitudes (Time 2 and 3) as well as reduction in abuse perpetration (Time 3). Participating schools have a greater proportion of non-White students and students on free/reduced lunch compared to schools that declined participation. Participants' self-reported ethnicities are 54.5% White, 29.0% Black, 1.4% Hispanic and the remainder, multi-racial, other, or not reported. This study will evaluate the effectiveness of a coach-delivered ARA/SV prevention program for middle school male athletes. Findings will add to the evidence base regarding developmentally appropriate violence prevention programs as well as the role of coaches in adolescent health promotion. Clinical Trials #: NCT02331238. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  20. The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Cosmological implications of the Fourier space wedges of the final sample

    Science.gov (United States)

    Grieb, Jan Niklas; Sánchez, Ariel G.; Salazar-Albornoz, Salvador; Scoccimarro, Román; Crocce, Martín; Dalla Vecchia, Claudio; Montesano, Francesco; Gil-Marín, Héctor; Ross, Ashley J.; Beutler, Florian; Rodríguez-Torres, Sergio; Chuang, Chia-Hsun; Prada, Francisco; Kitaura, Francisco-Shu; Cuesta, Antonio J.; Eisenstein, Daniel J.; Percival, Will J.; Vargas-Magaña, Mariana; Tinker, Jeremy L.; Tojeiro, Rita; Brownstein, Joel R.; Maraston, Claudia; Nichol, Robert C.; Olmstead, Matthew D.; Samushia, Lado; Seo, Hee-Jong; Streblyanska, Alina; Zhao, Gong-bo

    2017-05-01

    We extract cosmological information from the anisotropic power-spectrum measurements from the recently completed Baryon Oscillation Spectroscopic Survey (BOSS), extending the concept of clustering wedges to Fourier space. Making use of new fast-Fourier-transform-based estimators, we measure the power-spectrum clustering wedges of the BOSS sample by filtering out the information of Legendre multipoles ℓ > 4. Our modelling of these measurements is based on novel approaches to describe non-linear evolution, bias and redshift-space distortions, which we test using synthetic catalogues based on large-volume N-body simulations. We are able to include smaller scales than in previous analyses, resulting in tighter cosmological constraints. Using three overlapping redshift bins, we measure the angular-diameter distance, the Hubble parameter and the cosmic growth rate, and explore the cosmological implications of our full-shape clustering measurements in combination with cosmic microwave background and Type Ia supernova data. Assuming a Λ cold dark matter (ΛCDM) cosmology, we constrain the matter density to Ω M= 0.311_{-0.010}^{+0.009} and the Hubble parameter to H_0 = 67.6_{-0.6}^{+0.7} km s^{-1 Mpc^{-1}}, at a confidence level of 68 per cent. We also allow for non-standard dark energy models and modifications of the growth rate, finding good agreement with the ΛCDM paradigm. For example, we constrain the equation-of-state parameter to w = -1.019_{-0.039}^{+0.048}. This paper is part of a set that analyses the final galaxy-clustering data set from BOSS. The measurements and likelihoods presented here are combined with others in Alam et al. to produce the final cosmological constraints from BOSS.

  1. Clustering of risk-related modifiable behaviours and their association with overweight and obesity among a large sample of youth in the COMPASS study.

    Science.gov (United States)

    Laxer, Rachel E; Brownson, Ross C; Dubin, Joel A; Cooke, Martin; Chaurasia, Ashok; Leatherdale, Scott T

    2017-01-21

    Canadian youth exhibit a number of risky behaviours, some of which are associated with overweight and obesity. The purpose of this study was to examine the prevalence of 15 modifiable risk behaviours in a large sample of Canadian youth, to identify underlying subgroups based on patterns of health behaviours, and to examine the association between identified subgroups and overweight/obesity. Data from 18,587 grades 9-12 students in Year 1 (2012-13) of the COMPASS study and latent class analysis were used to identify patterns and clustering among 15 health behaviours (e.g., physical inactivity, sedentary behaviour, unhealthy eating, substance use). A logistic regression model examined the associations between these clusters and overweight/obesity status. Four distinct classes were identified: traditional school athletes, inactive screenagers, health conscious, and moderately active substance users. Each behavioural cluster demonstrated a distinct pattern of behaviours, some with a greater number of risk factors than others. Traditional school athletes (odds ratio (OR) 1.15, 95% CI 1.03-1.29), inactive screenagers (OR 1.33; 1.19-1.48), and moderately active substance users (OR 1.27; 1.14-1.43) were all significantly more likely to be overweight/obese compared to the health conscious group. Four distinct subpopulations of youth were identified based on their patterns of health and risk behaviours. The three clusters demonstrating poorer health behaviour were all at an increased risk of being overweight/obese compared to their somewhat healthier peers. Obesity-related public health interventions and health promotion efforts might be more effective if consideration is given to population segments with certain behavioural patterns, targeting subgroups at greatest risk of overweight or obesity.

  2. Clustering of risk-related modifiable behaviours and their association with overweight and obesity among a large sample of youth in the COMPASS study

    Directory of Open Access Journals (Sweden)

    Rachel E. Laxer

    2017-01-01

    Full Text Available Abstract Background Canadian youth exhibit a number of risky behaviours, some of which are associated with overweight and obesity. The purpose of this study was to examine the prevalence of 15 modifiable risk behaviours in a large sample of Canadian youth, to identify underlying subgroups based on patterns of health behaviours, and to examine the association between identified subgroups and overweight/obesity. Methods Data from 18,587 grades 9–12 students in Year 1 (2012–13 of the COMPASS study and latent class analysis were used to identify patterns and clustering among 15 health behaviours (e.g., physical inactivity, sedentary behaviour, unhealthy eating, substance use. A logistic regression model examined the associations between these clusters and overweight/obesity status. Results Four distinct classes were identified: traditional school athletes, inactive screenagers, health conscious, and moderately active substance users. Each behavioural cluster demonstrated a distinct pattern of behaviours, some with a greater number of risk factors than others. Traditional school athletes (odds ratio (OR 1.15, 95% CI 1.03–1.29, inactive screenagers (OR 1.33; 1.19–1.48, and moderately active substance users (OR 1.27; 1.14–1.43 were all significantly more likely to be overweight/obese compared to the health conscious group. Conclusions Four distinct subpopulations of youth were identified based on their patterns of health and risk behaviours. The three clusters demonstrating poorer health behaviour were all at an increased risk of being overweight/obese compared to their somewhat healthier peers. Obesity-related public health interventions and health promotion efforts might be more effective if consideration is given to population segments with certain behavioural patterns, targeting subgroups at greatest risk of overweight or obesity.

  3. Mixed effect regression analysis for a cluster-based two-stage outcome-auxiliary-dependent sampling design with a continuous outcome.

    Science.gov (United States)

    Xu, Wangli; Zhou, Haibo

    2012-09-01

    Two-stage design is a well-known cost-effective way for conducting biomedical studies when the exposure variable is expensive or difficult to measure. Recent research development further allowed one or both stages of the two-stage design to be outcome dependent on a continuous outcome variable. This outcome-dependent sampling feature enables further efficiency gain in parameter estimation and overall cost reduction of the study (e.g. Wang, X. and Zhou, H., 2010. Design and inference for cancer biomarker study with an outcome and auxiliary-dependent subsampling. Biometrics 66, 502-511; Zhou, H., Song, R., Wu, Y. and Qin, J., 2011. Statistical inference for a two-stage outcome-dependent sampling design with a continuous outcome. Biometrics 67, 194-202). In this paper, we develop a semiparametric mixed effect regression model for data from a two-stage design where the second-stage data are sampled with an outcome-auxiliary-dependent sample (OADS) scheme. Our method allows the cluster- or center-effects of the study subjects to be accounted for. We propose an estimated likelihood function to estimate the regression parameters. Simulation study indicates that greater study efficiency gains can be achieved under the proposed two-stage OADS design with center-effects when compared with other alternative sampling schemes. We illustrate the proposed method by analyzing a dataset from the Collaborative Perinatal Project.

  4. Significant rise of the prevalence and clinical features of childhood asthma in Qingdao China: cluster sampling investigation of 10,082 children.

    Science.gov (United States)

    Lin, Rongjun; Guan, Renzheng; Liu, Xiaomei; Zhao, Baochun; Guan, Jie; Lu, Ling

    2014-09-26

    Recent investigations suggested that the trend of childhood asthma has been stabilizing or even reversing in some countries. The observation provides contrast to our experience. Thus, the study aimed to investigate the prevalence and clinical features of asthma in children aged 0-14 years in Qingdao China, determine the changes of childhood asthma in China, and discover evidence that can allow better diagnosis and treatment of childhood asthma. A cluster sampling method was used. We randomly extracted the investigation clusters from schools, kindergartens, and communities in Qingdao. Subsequently, we interviewed the members of the clusters using a questionnaire from the International Study of Asthma and Allergies in Childhood (ISAAC) to find children with asthmatic symptoms. After determination by the doctors, more details on the asthmatic children were obtained by asking questions from the National Epidemiology Study of Asthma and Allergies in China questionnaire to obtain more details. We intended to survey 10,800 children. However, the actual number of children was 10,082. The prevalence of asthma in Qingdao children aged 0-14 years was 3.69%. The prevalence among male children was higher than in female (χ2 = 24.53,P China increased significantly based on data obtained ten years ago (2000). Respiratory tract infections were the most important precursors of asthma attack. The attack was most commonly manifested as cough. The treatment, especially the use of ICS, was more rational. However, a certain difference was found, which has yet to be contrasted with the Global Initiative for Asthma (GINA) project.

  5. Statistical properties of convex clustering

    OpenAIRE

    Tan, Kean Ming; Witten, Daniela

    2015-01-01

    In this manuscript, we study the statistical properties of convex clustering. We establish that convex clustering is closely related to single linkage hierarchical clustering and $k$-means clustering. In addition, we derive the range of the tuning parameter for convex clustering that yields a non-trivial solution. We also provide an unbiased estimator of the degrees of freedom, and provide a finite sample bound for the prediction error for convex clustering. We compare convex clustering to so...

  6. Randomization modeling to ascertain clustering patterns of human papillomavirus types detected in cervicovaginal samples in the United States.

    Directory of Open Access Journals (Sweden)

    Troy David Querec

    Full Text Available Detection of multiple human papillomavirus (HPV types in the genital tract is common. Associations among HPV types may impact HPV vaccination modeling and type replacement. The objectives were to determine the distribution of concurrent HPV type infections in cervicovaginal samples and examine type-specific associations. We analyzed HPV genotyping results from 32,245 cervicovaginal specimens collected from women aged 11 to 83 years in the United States from 2001 through 2011. Statistical power was enhanced by combining 6 separate studies. Expected concurrent infection frequencies from a series of permutation models, each with increasing fidelity to the real data, were compared with the observed data. Statistics were computed based on the distributional properties of the randomized data. Concurrent detection occurred more than expected with 0 or ≥3 HPV types and less than expected with 1 and 2 types. Some women bear a disproportionate burden of the HPV type prevalence. Type associations were observed that exceeded multiple hypothesis corrected significance. Multiple HPV types were detected more frequently than expected by chance and associations among particular HPV types were detected. However vaccine-targeted types were not specifically affected, supporting the expectation that current bivalent/quadrivalent HPV vaccination will not result in type replacement with other high-risk types.

  7. Pulsars in Globular Clusters

    OpenAIRE

    Camilo, Fernando; Rasio, Frederic A.

    2005-01-01

    More than 100 radio pulsars have been detected in 24 globular clusters. The largest observed samples are in Terzan 5 and 47 Tucanae, which together contain 45 pulsars. Accurate timing solutions, including positions in the cluster, are known for many of these pulsars. Here we provide an observational overview of some properties of pulsars in globular clusters, as well as properties of the globular clusters with detected pulsars. The many recent detections also provide a new opportunity to re-e...

  8. Cancer Clusters

    Science.gov (United States)

    ... Genetics Services Directory Cancer Prevention Overview Research Cancer Clusters On This Page What is a cancer cluster? ... the number of cancer cases in the suspected cluster Many reported clusters include too few cancer cases ...

  9. The SAMPL5 challenge for embedded-cluster integral equation theory: solvation free energies, aqueous p$K_a$, and cyclohexane–water log D

    CERN Document Server

    Tielker, Nicolas; Heil, Jochen; Kloss, Thomas; Ehrhart, Sebastian; Güssregen, Stefan; Schmidt, K. Friedemann; Kast, Stefan M.

    2016-01-01

    We predict cyclohexane–water distribution coefficients (log D7.4) for drug-like molecules taken from the SAMPL5 blind prediction challenge by the “embedded cluster reference interaction site model” (EC-RISM) integral equation theory. This task involves the coupled problem of predicting both partition coefficients (log P) of neutral species between the solvents and aqueous acidity constants (pKa) in order to account for a change of protonation states. The first issue is addressed by calibrating an EC-RISM-based model for solvation free energies derived from the “Minnesota Solvation Database” (MNSOL) for both water and cyclohexane utilizing a correction based on the partial molar volume, yielding a root mean square error (RMSE) of 2.4 kcal mol−1 for water and 0.8–0.9 kcal mol−1 for cyclohexane depending on the parametrization. The second one is treated by employing on one hand an empirical pKa model (MoKa) and, on the other hand, an EC-RISM-derived regression of published acidity constants (RMSE...

  10. The SAMPL5 challenge for embedded-cluster integral equation theory: solvation free energies, aqueous p K a, and cyclohexane-water log D

    Science.gov (United States)

    Tielker, Nicolas; Tomazic, Daniel; Heil, Jochen; Kloss, Thomas; Ehrhart, Sebastian; Güssregen, Stefan; Schmidt, K. Friedemann; Kast, Stefan M.

    2016-11-01

    We predict cyclohexane-water distribution coefficients (log D 7.4) for drug-like molecules taken from the SAMPL5 blind prediction challenge by the "embedded cluster reference interaction site model" (EC-RISM) integral equation theory. This task involves the coupled problem of predicting both partition coefficients (log P) of neutral species between the solvents and aqueous acidity constants (p K a) in order to account for a change of protonation states. The first issue is addressed by calibrating an EC-RISM-based model for solvation free energies derived from the "Minnesota Solvation Database" (MNSOL) for both water and cyclohexane utilizing a correction based on the partial molar volume, yielding a root mean square error (RMSE) of 2.4 kcal mol-1 for water and 0.8-0.9 kcal mol-1 for cyclohexane depending on the parametrization. The second one is treated by employing on one hand an empirical p K a model (MoKa) and, on the other hand, an EC-RISM-derived regression of published acidity constants (RMSE of 1.5 for a single model covering acids and bases). In total, at most 8 adjustable parameters are necessary (2-3 for each solvent and two for the p K a) for training solvation and acidity models. Applying the final models to the log D 7.4 dataset corresponds to evaluating an independent test set comprising other, composite observables, yielding, for different cyclohexane parametrizations, 2.0-2.1 for the RMSE with the first and 2.2-2.8 with the combined first and second SAMPL5 data set batches. Notably, a pure log P model (assuming neutral species only) performs statistically similarly for these particular compounds. The nature of the approximations and possible perspectives for future developments are discussed.

  11. Quantification of physical activity using the QAPACE Questionnaire: a two stage cluster sample design survey of children and adolescents attending urban school.

    Science.gov (United States)

    Barbosa, Nicolas; Sanchez, Carlos E; Patino, Efrain; Lozano, Benigno; Thalabard, Jean C; LE Bozec, Serge; Rieu, Michel

    2016-05-01

    Quantification of physical activity as energy expenditure is important since youth for the prevention of chronic non communicable diseases in adulthood. It is necessary to quantify physical activity expressed in daily energy expenditure (DEE) in school children and adolescents between 8-16 years, by age, gender and socioeconomic level (SEL) in Bogotá. This is a Two Stage Cluster Survey Sample. From a universe of 4700 schools and 760000 students from three existing socioeconomic levels in Bogotá (low, medium and high). The random sample was 20 schools and 1840 students (904 boys and 936 girls). Foreshadowing desertion of participants and inconsistency in the questionnaire responses, the sample size was increased. Thus, 6 individuals of each gender for each of the nine age groups were selected, resulting in a total sample of 2160 individuals. Selected students filled the QAPACE questionnaire under supervision. The data was analyzed comparing means with multivariate general linear model. Fixed factors used were: gender (boys and girls), age (8 to 16 years old) and tri-strata SEL (low, medium and high); as independent variables were assessed: height, weight, leisure time, expressed in hours/day and dependent variable: daily energy expenditure DEE (kJ.kg-1.day-1): during leisure time (DEE-LT), during school time (DEE-ST), during vacation time (DEE-VT), and total mean DEE per year (DEEm-TY) RESULTS: Differences in DEE by gender, in boys, LT and all DEE, with the SEL all variables were significant; but age-SEL was only significant in DEE-VT. In girls, with the SEL all variables were significant. The post hoc multiple comparisons tests were significant with age using Fisher's Least Significant Difference (LSD) test in all variables. For both genders and for all SELs the values in girls had the higher value except SEL high (5-6) The boys have higher values in DEE-LT, DEE-ST, DEE-VT; except in DEEm-TY in SEL (5-6) In SEL (5-6) all DEEs for both genders are highest. For SEL

  12. The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample

    Science.gov (United States)

    Alam, Shadab; Ata, Metin; Bailey, Stephen; Beutler, Florian; Bizyaev, Dmitry; Blazek, Jonathan A.; Bolton, Adam S.; Brownstein, Joel R.; Burden, Angela; Chuang, Chia-Hsun; Comparat, Johan; Cuesta, Antonio J.; Dawson, Kyle S.; Eisenstein, Daniel J.; Escoffier, Stephanie; Gil-Marín, Héctor; Grieb, Jan Niklas; Hand, Nick; Ho, Shirley; Kinemuchi, Karen; Kirkby, David; Kitaura, Francisco; Malanushenko, Elena; Malanushenko, Viktor; Maraston, Claudia; McBride, Cameron K.; Nichol, Robert C.; Olmstead, Matthew D.; Oravetz, Daniel; Padmanabhan, Nikhil; Palanque-Delabrouille, Nathalie; Pan, Kaike; Pellejero-Ibanez, Marcos; Percival, Will J.; Petitjean, Patrick; Prada, Francisco; Price-Whelan, Adrian M.; Reid, Beth A.; Rodríguez-Torres, Sergio A.; Roe, Natalie A.; Ross, Ashley J.; Ross, Nicholas P.; Rossi, Graziano; Rubiño-Martín, Jose Alberto; Saito, Shun; Salazar-Albornoz, Salvador; Samushia, Lado; Sánchez, Ariel G.; Satpathy, Siddharth; Schlegel, David J.; Schneider, Donald P.; Scóccola, Claudia G.; Seo, Hee-Jong; Sheldon, Erin S.; Simmons, Audrey; Slosar, Anže; Strauss, Michael A.; Swanson, Molly E. C.; Thomas, Daniel; Tinker, Jeremy L.; Tojeiro, Rita; Magaña, Mariana Vargas; Vazquez, Jose Alberto; Verde, Licia; Wake, David A.; Wang, Yuting; Weinberg, David H.; White, Martin; Wood-Vasey, W. Michael; Yèche, Christophe; Zehavi, Idit; Zhai, Zhongxu; Zhao, Gong-Bo

    2017-09-01

    We present cosmological results from the final galaxy clustering data set of the Baryon Oscillation Spectroscopic Survey, part of the Sloan Digital Sky Survey III. Our combined galaxy sample comprises 1.2 million massive galaxies over an effective area of 9329 deg2 and volume of 18.7 Gpc3, divided into three partially overlapping redshift slices centred at effective redshifts 0.38, 0.51 and 0.61. We measure the angular diameter distance DM and Hubble parameter H from the baryon acoustic oscillation (BAO) method, in combination with a cosmic microwave background prior on the sound horizon scale, after applying reconstruction to reduce non-linear effects on the BAO feature. Using the anisotropic clustering of the pre-reconstruction density field, we measure the product DMH from the Alcock-Paczynski (AP) effect and the growth of structure, quantified by fσ8(z), from redshift-space distortions (RSD). We combine individual measurements presented in seven companion papers into a set of consensus values and likelihoods, obtaining constraints that are tighter and more robust than those from any one method; in particular, the AP measurement from sub-BAO scales sharpens constraints from post-reconstruction BAOs by breaking degeneracy between DM and H. Combined with Planck 2016 cosmic microwave background measurements, our distance scale measurements simultaneously imply curvature ΩK = 0.0003 ± 0.0026 and a dark energy equation-of-state parameter w = -1.01 ± 0.06, in strong affirmation of the spatially flat cold dark matter (CDM) model with a cosmological constant (ΛCDM). Our RSD measurements of fσ8, at 6 per cent precision, are similarly consistent with this model. When combined with supernova Ia data, we find H0 = 67.3 ± 1.0 km s-1 Mpc-1 even for our most general dark energy model, in tension with some direct measurements. Adding extra relativistic species as a degree of freedom loosens the constraint only slightly, to H0 = 67.8 ± 1.2 km s-1 Mpc-1. Assuming flat

  13. HIV prevalence and related risk behaviours in female seasonal farm workers in Souss Massa Draa, Morocco: results from a cross-sectional survey using cluster-based sampling.

    Science.gov (United States)

    Bozicevic, Ivana; Guezzar, Fatiha; Stulhofer, Aleksandar; Bennani, Aziza; Handanagic, Senad; Barbaric, Jelena; El Rhilani, Houssine; Alami, Kamal; Khattabi, Hamida; Riedner, Gabriele; Maaroufi, Abderrahmane

    2017-06-08

    To determine prevalence of HIV and HIV-related behaviours in female seasonal farm workers (FSFWs) in two provinces of Souss Massa Draa (SMD) region in Morocco. SMD has a higher burden of HIV compared with other parts of Morocco and is characterised by a substantial aggregation of FSFW. We carried out a cross-sectional HIV biobehavioural survey using cluster-based sampling of farms in the provinces Chtouka Aït Baha and Taroudant Ouled Teïma in 2014. HIV testing was done using the Determine HIV-1/2 rapid test and reactive specimens were tested using ELISA and western blot. Collected data were post hoc weighted for region-based stratification and adjusted for clustering effects using complex survey functions of SPSS (V.21). Among those eligible to participate, the response rate was 92.8%. HIV prevalence was 0.9% (95% CI 0.4% to 2.4%) among 520 recruited participants. A high proportion of respondents (67.7%) had no education. Ever having sex was reported by 79.8% and among these, 12.7% ever exchanged sex for money or goods. Sixty-one per cent reported condom use at most recent commercial vaginal sex in the past 12 months. STI symptom recognition was found to be low because 62.4% and 46.8% of FSFW could not report any STI symptoms in men and women, respectively. Twenty-seven per cent of respondents had an HIV test in the past 12 months. In multivariable analysis, those with primary or higher education (adjusted OR (aOR)=2.38, 95% CI 1.33 to 4.27) and those who participated in an HIV educational session at their workplace (aOR=11.00, 95% CI 3.99 to 30.31) had higher odds of ever been tested for HIV. Although we found a relatively low HIV prevalence among FSFW in SMD, HIV interventions should be intensified, in particular, in a subgroup of women who are involved in sex work. 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/.

  14. The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: first measurement of baryon acoustic oscillations between redshift 0.8 and 2.2

    Science.gov (United States)

    Ata, Metin; Baumgarten, Falk; Bautista, Julian; Beutler, Florian; Bizyaev, Dmitry; Blanton, Michael R.; Blazek, Jonathan A.; Bolton, Adam S.; Brinkmann, Jonathan; Brownstein, Joel R.; Burtin, Etienne; Chuang, Chia-Hsun; Comparat, Johan; Dawson, Kyle S.; de la Macorra, Axel; Du, Wei; du Mas des Bourboux, Hélion; Eisenstein, Daniel J.; Gil-Marín, Héctor; Grabowski, Katie; Guy, Julien; Hand, Nick; Ho, Shirley; Hutchinson, Timothy A.; Ivanov, Mikhail M.; Kitaura, Francisco-Shu; Kneib, Jean-Paul; Laurent, Pierre; Le Goff, Jean-Marc; McEwen, Joseph E.; Mueller, Eva-Maria; Myers, Adam D.; Newman, Jeffrey A.; Palanque-Delabrouille, Nathalie; Pan, Kaike; Pâris, Isabelle; Pellejero-Ibanez, Marcos; Percival, Will J.; Petitjean, Patrick; Prada, Francisco; Prakash, Abhishek; Rodríguez-Torres, Sergio A.; Ross, Ashley J.; Rossi, Graziano; Ruggeri, Rossana; Sánchez, Ariel G.; Satpathy, Siddharth; Schlegel, David J.; Schneider, Donald P.; Seo, Hee-Jong; Slosar, Anže; Streblyanska, Alina; Tinker, Jeremy L.; Tojeiro, Rita; Vargas Magaña, Mariana; Vivek, M.; Wang, Yuting; Yèche, Christophe; Yu, Liang; Zarrouk, Pauline; Zhao, Cheng; Zhao, Gong-Bo; Zhu, Fangzhou

    2018-02-01

    We present measurements of the Baryon Acoustic Oscillation (BAO) scale in redshift-space using the clustering of quasars. We consider a sample of 147 000 quasars from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) distributed over 2044 square degrees with redshifts 0.8 0 at 6.6σ significance when testing a ΛCDM model with free curvature.

  15. Mortality in Iraq associated with the 2003-2011 war and occupation: findings from a national cluster sample survey by the university collaborative Iraq Mortality Study.

    Directory of Open Access Journals (Sweden)

    Amy Hagopian

    2013-10-01

    Full Text Available Previous estimates of mortality in Iraq attributable to the 2003 invasion have been heterogeneous and controversial, and none were produced after 2006. The purpose of this research was to estimate direct and indirect deaths attributable to the war in Iraq between 2003 and 2011.We conducted a survey of 2,000 randomly selected households throughout Iraq, using a two-stage cluster sampling method to ensure the sample of households was nationally representative. We asked every household head about births and deaths since 2001, and all household adults about mortality among their siblings. We used secondary data sources to correct for out-migration. From March 1, 2003, to June 30, 2011, the crude death rate in Iraq was 4.55 per 1,000 person-years (95% uncertainty interval 3.74-5.27, more than 0.5 times higher than the death rate during the 26-mo period preceding the war, resulting in approximately 405,000 (95% uncertainty interval 48,000-751,000 excess deaths attributable to the conflict. Among adults, the risk of death rose 0.7 times higher for women and 2.9 times higher for men between the pre-war period (January 1, 2001, to February 28, 2003 and the peak of the war (2005-2006. We estimate that more than 60% of excess deaths were directly attributable to violence, with the rest associated with the collapse of infrastructure and other indirect, but war-related, causes. We used secondary sources to estimate rates of death among emigrants. Those estimates suggest we missed at least 55,000 deaths that would have been reported by households had the households remained behind in Iraq, but which instead had migrated away. Only 24 households refused to participate in the study. An additional five households were not interviewed because of hostile or threatening behavior, for a 98.55% response rate. The reliance on outdated census data and the long recall period required of participants are limitations of our study.Beyond expected rates, most mortality

  16. Mortality in Iraq Associated with the 2003–2011 War and Occupation: Findings from a National Cluster Sample Survey by the University Collaborative Iraq Mortality Study

    Science.gov (United States)

    Hagopian, Amy; Flaxman, Abraham D.; Takaro, Tim K.; Esa Al Shatari, Sahar A.; Rajaratnam, Julie; Becker, Stan; Levin-Rector, Alison; Galway, Lindsay; Hadi Al-Yasseri, Berq J.; Weiss, William M.; Murray, Christopher J.; Burnham, Gilbert

    2013-01-01

    Background Previous estimates of mortality in Iraq attributable to the 2003 invasion have been heterogeneous and controversial, and none were produced after 2006. The purpose of this research was to estimate direct and indirect deaths attributable to the war in Iraq between 2003 and 2011. Methods and Findings We conducted a survey of 2,000 randomly selected households throughout Iraq, using a two-stage cluster sampling method to ensure the sample of households was nationally representative. We asked every household head about births and deaths since 2001, and all household adults about mortality among their siblings. We used secondary data sources to correct for out-migration. From March 1, 2003, to June 30, 2011, the crude death rate in Iraq was 4.55 per 1,000 person-years (95% uncertainty interval 3.74–5.27), more than 0.5 times higher than the death rate during the 26-mo period preceding the war, resulting in approximately 405,000 (95% uncertainty interval 48,000–751,000) excess deaths attributable to the conflict. Among adults, the risk of death rose 0.7 times higher for women and 2.9 times higher for men between the pre-war period (January 1, 2001, to February 28, 2003) and the peak of the war (2005–2006). We estimate that more than 60% of excess deaths were directly attributable to violence, with the rest associated with the collapse of infrastructure and other indirect, but war-related, causes. We used secondary sources to estimate rates of death among emigrants. Those estimates suggest we missed at least 55,000 deaths that would have been reported by households had the households remained behind in Iraq, but which instead had migrated away. Only 24 households refused to participate in the study. An additional five households were not interviewed because of hostile or threatening behavior, for a 98.55% response rate. The reliance on outdated census data and the long recall period required of participants are limitations of our study. Conclusions Beyond

  17. Mortality in Iraq associated with the 2003-2011 war and occupation: findings from a national cluster sample survey by the university collaborative Iraq Mortality Study.

    Science.gov (United States)

    Hagopian, Amy; Flaxman, Abraham D; Takaro, Tim K; Esa Al Shatari, Sahar A; Rajaratnam, Julie; Becker, Stan; Levin-Rector, Alison; Galway, Lindsay; Hadi Al-Yasseri, Berq J; Weiss, William M; Murray, Christopher J; Burnham, Gilbert

    2013-10-01

    Previous estimates of mortality in Iraq attributable to the 2003 invasion have been heterogeneous and controversial, and none were produced after 2006. The purpose of this research was to estimate direct and indirect deaths attributable to the war in Iraq between 2003 and 2011. We conducted a survey of 2,000 randomly selected households throughout Iraq, using a two-stage cluster sampling method to ensure the sample of households was nationally representative. We asked every household head about births and deaths since 2001, and all household adults about mortality among their siblings. We used secondary data sources to correct for out-migration. From March 1, 2003, to June 30, 2011, the crude death rate in Iraq was 4.55 per 1,000 person-years (95% uncertainty interval 3.74-5.27), more than 0.5 times higher than the death rate during the 26-mo period preceding the war, resulting in approximately 405,000 (95% uncertainty interval 48,000-751,000) excess deaths attributable to the conflict. Among adults, the risk of death rose 0.7 times higher for women and 2.9 times higher for men between the pre-war period (January 1, 2001, to February 28, 2003) and the peak of the war (2005-2006). We estimate that more than 60% of excess deaths were directly attributable to violence, with the rest associated with the collapse of infrastructure and other indirect, but war-related, causes. We used secondary sources to estimate rates of death among emigrants. Those estimates suggest we missed at least 55,000 deaths that would have been reported by households had the households remained behind in Iraq, but which instead had migrated away. Only 24 households refused to participate in the study. An additional five households were not interviewed because of hostile or threatening behavior, for a 98.55% response rate. The reliance on outdated census data and the long recall period required of participants are limitations of our study. Beyond expected rates, most mortality increases in Iraq

  18. Spatial cluster modelling

    CERN Document Server

    Lawson, Andrew B

    2002-01-01

    Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal ...

  19. Star clusters

    NARCIS (Netherlands)

    Gieles, M.

    2006-01-01

    Star clusters are observed in almost every galaxy. In this thesis we address several fundamental problems concerning the formation, evolution and disruption of star clusters. From observations of (young) star clusters in the interacting galaxy M51, we found that clusters are formed in complexes of

  20. Progress towards implementation of ACT malaria case-management in public health facilities in the Republic of Sudan: a cluster-sample survey.

    Science.gov (United States)

    Abdelgader, Tarig M; Ibrahim, Abdalla M; Elmardi, Khalid A; Githinji, Sophie; Zurovac, Dejan; Snow, Robert W; Noor, Abdisalan M

    2012-01-06

    Effective malaria case-management based on artemisinin-based combination therapy (ACT) and parasitological diagnosis is a major pillar within the 2007-2012 National Malaria Strategic Plan in the Sudan. Three years after the launch of the strategy a health facility survey was undertaken to evaluate case-management practices and readiness of the health facilities and health workers to implement a new malaria case-management strategy. A cross-sectional, cluster sample survey was undertaken at public health facilities in 15 states of Sudan. Data were collected using quality-of-care assessment methods. The main outcomes were the proportions of facilities with ACTs and malaria diagnostics; proportions of health workers exposed to malaria related health systems support activities; and composite and individual indicators of case-management practices for febrile outpatients stratified by age, availability of ACTs and diagnostics, use of malaria diagnostics, and test result. We evaluated 244 facilities, 294 health workers and 1,643 consultations for febrile outpatients (425 ACTs, 24% were trained in the use of malaria Rapid Diagnostic Tests, and 19% had received a supervisory visit including malaria case-management. At all health facilities 46% of febrile patients were parasitologically tested and 35% of patients were both, tested and treated according to test result. At facilities where AS+SP and malaria diagnostics were available 66% of febrile patients were tested and 51% were both, tested and treated according to test result. Among test positive patients 64% were treated with AS+SP but 24% were treated with artemether monotherapy. Among test negative patients only 17% of patients were treated for malaria. The majority of ACT dispensing and counseling practices were suboptimal. Five years following change of the policy from chloroquine to ACTs and 3 years before the end of the new malaria strategic plan chloroquine was successfully phased out from public facilities in

  1. Clustering of Galaxy Clusters at Intermediate Redshifts

    Science.gov (United States)

    Postman, Marc; Lauer, Tod R.; Oegerle, William

    2001-02-01

    We propose to continue a redshift survey of 141 objectively selected galaxy clusters to measure their clustering properties and constrain models of the formation of structure in the universe. This is the first redshift survey to probe cluster correlations on comoving scales of ~ 50h_75^-1 Mpc at z ~ 0.5 and will thus provide an original and important constraint on the evolution of large-scale structure. The cluster sample comes from our deep (I_AB ≤ 24), contiguous 16 deg^2 I-band KPNO 4-m survey. The proposed observations distinguish themselves from other ongoing distant cluster redshift work in that this survey will be able to provide meaningful constraints on the large-scale spatial distribution of moderate redshift clusters owing to the large angular area and contiguous geometry of the parent survey. The availability of the HET/LRS provides a highly efficient solution to the acquisition of redshifts for the 80 cluster candidates with 0.6 ≤ z_est ≤ 0.7. The systems with z_est > 0.6 are needed to assure complete sampling of the cluster population at z_obs ~ 0.5. The survey declination (52+/-2°) and observational strategy are extremely well-suited to the initial capabilities and queue observing mode of the HET. The 4m/RCSP is well suited to completing the survey of the z_est data. This survey began using the KPNO 4m to obtain redshifts for the 0.3 ≤ z_est < 0.6 sample. So far, we have observed 31 clusters and we're presently ~25% complete with the z_est < 0.6 observations (75% complete for z_est < 0.4). We have discovered at least 2 superclusters at z=0.23 and z=0.50.

  2. Weighted Clustering

    DEFF Research Database (Denmark)

    Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

    2012-01-01

    We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

  3. Modeling Clustered Data with Very Few Clusters.

    Science.gov (United States)

    McNeish, Daniel; Stapleton, Laura M

    2016-01-01

    Small-sample inference with clustered data has received increased attention recently in the methodological literature, with several simulation studies being presented on the small-sample behavior of many methods. However, nearly all previous studies focus on a single class of methods (e.g., only multilevel models, only corrections to sandwich estimators), and the differential performance of various methods that can be implemented to accommodate clustered data with very few clusters is largely unknown, potentially due to the rigid disciplinary preferences. Furthermore, a majority of these studies focus on scenarios with 15 or more clusters and feature unrealistically simple data-generation models with very few predictors. This article, motivated by an applied educational psychology cluster randomized trial, presents a simulation study that simultaneously addresses the extreme small sample and differential performance (estimation bias, Type I error rates, and relative power) of 12 methods to account for clustered data with a model that features a more realistic number of predictors. The motivating data are then modeled with each method, and results are compared. Results show that generalized estimating equations perform poorly; the choice of Bayesian prior distributions affects performance; and fixed effect models perform quite well. Limitations and implications for applications are also discussed.

  4. Cluster management.

    Science.gov (United States)

    Katz, R

    1992-11-01

    Cluster management is a management model that fosters decentralization of management, develops leadership potential of staff, and creates ownership of unit-based goals. Unlike shared governance models, there is no formal structure created by committees and it is less threatening for managers. There are two parts to the cluster management model. One is the formation of cluster groups, consisting of all staff and facilitated by a cluster leader. The cluster groups function for communication and problem-solving. The second part of the cluster management model is the creation of task forces. These task forces are designed to work on short-term goals, usually in response to solving one of the unit's goals. Sometimes the task forces are used for quality improvement or system problems. Clusters are groups of not more than five or six staff members, facilitated by a cluster leader. A cluster is made up of individuals who work the same shift. For example, people with job titles who work days would be in a cluster. There would be registered nurses, licensed practical nurses, nursing assistants, and unit clerks in the cluster. The cluster leader is chosen by the manager based on certain criteria and is trained for this specialized role. The concept of cluster management, criteria for choosing leaders, training for leaders, using cluster groups to solve quality improvement issues, and the learning process necessary for manager support are described.

  5. X-ray cavities in a sample of 83 SPT-selected clusters of galaxies. Tracing the evolution of AGN feedback in clusters of galaxies out to z = 1.2

    Energy Technology Data Exchange (ETDEWEB)

    Hlavacek-Larrondo, J.; McDonald, M.; Benson, B. A.; Forman, W. R.; Allen, S. W.; Bleem, L. E.; Ashby, M. L. N.; Bocquet, S.; Brodwin, M.; Dietrich, J. P.; Jones, C.; Liu, J.; Reichardt, C. L.; Saliwanchik, B. R.; Saro, A.; Schrabback, T.; Song, J.; Stalder, B.; Vikhlinin, A.; Zenteno, A.

    2015-05-18

    X-ray cavities are key tracers of mechanical (or radio mode) heating arising from the active galactic nuclei (AGNs) in brightest cluster galaxies (BCGs). We report on a survey for X-ray cavities in 83 massive, high-redshift ($0.4\\lt z\\lt 1.2$) clusters of galaxies selected by their Sunyaev-Zel'dovich signature in the South Pole Telescope data. Based on Chandra X-ray images, we find a total of six clusters having symmetric pairs of surface brightness depressions consistent with the picture of radio jets inflating X-ray cavities in the intracluster medium (ICM). The majority of these detections are of relatively low significance and require deeper follow-up data in order to be confirmed. Further, this search will miss small (<10 kpc) X-ray cavities that are unresolved by Chandra at high ($z\\gtrsim 0.5$) redshift. Despite these limitations, our results suggest that the power generated by AGN feedback in BCGs has remained unchanged for over half of the age of the universe ($\\gt 7$ Gyr at $z\\sim 0.8$). On average, the detected X-ray cavities have powers of $(0.8-5)\\times {{10}^{45}}\\ {\\rm erg}\\ {{{\\rm s}}^{-1}}$, enthalpies of $(3-6)\\times {{10}^{59}}\\ {\\rm erg}$, and radii of ~17 kpc. Integrating over 7 Gyr, we find that the supermassive black holes in BCGs may have accreted 108 to several ${{10}^{9}}\\;{{M}_{\\odot }}$ of material to power these outflows. This level of accretion indicates that significant supermassive black hole growth may occur not only at early times, in the quasar era, but at late times as well. We also find that X-ray cavities at high redshift may inject an excess heat of 0.1–1.0 keV per particle into the hot ICM above and beyond the energy needed to offset cooling. Although this result needs to be confirmed, we note that the magnitude of excess heating is similar to the energy needed to preheat clusters, break self-similarity, and explain the excess entropy in hot atmospheres.

  6. Primary prevention of childhood obesity through counselling sessions at Swedish child health centres : design, methods and baseline sample characteristics of the PRIMROSE cluster-randomised trial

    OpenAIRE

    Doring, Nora; Hansson, Lena M; Andersson, Elina Scheers; Bohman, Benjamin; Westin, Maria; Magnusson, Margaretha; Larsson, Christel; Sundblom, Elinor; Willmer, Mikaela; Blennow, Margareta; Heitmann, Berit L.; Forsberg, Lars; Wallin, Sanna; Tynelius, Per; Ghaderi, Ata

    2014-01-01

    Background Childhood obesity is a growing concern in Sweden. Children with overweight and obesity run a high risk of becoming obese as adults, and are likely to develop comorbidities. Despite the immense demand, there is still a lack of evidence-based comprehensive prevention programmes targeting pre-school children and their families in primary health care settings. The aims are to describe the design and methodology of the PRIMROSE cluster-randomised controlled trial, assess the relative va...

  7. The unique associations of sexual assault and intimate partner violence with PTSD symptom clusters in a traumatized substance-abusing sample.

    Science.gov (United States)

    Dworkin, Emily R; Mota, Natalie P; Schumacher, Julie A; Vinci, Christine; Coffey, Scott F

    2017-07-01

    There is a high occurrence of sexual assault (SA) and intimate partner violence (IPV) among people with substance use disorders and an established association between substance use and posttraumatic stress disorder (PTSD), but no research has examined associations between combinations of these traumas and PTSD symptom profiles among people who abuse substances. Thus, this study aimed to examine how combinations of SA and IPV histories contribute to the severity of symptoms within PTSD symptom clusters above and beyond the impact of exposure to other traumas in a substance abusing population. Participants were men and women (N = 219) with trauma histories seeking treatment in a substance abuse facility. Multivariate analyses of covariance examined differences on Clinician Administrated PTSD Scale cluster scores in people with experiences of SA and/or IPV in comparison to people with other types of trauma, controlling for number of PTSD criterion A events. SA was associated with increased symptom severity across all 3 PTSD symptom clusters, whereas IPV was not associated with differences in cluster scores. In addition, survivors of IPV had consistent levels of avoidance symptoms regardless of whether they had also experienced SA, but people who had not experienced IPV only evidenced increased avoidance symptoms when they had experienced SA. Follow-up analyses testing gender differences indicated that these findings were largely similar for men and women. SA should be assessed in people in substance use treatment settings to conceptualize their unique presentations of PTSD symptoms and inform treatment planning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. Use of a four-tiered graph to parse the factors leading to phenotypic clustering in bacteria: a case study based on samples from the Aletsch Glacier.

    Science.gov (United States)

    Svercel, Miroslav; Filippini, Manuela; Perony, Nicolas; Rossetti, Valentina; Bagheri, Homayoun C

    2013-01-01

    An understanding of bacterial diversity and evolution in any environment requires knowledge of phenotypic diversity. In this study, the underlying factors leading to phenotypic clustering were analyzed and interpreted using a novel approach based on a four-tiered graph. Bacterial isolates were organized into equivalence classes based on their phenotypic profile. Likewise, phenotypes were organized in equivalence classes based on the bacteria that manifest them. The linking of these equivalence classes in a four-tiered graph allowed for a quick visual identification of the phenotypic measurements leading to the clustering patterns deduced from principal component analyses. For evaluation of the method, we investigated phenotypic variation in enzyme production and carbon assimilation of members of the genera Pseudomonas and Serratia, isolated from the Aletsch Glacier in Switzerland. The analysis indicates that the genera isolated produce at least six common enzymes and can exploit a wide range of carbon resources, though some specialist species within the pseudomonads were also observed. We further found that pairwise distances between enzyme profiles strongly correlate with distances based on carbon profiles. However, phenotypic distances weakly correlate with phylogenetic distances. The method developed in this study facilitates a more comprehensive understanding of phenotypic clustering than what would be deduced from principal component analysis alone.

  9. Use of a four-tiered graph to parse the factors leading to phenotypic clustering in bacteria: a case study based on samples from the Aletsch Glacier.

    Directory of Open Access Journals (Sweden)

    Miroslav Svercel

    Full Text Available An understanding of bacterial diversity and evolution in any environment requires knowledge of phenotypic diversity. In this study, the underlying factors leading to phenotypic clustering were analyzed and interpreted using a novel approach based on a four-tiered graph. Bacterial isolates were organized into equivalence classes based on their phenotypic profile. Likewise, phenotypes were organized in equivalence classes based on the bacteria that manifest them. The linking of these equivalence classes in a four-tiered graph allowed for a quick visual identification of the phenotypic measurements leading to the clustering patterns deduced from principal component analyses. For evaluation of the method, we investigated phenotypic variation in enzyme production and carbon assimilation of members of the genera Pseudomonas and Serratia, isolated from the Aletsch Glacier in Switzerland. The analysis indicates that the genera isolated produce at least six common enzymes and can exploit a wide range of carbon resources, though some specialist species within the pseudomonads were also observed. We further found that pairwise distances between enzyme profiles strongly correlate with distances based on carbon profiles. However, phenotypic distances weakly correlate with phylogenetic distances. The method developed in this study facilitates a more comprehensive understanding of phenotypic clustering than what would be deduced from principal component analysis alone.

  10. Cluster Headache

    Science.gov (United States)

    ... re at risk of cluster headache. A family history. Having a parent or sibling who has had cluster headache might increase your risk. By Mayo Clinic Staff . Mayo Clinic Footer Legal Conditions and Terms ...

  11. Cluster Headache

    OpenAIRE

    Bergseng, Marta Næss

    1985-01-01

    Cluster headache is the most severe primary headache with recurrent pain attacks described as worse than giving birth. The aim of this paper was to make an overview of current knowledge on cluster headache with a focus on pathophysiology and treatment. This paper presents hypotheses of cluster headache pathophysiology, current treatment options and possible future therapy approaches. For years, the hypothalamus was regarded as the key structure in cluster headache, but is now thought to be pa...

  12. Meaningful Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Calapristi, Augustin J.; Crow, Vernon L.; Hetzler, Elizabeth G.; Turner, Alan E.

    2004-05-26

    We present an approach to the disambiguation of cluster labels that capitalizes on the notion of semantic similarity to assign WordNet senses to cluster labels. The approach provides interesting insights on how document clustering can provide the basis for developing a novel approach to word sense disambiguation.

  13. About the Clusters Program

    Science.gov (United States)

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

  14. Maternal and fetal genetic contributions to postterm birth: familial clustering in a population-based sample of 475,429 Swedish births.

    Science.gov (United States)

    Oberg, Anna S; Frisell, Thomas; Svensson, Anna C; Iliadou, Anastasia N

    2013-03-15

    This study examines the familial clustering and relative influence of genetic and environmental effects on postterm birth in the Swedish population by considering all full- and half-siblings born in Sweden between 1992 and 2004. Of the eligible 475,429 births, 21% occurred after 41 completed weeks and 5.5% occurred after 42 completed weeks of gestation. Odds of postterm birth increased if mothers were older, heavier, more educated, primiparous, or carrying a male fetus. The highest odds increase was seen in women with a previous postterm birth, both with the same partner (odds ratio = 4.4, 95% confidence interval: 4.0, 4.6) and after a partner change (odds ratio = 3.4, 95% confidence interval: 2.9, 3.9). Sisters of women with a postterm birth were also at increased odds of postterm birth (odds ratio = 1.8, 95% confidence interval: 1.6, 2.0) while brothers' partners were not. Half of the variation in postterm birth could not be explained by factors shared in families, and the remaining half was explained by genetic factors, namely fetal (26%) and maternal (21%) genetic factors. Familial clustering of postterm birth is attributed to genetic effects, and fetal genetic effects have a considerable influence on the liability of postterm birth.

  15. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

    On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

  16. Affinity Propagation Clustering Using Path Based Similarity

    OpenAIRE

    Yuan Jiang; Yuliang Liao; Guoxian Yu

    2016-01-01

    Clustering is a fundamental task in data mining. Affinity propagation clustering (APC) is an effective and efficient clustering technique that has been applied in various domains. APC iteratively propagates information between affinity samples, updates the responsibility matrix and availability matrix, and employs these matrices to choose cluster centers (or exemplars) of respective clusters. However, since it mainly uses negative Euclidean distance between exemplars and samples as the simila...

  17. An Abecedary of Sampling.

    Science.gov (United States)

    Doyle, Kenneth O., Jr.

    1979-01-01

    The vocabulary of sampling is examined in order to provide a clear understanding of basic sampling concepts. The basic vocabulary of sampling (population, probability sampling, precision and bias, stratification), the fundamental grammar of sampling (random sample), sample size and response rate, and cluster, multiphase, snowball, and panel…

  18. Analysis of Sunyaev-Zel'dovich effect mass-observable relations using South Pole Telescope observations of an X-ray selected sample of low-mass galaxy clusters and groups

    Energy Technology Data Exchange (ETDEWEB)

    Liu, J.; Mohr, J.; Saro, A.; Aird, K. A.; Ashby, M. L. N.; Bautz, M.; Bayliss, M.; Benson, B. A.; Bleem, L. E.; Bocquet, S.; Brodwin, M.; Carlstrom, J. E.; Chang, C. L.; Chiu, I.; Cho, H. M.; Clocchiatti, A.; Crawford, T. M.; Crites, A. T.; de Haan, T.; Desai, S.; Dietrich, J. P.; Dobbs, M. A.; Foley, R. J.; Gangkofner, D.; George, E. M.; Gladders, M. D.; Gonzalez, A. H.; Halverson, N. W.; Hennig, C.; Hlavacek-Larrondo, J.; Holder, G. P.; Holzapfel, W. L.; Hrubes, J. D.; Jones, C.; Keisler, R.; Lee, A. T.; Leitch, E. M.; Lueker, M.; Luong-Van, D.; McDonald, M.; McMahon, J. J.; Meyer, S. S.; Mocanu, L.; Murray, S. S.; Padin, S.; Pryke, C.; Reichardt, C. L.; Rest, A.; Ruel, J.; Ruhl, J. E.; Saliwanchik, B. R.; Sayre, J. T.; Schaffer, K. K.; Shirokoff, E.; Spieler, H. G.; Stalder, B.; Staniszewski, Z.; Stark, A. A.; Story, K.;  uhada, R.; Vanderlinde, K.; Vieira, J. D.; Vikhlinin, A.; Williamson, R.; Zahn, O.; Zenteno, A.

    2015-02-25

    We use microwave observations from the South Pole Telescope (SPT) to examine the Sunyaev–Zel'dovich effect (SZE) signatures of a sample of 46 X-ray selected groups and clusters drawn from ~6 deg2 of the XMM–Newton Blanco Cosmology Survey. These systems extend to redshift z = 1.02 and probe the SZE signal to the lowest X-ray luminosities (≥1042 erg s-1) yet; these sample characteristics make this analysis complementary to previous studies. We develop an analysis tool, using X-ray luminosity as a mass proxy, to extract selection-bias-corrected constraints on the SZE significance and Y_500 mass relations. The former is in good agreement with an extrapolation of the relation obtained from high-mass clusters. However, the latter, at low masses, while in good agreement with the extrapolation from the high-mass SPT clusters, is in tension at 2.8σ with the Planck constraints, indicating the low-mass systems exhibit lower SZE signatures in the SPT data. We also present an analysis of potential sources of contamination. For the radio galaxy point source population, we find 18 of our systems have 843 MHz Sydney University Molonglo Sky Survey sources within 2 arcmin of the X-ray centre, and three of these are also detected at significance >4 by SPT. Of these three, two are associated with the group brightest cluster galaxies, and the third is likely an unassociated quasar candidate. We examine the impact of these point sources on our SZE scaling relation analyses and find no evidence of biases. We also examine the impact of dusty galaxies using constraints from the 220 GHz data. The stacked sample provides 2.8σ significant evidence of dusty galaxy flux, which would correspond to an average underestimate of the SPT Y_500 signal that is (17 ± 9)per cent in this sample of low-mass systems. Finally, we explore the impact of future data from SPTpol and XMM-XXL, showing that it will lead to a factor of 4 to 5 tighter

  19. Analysis of Sunyaev–Zel'dovich effect mass–observable relations using South Pole Telescope observations of an X-ray selected sample of low-mass galaxy clusters and groups

    Energy Technology Data Exchange (ETDEWEB)

    Liu, J.; Mohr, J.; Saro, A.; Aird, K. A.; Ashby, M. L. N.; Bautz, M.; Bayliss, M.; Benson, B. A.; Bleem, L. E.; Bocquet, S.; Brodwin, M.; Carlstrom, J. E.; Chang, C. L.; Chiu, I.; Cho, H. M.; Clocchiatti, A.; Crawford, T. M.; Crites, A. T.; de Haan, T.; Desai, S.; Dietrich, J. P.; Dobbs, M. A.; Foley, R. J.; Gangkofner, D.; George, E. M.; Gladders, M. D.; Gonzalez, A. H.; Halverson, N. W.; Hennig, C.; Hlavacek-Larrondo, J.; Holder, G. P.; Holzapfel, W. L.; Hrubes, J. D.; Jones, C.; Keisler, R.; Lee, A. T.; Leitch, E. M.; Lueker, M.; Luong-Van, D.; McDonald, M.; McMahon, J. J.; Meyer, S. S.; Mocanu, L.; Murray, S. S.; Padin, S.; Pryke, C.; Reichardt, C. L.; Rest, A.; Ruel, J.; Ruhl, J. E.; Saliwanchik, B. R.; Sayre, J. T.; Schaffer, K. K.; Shirokoff, E.; Spieler, H. G.; Stalder, B.; Staniszewski, Z.; Stark, A. A.; Story, K.; Šuhada, R.; Vanderlinde, K.; Vieira, J. D.; Vikhlinin, A.; Williamson, R.; Zahn, O.; Zenteno, A.

    2015-02-26

    We use microwave observations from the South Pole Telescope (SPT) to examine the Sunyaev-Zel'dovich effect (SZE) signatures of a sample of 46 X-ray selected groups and clusters drawn from similar to 6 deg(2) of the XMM-Newton Blanco Cosmology Survey. These systems extend to redshift z = 1.02 and probe the SZE signal to the lowest X-ray luminosities (>= 10(42) erg s(-1)) yet; these sample characteristics make this analysis complementary to previous studies. We develop an analysis tool, using X-ray luminosity as a mass proxy, to extract selection-bias-corrected constraints on the SZE significance and Y-500 mass relations. The former is in good agreement with an extrapolation of the relation obtained from high-mass clusters. However, the latter, at low masses, while in good agreement with the extrapolation from the high-mass SPT clusters, is in tension at 2.8 sigma with the Planck constraints, indicating the low-mass systems exhibit lower SZE signatures in the SPT data. We also present an analysis of potential sources of contamination. For the radio galaxy point source population, we find 18 of our systems have 843 MHz Sydney University Molonglo Sky Survey sources within 2 arcmin of the X-ray centre, and three of these are also detected at significance >4 by SPT. Of these three, two are associated with the group brightest cluster galaxies, and the third is likely an unassociated quasar candidate. We examine the impact of these point sources on our SZE scaling relation analyses and find no evidence of biases. We also examine the impact of dusty galaxies using constraints from the 220 GHz data. The stacked sample provides 2.8 sigma significant evidence of dusty galaxy flux, which would correspond to an average underestimate of the SPT Y-500 signal that is (17 +/- 9) per cent in this sample of low-mass systems. Finally, we explore the impact of future data from SPTpol and XMM-XXL, showing that it will lead to a factor of 4 to 5 tighter constraints on these SZE mass

  20. Galaxy cluster's rotation

    Science.gov (United States)

    Manolopoulou, M.; Plionis, M.

    2017-03-01

    We study the possible rotation of cluster galaxies, developing, testing, and applying a novel algorithm which identifies rotation, if such does exist, as well as its rotational centre, its axis orientation, rotational velocity amplitude, and, finally, the clockwise or counterclockwise direction of rotation on the plane of the sky. To validate our algorithms we construct realistic Monte Carlo mock rotating clusters and confirm that our method provides robust indications of rotation. We then apply our methodology on a sample of Abell clusters with z ≲ 0.1 with member galaxies selected from the Sloan Digital Sky Survey DR10 spectroscopic data base. After excluding a number of substructured clusters, which could provide erroneous indications of rotation, and taking into account the expected fraction of misidentified coherent substructure velocities for rotation, provided by our Monte Carlo simulation analysis, we find that ∼23 per cent of our clusters are rotating under a set of strict criteria. Loosening the strictness of the criteria, on the expense of introducing spurious rotation indications, we find this fraction increasing to ∼28 per cent. We correlate our rotation indicators with the cluster dynamical state, provided either by their Bautz-Morgan type or by their X-ray isophotal shape and find for those clusters showing rotation within 1.5 h^{-1}_{70} Mpc that the significance of their rotation is related to the dynamically younger phases of cluster formation but after the initial anisotropic accretion and merging has been completed. Finally, finding rotational modes in galaxy clusters could lead to the necessity of correcting the dynamical cluster mass calculations.

  1. Approximation Clustering

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Approximation Clustering. Clustering within (1+ ε) of the optimum cost. ε is user defined tolerance. For metric spaces even approximating is. hard (below, say 30%). Euclidean k-median in fixed dimension can. be approximated in polynomial time.

  2. Simultaneous determination of 19 flavonoids in commercial trollflowers by using high-performance liquid chromatography and classification of samples by hierarchical clustering analysis.

    Science.gov (United States)

    Song, Zhiling; Hashi, Yuki; Sun, Hongyang; Liang, Yi; Lan, Yuexiang; Wang, Hong; Chen, Shizhong

    2013-12-01

    The flowers of Trollius species, named Jin Lianhua in Chinese, are widely used traditional Chinese herbs with vital biological activity that has been used for several decades in China to treat upper respiratory infections, pharyngitis, tonsillitis, and bronchitis. We developed a rapid and reliable method for simultaneous quantitative analysis of 19 flavonoids in trollflowers by using high-performance liquid chromatography (HPLC). Chromatography was performed on Inertsil ODS-3 C18 column, with gradient elution methanol-acetonitrile-water with 0.02% (v/v) formic acid. Content determination was used to evaluate the quality of commercial trollflowers from different regions in China, while three Trollius species (Trollius chinensis Bunge, Trollius ledebouri Reichb, Trollius buddae Schipcz) were explicitly distinguished by using hierarchical clustering analysis. The linearity, precision, accuracy, limit of detection, and limit of quantification were validated for the quantification method, which proved sensitive, accurate and reproducible indicating that the proposed approach was applicable for the routine analysis and quality control of trollflowers. © 2013.

  3. Cluster Matters

    DEFF Research Database (Denmark)

    Gulati, Mukesh; Lund-Thomsen, Peter; Suresh, Sangeetha

    2018-01-01

    In this chapter, we investigate corporate social responsibility (CSR) in industrial clusters in the Indian context. We use the definition of CSR as given in the Indian Ministry of Corporate Affairs’ National Voluntary Guidelines (NVGs) for Business Responsibility: ‘the commitment of an enterprise...... sell their products successfully in international markets, but there is also an increasingly large consumer base within India. Indeed, Indian industrial clusters have contributed to a substantial part of this growth process, and there are several hundred registered clusters within the country....... At the same time, several attempts have been made at promoting the adoption of CSR in MSMEs in Indian industrial clusters. In fact, India has proved to be a kind of laboratory for experimenting with different types of cluster-based CSR and is thus an interesting location in relation to the broader aim...

  4. Clustering Dycom

    KAUST Repository

    Minku, Leandro L.

    2017-10-06

    Background: Software Effort Estimation (SEE) can be formulated as an online learning problem, where new projects are completed over time and may become available for training. In this scenario, a Cross-Company (CC) SEE approach called Dycom can drastically reduce the number of Within-Company (WC) projects needed for training, saving the high cost of collecting such training projects. However, Dycom relies on splitting CC projects into different subsets in order to create its CC models. Such splitting can have a significant impact on Dycom\\'s predictive performance. Aims: This paper investigates whether clustering methods can be used to help finding good CC splits for Dycom. Method: Dycom is extended to use clustering methods for creating the CC subsets. Three different clustering methods are investigated, namely Hierarchical Clustering, K-Means, and Expectation-Maximisation. Clustering Dycom is compared against the original Dycom with CC subsets of different sizes, based on four SEE databases. A baseline WC model is also included in the analysis. Results: Clustering Dycom with K-Means can potentially help to split the CC projects, managing to achieve similar or better predictive performance than Dycom. However, K-Means still requires the number of CC subsets to be pre-defined, and a poor choice can negatively affect predictive performance. EM enables Dycom to automatically set the number of CC subsets while still maintaining or improving predictive performance with respect to the baseline WC model. Clustering Dycom with Hierarchical Clustering did not offer significant advantage in terms of predictive performance. Conclusion: Clustering methods can be an effective way to automatically generate Dycom\\'s CC subsets.

  5. Cluster analysis

    CERN Document Server

    Everitt, Brian S; Leese, Morven; Stahl, Daniel

    2011-01-01

    Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.Real life examples are used throughout to demons

  6. Cluster analysis of commercial samples of Bauhinia spp. using HPLC-UV/PDA and MCR-ALS/PCA without peak alignment procedure.

    Science.gov (United States)

    Ardila, Jorge Armando; Funari, Cristiano Soleo; Andrade, André Marques; Cavalheiro, Alberto José; Carneiro, Renato Lajarim

    2015-01-01

    Bauhinia forficata Link. is recognised by the Brazilian Health Ministry as a treatment of hypoglycemia and diabetes. Analytical methods are useful to assess the plant identity due the similarities found in plants from Bauhinia spp. HPLC-UV/PDA in combination with chemometric tools is an alternative widely used and suitable for authentication of plant material, however, the shifts of retention times for similar compounds in different samples is a problem. To perform comparisons between the authentic medicinal plant (Bauhinia forficata Link.) and samples commercially available in drugstores claiming to be "Bauhinia spp. to treat diabetes" and to evaluate the performance of multivariate curve resolution - alternating least squares (MCR-ALS) associated to principal component analysis (PCA) when compared to pure PCA. HPLC-UV/PDA data obtained from extracts of leaves were evaluated employing a combination of MCR-ALS and PCA, which allowed the use of the full chromatographic and spectrometric information without the need of peak alignment procedures. The use of MCR-ALS/PCA showed better results than the conventional PCA using only one wavelength. Only two of nine commercial samples presented characteristics similar to the authentic Bauhinia forficata spp., considering the full HPLC-UV/PDA data. The combination of MCR-ALS and PCA is very useful when applied to a group of samples where a general alignment procedure could not be applied due to the different chromatographic profiles. This work also demonstrates the need of more strict control from the health authorities regarding herbal products available on the market. Copyright © 2015 John Wiley & Sons, Ltd.

  7. Primary prevention of childhood obesity through counselling sessions at Swedish child health centres: design, methods and baseline sample characteristics of the PRIMROSE cluster-randomised trial.

    Science.gov (United States)

    Döring, Nora; Hansson, Lena M; Andersson, Elina Scheers; Bohman, Benjamin; Westin, Maria; Magnusson, Margaretha; Larsson, Christel; Sundblom, Elinor; Willmer, Mikaela; Blennow, Margareta; Heitmann, Berit L; Forsberg, Lars; Wallin, Sanna; Tynelius, Per; Ghaderi, Ata; Rasmussen, Finn

    2014-04-09

    Childhood obesity is a growing concern in Sweden. Children with overweight and obesity run a high risk of becoming obese as adults, and are likely to develop comorbidities. Despite the immense demand, there is still a lack of evidence-based comprehensive prevention programmes targeting pre-school children and their families in primary health care settings. The aims are to describe the design and methodology of the PRIMROSE cluster-randomised controlled trial, assess the relative validity of a food frequency questionnaire, and describe the baseline characteristics of the eligible young children and their mothers. The PRIMROSE trial targets first-time parents and their children at Swedish child health centres (CHC) in eight counties in Sweden. Randomisation is conducted at the CHC unit level. CHC nurses employed at the participating CHC received training in carrying out the intervention alongside their provision of regular services. The intervention programme, starting when the child is 8-9 months of age and ending at age 4, is based on social cognitive theory and employs motivational interviewing. Primary outcomes are children's body mass index and waist circumference at four years. Secondary outcomes are children's and mothers' eating habits (assessed by a food frequency questionnaire), and children's and mothers' physical activity (measured by accelerometer and a validated questionnaire), and mothers' body mass index and waist circumference. The on-going population-based PRIMROSE trial, which targets childhood obesity, is embedded in the regular national (routine) preventive child health services that are available free-of-charge to all young families in Sweden. Of the participants (n = 1369), 489 intervention and 550 control mothers (75.9%) responded to the validated physical activity and food frequency questionnaire at baseline (i.e., before the first intervention session, or, for children in the control group, before they reached 10 months of age). The

  8. Cluster editing

    DEFF Research Database (Denmark)

    Böcker, S.; Baumbach, Jan

    2013-01-01

    The Cluster Editing problem asks to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. Although the problem has been proven NP-complete several times, it has nevertheless attracted much research both from the theoretical and the applied side. The prob......The Cluster Editing problem asks to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. Although the problem has been proven NP-complete several times, it has nevertheless attracted much research both from the theoretical and the applied side....... The problem has been the inspiration for numerous algorithms in bioinformatics, aiming at clustering entities such as genes, proteins, phenotypes, or patients. In this paper, we review exact and heuristic methods that have been proposed for the Cluster Editing problem, and also applications...

  9. What Types of Pornography Do People Find Arousing and Do They Cluster? Assessing Types and Categories of Pornography in a Large-Scale Online Sample.

    Science.gov (United States)

    Hald, Gert Martin; Štulhofer, Aleksandar

    2016-09-01

    Previous research on exposure to different types of pornography has primarily relied on analyses of millions of search terms and histories or on user exposure patterns within a given time period rather than the self-reported frequency of consumption. Further, previous research has almost exclusively relied on theoretical or ad hoc overarching categorizations of different types of pornography, when investigating patterns of pornography exposure, rather than latent structure analyses of these exposure patterns. In contrast, using a large sample of 18- to 40-year-old heterosexual and nonheterosexual Croatian men and women, this study investigated the self-reported frequency of using 27 different types of pornography and statistically explored their latent structures. The results showed substantial differences in consumption patterns across gender and sexual orientation. However, latent structure analyses of the 27 different types of pornography assessed suggested that although several categories of consumption were gender and sexual orientation specific, common categories across the different types of pornography could be established. Based on this finding, a five-item scale was proposed to indicate the use of nonmainstream (paraphilic) pornographic content, as this type of pornography has often been targeted in previous research. To the best of our knowledge, no similar measurement tool has been proposed before.

  10. Bussines Clusters

    Directory of Open Access Journals (Sweden)

    Sarmiza Pencea

    2010-10-01

    Full Text Available Clusters are complex economic structures in which similar companies, their up-stream and down-stream business partners, universities, research institutes, educational units, various service providers, diverse private and public institutions concentrate geografically, striving to get economies of agglomeration and scale, to capitalize on the resulting spill over effects, to cut costs, to better harness resources, to exchange information and experience, to improve quality, innovation, skills and productivity. By somehow unexpectedly combining competition and cooperation, they form a new, sophisticated stage in the evolution of production structures in quest of higher efficiency. This paper forays into the world of clusters and clusterization, which seem to increasingly capture the interest of businesses, scholars and policy makers. It looks at what clusters are, how they arise, what are their specific features, what benefits and challenges they can generate for companies and for the regions in which they locate and if and how they should be fostered by industrial policy interventions. The conclusion is that clusters can be very important development triggers and therefore they should be encouraged and nurtured by adequate policy measures. They should not only be used as a regular policy tool, but be placed at the very center of the development strategies of emerging economies.

  11. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    The cluster theory attributed to Michael Porter has significantly influenced industrial policies in countries across Europe and North America since the beginning of the 1990s. Institutions such as the EU, OECD and the World Bank and governments in countries such as the UK, France, The Netherlands......, Portugal and New Zealand have adopted the concept. Public sector interventions that aim to support cluster development in industries most often focus upon economic policy goals such as enhanced employment and improved productivity, but rarely emphasise broader societal policy goals relating to e.......g. sustainability or quality of life. The purpose of this paper is to explore how and to what extent public sector interventions that aim at forcing cluster development in industries can support sustainable development as defined in the Brundtland tradition and more recently elaborated in such concepts as eco-industrialism...

  12. Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL

    National Research Council Canada - National Science Library

    Wang, Lili; Palmer, Andrew J; Cocker, Fiona; Sanderson, Kristy

    2017-01-01

    ...). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity...

  13. Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

    Directory of Open Access Journals (Sweden)

    Wenfen Liu

    2017-01-01

    Full Text Available Constrained spectral clustering (CSC method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely. In this paper, we propose a fast CSC algorithm via encoding landmark-based graph construction into a new CSC model and applying random sampling to decrease the data size after spectral embedding. Compared with the original model, the new algorithm has the similar results with the increase of its model size asymptotically; compared with the most efficient CSC algorithm known, the new algorithm runs faster and has a wider range of suitable data sets. Meanwhile, a scalable semisupervised cluster ensemble algorithm is also proposed via the combination of our fast CSC algorithm and dimensionality reduction with random projection in the process of spectral ensemble clustering. We demonstrate by presenting theoretical analysis and empirical results that the new cluster ensemble algorithm has advantages in terms of efficiency and effectiveness. Furthermore, the approximate preservation of random projection in clustering accuracy proved in the stage of consensus clustering is also suitable for the weighted k-means clustering and thus gives the theoretical guarantee to this special kind of k-means clustering where each point has its corresponding weight.

  14. Prevalence and Risk Factors of Overweight and Obesity among Children Aged 6-59 Months in Cameroon: A Multistage, Stratified Cluster Sampling Nationwide Survey.

    Science.gov (United States)

    Tchoubi, Sébastien; Sobngwi-Tambekou, Joëlle; Noubiap, Jean Jacques N; Asangbeh, Serra Lem; Nkoum, Benjamin Alexandre; Sobngwi, Eugene

    2015-01-01

    Childhood obesity is one of the most serious public health challenges of the 21st century. The prevalence of overweight and obesity among children (risk factors of overweight and obesity among children aged 6 months to 5 years in Cameroon in 2011. Four thousand five hundred and eighteen children (2205 boys and 2313 girls) aged between 6 to 59 months were sampled in the 2011 Demographic Health Survey (DHS) database. Body Mass Index (BMI) z-scores based on WHO 2006 reference population was chosen to estimate overweight (BMI z-score > 2) and obesity (BMI for age > 3). Regression analyses were performed to investigate risk factors of overweight/obesity. The prevalence of overweight and obesity was 8% (1.7% for obesity alone). Boys were more affected by overweight than girls with a prevalence of 9.7% and 6.4% respectively. The highest prevalence of overweight was observed in the Grassfield area (including people living in West and North-West regions) (15.3%). Factors that were independently associated with overweight and obesity included: having overweight mother (adjusted odds ratio (aOR) = 1.51; 95% CI 1.15 to 1.97) and obese mother (aOR = 2.19; 95% CI = 155 to 3.07), compared to having normal weight mother; high birth weight (aOR = 1.69; 95% CI 1.24 to 2.28) compared to normal birth weight; male gender (aOR = 1.56; 95% CI 1.24 to 1.95); low birth rank (aOR = 1.35; 95% CI 1.06 to 1.72); being aged between 13-24 months (aOR = 1.81; 95% CI = 1.21 to 2.66) and 25-36 months (aOR = 2.79; 95% CI 1.93 to 4.13) compared to being aged 45 to 49 months; living in the grassfield area (aOR = 2.65; 95% CI = 1.87 to 3.79) compared to living in Forest area. Muslim appeared as a protective factor (aOR = 0.67; 95% CI 0.46 to 0.95).compared to Christian religion. This study underlines a high prevalence of early childhood overweight with significant disparities between ecological areas of Cameroon. Risk factors of overweight included high maternal BMI, high birth weight, male gender, low

  15. Prevalence and Risk Factors of Overweight and Obesity among Children Aged 6–59 Months in Cameroon: A Multistage, Stratified Cluster Sampling Nationwide Survey

    Science.gov (United States)

    Tchoubi, Sébastien; Sobngwi-Tambekou, Joëlle; Noubiap, Jean Jacques N.; Asangbeh, Serra Lem; Nkoum, Benjamin Alexandre; Sobngwi, Eugene

    2015-01-01

    Background Childhood obesity is one of the most serious public health challenges of the 21st century. The prevalence of overweight and obesity among children (obesity among children aged 6 months to 5 years in Cameroon in 2011. Methods Four thousand five hundred and eighteen children (2205 boys and 2313 girls) aged between 6 to 59 months were sampled in the 2011 Demographic Health Survey (DHS) database. Body Mass Index (BMI) z-scores based on WHO 2006 reference population was chosen to estimate overweight (BMI z-score > 2) and obesity (BMI for age > 3). Regression analyses were performed to investigate risk factors of overweight/obesity. Results The prevalence of overweight and obesity was 8% (1.7% for obesity alone). Boys were more affected by overweight than girls with a prevalence of 9.7% and 6.4% respectively. The highest prevalence of overweight was observed in the Grassfield area (including people living in West and North-West regions) (15.3%). Factors that were independently associated with overweight and obesity included: having overweight mother (adjusted odds ratio (aOR) = 1.51; 95% CI 1.15 to 1.97) and obese mother (aOR = 2.19; 95% CI = 155 to 3.07), compared to having normal weight mother; high birth weight (aOR = 1.69; 95% CI 1.24 to 2.28) compared to normal birth weight; male gender (aOR = 1.56; 95% CI 1.24 to 1.95); low birth rank (aOR = 1.35; 95% CI 1.06 to 1.72); being aged between 13–24 months (aOR = 1.81; 95% CI = 1.21 to 2.66) and 25–36 months (aOR = 2.79; 95% CI 1.93 to 4.13) compared to being aged 45 to 49 months; living in the grassfield area (aOR = 2.65; 95% CI = 1.87 to 3.79) compared to living in Forest area. Muslim appeared as a protective factor (aOR = 0.67; 95% CI 0.46 to 0.95).compared to Christian religion. Conclusion This study underlines a high prevalence of early childhood overweight with significant disparities between ecological areas of Cameroon. Risk factors of overweight included high maternal BMI, high birth weight, male

  16. Fuzzy Clustering

    DEFF Research Database (Denmark)

    Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

    2000-01-01

    and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c...

  17. BOCCE, The Bologna Open Clusters Chemical Evolution Project: a large, homogeneous sample of Galactic open clusters. (Spanish Title: %t Proyecto BOCCE (The Bologna Open Clusters Chemical Evolution Project): una gran muestra homogénea de cúmulos abiertos galácticos)

    Science.gov (United States)

    Ahumada, A. V.; Bragaglia, A.; Tosi, M.; Marconi, G.

    The BOCCE project is a photometric and spectroscopic survey of Galactic open clusters (OCs), to be used as tracers of the properties and evolution of the Galactic disk. The main OCs parameters are derived in a precise and homogeneous way, and they will be used, for example, to determine the metallicity distribution in the Galactic disk and how it has evolved with time. We have presently data for about 40 OCs. We present here part of our last effort, concerning the photometric data obtained for NGC 2849.

  18. Intervene before leaving: clustered lot quality assurance sampling to monitor vaccination coverage at health district level before the end of a yellow fever and measles vaccination campaign in Sierra Leone in 2009.

    Science.gov (United States)

    Pezzoli, Lorenzo; Conteh, Ishata; Kamara, Wogba; Gacic-Dobo, Marta; Ronveaux, Olivier; Perea, William A; Lewis, Rosamund F

    2012-06-07

    In November 2009, Sierra Leone conducted a preventive yellow fever (YF) vaccination campaign targeting individuals aged nine months and older in six health districts. The campaign was integrated with a measles follow-up campaign throughout the country targeting children aged 9-59 months. For both campaigns, the operational objective was to reach 95% of the target population. During the campaign, we used clustered lot quality assurance sampling (C-LQAS) to identify areas of low coverage to recommend timely mop-up actions. We divided the country in 20 non-overlapping lots. Twelve lots were targeted by both vaccinations, while eight only by measles. In each lot, five clusters of ten eligible individuals were selected for each vaccine. The upper threshold (UT) was set at 90% and the lower threshold (LT) at 75%. A lot was rejected for low vaccination coverage if more than 7 unvaccinated individuals (not presenting vaccination card) were found. After the campaign, we plotted the C-LQAS results against the post-campaign coverage estimations to assess if early interventions were successful enough to increase coverage in the lots that were at the level of rejection before the end of the campaign. During the last two days of campaign, based on card-confirmed vaccination status, five lots out of 20 (25.0%) failed for having low measles vaccination coverage and three lots out of 12 (25.0%) for low YF coverage. In one district, estimated post-campaign vaccination coverage for both vaccines was still not significantly above the minimum acceptable level (LT = 75%) even after vaccination mop-up activities. C-LQAS during the vaccination campaign was informative to identify areas requiring mop-up activities to reach the coverage target prior to leaving the region. The only district where mop-up activities seemed to be unsuccessful might have had logistical difficulties that should be further investigated and resolved.

  19. Cluster Headache.

    Science.gov (United States)

    Salvesen

    1999-11-01

    The care of patients with cluster headache has at least two goals: 1) immediately abolishing an ongoing attack and 2) stopping or shortening a bout (a cluster period). The fierceness and the relative brevity of the attacks dictate the use of a fast-acting agent. There are probably three agents fulfilling these criteria: sumatriptan (by subcutaneous injection), oxygen (inhaled through a face mask), and ergotamines (by injection or, perhaps, sublingual tablets). An abundance of data from controlled studies as well as recent clinical experience probably favors sumatriptan as the most effective alternative, the most significant drawback being its high cost. Oxygen inhalation is free of side effects and may be effective but is inconvenient to use. Ergotamines in tablet form act less rapidly, and there are more contraindications to their use. In short-term prophylaxis, however, ergotamine may still be a drug of choice if the timing of the attacks allows planned use of the drug shortly before the attack. If the timing is more irregular, steroids may at least temporarily break a cycle (eg, prednisolone, 60 or 80 mg/d, gradually tapered to zero in 3 to 4 weeks). If more long-lasting prophylaxis is needed or expected, lithium carbonate, 900 mg/d, or verapamil, 360 mg/d, both have reasonable response rates. As for chronic cluster headache, lithium probably will still be the drug of choice. For a very limited group of patients with chronic cluster headache, surgery may be a last resort. The best surgical options are probably radiofrequency rhizotomy or microvascular decompression of the trigeminal nerve.

  20. Regional Innovation Clusters

    Data.gov (United States)

    Small Business Administration — The Regional Innovation Clusters serve a diverse group of sectors and geographies. Three of the initial pilot clusters, termed Advanced Defense Technology clusters,...

  1. Statistical significance for hierarchical clustering.

    Science.gov (United States)

    Kimes, Patrick K; Liu, Yufeng; Neil Hayes, David; Marron, James Stephen

    2017-09-01

    Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high-dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this article, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. © 2017, The International Biometric Society.

  2. A GMBCG Galaxy Cluster Catalog of 55,424 Rich Clusters from SDSS DR7

    Energy Technology Data Exchange (ETDEWEB)

    Hao, Jiangang; /Fermilab; McKay, Timothy A.; /Michigan U.; Koester, Benjamin P.; /Chicago U.; Rykoff, Eli S.; /UC, Santa Barbara /LBL, Berkeley; Rozo, Eduardo; /Chicago U.; Annis, James; /Fermilab; Wechsler, Risa H.; /SLAC; Evrard, August; /Michigan U.; Siegel, Seth R.; /Michigan U.; Becker, Matthew; /Chicago U.; Busha, Michael; /SLAC; Gerdes, David; /Michigan U.; Johnston, David E.; /Fermilab; Sheldon, Erin; /Brookhaven

    2011-08-22

    We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red sequence plus Brightest Cluster Galaxy (BCG) feature, which is unique for galaxy clusters and does not exist among field galaxies. Red sequence clustering in color space is detected using an Error Corrected Gaussian Mixture Model. We run GMBCG on 8240 square degrees of photometric data from SDSS DR7 to assemble the largest ever optical galaxy cluster catalog, consisting of over 55,000 rich clusters across the redshift range from 0.1 < z < 0.55. We present Monte Carlo tests of completeness and purity and perform cross-matching with X-ray clusters and with the maxBCG sample at low redshift. These tests indicate high completeness and purity across the full redshift range for clusters with 15 or more members.

  3. A GMBCG galaxy cluster catalog of 55,880 rich clusters from SDSS DR7

    Energy Technology Data Exchange (ETDEWEB)

    Hao, Jiangang; McKay, Timothy A.; Koester, Benjamin P.; Rykoff, Eli S.; Rozo, Eduardo; Annis, James; Wechsler, Risa H.; Evrard, August; Siegel, Seth R.; Becker, Matthew; Busha, Michael; /Fermilab /Michigan U. /Chicago U., Astron. Astrophys. Ctr. /UC, Santa Barbara /KICP, Chicago /KIPAC, Menlo Park /SLAC /Caltech /Brookhaven

    2010-08-01

    We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red sequence plus Brightest Cluster Galaxy (BCG) feature, which is unique for galaxy clusters and does not exist among field galaxies. Red sequence clustering in color space is detected using an Error Corrected Gaussian Mixture Model. We run GMBCG on 8240 square degrees of photometric data from SDSS DR7 to assemble the largest ever optical galaxy cluster catalog, consisting of over 55,000 rich clusters across the redshift range from 0.1 < z < 0.55. We present Monte Carlo tests of completeness and purity and perform cross-matching with X-ray clusters and with the maxBCG sample at low redshift. These tests indicate high completeness and purity across the full redshift range for clusters with 15 or more members.

  4. Modern survey sampling

    CERN Document Server

    Chaudhuri, Arijit

    2014-01-01

    Exposure to SamplingAbstract Introduction Concepts of Population, Sample, and SamplingInitial RamificationsAbstract Introduction Sampling Design, Sampling SchemeRandom Numbers and Their Uses in Simple RandomSampling (SRS)Drawing Simple Random Samples with and withoutReplacementEstimation of Mean, Total, Ratio of Totals/Means:Variance and Variance EstimationDetermination of Sample SizesA.2 Appendix to Chapter 2 A.More on Equal Probability Sampling A.Horvitz-Thompson EstimatorA.SufficiencyA.LikelihoodA.Non-Existence Theorem More Intricacies Abstract Introduction Unequal Probability Sampling StrategiesPPS Sampling Exploring Improved WaysAbstract Introduction Stratified Sampling Cluster SamplingMulti-Stage SamplingMulti-Phase Sampling: Ratio and RegressionEstimationviiviii ContentsControlled SamplingModeling Introduction Super-Population ModelingPrediction Approach Model-Assisted Approach Bayesian Methods Spatial SmoothingSampling on Successive Occasions: Panel Rotation Non-Response and Not-at-Homes Weighting Adj...

  5. Agrupamento em amostras de sementes de espécies florestais nativas do Estado do Rio Grande do Sul - Brasil Cluster in seeds samples of native forest species from the State of Rio Grande do Sul - Brazil

    Directory of Open Access Journals (Sweden)

    Fabiano de Oliveira Fortes

    2008-09-01

    Full Text Available Este trabalho teve como objetivos agrupar por espécie as matrizes de porta-sementes mais similares, utilizando as variáveis observadas em análises de sementes de espécies florestais nativas no Centro de Pesquisas Florestais e Conservação do Solo, Santa Maria, Rio Grande do Sul, analisadas a partir de 1997 até março de 2001. Para a análise de agrupamento, foram utilizadas todas as espécies que possuíam quatro ou mais análises de amostras de sementes por lote coletado, pelo método de agrupamento aglomerativo hierárquico tendo a distância euclidiana média padronizada como medida de similaridade. O dendograma foi construído utilizando o método da ligação completa. Utilizou-se também a técnica de componentes principais para a redução do número de variáveis. O gênero Schinus sp. e as espécies nativas Cassia leptophylla Vogel, Peltophorum dubium (Spreng. Taub., Cedrela fissilis Vell., Allophylus edulis (A. St.-Hil., Cambess. & A. Juss. Radlk., Lafoensia pacari A. St.-Hil., Enterolobium contortisiliquum (Vell. Morong. e Apuleia leiocarpa (Vogel J. F. Macbr. foram as espécies em que, no terceiro e quarto componentes principais, conseguiram explicar aproximadamente 80% da variação existente no conjunto de dados com a umidade e a percentagem de germinação de plântulas anormais, sendo eliminadas na maioria das espécies e as percentagem de germinação de plântulas normais e de sementes mortas presentes em todos os grupos. A análise de agrupamento mostrou-se eficiente na separação dos grupos de todas as espécies testadas sendo que a procedência pouco influenciou na formação dos grupos.This research had the objectives of clustering, the most similar seeds matrixes by species, using the observed variables in analysis of seed samples of native forest species in the Center of Forest Researches and Conservation of the Soil, Santa Maria, Rio Grande do Sul, since 1997 up to March 2001. For the cluster analysis, all the

  6. The Vermont Diabetes Information System (VDIS): Study Design and Subject Recruitment for a Cluster Randomized Trial of a Decision Support System in a Regional Sample of Primary Care Practices

    Science.gov (United States)

    MacLean, Charles D.; Littenberg, Benjamin; Gagnon, Michael; Reardon, Mimi; Turner, Paul D.; Jordan, Cy

    2008-01-01

    Background Despite evidence that optimal care for diabetes can result in reduced complications and improved economic outcomes, such care is often not achieved. The Vermont Diabetes Information System (VDIS) is a registry-based decision support and reminder system based on the Chronic Care Model and targeted to primary care physicians and their patients with diabetes. Purpose To develop and evaluate a regional decision support system for patients with diabetes. Methods Randomized trial of an information system with clustering at the practice level. Ten percent random sub sample of patients selected for a home interview. Subject and setting includes 10 hospitals, 121 primary care providers, and 7,348 patients in 55 Vermont and New York primary care practices. Results We report on the study design and baseline characteristics of the population. Patients have a mean age of 63 years and a mean glycosolated hemoglobin A1C of 7.1%. Sixty percent of the population has excellent glycemic control (A1C<7%); 45% have excellent lipid control (serum LDL-cholesterol < 100mg/dl and serum triglycerides < 400mg/dl). Twenty-five percent have excellent blood pressure control (<130/80 mm Hg). These results compare favorably to recent national reports. However, only 8% are in optimal control for all three of hyperglycemia, lipids and blood pressure. Conclusions Our experience to date indicates that a low cost decision support and information system based on the chronic care model is feasible in primary care practices that lack sophisticated electronic information systems. VDIS is well accepted by patients, providers, and laboratory staff. If proven beneficial in a rigorous, randomized, controlled evaluation, the intervention could be widely disseminated to practices across America and the world with a substantial impact on the outcomes and costs of diabetes. It could also be adapted to other chronic conditions. We anticipate the results of the study will be available in 2006. PMID

  7. Heavy hitters via cluster-preserving clustering

    DEFF Research Database (Denmark)

    Larsen, Kasper Green; Nelson, Jelani; Nguyen, Huy L.

    2016-01-01

    , providing correctness whp. In fact, a simpler version of our algorithm for p = 1 in the strict turnstile model answers queries even faster than the "dyadic trick" by roughly a log n factor, dominating it in all regards. Our main innovation is an efficient reduction from the heavy hitters to a clustering...... problem in which each heavy hitter is encoded as some form of noisy spectral cluster in a much bigger graph, and the goal is to identify every cluster. Since every heavy hitter must be found, correctness requires that every cluster be found. We thus need a "cluster-preserving clustering" algorithm......, that partitions the graph into clusters with the promise of not destroying any original cluster. To do this we first apply standard spectral graph partitioning, and then we use some novel combinatorial techniques to modify the cuts obtained so as to make sure that the original clusters are sufficiently preserved...

  8. Binary systems from quantum cluster equilibrium theory.

    Science.gov (United States)

    Brüssel, Marc; Perlt, Eva; Lehmann, Sebastian B C; von Domaros, Michael; Kirchner, Barbara

    2011-11-21

    An extension of the quantum cluster equilibrium theory to treat binary mixtures is introduced in this work. The necessary equations are derived and a possible implementation is presented. In addition an alternative sampling procedure using widely available experimental data for the quantum cluster equilibrium approach is suggested and tested. An illustrative example, namely, the binary mixture of water and dimethyl sulfoxide, is given to demonstrate the new approach. A basic cluster set is introduced containing the relevant cluster motifs. The populations computed by the quantum cluster equilibrium approach are compared to the experimental data. Furthermore, the excess Gibbs free energy is computed and compared to experiments as well.

  9. Mutation Clusters from Cancer Exome.

    Science.gov (United States)

    Kakushadze, Zura; Yu, Willie

    2017-08-15

    We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit a mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally-costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics, such as novel blood-test methods currently in development.

  10. Cluster headache

    Directory of Open Access Journals (Sweden)

    Ducros Anne

    2008-07-01

    Full Text Available Abstract Cluster headache (CH is a primary headache disease characterized by recurrent short-lasting attacks (15 to 180 minutes of excruciating unilateral periorbital pain accompanied by ipsilateral autonomic signs (lacrimation, nasal congestion, ptosis, miosis, lid edema, redness of the eye. It affects young adults, predominantly males. Prevalence is estimated at 0.5–1.0/1,000. CH has a circannual and circadian periodicity, attacks being clustered (hence the name in bouts that can occur during specific months of the year. Alcohol is the only dietary trigger of CH, strong odors (mainly solvents and cigarette smoke and napping may also trigger CH attacks. During bouts, attacks may happen at precise hours, especially during the night. During the attacks, patients tend to be restless. CH may be episodic or chronic, depending on the presence of remission periods. CH is associated with trigeminovascular activation and neuroendocrine and vegetative disturbances, however, the precise cautive mechanisms remain unknown. Involvement of the hypothalamus (a structure regulating endocrine function and sleep-wake rhythms has been confirmed, explaining, at least in part, the cyclic aspects of CH. The disease is familial in about 10% of cases. Genetic factors play a role in CH susceptibility, and a causative role has been suggested for the hypocretin receptor gene. Diagnosis is clinical. Differential diagnoses include other primary headache diseases such as migraine, paroxysmal hemicrania and SUNCT syndrome. At present, there is no curative treatment. There are efficient treatments to shorten the painful attacks (acute treatments and to reduce the number of daily attacks (prophylactic treatments. Acute treatment is based on subcutaneous administration of sumatriptan and high-flow oxygen. Verapamil, lithium, methysergide, prednisone, greater occipital nerve blocks and topiramate may be used for prophylaxis. In refractory cases, deep-brain stimulation of the

  11. Affinity Propagation Clustering Using Path Based Similarity

    Directory of Open Access Journals (Sweden)

    Yuan Jiang

    2016-07-01

    Full Text Available Clustering is a fundamental task in data mining. Affinity propagation clustering (APC is an effective and efficient clustering technique that has been applied in various domains. APC iteratively propagates information between affinity samples, updates the responsibility matrix and availability matrix, and employs these matrices to choose cluster centers (or exemplars of respective clusters. However, since it mainly uses negative Euclidean distance between exemplars and samples as the similarity between them, it is difficult to identify clusters with complex structure. Therefore, the performance of APC deteriorates on samples distributed with complex structure. To mitigate this problem, we propose an improved APC based on a path-based similarity (APC-PS. APC-PS firstly utilizes negative Euclidean distance to find exemplars of clusters. Then, it employs the path-based similarity to measure the similarity between exemplars and samples, and to explore the underlying structure of clusters. Next, it assigns non-exemplar samples to their respective clusters via that similarity. Our empirical study on synthetic and UCI datasets shows that the proposed APC-PS significantly outperforms original APC and other related approaches.

  12. Star clusters and K2

    Science.gov (United States)

    Dotson, Jessie; Barentsen, Geert; Cody, Ann Marie

    2018-01-01

    The K2 survey has expanded the Kepler legacy by using the repurposed spacecraft to observe over 20 star clusters. The sample includes open and globular clusters at all ages, including very young (1-10 Myr, e.g. Taurus, Upper Sco, NGC 6530), moderately young (0.1-1 Gyr, e.g. M35, M44, Pleiades, Hyades), middle-aged (e.g. M67, Ruprecht 147, NGC 2158), and old globular clusters (e.g. M9, M19, Terzan 5). K2 observations of stellar clusters are exploring the rotation period-mass relationship to significantly lower masses than was previously possible, shedding light on the angular momentum budget and its dependence on mass and circumstellar disk properties, and illuminating the role of multiplicity in stellar angular momentum. Exoplanets discovered by K2 in stellar clusters provides planetary systems ripe for modeling given the extensive information available about their ages and environment. I will review the star clusters sampled by K2 across 16 fields so far, highlighting several characteristics, caveats, and unexplored uses of the public data set along the way. With fuel expected to run out in 2018, I will discuss the closing Campaigns, highlight the final target selection opportunities, and explain the data archive and TESS-compatible software tools the K2 mission intends to leave behind for posterity.

  13. Separating Interviewer and Sampling-Point Effects

    OpenAIRE

    Rainer Schnell; Frauke Kreuter

    2003-01-01

    "Data used in nationwide face-to-face surveys are almost always collected in multistage cluster samples. The relative homogeneity of the clusters selected in this way can lead to design effects at the sampling stage. Interviewers can further homogenize answers within the small geographic clusters that form the sampling points. The study presented here was designed to distinguish between interviewer effects and sampling-point effects using interpenetrated samples for conducting ...

  14. The UCD Population of the Coma Cluster

    Science.gov (United States)

    Chiboucas, Kristin; Ferguson, Peter; Tully, R. Brent; Carter, David; Phillipps, Steven; Peng, Eric

    2017-03-01

    UCDs are super massive star clusters found largely in dense regions but have also been found around individual galaxies and in smaller groups. Their origin is still under debate but consensus is that they formed either during major galaxy mergers as mergers of super massive star clusters, are simply the high mass end of the globular cluster luminosity function and formed in the same way as globular clusters, or that they formed from the threshing of galaxies and are remnant nuclear star clusters, which themselves may have formed from the mergers of globular star clusters within galaxies. We are attempting to disentangle these competing formation scenarios with a large survey of UCDs in the Coma cluster. Using ACS two-passband imaging from the HST/ACS Coma Cluster Treasury Survey, we are using colors and sizes to identify the UCD cluster members. With a large sample within the core region of the Coma cluster, we will use the population size, properties, and spatial distribution, and comparison with the Coma globular cluster and nuclear star cluster populations to discriminate between the threshing and globular cluster scenarios. In particular, previously we have found a possible correlation of UCD colors with host galaxy and a possible excess of UCDs around a non-central giant galaxy with an unusually large globular cluster population, both suggestive of a globular cluster origin. With a larger sample size, we are investigating whether the color correlation with host persists and whether the UCD population is consistent with, or in excess of, the bright end of the GCLF. We present initial results from the survey.

  15. Changing cluster composition in cluster randomised controlled trials: design and analysis considerations.

    Science.gov (United States)

    Corrigan, Neil; Bankart, Michael J G; Gray, Laura J; Smith, Karen L

    2014-05-24

    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.

  16. Partitional clustering algorithms

    CERN Document Server

    2015-01-01

    This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

  17. Multitask spectral clustering by exploring intertask correlation.

    Science.gov (United States)

    Yang, Yang; Ma, Zhigang; Yang, Yi; Nie, Feiping; Shen, Heng Tao

    2015-05-01

    Clustering, as one of the most classical research problems in pattern recognition and data mining, has been widely explored and applied to various applications. Due to the rapid evolution of data on the Web, more emerging challenges have been posed on traditional clustering techniques: 1) correlations among related clustering tasks and/or within individual task are not well captured; 2) the problem of clustering out-of-sample data is seldom considered; and 3) the discriminative property of cluster label matrix is not well explored. In this paper, we propose a novel clustering model, namely multitask spectral clustering (MTSC), to cope with the above challenges. Specifically, two types of correlations are well considered: 1) intertask clustering correlation, which refers the relations among different clustering tasks and 2) intratask learning correlation, which enables the processes of learning cluster labels and learning mapping function to reinforce each other. We incorporate a novel l2,p -norm regularizer to control the coherence of all the tasks based on an assumption that related tasks should share a common low-dimensional representation. Moreover, for each individual task, an explicit mapping function is simultaneously learnt for predicting cluster labels by mapping features to the cluster label matrix. Meanwhile, we show that the learning process can naturally incorporate discriminative information to further improve clustering performance. We explore and discuss the relationships between our proposed model and several representative clustering techniques, including spectral clustering, k -means and discriminative k -means. Extensive experiments on various real-world datasets illustrate the advantage of the proposed MTSC model compared to state-of-the-art clustering approaches.

  18. ConsensusCluster: a software tool for unsupervised cluster discovery in numerical data.

    Science.gov (United States)

    Seiler, Michael; Huang, C Chris; Szalma, Sandor; Bhanot, Gyan

    2010-02-01

    We have created a stand-alone software tool, ConsensusCluster, for the analysis of high-dimensional single nucleotide polymorphism (SNP) and gene expression microarray data. Our software implements the consensus clustering algorithm and principal component analysis to stratify the data into a given number of robust clusters. The robustness is achieved by combining clustering results from data and sample resampling as well as by averaging over various algorithms and parameter settings to achieve accurate, stable clustering results. We have implemented several different clustering algorithms in the software, including K-Means, Partition Around Medoids, Self-Organizing Map, and Hierarchical clustering methods. After clustering the data, ConsensusCluster generates a consensus matrix heatmap to give a useful visual representation of cluster membership, and automatically generates a log of selected features that distinguish each pair of clusters. ConsensusCluster gives more robust and more reliable clusters than common software packages and, therefore, is a powerful unsupervised learning tool that finds hidden patterns in data that might shed light on its biological interpretation. This software is free and available from http://code.google.com/p/consensus-cluster .

  19. THE EXTENDED VIRGO CLUSTER CATALOG

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Suk; Rey, Soo-Chang; Lee, Youngdae; Chung, Jiwon; Pak, Mina; Yi, Wonhyeong; Lee, Woong [Department of Astronomy and Space Science, Chungnam National University, 99 Daehak-ro, Daejeon 305-764 (Korea, Republic of); Jerjen, Helmut [Research School of Astronomy and Astrophysics, The Australian National University, Cotter Road, Weston, ACT 2611 (Australia); Lisker, Thorsten [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg (ZAH), Mönchhofstraße 12-14, D-69120 Heidelberg (Germany); Sung, Eon-Chang [Korea Astronomy and Space Science institute, 776 Daedeokdae-ro, Daejeon 305-348 (Korea, Republic of)

    2015-01-01

    We present a new catalog of galaxies in the wider region of the Virgo cluster, based on the Sloan Digital Sky Survey (SDSS) Data Release 7. The Extended Virgo Cluster Catalog (EVCC) covers an area of 725 deg{sup 2} or 60.1 Mpc{sup 2}. It is 5.2 times larger than the footprint of the classical Virgo Cluster Catalog (VCC) and reaches out to 3.5 times the virial radius of the Virgo cluster. We selected 1324 spectroscopically targeted galaxies with radial velocities less than 3000 km s{sup –1}. In addition, 265 galaxies that have been overlooked in the SDSS spectroscopic survey but have available redshifts in the NASA Extragalactic Database are also included. Our selection process secured a total of 1589 galaxies, 676 of which are not included in the VCC. The certain and possible cluster members are defined by means of redshift comparison with a cluster infall model. We employed two independent and complementary galaxy classification schemes: the traditional morphological classification based on the visual inspection of optical images and a characterization of galaxies from their spectroscopic features. SDSS u, g, r, i, and z passband photometry of all EVCC galaxies was performed using Source Extractor. We compare the EVCC galaxies with the VCC in terms of morphology, spatial distribution, and luminosity function. The EVCC defines a comprehensive galaxy sample covering a wider range in galaxy density that is significantly different from the inner region of the Virgo cluster. It will be the foundation for forthcoming galaxy evolution studies in the extended Virgo cluster region, complementing ongoing and planned Virgo cluster surveys at various wavelengths.

  20. Mixture model modal clustering

    OpenAIRE

    Chacón, José E.

    2016-01-01

    The two most extended density-based approaches to clustering are surely mixture model clustering and modal clustering. In the mixture model approach, the density is represented as a mixture and clusters are associated to the different mixture components. In modal clustering, clusters are understood as regions of high density separated from each other by zones of lower density, so that they are closely related to certain regions around the density modes. If the true density is indeed in the as...

  1. Unsupervised ensemble minority clustering

    OpenAIRE

    Gonzàlez Pellicer, Edgar; Turmo Borras, Jorge

    2012-01-01

    Cluster analysis lies at the core of most unsupervised learning tasks. However, the majority of clustering algorithms depend on the all-in assumption, in which all objects belong to some cluster, and perform poorly on minority clustering tasks, in which a small fraction of signal data stands against a majority of noise. The approaches proposed so far for minority clustering are supervised: they require the number and distribution of the foreground and background clusters. In supervised learni...

  2. Vacancy-indium clusters in implanted germanium

    KAUST Repository

    Chroneos, Alexander I.

    2010-04-01

    Secondary ion mass spectroscopy measurements of heavily indium doped germanium samples revealed that a significant proportion of the indium dose is immobile. Using electronic structure calculations we address the possibility of indium clustering with point defects by predicting the stability of indium-vacancy clusters, InnVm. We find that the formation of large clusters is energetically favorable, which can explain the immobility of the indium ions. © 2010 Elsevier B.V. All rights reserved.

  3. Featured Image: Globular Cluster Orbits

    Science.gov (United States)

    Kohler, Susanna

    2017-04-01

    This figure (click for the full view) shows the meridional galactic orbits of 12 globular clusters that orbit the Milky Way. The recent release of stellar parallax data from Gaia allowed a team of scientists at Dartmouth College to improve measurements of a number of galactic globular clusters very old clusters of stars that can either orbit within the galactic disk and bulge or more distantly in the galactic halo. In a recent publication led by Erin OMalley, the team presents their findings and combines their new measurements for the clusters with proper motions from past studies to calculate the orbits that these globulars take. These calculations show us whether the clusters reside in the galactic disk and bulge (as only NGC 104 does in the sample shown here, since its orbit is confined to 8 kpc radially and 4 kpc vertically of the galactic center), or if they are halo clusters. To learn more about the authors work, you can check out the paper below!CitationErin M. OMalley et al 2017 ApJ 838 162. doi:10.3847/1538-4357/aa6574

  4. Management of cluster headache

    DEFF Research Database (Denmark)

    Tfelt-Hansen, Peer C; Jensen, Rigmor H

    2012-01-01

    and agitation. Patients may have up to eight attacks per day. Episodic cluster headache (ECH) occurs in clusters of weeks to months duration, whereas chronic cluster headache (CCH) attacks occur for more than 1 year without remissions. Management of cluster headache is divided into acute attack treatment...

  5. Clustering of correlated networks

    OpenAIRE

    Dorogovtsev, S. N.

    2003-01-01

    We obtain the clustering coefficient, the degree-dependent local clustering, and the mean clustering of networks with arbitrary correlations between the degrees of the nearest-neighbor vertices. The resulting formulas allow one to determine the nature of the clustering of a network.

  6. Cluster knockout reactions

    Indian Academy of Sciences (India)

    2014-04-07

    Apr 7, 2014 ... 2 fm) N–N interaction enhances clustering in the low density surface region of the nuclei. Therefore, to study the clustering aspect of the nuclei, one has to have high projectile energies but has to choose kinematics which probes the low momentum component of the bound clusters. While the cluster pickup ...

  7. Cluster knockout reactions

    Indian Academy of Sciences (India)

    2014-04-07

    Apr 7, 2014 ... Cluster knockout reactions are expected to reveal the amount of clustering (such as that of , d and even of heavier clusters such as 12C, 16O etc.) in the target nucleus. In simple terms, incident medium high-energy nuclear projectile interacts strongly with the cluster (present in the target nucleus) as if it ...

  8. Spitzer Survey of the Karin Cluster Asteroids

    NARCIS (Netherlands)

    Harris, Alan W.; Mueller, M.; Lisse, C.; Cheng, A.; Osip, D.

    2007-01-01

    The Karin cluster is one of the youngest known families of main-belt asteroids, dating back to a collisional event only 5.8 Myr ago. Using the Spitzer Space Telescope we have sampled the thermal continua of 17 Karin cluster asteroids, down to the smallest members discovered so far, in order to

  9. Bayesian Cosmic Web Reconstruction: BARCODE for Clusters

    NARCIS (Netherlands)

    Patrick Bos, E. G.; van de Weygaert, Rien; Kitaura, Francisco; Cautun, Marius

    2016-01-01

    We describe the Bayesian \\barcode\\ formalism that has been designed towards the reconstruction of the Cosmic Web in a given volume on the basis of the sampled galaxy cluster distribution. Based on the realization that the massive compact clusters are responsible for the major share of the large

  10. Assembly bias and splashback in galaxy clusters

    Science.gov (United States)

    Busch, Philipp; White, Simon D. M.

    2017-10-01

    We use publicly available data for the Millennium Simulation to explore the implications of the recent detection of assembly bias and splashback signatures in a large sample of galaxy clusters. These were identified in the Sloan Digital Sky Survey/Data Release 8 (SDSS/DR8) photometric data by the redMaPPer algorithm and split into high- and low-concentration subsamples based on the projected positions of cluster members. We use simplified versions of these procedures to build cluster samples of similar size from the simulation data. These match the observed samples quite well and show similar assembly bias and splashback signals. Previous theoretical work has found the logarithmic slope of halo density profiles to have a well-defined minimum whose depth decreases and whose radius increases with halo concentration. Projected profiles for the observed and simulated cluster samples show trends with concentration which are opposite to these predictions. In addition, for high-concentration clusters the minimum slope occurs at significantly smaller radius than predicted. We show that these discrepancies all reflect confusion between splashback features and features imposed on the profiles by the cluster identification and concentration estimation procedures. The strong apparent assembly bias is not reflected in the three-dimensional distribution of matter around clusters. Rather it is a consequence of the preferential contamination of low-concentration clusters by foreground or background groups.

  11. Evolution of the K-band Galaxy Cluster Luminosity Function and Scaling Relations

    OpenAIRE

    Lin, Yen-Ting; Mohr, Joseph J.; Gonzalez, Anthony H.; Stanford, S Adam

    2006-01-01

    We study the evolution of two fundamental properties of galaxy clusters: the luminosity function (LF) and the scaling relations between the total galaxy number N (or luminosity) and cluster mass M. Using a sample of 27 clusters (0

  12. Clustering in analytical chemistry.

    Science.gov (United States)

    Drab, Klaudia; Daszykowski, Michal

    2014-01-01

    Data clustering plays an important role in the exploratory analysis of analytical data, and the use of clustering methods has been acknowledged in different fields of science. In this paper, principles of data clustering are presented with a direct focus on clustering of analytical data. The role of the clustering process in the analytical workflow is underlined, and its potential impact on the analytical workflow is emphasized.

  13. Measurement of cluster-cluster interaction in liquids by deposition and AFM of silicon clusters onto HOPG surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Galinis, Gediminas; Torricelli, Gauthier; Akraiam, Atea; Haeften, Klaus von, E-mail: kvh6@le.ac.uk [University of Leicester, Department of Physics and Astronomy (United Kingdom)

    2012-08-15

    We have investigated the interaction and aggregation of novel fluorescent silicon nanoclusters in liquids by measuring the size distribution of dried clusters on graphite. The clusters were produced by gas aggregation and co-deposition with a beam of water vapour. Drops of the solutions were placed on freshly cleaved highly oriented pyrolitic graphite, subsequently vacuum dried and investigated by atomic force microscopy (AFM) in ultra high vacuum. The AFM images show single clusters and agglomerates. The height distributions are Gaussian-shaped with average heights of 1 nm and widths of 1 nm. The heights never exceed 3 nm. In some regions a second cluster layer is observed. In all samples the separation between first and second layers is larger than the separation between the first layer and the graphite substrate, which we attribute to a stronger interaction between clusters and surface than the cluster self-interaction. We conclude that the separation between first and second layer represents a much better fingerprint of the original size distribution of the clusters in solution than the height of the first layer. The observation of a second cluster layer is important for using silicon clusters as building blocks for cluster-assembled materials.

  14. THE SWIFT AGN AND CLUSTER SURVEY. II. CLUSTER CONFIRMATION WITH SDSS DATA

    Energy Technology Data Exchange (ETDEWEB)

    Griffin, Rhiannon D.; Dai, Xinyu [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, OK 73019 (United States); Kochanek, Christopher S. [Department of Astronomy, Ohio State University, Columbus, OH 43210 (United States); Bregman, Joel N., E-mail: Rhiannon.D.Griffin-1@ou.edu, E-mail: xdai@ou.edu, E-mail: ckochanek@astronomy.ohio-state.edu, E-mail: jbregman@umich.edu [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States)

    2016-01-15

    We study 203 (of 442) Swift AGN and Cluster Survey extended X-ray sources located in the SDSS DR8 footprint to search for galaxy over-densities in three-dimensional space using SDSS galaxy photometric redshifts and positions near the Swift cluster candidates. We find 104 Swift clusters with a >3σ galaxy over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmation as galaxy clusters. We present a series of cluster properties including the redshift, brightest cluster galaxy (BCG) magnitude, BCG-to-X-ray center offset, optical richness, and X-ray luminosity. We also detect red sequences in ∼85% of the 104 confirmed clusters. The X-ray luminosity and optical richness for the SDSS confirmed Swift clusters are correlated and follow previously established relations. The distribution of the separations between the X-ray centroids and the most likely BCG is also consistent with expectation. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≲ 0.3 and is still 80% complete up to z ≃ 0.4, consistent with the SDSS survey depth. These analysis results suggest that our Swift cluster selection algorithm has yielded a statistically well-defined cluster sample for further study of cluster evolution and cosmology. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 23, and 1 matches in optical, X-ray, and Sunyaev–Zel’dovich catalogs, respectively, and so the majority of these clusters are new detections.

  15. Clustering of agricultural enterprises

    Directory of Open Access Journals (Sweden)

    Michaela Beranová

    2013-01-01

    Full Text Available Agricultural business is a very specific branch which is characterized by very low financial performance while this characteristic is given mainly by external factors as market pricing of agricultural commodities on one side, and production costs of agricultural commodities on the other side. This way, agricultural enterprises recognize negative values of gross margin in the Profit and Loss Statement but positive value of operating profit after even there are items of costs which are deducted. These results are derived from agricultural production subsidies which are recognized as income in the P/L Statement. In connection with this fact, the government subsidies are a substantial component of financial performance of agricultural enterprises.Primary research proceeded on the statistical sample of one hundred agricultural companies, has shown that also other specifics influencing financial performance of these businesses exist here. In order to determine the influences, the cluster analysis has been applied at using more than 10 variables. This approach has led to construction of clusters (groups of agricultural business entities with different characteristics of the group. The objective of this paper is to identify the main determinants of financial performance of agricultural enterprises and to determine their influences under different economic characteristics of these business entities. For this purpose, the regression analysis has been subsequently applied on the groups of companies coming out from the cluster analysis. Besides the operating profit which is the main driving force of financial performance measured with the economic value added (EVA in agricultural enterprises, also capital structure and cost of capital have been observed as very strong influences on financial performance but these factors have different directions of their influence on the economic value added under different financial characteristics of agricultural

  16. Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data.

    Science.gov (United States)

    Yu, Zhiwen; Chen, Hantao; You, Jane; Liu, Jiming; Wong, Hau-San; Han, Guoqiang; Li, Le

    2015-01-01

    Performing clustering analysis is one of the important research topics in cancer discovery using gene expression profiles, which is crucial in facilitating the successful diagnosis and treatment of cancer. While there are quite a number of research works which perform tumor clustering, few of them considers how to incorporate fuzzy theory together with an optimization process into a consensus clustering framework to improve the performance of clustering analysis. In this paper, we first propose a random double clustering based cluster ensemble framework (RDCCE) to perform tumor clustering based on gene expression data. Specifically, RDCCE generates a set of representative features using a randomly selected clustering algorithm in the ensemble, and then assigns samples to their corresponding clusters based on the grouping results. In addition, we also introduce the random double clustering based fuzzy cluster ensemble framework (RDCFCE), which is designed to improve the performance of RDCCE by integrating the newly proposed fuzzy extension model into the ensemble framework. RDCFCE adopts the normalized cut algorithm as the consensus function to summarize the fuzzy matrices generated by the fuzzy extension models, partition the consensus matrix, and obtain the final result. Finally, adaptive RDCFCE (A-RDCFCE) is proposed to optimize RDCFCE and improve the performance of RDCFCE further by adopting a self-evolutionary process (SEPP) for the parameter set. Experiments on real cancer gene expression profiles indicate that RDCFCE and A-RDCFCE works well on these data sets, and outperform most of the state-of-the-art tumor clustering algorithms.

  17. Search for High Redshift Galaxy Clusters

    Science.gov (United States)

    Haarsma, D. B.; Butler, A. R.; Donahue, M. E.; Bruch, S. S.

    2005-12-01

    Distant galaxy clusters are key to understanding many current questions in cosmology, structure formation, and galaxy evolution, yet few z>1 clusters have been identified. The ROSAT Optical X-ray Survey (Donahue et al. 2002 ApJ 569, 689) searched for galaxy clusters using both optical and x-ray detection methods. While many clusters appeared in both wavebands, 10 targets which showed extended x-ray emission (a unique signature of cluster gas) did not show significant I-band emission (expected from elliptical galaxies in the cluster). These targets may be galaxy clusters with redshift greater than 1, which would appear faint in I due to the 400 nm break in elliptical galaxy spectra. In J and K bands, such galaxies would be easier to detect, and in April 2005 we imaged the 10 fields in J and K with the FLAMINGOS camera on the NOAO 4m telescope. The infrared colors are useful in identifying clusters, because all elliptical galaxies in a cluster are expected to have similar colors (i.e. the red sequence). We report preliminary identifications of high redshift galaxy clusters in our sample.

  18. What Makes Clusters Decline?

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    2015-01-01

    Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark....... The longitudinal study on the high-tech cluster reveals that technological lock-in and exit of key firms have contributed to decline. Entrepreneurship has a positive effect on the cluster’s adaptive capabilities, while multinational companies have contradicting effects by bringing in new resources to the cluster...

  19. Comprehensive cluster analysis with Transitivity Clustering.

    Science.gov (United States)

    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.

  20. Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

    National Research Council Canada - National Science Library

    Wenfen Liu; Mao Ye; Jianghong Wei; Xuexian Hu

    2017-01-01

    Constrained spectral clustering (CSC) method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely...

  1. Clustering high dimensional data

    DEFF Research Database (Denmark)

    Assent, Ira

    2012-01-01

    High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...... groups objects that are similar to one another, whereas dissimilar objects are assigned to different clusters, possibly separating out noise. In this manner, clusters describe the data structure in an unsupervised manner, i.e., without the need for class labels. A number of clustering paradigms exist...

  2. Estimating Cosmological Parameters and Cluster Masses through Escape Velocity Measurements in Galaxy Clusters

    Science.gov (United States)

    Gifford, Daniel William

    2016-08-01

    Galaxy clusters are large virialized structures that exist at the intersection of filaments of matter that make up the cosmic web. Due to their hierarchical growth history, they are excellent probes of the cosmology that governs our universe. Here, we aim to use clusters to better constrain cosmological parameters by systematically studying the uncertainties on galaxy cluster mass estimation for use in a halo mass function analysis. We find that the caustic technique is capable on average of recovering unbiased cluster masses to within 30% for well sampled systems. We also quantify potential statistical and systematic biases due to observational challenges. To address statistical biases in the caustic technique, we developed a new stacking algorithm to measure the average cluster mass for a single stack of projected cluster phase-spaces. By varying the number of galaxies and number of clusters we stack, we find that the single limited value is the total number of galaxies in the stack opening up the possibility for self-calibrated mass estimates of low mass or poorly sampled clusters in large surveys. We then utilize the SDSS-C4 catalog of galaxy clusters to place some of the tightest galaxy cluster based constraints on the matter density and power spectrum normalization for matter in our universe.

  3. Cluster Physics with Merging Galaxy Clusters

    Directory of Open Access Journals (Sweden)

    Sandor M. Molnar

    2016-02-01

    Full Text Available 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 LCDM model, where the total density is dominated by the cosmological constant ($Lambda$ 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 turbulenceare 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, thusour review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clustersis 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 telescopeswill 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.

  4. Marketing research cluster analysis

    Directory of Open Access Journals (Sweden)

    Marić Nebojša

    2002-01-01

    Full Text Available One area of applications of cluster analysis in marketing is identification of groups of cities and towns with similar demographic profiles. This paper considers main aspects of cluster analysis by an example of clustering 12 cities with the use of Minitab software.

  5. The Durban Auto Cluster

    DEFF Research Database (Denmark)

    Lorentzen, Jochen; Robbins, Glen; Barnes, Justin

    2004-01-01

    The paper describes the formation of the Durban Auto Cluster in the context of trade liberalization. It argues that the improvement of operational competitiveness of firms in the cluster is prominently due to joint action. It tests this proposition by comparing the gains from cluster activities...

  6. Cosmology with cluster surveys

    Indian Academy of Sciences (India)

    Surveys of clusters of galaxies provide us with a powerful probe of the density and nature of the dark energy. The red-shift distribution of detected clusters is highly sensitive to the dark energy equation of state parameter . Upcoming Sunyaev–Zel'dovich (SZ) surveys would provide us large yields of clusters to very high ...

  7. Cosmology with cluster surveys

    Indian Academy of Sciences (India)

    Cosmology with cluster surveys. SUBHABRATA MAJUMDAR. CITA, University of Toronto, Toronto, ON, M5S 3H8, Canada. E-mail: subha@cita.utoronto.ca. Abstract. Surveys of clusters of galaxies provide us with a powerful probe of the den- sity and nature of the dark energy. The red-shift distribution of detected clusters is.

  8. Formation of stellar clusters

    Science.gov (United States)

    Smilgys, Romas; Bonnell, Ian A.

    2017-12-01

    We investigate the triggering of star formation and the formation of stellar clusters in molecular clouds which form as the interstellar medium passes through spiral shocks. The spiral shock compresses gas into an ∼100 pc long main star formation ridge, where clusters form every 5-10 pc along the merger ridge. We use a gravitational potential-based cluster finding algorithm, which extracts individual clusters, calculates their physical properties and traces cluster evolution over multiple time-steps. Final cluster masses at the end of simulation range between 1000 and 30 000 M⊙ with their characteristic half-mass radii between 0.1 and 2 pc. These clusters form by gathering material from 10-20 pc size scales. Clusters also show a mass-specific angular momentum relation, where more massive clusters have larger specific angular momentum due to the larger size scales, and hence angular momentum from which they gather their mass. The evolution shows that more massive clusters experience hierarchical merging process, which increases stellar age spreads up to 2-3 Myr. Less massive clusters appear to grow by gathering nearby recently formed sinks, while more massive clusters with their large global gravitational potentials are increasing their mass growth from gas accretion.

  9. Relational aspects of clusters

    DEFF Research Database (Denmark)

    Gjerding, Allan Næs

    The present paper is the first preliminary account of a project being planned for 2013, focussing on the development of the biomedico cluster in North Denmark. The project focusses on the relational capabilities of the cluster in terms of a number of organizational roles which are argued...... to be necessary for the development and growth of the upcoming cluster in question....

  10. Structures of Mn clusters

    Indian Academy of Sciences (India)

    Abstract. The geometries of several Mn clusters in the size range Mn13–Mn23 are studied via the generalized gradient approximation to density functional theory. For the 13- and 19-atom clusters, the icosahedral structures are found to be most stable, while for the 15-atom cluster, the bcc structure is more favoured.

  11. Structures of Mn clusters

    Indian Academy of Sciences (India)

    Unknown

    Abstract. The geometries of several Mn clusters in the size range Mn13–Mn23 are studied via the generalized gradient approximation to density functional theory. For the 13- and 19-atom clusters, the icosahedral struc- tures are found to be most stable, while for the 15-atom cluster, the bcc structure is more favoured.

  12. Quantum Monte Carlo methods and lithium cluster properties. [Atomic clusters

    Energy Technology Data Exchange (ETDEWEB)

    Owen, R.K.

    1990-12-01

    Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) (0.1981), 0.1895(9) (0.1874(4)), 0.1530(34) (0.1599(73)), 0.1664(37) (0.1724(110)), 0.1613(43) (0.1675(110)) Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) (0.0203(12)), 0.0188(10) (0.0220(21)), 0.0247(8) (0.0310(12)), 0.0253(8) (0.0351(8)) Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.

  13. The C4 clustering algorithm: Clusters of galaxies in the Sloan Digital Sky Survey

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Christopher J.; Nichol, Robert; Reichart, Dan; Wechsler, Risa H.; Evrard, August; Annis, James; McKay, Timothy; Bahcall, Neta; Bernardi, Mariangela; Boehringer,; Connolly, Andrew; Goto, Tomo; Kniazev, Alexie; Lamb, Donald; Postman, Marc; Schneider, Donald; Sheth, Ravi; Voges, Wolfgang; /Cerro-Tololo InterAmerican Obs. /Portsmouth U.,

    2005-03-01

    We present the ''C4 Cluster Catalog'', a new sample of 748 clusters of galaxies identified in the spectroscopic sample of the Second Data Release (DR2) of the Sloan Digital Sky Survey (SDSS). The C4 cluster-finding algorithm identifies clusters as overdensities in a seven-dimensional position and color space, thus minimizing projection effects that have plagued previous optical cluster selection. The present C4 catalog covers {approx}2600 square degrees of sky and ranges in redshift from z = 0.02 to z = 0.17. The mean cluster membership is 36 galaxies (with redshifts) brighter than r = 17.7, but the catalog includes a range of systems, from groups containing 10 members to massive clusters with over 200 cluster members with redshifts. The catalog provides a large number of measured cluster properties including sky location, mean redshift, galaxy membership, summed r-band optical luminosity (L{sub r}), velocity dispersion, as well as quantitative measures of substructure and the surrounding large-scale environment. We use new, multi-color mock SDSS galaxy catalogs, empirically constructed from the {Lambda}CDM Hubble Volume (HV) Sky Survey output, to investigate the sensitivity of the C4 catalog to the various algorithm parameters (detection threshold, choice of passbands and search aperture), as well as to quantify the purity and completeness of the C4 cluster catalog. These mock catalogs indicate that the C4 catalog is {approx_equal}90% complete and 95% pure above M{sub 200} = 1 x 10{sup 14} h{sup -1}M{sub {circle_dot}} and within 0.03 {le} z {le} 0.12. Using the SDSS DR2 data, we show that the C4 algorithm finds 98% of X-ray identified clusters and 90% of Abell clusters within 0.03 {le} z {le} 0.12. Using the mock galaxy catalogs and the full HV dark matter simulations, we show that the L{sub r} of a cluster is a more robust estimator of the halo mass (M{sub 200}) than the galaxy line-of-sight velocity dispersion or the richness of the cluster

  14. Superposition Enhanced Nested Sampling

    Science.gov (United States)

    Martiniani, Stefano; Stevenson, Jacob D.; Wales, David J.; Frenkel, Daan

    2014-07-01

    The theoretical analysis of many problems in physics, astronomy, and applied mathematics requires an efficient numerical exploration of multimodal parameter spaces that exhibit broken ergodicity. Monte Carlo methods are widely used to deal with these classes of problems, but such simulations suffer from a ubiquitous sampling problem: The probability of sampling a particular state is proportional to its entropic weight. Devising an algorithm capable of sampling efficiently the full phase space is a long-standing problem. Here, we report a new hybrid method for the exploration of multimodal parameter spaces exhibiting broken ergodicity. Superposition enhanced nested sampling combines the strengths of global optimization with the unbiased or athermal sampling of nested sampling, greatly enhancing its efficiency with no additional parameters. We report extensive tests of this new approach for atomic clusters that are known to have energy landscapes for which conventional sampling schemes suffer from broken ergodicity. We also introduce a novel parallelization algorithm for nested sampling.

  15. Superposition Enhanced Nested Sampling

    Directory of Open Access Journals (Sweden)

    Stefano Martiniani

    2014-08-01

    Full Text Available The theoretical analysis of many problems in physics, astronomy, and applied mathematics requires an efficient numerical exploration of multimodal parameter spaces that exhibit broken ergodicity. Monte Carlo methods are widely used to deal with these classes of problems, but such simulations suffer from a ubiquitous sampling problem: The probability of sampling a particular state is proportional to its entropic weight. Devising an algorithm capable of sampling efficiently the full phase space is a long-standing problem. Here, we report a new hybrid method for the exploration of multimodal parameter spaces exhibiting broken ergodicity. Superposition enhanced nested sampling combines the strengths of global optimization with the unbiased or athermal sampling of nested sampling, greatly enhancing its efficiency with no additional parameters. We report extensive tests of this new approach for atomic clusters that are known to have energy landscapes for which conventional sampling schemes suffer from broken ergodicity. We also introduce a novel parallelization algorithm for nested sampling.

  16. Clusters of Pneumocystis carinii pneumonia

    DEFF Research Database (Denmark)

    Helweg-Larsen, J; Tsolaki, A G; Miller, Raymonde

    1998-01-01

    Genotyping at the internal transcribed spacer (ITS) regions of the nuclear rRNA operon was performed on isolates of P. carinii sp. f. hominis from three clusters of P. carinii pneumonia among eight patients with haematological malignancies and six with HIV infection. Nine different ITS sequence...... types of P. carinii sp. f. hominis were identified in the samples from the patients with haematological malignancies, suggesting that this cluster of cases of P. carinii pneumonia was unlikely to have resulted from nosocomial transmission. A common ITS sequence type was observed in two of the patients...... with haematological malignancies who shared a hospital room, and also in two of the patients with HIV infection who had prolonged close contact on the ward. In contrast, different ITS sequence types were detected in samples from an HIV-infected homosexual couple who shared the same household. These data suggest...

  17. Cluster analysis for applications

    CERN Document Server

    Anderberg, Michael R

    1973-01-01

    Cluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis.Comprised of 10 chapters, this book begins with an introduction to the subject o

  18. Deep spectroscopy of nearby galaxy clusters - II. The Hercules cluster

    Science.gov (United States)

    Agulli, I.; Aguerri, J. A. L.; Diaferio, A.; Dominguez Palmero, L.; Sánchez-Janssen, R.

    2017-06-01

    We carried out the deep spectroscopic observations of the nearby cluster A 2151 with AF2/WYFFOS@WHT. The caustic technique enables us to identify 360 members brighter than Mr = -16 and within 1.3R200. We separated the members into subsamples according to photometrical and dynamical properties such as colour, local environment and infall time. The completeness of the catalogue and our large sample allow us to analyse the velocity dispersion and the luminosity functions (LFs) of the identified populations. We found evidence of a cluster still in its collapsing phase. The LF of the red population of A 2151 shows a deficit of dwarf red galaxies. Moreover, the normalized LFs of the red and blue populations of A 2151 are comparable to the red and blue LFs of the field, even if the blue galaxies start dominating 1 mag fainter and the red LF is well represented by a single Schechter function rather than a double Schechter function. We discuss how the evolution of cluster galaxies depends on their mass: bright and intermediate galaxies are mainly affected by dynamical friction and internal/mass quenching, while the evolution of dwarfs is driven by environmental processes that need time and a hostile cluster environment to remove the gas reservoirs and halt the star formation.

  19. Clustering by Minimum Cut Hyperplanes.

    Science.gov (United States)

    Hofmeyr, David P

    2017-08-01

    Minimum normalised graph cuts are highly effective ways of partitioning unlabeled data, having been made popular by the success of spectral clustering. This work presents a novel method for learning hyperplane separators which minimise this graph cut objective, when data are embedded in Euclidean space. The optimisation problem associated with the proposed method can be formulated as a sequence of univariate subproblems, in which the optimal hyperplane orthogonal to a given vector is determined. These subproblems can be solved in log-linear time, by exploiting the trivial factorisation of the exponential function. Experimentation suggests that the empirical runtime of the overall algorithm is also log-linear in the number of data. Asymptotic properties of the minimum cut hyperplane, both for a finite sample, and for an increasing sample assumed to arise from an underlying probability distribution are discussed. In the finite sample case the minimum cut hyperplane converges to the maximum margin hyperplane as the scaling parameter is reduced to zero. Applying the proposed methodology, both for fixed scaling, and the large margin asymptotes, is shown to produce high quality clustering models in comparison with state-of-the-art clustering algorithms in experiments using a large collection of benchmark datasets.

  20. Clusters and how to make it work : Cluster strategy toolkit

    NARCIS (Netherlands)

    Anu Manickam; Karel van Berkel

    2014-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  1. Intrinsic alignment of redMaPPer clusters: cluster shape - matter density correlation

    OpenAIRE

    van Uitert, Edo; Joachimi, Benjamin

    2017-01-01

    We measure the alignment of the shapes of galaxy clusters, as traced by their satellite distributions, with the matter density field using the public redMaPPer catalogue based on Sloan Digital Sky Survey–Data Release 8 (SDSS-DR8), which contains 26 111 clusters up to z ∼ 0.6. The clusters are split into nine redshift and richness samples; in each of them, we detect a positive alignment, showing that clusters point towards density peaks. We interpret the measurements within the tidal alignment...

  2. Enhanced peptide quantification using spectral count clustering and cluster abundance

    Directory of Open Access Journals (Sweden)

    Lee Seungmook

    2011-10-01

    Full Text Available Abstract Background Quantification of protein expression by means of mass spectrometry (MS has been introduced in various proteomics studies. In particular, two label-free quantification methods, such as spectral counting and spectra feature analysis have been extensively investigated in a wide variety of proteomic studies. The cornerstone of both methods is peptide identification based on a proteomic database search and subsequent estimation of peptide retention time. However, they often suffer from restrictive database search and inaccurate estimation of the liquid chromatography (LC retention time. Furthermore, conventional peptide identification methods based on the spectral library search algorithms such as SEQUEST or SpectraST have been found to provide neither the best match nor high-scored matches. Lastly, these methods are limited in the sense that target peptides cannot be identified unless they have been previously generated and stored into the database or spectral libraries. To overcome these limitations, we propose a novel method, namely Quantification method based on Finding the Identical Spectral set for a Homogenous peptide (Q-FISH to estimate the peptide's abundance from its tandem mass spectrometry (MS/MS spectra through the direct comparison of experimental spectra. Intuitively, our Q-FISH method compares all possible pairs of experimental spectra in order to identify both known and novel proteins, significantly enhancing identification accuracy by grouping replicated spectra from the same peptide targets. Results We applied Q-FISH to Nano-LC-MS/MS data obtained from human hepatocellular carcinoma (HCC and normal liver tissue samples to identify differentially expressed peptides between the normal and disease samples. For a total of 44,318 spectra obtained through MS/MS analysis, Q-FISH yielded 14,747 clusters. Among these, 5,777 clusters were identified only in the HCC sample, 6,648 clusters only in the normal tissue sample

  3. The 3-Dimensional Structure of Galaxy Clusters

    Science.gov (United States)

    King, Lindsay

    NASA's Hubble Space Telescope Multi-Cycle Treasury Program CLASH (PI Postman) has provided the community with the most detailed views ever of the central regions of massive galaxy clusters. These galaxy clusters have also been observed with NASA's Chandra X-Ray Observatory, with the ground-based Subaru telescope, and with other ground- and space-based facilities, resulting in unprecedented multi-wavelength data sets of the most massive bound structures in the universe. Fitting 3-Dimensional mass models is crucial to understanding how mass is distributed in individual clusters, investigating the properties of dark matter, and testing our cosmological model. With the exquisite data available, the time is now ideal to undertake this analysis. We propose to use algorithms that we have developed and obtain mass models for the clusters from the CLASH sample. The project would use archival gravitational lensing data, X-ray data of the cluster's hot gas and additional constraints from Sunyaev-Zel'dovich (SZ) data. Specifically, we would model the 23 clusters for which both HST and Subaru data (or in one case WFI data) are publicly available, since the exquisite imaging of HST in the clusters' central regions is beautifully augmented by the wide field coverage of Subaru imaging. If the true 3-D shapes of clusters are not properly accounted for when analysing data, this can lead to inaccuracies in the mass density profiles of individual clusters - up to 50% bias in mass for the most highly triaxial systems. Our proposed project represents an independent analysis of the CLASH sample, complementary to that of the CLASH team, probing the triaxial shapes and orientations of the cluster dark matter halos and hot gas. Our findings will be relevant to the analysis of data from future missions such as JWST and Euclid, and also to ground-based surveys to be made with telescopes such as LSST.

  4. Cluster randomized trials for pharmacy practice research.

    Science.gov (United States)

    Gums, Tyler; Carter, Barry; Foster, Eric

    2016-06-01

    Introduction Cluster randomized trials (CRTs) are now the gold standard in health services research, including pharmacy-based interventions. Studies of behaviour, epidemiology, lifestyle modifications, educational programs, and health care models are utilizing the strengths of cluster randomized analyses. Methodology The key property of CRTs is the unit of randomization (clusters), which may be different from the unit of analysis (individual). Subject sample size and, ideally, the number of clusters is determined by the relationship of between-cluster and within-cluster variability. The correlation among participants recruited from the same cluster is known as the intraclass correlation coefficient (ICC). Generally, having more clusters with smaller ICC values will lead to smaller sample sizes. When selecting clusters, stratification before randomization may be useful in decreasing imbalances between study arms. Participant recruitment methods can differ from other types of randomized trials, as blinding a behavioural intervention cannot always be done. When to use CRTs can yield results that are relevant for making "real world" decisions. CRTs are often used in non-therapeutic intervention studies (e.g. change in practice guidelines). The advantages of CRT design in pharmacy research have been avoiding contamination and the generalizability of the results. A large CRT that studied physician-pharmacist collaborative management of hypertension is used in this manuscript as a CRT example. The trial, entitled Collaboration Among Pharmacists and physicians To Improve Outcomes Now (CAPTION), was implemented in primary care offices in the United States for hypertensive patients. Limitations CRT design limitations include the need for a large number of clusters, high costs, increased training, increased monitoring, and statistical complexity.

  5. Open source clustering software.

    Science.gov (United States)

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

    2004-06-12

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

  6. Agricultural Clusters in the Netherlands

    NARCIS (Netherlands)

    Schouten, M.A.; Heijman, W.J.M.

    2012-01-01

    Michael Porter was the first to use the term cluster in an economic context. He introduced the term in The Competitive Advantage of Nations (1990). The term cluster is also known as business cluster, industry cluster, competitive cluster or Porterian cluster. This article aims at determining and

  7. BioCluster: Tool for Identification and Clustering of Enterobacteriaceae Based on Biochemical Data

    Directory of Open Access Journals (Sweden)

    Ahmed Abdullah

    2015-06-01

    Full Text Available Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC and the Improved Hierarchical Clustering (IHC, a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1–47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/.

  8. BioCluster: tool for identification and clustering of Enterobacteriaceae based on biochemical data.

    Science.gov (United States)

    Abdullah, Ahmed; Sabbir Alam, S M; Sultana, Munawar; Hossain, M Anwar

    2015-06-01

    Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI) tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC) and the Improved Hierarchical Clustering (IHC), a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1-47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

  9. Simulating Error in Cluster Weak Lensing Tomography

    Science.gov (United States)

    Murphy, Kellen J.

    2012-01-01

    We present the results of an N-body simulation of the various sources of systematic error in constraining the dark energy equation of state via cluster weak lensing tomography. The use of tomographic techniques to constrain the dark energy equation of state parameter is a pivotal component of future large survey missions, however, the application of tomography to cosmic shear necessitates the exclusion of regions around galaxy clusters from analysis. We therefore test the applicability tomography to cluster-induced shear as a secondary, complementary sample through which estimates of the dark energy e.o.s. parameter can be made. Furthermore, we demonstrate the application of this technique to a test sample of 10 massive galaxy clusters imaged by the Hubble Space Telescope.

  10. Spectral clustering and its use in bioinformatics

    Science.gov (United States)

    Higham, Desmond J.; Kalna, Gabriela; Kibble, Milla

    2007-07-01

    We formulate a discrete optimization problem that leads to a simple and informative derivation of a widely used class of spectral clustering algorithms. Regarding the algorithms as attempting to bi-partition a weighted graph with N vertices, our derivation indicates that they are inherently tuned to tolerate all partitions into two non-empty sets, independently of the cardinality of the two sets. This approach also helps to explain the difference in behaviour observed between methods based on the unnormalized and normalized graph Laplacian. We also give a direct explanation of why Laplacian eigenvectors beyond the Fiedler vector may contain fine-detail information of relevance to clustering. We show numerical results on synthetic data to support the analysis. Further, we provide examples where normalized and unnormalized spectral clustering is applied to microarray data--here the graph summarizes similarity of gene activity across different tissue samples, and accurate clustering of samples is a key task in bioinformatics.

  11. Technique for fast and efficient hierarchical clustering

    Science.gov (United States)

    Stork, Christopher

    2013-10-08

    A fast and efficient technique for hierarchical clustering of samples in a dataset includes compressing the dataset to reduce a number of variables within each of the samples of the dataset. A nearest neighbor matrix is generated to identify nearest neighbor pairs between the samples based on differences between the variables of the samples. The samples are arranged into a hierarchy that groups the samples based on the nearest neighbor matrix. The hierarchy is rendered to a display to graphically illustrate similarities or differences between the samples.

  12. The VIMOS Public Extragalactic Redshift Survey (VIPERS). The growth of structure at 0.5 < z < 1.2 from redshift-space distortions in the clustering of the PDR-2 final sample

    Science.gov (United States)

    Pezzotta, A.; de la Torre, S.; Bel, J.; Granett, B. R.; Guzzo, L.; Peacock, J. A.; Garilli, B.; Scodeggio, M.; Bolzonella, M.; Abbas, U.; Adami, C.; Bottini, D.; Cappi, A.; Cucciati, O.; Davidzon, I.; Franzetti, P.; Fritz, A.; Iovino, A.; Krywult, J.; Le Brun, V.; Le Fèvre, O.; Maccagni, D.; Małek, K.; Marulli, F.; Polletta, M.; Pollo, A.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zanichelli, A.; Arnouts, S.; Branchini, E.; Coupon, J.; De Lucia, G.; Koda, J.; Ilbert, O.; Mohammad, F.; Moutard, T.; Moscardini, L.

    2017-07-01

    We present measurements of the growth rate of cosmological structure from the modelling of the anisotropic galaxy clustering measured in the final data release of the VIPERS survey. The analysis is carried out in configuration space and based on measurements of the first two even multipole moments of the anisotropic galaxy auto-correlation function, in two redshift bins spanning the range 0.5 programs 182.A-0886 and partly 070.A-9007. Also based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. The VIPERS web site is http://www.vipers.inaf.it/

  13. Investigations of Galaxy Clusters Using Gravitational Lensing

    Energy Technology Data Exchange (ETDEWEB)

    Wiesner, Matthew P. [Northern Illinois Univ., DeKalb, IL (United States)

    2014-08-01

    In this dissertation, we discuss the properties of galaxy clusters that have been determined using strong and weak gravitational lensing. A galaxy cluster is a collection of galaxies that are bound together by the force of gravity, while gravitational lensing is the bending of light by gravity. Strong lensing is the formation of arcs or rings of light surrounding clusters and weak lensing is a change in the apparent shapes of many galaxies. In this work we examine the properties of several samples of galaxy clusters using gravitational lensing. In Chapter 1 we introduce astrophysical theory of galaxy clusters and gravitational lensing. In Chapter 2 we examine evidence from our data that galaxy clusters are more concentrated than cosmology would predict. In Chapter 3 we investigate whether our assumptions about the number of galaxies in our clusters was valid by examining new data. In Chapter 4 we describe a determination of a relationship between mass and number of galaxies in a cluster at higher redshift than has been found before. In Chapter 5 we describe a model of the mass distribution in one of the ten lensing systems discovered by our group at Fermilab. Finally in Chapter 6 we summarize our conclusions.

  14. Microsoft Hyper-V cluster design

    CERN Document Server

    Siron, Eric

    2013-01-01

    This book is written in a friendly and practical style with numerous tutorials centred on common as well as atypical Hyper-V cluster designs. This book also features a sample cluster design throughout to help you learn how to design a Hyper-V in a real-world scenario.Microsoft Hyper-V Cluster Design is perfect for the systems administrator who has a good understanding of Windows Server in an Active Directory domain and is ready to expand into a highly available virtualized environment. It only expects that you will be familiar with basic hypervisor terminology.

  15. Cluster analysis for computer workload evaluation

    CERN Document Server

    Landau, K

    1976-01-01

    An introduction to computer workload analysis is given, showing its range of application in computer centre management, system and application programming. Cluster methods are discussed which can be used in conjunction with workload data and cluster algorithms are adapted to the specific set problem. Several samples of CDC 7600- accounting-data-collected at CERN, the European Organization for Nuclear Research-underwent a cluster analysis to determine job groups. The conclusions from resource usage of typical job groups in relation to computer workload analysis are discussed. (17 refs).

  16. Disentangling Porterian Clusters

    DEFF Research Database (Denmark)

    Jagtfelt, Tue

    This dissertation investigates the contemporary phenomenon of industrial clusters based on the work of Michael E. Porter, the central progenitor and promoter of the cluster notion. The dissertation pursues two central questions: 1) What is a cluster? and 2) How could Porter’s seemingly fuzzy...... to his membership on the Commission on Industrial Competitiveness, and that the cluster notion found in his influential book, Nations, represents a significant shift in his conception of cluster compared with his early conceptions. This shift, it is argued, is a deliberate attempt by Porter to create......, contested theory become so widely disseminated and applied as a normative and prescriptive strategy for economic development? The dissertation traces the introduction of the cluster notion into the EU’s Lisbon Strategy and demonstrates how its inclusion originates from Porter’s colleagues: Professor Örjan...

  17. From collisions to clusters

    DEFF Research Database (Denmark)

    Loukonen, Ville; Bork, Nicolai; Vehkamaki, Hanna

    2014-01-01

    The clustering of sulphuric acid with base molecules is one of the main pathways of new-particle formation in the Earth's atmosphere. First step in the clustering process is likely the formation of a (sulphuric acid)1(base)1(water)n cluster. Here, we present results from direct first......-principles molecular dynamics collision simulations of (sulphuric acid)1(water)0, 1 + (dimethylamine) → (sulphuric acid)1(dimethylamine)1(water)0, 1 cluster formation processes. The simulations indicate that the sticking factor in the collisions is unity: the interaction between the molecules is strong enough...... to overcome the possible initial non-optimal collision orientations. No post-collisional cluster break up is observed. The reasons for the efficient clustering are (i) the proton transfer reaction which takes place in each of the collision simulations and (ii) the subsequent competition over the proton...

  18. Clustering by Local Gravitation.

    Science.gov (United States)

    Wang, Zhiqiang; Yu, Zhiwen; Chen, C L Philip; You, Jane; Gu, Tianlong; Wong, Hau-San; Zhang, Jun

    2017-05-02

    The objective of cluster analysis is to partition a set of data points into several groups based on a suitable distance measure. We first propose a model called local gravitation among data points. In this model, each data point is viewed as an object with mass, and associated with a local resultant force (LRF) generated by its neighbors. The motivation of this paper is that there exist distinct differences between the LRFs (including magnitudes and directions) of the data points close to the cluster centers and at the boundary of the clusters. To capture these differences efficiently, two new local measures named centrality and coordination are further investigated. Based on empirical observations, two new clustering methods called local gravitation clustering and communication with local agents are designed, and several test cases are conducted to verify their effectiveness. The experiments on synthetic data sets and real-world data sets indicate that both clustering approaches achieve good performance on most of the data sets.

  19. Convex Discriminative Multitask Clustering.

    Science.gov (United States)

    Zhang, Xiao-Lei

    2015-01-01

    Multitask clustering tries to improve the clustering performance of multiple tasks simultaneously by taking their relationship into account. Most existing multitask clustering algorithms fall into the type of generative clustering, and none are formulated as convex optimization problems. In this paper, we propose two convex Discriminative Multitask Clustering (DMTC) objectives to address the problems. The first one aims to learn a shared feature representation, which can be seen as a technical combination of the convex multitask feature learning and the convex Multiclass Maximum Margin Clustering (M3C). The second one aims to learn the task relationship, which can be seen as a combination of the convex multitask relationship learning and M3C. The objectives of the two algorithms are solved in a uniform procedure by the efficient cutting-plane algorithm and further unified in the Bayesian framework. Experimental results on a toy problem and two benchmark data sets demonstrate the effectiveness of the proposed algorithms.

  20. Cluster Management Institutionalization

    DEFF Research Database (Denmark)

    Normann, Leo; Agger Nielsen, Jeppe

    2015-01-01

    This article explores a new management form – cluster management – in Danish public sector day care. Although cluster management has been widely adopted in Danish day care at the municipality level, it has attracted only sparse research attention. We use theoretical insights from Scandinavian...... institutionalism together with a longitudinal case-based inquiry into how cluster management has entered and penetrated the management practices of day care in Denmark. We demonstrate how cluster management became widely adopted in the day care field not only because of its intrinsic properties but also because...... of how it was legitimized as a “ready-to-use” management model. Further, our account reveals how cluster management translated into considerably different local variants as it travelled into specific organizations. However, these processes have not occurred sequentially with cluster management first...

  1. Active cluster crystals

    Science.gov (United States)

    Delfau, Jean-Baptiste; López, Cristóbal; Hernández-García, Emilio

    2017-09-01

    We study the appearance and properties of cluster crystals (solids in which the unit cell is occupied by a cluster of particles) in a two-dimensional system of self-propelled active Brownian particles with repulsive interactions. Self-propulsion deforms the clusters by depleting particle density inside, and for large speeds it melts the crystal. Continuous field descriptions at several levels of approximation allow us to identify the relevant physical mechanisms.

  2. Percolation in clustered networks

    OpenAIRE

    Miller, Joel C

    2009-01-01

    The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied clustered networks, but the networks often contain preferential mixing between high degree nodes. We introduce a class of random clustered networks and another class of random unclustered networks with the same prefer...

  3. Cluster Symmetries and Dynamics

    Directory of Open Access Journals (Sweden)

    Freer Martin

    2016-01-01

    Full Text Available Many light nuclei display behaviour that indicates that rather than behaving as an A-body systems, the protons and neutrons condense into clusters. The α-particle is the most obvious example of such clustering. This contribution examines the role of such α-clustering on the structure, symmetries and dynamics of the nuclei 8Be, 12C and 16O, recent experimental measurements and future perspectives.

  4. Data Mining with Clustering

    OpenAIRE

    Klímek, Petr

    2008-01-01

    One of the oppotunities in data mining is a use of clustering analysis. Clustering analysis belongs to unsupervised methods of data mining. We put here a focus on this method. Some basic principles are described in the second part of this paper. This method is examined on two examples from the marketing field. In the first example is used software Statgraphics 5.0Plus to solve clustering problem (nearest neighbour algorithm and Eucleidian distance); and in the second example is used Statistic...

  5. Spatial Scan Statistic: Selecting clusters and generating elliptic clusters

    OpenAIRE

    Christiansen, Lasse Engbo; Andersen, Jens Strodl

    2004-01-01

    The spatial scan statistic is widely used to search for clusters. This paper shows that the usually applied elimination of overlapping clusters to find secondary clusters is sensitive to smooth changes in the shape of the clusters. We present an algorithm for generation of set of confocal elliptic clusters. In addition, we propose a new way to present the information in a given set of clusters based on the significance of the clusters.

  6. Spatial Scan Statistic: Selecting clusters and generating elliptic clusters

    DEFF Research Database (Denmark)

    Christiansen, Lasse Engbo; Andersen, Jens Strodl

    2004-01-01

    The spatial scan statistic is widely used to search for clusters. This paper shows that the usually applied elimination of overlapping clusters to find secondary clusters is sensitive to smooth changes in the shape of the clusters. We present an algorithm for generation of set of confocal elliptic...... clusters. In addition, we propose a new way to present the information in a given set of clusters based on the significance of the clusters....

  7. 15th Cluster workshop

    CERN Document Server

    Laakso, Harri; Escoubet, C. Philippe; The Cluster Active Archive : Studying the Earth’s Space Plasma Environment

    2010-01-01

    Since the year 2000 the ESA Cluster mission has been investigating the small-scale structures and processes of the Earth's plasma environment, such as those involved in the interaction between the solar wind and the magnetospheric plasma, in global magnetotail dynamics, in cross-tail currents, and in the formation and dynamics of the neutral line and of plasmoids. This book contains presentations made at the 15th Cluster workshop held in March 2008. It also presents several articles about the Cluster Active Archive and its datasets, a few overview papers on the Cluster mission, and articles reporting on scientific findings on the solar wind, the magnetosheath, the magnetopause and the magnetotail.

  8. Multivariate cluster analysis of some major and trace elements ...

    African Journals Online (AJOL)

    Multivariate cluster analysis of some major and trace elements distribution in an unsaturated zone profile, Densu river basin, Ghana. ... to human activities. Cluster analysis of the samples shows only one sample is needed from depths characterised by similar physical properties of texture and colour. Key words: Unsaturated ...

  9. Metal Cluster Topology. 1. Osmium Carbonyl Clusters.

    Science.gov (United States)

    1986-01-29

    AD-A164 372 NETAL CLUSTER TOPOLOGY I OSNIUM CARDONYI. CLUSTERS(U) i ’ GEORGIA IiNIY ATHENS DEPT OF CHENISTRY R 8 KING UCr S 29 JAN 86 TR-15 NSSSI4-S5...to distinguish between globally delocalized (D) and edge-localized (L) polyhedra. Treatment of globally delocalized polyhedra leads clearly to the same...of five internal orbitals for two of the six vertex atoms will make the pair of edge-fused tetrahedra unfavorable except for some of the heavy

  10. Super Star Clusters

    Science.gov (United States)

    O'Connell, R. W.

    1994-05-01

    Super star clusters represent an extreme in the star formation process. They are very luminous, compact objects with L_V > 10(6) L_{V,sun} and diameters = 100 times higher than normal OB associations and clusters in ``giant H II regions''. Prior to HST about a dozen such objects had been identified in nearby galaxies, but at ground-based resolution they are nearly point sources. We review recent HST observations of individual super star clusters in NGC 1140, 1569, and 1705. They have half-light radii of only 2--3.5 pc, and some show evidence of substructure which should be resolvable with the repaired HST. After allowing for age differences, the surface brightness of NGC 1569-A is over 65 times higher than the core of 30 Doradus in the LMC and 1200 times higher than the mean rich LMC star cluster. In some cases, the energy released by the clusters into their surroundings is sufficient to drive galaxy-wide winds. Their properties make super star clusters good analogues of young globular clusters. In some, though not all, cases super star clusters appear to form in the aftermath of a merger or accretion event. The most impressive examples are the clusters detected by HST in NGC 1275 and 7252, one of which has the extraordinary luminosity ~ 6 times 10(8) L_{V,sun}. M82 affords a nearby view of a post-interaction system. HST imaging has identified over 80 super star clusters in its central regions with mean luminosities of ~ 3 times 10(6) L_{V,sun}. Their close packing and signs of interaction with the well-known supernova-driven wind suggest that they do not evolve independently. Super cluster evolution in starbursts is probably a collective phenomenon.

  11. Nonlocalized clustering and evolution of cluster structure in nuclei

    Science.gov (United States)

    Horiuchi, H.

    2017-06-01

    It is shown that the THSR (Tohsaki-Horiuchi-Schuck-Roepke) wave function describe well not only cluster-gas like structures but also ordinary cluster structures with spatial localization of clusters. Based on this fact, the container model has been proposed as a new model of cluster dynamics. For better description of cluster dynamics, extended version of container model has been introduced. The container model of cluster dynamics teaches us how is the evolution of cluster structure which starts from the ground state having shell-model structure to many kinds of cluster states up to the cluster-gas states.

  12. ChaMP Serendipitous Galaxy Cluster Survey

    Energy Technology Data Exchange (ETDEWEB)

    Barkhouse, Wayne A.; Green, P.J.; Vikhlinin, A.; Kim, D.-W.; Perley, D.; Cameron, R.; Silverman, J.; Mossman, A.; Burenin, R.; Jannuzi, B.T.; Kim, M.; Smith, M.G.; Smith,; Tananbaum, H.; Wilkes, B.J.; /Harvard-Smithsonian Ctr. Astrophys. /UC, Berkeley, Astron. Dept. /SLAC /Garching, Max Planck Inst., MPE /Moscow, Space Res. Inst. /NOAO, Tucson

    2006-04-03

    We present a survey of serendipitous extended X-ray sources and optical cluster candidates from the Chandra Multi-wavelength Project (ChaMP). Our main goal is to make an unbiased comparison of X-ray and optical cluster detection methods. In 130 archival Chandra pointings covering 13 square degrees, we use a wavelet decomposition technique to detect 55 extended sources, of which 6 are nearby single galaxies. Our X-ray cluster catalog reaches a typical flux limit of about {approx} 10{sup -14} erg s{sup -1} cm{sup -2}, with a median cluster core radius of 21''. For 56 of the 130 X-ray fields, we use the ChaMP's deep NOAO/4m MOSAIC g', r', and i' imaging to independently detect cluster candidates using a Voronoi tessellation and percolation (VTP) method. Red-sequence filtering decreases the galaxy fore/background contamination and provides photometric redshifts to z {approx} 0.7. From the overlapping 6.1 square degree X-ray/optical imaging, we find 115 optical clusters (of which 11% are in the X-ray catalog) and 28 X-ray clusters (of which 46% are in the optical VTP catalog). The median redshift of the 13 X-ray/optical clusters is 0.41, and their median X-ray luminosity (0.5-2 keV) is L{sub X} = (2.65 {+-} 0.19) x 10{sup 43} ergs s{sup -1}. The clusters in our sample that are only detected in our optical data are poorer on average ({approx} 4{sigma}) than the X-ray/optically matched clusters, which may partially explain the difference in the detection fractions.

  13. MOSAIC (MOthers' Advocates In the Community: protocol and sample description of a cluster randomised trial of mentor mother support to reduce intimate partner violence among pregnant or recent mothers

    Directory of Open Access Journals (Sweden)

    Taft Angela J

    2009-05-01

    Full Text Available Abstract Background Intimate partner violence (IPV is prevalent globally, experienced by a significant minority of women in the early childbearing years and is harmful to the mental and physical health of women and children. There are very few studies with rigorous designs which have tested the effectiveness of IPV interventions to improve the health and wellbeing of abused women. Evidence for the separate benefit to victims of social support, advocacy and non-professional mentoring suggested that a combined model may reduce the levels of violence, the associated mental health damage and may increase a woman's health, safety and connection with her children. This paper describes the development, design and implementation of a trial of mentor mother support set in primary care, including baseline characteristics of participating women. Methods/Design MOSAIC (MOtherS' Advocates In the Community was a cluster randomised trial embedded in general practice and maternal and child health (MCH nursing services in disadvantaged suburbs of Melbourne, Australia. Women who were pregnant or with infants, identified as abused or symptomatic of abuse, were referred by IPV-trained GPs and MCH nurses from 24 general practices and eight nurse teams from January 2006 to December 2007. Women in the intervention arm received up to 12 months support from trained and supported non-professional mentor mothers. Vietnamese health professionals also referred Vietnamese women to bilingual mentors in a sub-study. Baseline and follow-up surveys at 12 months measured IPV (CAS, depression (EPDS, general health (SF-36, social support (MOS-SF and attachment to children (PSI-SF. Significant development and piloting occurred prior to trial commencement. Implementation interviews with MCH nurses, GPs and mentors assisted further refinement of the intervention. In-depth interviews with participants and mentors, and follow-up surveys of MCH nurses and GPs at trial conclusion will

  14. PHAT Star Clusters in M31: Insight on Environmental Dependence of Star & Cluster Formation

    Science.gov (United States)

    Johnson, Lent C.; Dalcanton, Julianne; Seth, Anil; Beerman, Lori; Lewis, Alexia; Fouesneau, Morgan; Weisz, Daniel R.; Andromeda Project Team, PHAT Team

    2015-01-01

    Theoretical studies of star cluster formation suggest that the star formation efficiency (SFE) of a cluster's progenitor cloud dictates whether or not a gravitationally bound grouping will emerge from an embedded region after gas expulsion. I measure the fraction of stars formed in long-lived clusters relative to unbound field stars on a spatial resolved basis in the Andromeda galaxy. These observations test theoretical predictions that star clusters are formed within a hierarchical interstellar medium at peaks in the gas density where local SFEs are enhanced and regions become stellar dominated. Using data from the Panchromatic Hubble Andromeda Treasury (PHAT) survey and ancillary observations of M31's gas phase, I investigate how cluster formation correlates with galactic environment and galaxy-scale properties of the star formation. We construct a sample of >2700 star clusters through a crowd-sourced visual search of the high spatial resolution HST imaging data. Our catalog uses ~2 million image classifications collected by the Andromeda Project citizen science website to provide an unparalleled census of clusters that spans ~4 orders of magnitude in mass (50% completeness at ~500 M⊙ at careful catalog completeness characterization, made possible by thousands of synthetic cluster tests included during catalog construction work. We combine our high quality cluster sample with spatially resolved star formation histories, derived from CMD fitting of PHAT's photometry of ~117 million resolved field stars. We derived the fraction of stars formed in long-lived clusters and show that only a few percent of coeval stars are found in clusters within the 10-100 Myr age range. These results are consistent with theoretical predictions of declining bound fractions with decreasing star formation rate density.

  15. Securing Personal Network Clusters

    NARCIS (Netherlands)

    Jehangir, A.; Heemstra de Groot, S.M.

    2007-01-01

    A Personal Network is a self-organizing, secure and private network of a user’s devices notwithstanding their geographic location. It aims to utilize pervasive computing to provide users with new and improved services. In this paper we propose a model for securing Personal Network clusters. Clusters

  16. Neurostimulation in cluster headache

    DEFF Research Database (Denmark)

    Pedersen, Jeppe L; Barloese, Mads; Jensen, Rigmor H

    2013-01-01

    PURPOSE OF REVIEW: Neurostimulation has emerged as a viable treatment for intractable chronic cluster headache. Several therapeutic strategies are being investigated including stimulation of the hypothalamus, occipital nerves and sphenopalatine ganglion. The aim of this review is to provide...... effective strategy must be preferred as first-line therapy for intractable chronic cluster headache....

  17. Cauchy cluster process

    DEFF Research Database (Denmark)

    Ghorbani, Mohammad

    2013-01-01

    In this paper we introduce an instance of the well-know Neyman–Scott cluster process model with clusters having a long tail behaviour. In our model the offspring points are distributed around the parent points according to a circular Cauchy distribution. Using a modified Cramér-von Misses test...

  18. Cluster Synchronization Algorithms

    NARCIS (Netherlands)

    Xia, Weiguo; Cao, Ming

    2010-01-01

    This paper presents two approaches to achieving cluster synchronization in dynamical multi-agent systems. In contrast to the widely studied synchronization behavior, where all the coupled agents converge to the same value asymptotically, in the cluster synchronization problem studied in this paper,

  19. Mixed-Initiative Clustering

    Science.gov (United States)

    Huang, Yifen

    2010-01-01

    Mixed-initiative clustering is a task where a user and a machine work collaboratively to analyze a large set of documents. We hypothesize that a user and a machine can both learn better clustering models through enriched communication and interactive learning from each other. The first contribution or this thesis is providing a framework of…

  20. Reflections on cluster policies

    NARCIS (Netherlands)

    Brakman, Steven; van Marrewijk, Charles

    Economic activity tends to cluster. This results in productivity gains. For policy makers this offers an opportunity to formulate and promote policies that foster clustering of economic activity. Paradoxically, although agglomeration rents are often found in empirical research, a rationale for

  1. Calixarene-supported clusters

    DEFF Research Database (Denmark)

    Taylor, Stephanie M.; McIntosh, Ruaraidh D.; Piligkos, Stergios

    2012-01-01

    A combination of complementary cluster ligands results in the formation of a new calixarene-supported ferromagnetic [Mn(5)] cage that displays the characteristic bonding modes of each support.......A combination of complementary cluster ligands results in the formation of a new calixarene-supported ferromagnetic [Mn(5)] cage that displays the characteristic bonding modes of each support....

  2. Detecting clusters of mutations.

    Directory of Open Access Journals (Sweden)

    Tong Zhou

    Full Text Available Positive selection for protein function can lead to multiple mutations within a small stretch of DNA, i.e., to a cluster of mutations. Recently, Wagner proposed a method to detect such mutation clusters. His method, however, did not take into account that residues with high solvent accessibility are inherently more variable than residues with low solvent accessibility. Here, we propose a new algorithm to detect clustered evolution. Our algorithm controls for different substitution probabilities at buried and exposed sites in the tertiary protein structure, and uses random permutations to calculate accurate P values for inferred clusters. We apply the algorithm to genomes of bacteria, fly, and mammals, and find several clusters of mutations in functionally important regions of proteins. Surprisingly, clustered evolution is a relatively rare phenomenon. Only between 2% and 10% of the genes we analyze contain a statistically significant mutation cluster. We also find that not controlling for solvent accessibility leads to an excess of clusters in terminal and solvent-exposed regions of proteins. Our algorithm provides a novel method to identify functionally relevant divergence between groups of species. Moreover, it could also be useful to detect artifacts in automatically assembled genomes.

  3. Structural and dynamical modeling of WINGS clusters. I. The distribution of cluster galaxies of different morphological classes within regular and irregular clusters

    Science.gov (United States)

    Cava, A.; Biviano, A.; Mamon, G. A.; Varela, J.; Bettoni, D.; D'Onofrio, M.; Fasano, G.; Fritz, J.; Moles, M.; Moretti, A.; Poggianti, B.

    2017-10-01

    Context. We study the distribution of galaxies in nearby clusters to shed light on the evolutionary processes at work within clusters and prepare for a full dynamical analysis to be conducted in forthcoming papers of this series. Aims: We use the Wide-field Nearby Galaxy-clusters Survey (WINGS) database complemented with literature data. We assign galaxy membership to individual clusters, then select a sample of 67 clusters with at least 30 spectroscopic members each. 53 of these clusters do not show evidence of substructures in phase-space, as measured by the Dressler-Shectman test, while 14 do. We estimate the virial radii and circular velocities of the 67 clusters by a variety of proxies (velocity dispersion, X-ray temperature, and richness) and use these estimates to build stack samples from these 53 and 14 clusters, that we call "Reg" and "Irr" stacks, respectively. We show that our results are robust with regard to the choice of the virial radii and circular velocities used to scale galaxy radii and velocities in the stacking procedure. We determine the number-density and velocity-dispersion profiles of Elliptical (E), S0, and Spiral+Irregular (S) galaxies in the Reg and Irr samples, separately, and fit models to these profiles. Methods: The number density profiles of E, S0, and S galaxies are adequately described by either a Navarro, Frenk, & White (NFW) or a cored King model, both for the Reg and Irr samples, with a slight preference for the NFW model. The spatial distribution concentration increases from the S to the S0 and to the E populations, both in the Reg and the Irr stacks, reflecting the well-known morphology-radius relation. Reg clusters have a more concentrated spatial distribution of E and S0 galaxies than Irr clusters, while the spatial distributions of S galaxies in Reg and Irr clusters have a similar concentration. We propose a new phenomenological model that provides acceptable fits to the velocity dispersion profile of all our galaxy

  4. Negotiating Cluster Boundaries

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    2017-01-01

    Palm oil was introduced to Malay(si)a as an alternative to natural rubber, inheriting its cluster organizational structure. In the late 1960s, Malaysia became the world’s largest palm oil exporter. Based on archival material from British colonial institutions and agency houses, this paper focuses...... on the governance dynamics that drove institutional change within this cluster during decolonization. The analysis presents three main findings: (i) cluster boundaries are defined by continuous tug-of-war style negotiations between public and private actors; (ii) this interaction produces institutional change...... within the cluster, in the form of cumulative ‘institutional rounds’ – the correction or disruption of existing institutions or the creation of new ones; and (iii) this process leads to a broader inclusion of local actors in the original cluster configuration. The paper challenges the prevalent argument...

  5. Mathematical classification and clustering

    CERN Document Server

    Mirkin, Boris

    1996-01-01

    I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina­ torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de­ velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par­ titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in­ novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in ...

  6. Cool Cluster Correctly Correlated

    Energy Technology Data Exchange (ETDEWEB)

    Varganov, Sergey Aleksandrovich [Iowa State Univ., Ames, IA (United States)

    2005-01-01

    Atomic clusters are unique objects, which occupy an intermediate position between atoms and condensed matter systems. For a long time it was thought that physical and chemical properties of atomic dusters monotonically change with increasing size of the cluster from a single atom to a condensed matter system. However, recently it has become clear that many properties of atomic clusters can change drastically with the size of the clusters. Because physical and chemical properties of clusters can be adjusted simply by changing the cluster's size, different applications of atomic clusters were proposed. One example is the catalytic activity of clusters of specific sizes in different chemical reactions. Another example is a potential application of atomic clusters in microelectronics, where their band gaps can be adjusted by simply changing cluster sizes. In recent years significant advances in experimental techniques allow one to synthesize and study atomic clusters of specified sizes. However, the interpretation of the results is often difficult. The theoretical methods are frequently used to help in interpretation of complex experimental data. Most of the theoretical approaches have been based on empirical or semiempirical methods. These methods allow one to study large and small dusters using the same approximations. However, since empirical and semiempirical methods rely on simple models with many parameters, it is often difficult to estimate the quantitative and even qualitative accuracy of the results. On the other hand, because of significant advances in quantum chemical methods and computer capabilities, it is now possible to do high quality ab-initio calculations not only on systems of few atoms but on clusters of practical interest as well. In addition to accurate results for specific clusters, such methods can be used for benchmarking of different empirical and semiempirical approaches. The atomic clusters studied in this work contain from a few atoms

  7. OPEN CLUSTERS AS PROBES OF THE GALACTIC MAGNETIC FIELD. I. CLUSTER PROPERTIES

    Energy Technology Data Exchange (ETDEWEB)

    Hoq, Sadia; Clemens, D. P., E-mail: shoq@bu.edu, E-mail: clemens@bu.edu [Institute for Astrophysical Research, 725 Commonwealth Avenue, Boston University, Boston, MA 02215 (United States)

    2015-10-15

    Stars in open clusters are powerful probes of the intervening Galactic magnetic field via background starlight polarimetry because they provide constraints on the magnetic field distances. We use 2MASS photometric data for a sample of 31 clusters in the outer Galaxy for which near-IR polarimetric data were obtained to determine the cluster distances, ages, and reddenings via fitting theoretical isochrones to cluster color–magnitude diagrams. The fitting approach uses an objective χ{sup 2} minimization technique to derive the cluster properties and their uncertainties. We found the ages, distances, and reddenings for 24 of the clusters, and the distances and reddenings for 6 additional clusters that were either sparse or faint in the near-IR. The derived ranges of log(age), distance, and E(B−V) were 7.25–9.63, ∼670–6160 pc, and 0.02–1.46 mag, respectively. The distance uncertainties ranged from ∼8% to 20%. The derived parameters were compared to previous studies, and most cluster parameters agree within our uncertainties. To test the accuracy of the fitting technique, synthetic clusters with 50, 100, or 200 cluster members and a wide range of ages were fit. These tests recovered the input parameters within their uncertainties for more than 90% of the individual synthetic cluster parameters. These results indicate that the fitting technique likely provides reliable estimates of cluster properties. The distances derived will be used in an upcoming study of the Galactic magnetic field in the outer Galaxy.

  8. Cluster Ion Implantation in Graphite and Diamond

    DEFF Research Database (Denmark)

    Popok, Vladimir

    2014-01-01

    Cluster ion beam technique is a versatile tool which can be used for controllable formation of nanosize objects as well as modification and processing of surfaces and shallow layers on an atomic scale. The current paper present an overview and analysis of data obtained on a few sets of graphite a...... implantation. Implantation of cobalt and argon clusters into two different allotropic forms of carbon, namely, graphite and diamond is analysed and compared in order to approach universal theory of cluster stopping in matter.......Cluster ion beam technique is a versatile tool which can be used for controllable formation of nanosize objects as well as modification and processing of surfaces and shallow layers on an atomic scale. The current paper present an overview and analysis of data obtained on a few sets of graphite...... and diamond samples implanted by keV-energy size-selected cobalt and argon clusters. One of the emphases is put on pinning of metal clusters on graphite with a possibility of following selective etching of graphene layers. The other topic of concern is related to the development of scaling law for cluster...

  9. Gamma-ray Emission from Globular Clusters

    Science.gov (United States)

    Tam, Pak-Hin T.; Hui, Chung Y.; Kong, Albert K. H.

    2016-03-01

    Over the last few years, the data obtained using the Large Area Telescope (LAT) aboard the Fermi Gamma-ray Space Telescope has provided new insights on high-energy processes in globular clusters, particularly those involving compact objects such as MilliSecond Pulsars (MSPs). Gamma-ray emission in the 100 MeV to 10 GeV range has been detected from more than a dozen globular clusters in our galaxy, including 47 Tucanae and Terzan 5. Based on a sample of known gammaray globular clusters, the empirical relations between gamma-ray luminosity and properties of globular clusters such as their stellar encounter rate, metallicity, and possible optical and infrared photon energy densities, have been derived. The measured gamma-ray spectra are generally described by a power law with a cut-off at a few gigaelectronvolts. Together with the detection of pulsed γ-rays from two MSPs in two different globular clusters, such spectral signature lends support to the hypothesis that γ-rays from globular clusters represent collective curvature emission from magnetospheres of MSPs in the clusters. Alternative models, involving Inverse-Compton (IC) emission of relativistic electrons that are accelerated close to MSPs or pulsar wind nebula shocks, have also been suggested. Observations at >100 GeV by using Fermi/LAT and atmospheric Cherenkov telescopes such as H.E.S.S.-II, MAGIC-II, VERITAS, and CTA will help to settle some questions unanswered by current data.

  10. Gamma-ray Emission from Globular Clusters

    Directory of Open Access Journals (Sweden)

    Pak-Hin T. Tam

    2016-03-01

    Full Text Available Over the last few years, the data obtained using the Large Area Telescope (LAT aboard the Fermi Gamma-ray Space Telescope has provided new insights on high-energy processes in globular clusters, particularly those involving compact objects such as MilliSecond Pulsars (MSPs. Gamma-ray emission in the 100 MeV to 10 GeV range has been detected from more than a dozen globular clusters in our galaxy, including 47 Tucanae and Terzan 5. Based on a sample of known gammaray globular clusters, the empirical relations between gamma-ray luminosity and properties of globular clusters such as their stellar encounter rate, metallicity, and possible optical and infrared photon energy densities, have been derived. The measured gamma-ray spectra are generally described by a power law with a cut-off at a few gigaelectronvolts. Together with the detection of pulsed γ-rays from two MSPs in two different globular clusters, such spectral signature lends support to the hypothesis that γ-rays from globular clusters represent collective curvature emission from magnetospheres of MSPs in the clusters. Alternative models, involving Inverse-Compton (IC emission of relativistic electrons that are accelerated close to MSPs or pulsar wind nebula shocks, have also been suggested. Observations at >100 GeV by using Fermi/LAT and atmospheric Cherenkov telescopes such as H.E.S.S.-II, MAGIC-II, VERITAS, and CTA will help to settle some questions unanswered by current data.

  11. Studies in clustering theory

    Science.gov (United States)

    Stell, George

    In recent years the properties of percolation models have been studied intensively. The purpose of our project was to develop a general theory of percolation and clustering between particles of arbitrary size and shape, with arbitrary correlations between them. The goal of such a theory includes the treatment of continuum percolation as well as a novel treatment of lattice percolation. We made substantial progress toward this goal. The quantities basic to a description of clustering, the mean cluster size, mean number of clusters, etc., were developed. Concise formulas were given for the terms in such series, and proved, at least for sufficiently low densities, that the series are absolutely convergent. These series can now be used to construct Pade approximants that will allow one to probe the percolation transition. A scaled-particle theory of percolation was developed which gives analytic approximants for the mean number of clusters in a large class of two and three dimensional percolation models. Although this quantity is essential in many applications, e.g., explaining colligative properties, and interpreting low-angle light-scattering data, no systematic studies of it have been done before this work. Recently carried out detailed computer simulations show that the mean number of clusters is given to high accuracy by several of there approximations. Extensions of this work will allow calculation of the complete cluster size distribution.

  12. Sputtered Clusters from Niobium-Vanadium Alloys

    DEFF Research Database (Denmark)

    Schou, Jørgen; Hofer, W. O.

    1982-01-01

    A series of Nb&z.sbnd;V alloys have been irradiated by 6 keV argon ions. Homonuclear and heteronuclear clusters emitted from these alloys have been studied by means of post-ionization and/or secondary ion mass spectrometry. The intensity of clusters of atomic masses up to approximately 300 amu...... was related to the concentrations of Nb and V in the alloys. In addition, the behaviour of polyatomic cluster yields as a function of partial oxygen pressure was studied. At partial pressures larger than approximately 10 6Torr, the yields decreased with increasing partial pressures. By inclusion of the post......-ionized neutrals, the total secondary particle intensity was increased by a factor of 1.5 for clusters up to atomic masses of around 200 amu. Scanning electron microscopy revealed a varied surface topography with large differences from grain to grain for irradiated samples exposed for doses larger than 1018 atoms...

  13. Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

    2009-12-22

    Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

  14. Introduction to cluster dynamics

    CERN Document Server

    Reinhard, Paul-Gerhard

    2008-01-01

    Clusters as mesoscopic particles represent an intermediate state of matter between single atoms and solid material. The tendency to miniaturise technical objects requires knowledge about systems which contain a ""small"" number of atoms or molecules only. This is all the more true for dynamical aspects, particularly in relation to the qick development of laser technology and femtosecond spectroscopy. Here, for the first time is a highly qualitative introduction to cluster physics. With its emphasis on cluster dynamics, this will be vital to everyone involved in this interdisciplinary subje

  15. The concept of cluster

    DEFF Research Database (Denmark)

    Laursen, Lea Louise Holst; Møller, Jørgen

    2013-01-01

    villages in order to secure their future. This paper will address the concept of cluster-villages as a possible approach to strengthen the conditions of contemporary Danish villages. Cluster-villages is a concept that gather a number of villages in a network-structure where the villages both work together...... to forskellige positioner ser vi en ny mulighed for landsbyudvikling, som vi kalder Clustervillages. In order to investigate the potentials and possibilities of the cluster-village concept the paper will seek to unfold the concept strategically; looking into the benefits of such concept. Further, the paper seeks...

  16. Partially supervised speaker clustering.

    Science.gov (United States)

    Tang, Hao; Chu, Stephen Mingyu; Hasegawa-Johnson, Mark; Huang, Thomas S

    2012-05-01

    Content-based multimedia indexing, retrieval, and processing as well as multimedia databases demand the structuring of the media content (image, audio, video, text, etc.), one significant goal being to associate the identity of the content to the individual segments of the signals. In this paper, we specifically address the problem of speaker clustering, the task of assigning every speech utterance in an audio stream to its speaker. We offer a complete treatment to the idea of partially supervised speaker clustering, which refers to the use of our prior knowledge of speakers in general to assist the unsupervised speaker clustering process. By means of an independent training data set, we encode the prior knowledge at the various stages of the speaker clustering pipeline via 1) learning a speaker-discriminative acoustic feature transformation, 2) learning a universal speaker prior model, and 3) learning a discriminative speaker subspace, or equivalently, a speaker-discriminative distance metric. We study the directional scattering property of the Gaussian mixture model (GMM) mean supervector representation of utterances in the high-dimensional space, and advocate exploiting this property by using the cosine distance metric instead of the euclidean distance metric for speaker clustering in the GMM mean supervector space. We propose to perform discriminant analysis based on the cosine distance metric, which leads to a novel distance metric learning algorithm—linear spherical discriminant analysis (LSDA). We show that the proposed LSDA formulation can be systematically solved within the elegant graph embedding general dimensionality reduction framework. Our speaker clustering experiments on the GALE database clearly indicate that 1) our speaker clustering methods based on the GMM mean supervector representation and vector-based distance metrics outperform traditional speaker clustering methods based on the “bag of acoustic features” representation and statistical

  17. Raspberry Pi super cluster

    CERN Document Server

    Dennis, Andrew K

    2013-01-01

    This book follows a step-by-step, tutorial-based approach which will teach you how to develop your own super cluster using Raspberry Pi computers quickly and efficiently.Raspberry Pi Super Cluster is an introductory guide for those interested in experimenting with parallel computing at home. Aimed at Raspberry Pi enthusiasts, this book is a primer for getting your first cluster up and running.Basic knowledge of C or Java would be helpful but no prior knowledge of parallel computing is necessary.

  18. Spanning Tree Based Attribute Clustering

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Jorge, Cordero Hernandez

    2009-01-01

    inconsistent edges from a maximum spanning tree by starting appropriate initial modes, therefore generating stable clusters. It discovers sound clusters through simple graph operations and achieves significant computational savings. We compare the Star Discovery algorithm against earlier attribute clustering...

  19. Tune Your Brown Clustering, Please

    DEFF Research Database (Denmark)

    Derczynski, Leon; Chester, Sean; Bøgh, Kenneth Sejdenfaden

    2015-01-01

    Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly...

  20. X-Ray Morphological Analysis of the Planck ESZ Clusters

    Science.gov (United States)

    Lovisari, Lorenzo; Forman, William R.; Jones, Christine; Ettori, Stefano; Andrade-Santos, Felipe; Arnaud, Monique; Démoclès, Jessica; Pratt, Gabriel W.; Randall, Scott; Kraft, Ralph

    2017-09-01

    X-ray observations show that galaxy clusters have a very large range of morphologies. The most disturbed systems, which are good to study how clusters form and grow and to test physical models, may potentially complicate cosmological studies because the cluster mass determination becomes more challenging. Thus, we need to understand the cluster properties of our samples to reduce possible biases. This is complicated by the fact that different experiments may detect different cluster populations. For example, Sunyaev-Zeldovich (SZ) selected cluster samples have been found to include a greater fraction of disturbed systems than X-ray selected samples. In this paper we determine eight morphological parameters for the Planck Early Sunyaev-Zeldovich (ESZ) objects observed with XMM-Newton. We found that two parameters, concentration and centroid shift, are the best to distinguish between relaxed and disturbed systems. For each parameter we provide the values that allow selecting the most relaxed or most disturbed objects from a sample. We found that there is no mass dependence on the cluster dynamical state. By comparing our results with what was obtained with REXCESS clusters, we also confirm that the ESZ clusters indeed tend to be more disturbed, as found by previous studies.

  1. Cluster algorithms and computational complexity

    Science.gov (United States)

    Li, Xuenan

    Cluster algorithms for the 2D Ising model with a staggered field have been studied and a new cluster algorithm for path sampling has been worked out. The complexity properties of Bak-Seppen model and the Growing network model have been studied by using the Computational Complexity Theory. The dynamic critical behavior of the two-replica cluster algorithm is studied. Several versions of the algorithm are applied to the two-dimensional, square lattice Ising model with a staggered field. The dynamic exponent for the full algorithm is found to be less than 0.5. It is found that odd translations of one replica with respect to the other together with global flips are essential for obtaining a small value of the dynamic exponent. The path sampling problem for the 1D Ising model is studied using both a local algorithm and a novel cluster algorithm. The local algorithm is extremely inefficient at low temperature, where the integrated autocorrelation time is found to be proportional to the fourth power of correlation length. The dynamic exponent of the cluster algorithm is found to be zero and therefore proved to be much more efficient than the local algorithm. The parallel computational complexity of the Bak-Sneppen evolution model is studied. It is shown that Bak-Sneppen histories can be generated by a massively parallel computer in a time that is polylog in the length of the history, which means that the logical depth of producing a Bak-Sneppen history is exponentially less than the length of the history. The parallel dynamics for generating Bak-Sneppen histories is contrasted to standard Bak-Sneppen dynamics. The parallel computational complexity of the Growing Network model is studied. The growth of the network with linear kernels is shown to be not complex and an algorithm with polylog parallel running time is found. The growth of the network with gamma ≥ 2 super-linear kernels can be realized by a randomized parallel algorithm with polylog expected running time.

  2. Galaxy clusters and cosmology

    CERN Document Server

    White, S

    1994-01-01

    Galaxy clusters are the largest coherent objects in Universe. It has been known since 1933 that their dynamical properties require either a modification of the theory of gravity, or the presence of a dominant component of unseen material of unknown nature. Clusters still provide the best laboratories for studying the amount and distribution of this dark matter relative to the material which can be observed directly -- the galaxies themselves and the hot,X-ray-emitting gas which lies between them.Imaging and spectroscopy of clusters by satellite-borne X -ray telescopes has greatly improved our knowledge of the structure and composition of this intergalactic medium. The results permit a number of new approaches to some fundamental cosmological questions,but current indications from the data are contradictory. The observed irregularity of real clusters seems to imply recent formation epochs which would require a universe with approximately the critical density. On the other hand, the large baryon fraction observ...

  3. CSR in Industrial Clusters

    DEFF Research Database (Denmark)

    Lund-Thomsen, Peter; Pillay, Renginee G.

    2012-01-01

    Purpose – The paper seeks to review the literature on CSR in industrial clusters in developing countries, identifying the main strengths, weaknesses, and gaps in this literature, pointing to future research directions and policy implications in the area of CSR and industrial cluster development....... Design/methodology/approach – A literature review is conducted of both academic and policy-oriented writings that contain the keywords “industrial clusters” and “developing countries” in combination with one or more of the following terms: corporate social responsibility, environmental management, labor...... in this field and their comments incorporated in the final version submitted to Corporate Governance. Findings – The article traces the origins of the debate on industrial clusters and CSR in developing countries back to the early 1990s when clusters began to be seen as an important vehicle for local economic...

  4. Evolution of clustered storage

    CERN Multimedia

    CERN. Geneva; Van de Vyvre, Pierre

    2007-01-01

    The session actually featured two presentations: * Evolution of clustered storage by Lance Hukill, Quantum Corporation * ALICE DAQ - Usage of a Cluster-File System: Quantum StorNext by Pierre Vande Vyvre, CERN-PH the second one prepared at short notice by Pierre (thanks!) to present how the Quantum technologies are being used in the ALICE experiment. The abstract to Mr Hukill's follows. Clustered Storage is a technology that is driven by business and mission applications. The evolution of Clustered Storage solutions starts first at the alignment between End-users needs and Industry trends: * Push-and-Pull between managing for today versus planning for tomorrow * Breaking down the real business problems to the core applications * Commoditization of clients, servers, and target devices * Interchangeability, Interoperability, Remote Access, Centralized control * Oh, and yes, there is a budget and the "real world" to deal with This presentation will talk through these needs and trends, and then ask the question, ...

  5. How Clusters Work

    Science.gov (United States)

    Technology innovation clusters are geographic concentrations of interconnected companies, universities, and other organizations with a focus on environmental technology. They play a key role in addressing the nation’s pressing environmental problems.

  6. Air void clustering.

    Science.gov (United States)

    2015-06-01

    Air void clustering around coarse aggregate in concrete has been identified as a potential source of : low strengths in concrete mixes by several Departments of Transportation around the country. Research was : carried out to (1) develop a quantitati...

  7. Clustering of Emerging Flux

    Science.gov (United States)

    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.

  8. Balanced sampling

    NARCIS (Netherlands)

    Brus, D.J.

    2015-01-01

    In balanced sampling a linear relation between the soil property of interest and one or more covariates with known means is exploited in selecting the sampling locations. Recent developments make this sampling design attractive for statistical soil surveys. This paper introduces balanced sampling

  9. Comparison of Intra-cluster and M87 Halo Orphan Globular Clusters in the Virgo Cluster

    Science.gov (United States)

    Louie, Tiffany Kaye; Tuan, Jin Zong; Martellini, Adhara; Guhathakurta, Puragra; Toloba, Elisa; Peng, Eric; Longobardi, Alessia; Lim, Sungsoon

    2018-01-01

    We present a study of “orphan” globular clusters (GCs) — GCs with no identifiable nearby host galaxy — discovered in NGVS, a 104 deg2 CFHT/MegaCam imaging survey. At the distance of the Virgo cluster, GCs are bright enough to make good spectroscopic targets and many are barely resolved in good ground-based seeing. Our orphan GC sample is derived from a subset of NGVS-selected GC candidates that were followed up with Keck/DEIMOS spectroscopy. While our primary spectroscopic targets were candidate GC satellites of Virgo dwarf elliptical and ultra-diffuse galaxies, many objects turned out to be non-satellites based on a radial velocity mismatch with the Virgo galaxy they are projected close to. Using a combination of spectral characteristics (e.g., absorption vs. emission), Gaussian mixture modeling of radial velocity and positions, and extreme deconvolution analysis of ugrizk photometry and image morphology, these non-satellites were classified into: (1) intra-cluster GCs (ICGCs) in the Virgo cluster, (2) GCs in the outer halo of M87, (3) foreground Milky Way stars, and (4) background galaxies. The statistical distinction between ICGCs and M87 halo GCs is based on velocity distributions (mean of 1100 vs. 1300 km/s and dispersions of 700 vs. 400 km/s, respectively) and radial distribution (diffuse vs. centrally concentrated, respectively). We used coaddition to increase the spectral SNR for the two classes of orphan GCs and measured the equivalent widths (EWs) of the Mg b and H-beta absorption lines. These EWs were compared to single stellar population models to obtain mean age and metallicity estimates. The ICGCs and M87 halo GCs have = –0.6+/–0.3 and –0.4+/–0.3 dex, respectively, and mean ages of >~ 5 and >~ 10 Gyr, respectively. This suggests the M87 halo GCs formed in relatively high-mass galaxies that avoided being tidally disrupted by M87 until they were close to the cluster center, while IGCCs formed in relatively low-mass galaxies that were

  10. The Cluster-EAGLE project: global properties of simulated clusters with resolved galaxies

    Science.gov (United States)

    Barnes, David J.; Kay, Scott T.; Bahé, Yannick M.; Dalla Vecchia, Claudio; McCarthy, Ian G.; Schaye, Joop; Bower, Richard G.; Jenkins, Adrian; Thomas, Peter A.; Schaller, Matthieu; Crain, Robert A.; Theuns, Tom; White, Simon D. M.

    2017-10-01

    We introduce the Cluster-EAGLE (c-eagle) simulation project, a set of cosmological hydrodynamical zoom simulations of the formation of 30 galaxy clusters in the mass range of 1014 simulations adopt the state-of-the-art eagle galaxy formation model, with a gas particle mass of 1.8 × 106 M⊙ and physical softening length of 0.7 kpc. In this paper, we introduce the sample and present the low-redshift global properties of the clusters. We calculate the X-ray properties in a manner consistent with observational techniques, demonstrating the bias and scatter introduced by using estimated masses. We find the total stellar content and black hole masses of the clusters to be in good agreement with the observed relations. However, the clusters are too gas rich, suggesting that the active galactic nucleus (AGN) feedback model is not efficient enough at expelling gas from the high-redshift progenitors of the clusters. The X-ray properties, such as the spectroscopic temperature and the soft-band luminosity, and the Sunyaev-Zel'dovich properties are in reasonable agreement with the observed relations. However, the clusters have too high central temperatures and larger-than-observed entropy cores, which is likely driven by the AGN feedback after the cluster core has formed. The total metal content and its distribution throughout the intracluster medium are a good match to the observations.

  11. Globular clusters with Gaia

    Science.gov (United States)

    Pancino, E.; Bellazzini, M.; Giuffrida, G.; Marinoni, S.

    2017-05-01

    The treatment of crowded fields in Gaia data will only be a reality in a few years from now. In particular, for globular clusters, only the end-of-mission data (public in 2022-2023) will have the necessary full crowding treatment and will reach sufficient quality for the faintest stars. As a consequence, the work on the deblending and decontamination pipelines is still ongoing. We describe the present status of the pipelines for different Gaia instruments, and we model the end-of-mission crowding errors on the basis of available information. We then apply the nominal post-launch Gaia performances, appropriately worsened by the estimated crowding errors, to a set of 18 simulated globular clusters with different concentration, distance and field contamination. We conclude that there will be 103-104 stars with astrometric performances virtually untouched by crowding (contaminated by <1 mmag) in the majority of clusters. The most limiting factor will be field crowding, not cluster crowding: the most contaminated clusters will only contain 10-100 clean stars. We also conclude that (i) the systemic proper motions and parallaxes will be determined to 1 per cent or better up to ≃15 kpc, and the nearby clusters will have radial velocities to a few km s-1; (ii) internal kinematics will be of unprecedented quality, cluster masses will be determined to ≃10 per cent up to 15 kpc and beyond, and it will be possible to identify differences of a few km s-1 or less in the kinematics (if any) of cluster sub-populations up to 10 kpc and beyond; (iii) the brightest stars (V ≃ 17 mag) will have space-quality, wide-field photometry (mmag errors), and all Gaia photometry will have 1-3 per cent errors on the absolute photometric calibration.

  12. Structure of Silicon Clusters

    OpenAIRE

    Pan, Jun; Bahel, Atul; Ramakrishna, Mushti V.

    1995-01-01

    We determined the structures of silicon clusters in the 11-14 atom size range using the tight-binding molecular dynamics method. These calculations reveal that \\Si{11} is an icosahedron with one missing cap, \\Si{12} is a complete icosahedron, \\Si{13} is a surface capped icosahedron, and \\Si{14} is a 4-4-4 layer structure with two caps. The characteristic feature of these clusters is that they are all surface.

  13. GSAMPLE: Stata module to draw a random sample

    OpenAIRE

    Jann, Ben

    2006-01-01

    gsample draws a random sample from the data in memory. Simple random sampling (SRS) is supported, as well as unequal probability sampling (UPS), of which sampling with probabilities proportional to size (PPS) is a special case. Both methods, SRS and UPS/PPS, provide sampling with replacement and sampling without replacement. Furthermore, stratified sampling and cluster sampling is supported.

  14. Investigation of clustering in sets of analytical data

    Energy Technology Data Exchange (ETDEWEB)

    Kajfosz, J. [Institute of Nuclear Physics, Cracow (Poland)

    1993-04-01

    Foundation of the statistical method of cluster analysis are briefly presented and its usefulness for the examination and evaluation of analytical data obtained from series of samples investigated by PIXE, PIGE or other methods is discussed. A simple program for fast examination of dissimilarities between samples within an investigated series is described. Useful information on clustering for several hundreds of samples can be obtained with minimal time and storage requirements. (author). 5 refs, 10 figs.

  15. Extragalactic jets as probes of distant clusters of galaxies and the clusters occupied by bent radio AGN (COBRA) survey

    Science.gov (United States)

    Blanton, Elizabeth L.; Paterno-Mahler, Rachel; Wing, Joshua D.; Ashby, M. L. N.; Golden-Marx, Emmet; Brodwin, Mark; Douglass, E. M.; Randall, Scott W.; Clarke, T. E.

    2015-03-01

    We are conducting a large survey of distant clusters of galaxies using radio sources with bent jets and lobes as tracers. These radio sources are driven by AGN and achieve their bent morphologies through interaction with the surrounding gas found in clusters of galaxies. Based on low-redshift studies, these types of sources can be used to identify clusters very efficiently. We present initial results from our survey of 653 bent-double radio sources with optical hosts too faint to appear in the SDSS. The sample was observed in the infrared with Spitzer, and it has revealed ~200 distant clusters or proto-clusters in the redshift range z ~ 0.7 - 3.0. The sample of bent-doubles contains both quasars and radio galaxies enabling us to study both radiative and kinetic mode feedback in cluster and group environments at a wide range of redshifts.

  16. Determination of atomic cluster structure with cluster fusion algorithm

    DEFF Research Database (Denmark)

    Obolensky, Oleg I.; Solov'yov, Ilia; Solov'yov, Andrey V.

    2005-01-01

    We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters.......We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters....

  17. Uniform deposition of size-selected clusters using Lissajous scanning

    Energy Technology Data Exchange (ETDEWEB)

    Beniya, Atsushi; Watanabe, Yoshihide, E-mail: e0827@mosk.tytlabs.co.jp [Toyota Central R& D Labs., Inc., 41-1 Yokomichi, Nagakute, Aichi 480-1192 (Japan); Hirata, Hirohito [Toyota Motor Corporation, 1200 Mishuku, Susono, Shizuoka 410-1193 (Japan)

    2016-05-15

    Size-selected clusters can be deposited on the surface using size-selected cluster ion beams. However, because of the cross-sectional intensity distribution of the ion beam, it is difficult to define the coverage of the deposited clusters. The aggregation probability of the cluster depends on coverage, whereas cluster size on the surface depends on the position, despite the size-selected clusters are deposited. It is crucial, therefore, to deposit clusters uniformly on the surface. In this study, size-selected clusters were deposited uniformly on surfaces by scanning the cluster ions in the form of Lissajous pattern. Two sets of deflector electrodes set in orthogonal directions were placed in front of the sample surface. Triangular waves were applied to the electrodes with an irrational frequency ratio to ensure that the ion trajectory filled the sample surface. The advantages of this method are simplicity and low cost of setup compared with raster scanning method. The authors further investigated CO adsorption on size-selected Pt{sub n} (n = 7, 15, 20) clusters uniformly deposited on the Al{sub 2}O{sub 3}/NiAl(110) surface and demonstrated the importance of uniform deposition.

  18. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2006-01-01

    We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

  19. Statistical estimation of percolation cluster parameters

    OpenAIRE

    Moskalev, P. V.; Grebennikov, K. V.; Shitov, V. V.

    2011-01-01

    In this paper we study statistical methods of parameters estimation of the site percolation model. Advantages of the proposed method is demonstrated for the computing of the confidence interval of mass fractal dimension of a percolation clusters sampling, formed by the Monte Carlo method.

  20. Clustering metagenomic sequences with interpolated Markov models

    Science.gov (United States)

    2010-01-01

    Background Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and sequenced by traditional methods. Because the output from metagenomic sequencing is a large set of reads of unknown origin, clustering reads together that were sequenced from the same species is a crucial analysis step. Many effective approaches to this task rely on sequenced genomes in public databases, but these genomes are a highly biased sample that is not necessarily representative of environments interesting to many metagenomics projects. Results We present SCIMM (Sequence Clustering with Interpolated Markov Models), an unsupervised sequence clustering method. SCIMM achieves greater clustering accuracy than previous unsupervised approaches. We examine the limitations of unsupervised learning on complex datasets, and suggest a hybrid of SCIMM and supervised learning method Phymm called PHYSCIMM that performs better when evolutionarily close training genomes are available. Conclusions SCIMM and PHYSCIMM are highly accurate methods to cluster metagenomic sequences. SCIMM operates entirely unsupervised, making it ideal for environments containing mostly novel microbes. PHYSCIMM uses supervised learning to improve clustering in environments containing microbial strains from well-characterized genera. SCIMM and PHYSCIMM are available open source from http://www.cbcb.umd.edu/software/scimm. PMID:21044341

  1. Clustering metagenomic sequences with interpolated Markov models.

    Science.gov (United States)

    Kelley, David R; Salzberg, Steven L

    2010-11-02

    Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and sequenced by traditional methods. Because the output from metagenomic sequencing is a large set of reads of unknown origin, clustering reads together that were sequenced from the same species is a crucial analysis step. Many effective approaches to this task rely on sequenced genomes in public databases, but these genomes are a highly biased sample that is not necessarily representative of environments interesting to many metagenomics projects. We present SCIMM (Sequence Clustering with Interpolated Markov Models), an unsupervised sequence clustering method. SCIMM achieves greater clustering accuracy than previous unsupervised approaches. We examine the limitations of unsupervised learning on complex datasets, and suggest a hybrid of SCIMM and supervised learning method Phymm called PHYSCIMM that performs better when evolutionarily close training genomes are available. SCIMM and PHYSCIMM are highly accurate methods to cluster metagenomic sequences. SCIMM operates entirely unsupervised, making it ideal for environments containing mostly novel microbes. PHYSCIMM uses supervised learning to improve clustering in environments containing microbial strains from well-characterized genera. SCIMM and PHYSCIMM are available open source from http://www.cbcb.umd.edu/software/scimm.

  2. Clustering metagenomic sequences with interpolated Markov models

    Directory of Open Access Journals (Sweden)

    Kelley David R

    2010-11-01

    Full Text Available Abstract Background Sequencing of environmental DNA (often called metagenomics has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and sequenced by traditional methods. Because the output from metagenomic sequencing is a large set of reads of unknown origin, clustering reads together that were sequenced from the same species is a crucial analysis step. Many effective approaches to this task rely on sequenced genomes in public databases, but these genomes are a highly biased sample that is not necessarily representative of environments interesting to many metagenomics projects. Results We present SCIMM (Sequence Clustering with Interpolated Markov Models, an unsupervised sequence clustering method. SCIMM achieves greater clustering accuracy than previous unsupervised approaches. We examine the limitations of unsupervised learning on complex datasets, and suggest a hybrid of SCIMM and supervised learning method Phymm called PHYSCIMM that performs better when evolutionarily close training genomes are available. Conclusions SCIMM and PHYSCIMM are highly accurate methods to cluster metagenomic sequences. SCIMM operates entirely unsupervised, making it ideal for environments containing mostly novel microbes. PHYSCIMM uses supervised learning to improve clustering in environments containing microbial strains from well-characterized genera. SCIMM and PHYSCIMM are available open source from http://www.cbcb.umd.edu/software/scimm.

  3. NON-EQUILIBRIUM ELECTRONS IN THE OUTSKIRTS OF GALAXY CLUSTERS

    Energy Technology Data Exchange (ETDEWEB)

    Avestruz, Camille; Nagai, Daisuke; Lau, Erwin T. [Department of Physics, Yale University, New Haven, CT 06520 (United States); Nelson, Kaylea, E-mail: camille.avestruz@yale.edu, E-mail: camille.avestruz@yale.edu [Yale Center for Astronomy and Astrophysics, Yale University, New Haven, CT 06520 (United States)

    2015-08-01

    The analysis of X-ray and Sunyaev–Zel’dovich measurements of the intracluster medium (ICM) assumes that electrons are in thermal equilibrium with ions in the plasma. However, in the outskirts of galaxy clusters, the electron–ion equilibration timescale can become comparable to the Hubble time, leading to systematic biases in cluster mass estimates and mass-observable scaling relations. To quantify an upper limit of the impact of non-equilibrium electrons, we use a mass-limited sample of simulated galaxy clusters taken from a cosmological simulation with a two-temperature model that assumes the Spitzer equilibration time for the electrons and ions. We show that the temperature bias is more pronounced in more massive and rapidly accreting clusters. For the most extreme case, we find that the bias is of the order of 10% at half of the cluster virial radius and increases to 40% at the edge of the cluster. Gas in filaments is less susceptible to the non-equilibrium effect, leading to azimuthal variations in the temperature bias at large cluster-centric radii. Using mock Chandra observations of simulated clusters, we show that the bias manifests in ultra-deep X-ray observations of cluster outskirts and quantify the resulting biases in hydrostatic mass and cluster temperature derived from these observations. We provide a mass-dependent fitting function for the temperature bias profile, which can be useful for modeling the effect of electron-ion equilibration in galaxy clusters.

  4. The Alignment effect of brightest cluster galaxies in the SDSS

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Rita S.J.; Annis, Jim; Strauss, Michael A.; Lupton, Robert H.; Bahcall, Neta A.; Gunn, James E.; Kepner, Jeremy V.; Postman, Marc

    2001-10-01

    One of the most vital observational clues for unraveling the origin of Brightest Cluster Galaxies (BCG) is the observed alignment of the BCGs with their host cluster and its surroundings. We have examined the BCG-cluster alignment effect, using clusters of galaxies detected from the Sloan Digital Sky Survey (SDSS). We find that the BCGs are preferentially aligned with the principal axis of their hosts, to a much higher redshift (z >~ 0.3) than probed by previous studies (z <~ 0.1). The alignment effect strongly depends on the magnitude difference of the BCG and the second and third brightest cluster members: we find a strong alignment effect for the dominant BCGs, while less dominant BCGs do not show any departure from random alignment with respect to the cluster. We therefore claim that the alignment process originates from the same process that makes the BCG grow dominant, be it direct mergers in the early stage of cluster formation, or a later process that resembles the galactic cannibalism scenario. We do not find strong evidence for (or against) redshift evolution between 0sample size (< 200 clusters). However, we have developed a framework by which we can examine many more clusters in an automated fashion for the upcoming SDSS cluster catalogs, which will provide us with better statistics for systematic investigations of the alignment with redshift, richness and morphology of both the cluster and the BCG.

  5. Subspace K-means clustering

    NARCIS (Netherlands)

    Timmerman, Marieke E.; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

    2013-01-01

    To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the

  6. FINDCLUS : Fuzzy INdividual Differences CLUStering

    NARCIS (Netherlands)

    Giordani, Paolo; Kiers, Henk A. L.

    ADditive CLUStering (ADCLUS) is a tool for overlapping clustering of two-way proximity matrices (objects x objects). In Simple Additive Fuzzy Clustering (SAFC), a variant of ADCLUS is introduced providing a fuzzy partition of the objects, that is the objects belong to the clusters with the so-called

  7. The Baltimore and Utrecht models for cluster dissolution

    NARCIS (Netherlands)

    Lamers, H.J.G.L.M.

    2009-01-01

    The analysis of the age distributions of star cluster samples of different galaxies has resulted in two very different empirical models for the dissolution of star clusters: the Baltimore model and the Utrecht model. I describe these two models and their differences. The Baltimore model implies that

  8. Metal oxide/polyaniline nanocomposites: Cluster size and ...

    Indian Academy of Sciences (India)

    Wintec

    Metal oxide/polyaniline nanocomposites: Cluster size and composition dependent structural and ... tions have been studied to understand the effects of particle size, cluster size and magnetic inter-particle inter- actions. The sizes of the .... vibrating sample magnetometer (VSM-5, TOEI Industry. Co. Ltd, Tokyo, Japan).

  9. The connection between mass and light in galaxy clusters

    NARCIS (Netherlands)

    Sifón, Andalaft C.J.

    2016-01-01

    Galaxy clusters are the largest reservoirs of matter in the Universe, and as such are unique laboratories to understand the connection between dark and luminous, 'normal' matter. We use several techniques and galaxy cluster samples to study this connection from various angles. In particular, we try

  10. Cluster Implantation and Deposition Apparatus

    DEFF Research Database (Denmark)

    Hanif, Muhammad; Popok, Vladimir

    2015-01-01

    In the current report, a design and capabilities of a cluster implantation and deposition apparatus (CIDA) involving two different cluster sources are described. The clusters produced from gas precursors (Ar, N etc.) by PuCluS-2 can be used to study cluster ion implantation in order to develop...... contributions to the theory of cluster stopping in matter as well as for practical applications requiring ultra-shallow implantation and modification of surfaces on the nanoscale. Metal clusters from the magnetron cluster source are of interest for the production of optical sensors to detect specific biological...

  11. Weighing galaxy clusters with gas. II. On the origin of hydrostatic mass bias in ΛCDM galaxy clusters

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, Kaylea; Nagai, Daisuke; Yu, Liang [Department of Astronomy, Yale University, New Haven, CT 06520 (United States); Lau, Erwin T.; Rudd, Douglas H., E-mail: kaylea.nelson@yale.edu [Department of Physics, Yale University, New Haven, CT 06520 (United States)

    2014-02-20

    The use of galaxy clusters as cosmological probes hinges on our ability to measure their masses accurately and with high precision. Hydrostatic mass is one of the most common methods for estimating the masses of individual galaxy clusters, which suffer from biases due to departures from hydrostatic equilibrium. Using a large, mass-limited sample of massive galaxy clusters from a high-resolution hydrodynamical cosmological simulation, in this work we show that in addition to turbulent and bulk gas velocities, acceleration of gas introduces biases in the hydrostatic mass estimate of galaxy clusters. In unrelaxed clusters, the acceleration bias is comparable to the bias due to non-thermal pressure associated with merger-induced turbulent and bulk gas motions. In relaxed clusters, the mean mass bias due to acceleration is small (≲ 3%), but the scatter in the mass bias can be reduced by accounting for gas acceleration. Additionally, this acceleration bias is greater in the outskirts of higher redshift clusters where mergers are more frequent and clusters are accreting more rapidly. Since gas acceleration cannot be observed directly, it introduces an irreducible bias for hydrostatic mass estimates. This acceleration bias places limits on how well we can recover cluster masses from future X-ray and microwave observations. We discuss implications for cluster mass estimates based on X-ray, Sunyaev-Zel'dovich effect, and gravitational lensing observations and their impact on cluster cosmology.

  12. Globular Clusters - Guides to Galaxies

    CERN Document Server

    Richtler, Tom; Joint ESO-FONDAP Workshop on Globular Clusters

    2009-01-01

    The principal question of whether and how globular clusters can contribute to a better understanding of galaxy formation and evolution is perhaps the main driving force behind the overall endeavour of studying globular cluster systems. Naturally, this splits up into many individual problems. The objective of the Joint ESO-FONDAP Workshop on Globular Clusters - Guides to Galaxies was to bring together researchers, both observational and theoretical, to present and discuss the most recent results. Topics covered in these proceedings are: internal dynamics of globular clusters and interaction with host galaxies (tidal tails, evolution of cluster masses), accretion of globular clusters, detailed descriptions of nearby cluster systems, ultracompact dwarfs, formations of massive clusters in mergers and elsewhere, the ACS Virgo survey, galaxy formation and globular clusters, dynamics and kinematics of globular cluster systems and dark matter-related problems. With its wide coverage of the topic, this book constitute...

  13. Reproducibility of Cognitive Profiles in Psychosis Using Cluster Analysis.

    Science.gov (United States)

    Lewandowski, Kathryn E; Baker, Justin T; McCarthy, Julie M; Norris, Lesley A; Öngür, Dost

    2017-10-18

    Cognitive dysfunction is a core symptom dimension that cuts across the psychoses. Recent findings support classification of patients along the cognitive dimension using cluster analysis; however, data-derived groupings may be highly determined by sampling characteristics and the measures used to derive the clusters, and so their interpretability must be established. We examined cognitive clusters in a cross-diagnostic sample of patients with psychosis and associations with clinical and functional outcomes. We then compared our findings to a previous report of cognitive clusters in a separate sample using a different cognitive battery. Participants with affective or non-affective psychosis (n=120) and healthy controls (n=31) were administered the MATRICS Consensus Cognitive Battery, and clinical and community functioning assessments. Cluster analyses were performed on cognitive variables, and clusters were compared on demographic, cognitive, and clinical measures. Results were compared to findings from our previous report. A four-cluster solution provided a good fit to the data; profiles included a neuropsychologically normal cluster, a globally impaired cluster, and two clusters of mixed profiles. Cognitive burden was associated with symptom severity and poorer community functioning. The patterns of cognitive performance by cluster were highly consistent with our previous findings. We found evidence of four cognitive subgroups of patients with psychosis, with cognitive profiles that map closely to those produced in our previous work. Clusters were associated with clinical and community variables and a measure of premorbid functioning, suggesting that they reflect meaningful groupings: replicable, and related to clinical presentation and functional outcomes. (JINS, 2017, 23, 1-9).

  14. Calculating Cluster Masses via the Sunyaev-Zel'dovich Effect

    Science.gov (United States)

    Lindley, Ashley; Landry, D.; Bonamente, M.; Joy, M.; Bulbul, E.; Carlstrom, J. E.; Culverhouse, T. L.; Gralla, M.; Greer, C.; Hawkins, D.; Lamb, J. W.; Leitch, E. M.; Marrone, D. P.; Miller, A.; Mroczkowski, T.; Muchovej, S.; Plagge, T.; Woody, D.

    2012-05-01

    Accurate measurements of the total mass of galaxy clusters are key for measuring the cluster mass function and therefore investigating the evolution of the universe. We apply two new methods to measure cluster masses for five galaxy clusters contained within the Brightest Cluster Sample (BCS), an X-ray luminous statistically complete sample of 35 clusters at z=0.15-0.30. These methods distinctively use only observations of the Sunyaev-Zel'dovich (SZ) effect, for which the brightness is redshift independent. At the low redshifts of the BCS, X-ray observations can easily be used to determine cluster masses, providing convenient calibrators for our SZ mass calculations. These clusters have been observed with the Sunyaev-Zel'dovich Array (SZA), an interferometer that is part of the Combined Array for Research in Millimeter-wave Astronomy (CARMA) that has been optimized for accurate measurement of the SZ effect in clusters of galaxies at 30 GHz. One method implements a scaling relation that relates the integrated pressure, Y, as determined by the SZ observations to the mass of the cluster calculated via optical weak lensing. The second method makes use of the Virial theorem to determine the mass given the integrated pressure of the cluster. We find that masses calculated utilizing these methods within a radius r500 are consistent with X-ray masses, calculated by manipulating the surface brightness and temperature data within the same radius, thus concluding that these are viable methods for the determination of cluster masses via the SZ effect. We present preliminary results of our analysis for five galaxy clusters.

  15. Clustering Game Behavior Data

    DEFF Research Database (Denmark)

    Bauckhage, C.; Drachen, Anders; Sifa, Rafet

    2015-01-01

    Recent years have seen a deluge of behavioral data from players hitting the game industry. Reasons for this data surge are many and include the introduction of new business models, technical innovations, the popularity of online games, and the increasing persistence of games. Irrespective...... of the causes, the proliferation of behavioral data poses the problem of how to derive insights therefrom. Behavioral data sets can be large, time-dependent and high-dimensional. Clustering offers a way to explore such data and to discover patterns that can reduce the overall complexity of the data. Clustering...... and other techniques for player profiling and play style analysis have, therefore, become popular in the nascent field of game analytics. However, the proper use of clustering techniques requires expertise and an understanding of games is essential to evaluate results. With this paper, we address game data...

  16. Exotic cluster structures on

    CERN Document Server

    Gekhtman, M; Vainshtein, A

    2017-01-01

    This is the second paper in the series of papers dedicated to the study of natural cluster structures in the rings of regular functions on simple complex Lie groups and Poisson-Lie structures compatible with these cluster structures. According to our main conjecture, each class in the Belavin-Drinfeld classification of Poisson-Lie structures on \\mathcal{G} corresponds to a cluster structure in \\mathcal{O}(\\mathcal{G}). The authors have shown before that this conjecture holds for any \\mathcal{G} in the case of the standard Poisson-Lie structure and for all Belavin-Drinfeld classes in SL_n, n<5. In this paper the authors establish it for the Cremmer-Gervais Poisson-Lie structure on SL_n, which is the least similar to the standard one.

  17. Data Partitioning Technique to Enhance DBSCAN Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Safaa O. Al-Mamory

    2017-02-01

    Full Text Available Among density- based clustering techniques ,DBSCAN is a typical one because it can detect clusters with widely different shapes and sizes, but it fails to find clusters with different densities and for that we propose a new technique to enhance the performance of DBSCAN on data with different densities ,the new solution contains two novel tech¬niques ,one is the separation (partitioning technique that separate data into sparse and dense regions, and the other is the sampling technique that produce data with only one density distribution. the experimental results on synthetic data show that the new tech¬nique has a clustering

  18. Refractory chronic cluster headache

    DEFF Research Database (Denmark)

    Mitsikostas, Dimos D; Edvinsson, Lars; Jensen, Rigmor H

    2014-01-01

    Chronic cluster headache (CCH) often resists to prophylactic pharmaceutical treatments resulting in patients' life damage. In this rare but pragmatic situation escalation to invasive management is needed but framing criteria are lacking. We aimed to reach a consensus for refractory CCH definition...... for clinical and research use. The preparation of the final consensus followed three stages. Internal between authors, a larger between all European Headache Federation members and finally an international one among all investigators that have published clinical studies on cluster headache the last five years...

  19. Clustering via Kernel Decomposition

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan

    2006-01-01

    Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....

  20. Emergence of regional clusters

    DEFF Research Database (Denmark)

    Dahl, Michael S.; Østergaard, Christian Richter; Dalum, Bent

    2010-01-01

    The literature on regional clusters has increased considerably during the last decade. The emergence and growth patterns are usually explained by such factors as unique local culture, regional capabilities, tacit knowledge or the existence of location-specific externalities (knowledge spillovers......, networks, labour market pooling and specialised suppliers). However, these factors are not sufficient to explain the early formation of clusters. The dominant theories focus more on explaining ex-post dynamics than their early development. This chapter focuses on the early phase and uses an alternative...

  1. South Asian Cluster

    Directory of Open Access Journals (Sweden)

    Ionel Sergiu Pirju

    2014-12-01

    Full Text Available This article aims at presenting the South Asian cluster composed of India, Indonesia, Iran and Malaysia, the intercultural values that characterizes it, the supported leadership style and tracing the main macroeconomic considerations which characterizes them. The research is synchronic, analysing the contemporary situation of these countries without reference to their evolution in time, by using the positivist paradigm that explains the reality at one point. It will be analysed the overall cluster with the existing interactions between the countries that composes it, while the article being one of information will avoid building recommendation, or new theories.

  2. The effect of cluster size variability on statistical power in cluster-randomized trials.

    Directory of Open Access Journals (Sweden)

    Stephen A Lauer

    Full Text Available The frequency of cluster-randomized trials (CRTs in peer-reviewed literature has increased exponentially over the past two decades. CRTs are a valuable tool for studying interventions that cannot be effectively implemented or randomized at the individual level. However, some aspects of the design and analysis of data from CRTs are more complex than those for individually randomized controlled trials. One of the key components to designing a successful CRT is calculating the proper sample size (i.e. number of clusters needed to attain an acceptable level of statistical power. In order to do this, a researcher must make assumptions about the value of several variables, including a fixed mean cluster size. In practice, cluster size can often vary dramatically. Few studies account for the effect of cluster size variation when assessing the statistical power for a given trial. We conducted a simulation study to investigate how the statistical power of CRTs changes with variable cluster sizes. In general, we observed that increases in cluster size variability lead to a decrease in power.

  3. Subaru Weak Lensing Measurements of Four Strong Lensing Clusters: Are Lensing Clusters Over-Concentrated?

    Energy Technology Data Exchange (ETDEWEB)

    Oguri, Masamune; Hennawi, Joseph F.; Gladders, Michael D.; Dahle, Haakon; Natarajan, Priyamvada; Dalal, Neal; Koester, Benjamin P.; Sharon, Keren; Bayliss, Matthew

    2009-01-29

    We derive radial mass profiles of four strong lensing selected clusters which show prominent giant arcs (Abell 1703, SDSS J1446+3032, SDSS J1531+3414, and SDSS J2111-0115), by combining detailed strong lens modeling with weak lensing shear measured from deep Subaru Suprime-cam images. Weak lensing signals are detected at high significance for all four clusters, whose redshifts range from z = 0.28 to 0.64. We demonstrate that adding strong lensing information with known arc redshifts significantly improves constraints on the mass density profile, compared to those obtained from weak lensing alone. While the mass profiles are well fitted by the universal form predicted in N-body simulations of the {Lambda}-dominated cold dark matter model, all four clusters appear to be slightly more centrally concentrated (the concentration parameters c{sub vir} {approx} 8) than theoretical predictions, even after accounting for the bias toward higher concentrations inherent in lensing selected samples. Our results are consistent with previous studies which similarly detected a concentration excess, and increases the total number of clusters studied with the combined strong and weak lensing technique to ten. Combining our sample with previous work, we find that clusters with larger Einstein radii are more anomalously concentrated. We also present a detailed model of the lensing cluster Abell 1703 with constraints from multiple image families, and find the dark matter inner density profile to be cuspy with the slope consistent with -1, in agreement with expectations.

  4. Ananke: temporal clustering reveals ecological dynamics of microbial communities

    Directory of Open Access Journals (Sweden)

    Michael W. Hall

    2017-09-01

    Full Text Available Taxonomic markers such as the 16S ribosomal RNA gene are widely used in microbial community analysis. A common first step in marker-gene analysis is grouping genes into clusters to reduce data sets to a more manageable size and potentially mitigate the effects of sequencing error. Instead of clustering based on sequence identity, marker-gene data sets collected over time can be clustered based on temporal correlation to reveal ecologically meaningful associations. We present Ananke, a free and open-source algorithm and software package that complements existing sequence-identity-based clustering approaches by clustering marker-gene data based on time-series profiles and provides interactive visualization of clusters, including highlighting of internal OTU inconsistencies. Ananke is able to cluster distinct temporal patterns from simulations of multiple ecological patterns, such as periodic seasonal dynamics and organism appearances/disappearances. We apply our algorithm to two longitudinal marker gene data sets: faecal communities from the human gut of an individual sampled over one year, and communities from a freshwater lake sampled over eleven years. Within the gut, the segregation of the bacterial community around a food-poisoning event was immediately clear. In the freshwater lake, we found that high sequence identity between marker genes does not guarantee similar temporal dynamics, and Ananke time-series clusters revealed patterns obscured by clustering based on sequence identity or taxonomy. Ananke is free and open-source software available at https://github.com/beiko-lab/ananke.

  5. Galaxy Merger Candidates in High-redshift Cluster Environments

    Science.gov (United States)

    Delahaye, A. G.; Webb, T. M. A.; Nantais, J.; DeGroot, A.; Wilson, G.; Muzzin, A.; Yee, H. K. C.; Foltz, R.; Noble, A. G.; Demarco, R.; Tudorica, A.; Cooper, M. C.; Lidman, C.; Perlmutter, S.; Hayden, B.; Boone, K.; Surace, J.

    2017-07-01

    We compile a sample of spectroscopically and photometrically selected cluster galaxies from four high-redshift galaxy clusters (1.59Red-Sequence Cluster Survey (SpARCS), and a comparison field sample selected from the UKIDSS Deep Survey. Using near-infrared imaging from the Hubble Space Telescope, we classify potential mergers involving massive ({M}* ≥slant 3× {10}10 {M}⊙ ) cluster members by eye, based on morphological properties such as tidal distortions, double nuclei, and projected near neighbors within 20 kpc. With a catalog of 23 spectroscopic and 32 photometric massive cluster members across the four clusters and 65 spectroscopic and 26 photometric comparable field galaxies, we find that after taking into account contamination from interlopers, {11.0}-5.6+7.0 % of the cluster members are involved in potential mergers, compared to {24.7}-4.6+5.3 % of the field galaxies. We see no evidence of merger enhancement in the central cluster environment with respect to the field, suggesting that galaxy-galaxy merging is not a stronger source of galaxy evolution in cluster environments compared to the field at these redshifts.

  6. Language sampling

    DEFF Research Database (Denmark)

    Rijkhoff, Jan; Bakker, Dik

    1998-01-01

    This article has two aims: [1] to present a revised version of the sampling method that was originally proposed in 1993 by Rijkhoff, Bakker, Hengeveld and Kahrel, and [2] to discuss a number of other approaches to language sampling in the light of our own method. We will also demonstrate how our...... sampling method is used with different genetic classifications (Voegelin & Voegelin 1977, Ruhlen 1987, Grimes ed. 1997) and argue that —on the whole— our sampling technique compares favourably with other methods, especially in the case of exploratory research....

  7. 60 micron luminosity evolution of rich clusters of galaxies

    Energy Technology Data Exchange (ETDEWEB)

    Kelly, D.M.; Rieke, G.H. (Steward Observatory, Tucson, AZ (USA))

    1990-10-01

    The average 60-micron flux has been determined for a collection of optically selected galaxy clusters at redshifts ranging from 0.30 to 0.92. The result, 26 mJy per cluster, represents the faintest flux determination known of using the IRAS data base. The flux from this set of clusters has been compared to the 60-micron flux from a sample of nearby galaxy clusters. It is found that the far-infrared luminosity evolution in cluster galaxies can be no more than a factor of 1.7 from z = 0.4 to the present epoch. This upper limit is close to the evolution predicted for simple aging of the stellar populations. Additional processes such as mergers, cannibalism, or enhanced rates of starbursts appear to occur at a low enough level that they have little influence on the far-infrared emission from clusters over this redshift range. 38 refs.

  8. Large Crater Clustering tool

    Science.gov (United States)

    Laura, Jason; Skinner, James A.; Hunter, Marc A.

    2017-08-01

    In this paper we present the Large Crater Clustering (LCC) tool set, an ArcGIS plugin that supports the quantitative approximation of a primary impact location from user-identified locations of possible secondary impact craters or the long-axes of clustered secondary craters. The identification of primary impact craters directly supports planetary geologic mapping and topical science studies where the chronostratigraphic age of some geologic units may be known, but more distant features have questionable geologic ages. Previous works (e.g., McEwen et al., 2005; Dundas and McEwen, 2007) have shown that the source of secondary impact craters can be estimated from secondary impact craters. This work adapts those methods into a statistically robust tool set. We describe the four individual tools within the LCC tool set to support: (1) processing individually digitized point observations (craters), (2) estimating the directional distribution of a clustered set of craters, back projecting the potential flight paths (crater clusters or linearly approximated catenae or lineaments), (3) intersecting projected paths, and (4) intersecting back-projected trajectories to approximate the local of potential source primary craters. We present two case studies using secondary impact features mapped in two regions of Mars. We demonstrate that the tool is able to quantitatively identify primary impacts and supports the improved qualitative interpretation of potential secondary crater flight trajectories.

  9. doped stable clusters a

    Indian Academy of Sciences (India)

    ABHIJIT DUTTA

    2018-01-30

    ., showed that Ru-doped. Rh6 cluster is a better catalyst for the activation of methanol compared to pure Rh6. It may be noted that methanol activation occurs via O–H bond dissociation rather than C–H bond.25 Rhodium nano ...

  10. Greedy subspace clustering.

    Science.gov (United States)

    2016-09-01

    We consider the problem of subspace clustering: given points that lie on or near the union of many low-dimensional linear subspaces, recover the subspaces. To this end, one first identifies sets of points close to the same subspace and uses the sets ...

  11. Cluster - Smart Specialization Relationship

    Directory of Open Access Journals (Sweden)

    Florina Popa

    2016-01-01

    The paper refers to the relationship that is created in the regional economic space, between thecluster phenomenon and that of the strategy of smart specialization; in the process oftransformation of the regional economy, the smart specialization strategies take over clusters’policies and clusters integrate activities specific to areas of technological knowledge.

  12. Detecting alternative graph clusterings.

    Science.gov (United States)

    Mandala, Supreet; Kumara, Soundar; Yao, Tao

    2012-07-01

    The problem of graph clustering or community detection has enjoyed a lot of attention in complex networks literature. A quality function, modularity, quantifies the strength of clustering and on maximization yields sensible partitions. However, in most real world networks, there are an exponentially large number of near-optimal partitions with some being very different from each other. Therefore, picking an optimal clustering among the alternatives does not provide complete information about network topology. To tackle this problem, we propose a graph perturbation scheme which can be used to identify an ensemble of near-optimal and diverse clusterings. We establish analytical properties of modularity function under the perturbation which ensures diversity. Our approach is algorithm independent and therefore can leverage any of the existing modularity maximizing algorithms. We numerically show that our methodology can systematically identify very different partitions on several existing data sets. The knowledge of diverse partitions sheds more light into the topological organization and helps gain a more complete understanding of the underlying complex network.

  13. Cluster Decline and Resilience

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    -2011. Our longitudinal study reveals that technological lock-in and exit of key firms have contributed to impairment of the cluster’s resilience in adapting to disruptions. Entrepreneurship has a positive effect on cluster resilience, while multinational companies have contradicting effects by bringing...

  14. Clustering of resting state networks.

    Directory of Open Access Journals (Sweden)

    Megan H Lee

    Full Text Available The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm.The fuzzy-c-means clustering algorithm was applied to resting state fMRI data in cortical and subcortical gray matter from two groups acquired separately, one of 17 healthy individuals and the second of 21 healthy individuals. Different numbers of clusters and different starting conditions were used. A cluster dispersion measure determined the optimal numbers of clusters. An inner product metric provided a measure of similarity between different clusters. The two cluster result found the task-negative and task-positive systems. The cluster dispersion measure was minimized with seven and eleven clusters. Each of the clusters in the seven and eleven cluster result was associated with either the task-negative or task-positive system. Applying the algorithm to find seven clusters recovered previously described resting state networks, including the default mode network, frontoparietal control network, ventral and dorsal attention networks, somatomotor, visual, and language networks. The language and ventral attention networks had significant subcortical involvement. This parcellation was consistently found in a large majority of algorithm runs under different conditions and was robust to different methods of initialization.The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results. This work reinforces the observation that resting state networks are hierarchically organized.

  15. Clustering: a neural network approach.

    Science.gov (United States)

    Du, K-L

    2010-01-01

    Clustering is a fundamental data analysis method. It is widely used for pattern recognition, feature extraction, vector quantization (VQ), image segmentation, function approximation, and data mining. As an unsupervised classification technique, clustering identifies some inherent structures present in a set of objects based on a similarity measure. Clustering methods can be based on statistical model identification (McLachlan & Basford, 1988) or competitive learning. In this paper, we give a comprehensive overview of competitive learning based clustering methods. Importance is attached to a number of competitive learning based clustering neural networks such as the self-organizing map (SOM), the learning vector quantization (LVQ), the neural gas, and the ART model, and clustering algorithms such as the C-means, mountain/subtractive clustering, and fuzzy C-means (FCM) algorithms. Associated topics such as the under-utilization problem, fuzzy clustering, robust clustering, clustering based on non-Euclidean distance measures, supervised clustering, hierarchical clustering as well as cluster validity are also described. Two examples are given to demonstrate the use of the clustering methods.

  16. BRIGHTEST CLUSTER GALAXIES AT THE PRESENT EPOCH

    Energy Technology Data Exchange (ETDEWEB)

    Lauer, Tod R. [National Optical Astronomy Observatory, P.O. Box 26732, Tucson, AZ 85726 (United States); Postman, Marc [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Strauss, Michael A.; Graves, Genevieve J.; Chisari, Nora E. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

    2014-12-20

    We have obtained photometry and spectroscopy of 433 z ≤ 0.08 brightest cluster galaxies (BCGs) in a full-sky survey of Abell clusters to construct a BCG sample suitable for probing deviations from the local Hubble flow. The BCG Hubble diagram over 0 < z < 0.08 is consistent to within 2% of the Hubble relation specified by a Ω {sub m} = 0.3, Λ = 0.7 cosmology. This sample allows us to explore the structural and photometric properties of BCGs at the present epoch, their location in their hosting galaxy clusters, and the effects of the cluster environment on their structure and evolution. We revisit the L{sub m} -α relation for BCGs, which uses α, the log-slope of the BCG photometric curve of growth, to predict the metric luminosity in an aperture with 14.3 kpc radius, L{sub m} , for use as a distance indicator. Residuals in the relation are 0.27 mag rms. We measure central stellar velocity dispersions, σ, of the BCGs, finding the Faber-Jackson relation to flatten as the metric aperture grows to include an increasing fraction of the total BCG luminosity. A three-parameter ''metric plane'' relation using α and σ together gives the best prediction of L{sub m} , with 0.21 mag residuals. The distribution of projected spatial offsets, r{sub x} of BCGs from the X-ray-defined cluster center is a steep γ = –2.33 power law over 1 < r{sub x} < 10{sup 3} kpc. The median offset is ∼10 kpc, but ∼15% of the BCGs have r{sub x} > 100 kpc. The absolute cluster-dispersion normalized BCG peculiar velocity |ΔV {sub 1}|/σ {sub c} follows an exponential distribution with scale length 0.39 ± 0.03. Both L{sub m} and α increase with σ {sub c}. The α parameter is further moderated by both the spatial and velocity offset from the cluster center, with larger α correlated with the proximity of the BCG to the cluster mean velocity or potential center. At the same time, position in the cluster has little effect on L{sub m} . Likewise, residuals from

  17. Clustering context-specific gene regulatory networks.

    Science.gov (United States)

    Ramesh, Archana; Trevino, Robert; VON Hoff, Daniel D; Kim, Seungchan

    2010-01-01

    Gene regulatory networks (GRNs) learned from high throughput genomic data are often hard to visualize due to the large number of nodes and edges involved, rendering them difficult to appreciate. This becomes an important issue when modular structures are inherent in the inferred networks, such as in the recently proposed context-specific GRNs.(12) In this study, we investigate the application of graph clustering techniques to discern modularity in such highly complex graphs, focusing on context-specific GRNs. Identified modules are then associated with a subset of samples and the key pathways enriched in the module. Specifically, we study the use of Markov clustering and spectral clustering on cancer datasets to yield evidence on the possible association amongst different tumor types. Two sets of gene expression profiling data were analyzed to reveal context-specificity as well as modularity in genomic regulations.

  18. Venous Sampling

    Science.gov (United States)

    ... neck to help locate abnormally functioning glands or pituitary adenoma . This test is most often used after an unsuccessful neck exploration. Inferior petrosal sinus sampling , in which blood samples are taken from veins that drain the pituitary gland to study disorders related to pituitary hormone ...

  19. Sampling Development

    Science.gov (United States)

    Adolph, Karen E.; Robinson, Scott R.

    2011-01-01

    Research in developmental psychology requires sampling at different time points. Accurate depictions of developmental change provide a foundation for further empirical studies and theories about developmental mechanisms. However, overreliance on widely spaced sampling intervals in cross-sectional and longitudinal designs threatens the validity of…

  20. Language sampling

    DEFF Research Database (Denmark)

    Rijkhoff, Jan; Bakker, Dik

    1998-01-01

    This article has two aims: [1] to present a revised version of the sampling method that was originally proposed in 1993 by Rijkhoff, Bakker, Hengeveld and Kahrel, and [2] to discuss a number of other approaches to language sampling in the light of our own method. We will also demonstrate how our...

  1. The Richness Dependence of Galaxy Cluster Correlations: Results From A Redshift Survey Of Rich APM Clusters

    Science.gov (United States)

    Croft, R. A. C.; Dalton, G. B.; Efstathiou, G.; Sutherland, W. J.; Maddox, S. J.

    1997-01-01

    We analyze the spatial clustering properties of a new catalog of very rich galaxy clusters selected from the APM Galaxy Survey. These clusters are of comparable richness and space density to Abell Richness Class greater than or equal to 1 clusters, but selected using an objective algorithm from a catalog demonstrably free of artificial inhomogeneities. Evaluation of the two-point correlation function xi(sub cc)(r) for the full sample and for richer subsamples reveals that the correlation amplitude is consistent with that measured for lower richness APM clusters and X-ray selected clusters. We apply a maximum likelihood estimator to find the best fitting slope and amplitude of a power law fit to x(sub cc)(r), and to estimate the correlation length r(sub 0) (the value of r at which xi(sub cc)(r) is equal to unity). For clusters with a mean space density of 1.6 x 10(exp -6) h(exp 3) MpC(exp -3) (equivalent to the space density of Abell Richness greater than or equal to 2 clusters), we find r(sub 0) = 21.3(+11.1/-9.3) h(exp -1) Mpc (95% confidence limits). This is consistent with the weak richness dependence of xi(sub cc)(r) expected in Gaussian models of structure formation. In particular, the amplitude of xi(sub cc)(r) at all richnesses matches that of xi(sub cc)(r) for clusters selected in N-Body simulations of a low density Cold Dark Matter model.

  2. Magnetic clusters in ilmenite-hematite solid solutions

    DEFF Research Database (Denmark)

    Frandsen, Cathrine; Burton, B. P.; Rasmussen, Helge Kildahl

    2010-01-01

    We report the use of high-field 57Fe Mössbauer spectroscopy to resolve the magnetic ordering of ilmenite-hematite [xFeTiO3−(1−x)Fe2O3] solid solutions with x>0.5. We find that nanometer-sized hematite clusters exist within an ilmenite-like matrix. Although both phases are antiferromagnetically...... ordered, the hematite clusters show ferrimagnetic behavior due to superexchange coupling with Fe2+ in ilmenite. For ilmenite-rich samples (x=0.95), the clusters are isolated and superparamagnetic. For more hematite-rich samples with x=0.80 and x=0.70, the clusters interact to form a cluster glass....

  3. Ab initio Monte Carlo investigation of small lithium clusters.

    Energy Technology Data Exchange (ETDEWEB)

    Srinivas, S.

    1999-06-16

    Structural and thermal properties of small lithium clusters are studied using ab initio-based Monte Carlo simulations. The ab initio scheme uses a Hartree-Fock/density functional treatment of the electronic structure combined with a jump-walking Monte Carlo sampling of nuclear configurations. Structural forms of Li{sub 8} and Li{sub 9}{sup +} clusters are obtained and their thermal properties analyzed in terms of probability distributions of the cluster potential energy, average potential energy and configurational heat capacity all considered as a function of the cluster temperature. Details of the gradual evolution with temperature of the structural forms sampled are examined. Temperatures characterizing the onset of structural changes and isomer coexistence are identified for both clusters.

  4. Clustering gene expression data using a diffraction‐inspired framework

    Directory of Open Access Journals (Sweden)

    Dinger Steven C

    2012-11-01

    Full Text Available Abstract Background The recent developments in microarray technology has allowed for the simultaneous measurement of gene expression levels. The large amount of captured data challenges conventional statistical tools for analysing and finding inherent correlations between genes and samples. The unsupervised clustering approach is often used, resulting in the development of a wide variety of algorithms. Typical clustering algorithms require selecting certain parameters to operate, for instance the number of expected clusters, as well as defining a similarity measure to quantify the distance between data points. The diffraction‐based clustering algorithm however is designed to overcome this necessity for user‐defined parameters, as it is able to automatically search the data for any underlying structure. Methods The diffraction‐based clustering algorithm presented in this paper is tested using five well‐known expression datasets pertaining to cancerous tissue samples. The clustering results are then compared to those results obtained from conventional algorithms such as the k‐means, fuzzy c‐means, self‐organising map, hierarchical clustering algorithm, Gaussian mixture model and density‐based spatial clustering of applications with noise (DBSCAN. The performance of each algorithm is measured using an average external criterion and an average validity index. Results The diffraction‐based clustering algorithm is shown to be independent of the number of clusters as the algorithm searches the feature space and requires no form of parameter selection. The results show that the diffraction‐based clustering algorithm performs significantly better on the real biological datasets compared to the other existing algorithms. Conclusion The results of the diffraction‐based clustering algorithm presented in this paper suggest that the method can provide researchers with a new tool for successfully analysing microarray data.

  5. Environmental sampling

    Energy Technology Data Exchange (ETDEWEB)

    Puckett, J.M.

    1998-12-31

    Environmental Sampling (ES) is a technology option that can have application in transparency in nuclear nonproliferation. The basic process is to take a sample from the environment, e.g., soil, water, vegetation, or dust and debris from a surface, and through very careful sample preparation and analysis, determine the types, elemental concentration, and isotopic composition of actinides in the sample. The sample is prepared and the analysis performed in a clean chemistry laboratory (CCL). This ES capability is part of the IAEA Strengthened Safeguards System. Such a Laboratory is planned to be built by JAERI at Tokai and will give Japan an intrinsic ES capability. This paper presents options for the use of ES as a transparency measure for nuclear nonproliferation.

  6. Data clustering algorithms and applications

    CERN Document Server

    Aggarwal, Charu C

    2013-01-01

    Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as fea

  7. Testing the Large-scale Environments of Cool-core and Non-cool-core Clusters with Clustering Bias

    Science.gov (United States)

    Medezinski, Elinor; Battaglia, Nicholas; Coupon, Jean; Cen, Renyue; Gaspari, Massimo; Strauss, Michael A.; Spergel, David N.

    2017-02-01

    There are well-observed differences between cool-core (CC) and non-cool-core (NCC) clusters, but the origin of this distinction is still largely unknown. Competing theories can be divided into internal (inside-out), in which internal physical processes transform or maintain the NCC phase, and external (outside-in), in which the cluster type is determined by its initial conditions, which in turn leads to different formation histories (i.e., assembly bias). We propose a new method that uses the relative assembly bias of CC to NCC clusters, as determined via the two-point cluster-galaxy cross-correlation function (CCF), to test whether formation history plays a role in determining their nature. We apply our method to 48 ACCEPT clusters, which have well resolved central entropies, and cross-correlate with the SDSS-III/BOSS LOWZ galaxy catalog. We find that the relative bias of NCC over CC clusters is b = 1.42 ± 0.35 (1.6σ different from unity). Our measurement is limited by the small number of clusters with core entropy information within the BOSS footprint, 14 CC and 34 NCC clusters. Future compilations of X-ray cluster samples, combined with deep all-sky redshift surveys, will be able to better constrain the relative assembly bias of CC and NCC clusters and determine the origin of the bimodality.

  8. Locating irregularly shaped clusters of infection intensity

    Directory of Open Access Journals (Sweden)

    Niko Yiannakoulias

    2010-05-01

    Full Text Available Patterns of disease may take on irregular geographic shapes, especially when features of the physical environment influence risk. Identifying these patterns can be important for planning, and also identifying new environmental or social factors associated with high or low risk of illness. Until recently, cluster detection methods were limited in their ability to detect irregular spatial patterns, and limited to finding clusters that were roughly circular in shape. This approach has less power to detect irregularly-shaped, yet important spatial anomalies, particularly at high spatial resolutions. We employ a new method of finding irregularly-shaped spatial clusters at micro-geographical scales using both simulated and real data on Schistosoma mansoni and hookworm infection intensities. This method, which we refer to as the “greedy growth scan”, is a modification of the spatial scan method for cluster detection. Real data are based on samples of hookworm and S. mansoni from Kitengei, Makueni district, Kenya. Our analysis of simulated data shows how methods able to find irregular shapes are more likely to identify clusters along rivers than methods constrained to fixed geometries. Our analysis of infection intensity identifies two small areas within the study region in which infection intensity is elevated, possibly due to local features of the physical or social environment. Collectively, our results show that the “greedy growth scan” is a suitable method for exploratory geographical analysis of infection intensity data when irregular shapes are suspected, especially at micro-geographical scales.

  9. WEB Acces to the Open Cluster Database

    Science.gov (United States)

    Mermilliod, J.-C.

    More and more observations are published for stars in open clusters. These data allow to perform different kinds of studies on large samples of open clusters, and provide extensive real data to which evolutionary models and dynamical simulations can be compared. The main condition is that the data can be accessed easily. The database developed since 1987 at the Institute of Astronomy of the University of Lausanne fills this requirement. It is now possible to access it through its Web interface: (http://obswww.unige.ch/webda/) and retrieve data- and archive files, among several other possibilities. It also provides a collection of 239 cross-reference tables between the various numbering systems for each cluster and bibliography on open clusters. The possibility to query the database from scanned or plotted cluster maps makes the use quite easy and gives immediately the basic data for the selected stars. The collection of the published in a comprehensive database allows also to point out missing data and prepare observing programs. Collaboration to develop the site, include new data and provide additional facilities are welcomed.

  10. Elevating sampling

    Science.gov (United States)

    Labuz, Joseph M.; Takayama, Shuichi

    2014-01-01

    Sampling – the process of collecting, preparing, and introducing an appropriate volume element (voxel) into a system – is often under appreciated and pushed behind the scenes in lab-on-a-chip research. What often stands in the way between proof-of-principle demonstrations of potentially exciting technology and its broader dissemination and actual use, however, is the effectiveness of sample collection and preparation. The power of micro- and nanofluidics to improve reactions, sensing, separation, and cell culture cannot be accessed if sampling is not equally efficient and reliable. This perspective will highlight recent successes as well as assess current challenges and opportunities in this area. PMID:24781100

  11. Single-cluster dynamics for the random-cluster model

    NARCIS (Netherlands)

    Deng, Y.; Qian, X.; Blöte, H.W.J.

    We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

  12. Single-cluster dynamics for the random-cluster model

    NARCIS (Netherlands)

    Deng, Y.; Qian, X.; Blöte, H.W.J.

    2009-01-01

    We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

  13. Cluster forest based fuzzy logic for massive data clustering

    Science.gov (United States)

    Lahmar, Ines; Ben Ayed, Abdelkarim; Ben Halima, Mohamed; Alimi, Adel M.

    2017-03-01

    This article is focused in developing an improved cluster ensemble method based cluster forests. Cluster forests (CF) is considered as a version of clustering inspired from Random Forests (RF) in the context of clustering for massive data. It aggregates intermediate Fuzzy C-Means (FCM) clustering results via spectral clustering since pseudo-clustering results are presented in the spectral space in order to classify these data sets in the multidimensional data space. One of the main advantages is the use of FCM, which allows building fuzzy membership to all partitions of the datasets due to the fuzzy logic whereas the classical algorithms as K-means permitted to build just hard partitions. In the first place, we ameliorate the CF clustering algorithm with the integration of fuzzy FCM and we compare it with other existing clustering methods. In the second place, we compare K-means and FCM clustering methods with the agglomerative hierarchical clustering (HAC) and other theory presented methods using data benchmarks from UCI repository.

  14. [Variance estimation considering multistage sampling design in multistage complex sample analysis].

    Science.gov (United States)

    Li, Yichong; Zhao, Yinjun; Wang, Limin; Zhang, Mei; Zhou, Maigeng

    2016-03-01

    Multistage sampling is a frequently-used method in random sampling survey in public health. Clustering or independence between observations often exists in the sampling, often called complex sample, generated by multistage sampling. Sampling error may be underestimated and the probability of type I error may be increased if the multistage sample design was not taken into consideration in analysis. As variance (error) estimator in complex sample is often complicated, statistical software usually adopt ultimate cluster variance estimate (UCVE) to approximate the estimation, which simply assume that the sample comes from one-stage sampling. However, with increased sampling fraction of primary sampling unit, contribution from subsequent sampling stages is no more trivial, and the ultimate cluster variance estimate may, therefore, lead to invalid variance estimation. This paper summarize a method of variance estimation considering multistage sampling design. The performances are compared with UCVE and the method considering multistage sampling design by simulating random sampling under different sampling schemes using real world data. Simulation showed that as primary sampling unit (PSU) sampling fraction increased, UCVE tended to generate increasingly biased estimation, whereas accurate estimates were obtained by using the method considering multistage sampling design.

  15. Sample size estimation and sampling techniques for selecting a representative sample

    Directory of Open Access Journals (Sweden)

    Aamir Omair

    2014-01-01

    Full Text Available Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables/standard deviation of the outcome variable (for numerical variables, and the required precision (margin of accuracy from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.

  16. Eclipsing binaries in open clusters

    DEFF Research Database (Denmark)

    Southworth, John; Clausen, J.V.

    2006-01-01

    Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August......Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August...

  17. Galaxy clusters: Falling into line

    Science.gov (United States)

    Sifón, Cristóbal

    2017-07-01

    Analysis of Hubble Space Telescope observations shows that the well-known alignment between the central galaxy of a galaxy cluster and its host cluster has been in place for at least ten billion years.

  18. The Two-Point Correlation Function of Rich Clusters of Galaxies: Results from an Extended APM Cluster Redshift Survey

    OpenAIRE

    G. B. Dalton; Croft, R. A. C.; Efstathiou, G.; Sutherland, W.J.; Maddox, S. J.; Davis, M.

    1994-01-01

    We present new estimates of the spatial two-point correlation function of rich clusters of galaxies selected from the APM Galaxy Survey. We have measured redshifts for a sample of $364$ clusters out to a depth of $\\sim 450\\hmpc$. The clusters have a mean space density of $\\bar{n} = 3.4\\times 10^{-5}\\hmpccc$. The two-point correlation function, $\\xi_{cc}$, for this sample is equal to unity at a pair-separation of $r_0 = 14.3\\pm1.75\\hmpc$ (2$\\sigma$ errors), consistent with our earlier results ...

  19. Bayesian Cosmic Web Reconstruction: BARCODE for Clusters

    Science.gov (United States)

    Bos, E. G. Patrick; van de Weygaert, Rien; Kitaura, Francisco; Cautun, Marius

    2016-10-01

    We describe the Bayesian \\barcode\\ formalism that has been designed towards the reconstruction of the Cosmic Web in a given volume on the basis of the sampled galaxy cluster distribution. Based on the realization that the massive compact clusters are responsible for the major share of the large scale tidal force field shaping the anisotropic and in particular filamentary features in the Cosmic Web. Given the nonlinearity of the constraints imposed by the cluster configurations, we resort to a state-of-the-art constrained reconstruction technique to find a proper statistically sampled realization of the original initial density and velocity field in the same cosmic region. Ultimately, the subsequent gravitational evolution of these initial conditions towards the implied Cosmic Web configuration can be followed on the basis of a proper analytical model or an N-body computer simulation. The BARCODE formalism includes an implicit treatment for redshift space distortions. This enables a direct reconstruction on the basis of observational data, without the need for a correction of redshift space artifacts. In this contribution we provide a general overview of the the Cosmic Web connection with clusters and a description of the Bayesian BARCODE formalism. We conclude with a presentation of its successful workings with respect to test runs based on a simulated large scale matter distribution, in physical space as well as in redshift space.

  20. Merging Galaxy Clusters: Analysis of Simulated Analogs

    Science.gov (United States)

    Nguyen, Jayke; Wittman, David; Cornell, Hunter

    2018-01-01

    The nature of dark matter can be better constrained by observing merging galaxy clusters. However, uncertainty in the viewing angle leads to uncertainty in dynamical quantities such as 3-d velocities, 3-d separations, and time since pericenter. The classic timing argument links these quantities via equations of motion, but neglects effects of nonzero impact parameter (i.e. it assumes velocities are parallel to the separation vector), dynamical friction, substructure, and larger-scale environment. We present a new approach using n-body cosmological simulations that naturally incorporate these effects. By uniformly sampling viewing angles about simulated cluster analogs, we see projected merger parameters in the many possible configurations of a given cluster. We select comparable simulated analogs and evaluate the likelihood of particular merger parameters as a function of viewing angle. We present viewing angle constraints for a sample of observed mergers including the Bullet cluster and El Gordo, and show that the separation vectors are closer to the plane of the sky than previously reported.

  1. Cosmology with EMSS Clusters of Galaxies

    Science.gov (United States)

    Donahue, Megan; Voit, G. Mark

    1999-01-01

    We use ASCA observations of the Extended Medium Sensitivity Survey sample of clusters of galaxies to construct the first z = 0.5 - 0.8 cluster temperature function. This distant cluster temperature function, when compared to local z approximately 0 and to a similar moderate redshift (z = 0.3 - 0.4) temperature function strongly constrains the matter density of the universe. Best fits to the distributions of temperatures and redshifts of these cluster samples results in Omega(sub M) = 0.45 +/- 0.1 if Lambda = 0 and Omega = 0.27 +/- 0.1 if Lambda + Omega(sub M) = 1. The uncertainties are 1sigma statistical. We examine the systematics of our approach and find that systematics, stemming mainly from model assumptions and not measurement errors, are about the same size as the statistical uncertainty +/- 0.1. In this poster proceedings, we clarify the issue of a8 as reported in our paper Donahue & Voit (1999), since this was a matter of discussion at the meeting.

  2. Dynamical Cluster Approximation

    Science.gov (United States)

    Fotso, H.; Yang, S.; Chen, K.; Pathak, S.; Moreno, J.; Jarrell, M.; Mikelsons, K.; Khatami, E.; Galanakis, D.

    The dynamical cluster approximation (DCA) is a method which systematically incorporates nonlocal corrections to the dynamical mean-field approximation. Here we present a pedagogical discussion of the DCA by describing it as a Φ-derivable coarse-graining approximation in k-space, which maps an infinite lattice problem onto a periodic finite-sized cluster embedded in a self-consistently determined effective medium. We demonstrate the method by applying it to the two-dimensional Hubbard model. From this application, we show evidences of the presence of a quantum critical point (QCP) at a finite doping underneath the superconducting dome. The QCP is associated with the second-order terminus of a line of first order phase separation transitions. This critical point is driven to zero temperature by varying the band parameters, generating the QCP. The effect of the proximity of the QCP to the superconducting dome is also discussed.

  3. Data Mining of University Philanthropic Giving: Cluster-Discriminant Analysis and Pareto Effects

    Science.gov (United States)

    Le Blanc, Louis A.; Rucks, Conway T.

    2009-01-01

    A large sample of 33,000 university alumni records were cluster-analyzed to generate six groups relatively unique in their respective attribute values. The attributes used to cluster the former students included average gift to the university's foundation and to the alumni association for the same institution. Cluster detection is useful in this…

  4. Dairy Herd Mastitis Program in Argentina: Farm Clusters and Effects on Bulk Milk Somatic Cell Counts

    Directory of Open Access Journals (Sweden)

    C Vissio1*, SA Dieser2, CG Raspanti2, JA Giraudo1, CI Bogni2, LM Odierno2 and AJ Larriestra1

    2013-01-01

    Full Text Available This research has been conducted to characterize dairy farm clusters according to mastitis control program practiced among small and medium dairy producer from Argentina, and also to evaluate the effect of such farm cluster patterns on bulk milk somatic cell count (BMSCC. Two samples of 51 (cross-sectional and 38 (longitudinal herds were selected to identify farm clusters and study the influence of management on monthly BMSCC, respectively. The cross-sectional sample involved the milking routine and facilities assessment of each herd visited. Hierarchical cluster analysis was used to find the most discriminating farm attributes in the cross sectional sample. Afterward, the herd cluster typologies were identified in the longitudinal sample. Herd monthly BMSCC average was evaluated during 12 months fitting a linear mixed model. Two clusters were identified, the farms in the Cluster I applied a comprehensive mastitis program in opposite to Cluster II. Post-dipping, dry cow therapy and milking machine test were routinely applied in Cluster I. In the longitudinal study, 14 out of 38 dairy herds were labeled as Cluster I and the rest were assigned to Cluster II. Significant difference in BMSCC was found between cluster I and II (60,000 cells/mL. The present study showed the relevance and potential impact of promoting mastitis control practices among small and medium sized dairy producers in Argentina.

  5. A FABER-JACKSON RELATION FOR CLUSTERS OF GALAXIES - IMPLICATIONS FOR MODIFIED DYNAMICS

    NARCIS (Netherlands)

    SANDORS, RH

    In a sample of 20 rich clusters of galaxies, the mass of the hot X-ray emitting gas is correlated with the square of the gas temperature. Because the hot intra-cluster gas comprises most of the baryonic mass in rich clusters, this correlation implies a mass-velocity dispersion relation of the form

  6. Massive star clusters in galaxies.

    Science.gov (United States)

    Harris, William E

    2010-02-28

    The ensemble of all star clusters in a galaxy constitutes its star cluster system. In this review, the focus of the discussion is on the ability of star clusters, particularly the systems of old massive globular clusters (GCs), to mark the early evolutionary history of galaxies. I review current themes and key findings in GC research, and highlight some of the outstanding questions that are emerging from recent work.

  7. [Cluster analysis in biomedical researches].

    Science.gov (United States)

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

    2013-01-01

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

  8. Clustering signatures classify directed networks

    Science.gov (United States)

    Ahnert, S. E.; Fink, T. M. A.

    2008-09-01

    We use a clustering signature, based on a recently introduced generalization of the clustering coefficient to directed networks, to analyze 16 directed real-world networks of five different types: social networks, genetic transcription networks, word adjacency networks, food webs, and electric circuits. We show that these five classes of networks are cleanly separated in the space of clustering signatures due to the statistical properties of their local neighborhoods, demonstrating the usefulness of clustering signatures as a classifier of directed networks.

  9. The Assembly of Galaxy Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Berrier, Joel C.; Stewart, Kyle R.; Bullock, James S.; Purcell, Chris W.; Barton, Elizabeth J.; Wechsler, Risa H.

    2008-05-16

    We study the formation of fifty-three galaxy cluster-size dark matter halos (M = 10{sup 14.0-14.76} M{sub {circle_dot}}) formed within a pair of cosmological {Lambda}CDM N-body simulations, and track the accretion histories of cluster subhalos with masses large enough to host {approx} 0.1L{sub *} galaxies. By associating subhalos with cluster galaxies, we find the majority of galaxies in clusters experience no 'pre-processing' in the group environment prior to their accretion into the cluster. On average, {approx} 70% of cluster galaxies fall into the cluster potential directly from the field, with no luminous companions in their host halos at the time of accretion; and less than {approx} 12% are accreted as members of groups with five or more galaxies. Moreover, we find that cluster galaxies are significantly less likely to have experienced a merger in the recent past ({approx}< 6 Gyr) than a field halo of the same mass. These results suggest that local, cluster processes like ram-pressure stripping, galaxy harassment, or strangulation play the dominant role in explaining the difference between cluster and field populations at a fixed stellar mass; and that pre-evolution or past merging in the group environment is of secondary importance for setting cluster galaxy properties for most clusters. The accretion times for z = 0 cluster members are quite extended, with {approx} 20% incorporated into the cluster halo more than 7 Gyr ago and {approx} 20% within the last 2 Gyr. By comparing the observed morphological fractions in cluster and field populations, we estimate an approximate time-scale for late-type to early-type transformation within the cluster environment to be {approx} 6 Gyr.

  10. Clusters and entrepreneurship

    OpenAIRE

    Mercedes Delgado; Porter, Michael E.; Scott Stern

    2010-01-01

    This paper examines the role of regional clusters in regional entrepreneurship. We focus on the distinct influences of convergence and agglomeration on growth in the number of start-up firms as well as in employment in these new firms in a given region-industry. While reversion to the mean and diminishing returns to entrepreneurship at the region-industry level can result in a convergence effect, the presence of complementary economic activity creates externalities that enhance incentives and...

  11. South Asian Cluster

    OpenAIRE

    Ionel Sergiu Pirju

    2014-01-01

    This article aims at presenting the South Asian cluster composed of India, Indonesia, Iran and Malaysia, the intercultural values that characterizes it, the supported leadership style and tracing the main macroeconomic considerations which characterizes them. The research is synchronic, analysing the contemporary situation of these countries without reference to their evolution in time, by using the positivist paradigm that explains the reality at one point. It will be analysed th...

  12. Cosmology, Clusters and Calorimeters

    Science.gov (United States)

    Figueroa-Feliciano, Enectali

    2005-01-01

    I will review the current state of Cosmology with Clusters and discuss the application of microcalorimeter arrays to this field. With the launch of Astro-E2 this summer and a slew of new missions being developed, microcalorimeters are the next big thing in x-ray astronomy. I will cover the basics and not-so-basic concepts of microcalorimeter designs and look at the future to see where this technology will go.

  13. On clusters and clustering from atoms to fractals

    CERN Document Server

    Reynolds, PJ

    1993-01-01

    This book attempts to answer why there is so much interest in clusters. Clusters occur on all length scales, and as a result occur in a variety of fields. Clusters are interesting scientifically, but they also have important consequences technologically. The division of the book into three parts roughly separates the field into small, intermediate, and large-scale clusters. Small clusters are the regime of atomic and molecular physics and chemistry. The intermediate regime is the transitional regime, with its characteristics including the onset of bulk-like behavior, growth and aggregation, a

  14. Polarizability effect in metallic clusters

    Indian Academy of Sciences (India)

    Metallic clusters are one such cluster type, investigations of which go back to Knight et al's experiments [1]. After observing .... Accounting for theoretical studies [16–19] where the dynamical effect of the ... The essential question to investigate now is: how does the fragmentation take place and how does it depend on cluster ...

  15. Recovery Rate of Clustering Algorithms

    NARCIS (Netherlands)

    Li, Fajie; Klette, Reinhard; Wada, T; Huang, F; Lin, S

    2009-01-01

    This article provides a simple and general way for defining the recovery rate of clustering algorithms using a given family of old clusters for evaluating the performance of the algorithm when calculating a family of new clusters. Under the assumption of dealing with simulated data (i.e., known old

  16. Clustering objects from multiple collections

    NARCIS (Netherlands)

    Hollink, V.; van Someren, M.; de Boer, V.

    2009-01-01

    Clustering methods cluster objects on the basis of a similarity measure between the objects. In clustering tasks where the objects come from more than one collection often part of the similarity results from features that are related to the collections rather than features that are relevant for the

  17. Geographic Projection of Cluster Composites

    NARCIS (Netherlands)

    Nerbonne, J.; Bosveld-de Smet, L.M.; Kleiweg, P.; Blackwell, A.; Marriott, K.; Shimojima, A.

    2004-01-01

    A composite cluster map displays a fuzzy categorisation of geographic areas. It combines information from several sources to provide a visualisation of the significance of cluster borders. The basic technique renders the chance that two neighbouring locations are members of different clusters as the

  18. Subspace K-means clustering.

    Science.gov (United States)

    Timmerman, Marieke E; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

    2013-12-01

    To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning approaches. To evaluate subspace K-means, we performed a comparative simulation study, in which we manipulated the overlap of subspaces, the between-cluster variance, and the error variance. The study shows that the subspace K-means algorithm is sensitive to local minima but that the problem can be reasonably dealt with by using partitions of various cluster procedures as a starting point for the algorithm. Subspace K-means performs very well in recovering the true clustering across all conditions considered and appears to be superior to its competitor methods: K-means, reduced K-means, factorial K-means, mixtures of factor analyzers (MFA), and MCLUST. The best competitor method, MFA, showed a performance similar to that of subspace K-means in easy conditions but deteriorated in more difficult ones. Using data from a study on parental behavior, we show that subspace K-means analysis provides a rich insight into the cluster characteristics, in terms of both the relative positions of the clusters (via the centroids) and the shape of the clusters (via the within-cluster residuals).

  19. Cluster analysis of simulated gravitational wave triggers using constrained validation clustering

    Science.gov (United States)

    Zhang, Ting; Tang, Lappoon; Mukherjee, Soma

    2010-10-01

    The data collected in the science run of LIGO calls for a thorough analysis of the glitches seen in the gravitational wave channels, as well as in the auxiliary and environmental channels. Rapid growth in size and number of available databases requires fast and accurate data mining algorithms for timely glitch analysis. The study presents a new technique in cluster analysis that we call constrained validation clustering (CV clustering) for mining patterns in gravitational wave burst triggers. The approach avoids using Gaussianity assumptions on data distribution, and was shown to outperform a state of the art in clustering -- G-means -- when K, the number of clusters, is unknown (Tang et. al., 08); experimental results suggested that Guassian mixture assumption can be too strong as a machine learning bias in mining gravitational wave data, evidenced by very severe overfitting of data by G-means. Our current focus is on upgrading CV clustering to utilizing random sampling and stochastic optimization techniques. Preliminary results indicate that such an enhancement can potentially bring about a forty fold increase in computational efficiency while suffering minor degrade in model quality. A current future direction is in further improving quality of models learned by the algorithm for making it an effective approach for real LIGO data analysis.

  20. Precise clustering and density evolution of redMaPPer galaxy clusters versus MXXL simulation

    Science.gov (United States)

    Jimeno, Pablo; Broadhurst, Tom; Lazkoz, Ruth; Angulo, Raul; Diego, Jose-Maria; Umetsu, Keiichi; Chu, Ming-chung

    2017-04-01

    We construct a large, redshift-complete sample of distant galaxy clusters by correlating Sloan Digital Sky Survey Data Release 12 redshifts with clusters identified with the red-sequence Matched-filter Probabilistic Percolation (redMaPPer) algorithm. Our spectroscopic completeness is >97 per cent for ≃7000 clusters within the redMaPPer selection limit, z ≤ 0.325, so that our cluster correlation functions are much more precise than earlier work and not suppressed by uncertain photometric redshifts. We derive an accurate power-law mass-richness relation from the observed abundance with respect to the mass function from Millennium XXL (MXXL) simulations, adjusted to the Planck-weighted cosmology. The number density of clusters is found to decline by 20 per cent over the range 0.1 relation, whereas the observed amplitude of the correlation function at = 0.24 exceeds the MXXL prediction by 20 per cent at the ≃2.5σ level. This tension cannot be blamed on spurious, randomly located clusters as this would reduce the correlation amplitude. Full consistency between the correlation function and the abundances is achievable for the pre-Planck values of σ8 = 0.9, Ωm = 0.25 and h = 0.73, matching the improved distance ladder estimate of the Hubble constant.

  1. Entropy-rate clustering: cluster analysis via maximizing a submodular function subject to a matroid constraint.

    Science.gov (United States)

    Liu, Ming-Yu; Tuzel, Oncel; Ramalingam, Srikumar; Chellappa, Rama

    2014-01-01

    We propose a new objective function for clustering. This objective function consists of two components: the entropy rate of a random walk on a graph and a balancing term. The entropy rate favors formation of compact and homogeneous clusters, while the balancing function encourages clusters with similar sizes and penalizes larger clusters that aggressively group samples. We present a novel graph construction for the graph associated with the data and show that this construction induces a matroid--a combinatorial structure that generalizes the concept of linear independence in vector spaces. The clustering result is given by the graph topology that maximizes the objective function under the matroid constraint. By exploiting the submodular and monotonic properties of the objective function, we develop an efficient greedy algorithm. Furthermore, we prove an approximation bound of (1/2) for the optimality of the greedy solution. We validate the proposed algorithm on various benchmarks and show its competitive performances with respect to popular clustering algorithms. We further apply it for the task of superpixel segmentation. Experiments on the Berkeley segmentation data set reveal its superior performances over the state-of-the-art superpixel segmentation algorithms in all the standard evaluation metrics.

  2. Intrinsic alignment of redMaPPer clusters: cluster shape-matter density correlation

    Science.gov (United States)

    van Uitert, Edo; Joachimi, Benjamin

    2017-07-01

    We measure the alignment of the shapes of galaxy clusters, as traced by their satellite distributions, with the matter density field using the public redMaPPer catalogue based on Sloan Digital Sky Survey-Data Release 8 (SDSS-DR8), which contains 26 111 clusters up to z ˜ 0.6. The clusters are split into nine redshift and richness samples; in each of them, we detect a positive alignment, showing that clusters point towards density peaks. We interpret the measurements within the tidal alignment paradigm, allowing for a richness and redshift dependence. The intrinsic alignment (IA) amplitude at the pivot redshift z = 0.3 and pivot richness λ = 30 is A_IA^gen=12.6_{-1.2}^{+1.5}. We obtain tentative evidence that the signal increases towards higher richness and lower redshift. Our measurements agree well with results of maxBCG clusters and with dark-matter-only simulations. Comparing our results to the IA measurements of luminous red galaxies, we find that the IA amplitude of galaxy clusters forms a smooth extension towards higher mass. This suggests that these systems share a common alignment mechanism, which can be exploited to improve our physical understanding of IA.

  3. Design and Analysis Considerations for Cluster Randomized Controlled Trials That Have a Small Number of Clusters.

    Science.gov (United States)

    Deke, John

    2016-10-25

    Cluster randomized controlled trials (CRCTs) often require a large number of clusters in order to detect small effects with high probability. However, there are contexts where it may be possible to design a CRCT with a much smaller number of clusters (10 or fewer) and still detect meaningful effects. The objective is to offer recommendations for best practices in design and analysis for small CRCTs. I use simulations to examine alternative design and analysis approaches. Specifically, I examine (1) which analytic approaches control Type I errors at the desired rate, (2) which design and analytic approaches yield the most power, (3) what is the design effect of spurious correlations, and (4) examples of specific scenarios under which impacts of different sizes can be detected with high probability. I find that (1) mixed effects modeling and using Ordinary Least Squares (OLS) on data aggregated to the cluster level both control the Type I error rate, (2) randomization within blocks is always recommended, but how best to account for blocking through covariate adjustment depends on whether the precision gains offset the degrees of freedom loss, (3) power calculations can be accurate when design effects from small sample, spurious correlations are taken into account, and (4) it is very difficult to detect small effects with just four clusters, but with six or more clusters, there are realistic circumstances under which small effects can be detected with high probability. © The Author(s) 2016.

  4. Particle size distribution in ferrofluid macro-clusters

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Wah-Keat, E-mail: wklee@bnl.gov [X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, 9700S. Cass Avenue, Argonne, IL 60439 (United States); Ilavsky, Jan [X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, 9700S. Cass Avenue, Argonne, IL 60439 (United States)

    2013-03-15

    Under an applied magnetic field, many commercial and concentrated ferrofluids agglomerate and form large micron-sized structures. Although large diameter particles have been implicated in the formation of these macro-clusters, the question of whether the particle size distribution of the macro-clusters are the same as the original fluid remains open. Some studies suggest that these macro-clusters consist of larger particles, while others have shown that there is no difference in the particle size distribution between the macro-clusters and the original fluid. In this study, we use X-ray imaging to aid in a sample (diluted EFH-1 from Ferrotec) separation process and conclusively show that the average particle size in the macro-clusters is significantly larger than those in the original sample. The average particle size in the macro-clusters is 19.6 nm while the average particle size of the original fluid is 11.6 nm. - Highlights: Black-Right-Pointing-Pointer X-ray imaging was used to isolate ferrofluid macro-clusters under an applied field. Black-Right-Pointing-Pointer Small angle X-ray scattering was used to determine particle size distributions. Black-Right-Pointing-Pointer Results show that macro-clusters consist of particles that are larger than average.

  5. Coalescence of silver clusters by immersion in diluted HF solution

    Science.gov (United States)

    Milazzo, R. G.; Mio, A. M.; D'Arrigo, G.; Grimaldi, M. G.; Spinella, C.; Rimini, E.

    2015-07-01

    The galvanic displacement deposition of silver on H-terminated Si (100) in the time scale of seconds is instantaneous and characterized by a cluster density of 1011-1012 cm-2. The amount of deposited Ag follows a t1/2 dependence in agreement with a Cottrell diffusion limited mechanism. At the same time, during the deposition, the cluster density reduces by a factor 5. This behavior is in contrast with the assumption of immobile clusters. We show in the present work that coalescence and aggregation occur also in the samples immersed in the diluted hydrofluoric acid (HF) solution without the presence of Ag+. Clusters agglomerate according to a process of dynamic coalescence, typical of colloids, followed by atomic redistribution at the contact regions with the generation of multiple internal twins and stacking-faults. The normalized size distributions in terms of r/rmean follow also the prediction of the Smoluchowski ripening mechanism. No variation of the cluster density occurs for samples immersed in pure H2O solution. The different behavior might be associated to the strong attraction of clusters to oxide-terminated Si surface in presence of water. The silver clusters are instead weakly bound to hydrophobic H-terminated Si in presence of HF. HF causes then the detachment of clusters and a random movement on the silicon surface with mobility of about 10-13 cm2/s. Attractive interaction (probably van der Waals) among particles promotes coarsening.

  6. Magnetic properties of iron cluster/chromium matrix nanocomposites

    Directory of Open Access Journals (Sweden)

    Arne Fischer

    2015-05-01

    Full Text Available A custom-designed apparatus was used for the fine-tuned co-deposition of preformed Fe clusters into antiferromagnetic Cr matrices. Three series of samples with precisely defined cluster sizes, with accuracy to a few atoms, and controlled concentrations were fabricated, followed by a complete characterization of structure and magnetic performance. Relevant magnetic characteristics, reflecting the ferromagnetic/antiferromagnetic coupling between Fe clusters and the Cr matrix, i.e., blocking temperature, coercivity field, and exchange bias were measured and their dependence on cluster size and cluster concentration in the matrix was analyzed. It is evident that the blocking temperatures are clearly affected by both the cluster size and their concentration in the Cr matrix. In contrast the coercivity shows hardly any dependence on size or inter-cluster distance. The exchange bias was found to be strongly sensitive to the cluster size but not to the inter-cluster distances. Therefore, it was concluded to be an effect that is purely localized at the interfaces.

  7. A Study of RI Clusters Based on Symbiosis Theory

    Directory of Open Access Journals (Sweden)

    Wenchao Xu

    2017-03-01

    Full Text Available Research infrastructure (RI refers to a large and complex science research facility or system that conducts top-level science activities. In recent years, there has been a tendency toward geographical concentration of RIs and formation of RI clusters. Some of these RI clusters have become engines for regional social and economic development. It turns out that RI clusters present a new stage for RI sustainable development. The present paper tries to study RI clusters based on symbiosis theory in order to build an analytical framework for policy makers’ comprehensive understanding of RI clusters. Following the analytical framework, we study the symbiosis system and the symbiosis structures of an RI cluster by analyzing its major characteristics. In order to achieve a balanced symbiotic situation, a competitive model and a symbiosis model are proposed based on the Logistic Model. The analysis is grounded in the samples of China’s typical RI clusters and other cases in the world to give a vivid and convincing illustration. During the analysis process, an RI cluster is regarded as a complex ecological system and the organization and management of units in the cluster is the focus of the study. The authors hope that the paper will supplement the existing literature, which mainly focuses on the technological problems and the evaluation of RI’s socioeconomic effects, in the sense of a systematical analysis of the management problem of RI.

  8. Support Policies in Clusters: Prioritization of Support Needs by Cluster Members According to Cluster Life Cycle

    Directory of Open Access Journals (Sweden)

    Gulcin Salıngan

    2012-07-01

    Full Text Available Economic development has always been a moving target. Both the national and local governments have been facing the challenge of implementing the effective and efficient economic policy and program in order to best utilize their limited resources. One of the recent approaches in this area is called cluster-based economic analysis and strategy development. This study reviews key literature and some of the cluster based economic policies adopted by different governments. Based on this review, it proposes “the cluster life cycle” as a determining factor to identify the support requirements of clusters. A survey, designed based on literature review of International Cluster support programs, was conducted with 30 participants from 3 clusters with different maturity stage. This paper discusses the results of this study conducted among the cluster members in Eskişehir- Bilecik-Kütahya Region in Turkey on the requirement of the support to foster the development of related clusters.

  9. Dynamics, Chemical Abundances, and ages of Globular Clusters in the Virgo Cluster of Galaxies

    Science.gov (United States)

    Guhathakurta, Puragra; NGVS Collaboration

    2018-01-01

    We present a study of the dynamics, metallicities, and ages of globular clusters (GCs) in the Next Generation Virgo cluster Survey (NGVS), a deep, multi-band (u, g, r, i, z, and Ks), wide-field (104 deg2) imaging survey carried out using the 3.6-m Canada-France-Hawaii Telescope and MegaCam imager. GC candidates were selected from the NGVS survey using photometric and image morphology criteria and these were followed up with deep, medium-resolution, multi-object spectroscopy using the Keck II 10-m telescope and DEIMOS spectrograph. The primary spectroscopic targets were candidate GC satellites of dwarf elliptical (dE) and ultra-diffuse galaxies (UDGs) in the Virgo cluster. While many objects were confirmed as GC satellites of Virgo dEs and UDGs, many turned out to be non-satellites based on their radial velocity and/or positional mismatch any identifiable Virgo cluster galaxy. We have used a combination of spectral characteristics (e.g., presence of absorption vs. emission lines), new Gaussian mixture modeling of radial velocity and sky position data, and a new extreme deconvolution analysis of ugrizKs photometry and image morphology, to classify all the objects in our sample into: (1) GC satellites of dE galaxies, (2) GC satellites of UDGs, (3) intra-cluster GCs (ICGCs) in the Virgo cluster, (4) GCs in the outer halo of the central cluster galaxy M87, (5) foreground Milky Way stars, and (6) distant background galaxies. We use these data to study the dynamics and dark matter content of dE and UDGs in the Virgo cluster, place important constraints on the nature of dE nuclei, and study the origin of ICGCs versus GCs in the remote M87 halo.We are grateful for financial support from the NSF and NASA/STScI.

  10. The MUSIC of galaxy clusters - II. X-ray global properties and scaling relations

    Science.gov (United States)

    Biffi, V.; Sembolini, F.; De Petris, M.; Valdarnini, R.; Yepes, G.; Gottlöber, S.

    2014-03-01

    We present the X-ray properties and scaling relations of a large sample of clusters extracted from the Marenostrum MUltidark SImulations of galaxy Clusters (MUSIC) data set. We focus on a sub-sample of 179 clusters at redshift z ˜ 0.11, with 3.2 × 1014 h-1 M⊙ MUSIC clusters reasonably resemble the self-similar prediction, especially for correlations involving TX. The observational approach also allows for a more direct comparison with real clusters, from which we find deviations mainly due to the physical description of the ICM, affecting TX and, particularly, LX.

  11. Structural parameters of young star clusters: fractal analysis

    Science.gov (United States)

    Hetem, A.

    2017-07-01

    A unified view of star formation in the Universe demand detailed and in-depth studies of young star clusters. This work is related to our previous study of fractal statistics estimated for a sample of young stellar clusters (Gregorio-Hetem et al. 2015, MNRAS 448, 2504). The structural properties can lead to significant conclusions about the early stages of cluster formation: 1) virial conditions can be used to distinguish warm collapsed; 2) bound or unbound behaviour can lead to conclusions about expansion; and 3) fractal statistics are correlated to the dynamical evolution and age. The technique of error bars estimation most used in the literature is to adopt inferential methods (like bootstrap) to estimate deviation and variance, which are valid only for an artificially generated cluster. In this paper, we expanded the number of studied clusters, in order to enhance the investigation of the cluster properties and dynamic evolution. The structural parameters were compared with fractal statistics and reveal that the clusters radial density profile show a tendency of the mean separation of the stars increase with the average surface density. The sample can be divided into two groups showing different dynamic behaviour, but they have the same dynamic evolution, since the entire sample was revealed as being expanding objects, for which the substructures do not seem to have been completely erased. These results are in agreement with the simulations adopting low surface densities and supervirial conditions.

  12. Cluster analysis of clinical data identifies fibromyalgia subgroups.

    Directory of Open Access Journals (Sweden)

    Elisa Docampo

    Full Text Available INTRODUCTION: Fibromyalgia (FM is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. MATERIAL AND METHODS: 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. RESULTS: VARIABLES CLUSTERED INTO THREE INDEPENDENT DIMENSIONS: "symptomatology", "comorbidities" and "clinical scales". Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1, high symptomatology and comorbidities (Cluster 2, and high symptomatology but low comorbidities (Cluster 3, showing differences in measures of disease severity. CONCLUSIONS: We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment.

  13. Stochastically lighting up galaxies: Statistical implications of stellar clustering

    Science.gov (United States)

    da Silva, Robert Louis

    Stars form discretely. At the very least, they form in units of individual stars. However, their discreteness likely extends to much larger spatially and temporally correlated structures known as star clusters. This discreteness has a profound impact on the light that a population of stars will produce even at fixed star formation rate. Ignoring the effects of this clustering when analyzing observations can lead to significant errors and biases. This work presents an exploration of the effects of this clustering, the foundation of which is the construction of SLUG, a code which Stochastically Lights Up Galaxies. It accounts for the effects of clustering by populating composite stellar populations ("galaxies") one cluster at a time where each cluster is filled by individual stars whose evolution is tracked. This is the first code capable of exploring stochasticity for stellar populations composed of clusters and led to several significant insights in the field. Most notably, the scatter of luminosities due to stochastically placing clusters over the star formation history of a population greatly exceeds the effects of stochastically sampling a population with a stellar initial mass function. This has profound implications for interpretations of star formation rates, deriving initial mass functions, and the star formation rate distribution of the universe. We also explore the statistics of luminosities of clusters themselves, deriving an analytical method (CLOC) for calculating the full distribution of cluster order statistics roughly one billion times faster than a suite of Monte Carlo simulations. This giant leap forward in speed provides the groundwork for a previously impossible robust exploration of the relevant parameter space (e.g. dust opacity distributions, cluster mass function shape and cutoffs, and cluster disruption parameters).

  14. Statistics of sunspot group clusters

    Directory of Open Access Journals (Sweden)

    Getko Ryszarda

    2013-03-01

    Full Text Available The Zubrzycki method is utilized to find all sunspot groups which are close to each other during each Carrington rotation. The sunspot group areas and their positions for the years 1874–2008 are used. The descending, the ascending and the maximum phases of solar cycles for each solar hemisphere are considered separately. To establish the size of the region D where the clusters are searched, the correlation function dependent on the distance between two groups is applied. The method estimates the weighted area of each cluster. The weights dependent on the correlation function of distances between sunspot groups created each cluster. For each cluster the weighted position is also evaluated. The weights dependent on the areas of sunspot groups created a given cluster. The number distribution of the sunspot groups created each cluster and the cluster statistics within different phases of the 11-year cycle and within all considered solar cycles are also presented.

  15. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

    Science.gov (United States)

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

    2015-01-01

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

  16. Convex clustering: an attractive alternative to hierarchical clustering.

    Directory of Open Access Journals (Sweden)

    Gary K Chen

    2015-05-01

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

  17. Convex clustering: an attractive alternative to hierarchical clustering.

    Science.gov (United States)

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

    2015-05-01

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

  18. Hadoop cluster deployment

    CERN Document Server

    Zburivsky, Danil

    2013-01-01

    This book is a step-by-step tutorial filled with practical examples which will show you how to build and manage a Hadoop cluster along with its intricacies.This book is ideal for database administrators, data engineers, and system administrators, and it will act as an invaluable reference if you are planning to use the Hadoop platform in your organization. It is expected that you have basic Linux skills since all the examples in this book use this operating system. It is also useful if you have access to test hardware or virtual machines to be able to follow the examples in the book.

  19. *K-means and cluster models for cancer signatures

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2017-09-01

    Full Text Available We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF. *K-means’ computational cost is a fraction of NMF’s. Using 1389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.

  20. *K-means and cluster models for cancer signatures.

    Science.gov (United States)

    Kakushadze, Zura; Yu, Willie

    2017-09-01

    We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cost is a fraction of NMF's. Using 1389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma) stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.

  1. X-ray aspects of the DAFT/FADA clusters

    Science.gov (United States)

    Guennou, L.; Durret, F.; Lima Neto, G. B.; Adami, C.

    2012-12-01

    We have undertaken the DAFT/FADA survey with the aim of applying constraints on dark energy based on weak lensing tomography as well as obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range [0.4,0.9] for which there are HST archive data. We have analysed the XMM-Newton data available for 42 of these clusters to derive their X-ray temperatures and luminosities and search for substructures. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. We present preliminary results on the coupled X-ray and dynamical analyses of these clusters.

  2. the-wizz: clustering redshift estimation for everyone

    Science.gov (United States)

    Morrison, C. B.; Hildebrandt, H.; Schmidt, S. J.; Baldry, I. K.; Bilicki, M.; Choi, A.; Erben, T.; Schneider, P.

    2017-05-01

    We present the-wizz, an open source and user-friendly software for estimating the redshift distributions of photometric galaxies with unknown redshifts by spatially cross-correlating them against a reference sample with known redshifts. The main benefit of the-wizz is in separating the angular pair finding and correlation estimation from the computation of the output clustering redshifts allowing anyone to create a clustering redshift for their sample without the intervention of an 'expert'. It allows the end user of a given survey to select any subsample of photometric galaxies with unknown redshifts, match this sample's catalogue indices into a value-added data file and produce a clustering redshift estimation for this sample in a fraction of the time it would take to run all the angular correlations needed to produce a clustering redshift. We show results with this software using photometric data from the Kilo-Degree Survey (KiDS) and spectroscopic redshifts from the Galaxy and Mass Assembly survey and the Sloan Digital Sky Survey. The results we present for KiDS are consistent with the redshift distributions used in a recent cosmic shear analysis from the survey. We also present results using a hybrid machine learning-clustering redshift analysis that enables the estimation of clustering redshifts for individual galaxies. the-wizz can be downloaded at http://github.com/morriscb/The-wiZZ/.

  3. Symptom Clusters in People Living with HIV Attending Five Palliative Care Facilities in Two Sub-Saharan African Countries: A Hierarchical Cluster Analysis.

    Science.gov (United States)

    Moens, Katrien; Siegert, Richard J; Taylor, Steve; Namisango, Eve; Harding, Richard

    2015-01-01

    Symptom research across conditions has historically focused on single symptoms, and the burden of multiple symptoms and their interactions has been relatively neglected especially in people living with HIV. Symptom cluster studies are required to set priorities in treatment planning, and to lessen the total symptom burden. This study aimed to identify and compare symptom clusters among people living with HIV attending five palliative care facilities in two sub-Saharan African countries. Data from cross-sectional self-report of seven-day symptom prevalence on the 32-item Memorial Symptom Assessment Scale-Short Form were used. A hierarchical cluster analysis was conducted using Ward's method applying squared Euclidean Distance as the similarity measure to determine the clusters. Contingency tables, X2 tests and ANOVA were used to compare the clusters by patient specific characteristics and distress scores. Among the sample (N=217) the mean age was 36.5 (SD 9.0), 73.2% were female, and 49.1% were on antiretroviral therapy (ART). The cluster analysis produced five symptom clusters identified as: 1) dermatological; 2) generalised anxiety and elimination; 3) social and image; 4) persistently present; and 5) a gastrointestinal-related symptom cluster. The patients in the first three symptom clusters reported the highest physical and psychological distress scores. Patient characteristics varied significantly across the five clusters by functional status (worst functional physical status in cluster one, pART (highest proportions for clusters two and three, p=0.012); global distress (F=26.8, p<0.001), physical distress (F=36.3, p<0.001) and psychological distress subscale (F=21.8, p<0.001) (all subscales worst for cluster one, best for cluster four). The greatest burden is associated with cluster one, and should be prioritised in clinical management. Further symptom cluster research in people living with HIV with longitudinally collected symptom data to test cluster

  4. Unsupervised analysis of classical biomedical markers: robustness and medical relevance of patient clustering using bioinformatics tools.

    Directory of Open Access Journals (Sweden)

    Michal Markovich Gordon

    Full Text Available MOTIVATION: It has been proposed that clustering clinical markers, such as blood test results, can be used to stratify patients. However, the robustness of clusters formed with this approach to data pre-processing and clustering algorithm choices has not been evaluated, nor has clustering reproducibility. Here, we made use of the NHANES survey to compare clusters generated with various combinations of pre-processing and clustering algorithms, and tested their reproducibility in two separate samples. METHOD: Values of 44 biomarkers and 19 health/life style traits were extracted from the National Health and Nutrition Examination Survey (NHANES. The 1999-2002 survey was used for training, while data from the 2003-2006 survey was tested as a validation set. Twelve combinations of pre-processing and clustering algorithms were applied to the training set. The quality of the resulting clusters was evaluated both by considering their properties and by comparative enrichment analysis. Cluster assignments were projected to the validation set (using an artificial neural network and enrichment in health/life style traits in the resulting clusters was compared to the clusters generated from the original training set. RESULTS: The clusters obtained with different pre-processing and clustering combinations differed both in terms of cluster quality measures and in terms of reproducibility of enrichment with health/life style properties. Z-score normalization, for example, dramatically improved cluster quality and enrichments, as compared to unprocessed data, regardless of the clustering algorithm used. Clustering diabetes patients revealed a group of patients enriched with retinopathies. This could indicate that routine laboratory tests can be used to detect patients suffering from complications of diabetes, although other explanations for this observation should also be considered. CONCLUSIONS: Clustering according to classical clinical biomarkers is a robust

  5. Integrated spectral study of small angular diameter galactic open clusters

    Science.gov (United States)

    Clariá, J. J.; Ahumada, A. V.; Bica, E.; Pavani, D. B.; Parisi, M. C.

    2017-10-01

    This paper presents flux-calibrated integrated spectra obtained at Complejo Astronómico El Leoncito (CASLEO, Argentina) for a sample of 9 Galactic open clusters of small angular diameter. The spectra cover the optical range (3800-6800 Å), with a resolution of ∼14 Å. With one exception (Ruprecht 158), the selected clusters are projected into the fourth Galactic quadrant (282o age by comparing the continuum distribution and line strenghts of the cluster spectra with those of template cluster spectra with known parameters. We thus provide spectroscopic information independent from that derived through color-magnitude diagram studies. We found three clusters (Collinder 249, NGC 4463 and Ruprecht 122) younger than ∼40 Myr, four moderately young ones (BH 92, Harvard 5, Hogg 14 and Pismis 23) with ages within 200-400 Myr, and two intermediate-age ones (Ruprecht 158 and ESO 065-SC07) with ages within 1.0-2.2 Gyr. The derived foreground E(B - V) color excesses vary from around 0.0 in Ruprecht 158 to ∼1.1 in Pismis 23. In general terms, the results obtained show good agreement with previous photometric results. In Ruprecht 158 and BH 92, however, some differences are found between the parameters here obtained and previous values in the literature. Individual spectra of some comparatively bright stars located in the fields of 5 out of the 9 clusters here studied, allowed us to evaluate their membership status. The current cluster sample complements that of 46 open clusters previously studied by our group in an effort to gather a spectral library with several clusters per age bin. The cluster spectral library that we have been building is an important tool to tie studies of resolved and unresolved stellar content.

  6. Globular clusters - FADS and fallacies

    Science.gov (United States)

    White, Raymond E.

    1991-01-01

    The types of globular clusters observed in the Milky Way Galaxy are described together with their known characteristics, with special attention given to correcting the erroneous statements made earlier about globular clusters. Among these are the following statements: the Galaxy is surrounded by many hundreds of globular clusters; all globular clusters are located toward the Galactic center, all globular clusters are 'metal poor' and move about the Galaxy in highly elliptical paths; all globular clusters contain RR Lyrae-type variable stars, and the RR Lyrae stars found outside of globulars have come from cluster dissolution or ejection; all of the stars in a given cluster were born at the same time and have the same chemical composition; X-ray globulars are powered by central black holes; and the luminosity functions for globular clusters are well defined and well determined. Consideration is given to the fact that globular clusters in the Magellanic Clouds differ from those in the Milky Way by their age distribution and that the globulars of the SMC differ from those of the LMC.

  7. Faint Submillimeter Galaxies Behind Lensing Clusters

    Science.gov (United States)

    Hsu, Li-Yen; Lauchlan Cowie, Lennox; Barger, Amy J.; Desai, Vandana; Murphy, Eric J.

    2017-01-01

    Faint submillimeter galaxies are the major contributors to the submillimeter extragalactic background light and hence the dominant star-forming population in the dusty universe. Determining how much these galaxies overlap the optically selected samples is critical to fully account for the cosmic star formation history. Observations of massive cluster fields are the best way to explore this faint submillimeter population, thanks to gravitational lensing effects. We have been undertaking a lensing cluster survey with the SCUBA-2 camera on the James Clerk Maxwell Telescope to map nine galaxy clusters, including the northern five clusters in the HST Frontier Fields program. We have also been using the Submillimeter Array and the Very Large Array to determine the accurate positions of our detected sources. Our observations have discovered high-redshift dusty galaxies with far-infrared luminosities similar to that of the Milky Way or luminous infrared galaxies. Some of these galaxies are still undetected in deep optical and near-infrared images. These results suggest that a substantial amount of star formation in even the faint submillimeter population may be hidden from rest-frame optical surveys.

  8. Cosmic web type dependence of halo clustering

    Science.gov (United States)

    Fisher, J. D.; Faltenbacher, A.

    2018-01-01

    We use the Millennium Simulation to show that halo clustering varies significantly with cosmic web type. Haloes are classified as node, filament, sheet and void haloes based on the eigenvalue decomposition of the velocity shear tensor. The velocity field is sampled by the peculiar velocities of a fixed number of neighbouring haloes, and spatial derivatives are computed using a kernel borrowed from smoothed particle hydrodynamics. The classification scheme is used to examine the clustering of haloes as a function of web type for haloes with masses larger than 1011 h- 1 M⊙. We find that node haloes show positive bias, filament haloes show negligible bias and void and sheet haloes are antibiased independent of halo mass. Our findings suggest that the mass dependence of halo clustering is rooted in the composition of web types as a function of halo mass. The substantial fraction of node-type haloes for halo masses ≳ 2 × 1013 h- 1 M⊙ leads to positive bias. Filament-type haloes prevail at intermediate masses, 1012-1013 h- 1 M⊙, resulting in unbiased clustering. The large contribution of sheet-type haloes at low halo masses ≲ 1012 h- 1 M⊙ generates antibiasing.

  9. Large graph clustering using DCT-based graph clustering

    OpenAIRE

    Tsapanos, Nikolaos; Tefas, Anastasios; Nikolaidis, Nikolaos; Pitas, Ioannis

    2015-01-01

    With the proliferation of the World Wide Web, graph structures have arisen on social network/media sites. Such graphs usually number several million nodes, i.e., they can be characterized as Big Data. Graph clustering is an important analysis tool for other graph related tasks, such as compression, community discovery and recommendation systems, to name a few. We propose a novel extension to a graph clustering algorithm, that attempts to cluster a graph, through the optimization ofselected te...

  10. A Generalized Affinity Propagation Clustering Algorithm for Nonspherical Cluster Discovery

    OpenAIRE

    Qiu, Teng; Li, Yongjie

    2015-01-01

    Clustering analysis aims to discover the underlying clusters in the data points according to their similarities. It has wide applications ranging from bioinformatics to astronomy. Here, we proposed a Generalized Affinity Propagation (G-AP) clustering algorithm. Data points are first organized in a sparsely connected in-tree (IT) structure by a physically inspired strategy. Then, additional edges are added to the IT structure for those reachable nodes. This expanded structure is subsequently t...

  11. The observed clustering of damaging extratropical cyclones in Europe

    Science.gov (United States)

    Cusack, Stephen

    2016-04-01

    The clustering of severe European windstorms on annual timescales has substantial impacts on the (re-)insurance industry. Our knowledge of the risk is limited by large uncertainties in estimates of clustering from typical historical storm data sets covering the past few decades. Eight storm data sets are gathered for analysis in this study in order to reduce these uncertainties. Six of the data sets contain more than 100 years of severe storm information to reduce sampling errors, and observational errors are reduced by the diversity of information sources and analysis methods between storm data sets. All storm severity measures used in this study reflect damage, to suit (re-)insurance applications. The shortest storm data set of 42 years provides indications of stronger clustering with severity, particularly for regions off the main storm track in central Europe and France. However, clustering estimates have very large sampling and observational errors, exemplified by large changes in estimates in central Europe upon removal of one stormy season, 1989/1990. The extended storm records place 1989/1990 into a much longer historical context to produce more robust estimates of clustering. All the extended storm data sets show increased clustering between more severe storms from return periods (RPs) of 0.5 years to the longest measured RPs of about 20 years. Further, they contain signs of stronger clustering off the main storm track, and weaker clustering for smaller-sized areas, though these signals are more uncertain as they are drawn from smaller data samples. These new ultra-long storm data sets provide new information on clustering to improve our management of this risk.

  12. Validating clustering of molecular dynamics simulations using polymer models

    Directory of Open Access Journals (Sweden)

    Phillips Joshua L

    2011-11-01

    Full Text Available Abstract Background Molecular dynamics (MD simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our

  13. Small-scale Conformity of the Virgo Cluster Galaxies

    Science.gov (United States)

    Lee, Hye-Ran; Lee, Joon Hyeop; Jeong, Hyunjin; Park, Byeong-Gon

    2016-06-01

    We investigate the small-scale conformity in color between bright galaxies and their faint companions in the Virgo Cluster. Cluster member galaxies are spectroscopically determined using the Extended Virgo Cluster Catalog and the Sloan Digital Sky Survey Data Release 12. We find that the luminosity-weighted mean color of faint galaxies depends on the color of adjacent bright galaxy as well as on the cluster-scale environment (gravitational potential index). From this result for the entire area of the Virgo Cluster, it is not distinguishable whether the small-scale conformity is genuine or if it is artificially produced due to cluster-scale variation of galaxy color. To disentangle this degeneracy, we divide the Virgo Cluster area into three sub-areas so that the cluster-scale environmental dependence is minimized: A1 (central), A2 (intermediate), and A3 (outermost). We find conformity in color between bright galaxies and their faint companions (color-color slope significance S ˜ 2.73σ and correlation coefficient {cc}˜ 0.50) in A2, where the cluster-scale environmental dependence is almost negligible. On the other hand, the conformity is not significant or very marginal (S ˜ 1.75σ and {cc}˜ 0.27) in A1. The conformity is not significant either in A3 (S ˜ 1.59σ and {cc}˜ 0.44), but the sample size is too small in this area. These results are consistent with a scenario in which the small-scale conformity in a cluster is a vestige of infallen groups and these groups lose conformity as they come closer to the cluster center.

  14. Estimation and testing problems in auditory neuroscience via clustering.

    Science.gov (United States)

    Hwang, Youngdeok; Wright, Samantha; Hanlon, Bret M

    2017-09-01

    The processing of auditory information in neurons is an important area in neuroscience. We consider statistical analysis for an electrophysiological experiment related to this area. The recorded synaptic current responses from the experiment are observed as clusters, where the number of clusters is related to an important characteristic of the auditory system. This number is difficult to estimate visually because the clusters are blurred by biological variability. Using singular value decomposition and a Gaussian mixture model, we develop an estimator for the number of clusters. Additionally, we provide a method for hypothesis testing and sample size determination in the two-sample problem. We illustrate our approach with both simulated and experimental data. © 2017, The International Biometric Society.

  15. Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: a 3D approach.

    Science.gov (United States)

    Sahiner, Berkman; Chan, Heang-Ping; Hadjiiski, Lubomir M; Helvie, Mark A; Wei, Jun; Zhou, Chuan; Lu, Yao

    2012-01-01

    To design a computer-aided detection (CADe) system for clustered microcalcifications in reconstructed digital breast tomosynthesis (DBT) volumes and to perform a preliminary evaluation of the CADe system. IRB approval and informed consent were obtained in this study. A data set of two-view DBT of 72 breasts containing microcalcification clusters was collected from 72 subjects who were scheduled to undergo breast biopsy. Based on tissue sampling results, 17 cases had breast cancer and 55 were benign. A separate data set of two-view DBT of 38 breasts free of clustered microcalcifications from 38 subjects was collected to independently estimate the number of false-positives (FPs) generated by the CADe system. A radiologist experienced in breast imaging marked the biopsied cluster of microcalcifications with a 3D bounding box using all available clinical and imaging information. A CADe system was designed to detect microcalcification clusters in the reconstructed volume. The system consisted of prescreening, clustering, and false-positive reduction stages. In the prescreening stage, the conspicuity of microcalcification-like objects was increased by an enhancement-modulated 3D calcification response function. An iterative thresholding and 3D object growing method was used to detect cluster seed objects, which were used as potential centers of microcalcification clusters. In the cluster detection stage, microcalcification candidates were identified using a second iterative thresholding procedure, which was applied to the signal-to-noise ratio (SNR) enhanced image voxels with a positive calcification response. Starting with each cluster seed object as the initial cluster center, a dynamic clustering algorithm formed a cluster candidate by including microcalcification candidates within a 3D neighborhood of the cluster seed object that satisfied the clustering criteria. The number, size, and SNR of the microcalcifications in a cluster candidate and the cluster shape were

  16. The Initial Mass Function of the Arches Cluster

    Science.gov (United States)

    Hosek, Matthew; Lu, Jessica; Anderson, Jay; Ghez, Andrea; Morris, Mark; Do, Tuan; Clarkson, William; Albers, Saundra; Weisz, Daniel

    2018-01-01

    The Arches star cluster is only 26 pc (in projection) from Sgr A*, the supermassive black hole at the Galactic Center. This young massive cluster allows us to examine the impact of the extreme Galactic Center environment on the stellar Initial Mass Function (IMF). However, measuring the IMF of the Arches is challenging due to the highly variable extinction along the line of sight, which makes it difficult to separate cluster members from the field stars. We use high-precision proper motion and photometric measurements obtained with the Hubble Space Telescope to calculate cluster membership probabilities for stars down to ~2 M_sun out to the outskirts of the cluster (3 pc). In addition, we measure the effective temperatures of a small sample of cluster members in order to calibrate the mass-luminosity relationship using using Keck OSIRS K-band spectroscopy. We forward model these observations to simultaneously constrain the cluster IMF, age, distance, and extinction. We obtain an IMF that is shallower than what is observed locally, with a higher fraction of high-mass stars to low mass stars (i.e., “top-heavy”). We will compare the IMF of the Arches to similar clusters in the Galactic disk and quantify the effect of the GC environment on the star formation process.

  17. Progeny Clustering: A Method to Identify Biological Phenotypes

    Science.gov (United States)

    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

  18. THE EVOLUTION OF PROTOPLANETARY DISKS IN THE ARCHES CLUSTER

    Energy Technology Data Exchange (ETDEWEB)

    Olczak, C. [Astronomisches Rechen-Institut (ARI), Zentrum fuer Astronomie Universitaet Heidelberg, Moenchhofstrasse 12-14, D-69120 Heidelberg (Germany); Kaczmarek, T.; Pfalzner, S. [Max-Planck-Institut fuer Radioastronomie, Auf dem Huegel 7, D-53121 Bonn (Germany); Harfst, S. [Technische Universitaet Berlin, Zentrum fuer Astronomie und Astrophysik, Hardenbergstrasse 36, D-10623 Berlin (Germany); Portegies Zwart, S., E-mail: olczak@ari.uni-heidelberg.de [Sterrewacht Leiden, Leiden University, Postbus 9513, 2300 RA Leiden (Netherlands)

    2012-09-10

    Most stars form in a cluster environment. These stars are initially surrounded by disks from which potentially planetary systems form. Of all cluster environments, starburst clusters are probably the most hostile for planetary systems in our Galaxy. The intense stellar radiation and extreme density favor rapid destruction of circumstellar disks via photoevaporation and stellar encounters. Evolving a virialized model of the Arches cluster in the Galactic tidal field, we investigate the effect of stellar encounters on circumstellar disks in a prototypical starburst cluster. Despite its proximity to the deep gravitational potential of the Galactic center, only a moderate fraction of members escapes to form an extended pair of tidal tails. Our simulations show that encounters destroy one-third of the circumstellar disks in the cluster core within the first 2.5 Myr of evolution, preferentially affecting the least and most massive stars. A small fraction of these events causes rapid ejection and the formation of a weaker second pair of tidal tails that is overpopulated by disk-poor stars. Two predictions arise from our study. (1) If not destroyed by photoevaporation protoplanetary disks of massive late B- and early O-type stars represent the most likely hosts of planet formation in starburst clusters. (2) Multi-epoch K- and L-band photometry of the Arches cluster would provide the kinematically selected membership sample required to detect the additional pair of disk-poor tidal tails.

  19. Importance of sampling frequency when collecting diatoms

    Science.gov (United States)

    Wu, Naicheng; Faber, Claas; Sun, Xiuming; Qu, Yueming; Wang, Chao; Ivetic, Snjezana; Riis, Tenna; Ulrich, Uta; Fohrer, Nicola

    2016-11-01

    There has been increasing interest in diatom-based bio-assessment but we still lack a comprehensive understanding of how to capture diatoms’ temporal dynamics with an appropriate sampling frequency (ASF). To cover this research gap, we collected and analyzed daily riverine diatom samples over a 1-year period (25 April 2013-30 April 2014) at the outlet of a German lowland river. The samples were classified into five clusters (1-5) by a Kohonen Self-Organizing Map (SOM) method based on similarity between species compositions over time. ASFs were determined to be 25 days at Cluster 2 (June-July 2013) and 13 days at Cluster 5 (February-April 2014), whereas no specific ASFs were found at Cluster 1 (April-May 2013), 3 (August-November 2013) (>30 days) and Cluster 4 (December 2013 - January 2014) (<1 day). ASFs showed dramatic seasonality and were negatively related to hydrological wetness conditions, suggesting that sampling interval should be reduced with increasing catchment wetness. A key implication of our findings for freshwater management is that long-term bio-monitoring protocols should be developed with the knowledge of tracking algal temporal dynamics with an appropriate sampling frequency.

  20. Importance of sampling frequency when collecting diatoms

    KAUST Repository

    Wu, Naicheng

    2016-11-14

    There has been increasing interest in diatom-based bio-assessment but we still lack a comprehensive understanding of how to capture diatoms’ temporal dynamics with an appropriate sampling frequency (ASF). To cover this research gap, we collected and analyzed daily riverine diatom samples over a 1-year period (25 April 2013–30 April 2014) at the outlet of a German lowland river. The samples were classified into five clusters (1–5) by a Kohonen Self-Organizing Map (SOM) method based on similarity between species compositions over time. ASFs were determined to be 25 days at Cluster 2 (June-July 2013) and 13 days at Cluster 5 (February-April 2014), whereas no specific ASFs were found at Cluster 1 (April-May 2013), 3 (August-November 2013) (>30 days) and Cluster 4 (December 2013 - January 2014) (<1 day). ASFs showed dramatic seasonality and were negatively related to hydrological wetness conditions, suggesting that sampling interval should be reduced with increasing catchment wetness. A key implication of our findings for freshwater management is that long-term bio-monitoring protocols should be developed with the knowledge of tracking algal temporal dynamics with an appropriate sampling frequency.

  1. A catalog of 120 NGC open star clusters

    OpenAIRE

    Tadross, A. L.

    2011-01-01

    A sample of 145 JHK--2MASS observations of NGC open star clusters is studied, of which 132 have never been studied before. Twelve are classified as non-open clusters and 13 are re-estimated self-consistently, after applying the same methods in order to compare and calibrate our reduction procedures. The fundamental and structural parameters of the 120 new open clusters studied here are derived using color-magnitude diagrams of JHK Near-IR photometry with the fitting of solar metallicity isoch...

  2. X-Ray Properties of Lensing-Selected Clusters

    Science.gov (United States)

    Paterno-Mahler, Rachel; Sharon, Keren; Bayliss, Matthew; McDonald, Michael; Gladders, Michael; Johnson, Traci; Dahle, Hakon; Rigby, Jane R.; Whitaker, Katherine E.; Florian, Michael; Wuyts, Eva

    2017-08-01

    I will present preliminary results from the Michigan Swift X-ray observations of clusters from the Sloan Giant Arcs Survey (SGAS). These clusters were lensing selected based on the presence of a giant arc visible from SDSS. I will characterize the morphology of the intracluster medium (ICM) of the clusters in the sample, and discuss the offset between the X-ray centroid, the mass centroid as determined by strong lensing analysis, and the BCG position. I will also present early-stage work on the scaling relation between the lensing mass and the X-ray luminosity.

  3. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  4. Privacy-preserving distributed clustering

    DEFF Research Database (Denmark)

    Erkin, Zekeriya; Veugen, Thijs; Toft, Tomas

    2013-01-01

    Clustering is a very important tool in data mining and is widely used in on-line services for medical, financial and social environments. The main goal in clustering is to create sets of similar objects in a data set. The data set to be used for clustering can be owned by a single entity......, or in some cases, information from different databases is pooled to enrich the data so that the merged database can improve the clustering effort. However, in either case, the content of the database may be privacy sensitive and/or commercially valuable such that the owners may not want to share their data...... for distributed clustering that limits information leakage to the untrusted service provider that performs the clustering. To achieve this goal, we rely on cryptographic techniques, in particular homomorphic encryption, and further improve the state of the art of processing encrypted data in terms of efficiency...

  5. Fourier-transform light scattering of individual colloidal clusters.

    Science.gov (United States)

    Yu, HyeonSeung; Park, HyunJoo; Kim, Youngchan; Kim, Mahn Won; Park, YongKeun

    2012-07-01

    We present measurements of the scalar-field light scattering of individual dimer, trimer, and tetrahedron shapes among colloidal clusters. By measuring the electric field with quantitative phase imaging at the sample plane and then numerically propagating to the far-field scattering plane, the two-dimensional light-scattering patterns from individual colloidal clusters are effectively and precisely retrieved. The measured scattering patterns are consistent with simulated patterns calculated from the generalized multiparticle Mie solution.

  6. Stellar Populations of Brightest Cluster Galaxies and Intracluster Light

    Science.gov (United States)

    Edwards, Louise O. V.; Trierweiller, Isabella L.

    2017-03-01

    We present 3 representative cases from a sample of 16 local Brightest Cluster Galaxies observed using integral field spectroscopy. The observations extend to nearby neighbours and into the Intracluster Light (ICL). Population synthesis modeling shows that the ICL is younger and more metal poor compared to the BCG core and outskirts. This is consistent with a scenario in which the ICL grows by cluster processes, and alongside the growth of the BCG.

  7. I. Analysis of candidates for interacting galaxy clusters

    OpenAIRE

    Gonzalez, Elizabeth J.; Rios, Martín de los; Oio, Gabriel A.; Lang, Daniel Hernández; Tagliaferro, Tania Aguirre; Domínguez, Mariano J. R.; Castellón, José Luis Nilo; Cuevas, Héctor L.; Valotto, Carlos A.

    2018-01-01

    Merging galaxy clusters allows to study the different mass components, dark and baryonic, separately. Also their occurrence enables to test the $\\Lambda$CDM scenario and they could put constrains in the self interacting cross section of the dark matter particle. It is necessary to perform an homogeneous analysis of these systems. Hence, based in a recently presented sample of candidates for interacting galaxy clusters, we present the analysis of two of these cataloged systems. In this work, t...

  8. NCUBE - A clustering algorithm based on a discretized data space

    Science.gov (United States)

    Eigen, D. J.; Northouse, R. A.

    1974-01-01

    Cluster analysis involves the unsupervised grouping of data. The process provides an automatic procedure for generating known training samples for pattern classification. NCUBE, the clustering algorithm presented, is based upon the concept of imposing a gridwork on the data space. The NCUBE computer implementation of this concept provides an easily derived form of piecewise linear discrimination. This piecewise linear discrimination permits the separation of some types of data groups that are not linearly separable.

  9. A Statistical Approach to Galaxy Cluster Gas Inhomogeneity: Chandra Observations of Nearby Galaxy Clusters

    Science.gov (United States)

    Reese, Erik D.; Kawahara, H.; Kitayama, T.; Sasaki, S.; Suto, Y.

    2009-01-01

    Motivated by cosmological hydrodynamic simulations, the intracluster medium (ICM) inhomogeneity of galaxy clusters is modeled statistically with a lognormal model for density inhomogeneity. Through mock observations of synthetic clusters the relationship between density inhomogeneities and that of the X-ray surface brightness has been developed. This enables one to infer the statistical properties of the fluctuations of the underlying three-dimensional density distribution of real galaxy clusters from X-ray observations. We explore inhomogeneity in the intracluster medium by applying the above methodology to Chandra observations of a sample of nearby galaxy clusters. We also consider extensions of the model, including Poissonian effects and compare this hybrid lognormal-Poisson model to the nearby cluster Chandra data. EDR gratefully acknowledges support from JSPS (Japan Society for the Promotion of Science) Postdoctoral Fellowhip for Foreign Researchers award P07030. HK is supported by Grands-in-Aid for JSPS of Science Fellows. This work is also supported by Grant-in-Aid for Scientific research of Japanese Ministry of Education, Culture, Sports, Science and Technology (Nos. 20.10466, 19.07030, 16340053, 20340041, and 20540235) and by JSPS Core-to-Core Program "International Research Network for Dark Energy".

  10. Quantum annealing for combinatorial clustering

    Science.gov (United States)

    Kumar, Vaibhaw; Bass, Gideon; Tomlin, Casey; Dulny, Joseph

    2018-02-01

    Clustering is a powerful machine learning technique that groups "similar" data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between points. The straightforward approach involves examining all the possible assignments of points to each of the clusters. This approach guarantees the solution will be a global minimum; however, the number of possible assignments scales quickly with the number of data points and becomes computationally intractable even for very small datasets. In order to circumvent this issue, cost function minima are found using popular local search-based heuristic approaches such as k-means and hierarchical clustering. Due to their greedy nature, such techniques do not guarantee that a global minimum will be found and can lead to sub-optimal clustering assignments. Other classes of global search-based techniques, such as simulated annealing, tabu search, and genetic algorithms, may offer better quality results but can be too time-consuming to implement. In this work, we describe how quantum annealing can be used to carry out clustering. We map the clustering objective to a quadratic binary optimization problem and discuss two clustering algorithms which are then implemented on commercially available quantum annealing hardware, as well as on a purely classical solver "qbsolv." The first algorithm assigns N data points to K clusters, and the second one can be used to perform binary clustering in a hierarchical manner. We present our results in the form of benchmarks against well-known k-means clustering and discuss the advantages and disadvantages of the proposed techniques.

  11. Random matrix improved subspace clustering

    KAUST Repository

    Couillet, Romain

    2017-03-06

    This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based on vector channel observations in the context of massive MIMO wireless communication networks is provided.

  12. Mixture Model Averaging for Clustering

    OpenAIRE

    Wei, Yuhong; McNicholas, Paul D.

    2012-01-01

    In mixture model-based clustering applications, it is common to fit several models from a family and report clustering results from only the `best' one. In such circumstances, selection of this best model is achieved using a model selection criterion, most often the Bayesian information criterion. Rather than throw away all but the best model, we average multiple models that are in some sense close to the best one, thereby producing a weighted average of clustering results. Two (weighted) ave...

  13. Fuzzy Clustering in Parallel Universes

    OpenAIRE

    Wiswedel, Bernd; Berthold, Michael R.

    2005-01-01

    We propose a modified fuzzy c-means algorithm that operates on different feature spaces, so-called parallel universes, simultaneously. The method assigns membership values of patterns to different universes, which are then adopted throughout the training. This leads to better clustering results since patterns not contributing to clustering in a universe are (completely or partially) ignored. The outcome of the algorithm are clusters distributed over different parallel universes, each modeling...

  14. Water clusters in nonpolar cavities

    OpenAIRE

    Vaitheeswaran, Subramanian; Yin, Hao; Rasaiah, Jayendran C.; Hummer, Gerhard

    2004-01-01

    We explore the structure and thermodynamics of water clusters confined in nonpolar cavities. By calculating the grand-canonical partition function term by term, we show that small nonpolar cavities can be filled at equilibrium with highly structured water clusters. The structural and thermodynamic properties of these encapsulated water clusters are similar to those observed experimentally in the gas phase. Water filling is highly sensitive to the size of the cavity and the strength of the int...

  15. Decentralized clustering over adaptive networks

    OpenAIRE

    Khawatmi, Sahar; Zoubir, Abdelhak M.; Sayed, Ali H.

    2015-01-01

    Cooperation among agents across the network leads to better estimation accuracy. However, in many network applications the agents infer and track different models of interest in an environment where agents do not know beforehand which models are being observed by their neighbors. In this work, we propose an adaptive and distributed clustering technique that allows agents to learn and form clusters from streaming data in a robust manner. Once clusters are formed, cooperation among agents with ...

  16. CHEERS: The chemical evolution RGS sample

    Science.gov (United States)

    de Plaa, J.; Kaastra, J. S.; Werner, N.; Pinto, C.; Kosec, P.; Zhang, Y.-Y.; Mernier, F.; Lovisari, L.; Akamatsu, H.; Schellenberger, G.; Hofmann, F.; Reiprich, T. H.; Finoguenov, A.; Ahoranta, J.; Sanders, J. S.; Fabian, A. C.; Pols, O.; Simionescu, A.; Vink, J.; Böhringer, H.

    2017-11-01

    Context. The chemical yields of supernovae and the metal enrichment of the intra-cluster medium (ICM) are not well understood. The hot gas in clusters of galaxies has been enriched with metals originating from billions of supernovae and provides a fair sample of large-scale metal enrichment in the Universe. High-resolution X-ray spectra of clusters of galaxies provide a unique way of measuring abundances in the hot intracluster medium (ICM). The abundance measurements can provide constraints on the supernova explosion mechanism and the initial-mass function of the stellar population. This paper introduces the CHEmical Enrichment RGS Sample (CHEERS), which is a sample of 44 bright local giant ellipticals, groups, and clusters of galaxies observed with XMM-Newton. Aims: The CHEERS project aims to provide the most accurate set of cluster abundances measured in X-rays using this sample. This paper focuses specifically on the abundance measurements of O and Fe using the reflection grating spectrometer (RGS) on board XMM-Newton. We aim to thoroughly discuss the cluster to cluster abundance variations and the robustness of the measurements. Methods: We have selected the CHEERS sample such that the oxygen abundance in each cluster is detected at a level of at least 5σ in the RGS. The dispersive nature of the RGS limits the sample to clusters with sharp surface brightness peaks. The deep exposures and the size of the sample allow us to quantify the intrinsic scatter and the systematic uncertainties in the abundances using spectral modeling techniques. Results: We report the oxygen and iron abundances as measured with RGS in the core regions of all 44 clusters in the sample. We do not find a significant trend of O/Fe as a function of cluster temperature, but we do find an intrinsic scatter in the O and Fe abundances from cluster to cluster. The level of systematic uncertainties in the O/Fe ratio is estimated to be around 20-30%, while the systematic uncertainties in the

  17. Digging Deep in Pandora's Cluster

    Science.gov (United States)

    Blakeslee, John P.; Alamo-Martinez, Karla; Toloba, Elisa; Barro, Guillermo; Peng, Eric W.

    2015-01-01

    Abell 2744, the first and nearest (z=0.31) of the Hubble Frontier Fields, is extraordinarily rich in the number and variety of galaxies it contains. Nicknamed "Pandora's Cluster," it exhibits multiple peaks in the dark matter, X-ray, and galaxy density distributions, suggesting an ongoing collision of several massive clusters. The exceptional depth of the Hubble Frontier Field imaging now makes it possible to throw open Pandora's cluster and peer deep inside. To do this, we first model and remove the stellar light of the cluster galaxies; underneath we find not only distant background galaxies, but (like the Hope that lay at the bottom of Pandora's box) a large population of globular star clusters and compact cluster members within Abell 2744 itself. Our earlier work on the massive lensing cluster Abell 1689 (Alamo-Martinez et al. 2013) revealed the largest known population of globular clusters, with a spatial profile intermediate between the galaxy light and the dark matter. Abell 2744 is similarly massive, but far less regular in its density distribution; we examine what implications this has for the copious globular clusters coursing through its multiple cores.

  18. Optical properties of cluster plasma

    Energy Technology Data Exchange (ETDEWEB)

    Kishimoto, Yasuaki; Tajima, Toshiki [Japan Atomic Energy Research Inst., Neyagawa, Osaka (Japan). Kansai Research Establishment; Downer, M.C.

    1998-03-01

    It is shown that unlike a gas plasma or an electron plasma in a metal, an ionized clustered material (`cluster plasma`) permits propagation below the plasma cut-off of electromagnetic (EM) waves whose phase velocity is close to but below the speed of light. This results from the excitation of a plasma oscillation mode (and/or polarization mode) through the cluster surface which does not exist in usual gaseous plasma. The existence of this new optical mode, cluster mode, is confirmed via numerical simulation. (author)

  19. Semi-supervised clustering methods

    Science.gov (United States)

    Bair, Eric

    2013-01-01

    Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as “semi-supervised clustering” methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided. PMID:24729830

  20. THE PERSPECTIVE OF INNOVATION CLUSTERS

    Directory of Open Access Journals (Sweden)

    Ion CERTAN

    2013-01-01

    Full Text Available The paper studied the perspective, particularities and advantages of innovation clusters, the impact of innovation clusters on the country economics. The successful examples of cluster formation on the global level are been considered. The paper indicated the necessities of conversion the economy of Republic of Moldova to the innovation way of development, the necessities of using scientific achievements in the real sector of economy, the necessities of science, technology and innovation. There are allocated perspective industries, which can be prospective for innovative enterprises in Republic of Moldova. The paper is identified priorities for the clusters creation in Moldova.

  1. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    Benacquista Matthew J.

    2006-02-01

    Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing 10^4 - 10^7 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker-Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  2. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    Benacquista Matthew

    2002-01-01

    Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing $10^4 - 10^6$ stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct $N$-body integrations and Fokker--Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  3. Integrative cluster analysis in bioinformatics

    CERN Document Server

    Abu-Jamous, Basel; Nandi, Asoke K

    2015-01-01

    Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o

  4. The Confucian Asian cluster

    Directory of Open Access Journals (Sweden)

    Ionel Sergiu Pirju

    2013-11-01

    Full Text Available The Confucian Asian cluster consists of China, Hong Kong, Japan, Singapore, South Korea, and Taiwan. Confucian tradition countries were defined by achieving a consistent performance in the global economy, they still representing the major competitors in the EU and North American countries. Their progress is defined by a great national management that was able to influence beneficial management systems applied in organizations, these rules characterized by authority; aims to ensure the confidence in business. This article will present the intercultural values characterizing it, the leadership style and also tracing major macroeconomic considerations. The research is synchronic, analysing the contemporary situation of these countries, and the analysis will be interdisciplinary exploratory, identifying specific regional cultural elements.

  5. Sleep in cluster headache

    DEFF Research Database (Denmark)

    Barloese, M C J; Jennum, P J; Lund, N T

    2015-01-01

    BACKGROUND AND PURPOSE: Cluster headache (CH) is a primary headache disorder characterized by severe attacks of unilateral pain following a chronobiological pattern. There is a close connection with sleep as most attacks occur during sleep. Hypothalamic involvement and a particular association...... with rapid eye movement (REM) sleep have been suggested. Sleep in a large, well-characterized population of CH patients was investigated. METHODS: Polysomnography (PSG) was performed on two nights in 40 CH patients during active bout and one night in 25 age, sex and body mass index matched controls...... in hospital. Macrostructure and other features of sleep were analyzed and related to phenotype. Clinical headache characterization was obtained by semi-structured interview. RESULTS: Ninety-nine nights of PSG were analyzed. Findings included a reduced percentage of REM sleep (17.3% vs. 23.0%, P = 0...

  6. The global mass functions of 35 Galactic globular clusters: I. Observational data and correlations with cluster parameters

    Science.gov (United States)

    Sollima, A.; Baumgardt, H.

    2017-11-01

    We have derived the global mass functions of a sample of 35 Galactic globular clusters by comparing deep Hubble Space Telescope photometry with suitable multimass dynamical models. For a subset of 29 clusters with available radial velocity information we were also able to determine dynamical parameters, mass-to-light ratios and the mass fraction of dark remnants. The derived global mass functions are well described by single power-laws in the mass range $0.2 -1$. Less evolved clusters show deviations from a single-power law, indicating that the original shape of their mass distribution was not a power-law. We find a tight anticorrelation between the present-day mass function slopes and the half-mass relaxation times, which can be understood if clusters started from the same universal IMF and internal dynamical evolution is the main driver in shaping the present-day mass functions. Alternatively, IMF differences correlated with the present-day half-mass relaxation time are needed to explain the observed correlation. The large range of mass function slopes seen for our clusters implies that most globular clusters are dynamically highly evolved, a fact that seems difficult to reconcile with standard estimates for the dynamical evolution of clusters. The mass function slopes also correlate with the dark remnant fractions indicating a preferential retention of massive remnants in clusters subject to high mass-loss rates.

  7. The kinematic properties of dwarf early-type galaxies in the Virgo cluster

    NARCIS (Netherlands)

    Toloba, E.; Boselli, A.; Peletier, R. F.; Gorgas, J.; Zapatero Osorio, M.R.; Gorgas, J.; Maíz Apellániz, J.; Pardo, J.R.; Gil de Paz, A.

    2011-01-01

    We present new medium resolution kinematic data for a sample of 21 dwarf early-type galaxies (dEs) mainly in the Virgo cluster. These data are used to study the origin of dEs inhabiting clusters. Within them we detect two populations: half of the sample (52%) are rotationally supported and the other

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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. Graphical Abstract ᅟ.

  10. Herd Clustering: A synergistic data clustering approach using collective intelligence

    KAUST Repository

    Wong, Kachun

    2014-10-01

    Traditional data mining methods emphasize on analytical abilities to decipher data, assuming that data are static during a mining process. We challenge this assumption, arguing that we can improve the analysis by vitalizing data. In this paper, this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances are represented by moving particles. Particles attract each other locally and form clusters by themselves as shown in the case studies reported. To demonstrate its effectiveness, the performance of HC is compared to other state-of-the art clustering methods on more than thirty datasets using four performance metrics. An application for DNA motif discovery is also conducted. The results support the effectiveness of HC and thus the underlying philosophy. © 2014 Elsevier B.V.

  11. GibbsCluster: unsupervised clustering and alignment of peptide sequences

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

    2017-01-01

    Receptor interactions with short linear peptide fragments (ligands) are at the base of many biological signaling processes. Conserved and information-rich amino acid patterns, commonly called sequence motifs, shape and regulate these interactions. Because of the properties of a receptor......-ligand system or of the assay used to interrogate it, experimental data often contain multiple sequence motifs. GibbsCluster is a powerful tool for unsupervised motif discovery because it can simultaneously cluster and align peptide data. The GibbsCluster 2.0 presented here is an improved version incorporating...... insertion and deletions accounting for variations in motif length in the peptide input. In basic terms, the program takes as input a set of peptide sequences and clusters them into meaningful groups. It returns the optimal number of clusters it identified, together with the sequence alignment and sequence...

  12. Revisiting Scaling Relations for Giant Radio Halos in Galaxy Clusters

    Science.gov (United States)

    Cassano, R.; Ettori, S.; Brunetti, G.; Giacintucci, S.; Pratt, G. W.; Venturi, T.; Kale, R.; Dolag, K.; Markevitch, Maxim L.

    2013-01-01

    Many galaxy clusters host megaparsec-scale radio halos, generated by ultrarelativistic electrons in the magnetized intracluster medium. Correlations between the synchrotron power of radio halos and the thermal properties of the hosting clusters were established in the last decade, including the connection between the presence of a halo and cluster mergers. The X-ray luminosity and redshift-limited Extended GMRT Radio Halo Survey provides a rich and unique dataset for statistical studies of the halos. We uniformly analyze the radio and X-ray data for the GMRT cluster sample, and use the new Planck Sunyaev-Zel'dovich (SZ) catalog to revisit the correlations between the power of radio halos and the thermal properties of galaxy clusters. We find that the radio power at 1.4 GHz scales with the cluster X-ray (0.1-2.4 keV) luminosity computed within R(sub 500) as P(sub 1.4) approx. L(2.1+/-0.2) - 500). Our bigger and more homogenous sample confirms that the X-ray luminous (L(sub 500) > 5 × 10(exp 44) erg/s)) clusters branch into two populations-radio halos lie on the correlation, while clusters without radio halos have their radio upper limits well below that correlation. This bimodality remains if we excise cool cores from the X-ray luminosities. We also find that P(sub 1.4) scales with the cluster integrated SZ signal within R(sub 500), measured by Planck, as P(sub 1.4) approx. Y(2.05+/-0.28) - 500), in line with previous findings. However, contrary to previous studies that were limited by incompleteness and small sample size, we find that "SZ-luminous" Y(sub 500) > 6×10(exp -5) Mpc(exp 2) clusters show a bimodal behavior for the presence of radio halos, similar to that in the radio-X-ray diagram. Bimodality of both correlations can be traced to clusters dynamics, with radio halos found exclusively in merging clusters. These results confirm the key role of mergers for the origin of giant radio halos, suggesting that they trigger the relativistic particle acceleration.

  13. From a star cluster ensemble to its formation history

    Science.gov (United States)

    Schulz, Christine; Hilker, Michael

    2015-08-01

    Ultra-compact dwarf galaxies (UCDs) populate the high mass end of compact stellar systems. In fact, they share many properties with massive globular clusters (GCs) and are found in similar environments. In the Fornax galaxy cluster, the majority of UCDs are compatible with being the result of star cluster formation processes - as well as GCs are - while the rest of the UCDs probably formed by stripping off the stellar envelope of nucleated dwarf galaxies in the tidal field of the galaxy cluster. After excluding UCDs with dwarf galaxy origin we use the remaining GC/UCD sample as tracers of star formation events - in which the GCs/UCDs probably formed - during the assembly of the galaxies in the center of the galaxy cluster.The present day GC/UCD sample in Fornax is interpreted to be a superposition of individual star cluster populations formed in different star formation events in the past. It is assumed that every star cluster population forms during a formation epoch of length dt at a constant star-formation rate (SFR). The mass distribution of such a population is described by the embedded cluster mass function (ECMF) being a pure power law extending to an upper limit Mmax. Here, the observational finding is used that higher SFRs are connected to larger Mmax which is known as the SFR-Mmax relation.Only the high-mass end of the observed GC/UCD mass function is considered since high-mass star clusters are expected to suffer less from the tidal field of the host galaxy cluster, i.e. it is assumed that all high mass GCs/UCDs survived since their formation. Then, the considered part of the GC/UCD mass function is corrected for mass loss as well as for objects which did not form in a star cluster formation process. Finally, the GC/UCD mass function is iteratively decomposed into individual populations which are assumed to be distributed according to the ECMF with an individual upper limit Mmax. From the upper mass limit, Mmax, of each involved ECMF the required SFR is

  14. Differences in mortality in acute coronary syndrome symptom clusters.

    Science.gov (United States)

    Riegel, Barbara; Hanlon, Alexandra L; McKinley, Sharon; Moser, Debra K; Meischke, Hendrika; Doering, Lynn V; Davidson, Patricia; Pelter, Michele M; Dracup, Kathleen

    2010-03-01

    The timely and accurate identification of symptoms of acute coronary syndrome (ACS) is a challenge for patients and clinicians. It is unknown whether response times and clinical outcomes differ with specific symptoms. We sought to identify which ACS symptoms are related-symptom clusters-and to determine if sample characteristics, response times, and outcomes differ among symptom cluster groups. In a multisite randomized clinical trial, 3522 patients with known cardiovascular disease were followed up for 2 years. During follow-up, 331 (11%) had a confirmed ACS event. In this group, 8 presenting symptoms were analyzed using cluster analysis. Differences in symptom cluster group characteristics, delay times, and outcomes were examined. The sample was predominantly male (67%), older (mean 67.8, S.D. 11.6 years), and white (90%). Four symptom clusters were identified: Classic ACS characterized by chest pain; Pain Symptoms (neck, throat, jaw, back, shoulder, arm pain); Stress Symptoms (shortness of breath, sweating, nausea, indigestion, dread, anxiety); and Diffuse Symptoms, with a low frequency of most symptoms. Those in the Diffuse Symptoms cluster tended to be older (P = .08) and the Pain Symptoms group was most likely to have a history of angina (P = .01). After adjusting for differences, the Diffuse Symptoms cluster demonstrated higher mortality at 2 years (17%) than the other 3 clusters (2%-5%, P symptoms occur in groups or clusters. Uncharacteristic symptom patterns may delay diagnosis and treatment by clinicians even when patients seek care rapidly. Knowledge of common symptom patterns may facilitate rapid identification of ACS.

  15. Active Clustering with Model-Based Uncertainty Reduction.

    Science.gov (United States)

    Xiong, Caiming; Johnson, David M; Corso, Jason J

    2017-01-01

    Semi-supervised clustering seeks to augment traditional clustering methods by incorporating side information provided via human expertise in order to increase the semantic meaningfulness of the resulting clusters. However, most current methods are passive in the sense that the side information is provided beforehand and selected randomly. This may require a large number of constraints, some of which could be redundant, unnecessary, or even detrimental to the clustering results. Thus in order to scale such semi-supervised algorithms to larger problems it is desirable to pursue an active clustering method-i.e., an algorithm that maximizes the effectiveness of the available human labor by only requesting human input where it will have the greatest impact. Here, we propose a novel online framework for active semi-supervised spectral clustering that selects pairwise constraints as clustering proceeds, based on the principle of uncertainty reduction. Using a first-order Taylor expansion, we decompose the expected uncertainty reduction problem into a gradient and a step-scale, computed via an application of matrix perturbation theory and cluster-assignment entropy, respectively. The resulting model is used to estimate the uncertainty reduction potential of each sample in the dataset. We then present the human user with pairwise queries with respect to only the best candidate sample. We evaluate our method using three different image datasets (faces, leaves and dogs), a set of common UCI machine learning datasets and a gene dataset. The results validate our decomposition formulation and show that our method is consistently superior to existing state-of-the-art techniques, as well as being robust to noise and to unknown numbers of clusters.

  16. STAR FORMATION AND SUPERCLUSTER ENVIRONMENT OF 107 NEARBY GALAXY CLUSTERS

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, Seth A.; Hickox, Ryan C.; Wegner, Gary A. [Department of Physics and Astronomy, Dartmouth College, 6127 Wilder Laboratory, Hanover, NH 03755 (United States); Einasto, Maret; Vennik, Jaan [Tartu Observatory, 61602 Tõravere (Estonia)

    2017-01-20

    We analyze the relationship between star formation (SF), substructure, and supercluster environment in a sample of 107 nearby galaxy clusters using data from the Sloan Digital Sky Survey. Previous works have investigated the relationships between SF and cluster substructure, and cluster substructure and supercluster environment, but definitive conclusions relating all three of these variables has remained elusive. We find an inverse relationship between cluster SF fraction ( f {sub SF}) and supercluster environment density, calculated using the Galaxy luminosity density field at a smoothing length of 8 h {sup −1} Mpc (D8). The slope of f {sub SF} versus D8 is −0.008 ± 0.002. The f {sub SF} of clusters located in low-density large-scale environments, 0.244 ± 0.011, is higher than for clusters located in high-density supercluster cores, 0.202 ± 0.014. We also divide superclusters, according to their morphology, into filament- and spider-type systems. The inverse relationship between cluster f {sub SF} and large-scale density is dominated by filament- rather than spider-type superclusters. In high-density cores of superclusters, we find a higher f {sub SF} in spider-type superclusters, 0.229 ± 0.016, than in filament-type superclusters, 0.166 ± 0.019. Using principal component analysis, we confirm these results and the direct correlation between cluster substructure and SF. These results indicate that cluster SF is affected by both the dynamical age of the cluster (younger systems exhibit higher amounts of SF); the large-scale density of the supercluster environment (high-density core regions exhibit lower amounts of SF); and supercluster morphology (spider-type superclusters exhibit higher amounts of SF at high densities).

  17. Integrated HI emission in galaxy groups and clusters

    Science.gov (United States)

    Ai, Mei; Zhu, Ming; Fu, Jian

    2017-09-01

    The integrated HI emission from hierarchical structures such as groups and clusters of galaxies can be detected by FAST at intermediate redshifts. Here we propose to use FAST to study the evolution of the global HI content of clusters and groups over cosmic time by measuring their integrated HI emissions. We use the Virgo Cluster as an example to estimate the detection limit of FAST, and have estimated the integration time to detect a Virgo type cluster at different redshifts (from z = 0.1 to z = 1.5).We have also employed a semi-analytic model (SAM) to simulate the evolution of HI contents in galaxy clusters. Our simulations suggest that the HI mass of a Virgo-like cluster could be 2-3 times higher and the physical size could be more than 50% smaller when redshift increases from z = 0.3 to z = 1. Thus the integration time could be reduced significantly and gas rich clusters at intermediate redshifts can be detected by FAST in less than 2 hours of integration time. For the local Universe, we have also used SAM simulations to create mock catalogs of clusters to predict the outcomes from FAST all sky surveys. Comparing with the optically selected catalogs derived by cross matching the galaxy catalogs from the SDSS survey and the ALFALFA survey, we find that the HI mass distribution of the mock catalog with 20 s of integration time agrees well with that of observations. However, the mock catalog with 120 s of integration time predicts many more groups and clusters that contain a population of low mass HI galaxies not detected by the ALFALFA survey. A future deep HI blind sky survey with FAST would be able to test such prediction and set constraints on the numerical simulation models. The observational strategy and sample selections for future FAST observations of galaxy clusters at high redshifts are also discussed.

  18. Cluster-based tangible programming

    CSIR Research Space (South Africa)

    Smith, Andrew C

    2014-05-01

    Full Text Available Clustering is the act of grouping items that belong together. In this paper we explore clustering as a means to construct tangible program logic, and specifically as a means to use multiple tangible objects collectively as a single tangible program...

  19. The Nordic Mobile Telecommunication Cluster

    DEFF Research Database (Denmark)

    Jørgensen, Ulrik

    2000-01-01

    A study of the historic role of the Nordic mobile telephone and telecommunications cluster and its background in both coordinated innovation policies and societal developments in Scandinavia.......A study of the historic role of the Nordic mobile telephone and telecommunications cluster and its background in both coordinated innovation policies and societal developments in Scandinavia....

  20. Variation in verb cluster interruption

    NARCIS (Netherlands)

    Hendriks, Lotte

    2014-01-01

    Except for finite verbs in main clauses, verbs in Standard Dutch cluster together in a clause-final position. In certain Dutch dialects, non-verbal material can occur within this verb cluster (Verhasselt 1961; Koelmans 1965, among many others). These dialects vary with respect to which types of

  1. Two generalizations of Kohonen clustering

    Science.gov (United States)

    Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.

    1993-01-01

    The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

  2. Brightest Members of Rich and Poor Clusters of Galaxies.

    Science.gov (United States)

    Morbey, Christopher Leon

    Surface photometry of a sample of the brightest members of rich and poor clusters of galaxies has been carried out on plates obtained at the prime focus of the CTIO 4-m telescope. The following is a summary of the structural characteristics of the galaxies found in this study: (1) The brightest members in poor clusters are generally smaller and less luminous than those in rich cluster. Sometimes these giant galaxies, whether they exist in rich or poor clusters, appear to possess extended luminous envelopes. The range in envelop luminosity is much wider in the rich clusters than in the poor clusters. Envelopes with the greatest total luminosities tend to have lower surface brightness. (2) The variation with radius of the ellipticities and asymmetries of the brightest cluster members appears to be similar in rich and poor clusters. Generally, the ellipticities increase with increasing radius. No obvious twisting of the isophotes is apparent in any of the galaxies studied. (3) There is a significant correlation between the absolute magnitude of a first-ranked galaxy and the richness of its parent cluster. The correlation is almost independent of the Bautz-Morgan class. (4) All galaxies in this study have brightness profiles which are consistent with the relationship between surface brightness and the de Vaucouleurs effective radius discussed by Kormendy. The relationship is extended by nearly an order of magnitude in effective radius. (5) The structural parameter, (alpha), defined by Gunn and Oke correlates well with the core luminosities of the brightest cluster members. (6) A faint non-uniformly luminous ring is apparent just inside the extended luminous envelope of NGC 5400 (the dominant galaxy of the poor cluster MKW5). The results of this study support the view that clusters of galaxies evolve through the merging of cluster members in a way which, to a first approximation, is consistent with the statistical model of Geller and Peebles. In the rich clusters

  3. A review of the literature on symptom clusters in studies that included oncology patients receiving primary or adjuvant chemotherapy.

    Science.gov (United States)

    Ward Sullivan, Carmen; Leutwyler, Heather; Dunn, Laura B; Miaskowski, Christine

    2017-08-31

    To summarise the current state of knowledge of symptom clusters research from studies that included, as part of their sample, patients who were receiving primary or adjuvant chemotherapy. Since the concept of a symptom cluster was first introduced into the oncology literature in 2001, only four comprehensive reviews of symptom clusters research in oncology patients were identified that provide insights into this important concept in symptom management research. A comprehensive review of the literature. A comprehensive literature search was conducted for the years 2000 to 2016. Only 19 studies met the inclusion criteria for this literature review. These studies were evaluated in terms of the symptom assessment instruments used; the statistical analysis methods used; the symptom dimension(s) used to create the symptom cluster(s); the number and types of symptom clusters identified; and whether the specific symptom clusters changed over time. The number of symptom clusters identified ranged from one-seven. The majority of the studies used some type of factor analysis to create the symptom clusters. The most common symptom dimension used to create the clusters was symptom severity. A "gastrointestinal symptom cluster" was the most common symptom cluster identified. Across the eight longitudinal studies, for half of these studies the symptom clusters remained relatively stable over time. Additional research is needed in oncology patients to address the assessment of symptom clusters, the specific nature of symptom clusters and whether symptom clusters change over time. © 2017 John Wiley & Sons Ltd.

  4. Semantic Based Cluster Content Discovery in Description First Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    MUHAMMAD WASEEM KHAN

    2017-01-01

    Full Text Available In the field of data analytics grouping of like documents in textual data is a serious problem. A lot of work has been done in this field and many algorithms have purposed. One of them is a category of algorithms which firstly group the documents on the basis of similarity and then assign the meaningful labels to those groups. Description first clustering algorithm belong to the category in which the meaningful description is deduced first and then relevant documents are assigned to that description. LINGO (Label Induction Grouping Algorithm is the algorithm of description first clustering category which is used for the automatic grouping of documents obtained from search results. It uses LSI (Latent Semantic Indexing; an IR (Information Retrieval technique for induction of meaningful labels for clusters and VSM (Vector Space Model for cluster content discovery. In this paper we present the LINGO while it is using LSI during cluster label induction and cluster content discovery phase. Finally, we compare results obtained from the said algorithm while it uses VSM and Latent semantic analysis during cluster content discovery phase.

  5. Structure stability and spectroscopy of metal clusters

    Energy Technology Data Exchange (ETDEWEB)

    1993-01-01

    Theory based on self-consistent field-linear combinations of atomic orbitals-molecular orbital theory was applied to clusters. Four areas were covered: electronic structure, equilibrium geometries, and stability of charged clusters, interaction of metal clusters with H and halogen atoms, thermal stability of isolated clusters, and stability and optical properties of hetero-atomic clusters. (DLC)

  6. Unsupervised active learning based on hierarchical graph-theoretic clustering.

    Science.gov (United States)

    Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

    2009-10-01

    Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

  7. [Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses].

    Science.gov (United States)

    Ning, P; Guo, Y F; Sun, T Y; Zhang, H S; Chai, D; Li, X M

    2016-09-01

    To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis. A population sample of adult patients in Donghuamen community, Dongcheng district and Qinghe community, Haidian district, Beijing from April 2012 to January 2015, who had wheeze within the last 12 months, underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, total serum IgE levels, blood eosinophil level and a peak flow diary. Nine variables were chosen as evaluating parameters, including pre-salbutamol forced expired volume in one second(FEV1)/forced vital capacity(FVC) ratio, pre-salbutamol FEV1, percentage of post-salbutamol change in FEV1, residual capacity, diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level, peak expiratory flow(PEF) variability, serum IgE level, cumulative tobacco cigarette consumption (pack-years) and respiratory symptoms (cough and expectoration). Subjects' different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified. (1) Four clusters were identified by hierarchical cluster analysis. Cluster 1 was chronic bronchitis in smokers with normal pulmonary function. Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease (COPD) patients with mild airflow limitation. Cluster 3 included COPD patients with heavy smoking, poor quality of life and severe airflow limitation. Cluster 4 recognized atopic patients with mild airflow limitation, elevated serum IgE and clinical features of asthma. Significant differences were revealed regarding pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, maximal mid-expiratory flow curve(MMEF)% pred, carbon monoxide diffusing capacity per liter of alveolar(DLCO)/(VA)% pred, residual volume(RV)% pred, total serum IgE level, smoking history (pack-years), St.George's respiratory questionnaire

  8. Ancient Clusters in M33 -- Clues to Galaxy Formation

    Science.gov (United States)

    Chandar, Rupali; Goudfrooij, Paul; Puzia, Thomas

    2006-08-01

    We propose to obtain high-quality integrated-light spectroscopy for ≥≈100 ancient (older than a few Gyr) star clusters in M33, the only late-type spiral galaxy in the Local Group. Using line index measurements in the well-known Lick system, we will derive accurate velocities, ages, and chemical compositions for essentially all known ancient cluster candidates in this galaxy. Because M33 is a bulgeless system, this galaxy provides a unique opportunity to study for the first time, a ``pristine'' halo star cluster sample for a spiral galaxy, without contamination from a bulge component. Our immediate goals are to: (i) measure the kinematic properties (i.e. rotation, velocity dispersion) of ancient star clusters in M33; (ii) estimate the age and metallicity distributions of the halo M33 cluster system in order to constrain formation scenarios; and (iii) pursue a detailed study of the chemistry (i.e., (alpha)/Fe ratios) of these clusters to understand their formation timescales and how they compare with other ancient cluster systems in the Local Group. This proposal was approved last year; however due to technical difficulties at the MMT (for e.g., a rat-induced electrical fire), we only obtained ~20% of the observations. Here, we request one night with the MMT/Hectospec in order to complete our program.

  9. Radio Selection of the Most Distant Galaxy Clusters

    Science.gov (United States)

    Daddi, E.; Jin, S.; Strazzullo, V.; Sargent, M. T.; Wang, T.; Ferrari, C.; Schinnerer, E.; Smolčić, V.; Calabró, A.; Coogan, R.; Delhaize, J.; Delvecchio, I.; Elbaz, D.; Gobat, R.; Gu, Q.; Liu, D.; Novak, M.; Valentino, F.

    2017-09-01

    We show that the most distant X-ray-detected cluster known to date, Cl J1001 at {z}{spec}=2.506, hosts a strong overdensity of radio sources. Six of them are individually detected (within 10\\prime\\prime ) in deep 0\\buildrel{\\prime\\prime}\\over{.} 75 resolution VLA 3 GHz imaging, with {S}3{GHz}> 8 μ {Jy}. Of the six, an active galactic nucleus (AGN) likely affects the radio emission in two galaxies, while star formation is the dominant source powering the remaining four. We searched for cluster candidates over the full COSMOS 2 deg2 field using radio-detected 3 GHz sources and looking for peaks in {{{Σ }}}5 density maps. Cl J1001 is the strongest overdensity by far with > 10σ , with a simple {z}{phot}> 1.5 preselection. A cruder photometric rejection of zgeneration of forming galaxy clusters. In these remarkable structures, widespread star formation and AGN activity of massive galaxy cluster members, residing within the inner cluster core, will ultimately lead to radio continuum as one of the most effective means for their identification, with detection rates expected in the ballpark of 0.1-1 per square degree at z≳ 2.5. Samples of hundreds such high-redshift clusters could potentially constrain cosmological parameters and test cluster and galaxy formation models.

  10. Towards eliminating bias in cluster analysis of TB genotyped data.

    Directory of Open Access Journals (Sweden)

    Cari van Schalkwyk

    Full Text Available The relative contributions of transmission and reactivation of latent infection to TB cases observed clinically has been reported in many situations, but always with some uncertainty. Genotyped data from TB organisms obtained from patients have been used as the basis for heuristic distinctions between circulating (clustered strains and reactivated infections (unclustered strains. Naïve methods previously applied to the analysis of such data are known to provide biased estimates of the proportion of unclustered cases. The hypergeometric distribution, which generates probabilities of observing clusters of a given size as realized clusters of all possible sizes, is analyzed in this paper to yield a formal estimator for genotype cluster sizes. Subtle aspects of numerical stability, bias, and variance are explored. This formal estimator is seen to be stable with respect to the epidemiologically interesting properties of the cluster size distribution (the number of clusters and the number of singletons though it does not yield satisfactory estimates of the number of clusters of larger sizes. The problem that even complete coverage of genotyping, in a practical sampling frame, will only provide a partial view of the actual transmission network remains to be explored.

  11. Towards eliminating bias in cluster analysis of TB genotyped data.

    Science.gov (United States)

    van Schalkwyk, Cari; Cule, Madeleine; Welte, Alex; van Helden, Paul; van der Spuy, Gian; Uys, Pieter

    2012-01-01

    The relative contributions of transmission and reactivation of latent infection to TB cases observed clinically has been reported in many situations, but always with some uncertainty. Genotyped data from TB organisms obtained from patients have been used as the basis for heuristic distinctions between circulating (clustered strains) and reactivated infections (unclustered strains). Naïve methods previously applied to the analysis of such data are known to provide biased estimates of the proportion of unclustered cases. The hypergeometric distribution, which generates probabilities of observing clusters of a given size as realized clusters of all possible sizes, is analyzed in this paper to yield a formal estimator for genotype cluster sizes. Subtle aspects of numerical stability, bias, and variance are explored. This formal estimator is seen to be stable with respect to the epidemiologically interesting properties of the cluster size distribution (the number of clusters and the number of singletons) though it does not yield satisfactory estimates of the number of clusters of larger sizes. The problem that even complete coverage of genotyping, in a practical sampling frame, will only provide a partial view of the actual transmission network remains to be explored.

  12. Initialization independent clustering with actively self-training method.

    Science.gov (United States)

    Nie, Feiping; Xu, Dong; Li, Xuelong

    2012-02-01

    The results of traditional clustering methods are usually unreliable as there is not any guidance from the data labels, while the class labels can be predicted more reliable by the semisupervised learning if the labels of partial data are given. In this paper, we propose an actively self-training clustering method, in which the samples are actively selected as training set to minimize an estimated Bayes error, and then explore semisupervised learning to perform clustering. Traditional graph-based semisupervised learning methods are not convenient to estimate the Bayes error; we develop a specific regularization framework on graph to perform semisupervised learning, in which the Bayes error can be effectively estimated. In addition, the proposed clustering algorithm can be readily applied in a semisupervised setting with partial class labels. Experimental results on toy data and real-world data sets demonstrate the effectiveness of the proposed clustering method on the unsupervised and the semisupervised setting. It is worthy noting that the proposed clustering method is free of initialization, while traditional clustering methods are usually dependent on initialization.

  13. Color Gradients Within Globular Clusters: Restricted Numerical Simulation

    Directory of Open Access Journals (Sweden)

    Young-Jong Sohn

    1997-06-01

    Full Text Available The results of a restricted numerical simulation for the color gradients within globular clusters have been presented. The standard luminosity function of M3 and Salpeter's initial mass functions were used to generate model clusters as a fundamental population. Color gradients with the sample clusters for both King and power law cusp models of surface brightness distributions are discussed in the case of using the standard luminosity function. The dependence of color gradients on several parameters for the simulations with Salpeter's initial mass functions, such as slope of initial mass functions, cluster ages, metallicities, concentration parameters of King model, and slopes of power law, are also discussed. No significant radial color gradients are shown to the sample clusters which are regenerated by a random number generation technique with various parameters in both of King and power law cusp models of surface brightness distributions. Dynamical mass segregation and stellar evolution of horizontal branch stars and blue stragglers should be included for the general case of model simulations to show the observed radial color gradients within globular clusters.

  14. Supra-galactic colour patterns in globular cluster systems

    Science.gov (United States)

    Forte, Juan C.

    2017-07-01

    An analysis of globular cluster systems associated with galaxies included in the Virgo and Fornax Hubble Space Telescope-Advanced Camera Surveys reveals distinct (g - z) colour modulation patterns. These features appear on composite samples of globular clusters and, most evidently, in galaxies with absolute magnitudes Mg in the range from -20.2 to -19.2. These colour modulations are also detectable on some samples of globular clusters in the central galaxies NGC 1399 and NGC 4486 (and confirmed on data sets obtained with different instruments and photometric systems), as well as in other bright galaxies in these clusters. After discarding field contamination, photometric errors and statistical effects, we conclude that these supra-galactic colour patterns are real and reflect some previously unknown characteristic. These features suggest that the globular cluster formation process was not entirely stochastic but included a fraction of clusters that formed in a rather synchronized fashion over large spatial scales, and in a tentative time lapse of about 1.5 Gy at redshifts z between 2 and 4. We speculate that the putative mechanism leading to that synchronism may be associated with large scale feedback effects connected with violent star-forming events and/or with supermassive black holes.

  15. How Environment Affects Star Formation: Tracing Activity in High Redshift Galaxy Clusters

    Science.gov (United States)

    Alberts, Stacey; Pope, A.; Brodwin, M.; Atlee, D. W.; Lin, Y.; Chary, R.; Dey, A.; Eisenhardt, P. R.; Gettings, D.; Gonzalez, A. H.; Jannuzi, B.; Mancone, C.; Moustakas, J.; Snyder, G. F.; Stanford, S. A.; Stern, D.; Weiner, B. J.; Zeimann, G.

    2014-01-01

    The emerging picture of the evolution of cluster galaxies indicates that the epoch of z>1 is a crucial period of active star formation and mass assembly in clusters. In this dissertation, I leverage a uniformly-selected cluster sample from the IRAC Shallow Cluster Survey (ISCS) with Herschel imaging to analyse the star formation (SF) activity in cluster galaxies over the past ten billion years. This analysis is two-fold: 1) using 274 clusters across the 9 square degree Bootes field, I perform a stacking analysis of mass-limited samples of cluster and field galaxies using wide-field Herschel observations over a long redshift baseline, z=0.3-1.5. I find that the average SF activity in cluster galaxies is evolving faster than in the field, with field-like SF in the cluster cores and enhanced SF activity in the cluster outskirts at z>1.2. By further breaking down my analysis by galaxy mass and type, I determine which mechanisms are capable of driving this evolution. 2) I use unique, deep Herschel imaging of 11 spectroscopically-confirmed clusters from z=1.1-1.8 to study the properties of individual infrared bright cluster galaxies as a function of redshift and cluster-centric radius. Combined with ancillary data, I determine the star formation, dust, and AGN properties of the most active cluster galaxies and tie the evolution of these properties back to the environment by comparing to field populations. By combining these two approaches, I constrain cluster galaxy properties during a pivotal epoch of dust-obscured star formation activity and mass assembly in some of the most extreme structures in the Universe.

  16. A possibilistic approach to clustering

    Science.gov (United States)

    Krishnapuram, Raghu; Keller, James M.

    1993-01-01

    Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

  17. Comparative analysis of genomic signal processing for microarray data clustering.

    Science.gov (United States)

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  18. Some statistical properties of gene expression clustering for array data

    DEFF Research Database (Denmark)

    Abreu, G C G; Pinheiro, A; Drummond, R D

    2010-01-01

    DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressed genes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https......DNA arrays have been a rich source of data for the study of genomic expression of a wide variety of biological systems. Gene clustering is one of the paradigms quite used to assess the significance of a gene (or group of genes). However, most of the gene clustering techniques are applied to c...

  19. Clusters of personality disorder cognitions in the eating disorders.

    Science.gov (United States)

    Waller, Glenn; Ormonde, Lisa; Kuteyi, Yemi

    2013-01-01

    This study examined whether comorbid personality disorder pathology in the eating disorders clusters into broader patterns, and whether those clusters have clinical validity in terms of levels of eating pathology and axis 1 comorbidity. The sample consisted of 214 eating-disordered women who completed measures of personality disorder cognitions, eating pathology and axis 1 pathology at assessment. Three clusters of eating disorder patients emerged-low levels of personality pathology overall, high levels of cognitions underpinning anxiety-based personality pathology, and high levels of all of the dimensions of personality pathology. These groups were validated by differences in levels of eating cognitions and axis 1 pathology. Personality disorder cognitions are clinically relevant to the eating disorders, but they might best be understood as broader sets of cognitions ('anxiety-centred' and 'general'), rather than in terms of individual personality disorder comorbidity or existing DSM personality disorder clusters. Copyright © 2012 John Wiley & Sons, Ltd and Eating Disorders Association.

  20. Implementation of Clustering Algorithms for real datasets in Medical Diagnostics using MATLAB

    Directory of Open Access Journals (Sweden)

    B. Venkataramana

    2017-03-01

    Full Text Available As in the medical field, for one disease there require samples given by diagnosis. The samples will be analyzed by a doctor or a pharmacist. As the no. of patients increases their samples also increases, there require more time to analyze samples for deciding the stage of the disease. To analyze the sample every time requires a skilled person. The samples can be classified by applying them to clustering algorithms. Data clustering has been considered as the most important raw data analysis method used in data mining technology. Most of the clustering techniques proved their efficiency in many applications such as decision making systems, medical sciences, earth sciences etc. Partition based clustering is one of the main approach in clustering. There are various algorithms of data clustering, every algorithm has its own advantages and disadvantages. This work reports the results of classification performance of three such widely used algorithms namely K-means (KM, Fuzzy c-means and Fuzzy Possibilistic c-Means (FPCM clustering algorithms. To analyze these algorithms three known data sets from UCI machine learning repository are taken such as thyroid data, liver and wine. The efficiency of clustering output is compared with the classification performance, percentage of correctness. The experimental results show that K-means and FCM give same performance for liver data. And FCM and FPCM are giving same performance for thyroid and wine data. FPCM has more efficient classification performance in all the given data sets.