HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

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

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

PubMed

Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Probing high-redshift clusters with HST/ACS gravitational weak-lensing and Chandra x-ray observations

NASA Astrophysics Data System (ADS)

Jee, Myungkook James

2006-06-01

Clusters of galaxies, the largest gravitationally bound objects in the Universe, are useful tracers of cosmic evolution, and particularly detailed studies of still-forming clusters at high-redshifts can considerably enhance our understanding of the structure formation. We use two powerful methods that have become recently available for the study of these distant clusters: spaced- based gravitational weak-lensing and high-resolution X-ray observations. Detailed analyses of five high-redshift (0.8 < z < 1.3) clusters are presented based on the deep Advanced Camera for Surveys (ACS) and Chandra X-ray images. We show that, when the instrumental characteristics are properly understood, the newly installed ACS on the Hubble Space Telescope (HST) can detect subtle shape distortions of background galaxies down to the limiting magnitudes of the observations, which enables the mapping of the cluster dark matter in unprecedented high-resolution. The cluster masses derived from this HST /ACS weak-lensing study have been compared with those from the re-analyses of the archival Chandra X-ray data. We find that there are interesting offsets between the cluster galaxy, intracluster medium (ICM), and dark matter centroids, and possible scenarios are discussed. If the offset is confirmed to be uniquitous in other clusters, the explanation may necessitate major refinements in our current understanding of the nature of dark matter, as well as the cluster galaxy dynamics. CL0848+4452, the highest-redshift ( z = 1.27) cluster yet detected in weak-lensing, has a significant discrepancy between the weak- lensing and X-ray masses. If this trend is found to be severe and common also for other X-ray weak clusters at redshifts beyond the unity, the conventional X-ray determination of cluster mass functions, often inferred from their immediate X-ray properties such as the X-ray luminosity and temperature via the so-called mass-luminosity (M-L) and mass-temperature (M-T) relations, will become highly unstable in this redshift regime. Therefore, the relatively unbiased weak-lensing measurements of the cluster mass properties can be used to adequately calibrate the scaling relations in future high-redshift cluster investigations.

X-ray aspects of the DAFT/FADA clusters

NASA Astrophysics Data System (ADS)

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.

Infrared Multiple Photon Dissociation Spectroscopy Of Metal Cluster-Adducts

NASA Astrophysics Data System (ADS)

Cox, D. M.; Kaldor, A.; Zakin, M. R.

1987-01-01

Recent development of the laser vaporization technique combined with mass-selective detection has made possible new studies of the fundamental chemical and physical properties of unsupported transition metal clusters as a function of the number of constituent atoms. A variety of experimental techniques have been developed in our laboratory to measure ionization threshold energies, magnetic moments, and gas phase reactivity of clusters. However, studies have so far been unable to determine the cluster structure or the chemical state of chemisorbed species on gas phase clusters. The application of infrared multiple photon dissociation IRMPD to obtain the IR absorption properties of metal cluster-adsorbate species in a molecular beam is described here. Specifically using a high power, pulsed CO2 laser as the infrared source, the IRMPD spectrum for methanol chemisorbed on small iron clusters is measured as a function of the number of both iron atoms and methanols in the complex for different methanol isotopes. Both the feasibility and potential utility of IRMPD for characterizing metal cluster-adsorbate interactions are demonstrated. The method is generally applicable to any cluster or cluster-adsorbate system dependent only upon the availability of appropriate high power infrared sources.

Searching for galaxy clusters in the Kilo-Degree Survey

NASA Astrophysics Data System (ADS)

Radovich, M.; Puddu, E.; Bellagamba, F.; Roncarelli, M.; Moscardini, L.; Bardelli, S.; Grado, A.; Getman, F.; Maturi, M.; Huang, Z.; Napolitano, N.; McFarland, J.; Valentijn, E.; Bilicki, M.

2017-02-01

Aims: In this paper, we present the tools used to search for galaxy clusters in the Kilo Degree Survey (KiDS), and our first results. Methods: The cluster detection is based on an implementation of the optimal filtering technique that enables us to identify clusters as over-densities in the distribution of galaxies using their positions on the sky, magnitudes, and photometric redshifts. The contamination and completeness of the cluster catalog are derived using mock catalogs based on the data themselves. The optimal signal to noise threshold for the cluster detection is obtained by randomizing the galaxy positions and selecting the value that produces a contamination of less than 20%. Starting from a subset of clusters detected with high significance at low redshifts, we shift them to higher redshifts to estimate the completeness as a function of redshift: the average completeness is 85%. An estimate of the mass of the clusters is derived using the richness as a proxy. Results: We obtained 1858 candidate clusters with redshift 0

Characterization of micron-size hydrogen clusters using Mie scattering.

PubMed

Jinno, S; Tanaka, H; Matsui, R; Kanasaki, M; Sakaki, H; Kando, M; Kondo, K; Sugiyama, A; Uesaka, M; Kishimoto, Y; Fukuda, Y

2017-08-07

Hydrogen clusters with diameters of a few micrometer range, composed of 10 8-10 hydrogen molecules, have been produced for the first time in an expansion of supercooled, high-pressure hydrogen gas into a vacuum through a conical nozzle connected to a cryogenic pulsed solenoid valve. The size distribution of the clusters has been evaluated by measuring the angular distribution of laser light scattered from the clusters. The data were analyzed based on the Mie scattering theory combined with the Tikhonov regularization method including the instrumental functions, the validity of which was assessed by performing a calibration study using a reference target consisting of standard micro-particles with two different sizes. The size distribution of the clusters was found discrete peaked at 0.33 ± 0.03, 0.65 ± 0.05, 0.81 ± 0.06, 1.40 ± 0.06 and 2.00 ± 0.13 µm in diameter. The highly reproducible and impurity-free nature of the micron-size hydrogen clusters can be a promising target for laser-driven multi-MeV proton sources with the currently available high power lasers.

Structure and formation of highly luminescent protein-stabilized gold clusters† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc05086k

PubMed Central

Chevrier, D. M.; Thanthirige, V. D.; Luo, Z.; Driscoll, S.; Cho, P.; MacDonald, M. A.; Yao, Q.; Guda, R.; Xie, J.; Johnson, E. R.; Chatt, A.; Zheng, N.

2018-01-01

Highly luminescent gold clusters simultaneously synthesized and stabilized by protein molecules represent a remarkable category of nanoscale materials with promising applications in bionanotechnology as sensors. Nevertheless, the atomic structure and luminescence mechanism of these gold clusters are still unknown after several years of developments. Herein, we report findings on the structure, luminescence and biomolecular self-assembly of gold clusters stabilized by the large globular protein, bovine serum albumin. We highlight the surprising identification of interlocked gold-thiolate rings as the main gold structural unit. Importantly, such gold clusters are in a rigidified state within the protein scaffold, offering an explanation for their highly luminescent character. Combined free-standing cluster synthesis (without protecting protein scaffold) with rigidifying and un-rigidifying experiments, were designed to further verify the luminescence mechanism and gold atomic structure within the protein. Finally, the biomolecular self-assembly process of the protein-stabilized gold clusters was elucidated by time-dependent X-ray absorption spectroscopy measurements and density functional theory calculations. PMID:29732064

Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud

PubMed Central

Cianfrocco, Michael A; Leschziner, Andres E

2015-01-01

The advent of a new generation of electron microscopes and direct electron detectors has realized the potential of single particle cryo-electron microscopy (cryo-EM) as a technique to generate high-resolution structures. Calculating these structures requires high performance computing clusters, a resource that may be limiting to many likely cryo-EM users. To address this limitation and facilitate the spread of cryo-EM, we developed a publicly available ‘off-the-shelf’ computing environment on Amazon's elastic cloud computing infrastructure. This environment provides users with single particle cryo-EM software packages and the ability to create computing clusters with 16–480+ CPUs. We tested our computing environment using a publicly available 80S yeast ribosome dataset and estimate that laboratories could determine high-resolution cryo-EM structures for $50 to $1500 per structure within a timeframe comparable to local clusters. Our analysis shows that Amazon's cloud computing environment may offer a viable computing environment for cryo-EM. DOI: http://dx.doi.org/10.7554/eLife.06664.001 PMID:25955969

The enigmatic SAR202 cluster up close: shedding light on a globally distributed dark ocean lineage involved in sulfur cycling.

PubMed

Mehrshad, Maliheh; Rodriguez-Valera, Francisco; Amoozegar, Mohammad Ali; López-García, Purificación; Ghai, Rohit

2018-03-01

The dark ocean microbiota represents the unknown majority in the global ocean waters. The SAR202 cluster belonging to the phylum Chloroflexi was the first microbial lineage discovered to specifically inhabit the aphotic realm, where they are abundant and globally distributed. The absence of SAR202 cultured representatives is a significant bottleneck towards understanding their metabolic capacities and role in the marine environment. In this work, we use a combination of metagenome-assembled genomes from deep-sea datasets and publicly available single-cell genomes to construct a genomic perspective of SAR202 phylogeny, metabolism and biogeography. Our results suggest that SAR202 cluster members are medium sized, free-living cells with a heterotrophic lifestyle, broadly divided into two distinct clades. We present the first evidence of vertical stratification of these microbes along the meso- and bathypelagic ocean layers. Remarkably, two distinct species of SAR202 cluster are highly abundant in nearly all deep bathypelagic metagenomic datasets available so far. SAR202 members metabolize multiple organosulfur compounds, many appear to be sulfite-oxidizers and are predicted to play a major role in sulfur turnover in the dark water column. This concomitantly suggests an unsuspected availability of these nutrient sources to allow for the high abundance of these microbes in the deep sea.

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

PubMed Central

Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

2009-01-01

Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors. PMID:19698124

SCUD: fast structure clustering of decoys using reference state to remove overall rotation.

PubMed

Li, Hongzhi; Zhou, Yaoqi

2005-08-01

We developed a method for fast decoy clustering by using reference root-mean-squared distance (rRMSD) rather than commonly used pairwise RMSD (pRMSD) values. For 41 proteins with 2000 decoys each, the computing efficiency increases nine times without a significant change in the accuracy of near-native selections. Tests on additional protein decoys based on different reference conformations confirmed this result. Further analysis indicates that the pRMSD and rRMSD values are highly correlated (with an average correlation coefficient of 0.82) and the clusters obtained from pRMSD and rRMSD values are highly similar (the representative structures of the top five largest clusters from the two methods are 74% identical). SCUD (Structure ClUstering of Decoys) with an automatic cutoff value is available at http://theory.med.buffalo.edu. (c) 2005 Wiley Periodicals, Inc.

Clustering of diet- and activity-related parenting practices: cross-sectional findings of the INPACT study

PubMed Central

2013-01-01

Background Various diet- and activity-related parenting practices are positive determinants of child dietary and activity behaviour, including home availability, parental modelling and parental policies. There is evidence that parenting practices cluster within the dietary domain and within the activity domain. This study explores whether diet- and activity-related parenting practices cluster across the dietary and activity domain. Also examined is whether the clusters are related to child and parental background characteristics. Finally, to indicate the relevance of the clusters in influencing child dietary and activity behaviour, we examined whether clusters of parenting practices are related to these behaviours. Methods Data were used from 1480 parent–child dyads participating in the Dutch IVO Nutrition and Physical Activity Child cohorT (INPACT). Parents of children aged 8–11 years completed questionnaires at home assessing their diet- and activity-related parenting practices, child and parental background characteristics, and child dietary and activity behaviours. Principal component analysis (PCA) was used to identify clusters of parenting practices. Backward regression analysis was used to examine the relationship between child and parental background characteristics with cluster scores, and partial correlations to examine associations between cluster scores and child dietary and activity behaviours. Results PCA revealed five clusters of parenting practices: 1) high visibility and accessibility of screens and unhealthy food, 2) diet- and activity-related rules, 3) low availability of unhealthy food, 4) diet- and activity-related positive modelling, and 5) positive modelling on sports and fruit. Low parental education was associated with unhealthy cluster 1, while high(er) education was associated with healthy clusters 2, 3 and 5. Separate clusters were related to both child dietary and activity behaviour in the hypothesized directions: healthy clusters were positively related to obesity-reducing behaviours and negatively to obesity-inducing behaviours. Conclusion Parenting practices cluster across the dietary and activity domain. Parental education can be seen as an indicator of a broader parental context in which clusters of parenting practices operate. Separate clusters are related to both child dietary and activity behaviour. Interventions that focus on clusters of parenting practices to assist parents (especially low-educated parents) in changing their child’s dietary and activity behaviour seems justified. PMID:23531232

Spatial ecology of refuge selection by an herbivore under risk of predation

USGS Publications Warehouse

Wilson, Tammy L.; Rayburn, Andrew P.; Edwards, Thomas C.

2012-01-01

Prey species use structures such as burrows to minimize predation risk. The spatial arrangement of these resources can have important implications for individual and population fitness. For example, there is evidence that clustered resources can benefit individuals by reducing predation risk and increasing foraging opportunity concurrently, which leads to higher population density. However, the scale of clustering that is important in these processes has been ignored during theoretical and empirical development of resource models. Ecological understanding of refuge exploitation by prey can be improved by spatial analysis of refuge use and availability that incorporates the effect of scale. We measured the spatial distribution of pygmy rabbit (Brachylagus idahoensis) refugia (burrows) through censuses in four 6-ha sites. Point pattern analyses were used to evaluate burrow selection by comparing the spatial distribution of used and available burrows. The presence of food resources and additional overstory cover resources was further examined using logistic regression. Burrows were spatially clustered at scales up to approximately 25 m, and then regularly spaced at distances beyond ~40 m. Pygmy rabbit exploitation of burrows did not match availability. Burrows used by pygmy rabbits were likely to be located in areas with high overall burrow density (resource clusters) and high overstory cover, which together minimized predation risk. However, in some cases we observed an interaction between either overstory cover (safety) or understory cover (forage) and burrow density. The interactions show that pygmy rabbits will use burrows in areas with low relative burrow density (high relative predation risk) if understory food resources are high. This points to a potential trade-off whereby rabbits must sacrifice some safety afforded by additional nearby burrows to obtain ample forage resources. Observed patterns of clustered burrows and non-random burrow use improve understanding of the importance of spatial distribution of refugia for burrowing herbivores. The analyses used allowed for the estimation of the spatial scale where subtle trade-offs between predation avoidance and foraging opportunity are likely to occur in a natural system.

The first high resolution image of coronal gas in a starbursting cool core cluster

NASA Astrophysics Data System (ADS)

Johnson, Sean

2017-08-01

Galaxy clusters represent a unique laboratory for directly observing gas cooling and feedback due to their high masses and correspondingly high gas densities and temperatures. Cooling of X-ray gas observed in 1/3 of clusters, known as cool-core clusters, should fuel star formation at prodigious rates, but such high levels of star formation are rarely observed. Feedback from active galactic nuclei (AGN) is a leading explanation for the lack of star formation in most cool clusters, and AGN power is sufficient to offset gas cooling on average. Nevertheless, some cool core clusters exhibit massive starbursts indicating that our understanding of cooling and feedback is incomplete. Observations of 10^5 K coronal gas in cool core clusters through OVI emission offers a sensitive means of testing our understanding of cooling and feedback because OVI emission is a dominant coolant and sensitive tracer of shocked gas. Recently, Hayes et al. 2016 demonstrated that synthetic narrow-band imaging of OVI emission is possible through subtraction of long-pass filters with the ACS+SBC for targets at z=0.23-0.29. Here, we propose to use this exciting new technique to directly image coronal OVI emitting gas at high resolution in Abell 1835, a prototypical starbursting cool-core cluster at z=0.252. Abell 1835 hosts a strong cooling core, massive starburst, radio AGN, and at z=0.252, it offers a unique opportunity to directly image OVI at hi-res in the UV with ACS+SBC. With just 15 orbits of ACS+SBC imaging, the proposed observations will complete the existing rich multi-wavelength dataset available for Abell 1835 to provide new insights into cooling and feedback in clusters.

RELICS: Strong-lensing Analysis of the Massive Clusters MACS J0308.9+2645 and PLCK G171.9‑40.7

NASA Astrophysics Data System (ADS)

Acebron, Ana; Cibirka, Nathália; Zitrin, Adi; Coe, Dan; Agulli, Irene; Sharon, Keren; Bradač, Maruša; Frye, Brenda; Livermore, Rachael C.; Mahler, Guillaume; Salmon, Brett; Umetsu, Keiichi; Bradley, Larry; Andrade-Santos, Felipe; Avila, Roberto; Carrasco, Daniela; Cerny, Catherine; Czakon, Nicole G.; Dawson, William A.; Hoag, Austin T.; Huang, Kuang-Han; Johnson, Traci L.; Jones, Christine; Kikuchihara, Shotaro; Lam, Daniel; Lovisari, Lorenzo; Mainali, Ramesh; Oesch, Pascal A.; Ogaz, Sara; Ouchi, Masami; Past, Matthew; Paterno-Mahler, Rachel; Peterson, Avery; Ryan, Russell E.; Sendra-Server, Irene; Stark, Daniel P.; Strait, Victoria; Toft, Sune; Trenti, Michele; Vulcani, Benedetta

2018-05-01

Strong gravitational lensing by galaxy clusters has become a powerful tool for probing the high-redshift universe, magnifying distant and faint background galaxies. Reliable strong-lensing (SL) models are crucial for determining the intrinsic properties of distant, magnified sources and for constructing their luminosity function. We present here the first SL analysis of MACS J0308.9+2645 and PLCK G171.9‑40.7, two massive galaxy clusters imaged with the Hubble Space Telescope, in the framework of the Reionization Lensing Cluster Survey (RELICS). We use the light-traces-mass modeling technique to uncover sets of multiply imaged galaxies and constrain the mass distribution of the clusters. Our SL analysis reveals that both clusters have particularly large Einstein radii (θ E > 30″ for a source redshift of z s = 2), providing fairly large areas with high magnifications, useful for high-redshift galaxy searches (∼2 arcmin2 with μ > 5 to ∼1 arcmin2 with μ > 10, similar to a typical Hubble Frontier Fields cluster). We also find that MACS J0308.9+2645 hosts a promising, apparently bright (J ∼ 23.2–24.6 AB), multiply imaged high-redshift candidate at z ∼ 6.4. These images are among the brightest high-redshift candidates found in RELICS. Our mass models, including magnification maps, are made publicly available for the community through the Mikulski Archive for Space Telescopes.

The Seven Sisters DANCe. I. Empirical isochrones, luminosity, and mass functions of the Pleiades cluster

NASA Astrophysics Data System (ADS)

Bouy, H.; Bertin, E.; Sarro, L. M.; Barrado, D.; Moraux, E.; Bouvier, J.; Cuillandre, J.-C.; Berihuete, A.; Olivares, J.; Beletsky, Y.

2015-05-01

Context. The DANCe survey provides photometric and astrometric (position and proper motion) measurements for approximately 2 million unique sources in a region encompassing ~80 deg2 centered on the Pleiades cluster. Aims: We aim at deriving a complete census of the Pleiades and measure the mass and luminosity functions of the cluster. Methods: Using the probabilistic selection method previously described, we identified high probability members in the DANCe (i ≥ 14 mag) and Tycho-2 (V ≲ 12 mag) catalogues and studied the properties of the cluster over the corresponding luminosity range. Results: We find a total of 2109 high-probability members, of which 812 are new, making it the most extensive and complete census of the cluster to date. The luminosity and mass functions of the cluster are computed from the most massive members down to ~0.025 M⊙. The size, sensitivity, and quality of the sample result in the most precise luminosity and mass functions observed to date for a cluster. Conclusions: Our census supersedes previous studies of the Pleiades cluster populations, in terms of both sensitivity and accuracy. Based on service observations made with the William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias.Table 1 and Appendices are available in electronic form at http://www.aanda.orgDANCe catalogs (Tables 6 and 7) and full Tables 2-5 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/577/A148

X-ray and optical substructures of the DAFT/FADA survey clusters

NASA Astrophysics Data System (ADS)

Guennou, L.; Durret, F.; Adami, C.; Lima Neto, G. B.

2013-04-01

We have undertaken the DAFT/FADA survey with the double aim of setting constraints on dark energy based on weak lensing tomography and of obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range 0.4-0.9 for which there were 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. Out of these, a spatial analysis was possible for 30 clusters, but only 23 had deep enough X-ray data for a really robust analysis. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. Altogether, the X-ray sample of 23 clusters and the optical sample of 26 clusters have 14 clusters in common. We present preliminary results on the coupled X-ray and dynamical analyses of these 14 clusters.

Scalable clustering algorithms for continuous environmental flow cytometry.

PubMed

Hyrkas, Jeremy; Clayton, Sophie; Ribalet, Francois; Halperin, Daniel; Armbrust, E Virginia; Howe, Bill

2016-02-01

Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. hyrkas@cs.washington.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

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

Parisi, M. C.; Clariá, J. J.; Marcionni, N.

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 authorsmore » 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.« less

On the Chemical Abundances of Miras in Clusters: V1 in the Metal-rich Globular NGC 5927

NASA Astrophysics Data System (ADS)

D’Orazi, V.; Magurno, D.; Bono, G.; Matsunaga, N.; Braga, V. F.; Elgueta, S. S.; Fukue, K.; Hamano, S.; Inno, L.; Kobayashi, N.; Kondo, S.; Monelli, M.; Nonino, M.; Przybilla, N.; Sameshima, H.; Saviane, I.; Taniguchi, D.; Thevenin, F.; Urbaneja-Perez, M.; Watase, A.; Arai, A.; Bergemann, M.; Buonanno, R.; Dall’Ora, M.; Da Silva, R.; Fabrizio, M.; Ferraro, I.; Fiorentino, G.; Francois, P.; Gilmozzi, R.; Iannicola, G.; Ikeda, Y.; Jian, M.; Kawakita, H.; Kudritzki, R. P.; Lemasle, B.; Marengo, M.; Marinoni, S.; Martínez-Vázquez, C. E.; Minniti, D.; Neeley, J.; Otsubo, S.; Prieto, J. L.; Proxauf, B.; Romaniello, M.; Sanna, N.; Sneden, C.; Takenaka, K.; Tsujimoto, T.; Valenti, E.; Yasui, C.; Yoshikawa, T.; Zoccali, M.

2018-03-01

We present the first spectroscopic abundance determination of iron, α-elements (Si, Ca, and Ti), and sodium for the Mira variable V1 in the metal-rich globular cluster NGC 5927. We use high-resolution (R ∼ 28,000), high signal-to-noise ratio (∼200) spectra collected with WINERED, a near-infrared (NIR) spectrograph covering simultaneously the wavelength range 0.91–1.35 μm. The effective temperature and the surface gravity at the pulsation phase of the spectroscopic observation were estimated using both optical (V) and NIR time-series photometric data. We found that the Mira is metal-rich ([Fe/H] = ‑0.55 ± 0.15) and moderately α-enhanced ([α/Fe] = 0.15 ± 0.01, σ = 0.2). These values agree quite well with the mean cluster abundances based on high-resolution optical spectra of several cluster red giants available in the literature ([Fe/H] = ‑ 0.47 ± 0.06, [α/Fe] = + 0.24 ± 0.05). We also found a Na abundance of +0.35 ± 0.20 that is higher than the mean cluster abundance based on optical spectra (+0.18 ± 0.13). However, the lack of similar spectra for cluster red giants and that of corrections for departures from local thermodynamical equilibrium prevents us from establishing whether the difference is intrinsic or connected with multiple populations. These findings indicate a strong similarity between optical and NIR metallicity scales in spite of the difference in the experimental equipment, data analysis, and in the adopted spectroscopic diagnostics. Based on spectra collected with the WINERED spectrograph available as a visitor instrument at the ESO New Technology Telescope (NTT), La Silla, Chile (ESO Proposal: 098.D-0878(A), PI: G. Bono).

Kinematics and dynamics of the MKW/AWM poor clusters

NASA Technical Reports Server (NTRS)

Beers, Timothy C.; Kriessler, Jeffrey R.; Bird, Christina M.; Huchra, John P.

1995-01-01

We report 472 new redshifts for 416 galaxies in the regions of the 23 poor clusters of galaxies originally identified by Morgan, Kayser, and White (MKW), and Albert, White, and Morgan (AWM). Eighteen of the poor clusters now have 10 or more available redshifts within 1.5/h Mpc of the central galaxy; 11 clusters have at least 20 available redshifts. Based on the 21 clusters for which we have sufficient velocity information, the median velocity scale is 336 km/s, a factor of 2 smaller than found for rich clusters. Several of the poor clusters exhibit complex velocity distributions due to the presence of nearby clumps of galaxies. We check on the velocity of the dominant galaxy in each poor cluster relative to the remaining cluster members. Significantly high relative velocities of the dominant galaxy are found in only 4 of 21 poor clusters, 3 of which we suspect are due to contamination of the parent velocity distribution. Several statistical tests indicate that the D/cD galaxies are at the kinematic centers of the parent poor cluster velocity distributions. Mass-to-light ratios for 13 of the 15 poor clusters for which we have the required data are in the range 50 less than or = M/L(sub B(0)) less than or = 200 solar mass/solar luminosity. The complex nature of the regions surrounding many of the poor clusters suggests that these groupings may represent an early epoch of cluster formation. For example, the poor clusters MKW7 and MKWS are shown to be gravitationally bound and likely to merge to form a richer cluster within the next several Gyrs. Eight of the nine other poor clusters for which simple two-body dynamical models can be carried out are consistent with being bound to other clumps in their vicinity. Additional complex systems with more than two gravitationally bound clumps are observed among the poor clusters.

Theoretical research program to study transition metal trimers and embedded clusters

NASA Technical Reports Server (NTRS)

Walch, S. P.

1984-01-01

Small transition metal clusters were studied at a high level of approximation, including all the valence electrons in the calculation and extensive electron correlation, in order to understand the electronic structure of these small metal clusters. By comparison of dimers, trimers, and possibly higher clusters, the information obtained was used to provide insights into the electronic structure of bulk transition metals. Small metal clusters are currently of considerable experimental interest and some information is becomming available both from matrix electron spin resonance studies and from gas phase spectroscopy. Collaboration between theorists and experimentalists is thus expected to be especially profitable at this time since there is some experimental information which can serve to guide the theoretical work.

Diverse, high-quality test set for the validation of protein-ligand docking performance.

PubMed

Hartshorn, Michael J; Verdonk, Marcel L; Chessari, Gianni; Brewerton, Suzanne C; Mooij, Wijnand T M; Mortenson, Paul N; Murray, Christopher W

2007-02-22

A procedure for analyzing and classifying publicly available crystal structures has been developed. It has been used to identify high-resolution protein-ligand complexes that can be assessed by reconstructing the electron density for the ligand using the deposited structure factors. The complexes have been clustered according to the protein sequences, and clusters have been discarded if they do not represent proteins thought to be of direct interest to the pharmaceutical or agrochemical industry. Rules have been used to exclude complexes containing non-drug-like ligands. One complex from each cluster has been selected where a structure of sufficient quality was available. The final Astex diverse set contains 85 diverse, relevant protein-ligand complexes, which have been prepared in a format suitable for docking and are to be made freely available to the entire research community (http://www.ccdc.cam.ac.uk). The performance of the docking program GOLD against the new set is assessed using a variety of protocols. Relatively unbiased protocols give success rates of approximately 80% for redocking into native structures, but it is possible to get success rates of over 90% with some protocols.

P2P Technology for High-Performance Computing: An Overview

NASA Technical Reports Server (NTRS)

Follen, Gregory J. (Technical Monitor); Berry, Jason

2003-01-01

The transition from cluster computing to peer-to-peer (P2P) high-performance computing has recently attracted the attention of the computer science community. It has been recognized that existing local networks and dedicated clusters of headless workstations can serve as inexpensive yet powerful virtual supercomputers. It has also been recognized that the vast number of lower-end computers connected to the Internet stay idle for as long as 90% of the time. The growing speed of Internet connections and the high availability of free CPU time encourage exploration of the possibility to use the whole Internet rather than local clusters as massively parallel yet almost freely available P2P supercomputer. As a part of a larger project on P2P high-performance computing, it has been my goal to compile an overview of the 2P2 paradigm. I have studied various P2P platforms and I have compiled systematic brief descriptions of their most important characteristics. I have also experimented and obtained hands-on experience with selected P2P platforms focusing on those that seem promising with respect to P2P high-performance computing. I have also compiled relevant literature and web references. I have prepared a draft technical report and I have summarized my findings in a poster paper.

Hox cluster polarity in early transcriptional availability: a high order regulatory level of clustered Hox genes in the mouse.

PubMed

Roelen, Bernard A J; de Graaff, Wim; Forlani, Sylvie; Deschamps, Jacqueline

2002-11-01

The molecular mechanism underlying the 3' to 5' polarity of induction of mouse Hox genes is still elusive. While relief from a cluster-encompassing repression was shown to lead to all Hoxd genes being expressed like the 3'most of them, Hoxd1 (Kondo and Duboule, 1999), the molecular basis of initial activation of this 3'most gene, is not understood yet. We show that, already before primitive streak formation, prior to initial expression of the first Hox gene, a dramatic transcriptional stimulation of the 3'most genes, Hoxb1 and Hoxb2, is observed upon a short pulse of exogenous retinoic acid (RA), whereas it is not in the case for more 5', cluster-internal, RA-responsive Hoxb genes. In contrast, the RA-responding Hoxb1lacZ transgene that faithfully mimics the endogenous gene (Marshall et al., 1994) did not exhibit the sensitivity of Hoxb1 to precocious activation. We conclude that polarity in initial activation of Hoxb genes reflects a greater availability of 3'Hox genes for transcription, suggesting a pre-existing (susceptibility to) opening of the chromatin structure at the 3' extremity of the cluster. We discuss the data in the context of prevailing models involving differential chromatin opening in the directionality of clustered Hox gene transcription, and regarding the importance of the cluster context for correct timing of initial Hox gene expression.Interestingly, Cdx1 manifested the same early transcriptional availability as Hoxb1. Copyright 2002 Elsevier Science Ireland Ltd.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Cluster redshifts in five suspected superclusters

NASA Technical Reports Server (NTRS)

Ciardullo, R.; Ford, H.; Harms, R.

1985-01-01

Redshift surveys for rich superclusters were carried out in five regions of the sky containing surface-density enhancements of Abell clusters. While several superclusters are identified, projection effects dominate each field, and no system contains more than five rich clusters. Two systems are found to be especially interesting. The first, field 0136 10, is shown to contain a superposition of at least four distinct superclusters, with the richest system possessing a small velocity dispersion. The second system, 2206 - 22, though a region of exceedingly high Abell cluster surface density, appears to be a remarkable superposition of 23 rich clusters almost uniformly distributed in redshift space between 0.08 and 0.24. The new redshifts significantly increase the three-dimensional information available for the distance class 5 and 6 Abell clusters and allow the spatial correlation function around rich superclusters to be estimated.

Plug cluster engine concept for in-space missions

NASA Technical Reports Server (NTRS)

Obrien, C. J.; Aukerman, C. A.

1979-01-01

The development of a suitable orbital transfer vehicle (OTV) engine is discussed. The OTV's dimensions are limited by those of the Space Shuttle payload bay on which it will be carried. An approach to utilize the available diameter to achieve high area ratio and thus high engine performance, is presented. Unconventional nozzles, such as clusters of small thrusters around a large diameter contoured plug, are investigated to arrive at engine designs which feature lower chamber pressures, with attendant lower heat flux, lower wall temperature, longer fatigue life, and less critical turbomachinery. Attention is also given to plug nozzle technology, high area ratio module- and scarfed bell- Plug Cluster Engine (PCE) concepts, as well as PCE performance, weight, and assessment. A conceptual design of a PCE formed from a cluster of high area ratio, scarfed, bell nozzles proved to be competitive with bell and spike nozzle engines. PCE advantages cited include increased payload length due to shorter engine length, ability to increase or decrease the number of modules and thereby the thrust, and low cost due to utilization of off-the-shelf technology.

Matrix Assisted and/or Laser Desorption Ionization Quadrupole Ion Trap Time-of-Flight Mass Spectrometry of WO3 Clusters Formation in Gas Phase. Nanodiamonds, Fullerene, and Graphene Oxide Matrices

NASA Astrophysics Data System (ADS)

Ausekar, Mayuri Vilas; Mawale, Ravi Madhukar; Pazdera, Pavel; Havel, Josef

2018-03-01

The formation of W x O y +●/-● clusters in the gas phase was studied by laser desorption ionization (LDI) and matrix assisted laser desorption ionization (MALDI) of solid WO3. LDI produced (WO3) n + ●/- ● ( n = 1-7) clusters. In MALDI, when using nano-diamonds (NDs), graphene oxide (GO), or fullerene (C60) matrices, higher mass clusters were generated. In addition to (WO3) n -● clusters, oxygen-rich or -deficient species were found in both LDI and MALDI (with the total number of clusters exceeding one hundred ≈ 137). This is the first time that such matrices have been used for the generation of(WO3) n + ●/-● clusters in the gas phase, while new high mass clusters (WO3) n -● ( n = 12-19) were also detected. [Figure not available: see fulltext.

[Applying the clustering technique for characterising maintenance outsourcing].

PubMed

Cruz, Antonio M; Usaquén-Perilla, Sandra P; Vanegas-Pabón, Nidia N; Lopera, Carolina

2010-06-01

Using clustering techniques for characterising companies providing health institutions with maintenance services. The study analysed seven pilot areas' equipment inventory (264 medical devices). Clustering techniques were applied using 26 variables. Response time (RT), operation duration (OD), availability and turnaround time (TAT) were amongst the most significant ones. Average biomedical equipment obsolescence value was 0.78. Four service provider clusters were identified: clusters 1 and 3 had better performance, lower TAT, RT and DR values (56 % of the providers coded O, L, C, B, I, S, H, F and G, had 1 to 4 day TAT values:

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Cluster-Expansion Model for Complex Quinary Alloys: Application to Alnico Permanent Magnets

NASA Astrophysics Data System (ADS)

Nguyen, Manh Cuong; Zhou, Lin; Tang, Wei; Kramer, Matthew J.; Anderson, Iver E.; Wang, Cai-Zhuang; Ho, Kai-Ming

2017-11-01

An accurate and transferable cluster-expansion model for complex quinary alloys is developed. Lattice Monte Carlo simulation enabled by this cluster-expansion model is used to investigate temperature-dependent atomic structure of alnico alloys, which are considered as promising high-performance non-rare-earth permanent-magnet materials for high-temperature applications. The results of the Monte Carlo simulations are consistent with available experimental data and provide useful insights into phase decomposition, selection, and chemical ordering in alnico. The simulations also reveal a previously unrecognized D 03 alloy phase. This phase is very rich in Ni and exhibits very weak magnetization. Manipulating the size and location of this phase provides a possible route to improve the magnetic properties of alnico, especially coercivity.

Limited Service Availability, Readiness, and Use of Facility-Based Delivery Care in Haiti: A Study Linking Health Facility Data and Population Data

PubMed Central

Wang, Wenjuan; Winner, Michelle; Burgert-Brucker, Clara R

2017-01-01

Background: Understanding the barriers that women in Haiti face to giving birth at a health facility is important for improving coverage of facility delivery and reducing persistently high maternal mortality. We linked health facility survey data and population survey data to assess the role of the obstetric service environment in affecting women's use of facility delivery care. Methods: Data came from the 2012 Haiti Demographic and Health Survey (DHS) and the 2013 Haiti Service Provision Assessment (SPA) survey. DHS clusters and SPA facilities were linked with their geographic coordinate information. The final analysis sample from the DHS comprised 4,921 women who had a live birth in the 5 years preceding the survey. Service availability was measured with the number of facilities providing delivery services within a specified distance from the cluster (within 5 kilometers for urban areas and 10 kilometers for rural areas). We measured facility readiness to provide obstetric care using 37 indicators defined by the World Health Organization. Random-intercept logistic regressions were used to model the variation in individual use of facility-based delivery care and cluster-level service availability and readiness, adjusting for other factors. Results: Overall, 39% of women delivered their most recent birth at a health facility and 61% delivered at home, with disparities by residence (about 60% delivered at a health facility in urban areas vs. 24% in rural areas). About one-fifth (18%) of women in rural areas and one-tenth (12%) of women in nonmetropolitan urban areas lived in clusters where no facility offered delivery care within the specified distances, while nearly all women (99%) in the metropolitan area lived in clusters that had at least 2 such facilities. Urban clusters had better service readiness compared with rural clusters, with a wide range of variation in both areas. Regression models indicated that in both rural and nonmetropolitan urban areas availability of delivery services was significantly associated with women's greater likelihood of using facility-based delivery care after controlling for other covariates, while facilities' readiness to provide delivery services was also important in nonmetropolitan urban areas. Conclusion: Increasing physical access to delivery care should become a high priority in rural Haiti. In urban areas, where delivery services are more available than in rural areas, improving quality of care at facilities could potentially lead to increased coverage of facility delivery. PMID:28539502

Typology of eaters based on conventional and organic food consumption: results from the NutriNet-Santé cohort study.

PubMed

Baudry, Julia; Touvier, Mathilde; Allès, Benjamin; Péneau, Sandrine; Méjean, Caroline; Galan, Pilar; Hercberg, Serge; Lairon, Denis; Kesse-Guyot, Emmanuelle

2016-08-01

Limited information is available on large-scale populations regarding the socio-demographic and nutrient profiles and eating behaviour of consumers, taking into account both organic and conventional foods. The aims of this study were to draw up a typology of consumers according to their eating habits, based both on their dietary patterns and the mode of food production, and to outline their socio-demographic, behavioural and nutritional characteristics. Data were collected from 28 245 participants of the NutriNet-Santé study. Dietary information was obtained using a 264-item, semi-quantitative, organic FFQ. To identify clusters of consumers, principal component analysis was applied on sixteen conventional and sixteen organic food groups followed by a clustering procedure. The following five clusters of consumers were identified: (1) a cluster characterised by low energy intake, low consumption of organic food and high prevalence of inadequate nutrient intakes; (2) a cluster of big eaters of conventional foods with high intakes of SFA and cholesterol; (3) a cluster with high consumption of organic food and relatively adequate nutritional diet quality; (4) a group with a high percentage of organic food consumers, 14 % of which were either vegetarians or vegans, who exhibited a high nutritional diet quality and a low prevalence of inadequate intakes of most vitamins except B12; and (5) a group of moderate organic food consumers with a particularly high intake of proteins and alcohol and a poor nutritional diet quality. These findings may have implications for future aetiological studies investigating the potential impact of organic food consumption.

Resource Provisioning in SLA-Based Cluster Computing

NASA Astrophysics Data System (ADS)

Xiong, Kaiqi; Suh, Sang

Cluster computing is excellent for parallel computation. It has become increasingly popular. In cluster computing, a service level agreement (SLA) is a set of quality of services (QoS) and a fee agreed between a customer and an application service provider. It plays an important role in an e-business application. An application service provider uses a set of cluster computing resources to support e-business applications subject to an SLA. In this paper, the QoS includes percentile response time and cluster utilization. We present an approach for resource provisioning in such an environment that minimizes the total cost of cluster computing resources used by an application service provider for an e-business application that often requires parallel computation for high service performance, availability, and reliability while satisfying a QoS and a fee negotiated between a customer and the application service provider. Simulation experiments demonstrate the applicability of the approach.

Performance enhancement of a web-based picture archiving and communication system using commercial off-the-shelf server clusters.

PubMed

Liu, Yan-Lin; Shih, Cheng-Ting; Chang, Yuan-Jen; Chang, Shu-Jun; Wu, Jay

2014-01-01

The rapid development of picture archiving and communication systems (PACSs) thoroughly changes the way of medical informatics communication and management. However, as the scale of a hospital's operations increases, the large amount of digital images transferred in the network inevitably decreases system efficiency. In this study, a server cluster consisting of two server nodes was constructed. Network load balancing (NLB), distributed file system (DFS), and structured query language (SQL) duplication services were installed. A total of 1 to 16 workstations were used to transfer computed radiography (CR), computed tomography (CT), and magnetic resonance (MR) images simultaneously to simulate the clinical situation. The average transmission rate (ATR) was analyzed between the cluster and noncluster servers. In the download scenario, the ATRs of CR, CT, and MR images increased by 44.3%, 56.6%, and 100.9%, respectively, when using the server cluster, whereas the ATRs increased by 23.0%, 39.2%, and 24.9% in the upload scenario. In the mix scenario, the transmission performance increased by 45.2% when using eight computer units. The fault tolerance mechanisms of the server cluster maintained the system availability and image integrity. The server cluster can improve the transmission efficiency while maintaining high reliability and continuous availability in a healthcare environment.

Performance Enhancement of a Web-Based Picture Archiving and Communication System Using Commercial Off-the-Shelf Server Clusters

PubMed Central

Chang, Shu-Jun; Wu, Jay

2014-01-01

The rapid development of picture archiving and communication systems (PACSs) thoroughly changes the way of medical informatics communication and management. However, as the scale of a hospital's operations increases, the large amount of digital images transferred in the network inevitably decreases system efficiency. In this study, a server cluster consisting of two server nodes was constructed. Network load balancing (NLB), distributed file system (DFS), and structured query language (SQL) duplication services were installed. A total of 1 to 16 workstations were used to transfer computed radiography (CR), computed tomography (CT), and magnetic resonance (MR) images simultaneously to simulate the clinical situation. The average transmission rate (ATR) was analyzed between the cluster and noncluster servers. In the download scenario, the ATRs of CR, CT, and MR images increased by 44.3%, 56.6%, and 100.9%, respectively, when using the server cluster, whereas the ATRs increased by 23.0%, 39.2%, and 24.9% in the upload scenario. In the mix scenario, the transmission performance increased by 45.2% when using eight computer units. The fault tolerance mechanisms of the server cluster maintained the system availability and image integrity. The server cluster can improve the transmission efficiency while maintaining high reliability and continuous availability in a healthcare environment. PMID:24701580

Probing the History of Galaxy Clusters with Metallicity and Entropy Measurements

NASA Astrophysics Data System (ADS)

Elkholy, Tamer Yohanna

Galaxy clusters are the largest gravitationally bound objects found today in our Universe. The gas they contain, the intra-cluster medium (ICM), is heated to temperatures in the approximate range of 1 to 10 keV, and thus emits X-ray radiation. Studying the ICM through the spatial and spectral analysis of its emission returns the richest information about both the overall cosmological context which governs the formation of clusters, as well as the physical processes occurring within. The aim of this thesis is to learn about the history of the physical processes that drive the evolution of galaxy clusters, through careful, spatially resolved measurements of their metallicity and entropy content. A sample of 45 nearby clusters observed with Chandra is analyzed to produce radial density, temperature, entropy and metallicity profiles. The entropy profiles are computed to larger radial extents than in previous Chandra analyses. The results of this analysis are made available to the scientific community in an electronic database. Comparing metallicity and entropy in the outskirts of clusters, we find no signature on the entropy profiles of the ensemble of supernovae that produced the observed metals. In the centers of clusters, we find that the metallicities of high-mass clusters are much less dispersed than those of low-mass clusters. A comparison of metallicity with the regularity of the X-ray emission morphology suggests that metallicities in low-mass clusters are more susceptible to increase from violent events such as mergers. We also find that the variation in the stellar-to-gas mass ratio as a function of cluster mass can explain the variation of central metallicity with cluster mass, only if we assume that there is a constant level of metallicity for clusters of all masses, above which the observed galaxies add more metals in proportion to their mass. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Development of a small-scale computer cluster

NASA Astrophysics Data System (ADS)

Wilhelm, Jay; Smith, Justin T.; Smith, James E.

2008-04-01

An increase in demand for computing power in academia has necessitated the need for high performance machines. Computing power of a single processor has been steadily increasing, but lags behind the demand for fast simulations. Since a single processor has hard limits to its performance, a cluster of computers can have the ability to multiply the performance of a single computer with the proper software. Cluster computing has therefore become a much sought after technology. Typical desktop computers could be used for cluster computing, but are not intended for constant full speed operation and take up more space than rack mount servers. Specialty computers that are designed to be used in clusters meet high availability and space requirements, but can be costly. A market segment exists where custom built desktop computers can be arranged in a rack mount situation, gaining the space saving of traditional rack mount computers while remaining cost effective. To explore these possibilities, an experiment was performed to develop a computing cluster using desktop components for the purpose of decreasing computation time of advanced simulations. This study indicates that small-scale cluster can be built from off-the-shelf components which multiplies the performance of a single desktop machine, while minimizing occupied space and still remaining cost effective.

Clustering by reordering of similarity and Laplacian matrices: Application to galaxy clusters

NASA Astrophysics Data System (ADS)

Mahmoud, E.; Shoukry, A.; Takey, A.

2018-04-01

Similarity metrics, kernels and similarity-based algorithms have gained much attention due to their increasing applications in information retrieval, data mining, pattern recognition and machine learning. Similarity Graphs are often adopted as the underlying representation of similarity matrices and are at the origin of known clustering algorithms such as spectral clustering. Similarity matrices offer the advantage of working in object-object (two-dimensional) space where visualization of clusters similarities is available instead of object-features (multi-dimensional) space. In this paper, sparse ɛ-similarity graphs are constructed and decomposed into strong components using appropriate methods such as Dulmage-Mendelsohn permutation (DMperm) and/or Reverse Cuthill-McKee (RCM) algorithms. The obtained strong components correspond to groups (clusters) in the input (feature) space. Parameter ɛi is estimated locally, at each data point i from a corresponding narrow range of the number of nearest neighbors. Although more advanced clustering techniques are available, our method has the advantages of simplicity, better complexity and direct visualization of the clusters similarities in a two-dimensional space. Also, no prior information about the number of clusters is needed. We conducted our experiments on two and three dimensional, low and high-sized synthetic datasets as well as on an astronomical real-dataset. The results are verified graphically and analyzed using gap statistics over a range of neighbors to verify the robustness of the algorithm and the stability of the results. Combining the proposed algorithm with gap statistics provides a promising tool for solving clustering problems. An astronomical application is conducted for confirming the existence of 45 galaxy clusters around the X-ray positions of galaxy clusters in the redshift range [0.1..0.8]. We re-estimate the photometric redshifts of the identified galaxy clusters and obtain acceptable values compared to published spectroscopic redshifts with a 0.029 standard deviation of their differences.

Markov Chain Monte Carlo Joint Analysis of Chandra X-Ray Imaging Spectroscopy and Sunyaev-Zel'dovich Effect Data

NASA Technical Reports Server (NTRS)

Bonamente, Massimillano; Joy, Marshall K.; Carlstrom, John E.; Reese, Erik D.; LaRoque, Samuel J.

2004-01-01

X-ray and Sunyaev-Zel'dovich effect data can be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from Chandra, which provides both spatial and spectral information, and Sunyaev-Zel'dovich effect data were obtained from the BIMA and Owens Valley Radio Observatory (OVRO) arrays. We introduce a Markov Chain Monte Carlo procedure for the joint analysis of X-ray and Sunyaev- Zel'dovich effect data. The advantages of this method are the high computational efficiency and the ability to measure simultaneously the probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and also for derivative quantities such as the distance to the cluster. We demonstrate this technique by applying it to the Chandra X-ray data and the OVRO radio data for the galaxy cluster A611. Comparisons with traditional likelihood ratio methods reveal the robustness of the method. This method will be used in follow-up paper to determine the distances to a large sample of galaxy cluster.

First-principles investigation of the dissociation and coupling of methane on small copper clusters: Interplay of collision dynamics and geometric and electronic effects

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

Varghese, Jithin J.; Mushrif, Samir H., E-mail: shmushrif@ntu.edu.sg

Small metal clusters exhibit unique size and morphology dependent catalytic activity. The search for alternate minimum energy pathways and catalysts to transform methane to more useful chemicals and carbon nanomaterials led us to investigate collision induced dissociation of methane on small Cu clusters. We report here for the first time, the free energy barriers for the collision induced activation, dissociation, and coupling of methane on small Cu clusters (Cu{sub n} where n = 2–12) using ab initio molecular dynamics and metadynamics simulations. The collision induced activation of the stretching and bending vibrations of methane significantly reduces the free energy barriermore » for its dissociation. Increase in the cluster size reduces the barrier for dissociation of methane due to the corresponding increase in delocalisation of electron density within the cluster, as demonstrated using the electron localisation function topology analysis. This enables higher probability of favourable alignment of the C–H stretching vibration of methane towards regions of high electron density within the cluster and makes higher number of sites available for the chemisorption of CH{sub 3} and H upon dissociation. These characteristics contribute in lowering the barrier for dissociation of methane. Distortion and reorganisation of cluster geometry due to high temperature collision dynamics disturb electron delocalisation within them and increase the barrier for dissociation. Coupling reactions of CH{sub x} (x = 1–3) species and recombination of H with CH{sub x} have free energy barriers significantly lower than complete dehydrogenation of methane to carbon. Thus, competition favours the former reactions at high hydrogen saturation on the clusters.« less

GLOBULAR CLUSTER ABUNDANCES FROM HIGH-RESOLUTION, INTEGRATED-LIGHT SPECTROSCOPY. III. THE LARGE MAGELLANIC CLOUD: Fe AND AGES

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

Colucci, Janet E.; Bernstein, Rebecca A.; Cameron, Scott A.

2011-07-01

In this paper, we refine our method for the abundance analysis of high-resolution spectroscopy of the integrated light of unresolved globular clusters (GCs). This method was previously demonstrated for the analysis of old (>10 Gyr) Milky Way (MW) GCs. Here, we extend the technique to young clusters using a training set of nine GCs in the Large Magellanic Cloud. Depending on the signal-to-noise ratio of the data, we use 20-100 Fe lines per cluster to successfully constrain the ages of old clusters to within a {approx}5 Gyr range, the ages of {approx}2 Gyr clusters to a 1-2 Gyr range, andmore » the ages of the youngest clusters (0.05-1 Gyr) to a {approx}200 Myr range. We also demonstrate that we can measure [Fe/H] in clusters with any age less than 12 Gyr with similar or only slightly larger uncertainties (0.1-0.25 dex) than those obtained for old MW GCs (0.1 dex); the slightly larger uncertainties are due to the rapid evolution in stellar populations at these ages. In this paper, we present only Fe abundances and ages. In the next paper in this series, we present our complete analysis of {approx}20 elements for which we are able to measure abundances. For several of the clusters in this sample, there are no high-resolution abundances in the literature from individual member stars; our results are the first detailed chemical abundances available. The spectra used in this paper were obtained at Las Campanas with the echelle on the du Pont Telescope and with the MIKE spectrograph on the Magellan Clay Telescope.« less

Millisecond resolution electron fluxes from the Cluster satellites: Calibrated EDI ambient electron data

NASA Astrophysics Data System (ADS)

Förster, Matthias; Rashev, Mikhail; Haaland, Stein

2017-04-01

The Electron Drift Instrument (EDI) onboard Cluster can measure 500 eV and 1 keV electron fluxes with high time resolution during passive operation phases in its Ambient Electron (AE) mode. Data from this mode is available in the Cluster Science Archive since October 2004 with a cadence of 16 Hz in the normal mode or 128 Hz for burst mode telemetry intervals. The fluxes are recorded at pitch angles of 0, 90, and 180 degrees. This paper describes the calibration and validation of these measurements. The high resolution AE data allow precise temporal and spatial diagnostics of magnetospheric boundaries and will be used for case studies and statistical studies of low energy electron fluxes in the near-Earth space. We show examples of applications.

A clustering approach to segmenting users of internet-based risk calculators.

PubMed

Harle, C A; Downs, J S; Padman, R

2011-01-01

Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

Effect of video server topology on contingency capacity requirements

NASA Astrophysics Data System (ADS)

Kienzle, Martin G.; Dan, Asit; Sitaram, Dinkar; Tetzlaff, William H.

1996-03-01

Video servers need to assign a fixed set of resources to each video stream in order to guarantee on-time delivery of the video data. If a server has insufficient resources to guarantee the delivery, it must reject the stream request rather than slowing down all existing streams. Large scale video servers are being built as clusters of smaller components, so as to be economical, scalable, and highly available. This paper uses a blocking model developed for telephone systems to evaluate video server cluster topologies. The goal is to achieve high utilization of the components and low per-stream cost combined with low blocking probability and high user satisfaction. The analysis shows substantial economies of scale achieved by larger server images. Simple distributed server architectures can result in partitioning of resources with low achievable resource utilization. By comparing achievable resource utilization of partitioned and monolithic servers, we quantify the cost of partitioning. Next, we present an architecture for a distributed server system that avoids resource partitioning and results in highly efficient server clusters. Finally, we show how, in these server clusters, further optimizations can be achieved through caching and batching of video streams.

Conformational Clusters of Phosphorylated Tyrosine.

PubMed

Abdelrasoul, Maha; Ponniah, Komala; Mao, Alice; Warden, Meghan S; Elhefnawy, Wessam; Li, Yaohang; Pascal, Steven M

2017-12-06

Tyrosine phosphorylation plays an important role in many cellular and intercellular processes including signal transduction, subcellular localization, and regulation of enzymatic activity. In 1999, Blom et al., using the limited number of protein data bank (PDB) structures available at that time, reported that the side chain structures of phosphorylated tyrosine (pY) are partitioned into two conserved conformational clusters ( Blom, N.; Gammeltoft, S.; Brunak, S. J. Mol. Biol. 1999 , 294 , 1351 - 1362 ). We have used the spectral clustering algorithm to cluster the increasingly growing number of protein structures with pY sites, and have found that the pY residues cluster into three distinct side chain conformations. Two of these pY conformational clusters associate strongly with a narrow range of tyrosine backbone conformation. The novel cluster also highly correlates with the identity of the n + 1 residue, and is strongly associated with a sequential pYpY conformation which places two adjacent pY side chains in a specific relative orientation. Further analysis shows that the three pY clusters are associated with distinct distributions of cognate protein kinases.

RELICS: Strong Lens Models for Five Galaxy Clusters from the Reionization Lensing Cluster Survey

NASA Astrophysics Data System (ADS)

Cerny, Catherine; Sharon, Keren; Andrade-Santos, Felipe; Avila, Roberto J.; Bradač, Maruša; Bradley, Larry D.; Carrasco, Daniela; Coe, Dan; Czakon, Nicole G.; Dawson, William A.; Frye, Brenda L.; Hoag, Austin; Huang, Kuang-Han; Johnson, Traci L.; Jones, Christine; Lam, Daniel; Lovisari, Lorenzo; Mainali, Ramesh; Oesch, Pascal A.; Ogaz, Sara; Past, Matthew; Paterno-Mahler, Rachel; Peterson, Avery; Riess, Adam G.; Rodney, Steven A.; Ryan, Russell E.; Salmon, Brett; Sendra-Server, Irene; Stark, Daniel P.; Strolger, Louis-Gregory; Trenti, Michele; Umetsu, Keiichi; Vulcani, Benedetta; Zitrin, Adi

2018-06-01

Strong gravitational lensing by galaxy clusters magnifies background galaxies, enhancing our ability to discover statistically significant samples of galaxies at {\\boldsymbol{z}}> 6, in order to constrain the high-redshift galaxy luminosity functions. Here, we present the first five lens models out of the Reionization Lensing Cluster Survey (RELICS) Hubble Treasury Program, based on new HST WFC3/IR and ACS imaging of the clusters RXC J0142.9+4438, Abell 2537, Abell 2163, RXC J2211.7–0349, and ACT-CLJ0102–49151. The derived lensing magnification is essential for estimating the intrinsic properties of high-redshift galaxy candidates, and properly accounting for the survey volume. We report on new spectroscopic redshifts of multiply imaged lensed galaxies behind these clusters, which are used as constraints, and detail our strategy to reduce systematic uncertainties due to lack of spectroscopic information. In addition, we quantify the uncertainty on the lensing magnification due to statistical and systematic errors related to the lens modeling process, and find that in all but one cluster, the magnification is constrained to better than 20% in at least 80% of the field of view, including statistical and systematic uncertainties. The five clusters presented in this paper span the range of masses and redshifts of the clusters in the RELICS program. We find that they exhibit similar strong lensing efficiencies to the clusters targeted by the Hubble Frontier Fields within the WFC3/IR field of view. Outputs of the lens models are made available to the community through the Mikulski Archive for Space Telescopes.

FORS2/VLT survey of Milky Way globular clusters. II. Fe and Mg abundances of 51 Milky Way globular clusters on a homogeneous scale

NASA Astrophysics Data System (ADS)

Dias, B.; Barbuy, B.; Saviane, I.; Held, E. V.; Da Costa, G. S.; Ortolani, S.; Gullieuszik, M.; Vásquez, S.

2016-05-01

Context. Globular clusters trace the formation and evolution of the Milky Way and surrounding galaxies, and outline their chemical enrichment history. To accomplish these tasks it is important to have large samples of clusters with homogeneous data and analysis to derive kinematics, chemical abundances, ages and locations. Aims: We obtain homogeneous metallicities and α-element enhancement for 51 Galactic bulge, disc, and halo globular clusters that are among the most distant and/or highly reddened in the Galaxy's globular cluster system. We also provide membership selection based on stellar radial velocities and atmospheric parameters. The implications of our results are discussed. Methods: We observed R ~ 2000 spectra in the wavelength interval 456-586 nm for over 800 red giant stars in 51 Galactic globular clusters. We applied full spectrum fitting with the code ETOILE together with libraries of observed and synthetic spectra. We compared the mean abundances of all clusters with previous work and with field stars. We used the relation between mean metallicity and horizontal branch morphology defined by all clusters to select outliers for discussion. Results: [Fe/H], [Mg/Fe], and [α/Fe] were derived in a consistent way for almost one-third of all Galactic globular clusters. We find our metallicities are comparable to those derived from high-resolution data to within σ = 0.08 dex over the interval -2.5< [Fe/H] < 0.0. Furthermore, a comparison of previous metallicity scales with our values yields σ< 0.16 dex. We also find that the distribution of [Mg/Fe] and [α/Fe] with [Fe/H] for the 51 clusters follows the general trend exhibited by field stars. It is the first time that the following clusters have been included in a large sample of homogeneous stellar spectroscopic observations and metallicity derivation: BH 176, Djorg 2, Pal 10, NGC 6426, Lynga 7, and Terzan 8. In particular, only photometric metallicities were available previously for the first three clusters, and the available metallicity for NGC 6426 was based on integrated spectroscopy and photometry. Two other clusters, HP 1 and NGC 6558, are confirmed as candidates for the oldest globular clusters in the Milky Way. Conclusions: Stellar spectroscopy in the visible at R ~ 2000 for a large sample of globular clusters is a robust and efficient way to trace the chemical evolution of the host galaxy and to detect interesting objects for follow-up at higher resolution and with forthcoming giant telescopes. The technique used here can also be applied to globular cluster systems in nearby galaxies with current instruments and to distant galaxies with the advent of ELTs. Based on observations collected at the European Southern Observatory/Paranal, Chile, under programmes 68.B-0482(A), 69.D-0455(A), 71.D-0219(A), 077.D-0775(A), and 089.D-0493(B).Full Tables 1 and A.2 with the derived average parameters for the 758 red giant stars are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/590/A9

Cooperativity in self-limiting equilibrium self-associating systems

NASA Astrophysics Data System (ADS)

Freed, Karl F.

2012-11-01

A wide variety of highly cooperative self-assembly processes in biological and synthetic systems involve the assembly of a large number (m) of units into clusters, with m narrowly peaked about a large size m0 ≫ 1 and with a second peak centered about the m = 1 unassembled monomers. While very specific models have been proposed for the assembly of, for example, viral capsids and core-shell micelles of ß-casein, no available theory describes a thermodynamically general mechanism for this double peaked, highly cooperative equilibrium assembly process. This study provides a general mechanism for these cooperative processes by developing a minimal Flory-Huggins type theory. Beginning from the simplest non-cooperative, free association model in which the equilibrium constant for addition of a monomer to a cluster is independent of cluster size, the new model merely allows more favorable growth for clusters of intermediate sizes. The theory is illustrated by computing the phase diagram for cases of self-assembly on cooling or heating and for the mass distribution of the two phases.

Formation of Clustered DNA Damage after High-LET Irradiation: A Review

NASA Technical Reports Server (NTRS)

Hada, Megumi; Georgakilas, Alexandros G.

2008-01-01

Radiation can cause as well as cure cancer. The risk of developing radiation-induced cancer has traditionally been estimated from cancer incidence among survivors of the atomic bombs in Hiroshima and Nagasaki. These data provide the best estimate of human cancer risk over the dose range for low linear energy transfer (LET) radiations, such as X- or gamma-rays. The situation of estimating the real biological effects becomes even more difficult in the case of high LET particles encountered in space or as the result of domestic exposure to particles from radon gas emitters or other radioactive emitters like uranium-238. Complex DNA damage, i.e., the signature of high-LET radiations comprises by closely spaced DNA lesions forming a cluster of DNA damage. The two basic groups of complex DNA damage are double strand breaks (DSBs) and non-DSB oxidative clustered DNA lesions (OCDL). Theoretical analysis and experimental evidence suggest there is increased complexity and severity of complex DNA damage with increasing LET (linear energy transfer) and a high mutagenic or carcinogenic potential. Data available on the formation of clustered DNA damage (DSBs and OCDL) by high-LET radiations are often controversial suggesting a variable response to dose and type of radiation. The chemical nature and cellular repair mechanisms of complex DNA damage have been much less characterized than those of isolated DNA lesions like an oxidized base or a single strand break especially in the case of high-LET radiation. This review will focus on the induction of clustered DNA damage by high-LET radiations presenting the earlier and recent relative data.

Consumer clusters in Denmark based on coarse vegetable intake frequency, explained by hedonics, socio-demographic, health and food lifestyle factors. A cross-sectional national survey.

PubMed

Beck, Tove K; Jensen, Sidsel; Simmelsgaard, Sonni Hansen; Kjeldsen, Chris; Kidmose, Ulla

2015-08-01

Vegetable intake seems to play a protective role against major lifestyle diseases. Despite this, the Danish population usually eats far less than the recommended daily intake. The present study focused on the intake of 17 coarse vegetables and the potential barriers limiting their intake. The present study drew upon a large Danish survey (n = 1079) to study the intake of coarse vegetables among Danish consumers. Four population clusters were identified based on their intake of 17 different coarse vegetables, and profiled according to hedonics, socio-demographic, health, and food lifestyle factors. The four clusters were characterized by a very low intake frequency of coarse vegetables ('low frequency'), a low intake frequency of coarse vegetables; but high intake frequency of carrots ('carrot eaters'), a moderate coarse vegetable intake frequency and high intake frequency of beetroot ('beetroot eaters'), and a high intake frequency of all coarse vegetables ('high frequency'). There was a relationship between reported liking and reported intake frequency for all tested vegetables. Preference for foods with a sweet, salty or bitter taste, in general, was also identified to be decisive for the reported vegetable intake, as these differed across the clusters. Each cluster had distinct socio-demographic, health and food lifestyle profiles. 'Low frequency' was characterized by uninvolved consumers with lack of interest in food, 'carrot eaters' vegetable intake was driven by health aspects, 'beetroot eaters' were characterized as traditional food consumers, and 'high frequency' were individuals with a strong food engagement and high vegetable liking. 'Low frequency' identified more barriers than other consumer clusters and specifically regarded low availability of pre-cut/prepared coarse vegetables on the market as a barrier. Across all clusters a low culinary knowledge was identified as the main barrier. Copyright © 2015 Elsevier Ltd. All rights reserved.

On efficiency of fire simulation realization: parallelization with greater number of computational meshes

NASA Astrophysics Data System (ADS)

Valasek, Lukas; Glasa, Jan

2017-12-01

Current fire simulation systems are capable to utilize advantages of high-performance computer (HPC) platforms available and to model fires efficiently in parallel. In this paper, efficiency of a corridor fire simulation on a HPC computer cluster is discussed. The parallel MPI version of Fire Dynamics Simulator is used for testing efficiency of selected strategies of allocation of computational resources of the cluster using a greater number of computational cores. Simulation results indicate that if the number of cores used is not equal to a multiple of the total number of cluster node cores there are allocation strategies which provide more efficient calculations.

Clustervision: Visual Supervision of Unsupervised Clustering.

PubMed

Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; De Filippi, Christopher; Stewart, Walter F; Perer, Adam

2018-01-01

Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.

EClerize: A customized force-directed graph drawing algorithm for biological graphs with EC attributes.

PubMed

Danaci, Hasan Fehmi; Cetin-Atalay, Rengul; Atalay, Volkan

2018-03-26

Visualizing large-scale data produced by the high throughput experiments as a biological graph leads to better understanding and analysis. This study describes a customized force-directed layout algorithm, EClerize, for biological graphs that represent pathways in which the nodes are associated with Enzyme Commission (EC) attributes. The nodes with the same EC class numbers are treated as members of the same cluster. Positions of nodes are then determined based on both the biological similarity and the connection structure. EClerize minimizes the intra-cluster distance, that is the distance between the nodes of the same EC cluster and maximizes the inter-cluster distance, that is the distance between two distinct EC clusters. EClerize is tested on a number of biological pathways and the improvement brought in is presented with respect to the original algorithm. EClerize is available as a plug-in to cytoscape ( http://apps.cytoscape.org/apps/eclerize ).

SUPERNOVAE AND THEIR EXPANDING BLAST WAVES DURING THE EARLY EVOLUTION OF GALACTIC GLOBULAR CLUSTERS

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

Tenorio-Tagle, Guillermo; Silich, Sergiy; Muñoz-Tuñón, Casiana

2015-11-20

Our arguments deal with the early evolution of Galactic globular clusters and show why only a few of the supernovae (SNe) products were retained within globular clusters and only in the most massive cases (M ≥ 10{sup 6} M{sub ⊙}), while less massive clusters were not contaminated at all by SNe. Here, we show that SN blast waves evolving in a steep density gradient undergo blowout and end up discharging their energy and metals into the medium surrounding the clusters. This inhibits the dispersal and the contamination of the gas left over from a first stellar generation. Only the ejecta from well-centeredmore » SNe that evolve into a high-density medium available for a second stellar generation (2SG) in the most massive clusters would be retained. These are likely to mix their products with the remaining gas, eventually leading in these cases to an Fe-contaminated 2SG.« less

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

ATCA observations of the MACS-Planck Radio Halo Cluster Project. II. Radio observations of an intermediate redshift cluster sample

NASA Astrophysics Data System (ADS)

Martinez Aviles, G.; Johnston-Hollitt, M.; Ferrari, C.; Venturi, T.; Democles, J.; Dallacasa, D.; Cassano, R.; Brunetti, G.; Giacintucci, S.; Pratt, G. W.; Arnaud, M.; Aghanim, N.; Brown, S.; Douspis, M.; Hurier, J.; Intema, H. T.; Langer, M.; Macario, G.; Pointecouteau, E.

2018-04-01

Aim. A fraction of galaxy clusters host diffuse radio sources whose origins are investigated through multi-wavelength studies of cluster samples. We investigate the presence of diffuse radio emission in a sample of seven galaxy clusters in the largely unexplored intermediate redshift range (0.3 < z < 0.44). Methods: In search of diffuse emission, deep radio imaging of the clusters are presented from wide band (1.1-3.1 GHz), full resolution ( 5 arcsec) observations with the Australia Telescope Compact Array (ATCA). The visibilities were also imaged at lower resolution after point source modelling and subtraction and after a taper was applied to achieve better sensitivity to low surface brightness diffuse radio emission. In case of non-detection of diffuse sources, we set upper limits for the radio power of injected diffuse radio sources in the field of our observations. Furthermore, we discuss the dynamical state of the observed clusters based on an X-ray morphological analysis with XMM-Newton. Results: We detect a giant radio halo in PSZ2 G284.97-23.69 (z = 0.39) and a possible diffuse source in the nearly relaxed cluster PSZ2 G262.73-40.92 (z = 0.421). Our sample contains three highly disturbed massive clusters without clear traces of diffuse emission at the observed frequencies. We were able to inject modelled radio haloes with low values of total flux density to set upper detection limits; however, with our high-frequency observations we cannot exclude the presence of RH in these systems because of the sensitivity of our observations in combination with the high z of the observed clusters. The reduced images are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/611/A94

The highly ionized, high-velocity gas in NGC 6231

NASA Astrophysics Data System (ADS)

Massa, Derck

2017-02-01

It is well known that clusters of massive stars are influenced by the presence of strong winds, that they are sources of diffuse X-rays from shocked gas, and that this gas can be vented into the surrounding region or the halo through the champagne effect. However, the details of how these different environments interact and evolve are far from complete. This paper attributes the broad C IVλλ1500 absorption features (extending to -1900 km s-1) that are seen in the spectra of main sequence B stars in NGC 6231 to gas in the cluster environment and not the B stars themselves. It is shown that the presence of a WC star, WR 79, in the cluster makes this gas detectable because its wind enriches the cluster gas with carbon. Given the available data, it is not clear whether the absorbing gas is simply the far wind of WR 79 or a collective cluster wind enriched by carbon from the wind of WR 79. If it is simply due to the wind, then this wind must flow, unimpeded for more than 2 pc, suggesting that the inner region of the cluster is nearly devoid of obstructing material. If it is actually a collective wind from the cluster, then we could be witnessing an important stage of galactic feedback. In either case, the observations provide a unique and significant piece to the puzzle of how massive, open clusters evolve.

Effects of carbonyl bond, metal cluster dissociation, and evaporation rates on predictions of nanotube production in high-pressure carbon monoxide

NASA Technical Reports Server (NTRS)

Scott, Carl D.; Smalley, Richard E.

2003-01-01

The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNTs) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the conformation of CO2. It is shown that the production of CO2 is significantly greater for FeCO because of its lower bond energy as compared with that of NiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

Patterns and predictors of clustered risky health behaviors among adult survivors of childhood cancer: A report from the Childhood Cancer Survivor Study.

PubMed

Lown, E Anne; Hijiya, Nobuko; Zhang, Nan; Srivastava, Deo Kumar; Leisenring, Wendy M; Nathan, Paul C; Castellino, Sharon M; Devine, Katie A; Dilley, Kimberley; Krull, Kevin R; Oeffinger, Kevin C; Hudson, Melissa M; Armstrong, Gregory T; Robison, Leslie L; Ness, Kirsten K

2016-09-01

Health complications related to childhood cancer may be influenced by risky health behaviors (RHBs), particularly when RHBs co-occur. To the authors' knowledge, only limited information is available describing how RHBs cluster among survivors of childhood cancer and their siblings and the risk factors for co-occurring RHBs. Latent class analysis was used to identify RHB clusters using longitudinal survey data regarding smoking, alcohol use, and physical activity from adult survivors (4184 survivors) and siblings (1598 siblings) in the Childhood Cancer Survivor Study. Generalized logistic regression was used to evaluate associations between demographic characteristics, treatment exposures, psychological distress, health conditions, and cluster membership. Three RHB clusters were identified: a low-risk cluster, an insufficiently active cluster, and a high-risk cluster (tobacco and risky alcohol use and insufficient activity). Compared with siblings, survivors were more likely to be in the insufficiently active cluster (adjusted odds ratio [ORadj ], 1.17; 95% confidence interval [95% CI], 1.06-1.27) and were less likely to be in the high-risk cluster (ORadj , 0.79; 95% CI, 0.69-0.88). Risk factors for membership in the high-risk cluster included psychological distress (ORadj , 2.76; 95% CI, 1.98-3.86), low educational attainment (ORadj , 7.49; 95% CI, 5.15-10.88), income <$20,000 (ORadj , 2.62; 95% CI, 1.93-3.57), being divorced/separated or widowed (ORadj , 1.36; 95% CI, 1.03-1.79), and limb amputation (ORadj , 1.52; 95% CI, 1.03-2.24). Risk factors for the insufficiently active cluster included chronic health conditions, psychological distress, low education or income, being obese or overweight, female sex, nonwhite race/ethnicity, single marital status, cranial radiation, and cisplatin exposure. RHBs co-occur in survivors of childhood cancer and their siblings. Economic and educational disadvantages and psychological distress should be considered in screening and interventions to reduce RHBs. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2747-2756. © 2016 American Cancer Society. © 2016 American Cancer Society.

Prospects of molybdenum and rhenium octahedral cluster complexes as X-ray contrast agents.

PubMed

Krasilnikova, Anna A; Shestopalov, Michael A; Brylev, Konstantin A; Kirilova, Irina A; Khripko, Olga P; Zubareva, Kristina E; Khripko, Yuri I; Podorognaya, Valentina T; Shestopalova, Lidiya V; Fedorov, Vladimir E; Mironov, Yuri V

2015-03-01

Investigation of new X-ray contrast media for radiography is an important field of science since discovering of X-rays in 1895. Despite the wide diversity of available X-ray contrast media the toxicity, especially nephrotoxicity, is still a big problem to be solved. The octahedral metal-cluster complexes of the general formula [{M6Q8}L6] can be considered as quite promising candidates for the role of new radiocontrast media due to the high local concentration of heavy elements, high tuning ability of ligand environment and low toxicity. To exemplify this, the X-ray computed tomography experiments for the first time were carried out on some octahedral cluster complexes of molybdenum and rhenium. Based on the obtained data it was proposed to investigate the toxicological proprieties of cluster complex Na2H8[{Re6Se8}(P(CH2CH2CONH2)(CH2CH2COO)2)6]. Observed low cytotoxic and acute toxic effects along with rapid renal excretion of the cluster complex evidence its perspective as an X-ray contrast media for radiography. Copyright © 2014 Elsevier Inc. All rights reserved.

STAR CLUSTER FORMATION AND DESTRUCTION IN THE MERGING GALAXY NGC 3256

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

Mulia, A. J.; Chandar, R.; Whitmore, B. C.

2016-07-20

We use the Advanced Camera for Surveys on the Hubble Space Telescope to study the rich population of young massive star clusters in the main body of NGC 3256, a merging pair of galaxies with a high star formation rate (SFR) and SFR per unit area (Σ{sub SFR}). These clusters have luminosity and mass functions that follow power laws, dN / dL ∝ L{sup α} with α = 2.23 ± 0.07, and dN / dM ∝ M{sup β} with β = 1.86 ± 0.34 for τ < 10 Myr clusters, similar to those found in more quiescent galaxies. The agemore » distribution can be described by dN / dτ ∝ τ{sup γ}, with γ ≈ 0.67 ± 0.08 for clusters younger than about a few hundred million years, with no obvious dependence on cluster mass. This is consistent with a picture where ∼80% of the clusters are disrupted each decade in time. We investigate the claim that galaxies with high Σ{sub SFR} form clusters more efficiently than quiescent systems by determining the fraction of stars in bound clusters (Γ) and the CMF/SFR statistic (CMF is the cluster mass function) for NGC 3256 and comparing the results with those for other galaxies. We find that the CMF/SFR statistic for NGC 3256 agrees well with that found for galaxies with Σ{sub SFR} and SFRs that are lower by 1–3 orders of magnitude, but that estimates for Γ are only robust when the same sets of assumptions are applied. Currently, Γ values available in the literature have used different sets of assumptions, making it more difficult to compare the results between galaxies.« less

Star Cluster Formation and Destruction in the Merging Galaxy NGC 3256

NASA Astrophysics Data System (ADS)

Mulia, A. J.; Chandar, R.; Whitmore, B. C.

2016-07-01

We use the Advanced Camera for Surveys on the Hubble Space Telescope to study the rich population of young massive star clusters in the main body of NGC 3256, a merging pair of galaxies with a high star formation rate (SFR) and SFR per unit area (ΣSFR). These clusters have luminosity and mass functions that follow power laws, dN/dL ∝ L α with α = -2.23 ± 0.07, and dN/dM ∝ M β with β = -1.86 ± 0.34 for τ < 10 Myr clusters, similar to those found in more quiescent galaxies. The age distribution can be described by dN/dτ ∝ τ γ , with γ ≈ -0.67 ± 0.08 for clusters younger than about a few hundred million years, with no obvious dependence on cluster mass. This is consistent with a picture where ˜80% of the clusters are disrupted each decade in time. We investigate the claim that galaxies with high ΣSFR form clusters more efficiently than quiescent systems by determining the fraction of stars in bound clusters (Γ) and the CMF/SFR statistic (CMF is the cluster mass function) for NGC 3256 and comparing the results with those for other galaxies. We find that the CMF/SFR statistic for NGC 3256 agrees well with that found for galaxies with ΣSFR and SFRs that are lower by 1-3 orders of magnitude, but that estimates for Γ are only robust when the same sets of assumptions are applied. Currently, Γ values available in the literature have used different sets of assumptions, making it more difficult to compare the results between galaxies.

Patterns of amino acid conservation in human and animal immunodeficiency viruses.

PubMed

Voitenko, Olga S; Dhroso, Andi; Feldmann, Anna; Korkin, Dmitry; Kalinina, Olga V

2016-09-01

Due to their high genomic variability, RNA viruses and retroviruses present a unique opportunity for detailed study of molecular evolution. Lentiviruses, with HIV being a notable example, are one of the best studied viral groups: hundreds of thousands of sequences are available together with experimentally resolved three-dimensional structures for most viral proteins. In this work, we use these data to study specific patterns of evolution of the viral proteins, and their relationship to protein interactions and immunogenicity. We propose a method for identification of two types of surface residues clusters with abnormal conservation: extremely conserved and extremely variable clusters. We identify them on the surface of proteins from HIV and other animal immunodeficiency viruses. Both types of clusters are overrepresented on the interaction interfaces of viral proteins with other proteins, nucleic acids or low molecular-weight ligands, both in the viral particle and between the virus and its host. In the immunodeficiency viruses, the interaction interfaces are not more conserved than the corresponding proteins on an average, and we show that extremely conserved clusters coincide with protein-protein interaction hotspots, predicted as the residues with the largest energetic contribution to the interaction. Extremely variable clusters have been identified here for the first time. In the HIV-1 envelope protein gp120, they overlap with known antigenic sites. These antigenic sites also contain many residues from extremely conserved clusters, hence representing a unique interacting interface enriched both in extremely conserved and in extremely variable clusters of residues. This observation may have important implication for antiretroviral vaccine development. A Python package is available at https://bioinf.mpi-inf.mpg.de/publications/viral-ppi-pred/ voitenko@mpi-inf.mpg.de or kalinina@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Analysing and Navigating Natural Products Space for Generating Small, Diverse, But Representative Chemical Libraries.

PubMed

O'Hagan, Steve; Kell, Douglas B

2018-01-01

Armed with the digital availability of two natural products libraries, amounting to some 195 885 molecular entities, we ask the question of how we can best sample from them to maximize their "representativeness" in smaller and more usable libraries of 96, 384, 1152, and 1920 molecules. The term "representativeness" is intended to include diversity, but for numerical reasons (and the likelihood of being able to perform a QSAR) it is necessary to focus on areas of chemical space that are more highly populated. Encoding chemical structures as fingerprints using the RDKit "patterned" algorithm, we first assess the granularity of the natural products space using a simple clustering algorithm, showing that there are major regions of "denseness" but also a great many very sparsely populated areas. We then apply a "hybrid" hierarchical K-means clustering algorithm to the data to produce more statistically robust clusters from which representative and appropriate numbers of samples may be chosen. There is necessarily again a trade-off between cluster size and cluster number, but within these constraints, libraries containing 384 or 1152 molecules can be found that come from clusters that represent some 18 and 30% of the whole chemical space, with cluster sizes of, respectively, 50 and 27 or above, just about sufficient to perform a QSAR. By using the online availability of molecules via the Molport system (www.molport.com), we are also able to construct (and, for the first time, provide the contents of) a small virtual library of available molecules that provided effective coverage of the chemical space described. Consistent with this, the average molecular similarities of the contents of the libraries developed is considerably smaller than is that of the original libraries. The suggested libraries may have use in molecular or phenotypic screening, including for determining possible transporter substrates. © 2017 The Authors. Biotechnology Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

The X-ray luminosity functions of Abell clusters from the Einstein Cluster Survey

NASA Technical Reports Server (NTRS)

Burg, R.; Giacconi, R.; Forman, W.; Jones, C.

1994-01-01

We have derived the present epoch X-ray luminosity function of northern Abell clusters using luminosities from the Einstein Cluster Survey. The sample is sufficiently large that we can determine the luminosity function for each richness class separately with sufficient precision to study and compare the different luminosity functions. We find that, within each richness class, the range of X-ray luminosity is quite large and spans nearly a factor of 25. Characterizing the luminosity function for each richness class with a Schechter function, we find that the characteristic X-ray luminosity, L(sub *), scales with richness class as (L(sub *) varies as N(sub*)(exp gamma), where N(sub *) is the corrected, mean number of galaxies in a richness class, and the best-fitting exponent is gamma = 1.3 +/- 0.4. Finally, our analysis suggests that there is a lower limit to the X-ray luminosity of clusters which is determined by the integrated emission of the cluster member galaxies, and this also scales with richness class. The present sample forms a baseline for testing cosmological evolution of Abell-like clusters when an appropriate high-redshift cluster sample becomes available.

On Ion Clusters in the Interstellar Gas

NASA Technical Reports Server (NTRS)

Donn, Bertram

1960-01-01

In a recent paper V.I. Krassovsky (1958) predicts the occurrence of clusters of large numbers of atoms and molecules around ions in the interstellar gas. He then proposes a number of physicochemical processes that would be considerably enhanced by the high particle density in such clusters. In particular, he suggests that absorption by negative ions formed in the clusters would account for the interstellar extinction without any necessity for the presence of grains. Because of the important consequences that ion clusters could have, it is necessary to examine their occurrence more fully. This note re-examines the formation of ion clusters in space and shows that even ion-molecule pairs are essentially non-existent. Ion clusters have been considered by Bloom and Margenau (1952) from the same point of view as that used by Krassovsky, whose basic reference (Joffe and Semenov 1933) unfortunately is not available. A different approach has been used by Eyring, Hirschfelder, and Taylor (1936) following the methods of chemical equilibrium. Both the references cited here enable one to conclude that clustering is negligible. Therefore, the treatment of Eyring et al. is more appropriate than the method of Bloom and Margenau, which depends on the statistical equilibrium of an atmosphere in a force field.

Extended Star Formation or a Range of Stellar Rotation Velocities? The Nature of Extended Main Sequence Turnoffs in Intermediate-Age Star Clusters

NASA Astrophysics Data System (ADS)

Goudfrooij, Paul

2016-10-01

Recently, deep color-magnitude diagrams (CMDs) from HST data revealed that several massive intermediate-age star clusters in the Magellanic Clouds exhibit extended main-sequence turn-offs (eMSTOs), and in some cases also dual red clumps. This poses serious questions regarding the mechanisms responsible for the formation of massive star clusters and their well-known light-element abundance variations. The nature of eMSTOs is currently a hotly debated topic of study. Several recent studies indicate that the eMSTOs are caused by an age spread of about 100-500 Myr among cluster stars, while other studies indicate that eMSTOs can be caused by a coeval population in which the relevant stars span a range of rotation velocities. Formal evidence to (dis-)prove either scenario still remains at large, mainly because the available stellar tracks that incorporate the effects of rotation are only available for masses > 1.7 Msun whereas the stars in the known eMSTOs of intermediate-age clusters are less massive. To circumvent this issue, we identified a massive star cluster in the Large Magellanic Cloud (LMC) that has the right dynamical properties to host an eMSTO along with an age at which the effects of age spreads to CMD morphology are substantially different from those of spreads of rotation rates: the 600 Myr old cluster NGC 1831. We propose to obtain deep WFC3/UVIS imaging with filters F336W and F814W to analyze the morphologies of the MSTO and upper MS regions of NGC 1831 at high precision and compare with model predictions. This will have a lasting impact on our understanding of the eMSTO phenomenon and of star cluster formation in general.

Two Massive White Dwarfs from NGC 2323 and the Initial-Final Mass Relation for Progenitors of 4 to 6.5 M

NASA Astrophysics Data System (ADS)

Cummings, Jeffrey D.; Kalirai, Jason S.; Tremblay, P.-E.; Ramirez-Ruiz, Enrico

2016-02-01

We observed a sample of 10 white dwarf candidates in the rich open cluster NGC 2323 (M50) with the Keck Low-Resolution Imaging Spectrometer. The spectroscopy shows eight to be DA white dwarfs, with six of these having high signal-to-noise ratio appropriate for our analysis. Two of these white dwarfs are consistent with singly evolved cluster membership, and both are high mass ˜1.07 M⊙, and give equivalent progenitor masses of 4.69 M⊙. To supplement these new high-mass white dwarfs and analyze the initial-final mass relation (IFMR), we also looked at 30 white dwarfs from publicly available data that are mostly all high-mass (≳ 0.9 M⊙). These original published data exhibited significant scatter, and to test if this scatter is true or simply the result of systematics, we have uniformly analyzed the white dwarf spectra and have adopted thorough photometric techniques to derive uniform cluster parameters for their parent clusters. The resulting IFMR scatter is significantly reduced, arguing that mass-loss rates are not stochastic in nature and that within the ranges of metallicity and mass analyzed in this work mass loss is not highly sensitive to variations in metallicity. Lastly, when adopting cluster ages based on Y2 isochrones, the slope of the high-mass IFMR remains steep and consistent with that found from intermediate-mass white dwarfs, giving a linear IFMR from progenitor masses between 3 and 6.5 M⊙. In contrast, when adopting the slightly younger cluster ages based on PARSEC isochrones, the high-mass IFMR has a moderate turnover near an initial mass of 4 M⊙. Based on observations with the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA, was made possible by the generous financial support of the W.M. Keck Foundation.

ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster.

PubMed

Stocker, Gernot; Rieder, Dietmar; Trajanoski, Zlatko

2004-03-22

ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions. http://genome.tugraz.at/Software/ClusterControl

A catalogue of masses, structural parameters and velocity dispersion profiles of 112 Milky Way globular clusters

NASA Astrophysics Data System (ADS)

Baumgardt, H.; Hilker, M.

2018-05-01

We have determined masses, stellar mass functions and structural parameters of 112 Milky Way globular clusters by fitting a large set of N-body simulations to their velocity dispersion and surface density profiles. The velocity dispersion profiles were calculated based on a combination of more than 15,000 high-precision radial velocities which we derived from archival ESO/VLT and Keck spectra together with ˜20, 000 published radial velocities from the literature. Our fits also include the stellar mass functions of the globular clusters, which are available for 47 clusters in our sample, allowing us to self-consistently take the effects of mass segregation and ongoing cluster dissolution into account. We confirm the strong correlation between the global mass functions of globular clusters and their relaxation times recently found by Sollima & Baumgardt (2017). We also find a correlation of the escape velocity from the centre of a globular cluster and the fraction of first generation stars (FG) in the cluster recently derived for 57 globular clusters by Milone et al. (2017), but no correlation between the FG star fraction and the global mass function of a globular cluster. This could indicate that the ability of a globular cluster to keep the wind ejecta from the polluting star(s) is the crucial parameter determining the presence and fraction of second generation stars and not its later dynamical mass loss.

Use of keyword hierarchies to interpret gene expression patterns.

PubMed

Masys, D R; Welsh, J B; Lynn Fink, J; Gribskov, M; Klacansky, I; Corbeil, J

2001-04-01

High-density microarray technology permits the quantitative and simultaneous monitoring of thousands of genes. The interpretation challenge is to extract relevant information from this large amount of data. A growing variety of statistical analysis approaches are available to identify clusters of genes that share common expression characteristics, but provide no information regarding the biological similarities of genes within clusters. The published literature provides a potential source of information to assist in interpretation of clustering results. We describe a data mining method that uses indexing terms ('keywords') from the published literature linked to specific genes to present a view of the conceptual similarity of genes within a cluster or group of interest. The method takes advantage of the hierarchical nature of Medical Subject Headings used to index citations in the MEDLINE database, and the registry numbers applied to enzymes.

Monitoring Wetland Hydro-dynamics in the Prairie Pothole Region Using Landsat Time Series

NASA Astrophysics Data System (ADS)

Zhou, Q.; Rover, J.; Gallant, A.

2017-12-01

Wetlands provide a variety of ecosystem functions, while it is spatially and temporally dynamic. We mapped the dynamics of wetlands in the North Dakota Prairie Pothole Region using all available clear observations of Landsat sensor data from 1985 to 2014. We used a cluster analysis to group pixels exhibiting similar long-term spectral trends over seven Landsat bands, then applied the tasseled-cap transformation to evaluate the temporal characteristics of brightness, greenness, and wetness for each cluster. We tested relations between these three indices and hydrologic conditions, as represented by the Palmer Hydrological Drought Index (PHDI), using the cross-correlation analysis for each cluster performed over an eight-year moving window for the 30 years covered by the study. This temporal window size coincided with the timing of a major shift from a prolonged drought that occurred within the first eight years of the study period to wetter conditions that prevailed throughout the remaining years. The 20 cluster we produced represented a gradient from locations that continuously held water throughout the study period to locations that, at most, held water only for short periods in some years. The spatial distribution of the cluster groups reflected patterns of regional geologic and geomorphologic features. Comparisons of the PHDI to tasseled-cap wetness were the most straightforward to interpret among the results from the three indices. Wetness for most cluster groups had high positive correlations with PHDI during drought years, with the correlations reduced as the landscape entered a lengthy, wetter period; however, wetness generally remained highly and positively correlated with PHDI across all years for four cluster groups where the area exhibited two or more multi-year dry-wet cycles. These same four groups also had strong, generally negative correlations with tasseled-cap brightness. For other cluster groups, brightness often was strongly negatively correlated with the PHDI during the drought years, with the relation weakening for subsequent years of adequate or high moisture. Relations between tasseled-cap greenness and PHDI were highly variable among and within cluster groups. Results from this analysis support ongoing efforts to develop new products that characterize wetland dynamics.

Whole Genome Sequence and Phylogenetic Analysis Show Helicobacter pylori Strains from Latin America Have Followed a Unique Evolution Pathway

PubMed Central

Muñoz-Ramírez, Zilia Y.; Mendez-Tenorio, Alfonso; Kato, Ikuko; Bravo, Maria M.; Rizzato, Cosmeri; Thorell, Kaisa; Torres, Roberto; Aviles-Jimenez, Francisco; Camorlinga, Margarita; Canzian, Federico; Torres, Javier

2017-01-01

Helicobacter pylori (HP) genetics may determine its clinical outcomes. Despite high prevalence of HP infection in Latin America (LA), there have been no phylogenetic studies in the region. We aimed to understand the structure of HP populations in LA mestizo individuals, where gastric cancer incidence remains high. The genome of 107 HP strains from Mexico, Nicaragua and Colombia were analyzed with 59 publicly available worldwide genomes. To study bacterial relationship on whole genome level we propose a virtual hybridization technique using thousands of high-entropy 13 bp DNA probes to generate fingerprints. Phylogenetic virtual genome fingerprint (VGF) was compared with Multi Locus Sequence Analysis (MLST) and with phylogenetic analyses of cagPAI virulence island sequences. With MLST some Nicaraguan and Mexican strains clustered close to Africa isolates, whereas European isolates were spread without clustering and intermingled with LA isolates. VGF analysis resulted in increased resolution of populations, separating European from LA strains. Furthermore, clusters with exclusively Colombian, Mexican, or Nicaraguan strains were observed, where the Colombian cluster separated from Europe, Asia, and Africa, while Nicaraguan and Mexican clades grouped close to Africa. In addition, a mixed large LA cluster including Mexican, Colombian, Nicaraguan, Peruvian, and Salvadorian strains was observed; all LA clusters separated from the Amerind clade. With cagPAI sequence analyses LA clades clearly separated from Europe, Asia and Amerind, and Colombian strains formed a single cluster. A NeighborNet analyses suggested frequent and recent recombination events particularly among LA strains. Results suggests that in the new world, H. pylori has evolved to fit mestizo LA populations, already 500 years after the Spanish colonization. This co-adaption may account for regional variability in gastric cancer risk. PMID:28293542

UBO Detector - A cluster-based, fully automated pipeline for extracting white matter hyperintensities.

PubMed

Jiang, Jiyang; Liu, Tao; Zhu, Wanlin; Koncz, Rebecca; Liu, Hao; Lee, Teresa; Sachdev, Perminder S; Wen, Wei

2018-07-01

We present 'UBO Detector', a cluster-based, fully automated pipeline for extracting and calculating variables for regions of white matter hyperintensities (WMH) (available for download at https://cheba.unsw.edu.au/group/neuroimaging-pipeline). It takes T1-weighted and fluid attenuated inversion recovery (FLAIR) scans as input, and SPM12 and FSL functions are utilised for pre-processing. The candidate clusters are then generated by FMRIB's Automated Segmentation Tool (FAST). A supervised machine learning algorithm, k-nearest neighbor (k-NN), is applied to determine whether the candidate clusters are WMH or non-WMH. UBO Detector generates both image and text (volumes and the number of WMH clusters) outputs for whole brain, periventricular, deep, and lobar WMH, as well as WMH in arterial territories. The computation time for each brain is approximately 15 min. We validated the performance of UBO Detector by showing a) high segmentation (similarity index (SI) = 0.848) and volumetric (intraclass correlation coefficient (ICC) = 0.985) agreement between the UBO Detector-derived and manually traced WMH; b) highly correlated (r 2  > 0.9) and a steady increase of WMH volumes over time; and c) significant associations of periventricular (t = 22.591, p < 0.001) and deep (t = 14.523, p < 0.001) WMH volumes generated by UBO Detector with Fazekas rating scores. With parallel computing enabled in UBO Detector, the processing can take advantage of multi-core CPU's that are commonly available on workstations. In conclusion, UBO Detector is a reliable, efficient and fully automated WMH segmentation pipeline. Copyright © 2018 Elsevier Inc. All rights reserved.

Outcome-Driven Cluster Analysis with Application to Microarray Data.

PubMed

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

2015-01-01

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

Comparison of the response to phosphorus deficiency in two lupin species, Lupinus albus and L. angustifolius, with contrasting root morphology.

PubMed

Funayama-Noguchi, Sachiko; Noguchi, Ko; Terashima, Ichiro

2015-03-01

White lupin (Lupinus albus) produces cluster roots, an adaptation to low soil phosphorus (P). Cluster roots exude large levels of P-solubilizing compounds such as citrate and malate. In contrast, narrow leaf lupin (L. angustifolius) is closely related to L. albus, but does not produce cluster roots. To examine the different strategies for P acquisition, we compared the growth, biomass allocation, respiratory properties and construction cost between L. albus and L. angustifolius under P-deficient conditions. Both Lupinus species were grown in hydroponic culture with 1 or 100 μM P. Under the P-deficient regime, L. albus produced cluster roots with little change in biomass allocation, while L. angustifolius significantly increased biomass allocation to roots. The rate of cyanide-resistant SHAM (salicylhydroxamic acid)-sensitive respiration was high in cluster roots and very low in roots of L. angustifolius. These results suggest a low alternative oxidase (AOX) activity in L. angustifolius roots, and thus, ATP would be produced efficiently in L. angustifolius roots. The construction cost was highest in cluster roots and lowest in L. angustifolius roots. This study shows that under P deficiency, L. albus produces high-cost cluster roots to increase the P availability, while L. angustifolius produces large quantities of low-cost roots to enhance P uptake. © 2014 John Wiley & Sons Ltd.

Certification of Completion of Level-2 Milestone 464: Complete Phase 1 Integration of Site-Wide Global Parallel File System (SWGPFS)

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

Heidelberg, S T; Fitzgerald, K J; Richmond, G H

2006-01-24

There has been substantial development of the Lustre parallel filesystem prior to the configuration described below for this milestone. The initial Lustre filesystems that were deployed were directly connected to the cluster interconnect, i.e. Quadrics Elan3. That is, the clients (OSSes) and Meta-data Servers (MDS) were all directly connected to the cluster's internal high speed interconnect. This configuration serves a single cluster very well, but does not provide sharing of the filesystem among clusters. LLNL funded the development of high-efficiency ''portals router'' code by CFS (the company that develops Lustre) to enable us to move the Lustre servers to amore » GigE-connected network configuration, thus making it possible to connect to the servers from several clusters. With portals routing available, here is what changes: (1) another storage-only cluster is deployed to front the Lustre storage devices (these become the Lustre OSSes and MDS), (2) this ''Lustre cluster'' is attached via GigE connections to a large GigE switch/router cloud, (3) a small number of compute-cluster nodes are designated as ''gateway'' or ''portal router'' nodes, and (4) the portals router nodes are GigE-connected to the switch/router cloud. The Lustre configuration is then changed to reflect the new network paths. A typical example of this is a compute cluster and a related visualization cluster: the compute cluster produces the data (writes it to the Lustre filesystem), and the visualization cluster consumes some of the data (reads it from the Lustre filesystem). This process can be expanded by aggregating several collections of Lustre backend storage resources into one or more ''centralized'' Lustre filesystems, and then arranging to have several ''client'' clusters mount these centralized filesystems. The ''client clusters'' can be any combination of compute, visualization, archiving, or other types of cluster. This milestone demonstrates the operation and performance of a scaled-down version of such a large, centralized, shared Lustre filesystem concept.« less

Cluster optical coding: from biochips to counterfeit security

NASA Astrophysics Data System (ADS)

Haglmueller, Jakob; Alguel, Yilmaz; Mayer, Christian; Matyushin, Viacheslav; Bauer, Georg; Pittner, Fritz; Leitner, Alfred; Aussenegg, Franz R.; Schalkhammer, Thomas G.

2004-07-01

Spatially tuned resonant nano-clusters allow high local field enhancement when exited by electromagnetic radiation. A number of phenomena had been described and subsequently applied to novel nano- and bionano-devices. Decisive for these types of devices and sensors is the precise nanometric assembly, coupling the local field surrounding a cluster to allow resonance with other elements interacting with this field. In particular, the distance cluster-mirror or cluster-fluorophore gives rise to a variety of enhancement phenomena. High throughput transducers using metal cluster resonance technology are based on surface-enhancement of metal cluster light absorption (SEA). The optical property for the analytical application of metal cluster films is the so-called anomalous absorption. At a well defined nanometric distance of a cluster to a mirror the reflected electromagnetic field has the same phase at the position of the absorbing cluster as the incident fields. This feedback mechanism strongly enhances the effective cluster absorption coefficient. The system is characterised by a narrow reflection minimum. Based on this SEA-phenomenon (licensed to and further developed and optimized by NovemberAG, Germany Erlangen) a number of commercial products have been constructed. Brandsealing(R) uses the patented SEA cluster technology to produce optical codings. Cluster SEA thin film systems show a characteristic color-flip effect and are extremely mechanically and thermally robust. This is the basis for its application as an unique security feature. The specific spectroscopic properties as e.g. narrow band multi-resonance of the cluster layers allow the authentication of the optical code which can be easily achieved with a mobile hand-held reader developed by november AG and Siemens AG. Thus, these features are machine-readable which makes them superior to comparable technologies. Cluster labels are available in two formats: as a label for tamper-proof product packaging, and as a direct label, where label and logo are permanently applied directly and unremovable to the product surface. Together with Infineon Technologies and HUECK FOLIEN, the SEA technology is currently developed as a direct label for e.g. SmartCards.

Exploring data availability for the Environmental Quality Index to assess environmental health disparities

EPA Science Inventory

The interaction between environmental insults and human health is complex. Environmental exposures tend to cluster, with disamenities (e.g., landfills, industrial plants) often located in high-minority and largely poor neighborhoods, while wealthier neighborhoods contain amenitie...

Creating an Overall Environmental Quality Index: Assessing Available Data

EPA Science Inventory

Background and Objectives: The interaction between environmental insults and human health is a complex process. Environmental exposures tend to cluster and disamenities such as landfills or industrial plants are often located in neighborhoods with high a percentage of minority a...

Globular cluster chemistry in fast-rotating dwarf stars belonging to intermediate-age open clusters

NASA Astrophysics Data System (ADS)

Pancino, Elena

2018-06-01

The peculiar chemistry observed in multiple populations of Galactic globular clusters is not generally found in other systems such as dwarf galaxies and open clusters, and no model can currently fully explain it. Exploring the boundaries of the multiple-population phenomenon and the variation of its extent in the space of cluster mass, age, metallicity, and compactness has proven to be a fruitful line of investigation. In the framework of a larger project to search for multiple populations in open clusters that is based on literature and survey data, I found peculiar chemical abundance patterns in a sample of intermediate-age open clusters with publicly available data. More specifically, fast-rotating dwarf stars (v sin i ≥ 50 km s-1) that belong to four clusters (Pleiades, Ursa Major, Come Berenices, and Hyades) display a bimodality in either [Na/Fe] or [O/Fe], or both, with the low-Na and high-O peak more populated than the high-Na and low-O peak. Additionally, two clusters show a Na-O anti-correlation in the fast-rotating stars, and one cluster shows a large [Mg/Fe] variation in stars with high [Na/Fe], reaching the extreme Mg depletion observed in NGC 2808. Even considering that the sample sizes are small, these patterns call for attention in the light of a possible connection with the multiple population phenomenon of globular clusters. The specific chemistry observed in these fast-rotating dwarf stars is thought to be produced by a complex interplay of different diffusion and mixing mechanisms, such as rotational mixing and mass loss, which in turn are influenced by metallicity, binarity, mass, age, variability, and so on. However, with the sample in hand, it was not possible to identify which stellar parameters cause the observed Na and O bimodality and Na-O anti-correlation. This suggests that other stellar properties might be important in addition to stellar rotation. Stellar binarity might influence the rotational properties and enhance rotational mixing and mass loss of stars in a dense environment like that of clusters (especially globulars). In conclusion, rotation and binarity appear as a promising research avenue for better understanding multiple stellar populations in globular clusters; this is certainly worth exploring further.

A cluster-analytic approach towards multidimensional health-related behaviors in adolescents: the MoMo-Study

PubMed Central

2012-01-01

Background Although knowledge on single health-related behaviors and their association with health parameters is available, research on multiple health-related behaviors is needed to understand the interactions among these behaviors. The aims of the study were (a) to identify typical health-related behavior patterns in German adolescents focusing on physical activity, media use and dietary behavior; (b) to describe the socio-demographic correlates of the identified clusters and (c) to study their association with overweight. Methods Within the framework of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) and the “Motorik-Modul” (MoMo), 1,643 German adolescents (11–17 years) completed a questionnaire assessing the amount and type of weekly physical activity in sports clubs and during leisure time, weekly use of television, computer and console games and the frequency and amount of food consumption. From this data the three indices ‘physical activity’, ‘media use’ and ‘healthy nutrition’ were derived and included in a cluster analysis conducted with Ward’s Method and K-means analysis. Chi-square tests were performed to identify socio-demographic correlates of the clusters as well as their association with overweight. Results Four stable clusters representing typical health-related behavior patterns were identified: Cluster 1 (16.2%)—high scores in physical activity index and average scores in media use index and healthy nutrition index; cluster 2 (34.6%)—high healthy nutrition score and below average scores in the other two indices; cluster 3 (18.4%)—low physical activity score, low healthy nutrition score and very high media use score; cluster 4 (30.5%)—below average scores on all three indices. Boys were overrepresented in the clusters 1 and 3, and the relative number of adolescents with low socio-economic status as well as overweight was significantly higher than average in cluster 3. Conclusions Meaningful and stable clusters of health-related behavior were identified. These results confirm findings of another youth study hence supporting the assumption that these clusters represent typical behavior patterns of adolescents. These results are particularly relevant for the characterization of target groups for primary prevention of lifestyle diseases. PMID:23273134

New Galactic star clusters discovered in the VVV survey

NASA Astrophysics Data System (ADS)

Borissova, J.; Bonatto, C.; Kurtev, R.; Clarke, J. R. A.; Peñaloza, F.; Sale, S. E.; Minniti, D.; Alonso-García, J.; Artigau, E.; Barbá, R.; Bica, E.; Baume, G. L.; Catelan, M.; Chenè, A. N.; Dias, B.; Folkes, S. L.; Froebrich, D.; Geisler, D.; de Grijs, R.; Hanson, M. M.; Hempel, M.; Ivanov, V. D.; Kumar, M. S. N.; Lucas, P.; Mauro, F.; Moni Bidin, C.; Rejkuba, M.; Saito, R. K.; Tamura, M.; Toledo, I.

2011-08-01

Context. VISTA Variables in the Vía Láctea (VVV) is one of the six ESO Public Surveys operating on the new 4-m Visible and Infrared Survey Telescope for Astronomy (VISTA). VVV is scanning the Milky Way bulge and an adjacent section of the disk, where star formation activity is high. One of the principal goals of the VVV Survey is to find new star clusters of differentages. Aims: In order to trace the early epochs of star cluster formation we concentrated our search in the directions to those of known star formation regions, masers, radio, and infrared sources. Methods: The disk area covered by VVV was visually inspected using the pipeline processed and calibrated KS-band tile images for stellar overdensities. Subsequently, we examined the composite JHKS and ZJKS color images of each candidate. PSF photometry of 15 × 15 arcmin fields centered on the candidates was then performed on the Cambridge Astronomy Survey Unit reduced images. After statistical field-star decontamination, color-magnitude and color-color diagrams were constructed and analyzed. Results: We report the discovery of 96 new infrared open clusters and stellar groups. Most of the new cluster candidates are faint and compact (with small angular sizes), highly reddened, and younger than 5 Myr. For relatively well populated cluster candidates we derived their fundamental parameters such as reddening, distance, and age by fitting the solar-metallicity Padova isochrones to the color-magnitude diagrams. Based on observations gathered with VIRCAM, VISTA of the ESO as part of observing programs 172.B-2002Appendix A is available in electronic form at http://www.aanda.orgTable 1 is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/532/A131

The OGCleaner: filtering false-positive homology clusters.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Snell, Quinn; Bybee, Seth M

2017-01-01

Detecting homologous sequences in organisms is an essential step in protein structure and function prediction, gene annotation and phylogenetic tree construction. Heuristic methods are often employed for quality control of putative homology clusters. These heuristics, however, usually only apply to pairwise sequence comparison and do not examine clusters as a whole. We present the Orthology Group Cleaner (the OGCleaner), a tool designed for filtering putative orthology groups as homology or non-homology clusters by considering all sequences in a cluster. The OGCleaner relies on high-quality orthologous groups identified in OrthoDB to train machine learning algorithms that are able to distinguish between true-positive and false-positive homology groups. This package aims to improve the quality of phylogenetic tree construction especially in instances of lower-quality transcriptome assemblies. https://github.com/byucsl/ogcleaner CONTACT: sfujimoto@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Data-Driven Packet Loss Estimation for Node Healthy Sensing in Decentralized Cluster.

PubMed

Fan, Hangyu; Wang, Huandong; Li, Yong

2018-01-23

Decentralized clustering of modern information technology is widely adopted in various fields these years. One of the main reason is the features of high availability and the failure-tolerance which can prevent the entire system form broking down by a failure of a single point. Recently, toolkits such as Akka are used by the public commonly to easily build such kind of cluster. However, clusters of such kind that use Gossip as their membership managing protocol and use link failure detecting mechanism to detect link failures cannot deal with the scenario that a node stochastically drops packets and corrupts the member status of the cluster. In this paper, we formulate the problem to be evaluating the link quality and finding a max clique (NP-Complete) in the connectivity graph. We then proposed an algorithm that consists of two models driven by data from application layer to respectively solving these two problems. Through simulations with statistical data and a real-world product, we demonstrate that our algorithm has a good performance.

Applying spatial analysis tools in public health: an example using SaTScan to detect geographic targets for colorectal cancer screening interventions.

PubMed

Sherman, Recinda L; Henry, Kevin A; Tannenbaum, Stacey L; Feaster, Daniel J; Kobetz, Erin; Lee, David J

2014-03-20

Epidemiologists are gradually incorporating spatial analysis into health-related research as geocoded cases of disease become widely available and health-focused geospatial computer applications are developed. One health-focused application of spatial analysis is cluster detection. Using cluster detection to identify geographic areas with high-risk populations and then screening those populations for disease can improve cancer control. SaTScan is a free cluster-detection software application used by epidemiologists around the world to describe spatial clusters of infectious and chronic disease, as well as disease vectors and risk factors. The objectives of this article are to describe how spatial analysis can be used in cancer control to detect geographic areas in need of colorectal cancer screening intervention, identify issues commonly encountered by SaTScan users, detail how to select the appropriate methods for using SaTScan, and explain how method selection can affect results. As an example, we used various methods to detect areas in Florida where the population is at high risk for late-stage diagnosis of colorectal cancer. We found that much of our analysis was underpowered and that no single method detected all clusters of statistical or public health significance. However, all methods detected 1 area as high risk; this area is potentially a priority area for a screening intervention. Cluster detection can be incorporated into routine public health operations, but the challenge is to identify areas in which the burden of disease can be alleviated through public health intervention. Reliance on SaTScan's default settings does not always produce pertinent results.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Ecological Consistency of SSU rRNA-Based Operational Taxonomic Units at a Global Scale

PubMed Central

Schmidt, Thomas S. B.; Matias Rodrigues, João F.; von Mering, Christian

2014-01-01

Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate ‘true’ microbial taxa. Here, we explore the ecological consistency of OTUs – based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale. PMID:24763141

Pressure distribution of the high-redshift cluster of galaxies CL J1226.9+3332 with NIKA

NASA Astrophysics Data System (ADS)

Adam, R.; Comis, B.; Macías-Pérez, J.-F.; Adane, A.; Ade, P.; André, P.; Beelen, A.; Belier, B.; Benoît, A.; Bideaud, A.; Billot, N.; Blanquer, G.; Bourrion, O.; Calvo, M.; Catalano, A.; Coiffard, G.; Cruciani, A.; D'Addabbo, A.; Désert, F.-X.; Doyle, S.; Goupy, J.; Kramer, C.; Leclercq, S.; Martino, J.; Mauskopf, P.; Mayet, F.; Monfardini, A.; Pajot, F.; Pascale, E.; Perotto, L.; Pointecouteau, E.; Ponthieu, N.; Revéret, V.; Ritacco, A.; Rodriguez, L.; Savini, G.; Schuster, K.; Sievers, A.; Tucker, C.; Zylka, R.

2015-04-01

The thermal Sunyaev-Zel'dovich (tSZ) effect is expected to provide a low scatter mass proxy for galaxy clusters since it is directly proportional to the cluster thermal energy. The tSZ observations have proven to be a powerful tool for detecting and studying them, but high angular resolution observations are now needed to push their investigation to a higher redshift. In this paper, we report high angular (<20 arcsec) resolution tSZ observations of the high-redshift cluster CL J1226.9+3332 (z = 0.89). It was imaged at 150 and 260 GHz using the NIKA camera at the IRAM 30-m telescope. The 150 GHz map shows that CL J1226.9+3332 is morphologically relaxed on large scales with evidence of a disturbed core, while the 260 GHz channel is used mostly to identify point source contamination. NIKA data are combined with those of Planck and X-ray from Chandra to infer the cluster's radial pressure, density, temperature, and entropy distributions. The total mass profile of the cluster is derived, and we find M500 = 5.96+1.02-0.79 × 1014M⊙ within the radius R500 = 930+50-43 kpc, at a 68% confidence level. (R500 is the radius within which the average density is 500 times the critical density at the cluster's redshift.) NIKA is the prototype camera of NIKA2, a KIDs (kinetic inductance detectors) based instrument to be installed at the end of 2015. This work is, therefore, part of a pilot study aiming at optimizing tSZ NIKA2 large programs. The FITS file of the published maps is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/576/A12

High Intensity Femtosecond XUV Pulse Interactions with Atomic Clusters: Final Report

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

Ditmire, Todd

We propose to expand our recent studies on the interactions of intense extreme ultraviolet (XUV) femtosecond pulses with atomic and molecular clusters. The work described follows directly from work performed under BES support for the past grant period. During this period we upgraded the THOR laser at UT Austin by replacing the regenerative amplifier with optical parametric amplification (OPA) using BBO crystals. This increased the contrast of the laser, the total laser energy to ~1.2 J , and decreased the pulse width to below 30 fs. We built a new all reflective XUV harmonic beam line into expanded lab space. This enabled an increase influence by a factor ofmore » 25 and an increase in the intensity by a factor of 50. The goal of the program proposed in this renewal is to extend this class of experiments to available higher XUV intensity and a greater range of wavelengths. In particular we plan to perform experiments to confirm our hypothesis about the origin of the high charge states in these exploding clusters, an effect which we ascribe to plasma continuum lowering (ionization potential depression) in a cluster nano-­plasma. To do this we will perform experiments in which XUV pulses of carefully chosen wavelength irradiate clusters composed of only low-Z atoms and clusters with a mixture of this low-­Z atom with higher Z atoms. The latter clusters will exhibit higher electron densities and will serve to lower the ionization potential further than in the clusters composed only of low Z atoms. This should have a significant effect on the charge states produced in the exploding cluster. We will also explore the transition of explosions in these XUV irradiated clusters from hydrodynamic expansion to Coulomb explosion. The work proposed here will explore clusters of a wider range of constituents, including clusters from solids. Experiments on clusters from solids will be enabled by development we performed during the past grant period in which we constructed and tested a cluster generator based on the Laser Ablation of Microparticles (LAM) method.« less

Evidence for Cluster Evolution from an Improved Measurement of the Velocity Dispersion and Morphological Fraction of Cluster 1324+3011 at z=0.76

NASA Astrophysics Data System (ADS)

Lubin, Lori M.; Oke, J. B.; Postman, Marc

2002-10-01

We have carried out additional spectroscopic observations in the field of cluster Cl 1324+3011 at z=0.76. Combined with the spectroscopy recently presented by Postman, Lubin, & Oke, we now have spectroscopically confirmed 47 cluster members. With this significant number of redshifts, we measure accurately the cluster velocity dispersion to be 1016+126-93 km s-1. The distribution of velocity offsets is consistent with a Gaussian, indicating no substantial velocity substructure. As previously noted for other optically selected clusters at redshifts of z>~0.5, a comparison between the X-ray luminosity (LX) and the velocity dispersion (σ) of Cl 1324+3011 implies that this cluster is underluminous in X-rays by a factor of ~3-40 when compared with the LX-σ relation for local and moderate-redshift clusters. We also examine the morphologies of those cluster members that have available high angular resolution imaging with the Hubble Space Telescope (HST). There are 22 spectroscopically confirmed cluster members within the HST field of view. Twelve of these are visually classified as early-type (elliptical or S0) galaxies, implying an early-type fraction of 0.55+0.17-0.14 in this cluster. This fraction is a factor of ~1.5 lower than that observed in nearby rich clusters. Confirming previous cluster studies, the results for cluster Cl 1324+3011, combined with morphological studies of other massive clusters at redshifts of 0<=z<~1, suggest that the galaxy population in massive clusters is strongly evolving with redshift. This evolution implies that early-type galaxies are forming out of the excess of late-type (spiral, irregular, and peculiar) galaxies over the ~7 Gyr timescale.

Parenting styles, feeding styles and food-related parenting practices in relation to toddlers’ eating styles: A cluster-analytic approach

PubMed Central

Sleddens, Ester F. C.

2017-01-01

Introduction Toddlers’ eating behaviors are influenced by the way parents interact with their children. The objective of this study was to explore how five major constructs of general parenting behavior cluster in parents of toddlers. These parenting clusters were further explored to see how they differed in the use of feeding strategies (i.e. feeding styles and food parenting practices) and by reported child eating styles. Methods An online survey with 1005 mothers/caregivers (legal guardians) with at least one child between 12 and 36 months old was conducted in the United States in 2012, assessing general parenting behavior, feeding style, food parenting practices and the child eating styles. Results A three cluster solution of parenting style was found and clusters were labelled as overprotective/supervising, authoritarian, and authoritative. The clusters differed in terms of general parenting behaviors. Both overprotective and authoritative clusters showed high scores on structure, behavioral control, and nurturance. The overprotective cluster scored high on overprotection. The ‘authoritarian’ cluster showed lowest levels of nurturance, structure and behavioral control. Overprotective and authoritative parents showed very similar patterns in the use of food parenting practices, e.g. monitoring food intake, modeling, and promoting healthy food intake and availability at home. Overprotective parents also reported higher use of pressure to eat and involvement. Authoritarian parents reported high use of giving the child control over their food behaviors, emotion regulation, using food as a reward, and controlling food intake for weight control. Children’s eating styles did not largely vary by parenting cluster. Conclusion This study showed that a relatively new parenting style of overprotection is relevant for children’s eating behaviors. Overprotective parents reported food parenting practices that are known to be beneficial for children’s food intake, such as modelling healthy food intake, as well as more unfavorable practices such as pressure. Longitudinal data on parenting practices and their relation to healthy eating in children is needed to inform communication and interventions for parents, reinforcing key feeding strategies which have positive effects on child eating behaviors and addressing parenting styles that have unintended negative effects. PMID:28542555

Parenting styles, feeding styles and food-related parenting practices in relation to toddlers' eating styles: A cluster-analytic approach.

PubMed

van der Horst, Klazine; Sleddens, Ester F C

2017-01-01

Toddlers' eating behaviors are influenced by the way parents interact with their children. The objective of this study was to explore how five major constructs of general parenting behavior cluster in parents of toddlers. These parenting clusters were further explored to see how they differed in the use of feeding strategies (i.e. feeding styles and food parenting practices) and by reported child eating styles. An online survey with 1005 mothers/caregivers (legal guardians) with at least one child between 12 and 36 months old was conducted in the United States in 2012, assessing general parenting behavior, feeding style, food parenting practices and the child eating styles. A three cluster solution of parenting style was found and clusters were labelled as overprotective/supervising, authoritarian, and authoritative. The clusters differed in terms of general parenting behaviors. Both overprotective and authoritative clusters showed high scores on structure, behavioral control, and nurturance. The overprotective cluster scored high on overprotection. The 'authoritarian' cluster showed lowest levels of nurturance, structure and behavioral control. Overprotective and authoritative parents showed very similar patterns in the use of food parenting practices, e.g. monitoring food intake, modeling, and promoting healthy food intake and availability at home. Overprotective parents also reported higher use of pressure to eat and involvement. Authoritarian parents reported high use of giving the child control over their food behaviors, emotion regulation, using food as a reward, and controlling food intake for weight control. Children's eating styles did not largely vary by parenting cluster. This study showed that a relatively new parenting style of overprotection is relevant for children's eating behaviors. Overprotective parents reported food parenting practices that are known to be beneficial for children's food intake, such as modelling healthy food intake, as well as more unfavorable practices such as pressure. Longitudinal data on parenting practices and their relation to healthy eating in children is needed to inform communication and interventions for parents, reinforcing key feeding strategies which have positive effects on child eating behaviors and addressing parenting styles that have unintended negative effects.

Galaxy evolution in merging clusters: The passive core of the "Train Wreck" cluster of galaxies, A 520

NASA Astrophysics Data System (ADS)

Deshev, Boris; Finoguenov, Alexis; Verdugo, Miguel; Ziegler, Bodo; Park, Changbom; Hwang, Ho Seong; Haines, Christopher; Kamphuis, Peter; Tamm, Antti; Einasto, Maret; Hwang, Narae; Park, Byeong-Gon

2017-11-01

Aims: The mergers of galaxy clusters are the most energetic events in the Universe after the Big Bang. With the increased availability of multi-object spectroscopy and X-ray data, an ever increasing fraction of local clusters are recognised as exhibiting signs of recent or past merging events on various scales. Our goal is to probe how these mergers affect the evolution and content of their member galaxies. We specifically aim to answer the following questions: is the quenching of star formation in merging clusters enhanced when compared with relaxed clusters? Is the quenching preceded by a (short-lived) burst of star formation? Methods: We obtained optical spectroscopy of >400 galaxies in the field of the merging cluster Abell 520. We combine these observations with archival data to obtain a comprehensive picture of the state of star formation in the members of this merging cluster. Finally, we compare these observations with a control sample of ten non-merging clusters at the same redshift from The Arizona Cluster Redshift Survey (ACReS). We split the member galaxies into passive, star forming or recently quenched depending on their spectra. Results: The core of the merger shows a decreased fraction of star forming galaxies compared to clusters in the non-merging sample. This region, dominated by passive galaxies, is extended along the axis of the merger. We find evidence of rapid quenching of the galaxies during the core passage with no signs of a star burst on the time scales of the merger (≲0.4 Gyr). Additionally, we report the tentative discovery of an infalling group along the main filament feeding the merger, currently at 2.5 Mpc from the merger centre. This group contains a high fraction of star forming galaxies as well as approximately two thirds of all the recently quenched galaxies in our survey. The reduced spectra are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/607/A131

A dynamical study of Galactic globular clusters under different relaxation conditions

NASA Astrophysics Data System (ADS)

Zocchi, A.; Bertin, G.; Varri, A. L.

2012-03-01

Aims: We perform a systematic combined photometric and kinematic analysis of a sample of globular clusters under different relaxation conditions, based on their core relaxation time (as listed in available catalogs), by means of two well-known families of spherical stellar dynamical models. Systems characterized by shorter relaxation time scales are expected to be better described by isotropic King models, while less relaxed systems might be interpreted by means of non-truncated, radially-biased anisotropic f(ν) models, originally designed to represent stellar systems produced by a violent relaxation formation process and applied here for the first time to the study of globular clusters. Methods: The comparison between dynamical models and observations is performed by fitting simultaneously surface brightness and velocity dispersion profiles. For each globular cluster, the best-fit model in each family is identified, along with a full error analysis on the relevant parameters. Detailed structural properties and mass-to-light ratios are also explicitly derived. Results: We find that King models usually offer a good representation of the observed photometric profiles, but often lead to less satisfactory fits to the kinematic profiles, independently of the relaxation condition of the systems. For some less relaxed clusters, f(ν) models provide a good description of both observed profiles. Some derived structural characteristics, such as the total mass or the half-mass radius, turn out to be significantly model-dependent. The analysis confirms that, to answer some important dynamical questions that bear on the formation and evolution of globular clusters, it would be highly desirable to acquire larger numbers of accurate kinematic data-points, well distributed over the cluster field. Appendices are available in electronic form at http://www.aanda.org

An alternative validation strategy for the Planck cluster catalogue and y-distortion maps

NASA Astrophysics Data System (ADS)

Khatri, Rishi

2016-07-01

We present an all-sky map of the y-type distortion calculated from the full mission Planck High Frequency Instrument (HFI) data using the recently proposed approach to component separation, which is based on parametric model fitting and model selection. This simple model-selection approach enables us to distinguish between carbon monoxide (CO) line emission and y-type distortion, something that is not possible using the internal linear combination based methods. We create a mask to cover the regions of significant CO emission relying on the information in the χ2 map that was obtained when fitting for the y-distortion and CO emission to the lowest four HFI channels. We revisit the second Planck cluster catalogue and try to quantify the quality of the cluster candidates in an approach that is similar in spirit to Aghanim et al. (2015, A&A, 580, A138). We find that at least 93% of the clusters in the cosmology sample are free of CO contamination. We also find that 59% of unconfirmed candidates may have significant contamination from molecular clouds. We agree with Planck Collaboration XXVII (2016, A&A, in press) on the worst offenders. We suggest an alternative validation strategy of measuring and subtracting the CO emission from the Planck cluster candidates using radio telescopes, thus improving the reliability of the catalogue. Our CO mask and annotations to the Planck cluster catalogue, identifying cluster candidates with possible CO contamination, are made publicly available. The full Tables 1-3 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/592/A48

Study on the coloration response of a radiochromic film to MeV cluster ion beams

NASA Astrophysics Data System (ADS)

Yuri, Yosuke; Narumi, Kazumasa; Chiba, Atsuya; Hirano, Yoshimi; Saitoh, Yuichi

2017-11-01

A radiochromic film, Gafchromic HD-V2, is applied to a possible method of measuring a two-dimensional (2D) spatial profile of MeV cluster ion beams. The coloration responses of the HD-V2 film to MeV carbon and gold cluster ion beams are experimentally investigated since some cluster effect may appear. The degree of the film coloration is quantified as a change in optical density (OD) by reading the films with an image scanner for high-resolution measurement of the 2D beam profile. The OD response of HD-V2 is characterized as a function of the ion and atom fluence for comparison. The dependences of the OD response on the cluster size, kinetic energy, and ion species are discussed. It is found that the sensitivity of the OD change is reduced when the cluster size is large. The beam profile of MeV cluster ion beams delivered from the tandem accelerator in TIARA is characterized from the measurement result using HD-V2 films. The present results show that the use of the Gafchromic HD-V2 film is suitable for the detail beam profile measurement of MeV cluster ions, especially C60 ions, whose available intensity is rather low in comparison with that of monatomic ion beams.

antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

PubMed Central

Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko

2015-01-01

Abstract Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. PMID:25948579

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

2008-07-01

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

Model selection for clustering of pharmacokinetic responses.

PubMed

Guerra, Rui P; Carvalho, Alexandra M; Mateus, Paulo

2018-08-01

Pharmacokinetics comprises the study of drug absorption, distribution, metabolism and excretion over time. Clinical pharmacokinetics, focusing on therapeutic management, offers important insights towards personalised medicine through the study of efficacy and toxicity of drug therapies. This study is hampered by subject's high variability in drug blood concentration, when starting a therapy with the same drug dosage. Clustering of pharmacokinetics responses has been addressed recently as a way to stratify subjects and provide different drug doses for each stratum. This clustering method, however, is not able to automatically determine the correct number of clusters, using an user-defined parameter for collapsing clusters that are closer than a given heuristic threshold. We aim to use information-theoretical approaches to address parameter-free model selection. We propose two model selection criteria for clustering pharmacokinetics responses, founded on the Minimum Description Length and on the Normalised Maximum Likelihood. Experimental results show the ability of model selection schemes to unveil the correct number of clusters underlying the mixture of pharmacokinetics responses. In this work we were able to devise two model selection criteria to determine the number of clusters in a mixture of pharmacokinetics curves, advancing over previous works. A cost-efficient parallel implementation in Java of the proposed method is publicly available for the community. Copyright © 2018 Elsevier B.V. All rights reserved.

Mid-infrared Integrated-light Photometry Of LMC Star Clusters

NASA Astrophysics Data System (ADS)

Pessev, Peter; Goudfrooij, P.; Puzia, T.; Chandar, R.

2008-03-01

Massive star clusters (Galactic Globular Clusters and Populous Clusters in the Magellanic Clouds) are the best available approximation of Simple Stellar Populations (SSPs). Since the stellar populations in these nearby objects are studied in details, they provide fundamental age/metallicity templates for interpretation of the galaxy properties, testing and calibration of the SSP Models. Magellanic Cloud clusters are particularly important since they populate a region of the age/metallicity parameter space that is not easily accessible in our Galaxy. We present the first Mid-IR integrated-light measurements for six LMC clusters based on our Spitzer IRAC imaging program. Since we are targeting a specific group of intermediate-age clusters, our imaging goes deeper compared to SAGE-LMC survey data. We present a literature compilation of clusters' properties along with multi-wavelength integrated light photometry database spanning from the optical (Johnson U band) to the Mid-IR (IRAC Channel 4). This data provides an important empirical baseline for the interpretation of galaxy colors in the Mid-IR (especially high-z objects whose integrated-light is dominated by TP-AGB stars emission). It is also a valuable tool to check the SSP model predictions in the intermediate-age regime and provides calibration data for the next generation of SSP models.

Predicting healthcare outcomes in prematurely born infants using cluster analysis.

PubMed

MacBean, Victoria; Lunt, Alan; Drysdale, Simon B; Yarzi, Muska N; Rafferty, Gerrard F; Greenough, Anne

2018-05-23

Prematurely born infants are at high risk of respiratory morbidity following neonatal unit discharge, though prediction of outcomes is challenging. We have tested the hypothesis that cluster analysis would identify discrete groups of prematurely born infants with differing respiratory outcomes during infancy. A total of 168 infants (median (IQR) gestational age 33 (31-34) weeks) were recruited in the neonatal period from consecutive births in a tertiary neonatal unit. The baseline characteristics of the infants were used to classify them into hierarchical agglomerative clusters. Rates of viral lower respiratory tract infections (LRTIs) were recorded for 151 infants in the first year after birth. Infants could be classified according to birth weight and duration of neonatal invasive mechanical ventilation (MV) into three clusters. Cluster one (MV ≤5 days) had few LRTIs. Clusters two and three (both MV ≥6 days, but BW ≥or <882 g respectively), had significantly higher LRTI rates. Cluster two had a higher proportion of infants experiencing respiratory syncytial virus LRTIs (P = 0.01) and cluster three a higher proportion of rhinovirus LRTIs (P < 0.001) CONCLUSIONS: Readily available clinical data allowed classification of prematurely born infants into one of three distinct groups with differing subsequent respiratory morbidity in infancy. © 2018 Wiley Periodicals, Inc.

Open source clustering software.

PubMed

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

2004-06-12

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

A cluster of measles linked to an imported case, Finland, 2017.

PubMed

Seppälä, Elina; Zöldi, Viktor; Vuorinen, Sakari; Murtopuro, Satu; Elonsalo, Ulpu; van Beek, Janko; Haveri, Anu; Kontio, Mia; Savolainen-Kopra, Carita; Puumalainen, Taneli; Sane, Jussi

2017-08-17

One imported and five secondary cases of measles were detected in Finland between June and August 2017. The measles sequences available for five laboratory-confirmed cases were identical and belonged to serotype D8. The large number of potentially exposed Finnish and foreign individuals called for close cooperation of national and international public health authorities and other stakeholders. Raising awareness among healthcare providers and ensuring universally high vaccination coverage is crucial to prevent future clusters and outbreaks. This article is copyright of The Authors, 2017.

Genomic analysis of coxsackieviruses A1, A19, A22, enteroviruses 113 and 104: viruses representing two clades with distinct tropism within enterovirus C

PubMed Central

Haq, Saddef; Sameroff, Stephen; Howie, Stephen R. C.; Lipkin, W. Ian

2013-01-01

Coxsackieviruses (CV) A1, CV-A19 and CV-A22 have historically comprised a distinct phylogenetic clade within Enterovirus (EV) C. Several novel serotypes that are genetically similar to these three viruses have been recently discovered and characterized. Here, we report the coding sequence analysis of two genotypes of a previously uncharacterized serotype EV-C113 from Bangladesh and demonstrate that it is most similar to CV-A22 and EV-C116 within the capsid region. We sequenced novel genotypes of CV-A1, CV-A19 and CV-A22 from Bangladesh and observed a high rate of recombination within this group. We also report genomic analysis of the rarely reported EV-C104 circulating in the Gambia in 2009. All available EV-C104 sequences displayed a high degree of similarity within the structural genes but formed two clusters within the non-structural genes. One cluster included the recently reported EV-C117, suggesting an ancestral recombination between these two serotypes. Phylogenetic analysis of all available complete genome sequences indicated the existence of two subgroups within this distinct Enterovirus C clade: one has been exclusively recovered from gastrointestinal samples, while the other cluster has been implicated in respiratory disease. PMID:23761409

Organic carbon and nitrogen availability determine bacterial community composition in paddy fields of the Indo-Gangetic plain.

PubMed

Kumar, Arvind; Rai, Lal Chand

2017-07-01

Soil quality is an important factor and maintained by inhabited microorganisms. Soil physicochemical characteristics determine indigenous microbial population and rice provides food security to major population of the world. Therefore, this study aimed to assess the impact of physicochemical variables on bacterial community composition and diversity in conventional paddy fields which could reflect a real picture of the bacterial communities operating in the paddy agro-ecosystem. To fulfill the objective; soil physicochemical characterization, bacterial community composition and diversity analysis was carried out using culture-independent PCR-DGGE method from twenty soils distributed across eight districts. Bacterial communities were grouped into three clusters based on UPGMA cluster analysis of DGGE banding pattern. The linkage of measured physicochemical variables with bacterial community composition was analyzed by canonical correspondence analysis (CCA). CCA ordination biplot results were similar to UPGMA cluster analysis. High levels of species-environment correlations (0.989 and 0.959) were observed and the largest proportion of species data variability was explained by total organic carbon (TOC), available nitrogen, total nitrogen and pH. Thus, results suggest that TOC and nitrogen are key regulators of bacterial community composition in the conventional paddy fields. Further, high diversity indices and evenness values demonstrated heterogeneity and co-abundance of the bacterial communities.

Beating the tyranny of scale with a private cloud configured for Big Data

NASA Astrophysics Data System (ADS)

Lawrence, Bryan; Bennett, Victoria; Churchill, Jonathan; Juckes, Martin; Kershaw, Philip; Pepler, Sam; Pritchard, Matt; Stephens, Ag

2015-04-01

The Joint Analysis System, JASMIN, consists of a five significant hardware components: a batch computing cluster, a hypervisor cluster, bulk disk storage, high performance disk storage, and access to a tape robot. Each of the computing clusters consists of a heterogeneous set of servers, supporting a range of possible data analysis tasks - and a unique network environment makes it relatively trivial to migrate servers between the two clusters. The high performance disk storage will include the world's largest (publicly visible) deployment of the Panasas parallel disk system. Initially deployed in April 2012, JASMIN has already undergone two major upgrades, culminating in a system which by April 2015, will have in excess of 16 PB of disk and 4000 cores. Layered on the basic hardware are a range of services, ranging from managed services, such as the curated archives of the Centre for Environmental Data Archival or the data analysis environment for the National Centres for Atmospheric Science and Earth Observation, to a generic Infrastructure as a Service (IaaS) offering for the UK environmental science community. Here we present examples of some of the big data workloads being supported in this environment - ranging from data management tasks, such as checksumming 3 PB of data held in over one hundred million files, to science tasks, such as re-processing satellite observations with new algorithms, or calculating new diagnostics on petascale climate simulation outputs. We will demonstrate how the provision of a cloud environment closely coupled to a batch computing environment, all sharing the same high performance disk system allows massively parallel processing without the necessity to shuffle data excessively - even as it supports many different virtual communities, each with guaranteed performance. We will discuss the advantages of having a heterogeneous range of servers with available memory from tens of GB at the low end to (currently) two TB at the high end. There are some limitations of the JASMIN environment, the high performance disk environment is not fully available in the IaaS environment, and a planned ability to burst compute heavy jobs into the public cloud is not yet fully available. There are load balancing and performance issues that need to be understood. We will conclude with projections for future usage, and our plans to meet those requirements.

Structure and substructure analysis of DAFT/FADA galaxy clusters in the [0.4-0.9] redshift range

NASA Astrophysics Data System (ADS)

Guennou, L.; Adami, C.; Durret, F.; Lima Neto, G. B.; Ulmer, M. P.; Clowe, D.; LeBrun, V.; Martinet, N.; Allam, S.; Annis, J.; Basa, S.; Benoist, C.; Biviano, A.; Cappi, A.; Cypriano, E. S.; Gavazzi, R.; Halliday, C.; Ilbert, O.; Jullo, E.; Just, D.; Limousin, M.; Márquez, I.; Mazure, A.; Murphy, K. J.; Plana, H.; Rostagni, F.; Russeil, D.; Schirmer, M.; Slezak, E.; Tucker, D.; Zaritsky, D.; Ziegler, B.

2014-01-01

Context. The DAFT/FADA survey is based on the study of ~90 rich (masses found in the literature >2 × 1014 M⊙) and moderately distant clusters (redshifts 0.4 < z < 0.9), all with HST imaging data available. This survey has two main objectives: to constrain dark energy (DE) using weak lensing tomography on galaxy clusters and to build a database (deep multi-band imaging allowing photometric redshift estimates, spectroscopic data, X-ray data) of rich distant clusters to study their properties. Aims: We analyse the structures of all the clusters in the DAFT/FADA survey for which XMM-Newton and/or a sufficient number of galaxy redshifts in the cluster range are available, with the aim of detecting substructures and evidence for merging events. These properties are discussed in the framework of standard cold dark matter (ΛCDM) cosmology. Methods: In X-rays, we analysed the XMM-Newton data available, fit a β-model, and subtracted it to identify residuals. We used Chandra data, when available, to identify point sources. In the optical, we applied a Serna & Gerbal (SG) analysis to clusters with at least 15 spectroscopic galaxy redshifts available in the cluster range. We discuss the substructure detection efficiencies of both methods. Results: XMM-Newton data were available for 32 clusters, for which we derive the X-ray luminosity and a global X-ray temperature for 25 of them. For 23 clusters we were able to fit the X-ray emissivity with a β-model and subtract it to detect substructures in the X-ray gas. A dynamical analysis based on the SG method was applied to the clusters having at least 15 spectroscopic galaxy redshifts in the cluster range: 18 X-ray clusters and 11 clusters with no X-ray data. The choice of a minimum number of 15 redshifts implies that only major substructures will be detected. Ten substructures were detected both in X-rays and by the SG method. Most of the substructures detected both in X-rays and with the SG method are probably at their first cluster pericentre approach and are relatively recent infalls. We also find hints of a decreasing X-ray gas density profile core radius with redshift. Conclusions: The percentage of mass included in substructures was found to be roughly constant with redshift values of 5-15%, in agreement both with the general CDM framework and with the results of numerical simulations. Galaxies in substructures show the same general behaviour as regular cluster galaxies; however, in substructures, there is a deficiency of both late type and old stellar population galaxies. Late type galaxies with recent bursts of star formation seem to be missing in the substructures close to the bottom of the host cluster potential well. However, our sample would need to be increased to allow a more robust analysis. Tables 1, 2, 4 and Appendices A-C are available in electronic form at http://www.aanda.org

Characteristics of HIV-infected U.S. Army soldiers linked in molecular transmission clusters, 2001-2012

PubMed Central

Jagodzinski, Linda L.; Liu, Ying; Pham, Peter T.; Kijak, Gustavo H.; Tovanabutra, Sodsai; McCutchan, Francine E.; Scoville, Stephanie L.; Cersovsky, Steven B.; Michael, Nelson L.; Scott, Paul T.; Peel, Sheila A.

2017-01-01

Objective Recent surveillance data suggests the United States (U.S.) Army HIV epidemic is concentrated among men who have sex with men. To identify potential targets for HIV prevention strategies, the relationship between demographic and clinical factors and membership within transmission clusters based on baseline pol sequences of HIV-infected Soldiers from 2001 through 2012 were analyzed. Methods We conducted a retrospective analysis of baseline partial pol sequences, demographic and clinical characteristics available for all Soldiers in active service and newly-diagnosed with HIV-1 infection from January 1, 2001 through December 31, 2012. HIV-1 subtype designations and transmission clusters were identified from phylogenetic analysis of sequences. Univariate and multivariate logistic regression models were used to evaluate and adjust for the association between characteristics and cluster membership. Results Among 518 of 995 HIV-infected Soldiers with available partial pol sequences, 29% were members of a transmission cluster. Assignment to a southern U.S. region at diagnosis and year of diagnosis were independently associated with cluster membership after adjustment for other significant characteristics (p<0.10) of age, race, year of diagnosis, region of duty assignment, sexually transmitted infections, last negative HIV test, antiretroviral therapy, and transmitted drug resistance. Subtyping of the pol fragment indicated HIV-1 subtype B infection predominated (94%) among HIV-infected Soldiers. Conclusion These findings identify areas to explore as HIV prevention targets in the U.S. Army. An increased frequency of current force testing may be justified, especially among Soldiers assigned to duty in installations with high local HIV prevalence such as southern U.S. states. PMID:28759645

Universal dynamical properties preclude standard clustering in a large class of biochemical data.

PubMed

Gomez, Florian; Stoop, Ralph L; Stoop, Ruedi

2014-09-01

Clustering of chemical and biochemical data based on observed features is a central cognitive step in the analysis of chemical substances, in particular in combinatorial chemistry, or of complex biochemical reaction networks. Often, for reasons unknown to the researcher, this step produces disappointing results. Once the sources of the problem are known, improved clustering methods might revitalize the statistical approach of compound and reaction search and analysis. Here, we present a generic mechanism that may be at the origin of many clustering difficulties. The variety of dynamical behaviors that can be exhibited by complex biochemical reactions on variation of the system parameters are fundamental system fingerprints. In parameter space, shrimp-like or swallow-tail structures separate parameter sets that lead to stable periodic dynamical behavior from those leading to irregular behavior. We work out the genericity of this phenomenon and demonstrate novel examples for their occurrence in realistic models of biophysics. Although we elucidate the phenomenon by considering the emergence of periodicity in dependence on system parameters in a low-dimensional parameter space, the conclusions from our simple setting are shown to continue to be valid for features in a higher-dimensional feature space, as long as the feature-generating mechanism is not too extreme and the dimension of this space is not too high compared with the amount of available data. For online versions of super-paramagnetic clustering see http://stoop.ini.uzh.ch/research/clustering. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

[Influence of immigration on tuberculosis transmission patterns in Castellón, Spain (2004-2007)].

PubMed

Gil, María; Moreno, Rosario; Marín, Margarita; Romeu, Maria Ángeles; Gomila, Bárbara; González, Francisco

2011-01-01

This study aimed to identify tuberculosis transmission patterns in Castellón in a period of major demographic changes. A prospective study of patients with positive culture in the province of Castellon over a 4-year period (2004-2007) was carried out. Cases were described by year and nationality and were compared with those reported to the Department of Public Health. We studied the population with available molecular patterns, identified through restriction fragment length polymorphism (RFLP) and analyzed the variables from patient clusters, based on data collected in surveys of the Department of Health and the Laboratory Management Program. According to data from the Department of Public Health, the overall rate of tuberculosis per 100,000 inhabitants in the province of Castellón was 15.7 in 2004, 19.9 in 2005, 18.2 in 2006 and 17.5 in 2007. In our laboratory, strains were identified from 301 patients, representing 77% (301/390) of reported cases and 94% (301/321) of reported cases with a positive culture. The percentage of tuberculosis among foreigners increased with age, exceeding 50% in 2007. Molecular studies were available in 95% of patients (286); 58% were Spanish and 42% were foreigners, of whom 54% were Romanians. The cluster percentage was 40%, with 30% of mixed clusters. According to conventional contact studies, 85% of patients in clusters had been considered isolated cases. The increased rate of tuberculosis in Castellón was mainly due to the increasing number of cases among foreigners, mostly Romanians. The availability of molecular studies in all patients with a positive culture allowed us to analyze how and where tuberculosis is transmitted in our province. Forty percent of the patients were grouped into clusters; of these, mixed clusters accounted for one third, indicating the high integration of immigrants in our area. Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections

PubMed Central

Jaeger, Sébastien; Thieffry, Denis

2017-01-01

Abstract Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. PMID:28591841

Characterization of HIV Transmission in South-East Austria

PubMed Central

Kessler, Harald H.; Haas, Bernhard; Stelzl, Evelyn; Weninger, Karin; Little, Susan J.; Mehta, Sanjay R.

2016-01-01

To gain deeper insight into the epidemiology of HIV-1 transmission in South-East Austria we performed a retrospective analysis of 259 HIV-1 partial pol sequences obtained from unique individuals newly diagnosed with HIV infection in South-East Austria from 2008 through 2014. After quality filtering, putative transmission linkages were inferred when two sequences were ≤1.5% genetically different. Multiple linkages were resolved into putative transmission clusters. Further phylogenetic analyses were performed using BEAST v1.8.1. Finally, we investigated putative links between the 259 sequences from South-East Austria and all publicly available HIV polymerase sequences in the Los Alamos National Laboratory HIV sequence database. We found that 45.6% (118/259) of the sampled sequences were genetically linked with at least one other sequence from South-East Austria forming putative transmission clusters. Clustering individuals were more likely to be men who have sex with men (MSM; p<0.001), infected with subtype B (p<0.001) or subtype F (p = 0.02). Among clustered males who reported only heterosexual (HSX) sex as an HIV risk, 47% clustered closely with MSM (either as pairs or within larger MSM clusters). One hundred and seven of the 259 sequences (41.3%) from South-East Austria had at least one putative inferred linkage with sequences from a total of 69 other countries. In conclusion, analysis of HIV-1 sequences from newly diagnosed individuals residing in South-East Austria revealed a high degree of national and international clustering mainly within MSM. Interestingly, we found that a high number of heterosexual males clustered within MSM networks, suggesting either linkage between risk groups or misrepresentation of sexual risk behaviors by subjects. PMID:26967154

Characterization of HIV Transmission in South-East Austria.

PubMed

Hoenigl, Martin; Chaillon, Antoine; Kessler, Harald H; Haas, Bernhard; Stelzl, Evelyn; Weninger, Karin; Little, Susan J; Mehta, Sanjay R

2016-01-01

To gain deeper insight into the epidemiology of HIV-1 transmission in South-East Austria we performed a retrospective analysis of 259 HIV-1 partial pol sequences obtained from unique individuals newly diagnosed with HIV infection in South-East Austria from 2008 through 2014. After quality filtering, putative transmission linkages were inferred when two sequences were ≤1.5% genetically different. Multiple linkages were resolved into putative transmission clusters. Further phylogenetic analyses were performed using BEAST v1.8.1. Finally, we investigated putative links between the 259 sequences from South-East Austria and all publicly available HIV polymerase sequences in the Los Alamos National Laboratory HIV sequence database. We found that 45.6% (118/259) of the sampled sequences were genetically linked with at least one other sequence from South-East Austria forming putative transmission clusters. Clustering individuals were more likely to be men who have sex with men (MSM; p<0.001), infected with subtype B (p<0.001) or subtype F (p = 0.02). Among clustered males who reported only heterosexual (HSX) sex as an HIV risk, 47% clustered closely with MSM (either as pairs or within larger MSM clusters). One hundred and seven of the 259 sequences (41.3%) from South-East Austria had at least one putative inferred linkage with sequences from a total of 69 other countries. In conclusion, analysis of HIV-1 sequences from newly diagnosed individuals residing in South-East Austria revealed a high degree of national and international clustering mainly within MSM. Interestingly, we found that a high number of heterosexual males clustered within MSM networks, suggesting either linkage between risk groups or misrepresentation of sexual risk behaviors by subjects.

Development of an Environmental Quality Index to assess environmental public health disparities - What data are available?

EPA Science Inventory

Assessing exposure to environmental insults and human health outcomes is complex. Environmental exposures tend to cluster spatially, with disamenities (e.g., landfills, industrial plants) often located in high-minority and largely poor neighborhoods, while wealthier neighborhoods...

Cake: a bioinformatics pipeline for the integrated analysis of somatic variants in cancer genomes

PubMed Central

Rashid, Mamunur; Robles-Espinoza, Carla Daniela; Rust, Alistair G.; Adams, David J.

2013-01-01

Summary: We have developed Cake, a bioinformatics software pipeline that integrates four publicly available somatic variant-calling algorithms to identify single nucleotide variants with higher sensitivity and accuracy than any one algorithm alone. Cake can be run on a high-performance computer cluster or used as a stand-alone application. Availabilty: Cake is open-source and is available from http://cakesomatic.sourceforge.net/ Contact: da1@sanger.ac.uk Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:23803469

Cosmology with XMM galaxy clusters: the X-CLASS/GROND catalogue and photometric redshifts

NASA Astrophysics Data System (ADS)

Ridl, J.; Clerc, N.; Sadibekova, T.; Faccioli, L.; Pacaud, F.; Greiner, J.; Krühler, T.; Rau, A.; Salvato, M.; Menzel, M.-L.; Steinle, H.; Wiseman, P.; Nandra, K.; Sanders, J.

2017-06-01

The XMM Cluster Archive Super Survey (X-CLASS) is a serendipitously detected X-ray-selected sample of 845 galaxy clusters based on 2774 XMM archival observations and covering an approximately 90 deg2 spread across the high-Galactic latitude (|b| > 20°) sky. The primary goal of this survey is to produce a well-selected sample of galaxy clusters on which cosmological analyses can be performed. This paper presents the photometric redshift follow-up of a high signal-to-noise ratio subset of 265 of these clusters with declination δ < +20° with Gamma-Ray Burst Optical and Near-Infrared Detector (GROND), a 7-channel (grizJHK) simultaneous imager on the MPG 2.2-m telescope at the ESO La Silla Observatory. We use a newly developed technique based on the red sequence colour-redshift relation, enhanced with information coming from the X-ray detection to provide photometric redshifts for this sample. We determine photometric redshifts for 232 clusters, finding a median redshift of z = 0.39 with an accuracy of Δz = 0.02(1 + z) when compared to a sample of 76 spectroscopically confirmed clusters. We also compute X-ray luminosities for the entire sample and find a median bolometric luminosity of 7.2 × 1043 erg s-1 and a median temperature of 2.9 keV. We compare our results to those of the XMM-XCS and XMM-XXL surveys, finding good agreement in both samples. The X-CLASS catalogue is available online at http://xmm-lss.in2p3.fr:8080/l4sdb/.

Scalable Algorithms for Clustering Large Geospatiotemporal Data Sets on Manycore Architectures

NASA Astrophysics Data System (ADS)

Mills, R. T.; Hoffman, F. M.; Kumar, J.; Sreepathi, S.; Sripathi, V.

2016-12-01

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery using data sets fused from disparate sources. Traditional algorithms and computing platforms are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of available parallelism in state-of-the-art high-performance computing platforms can enable such analysis. We describe a massively parallel implementation of accelerated k-means clustering and some optimizations to boost computational intensity and utilization of wide SIMD lanes on state-of-the art multi- and manycore processors, including the second-generation Intel Xeon Phi ("Knights Landing") processor based on the Intel Many Integrated Core (MIC) architecture, which includes several new features, including an on-package high-bandwidth memory. We also analyze the code in the context of a few practical applications to the analysis of climatic and remotely-sensed vegetation phenology data sets, and speculate on some of the new applications that such scalable analysis methods may enable.

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

NASA Astrophysics Data System (ADS)

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.

Genetic diversity analysis of Gossypium arboreum germplasm accessions using genotyping-by-sequencing.

PubMed

Li, Ruijuan; Erpelding, John E

2016-10-01

The diploid cotton species Gossypium arboreum possesses many favorable agronomic traits such as drought tolerance and disease resistance, which can be utilized in the development of improved upland cotton cultivars. The USDA National Plant Germplasm System maintains more than 1600 G. arboreum accessions. Little information is available on the genetic diversity of the collection thereby limiting the utilization of this cotton species. The genetic diversity and population structure of the G. arboreum germplasm collection were assessed by genotyping-by-sequencing of 375 accessions. Using genome-wide single nucleotide polymorphism sequence data, two major clusters were inferred with 302 accessions in Cluster 1, 64 accessions in Cluster 2, and nine accessions unassigned due to their nearly equal membership to each cluster. These two clusters were further evaluated independently resulting in the identification of two sub-clusters for the 302 Cluster 1 accessions and three sub-clusters for the 64 Cluster 2 accessions. Low to moderate genetic diversity between clusters and sub-clusters were observed indicating a narrow genetic base. Cluster 2 accessions were more genetically diverse and the majority of the accessions in this cluster were landraces. In contrast, Cluster 1 is composed of varieties or breeding lines more recently added to the collection. The majority of the accessions had kinship values ranging from 0.6 to 0.8. Eight pairs of accessions were identified as potential redundancies due to their high kinship relatedness. The genetic diversity and genotype data from this study are essential to enhance germplasm utilization to identify genetically diverse accessions for the detection of quantitative trait loci associated with important traits that would benefit upland cotton improvement.

densityCut: an efficient and versatile topological approach for automatic clustering of biological data

PubMed Central

Ding, Jiarui; Shah, Sohrab; Condon, Anne

2016-01-01

Motivation: Many biological data processing problems can be formalized as clustering problems to partition data points into sensible and biologically interpretable groups. Results: This article introduces densityCut, a novel density-based clustering algorithm, which is both time- and space-efficient and proceeds as follows: densityCut first roughly estimates the densities of data points from a K-nearest neighbour graph and then refines the densities via a random walk. A cluster consists of points falling into the basin of attraction of an estimated mode of the underlining density function. A post-processing step merges clusters and generates a hierarchical cluster tree. The number of clusters is selected from the most stable clustering in the hierarchical cluster tree. Experimental results on ten synthetic benchmark datasets and two microarray gene expression datasets demonstrate that densityCut performs better than state-of-the-art algorithms for clustering biological datasets. For applications, we focus on the recent cancer mutation clustering and single cell data analyses, namely to cluster variant allele frequencies of somatic mutations to reveal clonal architectures of individual tumours, to cluster single-cell gene expression data to uncover cell population compositions, and to cluster single-cell mass cytometry data to detect communities of cells of the same functional states or types. densityCut performs better than competing algorithms and is scalable to large datasets. Availability and Implementation: Data and the densityCut R package is available from https://bitbucket.org/jerry00/densitycut_dev. Contact: condon@cs.ubc.ca or sshah@bccrc.ca or jiaruid@cs.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153661

Joint spatial-spectral hyperspectral image clustering using block-diagonal amplified affinity matrix

NASA Astrophysics Data System (ADS)

Fan, Lei; Messinger, David W.

2018-03-01

The large number of spectral channels in a hyperspectral image (HSI) produces a fine spectral resolution to differentiate between materials in a scene. However, difficult classes that have similar spectral signatures are often confused while merely exploiting information in the spectral domain. Therefore, in addition to spectral characteristics, the spatial relationships inherent in HSIs should also be considered for incorporation into classifiers. The growing availability of high spectral and spatial resolution of remote sensors provides rich information for image clustering. Besides the discriminating power in the rich spectrum, contextual information can be extracted from the spatial domain, such as the size and the shape of the structure to which one pixel belongs. In recent years, spectral clustering has gained popularity compared to other clustering methods due to the difficulty of accurate statistical modeling of data in high dimensional space. The joint spatial-spectral information could be effectively incorporated into the proximity graph for spectral clustering approach, which provides a better data representation by discovering the inherent lower dimensionality from the input space. We embedded both spectral and spatial information into our proposed local density adaptive affinity matrix, which is able to handle multiscale data by automatically selecting the scale of analysis for every pixel according to its neighborhood of the correlated pixels. Furthermore, we explored the "conductivity method," which aims at amplifying the block diagonal structure of the affinity matrix to further improve the performance of spectral clustering on HSI datasets.

Effects of Carbonyl Bond and Metal Cluster Dissociation and Evaporation Rates on Predictions of Nanotube Production in HiPco

NASA Technical Reports Server (NTRS)

Scott, Carl D.; Smalley, Richard E.

2002-01-01

The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNT) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the co-formation of CO2. It is shown that the production of CO2 is significantly greater for FeCO due to its lower bond energy as compared with that ofNiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

Clustering of samples and variables with mixed-type data

PubMed Central

Edelmann, Dominic; Kopp-Schneider, Annette

2017-01-01

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

Poisson Mixture Regression Models for Heart Disease Prediction.

PubMed

Mufudza, Chipo; Erol, Hamza

2016-01-01

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

Poisson Mixture Regression Models for Heart Disease Prediction

PubMed Central

Erol, Hamza

2016-01-01

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

Mass profile and dynamical status of the z ~ 0.8 galaxy cluster LCDCS 0504

NASA Astrophysics Data System (ADS)

Guennou, L.; Biviano, A.; Adami, C.; Limousin, M.; Lima Neto, G. B.; Mamon, G. A.; Ulmer, M. P.; Gavazzi, R.; Cypriano, E. S.; Durret, F.; Clowe, D.; LeBrun, V.; Allam, S.; Basa, S.; Benoist, C.; Cappi, A.; Halliday, C.; Ilbert, O.; Johnston, D.; Jullo, E.; Just, D.; Kubo, J. M.; Márquez, I.; Marshall, P.; Martinet, N.; Maurogordato, S.; Mazure, A.; Murphy, K. J.; Plana, H.; Rostagni, F.; Russeil, D.; Schirmer, M.; Schrabback, T.; Slezak, E.; Tucker, D.; Zaritsky, D.; Ziegler, B.

2014-06-01

Context. Constraints on the mass distribution in high-redshift clusters of galaxies are currently not very strong. Aims: We aim to constrain the mass profile, M(r), and dynamical status of the z ~ 0.8 LCDCS 0504 cluster of galaxies that is characterized by prominent giant gravitational arcs near its center. Methods: Our analysis is based on deep X-ray, optical, and infrared imaging as well as optical spectroscopy, collected with various instruments, which we complemented with archival data. We modeled the mass distribution of the cluster with three different mass density profiles, whose parameters were constrained by the strong lensing features of the inner cluster region, by the X-ray emission from the intracluster medium, and by the kinematics of 71 cluster members. Results: We obtain consistent M(r) determinations from three methods based on kinematics (dispersion-kurtosis, caustics, and MAMPOSSt), out to the cluster virial radius, ≃1.3 Mpc and beyond. The mass profile inferred by the strong lensing analysis in the central cluster region is slightly higher than, but still consistent with, the kinematics estimate. On the other hand, the X-ray based M(r) is significantly lower than the kinematics and strong lensing estimates. Theoretical predictions from ΛCDM cosmology for the concentration-mass relation agree with our observational results, when taking into account the uncertainties in the observational and theoretical estimates. There appears to be a central deficit in the intracluster gas mass fraction compared with nearby clusters. Conclusions: Despite the relaxed appearance of this cluster, the determinations of its mass profile by different probes show substantial discrepancies, the origin of which remains to be determined. The extension of a dynamical analysis similar to that of other clusters of the DAFT/FADA survey with multiwavelength data of sufficient quality will allow shedding light on the possible systematics that affect the determination of mass profiles of high-z clusters, which is possibly related to our incomplete understanding of intracluster baryon physics. Table 2 is available in electronic form at http://www.aanda.org

Model-based Clustering of High-Dimensional Data in Astrophysics

NASA Astrophysics Data System (ADS)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

An empirical method to cluster objective nebulizer adherence data among adults with cystic fibrosis.

PubMed

Hoo, Zhe H; Campbell, Michael J; Curley, Rachael; Wildman, Martin J

2017-01-01

The purpose of using preventative inhaled treatments in cystic fibrosis is to improve health outcomes. Therefore, understanding the relationship between adherence to treatment and health outcome is crucial. Temporal variability, as well as absolute magnitude of adherence affects health outcomes, and there is likely to be a threshold effect in the relationship between adherence and outcomes. We therefore propose a pragmatic algorithm-based clustering method of objective nebulizer adherence data to better understand this relationship, and potentially, to guide clinical decisions. This clustering method consists of three related steps. The first step is to split adherence data for the previous 12 months into four 3-monthly sections. The second step is to calculate mean adherence for each section and to score the section based on mean adherence. The third step is to aggregate the individual scores to determine the final cluster ("cluster 1" = very low adherence; "cluster 2" = low adherence; "cluster 3" = moderate adherence; "cluster 4" = high adherence), and taking into account adherence trend as represented by sequential individual scores. The individual scores should be displayed along with the final cluster for clinicians to fully understand the adherence data. We present three cases to illustrate the use of the proposed clustering method. This pragmatic clustering method can deal with adherence data of variable duration (ie, can be used even if 12 months' worth of data are unavailable) and can cluster adherence data in real time. Empirical support for some of the clustering parameters is not yet available, but the suggested classifications provide a structure to investigate parameters in future prospective datasets in which there are accurate measurements of nebulizer adherence and health outcomes.

Applications of Nanoparticle-Containing Plasmas for High-Order Harmonic Generation of Laser Radiation

NASA Astrophysics Data System (ADS)

Ganeev, Rashid A.

The use of nanoparticles for efficient conversion of the wavelength of ultrashort laser toward the deep UV spectral range through harmonic generation is an attractive application of cluster-containing plasmas. Note that earlier observations of HHG in nanoparticles were limited by using the exotic gas clusters formed during fast cooling of atomic flow from the gas jets 1-4. One can assume the difficulties in definition of the structure of such clusters and the ratio between nanoparticles and atoms/ions in the gas flow. The characterization of gas phase cluster production was currently improved using the sophisticated techniques (e.g., a control of nanoparticle mass and spatial distribution, see the review 5). In the meantime, the plasma nanoparticle HHG has demonstrated some advantages over gas cluster HHG 6. The application of commercially available nanopowders allowed for precisely defining the sizes and structure of these clusters in the plume. The laser ablation technique made possible the predictable manipulation of plasma characteristics, which led to the creation of laser plumes containing mainly nanoparticles with known spatial structure. The latter allows the application of such plumes in nonlinear optics, X-ray emission of clusters, deposition of nanoparticles with fixed parameters on the substrates for semiconductor industry, production of nanostructured and nanocomposite films, etc.

Clustering techniques: measuring the performance of contract service providers.

PubMed

Cruz, Antonio Miguel; Perilla, Sandra Patricia Usaquén; Pabón, Nidia Nelly Vanegas

2010-01-01

This paper investigates the use of clustering technique to characterize the providers of maintenance services in a health-care institution according to their performance. A characterization of the inventory of equipment from seven pilot areas was carried out first (including 264 medical devices). The characterization study concluded that the inventory on a whole is old [exploitation time (ET)/useful life (UL) average is 0.78] and has high maintenance service costs relative to the original cost of acquisition (service cost /acquisition cost average 8.61%). A monitoring of the performance of maintenance service providers was then conducted. The variables monitored were response time (RT), service time (ST), availability, and turnaround time (TAT). Finally, the study grouped maintenance service providers into clusters according to performance. The study grouped maintenance service providers into the following clusters. Cluster 0: Identified with the best performance, the lowest values of TAT, RT, and ST, with an average TAT value of 1.46 days; Clusters 1 and 2: Identified with the poorest performance, highest values of TAT, RT, and ST, and an average TAT value of 9.79 days; and Cluster 3: Identified by medium-quality performance, intermediate values of TAT, RT, and ST, and an average TAT value of 2.56 days.

The central dynamics of M3, M13, and M92: stringent limits on the masses of intermediate-mass black holes

NASA Astrophysics Data System (ADS)

Kamann, S.; Wisotzki, L.; Roth, M. M.; Gerssen, J.; Husser, T.-O.; Sandin, C.; Weilbacher, P.

2014-06-01

We used the PMAS integral field spectrograph to obtain large sets of radial velocities in the central regions of three northern Galactic globular clusters: M3, M13, and M92. By applying the novel technique of crowded field 3D spectroscopy, we measured radial velocities for about 80 stars within the central ~10″ of each cluster. These are by far the largest spectroscopic datasets obtained in the innermost parts of these clusters up to now. To obtain kinematical data across the whole extent of the clusters, we complement our data with measurements available in the literature. We combine our velocity measurements with surface brightness profiles to analyse the internal dynamics of each cluster using spherical Jeans models, and investigate whether our data provide evidence for an intermediate-mass black hole in any of the clusters. The surface brightness profiles reveal that all three clusters are consistent with a core profile, although shallow cusps cannot be excluded. We find that spherical Jeans models with a constant mass-to-light ratio provide a good overall representation of the kinematical data. A massive black hole is required in none of the three clusters to explain the observed kinematics. Our 1σ (3σ) upper limits are 5300 M⊙ (12 000 M⊙) for M3, 8600 M⊙ (13 000 M⊙) for M13, and 980 M⊙ (2700 M⊙) for M92. A puzzling circumstance is the existence of several potential high velocity stars in M3 and M13, as their presence can account for the majority of the discrepancies that we find in our mass limits compared to M92. Based on observations collected at the Centro Astronómico Hispano-Alemán (CAHA) at Calar Alto, operated jointly by the Max-Planck Institut für Astronomie and the Instituto de Astrofísica de Andalucía (CSIC).Appendices are available in electronic form at http://www.aanda.orgTables D.1 to D.6 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/566/A58

Membrane Order Is a Key Regulator of Divalent Cation-Induced Clustering of PI(3,5)P2 and PI(4,5)P2.

PubMed

Sarmento, Maria J; Coutinho, Ana; Fedorov, Aleksander; Prieto, Manuel; Fernandes, Fábio

2017-10-31

Although the evidence for the presence of functionally important nanosized phosphorylated phosphoinositide (PIP)-rich domains within cellular membranes has accumulated, very limited information is available regarding the structural determinants for compartmentalization of these phospholipids. Here, we used a combination of fluorescence spectroscopy and microscopy techniques to characterize differences in divalent cation-induced clustering of PI(4,5)P 2 and PI(3,5)P 2 . Through these methodologies we were able to detect differences in divalent cation-induced clustering efficiency and cluster size. Ca 2+ -induced PI(4,5)P 2 clusters are shown to be significantly larger than the ones observed for PI(3,5)P 2 . Clustering of PI(4,5)P 2 is also detected at physiological concentrations of Mg 2+ , suggesting that in cellular membranes, these molecules are constitutively driven to clustering by the high intracellular concentration of divalent cations. Importantly, it is shown that lipid membrane order is a key factor in the regulation of clustering for both PIP isoforms, with a major impact on cluster sizes. Clustered PI(4,5)P 2 and PI(3,5)P 2 are observed to present considerably higher affinity for more ordered lipid phases than the monomeric species or than PI(4)P, possibly reflecting a more general tendency of clustered lipids for insertion into ordered domains. These results support a model for the description of the lateral organization of PIPs in cellular membranes, where both divalent cation interaction and membrane order are key modulators defining the lateral organization of these lipids.

Prediction of strontium bromide laser efficiency using cluster and decision tree analysis

NASA Astrophysics Data System (ADS)

Iliev, Iliycho; Gocheva-Ilieva, Snezhana; Kulin, Chavdar

2018-01-01

Subject of investigation is a new high-powered strontium bromide (SrBr2) vapor laser emitting in multiline region of wavelengths. The laser is an alternative to the atom strontium lasers and electron free lasers, especially at the line 6.45 μm which line is used in surgery for medical processing of biological tissues and bones with minimal damage. In this paper the experimental data from measurements of operational and output characteristics of the laser are statistically processed by means of cluster analysis and tree-based regression techniques. The aim is to extract the more important relationships and dependences from the available data which influence the increase of the overall laser efficiency. There are constructed and analyzed a set of cluster models. It is shown by using different cluster methods that the seven investigated operational characteristics (laser tube diameter, length, supplied electrical power, and others) and laser efficiency are combined in 2 clusters. By the built regression tree models using Classification and Regression Trees (CART) technique there are obtained dependences to predict the values of efficiency, and especially the maximum efficiency with over 95% accuracy.

Data-Driven Packet Loss Estimation for Node Healthy Sensing in Decentralized Cluster

PubMed Central

Fan, Hangyu; Wang, Huandong; Li, Yong

2018-01-01

Decentralized clustering of modern information technology is widely adopted in various fields these years. One of the main reason is the features of high availability and the failure-tolerance which can prevent the entire system form broking down by a failure of a single point. Recently, toolkits such as Akka are used by the public commonly to easily build such kind of cluster. However, clusters of such kind that use Gossip as their membership managing protocol and use link failure detecting mechanism to detect link failures cannot deal with the scenario that a node stochastically drops packets and corrupts the member status of the cluster. In this paper, we formulate the problem to be evaluating the link quality and finding a max clique (NP-Complete) in the connectivity graph. We then proposed an algorithm that consists of two models driven by data from application layer to respectively solving these two problems. Through simulations with statistical data and a real-world product, we demonstrate that our algorithm has a good performance. PMID:29360792

Spatial organization and dynamics of RNase E and ribosomes in Caulobacter crescentus.

PubMed

Bayas, Camille A; Wang, Jiarui; Lee, Marissa K; Schrader, Jared M; Shapiro, Lucy; Moerner, W E

2018-04-17

We report the dynamic spatial organization of Caulobacter crescentus RNase E (RNA degradosome) and ribosomal protein L1 (ribosome) using 3D single-particle tracking and superresolution microscopy. RNase E formed clusters along the central axis of the cell, while weak clusters of ribosomal protein L1 were deployed throughout the cytoplasm. These results contrast with RNase E and ribosome distribution in Escherichia coli , where RNase E colocalizes with the cytoplasmic membrane and ribosomes accumulate in polar nucleoid-free zones. For both RNase E and ribosomes in Caulobacter , we observed a decrease in confinement and clustering upon transcription inhibition and subsequent depletion of nascent RNA, suggesting that RNA substrate availability for processing, degradation, and translation facilitates confinement and clustering. Importantly, RNase E cluster positions correlated with the subcellular location of chromosomal loci of two highly transcribed rRNA genes, suggesting that RNase E's function in rRNA processing occurs at the site of rRNA synthesis. Thus, components of the RNA degradosome and ribosome assembly are spatiotemporally organized in Caulobacter , with chromosomal readout serving as the template for this organization.

Effects of phosphorus supply on growth, phosphate concentration and cluster-root formation in three Lupinus species

PubMed Central

Abdolzadeh, Ahmad; Wang, Xing; Veneklaas, Erik J.; Lambers, Hans

2010-01-01

Background and Aims In some lupin species, phosphate deficiency induces cluster-root formation, which enhances P uptake by increasing root surface area and, more importantly, the release of root exudates which enhances P availability. Methods Three species of Lupinus, L. albus, L. atlanticus and L. micranthus, with inherently different relative growth rates were cultivated under hydroponics in a greenhouse at four phosphate concentrations (1, 10, 50 and 150 µm) to compare the role of internal P in regulating cluster-root formation. Key Results The highest growth rate was observed in L. atlanticus, followed by L. albus and L. micranthus. At 1 µm P, cluster-root formation was markedly induced in all three species. The highest P uptake and accumulation was observed in L. micranthus, followed by L. atlanticus and then L. albus. Inhibition of cluster-root formation was severe at 10 µm P in L. atlanticus, but occurred stepwise with increasing P concentration in the root medium in L. albus. Conclusions In L. atlanticus and L. albus cluster-root formation was suppressed by P treatments above 10 µm, indicating a P-inducible regulating system for cluster-root formation, as expected. By contrast, production of cluster roots in L. micranthus, in spite of a high internal P concentration, indicated a lower sensitivity to P status, which allowed P-toxicity symptoms to develop. PMID:20037142

antiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters.

PubMed

Weber, Tilmann; Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko; Medema, Marnix H

2015-07-01

Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Spatial distribution of 12 class B notifiable infectious diseases in China: A retrospective study.

PubMed

Zhu, Bin; Fu, Yang; Liu, Jinlin; Mao, Ying

2018-01-01

China is the largest developing country with a relatively developed public health system. To further prevent and eliminate the spread of infectious diseases, China has listed 39 notifiable infectious diseases characterized by wide prevalence or great harm, and classified them into classes A, B, and C, with severity decreasing across classes. Class A diseases have been almost eradicated in China, thus making class B diseases a priority in infectious disease prevention and control. In this retrospective study, we analyze the spatial distribution patterns of 12 class B notifiable infectious diseases that remain active all over China. Global and local Moran's I and corresponding graphic tools are adopted to explore and visualize the global and local spatial distribution of the incidence of the selected epidemics, respectively. Inter-correlations of clustering patterns of each pair of diseases and a cumulative summary of the high/low cluster frequency of the provincial units are also provided by means of figures and maps. Of the 12 most commonly notifiable class B infectious diseases, viral hepatitis and tuberculosis show high incidence rates and account for more than half of the reported cases. Almost all the diseases, except pertussis, exhibit positive spatial autocorrelation at the provincial level. All diseases feature varying spatial concentrations. Nevertheless, associations exist between spatial distribution patterns, with some provincial units displaying the same type of cluster features for two or more infectious diseases. Overall, high-low (unit with high incidence surrounded by units with high incidence, the same below) and high-high spatial cluster areas tend to be prevalent in the provincial units located in western and southwest China, whereas low-low and low-high spatial cluster areas abound in provincial units in north and east China. Despite the various distribution patterns of 12 class B notifiable infectious diseases, certain similarities between their spatial distributions are present. Substantial evidence is available to support disease-specific, location-specific, and disease-combined interventions. Regarding provinces that show high-high/high-low patterns of multiple diseases, comprehensive interventions targeting different diseases should be established. As to the adjacent provincial units revealing similar patterns, coordinated actions need to be taken across borders.

Geomorphological analysis of boulders and polygons on Martian periglacial patterned ground terrains

NASA Astrophysics Data System (ADS)

Orloff, Travis C.

Images from the High Resolution Imaging Science Experiment Camera onboard the Mars Reconnaisance Orbiter show the surface in higher detail than previously capable. I look at a landscape on Mars called permafrost patterned ground which covers ˜10 million square kilometers of the surface at high latitudes (>50°). Using the new high resolution images available we objectively characterize permafrost patterned ground terrains as an alternative to observational surveys which while detailed suffer from subjective bias. I take two dimensional Fourier transforms of individual images of Martian permafrost patterned ground to find the scale most representative of the terrain. This scale acts as a proxy for the size of the polygons themselves. Then I look at the distribution of spectral scales in the northern hemisphere between 50-70° and find correlations to previous studies and with the extent of ground ice in the surface. The high resolution images also show boulders clustering with respect to the underlying pattern. I make the first detailed observations of these clustered boulders and use crater counting to place constraints on the time it takes for boulders to cluster. Finally, I present a potential mechanism for the process that clusters the boulders that takes the specifics of the Martian environment to account. Boulders lying on the surface get trapped in seasonal CO2 frost while ice in the near surface contracts in the winter. The CO2 frost sublimates in spring/summer allowing the boulders to move when the near surface ice expands in summer. Repeated iterations lead to boulders that cluster in the polygon edges. Using a thermal model of the subsurface with Mars conditions and an elastic model of a polygon I show boulders could move as much as ˜0.1mm per year in the present day.

Reanalysis of 24 Nearby Open Clusters using Gaia data

NASA Astrophysics Data System (ADS)

Yen, Steffi X.; Reffert, Sabine; Röser, Siegfried; Schilbach, Elena; Kharchenko, Nina V.; Piskunov, Anatoly E.

2018-04-01

We have developed a fully automated cluster characterization pipeline, which simultaneously determines cluster membership and fits the fundamental cluster parameters: distance, reddening, and age. We present results for 24 established clusters and compare them to literature values. Given the large amount of stellar data for clusters available from Gaia DR2 in 2018, this pipeline will be beneficial to analyzing the parameters of open clusters in our Galaxy.

Low-income women's reproductive weight patterns empirically based clusters of prepregnant, gestational, and postpartum weights.

PubMed

Walker, Lorraine O

2009-01-01

Women have varying weight responses to pregnancy and the postpartum period. The purpose of this study was to derive sub-groups of women based on differing reproductive weight clusters; to validate clusters by reference to adequacy of gestational weight gain (GWG) and postpartum incremental weight shifts; and to examine associations between clusters and demographic, behavioral, and psychosocial variables. A cluster analysis was conducted of a multi-ethnic/racial sample of low-income women (n = 247). Clusters were derived from three weight variables: prepregnant body mass index, GWG, and postpartum retained weight. Five clusters were derived: Cluster 1, normal weight-high prenatal gain-average retain; cluster 2, normal weight-low prenatal gain-zero retain; cluster 3, high normal weight-high prenatal gain-high retain; cluster 4, obese-low prenatal gain-average retain; and cluster 5, overweight-very high prenatal gain-very high retain. Clusters differed with regard to postpartum weight shifts (p < .001), with clusters 3, 4, and 5, mostly gaining weight between 6 weeks and 12 months postpartum, whereas clusters 1 and 2 were losing weight. Clusters were also associated with race/ethnicity (p < .01), breastfeeding immediately postdelivery (p < .01), smoking at 12 months (p < .05), and reaching weight goals at 6 and 12 months (p < .001), but not depressive symptoms, fat intake habits, or physical activity. In a five-cluster solution, postpartum weight shifts, ethnicity, and initial breastfeeding were among factors associated with clusters. Monitoring of weight and appropriate intervention beyond the 6 weeks after birth is needed for low-income women in high normal weight, overweight, and obese clusters.

A Resource Manual for Career Education in the Des Moines Area.

ERIC Educational Resources Information Center

Drake Univ., Des Moines, IA.

Information contained in this resource manual is designed to help educators become more familiar with career opportunities available to high school graduates in the local (Des Moines) labor market, and employer requirements for entry into these career areas. Fifteen occupational clusters are investigated: Agribusiness and natural resources,…

CRISPR/Cas9 mediated high efficiency knockout of the eye color gene vermillion in Helicoverpa zea (Boddie)

USDA-ARS?s Scientific Manuscript database

Among various genome editing tools available for functional genomic studies, reagents based on clustered regularly interspersed palindromic repeats (CRISPR) have gained popularity due to ease and versatility. CRISPR reagents consists of ribonucleoprotein (RNP) complexes formed by combining guide RNA...

CORM: An R Package Implementing the Clustering of Regression Models Method for Gene Clustering

PubMed Central

Shi, Jiejun; Qin, Li-Xuan

2014-01-01

We report a new R package implementing the clustering of regression models (CORM) method for clustering genes using gene expression data and provide data examples illustrating each clustering function in the package. The CORM package is freely available at CRAN from http://cran.r-project.org. PMID:25452684

Massive and refined: A sample of large galaxy clusters simulated at high resolution. I: Thermal gas and properties of shock waves

NASA Astrophysics Data System (ADS)

Vazza, F.; Brunetti, G.; Gheller, C.; Brunino, R.

2010-11-01

We present a sample of 20 massive galaxy clusters with total virial masses in the range of 6 × 10 14 M ⊙ ⩽ Mvir ⩽ 2 × 10 15 M ⊙, re-simulated with a customized version of the 1.5. ENZO code employing adaptive mesh refinement. This technique allowed us to obtain unprecedented high spatial resolution (≈25 kpc/h) up to the distance of ˜3 virial radii from the clusters center, and makes it possible to focus with the same level of detail on the physical properties of the innermost and of the outermost cluster regions, providing new clues on the role of shock waves and turbulent motions in the ICM, across a wide range of scales. In this paper, a first exploratory study of this data set is presented. We report on the thermal properties of galaxy clusters at z = 0. Integrated and morphological properties of gas density, gas temperature, gas entropy and baryon fraction distributions are discussed, and compared with existing outcomes both from the observational and from the numerical literature. Our cluster sample shows an overall good consistency with the results obtained adopting other numerical techniques (e.g. Smoothed Particles Hydrodynamics), yet it provides a more accurate representation of the accretion patterns far outside the cluster cores. We also reconstruct the properties of shock waves within the sample by means of a velocity-based approach, and we study Mach numbers and energy distributions for the various dynamical states in clusters, giving estimates for the injection of Cosmic Rays particles at shocks. The present sample is rather unique in the panorama of cosmological simulations of massive galaxy clusters, due to its dynamical range, statistics of objects and number of time outputs. For this reason, we deploy a public repository of the available data, accessible via web portal at http://data.cineca.it.

The Grism Lens-amplified Survey from Space (GLASS). IV. Mass Reconstruction of the Lensing Cluster Abell 2744 from Frontier Field Imaging and GLASS Spectroscopy

NASA Astrophysics Data System (ADS)

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

2015-09-01

We present a strong and weak lensing reconstruction of the massive cluster Abell 2744, the first cluster for which deep Hubble Frontier Fields (HFF) images and spectroscopy from the Grism Lens-Amplified Survey from Space (GLASS) are available. By performing a targeted search for emission lines in multiply imaged sources using the GLASS spectra, we obtain five high-confidence spectroscopic redshifts and two tentative ones. We confirm one strongly lensed system by detecting the same emission lines in all three multiple images. We also search for additional line emitters blindly and use the full GLASS spectroscopic catalog to test reliability of photometric redshifts for faint line emitters. We see a reasonable agreement between our photometric and spectroscopic redshift measurements, when including nebular emission in photometric redshift estimations. We introduce a stringent procedure to identify only secure multiple image sets based on colors, morphology, and spectroscopy. By combining 7 multiple image systems with secure spectroscopic redshifts (at 5 distinct redshift planes) with 18 multiple image systems with secure photometric redshifts, we reconstruct the gravitational potential of the cluster pixellated on an adaptive grid, using a total of 72 images. The resulting mass map is compared with a stellar mass map obtained from the deep Spitzer Frontier Fields data to study the relative distribution of stars and dark matter in the cluster. We find that the stellar to total mass ratio varies substantially across the cluster field, suggesting that stars do not trace exactly the total mass in this interacting system. The maps of convergence, shear, and magnification are made available in the standard HFF format.

THE GRISM LENS-AMPLIFIED SURVEY FROM SPACE (GLASS). IV. MASS RECONSTRUCTION OF THE LENSING CLUSTER ABELL 2744 FROM FRONTIER FIELD IMAGING AND GLASS SPECTROSCOPY

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

Wang, X.; Schmidt, K. B.; Jones, T. A.

2015-09-20

We present a strong and weak lensing reconstruction of the massive cluster Abell 2744, the first cluster for which deep Hubble Frontier Fields (HFF) images and spectroscopy from the Grism Lens-Amplified Survey from Space (GLASS) are available. By performing a targeted search for emission lines in multiply imaged sources using the GLASS spectra, we obtain five high-confidence spectroscopic redshifts and two tentative ones. We confirm one strongly lensed system by detecting the same emission lines in all three multiple images. We also search for additional line emitters blindly and use the full GLASS spectroscopic catalog to test reliability of photometricmore » redshifts for faint line emitters. We see a reasonable agreement between our photometric and spectroscopic redshift measurements, when including nebular emission in photometric redshift estimations. We introduce a stringent procedure to identify only secure multiple image sets based on colors, morphology, and spectroscopy. By combining 7 multiple image systems with secure spectroscopic redshifts (at 5 distinct redshift planes) with 18 multiple image systems with secure photometric redshifts, we reconstruct the gravitational potential of the cluster pixellated on an adaptive grid, using a total of 72 images. The resulting mass map is compared with a stellar mass map obtained from the deep Spitzer Frontier Fields data to study the relative distribution of stars and dark matter in the cluster. We find that the stellar to total mass ratio varies substantially across the cluster field, suggesting that stars do not trace exactly the total mass in this interacting system. The maps of convergence, shear, and magnification are made available in the standard HFF format.« less

On the assessment of the nature of open star clusters and the determination of their basic parameters with limited data

NASA Astrophysics Data System (ADS)

Carraro, Giovanni; Baume, Gustavo; Seleznev, Anton F.; Costa, Edgardo

2017-07-01

Our knowledge of stellar evolution and of the structure and chemical evolution of the Galactic disk largely builds on the study of open star clusters. Because of their crucial role in these relevant topics, large homogeneous catalogues of open cluster parameters are highly desirable. Although efforts have been made to develop automatic tools to analyse large numbers of clusters, the results obtained so far vary from study to study, and sometimes are very contradictory when compared to dedicated studies of individual clusters. In this work we highlight the common causes of these discrepancies for some open clusters, and show that at present dedicated studies yield a much better assessment of the nature of star clusters, even in the absence of ideal data-sets. We make use of deep, wide-field, multi-colour photometry to discuss the nature of six strategically selected open star clusters: Trumpler 22, Lynga 6, Hogg 19, Hogg 21, Pismis 10 and Pismis 14. We have precisely derived their basic parameters by means of a combination of star counts and photometric diagrams. Trumpler 22 and Lynga 6 are included in our study because they are widely known, and thus provided a check of our data and methodology. The remaining four clusters are very poorly known, and their available parameters have been obtained using automatic tools only. Our results are in some cases in severe disagreement with those from automatic surveys.

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

PubMed

Castro-Mondragon, Jaime Abraham; Jaeger, Sébastien; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2017-07-27

Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Evolution of the Globular Cluster System in a Triaxial Galaxy: Can a Galactic Nucleus Form by Globular Cluster Capture?

NASA Astrophysics Data System (ADS)

Capuzzo-Dolcetta, Roberto

1993-10-01

Among the possible phenomena inducing evolution of the globular cluster system in an elliptical galaxy, dynamical friction due to field stars and tidal disruption caused by a central nucleus is of crucial importance. The aim of this paper is the study of the evolution of the globular cluster system in a triaxial galaxy in the presence of these phenomena. In particular, the possibility is examined that some galactic nuclei have been formed by frictionally decayed globular clusters moving in a triaxial potential. We find that the initial rapid growth of the nucleus, due mainly to massive clusters on box orbits falling in a short time scale into the galactic center, is later slowed by tidal disruption induced by the nucleus itself on less massive clusters in the way described by Ostriker, Binney, and Saha. The efficiency of dynamical friction is such to carry to the center of the galaxy enough globular cluster mass available to form a compact nucleus, but the actual modes and results of cluster-cluster encounters in the central potential well are complicated phenomena which remains to be investigated. The mass of the resulting nucleus is determined by the mutual feedback of the described processes, together with the initial spatial, velocity, and mass distributions of the globular cluster family. The effect on the system mass function is studied, showing the development of a low- and high-mass turnover even with an initially flat mass function. Moreover, in this paper is discussed the possibility that the globular cluster fall to the galactic center has been a cause of primordial violent galactic activity. An application of the model to M31 is presented.

Flow over gravel beds with clusters

NASA Astrophysics Data System (ADS)

Little, M.; Venditti, J. G.

2014-12-01

The structure of a gravel bed has been shown to alter the entrainment threshold. Structures such as clusters, reticulate stone cells and other discrete structures lock grains together, making it more difficult for them to be mobilized. These structures also generate form drag, reducing the shear stress available for mobilization. Form drag over gravel beds is often assumed to be negligible, but this assumption is not well supported. Here, we explore how cluster density and arrangement affect flow resistance and the flow structure over a fixed gravel bed in a flume experiment. Cluster density was varied from 6 to 68.3 clusters per square meter which corresponds to areal bed coverages of 2 to 17%. We used regular, irregular and random arrangements of the clusters. Our results show that flow resistance over a planar gravel bed initially declines, then increases with flow depth. The addition of clusters increases flow resistance, but the effect is dependent on cluster density, flow depth and arrangement. At the highest density, clusters can increase flow resistance as by as much as 8 times when compared to flat planar bed with no grain-related form drag. Spatially resolved observations of flow over the clusters indicate that a well-defined wake forms in the lee of each cluster. At low cluster density, the wakes are isolated and weak. As cluster density increases, the wakes become stronger. At the highest density, the wakes interact and the within cluster flow field detaches from the overlying flow. This generates a distinct shear layer at the height of the clusters. In spite of this change in the flow field at high density, our results suggest that flow resistance simply increases with cluster density. Our results suggest that the form drag associated with a gravel bed can be substantial and that it depends on the arrangement of the grains on the bed.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

PubMed

Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

SPECTROSCOPIC ABUNDANCES AND MEMBERSHIP IN THE WOLF 630 MOVING GROUP

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

Bubar, Eric J.; King, Jeremy R., E-mail: ebubar@gmail.co, E-mail: jking2@ces.clemson.ed

The concept of kinematic assemblages evolving from dispersed stellar clusters has remained contentious since Eggen's initial formulation of moving groups in the 1960s. With high-quality parallaxes from the Hipparcos space astrometry mission, distance measurements for thousands of nearby, seemingly isolated stars are currently available. With these distances, a high-resolution spectroscopic abundance analysis can be brought to bear on the alleged members of these moving groups. If a structure is a relic of an open cluster, the members can be expected to be monolithic in age and abundance in as much as homogeneity is observed in young open clusters. In thismore » work, we have examined 34 putative members of the proposed Wolf 630 moving group using high-resolution stellar spectroscopy. The stars of the sample have been chemically tagged to determine abundance homogeneity and confirm the existence of a homogeneous subsample of 19 stars. Fitting the homogeneous subsample with Yale-Yonsei isochrones yields a single evolutionary sequence of {approx}2.7 {+-} 0.5 Gyr. It is concluded that this 19 star subsample of the Wolf 630 moving group sample of 34 stars could represent a dispersed cluster with an ([Fe/H]) = -0.01 {+-} 0.02 and an age of 2.7 {+-} 0.5 Gyr. In addition, chemical abundances of Na and Al in giants are examined for indications of enhancements as observed in field giants of old open clusters; overexcitation/ionization effects are explored in the cooler dwarfs of the sample; and oxygen is derived from the infrared triplet and the forbidden line at {lambda}6300.« less

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

PubMed Central

Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

Cluster analysis of sputum cytokine-high profiles reveals diversity in T(h)2-high asthma patients.

PubMed

Seys, Sven F; Scheers, Hans; Van den Brande, Paul; Marijsse, Gudrun; Dilissen, Ellen; Van Den Bergh, Annelies; Goeminne, Pieter C; Hellings, Peter W; Ceuppens, Jan L; Dupont, Lieven J; Bullens, Dominique M A

2017-02-23

Asthma is characterized by a heterogeneous inflammatory profile and can be subdivided into T(h)2-high and T(h)2-low airway inflammation. Profiling of a broader panel of airway cytokines in large unselected patient cohorts is lacking. Patients (n = 205) were defined as being "cytokine-low/high" if sputum mRNA expression of a particular cytokine was outside the respective 10 th /90 th percentile range of the control group (n = 80). Unsupervised hierarchical clustering was used to determine clusters based on sputum cytokine profiles. Half of patients (n = 108; 52.6%) had a classical T(h)2-high ("IL-4-, IL-5- and/or IL-13-high") sputum cytokine profile. Unsupervised cluster analysis revealed 5 clusters. Patients with an "IL-4- and/or IL-13-high" pattern surprisingly did not cluster but were equally distributed among the 5 clusters. Patients with an "IL-5-, IL-17A-/F- and IL-25- high" profile were restricted to cluster 1 (n = 24) with increased sputum eosinophil as well as neutrophil counts and poor lung function parameters at baseline and 2 years later. Four other clusters were identified: "IL-5-high or IL-10-high" (n = 16), "IL-6-high" (n = 8), "IL-22-high" (n = 25). Cluster 5 (n = 132) consists of patients without "cytokine-high" pattern or patients with only high IL-4 and/or IL-13. We identified 5 unique asthma molecular phenotypes by biological clustering. Type 2 cytokines cluster with non-type 2 cytokines in 4 out of 5 clusters. Unsupervised analysis thus not supports a priori type 2 versus non-type 2 molecular phenotypes. www.clinicaltrials.gov NCT01224938. Registered 18 October 2010.

Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.

PubMed

Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo

2016-07-19

Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .

Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

PubMed

Lee, Hyejoo; Malaspina, Dolores; Ahn, Hongshik; Perrin, Mary; Opler, Mark G; Kleinhaus, Karine; Harlap, Susan; Goetz, Raymond; Antonius, Daniel

2011-05-01

Paternal age related schizophrenia (PARS) has been proposed as a subgroup of schizophrenia with distinct etiology, pathophysiology and symptoms. This study uses a k-means clustering analysis approach to generate hypotheses about differences between PARS and other cases of schizophrenia. We studied PARS (operationally defined as not having any family history of schizophrenia among first and second-degree relatives and fathers' age at birth ≥ 35 years) in a series of schizophrenia cases recruited from a research unit. Data were available on demographic variables, symptoms (Positive and Negative Syndrome Scale; PANSS), cognitive tests (Wechsler Adult Intelligence Scale-Revised; WAIS-R) and olfaction (University of Pennsylvania Smell Identification Test; UPSIT). We conducted a series of k-means clustering analyses to identify clusters of cases containing high concentrations of PARS. Two analyses generated clusters with high concentrations of PARS cases. The first analysis (N=136; PARS=34) revealed a cluster containing 83% PARS cases, in which the patients showed a significant discrepancy between verbal and performance intelligence. The mean paternal and maternal ages were 41 and 33, respectively. The second analysis (N=123; PARS=30) revealed a cluster containing 71% PARS cases, of which 93% were females; the mean age of onset of psychosis, at 17.2, was significantly early. These results strengthen the evidence that PARS cases differ from other patients with schizophrenia. Hypothesis-generating findings suggest that features of PARS may include a discrepancy between verbal and performance intelligence, and in females, an early age of onset. These findings provide a rationale for separating these phenotypes from others in future clinical, genetic and pathophysiologic studies of schizophrenia and in considering responses to treatment. Copyright © 2011 Elsevier B.V. All rights reserved.

Mainshock-Aftershocks Clustering Detection in Volcanic Regions

NASA Astrophysics Data System (ADS)

Garza Giron, R.; Brodsky, E. E.; Prejean, S. G.

2017-12-01

Crustal earthquakes tend to break their general Poissonean process behavior by gathering into two main kinds of seismic bursts: swarms and mainshock-aftershocks sequences. The former is commonly related to volcanic or geothermal processes whereas the latter is a characteristic feature of tectonically driven seismicity. We explore the mainshock-aftershock clustering behavior of different active volcanic regions in Japan and its comparison to non-volcanic regions. We find that aftershock production in volcanoes shows mainshock-aftershocks clustering similar to what is observed in non-volcanic areas. The ratio of volanic areas that cluster in mainshock-aftershocks sequences vs the areas that do not is comparable to the ratio of non-volcanic regions that show clustering vs the ones that do not. Furthermore, the level of production of aftershocks for most volcanic areas where clustering is present seems to be of the same order of magnitude, or slightly higher, as the median of the non-volcanic regions. An interesting example of highly aftershock-productive volcanoes emerges from the 2000 Miyakejima dike intrusion. A big seismic cluster started to build up rapidly in the south-west flank of Miyakejima to later propagate to the north-west towards the Kozushima and Niijima volcanoes. In Miyakejima the seismicity showed a swarm-like signature with a constant earthquake rate, whereas Kozushima and Niijima both had expressions of highly productive mainshock-aftershocks sequences. These findings are surprising given the alternative mechanisms available in volcanic systems for releasing deviatoric strain. We speculate that aftershock behavior might hold a relationship with the rheological properties of the rocks of each system and with the capacity of a system to accumulate or release the internal pressures caused by magmatic or hydrothermal systems.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Frequency-sensitive competitive learning for scalable balanced clustering on high-dimensional hyperspheres.

PubMed

Banerjee, Arindam; Ghosh, Joydeep

2004-05-01

Competitive learning mechanisms for clustering, in general, suffer from poor performance for very high-dimensional (>1000) data because of "curse of dimensionality" effects. In applications such as document clustering, it is customary to normalize the high-dimensional input vectors to unit length, and it is sometimes also desirable to obtain balanced clusters, i.e., clusters of comparable sizes. The spherical kmeans (spkmeans) algorithm, which normalizes the cluster centers as well as the inputs, has been successfully used to cluster normalized text documents in 2000+ dimensional space. Unfortunately, like regular kmeans and its soft expectation-maximization-based version, spkmeans tends to generate extremely imbalanced clusters in high-dimensional spaces when the desired number of clusters is large (tens or more). This paper first shows that the spkmeans algorithm can be derived from a certain maximum likelihood formulation using a mixture of von Mises-Fisher distributions as the generative model, and in fact, it can be considered as a batch-mode version of (normalized) competitive learning. The proposed generative model is then adapted in a principled way to yield three frequency-sensitive competitive learning variants that are applicable to static data and produced high-quality and well-balanced clusters for high-dimensional data. Like kmeans, each iteration is linear in the number of data points and in the number of clusters for all the three algorithms. A frequency-sensitive algorithm to cluster streaming data is also proposed. Experimental results on clustering of high-dimensional text data sets are provided to show the effectiveness and applicability of the proposed techniques. Index Terms-Balanced clustering, expectation maximization (EM), frequency-sensitive competitive learning (FSCL), high-dimensional clustering, kmeans, normalized data, scalable clustering, streaming data, text clustering.

The Integrated Cluster Finder for the ARCHES project

NASA Astrophysics Data System (ADS)

Mints, Alexey; Schwope, Axel; Rosen, Simon; Pineau, François-Xavier; Carrera, Francisco

2017-01-01

Context. Clusters of galaxies are important for cosmology and astrophysics. They may be discovered through either the summed optical/IR radiation originating from their member galaxies or via X-ray emission originating from the hot intracluster medium. X-ray samples are not affected by projection effects but a redshift determination typically needs optical and infrared follow-up to then infer X-ray temperatures and luminosities. Aims: We want to confirm serendipitously discovered X-ray emitting cluster candidates and measure their cosmological redshift through the analysis and exploration of multi-wavelength photometric catalogues. Methods: We developed a tool, the Integrated Cluster Finder (ICF), to search for clusters by determining overdensities of potential member galaxies in optical and infrared catalogues. Based on a spectroscopic meta-catalogue we calibrated colour-redshift relations that combine optical (SDSS) and IR data (UKIDSS, WISE). The tool is used to quantify the overdensity of galaxies against the background via a modified redMaPPer technique and to quantify the confidence of a cluster detection. Results: Cluster finding results are compared to reference catalogues found in the literature. The results agree to within 95-98%. The tool is used to confirm 488 out of 830 cluster candidates drawn from 3XMMe in the footprint of the SDSS and CFHT catalogues. Conclusions: The ICF is a flexible and highly efficient tool to search for galaxy clusters in multiple catalogues and is freely available to the community. It may be used to identify the cluster content in future X-ray catalogues from XMM-Newton and eventually from eROSITA.

Diversity in phenotypic and nutritional traits in vegetable amaranth (Amaranthus tricolor), a nutritionally underutilised crop.

PubMed

Shukla, Sudhir; Bhargava, Atul; Chatterjee, Avijeet; Pandey, Avinash Chandra; Mishra, Brij K

2010-01-15

Assessment of genetic diversity in a crop-breeding programme helps in the identification of diverse parental combinations to create segregating progenies with maximum genetic variability and facilitates introgression of desirable genes from diverse germplasm into the available genetic base. In the present study, 39 strains of vegetable amaranth (Amaranthus tricolor) were evaluated for eight morphological and seven quality traits for two test seasons to study the extent of genetic divergence among the strains. Multivariate analysis showed that the first four principal components contributed 67.55% of the variability. Cluster analysis grouped the strains into six clusters that displayed a wide range of diversity for most of the traits. Cluster analysis has proved to be an effective method in grouping strains that may facilitate effective management and utilisation in crop-breeding programmes. The diverse strains falling in different clusters were identified, which can be utilised in different hybridisation programmes to develop high-foliage-yielding varieties rich in nutritional components. Copyright (c) 2009 Society of Chemical Industry.

A clustered origin for isolated massive stars

NASA Astrophysics Data System (ADS)

Lucas, William E.; Rybak, Matus; Bonnell, Ian A.; Gieles, Mark

2018-03-01

High-mass stars are commonly found in stellar clusters promoting the idea that their formation occurs due to the physical processes linked with a young stellar cluster. It has recently been reported that isolated high-mass stars are present in the Large Magellanic Cloud. Due to their low velocities, it has been argued that these are high-mass stars which formed without a surrounding stellar cluster. In this paper, we present an alternative explanation for the origin of these stars in which they formed in a cluster environment but are subsequently dispersed into the field as their natal cluster is tidally disrupted in a merger with a higher mass cluster. They escape the merged cluster with relatively low velocities typical of the cluster interaction and thus of the larger scale velocity dispersion, similarly to the observed stars. N-body simulations of cluster mergers predict a sizeable population of low-velocity (≤20 km s-1), high-mass stars at distances of >20 pc from the cluster. High-mass clusters in which gas poor mergers are frequent would be expected to commonly have haloes of young stars, including high-mass stars, which were actually formed in a cluster environment.

The use of oxygen in cluster headache treatment worldwide - a survey of the International Headache Society (IHS).

PubMed

Evers, Stefan; Rapoport, Alan

2017-04-01

Background Oxygen is recommended for the treatment of acute cluster headache attacks. However, it is not available worldwide. Methods The International Headache Society performed a survey among its national member societies on the availability and the restrictions for oxygen in the treatment of cluster headache. Results Oxygen is reimbursed in 50% of all countries responding ( n = 22). There are additional restrictions in the reimbursement of the facial mask and with respect to age. Conclusion Oxygen for the treatment of cluster headache attack is not reimbursed worldwide. Headache societies should pressure national/public health authorities to reimburse oxygen for cluster headache in all countries.

A novel symptom cluster analysis among ambulatory HIV/AIDS patients in Uganda.

PubMed

Namisango, Eve; Harding, Richard; Katabira, Elly T; Siegert, Richard J; Powell, Richard A; Atuhaire, Leonard; Moens, Katrien; Taylor, Steve

2015-01-01

Symptom clusters are gaining importance given HIV/AIDS patients experience multiple, concurrent symptoms. This study aimed to: determine clusters of patients with similar symptom combinations; describe symptom combinations distinguishing the clusters; and evaluate the clusters regarding patient socio-demographic, disease and treatment characteristics, quality of life (QOL) and functional performance. This was a cross-sectional study of 302 adult HIV/AIDS outpatients consecutively recruited at two teaching and referral hospitals in Uganda. Socio-demographic and seven-day period symptom prevalence and distress data were self-reported using the Memorial Symptom Assessment Schedule. QOL was assessed using the Medical Outcome Scale and functional performance using the Karnofsky Performance Scale. Symptom clusters were established using hierarchical cluster analysis with squared Euclidean distances using Ward's clustering methods based on symptom occurrence. Analysis of variance compared clusters on mean QOL and functional performance scores. Patient subgroups were categorised based on symptom occurrence rates. Five symptom occurrence clusters were identified: Cluster 1 (n=107), high-low for sensory discomfort and eating difficulties symptoms; Cluster 2 (n=47), high-low for psycho-gastrointestinal symptoms; Cluster 3 (n=71), high for pain and sensory disturbance symptoms; Cluster 4 (n=35), all high for general HIV/AIDS symptoms; and Cluster 5 (n=48), all low for mood-cognitive symptoms. The all high occurrence cluster was associated with worst functional status, poorest QOL scores and highest symptom-associated distress. Use of antiretroviral therapy was associated with all high symptom occurrence rate (Fisher's exact=4, P<0.001). CD4 count group below 200 was associated with the all high occurrence rate symptom cluster (Fisher's exact=41, P<0.001). Symptom clusters have a differential, affect HIV/AIDS patients' self-reported outcomes, with the subgroup experiencing high-symptom occurrence rates having a higher risk of poorer outcomes. Identification of symptom clusters could provide insights into commonly co-occurring symptoms that should be jointly targeted for management in patients with multiple complaints.

Lens models under the microscope: comparison of Hubble Frontier Field cluster magnification maps

NASA Astrophysics Data System (ADS)

Priewe, Jett; Williams, Liliya L. R.; Liesenborgs, Jori; Coe, Dan; Rodney, Steven A.

2017-02-01

Using the power of gravitational lensing magnification by massive galaxy clusters, the Hubble Frontier Fields provide deep views of six patches of the high-redshift Universe. The combination of deep Hubble imaging and exceptional lensing strength has revealed the greatest numbers of multiply-imaged galaxies available to constrain models of cluster mass distributions. However, even with O(100) images per cluster, the uncertainties associated with the reconstructions are not negligible. The goal of this paper is to show the diversity of model magnification predictions. We examine seven and nine mass models of Abell 2744 and MACS J0416, respectively, submitted to the Mikulski Archive for Space Telescopes for public distribution in 2015 September. The dispersion between model predictions increases from 30 per cent at common low magnifications (μ ˜ 2) to 70 per cent at rare high magnifications (μ ˜ 40). MACS J0416 exhibits smaller dispersions than Abell 2744 for 2 < μ < 10. We show that magnification maps based on different lens inversion techniques typically differ from each other by more than their quoted statistical errors. This suggests that some models underestimate the true uncertainties, which are primarily due to various lensing degeneracies. Though the exact mass sheet degeneracy is broken, its generalized counterpart is not broken at least in Abell 2744. Other local degeneracies are also present in both clusters. Our comparison of models is complementary to the comparison of reconstructions of known synthetic mass distributions. By focusing on observed clusters, we can identify those that are best constrained, and therefore provide the clearest view of the distant Universe.

GibbsCluster: unsupervised clustering and alignment of peptide sequences.

PubMed

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-07-03

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

Self-similarity of temperature profiles in distant galaxy clusters: the quest for a universal law

NASA Astrophysics Data System (ADS)

Baldi, A.; Ettori, S.; Molendi, S.; Gastaldello, F.

2012-09-01

Context. We present the XMM-Newton temperature profiles of 12 bright (LX > 4 × 1044 erg s-1) clusters of galaxies at 0.4 < z < 0.9, having an average temperature in the range 5 ≲ kT ≲ 11 keV. Aims: The main goal of this paper is to study for the first time the temperature profiles of a sample of high-redshift clusters, to investigate their properties, and to define a universal law to describe the temperature radial profiles in galaxy clusters as a function of both cosmic time and their state of relaxation. Methods: We performed a spatially resolved spectral analysis, using Cash statistics, to measure the temperature in the intracluster medium at different radii. Results: We extracted temperature profiles for the clusters in our sample, finding that all profiles are declining toward larger radii. The normalized temperature profiles (normalized by the mean temperature T500) are found to be generally self-similar. The sample was subdivided into five cool-core (CC) and seven non cool-core (NCC) clusters by introducing a pseudo-entropy ratio σ = (TIN/TOUT) × (EMIN/EMOUT)-1/3 and defining the objects with σ < 0.6 as CC clusters and those with σ ≥ 0.6 as NCC clusters. The profiles of CC and NCC clusters differ mainly in the central regions, with the latter exhibiting a slightly flatter central profile. A significant dependence of the temperature profiles on the pseudo-entropy ratio σ is detected by fitting a function of r and σ, showing an indication that the outer part of the profiles becomes steeper for higher values of σ (i.e. transitioning toward the NCC clusters). No significant evidence of redshift evolution could be found within the redshift range sampled by our clusters (0.4 < z < 0.9). A comparison of our high-z sample with intermediate clusters at 0.1 < z < 0.3 showed how the CC and NCC cluster temperature profiles have experienced some sort of evolution. This can happen because higher z clusters are at a less advanced stage of their formation and did not have enough time to create a relaxed structure, which is characterized by a central temperature dip in CC clusters and by flatter profiles in NCC clusters. Conclusions: This is the first time that a systematic study of the temperature profiles of galaxy clusters at z > 0.4 has been attempted. We were able to define the closest possible relation to a universal law for the temperature profiles of galaxy clusters at 0.1 < z < 0.9, showing a dependence on both the relaxation state of the clusters and the redshift. Appendix A is only available in electronic form at http://www.aanda.org

High-accuracy identification of incident HIV-1 infections using a sequence clustering based diversity measure.

PubMed

Xia, Xia-Yu; Ge, Meng; Hsi, Jenny H; He, Xiang; Ruan, Yu-Hua; Wang, Zhi-Xin; Shao, Yi-Ming; Pan, Xian-Ming

2014-01-01

Accurate estimates of HIV-1 incidence are essential for monitoring epidemic trends and evaluating intervention efforts. However, the long asymptomatic stage of HIV-1 infection makes it difficult to effectively distinguish incident infections from chronic ones. Current incidence assays based on serology or viral sequence diversity are both still lacking in accuracy. In the present work, a sequence clustering based diversity (SCBD) assay was devised by utilizing the fact that viral sequences derived from each transmitted/founder (T/F) strain tend to cluster together at early stage, and that only the intra-cluster diversity is correlated with the time since HIV-1 infection. The dot-matrix pairwise alignment was used to eliminate the disproportional impact of insertion/deletions (indels) and recombination events, and so was the proportion of clusterable sequences (Pc) as an index to identify late chronic infections with declined viral genetic diversity. Tested on a dataset containing 398 incident and 163 chronic infection cases collected from the Los Alamos HIV database (last modified 2/8/2012), our SCBD method achieved 99.5% sensitivity and 98.8% specificity, with an overall accuracy of 99.3%. Further analysis and evaluation also suggested its performance was not affected by host factors such as the viral subtypes and transmission routes. The SCBD method demonstrated the potential of sequencing based techniques to become useful for identifying incident infections. Its use may be most advantageous for settings with low to moderate incidence relative to available resources. The online service is available at http://www.bioinfo.tsinghua.edu.cn:8080/SCBD/index.jsp.

Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

ERIC Educational Resources Information Center

Younge, Andrew J.

2016-01-01

With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their scientific computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for…

The luminosity function of star clusters in 20 star-forming galaxies based on Hubble legacy archive photometry

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

Whitmore, Bradley C.; Bowers, Ariel S.; Lindsay, Kevin

2014-04-01

Luminosity functions (LFs) have been determined for star cluster populations in 20 nearby (4-30 Mpc), star-forming galaxies based on Advanced Camera for Surveys source lists generated by the Hubble Legacy Archive (HLA). These cluster catalogs provide one of the largest sets of uniform, automatically generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster LF can be approximated by a power law, dN/dL∝L {sup α}, with an average value for α ofmore » –2.37 and rms scatter = 0.18 when using the F814W ('I') band. A comparison of fitting results based on methods that use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum likelihood) method to give slightly more negative values of α for galaxies with steeper LFs. We find that galaxies with high rates of star formation (or equivalently, with the brightest or largest numbers of clusters) have a slight tendency to have shallower values of α. In particular, the Antennae galaxy (NGC 4038/39), a merging system with a relatively high star formation rate (SFR), has the second flattest LF in the sample. A tentative correlation may also be present between Hubble type and values of α, in the sense that later type galaxies (i.e., Sd and Sm) appear to have flatter LFs. Hence, while there do appear to be some weak correlations, the relative similarity in the values of α for a large number of star-forming galaxies suggests that, to first order, the LFs are fairly universal. We examine the bright end of the LFs and find evidence for a downturn, although it only pertains to about 1% of the clusters. Our uniform database results in a small scatter (≈0.4 to 0.5 mag) in the correlation between the magnitude of the brightest cluster (M {sub brightest}) and log of the number of clusters brighter than M{sub I} = –9 (log N). We also examine the magnitude of the brightest cluster versus log SFR for a sample including both dwarf galaxies and ULIRGs. This shows that the correlation extends over roughly six orders of magnitude but with scatter that is larger than for our spiral sample, probably because of the high levels of extinction in many of the LIRGs.« less

Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

PubMed

Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

2015-03-01

Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new potentially true human protein complexes were suggested as candidates for further validation using experimental techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression

PubMed Central

Poole, William; Leinonen, Kalle; Shmulevich, Ilya

2017-01-01

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C. PMID:28170390

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression.

PubMed

Poole, William; Leinonen, Kalle; Shmulevich, Ilya; Knijnenburg, Theo A; Bernard, Brady

2017-02-01

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C.

Gene Cluster Encoding Cholate Catabolism in Rhodococcus spp.

PubMed Central

Wilbrink, Maarten H.; Casabon, Israël; Stewart, Gordon R.; Liu, Jie; van der Geize, Robert; Eltis, Lindsay D.

2012-01-01

Bile acids are highly abundant steroids with important functions in vertebrate digestion. Their catabolism by bacteria is an important component of the carbon cycle, contributes to gut ecology, and has potential commercial applications. We found that Rhodococcus jostii RHA1 grows well on cholate, as well as on its conjugates, taurocholate and glycocholate. The transcriptome of RHA1 growing on cholate revealed 39 genes upregulated on cholate, occurring in a single gene cluster. Reverse transcriptase quantitative PCR confirmed that selected genes in the cluster were upregulated 10-fold on cholate versus on cholesterol. One of these genes, kshA3, encoding a putative 3-ketosteroid-9α-hydroxylase, was deleted and found essential for growth on cholate. Two coenzyme A (CoA) synthetases encoded in the cluster, CasG and CasI, were heterologously expressed. CasG was shown to transform cholate to cholyl-CoA, thus initiating side chain degradation. CasI was shown to form CoA derivatives of steroids with isopropanoyl side chains, likely occurring as degradation intermediates. Orthologous gene clusters were identified in all available Rhodococcus genomes, as well as that of Thermomonospora curvata. Moreover, Rhodococcus equi 103S, Rhodococcus ruber Chol-4 and Rhodococcus erythropolis SQ1 each grew on cholate. In contrast, several mycolic acid bacteria lacking the gene cluster were unable to grow on cholate. Our results demonstrate that the above-mentioned gene cluster encodes cholate catabolism and is distinct from a more widely occurring gene cluster encoding cholesterol catabolism. PMID:23024343

The DAFT/FADA survey. I.Photometric redshifts along lines of sight to clusters in the z=[0.4,0.9] interval

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

Guennou, L.; /Northwestern U. /Marseille, Lab. Astrophys.; Adami, C.

2010-08-01

As a contribution to the understanding of the dark energy concept, the Dark energy American French Team (DAFT, in French FADA) has started a large project to characterize statistically high redshift galaxy clusters, infer cosmological constraints from Weak Lensing Tomography, and understand biases relevant for constraining dark energy and cluster physics in future cluster and cosmological experiments. Aims. The purpose of this paper is to establish the basis of reference for the photo-z determination used in all our subsequent papers, including weak lensing tomography studies. This project is based on a sample of 91 high redshift (z {ge} 0.4), massivemore » ({approx}> 3 x 10{sup 14} M{sub {circle_dot}}) clusters with existing HST imaging, for which we are presently performing complementary multi-wavelength imaging. This allows us in particular to estimate spectral types and determine accurate photometric redshifts for galaxies along the lines of sight to the first ten clusters for which all the required data are available down to a limit of I{sub AB} = 24./24.5 with the LePhare software. The accuracy in redshift is of the order of 0.05 for the range 0.2 {le} z {le} 1.5. We verified that the technique applied to obtain photometric redshifts works well by comparing our results to with previous works. In clusters, photo-z accuracy is degraded for bright absolute magnitudes and for the latest and earliest type galaxies. The photo-z accuracy also only slightly varies as a function of the spectral type for field galaxies. As a consequence, we find evidence for an environmental dependence of the photo-z accuracy, interpreted as the standard used Spectral Energy Distributions being not very well suited to cluster galaxies. Finally, we modeled the LCDCS 0504 mass with the strong arcs detected along this line of sight.« less

The evolution of the cluster optical galaxy luminosity function between z = 0.4 and 0.9 in the DAFT/FADA survey

NASA Astrophysics Data System (ADS)

Martinet, Nicolas; Durret, Florence; Guennou, Loïc; Adami, Christophe; Biviano, Andrea; Ulmer, Melville P.; Clowe, Douglas; Halliday, Claire; Ilbert, Olivier; Márquez, Isabel; Schirmer, Mischa

2015-03-01

Context. There is some disagreement about the abundance of faint galaxies in high-redshift clusters, with contradictory results in the literature arising from studies of the optical galaxy luminosity function (GLF) for small cluster samples. Aims: We compute GLFs for one of the largest medium-to-high-redshift (0.4 ≤ z < 0.9) cluster samples to date in order to probe the abundance of faint galaxies in clusters. We also study how the GLF depends on cluster redshift, mass, and substructure and compare the GLFs of clusters with those of the field. We separately investigate the GLFs of blue and red-sequence (RS) galaxies to understand the evolution of different cluster populations. Methods: We calculated the GLFs for 31 clusters taken from the DAFT/FADA survey in the B,V,R, and I rest-frame bands. We used photometric redshifts computed from BVRIZJ images to constrain galaxy cluster membership. We carried out a detailed estimate of the completeness of our data. We distinguished the red-sequence and blue galaxies using a V - I versus I colour-magnitude diagram. We studied the evolution of these two populations with redshift. We fitted Schechter functions to our stacked GLFs to determine average cluster characteristics. Results: We find that the shapes of our GLFs are similar for the B,V,R, and I bands with a drop at the red GLF faint ends that is more pronounced at high redshift: αred ~ -0.5 at 0.40 ≤ z < 0.65 and αred > 0.1 at 0.65 ≤ z < 0.90. The blue GLFs have a steeper faint end (αblue ~ -1.6) than the red GLFs, which appears to be independent of redshift. For the full cluster sample, blue and red GLFs meet at MV = -20, MR = -20.5, and MI = -20.3. A study of how galaxy types evolve with redshift shows that late-type galaxies appear to become early types between z ~ 0.9 and today. Finally, the faint ends of the red GLFs of more massive clusters appear to be richer than less massive clusters, which is more typical of the lower redshift behaviour. Conclusions: Our results indicate that these clusters form at redshifts higher than z = 0.9 from galaxy structures that already have an established red sequence. Late-type galaxies then appear to evolve into early types, enriching the red sequence between this redshift and today. This effect is consistent with the evolution of the faint-end slope of the red sequence and the galaxy type evolution that we find. Finally, faint galaxies accreted from the field environment at all redshifts might have replaced the blue late-type galaxies that converted into early types, explaining the lack of evolution in the faint-end slopes of the blue GLFs. Appendix is available in electronic form at http://www.aanda.org

Predicting solar radiation based on available weather indicators

NASA Astrophysics Data System (ADS)

Sauer, Frank Joseph

Solar radiation prediction models are complex and require software that is not available for the household investor. The processing power within a normal desktop or laptop computer is sufficient to calculate similar models. This barrier to entry for the average consumer can be fixed by a model simple enough to be calculated by hand if necessary. Solar radiation modeling has been historically difficult to predict and accurate models have significant assumptions and restrictions on their use. Previous methods have been limited to linear relationships, location restrictions, or input data limits to one atmospheric condition. This research takes a novel approach by combining two techniques within the computational limits of a household computer; Clustering and Hidden Markov Models (HMMs). Clustering helps limit the large observation space which restricts the use of HMMs. Instead of using continuous data, and requiring significantly increased computations, the cluster can be used as a qualitative descriptor of each observation. HMMs incorporate a level of uncertainty and take into account the indirect relationship between meteorological indicators and solar radiation. This reduces the complexity of the model enough to be simply understood and accessible to the average household investor. The solar radiation is considered to be an unobservable state that each household will be unable to measure. The high temperature and the sky coverage are already available through the local or preferred source of weather information. By using the next day's prediction for high temperature and sky coverage, the model groups the data and then predicts the most likely range of radiation. This model uses simple techniques and calculations to give a broad estimate for the solar radiation when no other universal model exists for the average household.

Weak lensing study of 16 DAFT/FADA clusters: Substructures and filaments

NASA Astrophysics Data System (ADS)

Martinet, Nicolas; Clowe, Douglas; Durret, Florence; Adami, Christophe; Acebrón, Ana; Hernandez-García, Lorena; Márquez, Isabel; Guennou, Loic; Sarron, Florian; Ulmer, Mel

2016-05-01

While our current cosmological model places galaxy clusters at the nodes of a filament network (the cosmic web), we still struggle to detect these filaments at high redshifts. We perform a weak lensing study for a sample of 16 massive, medium-high redshift (0.4

Neuro- and social-cognitive clustering highlights distinct profiles in adults with anorexia nervosa.

PubMed

Renwick, Beth; Musiat, Peter; Lose, Anna; DeJong, Hannah; Broadbent, Hannah; Kenyon, Martha; Loomes, Rachel; Watson, Charlotte; Ghelani, Shreena; Serpell, Lucy; Richards, Lorna; Johnson-Sabine, Eric; Boughton, Nicky; Treasure, Janet; Schmidt, Ulrike

2015-01-01

This study aimed to explore the neuro- and social-cognitive profile of a consecutive series of adult outpatients with anorexia nervosa (AN) when compared with widely available age and gender matched historical control data. The relationship between performance profiles, clinical characteristics, service utilization, and treatment adherence was also investigated. Consecutively recruited outpatients with a broad diagnosis of AN (restricting subtype AN-R: n = 44, binge-purge subtype AN-BP: n = 33 or Eating Disorder Not Otherwise Specified-AN subtype EDNOS-AN: n = 23) completed a comprehensive set of neurocognitive (set-shifting, central coherence) and social-cognitive measures (Emotional Theory of Mind). Data were subjected to hierarchical cluster analysis and a discriminant function analysis. Three separate, meaningful clusters emerged. Cluster 1 (n = 45) showed overall average to high average neuro- and social- cognitive performance, Cluster 2 (n = 38) showed mixed performance characterized by distinct strengths and weaknesses, and Cluster 3 (n = 17) showed poor overall performance (Autism Spectrum disorder (ASD) like cluster). The three clusters did not differ in terms of eating disorder symptoms, comorbid features or service utilization and treatment adherence. A discriminant function analysis confirmed that the clusters were best characterized by performance in perseveration and set-shifting measures. The findings suggest that considerable neuro- and social-cognitive heterogeneity exists in patients with AN, with a subset showing ASD-like features. The value of this method of profiling in predicting longer term patient outcomes and in guiding development of etiologically targeted treatments remains to be seen. © 2014 Wiley Periodicals, Inc.

MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC–MS metabolomic datasets

PubMed Central

Edmands, William M. B.; Barupal, Dinesh K.; Scalbert, Augustin

2015-01-01

Summary: MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker—MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R). Availability and implementation: All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC–MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository. Contact: ScalbertA@iarc.fr PMID:25348215

High prevalence of cardiometabolic risk factors in young employees of Information Technology industry.

PubMed

Limaye, Tejas Y; Kulkarni, Ravindra L; Deokar, Manisha R; Kumaran, Kalyanaraman

2016-01-01

We assessed the burden of cardiometabolic risk factors in Information Technology (IT) employees as they are exposed to adverse lifestyle. In this cross-sectional study, health records were obtained from two IT industries in Pune. Prevalence of cardiometabolic risk factors [hyperglycemia, high blood pressure (BP), hypertriglyceridemia, high low-density lipoprotein (LDL)-cholesterol, low high-density lipoprotein (HDL)-cholesterol, and overweight/obesity] was determined using standard cutoffs. We also examined clustering of risk factors (≥two risk factors). Data were available on 1,350 of 5,800 employees (mean age: 33 ± 6 years, 78% men). Prevalence of diabetes and hypertension was 2.5% and 13.5%, respectively. Prevalence of prediabetes, borderline high BP, hypertriglyceridemia, high LDL-cholesterol, low HDL-cholesterol, and overweight/obesity was 6.5%, 20.3%, 21%, 22.1%, 70.1%, and 51.4%, respectively. Risk factor clustering was observed in 63.5% that increased with age (P < 0.001). Given the high burden of risk factors at relatively young age, spreading awareness and promoting healthy lifestyle through workplace interventions are warranted.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Behavioral Health Risk Profiles of Undergraduate University Students in England, Wales, and Northern Ireland: A Cluster Analysis.

PubMed

El Ansari, Walid; Ssewanyana, Derrick; Stock, Christiane

2018-01-01

Limited research has explored clustering of lifestyle behavioral risk factors (BRFs) among university students. This study aimed to explore clustering of BRFs, composition of clusters, and the association of the clusters with self-rated health and perceived academic performance. We assessed (BRFs), namely tobacco smoking, physical inactivity, alcohol consumption, illicit drug use, unhealthy nutrition, and inadequate sleep, using a self-administered general Student Health Survey among 3,706 undergraduates at seven UK universities. A two-step cluster analysis generated: Cluster 1 (the high physically active and health conscious) with very high health awareness/consciousness, good nutrition, and physical activity (PA), and relatively low alcohol, tobacco, and other drug (ATOD) use. Cluster 2 (the abstinent) had very low ATOD use, high health awareness, good nutrition, and medium high PA. Cluster 3 (the moderately health conscious) included the highest regard for healthy eating, second highest fruit/vegetable consumption, and moderately high ATOD use. Cluster 4 (the risk taking) showed the highest ATOD use, were the least health conscious, least fruit consuming, and attached the least importance on eating healthy. Compared to the healthy cluster (Cluster 1), students in other clusters had lower self-rated health, and particularly, students in the risk taking cluster (Cluster 4) reported lower academic performance. These associations were stronger for men than for women. Of the four clusters, Cluster 4 had the youngest students. Our results suggested that prevention among university students should address multiple BRFs simultaneously, with particular focus on the younger students.

An automated workflow for parallel processing of large multiview SPIM recordings

PubMed Central

Schmied, Christopher; Steinbach, Peter; Pietzsch, Tobias; Preibisch, Stephan; Tomancak, Pavel

2016-01-01

Summary: Selective Plane Illumination Microscopy (SPIM) allows to image developing organisms in 3D at unprecedented temporal resolution over long periods of time. The resulting massive amounts of raw image data requires extensive processing interactively via dedicated graphical user interface (GUI) applications. The consecutive processing steps can be easily automated and the individual time points can be processed independently, which lends itself to trivial parallelization on a high performance computing (HPC) cluster. Here, we introduce an automated workflow for processing large multiview, multichannel, multiillumination time-lapse SPIM data on a single workstation or in parallel on a HPC cluster. The pipeline relies on snakemake to resolve dependencies among consecutive processing steps and can be easily adapted to any cluster environment for processing SPIM data in a fraction of the time required to collect it. Availability and implementation: The code is distributed free and open source under the MIT license http://opensource.org/licenses/MIT. The source code can be downloaded from github: https://github.com/mpicbg-scicomp/snakemake-workflows. Documentation can be found here: http://fiji.sc/Automated_workflow_for_parallel_Multiview_Reconstruction. Contact: schmied@mpi-cbg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26628585

Turbulence in the Intracluster Medium: XMM-Newton legacy

NASA Astrophysics Data System (ADS)

Pinto, C.; Fabian, A.; Sanders, J.; De Plaa, J.

2017-10-01

The kinematics structure of the Intracluster Medium (ICM) in clusters of galaxies is heir of their past evolution. AGN feedback, sloshing of gas within the potential well, and galaxy mergers are thought to generate turbulence of several hundred km/s into the ICM. Accurate measurements of velocity widths provide the means to understand the effects of these energetic phenomena onto the evolution of the clusters. In this talk I will review our recent measurements of turbulence using the high-resolution grating and microcalorimeter spectrometers on board XMM-Newton and Hitomi, respectively. Most recently, we have produced the largest XMM-Newton/RGS grating catalogue totalling about a hundred objects, which merge the recent CHEERS campaign and the efforts of the last decade as well as the newest observations of clusters and groups of galaxies. This catalogue includes all high-quality grating spectra publicly available by January 2017 and provides the XMM-Newton legacy for the future work. In this talk, I will discuss the first results with particular focus on the measurements of velocity broadening and the new constraints on turbulence.

Perceptions of firms within a cluster regarding the cluster's function and success: Amish furniture manufacturing in Ohio

Treesearch

Matthew S. Bumgardner; Gary W. Graham; P. Charles Goebel; Robert L. Romig

2011-01-01

The Amish-based furniture manufacturing cluster in and around Holmes County, OH, is home to some 400 shops and has become an important regional driver of demand for hardwood products. The cluster has expanded even as the broader domestic furniture industry has declined. Clustering dynamics are seen as important to the success, but little information has been available...

MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics.

PubMed

The, Matthew; Käll, Lukas

2016-03-04

Shotgun proteomics experiments generate large amounts of fragment spectra as primary data, normally with high redundancy between and within experiments. Here, we have devised a clustering technique to identify fragment spectra stemming from the same species of peptide. This is a powerful alternative method to traditional search engines for analyzing spectra, specifically useful for larger scale mass spectrometry studies. As an aid in this process, we propose a distance calculation relying on the rarity of experimental fragment peaks, following the intuition that peaks shared by only a few spectra offer more evidence than peaks shared by a large number of spectra. We used this distance calculation and a complete-linkage scheme to cluster data from a recent large-scale mass spectrometry-based study. The clusterings produced by our method have up to 40% more identified peptides for their consensus spectra compared to those produced by the previous state-of-the-art method. We see that our method would advance the construction of spectral libraries as well as serve as a tool for mining large sets of fragment spectra. The source code and Ubuntu binary packages are available at https://github.com/statisticalbiotechnology/maracluster (under an Apache 2.0 license).

Atomistic clustering-ordering and high-strain deformation of an Al0.1CrCoFeNi high-entropy alloy

PubMed Central

Sharma, Aayush; Singh, Prashant; Johnson, Duane D.; Liaw, Peter K.; Balasubramanian, Ganesh

2016-01-01

Computational investigations of structural, chemical, and deformation behavior in high-entropy alloys (HEAs), which possess notable mechanical strength, have been limited due to the absence of applicable force fields. To extend investigations, we propose a set of intermolecular potential parameters for a quinary Al-Cr-Co-Fe-Ni alloy, using the available ternary Embedded Atom Method and Lennard-Jones potential in classical molecular-dynamics simulations. The simulation results are validated by a comparison to first-principles Korringa-Kohn-Rostoker (KKR) - Coherent Potential Approximation (CPA) [KKR-CPA] calculations for the HEA structural properties (lattice constants and bulk moduli), relative stability, pair probabilities, and high-temperature short-range ordering. The simulation (MD)-derived properties are in quantitative agreement with KKR-CPA calculations (first-principles) and experiments. We study AlxCrCoFeNi for Al ranging from 0 ≤ x ≤2 mole fractions, and find that the HEA shows large chemical clustering over a wide temperature range for x < 0.5. At various temperatures high-strain compression promotes atomistic rearrangements in Al0.1CrCoFeNi, resulting in a clustering-to-ordering transition that is absent for tensile loading. Large fluctuations under stress, and at higher temperatures, are attributed to the thermo-plastic instability in Al0.1CrCoFeNi. PMID:27498807

Atomistic clustering-ordering and high-strain deformation of an Al 0.1CrCoFeNi high-entropy alloy

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

Sharma, Aayush; Singh, Prashant; Johnson, Duane D.

2016-08-08

Here, computational investigations of structural, chemical, and deformation behavior in high-entropy alloys (HEAs), which possess notable mechanical strength, have been limited due to the absence of applicable force fields. To extend investigations, we propose a set of intermolecular potential parameters for a quinary Al-Cr-Co-Fe-Ni alloy, using the available ternary Embedded Atom Method and Lennard-Jones potential in classical molecular-dynamics simulations. The simulation results are validated by a comparison to first-principles Korringa-Kohn-Rostoker (KKR) - Coherent Potential Approximation (CPA) [KKR-CPA] calculations for the HEA structural properties (lattice constants and bulk moduli), relative stability, pair probabilities, and high-temperature short-range ordering. The simulation (MD)-derived propertiesmore » are in quantitative agreement with KKR-CPA calculations (first-principles) and experiments. We study Al xCrCoFeNi for Al ranging from 0 ≤ x ≤2 mole fractions, and find that the HEA shows large chemical clustering over a wide temperature range for x < 0.5. At various temperatures high-strain compression promotes atomistic rearrangements in Al 0.1CrCoFeNi, resulting in a clustering-to-ordering transition that is absent for tensile loading. Large fluctuations under stress, and at higher temperatures, are attributed to the thermo-plastic instability in Al 0.1CrCoFeNi.« less

Mean-cluster approach indicates cell sorting time scales are determined by collective dynamics

NASA Astrophysics Data System (ADS)

Beatrici, Carine P.; de Almeida, Rita M. C.; Brunnet, Leonardo G.

2017-03-01

Cell migration is essential to cell segregation, playing a central role in tissue formation, wound healing, and tumor evolution. Considering random mixtures of two cell types, it is still not clear which cell characteristics define clustering time scales. The mass of diffusing clusters merging with one another is expected to grow as td /d +2 when the diffusion constant scales with the inverse of the cluster mass. Cell segregation experiments deviate from that behavior. Explanations for that could arise from specific microscopic mechanisms or from collective effects, typical of active matter. Here we consider a power law connecting diffusion constant and cluster mass to propose an analytic approach to model cell segregation where we explicitly take into account finite-size corrections. The results are compared with active matter model simulations and experiments available in the literature. To investigate the role played by different mechanisms we considered different hypotheses describing cell-cell interaction: differential adhesion hypothesis and different velocities hypothesis. We find that the simulations yield normal diffusion for long time intervals. Analytic and simulation results show that (i) cluster evolution clearly tends to a scaling regime, disrupted only at finite-size limits; (ii) cluster diffusion is greatly enhanced by cell collective behavior, such that for high enough tendency to follow the neighbors, cluster diffusion may become independent of cluster size; (iii) the scaling exponent for cluster growth depends only on the mass-diffusion relation, not on the detailed local segregation mechanism. These results apply for active matter systems in general and, in particular, the mechanisms found underlying the increase in cell sorting speed certainly have deep implications in biological evolution as a selection mechanism.

ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.

PubMed

Oluwadare, Oluwatosin; Cheng, Jianlin

2017-11-14

With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function. Here, we formulate the TAD identification problem as an unsupervised machine learning (clustering) problem, and develop a new TAD identification method called ClusterTAD. We introduce a novel method to represent chromosomal contacts as features to be used by the clustering algorithm. Our results show that ClusterTAD can accurately predict the TADs on a simulated Hi-C data. Our method is also largely complementary and consistent with existing methods on the real Hi-C datasets of two mouse cells. The validation with the chromatin immunoprecipitation (ChIP) sequencing (ChIP-Seq) data shows that the domain boundaries identified by ClusterTAD have a high enrichment of CTCF binding sites, promoter-related marks, and enhancer-related histone modifications. As ClusterTAD is based on a proven clustering approach, it opens a new avenue to apply a large array of clustering methods developed in the machine learning field to the TAD identification problem. The source code, the results, and the TADs generated for the simulated and real Hi-C datasets are available here: https://github.com/BDM-Lab/ClusterTAD .

HIFLUGCS: X-ray luminosity-dynamical mass relation and its implications for mass calibrations with the SPIDERS and 4MOST surveys

NASA Astrophysics Data System (ADS)

Zhang, Yu-Ying; Reiprich, Thomas H.; Schneider, Peter; Clerc, Nicolas; Merloni, Andrea; Schwope, Axel; Borm, Katharina; Andernach, Heinz; Caretta, César A.; Wu, Xiang-Ping

2017-03-01

We present the relation of X-ray luminosity versus dynamical mass for 63 nearby clusters of galaxies in a flux-limited sample, the HIghest X-ray FLUx Galaxy Cluster Sample (HIFLUGCS, consisting of 64 clusters). The luminosity measurements are obtained based on 1.3 Ms of clean XMM-Newton data and ROSAT pointed observations. The masses are estimated using optical spectroscopic redshifts of 13647 cluster galaxies in total. We classify clusters into disturbed and undisturbed based on a combination of the X-ray luminosity concentration and the offset between the brightest cluster galaxy and X-ray flux-weighted center. Given sufficient numbers (I.e., ≥45) of member galaxies when the dynamical masses are computed, the luminosity versus mass relations agree between the disturbed and undisturbed clusters. The cool-core clusters still dominate the scatter in the luminosity versus mass relation even when a core-corrected X-ray luminosity is used, which indicates that the scatter of this scaling relation mainly reflects the structure formation history of the clusters. As shown by the clusters with only few spectroscopically confirmed members, the dynamical masses can be underestimated and thus lead to a biased scaling relation. To investigate the potential of spectroscopic surveys to follow up high-redshift galaxy clusters or groups observed in X-ray surveys for the identifications and mass calibrations, we carried out Monte Carlo resampling of the cluster galaxy redshifts and calibrated the uncertainties of the redshift and dynamical mass estimates when only reduced numbers of galaxy redshifts per cluster are available. The resampling considers the SPIDERS and 4MOST configurations, designed for the follow-up of the eROSITA clusters, and was carried out for each cluster in the sample at the actual cluster redshift as well as at the assigned input cluster redshifts of 0.2, 0.4, 0.6, and 0.8. To follow up very distant clusters or groups, we also carried out the mass calibration based on the resampling with only ten redshifts per cluster, and redshift calibration based on the resampling with only five and ten redshifts per cluster, respectively. Our results demonstrate the power of combining upcoming X-ray and optical spectroscopic surveys for mass calibration of clusters. The scatter in the dynamical mass estimates for the clusters with at least ten members is within 50%.

Strong Lensing Analysis of the Galaxy Cluster MACS J1319.9+7003 and the Discovery of a Shell Galaxy

NASA Astrophysics Data System (ADS)

Zitrin, Adi

2017-01-01

We present a strong-lensing (SL) analysis of the galaxy cluster MACS J1319.9+7003 (z = 0.33, also known as Abell 1722), as part of our ongoing effort to analyze massive clusters with archival Hubble Space Telescope (HST) imaging. We spectroscopically measured with Keck/Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE) two galaxies multiply imaged by the cluster. Our analysis reveals a modest lens, with an effective Einstein radius of {θ }e(z=2)=12+/- 1\\prime\\prime , enclosing 2.1+/- 0.3× {10}13 M⊙. We briefly discuss the SL properties of the cluster, using two different modeling techniques (see the text for details), and make the mass models publicly available (ftp://wise-ftp.tau.ac.il/pub/adiz/MACS1319/). Independently, we identified a noteworthy, young shell galaxy (SG) system forming around two likely interacting cluster members, 20″ north of the brightest cluster galaxy. SGs are rare in galaxy clusters, and indeed, a simple estimate reveals that they are only expected in roughly one in several dozen, to several hundred, massive galaxy clusters (the estimate can easily change by an order of magnitude within a reasonable range of characteristic values relevant for the calculation). Taking advantage of our lens model best-fit, mass-to-light scaling relation for cluster members, we infer that the total mass of the SG system is ˜ 1.3× {10}11 {M}⊙ , with a host-to-companion mass ratio of about 10:1. Despite being rare in high density environments, the SG constitutes an example to how stars of cluster galaxies are efficiently redistributed to the intra-cluster medium. Dedicated numerical simulations for the observed shell configuration, perhaps aided by the mass model, might cast interesting light on the interaction history and properties of the two galaxies. An archival HST search in galaxy cluster images can reveal more such systems.

Phosphorus-mobilization ecosystem engineering: the roles of cluster roots and carboxylate exudation in young P-limited ecosystems

PubMed Central

Lambers, Hans; Bishop, John G.; Hopper, Stephen D.; Laliberté, Etienne; Zúñiga-Feest, Alejandra

2012-01-01

Background Carboxylate-releasing cluster roots of Proteaceae play a key role in acquiring phosphorus (P) from ancient nutrient-impoverished soils in Australia. However, cluster roots are also found in Proteaceae on young, P-rich soils in Chile where they allow P acquisition from soils that strongly sorb P. Scope Unlike Proteaceae in Australia that tend to proficiently remobilize P from senescent leaves, Chilean Proteaceae produce leaf litter rich in P. Consequently, they may act as ecosystem engineers, providing P for plants without specialized roots to access sorbed P. We propose a similar ecosystem-engineering role for species that release large amounts of carboxylates in other relatively young, strongly P-sorbing substrates, e.g. young acidic volcanic deposits and calcareous dunes. Many of these species also fix atmospheric nitrogen and release nutrient-rich litter, but their role as ecosystem engineers is commonly ascribed only to their diazotrophic nature. Conclusions We propose that the P-mobilizing capacity of Proteaceae on young soils, which contain an abundance of P, but where P is poorly available, in combination with inefficient nutrient remobilization from senescing leaves allows these species to function as ecosystem engineers. We suggest that diazotrophic species that colonize young soils with strong P-sorption potential should be considered for their positive effect on P availability, as well as their widely accepted role in nitrogen fixation. Their P-mobilizing activity possibly also enhances their nitrogen-fixing capacity. These diazotrophic species may therefore facilitate the establishment and growth of species with less-efficient P-uptake strategies on more-developed soils with low P availability through similar mechanisms. We argue that the significance of cluster roots and high carboxylate exudation in the development of young ecosystems is probably far more important than has been envisaged thus far. PMID:22700940

Phosphorus-mobilization ecosystem engineering: the roles of cluster roots and carboxylate exudation in young P-limited ecosystems.

PubMed

Lambers, Hans; Bishop, John G; Hopper, Stephen D; Laliberté, Etienne; Zúñiga-Feest, Alejandra

2012-07-01

Carboxylate-releasing cluster roots of Proteaceae play a key role in acquiring phosphorus (P) from ancient nutrient-impoverished soils in Australia. However, cluster roots are also found in Proteaceae on young, P-rich soils in Chile where they allow P acquisition from soils that strongly sorb P. Unlike Proteaceae in Australia that tend to proficiently remobilize P from senescent leaves, Chilean Proteaceae produce leaf litter rich in P. Consequently, they may act as ecosystem engineers, providing P for plants without specialized roots to access sorbed P. We propose a similar ecosystem-engineering role for species that release large amounts of carboxylates in other relatively young, strongly P-sorbing substrates, e.g. young acidic volcanic deposits and calcareous dunes. Many of these species also fix atmospheric nitrogen and release nutrient-rich litter, but their role as ecosystem engineers is commonly ascribed only to their diazotrophic nature. We propose that the P-mobilizing capacity of Proteaceae on young soils, which contain an abundance of P, but where P is poorly available, in combination with inefficient nutrient remobilization from senescing leaves allows these species to function as ecosystem engineers. We suggest that diazotrophic species that colonize young soils with strong P-sorption potential should be considered for their positive effect on P availability, as well as their widely accepted role in nitrogen fixation. Their P-mobilizing activity possibly also enhances their nitrogen-fixing capacity. These diazotrophic species may therefore facilitate the establishment and growth of species with less-efficient P-uptake strategies on more-developed soils with low P availability through similar mechanisms. We argue that the significance of cluster roots and high carboxylate exudation in the development of young ecosystems is probably far more important than has been envisaged thus far.

Adapted managerial mathematical model to study the functions and interactions between enterprises in high-tech cluster

NASA Astrophysics Data System (ADS)

Anguelov, Kiril P.; Kaynakchieva, Vesela G.

2017-12-01

The aim of the current study is to research and analyze Adapted managerial mathematical model to study the functions and interactions between enterprises in high-tech cluster, and his approbation in given high-tech cluster; to create high-tech cluster, taking into account the impact of relationships between individual units in the cluster-Leading Enterprises, network of Enterprises subcontractors, economic infrastructure.

High Performance Computer Cluster for Theoretical Studies of Roaming in Chemical Reactions

DTIC Science & Technology

2016-08-30

High-performance Computer Cluster for Theoretical Studies of Roaming in Chemical Reactions A dedicated high-performance computer cluster was...SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Computer cluster ...peer-reviewed journals: Final Report: High-performance Computer Cluster for Theoretical Studies of Roaming in Chemical Reactions Report Title A dedicated

Clustering the Orion B giant molecular cloud based on its molecular emission

NASA Astrophysics Data System (ADS)

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Context. Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims: We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods: We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional probability density function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results: A clustering analysis based only on the J = 1-0 lines of three isotopologues of CO proves sufficient to reveal distinct density/column density regimes (nH 100 cm-3, 500 cm-3, and >1000 cm-3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1-0 line of HCO+ and the N = 1-0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH 7 × 103 cm-3, 4 × 104 cm-3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1-0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Conclusions: Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers. Data products associated with this paper are available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/610/A12 and at http://www.iram.fr/ pety/ORION-B

Downregulation of miR-99a/let-7c/miR-125b miRNA cluster predicts clinical outcome in patients with unresected malignant pleural mesothelioma

PubMed Central

Genova, Carlo; Mora, Marco; Dal Bello, Maria Giovanna; Vanni, Irene; Alama, Angela; Rijavec, Erika; Biello, Federica; Barletta, Giulia; Merlo, Domenico Franco; Valentino, Alessandro; Ferro, Paola; Ravetti, Gian Luigi; Stigliani, Sara; Vigani, Antonella; Fedeli, Franco; Beer, David G.; Roncella, Silvio; Grossi, Francesco

2017-01-01

Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal overall survival (OS) and to date no molecular markers are available to guide patient management. This study aimed to identify a prognostic miRNA signature in MPM patients who did not undergo tumor resection. Whole miRNA profiling using a microarray platform was performed using biopsies on 27 unresected MPM patients with distinct clinical outcome: 15 patients had short survival (OS<12 months) and 12 patients had long survival (OS>36 months). Three prognostic miRNAs (mir-99a, let-7c, and miR-125b) encoded at the same cluster (21q21) were selected for further validation and tested on publicly available miRNA sequencing data from 72 MPM patients with survival data. A risk model was built based on these 3 miRNAs that was validated by quantitative PCR in an independent set of 30 MPM patients. High-risk patients had shorter median OS (7.6 months) as compared with low-risk patients (median not reached). In the multivariate Cox model, a high-risk score was independently associated with shorter OS (HR=3.14; 95% CI, 1.18–8.34; P=0.022). Our study identified that the downregulation of the miR-99a/let-7/miR-125b miRNA cluster predicts poor outcome in unresected MPM. PMID:28978143

A Legacy Archive Program Providing Optical/NIR-selected Multiwavelength Catalogs and High-level Science Products of the HST Frontier Fields

NASA Astrophysics Data System (ADS)

Marchesini, Danilo

2015-10-01

We propose to construct public multi-wavelength and value-added catalogs for the HST Frontier Fields (HFF), a multi-cycle imaging program of 6 deep fields centered on strong lensing galaxy clusters and 6 deep blank fields. Whereas the main goal of the HFF is to explore the first billion years of galaxy evolution, this dataset has a unique combination of area and depth that will propel forward our knowledge of galaxy evolution down to and including the foreground cluster redshift (z=0.3-0.5). However, such scientific exploitation requires high-quality, homogeneous, multi-wavelength (from the UV to the mid-infrared) photometric catalogs, supplemented by photometric redshifts, rest-frame colors and luminosities, stellar masses, star-formation rates, and structural parameters. We will use our expertise and existing infrastructure - created for the 3D-HST and CANDELS projects - to build such a data product for the 12 fields of the HFF, using all available imaging data (from HST, Spitzer, and ground-based facilities) as well as all available HST grism data (e.g., GLASS). A broad range of research topics will benefit from such a public database, including but not limited to the faint end of the cluster mass function, the field mass function at z>2, and the build-up of the quiescent population at z>4. In addition, our work will provide an essential basis for follow-up studies and future planning with, for example, ALMA and JWST.

The Rényi divergence enables accurate and precise cluster analysis for localisation microscopy.

PubMed

Staszowska, Adela D; Fox-Roberts, Patrick; Hirvonen, Liisa M; Peddie, Christopher J; Collinson, Lucy M; Jones, Gareth E; Cox, Susan

2018-06-01

Clustering analysis is a key technique for quantitatively characterising structures in localisation microscopy images. To build up accurate information about biological structures, it is critical that the quantification is both accurate (close to the ground truth) and precise (has small scatter and is reproducible). Here we describe how the Rényi divergence can be used for cluster radius measurements in localisation microscopy data. We demonstrate that the Rényi divergence can operate with high levels of background and provides results which are more accurate than Ripley's functions, Voronoi tesselation or DBSCAN. Data supporting this research will be made accessible via a web link. Software codes developed for this work can be accessed via http://coxphysics.com/Renyi_divergence_software.zip. Implemented in C ++. Correspondence and requests for materials can be also addressed to the corresponding author. adela.staszowska@gmail.com or susan.cox@kcl.ac.uk. Supplementary data are available at Bioinformatics online.

Iridium Clusters Encapsulated in Carbon Nanospheres as Nanocatalysts for Methylation of (Bio)Alcohols.

PubMed

Liu, Qiang; Xu, Guoqiang; Wang, Zhendong; Liu, Xiaoran; Wang, Xicheng; Dong, Linlin; Mu, Xindong; Liu, Huizhou

2017-12-08

C-H methylation is an attractive chemical transformation for C-C bonds construction in organic chemistry, yet efficient methylation of readily available (bio)alcohols in water using methanol as sustainable C1 feedstock is limited. Herein, iridium nanocatalysts encapsulated in yolk-shell-structured mesoporous carbon nanospheres (Ir@YSMCNs) were synthesized for this transformation. Monodispersed Ir clusters (ca. 1.0 nm) were encapsulated in situ and spatially isolated within YSMCNs by a silica-assisted sol-gel emulsion strategy. A selection of (bio)alcohols (19 examples) was selectively methylated in aqueous phase with good-to-high yields over the developed Ir@YSMCNs. The improved catalytic efficiencies in terms of activity and selectivity together with the good stability and recyclability were contributable to the ultrasmall Ir clusters with oxidation chemical state as a consequence of the confinement effect of YSMCNs with interconnected nanostructures. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A comprehensive comparative test of seven widely used spectral synthesis models against multi-band photometry of young massive-star clusters

NASA Astrophysics Data System (ADS)

Wofford, A.; Charlot, S.; Bruzual, G.; Eldridge, J. J.; Calzetti, D.; Adamo, A.; Cignoni, M.; de Mink, S. E.; Gouliermis, D. A.; Grasha, K.; Grebel, E. K.; Lee, J. C.; Östlin, G.; Smith, L. J.; Ubeda, L.; Zackrisson, E.

2016-04-01

We test the predictions of spectral synthesis models based on seven different massive-star prescriptions against Legacy ExtraGalactic UV Survey (LEGUS) observations of eight young massive clusters in two local galaxies, NGC 1566 and NGC 5253, chosen because predictions of all seven models are available at the published galactic metallicities. The high angular resolution, extensive cluster inventory, and full near-ultraviolet to near-infrared photometric coverage make the LEGUS data set excellent for this study. We account for both stellar and nebular emission in the models and try two different prescriptions for attenuation by dust. From Bayesian fits of model libraries to the observations, we find remarkably low dispersion in the median E(B - V) (˜0.03 mag), stellar masses (˜104 M⊙), and ages (˜1 Myr) derived for individual clusters using different models, although maximum discrepancies in these quantities can reach 0.09 mag and factors of 2.8 and 2.5, respectively. This is for ranges in median properties of 0.05-0.54 mag, 1.8-10 × 104 M⊙, and 1.6-40 Myr spanned by the clusters in our sample. In terms of best fit, the observations are slightly better reproduced by models with interacting binaries and least well reproduced by models with single rotating stars. Our study provides a first quantitative estimate of the accuracies and uncertainties of the most recent spectral synthesis models of young stellar populations, demonstrates the good progress of models in fitting high-quality observations, and highlights the needs for a larger cluster sample and more extensive tests of the model parameter space.

Pep2Path: automated mass spectrometry-guided genome mining of peptidic natural products.

PubMed

Medema, Marnix H; Paalvast, Yared; Nguyen, Don D; Melnik, Alexey; Dorrestein, Pieter C; Takano, Eriko; Breitling, Rainer

2014-09-01

Nonribosomally and ribosomally synthesized bioactive peptides constitute a source of molecules of great biomedical importance, including antibiotics such as penicillin, immunosuppressants such as cyclosporine, and cytostatics such as bleomycin. Recently, an innovative mass-spectrometry-based strategy, peptidogenomics, has been pioneered to effectively mine microbial strains for novel peptidic metabolites. Even though mass-spectrometric peptide detection can be performed quite fast, true high-throughput natural product discovery approaches have still been limited by the inability to rapidly match the identified tandem mass spectra to the gene clusters responsible for the biosynthesis of the corresponding compounds. With Pep2Path, we introduce a software package to fully automate the peptidogenomics approach through the rapid Bayesian probabilistic matching of mass spectra to their corresponding biosynthetic gene clusters. Detailed benchmarking of the method shows that the approach is powerful enough to correctly identify gene clusters even in data sets that consist of hundreds of genomes, which also makes it possible to match compounds from unsequenced organisms to closely related biosynthetic gene clusters in other genomes. Applying Pep2Path to a data set of compounds without known biosynthesis routes, we were able to identify candidate gene clusters for the biosynthesis of five important compounds. Notably, one of these clusters was detected in a genome from a different subphylum of Proteobacteria than that in which the molecule had first been identified. All in all, our approach paves the way towards high-throughput discovery of novel peptidic natural products. Pep2Path is freely available from http://pep2path.sourceforge.net/, implemented in Python, licensed under the GNU General Public License v3 and supported on MS Windows, Linux and Mac OS X.

Stellar abundances and ages for metal-rich Milky Way globular clusters. Stellar parameters and elemental abundances for 9 HB stars in NGC 6352

NASA Astrophysics Data System (ADS)

Feltzing, S.; Primas, F.; Johnson, R. A.

2009-01-01

Context: Metal-rich globular clusters provide important tracers of the formation of our Galaxy. Moreover, and not less important, they are very important calibrators for the derivation of properties of extra-galactic metal-rich stellar populations. Nonetheless, only a few of the metal-rich globular clusters in the Milky Way have been studied using high-resolution stellar spectra to derive elemental abundances. Additionally, Rosenberg et al. identified a small group of metal-rich globular clusters that appeared to be about 2 billion years younger than the bulk of the Milky Way globular clusters. However, it is unclear if like is compared with like in this dataset as we do not know the enhancement of α-elements in the clusters and the amount of α-elements is well known to influence the derivation of ages for globular clusters. Aims: We derive elemental abundances for the metal-rich globular cluster NGC 6352 and we present our methods to be used in up-coming studies of other metal-rich globular clusters. Methods: We present a study of elemental abundances for α- and iron-peak elements for nine HB stars in the metal-rich globular cluster NGC 6352. The elemental abundances are based on high-resolution, high signal-to-noise spectra obtained with the UVES spectrograph on VLT. The elemental abundances have been derived using standard LTE calculations and stellar parameters have been derived from the spectra themselves by requiring ionizational as well as excitational equilibrium. Results: We find that NGC 6352 has [Fe/H] = -0.55, is enhanced in the α-elements to about +0.2 dex for Ca, Si, and Ti relative to Fe. For the iron-peak elements we find solar values. Based on the spectroscopically derived stellar parameters we find that an E(B-V) = 0.24 and (m-M) ≃ 14.05 better fits the data than the nominal values. An investigation of log gf-values for suitable Fe i lines lead us to the conclusion that the commonly used correction to the May et al. (1974) data should not be employed. Full Table [see full text] are also only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/493/913 Based on observations collected at the European Southern Observatory, Chile, ESO No. 69.B-0467.

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

PubMed

Le Meur, Nolwenn

2013-02-01

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

birgHPC: creating instant computing clusters for bioinformatics and molecular dynamics.

PubMed

Chew, Teong Han; Joyce-Tan, Kwee Hong; Akma, Farizuwana; Shamsir, Mohd Shahir

2011-05-01

birgHPC, a bootable Linux Live CD has been developed to create high-performance clusters for bioinformatics and molecular dynamics studies using any Local Area Network (LAN)-networked computers. birgHPC features automated hardware and slots detection as well as provides a simple job submission interface. The latest versions of GROMACS, NAMD, mpiBLAST and ClustalW-MPI can be run in parallel by simply booting the birgHPC CD or flash drive from the head node, which immediately positions the rest of the PCs on the network as computing nodes. Thus, a temporary, affordable, scalable and high-performance computing environment can be built by non-computing-based researchers using low-cost commodity hardware. The birgHPC Live CD and relevant user guide are available for free at http://birg1.fbb.utm.my/birghpc.

New Mycobacterium tuberculosis Complex Sublineage, Brazzaville, Congo

PubMed Central

Malm, Sven; Linguissi, Laure S. Ghoma; Tekwu, Emmanuel M.; Vouvoungui, Jeannhey C.; Kohl, Thomas A.; Beckert, Patrick; Sidibe, Anissa; Rüsch-Gerdes, Sabine; Madzou-Laboum, Igor K.; Kwedi, Sylvie; Penlap Beng, Véronique; Frank, Matthias; Ntoumi, Francine

2017-01-01

Tuberculosis is a leading cause of illness and death in Congo. No data are available about the population structure and transmission dynamics of the Mycobacterium tuberculosis complex strains prevalent in this central Africa country. On the basis of single-nucleotide polymorphisms detected by whole-genome sequencing, we phylogenetically characterized 74 MTBC isolates from Brazzaville, the capital of Congo. The diversity of the study population was high; most strains belonged to the Euro-American lineage, which split into Latin American Mediterranean, Uganda I, Uganda II, Haarlem, X type, and a new dominant sublineage named Congo type (n = 26). Thirty strains were grouped in 5 clusters (each within 12 single-nucleotide polymorphisms), from which 23 belonged to the Congo type. High cluster rates and low genomic diversity indicate recent emergence and transmission of the Congo type, a new Euro-American sublineage of MTBC. PMID:28221129

New Mycobacterium tuberculosis Complex Sublineage, Brazzaville, Congo.

PubMed

Malm, Sven; Linguissi, Laure S Ghoma; Tekwu, Emmanuel M; Vouvoungui, Jeannhey C; Kohl, Thomas A; Beckert, Patrick; Sidibe, Anissa; Rüsch-Gerdes, Sabine; Madzou-Laboum, Igor K; Kwedi, Sylvie; Penlap Beng, Véronique; Frank, Matthias; Ntoumi, Francine; Niemann, Stefan

2017-03-01

Tuberculosis is a leading cause of illness and death in Congo. No data are available about the population structure and transmission dynamics of the Mycobacterium tuberculosis complex strains prevalent in this central Africa country. On the basis of single-nucleotide polymorphisms detected by whole-genome sequencing, we phylogenetically characterized 74 MTBC isolates from Brazzaville, the capital of Congo. The diversity of the study population was high; most strains belonged to the Euro-American lineage, which split into Latin American Mediterranean, Uganda I, Uganda II, Haarlem, X type, and a new dominant sublineage named Congo type (n = 26). Thirty strains were grouped in 5 clusters (each within 12 single-nucleotide polymorphisms), from which 23 belonged to the Congo type. High cluster rates and low genomic diversity indicate recent emergence and transmission of the Congo type, a new Euro-American sublineage of MTBC.

Somatic cell nuclear transfer followed by CRIPSR/CAS9 microinjection results in highly efficient genome editing in cloned pigs

USDA-ARS?s Scientific Manuscript database

The domestic pig is an ideal “dual purpose” animal model for agricultural and biomedical research. With the availability of genome editing tools [e.g. clustered regularly interspersed short palindromic repeat (CRISPR) and associated nuclease Cas9 (CRISPR/Cas9)] it is now possible to perform site-sp...

Discovering Massive z > 1 Galaxy Clusters with Spitzer and SPTpol

NASA Astrophysics Data System (ADS)

Bleem, Lindsey; Brodwin, Mark; Ashby, Matthew; Stalder, Brian; Klein, Matthias; Gladders, Michael; Stanford, Spencer; Canning, Rebecca

2018-05-01

We propose to obtain Spitzer/IRAC imaging of 50 high-redshift galaxy cluster candidates derived from two new completed SZ cluster surveys by the South Pole Telescope. Clusters from the deep SPTpol 500-square-deg main survey will extend high-redshift SZ cluster science to lower masses (median M500 2x10^14Msun) while systems drawn from the wider 2500-sq-deg SPTpol Extended Cluster Survey are some of the rarest most massive high-z clusters in the observable universe. The proposed small 10 h program will enable (1) confirmation of these candidates as high-redshift clusters, (2) measurements of the cluster redshifts (sigma_z/(1+z) 0.03), and (3) estimates of the stellar masses of the brightest cluster members. These observations will yield exciting and timely targets for the James Webb Space Telescope--and, combined with lower-z systems--will both extend cluster tests of dark energy to z>1 as well as enable studies of galaxy evolution in the richest environments for a mass-limited cluster sample from 0

The M 16 molecular complex under the influence of NGC 6611. Herschel's perspective of the heating effect on the Eagle Nebula

NASA Astrophysics Data System (ADS)

Hill, T.; Motte, F.; Didelon, P.; White, G. J.; Marston, A. P.; Nguyên Luong, Q.; Bontemps, S.; André, Ph.; Schneider, N.; Hennemann, M.; Sauvage, M.; Di Francesco, J.; Minier, V.; Anderson, L. D.; Bernard, J. P.; Elia, D.; Griffin, M. J.; Li, J. Z.; Peretto, N.; Pezzuto, S.; Polychroni, D.; Roussel, H.; Rygl, K. L. J.; Schisano, E.; Sousbie, T.; Testi, L.; Thompson, D. Ward; Zavagno, A.

2012-06-01

We present Herschel images from the HOBYS key program of the Eagle Nebula (M 16) in the far-infrared and sub-millimetre, using the PACS and SPIRE cameras at 70 μm, 160 μm, 250 μm, 350 μm, 500 μm. M 16, home to the Pillars of Creation, is largely under the influence of the nearby NGC 6611 high-mass star cluster. The Herschel images reveal a clear dust temperature gradient running away from the centre of the cavity carved by the OB cluster. We investigate the heating effect of NGC 6611 on the entire M 16 star-forming complex seen by Herschel including the diffuse cloud environment and the dense filamentary structures identified in this region. In addition, we interpret the three-dimensional geometry of M 16 with respect to the nebula, its surrounding environment, and the NGC 6611 cavity. The dust temperature and column density maps reveal a prominent eastern filament running north-south and away from the high-mass star-forming central region and the NGC 6611 cluster, as well as a northern filament which extends around and away from the cluster. The dust temperature in each of these filaments decreases with increasing distance from the NGC 6611 cluster, indicating a heating penetration depth of ~10 pc in each direction in 3-6 × 1022 cm-2 column density filaments. We show that in high-mass star-forming regions OB clusters impact the temperature of future star-forming sites, modifying the initialconditions for collapse and effecting the evolutionary criteria of protostars developed from spectral energy distributions. Possible scenarios for the origin of the morphology seen in this region are discussed, including a western equivalent to the eastern filament, which was destroyed by the creation of the OB cluster and its subsequent winds and radiation. Herschel is a ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.Appendices are available in electronic form at http://www.aanda.org

A new clustering of antibody CDR loop conformations

PubMed Central

North, Benjamin; Lehmann, Andreas; Dunbrack, Roland L.

2010-01-01

Previous analyses of the complementarity determining regions (CDRs) of antibodies have focused on a small number of “canonical” conformations for each loop. This is primarily the result of the work of Chothia and colleagues, most recently in 1997. Because of the widespread utility of antibodies, we have revisited the clustering of conformations of the six CDR loops with the much larger amount of structural information currently available. In this work, we were careful to use a high-quality data set by eliminating low-resolution structures and CDRs with high B-factors or high conformational energies. We used a distance function based on directional statistics and an effective clustering algorithm using affinity propagation. With this data set of over 300 non-redundant antibody structures, we were able to cover 28 CDR-length combinations (e.g., L1 length 11, or “L1-11” in our nomenclature) for L1, L2, L3, H1 and H2. The Chothia analysis covered only 20 CDR-lengths. Only four of these had more than one conformational cluster, of which two could easily be distinguished by gene source (mouse/human; κ/λ) and one purely by the presence and positions of Pro residues (L3-9). Thus using the Chothia analysis does not require the complicated set of “structure-determining residues” that is often assumed. Of our 28 CDR-lengths, 15 of them have multiple conformational clusters including ten for which Chothia had only one canonical class. We have a total of 72 clusters for the non-H3 CDRs; approximately 85% of the non-H3 sequences can be assigned to a conformational cluster based on gene source and/or sequence. We found that earlier predictions of “bulged” vs. “non-bulged” conformations based on the presence or absence of anchor residues Arg/Lys94 and Asp101 of H3 have not held up, since all four combinations lead to a majority of conformations that are bulged. Thus the earlier analyses have been significantly enhanced by the increased data. We believe the new classification will lead to improved methods for antibody structure prediction and design. PMID:21035459

Optimal Partitioning of a Data Set Based on the "p"-Median Model

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich

2008-01-01

Although the "K"-means algorithm for minimizing the within-cluster sums of squared deviations from cluster centroids is perhaps the most common method for applied cluster analyses, a variety of other criteria are available. The "p"-median model is an especially well-studied clustering problem that requires the selection of "p" objects to serve as…

K2: A NEW METHOD FOR THE DETECTION OF GALAXY CLUSTERS BASED ON CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY MULTICOLOR IMAGES

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

Thanjavur, Karun; Willis, Jon; Crampton, David, E-mail: karun@uvic.c

2009-11-20

We have developed a new method, K2, optimized for the detection of galaxy clusters in multicolor images. Based on the Red Sequence approach, K2 detects clusters using simultaneous enhancements in both colors and position. The detection significance is robustly determined through extensive Monte Carlo simulations and through comparison with available cluster catalogs based on two different optical methods, and also on X-ray data. K2 also provides quantitative estimates of the candidate clusters' richness and photometric redshifts. Initially, K2 was applied to the two color (gri) 161 deg{sup 2} images of the Canada-France-Hawaii Telescope Legacy Survey Wide (CFHTLS-W) data. Our simulationsmore » show that the false detection rate for these data, at our selected threshold, is only approx1%, and that the cluster catalogs are approx80% complete up to a redshift of z = 0.6 for Fornax-like and richer clusters and to z approx 0.3 for poorer clusters. Based on the g-, r-, and i-band photometric catalogs of the Terapix T05 release, 35 clusters/deg{sup 2} are detected, with 1-2 Fornax-like or richer clusters every 2 deg{sup 2}. Catalogs containing data for 6144 galaxy clusters have been prepared, of which 239 are rich clusters. These clusters, especially the latter, are being searched for gravitational lenses-one of our chief motivations for cluster detection in CFHTLS. The K2 method can be easily extended to use additional color information and thus improve overall cluster detection to higher redshifts. The complete set of K2 cluster catalogs, along with the supplementary catalogs for the member galaxies, are available on request from the authors.« less

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

PubMed

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

2016-10-15

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

Block Ignition Inertial Confinement Fusion (ICF) with Condensed Matter Cluster Type Targets for p-B11 Powered Space Propulsion

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

Miley, George H.; Hora, H.; Badziak, J.

The use of laser-driven Inertial Confinement Fusion (ICF) for space propulsion has been the subject of several earlier conceptual design studies, (see: Orth, 1998; and other references therein). However, these studies were based on older ICF technology using either 'direct' or 'in-direct x-ray driven' type target irradiation. Important new directions have opened for laser ICF in recent years following the development of 'chirped' lasers capable of ultra short pulses with powers of TW up to few PW which leads to the concept of 'fast ignition (FI)' to achieve higher energy gains from target implosions. In a recent publication the authorsmore » showed that use of a modified type of FI, termed 'block ignition' (Miley et al., 2008), could meet many of the requirements anticipated (but not then available) by the designs of the Vehicle for Interplanetary Space Transport Applications (VISTA) ICF fusion propulsion ship (Orth, 2008) for deep space missions. Subsequently the first author devised and presented concepts for imbedding high density condensed matter 'clusters' of deuterium into the target to obtain ultra high local fusion reaction rates (Miley, 2008). Such rates are possible due to the high density of the clusters (over an order of magnitude above cryogenic deuterium). Once compressed by the implosion, the yet higher density gives an ultra high reaction rate over the cluster volume since the fusion rate is proportional to the square of the fuel density. Most recently, a new discovery discussed here indicates that the target matrix could be composed of B{sup 11} with proton clusters imbedded. This then makes p-B{sup 11} fusion practical, assuming all of the physics issues such as stability of the clusters during compression are resolved. Indeed, p-B{sup 11} power is ideal for fusion propulsion since it has a minimum of unwanted side products while giving most of the reaction energy to energetic alpha particles which can be directed into an exhaust (propulsion) nozzle. Power plants using p-B{sup 11} have been discussed for such applications before, but prior designs face formidable physics/technology issues, largely overcome with the present approach.« less

WINGS-SPE. III. Equivalent width measurements, spectral properties, and evolution of local cluster galaxies

NASA Astrophysics Data System (ADS)

Fritz, J.; Poggianti, B. M.; Cava, A.; Moretti, A.; Varela, J.; Bettoni, D.; Couch, W. J.; D'Onofrio D'Onofrio, M.; Dressler, A.; Fasano, G.; Kjærgaard, P.; Marziani, P.; Moles, M.; Omizzolo, A.

2014-06-01

Context. Cluster galaxies are the ideal sites to look at when studying the influence of the environment on the various aspects of the evolution of galaxies, such as the changes in their stellar content and morphological transformations. In the framework of wings, the WIde-field Nearby Galaxy-cluster Survey, we have obtained optical spectra for ~6000 galaxies selected in fields centred on 48 local (0.04 < z < 0.07) X-ray selected clusters to tackle these issues. Aims: By classifying the spectra based on given spectral lines, we investigate the frequency of the various spectral types as a function of both the clusters' properties and the galaxies' characteristics. In this way, using the same classification criteria adopted for studies at higher redshift, we can consistently compare the properties of the local cluster population to those of their more distant counterparts. Methods: We describe a method that we have developed to automatically measure the equivalent width of spectral lines in a robust way, even in spectra with a non optimal signal-to-noise ratio. This way, we can derive a spectral classification reflecting the stellar content, based on the presence and strength of the [Oii] and Hδ lines. Results: After a quality check, we are able to measure 4381 of the ~6000 originally observed spectra in the fields of 48 clusters, of which 2744 are spectroscopically confirmed cluster members. The spectral classification is then analysed as a function of galaxies' luminosity, stellar mass, morphology, local density, and host cluster's global properties and compared to higher redshift samples (MORPHS and EDisCS). The vast majority of galaxies in the local clusters population are passive objects, being also the most luminous and massive. At a magnitude limit of MV < -18, galaxies in a post-starburst phase represent only ~11% of the cluster population, and this fraction is reduced to ~5% at MV < -19.5, which compares to the 18% at the same magnitude limit for high-z clusters. "Normal" star-forming galaxies (e(c)) are proportionally more common in local clusters. Conclusions: The relative occurrence of post-starbursts suggests a very similar quenching efficiency in clusters at redshifts in the 0 to ~1 range. Furthermore, more important than the global environment, the local density seems to be the main driver of galaxy evolution in local clusters at least with respect to their stellar populations content. Based on observations taken at the Anglo Australian Telescope (3.9 m- AAT) and at the William Herschel Telescope (4.2 m-WHT).Full Table A.1 is available in electronic form at both the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/566/A32 and by querying the wings database at http://web.oapd.inaf.it/wings/new/index.htmlAppendices are available in electronic form at http://www.aanda.org

MUSE crowded field 3D spectroscopy of over 12 000 stars in the globular cluster NGC 6397. I. The first comprehensive HRD of a globular cluster

NASA Astrophysics Data System (ADS)

Husser, Tim-Oliver; Kamann, Sebastian; Dreizler, Stefan; Wendt, Martin; Wulff, Nina; Bacon, Roland; Wisotzki, Lutz; Brinchmann, Jarle; Weilbacher, Peter M.; Roth, Martin M.; Monreal-Ibero, Ana

2016-04-01

Aims: We demonstrate the high multiplex advantage of crowded field 3D spectroscopy with the new integral field spectrograph MUSE by means of a spectroscopic analysis of more than 12 000 individual stars in the globular cluster NGC 6397. Methods: The stars are deblended with a point spread function fitting technique, using a photometric reference catalogue from HST as prior, including relative positions and brightnesses. This catalogue is also used for a first analysis of the extracted spectra, followed by an automatic in-depth analysis via a full-spectrum fitting method based on a large grid of PHOENIX spectra. Results: We analysed the largest sample so far available for a single globular cluster of 18 932 spectra from 12 307 stars in NGC 6397. We derived a mean radial velocity of vrad = 17.84 ± 0.07 km s-1 and a mean metallicity of [Fe/H] = -2.120 ± 0.002, with the latter seemingly varying with temperature for stars on the red giant branch (RGB). We determine Teff and [Fe/H] from the spectra, and log g from HST photometry. This is the first very comprehensive Hertzsprung-Russell diagram (HRD) for a globular cluster based on the analysis of several thousands of stellar spectra, ranging from the main sequence to the tip of the RGB. Furthermore, two interesting objects were identified; one is a post-AGB star and the other is a possible millisecond-pulsar companion. Data products are available at http://muse-vlt.eu/scienceBased on observations obtained at the Very Large Telescope (VLT) of the European Southern Observatory, Paranal, Chile (ESO Programme ID 60.A-9100(C)).

Lens models and magnification maps of the six Hubble Frontier Fields clusters

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

Johnson, Traci L.; Sharon, Keren; Bayliss, Matthew B.

2014-12-10

We present strong-lensing models as well as mass and magnification maps for the cores of the six Hubble Space Telescope (HST) Frontier Fields galaxy clusters. Our parametric lens models are constrained by the locations and redshifts of multiple image systems of lensed background galaxies. We use a combination of photometric redshifts and spectroscopic redshifts of the lensed background sources obtained by us (for A2744 and AS1063), collected from the literature, or kindly provided by the lensing community. Using our results, we (1) compare the derived mass distribution of each cluster to its light distribution, (2) quantify the cumulative magnification powermore » of the HST Frontier Fields clusters, (3) describe how our models can be used to estimate the magnification and image multiplicity of lensed background sources at all redshifts and at any position within the cluster cores, and (4) discuss systematic effects and caveats resulting from our modeling methods. We specifically investigate the effect of the use of spectroscopic and photometric redshift constraints on the uncertainties of the resulting models. We find that the photometric redshift estimates of lensed galaxies are generally in excellent agreement with spectroscopic redshifts, where available. However, the flexibility associated with relaxed redshift priors may cause the complexity of large-scale structure that is needed to account for the lensing signal to be underestimated. Our findings thus underline the importance of spectroscopic arc redshifts, or tight photometric redshift constraints, for high precision lens models. All products from our best-fit lens models (magnification, convergence, shear, deflection field) and model simulations for estimating errors are made available via the Mikulski Archive for Space Telescopes.« less

Evolution of the early-type galaxy fraction in clusters since z = 0.8

NASA Astrophysics Data System (ADS)

Simard, L.; Clowe, D.; Desai, V.; Dalcanton, J. J.; von der Linden, A.; Poggianti, B. M.; White, S. D. M.; Aragón-Salamanca, A.; De Lucia, G.; Halliday, C.; Jablonka, P.; Milvang-Jensen, B.; Saglia, R. P.; Pelló, R.; Rudnick, G. H.; Zaritsky, D.

2009-12-01

We study the morphological content of a large sample of high-redshift clusters to determine its dependence on cluster mass and redshift. Quantitative morphologies are based on PSF-convolved, 2D bulge+disk decompositions of cluster and field galaxies on deep Very Large Telescope FORS2 images of eighteen, optically-selected galaxy clusters at 0.45 < z < 0.80 observed as part of the ESO Distant Cluster Survey (“EDisCS”). Morphological content is characterized by the early-type galaxy fraction f_et, and early-type galaxies are objectively selected based on their bulge fraction and image smoothness. This quantitative selection is equivalent to selecting galaxies visually classified as E or S0. Changes in early-type fractions as a function of cluster velocity dispersion, redshift and star-formation activity are studied. A set of 158 clusters extracted from the Sloan Digital Sky Survey is analyzed exactly as the distant EDisCS sample to provide a robust local comparison. We also compare our results to a set of clusters from the Millennium Simulation. Our main results are: (1) the early-type fractions of the SDSS and EDisCS clusters exhibit no clear trend as a function of cluster velocity dispersion. (2) Mid-z EDisCS clusters around σ = 500 km s-1 have f_et ≃ 0.5 whereas high-z EDisCS clusters have f_et ≃ 0.4. This represents a ~25% increase over a time interval of 2 Gyr. (3) There is a marked difference in the morphological content of EDisCS and SDSS clusters. None of the EDisCS clusters have early-type galaxy fractions greater than 0.6 whereas half of the SDSS clusters lie above this value. This difference is seen in clusters of all velocity dispersions. (4) There is a strong and clear correlation between morphology and star formation activity in SDSS and EDisCS clusters in the sense that decreasing fractions of [OII] emitters are tracked by increasing early-type fractions. This correlation holds independent of cluster velocity dispersion and redshift even though the fraction of [OII] emitters decreases from z ˜0.8 to z ˜ 0.06 in all environments. Our results pose an interesting challenge to structural transformation and star formation quenching processes that strongly depend on the global cluster environment (e.g., a dense ICM) and suggest that cluster membership may be of lesser importance than other variables in determining galaxy properties. Based on observations obtained in visitor and service modes at the ESO Very Large Telescope (VLT) as part of the Large Programme 166.A-0162 (the ESO Distant Cluster Survey). Also based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with proposal 9476. Support for this proposal was provided by NASA through a grant from the Space Telescope Science Institute. Table [see full textsee full textsee full textsee full textsee full text] is only available in electronic form at http://www.aanda.org

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

PubMed

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

2015-09-01

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

Patterns of victimization between and within peer clusters in a high school social network.

PubMed

Swartz, Kristin; Reyns, Bradford W; Wilcox, Pamela; Dunham, Jessica R

2012-01-01

This study presents a descriptive analysis of patterns of violent victimization between and within the various cohesive clusters of peers comprising a sample of more than 500 9th-12th grade students from one high school. Social network analysis techniques provide a visualization of the overall friendship network structure and allow for the examination of variation in victimization across the various peer clusters within the larger network. Social relationships among clusters with varying levels of victimization are also illustrated so as to provide a sense of possible spatial clustering or diffusion of victimization across proximal peer clusters. Additionally, to provide a sense of the sorts of peer clusters that support (or do not support) victimization, characteristics of clusters at both the high and low ends of the victimization scale are discussed. Finally, several of the peer clusters at both the high and low ends of the victimization continuum are "unpacked", allowing examination of within-network individual-level differences in victimization for these select clusters.

Noninvasive neuromodulation in migraine and cluster headache.

PubMed

Starling, Amaal

2018-06-01

The purpose of this narrative review is to provide an overview of the currently available noninvasive neuromodulation devices for the treatment of migraine and cluster headache. Over the last decade, several noninvasive devices have undergone development and clinical trials to evaluate efficacy and safety. Based on this body of work, single-pulse transcranial magnetic stimulation, transcutaneous supraorbital neurostimulation, and noninvasive vagal nerve stimulation devices have been cleared by the United States Food and Drug Administration and are available for clinical use for the treatment of primary headache disorders. Overall, these novel noninvasive devices appear to be safe, well tolerated, and have demonstrated promising results in clinical trials in both migraine and cluster headache. This narrative review will provide a summary and update of the proposed mechanisms of action, evidence, safety, and future directions of various currently available modalities of noninvasive neuromodulation for the treatment of migraine and cluster headache.

Farm, household, and farmer characteristics associated with changes in management practices and technology adoption among dairy smallholders.

PubMed

Martínez-García, Carlos Galdino; Ugoretz, Sarah Janes; Arriaga-Jordán, Carlos Manuel; Wattiaux, Michel André

2015-02-01

This study explored whether technology adoption and changes in management practices were associated with farm structure, household, and farmer characteristics and to identify processes that may foster productivity and sustainability of small-scale dairy farming in the central highlands of Mexico. Factor analysis of survey data from 44 smallholders identified three factors-related to farm size, farmer's engagement, and household structure-that explained 70 % of cumulative variance. The subsequent hierarchical cluster analysis yielded three clusters. Cluster 1 included the most senior farmers with fewest years of education but greatest years of experience. Cluster 2 included farmers who reported access to extension, cooperative services, and more management changes. Cluster 2 obtained 25 and 35 % more milk than farmers in clusters 1 and 3, respectively. Cluster 3 included the youngest farmers, with most years of education and greatest availability of family labor. Access to a network and membership in a community of peers appeared as important contributors to success. Smallholders gravitated towards easy to implement technologies that have immediate benefits. Nonusers of high investment technologies found them unaffordable because of cost, insufficient farm size, and lack of knowledge or reliable electricity. Multivariate analysis may be a useful tool in planning extension activities and organizing channels of communication to effectively target farmers with varying needs, constraints, and motivations for change and in identifying farmers who may exemplify models of change for others who manage farms that are structurally similar but performing at a lower level.

Galaxy CloudMan: delivering cloud compute clusters.

PubMed

Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

2010-12-21

Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

Galaxy CloudMan: delivering cloud compute clusters

PubMed Central

2010-01-01

Background Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is “cloud computing”, which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate “as is” use by experimental biologists. Results We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon’s EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. Conclusions The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge. PMID:21210983

Dolidze-35: Results for a Possible Open Cluster

NASA Astrophysics Data System (ADS)

Gulledge, Deborah J.; Borges, Richard A.; Juelfs, Elizabeth; Allyn Smith, J.; Olive, Mary E.; McDonald, Christopher P.; Williams, Sarah M.; Cohen, Eden M.; Gawel, Jason D.; McCole, Bambi A.; Robertson, Jacob M.; Wilson, Tyler; Young, William J.; Buckner, Spencer L.; Allen, Nic R.; Head, H. Hope

2016-01-01

Dolidze-35 is an under-observed northern hemisphere open cluster. It is noted in WEBDA as "No data available for this cluster". As such, we chose this cluster as an undergraduate class project to investigate its existence. We present SDSS-ugriz magnitudes for the possible cluster and cross these with existing JHK data obtained from 2MASS. Selection of possible members is aided by the proper motion study of Krone-Martins (2010).

ClueNet: Clustering a temporal network based on topological similarity rather than denseness.

PubMed

Crawford, Joseph; Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of "topologically related" nodes, where the resulting topology-based clusters are expected to "correlate" well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data-their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance.

ALMA Pinpoints a Strong Overdensity of U/LIRGs in the Massive Cluster XCS J2215 at z = 1.46

NASA Astrophysics Data System (ADS)

Stach, Stuart M.; Swinbank, A. M.; Smail, Ian; Hilton, Matt; Simpson, J. M.; Cooke, E. A.

2017-11-01

We surveyed the core regions of the z = 1.46 cluster XCS J2215.9-1738 with the Atacama Large Millimeter Array (ALMA) and the MUSE-GALACSI spectrograph on the Very Large Telescope (VLT). We obtained high spatial resolution observations with ALMA of the 1.2 mm dust continuum and molecular gas emission in the central regions of the cluster. These observations detect 14 significant millimeter sources in a region with a projected diameter of just ˜500 kpc (˜1‧). For six of these galaxies, we also obtain 12CO(2-1) and 12CO(5-4) line detections, confirming them as cluster members, and a further five of our millimeter galaxies have archival 12CO(2-1) detections, which also place them in the cluster. An additional two millimeter galaxies have photometric redshifts consistent with cluster membership, although neither show strong line emission in the MUSE spectra. This suggests that the bulk (≥11/14, ˜80%) of the submillimeter sources in the field are in fact luminous infrared galaxies lying within this young cluster. We then use our sensitive new observations to constrain the dust-obscured star formation activity and cold molecular gas within this cluster. We find hints that the cooler dust and gas components within these galaxies may have been influenced by their environment, reducing the gas reservoir available for their subsequent star formation. We also find that these actively star-forming galaxies have dynamical masses and stellar population ages expected for the progenitors of massive, early-type galaxies in local clusters, potentially linking these populations.

Machine-learned cluster identification in high-dimensional data.

PubMed

Ultsch, Alfred; Lötsch, Jörn

2017-02-01

High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect clusters. We analyzed whether this can be avoided by using emergent self-organizing feature maps (ESOM). Data sets with different degrees of complexity were submitted to ESOM analysis with large numbers of neurons, using an interactive R-based bioinformatics tool. On top of the trained ESOM the distance structure in the high dimensional feature space was visualized in the form of a so-called U-matrix. Clustering results were compared with those provided by classical common cluster algorithms including single linkage, Ward and k-means. Ward clustering imposed cluster structures on cluster-less "golf ball", "cuboid" and "S-shaped" data sets that contained no structure at all (random data). Ward clustering also imposed structures on permuted real world data sets. By contrast, the ESOM/U-matrix approach correctly found that these data contain no cluster structure. However, ESOM/U-matrix was correct in identifying clusters in biomedical data truly containing subgroups. It was always correct in cluster structure identification in further canonical artificial data. Using intentionally simple data sets, it is shown that popular clustering algorithms typically used for biomedical data sets may fail to cluster data correctly, suggesting that they are also likely to perform erroneously on high dimensional biomedical data. The present analyses emphasized that generally established classical hierarchical clustering algorithms carry a considerable tendency to produce erroneous results. By contrast, unsupervised machine-learned analysis of cluster structures, applied using the ESOM/U-matrix method, is a viable, unbiased method to identify true clusters in the high-dimensional space of complex data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Effects of Non-Clustering of Refugees.

ERIC Educational Resources Information Center

Conick, John E.

1983-01-01

Describes the approach to resettlement for recently arrived refugees implemented within the state of South Carolina. Suggests that non-clustering of refugees leads to quick acculturation if there is wide community support, but that certain services are more readily available when refugees are clustered. (GC)

Inflation data clustering of some cities in Indonesia

NASA Astrophysics Data System (ADS)

Setiawan, Adi; Susanto, Bambang; Mahatma, Tundjung

2017-06-01

In this paper, it is presented how to cluster inflation data of cities in Indonesia by using k-means cluster method and fuzzy c-means method. The data that are used is limited to the monthly inflation data from 15 cities across Indonesia which have highest weight of donations and is supplemented with 5 cities used in the calculation of inflation in Indonesia. When they are applied into two clusters with k = 2 for k-means cluster method and c = 2, w = 1.25 for fuzzy c-means cluster method, Ambon, Manado and Jayapura tend to become one cluster (high inflation) meanwhile other cities tend to become members of other cluster (low inflation). However, if they are applied into two clusters with c=2, w=1.5, Surabaya, Medan, Makasar, Samarinda, Makasar, Manado, Ambon dan Jayapura tend to become one cluster (high inflation) meanwhile other cities tend to become members of other cluster (low inflation). Furthermore, when we use two clusters with k=3 for k-means cluster method and c=3, w = 1.25 for fuzzy c-means cluster method, Ambon tends to become member of first cluster (high inflation), Manado and Jayapura tend to become member of second cluster (moderate inflation), other cities tend to become members of third cluster (low inflation). If it is applied c=3, w = 1.5, Ambon, Manado and Jayapura tend to become member of first cluster (high inflation), Surabaya, Bandung, Medan, Makasar, Banyuwangi, Denpasar, Samarinda dan Mataram tend to become members of second cluster (moderate inflation), meanwhile other cities tend to become members of third cluster (low inflation). Similarly, interpretation can be made to the results of applying 5 clusters.

Connecting massive galaxies to dark matter haloes in BOSS - I. Is galaxy colour a stochastic process in high-mass haloes?

NASA Astrophysics Data System (ADS)

Saito, Shun; Leauthaud, Alexie; Hearin, Andrew P.; Bundy, Kevin; Zentner, Andrew R.; Behroozi, Peter S.; Reid, Beth A.; Sinha, Manodeep; Coupon, Jean; Tinker, Jeremy L.; White, Martin; Schneider, Donald P.

2016-08-01

We use subhalo abundance matching (SHAM) to model the stellar mass function (SMF) and clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) `CMASS' sample at z ˜ 0.5. We introduce a novel method which accounts for the stellar mass incompleteness of CMASS as a function of redshift, and produce CMASS mock catalogues which include selection effects, reproduce the overall SMF, the projected two-point correlation function wp, the CMASS dn/dz, and are made publicly available. We study the effects of assembly bias above collapse mass in the context of `age matching' and show that these effects are markedly different compared to the ones explored by Hearin et al. at lower stellar masses. We construct two models, one in which galaxy colour is stochastic (`AbM' model) as well as a model which contains assembly bias effects (`AgM' model). By confronting the redshift dependent clustering of CMASS with the predictions from our model, we argue that that galaxy colours are not a stochastic process in high-mass haloes. Our results suggest that the colours of galaxies in high-mass haloes are determined by other halo properties besides halo peak velocity and that assembly bias effects play an important role in determining the clustering properties of this sample.

Semi-supervised clustering for parcellating brain regions based on resting state fMRI data

NASA Astrophysics Data System (ADS)

Cheng, Hewei; Fan, Yong

2014-03-01

Many unsupervised clustering techniques have been adopted for parcellating brain regions of interest into functionally homogeneous subregions based on resting state fMRI data. However, the unsupervised clustering techniques are not able to take advantage of exiting knowledge of the functional neuroanatomy readily available from studies of cytoarchitectonic parcellation or meta-analysis of the literature. In this study, we propose a semi-supervised clustering method for parcellating amygdala into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented under the framework of graph partitioning, and adopts prior information and spatial consistent constraints to obtain a spatially contiguous parcellation result. The graph partitioning problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated for parcellating amygdala into 3 subregions based on resting state fMRI data of 28 subjects. The experiment results have demonstrated that the proposed method is more robust than unsupervised clustering and able to parcellate amygdala into centromedial, laterobasal, and superficial parts with improved functionally homogeneity compared with the cytoarchitectonic parcellation result. The validity of the parcellation results is also supported by distinctive functional and structural connectivity patterns of the subregions and high consistency between coactivation patterns derived from a meta-analysis and functional connectivity patterns of corresponding subregions.

Self-assembly of high-nuclearity lanthanide-based nanoclusters for potential bioimaging applications

NASA Astrophysics Data System (ADS)

Yang, Xiaoping; Wang, Shiqing; Schipper, Desmond; Zhang, Lijie; Li, Zongping; Huang, Shaoming; Yuan, Daqiang; Chen, Zhongning; Gnanam, Annie J.; Hall, Justin W.; King, Tyler L.; Que, Emily; Dieye, Yakhya; Vadivelu, Jamuna; Brown, Katherine A.; Jones, Richard A.

2016-05-01

Two series of Cd-Ln and Ni-Ln clusters [Ln8Cd24L12(OAc)44(48)Cl4(0)] and [Ln8Ni6L6(OAc)24(EtOH)6(H2O)2] were constructed using a flexible ligand. The Cd-Ln clusters exhibit interesting nano-drum-like structures which allows direct visualization by TEM. Luminex MicroPlex Microspheres loaded with the Cd-Sm cluster were visualized using epifluorescence microscopy. Cytotoxicity studies on A549 and AGS cancer cell lines showed that the materials have mild to moderate cytotoxicity.Two series of Cd-Ln and Ni-Ln clusters [Ln8Cd24L12(OAc)44(48)Cl4(0)] and [Ln8Ni6L6(OAc)24(EtOH)6(H2O)2] were constructed using a flexible ligand. The Cd-Ln clusters exhibit interesting nano-drum-like structures which allows direct visualization by TEM. Luminex MicroPlex Microspheres loaded with the Cd-Sm cluster were visualized using epifluorescence microscopy. Cytotoxicity studies on A549 and AGS cancer cell lines showed that the materials have mild to moderate cytotoxicity. Electronic supplementary information (ESI) available: Full experimental and characterization details for 1-5. CCDC 1007468, 1007469 and 1007472-1007474. For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/c6nr00642f

A hierarchical model for clustering m(6)A methylation peaks in MeRIP-seq data.

PubMed

Cui, Xiaodong; Meng, Jia; Zhang, Shaowu; Rao, Manjeet K; Chen, Yidong; Huang, Yufei

2016-08-22

The recent advent of the state-of-art high throughput sequencing technology, known as Methylated RNA Immunoprecipitation combined with RNA sequencing (MeRIP-seq) revolutionizes the area of mRNA epigenetics and enables the biologists and biomedical researchers to have a global view of N (6)-Methyladenosine (m(6)A) on transcriptome. Yet there is a significant need for new computation tools for processing and analysing MeRIP-Seq data to gain a further insight into the function and m(6)A mRNA methylation. We developed a novel algorithm and an open source R package ( http://compgenomics.utsa.edu/metcluster ) for uncovering the potential types of m(6)A methylation by clustering the degree of m(6)A methylation peaks in MeRIP-Seq data. This algorithm utilizes a hierarchical graphical model to model the reads account variance and the underlying clusters of the methylation peaks. Rigorous statistical inference is performed to estimate the model parameter and detect the number of clusters. MeTCluster is evaluated on both simulated and real MeRIP-seq datasets and the results demonstrate its high accuracy in characterizing the clusters of methylation peaks. Our algorithm was applied to two different sets of real MeRIP-seq datasets and reveals a novel pattern that methylation peaks with less peak enrichment tend to clustered in the 5' end of both in both mRNAs and lncRNAs, whereas those with higher peak enrichment are more likely to be distributed in CDS and towards the 3'end of mRNAs and lncRNAs. This result might suggest that m(6)A's functions could be location specific. In this paper, a novel hierarchical graphical model based algorithm was developed for clustering the enrichment of methylation peaks in MeRIP-seq data. MeTCluster is written in R and is publicly available.

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

The Mass Function of Abell Clusters

NASA Astrophysics Data System (ADS)

Chen, J.; Huchra, J. P.; McNamara, B. R.; Mader, J.

1998-12-01

The velocity dispersion and mass functions for rich clusters of galaxies provide important constraints on models of the formation of Large-Scale Structure (e.g., Frenk et al. 1990). However, prior estimates of the velocity dispersion or mass function for galaxy clusters have been based on either very small samples of clusters (Bahcall and Cen 1993; Zabludoff et al. 1994) or large but incomplete samples (e.g., the Girardi et al. (1998) determination from a sample of clusters with more than 30 measured galaxy redshifts). In contrast, we approach the problem by constructing a volume-limited sample of Abell clusters. We collected individual galaxy redshifts for our sample from two major galaxy velocity databases, the NASA Extragalactic Database, NED, maintained at IPAC, and ZCAT, maintained at SAO. We assembled a database with velocity information for possible cluster members and then selected cluster members based on both spatial and velocity data. Cluster velocity dispersions and masses were calculated following the procedures of Danese, De Zotti, and di Tullio (1980) and Heisler, Tremaine, and Bahcall (1985), respectively. The final velocity dispersion and mass functions were analyzed in order to constrain cosmological parameters by comparison to the results of N-body simulations. Our data for the cluster sample as a whole and for the individual clusters (spatial maps and velocity histograms) in our sample is available on-line at http://cfa-www.harvard.edu/ huchra/clusters. This website will be updated as more data becomes available in the master redshift compilations, and will be expanded to include more clusters and large groups of galaxies.

Cluster analysis and its application to healthcare claims data: a study of end-stage renal disease patients who initiated hemodialysis.

PubMed

Liao, Minlei; Li, Yunfeng; Kianifard, Farid; Obi, Engels; Arcona, Stephen

2016-03-02

Cluster analysis (CA) is a frequently used applied statistical technique that helps to reveal hidden structures and "clusters" found in large data sets. However, this method has not been widely used in large healthcare claims databases where the distribution of expenditure data is commonly severely skewed. The purpose of this study was to identify cost change patterns of patients with end-stage renal disease (ESRD) who initiated hemodialysis (HD) by applying different clustering methods. A retrospective, cross-sectional, observational study was conducted using the Truven Health MarketScan® Research Databases. Patients aged ≥18 years with ≥2 ESRD diagnoses who initiated HD between 2008 and 2010 were included. The K-means CA method and hierarchical CA with various linkage methods were applied to all-cause costs within baseline (12-months pre-HD) and follow-up periods (12-months post-HD) to identify clusters. Demographic, clinical, and cost information was extracted from both periods, and then examined by cluster. A total of 18,380 patients were identified. Meaningful all-cause cost clusters were generated using K-means CA and hierarchical CA with either flexible beta or Ward's methods. Based on cluster sample sizes and change of cost patterns, the K-means CA method and 4 clusters were selected: Cluster 1: Average to High (n = 113); Cluster 2: Very High to High (n = 89); Cluster 3: Average to Average (n = 16,624); or Cluster 4: Increasing Costs, High at Both Points (n = 1554). Median cost changes in the 12-month pre-HD and post-HD periods increased from $185,070 to $884,605 for Cluster 1 (Average to High), decreased from $910,930 to $157,997 for Cluster 2 (Very High to High), were relatively stable and remained low from $15,168 to $13,026 for Cluster 3 (Average to Average), and increased from $57,909 to $193,140 for Cluster 4 (Increasing Costs, High at Both Points). Relatively stable costs after starting HD were associated with more stable scores on comorbidity index scores from the pre-and post-HD periods, while increasing costs were associated with more sharply increasing comorbidity scores. The K-means CA method appeared to be the most appropriate in healthcare claims data with highly skewed cost information when taking into account both change of cost patterns and sample size in the smallest cluster.

An automated method for finding molecular complexes in large protein interaction networks

PubMed Central

Bader, Gary D; Hogue, Christopher WV

2003-01-01

Background Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. Results This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Conclusion Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from . PMID:12525261

Chemical analysis of eight giant stars of the globular cluster NGC 6366

NASA Astrophysics Data System (ADS)

Puls, Arthur A.; Alves-Brito, Alan; Campos, Fabíola; Dias, Bruno; Barbuy, Beatriz

2018-05-01

The metal-rich Galactic globular cluster NGC 6366 is the fifth closest to the Sun. Despite its interest, it has received scarce attention, and little is known about its internal structure. Its kinematics suggests a link to the halo, but its metallicity indicates otherwise. We present a detailed chemical analysis of eight giant stars of NGC 6366, using high-resolution and high-quality spectra (R > 40 000, S/N > 60) obtained at the VLT (8.2 m) and CFHT (3.6 m) telescopes. We attempted to characterize its chemistry and to search for evidence of multiple stellar populations. The atmospheric parameters were derived using the method of excitation and ionization equilibrium of Fe I and Fe II lines and from those atmospheric parameters we calculated the abundances for other elements and found that none of the elements measured presents star-to-star variation greater than the uncertainties. We compared the derived abundances with those of other globular clusters and field stars available in the literature. We determined a mean [Fe/H] = -0.60 ± 0.03 for NGC 6366 and found some similarity of this object with M 71, another inner halo globular cluster. The Na-O anticorrelation extension is short and no star-to-star variation in Al is found. The presence of second generation stars is not evident in NGC 6366.

Longitudinal Study of Career Cluster Persistence from 8th Grade to 12th Grade with a Focus on the Science, Technology, Engineering, & Math Career Cluster

NASA Astrophysics Data System (ADS)

Wagner, Judson

Today's technology driven global economy has put pressure on the American education system to produce more students who are prepared for careers in Science, Technology, Engineering, and Math (STEM). Adding to this pressure is the demand for a more diverse workforce that can stimulate the development of new ideas and innovation. This in turn requires more female and under represented minority groups to pursue future careers in STEM. Though STEM careers include many of the highest paid professionals, school systems are dealing with exceptionally high numbers of students, especially female and under represented minorities, who begin but do not persist to STEM degree completion. Using the Expectancy-Value Theory (EVT) framework that attributes student motivation to a combination of intrinsic, utility, and attainment values, this study analyzed readily available survey data to gauge students' career related values. These values were indirectly investigated through a longitudinal approach, spanning five years, on the predictive nature of 8 th grade survey-derived recommendations for students to pursue a future in a particular career cluster. Using logistic regression analysis, it was determined that this 8 th grade data, particularly in STEM, provides significantly high probabilities of a 12th grader's average grade, SAT-Math score, the math and science elective courses they take, and most importantly, interest in the same career cluster.

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

PubMed

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

2012-01-30

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

De novo assembly of the transcriptome of the non-model plant Streptocarpus rexii employing a novel heuristic to recover locus-specific transcript clusters.

PubMed

Chiara, Matteo; Horner, David S; Spada, Alberto

2013-01-01

De novo transcriptome characterization from Next Generation Sequencing data has become an important approach in the study of non-model plants. Despite notable advances in the assembly of short reads, the clustering of transcripts into unigene-like (locus-specific) clusters remains a somewhat neglected subject. Indeed, closely related paralogous transcripts are often merged into single clusters by current approaches. Here, a novel heuristic method for locus-specific clustering is compared to that implemented in the de novo assembler Oases, using the same initial transcript collections, derived from Arabidopsis thaliana and the developmental model Streptocarpus rexii. We show that the proposed approach improves cluster specificity in the A. thaliana dataset for which the reference genome is available. Furthermore, for the S. rexii data our filtered transcript collection matches a larger number of distinct annotated loci in reference genomes than the Oases set, while containing a reduced overall number of loci. A detailed discussion of advantages and limitations of our approach in processing de novo transcriptome reconstructions is presented. The proposed method should be widely applicable to other organisms, irrespective of the transcript assembly method employed. The S. rexii transcriptome is available as a sophisticated and augmented publicly available online database.

The Psychology of Yoga Practitioners: A Cluster Analysis.

PubMed

Genovese, Jeremy E C; Fondran, Kristine M

2017-11-01

Yoga practitioners (N = 261) completed the revised Expression of Spirituality Inventory (ESI) and the Multidimensional Body-Self Relations Questionnaire. Cluster analysis revealed three clusters: Cluster A scored high on all four spiritual constructs. They had high positive evaluations of their appearance, but a lower orientation towards their appearance. They tended to have a high evaluation of their fitness and health, and higher body satisfaction. Cluster B showed lower scores on the spiritual constructs. Like Cluster A, members of Cluster B tended to show high positive evaluations of appearance and fitness. They also had higher body satisfaction. Members of Cluster B had a higher fitness orientation and a higher appearance orientation than members of Cluster A. Members of Cluster C had low scores for all spiritual constructs. They had a low evaluation of, and unhappiness with, their appearance. They were unhappy with the size and appearance of their bodies. They tended to see themselves as overweight. There was a significant difference in years of practice between the three groups (Kruskall -Wallis, p = .0041). Members of Cluster A have the most years of yoga experience and members of Cluster B have more yoga experience than members of Cluster C. These results suggest the possible existence of a developmental trajectory for yoga practitioners. Such a developmental sequence may have important implications for yoga practice and instruction.

The Psychology of Yoga Practitioners: A Cluster Analysis.

PubMed

Genovese, Jeremy E C; Fondran, Kristine M

2017-03-30

Yoga practitioners (N = 261) completed the revised Expression of Spirituality Inventory (ESI) and the Multidimensional Body-Self Relations Questionnaire. Cluster analysis revealed three clusters: Cluster A scored high on all four spiritual constructs. They had high positive evaluations of their appearance, but a lower orientation towards their appearance. They tended to have a high evaluation of their fitness and health, and higher body satisfaction. Cluster B showed lower scores on the spiritual constructs. Like Cluster A, members of Cluster B tended to show high positive evaluations of appearance and fitness. They also had higher body satisfaction. Members of Cluster B had a higher fitness orientation and a higher appearance orientation than members of Cluster A. Members of Cluster C had low scores for all spiritual constructs. They had a low evaluation of, and unhappiness with, their appearance. They were unhappy with the size and appearance of their bodies. They tended to see themselves as overweight. There was a significant difference in years of practice between the three groups (Kruskall-Wallis, p = .0041). Members of Cluster A have the most years of yoga experience and members of Cluster B have more yoga experience than members of Cluster C. These results suggest the possible existence of a developmental trajectory for yoga practitioners. Such a developmental sequence may have important implications for yoga practice and instruction.

K2 eclipsing binaries in the benchmark open cluster Ruprecht 147

NASA Astrophysics Data System (ADS)

Torres, Guillermo

Open clusters are ideal laboratories to study stellar astrophysics. They represent homogeneous collections of hundreds or thousands of stars that were formed together and should therefore have the same age, chemical composition, space motion, and distance. Easily measured properties for member stars such as the brightness and color can be used to infer some of the characteristics of the ensemble including the age and distance, by comparing with model isochrones in the color-magnitude diagram. In recent years space missions such as CoRoT and Kepler have enabled the detection of solar-like oscillations in some of the brighter open cluster members, which can yield asteroseismic estimates of the stellar masses and radii through simple scaling relations anchored on the Sun, and also ages under certain assumptions. Furthermore, when photometric rotation periods of stars can be measured in them, clusters will well-known ages then become essential calibrators for gyrochronology relations, which describe how stars spin down as they get older due to magnetic braking from stellar winds. These relations are important because they provide one of the few empirical ways to age-date field stars. For clusters endowed with detached, double-lined eclipsing binaries amenable to study, even stronger constraints on their properties become available that are of an entirely different nature. The absolute masses and radii of the binary components can be measured very accurately and in a model-independent way, providing an opportunity for stringent tests of stellar evolution theory. The ages that can also be obtained by comparison with models can serve to validate other age estimates mentioned above. Ruprecht 147 is remarkable in that it permits all of these types of studies at the same time. It is the oldest nearby open cluster, with an age of about 3 Gyr and a distance of only 300 pc. This makes it a favorable target for follow-up studies. The metallicity is well determined from previous spectroscopic investigations. It was observed photometrically by the K2 mission for 80 days in late 2015, enabling both asteroseismic and rotation period studies of dozens of members. What makes it truly unique, however, is that it has no less than five eclipsing binaries brighter than 13th magnitude that lend themselves to high-precision mass and radius determinations. No other open cluster has as many, let alone an old one. The brightest binary happens to be at the tip of the turnoff and provides an unusually strong constraint on age. A very special opportunity for study has thus presented itself. This is a proposal to analyze publicly available K2 photometry for the five bright eclipsing binaries discovered in Ruprecht 147, with the goal of fashioning the cluster into an important new benchmark for high-precision testing of stellar astrophysics. We will supplement the K2 light curves, processed with special detrending techniques, with ground-based spectroscopic observations yielding radial velocities for the stars. With these we will derive accurate masses, radii, and temperatures for the components of each binary using well-proven classical methodologies. The impact of the project is that the large number of binaries will allow for an unprecedented and extraordinarily strong test of stellar evolution theory over a range of masses, not available for any other open cluster. The ages we will infer are completely independent of, and of a different nature than other estimates in Ruprecht 147, coming from isochrone fitting in the colormagnitude diagram, asteroseismology of the brighter cluster members, or the use of gyrochronology relations. We will thus have a unique opportunity to cross-validate four different age-dating techniques in the same cluster. Additionally, our accurate eclipsing binary masses and radii will enable crucial tests of the asteroseismic scaling relations, which will improve their use for single stars.

Cluster Adjusted Regression for Displaced Subject Data (CARDS): Marginal Inference under Potentially Informative Temporal Cluster Size Profiles

PubMed Central

Bible, Joe; Beck, James D.; Datta, Somnath

2016-01-01

Summary Ignorance of the mechanisms responsible for the availability of information presents an unusual problem for analysts. It is often the case that the availability of information is dependent on the outcome. In the analysis of cluster data we say that a condition for informative cluster size (ICS) exists when the inference drawn from analysis of hypothetical balanced data varies from that of inference drawn on observed data. Much work has been done in order to address the analysis of clustered data with informative cluster size; examples include Inverse Probability Weighting (IPW), Cluster Weighted Generalized Estimating Equations (CWGEE), and Doubly Weighted Generalized Estimating Equations (DWGEE). When cluster size changes with time, i.e., the data set possess temporally varying cluster sizes (TVCS), these methods may produce biased inference for the underlying marginal distribution of interest. We propose a new marginalization that may be appropriate for addressing clustered longitudinal data with TVCS. The principal motivation for our present work is to analyze the periodontal data collected by Beck et al. (1997, Journal of Periodontal Research 6, 497–505). Longitudinal periodontal data often exhibits both ICS and TVCS as the number of teeth possessed by participants at the onset of study is not constant and teeth as well as individuals may be displaced throughout the study. PMID:26682911

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-09-01

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

Recent Transmission Clustering of HIV-1 C and CRF17_BF Strains Characterized by NNRTI-Related Mutations among Newly Diagnosed Men in Central Italy

PubMed Central

Orchi, Nicoletta; Gori, Caterina; Bertoli, Ada; Forbici, Federica; Montella, Francesco; Pennica, Alfredo; De Carli, Gabriella; Giuliani, Massimo; Continenza, Fabio; Pinnetti, Carmela; Nicastri, Emanuele; Ceccherini-Silberstein, Francesca; Mastroianni, Claudio Maria; Girardi, Enrico; Andreoni, Massimo; Antinori, Andrea; Santoro, Maria Mercedes; Perno, Carlo Federico

2015-01-01

Background Increased evidence of relevant HIV-1 epidemic transmission in European countries is being reported, with an increased circulation of non-B-subtypes. Here, we present two recent HIV-1 non-B transmission clusters characterized by NNRTI-related amino-acidic mutations among newly diagnosed HIV-1 infected men, living in Rome (Central-Italy). Methods Pol and V3 sequences were available at the time of diagnosis for all individuals. Maximum-Likelihood and Bayesian phylogenetic-trees with bootstrap and Bayesian-probability supports defined transmission-clusters. HIV-1 drug-resistance and V3-tropism were also evaluated. Results Among 534 new HIV-1 non-B cases, diagnosed from 2011 to 2014, in Central-Italy, 35 carried virus gathering in two distinct clusters, including 27 HIV-1 C and 8 CRF17_BF subtypes, respectively. Both clusters were centralized in Rome, and their origin was estimated to have been after 2007. All individuals within both clusters were males and 37.1% of them had been recently-infected. While C-cluster was entirely composed by Italian men-who-have-sex-with-men, with a median-age of 34 years (IQR:30–39), individuals in CRF17_BF-cluster were older, with a median-age of 51 years (IQR:48–59) and almost all reported sexual-contacts with men and women. All carried R5-tropic viruses, with evidence of atypical or resistance amino-acidic mutations related to NNRTI-drugs (K103Q in C-cluster, and K101E+E138K in CRF17_BF-cluster). Conclusions These two epidemiological clusters provided evidence of a strong and recent circulation of C and CRF17_BF strains in central Italy, characterized by NNRTI-related mutations among men engaging in high-risk behaviours. These findings underline the role of molecular epidemiology in identifying groups at increased risk of HIV-1 transmission, and in enhancing additional prevention efforts. PMID:26270824

Repair of clustered DNA damage caused by high LET radiation in human fibroblasts

NASA Technical Reports Server (NTRS)

Rydberg, B.; Lobrich, M.; Cooper, P. K.; Chatterjee, A. (Principal Investigator)

1998-01-01

It has recently been demonstrated experimentally that DNA damage induced by high LET radiation in mammalian cells is non-randomly distributed along the DNA molecule in the form of clusters of various sizes. The sizes of such clusters range from a few base-pairs to at least 200 kilobase-pairs. The high biological efficiency of high LET radiation for induction of relevant biological endpoints is probably a consequence of this clustering, although the exact mechanisms by which the clustering affects the biological outcome is not known. We discuss here results for induction and repair of base damage, single-strand breaks and double-strand breaks for low and high LET radiations. These results are discussed in the context of clustering. Of particular interest is to determine how clustering at different scales affects overall rejoining and fidelity of rejoining of DNA double-strand breaks. However, existing methods for measuring repair of DNA strand breaks are unable to resolve breaks that are close together in a cluster. This causes problems in interpretation of current results from high LET radiation and will require new methods to be developed.

Clustering of multiple energy balance related behaviors is associated with body fat composition indicators in adolescents: Results from the HELENA and ELANA studies.

PubMed

Moreira, Naiara Ferraz; da Veiga, Gloria Valeria; Santaliestra-Pasías, Alba María; Androutsos, Odysseas; Cuenca-García, Magdalena; de Oliveira, Alessandra Silva Dias; Pereira, Rosangela Alves; de Moraes, Anelise Bezerra de Vasconcelos; Van den Bussche, Karen; Censi, Laura; González-Gross, Marcela; Cañada, David; Gottrand, Frederic; Kafatos, Anthony; Marcos, Ascensión; Widhalm, Kurt; Mólnar, Dénes; Moreno, Luis Alberto

2018-01-01

The objective of this study was to identify clustering patterns of four energy balance-related behaviors (EBRB): television (TV) watching, moderate and vigorous physical activity (MVPA), consumption of fruits and vegetables (F&V), and consumption of sugar-sweetened beverages (SSB), among European and Brazilian adolescents. EBRB associations with different body fat composition indicators were then evaluated. Participants included adolescents from eight European countries in the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescents) study (n = 2,057, 53.8% female; age: 12.5-17.5 years) and from the metropolitan region of Rio de Janeiro/Brazil in the ELANA study (the Adolescent Nutritional Assessment Longitudinal Study) (n = 968, 53.2% female; age: 13.5-19 years). EBRB data allowed for sex- and study-specific clusters. Associations were estimated by ANOVA and odds ratios. Five clustering patterns were identified. Four similar clusters were identified for each sex and study. Among boys, different cluster identified was characterized by high F&V consumption in the HELENA study and high TV watching and high MVPA time in the ELANA study. Among girls, the different clusters identified was characterized by high F&V consumption in both studies and, additionally, high SSB consumption in the ELANA study. Regression analysis showed that clusters characterized by high SSB consumption in European boys; high TV watching, and high TV watching plus high MVPA in Brazilian boys; and high MVPA, and high SSB and F&V consumption in Brazilian girls, were positively associated with different body fat composition indicators. Common clusters were observed in adolescents from Europe and Brazil, however, no cluster was identified as being completely healthy or unhealthy. Each cluster seems to impact on body composition indicators, depending on the group. Public health actions should aim to promote adequate practices of EBRB. Copyright © 2017. Published by Elsevier Ltd.

Fundamental parameters of the highly reddened young open clusters Westerlund 1 and 2

NASA Astrophysics Data System (ADS)

Piatti, A. E.; Bica, E.; Claria, J. J.

1998-02-01

We study the compact open clusters Westerlund1 (BH197) and Westerlund2. We present CCD integrated spectroscopy for both clusters, and CCD imaging in the V and I bands for the former one. So far, Westerlund1 is possibly the most reddened open cluster studied in detail (Av ~ 13.0). It has an age of 8 +/- 3 Myr and a distance from the Sun of d_sun ~ 1.0 +/- 0.4 kpc. For Westerlund2 we derive a visual absorption AV~ 5.0 mag, an age of 2-3 Myr, and d_sun=5.7+/- 0.3 kpc. From luminosity and structural arguments we conclude that Westerlund1, although young and compact, it is a massive cluster, in contrast to Westerlund2. Based on observations made at Complejo Astronómico El Leoncito, which is operated under agreement between the Consejo Nacional de Investigaciones Cientificas y Tecnicas de la Republica Argentina and the Universities of La Plata, Cordoba and San Juan, Argentina, and at the University of Toronto (David Dunlap Observatory) 24-inch telescope, Las Campanas, Chile. The photometric observations are available at CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/Abstract.html

A Scalable Monitoring for the CMS Filter Farm Based on Elasticsearch

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

Andre, J.M.; et al.

2015-12-23

A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small documents using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured informationmore » can be queried in non-predetermined ways. The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing natural horizontal scaling. A separate central” es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters. The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2.« less

RNA-Seq Analysis Using De Novo Transcriptome Assembly as a Reference for the Salmon Louse Caligus rogercresseyi

PubMed Central

Gallardo-Escárate, Cristian; Valenzuela-Muñoz, Valentina; Nuñez-Acuña, Gustavo

2014-01-01

Despite the economic and environmental impacts that sea lice infestations have on salmon farming worldwide, genomic data generated by high-throughput transcriptome sequencing for different developmental stages, sexes, and strains of sea lice is still limited or unknown. In this study, RNA-seq analysis was performed using de novo transcriptome assembly as a reference for evidenced transcriptional changes from six developmental stages of the salmon louse Caligus rogercresseyi. EST-datasets were generated from the nauplius I, nauplius II, copepodid and chalimus stages and from female and male adults using MiSeq Illumina sequencing. A total of 151,788,682 transcripts were yielded, which were assembled into 83,444 high quality contigs and subsequently annotated into roughly 24,000 genes based on known proteins. To identify differential transcription patterns among salmon louse stages, cluster analyses were performed using normalized gene expression values. Herein, four clusters were differentially expressed between nauplius I–II and copepodid stages (604 transcripts), five clusters between copepodid and chalimus stages (2,426 transcripts), and six clusters between female and male adults (2,478 transcripts). Gene ontology analysis revealed that the nauplius I–II, copepodid and chalimus stages are mainly annotated to aminoacid transfer/repair/breakdown, metabolism, molting cycle, and nervous system development. Additionally, genes showing differential transcription in female and male adults were highly related to cytoskeletal and contractile elements, reproduction, cell development, morphogenesis, and transcription-translation processes. The data presented in this study provides the most comprehensive transcriptome resource available for C. rogercresseyi, which should be used for future genomic studies linked to host-parasite interactions. PMID:24691066

RNA-Seq analysis using de novo transcriptome assembly as a reference for the salmon louse Caligus rogercresseyi.

PubMed

Gallardo-Escárate, Cristian; Valenzuela-Muñoz, Valentina; Nuñez-Acuña, Gustavo

2014-01-01

Despite the economic and environmental impacts that sea lice infestations have on salmon farming worldwide, genomic data generated by high-throughput transcriptome sequencing for different developmental stages, sexes, and strains of sea lice is still limited or unknown. In this study, RNA-seq analysis was performed using de novo transcriptome assembly as a reference for evidenced transcriptional changes from six developmental stages of the salmon louse Caligus rogercresseyi. EST-datasets were generated from the nauplius I, nauplius II, copepodid and chalimus stages and from female and male adults using MiSeq Illumina sequencing. A total of 151,788,682 transcripts were yielded, which were assembled into 83,444 high quality contigs and subsequently annotated into roughly 24,000 genes based on known proteins. To identify differential transcription patterns among salmon louse stages, cluster analyses were performed using normalized gene expression values. Herein, four clusters were differentially expressed between nauplius I-II and copepodid stages (604 transcripts), five clusters between copepodid and chalimus stages (2,426 transcripts), and six clusters between female and male adults (2,478 transcripts). Gene ontology analysis revealed that the nauplius I-II, copepodid and chalimus stages are mainly annotated to aminoacid transfer/repair/breakdown, metabolism, molting cycle, and nervous system development. Additionally, genes showing differential transcription in female and male adults were highly related to cytoskeletal and contractile elements, reproduction, cell development, morphogenesis, and transcription-translation processes. The data presented in this study provides the most comprehensive transcriptome resource available for C. rogercresseyi, which should be used for future genomic studies linked to host-parasite interactions.

Application of fuzzy c-means clustering to PRTR chemicals uncovering their release and toxicity characteristics.

PubMed

Xue, Mianqiang; Zhou, Liang; Kojima, Naoya; Dos Muchangos, Leticia Sarmento; Machimura, Takashi; Tokai, Akihiro

2018-05-01

Increasing manufacture and usage of chemicals have not been matched by the increase in our understanding of their risks. Pollutant release and transfer register (PRTR) is becoming a popular measure for collecting chemical data and enhancing the public right to know. However, these data are usually in high dimensionality which restricts their wider use. The present study partitions Japanese PRTR chemicals into five fuzzy clusters by fuzzy c-mean clustering (FCM) to explore the implicit information. Each chemical with membership degrees belongs to each cluster. Cluster I features high releases from non-listed industries and the household sector and high environmental toxicity. Cluster II is characterized by high reported releases and transfers from 24 listed industries above the threshold, mutagenicity, and high environmental toxicity. Chemicals in cluster III have characteristics of high releases from non-listed industries and low toxicity. Cluster IV is characterized by high reported releases and transfers from 24 listed industries above the threshold and extremely high environmental toxicity. Cluster V is characterized by low releases yet mutagenicity and high carcinogenicity. Chemicals with the highest membership degree were identified as representatives for each cluster. For the highest membership degree, half of the chemicals have a value higher than 0.74. If we look at both the highest and the second highest membership degrees simultaneously, about 94% of the chemicals have a value higher than 0.5. FCM can serve as an approach to uncover the implicit information of highly complex chemical dataset, which subsequently supports the strategy development for efficient and effective chemical management. Copyright © 2017 Elsevier B.V. All rights reserved.

Thermal and Non-thermal Nature of the Soft Excess Emission from Sersic 159-03 observed with XMM-Newton

NASA Technical Reports Server (NTRS)

Bonamente, Massimiliano; Lieu, Richard; Mittaz, Jonathan P. D.; Kaastra, Jelle S.; Nevalainen, Jukka

2005-01-01

Several nearby clusters exhibit an excess of soft X-ray radiation which cannot be attributed to the hot virialized intra-cluster medium. There is no consensus to date on the origin of the excess emission: it could be either of thermal origin, or due to an inverse Compton scattering of the cosmic microwave background. Using high resolution XMM-Newton data of Sersic 159-03 we first show that strong soft excess emission is detected out to a radial distance of 0.9 Mpc. The data are interpreted using the two viable models available, i.e., by invoking a warm reservoir of thermal gas, or relativistic electrons which are part of a cosmic ray population. The thermal model leads to a better goodness-of-fit, and the emitting warm gas must be high in mass and low in metallicity.

Signature of non-isotropic distribution of stellar rotation inclination angles in the Praesepe cluster

NASA Astrophysics Data System (ADS)

Kovacs, Geza

2018-04-01

The distribution of the stellar rotation axes of 113 main sequence stars in the open cluster Praesepe are examined by using current photometric rotation periods, spectroscopic rotation velocities, and estimated stellar radii. Three different samples of stellar rotation data on spotted stars from the Galactic field and two independent samples of planetary hosts are used as control samples to support the consistency of the analysis. Considering the high completeness of the Praesepe sample and the behavior of the control samples, we find that the main sequence F - K stars in this cluster are susceptible to rotational axis alignment. Using a cone model, the most likely inclination angle is 76° ± 14° with a half opening angle of 47° ± 24°. Non-isotropic distribution of the inclination angles is preferred over the isotropic distribution, except if the rotation velocities used in this work are systematically overestimated. We found no indication of this being the case on the basis of the currently available data. Data are only available at the CDS, together with the other two compiled datasets used in this paper, via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/612/L2

Camps 2.0: exploring the sequence and structure space of prokaryotic, eukaryotic, and viral membrane proteins.

PubMed

Neumann, Sindy; Hartmann, Holger; Martin-Galiano, Antonio J; Fuchs, Angelika; Frishman, Dmitrij

2012-03-01

Structural bioinformatics of membrane proteins is still in its infancy, and the picture of their fold space is only beginning to emerge. Because only a handful of three-dimensional structures are available, sequence comparison and structure prediction remain the main tools for investigating sequence-structure relationships in membrane protein families. Here we present a comprehensive analysis of the structural families corresponding to α-helical membrane proteins with at least three transmembrane helices. The new version of our CAMPS database (CAMPS 2.0) covers nearly 1300 eukaryotic, prokaryotic, and viral genomes. Using an advanced classification procedure, which is based on high-order hidden Markov models and considers both sequence similarity as well as the number of transmembrane helices and loop lengths, we identified 1353 structurally homogeneous clusters roughly corresponding to membrane protein folds. Only 53 clusters are associated with experimentally determined three-dimensional structures, and for these clusters CAMPS is in reasonable agreement with structure-based classification approaches such as SCOP and CATH. We therefore estimate that ∼1300 structures would need to be determined to provide a sufficient structural coverage of polytopic membrane proteins. CAMPS 2.0 is available at http://webclu.bio.wzw.tum.de/CAMPS2.0/. Copyright © 2011 Wiley Periodicals, Inc.

B38: an all-boron fullerene analogue

NASA Astrophysics Data System (ADS)

Lv, Jian; Wang, Yanchao; Zhu, Li; Ma, Yanming

2014-09-01

Fullerene-like structures formed by elements other than carbon have long been sought. Finding all-boron (B) fullerene-like structures is challenging due to the geometrical frustration arising from competitions among various structural motifs. We report here the prediction of a B38 fullerene analogue found through first-principles swarm structure searching calculations. The structure is highly symmetric and consists of 56 triangles and four hexagons, which provide an optimal void in the center of the cage. Energetically, it is more favorable than the planar and tubular structures, and possesses an unusually high chemical stability: a large energy gap (~2.25 eV) and a high double aromaticity, superior to those of most aromatic quasi-planar B12 and double-ring B20 clusters. Our findings represent a key step forward towards to the understanding of structures of medium-sized B clusters and map out the experimental direction of the synthesis of an all-B fullerene analogue.Fullerene-like structures formed by elements other than carbon have long been sought. Finding all-boron (B) fullerene-like structures is challenging due to the geometrical frustration arising from competitions among various structural motifs. We report here the prediction of a B38 fullerene analogue found through first-principles swarm structure searching calculations. The structure is highly symmetric and consists of 56 triangles and four hexagons, which provide an optimal void in the center of the cage. Energetically, it is more favorable than the planar and tubular structures, and possesses an unusually high chemical stability: a large energy gap (~2.25 eV) and a high double aromaticity, superior to those of most aromatic quasi-planar B12 and double-ring B20 clusters. Our findings represent a key step forward towards to the understanding of structures of medium-sized B clusters and map out the experimental direction of the synthesis of an all-B fullerene analogue. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr01846j

STAR CLUSTERS IN M33: UPDATED UBVRI PHOTOMETRY, AGES, METALLICITIES, AND MASSES

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

Fan, Zhou; De Grijs, Richard, E-mail: zfan@bao.ac.cn, E-mail: grijs@pku.edu.cn

2014-04-01

The photometric characterization of M33 star clusters is far from complete. In this paper, we present homogeneous UBVRI photometry of 708 star clusters and cluster candidates in M33 based on archival images from the Local Group Galaxies Survey, which covers 0.8 deg{sup 2} along the galaxy's major axis. Our photometry includes 387, 563, 616, 580, and 478 objects in the UBVRI bands, respectively, of which 276, 405, 430, 457, and 363 do not have previously published UBVRI photometry. Our photometry is consistent with previous measurements (where available) in all filters. We adopted Sloan Digital Sky Survey ugriz photometry for complementarymore » purposes, as well as Two Micron All Sky Survey near-infrared JHK photometry where available. We fitted the spectral-energy distributions of 671 star clusters and candidates to derive their ages, metallicities, and masses based on the updated PARSEC simple stellar populations synthesis models. The results of our χ{sup 2} minimization routines show that only 205 of the 671 clusters (31%) are older than 2 Gyr, which represents a much smaller fraction of the cluster population than that in M31 (56%), suggesting that M33 is dominated by young star clusters (<1 Gyr). We investigate the mass distributions of the star clusters—both open and globular clusters—in M33, M31, the Milky Way, and the Large Magellanic Cloud. Their mean values are log (M {sub cl}/M {sub ☉}) = 4.25, 5.43, 2.72, and 4.18, respectively. The fraction of open to globular clusters is highest in the Milky Way and lowest in M31. Our comparisons of the cluster ages, masses, and metallicities show that our results are basically in agreement with previous studies (where objects in common are available); differences can be traced back to differences in the models adopted, the fitting methods used, and stochastic sampling effects.« less

Distant clusters of galaxies in the 2XMM/SDSS footprint: follow-up observations with the LBT

NASA Astrophysics Data System (ADS)

Rabitz, A.; Lamer, G.; Schwope, A.; Takey, A.

2017-11-01

Context. Galaxy clusters at high redshift are important to test cosmological models and models for the growth of structure. They are difficult to find in wide-angle optical surveys, however, leaving dedicated follow-up of X-ray selected candidates as one promising identification route. Aims: We aim to increase the number of galaxy clusters beyond the SDSS-limit, z 0.75. Methods: We compiled a list of extended X-ray sources from the 2XMMp catalogue within the footprint of the Sloan Digital Sky Survey. Fields without optical counterpart were selected for further investigation. Deep optical imaging and follow-up spectroscopy were obtained with the Large Binocular Telescope, Arizona (LBT), of those candidates not known to the literature. Results: From initially 19 candidates, selected by visually screening X-ray images of 478 XMM-Newton observations and the corresponding SDSS images, 6 clusters were found in the literature. Imaging data through r,z filters were obtained for the remaining candidates, and 7 were chosen for multi-object (MOS) spectroscopy. Spectroscopic redshifts, optical magnitudes, and X-ray parameters (flux, temperature, and luminosity) are presented for the clusters with spectroscopic redshifts. The distant clusters studied here constitute one additional redshift bin for studies of the LX-T relation, which does not seem to evolve from high to low redshifts. Conclusions: The selection method of distant galaxy clusters presented here was highly successful. It is based solely on archival optical (SDSS) and X-ray (XMM-Newton) data. Out of 19 selected candidates, 6 of the 7 candidates selected for spectroscopic follow-up were verified as distant clusters, a further candidate is most likely a group of galaxies at z 1.21. Out of the remaining 12 candidates, 6 were known previously as galaxy clusters, one object is a likely X-ray emission from an AGN radio jet, and for 5 we see no clear evidence for them to be high-redshift galaxy clusters. Based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA.The LBT is an international collaboration among institutions in the United States, Italy and Germany. LBT Corporation partners are: the University of Arizona on behalf of the Arizona Board of Regents; Istituto Nazionale di Astrofisica, Italy; LBT Beteiligungsgesellschaft, Germany, representing the Max-Planck Society, The Leibniz Institute for Astrophysics Potsdam, and Heidelberg University; The Ohio State University, and The Research Corporation, on behalf of The University of Notre Dame, University of Minnesota and University of Virginia - http://www.lbto.org/for-investigators.htmlThe catalogue, similar to Table A.1, is also available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/607/A56

Homogeneity Pursuit

PubMed Central

Ke, Tracy; Fan, Jianqing; Wu, Yichao

2014-01-01

This paper explores the homogeneity of coefficients in high-dimensional regression, which extends the sparsity concept and is more general and suitable for many applications. Homogeneity arises when regression coefficients corresponding to neighboring geographical regions or a similar cluster of covariates are expected to be approximately the same. Sparsity corresponds to a special case of homogeneity with a large cluster of known atom zero. In this article, we propose a new method called clustering algorithm in regression via data-driven segmentation (CARDS) to explore homogeneity. New mathematics are provided on the gain that can be achieved by exploring homogeneity. Statistical properties of two versions of CARDS are analyzed. In particular, the asymptotic normality of our proposed CARDS estimator is established, which reveals better estimation accuracy for homogeneous parameters than that without homogeneity exploration. When our methods are combined with sparsity exploration, further efficiency can be achieved beyond the exploration of sparsity alone. This provides additional insights into the power of exploring low-dimensional structures in high-dimensional regression: homogeneity and sparsity. Our results also shed lights on the properties of the fussed Lasso. The newly developed method is further illustrated by simulation studies and applications to real data. Supplementary materials for this article are available online. PMID:26085701

Young Galaxy Candidates in the Hubble Frontier Fields. IV. MACS J1149.5+2223

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zitrin, Adi; Infante, Leopoldo; Laporte, Nicolas; Huang, Xingxing; Moustakas, John; Ford, Holland C.; Shu, Xinwen; Wang, Junxian; Diego, Jose M.; Bauer, Franz E.; Troncoso Iribarren, Paulina; Broadhurst, Tom; Molino, Alberto

2017-02-01

We search for high-redshift dropout galaxies behind the Hubble Frontier Fields (HFF) galaxy cluster MACS J1149.5+2223, a powerful cosmic lens that has revealed a number of unique objects in its field. Using the deep images from the Hubble and Spitzer space telescopes, we find 11 galaxies at z > 7 in the MACS J1149.5+2223 cluster field, and 11 in its parallel field. The high-redshift nature of the bright z ≃ 9.6 galaxy MACS1149-JD, previously reported by Zheng et al., is further supported by non-detection in the extremely deep optical images from the HFF campaign. With the new photometry, the best photometric redshift solution for MACS1149-JD reduces slightly to z = 9.44 ± 0.12. The young galaxy has an estimated stellar mass of (7+/- 2)× {10}8 {M}⊙ , and was formed at z={13.2}-1.6+1.9 when the universe was ≈300 Myr old. Data available for the first four HFF clusters have already enabled us to find faint galaxies to an intrinsic magnitude of {M}{UV}≃ -15.5, approximately a factor of 10 deeper than the parallel fields.

Genomic Analysis of 15 Human Coronaviruses OC43 (HCoV-OC43s) Circulating in France from 2001 to 2013 Reveals a High Intra-Specific Diversity with New Recombinant Genotypes

PubMed Central

Kin, Nathalie; Miszczak, Fabien; Lin, Wei; Ar Gouilh, Meriadeg; Vabret, Astrid

2015-01-01

Human coronavirus OC43 (HCoV-OC43) is one of five currently circulating human coronaviruses responsible for respiratory infections. Like all coronaviruses, it is characterized by its genome’s high plasticity. The objectives of the current study were to detect genetically distinct genotypes and eventually recombinant genotypes in samples collected in Lower Normandy between 2001 and 2013. To this end, we sequenced complete nsp12, S, and N genes of 15 molecular isolates of HCoV-OC43 from clinical samples and compared them to available data from the USA, Belgium, and Hong-Kong. A new cluster E was invariably detected from nsp12, S, and N data while the analysis of nsp12 and N genes revealed the existence of new F and G clusters respectively. The association of these different clusters of genes in our specimens led to the description of thirteen genetically distinct genotypes, among which eight recombinant viruses were discovered. Identification of these recombinant viruses, together with temporal analysis and tMRCA estimation, provides important information for understanding the dynamics of the evolution of these epidemic coronaviruses. PMID:26008694

Deep multi-frequency rotation measure tomography of the galaxy cluster A2255

NASA Astrophysics Data System (ADS)

Pizzo, R. F.; de Bruyn, A. G.; Bernardi, G.; Brentjens, M. A.

2011-01-01

Aims: By studying the polarimetric properties of the radio galaxies and the radio filaments belonging to the galaxy cluster Abell 2255, we aim to unveil their 3-dimensional location within the cluster. Methods: We performed WSRT observations of A2255 at 18, 21, 25, 85, and 200 cm. The polarization images of the cluster were processed through rotation measure (RM) synthesis, producing three final RM cubes. Results: The radio galaxies and the filaments at the edges of the halo are detected in the high-frequency RM cube, obtained by combining the data at 18, 21, and 25 cm. Their Faraday spectra show different levels of complexity. The radio galaxies lying near by the cluster center have Faraday spectra with multiple peaks, while those at large distances show only one peak, as do the filaments. Similar RM distributions are observed for the external radio galaxies and for the filaments, with much lower average RM values and RM variance than those found in previous works for the central radio galaxies. The 85 cm RM cube is dominated by the Galactic foreground emission, but it also shows features associated with the cluster. At 2 m, no polarized emission from A2255 nor our Galaxy is detected. Conclusions: The radial trend observed in the RM distributions of the radio galaxies and in the complexity of their Faraday spectra favors the interpretation that the external Faraday screen for all the sources in A2255 is the ICM. Its differential contribution depends on the amount of medium that the radio signal crosses along the line of sight. The filaments should therefore be located at the periphery of the cluster, and their apparent central location comes from projection effects. Their high fractional polarization and morphology suggest that they are relics rather than part of a genuine radio halo. Their inferred large distance from the cluster center and their geometry could argue for an association with large-scale structure (LSS) shocks. The RM cubes in gif format are only available in electronic form at http://www.aanda.org. To request the RM cubes in FITS format, please contact R. F. Pizzo at: pizzo@astron.nl

The role of highly oxygenated molecules (HOMs) in determining the composition of ambient ions in the boreal forest

NASA Astrophysics Data System (ADS)

Bianchi, Federico; Garmash, Olga; He, Xucheng; Yan, Chao; Iyer, Siddharth; Rosendahl, Ida; Xu, Zhengning; Rissanen, Matti P.; Riva, Matthieu; Taipale, Risto; Sarnela, Nina; Petäjä, Tuukka; Worsnop, Douglas R.; Kulmala, Markku; Ehn, Mikael; Junninen, Heikki

2017-11-01

In order to investigate the negative ions in the boreal forest we have performed measurements to chemically characterise the composition of negatively charged clusters containing highly oxygenated molecules (HOMs). Additionally, we compared this information with the chemical composition of the neutral gas-phase molecules detected in the ambient atmosphere during the same period. The chemical composition of the ions was retrieved using an atmospheric pressure interface time-of-flight mass spectrometer (APi-TOF-MS) while the gas-phase neutral molecules (mainly sulfuric acid and HOMs) were characterised using the same mass spectrometer coupled to a nitrate-based chemical ionisation unit (CI-APi-TOF). Overall, we divided the identified HOMs in two classes: HOMs containing only carbon, hydrogen and oxygen and nitrogen-containing HOMs or organonitrates (ONs). During the day, among the ions, in addition to the well-known pure sulfuric acid clusters, we found a large number of HOMs clustered with nitrate (NO3-) or bisulfate (HSO4-), with the first one being more abundant. During the night, the distribution of ions, mainly composed of HOM clustered with NO3-, was very similar to the neutral compounds that are detected in the CI-APi-TOF as adducts with the artificially introduced primary ion (NO3-). For the first time, we identified several clusters containing up to 40 carbon atoms. These ions are formed by up to four oxidised α-pinene units clustered with NO3-. While we know that dimers (16-20 carbon atoms) are probably formed by a covalent bond between two α-pinene oxidised units, it is still unclear what bonding formed larger clusters. Finally, diurnal profiles of the negative ions were consistent with the neutral compounds revealing that ONs peak during the day while HOMs are more abundant at night-time. However, during the day, a large fraction of the negative charge is taken up by the pure sulfuric acid clusters causing differences between ambient ions and neutral compounds (i.e. less available charge for HOM and ON).

Legacy ExtraGalactic UV Survey (LEGUS): The HST View of Star Formation in Nearby Galaxies

NASA Astrophysics Data System (ADS)

Calzetti, Daniela; Lee, J. C.; Adamo, A.; Aloisi, A.; Andrews, J. E.; Brown, T. M.; Chandar, R.; Christian, C. A.; Cignoni, M.; Clayton, G. C.; Da Silva, R. L.; de Mink, S. E.; Dobbs, C.; Elmegreen, B.; Elmegreen, D. M.; Evans, A. S.; Fumagalli, M.; Gallagher, J. S.; Gouliermis, D.; Grebel, E.; Herrero-Davo`, A.; Hilbert, B.; Hunter, D. A.; Johnson, K. E.; Kennicutt, R.; Kim, H.; Krumholz, M. R.; Lennon, D. J.; Martin, C. D.; Nair, P.; Nota, A.; Pellerin, A.; Prieto, J.; Regan, M. W.; Sabbi, E.; Schaerer, D.; Schiminovich, D.; Smith, L. J.; Thilker, D. A.; Tosi, M.; Van Dyk, S. D.; Walterbos, R. A.; Whitmore, B. C.; Wofford, A.

2014-01-01

The Treasury program LEGUS (HST/GO-13364) is the first HST UV Atlas of nearby galaxies, and is aimed at the thorough investigation of star formation and its relation with galaxy environment, from the scales of individual stars to those of ~kpc clustered structures. The 154-orbits program is obtaining NUV,U,B,V,I images of 50 star-forming galaxies in the distance range 4-12 Mpc, covering the full range of morphology, star formation rate (SFR), mass, metallicity, internal structure, and interaction state found in the local Universe. The imaging survey will yield accurate recent (<50 Myr) star formation histories (SFHs) from resolved massive stars, and the extinction-corrected ages and masses of star clusters and associations. These extensive inventories of massive stars, clustered systems, and SFHs will be used to: (1) quantify how the clustering of star formation evolves both in space and in time; (2) discriminate among models of star cluster evolution; (3) investigate the effects of SFH on the UV SFR calibrations; (4) explore the impact of environment on star formation and cluster evolution across the full range of galactic and ISM properties. LEGUS observations will inform theories of star formation and galaxy evolution, and improve the understanding of the physical underpinning of the gas-star formation relation and the nature of the clumpy star formation at high redshift. LEGUS will generate the most homogeneous high-resolution, wide-field UV dataset to date, building and expanding on the GALEX legacy. Data products that will be delivered to the community include: catalogs of massive stars and star clusters, catalogs of star cluster properties (ages, masses, extinction), and a one-stop shop for all the ancillary data available for this well-studied galaxy sample. LEGUS will provide the reference survey and the foundation for future observations with JWST and with ALMA. This abstract accompanies another one from the same project, and presents the status of the project, its structure, and the data products that will be delivered to the community; the other abstract presents the science goals of LEGUS and how these will be addressed by the HST observations.

clusterProfiler: an R package for comparing biological themes among gene clusters.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Han, Yanyan; He, Qing-Yu

2012-05-01

Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

CGDM: collaborative genomic data model for molecular profiling data using NoSQL.

PubMed

Wang, Shicai; Mares, Mihaela A; Guo, Yi-Ke

2016-12-01

High-throughput molecular profiling has greatly improved patient stratification and mechanistic understanding of diseases. With the increasing amount of data used in translational medicine studies in recent years, there is a need to improve the performance of data warehouses in terms of data retrieval and statistical processing. Both relational and Key Value models have been used for managing molecular profiling data. Key Value models such as SeqWare have been shown to be particularly advantageous in terms of query processing speed for large datasets. However, more improvement can be achieved, particularly through better indexing techniques of the Key Value models, taking advantage of the types of queries which are specific for the high-throughput molecular profiling data. In this article, we introduce a Collaborative Genomic Data Model (CGDM), aimed at significantly increasing the query processing speed for the main classes of queries on genomic databases. CGDM creates three Collaborative Global Clustering Index Tables (CGCITs) to solve the velocity and variety issues at the cost of limited extra volume. Several benchmarking experiments were carried out, comparing CGDM implemented on HBase to the traditional SQL data model (TDM) implemented on both HBase and MySQL Cluster, using large publicly available molecular profiling datasets taken from NCBI and HapMap. In the microarray case, CGDM on HBase performed up to 246 times faster than TDM on HBase and 7 times faster than TDM on MySQL Cluster. In single nucleotide polymorphism case, CGDM on HBase outperformed TDM on HBase by up to 351 times and TDM on MySQL Cluster by up to 9 times. The CGDM source code is available at https://github.com/evanswang/CGDM. y.guo@imperial.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A coarse to fine minutiae-based latent palmprint matching.

PubMed

Liu, Eryun; Jain, Anil K; Tian, Jie

2013-10-01

With the availability of live-scan palmprint technology, high resolution palmprint recognition has started to receive significant attention in forensics and law enforcement. In forensic applications, latent palmprints provide critical evidence as it is estimated that about 30 percent of the latents recovered at crime scenes are those of palms. Most of the available high-resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy. Considering the large number of minutiae (about 1,000 minutiae in a full palmprint compared to about 100 minutiae in a rolled fingerprint) and large area of foreground region in full palmprints, novel strategies need to be developed for efficient and robust latent palmprint matching. In this paper, a coarse to fine matching strategy based on minutiae clustering and minutiae match propagation is designed specifically for palmprint matching. To deal with the large number of minutiae, a local feature-based minutiae clustering algorithm is designed to cluster minutiae into several groups such that minutiae belonging to the same group have similar local characteristics. The coarse matching is then performed within each cluster to establish initial minutiae correspondences between two palmprints. Starting with each initial correspondence, a minutiae match propagation algorithm searches for mated minutiae in the full palmprint. The proposed palmprint matching algorithm has been evaluated on a latent-to-full palmprint database consisting of 446 latents and 12,489 background full prints. The matching results show a rank-1 identification accuracy of 79.4 percent, which is significantly higher than the 60.8 percent identification accuracy of a state-of-the-art latent palmprint matching algorithm on the same latent database. The average computation time of our algorithm for a single latent-to-full match is about 141 ms for genuine match and 50 ms for impostor match, on a Windows XP desktop system with 2.2-GHz CPU and 1.00-GB RAM. The computation time of our algorithm is an order of magnitude faster than a previously published state-of-the-art-algorithm.

THE SPITZER SPACE TELESCOPE SURVEY OF THE ORION A AND B MOLECULAR CLOUDS. II. THE SPATIAL DISTRIBUTION AND DEMOGRAPHICS OF DUSTY YOUNG STELLAR OBJECTS

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

Megeath, S. T.; Kryukova, E.; Gutermuth, R.

2016-01-15

We analyze the spatial distribution of dusty young stellar objects (YSOs) identified in the Spitzer Survey of the Orion Molecular clouds, augmenting these data with Chandra X-ray observations to correct for incompleteness in dense clustered regions. We also devise a scheme to correct for spatially varying incompleteness when X-ray data are not available. The local surface densities of the YSOs range from 1 pc{sup −2} to over 10,000 pc{sup −2}, with protostars tending to be in higher density regions. This range of densities is similar to other surveyed molecular clouds with clusters, but broader than clouds without clusters. By identifyingmore » clusters and groups as continuous regions with surface densities ≥10 pc{sup −2}, we find that 59% of the YSOs are in the largest cluster, the Orion Nebula Cluster (ONC), while 13% of the YSOs are found in a distributed population. A lower fraction of protostars in the distributed population is evidence that it is somewhat older than the groups and clusters. An examination of the structural properties of the clusters and groups shows that the peak surface densities of the clusters increase approximately linearly with the number of members. Furthermore, all clusters with more than 70 members exhibit asymmetric and/or highly elongated structures. The ONC becomes azimuthally symmetric in the inner 0.1 pc, suggesting that the cluster is only ∼2 Myr in age. We find that the star formation efficiency (SFE) of the Orion B cloud is unusually low, and that the SFEs of individual groups and clusters are an order of magnitude higher than those of the clouds. Finally, we discuss the relationship between the young low mass stars in the Orion clouds and the Orion OB 1 association, and we determine upper limits to the fraction of disks that may be affected by UV radiation from OB stars or dynamical interactions in dense, clustered regions.« less

A cluster randomized implementation trial to measure the effectiveness of an intervention package aiming to increase the utilization of skilled birth attendants by women for childbirth: study protocol

PubMed Central

2014-01-01

Background Nepal is on track to achieve MDG 5 but there is a huge sub-national disparity with existing high maternal mortality in western and hilly regions. The national priority is to reduce this disparity to achieve the goal at sub-national level. Evidences from developing countries show that increasing utilization of skilled attendant at birth is an important indicator for reducing maternal death. Further, there is a very low utilization during childbirth in western and hilly regions of Nepal which clearly depicts the barriers in utilization of skilled birth attendants. So, there is a need to overcome the identified barriers to increase the utilization thereby decreasing the maternal mortality. The hypothesis of this study is that through a package of interventions the utilization of skilled birth attendants will be increased and hence improve maternal health in Nepal. Method/Design This study involves a cluster randomized controlled trial involving approximately 5000 pregnant women in 36 clusters. The 18 intervention clusters will receive the following interventions: i) mobilization of family support for pregnant women to reach the health facility, ii) availability of emergency funds for institutional childbirth, iii) availability of transport options to reach a health facility for childbirth, iv) training to health workers on communication skills, v) security provisions for SBAs to reach services 24/24 through community mobilization; 18 control clusters will not receive the intervention package. The final evaluation of the intervention is planned to be completed by October 2014. Primary study output of this study is utilization of SBA services. Secondary study outputs measure the uptake of antenatal care, post natal checkup for mother and baby, availability of transportation for childbirth, operation of emergency fund, improved reception of women at health services, and improved physical security of SBAs. Discussion The intervention package is designed to increase the utilization of skilled birth attendants by overcoming the barriers related to awareness, finance, transport, security etc. If proven effective, the Ministry of Health has committed to scale up the intervention package throughout the country. Trial registration number ISRCTN78892490. PMID:24646123

Accelerating epistasis analysis in human genetics with consumer graphics hardware.

PubMed

Sinnott-Armstrong, Nicholas A; Greene, Casey S; Cancare, Fabio; Moore, Jason H

2009-07-24

Human geneticists are now capable of measuring more than one million DNA sequence variations from across the human genome. The new challenge is to develop computationally feasible methods capable of analyzing these data for associations with common human disease, particularly in the context of epistasis. Epistasis describes the situation where multiple genes interact in a complex non-linear manner to determine an individual's disease risk and is thought to be ubiquitous for common diseases. Multifactor Dimensionality Reduction (MDR) is an algorithm capable of detecting epistasis. An exhaustive analysis with MDR is often computationally expensive, particularly for high order interactions. This challenge has previously been met with parallel computation and expensive hardware. The option we examine here exploits commodity hardware designed for computer graphics. In modern computers Graphics Processing Units (GPUs) have more memory bandwidth and computational capability than Central Processing Units (CPUs) and are well suited to this problem. Advances in the video game industry have led to an economy of scale creating a situation where these powerful components are readily available at very low cost. Here we implement and evaluate the performance of the MDR algorithm on GPUs. Of primary interest are the time required for an epistasis analysis and the price to performance ratio of available solutions. We found that using MDR on GPUs consistently increased performance per machine over both a feature rich Java software package and a C++ cluster implementation. The performance of a GPU workstation running a GPU implementation reduces computation time by a factor of 160 compared to an 8-core workstation running the Java implementation on CPUs. This GPU workstation performs similarly to 150 cores running an optimized C++ implementation on a Beowulf cluster. Furthermore this GPU system provides extremely cost effective performance while leaving the CPU available for other tasks. The GPU workstation containing three GPUs costs $2000 while obtaining similar performance on a Beowulf cluster requires 150 CPU cores which, including the added infrastructure and support cost of the cluster system, cost approximately $82,500. Graphics hardware based computing provides a cost effective means to perform genetic analysis of epistasis using MDR on large datasets without the infrastructure of a computing cluster.

A cluster randomized implementation trial to measure the effectiveness of an intervention package aiming to increase the utilization of skilled birth attendants by women for childbirth: study protocol.

PubMed

Bhandari, Gajananda P; Subedi, Narayan; Thapa, Janak; Choulagai, Bishnu; Maskey, Mahesh K; Onta, Sharad R

2014-03-19

Nepal is on track to achieve MDG 5 but there is a huge sub-national disparity with existing high maternal mortality in western and hilly regions. The national priority is to reduce this disparity to achieve the goal at sub-national level. Evidences from developing countries show that increasing utilization of skilled attendant at birth is an important indicator for reducing maternal death. Further, there is a very low utilization during childbirth in western and hilly regions of Nepal which clearly depicts the barriers in utilization of skilled birth attendants. So, there is a need to overcome the identified barriers to increase the utilization thereby decreasing the maternal mortality. The hypothesis of this study is that through a package of interventions the utilization of skilled birth attendants will be increased and hence improve maternal health in Nepal. This study involves a cluster randomized controlled trial involving approximately 5000 pregnant women in 36 clusters. The 18 intervention clusters will receive the following interventions: i) mobilization of family support for pregnant women to reach the health facility, ii) availability of emergency funds for institutional childbirth, iii) availability of transport options to reach a health facility for childbirth, iv) training to health workers on communication skills, v) security provisions for SBAs to reach services 24/24 through community mobilization; 18 control clusters will not receive the intervention package. The final evaluation of the intervention is planned to be completed by October 2014. Primary study output of this study is utilization of SBA services. Secondary study outputs measure the uptake of antenatal care, post natal checkup for mother and baby, availability of transportation for childbirth, operation of emergency fund, improved reception of women at health services, and improved physical security of SBAs. The intervention package is designed to increase the utilization of skilled birth attendants by overcoming the barriers related to awareness, finance, transport, security etc. If proven effective, the Ministry of Health has committed to scale up the intervention package throughout the country. ISRCTN78892490.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Trajectories of Symptom Clusters, Performance Status, and Quality of Life During Concurrent Chemoradiotherapy in Patients With High-Grade Brain Cancers.

PubMed

Kim, Sang-Hee; Byun, Youngsoon

Symptom clusters must be identified in patients with high-grade brain cancers for effective symptom management during cancer-related therapy. The aims of this study were to identify symptom clusters in patients with high-grade brain cancers and to determine the relationship of each cluster with the performance status and quality of life (QOL) during concurrent chemoradiotherapy (CCRT). Symptoms were assessed using the Memorial Symptom Assessment Scale, and the performance status was evaluated using the Karnofsky Performance Scale. Quality of life was assessed using the Functional Assessment of Cancer Therapy-General. This prospective longitudinal survey was conducted before CCRT and at 2 to 3 weeks and 4 to 6 weeks after the initiation of CCRT. A total of 51 patients with newly diagnosed primary malignant brain cancer were included. Six symptom clusters were identified, and 2 symptom clusters were present at each time point (ie, "negative emotion" and "neurocognitive" clusters before CCRT, "negative emotion and decreased vitality" and "gastrointestinal and decreased sensory" clusters at 2-3 weeks, and "body image and decreased vitality" and "gastrointestinal" clusters at 4-6 weeks). The symptom clusters at each time point demonstrated a significant relationship with the performance status or QOL. Differences were observed in symptom clusters in patients with high-grade brain cancers during CCRT. In addition, the symptom clusters were correlated with the performance status and QOL of patients, and these effects could change during CCRT. The results of this study will provide suggestions for interventions to treat or prevent symptom clusters in patients with high-grade brain cancer during CCRT.

The antiSMASH database, a comprehensive database of microbial secondary metabolite biosynthetic gene clusters.

PubMed

Blin, Kai; Medema, Marnix H; Kottmann, Renzo; Lee, Sang Yup; Weber, Tilmann

2017-01-04

Secondary metabolites produced by microorganisms are the main source of bioactive compounds that are in use as antimicrobial and anticancer drugs, fungicides, herbicides and pesticides. In the last decade, the increasing availability of microbial genomes has established genome mining as a very important method for the identification of their biosynthetic gene clusters (BGCs). One of the most popular tools for this task is antiSMASH. However, so far, antiSMASH is limited to de novo computing results for user-submitted genomes and only partially connects these with BGCs from other organisms. Therefore, we developed the antiSMASH database, a simple but highly useful new resource to browse antiSMASH-annotated BGCs in the currently 3907 bacterial genomes in the database and perform advanced search queries combining multiple search criteria. antiSMASH-DB is available at http://antismash-db.secondarymetabolites.org/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Investigating the role of small vent volcanism during the development of Tharsis Province, Mars

NASA Astrophysics Data System (ADS)

Richardson, J. A.; Bleacher, J. E.; Connor, C.; Connor, L.; Glaze, L. S.

2014-12-01

Clusters of tens to hundreds of small volcanic vents have recently been recognized as a major component of Tharsis Province volcanism. These volcanic fields are formed from distributed-style, possibly monogenetic, volcanism and are composed of low sloped edifices with diameters of tens of kilometers and heights of tens to hundreds of meters. We report a new catalog of these small volcanic vents, now available through the USGS Astrogeology Science Center. This catalog was created with the use of gridded topographic data from the Mars Orbiter Laser Altimeter (MOLA) and images from the Thermal Emission Imaging System (THEMIS) and the High Resolution Stereo Camera (HRSC). We are now investigating isolated clusters of distributed volcanism in Tharsis with this dataset. We hypothesize that these clusters are formed from significant magmatic events that played a large role in the development of Tharsis. Currently, the catalog contains 1075 unique volcanic vents in the Tharsis Province. With the catalog, potentially isolated volcano clusters are identified with vent density estimation. Vent intensity for clusters is found to be 1 vent per 1000 sq km or less. Crater retention rates for one such cluster, Syria Planum, indicates that these distributed volcanic systems might continue as long as 700 Ma, or that monogenetic volcanic systems overprint older systems. Using a modified basal outlining algorithm with MOLA gridded data, shield volumes are found to be between 1-20 cubic km. Current results show distributed-style volcanism occuring in Tharsis orders of magnitude more dispersed than analogous volcano clusers on Earth, while individual edifices are found to be an order of magnitude larger than volcanoes in Earth clusters. Proof of concept results are reported for three identified clusters: Arsia Mons Caldera, Syria Planum, and Southern Pavonis Mons.

Evolution of the cluster optical galaxy luminosity function in the CFHTLS: breaking the degeneracy between mass and redshift

NASA Astrophysics Data System (ADS)

Sarron, F.; Martinet, N.; Durret, F.; Adami, C.

2018-06-01

Obtaining large samples of galaxy clusters is important for cosmology: cluster counts as a function of redshift and mass can constrain the parameters of our Universe. They are also useful in order to understand the formation and evolution of clusters. We develop an improved version of the Adami & MAzure Cluster FInder (AMACFI), now the Adami, MAzure & Sarron Cluster FInder (AMASCFI), and apply it to the 154 deg2 of the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) to obtain a large catalogue of 1371 cluster candidates with mass M200 > 1014 M⊙ and redshift z ≤ 0.7. We derive the selection function of the algorithm from the Millennium simulation, and cluster masses from a richness-mass scaling relation built from matching our candidates with X-ray detections. We study the evolution of these clusters with mass and redshift by computing the i'-band galaxy luminosity functions (GLFs) for the early-type (ETGs) and late-type galaxies (LTGs). This sample is 90% pure and 70% complete, and therefore our results are representative of a large fraction of the cluster population in these redshift and mass ranges. We find an increase in both the ETG and LTG faint populations with decreasing redshift (with Schechter slopes αETG = -0.65 ± 0.03 and αLTG = -0.95 ± 0.04 at z = 0.6, and αETG = -0.79 ± 0.02 and αLTG = -1.26 ± 0.03 at z = 0.2) and also a decrease in the LTG (but not the ETG) bright end. Our large sample allows us to break the degeneracy between mass and redshift, finding that the redshift evolution is more pronounced in high-mass clusters, but that there is no significant dependence of the faint end on mass for a given redshift. These results show that the cluster red sequence is mainly formed at redshift z > 0.7, and that faint ETGs continue to enrich the red sequence through quenching of brighter LTGs at z ≤ 0.7. The efficiency of this quenching is higher in large-mass clusters, while the accretion rate of faint LTGs is lower as the more massive clusters have already emptied most of their environment at higher redshifts. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, 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 available at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS.The candidate cluster catalog is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/613/A67

Astrophysical properties of star clusters in the Magellanic Clouds homogeneously estimated by ASteCA

NASA Astrophysics Data System (ADS)

Perren, G. I.; Piatti, A. E.; Vázquez, R. A.

2017-06-01

Aims: We seek to produce a homogeneous catalog of astrophysical parameters of 239 resolved star clusters, located in the Small and Large Magellanic Clouds, observed in the Washington photometric system. Methods: The cluster sample was processed with the recently introduced Automated Stellar Cluster Analysis (ASteCA) package, which ensures both an automatized and a fully reproducible treatment, together with a statistically based analysis of their fundamental parameters and associated uncertainties. The fundamental parameters determined for each cluster with this tool, via a color-magnitude diagram (CMD) analysis, are metallicity, age, reddening, distance modulus, and total mass. Results: We generated a homogeneous catalog of structural and fundamental parameters for the studied cluster sample and performed a detailed internal error analysis along with a thorough comparison with values taken from 26 published articles. We studied the distribution of cluster fundamental parameters in both Clouds and obtained their age-metallicity relationships. Conclusions: The ASteCA package can be applied to an unsupervised determination of fundamental cluster parameters, which is a task of increasing relevance as more data becomes available through upcoming surveys. A table with the estimated fundamental parameters for the 239 clusters analyzed is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/602/A89

Estimating multilevel logistic regression models when the number of clusters is low: a comparison of different statistical software procedures.

PubMed

Austin, Peter C

2010-04-22

Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public health, epidemiological, and educational research. Procedures for estimating the parameters of such models are available in many statistical software packages. There is currently little evidence on the minimum number of clusters necessary to reliably fit multilevel regression models. We conducted a Monte Carlo study to compare the performance of different statistical software procedures for estimating multilevel logistic regression models when the number of clusters was low. We examined procedures available in BUGS, HLM, R, SAS, and Stata. We found that there were qualitative differences in the performance of different software procedures for estimating multilevel logistic models when the number of clusters was low. Among the likelihood-based procedures, estimation methods based on adaptive Gauss-Hermite approximations to the likelihood (glmer in R and xtlogit in Stata) or adaptive Gaussian quadrature (Proc NLMIXED in SAS) tended to have superior performance for estimating variance components when the number of clusters was small, compared to software procedures based on penalized quasi-likelihood. However, only Bayesian estimation with BUGS allowed for accurate estimation of variance components when there were fewer than 10 clusters. For all statistical software procedures, estimation of variance components tended to be poor when there were only five subjects per cluster, regardless of the number of clusters.

Spatial distribution of 12 class B notifiable infectious diseases in China: A retrospective study

PubMed Central

Zhu, Bin; Fu, Yang; Liu, Jinlin

2018-01-01

Background China is the largest developing country with a relatively developed public health system. To further prevent and eliminate the spread of infectious diseases, China has listed 39 notifiable infectious diseases characterized by wide prevalence or great harm, and classified them into classes A, B, and C, with severity decreasing across classes. Class A diseases have been almost eradicated in China, thus making class B diseases a priority in infectious disease prevention and control. In this retrospective study, we analyze the spatial distribution patterns of 12 class B notifiable infectious diseases that remain active all over China. Methods Global and local Moran’s I and corresponding graphic tools are adopted to explore and visualize the global and local spatial distribution of the incidence of the selected epidemics, respectively. Inter-correlations of clustering patterns of each pair of diseases and a cumulative summary of the high/low cluster frequency of the provincial units are also provided by means of figures and maps. Results Of the 12 most commonly notifiable class B infectious diseases, viral hepatitis and tuberculosis show high incidence rates and account for more than half of the reported cases. Almost all the diseases, except pertussis, exhibit positive spatial autocorrelation at the provincial level. All diseases feature varying spatial concentrations. Nevertheless, associations exist between spatial distribution patterns, with some provincial units displaying the same type of cluster features for two or more infectious diseases. Overall, high–low (unit with high incidence surrounded by units with high incidence, the same below) and high–high spatial cluster areas tend to be prevalent in the provincial units located in western and southwest China, whereas low–low and low–high spatial cluster areas abound in provincial units in north and east China. Conclusion Despite the various distribution patterns of 12 class B notifiable infectious diseases, certain similarities between their spatial distributions are present. Substantial evidence is available to support disease-specific, location-specific, and disease-combined interventions. Regarding provinces that show high–high/high–low patterns of multiple diseases, comprehensive interventions targeting different diseases should be established. As to the adjacent provincial units revealing similar patterns, coordinated actions need to be taken across borders. PMID:29621351

Is Technology-Mediated Parental Monitoring Related to Adolescent Substance Use?

PubMed

Rudi, Jessie; Dworkin, Jodi

2018-01-03

Prevention researchers have identified parental monitoring leading to parental knowledge to be a protective factor against adolescent substance use. In today's digital society, parental monitoring can occur using technology-mediated communication methods, such as text messaging, email, and social networking sites. The current study aimed to identify patterns, or clusters, of in-person and technology-mediated monitoring behaviors, and examine differences between the patterns (clusters) in adolescent substance use. Cross-sectional survey data were collected from 289 parents of adolescents using Facebook and Amazon Mechanical Turk (MTurk). Cluster analyses were computed to identify patterns of in-person and technology-mediated monitoring behaviors, and chi-square analyses were computed to examine differences in substance use between the identified clusters. Three monitoring clusters were identified: a moderate in-person and moderate technology-mediated monitoring cluster (moderate-moderate), a high in-person and high technology-mediated monitoring cluster (high-high), and a high in-person and low technology-mediated monitoring cluster (high-low). Higher frequency of technology-mediated parental monitoring was not associated with lower levels of substance use. Results show that higher levels of technology-mediated parental monitoring may not be associated with adolescent substance use.

Spatiotemporal clusters of malaria cases at village level, northwest Ethiopia.

PubMed

Alemu, Kassahun; Worku, Alemayehu; Berhane, Yemane; Kumie, Abera

2014-06-06

Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Spatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit. Malaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages. The study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.

VizieR Online Data Catalog: XCS-DR1 Cluster Catalogue (Mehrtens+, 2012)

NASA Astrophysics Data System (ADS)

Mehrtens, N.; Romer, A. K.; Hilton, M.; Lloyd-Davies, E. J.; Miller, C. J.; Stanford, S. A.; Hosmer, M.; Hoyle, B.; Collins, C. A.; Liddle, A. R.; Viana, P. T. P.; Nichol, R. C.; Stott, J. P.; Dubois, E. N.; Kay, S. T.; Sahlen, M.; Young, O.; Short, C. J.; Christodoulou, L.; Watson, W. A.; Davidson, M.; Harrison, C. D.; Baruah, L.; Smith, M.; Burke, C.; Mayers, J. A.; Deadman, P.-J.; Rooney, P. J.; Edmondson, E. M.; West, M.; Campbell, H. C.; Edge, A. C.; Mann, R. G.; Sabirli, K.; Wake, D.; Benoist, C.; da Costa, L.; Maia, M. A. G.; Ogando, R.

2013-04-01

The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we present the first data release from the XMM Cluster Survey (XCS-DR1). This consists of 503 optically confirmed, serendipitously detected, X-ray clusters. Of these clusters, 256 are new to the literature and 357 are new X-ray discoveries. We present 463 clusters with a redshift estimate (0.06

The Biggest Bangs Since the Big Bang: Unveiling Mergers of Galaxy Clusters with Radio Halos/Relics Using X-ray Temperature Maps

NASA Astrophysics Data System (ADS)

Burns, Jack

Galaxy clusters are assembled through large and small mergers which are the most energetic events ( bangs ) since the Big Bang. Cluster mergers stir the ICM creating shocks and turbulence which are illuminated by Mpc-sized radio features called relics and halos. These shocks heat the ICM and are detected in x-rays via thermal emission. Disturbed morphologies in x-ray surface brightness and temperatures are direct evidence for cluster mergers. In the radio, relics (in the outskirts of the clusters) and halos (located near the cluster core) are clear signposts of recent mergers. Our recent cosmological simulations suggest that around a merger event, radio emission peaks very sharply (and briefly) while the x-ray emission rises and decays slowly. Hence, a sample of galaxy clusters that shows both luminous x-ray and radio relics/halos are clear candidates for very recent mergers. We propose to analyze a unique sample of 48 galaxy clusters with (i) known radio relics and/or halos and (ii) significant archival x-ray observations (e 50 ksec) from Chandra and/or XMM. We will use a new x-ray data analysis pipeline, implemented on a parallelprocessor supercomputer, to create x-ray surface brightness, high fidelity temperature, and pressure maps of these clusters in order to study merging activity. In addition, we will use a control sample of clusters from the HIFLUGCS catalog which do not show radio relics/halos or any significant x-ray surface brightness substructure, thus devoid of recent mergers. The temperature maps will be made using 3 different map-making techniques: Weighted Voronoi Tessellation, Adaptive Circular Binning, and Contour Binning. We also plan to use archival Suzaku data for 22 clusters in our sample and study the x-ray temperatures at the outskirts of the clusters. All 48 clusters have archival radio data at d1.4 GHz which will be re-analyzed using advanced algorithms in NRAO s CASA software. We also have new radio data on a subset of these clusters and have proposed to observe more of them with the increased sensitivity of the JVLA and GMRT at 0.25-1.4 GHz. Using the systematically analyzed x-ray and radio data, we propose to pursue the detailed link between cluster mergers and the formation of radio relics/halos. (a) How do radio relics form? Radio relics are believed to be created via re-acceleration of cosmic ray electrons through diffusive shock acceleration, a 1st order Fermi mechanism. Hence, there should be a correlation between shocks detected in the x-ray and radio. We plan to use our newly developed 2-D shock-finder using jumps within xray temperature maps, and complement the results with radio Mach numbers derived from radio spectral indices. Shocks detected in our simulations using a 3-D shock-finder will be used to understand the effects of projections in observations. (b) How do radio halos form? It is not clear if the formation of radio halos is due to turbulent acceleration (2nd order Fermi process) or due to more efficient 1st order Fermi mechanism via distributed small-scale shocks. Since radio halos reside in merging clusters, the x-ray temperature structure should show the un-relaxed nature of the cluster. We will study this through temperature asymmetry and power ratios (between two multipoles). We also propose to use pressure maps to derive a 2-D power spectrum of pressure fluctuations and deduce the turbulent velocity field. We will then derive the associated radio power and spectral indices to compare with the radio observations. We will test our results using clusters with and without radio halos. We will make these high fidelity temperature, surface brightness, pressure and entropy maps available to the astronomical community via the National Virtual Observatory. We will also make our x-ray temperature map-making scripts implemented on parallel supercomputers available for community use.

Country clustering applied to the water & sanitation sector: a new tool with potential applications in research & policy

PubMed Central

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2013-01-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were unique from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. PMID:24054545

HIGH-ENERGY NEUTRINOS FROM SOURCES IN CLUSTERS OF GALAXIES

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

Fang, Ke; Olinto, Angela V.

2016-09-01

High-energy cosmic rays can be accelerated in clusters of galaxies, by mega-parsec scale shocks induced by the accretion of gas during the formation of large-scale structures, or by powerful sources harbored in clusters. Once accelerated, the highest energy particles leave the cluster via almost rectilinear trajectories, while lower energy ones can be confined by the cluster magnetic field up to cosmological time and interact with the intracluster gas. Using a realistic model of the baryon distribution and the turbulent magnetic field in clusters, we studied the propagation and hadronic interaction of high-energy protons in the intracluster medium. We report themore » cumulative cosmic-ray and neutrino spectra generated by galaxy clusters, including embedded sources, and demonstrate that clusters can contribute a significant fraction of the observed IceCube neutrinos above 30 TeV while remaining undetected in high-energy cosmic rays and γ rays for reasonable choices of parameters and source scenarios.« less

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

PubMed

Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto

2010-03-09

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

Establishing Linux Clusters for High-Performance Computing (HPC) at NPS

DTIC Science & Technology

2004-09-01

52 e. Intel Roll..................................................................................53 f. Area51 Roll...results of generating md5summ for Area51 roll. All the file information is available. This number can be used to be checked against the number that the...vendor provides fro the particular piece of software. ......51 Figure 22 The given md5summ for Area51 roll form the download site. This number can

Very Broad [O III] λλ4959, 5007 Emission from the NGC 4472 Globular Cluster RZ 2109 and Implications for the Mass of Its Black Hole X-Ray Source

NASA Astrophysics Data System (ADS)

Zepf, Stephen E.; Stern, Daniel; Maccarone, Thomas J.; Kundu, Arunav; Kamionkowski, Marc; Rhode, Katherine L.; Salzer, John J.; Ciardullo, Robin; Gronwall, Caryl

2008-08-01

We present Keck LRIS spectroscopy of the black hole-hosting globular cluster RZ 2109 in the Virgo elliptical galaxy NGC 4472. We find that this object has extraordinarily broad [O III] λ5007 and [O III] λ4959 emission lines, with velocity widths of approximately 2000 km s-1. This result has significant implications for the nature of this accreting black hole system and the mass of the globular cluster black hole. We show that the broad [O III] λ5007 emission must arise from material driven at high velocity from the black hole system. This is because the volume available near the black hole is too small by many orders of magnitude to have enough [O III]-emitting atoms to account for the observed L([O III] λ5007) at high velocities, even if this volume is filled with oxygen at the critical density for [O III] λ5007. The Balmer emission is also weak, indicating the observed [O III] is not due to shocks. We therefore conclude that the [O III] λλ4959, 5007 is produced by photoionization of material driven across the cluster. The only known way to drive significant material at high velocity is for a system accreting mass near or above its Eddington limit, which indicates a stellar-mass black hole. Since it is dynamically implausible to form an accreting stellar-mass black hole system in a globular cluster with an intermediate-mass black hole (IMBH), it appears this massive globular cluster does not have an IMBH. We discuss further tests of this conclusion, and its implications for the MBH - Mstellar and MBH - σ relations. Based on observations made 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.

Transition from HEU to LEU fuel in Romania`s 14-MW TRIGA reactor

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

Bretscher, M.M.; Snelgrove, J.L.

1991-12-31

The 14-MW TRIGA steady state reactor (SSR) located in Pitesti, Romania, first went critical in the fall of 1979. Initially, the core configuration for full power operation used 29 fuel clusters each containing a 5 {times} 5 square array of HEU (10 wt%) -- ZrH -- Er (2.8 wt%) fuel-moderator rods (1.295 cm o.d.) clad in Incology. With a total inventory of 35 HEU fuel clusters, burnup considerations required a gradual expansion of the core from 29 to 32 and finally to 35 clusters before the reactor was shut down because of insufficient excess reactivity. At this time each ofmore » the original 29 fuel clusters had an overage {sup 235}U burnup in the range from 50 to 62%. Because of the US policy regarding the export of highly enriched uranium, fresh HEU TRIGA replacement fuel is not available. After a number of safety-related measurements, the SSR is expected to resume full power operation in the near future using a mixed core containing five LEU TRIGA clusters of the same geometry as the original fuel but with fuel-moderator rods containing 45 wt% U (19.7% {sup 235}U enrichment) and 1.1 wt% Er. Rods for 14 additional LEU fuel clusters will be fabricated by General Atomics. In support of the SSR mixed core operation numerous neutronic calculations have been performed. This paper presents some of the results of those calculations.« less

GLASS: The Grism Lens-Amplified Survey From Space. HST Grism Spectroscopy of the Frontier Fields

NASA Astrophysics Data System (ADS)

Schmidt, Kasper B.; Schmidt

The Grism Lens-Amplified Survey From Space (GLASS) is a 140 orbit spectroscopic survey of 10 massive galaxy clusters, including the six Hubble Frontier Fields. GLASS has observed the cluster cores with the HST-WFC3 G102 and G141 grisms providing a wide wavelength coverage in the near-infrared from roughly 0.8-1.7μm. The parallel fields were observed through the optical ACS G800L grism. Taking advantage of the lensing magnification of the clusters, GLASS reaches intrinsic spectroscopic 1σ flux limits of roughly 10-18erg/s/cm2 and improved spatial resolution for lensed sources behind the clusters. These features are particularly useful for the three main science drivers of GLASS which are, I) exploring the universe at the epoch of reionization, II) describe how metals cycle in and out of galaxies, and III) asses the environmental dependence of galaxy evolution. The former two benefit highly from the improved depth and increased resolution provided by the cluster lensing. Apart from the main science drivers, a slew of ancillary science has been enabled by the survey, including improving cluster lens modeling and searches for supernovae. Here we present the survey and the GLASS data releases, which are continuously being made available to the community through https://archive.stsci.edu/prepds/glass/. For further information we refer to Schmidt et al. (2014), Treu et al. (2015), and http://glass.physics.ucsb.edu.

Using container orchestration to improve service management at the RAL Tier-1

NASA Astrophysics Data System (ADS)

Lahiff, Andrew; Collier, Ian

2017-10-01

In recent years container orchestration has been emerging as a means of gaining many potential benefits compared to a traditional static infrastructure, such as increased utilisation through multi-tenancy, improved availability due to self-healing, and the ability to handle changing loads due to elasticity and auto-scaling. To this end we have been investigating migrating services at the RAL Tier-1 to an Apache Mesos cluster. In this model the concept of individual machines is abstracted away and services are run in containers on a cluster of machines, managed by schedulers, enabling a high degree of automation. Here we describe Mesos, the infrastructure deployed at RAL, and describe in detail the explicit example of running a batch farm on Mesos.

How Well Do We Know The Supernova Equation of State?

NASA Astrophysics Data System (ADS)

Hempel, Matthias; Oertel, Micaela; Typel, Stefan; Klähn, Thomas

We give an overview about equations of state (EOS) which are currently available for simulations of core-collapse supernovae and neutron star mergers. A few selected important aspects of the EOS, such as the symmetry energy, the maximum mass of neutron stars, and cluster formation, are confronted with constraints from experiments and astrophysical observations. There are just very few models which are compatible even with this very restricted set of constraints. These remaining models illustrate the uncertainty of the uniform nuclear matter EOS at high densities. In addition, at finite temperatures the medium modifications of nuclear clusters represent a conceptual challenge. In conclusion, there has been significant development in the recent years, but there is still need for further improved general purpose EOS tables.

Alternatives to Multilevel Modeling for the Analysis of Clustered Data

ERIC Educational Resources Information Center

Huang, Francis L.

2016-01-01

Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…

Dispersed or Clustered Housing for Adults with Intellectual Disability: A Systematic Review

ERIC Educational Resources Information Center

Mansell, Jim; Beadle-Brown, Julie

2009-01-01

Background: The purpose of this review was to evaluate the available research on the quality and costs of dispersed community-based housing when compared with clustered housing. Methods: Searches against specified criteria yielded 19 papers based on 10 studies presenting data comparing dispersed housing with some kind of clustered housing (village…

Improving Performance for Gifted Students in a Cluster Grouping Model

ERIC Educational Resources Information Center

Brulles, Dina; Saunders, Rachel; Cohn, Sanford J.

2010-01-01

Although experts in gifted education widely promote cluster grouping gifted students, little empirical evidence is available to attest to its effectiveness. This study is an example of comparative action research in the form of a quantitative case study that focused on the mandated cluster grouping practices for gifted students in an urban…

Optimal colour quality of LED clusters based on memory colours.

PubMed

Smet, Kevin; Ryckaert, Wouter R; Pointer, Michael R; Deconinck, Geert; Hanselaer, Peter

2011-03-28

The spectral power distributions of tri- and tetrachromatic clusters of Light-Emitting-Diodes, composed of simulated and commercially available LEDs, were optimized with a genetic algorithm to maximize the luminous efficacy of radiation and the colour quality as assessed by the memory colour quality metric developed by the authors. The trade-off of the colour quality as assessed by the memory colour metric and the luminous efficacy of radiation was investigated by calculating the Pareto optimal front using the NSGA-II genetic algorithm. Optimal peak wavelengths and spectral widths of the LEDs were derived, and over half of them were found to be close to Thornton's prime colours. The Pareto optimal fronts of real LED clusters were always found to be smaller than those of the simulated clusters. The effect of binning on designing a real LED cluster was investigated and was found to be quite large. Finally, a real LED cluster of commercially available AlGaInP, InGaN and phosphor white LEDs was optimized to obtain a higher score on memory colour quality scale than its corresponding CIE reference illuminant.

Cluster subgroups based on overall pressure pain sensitivity and psychosocial factors in chronic musculoskeletal pain: Differences in clinical outcomes.

PubMed

Almeida, Suzana C; George, Steven Z; Leite, Raquel D V; Oliveira, Anamaria S; Chaves, Thais C

2018-05-17

We aimed to empirically derive psychosocial and pain sensitivity subgroups using cluster analysis within a sample of individuals with chronic musculoskeletal pain (CMP) and to investigate derived subgroups for differences in pain and disability outcomes. Eighty female participants with CMP answered psychosocial and disability scales and were assessed for pressure pain sensitivity. A cluster analysis was used to derive subgroups, and analysis of variance (ANOVA) was used to investigate differences between subgroups. Psychosocial factors (kinesiophobia, pain catastrophizing, anxiety, and depression) and overall pressure pain threshold (PPT) were entered into the cluster analysis. Three subgroups were empirically derived: cluster 1 (high pain sensitivity and high psychosocial distress; n = 12) characterized by low overall PPT and high psychosocial scores; cluster 2 (high pain sensitivity and intermediate psychosocial distress; n = 39) characterized by low overall PPT and intermediate psychosocial scores; and cluster 3 (low pain sensitivity and low psychosocial distress; n = 29) characterized by high overall PPT and low psychosocial scores compared to the other subgroups. Cluster 1 showed higher values for mean pain intensity (F (2,77)  = 10.58, p < 0.001) compared with cluster 3, and cluster 1 showed higher values for disability (F (2,77)  = 3.81, p = 0.03) compared with both clusters 2 and 3. Only cluster 1 was distinct from cluster 3 according to both pain and disability outcomes. Pain catastrophizing, depression, and anxiety were the psychosocial variables that best differentiated the subgroups. Overall, these results call attention to the importance of considering pain sensitivity and psychosocial variables to obtain a more comprehensive characterization of CMP patients' subtypes.

Visualization of genome signatures of eukaryote genomes by batch-learning self-organizing map with a special emphasis on Drosophila genomes.

PubMed

Abe, Takashi; Hamano, Yuta; Ikemura, Toshimichi

2014-01-01

A strategy of evolutionary studies that can compare vast numbers of genome sequences is becoming increasingly important with the remarkable progress of high-throughput DNA sequencing methods. We previously established a sequence alignment-free clustering method "BLSOM" for di-, tri-, and tetranucleotide compositions in genome sequences, which can characterize sequence characteristics (genome signatures) of a wide range of species. In the present study, we generated BLSOMs for tetra- and pentanucleotide compositions in approximately one million sequence fragments derived from 101 eukaryotes, for which almost complete genome sequences were available. BLSOM recognized phylotype-specific characteristics (e.g., key combinations of oligonucleotide frequencies) in the genome sequences, permitting phylotype-specific clustering of the sequences without any information regarding the species. In our detailed examination of 12 Drosophila species, the correlation between their phylogenetic classification and the classification on the BLSOMs was observed to visualize oligonucleotides diagnostic for species-specific clustering.

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

PubMed

Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

Evolutionary models of rotating dense stellar systems: challenges in software and hardware

NASA Astrophysics Data System (ADS)

Fiestas, Jose

2016-02-01

We present evolutionary models of rotating self-gravitating systems (e.g. globular clusters, galaxy cores). These models are characterized by the presence of initial axisymmetry due to rotation. Central black hole seeds are alternatively included in our models, and black hole growth due to consumption of stellar matter is simulated until the central potential dominates the kinematics in the core. Goal is to study the long-term evolution (~ Gyr) of relaxed dense stellar systems, which deviate from spherical symmetry, their morphology and final kinematics. With this purpose, we developed a 2D Fokker-Planck analytical code, which results we confirm by detailed N-Body techniques, applying a high performance code, developed for GPU machines. We compare our models to available observations of galactic rotating globular clusters, and conclude that initial rotation modifies significantly the shape and lifetime of these systems, and can not be neglected in studying the evolution of globular clusters, and the galaxy itself.

Natural-product-derived fragments for fragment-based ligand discovery

NASA Astrophysics Data System (ADS)

Over, Björn; Wetzel, Stefan; Grütter, Christian; Nakai, Yasushi; Renner, Steffen; Rauh, Daniel; Waldmann, Herbert

2013-01-01

Fragment-based ligand and drug discovery predominantly employs sp2-rich compounds covering well-explored regions of chemical space. Despite the ease with which such fragments can be coupled, this focus on flat compounds is widely cited as contributing to the attrition rate of the drug discovery process. In contrast, biologically validated natural products are rich in stereogenic centres and populate areas of chemical space not occupied by average synthetic molecules. Here, we have analysed more than 180,000 natural product structures to arrive at 2,000 clusters of natural-product-derived fragments with high structural diversity, which resemble natural scaffolds and are rich in sp3-configured centres. The structures of the cluster centres differ from previously explored fragment libraries, but for nearly half of the clusters representative members are commercially available. We validate their usefulness for the discovery of novel ligand and inhibitor types by means of protein X-ray crystallography and the identification of novel stabilizers of inactive conformations of p38α MAP kinase and of inhibitors of several phosphatases.

Open star clusters and Galactic structure

NASA Astrophysics Data System (ADS)

Joshi, Yogesh C.

2018-04-01

In order to understand the Galactic structure, we perform a statistical analysis of the distribution of various cluster parameters based on an almost complete sample of Galactic open clusters yet available. The geometrical and physical characteristics of a large number of open clusters given in the MWSC catalogue are used to study the spatial distribution of clusters in the Galaxy and determine the scale height, solar offset, local mass density and distribution of reddening material in the solar neighbourhood. We also explored the mass-radius and mass-age relations in the Galactic open star clusters. We find that the estimated parameters of the Galactic disk are largely influenced by the choice of cluster sample.

Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.

PubMed

Andreatta, Massimo; Lund, Ole; Nielsen, Morten

2013-01-01

Proteins recognizing short peptide fragments play a central role in cellular signaling. As a result of high-throughput technologies, peptide-binding protein specificities can be studied using large peptide libraries at dramatically lower cost and time. Interpretation of such large peptide datasets, however, is a complex task, especially when the data contain multiple receptor binding motifs, and/or the motifs are found at different locations within distinct peptides. The algorithm presented in this article, based on Gibbs sampling, identifies multiple specificities in peptide data by performing two essential tasks simultaneously: alignment and clustering of peptide data. We apply the method to de-convolute binding motifs in a panel of peptide datasets with different degrees of complexity spanning from the simplest case of pre-aligned fixed-length peptides to cases of unaligned peptide datasets of variable length. Example applications described in this article include mixtures of binders to different MHC class I and class II alleles, distinct classes of ligands for SH3 domains and sub-specificities of the HLA-A*02:01 molecule. The Gibbs clustering method is available online as a web server at http://www.cbs.dtu.dk/services/GibbsCluster.

OCCAM: a flexible, multi-purpose and extendable HPC cluster

NASA Astrophysics Data System (ADS)

Aldinucci, M.; Bagnasco, S.; Lusso, S.; Pasteris, P.; Rabellino, S.; Vallero, S.

2017-10-01

The Open Computing Cluster for Advanced data Manipulation (OCCAM) is a multipurpose flexible HPC cluster designed and operated by a collaboration between the University of Torino and the Sezione di Torino of the Istituto Nazionale di Fisica Nucleare. It is aimed at providing a flexible, reconfigurable and extendable infrastructure to cater to a wide range of different scientific computing use cases, including ones from solid-state chemistry, high-energy physics, computer science, big data analytics, computational biology, genomics and many others. Furthermore, it will serve as a platform for R&D activities on computational technologies themselves, with topics ranging from GPU acceleration to Cloud Computing technologies. A heterogeneous and reconfigurable system like this poses a number of challenges related to the frequency at which heterogeneous hardware resources might change their availability and shareability status, which in turn affect methods and means to allocate, manage, optimize, bill, monitor VMs, containers, virtual farms, jobs, interactive bare-metal sessions, etc. This work describes some of the use cases that prompted the design and construction of the HPC cluster, its architecture and resource provisioning model, along with a first characterization of its performance by some synthetic benchmark tools and a few realistic use-case tests.

Mothe-Diniz Asteroid Dynamical Families V1.0

NASA Astrophysics Data System (ADS)

Mothe-Diniz, T.; Roig, F.; Carvano, J. M.

2006-03-01

This dataset contains an updated compilation of asteroid families and clusters, resulting from the application of the Hierarchical Clustering Method (HCM) on a set of around 120,000 asteroids with available proper elements. Whenever available, the classification in the Bus taxonomy is provided for family members, based on spectra from the SMASS, SMASS2 and S3OS2 spectroscopic surveys.

Clustering the Orion B giant molecular cloud based on its molecular emission.

PubMed

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. A clustering analysis based only on the J = 1 - 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes ( n H ~ 100 cm -3 , ~ 500 cm -3 , and > 1000 cm -3 ), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 - 0 line of HCO + and the N = 1 - 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO + and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO + intensity ratio in UV-illuminated regions. Finer distinctions in density classes ( n H ~ 7 × 10 3 cm -3 ~ 4 × 10 4 cm -3 ) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO + (1 - 0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers.

Cluster analysis differentiates high and low community functioning in schizophrenia: Subgroups differ on working memory but not other neurocognitive domains.

PubMed

Alden, Eva C; Cobia, Derin J; Reilly, James L; Smith, Matthew J

2015-10-01

Schizophrenia is characterized by impairment in multiple aspects of community functioning. Available literature suggests that community functioning may be enhanced through cognitive remediation, however, evidence is limited regarding whether specific neurocognitive domains may be treatment targets. We characterized schizophrenia subjects based on their level of community functioning through cluster analysis in an effort to identify whether specific neurocognitive domains were associated with variation in functioning. Schizophrenia (SCZ, n=60) and control (CON, n=45) subjects completed a functional capacity task, social competence role-play, functional attainment interview, and a neuropsychological battery. Multiple cluster analytic techniques were used on the measures of functioning in the schizophrenia subjects to generate functionally-defined subgroups. MANOVA evaluated between-group differences in neurocognition. The cluster analysis revealed two distinct groups, consisting of 36 SCZ characterized by high levels of community functioning (HF-SCZ) and 24 SCZ with low levels of community functioning (LF-SCZ). There was a main group effect for neurocognitive performance (p<0.001) with CON outperforming both SCZ groups in all neurocognitive domains. Post-hoc tests revealed that HF-SCZ had higher verbal working memory compared to LF-SCZ (p≤0.05, Cohen's d=0.78) but the two groups did not differ in remaining domains. The cluster analysis classified schizophrenia subjects in HF-SCZ and LF-SCZ using a multidimensional assessment of community functioning. Moreover, HF-SCZ demonstrated rather preserved verbal working memory relative to LF-SCZ. The results suggest that verbal working memory may play a critical role in community functioning, and is a potential cognitive treatment target for schizophrenia subjects. Copyright © 2015 Elsevier B.V. All rights reserved.

Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

PubMed Central

DeMaere, Matthew Z.

2016-01-01

Background Chromosome conformation capture, coupled with high throughput DNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised. Methods We developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure. Results When all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft-clustering extension of the Louvain method achieves the highest performance. Discussion Previously, only hard-clustering algorithms have been applied to metagenomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development. PMID:27843713

International scientific collaboration in HIV and HPV: a network analysis.

PubMed

Vanni, Tazio; Mesa-Frias, Marco; Sanchez-Garcia, Ruben; Roesler, Rafael; Schwartsmann, Gilberto; Goldani, Marcelo Z; Foss, Anna M

2014-01-01

Research endeavours require the collaborative effort of an increasing number of individuals. International scientific collaborations are particularly important for HIV and HPV co-infection studies, since the burden of disease is rising in developing countries, but most experts and research funds are found in developed countries, where the prevalence of HIV is low. The objective of our study was to investigate patterns of international scientific collaboration in HIV and HPV research using social network analysis. Through a systematic review of the literature, we obtained epidemiological data, as well as data on countries and authors involved in co-infection studies. The collaboration network was analysed in respect to the following: centrality, density, modularity, connected components, distance, clustering and spectral clustering. We observed that for many low- and middle-income countries there were no epidemiological estimates of HPV infection of the cervix among HIV-infected individuals. Most studies found only involved researchers from the same country (64%). Studies derived from international collaborations including high-income countries and either low- or middle-income countries had on average three times larger sample sizes than those including only high-income countries or low-income countries. The high global clustering coefficient (0.9) coupled with a short average distance between researchers (4.34) suggests a "small-world phenomenon." Researchers from high-income countries seem to have higher degree centrality and tend to cluster together in densely connected communities. We found a large well-connected community, which encompasses 70% of researchers, and 49 other small isolated communities. Our findings suggest that in the field of HIV and HPV, there seems to be both room and incentives for researchers to engage in collaborations between countries of different income-level. Through international collaboration resources available to researchers in high-income countries can be efficiently used to enroll more participants in low- and middle-income countries.

A platonic solid templating Archimedean solid: an unprecedented nanometre-sized Ag37 cluster

NASA Astrophysics Data System (ADS)

Li, Xiao-Yu; Su, Hai-Feng; Yu, Kai; Tan, Yuan-Zhi; Wang, Xing-Po; Zhao, Ya-Qin; Sun, Di; Zheng, Lan-Sun

2015-04-01

The spontaneous formation of discrete spherical nanosized molecules is prevalent in nature, but the authentic structural mimicry of such highly symmetric polyhedra from edge sharing of regular polygons has remained elusive. Here we present a novel ball-shaped {(HNEt3)[Ag37S4(SC6H4tBu)24(CF3COO)6(H2O)12]} cluster (1) that is assembled via a one-pot process from polymeric {(HNEt3)2[Ag10(SC6H4tBu)12]}n and CF3COOAg. Single crystal X-ray analysis confirmed that 1 is a Td symmetric spherical molecule with a [Ag36(SC6H4tBu)24] anion shell enwrapping a AgS4 tetrahedron. The shell topology of 1 belongs to one of 13 Archimedean solids, a truncated tetrahedron with four edge-shared hexagons and trigons, which are supported by a AgS4 Platonic solid in the core. Interestingly, the cluster emits green luminescence centered at 515 nm at room temperature. Our investigations have provided a promising synthetic protocol for a high-nuclearity silver cluster based on underlying geometrical principles.The spontaneous formation of discrete spherical nanosized molecules is prevalent in nature, but the authentic structural mimicry of such highly symmetric polyhedra from edge sharing of regular polygons has remained elusive. Here we present a novel ball-shaped {(HNEt3)[Ag37S4(SC6H4tBu)24(CF3COO)6(H2O)12]} cluster (1) that is assembled via a one-pot process from polymeric {(HNEt3)2[Ag10(SC6H4tBu)12]}n and CF3COOAg. Single crystal X-ray analysis confirmed that 1 is a Td symmetric spherical molecule with a [Ag36(SC6H4tBu)24] anion shell enwrapping a AgS4 tetrahedron. The shell topology of 1 belongs to one of 13 Archimedean solids, a truncated tetrahedron with four edge-shared hexagons and trigons, which are supported by a AgS4 Platonic solid in the core. Interestingly, the cluster emits green luminescence centered at 515 nm at room temperature. Our investigations have provided a promising synthetic protocol for a high-nuclearity silver cluster based on underlying geometrical principles. Electronic supplementary information (ESI) available: detailed synthesis procedure, tables, crystal data in CIF files, IR data, TGA results and powder X-ray diffractogram for 1. CCDC 1042228. See DOI: 10.1039/c5nr01222h

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

PubMed Central

2010-01-01

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data. PMID:20937082

Digital genome-wide ncRNA expression, including SnoRNAs, across 11 human tissues using polyA-neutral amplification.

PubMed

Castle, John C; Armour, Christopher D; Löwer, Martin; Haynor, David; Biery, Matthew; Bouzek, Heather; Chen, Ronghua; Jackson, Stuart; Johnson, Jason M; Rohl, Carol A; Raymond, Christopher K

2010-07-26

Non-coding RNAs (ncRNAs) are an essential class of molecular species that have been difficult to monitor on high throughput platforms due to frequent lack of polyadenylation. Using a polyadenylation-neutral amplification protocol and next-generation sequencing, we explore ncRNA expression in eleven human tissues. ncRNAs 7SL, U2, 7SK, and HBII-52 are expressed at levels far exceeding mRNAs. C/D and H/ACA box snoRNAs are associated with rRNA methylation and pseudouridylation, respectively: spleen expresses both, hypothalamus expresses mainly C/D box snoRNAs, and testes show enriched expression of both H/ACA box snoRNAs and RNA telomerase TERC. Within the snoRNA 14q cluster, 14q(I-6) is expressed at much higher levels than other cluster members. More reads align to mitochondrial than nuclear tRNAs. Many lincRNAs are actively transcribed, particularly those overlapping known ncRNAs. Within the Prader-Willi syndrome loci, the snoRNA HBII-85 (group I) cluster is highly expressed in hypothalamus, greater than in other tissues and greater than group II or III. Additionally, within the disease locus we find novel transcription across a 400,000 nt span in ovaries. This genome-wide polyA-neutral expression compendium demonstrates the richness of ncRNA expression, their high expression patterns, their function-specific expression patterns, and is publicly available.

Building CHAOS: An Operating System for Livermore Linux Clusters

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

Garlick, J E; Dunlap, C M

2003-02-21

The Livermore Computing (LC) Linux Integration and Development Project (the Linux Project) produces and supports the Clustered High Availability Operating System (CHAOS), a cluster operating environment based on Red Hat Linux. Each CHAOS release begins with a set of requirements and ends with a formally tested, packaged, and documented release suitable for use on LC's production Linux clusters. One characteristic of CHAOS is that component software packages come from different sources under varying degrees of project control. Some are developed by the Linux Project, some are developed by other LC projects, some are external open source projects, and some aremore » commercial software packages. A challenge to the Linux Project is to adhere to release schedules and testing disciplines in a diverse, highly decentralized development environment. Communication channels are maintained for externally developed packages in order to obtain support, influence development decisions, and coordinate/understand release schedules. The Linux Project embraces open source by releasing locally developed packages under open source license, by collaborating with open source projects where mutually beneficial, and by preferring open source over proprietary software. Project members generally use open source development tools. The Linux Project requires system administrators and developers to work together to resolve problems that arise in production. This tight coupling of production and development is a key strategy for making a product that directly addresses LC's production requirements. It is another challenge to balance support and development activities in such a way that one does not overwhelm the other.« less

Structure, Stabilities, Thermodynamic Properties, and IR Spectra of Acetylene Clusters (C2H2)n=2-5.

PubMed

Karthikeyan, S; Lee, Han Myoung; Kim, Kwang S

2010-10-12

There are no clear conclusions over the structures of the acetylene clusters. In this regard, we have carried out high-level calculations for acetylene clusters (C2H2)2-5 using dispersion-corrected density functional theory (DFT-D), Møller-Plesset second-order perturbation theory (MP2); and coupled-cluster theory with single, double, and perturbative triple excitations [CCSD(T)] at the complete basis set limit. The lowest energy structure of the acetylene dimer has a T-shaped structure of C2v symmetry, but it is nearly isoenergetic to the displaced stacked structure of C2h symmetry. We find that the structure shows the quantum statistical distribution for configurations between the T-shaped and displaced stacked structures for which the average angle (|θ̃|) between two acetylene molecules would be 53-78°, close to the T-shaped structure. The trimer has a triangular structure of C3h symmetry. The tetramer has two lowest energy isomers of S4 and C2h symmetry in zero-point energy (ZPE)-uncorrected energy (ΔEe), but one lowest energy isomer of C2v symmetry in ZPE-corrected energy (ΔE0). For the pentamer, the global minimum structure is C1 symmetry with eight sets of T-type π-H interactions and a set of π-π interactions. Our high-level ab initio calculations are consistent with available experimental data.

Automated bow shock and radiation belt edge identification methods and their application for Cluster, THEMIS/ARTEMIS and Van Allen Probes data

NASA Astrophysics Data System (ADS)

Facsko, Gabor; Sibeck, David; Balogh, Tamas; Kis, Arpad; Wesztergom, Viktor

2017-04-01

The bow shock and the outer rim of the outer radiation belt are detected automatically by our algorithm developed as a part of the Boundary Layer Identification Code Cluster Active Archive project. The radiation belt positions are determined from energized electron measurements working properly onboard all Cluster spacecraft. For bow shock identification we use magnetometer data and, when available, ion plasma instrument data. In addition, electrostatic wave instrument electron density, spacecraft potential measurements and wake indicator auxiliary data are also used so the events can be identified by all Cluster probes in highly redundant way, as the magnetometer and these instruments are still operational in all spacecraft. The capability and performance of the bow shock identification algorithm were tested using known bow shock crossing determined manually from January 29, 2002 to February 3,. The verification enabled 70% of the bow shock crossings to be identified automatically. The method shows high flexibility and it can be applied to observations from various spacecraft. Now these tools have been applied to Time History of Events and Macroscale Interactions during Substorms (THEMIS)/Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) magnetic field, plasma and spacecraft potential observations to identify bow shock crossings; and to Van Allen Probes supra-thermal electron observations to identify the edges of the radiation belt. The outcomes of the algorithms are checked manually and the parameters used to search for bow shock identification are refined.

A gas-rich AGN near the centre of a galaxy cluster at z ~ 1.4

NASA Astrophysics Data System (ADS)

Casasola, V.; Magrini, L.; Combes, F.; Mignano, A.; Sani, E.; Paladino, R.; Fontani, F.

2013-10-01

Context. The formation of the first virialized structures in overdensities dates back to ~9 Gyr ago, i.e. in the redshift range z ~ 1.4-1.6. Some models of structure formation predict that the star formation activity in clusters was high at that epoch, implying large reservoirs of cold molecular gas. Aims: Aiming at finding a trace of this expected high molecular gas content in primeval clusters, we searched for the 12CO(2-1) line emission in the most luminous active galactic nucleus (AGN) of the cluster around the radio galaxy 7C 1756+6520 at z ~ 1.4, one of the farthest spectroscopic confirmed clusters. This AGN, called AGN.1317, is located in the neighbourhood of the central radio galaxy at a projected distance of ~780 kpc. Methods: The IRAM Plateau de Bure Interferometer was used to investigate the molecular gas quantity in AGN.1317, observing the 12CO(2-1) emission line. Results: We detect CO emission in an AGN belonging to a galaxy cluster at z ~ 1.4. We measured a molecular gas mass of 1.1 × 1010M⊙, comparable to that found in submillimeter galaxies. In optical images, AGN.1317 does not seem to be part of a galaxy interaction or merger. We also derived the nearly instantaneous star formation rate (SFR) from Hα flux obtaining a SFR ~ 65 M⊙ yr-1. This suggests that AGN.1317 is actively forming stars and will exhaust its reservoir of cold gas in ~0.2-1.0 Gyr. Based on observations carried out with the IRAM Plateau de Bure Interferometer. IRAM is supported by INSU/CNRS (France), MPG (Germany), and IGN (Spain).Reduced IRAM data is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/558/A60

CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment.

PubMed

Oh, Jeongsu; Choi, Chi-Hwan; Park, Min-Kyu; Kim, Byung Kwon; Hwang, Kyuin; Lee, Sang-Heon; Hong, Soon Gyu; Nasir, Arshan; Cho, Wan-Sup; Kim, Kyung Mo

2016-01-01

High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology-a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr.

CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment

PubMed Central

Park, Min-Kyu; Kim, Byung Kwon; Hwang, Kyuin; Lee, Sang-Heon; Hong, Soon Gyu; Nasir, Arshan; Cho, Wan-Sup; Kim, Kyung Mo

2016-01-01

High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology–a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr. PMID:26954507

High Performance Computing Based Parallel HIearchical Modal Association Clustering (HPAR HMAC)

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

Patlolla, Dilip R; Surendran Nair, Sujithkumar; Graves, Daniel A.

For many applications, clustering is a crucial step in order to gain insight into the makeup of a dataset. The best approach to a given problem often depends on a variety of factors, such as the size of the dataset, time restrictions, and soft clustering requirements. The HMAC algorithm seeks to combine the strengths of 2 particular clustering approaches: model-based and linkage-based clustering. One particular weakness of HMAC is its computational complexity. HMAC is not practical for mega-scale data clustering. For high-definition imagery, a user would have to wait months or years for a result; for a 16-megapixel image, themore » estimated runtime skyrockets to over a decade! To improve the execution time of HMAC, it is reasonable to consider an multi-core implementation that utilizes available system resources. An existing imple-mentation (Ray and Cheng 2014) divides the dataset into N partitions - one for each thread prior to executing the HMAC algorithm. This implementation benefits from 2 types of optimization: parallelization and divide-and-conquer. By running each partition in parallel, the program is able to accelerate computation by utilizing more system resources. Although the parallel implementation provides considerable improvement over the serial HMAC, it still suffers from poor computational complexity, O(N2). Once the maximum number of cores on a system is exhausted, the program exhibits slower behavior. We now consider a modification to HMAC that involves a recursive partitioning scheme. Our modification aims to exploit divide-and-conquer benefits seen by the parallel HMAC implementation. At each level in the recursion tree, partitions are divided into 2 sub-partitions until a threshold size is reached. When the partition can no longer be divided without falling below threshold size, the base HMAC algorithm is applied. This results in a significant speedup over the parallel HMAC.« less

Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs)

PubMed Central

2013-01-01

Background The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of ‘ad hoc’ gene expression data-sets. Results By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. Conclusions Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation. PMID:24088245

Al7CX (X=Li-Cs) clusters: Stability and the prospect for cluster materials

NASA Astrophysics Data System (ADS)

Ashman, C.; Khanna, S. N.; Pederson, M. R.; Kortus, J.

2000-12-01

Al7C clusters, recently found to have a high-electron affinity and exceptional stability, are shown to form ionic molecules when combined with alkali-metal atoms. Our studies, based on an ab initio gradient-corrected density-functional scheme, show that Al7CX (X=Li-Cs) clusters have a very low-electron affinity and a high-ionization potential. When combined, the two- and four-atom composite clusters of Al7CLi units leave the Al7C clusters almost intact. Preliminary studies indicate that Al7CLi may be suitable to form cluster-based materials.

D-Cluster Converter Foil for Laser-Accelerated Deuteron Beams: Towards Deuteron-Beam-Driven Fast Ignition

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

Miley, George H.

Fast Ignition (FI) uses Petawatt laser generated particle beam pulse to ignite a small volume called a pre-compressed Inertial Confinement Fusion (ICF) target, and is the favored method to achieve the high energy gain per target burn needed for an attractive ICF power plant. Ion beams such as protons, deuterons or heavier carbon ions are especially appealing for FI as they have relative straight trajectory, and easier to focus on the fuel capsule. But current experiments have encountered problems with the 'converter-foil' which is irradiated by the Petawatt laser to produce the ion beams. The problems include depletion of themore » available ions in the convertor foils, and poor energy efficiency (ion beam energy/ input laser energy). We proposed to develop a volumetrically-loaded ultra-high-density deuteron deuterium cluster material as the basis for converter-foil for deuteron beam generation. The deuterons will fuse with the ICF DT while they slow down, providing an extra 'bonus' energy gain in addition to heating the hot spot. Also, due to the volumetric loading, the foil will provide sufficient energetic deuteron beam flux for 'hot spot' ignition, while avoiding the depletion problem encountered by current proton-driven FI foils. After extensive comparative studies, in Phase I, high purity PdO/Pd/PdO foils were selected for the high packing fraction D-Cluster converter foils. An optimized loading process has been developed to increase the cluster packing fraction in this type of foil. As a result, the packing fraction has been increased from 0.1% to 10% - meeting the original Phase I goal and representing a significant progress towards the beam intensities needed for both FI and pulsed neutron applications. Fast Ignition provides a promising approach to achieve high energy gain target performance needed for commercial Inertial Confinement Fusion (ICF). This is now a realistic goal for near term in view of the anticipated ICF target burn at the National Ignition Facility (NIF) in CA within a year. This will usher in the technology development Phase of ICF after years of research aimed at achieving breakeven experiment. Methods to achieve the high energy gain needed for a competitive power plant will then be a key developmental issue, and our D-cluster target for Fast Ignition (FI) is expected to meet that need.« less

The Cluster Environment of Two High-mass Protostars

NASA Astrophysics Data System (ADS)

Montes, Virginie; Hofner, Peter

2017-06-01

Characterizing the environment and stellar population in which high-mass stars form is an important step to decide between the main massive star formation theories. In the monolithic collapse model, the mass of the core will determine the final stellar mass (e.g., McKee & Tan 2003). In contrast, in the competitive accretion model (e.g., Bonnell & Bate 2006), the mass of the high-mass star is related to the properties of the cluster. As dynamical processes substantially affect the appearance of a cluster, we study early stages of high-mass star formation. These regions often show extended emission from hot dust at infrared wavelengths, which can cause difficulties to define the cluster. We use a multi-wavelength technique to study nearby high-mass star clusters, based on X-ray observations with the Chandra X-Ray Telescope, in conjunction with infrared data and VLA data. The technique relies on the fact that YSOs are particularly bright in X-ray and that contamination is relatively small. X-ray observations allow us to determine the cluster size. The cluster membership and YSOs classification is established using infrared identification of the X-ray sources, and color-color and color-magnitude diagrams.In this talk, I will present our findings on the cluster study of two high-mass star forming regions: IRAS 20126+4104 and IRAS 16562-3959. While most massive stars appear to be formed in rich a cluster environment, those two sources are candidates for the formation of massive stars in a relatively poor cluster. In contrast to what was found in previous studies (Qiu et al. 2008), the dominant B0-type protostar in IRAS 20126+4104 is associated with a small cluster of low-mass stars. I will also show our current work on IRAS 16562-3959, which contains one of the most luminous O-type protostars in the Galaxy. In the vicinity of this particularly interesting region there is a multitude of small clusters, for which I will present how their stellar population differ from the high-mass star-forming cluster IRAS 16562-3959.

Development of Metal Cluster-Based Energetic Materials at NSWC-IHD

DTIC Science & Technology

2011-01-01

reactivity of NixAly + clusters with nitromethane was investigated using a gas-phase molecular beam system. Results indicate that nitromethane is highly...clusters make up the subunit of a molecular metal-based energetic material. The reactivity of NixAly+ clusters with nitromethane was investigated using...a gas-phase molecular beam system. Results indicate that nitromethane is highly reactive toward the NixAly+ clusters and suggests it would not make

Triosmium Clusters on a Support: Determination of Structure by X-Ray Absorption Spectroscopy and High-Resolution Microscopy

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

Shareghe, Mehraeen; Chi, Miaofang; Browning, Nigel D.

2011-01-01

The structures of small, robust metal clusters on a solid support were determined by a combination of spectroscopic and microscopic methods: extended X-ray absorption fine structure (EXAFS) spectroscopy, scanning transmission electron microscopy (STEM), and aberration-corrected STEM. The samples were synthesized from [Os{sub 3}(CO){sub 12}] on MgO powder to provide supported clusters intended to be triosmium. The results demonstrate that the supported clusters are robust in the absence of oxidants. Conventional high-angle annular dark-field (HAADF) STEM images demonstrate a high degree of uniformity of the clusters, with root-mean-square (rms) radii of 2.03 {+-} 0.06 {angstrom}. The EXAFS OsOs coordination number ofmore » 2.1 {+-} 0.4 confirms the presence of triosmium clusters on average and correspondingly determines an average rms cluster radius of 2.02 {+-} 0.04 {angstrom}. The high-resolution STEM images show the individual Os atoms in the clusters, confirming the triangular structures of their frames and determining OsOs distances of 2.80 {+-} 0.14 {angstrom}, matching the EXAFS value of 2.89 {+-} 0.06 {angstrom}. IR and EXAFS spectra demonstrate the presence of CO ligands on the clusters. This set of techniques is recommended as optimal for detailed and reliable structural characterization of supported clusters.« less

Stressful jobs and non-stressful jobs: a cluster analysis of office jobs.

PubMed

Carayon, P

1994-02-01

The purpose of the study was to determine if office jobs could be characterized by a small number of combinations of stressors that could be related to job-title information and self-report of psychological strain. Two-hundred-and-sixty-two office workers from three public service organizations provided data on nine job stressors and seven indicators of psychological strain. Using cluster analysis on the nine stressors, office jobs were classified into three clusters. The first cluster included jobs with high skill utilization, task clarity, job control and social support and low future ambiguity, but also high on job demands such as quantitative work-load, attention and work pressure. The second cluster included jobs with high demands and future ambiguity and low skill utilization, task clarity, job control and social support. The third cluster was intermediary between the first two clusters. The three clusters were related to job-title information. The second cluster was the highest on a range of psychological strain indicators, while the other two clusters were high on certain strain indicators but low on others. The study showed that office jobs could be characterized by a small number of combinations of stressors that were related to job-title information and psychological strain.

High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya.

PubMed

Jia, Peng; Anderson, John D; Leitner, Michael; Rheingans, Richard

2016-01-01

Access to sanitation facilities is imperative in reducing the risk of multiple adverse health outcomes. A distinct disparity in sanitation exists among different wealth levels in many low-income countries, which may hinder the progress across each of the Millennium Development Goals. The surveyed households in 397 clusters from 2008-2009 Kenya Demographic and Health Surveys were divided into five wealth quintiles based on their national asset scores. A series of spatial analysis methods including excess risk, local spatial autocorrelation, and spatial interpolation were applied to observe disparities in coverage of improved sanitation among different wealth categories. The total number of the population with improved sanitation was estimated by interpolating, time-adjusting, and multiplying the surveyed coverage rates by high-resolution population grids. A comparison was then made with the annual estimates from United Nations Population Division and World Health Organization /United Nations Children's Fund Joint Monitoring Program for Water Supply and Sanitation. The Empirical Bayesian Kriging interpolation produced minimal root mean squared error for all clusters and five quintiles while predicting the raw and spatial coverage rates of improved sanitation. The coverage in southern regions was generally higher than in the north and east, and the coverage in the south decreased from Nairobi in all directions, while Nyanza and North Eastern Province had relatively poor coverage. The general clustering trend of high and low sanitation improvement among surveyed clusters was confirmed after spatial smoothing. There exists an apparent disparity in sanitation among different wealth categories across Kenya and spatially smoothed coverage rates resulted in a closer estimation of the available statistics than raw coverage rates. Future intervention activities need to be tailored for both different wealth categories and nationally where there are areas of greater needs when resources are limited.

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets

PubMed Central

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L.; Dianes, José A.; del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W.; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-01-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra. PMID:27493588

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets.

PubMed

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L; Dianes, José A; Del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-08-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.

Open clusters. III. Fundamental parameters of B stars in NGC 6087, NGC 6250, NGC 6383, and NGC 6530 B-type stars with circumstellar envelopes

NASA Astrophysics Data System (ADS)

Aidelman, Y.; Cidale, L. S.; Zorec, J.; Panei, J. A.

2018-02-01

Context. Stellar physical properties of star clusters are poorly known and the cluster parameters are often very uncertain. Methods: Our goals are to perform a spectrophotometric study of the B star population in open clusters to derive accurate stellar parameters, search for the presence of circumstellar envelopes, and discuss the characteristics of these stars. The BCD spectrophotometric system is a powerful method to obtain stellar fundamental parameters from direct measurements of the Balmer discontinuity. To this end, we wrote the interactive code MIDE3700. The BCD parameters can also be used to infer the main properties of open clusters: distance modulus, color excess, and age. Furthermore, we inspected the Balmer discontinuity to provide evidence for the presence of circumstellar disks and identify Be star candidates. We used an additional set of high-resolution spectra in the Hα region to confirm the Be nature of these stars. Results: We provide Teff, log g, Mv, Mbol, and spectral types for a sample of 68 stars in the field of the open clusters NGC 6087, NGC 6250, NGC 6383, and NGC 6530, as well as the cluster distances, ages, and reddening. Then, based on a sample of 230 B stars in the direction of the 11 open clusters studied along this series of three papers, we report 6 new Be stars, 4 blue straggler candidates, and 15 B-type stars (called Bdd) with a double Balmer discontinuity, which indicates the presence of circumstellar envelopes. We discuss the distribution of the fraction of B, Be, and Bdd star cluster members per spectral subtype. The majority of the Be stars are dwarfs and present a maximum at the spectral type B2-B4 in young and intermediate-age open clusters (<40 Myr). Another maximum of Be stars is observed at the spectral type B6-B8 in open clusters older than 40 Myr, where the population of Bdd stars also becomes relevant. The Bdd stars seem to be in a passive emission phase. Conclusions: Our results support previous statements that the Be phenomenon is present along the whole main sequence band and occurs in very different evolutionary states. We find clear evidence of an increase of stars with circumstellar envelopes with cluster age. The Be phenomenon reaches its maximum in clusters of intermediate age (10-40 Myr) and the number of B stars with circumstellar envelopes (Be plus Bdd stars) is also high for the older clusters (40-100 Myr). Observations taken at CASLEO, operating under agreement of CONICET and the Universities of La Plata, Córdoba, and San Juan, Argentina.Tables 1, 2, 9-16 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/610/A30

Desktop supercomputer: what can it do?

NASA Astrophysics Data System (ADS)

Bogdanov, A.; Degtyarev, A.; Korkhov, V.

2017-12-01

The paper addresses the issues of solving complex problems that require using supercomputers or multiprocessor clusters available for most researchers nowadays. Efficient distribution of high performance computing resources according to actual application needs has been a major research topic since high-performance computing (HPC) technologies became widely introduced. At the same time, comfortable and transparent access to these resources was a key user requirement. In this paper we discuss approaches to build a virtual private supercomputer available at user's desktop: a virtual computing environment tailored specifically for a target user with a particular target application. We describe and evaluate possibilities to create the virtual supercomputer based on light-weight virtualization technologies, and analyze the efficiency of our approach compared to traditional methods of HPC resource management.

The WHISPER Relaxation Sounder and the CLUSTER Active Archive

NASA Astrophysics Data System (ADS)

Trotignon, J. G.; Décréau, P. M. E.; Rauch, J. L.; Vallières, X.; Rochel, A.; Kougblénou, S.; Lointier, G.; Facskó, G.; Canu, P.; Darrouzet, F.; Masson, A.

The Waves of HIgh frequency and Sounder for Probing of Electron density by Relaxation (WHISPER) instrument is part of the Wave Experiment Consortium (WEC) of the CLUSTER mission. With the help of the long double sphere antennae of the Electric Field and Wave (EFW) instrument and the Digital Wave Processor (DWP), it delivers active (sounding) and natural (transmitter off) electric field spectra, respectively from 4 to 82 kHz, and from 2 to 80 kHz. These frequency ranges have been chosen to include the electron plasma frequency, which is closely related to the total electron density, in most of the regions encountered by the CLUSTER spacecraft. Presented here is an overview of the WHISPER data products available in the CLUSTER Active Archive (CAA). The instrument and its performance are first recalled. The way the WHISPER products are obtained is then described, with particular attention being paid to the density determination. Both sounding and natural measurements are commonly used in this process, which depends on the ambient plasma regime. This is illustrated using drawings similar to the Bryant plots commonly used in the CLUSTER master science plan. These give a clear overview of typical density values and the parts of the orbits where they are obtained. More information on the applied software or on the quality/reliability of the density determination can also be highlighted.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

PubMed

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Mapping the Indonesian territory, based on pollution, social demography and geographical data, using self organizing feature map

NASA Astrophysics Data System (ADS)

Hernawati, Kuswari; Insani, Nur; Bambang S. H., M.; Nur Hadi, W.; Sahid

2017-08-01

This research aims to mapping the 33 (thirty-three) provinces in Indonesia, based on the data on air, water and soil pollution, as well as social demography and geography data, into a clustered model. The method used in this study was unsupervised method that combines the basic concept of Kohonen or Self-Organizing Feature Maps (SOFM). The method is done by providing the design parameters for the model based on data related directly/ indirectly to pollution, which are the demographic and social data, pollution levels of air, water and soil, as well as the geographical situation of each province. The parameters used consists of 19 features/characteristics, including the human development index, the number of vehicles, the availability of the plant's water absorption and flood prevention, as well as geographic and demographic situation. The data used were secondary data from the Central Statistics Agency (BPS), Indonesia. The data are mapped into SOFM from a high-dimensional vector space into two-dimensional vector space according to the closeness of location in term of Euclidean distance. The resulting outputs are represented in clustered grouping. Thirty-three provinces are grouped into five clusters, where each cluster has different features/characteristics and level of pollution. The result can used to help the efforts on prevention and resolution of pollution problems on each cluster in an effective and efficient way.

A Computational Cluster for Multiscale Simulations of Ionic Liquids

DTIC Science & Technology

2008-09-16

AND SUBTITLE DURIP: A Computational Cluster for Multiscale Simulations of Ionic Liquids 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA955007-1-0512 5c...AVAILABILITY STATEMENT ZO\\5oc\\\\%1>^ 13. SUPPLEMENTARY NOTES 14. ABSTRACT The focus of this project was to acquire and use computer cluster nodes...by ANSI Std. Z39.18 Adobe Professional 7.0 Comprehensive Final Report: Gregory A. Voth, PI Contract/Grant Title: DURIP: A Computational Cluster for

ClueNet: Clustering a temporal network based on topological similarity rather than denseness

PubMed Central

Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of “topologically related” nodes, where the resulting topology-based clusters are expected to “correlate” well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data—their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance. PMID:29738568

Country clustering applied to the water and sanitation sector: a new tool with potential applications in research and policy.

PubMed

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2014-03-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were distinct from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. Copyright © 2013 Elsevier GmbH. All rights reserved.

Urban hospital 'clusters' do shift high-risk procedures to key facilities, but more could be done.

PubMed

Luke, Roice D; Luke, Tyler; Muller, Nancy

2011-09-01

Since the 1990s, rapid consolidation in the hospital sector has resulted in the vast majority of hospitals joining systems that already had a considerable presence within their markets. We refer to these important local and regional systems as "clusters." To determine whether hospital clusters have taken measurable steps aimed at improving the quality of care-specifically, by concentrating low-volume, high-complexity services within selected "lead" facilities-this study examined within-cluster concentrations of high-risk cases for seven surgical procedures. We found that lead hospitals on average performed fairly high percentages of the procedures per cluster, ranging from 59 percent for esophagectomy to 87 percent for aortic valve replacement. The numbers indicate that hospitals might need to work with rival facilities outside their cluster to concentrate cases for the lowest-volume procedures, such as esophagectomies, whereas coordination among cluster members might be sufficient for higher-volume procedures. The results imply that policy makers should focus on clusters' potential for restructuring care and further coordinating services across hospitals in local areas.

MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters.

PubMed

Abreu, Rui Mv; Froufe, Hugo Jc; Queiroz, Maria João Rp; Ferreira, Isabel Cfr

2010-10-28

Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a potential maximum speed-up of 10x, the parallel algorithm of MOLA performed with a speed-up of 8,64× using AutoDock4 and 8,60× using Vina.

Membership determination of open clusters based on a spectral clustering method

NASA Astrophysics Data System (ADS)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

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

PubMed

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

2015-01-01

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

Messier 35 (NGC 2168) DANCe. I. Membership, proper motions, and multiwavelength photometry

NASA Astrophysics Data System (ADS)

Bouy, H.; Bertin, E.; Barrado, D.; Sarro, L. M.; Olivares, J.; Moraux, E.; Bouvier, J.; Cuillandre, J.-C.; Ribas, Á.; Beletsky, Y.

2015-03-01

Context. Messier 35 (NGC 2168) is an important young nearby cluster. Its age, richness and relative proximity make it an ideal target for stellar evolution studies. The Kepler K2 mission recently observed it and provided a high accuracy photometric time series of a large number of sources in this area of the sky. Identifying the cluster's members is therefore of high importance to optimize the interpretation and analysis of the Kepler K2 data. Aims: We aim to identify the cluster's members by deriving membership probabilities for the sources within 1° of the cluster's center, which is farther away than equivalent previous studies. Methods: We measure accurate proper motions and multiwavelength (optical and near-infrared) photometry using ground-based archival images of the cluster. We use these measurements to compute membership probabilities. The list of candidate members from the literature is used as a training set to identify the cluster's locus in a multidimensional space made of proper motions, luminosities, and colors. Results: The final catalog includes 338 892 sources with multiwavelength photometry. Approximately half (194 452) were detected at more than two epochs and we measured their proper motion and used it to derive membership probability. A total of 4349 candidate members with membership probabilities greater than 50% are found in this sample in the luminosity range between 10 mag and 22 mag. The slow proper motion of the cluster and the overlap of its sequence with the field and background sequences in almost all color-magnitude and color-color diagrams complicate the analysis and the contamination level is expected to be significant. Our study, nevertheless, provides a coherent and quantitative membership analysis of Messier 35 based on a large fraction of the best ground-based data sets obtained over the past 18 years. As such, it represents a valuable input for follow-up studies using, in particular, the Kepler K2 photometric time series. Table 3 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/575/A120

High- and low-level hierarchical classification algorithm based on source separation process

NASA Astrophysics Data System (ADS)

Loghmari, Mohamed Anis; Karray, Emna; Naceur, Mohamed Saber

2016-10-01

High-dimensional data applications have earned great attention in recent years. We focus on remote sensing data analysis on high-dimensional space like hyperspectral data. From a methodological viewpoint, remote sensing data analysis is not a trivial task. Its complexity is caused by many factors, such as large spectral or spatial variability as well as the curse of dimensionality. The latter describes the problem of data sparseness. In this particular ill-posed problem, a reliable classification approach requires appropriate modeling of the classification process. The proposed approach is based on a hierarchical clustering algorithm in order to deal with remote sensing data in high-dimensional space. Indeed, one obvious method to perform dimensionality reduction is to use the independent component analysis process as a preprocessing step. The first particularity of our method is the special structure of its cluster tree. Most of the hierarchical algorithms associate leaves to individual clusters, and start from a large number of individual classes equal to the number of pixels; however, in our approach, leaves are associated with the most relevant sources which are represented according to mutually independent axes to specifically represent some land covers associated with a limited number of clusters. These sources contribute to the refinement of the clustering by providing complementary rather than redundant information. The second particularity of our approach is that at each level of the cluster tree, we combine both a high-level divisive clustering and a low-level agglomerative clustering. This approach reduces the computational cost since the high-level divisive clustering is controlled by a simple Boolean operator, and optimizes the clustering results since the low-level agglomerative clustering is guided by the most relevant independent sources. Then at each new step we obtain a new finer partition that will participate in the clustering process to enhance semantic capabilities and give good identification rates.

A knowledge-driven approach to cluster validity assessment.

PubMed

Bolshakova, Nadia; Azuaje, Francisco; Cunningham, Pádraig

2005-05-15

This paper presents an approach to assessing cluster validity based on similarity knowledge extracted from the Gene Ontology. The program is freely available for non-profit use on request from the authors.

Links between patterns of racial socialization and discrimination experiences and psychological adjustment: a cluster analysis.

PubMed

Ajayi, Alex A; Syed, Moin

2014-10-01

This study used a person-oriented analytic approach to identify meaningful patterns of barriers-focused racial socialization and perceived racial discrimination experiences in a sample of 295 late adolescents. Using cluster analysis, three distinct groups were identified: Low Barrier Socialization-Low Discrimination, High Barrier Socialization-Low Discrimination, and High Barrier Socialization-High Discrimination clusters. These groups were substantively unique in terms of the frequency of racial socialization messages about bias preparation and out-group mistrust its members received and their actual perceived discrimination experiences. Further, individuals in the High Barrier Socialization-High Discrimination cluster reported significantly higher depressive symptoms than those in the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. However, no differences in adjustment were observed between the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. Overall, the findings highlight important individual differences in how young people of color experience their race and how these differences have significant implications on psychological adjustment. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

ClubSub-P: Cluster-Based Subcellular Localization Prediction for Gram-Negative Bacteria and Archaea

PubMed Central

Paramasivam, Nagarajan; Linke, Dirk

2011-01-01

The subcellular localization (SCL) of proteins provides important clues to their function in a cell. In our efforts to predict useful vaccine targets against Gram-negative bacteria, we noticed that misannotated start codons frequently lead to wrongly assigned SCLs. This and other problems in SCL prediction, such as the relatively high false-positive and false-negative rates of some tools, can be avoided by applying multiple prediction tools to groups of homologous proteins. Here we present ClubSub-P, an online database that combines existing SCL prediction tools into a consensus pipeline from more than 600 proteomes of fully sequenced microorganisms. On top of the consensus prediction at the level of single sequences, the tool uses clusters of homologous proteins from Gram-negative bacteria and from Archaea to eliminate false-positive and false-negative predictions. ClubSub-P can assign the SCL of proteins from Gram-negative bacteria and Archaea with high precision. The database is searchable, and can easily be expanded using either new bacterial genomes or new prediction tools as they become available. This will further improve the performance of the SCL prediction, as well as the detection of misannotated start codons and other annotation errors. ClubSub-P is available online at http://toolkit.tuebingen.mpg.de/clubsubp/ PMID:22073040

MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC-MS metabolomic datasets.

PubMed

Edmands, William M B; Barupal, Dinesh K; Scalbert, Augustin

2015-03-01

MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker-MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R). All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC-MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository. © The Author 2014. Published by Oxford University Press.

Evaluation of food-relevant chemicals in the ToxCast high ...

EPA Pesticide Factsheets

There are thousands of chemicals that are directly added to or come in contact with food, many of which have undergone little to no toxicological evaluation. The ToxCast high-throughput screening (HTS) program has evaluated over 1,800 chemicals in concentration-response across ~820 assay endpoints and continues to grow; with all data completely available to the public, this resource serves as a unique opportunity to evaluate the bioactivity of chemicals in vitro. This study investigated the chemical landscape of the food-relevant chemical universe using cheminformatics analyses, and subsequently evaluated the bioactivity of food-relevant chemicals included in the ToxCast HTS program. Initially, a list of 9,437 food-relevant chemicals was compiled by comprehensively mining publicly available sources for direct food additives, food contact substances, indirect food additives, and pesticides. Of these food-relevant chemicals, 4,638 were associated with curated structure definition files amenable to defining physical/chemical features used to generate chemical fingerprints. Clustering was conducted based on the chemical fingerprints using a self-organizing map approach. This revealed that pesticides, food contact substances, and direct food additives generally clustered apart from one another, supporting that these categories reflect not only different uses but also distinct chemistries. Subsequently, 967 of the 9,437 food-relevant chemicals were identified in the T

Robust continuous clustering

PubMed Central

Shah, Sohil Atul

2017-01-01

Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank. PMID:28851838

OpenCluster: A Flexible Distributed Computing Framework for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Statistical analysis of short-term water stress conditions at Riggs Creek OzFlux tower site

NASA Astrophysics Data System (ADS)

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

2017-10-01

A large range of indices and proxies are available to describe the water stress conditions of an area subject to different applications, which have varying capabilities and limitations depending on the prevailing local climatic conditions and land cover. The present study uses a range of spatio-temporally high-resolution (daily and within daily) data sources to evaluate a number of drought indices (DIs) for the Riggs Creek OzFlux tower site in southeastern Australia. Therefore, the main aim of this study is to evaluate the statistical characteristics of individual DIs subject to short-term water stress conditions. In order to derive a more general and therefore representative DI, a new criterion is required to specify the statistical similarity between each pair of indices to allow determining the dominant drought types along with their representative DIs. The results show that the monitoring of water stress at this case study area can be achieved by evaluating the individual behaviour of three clusters of (i) vegetation conditions, (ii) water availability and (iii) water consumptions. This indicates that it is not necessary to assess all individual DIs one by one to derive a comprehensive and informative data set about the water stress of an area; instead, this can be achieved by analysing one of the DIs from each cluster or deriving a new combinatory index for each cluster, based on established combination methods.

HGDP and HapMap Analysis by Ancestry Mapper Reveals Local and Global Population Relationships

PubMed Central

Magalhães, Tiago R.; Casey, Jillian P.; Conroy, Judith; Regan, Regina; Fitzpatrick, Darren J.; Shah, Naisha; Sobral, João; Ennis, Sean

2012-01-01

Knowledge of human origins, migrations, and expansions is greatly enhanced by the availability of large datasets of genetic information from different populations and by the development of bioinformatic tools used to analyze the data. We present Ancestry Mapper, which we believe improves on existing methods, for the assignment of genetic ancestry to an individual and to study the relationships between local and global populations. The principle function of the method, named Ancestry Mapper, is to give each individual analyzed a genetic identifier, made up of just 51 genetic coordinates, that corresponds to its relationship to the HGDP reference population. As a consequence, the Ancestry Mapper Id (AMid) has intrinsic biological meaning and provides a tool to measure similarity between world populations. We applied Ancestry Mapper to a dataset comprised of the HGDP and HapMap data. The results show distinctions at the continental level, while simultaneously giving details at the population level. We clustered AMids of HGDP/HapMap and observe a recapitulation of human migrations: for a small number of clusters, individuals are grouped according to continental origins; for a larger number of clusters, regional and population distinctions are evident. Calculating distances between AMids allows us to infer ancestry. The number of coordinates is expandable, increasing the power of Ancestry Mapper. An R package called Ancestry Mapper is available to apply this method to any high density genomic data set. PMID:23189146

HGDP and HapMap analysis by Ancestry Mapper reveals local and global population relationships.

PubMed

Magalhães, Tiago R; Casey, Jillian P; Conroy, Judith; Regan, Regina; Fitzpatrick, Darren J; Shah, Naisha; Sobral, João; Ennis, Sean

2012-01-01

Knowledge of human origins, migrations, and expansions is greatly enhanced by the availability of large datasets of genetic information from different populations and by the development of bioinformatic tools used to analyze the data. We present Ancestry Mapper, which we believe improves on existing methods, for the assignment of genetic ancestry to an individual and to study the relationships between local and global populations. The principle function of the method, named Ancestry Mapper, is to give each individual analyzed a genetic identifier, made up of just 51 genetic coordinates, that corresponds to its relationship to the HGDP reference population. As a consequence, the Ancestry Mapper Id (AMid) has intrinsic biological meaning and provides a tool to measure similarity between world populations. We applied Ancestry Mapper to a dataset comprised of the HGDP and HapMap data. The results show distinctions at the continental level, while simultaneously giving details at the population level. We clustered AMids of HGDP/HapMap and observe a recapitulation of human migrations: for a small number of clusters, individuals are grouped according to continental origins; for a larger number of clusters, regional and population distinctions are evident. Calculating distances between AMids allows us to infer ancestry. The number of coordinates is expandable, increasing the power of Ancestry Mapper. An R package called Ancestry Mapper is available to apply this method to any high density genomic data set.

Fibers in the NGC 1333 proto-cluster

NASA Astrophysics Data System (ADS)

Hacar, A.; Tafalla, M.; Alves, J.

2017-10-01

Are the initial conditions for clustered star formation the same as for non-clustered star formation? To investigate the initial gas properties in young proto-clusters we carried out a comprehensive and high-sensitivity study of the internal structure, density, temperature, and kinematics of the dense gas content of the NGC 1333 region in Perseus, one of the nearest and best studied embedded clusters. The analysis of the gas velocities in the position-position-velocity space reveals an intricate underlying gas organization both in space and velocity. We identified a total of 14 velocity-coherent, (tran-)sonic structures within NGC 1333, with similar physical and kinematic properties than those quiescent, star-forming (aka fertile) fibers previously identified in low-mass star-forming clouds. These fibers are arranged in a complex spatial network, build-up the observed total column density, and contain the dense cores and protostars in this cloud. Our results demonstrate that the presence of fibers is not restricted to low-mass clouds but can be extended to regions of increasing mass and complexity. We propose that the observational dichotomy between clustered and non-clustered star-forming regions might be naturally explained by the distinct spatial density of fertile fibers in these environments. Based on observations carried out under project number 169-11 with the IRAM 30 m Telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain).Based on observations with the 100-m telescope of the MPIfR (Max-Planck-Institut für Radioastronomie) at Effelsberg.Molecular line observations (spectral cubes) are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/606/A123

NGC 6535: the lowest mass Milky Way globular cluster with a Na-O anti-correlation? Cluster mass and age in the multiple population context

NASA Astrophysics Data System (ADS)

Bragaglia, A.; Carretta, E.; D'Orazi, V.; Sollima, A.; Donati, P.; Gratton, R. G.; Lucatello, S.

2017-11-01

To understand globular clusters (GCs) we need to comprehend how their formation process was able to produce their abundance distribution of light elements. In particular, we seek to figure out which stars imprinted the peculiar chemical signature of GCs. One of the best ways is to study the light-element anti-correlations in a large sample of GCs that are analysed homogeneously. As part of our spectroscopic survey of GCs with FLAMES, we present here the results of our study of about 30 red giant member stars in the low-mass, low-metallicity Milky Way cluster NGC 6535. We measured the metallicity (finding [Fe/H] =-1.95, rms = 0.04 dex in our homogeneous scale) and other elements of the cluster and, in particular, we concentrate here on O and Na abundances. These elements define the normal Na-O anti-correlation of classical GCs, making NGC 6535 perhaps the lowest mass cluster with a confirmed presence of multiple populations. We updated the census of Galactic and extragalactic GCs for which a statement on the presence or absence of multiple populations can be made on the basis of high-resolution spectroscopy preferentially, or photometry and low-resolution spectroscopy otherwise; we also discuss the importance of mass and age of the clusters as factors for multiple populations. Based on observations collected at ESO telescopes under programme 093.B-0583.Table 2 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/607/A44

ICAP - An Interactive Cluster Analysis Procedure for analyzing remotely sensed data

NASA Technical Reports Server (NTRS)

Wharton, S. W.; Turner, B. J.

1981-01-01

An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. ICAP differs from conventional clustering algorithms by allowing the analyst to optimize the cluster configuration by inspection, rather than by manipulating process parameters. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters, and the analyst, who can evaluate and elect to modify the cluster structure. Clusters can be deleted, or lumped together pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The principal advantage of this approach is that it allows prior information (when available) to be used directly in the analysis, since the analyst interacts with ICAP in a straightforward manner, using basic terms with which he is more likely to be familiar. Results from testing ICAP showed that an informed use of ICAP can improve classification, as compared to an existing cluster analysis procedure.

Semi-supervised clustering methods.

PubMed

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.

Effects of radiation reaction in the interaction between cluster media and high intensity lasers in the radiation dominant regime

NASA Astrophysics Data System (ADS)

Iwata, Natsumi; Nagatomo, Hideo; Fukuda, Yuji; Matsui, Ryutaro; Kishimoto, Yasuaki

2016-06-01

Interaction between media composed of clusters and high intensity lasers in the radiation dominant regime, i.e., intensity of 10 22 - 23 W / cm 2 , is studied based on the particle-in-cell simulation that includes the radiation reaction. By introducing target materials that have the same total mass but different internal structures, i.e., uniform plasma and cluster media with different cluster radii, we investigate the effect of the internal structure on the interaction dynamics, high energy radiation emission, and its reaction. Intense radiation emission is found in the cluster media where electrons exhibit non-ballistic motions suffering from strong accelerations by both the penetrated laser field and charge separation field of clusters. As a result, the clustered structure increases the energy conversion into high energy radiations significantly at the expense of the conversion into particles, while the total absorption rate into radiation and particles remains unchanged from the absorption rate into particles in the case without radiation reaction. The maximum ion energy achieved in the interaction with cluster media is found to be decreased through the radiation reaction to electrons into the same level with that achieved in the interaction with the uniform plasma. The clustered structure thus enhances high energy radiation emission rather than the ion acceleration in the considered intensity regime.

Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study.

PubMed

Barker, Daniel; D'Este, Catherine; Campbell, Michael J; McElduff, Patrick

2017-03-09

Stepped wedge cluster randomised trials frequently involve a relatively small number of clusters. The most common frameworks used to analyse data from these types of trials are generalised estimating equations and generalised linear mixed models. A topic of much research into these methods has been their application to cluster randomised trial data and, in particular, the number of clusters required to make reasonable inferences about the intervention effect. However, for stepped wedge trials, which have been claimed by many researchers to have a statistical power advantage over the parallel cluster randomised trial, the minimum number of clusters required has not been investigated. We conducted a simulation study where we considered the most commonly used methods suggested in the literature to analyse cross-sectional stepped wedge cluster randomised trial data. We compared the per cent bias, the type I error rate and power of these methods in a stepped wedge trial setting with a binary outcome, where there are few clusters available and when the appropriate adjustment for a time trend is made, which by design may be confounding the intervention effect. We found that the generalised linear mixed modelling approach is the most consistent when few clusters are available. We also found that none of the common analysis methods for stepped wedge trials were both unbiased and maintained a 5% type I error rate when there were only three clusters. Of the commonly used analysis approaches, we recommend the generalised linear mixed model for small stepped wedge trials with binary outcomes. We also suggest that in a stepped wedge design with three steps, at least two clusters be randomised at each step, to ensure that the intervention effect estimator maintains the nominal 5% significance level and is also reasonably unbiased.

Improving clustering with metabolic pathway data.

PubMed

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

2014-04-10

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

Computational investigation on the structures and electronic properties of the nanosized rhenium clusters

DOE PAGES

Zhao, Run -Ning; Chen, Rui; Yuan, Yan -Hong; ...

2017-08-10

Here, the stable equilibrium geometries, relative stabilities, and electronic and magnetic characteristics of Re n (n = 2–16) clusters were investigated by density functional theory method. The calculated fragmentation energies and second-order differences of energies exhibited interestingly that the stabilities of Re n (n = 2–16) clusters show a dramatic odd-even alternative behavior of the cluster size n: with the even-numbered Ren clusters being obviously more stable than their neighboring odd-numbered Re n clusters (beside n = 11). Simultaneously, the calculated HOMO-LUMO gaps of Re n (n = 6–16) display an oscillatory feature at large-sized Ren clusters. From the calculatedmore » magnetic moments and growth behaviors of Rhenium clusters, the magnetic Re 6 unit can be seen as the building block for the novel magnetic cluster-assembled nanomaterial. Such calculated results are in good agreement with the available experimental measurements.« less

Computational investigation on the structures and electronic properties of the nanosized rhenium clusters

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

Zhao, Run -Ning; Chen, Rui; Yuan, Yan -Hong

Here, the stable equilibrium geometries, relative stabilities, and electronic and magnetic characteristics of Re n (n = 2–16) clusters were investigated by density functional theory method. The calculated fragmentation energies and second-order differences of energies exhibited interestingly that the stabilities of Re n (n = 2–16) clusters show a dramatic odd-even alternative behavior of the cluster size n: with the even-numbered Ren clusters being obviously more stable than their neighboring odd-numbered Re n clusters (beside n = 11). Simultaneously, the calculated HOMO-LUMO gaps of Re n (n = 6–16) display an oscillatory feature at large-sized Ren clusters. From the calculatedmore » magnetic moments and growth behaviors of Rhenium clusters, the magnetic Re 6 unit can be seen as the building block for the novel magnetic cluster-assembled nanomaterial. Such calculated results are in good agreement with the available experimental measurements.« less

Investigating Faculty Familiarity with Assessment Terminology by Applying Cluster Analysis to Interpret Survey Data

ERIC Educational Resources Information Center

Raker, Jeffrey R.; Holme, Thomas A.

2014-01-01

A cluster analysis was conducted with a set of survey data on chemistry faculty familiarity with 13 assessment terms. Cluster groupings suggest a high, middle, and low overall familiarity with the terminology and an independent high and low familiarity with terms related to fundamental statistics. The six resultant clusters were found to be…

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space

PubMed Central

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-01-01

Motivation: UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. Application: We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. Results: We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. Availability: A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request. Contact: lonshy@cs.huji.ac.il PMID:18586742

Quenching of Star-formation Activity of High-redshift Galaxies in Clusters and Field

NASA Astrophysics Data System (ADS)

Lee, Seong-Kook; Im, Myungshin; Kim, Jae-Woo; Lotz, Jennifer; McPartland, Conor; Peth, Michael; Koekemoer, Anton

At local, galaxy properties are well known to be clearly different in different environments. However, it is still an open question how this environment-dependent trend has been shaped. We present the results of our investigation about the evolution of star-formation properties of galaxies over a wide redshift range, from z ~ 2 to z ~ 0.5, focusing its dependence on their stellar mass and environment (Lee et al. 2015). In the UKIDSS/UDS region, covering ~2800 square arcmin, we estimated photometric redshifts and stellar population properties, such as stellar masses and star-formation rates, using the deep optical and near-infrared data available in this field. Then, we identified galaxy cluster candidates within the given redshift range. Through the analysis and comparison of star-formation (SF) properties of galaxies in clusters and in field, we found interesting results regarding the evolution of SF properties of galaxies: (1) regardless of redshifts, stellar mass is a key parameter controlling quenching of star formation in galaxies; (2) At z < 1, environmental effects become important at quenching star formation regardless of stellar mass of galaxies; and (3) However, the result of the environmental quenching is prominent only for low mass galaxies (M* < 1010 M⊙) since the star formation in most of high mass galaxies are already quenched at z > 1.

High-resolution optical imaging of the core of the globular cluster M15 with FastCam

NASA Astrophysics Data System (ADS)

Díaz-Sánchez, Anastasio; Pérez-Garrido, Antonio; Villó, Isidro; Rebolo, Rafael; Pérez-Prieto, Jorge A.; Oscoz, Alejandro; Hildebrandt, Sergi R.; López, Roberto; Rodríguez, Luis F.

2012-07-01

We present high-resolution I -band imaging of the core of the globular cluster M15 obtained at the 2.5-m Nordic Optical Telescope with FastCam, a low readout noise L3CCD-based instrument. Short exposure times (30 ms) were used to record 200 000 images (512 × 512 pixels each) over a period of 2 h and 43 min. The lucky imaging technique was then applied to generate a final image of the cluster centre with full width at half-maximum ˜0.1 arcsec and 13 × 13 arcsec 2 field of view. We obtained a catalogue of objects in this region with a limiting magnitude of I = 19.5. I -band photometry and astrometry are reported for 1181 stars. This is the deepest I -band observation of the M15 core at this spatial resolution. Simulations show that crowding is limiting the completeness of the catalogue. At shorter wavelengths, a similar number of objects have been reported using Hubble Space Telescope (HST )/Wide Field Planetary Camera observations of the same field. The cross-match with the available HST catalogues allowed us to produce colour-magnitude diagrams where we identify new blue straggler star candidates and previously known stars of this class.

Application of a clustering-remote sensing method in analyzing security patterns

NASA Astrophysics Data System (ADS)

López-Caloca, Alejandra; Martínez-Viveros, Elvia; Chapela-Castañares, José Ignacio

2009-04-01

In Mexican academic and government circles, research on criminal spatial behavior has been neglected. Only recently has there been an interest in criminal data geo-reference. However, more sophisticated spatial analyses models are needed to disclose spatial patterns of crime and pinpoint their changes overtime. The main use of these models lies in supporting policy making and strategic intelligence. In this paper we present a model for finding patterns associated with crime. It is based on a fuzzy logic algorithm which finds the best fit within cluster numbers and shapes of groupings. We describe the methodology for building the model and its validation. The model was applied to annual data for types of felonies from 2005 to 2006 in the Mexican city of Hermosillo. The results are visualized as a standard deviational ellipse computed for the points identified to be a "cluster". These areas indicate a high to low demand for public security, and they were cross-related to urban structure analyzed by SPOT images and statistical data such as population, poverty levels, urbanization, and available services. The fusion of the model results with other geospatial data allows detecting obstacles and opportunities for crime commission in specific high risk zones and guide police activities and criminal investigations.

Spatial imaging of carbon reactivity centers in Pd/C catalytic systems† †Electronic supplementary information (ESI) available: Detailed experimental procedures and FE-SEM images. See DOI: 10.1039/c5sc00802f

PubMed Central

Pentsak, E. O.; Kashin, A. S.; Polynski, M. V.; Kvashnina, K. O.; Glatzel, P.

2015-01-01

Gaining insight into Pd/C catalytic systems aimed at locating reactive centers on carbon surfaces, revealing their properties and estimating the number of reactive centers presents a challenging problem. In the present study state-of-the-art experimental techniques involving ultra high resolution SEM/STEM microscopy (1 Å resolution), high brilliance X-ray absorption spectroscopy and theoretical calculations on truly nanoscale systems were utilized to reveal the role of carbon centers in the formation and nature of Pd/C catalytic materials. Generation of Pd clusters in solution from the easily available Pd2dba3 precursor and the unique reactivity of the Pd clusters opened an excellent opportunity to develop an efficient procedure for the imaging of a carbon surface. Defect sites and reactivity centers of a carbon surface were mapped in three-dimensional space with high resolution and excellent contrast using a user-friendly nanoscale imaging procedure. The proposed imaging approach takes advantage of the specific interactions of reactive carbon centers with Pd clusters, which allows spatial information about chemical reactivity across the Pd/C system to be obtained using a microscopy technique. Mapping the reactivity centers with Pd markers provided unique information about the reactivity of the graphene layers and showed that >2000 reactive centers can be located per 1 μm2 of the surface area of the carbon material. A computational study at a PBE-D3-GPW level differentiated the relative affinity of the Pd2 species to the reactive centers of graphene. These findings emphasized the spatial complexity of the carbon material at the nanoscale and indicated the importance of the surface defect nature, which exhibited substantial gradients and variations across the surface area. The findings show the crucial role of the structure of the carbon support, which governs the formation of Pd/C systems and their catalytic activity. PMID:29511504

Cluster analysis of bone microarchitecture from high resolution peripheral quantitative computed tomography demonstrates two separate phenotypes associated with high fracture risk in men and women.

PubMed

Edwards, M H; Robinson, D E; Ward, K A; Javaid, M K; Walker-Bone, K; Cooper, C; Dennison, E M

2016-07-01

Osteoporosis is a major healthcare problem which is conventionally assessed by dual energy X-ray absorptiometry (DXA). New technologies such as high resolution peripheral quantitative computed tomography (HRpQCT) also predict fracture risk. HRpQCT measures a number of bone characteristics that may inform specific patterns of bone deficits. We used cluster analysis to define different bone phenotypes and their relationships to fracture prevalence and areal bone mineral density (BMD). 177 men and 159 women, in whom fracture history was determined by self-report and vertebral fracture assessment, underwent HRpQCT of the distal radius and femoral neck DXA. Five clusters were derived with two clusters associated with elevated fracture risk. "Cluster 1" contained 26 women (50.0% fractured) and 30 men (50.0% fractured) with a lower mean cortical thickness and cortical volumetric BMD, and in men only, a mean total and trabecular area more than the sex-specific cohort mean. "Cluster 2" contained 20 women (50.0% fractured) and 14 men (35.7% fractured) with a lower mean trabecular density and trabecular number than the sex-specific cohort mean. Logistic regression showed fracture rates in these clusters to be significantly higher than the lowest fracture risk cluster [5] (p<0.05). Mean femoral neck areal BMD was significantly lower than cluster 5 in women in cluster 1 and 2 (p<0.001 for both), and in men, in cluster 2 (p<0.001) but not 1 (p=0.220). In conclusion, this study demonstrates two distinct high risk clusters in both men and women which may differ in etiology and response to treatment. As cluster 1 in men does not have low areal BMD, these men may not be identified as high risk by conventional DXA alone. Copyright © 2016. Published by Elsevier Inc.

Elastic K-means using posterior probability.

PubMed

Zheng, Aihua; Jiang, Bo; Li, Yan; Zhang, Xuehan; Ding, Chris

2017-01-01

The widely used K-means clustering is a hard clustering algorithm. Here we propose a Elastic K-means clustering model (EKM) using posterior probability with soft capability where each data point can belong to multiple clusters fractionally and show the benefit of proposed Elastic K-means. Furthermore, in many applications, besides vector attributes information, pairwise relations (graph information) are also available. Thus we integrate EKM with Normalized Cut graph clustering into a single clustering formulation. Finally, we provide several useful matrix inequalities which are useful for matrix formulations of learning models. Based on these results, we prove the correctness and the convergence of EKM algorithms. Experimental results on six benchmark datasets demonstrate the effectiveness of proposed EKM and its integrated model.

Clustering cancer gene expression data by projective clustering ensemble

PubMed Central

Yu, Xianxue; Yu, Guoxian

2017-01-01

Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data. PMID:28234920

Understanding Statistical Power in Cluster Randomized Trials: Challenges Posed by Differences in Notation and Terminology

ERIC Educational Resources Information Center

Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael

2014-01-01

Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…

Ultraviolet studies of O and B stars in the LMC cluster NGC 2100, the SMC cluster NGC 330 and the Galactic cluster NGC 6530

NASA Technical Reports Server (NTRS)

Boehm-Vitense, E.; Hodge, P.

1984-01-01

High-resolution and low-resolution IUE spectra of O and B stars in the LMC cluster NGC 2100, the SMC cluster NGC 330, and the young Galactic cluster NGC 6530 are investigated. Temperatures and luminosities are determined. In the LMC and SMC clusters, the most luminous stars are evolved stars on the horizontal supergiant branch, while in NGC 6530 the stars are all still on the main sequence. Extinction laws were determined. They confirm the known differences between LMC and Galactic extinctions. No mass loss was detected for the evolved B stars in the LMC and SMC clusters, while the high-luminosity stars in NGC 6530 show P Cygni profiles.

How Do Social Capital and HIV/AIDS Outcomes Geographically Cluster and Which Sociocontextual Mechanisms Predict Differences Across Clusters?

PubMed

Ransome, Yusuf; Dean, Lorraine T; Crawford, Natalie D; Metzger, David S; Blank, Michael B; Nunn, Amy S

2017-09-01

Place of residence has been associated with HIV transmission risks. Social capital, defined as features of social organization that improve efficiency of society by facilitating coordinated actions, often varies by neighborhood, and hypothesized to have protective effects on HIV care continuum outcomes. We examined whether the association between social capital and 2 HIV care continuum outcomes clustered geographically and whether sociocontextual mechanisms predict differences across clusters. Bivariate Local Moran's I evaluated geographical clustering in the association between social capital (participation in civic and social organizations, 2006, 2008, 2010) and [5-year (2007-2011) prevalence of late HIV diagnosis and linkage to HIV care] across Philadelphia, PA, census tracts (N = 378). Maps documented the clusters and multinomial regression assessed which sociocontextual mechanisms (eg, racial composition) predict differences across clusters. We identified 4 significant clusters (high social capital-high HIV/AIDS, low social capital-low HIV/AIDS, low social capital-high HIV/AIDS, and high social capital-low HIV/AIDS). Moran's I between social capital and late HIV diagnosis was (I = 0.19, z = 9.54, P < 0.001) and linkage to HIV care (I = 0.06, z = 3.274, P = 0.002). In multivariable analysis, median household income predicted differences across clusters, particularly where social capital was lowest and HIV burden the highest, compared with clusters with high social capital and lowest HIV burden. The association between social participation and HIV care continuum outcomes cluster geographically in Philadelphia, PA. HIV prevention interventions should account for this phenomenon. Reducing geographic disparities will require interventions tailored to each continuum step and that address socioeconomic factors such as neighborhood median income.

The Gaia-ESO Survey: Structural and dynamical properties of the young cluster Chamaeleon I

NASA Astrophysics Data System (ADS)

Sacco, G. G.; Spina, L.; Randich, S.; Palla, F.; Parker, R. J.; Jeffries, R. D.; Jackson, R.; Meyer, M. R.; Mapelli, M.; Lanzafame, A. C.; Bonito, R.; Damiani, F.; Franciosini, E.; Frasca, A.; Klutsch, A.; Prisinzano, L.; Tognelli, E.; Degl'Innocenti, S.; Prada Moroni, P. G.; Alfaro, E. J.; Micela, G.; Prusti, T.; Barrado, D.; Biazzo, K.; Bouy, H.; Bravi, L.; Lopez-Santiago, J.; Wright, N. J.; Bayo, A.; Gilmore, G.; Bragaglia, A.; Flaccomio, E.; Koposov, S. E.; Pancino, E.; Casey, A. R.; Costado, M. T.; Donati, P.; Hourihane, A.; Jofré, P.; Lardo, C.; Lewis, J.; Magrini, L.; Monaco, L.; Morbidelli, L.; Sousa, S. G.; Worley, C. C.; Zaggia, S.

2017-05-01

Investigating the physical mechanisms driving the dynamical evolution of young star clusters is fundamental to our understanding of the star formation process and the properties of the Galactic field stars. The young ( 2 Myr) and partially embedded cluster Chamaeleon I is one of the closest laboratories for the study of the early stages of star cluster dynamics in a low-density environment. The aim of this work is to study the structural and kinematical properties of this cluster combining parameters from the high-resolution spectroscopic observations of the Gaia-ESO Survey with data from the literature. Our main result is the evidence of a large discrepancy between the velocity dispersion (σstars = 1.14 ± 0.35 km s-1) of the stellar population and the dispersion of the pre-stellar cores ( 0.3 km s-1) derived from submillimeter observations. The origin of this discrepancy, which has been observed in other young star clusters, is not clear. It has been suggested that it may be due to either the effect of the magnetic field on the protostars and the filaments or to the dynamical evolution of stars driven by two-body interactions. Furthermore, the analysis of the kinematic properties of the stellar population puts in evidence a significant velocity shift ( 1 km s-1) between the two subclusters located around the north and south main clouds of the cluster. This result further supports a scenario where clusters form from the evolution of multiple substructures rather than from a monolithic collapse. Using three independent spectroscopic indicators (the gravity indicator γ, the equivalent width of the Li line at 6708 Å, and the Hα 10% width), we performed a new membership selection. We found six new cluster members all located in the outer region of the cluster, proving that Chamaeleon I is probably more extended than previously thought. Starting from the positions and masses of the cluster members, we derived the level of substructure Q, the surface density Σ, and the level of mass segregation ΛMSR of the cluster. The comparison between these structural properties and the results of N-body simulations suggests that the cluster formed in a low-density environment, in virial equilibrium or a supervirial state, and highly substructured. This work is one of the last ones carried out with the help and support of our friend and colleague Francesco Palla, who passed away on 26 January 2016.Full Tables 1 and 2 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/601/A97Based on observations made with the ESO/VLT, at Paranal Observatory, under program 188.B-3002 (The Gaia-ESO Public Spectroscopic Survey).

Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Hayden, David; Thompson, David R.; Castano, Rebecca

2013-01-01

Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangement

VI photometry of the galactic cluster Berkeley 66

NASA Astrophysics Data System (ADS)

Guarnieri, M. D.; Carraro, G.

1997-03-01

A colour magnitude diagram (CMD) extending to V ~= 19 mag is given for 444 stars in the region of the galactic cluster Berkeley 66. The V and I photometry of a nearby field is also reported. This object appears very faint, highly contaminated by foreground stars and very reddened. The apparent distance modulus (m-M) and the colour excess E_{V-I} are guessed to be 17.5 and 1.1, respectively, with an uncertainty of at least 30%. Adopting these values the comparison of the CMD with theoretical isochrones from the Padova group provides an age around 1.0 Gyr. Based on observations carried out at Pino Torinese Observatory, Torino, Italy. Table 2 is available only in electronic form at the CDS via anonymous ftp 130.79.128.5.

One-way quantum computing in superconducting circuits

NASA Astrophysics Data System (ADS)

Albarrán-Arriagada, F.; Alvarado Barrios, G.; Sanz, M.; Romero, G.; Lamata, L.; Retamal, J. C.; Solano, E.

2018-03-01

We propose a method for the implementation of one-way quantum computing in superconducting circuits. Measurement-based quantum computing is a universal quantum computation paradigm in which an initial cluster state provides the quantum resource, while the iteration of sequential measurements and local rotations encodes the quantum algorithm. Up to now, technical constraints have limited a scalable approach to this quantum computing alternative. The initial cluster state can be generated with available controlled-phase gates, while the quantum algorithm makes use of high-fidelity readout and coherent feedforward. With current technology, we estimate that quantum algorithms with above 20 qubits may be implemented in the path toward quantum supremacy. Moreover, we propose an alternative initial state with properties of maximal persistence and maximal connectedness, reducing the required resources of one-way quantum computing protocols.

Exploratory Item Classification Via Spectral Graph Clustering

PubMed Central

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2017-01-01

Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class analysis, often induce a high computational overhead and have difficulty handling missing data, especially in the presence of high-dimensional responses. In this article, the authors propose a spectral clustering algorithm for exploratory item cluster analysis. The method is computationally efficient, effective for data with missing or incomplete responses, easy to implement, and often outperforms traditional clustering algorithms in the context of high dimensionality. The spectral clustering algorithm is based on graph theory, a branch of mathematics that studies the properties of graphs. The algorithm first constructs a graph of items, characterizing the similarity structure among items. It then extracts item clusters based on the graphical structure, grouping similar items together. The proposed method is evaluated through simulations and an application to the revised Eysenck Personality Questionnaire. PMID:29033476

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

2003-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi-component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma-sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), electron energy-loss spectroscopy (EELS) and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia- yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging from 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

1990-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi- component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma- sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia-yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging fiom 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Effects of an intervention strategy for school children aimed at reducing overweight and obesity within the State of Mexico.

PubMed

Morales-Ruán, María del Carmen; Shamah-Levy, Teresa; Amaya-Castellanos, Claudia Isabel; Salazar-Coronel, Araceli Apolonia; Jiménez-Aguilar, Alejandra; Amaya-Castellanos, Maritza Alejandra; Méndez-Gómez Humarán, Ignacio

2014-01-01

This study explored the intervention effect of the "Nutrition on the Go" strategy on the prevalence of overweight and obesity (OW+O), according to the role played by different patterns. Pattern Groups (PG) were determined based on schools' food availability and other variables at individual level: nutrition knowledge, physical activity, socioeconomic level and self-efficacy, using an ecological approach. The PG classification was achieved using Ward's cluster method. The prevalence of OW+O was higher in PGI (intermediate food availability and high socioeconomic index [SEI]) compared to PG 2 (high availability of food and lower SEI) and PG 3 (low availability of food and medium SEI) with a lower prevalence (p<0.00I). The PG-intervention interaction showed differences for PG 3 (p=0.066), the stage-PG interaction showed differences between PGs I and 3 (p=0.014) and between PGs 2 and 3 (p=0.055). Differences between PGs have important implications for the prevalence of OW+O.

Surface enhanced Raman spectroscopy (SERS) from a molecule adsorbed on a nanoscale silver particle cluster in a holographic plate

NASA Astrophysics Data System (ADS)

Jusinski, Leonard E.; Bahuguna, Ramen; Das, Amrita; Arya, Karamjeet

2006-02-01

Surface enhanced Raman spectroscopy has become a viable technique for the detection of single molecules. This highly sensitive technique is due to the very large (up to 14 orders in magnitude) enhancement in the Raman cross section when the molecule is adsorbed on a metal nanoparticle cluster. We report here SERS (Surface Enhanced Raman Spectroscopy) experiments performed by adsorbing analyte molecules on nanoscale silver particle clusters within the gelatin layer of commercially available holographic plates which have been developed and fixed. The Ag particles range in size between 5 - 30 nanometers (nm). Sample preparation was performed by immersing the prepared holographic plate in an analyte solution for a few minutes. We report here the production of SERS signals from Rhodamine 6G (R6G) molecules of nanomolar concentration. These measurements demonstrate a fast, low cost, reproducible technique of producing SERS substrates in a matter of minutes compared to the conventional procedure of preparing Ag clusters from colloidal solutions. SERS active colloidal solutions require up to a full day to prepare. In addition, the preparations of colloidal aggregates are not consistent in shape, contain additional interfering chemicals, and do not generate consistent SERS enhancement. Colloidal solutions require the addition of KCl or NaCl to increase the ionic strength to allow aggregation and cluster formation. We find no need to add KCl or NaCl to create SERS active clusters in the holographic gelatin matrix. These holographic plates, prepared using simple, conventional procedures, can be stored in an inert environment and preserve SERS activity after several weeks subsequent to preparation.

Membership, binarity, and rotation of F-G-K stars in the open cluster Blanco 1

NASA Astrophysics Data System (ADS)

Mermilliod, J.-C.; Platais, I.; James, D. J.; Grenon, M.; Cargile, P. A.

2008-07-01

Context: The nearby open cluster Blanco 1 is of considerable astrophysical interest for formation and evolution studies of open clusters because it is the third highest Galactic latitude cluster known. It has been observed often, but so far no definitive and comprehensive membership determination is readily available. Aims: An observing programme was carried out to study the stellar population of Blanco 1, and especially the membership and binary frequency of the F5-K0 dwarfs. Methods: We obtained radial-velocities with the CORAVEL spectrograph in the field of Blanco 1 for a sample of 148 F-G-K candidate stars in the magnitude range 10 < V < 14. New proper motions and UBVI CCD photometric data from two extensive surveys were obtained independently and are used to establish reliable cluster membership assignments in concert with radial-velocity data. Results: The membership of 68 stars is confirmed on the basis of proper motion, radial velocity, and photometric criteria. Fourteen spectroscopic- and suspected binaries (2 SB2s, 9 SB1s, 3 SB?) have been discovered among the confirmed members. Thirteen additional stars are located above the main sequence or close to the binary ridge, with radial velocities and proper motions supporting their membership. These are probable binaries with wide separations. Nine binaries (7 SB1 and 2 SB2) were detected among the field stars. The spectroscopic binary frequency among members is 20% (14/68); however, the overall binary rate reaches 40% (27/68) if one includes the photometric binaries. The cluster mean heliocentric radial velocity is +5.53 ± 0.11 km s-1 based on the most reliable 49 members. The V sin i distribution is similar to that of the Pleiades, confirming the age similarities between the two clusters. Conclusions: This study clearly demonstrates that, in spite of the cluster's high Galactic latitude, three membership criteria - radial velocity, proper motion, and photometry - are necessary for performing a reliable membership selection. Furthermore, even with accurate and extensive data, ambiguous cases still remain. Based on observations collected with the Danish 1.54-m and the Swiss telescopes at the European Southern Observatory, La Silla, Chile, and with the old YALO 1-m telescope at the Cerro Tololo InterAmerican Observatory, Chile. Table [see full textsee full textsee full textsee full textsee full textsee full text] is also available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/485/95

Relative risk estimates from spatial and space-time scan statistics: Are they biased?

PubMed Central

Prates, Marcos O.; Kulldorff, Martin; Assunção, Renato M.

2014-01-01

The purely spatial and space-time scan statistics have been successfully used by many scientists to detect and evaluate geographical disease clusters. Although the scan statistic has high power in correctly identifying a cluster, no study has considered the estimates of the cluster relative risk in the detected cluster. In this paper we evaluate whether there is any bias on these estimated relative risks. Intuitively, one may expect that the estimated relative risks has upward bias, since the scan statistic cherry picks high rate areas to include in the cluster. We show that this intuition is correct for clusters with low statistical power, but with medium to high power the bias becomes negligible. The same behaviour is not observed for the prospective space-time scan statistic, where there is an increasing conservative downward bias of the relative risk as the power to detect the cluster increases. PMID:24639031

Are Early Somatic Embryos of the Norway Spruce (Picea abies (L.) Karst.) Organised?

PubMed Central

Petrek, Jiri; Zitka, Ondrej; Adam, Vojtech; Bartusek, Karel; Anjum, Naser A.; Pereira, Eduarda; Havel, Ladislav; Kizek, Rene

2015-01-01

Background Somatic embryogenesis in conifer species has great potential for the forestry industry. Hence, a number of methods have been developed for their efficient and rapid propagation through somatic embryogenesis. Although information is available regarding the previous process-mediated generation of embryogenic cells to form somatic embryos, there is a dearth of information in the literature on the detailed structure of these clusters. Methodology/Principal Findings The main aim of this study was to provide a more detailed structure of the embryogenic tissue clusters obtained through the in vitro propagation of the Norway spruce (Picea abies (L.) Karst.). We primarily focused on the growth of early somatic embryos (ESEs). The data on ESE growth suggested that there may be clear distinctions between their inner and outer regions. Therefore, we selected ESEs collected on the 56th day after sub-cultivation to dissect the homogeneity of the ESE clusters. Two colourimetric assays (acetocarmine and fluorescein diacetate/propidium iodide staining) and one metabolic assay based on the use of 2,3,5-triphenyltetrazolium chloride uncovered large differences in the metabolic activity inside the cluster. Next, we performed nuclear magnetic resonance measurements. The ESE cluster seemed to be compactly aggregated during the first four weeks of cultivation; thereafter, the difference between the 1H nuclei concentration in the inner and outer clusters was more evident. There were clear differences in the visual appearance of embryos from the outer and inner regions. Finally, a cluster was divided into six parts (three each from the inner and the outer regions of the embryo) to determine their growth and viability. The innermost embryos (centripetally towards the cluster centre) could grow after sub-cultivation but exhibited the slowest rate and required the longest time to reach the common growth rate. To confirm our hypothesis on the organisation of the ESE cluster, we investigated the effect of cluster orientation on the cultivation medium and the influence of the change of the cluster’s three-dimensional orientation on its development. Maintaining the same position when transferring ESEs into new cultivation medium seemed to be necessary because changes in the orientation significantly affected ESE growth. Conclusions and Significance This work illustrated the possible inner organisation of ESEs. The outer layer of ESEs is formed by individual somatic embryos with high metabolic activity (and with high demands for nutrients, oxygen and water), while an embryonal group is directed outside of the ESE cluster. Somatic embryos with depressed metabolic activity were localised in the inner regions, where these embryonic tissues probably have a very important transport function. PMID:26624287

Cognitive-affective depression and somatic symptoms clusters are differentially associated with maternal parenting and coparenting.

PubMed

Lamela, Diogo; Jongenelen, Inês; Morais, Ana; Figueiredo, Bárbara

2017-09-01

Both depressive and somatic symptoms are significant predictors of parenting and coparenting problems. However, despite clear evidence of their co-occurrence, no study to date has examined the association between depressive-somatic symptoms clusters and parenting and coparenting. The current research sought to identify and cross-validate clusters of cognitive-affective depressive symptoms and nonspecific somatic symptoms, as well as to test whether clusters would differ on parenting and coparenting problems across three independent samples of mothers. Participants in Studies 1 and 3 consisted of 409 and 652 community mothers, respectively. Participants in Study 2 consisted of 162 mothers exposed to intimate partner violence. All participants prospectively completed self-report measures of depressive and nonspecific somatic symptoms and parenting (Studies 1 and 2) or coparenting (Study 3). Across studies, three depression-somatic symptoms clusters were identified: no symptoms, high depression and low nonspecific somatic symptoms, and high depression and nonspecific somatic symptoms. The high depression-somatic symptoms cluster was associated with the highest levels of child physical maltreatment risk (Study 1) and overt-conflict coparenting (Study 3). No differences in perceived maternal competence (Study 2) and cooperative and undermining coparenting (Study 3) were found between the high depression and low somatic symptoms cluster and the high depression-somatic symptoms cluster. The results provide novel evidence for the strong associations between clusters of depression and nonspecific somatic symptoms and specific parenting and coparenting problems. Cluster stability across three independent samples suggest that they may be generalizable. The results inform preventive approaches and evidence-based psychotherapeutic treatments. Copyright © 2017 Elsevier B.V. All rights reserved.

High Performance Data Transfer for Distributed Data Intensive Sciences

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

Fang, Chin; Cottrell, R 'Les' A.; Hanushevsky, Andrew B.

We report on the development of ZX software providing high performance data transfer and encryption. The design scales in: computation power, network interfaces, and IOPS while carefully balancing the available resources. Two U.S. patent-pending algorithms help tackle data sets containing lots of small files and very large files, and provide insensitivity to network latency. It has a cluster-oriented architecture, using peer-to-peer technologies to ease deployment, operation, usage, and resource discovery. Its unique optimizations enable effective use of flash memory. Using a pair of existing data transfer nodes at SLAC and NERSC, we compared its performance to that of bbcp andmore » GridFTP and determined that they were comparable. With a proof of concept created using two four-node clusters with multiple distributed multi-core CPUs, network interfaces and flash memory, we achieved 155Gbps memory-to-memory over a 2x100Gbps link aggregated channel and 70Gbps file-to-file with encryption over a 5000 mile 100Gbps link.« less

Planck, Herschel & Spitzer unveil overdense z>2 regions

NASA Astrophysics Data System (ADS)

Dole, Herve; Chary, Ranga-Ram; Chary, Ranga; Frye, Brenda; Martinache, Clement; Guery, David; Le Floc'h, Emeric; Altieri, Bruno; Flores-Cacho, Ines; Giard, Martin; Hurier, Guillaume; Lagache, Guilaine; Montier, Ludovic; Nesvadba, Nicole; Omont, Alain; Pointecouteau, Etienne; Pierini, Daniele; Puget, Jean-Loup; Scott, Douglas; Soucail, Genevieve

2014-12-01

At which cosmic epoch did massive galaxy clusters assemble their baryons? How does star formation occur in the most massive, most rapidly collapsing dark-matter-dense environments in the early Universe? To answer these questions, we take the completely novel approach to select the most extreme z>~2 star-forming overdensities seen over the entire sky. This selection nicely complements the other existing selections for high redshift clusters (i.e., by stellar mass, or by total mass like Sunyaev-Zeldovish (SZ) or X-ray selection). We make use of the Planck all-sky submillimetre survey to systematically identify the rarest, most luminous high-redshift sub-mm sources on the sky, either strongly gravitationally lensed galaxies, or the joint FIR/sub-mm emission from multiple intense starbursts. We observed 228 Planck sources with Herschel/SPIRE and discovered that most of them are overdensities of red galaxies with extremely high star formation rates (typically 7.e3 Msun/yr for a structure). Only Spitzer data can allow a better understanding of these promising Planck+Herschel selected sources, as is shown on a first set of IRAC data on 40 targets in GO9: (i) the good angular resolution and sensitivity of IRAC allows a proper determination of the clustered nature of each Herschel/SPIRE source; (ii) IRAC photometry (often associated with J, K) allows a good estimate of the colors and approximate photometric redshift. Note spectroscopic redshifts are available for two cluster candidates, at z=1.7 and z=2.3, confirming their high redshift nature. The successful GO9 observation of 40 fields showed that about half to be >7sigma overdensities of red IRAC sources. These observations were targeting the whole range of Herschel overdensities and significances. We need to go deeper into the Spitzer sample and acquire complete coverage of the most extreme Herschel overdensities (54 new fields). Such a unique sample has legacy value, and this is the last opportunity prior to JWST, WFIRST and Euclid.

VizieR Online Data Catalog: Globular and open clusters observed by SDSS/SEGUE (Morrison+, 2016)

NASA Astrophysics Data System (ADS)

Morrison, H. L.; Ma, Z.; Clem, J. L.; An, D.; Connor, T.; Schechtman-Rook, A.; Casagrande, L.; Rockosi, C.; Yanny, B.; Harding, P.; Beers, T. C.; Johnson, J. A.; Schneider, D. P.

2018-03-01

The SEGUE project observed a number of globular and open clusters for calibration purposes. For calibration of the red giants, we selected the globular clusters M92, M13 and M71 (spanning metallicities from -2.4 to -0.8) and the open clusters Be 29, NGC 7789 and NGC 6791, whose [Fe/H] values range from -0.4 to +0.4. In all but one case, the clusters are within the SDSS footprint and so ugriz photometry is available for the cluster stars. The SDSS cluster images were analyzed using DAOPHOT (Stetson 1987PASP...99..191S) by An et al. (2008ApJS..179..326A) because the SDSS photometric pipeline was not designed to handle crowded fields. (8 data files).

Label-free high-throughput detection and quantification of circulating melanoma tumor cell clusters by linear-array-based photoacoustic tomography

NASA Astrophysics Data System (ADS)

Hai, Pengfei; Zhou, Yong; Zhang, Ruiying; Ma, Jun; Li, Yang; Shao, Jin-Yu; Wang, Lihong V.

2017-04-01

Circulating tumor cell (CTC) clusters, arising from multicellular groupings in a primary tumor, greatly elevate the metastatic potential of cancer compared with single CTCs. High-throughput detection and quantification of CTC clusters are important for understanding the tumor metastatic process and improving cancer therapy. Here, we applied a linear-array-based photoacoustic tomography (LA-PAT) system and improved the image reconstruction for label-free high-throughput CTC cluster detection and quantification in vivo. The feasibility was first demonstrated by imaging CTC cluster ex vivo. The relationship between the contrast-to-noise ratios (CNRs) and the number of cells in melanoma tumor cell clusters was investigated and verified. Melanoma CTC clusters with a minimum of four cells could be detected, and the number of cells could be computed from the CNR. Finally, we demonstrated imaging of injected melanoma CTC clusters in rats in vivo. Similarly, the number of cells in the melanoma CTC clusters could be quantified. The data showed that larger CTC clusters had faster clearance rates in the bloodstream, which agreed with the literature. The results demonstrated the capability of LA-PAT to detect and quantify melanoma CTC clusters in vivo and showed its potential for tumor metastasis study and cancer therapy.

C 60 as a chemical Faraday cage for three ferromagnetic Fe atoms

NASA Astrophysics Data System (ADS)

Gao, Guohua; Kang, Hong Seok

2008-09-01

Based on calculations using density functional theory, we show that C 60 can act as a chemical Faraday cage in which a highly magnetic metal cluster with a high chemical reactivity can be encapsulated. As an example, we find that C 60 can encapsulate a Fe 3 cluster, while it is much less likely to encapsulate a Fe 2 cluster. Spin multiplicity (=9) of the Fe 3@C 60 is very high, being comparable to that (=11) of a free Fe 3 cluster. Geometrically, the triangular plane of the cluster is perpendicular to a S6 axis of the fullerene.

Methamphetamine injecting is associated with phylogenetic clustering of hepatitis C virus infection among street-involved youth in Vancouver, Canada*

PubMed Central

Cunningham, Evan; Jacka, Brendan; DeBeck, Kora; Applegate, Tanya A; Harrigan, P. Richard; Krajden, Mel; Marshall, Brandon DL; Montaner, Julio; Lima, Viviane Dias; Olmstead, Andrea; Milloy, M-J; Wood, Evan; Grebely, Jason

2015-01-01

Background Among prospective cohorts of people who inject drugs (PWID), phylogenetic clustering of HCV infection has been observed. However, the majority of studies have included older PWID, representing distant transmission events. The aim of this study was to investigate phylogenetic clustering of HCV infection among a cohort of street-involved youth. Methods Data were derived from a prospective cohort of street-involved youth aged 14–26 recruited between 2005 and 2012 in Vancouver, Canada (At Risk Youth Study, ARYS). HCV RNA testing and sequencing (Core-E2) were performed on HCV positive participants. Phylogenetic trees were inferred using maximum likelihood methods and clusters were identified using ClusterPicker (Core-E2 without HVR1, 90% bootstrap threshold, 0.05 genetic distance threshold). Results Among 945 individuals enrolled in ARYS, 16% (n=149, 100% recent injectors) were HCV antibody positive at baseline interview (n=86) or seroconverted during follow-up (n=63). Among HCV antibody positive participants with available samples (n=131), 75% (n=98) had detectable HCV RNA and 66% (n=65, mean age 23, 58% with recent methamphetamine injection, 31% female, 3% HIV+) had available Core-E2 sequences. Of those with Core-E2 sequence, 14% (n=9) were in a cluster (one cluster of three) or pair (two pairs), with all reporting recent methamphetamine injection. Recent methamphetamine injection was associated with membership in a cluster or pair (P=0.009). Conclusion In this study of street-involved youth with HCV infection and recent injecting, 14% demonstrated phylogenetic clustering. Phylogenetic clustering was associated with recent methamphetamine injection, suggesting that methamphetamine drug injection may play an important role in networks of HCV transmission. PMID:25977204

Semi-supervised clustering methods

PubMed Central

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

Cluster-lensing: A Python Package for Galaxy Clusters and Miscentering

NASA Astrophysics Data System (ADS)

Ford, Jes; VanderPlas, Jake

2016-12-01

We describe a new open source package for calculating properties of galaxy clusters, including Navarro, Frenk, and White halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density {{Σ }}(R) and differential surface mass density {{Δ }}{{Σ }}(R) profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo. Full documentation, source code, and installation instructions are available at http://jesford.github.io/cluster-lensing/.

m-BIRCH: an online clustering approach for computer vision applications

NASA Astrophysics Data System (ADS)

Madan, Siddharth K.; Dana, Kristin J.

2015-03-01

We adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), to incrementally cluster large datasets of features commonly used in multimedia and computer vision. We call the adapted version modified-BIRCH (m-BIRCH). The algorithm uses only a fraction of the dataset memory to perform clustering, and updates the clustering decisions when new data comes in. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in data summarization. We use m-BIRCH to cluster 840K color SIFT descriptors, and 60K outlier corrupted grayscale patches. We use the algorithm to cluster datasets consisting of challenging non-convex clustering patterns. Our implementation of the algorithm provides an useful clustering tool and is made publicly available.

Cosmology from galaxy clusters as observed by Planck

NASA Astrophysics Data System (ADS)

Pierpaoli, Elena

We propose to use current all-sky data on galaxy clusters in the radio/infrared bands in order to constrain cosmology. This will be achieved performing parameter estimation with number counts and power spectra for galaxy clusters detected by Planck through their Sunyaev—Zeldovich signature. The ultimate goal of this proposal is to use clusters as tracers of matter density in order to provide information about fundamental properties of our Universe, such as the law of gravity on large scale, early Universe phenomena, structure formation and the nature of dark matter and dark energy. We will leverage on the availability of a larger and deeper cluster catalog from the latest Planck data release in order to include, for the first time, the cluster power spectrum in the cosmological parameter determination analysis. Furthermore, we will extend clusters' analysis to cosmological models not yet investigated by the Planck collaboration. These aims require a diverse set of activities, ranging from the characterization of the clusters' selection function, the choice of the cosmological cluster sample to be used for parameter estimation, the construction of mock samples in the various cosmological models with correct correlation properties in order to produce reliable selection functions and noise covariance matrices, and finally the construction of the appropriate likelihood for number counts and power spectra. We plan to make the final code available to the community and compatible with the most widely used cosmological parameter estimation code. This research makes use of data from the NASA satellites Planck and, less directly, Chandra, in order to constrain cosmology; and therefore perfectly fits the NASA objectives and the specifications of this solicitation.

nanoparticles

NASA Astrophysics Data System (ADS)

Andreu-Cabedo, Patricia; Mondragon, Rosa; Hernandez, Leonor; Martinez-Cuenca, Raul; Cabedo, Luis; Julia, J. Enrique

2014-10-01

Thermal energy storage (TES) is extremely important in concentrated solar power (CSP) plants since it represents the main difference and advantage of CSP plants with respect to other renewable energy sources such as wind, photovoltaic, etc. CSP represents a low-carbon emission renewable source of energy, and TES allows CSP plants to have energy availability and dispatchability using available industrial technologies. Molten salts are used in CSP plants as a TES material because of their high operational temperature and stability of up to 500°C. Their main drawbacks are their relative poor thermal properties and energy storage density. A simple cost-effective way to improve thermal properties of fluids is to dope them with nanoparticles, thus obtaining the so-called salt-based nanofluids. In this work, solar salt used in CSP plants (60% NaNO3 + 40% KNO3) was doped with silica nanoparticles at different solid mass concentrations (from 0.5% to 2%). Specific heat was measured by means of differential scanning calorimetry (DSC). A maximum increase of 25.03% was found at an optimal concentration of 1 wt.% of nanoparticles. The size distribution of nanoparticle clusters present in the salt at each concentration was evaluated by means of scanning electron microscopy (SEM) and image processing, as well as by means of dynamic light scattering (DLS). The cluster size and the specific surface available depended on the solid content, and a relationship between the specific heat increment and the available particle surface area was obtained. It was proved that the mechanism involved in the specific heat increment is based on a surface phenomenon. Stability of samples was tested for several thermal cycles and thermogravimetric analysis at high temperature was carried out, the samples being stable.

http://www.esa.int/esaSC/Pr_21_2004_s_en.html

NASA Astrophysics Data System (ADS)

2004-09-01

X-ray brightness map hi-res Size hi-res: 38 Kb Credits: ESA/ XMM-Newton/ Patrick Henry et al. X-ray brightness map This map shows "surface brightness" or how luminous the region is. The larger of the two galaxy clusters is brighter, shown here as a white and red spot. A second cluster resides about "2 o'clock" from this, shown by a batch of yellow surrounded by green. Luminosity is related to density, so the densest regions (cluster cores) are the brightest regions. The white color corresponds to regions of the highest surface brightness, followed by red, orange, yellow, green, blue and purple. High resolution version (JPG format) 38 Kb High resolution version (TIFF format) 525 Kb Temperature map Credits: NASA Artist’s impression of cosmic head on collision The event details what the scientists are calling the perfect cosmic storm: galaxy clusters that collided like two high-pressure weather fronts and created hurricane-like conditions, tossing galaxies far from their paths and churning shock waves of 100-million-degree gas through intergalactic space. The tiny dots in this artist's concept are galaxies containing thousand million of stars. Animated GIF version Temperature map hi-res Size hi-res: 57 Kb Credits: ESA/ XMM-Newton/ Patrick Henry et al. Temperature map This image shows the temperature of gas in and around the two merging galaxy clusters, based directly on X-ray data. The galaxies themselves are difficult to identify; the image highlights the hot ‘invisible’ gas between the clusters heated by shock waves. The white colour corresponds to regions of the highest temperature - million of degrees, hotter than the surface of the Sun - followed by red, orange, yellow and blue. High resolution version (JPG format) 57 Kb High resolution version (TIFF format) 819 Kb The event details what the scientists are calling the ‘perfect cosmic storm’: galaxy clusters that collided like two high-pressure weather fronts and created hurricane-like conditions, tossing galaxies far from their paths and churning shock waves of 100-million-degree gas through intergalactic space. This unprecedented view of a merger in action crystallises the theory that the Universe built its magnificent hierarchal structure from the ‘bottom up’ - essentially through mergers of smaller galaxies and galaxy clusters into bigger ones. "Here before our eyes we see the making of one of the biggest objects in the Universe," said Dr Patrick Henry of the University of Hawaii, who led the study. "What was once two distinct but smaller galaxy clusters 300 million years ago is now one massive cluster in turmoil.” Henry and his colleagues, Alexis Finoguenov and Ulrich Briel of the Max-Planck Institute for Extraterrestrial Physics in Germany, present these results in an upcoming issue of the Astrophysical Journal. The forecast for the new super-cluster, they said, is 'clear and calm' now that the worst of the storm has passed. Galaxy clusters are the largest gravitationally bound structures in Universe, containing hundreds to thousands of galaxies. Our Milky Way galaxy is part of a small group of galaxies but is not gravitationally bound to the closest cluster, the Virgo Cluster. We are destined for a collision in a few thousand million years, though. The cluster named Abell 754 in the constellation Hydra has been known for decades. However, to the scientists' surprise, the new observation reveals that the merger may have occurred from the opposite direction than what was thought. They found evidence for this by tracing the wreckage today left in the merger's wake, spanning a distance of millions of light years. While other large mergers are known, none has been measured in such detail as Abell 754. For the first time, the scientists could create a complete ‘weather map’ of Abell 754 and thus determine a forecast. This map contains information about the temperature, pressure and density of the new cluster. As in all clusters, most the ordinary matter is in the form of gas between the galaxies and not locked up in the galaxies or stars themselves. The massive forces of the merging clusters accelerated intergalactic gas to great speeds. This resulted in shock waves that heat the gas to very high temperatures, which then radiated X-ray light, far more energetic than the visible light our eyes can detect. XMM-Newton, in orbit, detects this type of high-energy light. The dynamics of the merger revealed by XMM-Newton point to a cluster in transition. "One cluster has apparently smashed into the other from the 'north-west' and has since made one pass through," said Finoguenov. "Now, gravity will pull the remnants of this first cluster back towards the core of the second. Over the next few thousand million of years, the remnants of the clusters will settle and the merger will be complete." The observation implies that the largest structures in the Universe are essentially still forming in the modern era. Abell 754 is relatively close, about 800 million light years away. The construction boom may soon be over in a few more thousand million years though. A mysterious substance dubbed 'dark energy' appears to be accelerating the Universe's expansion rate. This means that objects are flying apart from each other at an ever-increasing speed and that clusters may eventually never have the opportunity to collide with each other. X-ray observations of galaxy clusters such as Abell 754 will help to better define dark energy and also dark matter, an ‘invisible’ and mysterious substance that appears to comprise over 80 percent of a galaxy cluster's mass. Notes for editors: This observation was announced at a NASA Internet press conference today. A paper describing these results, by Patrick Henry and his collaborators, will be published in the Astrophysical Journal. Images and other visual material are available at: http://www.gsfc.nasa.gov/topstory/2004/0831galaxymerger_media.html More about XMM-Newton ESA's XMM-Newton can detect more X-ray sources than any previous satellite and is helping to solve many cosmic mysteries of the violent Universe, from black holes to the formation of galaxies. It was launched on 10 December 1999, using an Ariane-5 rocket, from French Guiana. It is expected to return data for a decade. XMM-Newton's high-tech design uses over 170 wafer-thin cylindrical mirrors spread over three telescopes. Its orbit takes it almost a third of the way to the Moon, so that astronomers can enjoy long, uninterrupted views of celestial objects.

Cluster of atypical adult Guillain-Barré syndrome temporally associated with neurological illness due to EV-D68 in children, South Wales, United Kingdom, October 2015 to January 2016.

PubMed

Williams, Christopher J; Thomas, Rhys H; Pickersgill, Trevor P; Lyons, Marion; Lowe, Gwen; Stiff, Rhianwen E; Moore, Catherine; Jones, Rachel; Howe, Robin; Brunt, Huw; Ashman, Anna; Mason, Brendan W

2016-01-01

We report a cluster of atypical Guillain-Barré syndrome in 10 adults temporally related to a cluster of four children with acute flaccid paralysis, over a 3-month period in South Wales, United Kingdom. All adult cases were male, aged between 24 and 77 years. Seven had prominent facial diplegia at onset. Available electrophysiological studies showed axonal involvement in five adults. Seven reported various forms of respiratory disease before onset of neurological symptoms. The ages of children ranged from one to 13 years, three of the four were two years old or younger. Enterovirus testing is available for three children; two had evidence of enterovirus D68 infection in stool or respiratory samples. We describe the clinical features, epidemiology and state of current investigations for these unusual clusters of illness.

A search for X-ray bright distant clusters of galaxies

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

The Luminosity Function of Star Clusters in 20 Star-forming Galaxies Based on Hubble Legacy Archive Photometry

NASA Astrophysics Data System (ADS)

Whitmore, Bradley C.; Chandar, Rupali; Bowers, Ariel S.; Larsen, Soeren; Lindsay, Kevin; Ansari, Asna; Evans, Jessica

2014-04-01

Luminosity functions (LFs) have been determined for star cluster populations in 20 nearby (4-30 Mpc), star-forming galaxies based on Advanced Camera for Surveys source lists generated by the Hubble Legacy Archive (HLA). These cluster catalogs provide one of the largest sets of uniform, automatically generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster LF can be approximated by a power law, dN/dLvpropL α, with an average value for α of -2.37 and rms scatter = 0.18 when using the F814W ("I") band. A comparison of fitting results based on methods that use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum likelihood) method to give slightly more negative values of α for galaxies with steeper LFs. We find that galaxies with high rates of star formation (or equivalently, with the brightest or largest numbers of clusters) have a slight tendency to have shallower values of α. In particular, the Antennae galaxy (NGC 4038/39), a merging system with a relatively high star formation rate (SFR), has the second flattest LF in the sample. A tentative correlation may also be present between Hubble type and values of α, in the sense that later type galaxies (i.e., Sd and Sm) appear to have flatter LFs. Hence, while there do appear to be some weak correlations, the relative similarity in the values of α for a large number of star-forming galaxies suggests that, to first order, the LFs are fairly universal. We examine the bright end of the LFs and find evidence for a downturn, although it only pertains to about 1% of the clusters. Our uniform database results in a small scatter (≈0.4 to 0.5 mag) in the correlation between the magnitude of the brightest cluster (M brightest) and log of the number of clusters brighter than MI = -9 (log N). We also examine the magnitude of the brightest cluster versus log SFR for a sample including both dwarf galaxies and ULIRGs. This shows that the correlation extends over roughly six orders of magnitude but with scatter that is larger than for our spiral sample, probably because of the high levels of extinction in many of the LIRGs. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Also based on data obtained from the Hubble Legacy Archive, which is a collaboration between the Space Telescope Science Institute (STScI/NASA), the Space Telescope European Coordinating Facility (ST-ECF/ESA), and the Canadian Astronomy Data Centre (CADC/NRC/CSA). Support for Program number 11781 was provided by NASA through a grant from the Space Telescope Science Institute.

Clusters, Groups, and Filaments in the Chandra Deep Field-South up to Redshift 1

NASA Astrophysics Data System (ADS)

Dehghan, S.; Johnston-Hollitt, M.

2014-03-01

We present a comprehensive structure detection analysis of the 0.3 deg2 area of the MUSYC-ACES field, which covers the Chandra Deep Field-South (CDFS). Using a density-based clustering algorithm on the MUSYC and ACES photometric and spectroscopic catalogs, we find 62 overdense regions up to redshifts of 1, including clusters, groups, and filaments. We also present the detection of a relatively small void of ~10 Mpc2 at z ~ 0.53. All structures are confirmed using the DBSCAN method, including the detection of nine structures previously reported in the literature. We present a catalog of all structures present, including their central position, mean redshift, velocity dispersions, and classification based on their morphological and spectroscopic distributions. In particular, we find 13 galaxy clusters and 6 large groups/small clusters. Comparison of these massive structures with published XMM-Newton imaging (where available) shows that 80% of these structures are associated with diffuse, soft-band (0.4-1 keV) X-ray emission, including 90% of all objects classified as clusters. The presence of soft-band X-ray emission in these massive structures (M 200 >= 4.9 × 1013 M ⊙) provides a strong independent confirmation of our methodology and classification scheme. In the closest two clusters identified (z < 0.13) high-quality optical imaging from the Deep2c field of the Garching-Bonn Deep Survey reveals the cD galaxies and demonstrates that they sit at the center of the detected X-ray emission. Nearly 60% of the clusters, groups, and filaments are detected in the known enhanced density regions of the CDFS at z ~= 0.13, 0.52, 0.68, and 0.73. Additionally, all of the clusters, bar the most distant, are found in these overdense redshift regions. Many of the clusters and groups exhibit signs of ongoing formation seen in their velocity distributions, position within the detected cosmic web, and in one case through the presence of tidally disrupted central galaxies exhibiting trails of stars. These results all provide strong support for hierarchical structure formation up to redshifts of 1.

The old open cluster NGC 2112: updated estimates of fundamental parameters based on a membership analysis†

NASA Astrophysics Data System (ADS)

Carraro, G.; Villanova, S.; Demarque, P.; Moni Bidin, C.; McSwain, M. V.

2008-05-01

We report on a new, wide-field (20 × 20 arcmin2), multicolour (UBVI), photometric campaign in the area of the nearby old open cluster NGC 2112. At the same time, we provide medium-resolution spectroscopy of 35 (and high-resolution of additional 5) red giant and turn-off stars. This material is analysed with the aim to update the fundamental parameters of this traditionally difficult cluster, which is very sparse and suffers from heavy field star contamination. Among the 40 stars with spectra, we identified 21 bona fide radial velocity members which allow us to put more solid constraints on the cluster's metal abundance, long suggested to be as low as the metallicity of globulars. As indicated earlier by us on a purely photometric basis, the cluster [Fe/H] abundance is slightly supersolar ([Fe/H] = 0.16 +/- 0.03) and close to the Hyades value, as inferred from a detailed abundance analysis of three of the five stars with higher resolution spectra. Abundance ratios are also marginally supersolar. Based on this result, we revise the properties of NGC 2112 using stellar models from the Padova and Yale-Yonsei groups. For this metal abundance, we find that the cluster's age, reddening and distance values are 1.8 Gyr, 0.60 mag and 940 pc, respectively. Both the Yale-Yonsei and Padova models predict the same values for the fundamental parameters within the errors. Overall, NGC 2112 is a typical solar neighbourhood, thin-disc star cluster, sharing the same chemical properties of F-G stars and open clusters close to the Sun. This investigation outlines the importance of a detailed membership analysis in the study of disc star clusters. This paper includes data gathered with the 6.5 Magellan Telescopes, located at Las Campanas Observatory, Chile. The data discussed in this paper will be made available at the WEBDA open cluster data base http://www.univie.ac.at/webda, which is maintained by E. Paunzen and J.-C. Mermilliod. ‡ E-mail: gcarraro@eso.org (GC); sandro.villanova@unipd.it (SV); demarque@astro.yale.edu (PD); mbidin@das.uchile.cl (CMB); mcswain@lehigh.edu(MVM)

An Observational Study of Blended Young Stellar Clusters in the Galactic Plane - Do Massive Stars form First?

NASA Astrophysics Data System (ADS)

Martínez-Galarza, Rafael; Protopapas, Pavlos; Smith, Howard A.; Morales, Esteban

2018-01-01

From an observational point of view, the early life of massive stars is difficult to understand partly because star formation occurs in crowded clusters where individual stars often appear blended together in the beams of infrared telescopes. This renders the characterization of the physical properties of young embedded clusters via spectral energy distribution (SED) fitting a challenging task. Of particular relevance for the testing of star formation models is the question of whether the claimed universality of the IMF (references) is reflected in an equally universal integrated galactic initial mass function (IGIMF) of stars. In other words, is the set of all stellar masses in the galaxy sampled from a single universal IMF, or does the distribution of masses depend on the environment, making the IGIMF different from the canonical IMF? If the latter is true, how different are the two? We present a infrared SED analysis of ~70 Spitzer-selected, low mass ($<100~\\rm{M}_{\\odot}$), galactic blended clusters. For all of the clusters we obtain the most probable individual SED of each member and derive their physical properties, effectively deblending the confused emission from individual YSOs. Our algorithm incorporates a combined probabilistic model of the blended SEDs and the unresolved images in the long-wavelength end. We find that our results are compatible with competitive accretion in the central regions of young clusters, with the most massive stars forming early on in the process and less massive stars forming about 1Myr later. We also find evidence for a relationship between the total stellar mass of the cluster and the mass of the most massive member that favors optimal sampling in the cluster and disfavors random sampling for the canonical IMF, implying that star formation is self-regulated, and that the mass of the most massive star in a cluster depends on the available resources. The method presented here is easily adapted to future observations of clustered regions of star formation with JWST and other high resolution facilities.

Steganalysis feature improvement using expectation maximization

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M.; Peterson, Gilbert L.; Agaian, Sos S.

2007-04-01

Images and data files provide an excellent opportunity for concealing illegal or clandestine material. Currently, there are over 250 different tools which embed data into an image without causing noticeable changes to the image. From a forensics perspective, when a system is confiscated or an image of a system is generated the investigator needs a tool that can scan and accurately identify files suspected of containing malicious information. The identification process is termed the steganalysis problem which focuses on both blind identification, in which only normal images are available for training, and multi-class identification, in which both the clean and stego images at several embedding rates are available for training. In this paper an investigation of a clustering and classification technique (Expectation Maximization with mixture models) is used to determine if a digital image contains hidden information. The steganalysis problem is for both anomaly detection and multi-class detection. The various clusters represent clean images and stego images with between 1% and 10% embedding percentage. Based on the results it is concluded that the EM classification technique is highly suitable for both blind detection and the multi-class problem.

Horizontal transfer of a large and highly toxic secondary metabolic gene cluster between fungi.

PubMed

Slot, Jason C; Rokas, Antonis

2011-01-25

Genes involved in intermediary and secondary metabolism in fungi are frequently physically linked or clustered. For example, in Aspergillus nidulans the entire pathway for the production of sterigmatocystin (ST), a highly toxic secondary metabolite and a precursor to the aflatoxins (AF), is located in a ∼54 kb, 23 gene cluster. We discovered that a complete ST gene cluster in Podospora anserina was horizontally transferred from Aspergillus. Phylogenetic analysis shows that most Podospora cluster genes are adjacent to or nested within Aspergillus cluster genes, although the two genera belong to different taxonomic classes. Furthermore, the Podospora cluster is highly conserved in content, sequence, and microsynteny with the Aspergillus ST/AF clusters and its intergenic regions contain 14 putative binding sites for AflR, the transcription factor required for activation of the ST/AF biosynthetic genes. Examination of ∼52,000 Podospora expressed sequence tags identified transcripts for 14 genes in the cluster, with several expressed at multiple life cycle stages. The presence of putative AflR-binding sites and the expression evidence for several cluster genes, coupled with the recent independent discovery of ST production in Podospora [1], suggest that this HGT event probably resulted in a functional cluster. Given the abundance of metabolic gene clusters in fungi, our finding that one of the largest known metabolic gene clusters moved intact between species suggests that such transfers might have significantly contributed to fungal metabolic diversity. PAPERFLICK: Copyright © 2011 Elsevier Ltd. All rights reserved.

TMEM88, CCL14 and CLEC3B as prognostic biomarkers for prognosis and palindromia of human hepatocellular carcinoma.

PubMed

Zhang, Xin; Wan, Jin-Xiang; Ke, Zun-Ping; Wang, Feng; Chai, Hai-Xia; Liu, Jia-Qiang

2017-07-01

Hepatocellular carcinoma is one of the most mortal and prevalent cancers with increasing incidence worldwide. Elucidating genetic driver genes for prognosis and palindromia of hepatocellular carcinoma helps managing clinical decisions for patients. In this study, the high-throughput RNA sequencing data on platform IlluminaHiSeq of hepatocellular carcinoma were downloaded from The Cancer Genome Atlas with 330 primary hepatocellular carcinoma patient samples. Stable key genes with differential expressions were identified with which Kaplan-Meier survival analysis was performed using Cox proportional hazards test in R language. Driver genes influencing the prognosis of this disease were determined using clustering analysis. Functional analysis of driver genes was performed by literature search and Gene Set Enrichment Analysis. Finally, the selected driver genes were verified using external dataset GSE40873. A total of 5781 stable key genes were identified, including 156 genes definitely related to prognoses of hepatocellular carcinoma. Based on the significant key genes, samples were grouped into five clusters which were further integrated into high- and low-risk classes based on clinical features. TMEM88, CCL14, and CLEC3B were selected as driver genes which clustered high-/low-risk patients successfully (generally, p = 0.0005124445). Finally, survival analysis of the high-/low-risk samples from external database illustrated significant difference with p value 0.0198. In conclusion, TMEM88, CCL14, and CLEC3B genes were stable and available in predicting the survival and palindromia time of hepatocellular carcinoma. These genes could function as potential prognostic genes contributing to improve patients' outcomes and survival.

Electron scattering in large water clusters from photoelectron imaging with high harmonic radiation.

PubMed

Gartmann, Thomas E; Hartweg, Sebastian; Ban, Loren; Chasovskikh, Egor; Yoder, Bruce L; Signorell, Ruth

2018-06-06

Low-energy electron scattering in water clusters (H2O)n with average cluster sizes of n < 700 is investigated by angle-resolved photoelectron spectroscopy using high harmonic radiation at photon energies of 14.0, 20.3, and 26.5 eV for ionization from the three outermost valence orbitals. The measurements probe the evolution of the photoelectron anisotropy parameter β as a function of cluster size. A remarkably steep decrease of β with increasing cluster size is observed, which for the largest clusters reaches liquid bulk values. Detailed electron scattering calculations reveal that neither gas nor condensed phase scattering can explain the cluster data. Qualitative agreement between experiment and simulations is obtained with scattering calculations that treat cluster scattering as an intermediate case between gas and condensed phase scattering.

Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011.

PubMed

Shields, Timothy; Pinchoff, Jessie; Lubinda, Jailos; Hamapumbu, Harry; Searle, Kelly; Kobayashi, Tamaki; Thuma, Philip E; Moss, William J; Curriero, Frank C

2016-05-31

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

Lithium in Open Cluster Red Giants Hosting Substellar Companions

NASA Technical Reports Server (NTRS)

Carlberg, Joleen K.; Smith, Verne V.; Cunha, Katia; Carpenter, Kenneth G.

2016-01-01

We have measured stellar parameters, [Fe/H], lithium abundances, rotation, and (12)C/13C in a small sample of red giants (RGs) in three open clusters that are each home to a RG star that hosts a substellar companion (SSC) (NGC 2423 3, NGC 4349 127, and BD+12 1917 in M67). Our goal is to explore whether the presence of SSCs influences the Li content. Both (12)C/13C and stellar rotation are measured as additional tracers of stellar mixing. One of the companion hosts, NGC 2423?3, is found to be Li-rich with A(Li)(sub NLTE) = 1.56 dex, and this abundance is significantly higher than the A(Li) of the two comparison stars in NGC 2423. All three SSC hosts have the highest A(Li) and (12)C/13C when compared to the control RGs in their respective clusters; however, except for NGC 2423?3, at least one control star has similarly high abundances within the uncertainties. Higher A(Li) could suggest that the formation or presence of planets plays a role in the degree of internal mixing on or before the RG branch. However, a multitude of factors affect A(Li) during the RG phase, and when the abundances of our sample are compared with the abundances of RGs in other open clusters available in the literature, we find that they all fall well within a much larger distribution of A(Li) and (12)C/13C. Thus, even the high Li in NGC 2423 3 cannot be concretely tied to the presence of the SSC.

Biochemical and Genetic Characterization of the vanC-2 Vancomycin Resistance Gene Cluster of Enterococcus casseliflavus ATCC 25788

PubMed Central

Dutta, Ireena; Reynolds, Peter E.

2002-01-01

The vanC-2 cluster of Enterococcus casseliflavus ATCC 25788 consisted of five genes (vanC-2, vanXYC-2, vanTC-2, vanRC-2, and vanSC-2) and shared the same organization as the vanC cluster of E. gallinarum BM4174. The proteins encoded by these genes displayed a high degree of amino acid identity to the proteins encoded within the vanC gene cluster. The putative d,d-dipeptidase-d,d-carboxypeptidase, VanXYC-2, exhibited 81% amino acid identity to VanXYC, and VanTC-2 displayed 65% amino acid identity to the serine racemase, VanT. VanRC-2 and VanSC-2 displayed high degrees of identity to VanRC and VanSC, respectively, and contained the conserved residues identified as important to their function as a response regulator and histidine kinase, respectively. Resistance to vancomycin was expressed inducibly in E. casseliflavus ATCC 25788 and required an extended period of induction. Analysis of peptidoglycan precursors revealed that UDP-N-acetylmuramyl-l-Ala-δ-d-Glu-l-Lys-d-Ala-d-Ser could not be detected until several hours after the addition of vancomycin, and its appearance coincided with the resumption of growth. The introduction of additional copies of the vanTC-2 gene, encoding a putative serine racemase, and the presence of supplementary d-serine in the growth medium both significantly reduced the period before growth resumed after addition of vancomycin. This suggested that the availability of d-serine plays an important role in the induction process. PMID:12234834

Lithium in Open Cluster Red Giants Hosting Substellar Companions

NASA Astrophysics Data System (ADS)

Carlberg, Joleen K.; Smith, Verne V.; Cunha, Katia; Carpenter, Kenneth G.

2016-02-01

We have measured stellar parameters, [Fe/H], lithium abundances, rotation, and 12C/13C in a small sample of red giants (RGs) in three open clusters that are each home to a RG star that hosts a substellar companion (SSC) (NGC 2423 3, NGC 4349 127, and BD+12 1917 in M67). Our goal is to explore whether the presence of SSCs influences the Li content. Both 12C/13C and stellar rotation are measured as additional tracers of stellar mixing. One of the companion hosts, NGC 2423 3, is found to be Li-rich with A(Li){}{{NLTE}} = 1.56 dex, and this abundance is significantly higher than the A(Li) of the two comparison stars in NGC 2423. All three SSC hosts have the highest A(Li) and 12C/13C when compared to the control RGs in their respective clusters; however, except for NGC 2423 3, at least one control star has similarly high abundances within the uncertainties. Higher A(Li) could suggest that the formation or presence of planets plays a role in the degree of internal mixing on or before the RG branch. However, a multitude of factors affect A(Li) during the RG phase, and when the abundances of our sample are compared with the abundances of RGs in other open clusters available in the literature, we find that they all fall well within a much larger distribution of A(Li) and 12C/13C. Thus, even the high Li in NGC 2423 3 cannot be concretely tied to the presence of the SSC.

Scalable Unix commands for parallel processors : a high-performance implementation.

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

Ong, E.; Lusk, E.; Gropp, W.

2001-06-22

We describe a family of MPI applications we call the Parallel Unix Commands. These commands are natural parallel versions of common Unix user commands such as ls, ps, and find, together with a few similar commands particular to the parallel environment. We describe the design and implementation of these programs and present some performance results on a 256-node Linux cluster. The Parallel Unix Commands are open source and freely available.

Widefield Imaging: Selected Strategies for Processing Light-Contaminated Data

NASA Astrophysics Data System (ADS)

Cannistra, Stephen A.

The beauty of nebulae, galaxies, and star clusters takes on new meaning when portrayed in a widefield view, where familiar objects that are commonly seen in isolation are now shown in relation to one another. Through the use of high quality, short focal length optics combined with large, commercially available CCD chips, it is possible to capture broad regions of sky that an older generation of astrophotographers could only dream of.

StarBooster Demonstrator Cluster Configuration Analysis/Verification Program

NASA Technical Reports Server (NTRS)

DeTurris, Dianne J.

2003-01-01

In order to study the flight dynamics of the cluster configuration of two first stage boosters and upper-stage, flight-testing of subsonic sub-scale models has been undertaken using two glideback boosters launched on a center upper-stage. Three high power rockets clustered together were built and flown to demonstrate vertical launch, separation and horizontal recovery of the boosters. Although the boosters fly to conventional aircraft landing, the centerstage comes down separately under its own parachute. The goal of the project has been to collect data during separation and flight for comparison with a six degree of freedom simulation. The configuration for the delta wing canard boosters comes from a design by Starcraft Boosters, Inc. The subscale rockets were constructed of foam covered in carbon or fiberglass and were launched with commercially available solid rocket motors. The first set of boosters built were 3-ft tall with a 4-ft tall centerstage, and two additional sets of boosters were made that were each over 5-ft tall with a 7.5 ft centerstage. The rocket cluster is launched vertically, then after motor bum out the boosters are separated and flown to a horizontal landing under radio-control. An on-board data acquisition system recorded data during both the launch and glide phases of flight.

OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes

PubMed Central

Li, Li; Stoeckert, Christian J.; Roos, David S.

2003-01-01

The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of “recent” paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. PMID:12952885

High-throughput shadow mask printing of passive electrical components on paper by supersonic cluster beam deposition

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

Caruso, Francesco; Bellacicca, Andrea; Milani, Paolo, E-mail: pmilani@mi.infn.it

We report the rapid prototyping of passive electrical components (resistors and capacitors) on plain paper by an additive and parallel technology consisting of supersonic cluster beam deposition (SCBD) coupled with shadow mask printing. Cluster-assembled films have a growth mechanism substantially different from that of atom-assembled ones providing the possibility of a fine tuning of their electrical conduction properties around the percolative conduction threshold. Exploiting the precise control on cluster beam intensity and shape typical of SCBD, we produced, in a one-step process, batches of resistors with resistance values spanning a range of two orders of magnitude. Parallel plate capacitors withmore » paper as the dielectric medium were also produced with capacitance in the range of tens of picofarads. Compared to standard deposition technologies, SCBD allows for a very efficient use of raw materials and the rapid production of components with different shape and dimensions while controlling independently the electrical characteristics. Discrete electrical components produced by SCBD are very robust against deformation and bending, and they can be easily assembled to build circuits with desired characteristics. The availability of large batches of these components enables the rapid and cheap prototyping and integration of electrical components on paper as building blocks of more complex systems.« less

Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition

PubMed Central

Saeed, Isaam; Tang, Sen-Lin; Halgamuge, Saman K.

2012-01-01

An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis. PMID:22180538

The GALAH survey: chemical tagging of star clusters and new members in the Pleiades

NASA Astrophysics Data System (ADS)

Kos, Janez; Bland-Hawthorn, Joss; Freeman, Ken; Buder, Sven; Traven, Gregor; De Silva, Gayandhi M.; Sharma, Sanjib; Asplund, Martin; Duong, Ly; Lin, Jane; Lind, Karin; Martell, Sarah; Simpson, Jeffrey D.; Stello, Dennis; Zucker, Daniel B.; Zwitter, Tomaž; Anguiano, Borja; Da Costa, Gary; D'Orazi, Valentina; Horner, Jonathan; Kafle, Prajwal R.; Lewis, Geraint; Munari, Ulisse; Nataf, David M.; Ness, Melissa; Reid, Warren; Schlesinger, Katie; Ting, Yuan-Sen; Wyse, Rosemary

2018-02-01

The technique of chemical tagging uses the elemental abundances of stellar atmospheres to 'reconstruct' chemically homogeneous star clusters that have long since dispersed. The GALAH spectroscopic survey - which aims to observe one million stars using the Anglo-Australian Telescope - allows us to measure up to 30 elements or dimensions in the stellar chemical abundance space, many of which are not independent. How to find clustering reliably in a noisy high-dimensional space is a difficult problem that remains largely unsolved. Here, we explore t-distributed stochastic neighbour embedding (t-SNE) - which identifies an optimal mapping of a high-dimensional space into fewer dimensions - whilst conserving the original clustering information. Typically, the projection is made to a 2D space to aid recognition of clusters by eye. We show that this method is a reliable tool for chemical tagging because it can: (i) resolve clustering in chemical space alone, (ii) recover known open and globular clusters with high efficiency and low contamination, and (iii) relate field stars to known clusters. t-SNE also provides a useful visualization of a high-dimensional space. We demonstrate the method on a data set of 13 abundances measured in the spectra of 187 000 stars by the GALAH survey. We recover seven of the nine observed clusters (six globular and three open clusters) in chemical space with minimal contamination from field stars and low numbers of outliers. With chemical tagging, we also identify two Pleiades supercluster members (which we confirm kinematically), one as far as 6° - one tidal radius away from the cluster centre.

Hot spot analysis applied to identify ecosystem services potential in Lithuania

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Depellegrin, Daniel; Misiune, Ieva

2016-04-01

Hot spot analysis are very useful to identify areas with similar characteristics. This is important for a sustainable use of the territory, since we can identify areas that need to be protected, or restored. This is a great advantage in terms of land use planning and management, since we can allocate resources, reduce the economical costs and do a better intervention in the landscape. Ecosystem services (ES) are different according land use. Since landscape is very heterogeneous, it is of major importance understand their spatial pattern and where are located the areas that provide better ES and the others that provide less services. The objective of this work is to use hot-spot analysis to identify areas with the most valuable ES in Lithuania. CORINE land-cover (CLC) of 2006 was used as the main spatial information. This classification uses a grid of 100 m resolution and extracted a total of 31 land use types. ES ranking was carried out based on expert knowledge. They were asked to evaluate the ES potential of each different CLC from 0 (no potential) to 5 (very high potential). Hot spot analysis were evaluated using the Getis-ord test, which identifies cluster analysis available in ArcGIS toolbox. This tool identifies areas with significantly high low values and significant high values at a p level of 0.05. In this work we used hot spot analysis to assess the distribution of providing, regulating cultural and total (sum of the previous 3) ES. The Z value calculated from Getis-ord was used to statistical analysis to access the clusters of providing, regulating cultural and total ES. ES with high Z value show that they have a high number of cluster areas with high potential of ES. The results showed that the Z-score was significantly different among services (Kruskal Wallis ANOVA =834. 607, p<0.001). The Z score of providing services (0.096±2.239) were significantly higher than the total (0.093±2.045), cultural (0.080±1.979) and regulating (0.076±1.961). These results suggested that providing services are more clustered than the remaining. Ecosystem Services Z score were significantly correlated, regulating vs total (0.98, p<0.0001), regulating vs cultural (0.97, p<0.0001), cultural vs total (0.96, p<0.0001), providing vs total (0.69, p<0.0001), regulating vs providing (0.56, p<0.0001) and providing vs cultural (0.56, p<0.0001). According to these results, ES distribution potential showed a similar pattern, especially regulating, cultural and total. This an evidence that the the areas that showed high and low significant regulating and cultural ES clusters are similar. The spatial distribution of these clusters is very high, which may be attributed to the landscape diversity and fragmentation.

A simulation of the intracluster medium with feedback from cluster galaxies

NASA Technical Reports Server (NTRS)

Metzler, Christopher A.; Evrard, August E.

1994-01-01

We detail method and report first results from a three-dimensional hydrodynamical and N-body simulation of the formation and evolution of a Coma-sized cluster of galaxies, with the intent of studying the history of the hot, X-ray emitting intracluster medium. Cluster gas, galaxies, and dark matter are included in the model. The galaxies and dark matter fell gravitational forces; the cluster gas also undergoes hydrodynamical effects such as shock heating and PdV work. For the first time in three dimensions, we include modeling of ejection of processed gas from the simulated galaxies by winds, including heating and heavy element enrichment. For comparison, we employ a `pure infall' simulation using the same initial conditions but with no galaxies or winds. We employ an extreme ejection history for galactic feedback in order to define the boundary of likely models. As expected, feedback raises the entropy of the intracluster gas, preventing it from collapsing to densities as high as those attained in the infall model. The effect is more pronounced in subclusters formed at high redshift. The cluster with feedback is always less X-ray luminous, but experiences more rapid luminosity evolution, than the pure infall cluster. Even employing an extreme ejection model, the final gas temperature is only approximately 15% larger than in the infall model. The radial temperature profile is very nearly isothermal within 1.5 Mpc. The cluster galaxies in the feedback model have a velocity dispersion approximately 15% lower than the dark matter. This results in the true ratio of specific energies in galaxies to gas being less than one, beta(sub spec) approximately 0.7. The infall model predicts beta(sub spec) approximately 1.2. Large excursions in these values occur over time, following the complex dynamical history of the cluster. The morphology of the X-ray emission is little affected by feedback. The emission profiles of both clusters are well described by the standard beta-model with beta(sub fit) approximately equal to 0.7 - 0.9. X-ray mass estimates based on the assumptions of hydrostatic equilibrium and the applicability of the beta-model are quite accurate in both cases. A strong, radial iron abundance gradient is present, which develops as a consequence of the steepening of the galaxy density profile over time. Spectroscopic observations using nonimaging detectors with wide (approximately 45 min) fields of view dramatically smear the gradient. Observations with arcminute resolution, made available with the ASCA satellite, would readily resolve the gradient.

A Multidisciplinary Investigation of a Polycythemia Vera Cancer Cluster of Unknown Origin

PubMed Central

Seaman, Vincent; Dearwent, Steve M; Gable, Debra; Lewis, Brian; Metcalf, Susan; Orloff, Ken; Tierney, Bruce; Zhu, Jane; Logue, James; Marchetto, David; Ostroff, Stephen; Hoffman, Ronald; Xu, Mingjiang; Carey, David; Erlich, Porat; Gerhard, Glenn; Roda, Paul; Iannuzzo, Joseph; Lewis, Robert; Mellow, John; Mulvihill, Linda; Myles, Zachary; Wu, Manxia; Frank, Arthur; Gross-Davis, Carol Ann; Klotz, Judith; Lynch, Adam; Weissfeld, Joel; Weinberg, Rona; Cole, Henry

2010-01-01

Cancer cluster investigations rarely receive significant public health resource allocations due to numerous inherent challenges and the limited success of past efforts. In 2008, a cluster of polycythemia vera, a rare blood cancer with unknown etiology, was identified in northeast Pennsylvania. A multidisciplinary group of federal and state agencies, academic institutions, and local healthcare providers subsequently developed a multifaceted research portfolio designed to better understand the cause of the cluster. This research agenda represents a unique and important opportunity to demonstrate that cancer cluster investigations can produce desirable public health and scientific outcomes when necessary resources are available. PMID:20617023

A conserved gene cluster as a putative functional unit in insect innate immunity.

PubMed

Somogyi, Kálmán; Sipos, Botond; Pénzes, Zsolt; Andó, István

2010-11-05

The Nimrod gene superfamily is an important component of the innate immune response. The majority of its member genes are located in close proximity within the Drosophila melanogaster genome and they lie in a larger conserved cluster ("Nimrod cluster"), made up of non-related groups (families, superfamilies) of genes. This cluster has been a part of the Arthropod genomes for about 300-350 million years. The available data suggest that the Nimrod cluster is a functional module of the insect innate immune response. Copyright © 2010 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Digital Genome-Wide ncRNA Expression, Including SnoRNAs, across 11 Human Tissues Using PolyA-Neutral Amplification

PubMed Central

Castle, John C.; Armour, Christopher D.; Löwer, Martin; Haynor, David; Biery, Matthew; Bouzek, Heather; Chen, Ronghua; Jackson, Stuart; Johnson, Jason M.; Rohl, Carol A.; Raymond, Christopher K.

2010-01-01

Non-coding RNAs (ncRNAs) are an essential class of molecular species that have been difficult to monitor on high throughput platforms due to frequent lack of polyadenylation. Using a polyadenylation-neutral amplification protocol and next-generation sequencing, we explore ncRNA expression in eleven human tissues. ncRNAs 7SL, U2, 7SK, and HBII-52 are expressed at levels far exceeding mRNAs. C/D and H/ACA box snoRNAs are associated with rRNA methylation and pseudouridylation, respectively: spleen expresses both, hypothalamus expresses mainly C/D box snoRNAs, and testes show enriched expression of both H/ACA box snoRNAs and RNA telomerase TERC. Within the snoRNA 14q cluster, 14q(I-6) is expressed at much higher levels than other cluster members. More reads align to mitochondrial than nuclear tRNAs. Many lincRNAs are actively transcribed, particularly those overlapping known ncRNAs. Within the Prader-Willi syndrome loci, the snoRNA HBII-85 (group I) cluster is highly expressed in hypothalamus, greater than in other tissues and greater than group II or III. Additionally, within the disease locus we find novel transcription across a 400,000 nt span in ovaries. This genome-wide polyA-neutral expression compendium demonstrates the richness of ncRNA expression, their high expression patterns, their function-specific expression patterns, and is publicly available. PMID:20668672

HPC enabled real-time remote processing of laparoscopic surgery

NASA Astrophysics Data System (ADS)

Ronaghi, Zahra; Sapra, Karan; Izard, Ryan; Duffy, Edward; Smith, Melissa C.; Wang, Kuang-Ching; Kwartowitz, David M.

2016-03-01

Laparoscopic surgery is a minimally invasive surgical technique. The benefit of small incisions has a disadvantage of limited visualization of subsurface tissues. Image-guided surgery (IGS) uses pre-operative and intra-operative images to map subsurface structures. One particular laparoscopic system is the daVinci-si robotic surgical system. The video streams generate approximately 360 megabytes of data per second. Real-time processing this large stream of data on a bedside PC, single or dual node setup, has become challenging and a high-performance computing (HPC) environment may not always be available at the point of care. To process this data on remote HPC clusters at the typical 30 frames per second rate, it is required that each 11.9 MB video frame be processed by a server and returned within 1/30th of a second. We have implement and compared performance of compression, segmentation and registration algorithms on Clemson's Palmetto supercomputer using dual NVIDIA K40 GPUs per node. Our computing framework will also enable reliability using replication of computation. We will securely transfer the files to remote HPC clusters utilizing an OpenFlow-based network service, Steroid OpenFlow Service (SOS) that can increase performance of large data transfers over long-distance and high bandwidth networks. As a result, utilizing high-speed OpenFlow- based network to access computing clusters with GPUs will improve surgical procedures by providing real-time medical image processing and laparoscopic data.

Linear-array-based photoacoustic tomography for label-free high-throughput detection and quantification of circulating melanoma tumor cell clusters

NASA Astrophysics Data System (ADS)

Hai, Pengfei; Zhou, Yong; Zhang, Ruiying; Ma, Jun; Li, Yang; Wang, Lihong V.

2017-03-01

Circulating tumor cell (CTC) clusters arise from multicellular grouping in the primary tumor and elevate the metastatic potential by 23 to 50 fold compared to single CTCs. High throughout detection and quantification of CTC clusters is critical for understanding the tumor metastasis process and improving cancer therapy. In this work, we report a linear-array-based photoacoustic tomography (LA-PAT) system capable of label-free high-throughput CTC cluster detection and quantification in vivo. LA-PAT detects CTC clusters and quantifies the number of cells in them based on the contrast-to-noise ratios (CNRs) of photoacoustic signals. The feasibility of LA-PAT was first demonstrated by imaging CTC clusters ex vivo. LA-PAT detected CTC clusters in the blood-filled microtubes and computed the number of cells in the clusters. The size distribution of the CTC clusters measured by LA-PAT agreed well with that obtained by optical microscopy. We demonstrated the ability of LA-PAT to detect and quantify CTC clusters in vivo by imaging injected CTC clusters in rat tail veins. LA-PAT detected CTC clusters immediately after injection as well as when they were circulating in the rat bloodstreams. Similarly, the numbers of cells in the clusters were computed based on the CNRs of the photoacoustic signals. The data showed that larger CTC clusters disappear faster than the smaller ones. The results prove the potential of LA-PAT as a promising tool for both preclinical tumor metastasis studies and clinical cancer therapy evaluation.

Spatial patterns in electoral wards with high lymphoma incidence in Yorkshire health region.

PubMed Central

Barnes, N.; Cartwright, R. A.; O'Brien, C.; Roberts, B.; Richards, I. D.; Bird, C. C.

1987-01-01

The possibilities of clustering between those electoral wards which display higher than expected incidences of cases of the lymphomas occurring between 1978 and 1982 are examined. Clusters are defined as being those wards with cases in excess (at a probability of less than 10%) which are geographically adjacent to each other. A separate analysis extends the definition of cluster to include high incidence wards that are adjacent or separated by one other ward. The results indicate that many high incidence lymphoma wards do occur close together and when computer simulations are used to compute expected results, many of the observed results are shown to be highly improbable both in the overall number of clustering wards and in the largest number of wards comprising a 'cluster'. PMID:3663469

PuReD-MCL: a graph-based PubMed document clustering methodology.

PubMed

Theodosiou, T; Darzentas, N; Angelis, L; Ouzounis, C A

2008-09-01

Biomedical literature is the principal repository of biomedical knowledge, with PubMed being the most complete database collecting, organizing and analyzing such textual knowledge. There are numerous efforts that attempt to exploit this information by using text mining and machine learning techniques. We developed a novel approach, called PuReD-MCL (Pubmed Related Documents-MCL), which is based on the graph clustering algorithm MCL and relevant resources from PubMed. PuReD-MCL avoids using natural language processing (NLP) techniques directly; instead, it takes advantage of existing resources, available from PubMed. PuReD-MCL then clusters documents efficiently using the MCL graph clustering algorithm, which is based on graph flow simulation. This process allows users to analyse the results by highlighting important clues, and finally to visualize the clusters and all relevant information using an interactive graph layout algorithm, for instance BioLayout Express 3D. The methodology was applied to two different datasets, previously used for the validation of the document clustering tool TextQuest. The first dataset involves the organisms Escherichia coli and yeast, whereas the second is related to Drosophila development. PuReD-MCL successfully reproduces the annotated results obtained from TextQuest, while at the same time provides additional insights into the clusters and the corresponding documents. Source code in perl and R are available from http://tartara.csd.auth.gr/~theodos/

Posttranslational stability of the heme biosynthetic enzyme ferrochelatase is dependent on iron availability and intact iron-sulfur cluster assembly machinery

PubMed Central

Crooks, Daniel R.; Ghosh, Manik C.; Haller, Ronald G.; Tong, Wing-Hang

2010-01-01

Mammalian ferrochelatase, the terminal enzyme in the heme biosynthetic pathway, possesses an iron-sulfur [2Fe-2S] cluster that does not participate in catalysis. We investigated ferrochelatase expression in iron-deficient erythropoietic tissues of mice lacking iron regulatory protein 2, in iron-deficient murine erythroleukemia cells, and in human patients with ISCU myopathy. Ferrochelatase activity and protein levels were dramatically decreased in Irp2−/− spleens, whereas ferrochelatase mRNA levels were increased, demonstrating posttranscriptional regulation of ferrochelatase in vivo. Translation of ferrochelatase mRNA was unchanged in iron-depleted murine erythroleukemia cells, and the stability of mature ferrochelatase protein was also unaffected. However, the stability of newly formed ferrochelatase protein was dramatically decreased during iron deficiency. Ferrochelatase was also severely depleted in muscle biopsies and cultured myoblasts from patients with ISCU myopathy, a disease caused by deficiency of a scaffold protein required for Fe-S cluster assembly. Together, these data suggest that decreased Fe-S cluster availability because of cellular iron depletion or impaired Fe-S cluster assembly causes reduced maturation and stabilization of apo-ferrochelatase, providing a direct link between Fe-S biogenesis and completion of heme biosynthesis. We propose that decreased heme biosynthesis resulting from impaired Fe-S cluster assembly can contribute to the pathogenesis of diseases caused by defective Fe-S cluster biogenesis. PMID:19965627

Precise strong lensing mass profile of the CLASH galaxy cluster MACS 2129

NASA Astrophysics Data System (ADS)

Monna, A.; Seitz, S.; Balestra, I.; Rosati, P.; Grillo, C.; Halkola, A.; Suyu, S. H.; Coe, D.; Caminha, G. B.; Frye, B.; Koekemoer, A.; Mercurio, A.; Nonino, M.; Postman, M.; Zitrin, A.

2017-04-01

We present a detailed strong lensing (SL) mass reconstruction of the core of the galaxy cluster MACS J2129.4-0741 (zcl = 0.589) obtained by combining high-resolution Hubble Space Telescope photometry from the CLASH (Cluster Lensing And Supernovae survey with Hubble) survey with new spectroscopic observations from the CLASH-VLT (Very Large Telescope) survey. A background bright red passive galaxy at zsp = 1.36, sextuply lensed in the cluster core, has four radial lensed images located over the three central cluster members. Further 19 background lensed galaxies are spectroscopically confirmed by our VLT survey, including 3 additional multiple systems. A total of 31 multiple images are used in the lensing analysis. This allows us to trace with high precision the total mass profile of the cluster in its very inner region (R < 100 kpc). Our final lensing mass model reproduces the multiple images systems identified in the cluster core with high accuracy of 0.4 arcsec. This translates to a high-precision mass reconstruction of MACS 2129, which is constrained at a level of 2 per cent. The cluster has Einstein parameter ΘE = (29 ± 4) arcsec and a projected total mass of Mtot(<ΘE) = (1.35 ± 0.03) × 1014 M⊙ within such radius. Together with the cluster mass profile, we provide here also the complete spectroscopic data set for the cluster members and lensed images measured with VLT/Visible Multi-Object Spectrograph within the CLASH-VLT survey.

Clustered DNA damages induced by high and low LET radiation, including heavy ions

NASA Technical Reports Server (NTRS)

Sutherland, B. M.; Bennett, P. V.; Schenk, H.; Sidorkina, O.; Laval, J.; Trunk, J.; Monteleone, D.; Sutherland, J.; Lowenstein, D. I. (Principal Investigator)

2001-01-01

Clustered DNA damages--here defined as two or more lesions (strand breaks, oxidized purines, oxidized pyrimidines or abasic sites) within a few helical turns--have been postulated as difficult to repair accurately, and thus highly significant biological lesions. Further, attempted repair of clusters may produce double strand breaks (DSBs). However, until recently, there was no way to measure ionizing radiation-induced clustered damages, except DSB. We recently described an approach for measuring classes of clustered damages (oxidized purine clusters, oxidized pyrimidine clusters, abasic clusters, along with DSB). We showed that ionizing radiation (gamma rays and Fe ions, 1 GeV/amu) does induce such clusters in genomic DNA in solution and in human cells. These studies also showed that each damage cluster results from one radiation hit (and its track), thus indicating that they can be induced by very low doses of radiation, i.e. two independent hits are not required for cluster induction. Further, among all complex damages, double strand breaks comprise--at most-- 20%, with the other clustered damages being at least 80%.

Elastic K-means using posterior probability

PubMed Central

Zheng, Aihua; Jiang, Bo; Li, Yan; Zhang, Xuehan; Ding, Chris

2017-01-01

The widely used K-means clustering is a hard clustering algorithm. Here we propose a Elastic K-means clustering model (EKM) using posterior probability with soft capability where each data point can belong to multiple clusters fractionally and show the benefit of proposed Elastic K-means. Furthermore, in many applications, besides vector attributes information, pairwise relations (graph information) are also available. Thus we integrate EKM with Normalized Cut graph clustering into a single clustering formulation. Finally, we provide several useful matrix inequalities which are useful for matrix formulations of learning models. Based on these results, we prove the correctness and the convergence of EKM algorithms. Experimental results on six benchmark datasets demonstrate the effectiveness of proposed EKM and its integrated model. PMID:29240756

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

DOE PAGES

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.; ...

2017-11-23

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. Here, we find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 10 5–6 M ⊙ collectively to high density, at which point it rapidly turns into stars beforemore » stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ~420 Myr till the end of the simulation. Finally, because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.« less

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

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

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. Here, we find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 10 5–6 M ⊙ collectively to high density, at which point it rapidly turns into stars beforemore » stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ~420 Myr till the end of the simulation. Finally, because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.« less

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

NASA Astrophysics Data System (ADS)

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.; Hopkins, Philip F.; Hayward, Christopher C.; Wetzel, Andrew; Faucher-Giguère, Claude-André; Kereš, Dušan; Garrison-Kimmel, Shea; Murray, Norman

2018-03-01

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. We find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 105-6 M⊙ collectively to high density, at which point it rapidly turns into stars before stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ˜420 Myr till the end of the simulation. Because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.

Clustered DNA damages induced in human hematopoietic cells by low doses of ionizing radiation

NASA Technical Reports Server (NTRS)

Sutherland, Betsy M.; Bennett, Paula V.; Cintron-Torres, Nela; Hada, Megumi; Trunk, John; Monteleone, Denise; Sutherland, John C.; Laval, Jacques; Stanislaus, Marisha; Gewirtz, Alan

2002-01-01

Ionizing radiation induces clusters of DNA damages--oxidized bases, abasic sites and strand breaks--on opposing strands within a few helical turns. Such damages have been postulated to be difficult to repair, as are double strand breaks (one type of cluster). We have shown that low doses of low and high linear energy transfer (LET) radiation induce such damage clusters in human cells. In human cells, DSB are about 30% of the total of complex damages, and the levels of DSBs and oxidized pyrimidine clusters are similar. The dose responses for cluster induction in cells can be described by a linear relationship, implying that even low doses of ionizing radiation can produce clustered damages. Studies are in progress to determine whether clusters can be produced by mechanisms other than ionizing radiation, as well as the levels of various cluster types formed by low and high LET radiation.

Computational Design of Clusters for Catalysis

NASA Astrophysics Data System (ADS)

Jimenez-Izal, Elisa; Alexandrova, Anastassia N.

2018-04-01

When small clusters are studied in chemical physics or physical chemistry, one perhaps thinks of the fundamental aspects of cluster electronic structure, or precision spectroscopy in ultracold molecular beams. However, small clusters are also of interest in catalysis, where the cold ground state or an isolated cluster may not even be the right starting point. Instead, the big question is: What happens to cluster-based catalysts under real conditions of catalysis, such as high temperature and coverage with reagents? Myriads of metastable cluster states become accessible, the entire system is dynamic, and catalysis may be driven by rare sites present only under those conditions. Activity, selectivity, and stability are highly dependent on size, composition, shape, support, and environment. To probe and master cluster catalysis, sophisticated tools are being developed for precision synthesis, operando measurements, and multiscale modeling. This review intends to tell the messy story of clusters in catalysis.

Effects of single atom doping on the ultrafast electron dynamics of M1Au24(SR)18 (M = Pd, Pt) nanoclusters

NASA Astrophysics Data System (ADS)

Zhou, Meng; Qian, Huifeng; Sfeir, Matthew Y.; Nobusada, Katsuyuki; Jin, Rongchao

2016-03-01

Atomically precise, doped metal clusters are receiving wide research interest due to their synergistic properties dependent on the metal composition. To understand the electronic properties of doped clusters, it is highly desirable to probe the excited state behavior. Here, we report the ultrafast relaxation dynamics of doped M1@Au24(SR)18 (M = Pd, Pt; R = CH2CH2Ph) clusters using femtosecond visible and near infrared transient absorption spectroscopy. Three relaxation components are identified for both mono-doped clusters: (1) sub-picosecond relaxation within the M1Au12 core states; (2) core to shell relaxation in a few picoseconds; and (3) relaxation back to the ground state in more than one nanosecond. Despite similar relaxation pathways for the two doped nanoclusters, the coupling between the metal core and surface ligands is accelerated by over 30% in the case of the Pt dopant compared with the Pd dopant. Compared to Pd doping, the case of Pt doping leads to much more drastic changes in the steady state and transient absorption of the clusters, which indicates that the 5d orbitals of the Pt atom are more strongly mixed with Au 5d and 6s orbitals than the 4d orbitals of the Pd dopant. These results demonstrate that a single foreign atom can lead to entirely different excited state spectral features of the whole cluster compared to the parent Au25(SR)18 cluster. The detailed excited state dynamics of atomically precise Pd/Pt doped gold clusters help further understand their properties and benefit the development of energy-related applications.Atomically precise, doped metal clusters are receiving wide research interest due to their synergistic properties dependent on the metal composition. To understand the electronic properties of doped clusters, it is highly desirable to probe the excited state behavior. Here, we report the ultrafast relaxation dynamics of doped M1@Au24(SR)18 (M = Pd, Pt; R = CH2CH2Ph) clusters using femtosecond visible and near infrared transient absorption spectroscopy. Three relaxation components are identified for both mono-doped clusters: (1) sub-picosecond relaxation within the M1Au12 core states; (2) core to shell relaxation in a few picoseconds; and (3) relaxation back to the ground state in more than one nanosecond. Despite similar relaxation pathways for the two doped nanoclusters, the coupling between the metal core and surface ligands is accelerated by over 30% in the case of the Pt dopant compared with the Pd dopant. Compared to Pd doping, the case of Pt doping leads to much more drastic changes in the steady state and transient absorption of the clusters, which indicates that the 5d orbitals of the Pt atom are more strongly mixed with Au 5d and 6s orbitals than the 4d orbitals of the Pd dopant. These results demonstrate that a single foreign atom can lead to entirely different excited state spectral features of the whole cluster compared to the parent Au25(SR)18 cluster. The detailed excited state dynamics of atomically precise Pd/Pt doped gold clusters help further understand their properties and benefit the development of energy-related applications. Electronic supplementary information (ESI) available: The pump dependent transient absorption spectra and the corresponding global analysis results. See DOI: 10.1039/c6nr01008c

Cluster analysis of fasciolosis in dairy cow herds in Munster province of Ireland and detection of major climatic and environmental predictors of the exposure risk.

PubMed

Selemetas, Nikolaos; Phelan, Paul; O'Kiely, Padraig; de Waal, Theo

2015-03-19

Fasciolosis caused by Fasciola hepatica is a widespread parasitic disease in cattle farms. The aim of this study was to detect clusters of fasciolosis in dairy cow herds in Munster Province, Ireland and to identify significant climatic and environmental predictors of the exposure risk. In total, 1,292 dairy herds across Munster was sampled in September 2012 providing a single bulk tank milk (BTM) sample. The analysis of samples by an in-house antibody-detection enzyme-linked immunosorbent assay (ELISA), showed that 65% of the dairy herds (n = 842) had been exposed to F. hepatica. Using the Getis-Ord Gi* statistic, 16 high-risk and 24 low-risk (P <0.01) clusters of fasciolosis were identified. The spatial distribution of high-risk clusters was more dispersed and mainly located in the northern and western regions of Munster compared to the low-risk clusters that were mostly concentrated in the southern and eastern regions. The most significant classes of variables that could reflect the difference between high-risk and low-risk clusters were the total number of wet-days and rain-days, rainfall, the normalized difference vegetation index (NDVI), temperature and soil type. There was a bigger proportion of well-drained soils among the low-risk clusters, whereas poorly drained soils were more common among the high-risk clusters. These results stress the role of precipitation, grazing, temperature and drainage on the life cycle of F. hepatica in the temperate Irish climate. The findings of this study highlight the importance of cluster analysis for identifying significant differences in climatic and environmental variables between high-risk and low-risk clusters of fasciolosis in Irish dairy herds.

VizieR Online Data Catalog: Catalogue of variable stars in open clusters (Zejda+, 2012)

NASA Astrophysics Data System (ADS)

Zejda, M.; Paunzen, E.; Baumann, B.; Mikulasek, Z.; Liska, J.

2012-08-01

The catalogue of variable stars in open clusters were prepared by cross-matching of Variable Stars Index (http://www.aavso.org/vsx) version Apr 29, 2012 (available online, Cat. B/vsx) against the version 3.1. catalogue of open clusters DAML02 (Dias et al. 2002A&A...389..871D, Cat. B/ocl) available on the website http://www.astro.iag.usp.br/~wilton. The open clusters were divided into two categories according to their size, where the limiting diameter was 60 arcmin. The list of all suspected variables and variable stars located within the fields of open clusters up to two times of given cluster radius were generated (Table 1). 8938 and 9127 variable stars are given in 461 "smaller" and 74 "larger" clusters, respectively. All found variable stars were matched against the PPMXL catalog of positions and proper motions within the ICRS (Roeser et al., 2010AJ....139.2440R, Cat. I/317). Proper motion data were included in our catalogue. Unfortunately, a homogeneous data set of mean cluster proper motions has not been available until now. Therefore we used the following sources (sorted alphabetically) to compile a new catalogue: Baumgardt et al. (2000, Cat. J/A+AS/146/251): based on the Hipparcos catalogue Beshenov & Loktin (2004A&AT...23..103B): based on the Tycho-2 catalogue Dias et al. (2001, Cat. J/A+A/376/441, 2002A&A...389..871D, Cat. B/ocl): based on the Tycho-2 catalogue Dias et al. (2006, Cat. J/A+A/446/949): based on the UCAC2 catalog (Zacharias et al., 2004AJ....127.3043Z, Cat. I/289) Frinchaboy & Majewski (2008, Cat. J/AJ/136/118): based on the Tycho-2 catalogue Kharchenko et al. (2005, J/A+A/438/1163): based on the ASCC2.5 catalogue (Kharchenko, 2001KFNT...17..409K, Cat. I/280) Krone-Martins et al. (2010, Cat. J/A+A/516/A3): based on the Bordeaux PM2000 proper motion catalogue (Ducourant et al., 2006A&A...448.1235D, Cat. I/300) Robichon et al. (1999, Cat. J/A+A/345/471): based on the Hipparcos catalogue van Leeuwen (2009A&A...497..209V): based on the new Hipparcos catalogue. In total, a catalogue of proper motions for 879 open clusters (Table 2), from which 436 have more than one available measurement, was compiled. (3 data files).

Polyoxovanadate-alkoxide clusters as multi-electron charge carriers for symmetric non-aqueous redox flow batteries† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc05295b

PubMed Central

VanGelder, L. E.; Kosswattaarachchi, A. M.; Forrestel, P. L.

2018-01-01

Non-aqueous redox flow batteries have emerged as promising systems for large-capacity, reversible energy storage, capable of meeting the variable demands of the electrical grid. Here, we investigate the potential for a series of Lindqvist polyoxovanadate-alkoxide (POV-alkoxide) clusters, [V6O7(OR)12] (R = CH3, C2H5), to serve as the electroactive species for a symmetric, non-aqueous redox flow battery. We demonstrate that the physical and electrochemical properties of these POV-alkoxides make them suitable for applications in redox flow batteries, as well as the ability for ligand modification at the bridging alkoxide moieties to yield significant improvements in cluster stability during charge–discharge cycling. Indeed, the metal–oxide core remains intact upon deep charge–discharge cycling, enabling extremely high coulombic efficiencies (∼97%) with minimal overpotential losses (∼0.3 V). Furthermore, the bulky POV-alkoxide demonstrates significant resistance to deleterious crossover, which will lead to improved lifetime and efficiency in a redox flow battery. PMID:29675217

The HST Frontier Fields

NASA Astrophysics Data System (ADS)

Lotz, Jennifer; Mountain, M.; Grogin, N. A.; Koekemoer, A. M.; Capak, P. L.; Mack, J.; Coe, D. A.; Barker, E. A.; Adler, D. S.; Avila, R. J.; Anderson, J.; Casertano, S.; Christian, C. A.; Gonzaga, S.; Ferguson, H. C.; Fruchter, A. S.; Jenkner, H.; Jordan, I. J.; Hammer, D.; Hilbert, B.; Lawton, B. L.; Lee, J. C.; Lucas, R. A.; MacKenty, J. W.; Mutchler, M. J.; Ogaz, S.; Reid, I. N.; Royle, P.; Robberto, M.; Sembach, K.; Smith, L. J.; Sokol, J.; Surace, J. A.; Taylor, D.; Tumlinson, J.; Viana, A.; Williams, R. E.; Workman, W.

2014-01-01

Using Director's Discretionary observing time, HST is undertaking a revolutionary deep field observing program to peer deeper into the Universe than ever before. The Frontier Fields will combine the power of HST with the natural gravitational telescopes of high-magnification clusters of galaxies to produce the deepest observations of clusters and their lensed galaxies and the second-deepest observations of blank fields ever obtained. Up to six strong-lensing clusters (Abell 2744, MACSJ0416.1-2403, MACSJ0717.5+3745, MACSJ1149.5+2223, AbellS1063, and Abell 370) will be targeted with coordinated parallels of adjacent blank fields with ACS/WFC and WFC3/IR cameras to ~29th ABmag depths in seven bandpasses over the next three years. These observations will reveal distant galaxy populations ~10-100 times fainter than any previously observed, and improve our statistical understanding of galaxies during the epoch of reionization. Here we present Hubble Space Telescope observations of the first set of the Frontier Fields, Abell 2744, and describe the HST Frontier Fields observing strategy and schedule. All data for this observing program is nonproprietary and available immediately upon entry into the Mikulski Archive for Space Telescopes.

Pattern Activity Clustering and Evaluation (PACE)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Banas, Christopher; Paul, Michael; Bussjager, Becky; Seetharaman, Guna

2012-06-01

With the vast amount of network information available on activities of people (i.e. motions, transportation routes, and site visits) there is a need to explore the salient properties of data that detect and discriminate the behavior of individuals. Recent machine learning approaches include methods of data mining, statistical analysis, clustering, and estimation that support activity-based intelligence. We seek to explore contemporary methods in activity analysis using machine learning techniques that discover and characterize behaviors that enable grouping, anomaly detection, and adversarial intent prediction. To evaluate these methods, we describe the mathematics and potential information theory metrics to characterize behavior. A scenario is presented to demonstrate the concept and metrics that could be useful for layered sensing behavior pattern learning and analysis. We leverage work on group tracking, learning and clustering approaches; as well as utilize information theoretical metrics for classification, behavioral and event pattern recognition, and activity and entity analysis. The performance evaluation of activity analysis supports high-level information fusion of user alerts, data queries and sensor management for data extraction, relations discovery, and situation analysis of existing data.

Tissue Gene Expression Analysis Using Arrayed Normalized cDNA Libraries

PubMed Central

Eickhoff, Holger; Schuchhardt, Johannes; Ivanov, Igor; Meier-Ewert, Sebastian; O'Brien, John; Malik, Arif; Tandon, Neeraj; Wolski, Eryk-Witold; Rohlfs, Elke; Nyarsik, Lajos; Reinhardt, Richard; Nietfeld, Wilfried; Lehrach, Hans

2000-01-01

We have used oligonucleotide-fingerprinting data on 60,000 cDNA clones from two different mouse embryonic stages to establish a normalized cDNA clone set. The normalized set of 5,376 clones represents different clusters and therefore, in almost all cases, different genes. The inserts of the cDNA clones were amplified by PCR and spotted on glass slides. The resulting arrays were hybridized with mRNA probes prepared from six different adult mouse tissues. Expression profiles were analyzed by hierarchical clustering techniques. We have chosen radioactive detection because it combines robustness with sensitivity and allows the comparison of multiple normalized experiments. Sensitive detection combined with highly effective clustering algorithms allowed the identification of tissue-specific expression profiles and the detection of genes specifically expressed in the tissues investigated. The obtained results are publicly available (http://www.rzpd.de) and can be used by other researchers as a digital expression reference. [The sequence data described in this paper have been submitted to the EMBL data library under accession nos. AL360374–AL36537.] PMID:10958641

Dynamic microscopy of nanoscale cluster growth at the solid-liquid interface.

PubMed

Williamson, M J; Tromp, R M; Vereecken, P M; Hull, R; Ross, F M

2003-08-01

Dynamic processes at the solid-liquid interface are of key importance across broad areas of science and technology. Electrochemical deposition of copper, for example, is used for metallization in integrated circuits, and a detailed understanding of nucleation, growth and coalescence is essential in optimizing the final microstructure. Our understanding of processes at the solid-vapour interface has advanced tremendously over the past decade due to the routine availability of real-time, high-resolution imaging techniques yielding data that can be compared quantitatively with theory. However, the difficulty of studying the solid-liquid interface leaves our understanding of processes there less complete. Here we analyse dynamic observations--recorded in situ using a novel transmission electron microscopy technique--of the nucleation and growth of nanoscale copper clusters during electrodeposition. We follow in real time the evolution of individual clusters, and compare their development with simulations incorporating the basic physics of electrodeposition during the early stages of growth. The experimental technique developed here is applicable to a broad range of dynamic phenomena at the solid-liquid interface.

A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification.

PubMed

Peikari, Mohammad; Salama, Sherine; Nofech-Mozes, Sharon; Martel, Anne L

2018-05-08

Completely labeled pathology datasets are often challenging and time-consuming to obtain. Semi-supervised learning (SSL) methods are able to learn from fewer labeled data points with the help of a large number of unlabeled data points. In this paper, we investigated the possibility of using clustering analysis to identify the underlying structure of the data space for SSL. A cluster-then-label method was proposed to identify high-density regions in the data space which were then used to help a supervised SVM in finding the decision boundary. We have compared our method with other supervised and semi-supervised state-of-the-art techniques using two different classification tasks applied to breast pathology datasets. We found that compared with other state-of-the-art supervised and semi-supervised methods, our SSL method is able to improve classification performance when a limited number of labeled data instances are made available. We also showed that it is important to examine the underlying distribution of the data space before applying SSL techniques to ensure semi-supervised learning assumptions are not violated by the data.

A Hybrid Cloud Computing Service for Earth Sciences

NASA Astrophysics Data System (ADS)

Yang, C. P.

2016-12-01

Cloud Computing is becoming a norm for providing computing capabilities for advancing Earth sciences including big Earth data management, processing, analytics, model simulations, and many other aspects. A hybrid spatiotemporal cloud computing service is bulit at George Mason NSF spatiotemporal innovation center to meet this demands. This paper will report the service including several aspects: 1) the hardware includes 500 computing services and close to 2PB storage as well as connection to XSEDE Jetstream and Caltech experimental cloud computing environment for sharing the resource; 2) the cloud service is geographically distributed at east coast, west coast, and central region; 3) the cloud includes private clouds managed using open stack and eucalyptus, DC2 is used to bridge these and the public AWS cloud for interoperability and sharing computing resources when high demands surfing; 4) the cloud service is used to support NSF EarthCube program through the ECITE project, ESIP through the ESIP cloud computing cluster, semantics testbed cluster, and other clusters; 5) the cloud service is also available for the earth science communities to conduct geoscience. A brief introduction about how to use the cloud service will be included.

Clustering the Orion B giant molecular cloud based on its molecular emission

PubMed Central

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2017-01-01

Context Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results A clustering analysis based only on the J = 1 – 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes (nH ~ 100 cm−3, ~ 500 cm−3, and > 1000 cm−3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 − 0 line of HCO+ and the N = 1 − 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH ~ 7 × 103 cm−3 ~ 4 × 104 cm−3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1 – 0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Conclusions Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers. PMID:29456256

Structure and substructure analysis of DAFT/FADA galaxy clusters in the [0.4–0.9] redshift range

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

Guennou, L.; et al.

2014-01-17

Context. The DAFT/FADA survey is based on the study of ~90 rich(masses found in the literature >2 x 10^14 M_⊙)and moderately distant clusters (redshifts 0.4 < z < 0.9), all withHST imaging data available. This survey has two main objectives: to constrain dark energy(DE) using weak lensing tomography on galaxy clusters and to build a database (deepmulti-band imaging allowing photometric redshift estimates, spectroscopic data, X-raydata) of rich distant clusters to study their properties.

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

PubMed

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

2012-06-01

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

Effects of selected socio-demographic characteristics on nutrition knowledge and eating behavior of elementary students in two provinces in China.

PubMed

Qian, Ling; Zhang, Fan; Newman, Ian M; Shell, Duane F; Du, Weijing

2017-07-14

National and international child health surveys have indicated an increase in childhood obesity in China. The increase has been attributed to a rising standard of living, increasing availability of unhealthy foods, and a lack of knowledge about healthy diet. The objective of this study was to assess the effect of selected socio-demographic characteristics on the BMI, nutrition knowledge, and eating behavior of elementary school children. Multistage stratified cluster sampling was used. Information on demographics, nutrition knowledge, and eating behavior was gathered by means of questionnaires. The schools' doctors provided the height and weight data. The study was set in one economically advantaged and one economically disadvantaged province in China. The participants were Grade 3 students, ages 8-10 years (N = 3922). A cluster analysis identified four socio-demographic variables distinguished by parental education and family living arrangement. A one-way ANOVA compared differences among the clusters in BMI, child nutrition knowledge, and child eating behavior. Students in the cluster with lowest parent education level had the lowest nutrition knowledge scores and eating behavior scores. There was no significant benefit from college education versus high school education of parents in the other three clusters. BMI was not affected by parent education level. The nutrition status of elementary school age children will benefit most by increasing the general level of education for those adults who are presently least educated.

Gemini spectroscopy of the outer disk star cluster BH176

NASA Astrophysics Data System (ADS)

Sharina, M. E.; Donzelli, C. J.; Davoust, E.; Shimansky, V. V.; Charbonnel, C.

2014-10-01

Context. BH176 is an old metal-rich star cluster. It is spatially and kinematically consistent with belonging to the Monoceros Ring. It is larger in size and more distant from the Galactic plane than typical open clusters, and it does not belong to the Galactic bulge. Aims: Our aim is to determine the origin of this unique object by accurately determining its distance, metallicity, and age. The best way to reach this goal is to combine spectroscopic and photometric methods. Methods: We present medium-resolution observations of red clump and red giant branch stars in BH176 obtained with the Gemini South Multi-Object Spectrograph. We derive radial velocities, metallicities, effective temperatures, and surface gravities of the observed stars and use these parameters to distinguish member stars from field objects. Results: We determine the following parameters for BH176: Vh = 0 ± 15 km s-1, [Fe/H] = -0.1 ± 0.1, age 7 ± 0.5 Gyr, E(V - I) = 0.79 ± 0.03, distance 15.2 ± 0.2 kpc, α-element abundance [α/Fe] ~ 0.25 dex (the mean of [Mg/Fe], and [Ca/Fe]). Conclusions: BH176 is a member of old Galactic open clusters that presumably belong to the thick disk. It may have originated as a massive star cluster after the encounter of the forming thin disk with a high-velocity gas cloud or as a satellite dwarf galaxy. Appendix A is available in electronic form at http://www.aanda.org

The potassium abundance in the globular clusters NGC 104, NGC 6752 and NGC 6809

NASA Astrophysics Data System (ADS)

Mucciarelli, A.; Merle, T.; Bellazzini, M.

2017-04-01

We derived potassium abundances in red-giant-branch stars in the Galactic globular clusters NGC 104 (144 stars), NGC 6752 (134 stars), and NGC 6809 (151 stars) using high-resolution spectra collected with FLAMES at the ESO - Very Large Telescope. In the samples we consider, we do not find significant intrinsic spreads in [K/Fe], which confirms the previous findings, but which is at variance with the cases of the massive clusters NGC 2419 and NGC 2808. Additionally, marginally significant [K/Fe]-[O/Fe] anti-correlations are found in NGC 104 and NGC 6809, and [K/Fe]-[Na/Fe] correlations are found in NGC 104 and NGC 6752. No evidence of [K/Fe]-[Mg/Fe] anti-correlation are found. The results of our analysis are consistent with a scenario in which the process leading to the multi-populations in globular clusters also implies enrichment in the K abundance, the amplitude of the associated [K/Fe] enhancement becoming measurable only in stars showing the most extreme effects of O and Mg depletion. Stars enhanced in [K/Fe] have so far only been found in clusters harbouring some Mg-poor stars, while the other globulars, without a Mg-poor sub-population, show small or null [K/Fe] spreads. Full Table 1 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/600/A104

Real- and redshift-space halo clustering in f(R) cosmologies

NASA Astrophysics Data System (ADS)

Arnalte-Mur, Pablo; Hellwing, Wojciech A.; Norberg, Peder

2017-05-01

We present two-point correlation function statistics of the mass and the haloes in the chameleon f(R) modified gravity scenario using a series of large-volume N-body simulations. Three distinct variations of f(R) are considered (F4, F5 and F6) and compared to a fiducial Λ cold dark matter (ΛCDM) model in the redshift range z ∈ [0, 1]. We find that the matter clustering is indistinguishable for all models except for F4, which shows a significantly steeper slope. The ratio of the redshift- to real-space correlation function at scales >20 h-1 Mpc agrees with the linear General Relativity (GR) Kaiser formula for the viable f(R) models considered. We consider three halo populations characterized by spatial abundances comparable to that of luminous red galaxies and galaxy clusters. The redshift-space halo correlation functions of F4 and F5 deviate significantly from ΛCDM at intermediate and high redshift, as the f(R) halo bias is smaller than or equal to that of the ΛCDM case. Finally, we introduce a new model-independent clustering statistic to distinguish f(R) from GR: the relative halo clustering ratio - R. The sampling required to adequately reduce the scatter in R will be available with the advent of the next-generation galaxy redshift surveys. This will foster a prospective avenue to obtain largely model-independent cosmological constraints on this class of modified gravity models.

Food consumption and cardiovascular risk factors in European children: the IDEFICS study.

PubMed

Bel-Serrat, S; Mouratidou, T; Börnhorst, C; Peplies, J; De Henauw, S; Marild, S; Molnár, D; Siani, A; Tornaritis, M; Veidebaum, T; Krogh, V; Moreno, L A

2013-06-01

Few studies addressing the relationship between food consumption and cardiovascular disease or metabolic risk have been conducted in children. Previous findings have indicated greater metabolic risk in children with high intakes of solid hydrogenated fat and white bread, and low consumption of fruits, vegetables and dairy products. In a large multinational sample of 2 to 9 years old children, high consumption of sweetened beverages and low intake of nuts and seeds, sweets, breakfast cereals, jam and honey and chocolate and nut-based spreads were directly associated with increased clustered cardiovascular disease risk. These findings add new evidence to the limited literature available in young populations on the role that diet may play on cardiovascular health. To investigate food consumption in relation to clustered cardiovascular disease (CVD) risk. Children (n = 5548, 51.6% boys) from eight European countries participated in the IDEFICS study baseline survey (2007-2008). Z-scores of individual CVD risk factors were summed to compute sex- and age-specific (2-<6 years/6-9 years) clustered CVD risk scores A (all components, except cardiorespiratory fitness) and B (all components). The association of clustered CVD risk and tertiles of food group consumption was examined. Odds ratio (OR) of having clustered CVD risk A increased in older children with higher consumption of chocolate and nut-based spreads (boys: OR = 0.46; 95% CI = 0.32-0.69; girls: OR = 0.60; 95% CI = 0.42-0.86), jam and honey (girls: OR = 0.45; 95% CI = 0.26-0.78) and sweets (boys: OR = 0.69; 95% CI = 0.48-0.98). OR of being at risk significantly increased with the highest consumption of soft drinks (younger boys) and manufactured juices (older girls). Concerning CVD risk score B, older boys and girls in the highest tertile of consumption of breakfast cereals were 0.41 (95% CI = 0.21-0.79) and 0.45 (95% CI = 0.22-0.93) times, respectively, less likely to be at risk than those in tertile 1. High consumption of sugar-sweetened beverages and low intake of breakfast cereals, jam and honey, sweets and chocolate and nut-based spreads seem to adversely affect clustered CVD risk. © 2012 The Authors. Pediatric Obesity © 2012 International Association for the Study of Obesity.

Topology in two dimensions. II - The Abell and ACO cluster catalogues

NASA Astrophysics Data System (ADS)

Plionis, Manolis; Valdarnini, Riccardo; Coles, Peter

1992-09-01

We apply a method for quantifying the topology of projected galaxy clustering to the Abell and ACO catalogues of rich clusters. We use numerical simulations to quantify the statistical bias involved in using high peaks to define the large-scale structure, and we use the results obtained to correct our observational determinations for this known selection effect and also for possible errors introduced by boundary effects. We find that the Abell cluster sample is consistent with clusters being identified with high peaks of a Gaussian random field, but that the ACO shows a slight meatball shift away from the Gaussian behavior over and above that expected purely from the high-peak selection. The most conservative explanation of this effect is that it is caused by some artefact of the procedure used to select the clusters in the two samples.

UV-light-driven prebiotic synthesis of iron-sulfur clusters

NASA Astrophysics Data System (ADS)

Bonfio, Claudia; Valer, Luca; Scintilla, Simone; Shah, Sachin; Evans, David J.; Jin, Lin; Szostak, Jack W.; Sasselov, Dimitar D.; Sutherland, John D.; Mansy, Sheref S.

2017-12-01

Iron-sulfur clusters are ancient cofactors that play a fundamental role in metabolism and may have impacted the prebiotic chemistry that led to life. However, it is unclear whether iron-sulfur clusters could have been synthesized on prebiotic Earth. Dissolved iron on early Earth was predominantly in the reduced ferrous state, but ferrous ions alone cannot form polynuclear iron-sulfur clusters. Similarly, free sulfide may not have been readily available. Here we show that UV light drives the synthesis of [2Fe-2S] and [4Fe-4S] clusters through the photooxidation of ferrous ions and the photolysis of organic thiols. Iron-sulfur clusters coordinate to and are stabilized by a wide range of cysteine-containing peptides and the assembly of iron-sulfur cluster-peptide complexes can take place within model protocells in a process that parallels extant pathways. Our experiments suggest that iron-sulfur clusters may have formed easily on early Earth, facilitating the emergence of an iron-sulfur-cluster-dependent metabolism.

Magnetic switching in Crx (x = 2-8) and its oxide cluster series

NASA Astrophysics Data System (ADS)

Shah, Esha V.; Roy, Debesh R.

2018-04-01

First principle studies on the magnetic ground state structure, noncollinearity, binding energy and various electronic properties of a series of Crx (x = 2-8) clusters are performed. In order to investigate the effect of ionization and oxidation on the clusters, the anionic (Crx-) and oxidized (CrxO2) analogues of those clusters are also studied in detail. To calculate adiabatic electron affinity of CrxO2 clusters, additionally CrxO2- analogues are also included in the present work. An interesting even (non-magnetic) - odd (magnetic) feature in the considered cluster series has been noticed. The similar behavior is also reflected from their electronic properties as even (less reactive) - odd (more reactive). The most of the neutral and ionized chromium clusters, viz., Crx and Crx- are found to be noncollinear in their ground states, whereas oxidation stabilized those clusters into the collinear spin alignments. The bond distances of Cr clusters are found to be close with available experimental studies.

Gas loss in simulated galaxies as they fall into clusters

PubMed Central

Cen, Renyue; Pop, Ana Roxana; Bahcall, Neta A.

2014-01-01

We use high-resolution cosmological hydrodynamic galaxy formation simulations to gain insights into how galaxies lose their cold gas at low redshift as they migrate from the field to the high-density regions of clusters of galaxies. We find that beyond three cluster virial radii, the fraction of gas-rich galaxies is constant, representing the field. Within three cluster-centric radii, the fraction of gas-rich galaxies declines steadily with decreasing radius, reaching <10% near the cluster center. Our results suggest galaxies start to feel the effect of the cluster environment on their gas content well beyond the cluster virial radius. We show that almost all gas-rich galaxies at the cluster virial radius are falling in for the first time at nearly radial orbits. Furthermore, we find that almost no galaxy moving outward at the cluster virial radius is gas-rich (with a gas-to-baryon ratio greater than 1%). These results suggest that galaxies that fall into clusters lose their cold gas within a single radial round-trip. PMID:24843167

Gas loss in simulated galaxies as they fall into clusters.

PubMed

Cen, Renyue; Pop, Ana Roxana; Bahcall, Neta A

2014-06-03

We use high-resolution cosmological hydrodynamic galaxy formation simulations to gain insights into how galaxies lose their cold gas at low redshift as they migrate from the field to the high-density regions of clusters of galaxies. We find that beyond three cluster virial radii, the fraction of gas-rich galaxies is constant, representing the field. Within three cluster-centric radii, the fraction of gas-rich galaxies declines steadily with decreasing radius, reaching <10% near the cluster center. Our results suggest galaxies start to feel the effect of the cluster environment on their gas content well beyond the cluster virial radius. We show that almost all gas-rich galaxies at the cluster virial radius are falling in for the first time at nearly radial orbits. Furthermore, we find that almost no galaxy moving outward at the cluster virial radius is gas-rich (with a gas-to-baryon ratio greater than 1%). These results suggest that galaxies that fall into clusters lose their cold gas within a single radial round-trip.

Do Practical Standard Coupled Cluster Calculations Agree Better than Kohn–Sham Calculations with Currently Available Functionals When Compared to the Best Available Experimental Data for Dissociation Energies of Bonds to 3d Transition Metals?

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

Xu, Xuefei; Zhang, Wenjing; Tang, Mingsheng

2015-05-12

Coupled-cluster (CC) methods have been extensively used as the high-level approach in quantum electronic structure theory to predict various properties of molecules when experimental results are unavailable. It is often assumed that CC methods, if they include at least up to connected-triple-excitation quasiperturbative corrections to a full treatment of single and double excitations (in particular, CCSD(T)), and a very large basis set, are more accurate than Kohn–Sham (KS) density functional theory (DFT). In the present work, we tested and compared the performance of standard CC and KS methods on bond energy calculations of 20 3d transition metal-containing diatomic molecules againstmore » the most reliable experimental data available, as collected in a database called 3dMLBE20. It is found that, although the CCSD(T) and higher levels CC methods have mean unsigned deviations from experiment that are smaller than most exchange-correlation functionals for metal–ligand bond energies of transition metals, the improvement is less than one standard deviation of the mean unsigned deviation. Furthermore, on average, almost half of the 42 exchange-correlation functionals that we tested are closer to experiment than CCSD(T) with the same extended basis set for the same molecule. The results show that, when both relativistic and core–valence correlation effects are considered, even the very high-level (expensive) CC method with single, double, triple, and perturbative quadruple cluster operators, namely, CCSDT(2)Q, averaged over 20 bond energies, gives a mean unsigned deviation (MUD(20) = 4.7 kcal/mol when one correlates only valence, 3p, and 3s electrons of transition metals and only valence electrons of ligands, or 4.6 kcal/mol when one correlates all core electrons except for 1s shells of transition metals, S, and Cl); and that is similar to some good xc functionals (e.g., B97-1 (MUD(20) = 4.5 kcal/mol) and PW6B95 (MUD(20) = 4.9 kcal/mol)) when the same basis set is used. We found that, for both coupled cluster calculations and KS calculations, the T1 diagnostics correlate the errors better than either the M diagnostics or the B1 DFT-based diagnostics. The potential use of practical standard CC methods as a benchmark theory is further confounded by the finding that CC and DFT methods usually have different signs of the error. We conclude that the available experimental data do not provide a justification for using conventional single-reference CC theory calculations to validate or test xc functionals for systems involving 3d transition metals.« less

Identification of cognitive profiles among women considering BRCA1/2 testing through the utilisation of cluster analytic techniques.

PubMed

Roussi, Pagona; Sherman, Kerry A; Miller, Suzanne M; Hurley, Karen; Daly, Mary B; Godwin, Andrew; Buzaglo, Joanne S; Wen, Kuang-Yi

2011-10-01

Based on the cognitive-social health information processing model, we identified cognitive profiles of women at risk for breast and ovarian cancer. Prior to genetic counselling, participants (N = 171) completed a study questionnaire concerning their cognitive and affective responses to being at genetic risk. Using cluster analysis, four cognitive profiles were generated: (a) high perceived risk/low coping; (b) low value of screening/high expectancy of cancer; (c) moderate perceived risk/moderate efficacy of prevention/low informativeness of test result; and (d) high efficacy of prevention/high coping. The majority of women in Clusters One, Two and Three had no personal history of cancer, whereas Cluster Four consisted almost entirely of women affected with cancer. Women in Cluster One had the highest number of affected relatives and experienced higher levels of distress than women in the other three clusters. These results highlight the need to consider the psychological profile of women undergoing genetic testing when designing counselling interventions and messages.

High β effects on cosmic ray streaming in galaxy clusters

NASA Astrophysics Data System (ADS)

Wiener, Joshua; Zweibel, Ellen G.; Oh, S. Peng

2018-01-01

Diffuse, extended radio emission in galaxy clusters, commonly referred to as radio haloes, indicate the presence of high energy cosmic ray (CR) electrons and cluster-wide magnetic fields. We can predict from theory the expected surface brightness of a radio halo, given magnetic field and CR density profiles. Previous studies have shown that the nature of CR transport can radically effect the expected radio halo emission from clusters (Wiener, Oh & Guo 2013). Reasonable levels of magnetohydrodynamic (MHD) wave damping can lead to significant CR streaming speeds. But a careful treatment of MHD waves in a high β plasma, as expected in cluster environments, reveals damping rates may be enhanced by a factor of β1/2. This leads to faster CR streaming and lower surface brightnesses than without this effect. In this work, we re-examine the simplified, 1D Coma cluster simulations (with radial magnetic fields) of Wiener et al. (2013) and discuss observable consequences of this high β damping. Future work is required to study this effect in more realistic simulations.

Analysis of local bond-orientational order for liquid gallium at ambient pressure: Two types of cluster structures.

PubMed

Chen, Lin-Yuan; Tang, Ping-Han; Wu, Ten-Ming

2016-07-14

In terms of the local bond-orientational order (LBOO) parameters, a cluster approach to analyze local structures of simple liquids was developed. In this approach, a cluster is defined as a combination of neighboring seeds having at least nb local-orientational bonds and their nearest neighbors, and a cluster ensemble is a collection of clusters with a specified nb and number of seeds ns. This cluster analysis was applied to investigate the microscopic structures of liquid Ga at ambient pressure (AP). The liquid structures studied were generated through ab initio molecular dynamics simulations. By scrutinizing the static structure factors (SSFs) of cluster ensembles with different combinations of nb and ns, we found that liquid Ga at AP contained two types of cluster structures, one characterized by sixfold orientational symmetry and the other showing fourfold orientational symmetry. The SSFs of cluster structures with sixfold orientational symmetry were akin to the SSF of a hard-sphere fluid. On the contrary, the SSFs of cluster structures showing fourfold orientational symmetry behaved similarly as the anomalous SSF of liquid Ga at AP, which is well known for exhibiting a high-q shoulder. The local structures of a highly LBOO cluster whose SSF displayed a high-q shoulder were found to be more similar to the structure of β-Ga than those of other solid phases of Ga. More generally, the cluster structures showing fourfold orientational symmetry have an inclination to resemble more to β-Ga.