Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

PubMed Central

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods. Conclusions Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems. PMID:22643026

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties

NASA Astrophysics Data System (ADS)

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-01

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi4, NLi5, CLi6, BLI7 and Al12Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability (β ) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties.

PubMed

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-25

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi 4 , NLi 5 , CLi 6 , BLI 7 and Al 12 Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability ([Formula: see text]) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Catalysis applications of size-selected cluster deposition

DOE PAGES

Vajda, Stefan; White, Michael G.

2015-10-23

In this Perspective, we review recent studies of size-selected cluster deposition for catalysis applications performed at the U.S. DOE National Laboratories, with emphasis on work at Argonne National Laboratory (ANL) and Brookhaven National Laboratory (BNL). The focus is on the preparation of model supported catalysts in which the number of atoms in the deposited clusters is precisely controlled using a combination of gas-phase cluster ion sources, mass spectrometry, and soft-landing techniques. This approach is particularly effective for investigations of small nanoclusters, 0.5-2 nm (<200 atoms), where the rapid evolution of the atomic and electronic structure makes it essential to havemore » precise control over cluster size. Cluster deposition allows for independent control of cluster size, coverage, and stoichiometry (e.g., the metal-to-oxygen ratio in an oxide cluster) and can be used to deposit on any substrate without constraints of nucleation and growth. Examples are presented for metal, metal oxide, and metal sulfide cluster deposition on a variety of supports (metals, oxides, carbon/diamond) where the reactivity, cluster-support electronic interactions, and cluster stability and morphology are investigated. Both UHV and in situ/operando studies are presented that also make use of surface-sensitive X-ray characterization tools from synchrotron radiation facilities. Novel applications of cluster deposition to electrochemistry and batteries are also presented. This review also highlights the application of modern ab initio electronic structure calculations (density functional theory), which can essentially model the exact experimental system used in the laboratory (i.e., cluster and support) to provide insight on atomic and electronic structure, reaction energetics, and mechanisms. As amply demonstrated in this review, the powerful combination of atomically precise cluster deposition and theory is able to address fundamental aspects of size-effects, cluster-support interactions, and reaction mechanisms of cluster materials that are central to how catalysts function. Lastly, the insight gained from such studies can be used to further the development of novel nanostructured catalysts with high activity and selectivity.« less

Testing for X-Ray–SZ Differences and Redshift Evolution in the X-Ray Morphology of Galaxy Clusters

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

Nurgaliev, D.; McDonald, M.; Benson, B. A.

We present a quantitative study of the X-ray morphology of galaxy clusters, as a function of their detection method and redshift. We analyze two separate samples of galaxy clusters: a sample of 36 clusters atmore » $$0.35\\lt z\\lt 0.9$$ selected in the X-ray with the ROSAT PSPC 400 deg(2) survey, and a sample of 90 clusters at $$0.25\\lt z\\lt 1.2$$ selected via the Sunyaev–Zel’dovich (SZ) effect with the South Pole Telescope. Clusters from both samples have similar-quality Chandra observations, which allow us to quantify their X-ray morphologies via two distinct methods: centroid shifts (w) and photon asymmetry ($${A}_{\\mathrm{phot}}$$). The latter technique provides nearly unbiased morphology estimates for clusters spanning a broad range of redshift and data quality. We further compare the X-ray morphologies of X-ray- and SZ-selected clusters with those of simulated clusters. We do not find a statistically significant difference in the measured X-ray morphology of X-ray and SZ-selected clusters over the redshift range probed by these samples, suggesting that the two are probing similar populations of clusters. We find that the X-ray morphologies of simulated clusters are statistically indistinguishable from those of X-ray- or SZ-selected clusters, implying that the most important physics for dictating the large-scale gas morphology (outside of the core) is well-approximated in these simulations. Finally, we find no statistically significant redshift evolution in the X-ray morphology (both for observed and simulated clusters), over the range of $$z\\sim 0.3$$ to $$z\\sim 1$$, seemingly in contradiction with the redshift-dependent halo merger rate predicted by simulations.« less

Testing for X-Ray–SZ Differences and Redshift Evolution in the X-Ray Morphology of Galaxy Clusters

DOE PAGES

Nurgaliev, D.; McDonald, M.; Benson, B. A.; ...

2017-05-16

We present a quantitative study of the X-ray morphology of galaxy clusters, as a function of their detection method and redshift. We analyze two separate samples of galaxy clusters: a sample of 36 clusters atmore » $$0.35\\lt z\\lt 0.9$$ selected in the X-ray with the ROSAT PSPC 400 deg(2) survey, and a sample of 90 clusters at $$0.25\\lt z\\lt 1.2$$ selected via the Sunyaev–Zel’dovich (SZ) effect with the South Pole Telescope. Clusters from both samples have similar-quality Chandra observations, which allow us to quantify their X-ray morphologies via two distinct methods: centroid shifts (w) and photon asymmetry ($${A}_{\\mathrm{phot}}$$). The latter technique provides nearly unbiased morphology estimates for clusters spanning a broad range of redshift and data quality. We further compare the X-ray morphologies of X-ray- and SZ-selected clusters with those of simulated clusters. We do not find a statistically significant difference in the measured X-ray morphology of X-ray and SZ-selected clusters over the redshift range probed by these samples, suggesting that the two are probing similar populations of clusters. We find that the X-ray morphologies of simulated clusters are statistically indistinguishable from those of X-ray- or SZ-selected clusters, implying that the most important physics for dictating the large-scale gas morphology (outside of the core) is well-approximated in these simulations. Finally, we find no statistically significant redshift evolution in the X-ray morphology (both for observed and simulated clusters), over the range of $$z\\sim 0.3$$ to $$z\\sim 1$$, seemingly in contradiction with the redshift-dependent halo merger rate predicted by simulations.« less

Clustering and group selection of multiple criteria alternatives with application to space-based networks.

PubMed

Malakooti, Behnam; Yang, Ziyong

2004-02-01

In many real-world problems, the range of consequences of different alternatives are considerably different. In addition, sometimes, selection of a group of alternatives (instead of only one best alternative) is necessary. Traditional decision making approaches treat the set of alternatives with the same method of analysis and selection. In this paper, we propose clustering alternatives into different groups so that different methods of analysis, selection, and implementation for each group can be applied. As an example, consider the selection of a group of functions (or tasks) to be processed by a group of processors. The set of tasks can be grouped according to their similar criteria, and hence, each cluster of tasks to be processed by a processor. The selection of the best alternative for each clustered group can be performed using existing methods; however, the process of selecting groups is different than the process of selecting alternatives within a group. We develop theories and procedures for clustering discrete multiple criteria alternatives. We also demonstrate how the set of alternatives is clustered into mutually exclusive groups based on 1) similar features among alternatives; 2) ideal (or most representative) alternatives given by the decision maker; and 3) other preferential information of the decision maker. The clustering of multiple criteria alternatives also has the following advantages. 1) It decreases the set of alternatives to be considered by the decision maker (for example, different decision makers are assigned to different groups of alternatives). 2) It decreases the number of criteria. 3) It may provide a different approach for analyzing multiple decision makers problems. Each decision maker may cluster alternatives differently, and hence, clustering of alternatives may provide a basis for negotiation. The developed approach is applicable for solving a class of telecommunication networks problems where a set of objects (such as routers, processors, or intelligent autonomous vehicles) are to be clustered into similar groups. Objects are clustered based on several criteria and the decision maker's preferences.

Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays.

PubMed

Kanie, Kei; Kondo, Yuto; Owaki, Junki; Ikeda, Yurika; Narita, Yuji; Kato, Ryuji; Honda, Hiroyuki

2016-11-19

The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM) provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV), an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I), and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides.

Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays

PubMed Central

Kanie, Kei; Kondo, Yuto; Owaki, Junki; Ikeda, Yurika; Narita, Yuji; Kato, Ryuji; Honda, Hiroyuki

2016-01-01

The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM) provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV), an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I), and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides. PMID:28952593

Rapid Detection of Positive Selection in Genes and Genomes Through Variation Clusters

PubMed Central

Wagner, Andreas

2007-01-01

Positive selection in genes and genomes can point to the evolutionary basis for differences among species and among races within a species. The detection of positive selection can also help identify functionally important protein regions and thus guide protein engineering. Many existing tests for positive selection are excessively conservative, vulnerable to artifacts caused by demographic population history, or computationally very intensive. I here propose a simple and rapid test that is complementary to existing tests and that overcomes some of these problems. It relies on the null hypothesis that neutrally evolving DNA regions should show a Poisson distribution of nucleotide substitutions. The test detects significant deviations from this expectation in the form of variation clusters, highly localized groups of amino acid changes in a coding region. In applying this test to several thousand human–chimpanzee gene orthologs, I show that such variation clusters are not generally caused by relaxed selection. They occur in well-defined domains of a protein's tertiary structure and show a large excess of amino acid replacement over silent substitutions. I also identify multiple new human–chimpanzee orthologs subject to positive selection, among them genes that are involved in reproductive functions, immune defense, and the nervous system. PMID:17603100

Clinical Characteristics of Exacerbation-Prone Adult Asthmatics Identified by Cluster Analysis.

PubMed

Kim, Mi Ae; Shin, Seung Woo; Park, Jong Sook; Uh, Soo Taek; Chang, Hun Soo; Bae, Da Jeong; Cho, You Sook; Park, Hae Sim; Yoon, Ho Joo; Choi, Byoung Whui; Kim, Yong Hoon; Park, Choon Sik

2017-11-01

Asthma is a heterogeneous disease characterized by various types of airway inflammation and obstruction. Therefore, it is classified into several subphenotypes, such as early-onset atopic, obese non-eosinophilic, benign, and eosinophilic asthma, using cluster analysis. A number of asthmatics frequently experience exacerbation over a long-term follow-up period, but the exacerbation-prone subphenotype has rarely been evaluated by cluster analysis. This prompted us to identify clusters reflecting asthma exacerbation. A uniform cluster analysis method was applied to 259 adult asthmatics who were regularly followed-up for over 1 year using 12 variables, selected on the basis of their contribution to asthma phenotypes. After clustering, clinical profiles and exacerbation rates during follow-up were compared among the clusters. Four subphenotypes were identified: cluster 1 was comprised of patients with early-onset atopic asthma with preserved lung function, cluster 2 late-onset non-atopic asthma with impaired lung function, cluster 3 early-onset atopic asthma with severely impaired lung function, and cluster 4 late-onset non-atopic asthma with well-preserved lung function. The patients in clusters 2 and 3 were identified as exacerbation-prone asthmatics, showing a higher risk of asthma exacerbation. Two different phenotypes of exacerbation-prone asthma were identified among Korean asthmatics using cluster analysis; both were characterized by impaired lung function, but the age at asthma onset and atopic status were different between the two. Copyright © 2017 The Korean Academy of Asthma, Allergy and Clinical Immunology · The Korean Academy of Pediatric Allergy and Respiratory Disease

Characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts

NASA Astrophysics Data System (ADS)

Chen, Siyue; Leung, Henry; Dondo, Maxwell

2014-05-01

As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis.

PubMed

Bennett, Robert M; Russell, Jon; Cappelleri, Joseph C; Bushmakin, Andrew G; Zlateva, Gergana; Sadosky, Alesia

2010-06-28

The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain > or =40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.

The ROSAT Brightest Cluster Sample - I. The compilation of the sample and the cluster log N-log S distribution

NASA Astrophysics Data System (ADS)

Ebeling, H.; Edge, A. C.; Bohringer, H.; Allen, S. W.; Crawford, C. S.; Fabian, A. C.; Voges, W.; Huchra, J. P.

1998-12-01

We present a 90 per cent flux-complete sample of the 201 X-ray-brightest clusters of galaxies in the northern hemisphere (delta>=0 deg), at high Galactic latitudes (|b|>=20 deg), with measured redshifts z<=0.3 and fluxes higher than 4.4x10^-12 erg cm^-2 s^-1 in the 0.1-2.4 keV band. The sample, called the ROSAT Brightest Cluster Sample (BCS), is selected from ROSAT All-Sky Survey data and is the largest X-ray-selected cluster sample compiled to date. In addition to Abell clusters, which form the bulk of the sample, the BCS also contains the X-ray-brightest Zwicky clusters and other clusters selected from their X-ray properties alone. Effort has been made to ensure the highest possible completeness of the sample and the smallest possible contamination by non-cluster X-ray sources. X-ray fluxes are computed using an algorithm tailored for the detection and characterization of X-ray emission from galaxy clusters. These fluxes are accurate to better than 15 per cent (mean 1sigma error). We find the cumulative logN-logS distribution of clusters to follow a power law kappa S^alpha with alpha=1.31^+0.06_-0.03 (errors are the 10th and 90th percentiles) down to fluxes of 2x10^-12 erg cm^-2 s^-1, i.e. considerably below the BCS flux limit. Although our best-fitting slope disagrees formally with the canonical value of -1.5 for a Euclidean distribution, the BCS logN-logS distribution is consistent with a non-evolving cluster population if cosmological effects are taken into account. Our sample will allow us to examine large-scale structure in the northern hemisphere, determine the spatial cluster-cluster correlation function, investigate correlations between the X-ray and optical properties of the clusters, establish the X-ray luminosity function for galaxy clusters, and discuss the implications of the results for cluster evolution.

Source selection for cluster weak lensing measurements in the Hyper Suprime-Cam survey

NASA Astrophysics Data System (ADS)

Medezinski, Elinor; Oguri, Masamune; Nishizawa, Atsushi J.; Speagle, Joshua S.; Miyatake, Hironao; Umetsu, Keiichi; Leauthaud, Alexie; Murata, Ryoma; Mandelbaum, Rachel; Sifón, Cristóbal; Strauss, Michael A.; Huang, Song; Simet, Melanie; Okabe, Nobuhiro; Tanaka, Masayuki; Komiyama, Yutaka

2018-03-01

We present optimized source galaxy selection schemes for measuring cluster weak lensing (WL) mass profiles unaffected by cluster member dilution from the Subaru Hyper Suprime-Cam Strategic Survey Program (HSC-SSP). The ongoing HSC-SSP survey will uncover thousands of galaxy clusters to z ≲ 1.5. In deriving cluster masses via WL, a critical source of systematics is contamination and dilution of the lensing signal by cluster members, and by foreground galaxies whose photometric redshifts are biased. Using the first-year CAMIRA catalog of ˜900 clusters with richness larger than 20 found in ˜140 deg2 of HSC-SSP data, we devise and compare several source selection methods, including selection in color-color space (CC-cut), and selection of robust photometric redshifts by applying constraints on their cumulative probability distribution function (P-cut). We examine the dependence of the contamination on the chosen limits adopted for each method. Using the proper limits, these methods give mass profiles with minimal dilution in agreement with one another. We find that not adopting either the CC-cut or P-cut methods results in an underestimation of the total cluster mass (13% ± 4%) and the concentration of the profile (24% ± 11%). The level of cluster contamination can reach as high as ˜10% at R ≈ 0.24 Mpc/h for low-z clusters without cuts, while employing either the P-cut or CC-cut results in cluster contamination consistent with zero to within the 0.5% uncertainties. Our robust methods yield a ˜60 σ detection of the stacked CAMIRA surface mass density profile, with a mean mass of M200c = [1.67 ± 0.05(stat)] × 1014 M⊙/h.

Planck 2015 results. XXVII. The second Planck catalogue of Sunyaev-Zeldovich sources

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Barrena, R.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bikmaev, I.; Böhringer, H.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burenin, R.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Carvalho, P.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Chon, G.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Dahle, H.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Eisenhardt, P. R. M.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Feroz, F.; Ferragamo, A.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Génova-Santos, R. T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Grainge, K. J. B.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Hempel, A.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jin, T.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Khamitov, I.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mak, D. S. Y.; Mandolesi, N.; Mangilli, A.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Mazzotta, P.; McGehee, P.; Mei, S.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nastasi, A.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Olamaie, M.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrott, Y. C.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reach, W. T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rozo, E.; Rubiño-Martín, J. A.; Rumsey, C.; Rusholme, B.; Rykoff, E. S.; Sandri, M.; Santos, D.; Saunders, R. D. E.; Savelainen, M.; Savini, G.; Schammel, M. P.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Shimwell, T. W.; Spencer, L. D.; Stanford, S. A.; Stern, D.; Stolyarov, V.; Stompor, R.; Streblyanska, A.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tramonte, D.; Tristram, M.; Tucci, M.; Tuovinen, J.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; White, S. D. M.; Wright, E. L.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest systematic all-sky surveyof galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data sets, and is the first SZ-selected cluster survey containing >103 confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that the estimates of the SZ strength parameter Y5R500are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical, and X-ray data sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under-luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples.

Planck 2015 results: XXVII. The second Planck catalogue of Sunyaev-Zeldovich sources

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

Here, we present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest systematic all-sky surveyof galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data sets, and is the first SZ-selected cluster survey containing >103 confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that themore » estimates of the SZ strength parameter Y5R500are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical, and X-ray data sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under-luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples.« less

Copper cluster size effect in methanol synthesis from CO 2

DOE PAGES

Yang, Bing; Liu, Cong; Halder, Avik; ...

2017-05-08

Here, size-selected Cu n catalysts ( n = 3, 4, 20) were synthesized on Al 2O 3 thin films using mass-selected cluster deposition. A systematic study of size and support effects was carried out for CO 2 hydrogenation at atmospheric pressure using a combination of in situ grazing incidence X-ray absorption spectroscopy, catalytic activity measurement, and first-principles calculations. The catalytic activity for methanol synthesis is found to strongly vary as a function of the cluster size; the Cu 4/Al 2O 3 catalyst shows the highest turnover rate for CH 3OH production. With only one atom less than Cu 4, Cumore » 3 showed less than 50% activity. Density functional theory calculations predict that the activities of the gas-phase Cu clusters increase as the cluster size decreases; however, the stronger charge transfer interaction with Al 2O 3 support for Cu 3 than for Cu 4 leads to remarkably reduced binding strength between the adsorbed intermediates and supported Cu 3, which subsequently results in a less favorable energetic pathway to transform carbon dioxide to methanol.« less

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Cosmological constraints from X-ray all sky surveys, from CODEX to eROSITA

NASA Astrophysics Data System (ADS)

Finoguenov, A.

2017-10-01

Large area cluster cosmology has long become a multiwavelength discipline. Understanding the effect of various selections is currently the main path to improving on the validity of cluster cosmological results. Many of these results are based on the large area sample derived from RASS data. We perform wavelet detection of X-ray sources and make extensive simulations of the detection of clusters in the RASS data. We assign an optical richness to each of the 25,000 detected X-ray sources in the 10,000 square degrees of SDSS BOSS area. We show that there is no obvious separation of sources on galaxy clusters and AGN, based on distribution of systems on their richness. We conclude that previous catalogs, such as MACS, REFLEX are all subject to a complex optical selection function, in addition to an X-ray selection. We provide a complete model of identification of cluster counts are galaxy clusters, which includes chance identification, effect of AGN halo occupation distribution and the thermal emission of ICM. Finally we present the cosmological results obtained using this sample.

The XXL Survey. II. The bright cluster sample: catalogue and luminosity function

NASA Astrophysics Data System (ADS)

Pacaud, F.; Clerc, N.; Giles, P. A.; Adami, C.; Sadibekova, T.; Pierre, M.; Maughan, B. J.; Lieu, M.; Le Fèvre, J. P.; Alis, S.; Altieri, B.; Ardila, F.; Baldry, I.; Benoist, C.; Birkinshaw, M.; Chiappetti, L.; Démoclès, J.; Eckert, D.; Evrard, A. E.; Faccioli, L.; Gastaldello, F.; Guennou, L.; Horellou, C.; Iovino, A.; Koulouridis, E.; Le Brun, V.; Lidman, C.; Liske, J.; Maurogordato, S.; Menanteau, F.; Owers, M.; Poggianti, B.; Pomarède, D.; Pompei, E.; Ponman, T. J.; Rapetti, D.; Reiprich, T. H.; Smith, G. P.; Tuffs, R.; Valageas, P.; Valtchanov, I.; Willis, J. P.; Ziparo, F.

2016-06-01

Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. The survey will ultimately uncover several hundreds of galaxy clusters out to a redshift of ~2 at a sensitivity of ~10-14 erg s-1 cm-2 in the [0.5-2] keV band. Aims: This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of 3 × 10-14 erg s-1 cm-2 on the source flux within a 1' aperture. Methods: The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results: The bright cluster sample consists of systems with masses between M500 = 7 × 1013 and 3 × 1014 M⊙, mostly located between z = 0.1 and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the prediction from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of σ8 and/or ΩM appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to z ~ 1. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters. Based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. Based on observations made with ESO Telescopes at the La Silla and Paranal Observatories under programme ID 089.A-0666 and LP191.A-0268.The Master Catalogue is 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/A2

Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

PubMed

Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

2016-01-01

Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Scalable properties of metal clusters: A comparative study of modern exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Koitz, Ralph; Soini, Thomas M.; Genest, Alexander; Trickey, S. B.; Rösch, Notker

2012-07-01

The performance of eight generalized gradient approximation exchange-correlation (xc) functionals is assessed by a series of scalar relativistic all-electron calculations on octahedral palladium model clusters Pdn with n = 13, 19, 38, 55, 79, 147 and the analogous clusters Aun (for n up through 79). For these model systems, we determined the cohesive energies and average bond lengths of the optimized octahedral structures. We extrapolate these values to the bulk limits and compare with the corresponding experimental values. While the well-established functionals BP, PBE, and PW91 are the most accurate at predicting energies, the more recent forms PBEsol, VMTsol, and VT{84}sol significantly improve the accuracy of geometries. The observed trends are largely similar for both Pd and Au. In the same spirit, we also studied the scalability of the ionization potentials and electron affinities of the Pd clusters, and extrapolated those quantities to estimates of the work function. Overall, the xc functionals can be classified into four distinct groups according to the accuracy of the computed parameters. These results allow a judicious selection of xc approximations for treating transition metal clusters.

A new clustering strategy

NASA Astrophysics Data System (ADS)

Feng, Jian-xin; Tang, Jia-fu; Wang, Guang-xing

2007-04-01

On the basis of the analysis of clustering algorithm that had been proposed for MANET, a novel clustering strategy was proposed in this paper. With the trust defined by statistical hypothesis in probability theory and the cluster head selected by node trust and node mobility, this strategy can realize the function of the malicious nodes detection which was neglected by other clustering algorithms and overcome the deficiency of being incapable of implementing the relative mobility metric of corresponding nodes in the MOBIC algorithm caused by the fact that the receiving power of two consecutive HELLO packet cannot be measured. It's an effective solution to cluster MANET securely.

Evolutionarily conserved mechanisms for the selection and maintenance of behavioural activity.

PubMed

Fiore, Vincenzo G; Dolan, Raymond J; Strausfeld, Nicholas J; Hirth, Frank

2015-12-19

Survival and reproduction entail the selection of adaptive behavioural repertoires. This selection manifests as phylogenetically acquired activities that depend on evolved nervous system circuitries. Lorenz and Tinbergen already postulated that heritable behaviours and their reliable performance are specified by genetically determined programs. Here we compare the functional anatomy of the insect central complex and vertebrate basal ganglia to illustrate their role in mediating selection and maintenance of adaptive behaviours. Comparative analyses reveal that central complex and basal ganglia circuitries share comparable lineage relationships within clusters of functionally integrated neurons. These clusters are specified by genetic mechanisms that link birth time and order to their neuronal identities and functions. Their subsequent connections and associated functions are characterized by similar mechanisms that implement dimensionality reduction and transition through attractor states, whereby spatially organized parallel-projecting loops integrate and convey sensorimotor representations that select and maintain behavioural activity. In both taxa, these neural systems are modulated by dopamine signalling that also mediates memory-like processes. The multiplicity of similarities between central complex and basal ganglia suggests evolutionarily conserved computational mechanisms for action selection. We speculate that these may have originated from ancestral ground pattern circuitries present in the brain of the last common ancestor of insects and vertebrates. © 2015 The Authors.

Evolutionarily conserved mechanisms for the selection and maintenance of behavioural activity

PubMed Central

Fiore, Vincenzo G.; Dolan, Raymond J.; Strausfeld, Nicholas J.; Hirth, Frank

2015-01-01

Survival and reproduction entail the selection of adaptive behavioural repertoires. This selection manifests as phylogenetically acquired activities that depend on evolved nervous system circuitries. Lorenz and Tinbergen already postulated that heritable behaviours and their reliable performance are specified by genetically determined programs. Here we compare the functional anatomy of the insect central complex and vertebrate basal ganglia to illustrate their role in mediating selection and maintenance of adaptive behaviours. Comparative analyses reveal that central complex and basal ganglia circuitries share comparable lineage relationships within clusters of functionally integrated neurons. These clusters are specified by genetic mechanisms that link birth time and order to their neuronal identities and functions. Their subsequent connections and associated functions are characterized by similar mechanisms that implement dimensionality reduction and transition through attractor states, whereby spatially organized parallel-projecting loops integrate and convey sensorimotor representations that select and maintain behavioural activity. In both taxa, these neural systems are modulated by dopamine signalling that also mediates memory-like processes. The multiplicity of similarities between central complex and basal ganglia suggests evolutionarily conserved computational mechanisms for action selection. We speculate that these may have originated from ancestral ground pattern circuitries present in the brain of the last common ancestor of insects and vertebrates. PMID:26554043

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.

Constraints on the richness-mass relation and the optical-SZE positional offset distribution for SZE-selected clusters

DOE PAGES

Saro, A.

2015-10-12

In this study, we cross-match galaxy cluster candidates selected via their Sunyaev–Zel'dovich effect (SZE) signatures in 129.1 deg 2 of the South Pole Telescope 2500d SPT-SZ survey with optically identified clusters selected from the Dark Energy Survey science verification data. We identify 25 clusters between 0.1 ≲ z ≲ 0.8 in the union of the SPT-SZ and redMaPPer (RM) samples. RM is an optical cluster finding algorithm that also returns a richness estimate for each cluster. We model the richness λ-mass relation with the following function 500> ∝ B λlnM 500 + C λlnE(z) and use SPT-SZ cluster masses andmore » RM richnesses λ to constrain the parameters. We find B λ = 1.14 +0.21 –0.18 and C λ = 0.73 +0.77 –0.75. The associated scatter in mass at fixed richness is σ lnM|λ = 0.18 +0.08 –0.05 at a characteristic richness λ = 70. We demonstrate that our model provides an adequate description of the matched sample, showing that the fraction of SPT-SZ-selected clusters with RM counterparts is consistent with expectations and that the fraction of RM-selected clusters with SPT-SZ counterparts is in mild tension with expectation. We model the optical-SZE cluster positional offset distribution with the sum of two Gaussians, showing that it is consistent with a dominant, centrally peaked population and a subdominant population characterized by larger offsets. We also cross-match the RM catalogue with SPT-SZ candidates below the official catalogue threshold significance ξ = 4.5, using the RM catalogue to provide optical confirmation and redshifts for 15 additional clusters with ξ ϵ [4, 4.5].« less

MEASURING THE LUMINOSITY AND VIRIAL BLACK HOLE MASS DEPENDENCE OF QUASAR–GALAXY CLUSTERING AT z ∼ 0.8

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

Krolewski, Alex G.; Eisenstein, Daniel J., E-mail: akrolewski@college.harvard.edu

2015-04-10

We study the dependence of quasar clustering on quasar luminosity and black hole mass by measuring the angular overdensity of photometrically selected galaxies imaged by the Wide-field Infrared Survey Explorer (WISE) about z ∼ 0.8 quasars from SDSS. By measuring the quasar–galaxy cross-correlation function and using photometrically selected galaxies, we achieve a higher density of tracer objects and a more sensitive detection of clustering than measurements of the quasar autocorrelation function. We test models of quasar formation and evolution by measuring the luminosity dependence of clustering amplitude. We find a significant overdensity of WISE galaxies about z ∼ 0.8 quasarsmore » at 0.2–6.4 h{sup −1} Mpc in projected comoving separation. We find no appreciable increase in clustering amplitude with quasar luminosity across a decade in luminosity, and a power-law fit between luminosity and clustering amplitude gives an exponent of −0.01 ± 0.06 (1 σ error). We also fail to find a significant relationship between clustering amplitude and black hole mass, although our dynamic range in true mass is suppressed due to the large uncertainties in virial black hole mass estimates. Our results indicate that a small range in host dark matter halo mass maps to a large range in quasar luminosity.« less

The Swift AGN and Cluster Survey

NASA Astrophysics Data System (ADS)

Dai, Xinyu

A key question in astrophysics is to constrain the evolution of the largest gravitationally bound structures in the universe. The serendipitous observations of Swift-XRT form an excellent medium-deep and wide soft X-ray survey, with a sky area of 160 square degrees at the flux limit of 5e-15 erg/s/cm^2. This survey is about an order of magnitude deeper than previous surveys of similar areas, and an order of magnitude wider than previous surveys of similar depth. It is comparable to the planned eROSITA deep survey, but already with the data several years ahead. The unique combination of the survey area and depth enables it to fill in the gap between the deep, pencil beam surveys (such as the Chandra Deep Fields) and the shallow, wide area surveys measured with ROSAT. With it, we will place independent and complementary measurements on the number counts and luminosity functions of X-ray sources. It has been proved that this survey is excellent for X-ray selected galaxy cluster surveys, based on our initial analysis of 1/4 of the fields and other independent studies. The highest priority goal is to produce the largest, uniformly selected catalog of X-ray selected clusters and increase the sample of intermediate to high redshift clusters (z > 0.5) by an order of magnitude. From this catalog, we will study the evolution of cluster number counts, luminosity function, scaling relations, and eventually the mass function. For example, various smaller scale surveys concluded divergently on the evolution of a key scaling relation, between temperature and luminosity of clusters. With the statistical power from this large sample, we will resolve the debate whether clusters evolve self-similarly. This is a crucial step in mapping cluster evolution and constraining cosmological models. First, we propose to extract the complete serendipitous extended source list for all Swift-XRT data to 2015. Second, we will use optical/IR observations to further identify galaxy clusters. These optical/IR observations include data from the SDSS, WISE, and deep optical follow-up observations from the APO, MDM, Magellan, and NOAO telescopes. WISE will confirm all z0.5 clusters. We will use ground-based observations to measure redshifts for z>0.5 clusters, with a focus of measuring 1/10 of the spectroscopic redshifts of z>0.5 clusters within the budget period. Third, we will analyze our deep Suzaku Xray follow-up observations of a sample of medium redshift clusters, and the 1/10 bright Swift clusters suitable for spectral analysis. We will also perform stacking analysis using the Swift data for clusters in different redshift bins to constrain the evolution of cluster properties.

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

Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps ofmore » X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.« less

Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering.

PubMed

Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray

2004-01-01

One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.

THE CLUSTERING CHARACTERISTICS OF H I-SELECTED GALAXIES FROM THE 40% ALFALFA SURVEY

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

Martin, Ann M.; Giovanelli, Riccardo; Haynes, Martha P.

The 40% Arecibo Legacy Fast ALFA survey catalog ({alpha}.40) of {approx}10,150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the real-space correlation function and model it as a power law, {xi}(r) = (r/r{sub 0}){sup -{gamma}}, on scales <10 h{sup -1} Mpc. As the largest sample of blindly H I-selected galaxies to date, {alpha}.40 provides detailed understanding of the clustering of this population. We find {gamma} = 1.51 {+-} 0.09 and r{sub 0} = 3.3 + 0.3, -0.2more » h{sup -1} Mpc, reinforcing the understanding that gas-rich galaxies represent the most weakly clustered galaxy population known; we also observe a departure from a pure power-law shape at intermediate scales, as predicted in {Lambda}CDM halo occupation distribution models. Furthermore, we measure the bias parameter for the {alpha}.40 galaxy sample and find that H I galaxies are severely antibiased on small scales, but only weakly antibiased on large scales. The robust measurement of the correlation function for gas-rich galaxies obtained via the {alpha}.40 sample constrains models of the distribution of H I in simulated galaxies, and will be employed to better understand the role of gas in environmentally dependent galaxy evolution.« less

The two-point correlation function for groups of galaxies in the Center for Astrophysics redshift survey

NASA Technical Reports Server (NTRS)

Ramella, Massimo; Geller, Margaret J.; Huchra, John P.

1990-01-01

The large-scale distribution of groups of galaxies selected from complete slices of the CfA redshift survey extension is examined. The survey is used to reexamine the contribution of group members to the galaxy correlation function. The relationship between the correlation function for groups and those calculated for rich clusters is discussed, and the results for groups are examined as an extension of the relation between correlation function amplitude and richness. The group correlation function indicates that groups and individual galaxies are equivalent tracers of the large-scale matter distribution. The distribution of group centers is equivalent to random sampling of the galaxy distribution. The amplitude of the correlation function for groups is consistent with an extrapolation of the amplitude-richness relation for clusters. The amplitude scaled by the mean intersystem separation is also consistent with results for richer clusters.

Interaction of size-selected gold nanoclusters with dopamine

NASA Astrophysics Data System (ADS)

Montone, Georgia R.; Hermann, Eric; Kandalam, Anil K.

2016-12-01

We present density functional theory based results on the interaction of size-selected gold nanoclusters, Au10 and Au20, with dopamine molecule. The gold clusters interact strongly with the nitrogen site of dopamine, thereby forming stable gold-dopamine complexes. Our calculations further show that there is no site specificity on the planar Au10 cluster with all the edge gold atoms equally preferred. On the other hand, in the pyramidal Au20 cluster, the vertex metal atom is the most active site. As the size increased from Au10 to Au20, the interaction strength has shown a declining trend. The effect of aqueous environment on the interaction strengths were also studied by solvation model. It is found that the presence of solvent water stabilizes the interaction between the metal cluster and dopamine molecule, even though for Au10 cluster the energy ordering of the isomers changed from that of the gas-phase.

Studies of the evolution of the x ray emission of clusters of galaxies

NASA Technical Reports Server (NTRS)

Henry, J. Patrick

1990-01-01

The x ray luminosity function of clusters of galaxies was determined at different cosmic epoches using data from the Einstein Observatory Extended Medium Survey. The sample consisted of 67 x ray selected clusters that were grouped into three redshift shells. Evolution was detected in the x ray properties of clusters. The present volume density of high luminosity clusters was found to be greater than it was in the past. This result is the first convincing evidence for evolution in the x ray properties of clusters. Investigations into the constraints provided by these data on various Cold Dark Matter models are underway.

The Cluster-EAGLE project: velocity bias and the velocity dispersion-mass relation of cluster galaxies

NASA Astrophysics Data System (ADS)

Armitage, Thomas J.; Barnes, David J.; Kay, Scott T.; Bahé, Yannick M.; Dalla Vecchia, Claudio; Crain, Robert A.; Theuns, Tom

2018-03-01

We use the Cluster-EAGLE simulations to explore the velocity bias introduced when using galaxies, rather than dark matter particles, to estimate the velocity dispersion of a galaxy cluster, a property known to be tightly correlated with cluster mass. The simulations consist of 30 clusters spanning a mass range 14.0 ≤ log10(M200 c/M⊙) ≤ 15.4, with their sophisticated subgrid physics modelling and high numerical resolution (subkpc gravitational softening), making them ideal for this purpose. We find that selecting galaxies by their total mass results in a velocity dispersion that is 5-10 per cent higher than the dark matter particles. However, selecting galaxies by their stellar mass results in an almost unbiased (<5 per cent) estimator of the velocity dispersion. This result holds out to z = 1.5 and is relatively insensitive to the choice of cluster aperture, varying by less than 5 per cent between r500 c and r200 m. We show that the velocity bias is a function of the time spent by a galaxy inside the cluster environment. Selecting galaxies by their total mass results in a larger bias because a larger fraction of objects have only recently entered the cluster and these have a velocity bias above unity. Galaxies that entered more than 4 Gyr ago become progressively colder with time, as expected from dynamical friction. We conclude that velocity bias should not be a major issue when estimating cluster masses from kinematic methods.

Size-selective reactivity of subnanometer Ag 4 and Ag 16 clusters on a TiO 2 surface

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

Chen, Po-Tuan; Tyo, Eric C.; Hayashi, Michitoshi

Size-selected Ag 4 and Ag 16 clusters on a titania surface have been studied for their potential in CO oxidation using theoretical calculations and X-ray absorption near edge spectroscopy. The first peak at the measured Ag K-edge of Ag 16@TiO 2 is more prominent in air than in carbon monoxide environment, but no variation was found between the spectra of Ag 4@TiO 2 in air and in carbon monoxide environments. Density functional theory calculations show a preference for molecular oxygen adsorption for Ag 4@TiO 2 and that for a dissociative one on Ag 16@TiO 2, while carbon monoxide reactions withmore » adsorbed oxygen reduced the Ag 16@TiO 2 cluster. The dissociated oxygen atoms increased the oxidation state of Ag 16 cluster and resulted in the prominent first peak in Ag K-edge spectrum in quasi-particle theory calculations, with the subsequent carbon monoxide oxidation reversing the character of Ag K-edge spectrum associated with the reduction of the cluster. Finally, the results provide insight into the size selectivity of supported subnanometer silver clusters in their interactions with oxygen and carbon monoxide, with implications on the cluster catalytic properties in oxidative reactions.« less

Size-selective reactivity of subnanometer Ag 4 and Ag 16 clusters on a TiO 2 surface

DOE PAGES

Chen, Po-Tuan; Tyo, Eric C.; Hayashi, Michitoshi; ...

2017-03-08

Size-selected Ag 4 and Ag 16 clusters on a titania surface have been studied for their potential in CO oxidation using theoretical calculations and X-ray absorption near edge spectroscopy. The first peak at the measured Ag K-edge of Ag 16@TiO 2 is more prominent in air than in carbon monoxide environment, but no variation was found between the spectra of Ag 4@TiO 2 in air and in carbon monoxide environments. Density functional theory calculations show a preference for molecular oxygen adsorption for Ag 4@TiO 2 and that for a dissociative one on Ag 16@TiO 2, while carbon monoxide reactions withmore » adsorbed oxygen reduced the Ag 16@TiO 2 cluster. The dissociated oxygen atoms increased the oxidation state of Ag 16 cluster and resulted in the prominent first peak in Ag K-edge spectrum in quasi-particle theory calculations, with the subsequent carbon monoxide oxidation reversing the character of Ag K-edge spectrum associated with the reduction of the cluster. Finally, the results provide insight into the size selectivity of supported subnanometer silver clusters in their interactions with oxygen and carbon monoxide, with implications on the cluster catalytic properties in oxidative reactions.« less

Higher order correlations of IRAS galaxies

NASA Technical Reports Server (NTRS)

Meiksin, Avery; Szapudi, Istvan; Szalay, Alexander

1992-01-01

The higher order irreducible angular correlation functions are derived up to the eight-point function, for a sample of 4654 IRAS galaxies, flux-limited at 1.2 Jy in the 60 microns band. The correlations are generally found to be somewhat weaker than those for the optically selected galaxies, consistent with the visual impression of looser clusters in the IRAS sample. It is found that the N-point correlation functions can be expressed as the symmetric sum of products of N - 1 two-point functions, although the correlations above the four-point function are consistent with zero. The coefficients are consistent with the hierarchical clustering scenario as modeled by Hamilton and by Schaeffer.

The Clustering of High-redshift (2.9 ≤ z ≤ 5.1) Quasars in SDSS Stripe 82

NASA Astrophysics Data System (ADS)

Timlin, John D.; Ross, Nicholas P.; Richards, Gordon T.; Myers, Adam D.; Pellegrino, Andrew; Bauer, Franz E.; Lacy, Mark; Schneider, Donald P.; Wollack, Edward J.; Zakamska, Nadia L.

2018-05-01

We present a measurement of the two-point autocorrelation function of photometrically selected high-z quasars over ∼100 deg2 on the Sloan Digital Sky Survey Stripe 82 field. Selection is performed using three machine-learning algorithms in a six-dimensional optical/mid-infrared color space. Optical data from the Sloan Digital Sky Survey are combined with overlapping deep mid-infrared data from the Spitzer IRAC Equatorial Survey and the Spitzer-HETDEX Exploratory Large-Area survey. Our selection algorithms are trained on the colors of known high-z quasars. The selected quasar sample consists of 1378 objects and contains both spectroscopically confirmed quasars and photometrically selected quasar candidates. These objects span a redshift range of 2.9 ≤ z ≤ 5.1 and are generally fainter than i = 20.2, a regime that has lacked sufficient number density to perform autocorrelation function measurements of photometrically classified quasars. We compute the angular correlation function of these data, marginally detecting quasar clustering. We fit a single power law with an index of δ = 1.39 ± 0.618 and amplitude of θ 0 = 0.‧71 ± 0.‧546 . A dark matter model is fit to the angular correlation function to estimate the linear bias. At the average redshift of our survey (< z> =3.38), the bias is b = 6.78 ± 1.79. Using this bias, we calculate a characteristic dark matter halo mass of 1.70–9.83× {10}12{h}-1 {M}ȯ . Our bias estimate suggests that quasar feedback intermittently shuts down the accretion of gas onto the central supermassive black hole at early times. If confirmed, these results hint at a level of luminosity dependence in the clustering of quasars at high-z.

The X-CLASS-redMaPPer galaxy cluster comparison. I. Identification procedures

NASA Astrophysics Data System (ADS)

Sadibekova, T.; Pierre, M.; Clerc, N.; Faccioli, L.; Gastaud, R.; Le Fevre, J.-P.; Rozo, E.; Rykoff, E.

2014-11-01

Context. This paper is the first in a series undertaking a comprehensive correlation analysis between optically selected and X-ray-selected cluster catalogues. The rationale of the project is to develop a holistic picture of galaxy clusters utilising optical and X-ray-cluster-selected catalogues with well-understood selection functions. Aims: Unlike most of the X-ray/optical cluster correlations to date, the present paper focuses on the non-matching objects in either waveband. We investigate how the differences observed between the optical and X-ray catalogues may stem from (1) a shortcoming of the detection algorithms; (2) dispersion in the X-ray/optical scaling relations; or (3) substantial intrinsic differences between the cluster populations probed in the X-ray and optical bands. The aim is to inventory and elucidate these effects in order to account for selection biases in the further determination of X-ray/optical cluster scaling relations. Methods: We correlated the X-CLASS serendipitous cluster catalogue extracted from the XMM archive with the redMaPPer optical cluster catalogue derived from the Sloan Digital Sky Survey (DR8). We performed a detailed and, in large part, interactive analysis of the matching output from the correlation. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters, respectively. X-ray cluster matching rates were analysed as a function of optical richness. In the second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10-15 erg s-1 cm-2 in the [0.5-2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Results: We find that all rich (λ ≥ 80) clusters are detected in X-rays out to z = 0.6. Below this redshift, the richness threshold for X-ray detection steadily decreases with redshift. Likewise, all X-ray bright clusters are detected by redMaPPer. After correcting for obvious pipeline shortcomings (about 10% of the cases both in optical and X-ray), ~50% of the redMaPPer (down to a richness of 20) are found to coincide with an X-CLASS cluster; when considering X-ray sources of any type, this fraction increases to ~80%; for the remaining objects, the stacking analysis finds a weak signal within 0.5 Mpc around the cluster optical centres. The fraction of clusters totally dominated by AGN-type emission appears to be a few percent. Conversely, ~40% of the X-CLASS clusters are identified with a redMaPPer (down to a richness of 20) - part of the non-matches being due to the X-CLASS sample extending further out than redMaPPer (z< 1.5 vs. z< 0.6), but extending the correlation down to a richness of 5 raises the matching rate to ~65%. Conclusions: This state-of-the-art study involving two well-validated cluster catalogues has shown itself to be complex, and it points to a number of issues inherent to blind cross-matching, owing both to pipeline shortcomings and cluster peculiar properties. These can only been accounted for after a manual check. The combined X-ray and optical scaling relations will be presented in a subsequent article.

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.

Evidence against the selfish operon theory.

PubMed

Pál, Csaba; Hurst, Laurence D

2004-06-01

According to the selfish operon hypothesis, the clustering of genes and their subsequent organization into operons is beneficial for the constituent genes because it enables the horizontal gene transfer of weakly selected, functionally coupled genes. The majority of these are expected to be non-essential genes. From our analysis of the Escherichia coli genome, we conclude that the selfish operon hypothesis is unlikely to provide a general explanation for clustering nor can it account for the gene composition of operons. Contrary to expectations, essential genes with related functions have an especially strong tendency to cluster, even if they are not in operons. Moreover, essential genes are particularly abundant in operons.

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

Coverage Dependent Charge Reduction of Cationic Gold Clusters on Surfaces Prepared Using Soft Landing of Mass-selected Ions

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

Johnson, Grant E.; Priest, Thomas A.; Laskin, Julia

2012-11-29

The ionic charge state of monodisperse cationic gold clusters on surfaces may be controlled by selecting the coverage of mass-selected ions soft landed onto a substrate. Polydisperse diphosphine-capped gold clusters were synthesized in solution by reduction of chloro(triphenylphosphine)gold(I) with borane tert-butylamine in the presence of 1,3-bis(diphenylphosphino)propane. The polydisperse gold clusters were introduced into the gas phase by electrospray ionization and mass selection was employed to select a multiply charged cationic cluster species (Au11L53+, m/z = 1409, L = 1,3-bis(diphenylphosphino)propane) which was delivered to the surfaces of four different self-assembled monolayers on gold (SAMs) at coverages of 1011 and 1012 clusters/mm2.more » Employing the spatial profiling capabilities of in-situ time-of-flight secondary ion mass spectrometry (TOF-SIMS) it is shown that, in addition to the chemical functionality of the monolayer (as demonstrated previously: ACS Nano, 2012, 6, 573) the coverage of cationic gold clusters on the surface may be used to control the distribution of ionic charge states of the soft-landed multiply charged clusters. In the case of a 1H,1H,2H,2H-perfluorodecanethiol SAM (FSAM) almost complete retention of charge by the deposited Au11L53+ clusters was observed at a lower coverage of 1011 clusters/mm2. In contrast, at a higher coverage of 1012 clusters/mm2, pronounced reduction of charge to Au11L52+ and Au11L5+ was observed on the FSAM. When soft landed onto 16- and 11-mercaptohexadecanoic acid surfaces on gold (16,11-COOH-SAMs), the mass-selected Au11L53+ clusters exhibited partial reduction of charge to Au11L52+ at lower coverage and additional reduction of charge to both Au11L52+ and Au11L5+ at higher coverage. The reduction of charge was found to be more pronounced on the surface of the shorter (thinner) C11 than the longer (thicker) C16-COOH-SAM. On the surface of the 1-dodecanethiol (HSAM) monolayer, the most abundant charge state was found to be Au11L52+ at lower coverage and Au11L5+ at higher coverage, respectively. A coverage-dependent electron tunneling mechanism is proposed to account for the observed reduction of charge of mass-selected multiply charged gold clusters soft landed on SAMs. The results demonstrate that one of the critical parameters that influence the chemical and physical properties of supported metal clusters, ionic charge state, may be controlled by selecting the coverage of charged species soft landed onto surfaces.« less

Observing the clustering properties of galaxy clusters in dynamical dark-energy cosmologies

NASA Astrophysics Data System (ADS)

Fedeli, C.; Moscardini, L.; Bartelmann, M.

2009-06-01

We study the clustering properties of galaxy clusters expected to be observed by various forthcoming surveys both in the X-ray and sub-mm regimes by the thermal Sunyaev-Zel'dovich effect. Several different background cosmological models are assumed, including the concordance ΛCDM and various cosmologies with dynamical evolution of the dark energy. Particular attention is paid to models with a significant contribution of dark energy at early times which affects the process of structure formation. Past light cone and selection effects in cluster catalogs are carefully modeled by realistic scaling relations between cluster mass and observables and by properly taking into account the selection functions of the different instruments. The results show that early dark-energy models are expected to produce significantly lower values of effective bias and both spatial and angular correlation amplitudes with respect to the standard ΛCDM model. Among the cluster catalogs studied in this work, it turns out that those based on eRosita, Planck, and South Pole Telescope observations are the most promising for distinguishing between various dark-energy models.

Clustering of galaxies near damped Lyman-alpha systems with (z) = 2.6

NASA Technical Reports Server (NTRS)

Wolfe, A. M

1993-01-01

The galaxy two-point correlation function, xi, at (z) = 2.6 is determined by comparing the number of Ly-alpha-emitting galaxies in narrowband CCD fields selected for the presence of damped L-alpha absorption to their number in randomly selected control fields. Comparisons between the presented determination of (xi), a density-weighted volume average of xi, and model predictions for (xi) at large redshifts show that models in which the clustering pattern is fixed in proper coordinates are highly unlikely, while better agreement is obtained if the clustering pattern is fixed in comoving coordinates. Therefore, clustering of Ly-alpha-emitting galaxies around damped Ly-alpha systems at large redshifts is strong. It is concluded that the faint blue galaxies are drawn from a parent population different from normal galaxies, the presumed offspring of damped Ly-alpha systems.

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

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.

High–frequency cluster radio galaxies: Luminosity functions and implications for SZE–selected cluster samples

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

Gupta, Nikhel; Saro, A.; Mohr, J. J.

We study the overdensity of point sources in the direction of X-ray-selected galaxy clusters from the meta-catalogue of X-ray-detected clusters of galaxies (MCXC; < z > = 0.14) at South Pole Telescope (SPT) and Sydney University Molonglo Sky Survey (SUMSS) frequencies. Flux densities at 95, 150 and 220 GHz are extracted from the 2500 deg 2 SPT-SZ survey maps at the locations of SUMSS sources, producing a multifrequency catalogue of radio galaxies. In the direction of massive galaxy clusters, the radio galaxy flux densities at 95 and 150 GHz are biased low by the cluster Sunyaev–Zel’dovich Effect (SZE) signal, whichmore » is negative at these frequencies. We employ a cluster SZE model to remove the expected flux bias and then study these corrected source catalogues. We find that the high-frequency radio galaxies are centrally concentrated within the clusters and that their luminosity functions (LFs) exhibit amplitudes that are characteristically an order of magnitude lower than the cluster LF at 843 MHz. We use the 150 GHz LF to estimate the impact of cluster radio galaxies on an SPT-SZ like survey. The radio galaxy flux typically produces a small bias on the SZE signal and has negligible impact on the observed scatter in the SZE mass–observable relation. If we assume there is no redshift evolution in the radio galaxy LF then 1.8 ± 0.7 per cent of the clusters with detection significance ξ ≥ 4.5 would be lost from the sample. As a result, allowing for redshift evolution of the form (1 + z) 2.5 increases the incompleteness to 5.6 ± 1.0 per cent. Improved constraints on the evolution of the cluster radio galaxy LF require a larger cluster sample extending to higher redshift.« less

High–frequency cluster radio galaxies: Luminosity functions and implications for SZE–selected cluster samples

DOE PAGES

Gupta, Nikhel; Saro, A.; Mohr, J. J.; ...

2017-01-15

We study the overdensity of point sources in the direction of X-ray-selected galaxy clusters from the meta-catalogue of X-ray-detected clusters of galaxies (MCXC; < z > = 0.14) at South Pole Telescope (SPT) and Sydney University Molonglo Sky Survey (SUMSS) frequencies. Flux densities at 95, 150 and 220 GHz are extracted from the 2500 deg 2 SPT-SZ survey maps at the locations of SUMSS sources, producing a multifrequency catalogue of radio galaxies. In the direction of massive galaxy clusters, the radio galaxy flux densities at 95 and 150 GHz are biased low by the cluster Sunyaev–Zel’dovich Effect (SZE) signal, whichmore » is negative at these frequencies. We employ a cluster SZE model to remove the expected flux bias and then study these corrected source catalogues. We find that the high-frequency radio galaxies are centrally concentrated within the clusters and that their luminosity functions (LFs) exhibit amplitudes that are characteristically an order of magnitude lower than the cluster LF at 843 MHz. We use the 150 GHz LF to estimate the impact of cluster radio galaxies on an SPT-SZ like survey. The radio galaxy flux typically produces a small bias on the SZE signal and has negligible impact on the observed scatter in the SZE mass–observable relation. If we assume there is no redshift evolution in the radio galaxy LF then 1.8 ± 0.7 per cent of the clusters with detection significance ξ ≥ 4.5 would be lost from the sample. As a result, allowing for redshift evolution of the form (1 + z) 2.5 increases the incompleteness to 5.6 ± 1.0 per cent. Improved constraints on the evolution of the cluster radio galaxy LF require a larger cluster sample extending to higher redshift.« less

Constraints on the Energy Density Content of the Universe Using Only Clusters of Galaxies

NASA Technical Reports Server (NTRS)

Molnar, Sandor M.; Haiman, Zoltan; Birkinshaw, Mark

2003-01-01

We demonstrate that it is possible to constrain the energy content of the Universe with high accuracy using observations of clusters of galaxies only. The degeneracies in the cosmological parameters are lifted by combining constraints from different observables of galaxy clusters. We show that constraints on cosmological parameters from galaxy cluster number counts as a function of redshift and accurate angular diameter distance measurements to clusters are complementary to each other and their combination can constrain the energy density content of the Universe well. The number counts can be obtained from X-ray and/or SZ (Sunyaev-Zeldovich effect) surveys, the angular diameter distances can be determined from deep observations of the intra-cluster gas using their thermal bremsstrahlung X-ray emission and the SZ effect (X-SZ method). In this letter we combine constraints from simulated cluster number counts expected from a 12 deg2 SZ cluster survey and constraints from simulated angular diameter distance measurements based on using the X-SZ method assuming an expected accuracy of 7% in the angular diameter distance determination of 70 clusters with redshifts less than 1.5. We find that R, can be determined within about 25%, A within 20%, and w within 16%. Any cluster survey can be used to select clusters for high accuracy distance measurements, but we assumed accurate angular diameter distance measurements for only 70 clusters since long observations are necessary to achieve high accuracy in distance measurements. Thus the question naturally arises: How to select clusters of galaxies for accurate diameter distance determinations? In this letter, as an example, we demonstrate that it is possible to optimize this selection changing the number of clusters observed, and the upper cut off of their redshift range. We show that constraints on cosmological parameters from combining cluster number counts and angular diameter distance measurements, as opposed to general expectations, will not improve substantially selecting clusters with redshifts higher than one. This important conclusion allow us to restrict our cluster sample to clusters closer than one, in a range where the observational time for accurate distance measurements are more manageable. Subject headings: cosmological parameters - cosmology: theory - galaxies: clusters: general - X-rays: galaxies: clusters

Selective binding and lateral clustering of α5β1 and αvβ3 integrins: Unraveling the spatial requirements for cell spreading and focal adhesion assembly

PubMed Central

Schaufler, Viktoria; Czichos-Medda, Helmi; Hirschfeld-Warnecken, Vera; Neubauer, Stefanie; Rechenmacher, Florian; Medda, Rebecca; Kessler, Horst; Geiger, Benjamin; Spatz, Joachim P.; Cavalcanti-Adam, E. Ada

2016-01-01

ABSTRACT Coordination of the specific functions of α5β1 and αvβ3 integrins is crucial for the precise regulation of cell adhesion, spreading and migration, yet the contribution of differential integrin-specific crosstalk to these processes remains unclear. To determine the specific functions of αvβ3 and α5β1 integrins, we used nanoarrays of gold particles presenting immobilized, integrin-selective peptidomimetic ligands. Integrin binding to the peptidomimetics is highly selective, and cells can spread on both ligands. However, spreading is faster and the projected cell area is greater on α5β1 ligand; both depend on ligand spacing. Quantitative analysis of adhesion plaques shows that focal adhesion size is increased in cells adhering to αvβ3 ligand at 30 and 60 nm spacings. Analysis of αvβ3 and α5β1 integrin clusters indicates that fibrillar adhesions are more prominent in cells adhering to α5β1 ligand, while clusters are mostly localized at the cell margins in cells adhering to αvβ3 ligand. αvβ3 integrin clusters are more pronounced on αvβ3 ligand, though they can also be detected in cells adhering to α5β1 ligand. Furthermore, α5β1 integrin clusters are present in cells adhering to α5β1 ligand, and often colocalize with αvβ3 clusters. Taken together, these findings indicate that the activation of αvβ3 integrin by ligand binding is dispensable for initial adhesion and spreading, but essential to formation of stable focal adhesions. PMID:27003228

The Correlation Function of Galaxy Clusters and Detection of Baryon Acoustic Oscillations

NASA Astrophysics Data System (ADS)

Hong, T.; Han, J. L.; Wen, Z. L.; Sun, L.; Zhan, H.

2012-04-01

We calculate the correlation function of 13,904 galaxy clusters of z <= 0.4 selected from the cluster catalog of Wen et al. The correlation function can be fitted with a power-law model ξ(r) = (r/R 0)-γ on the scales of 10 h -1 Mpc <= r <= 50 h -1 Mpc, with a larger correlation length of R 0 = 18.84 ± 0.27 h -1 Mpc for clusters with a richness of R >= 15 and a smaller length of R 0 = 16.15 ± 0.13 h -1 Mpc for clusters with a richness of R >= 5. The power-law index of γ = 2.1 is found to be almost the same for all cluster subsamples. A pronounced baryon acoustic oscillations (BAO) peak is detected at r ~ 110 h -1 Mpc with a significance of ~1.9σ. By analyzing the correlation function in the range of 20 h -1 Mpc <= r <= 200 h -1 Mpc, we find that the constraints on distance parameters are Dv (zm = 0.276) = 1077 ± 55(1σ) Mpc and h = 0.73 ± 0.039(1σ), which are consistent with the cosmology derived from Wilkinson Microwave Anisotropy Probe (WMAP) seven-year data. However, the BAO signal from the cluster sample is stronger than expected and leads to a rather low matter density Ω m h 2 = 0.093 ± 0.0077(1σ), which deviates from the WMAP7 result by more than 3σ. The correlation function of the GMBCG cluster sample is also calculated and our detection of the BAO feature is confirmed.

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Bridging single and multireference coupled cluster theories with universal state selective formalism

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

Bhaskaran-Nair, Kiran; Kowalski, Karol

2013-05-28

The universal state selective (USS) multireference approach is used to construct new energy functionals which offers a unique possibility of bridging single and multireference coupled cluster theories (SR/MRCC). These functionals, which can be used to develop iterative and non-iterative approaches, utilize a special form of the trial wavefunctions, which assure additive separability (or size-consistency) of the USS energies in the non-interacting subsystem limit. When the USS formalism is combined with approximate SRCC theories, the resulting formalism can be viewed as a size-consistent version of the method of moments of coupled cluster equations (MMCC) employing a MRCC trial wavefunction. Special casesmore » of the USS formulations, which utilize single reference state specific CC (V.V. Ivanov, D.I. Lyakh, L. Adamowicz, Phys. Chem. Chem. Phys. 11, 2355 (2009)) and tailored CC (T. Kinoshita, O. Hino, R.J. Bartlett, J. Chem. Phys. 123, 074106 (2005)) expansions are also discussed.« less

Diverse specificity and effector function among human antibodies to HIV-1 envelope glycoprotein epitopes exposed by CD4 binding

DOE PAGES

Guan, Yongjun; Pazgier, Marzena; Sajadi, Mohammad M.; ...

2012-12-13

The HIV-1 envelope glycoprotein (Env) undergoes conformational transitions consequent to CD4 binding and coreceptor engagement during viral entry. The physical steps in this process are becoming defined, but less is known about their significance as targets of antibodies potentially protective against HIV-1 infection. Here we probe the functional significance of transitional epitope exposure by characterizing 41 human mAbs specific for epitopes exposed on trimeric Env after CD4 engagement. These mAbs recognize three epitope clusters: cluster A, the gp120 face occluded by gp41 in trimeric Env; cluster B, a region proximal to the coreceptor-binding site (CoRBS) and involving the V1/V2 domain;more » and cluster C, the coreceptor-binding site. The mAbs were evaluated functionally by antibody-dependent, cell-mediated cytotoxicity (ADCC) and for neutralization of Tiers 1 and 2 pseudoviruses. All three clusters included mAbs mediating ADCC. However, there was a strong potency bias for cluster A, which harbors at least three potent ADCC epitopes whose cognate mAbs have electropositive paratopes. Cluster A epitopes are functional ADCC targets during viral entry in an assay format using virion-sensitized target cells. In contrast, only cluster C contained epitopes that were recognized by neutralizing mAbs. There was significant diversity in breadth and potency that correlated with epitope fine specificity. In contrast, ADCC potency had no relationship with neutralization potency or breadth for any epitope cluster. In conclusion, Fc-mediated effector function and neutralization coselect with specificity in anti-Env antibody responses, but the nature of selection is distinct for these two antiviral activities.« less

Secure and Fair Cluster Head Selection Protocol for Enhancing Security in Mobile Ad Hoc Networks

PubMed Central

Paramasivan, B.; Kaliappan, M.

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP. PMID:25143986

Secure and fair cluster head selection protocol for enhancing security in mobile ad hoc networks.

PubMed

Paramasivan, B; Kaliappan, M

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP.

A Globular Cluster Luminosity Function Distance to NGC 4993 Hosting a Binary Neutron Star Merger GW170817/GRB 170817A

NASA Astrophysics Data System (ADS)

Lee, Myung Gyoon; Kang, Jisu; Im, Myungshin

2018-05-01

NGC 4993 hosts a binary neutron star merger, GW170817/GRB 170817A, emitting gravitational waves and electromagnetic waves. The distance to this galaxy is not well established. We select the globular cluster candidates from the Hubble Space Telescope (HST)/ACS F606W images of NGC 4993 in the archive, using the structural parameters of the detected sources. The radial number density distribution of these candidates shows a significant central concentration around the galaxy center at the galactocentric distance r < 50″, showing that they are mostly the members of NGC 4993. Also, the luminosity function of these candidates is fit well by a Gaussian function. Therefore, the selected candidates at r < 50″ are mostly considered to be globular clusters in NGC 4993. We derive an extinction-corrected turnover Vega magnitude in the luminosity function of the globular clusters at 20″ < r < 50″, F606W (max)0 = 25.36 ± 0.08 (V 0 = 25.52 ± 0.11) mag. Adopting the calibration of the turnover magnitudes of the globular clusters, M V (max) = ‑7.58 ± 0.11, we derive a distance to NGC 4993, d = 41.65 ± 3.00 Mpc ({(m-M)}0 = 33.10+/- 0.16). The systematic error of this method can be as large as ±0.3 mag. This value is consistent with the previous distance estimates based on the fundamental plane relation and the gravitational wave method in the literature. The distance in this study can be used to constrain the values of the parameters including the inclination angle of the binary system in the models of gravitational wave analysis.

A two-step initial mass function:. Consequences of clustered star formation for binary properties

NASA Astrophysics Data System (ADS)

Durisen, R. H.; Sterzik, M. F.; Pickett, B. K.

2001-06-01

If stars originate in transient bound clusters of moderate size, these clusters will decay due to dynamic interactions in which a hard binary forms and ejects most or all the other stars. When the cluster members are chosen at random from a reasonable initial mass function (IMF), the resulting binary characteristics do not match current observations. We find a significant improvement in the trends of binary properties from this scenario when an additional constraint is taken into account, namely that there is a distribution of total cluster masses set by the masses of the cloud cores from which the clusters form. Two distinct steps then determine final stellar masses - the choice of a cluster mass and the formation of the individual stars. We refer to this as a ``two-step'' IMF. Simple statistical arguments are used in this paper to show that a two-step IMF, combined with typical results from dynamic few-body system decay, tends to give better agreement between computed binary characteristics and observations than a one-step mass selection process.

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: modelling the clustering and halo occupation distribution of BOSS CMASS galaxies in the Final Data Release

NASA Astrophysics Data System (ADS)

Rodríguez-Torres, Sergio A.; Chuang, Chia-Hsun; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Behroozi, Peter; Hahn, Chang Hoon; Comparat, Johan; Yepes, Gustavo; Montero-Dorta, Antonio D.; Brownstein, Joel R.; Maraston, Claudia; McBride, Cameron K.; Tinker, Jeremy; Gottlöber, Stefan; Favole, Ginevra; Shu, Yiping; Kitaura, Francisco-Shu; Bolton, Adam; Scoccimarro, Román; Samushia, Lado; Schlegel, David; Schneider, Donald P.; Thomas, Daniel

2016-08-01

We present a study of the clustering and halo occupation distribution of Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies in the redshift range 0.43 < z < 0.7 drawn from the Final SDSS-III Data Release. We compare the BOSS results with the predictions of a halo abundance matching (HAM) clustering model that assigns galaxies to dark matter haloes selected from the large BigMultiDark N-body simulation of a flat Λ cold dark matter Planck cosmology. We compare the observational data with the simulated ones on a light cone constructed from 20 subsequent outputs of the simulation. Observational effects such as incompleteness, geometry, veto masks and fibre collisions are included in the model, which reproduces within 1σ errors the observed monopole of the two-point correlation function at all relevant scales: from the smallest scales, 0.5 h-1 Mpc, up to scales beyond the baryon acoustic oscillation feature. This model also agrees remarkably well with the BOSS galaxy power spectrum (up to k ˜ 1 h Mpc-1), and the three-point correlation function. The quadrupole of the correlation function presents some tensions with observations. We discuss possible causes that can explain this disagreement, including target selection effects. Overall, the standard HAM model describes remarkably well the clustering statistics of the CMASS sample. We compare the stellar-to-halo mass relation for the CMASS sample measured using weak lensing in the Canada-France-Hawaii Telescope Stripe 82 Survey with the prediction of our clustering model, and find a good agreement within 1σ. The BigMD-BOSS light cone including properties of BOSS galaxies and halo properties is made publicly available.

Cluster cosmology with next-generation surveys.

NASA Astrophysics Data System (ADS)

Ascaso, B.

2017-03-01

The advent of next-generation surveys will provide a large number of cluster detections that will serve the basis for constraining cos mological parameters using cluster counts. The main two observational ingredients needed are the cluster selection function and the calibration of the mass-observable relation. In this talk, we present the methodology designed to obtain robust predictions of both ingredients based on realistic cosmological simulations mimicking the following next-generation surveys: J-PAS, LSST and Euclid. We display recent results on the selection functions for these mentioned surveys together with others coming from other next-generation surveys such as eROSITA, ACTpol and SPTpol. We notice that the optical and IR surveys will reach the lowest masses between 0.3

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

PubMed

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

An improved method to detect correct protein folds using partial clustering.

PubMed

Zhou, Jianjun; Wishart, David S

2013-01-16

Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient "partial" clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either C(α) RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance.

An improved method to detect correct protein folds using partial clustering

PubMed Central

2013-01-01

Background Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient “partial“ clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. Results We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either Cα RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. Conclusions The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance. PMID:23323835

Rapid diversification of FoxP2 in teleosts through gene duplication in the teleost-specific whole genome duplication event.

PubMed

Song, Xiaowei; Wang, Yajun; Tang, Yezhong

2013-01-01

As one of the most conserved genes in vertebrates, FoxP2 is widely involved in a number of important physiological and developmental processes. We systematically studied the evolutionary history and functional adaptations of FoxP2 in teleosts. The duplicated FoxP2 genes (FoxP2a and FoxP2b), which were identified in teleosts using synteny and paralogon analysis on genome databases of eight organisms, were probably generated in the teleost-specific whole genome duplication event. A credible classification with FoxP2, FoxP2a and FoxP2b in phylogenetic reconstructions confirmed the teleost-specific FoxP2 duplication. The unavailability of FoxP2b in Danio rerio suggests that the gene was deleted through nonfunctionalization of the redundant copy after the Otocephala-Euteleostei split. Heterogeneity in evolutionary rates among clusters consisting of FoxP2 in Sarcopterygii (Cluster 1), FoxP2a in Teleostei (Cluster 2) and FoxP2b in Teleostei (Cluster 3), particularly between Clusters 2 and 3, reveals asymmetric functional divergence after the gene duplication. Hierarchical cluster analyses of hydrophobicity profiles demonstrated significant structural divergence among the three clusters with verification of subsequent stepwise discriminant analysis, in which FoxP2 of Leucoraja erinacea and Lepisosteus oculatus were classified into Cluster 1, whereas FoxP2b of Salmo salar was grouped into Cluster 2 rather than Cluster 3. The simulated thermodynamic stability variations of the forkhead box domain (monomer and homodimer) showed remarkable divergence in FoxP2, FoxP2a and FoxP2b clusters. Relaxed purifying selection and positive Darwinian selection probably were complementary driving forces for the accelerated evolution of FoxP2 in ray-finned fishes, especially for the adaptive evolution of FoxP2a and FoxP2b in teleosts subsequent to the teleost-specific gene duplication.

Rapid Diversification of FoxP2 in Teleosts through Gene Duplication in the Teleost-Specific Whole Genome Duplication Event

PubMed Central

Song, Xiaowei; Wang, Yajun; Tang, Yezhong

2013-01-01

As one of the most conserved genes in vertebrates, FoxP2 is widely involved in a number of important physiological and developmental processes. We systematically studied the evolutionary history and functional adaptations of FoxP2 in teleosts. The duplicated FoxP2 genes (FoxP2a and FoxP2b), which were identified in teleosts using synteny and paralogon analysis on genome databases of eight organisms, were probably generated in the teleost-specific whole genome duplication event. A credible classification with FoxP2, FoxP2a and FoxP2b in phylogenetic reconstructions confirmed the teleost-specific FoxP2 duplication. The unavailability of FoxP2b in Danio rerio suggests that the gene was deleted through nonfunctionalization of the redundant copy after the Otocephala-Euteleostei split. Heterogeneity in evolutionary rates among clusters consisting of FoxP2 in Sarcopterygii (Cluster 1), FoxP2a in Teleostei (Cluster 2) and FoxP2b in Teleostei (Cluster 3), particularly between Clusters 2 and 3, reveals asymmetric functional divergence after the gene duplication. Hierarchical cluster analyses of hydrophobicity profiles demonstrated significant structural divergence among the three clusters with verification of subsequent stepwise discriminant analysis, in which FoxP2 of Leucoraja erinacea and Lepisosteus oculatus were classified into Cluster 1, whereas FoxP2b of Salmo salar was grouped into Cluster 2 rather than Cluster 3. The simulated thermodynamic stability variations of the forkhead box domain (monomer and homodimer) showed remarkable divergence in FoxP2, FoxP2a and FoxP2b clusters. Relaxed purifying selection and positive Darwinian selection probably were complementary driving forces for the accelerated evolution of FoxP2 in ray-finned fishes, especially for the adaptive evolution of FoxP2a and FoxP2b in teleosts subsequent to the teleost-specific gene duplication. PMID:24349554

Panoramic Views of Cluster Evolution Since z = 3

NASA Astrophysics Data System (ADS)

Kodama, Tadayuki; Tanaka, M.; Tanaka, Ichi; Kajisawa, M.

2007-05-01

We have been conducting PISCES project (Panoramic Imaging and Spectroscopy of Cluster Evolution with Subaru) with making use of the wide-field imaging capability of Subaru. Our motivations are first to map out large scale structure and local environment of galaxies therein, and then to investigate the variation in galaxy properties as a function of environment and mass. We have completed multi-colour imaging of 8 distant clusters between 0.42) by wide-field near-infrared imaging of proto-clusters around radio loud galaxies, some of which are known to show a large number of Lya/Ha emitters at the same redshift of the radio galaxies. We have seen clear excess of near-infrared selected galaxies (including DRG) around many of the radio galaxies, suggesting that these are indeed likely to be proto-clusters with not only young emitters but also evolved populations. Spatial distribution of such NIR selected galaxies is filamentary and track similar structures traced by the emitters, but showing little individual overlap. The above two wide-field studies of dense environments and their surroundings will tell us galaxy evolution during the course of cluster assembly over more than 80 per cent of the age of the Universe.

A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

PubMed Central

Wang, Zhihao; Yi, Jing

2016-01-01

For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291

Order statistics applied to the most massive and most distant galaxy clusters

NASA Astrophysics Data System (ADS)

Waizmann, J.-C.; Ettori, S.; Bartelmann, M.

2013-06-01

In this work, we present an analytic framework for calculating the individual and joint distributions of the nth most massive or nth highest redshift galaxy cluster for a given survey characteristic allowing us to formulate Λ cold dark matter (ΛCDM) exclusion criteria. We show that the cumulative distribution functions steepen with increasing order, giving them a higher constraining power with respect to the extreme value statistics. Additionally, we find that the order statistics in mass (being dominated by clusters at lower redshifts) is sensitive to the matter density and the normalization of the matter fluctuations, whereas the order statistics in redshift is particularly sensitive to the geometric evolution of the Universe. For a fixed cosmology, both order statistics are efficient probes of the functional shape of the mass function at the high-mass end. To allow a quick assessment of both order statistics, we provide fits as a function of the survey area that allow percentile estimation with an accuracy better than 2 per cent. Furthermore, we discuss the joint distributions in the two-dimensional case and find that for the combination of the largest and the second largest observation, it is most likely to find them to be realized with similar values with a broadly peaked distribution. When combining the largest observation with higher orders, it is more likely to find a larger gap between the observations and when combining higher orders in general, the joint probability density function peaks more strongly. Having introduced the theory, we apply the order statistical analysis to the Southpole Telescope (SPT) massive cluster sample and metacatalogue of X-ray detected clusters of galaxies catalogue and find that the 10 most massive clusters in the sample are consistent with ΛCDM and the Tinker mass function. For the order statistics in redshift, we find a discrepancy between the data and the theoretical distributions, which could in principle indicate a deviation from the standard cosmology. However, we attribute this deviation to the uncertainty in the modelling of the SPT survey selection function. In turn, by assuming the ΛCDM reference cosmology, order statistics can also be utilized for consistency checks of the completeness of the observed sample and of the modelling of the survey selection function.

Reactions of mixed silver-gold cluster cations AgmAun+ (m+n=4,5,6) with CO: Radiative association kinetics and density functional theory computations

NASA Astrophysics Data System (ADS)

Neumaier, Marco; Weigend, Florian; Hampe, Oliver; Kappes, Manfred M.

2006-09-01

Near thermal energy reactive collisions of small mixed metal cluster cations AgmAun+ (m +n=4, 5, and 6) with carbon monoxide have been studied in the room temperature Penning trap of a Fourier transform ion-cyclotron-resonance mass spectrometer as a function of cluster size and composition. The tetrameric species AgAu3+ and Ag2Au2+ are found to react dissociatively by way of Au or Ag atom loss, respectively, to form the cluster carbonyl AgAu2CO+. In contrast, measurements on a selection of pentamers and hexamers show that CO is added with absolute rate constants that decrease with increasing silver content. Experimentally determined absolute rate constants for CO adsorption were analyzed using the radiative association kinetics model to obtain cluster cation-CO binding energies ranging from 0.77to1.09eV. High-level ab initio density functional theory (DFT) computations identifying the lowest-energy cluster isomers and the respective CO adsorption energies are in good agreement with the experimental findings clearly showing that CO binds in a "head-on" fashion to a gold atom in the mixed clusters. DFT exploration of reaction pathways in the case of Ag2Au2+ suggests that exoergicities are high enough to access the minimum energy products for all reactive clusters probed.

Low-energy collisions of helium clusters with size-selected cobalt cluster ions

NASA Astrophysics Data System (ADS)

Odaka, Hideho; Ichihashi, Masahiko

2017-04-01

Collisions of helium clusters with size-selected cobalt cluster ions, Com+ (m ≤ 5), were studied experimentally by using a merging beam technique. The product ions, Com+Hen (cluster complexes), were mass-analyzed, and this result indicates that more than 20 helium atoms can be attached onto Com+ at the relative velocities of 103 m/s. The measured size distributions of the cluster complexes indicate that there are relatively stable complexes: Co2+Hen (n = 2, 4, 6, and 12), Co3+Hen (n = 3, 6), Co4+He4, and Co5+Hen (n = 3, 6, 8, and 10). These stabilities are explained in terms of their geometric structures. The yields of the cluster complexes were also measured as a function of the relative velocity (1 × 102-4 × 103 m/s), and this result demonstrates that the main interaction in the collision process changes with the increase of the collision energy from the electrostatic interaction, which includes the induced deformation of HeN, to the hard-sphere interaction. Supplementary material in the form of one pdf file available from the Journal web page at http://https://doi.org/10.1140/epjd/e2017-80015-0

Microsolvation of the 5-hydroxyindole cation (5HI+) with nonpolar and quadrupolar ligands: Infrared photodissociation spectra of 5HI+-Ln clusters with L = Ar and N2 (n ≤ 3)

NASA Astrophysics Data System (ADS)

Klyne, Johanna; Dopfer, Otto

2017-07-01

Solvation of biomolecules and their building blocks has a strong influence on their structure and function. Herein we characterize the initial microsolvation of the 5-hydroxyindole cation (5HI+) in its 2A″ ground electronic state with nonpolar and quadrupolar ligands (L = Ar, N2) by infrared photodissociation (IRPD) spectroscopy of cold and mass-selected 5HI+-Ln (n ≤ 3) clusters in a molecular beam and dispersion-corrected density functional theory calculations (B3LYP-D3/aug-cc-pVTZ). The isomer-selective OH and NH stretch frequency shifts (ΔνOH/NH) disentangle the competition between H-bonding to the acidic OH and NH groups and π-stacking to the conjugated bicyclic aromatic π-electron system, the intermolecular interaction strengths, and the cluster growth sequence. For 5HI+-Arn, H-bonding and π-stacking strongly compete, indicating that dispersion forces are important for the interaction of 5HI+ with nonpolar ligands. In contrast, for 5HI+-(N2)n clusters, the H-bonds are much stronger than the π-bonds and largely determine the initial solvation process. In all clusters, the OH…L bonds are stronger than the NH…L bonds followed by the π-bonds. The interaction of 5HI+ with N2 is roughly twice stronger than with Ar, mainly due to the additional quadrupole moment of N2. The nature and strength of the individual interactions are quantified by the noncovalent interaction approach. Comparison of 5HI+-L with the corresponding neutral clusters reveals the strong impact of ionization on the total and relative interaction strengths of the H-bonds and π-bonds. In addition, comparison of 5HI+-L with corresponding clusters of the phenol, indole, and pyrrole radical cations illustrates the effects of substitution of functional groups and the addition of aromatic rings to the various subunits of 5HI on the intermolecular potential.

Algorithms and software used in selecting structure of machine-training cluster based on neurocomputers

NASA Astrophysics Data System (ADS)

Romanchuk, V. A.; Lukashenko, V. V.

2018-05-01

The technique of functioning of a control system by a computing cluster based on neurocomputers is proposed. Particular attention is paid to the method of choosing the structure of the computing cluster due to the fact that the existing methods are not effective because of a specialized hardware base - neurocomputers, which are highly parallel computer devices with an architecture different from the von Neumann architecture. A developed algorithm for choosing the computational structure of a cloud cluster is described, starting from the direction of data transfer in the flow control graph of the program and its adjacency matrix.

Hot and solid gallium clusters: too small to melt.

PubMed

Breaux, Gary A; Benirschke, Robert C; Sugai, Toshiki; Kinnear, Brian S; Jarrold, Martin F

2003-11-21

A novel multicollision induced dissociation scheme is employed to determine the energy content for mass-selected gallium cluster ions as a function of their temperature. Measurements were performed for Ga(+)(n) (n=17 39, and 40) over a 90-720 K temperature range. For Ga+39 and Ga+40 a broad maximum in the heat capacity-a signature of a melting transition for a small cluster-occurs at around 550 K. Thus small gallium clusters melt at substantially above the 302.9 K melting point of bulk gallium, in conflict with expectations that they will remain liquid to below 150 K. No melting transition is observed for Ga+17.

Identification of hub subnetwork based on topological features of genes in breast cancer

PubMed Central

ZHUANG, DA-YONG; JIANG, LI; HE, QING-QING; ZHOU, PENG; YUE, TAO

2015-01-01

The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer. PMID:25573623

The SAMI Galaxy Survey: the cluster redshift survey, target selection and cluster properties

NASA Astrophysics Data System (ADS)

Owers, M. S.; Allen, J. T.; Baldry, I.; Bryant, J. J.; Cecil, G. N.; Cortese, L.; Croom, S. M.; Driver, S. P.; Fogarty, L. M. R.; Green, A. W.; Helmich, E.; de Jong, J. T. A.; Kuijken, K.; Mahajan, S.; McFarland, J.; Pracy, M. B.; Robotham, A. G. S.; Sikkema, G.; Sweet, S.; Taylor, E. N.; Verdoes Kleijn, G.; Bauer, A. E.; Bland-Hawthorn, J.; Brough, S.; Colless, M.; Couch, W. J.; Davies, R. L.; Drinkwater, M. J.; Goodwin, M.; Hopkins, A. M.; Konstantopoulos, I. S.; Foster, C.; Lawrence, J. S.; Lorente, N. P. F.; Medling, A. M.; Metcalfe, N.; Richards, S. N.; van de Sande, J.; Scott, N.; Shanks, T.; Sharp, R.; Thomas, A. D.; Tonini, C.

2017-06-01

We describe the selection of galaxies targeted in eight low-redshift clusters (APMCC0917, A168, A4038, EDCC442, A3880, A2399, A119 and A85; 0.029 < z < 0.058) as part of the Sydney-AAO Multi-Object Integral field spectrograph Galaxy Survey (SAMI-GS). We have conducted a redshift survey of these clusters using the AAOmega multi-object spectrograph on the 3.9-m Anglo-Australian Telescope. The redshift survey is used to determine cluster membership and to characterize the dynamical properties of the clusters. In combination with existing data, the survey resulted in 21 257 reliable redshift measurements and 2899 confirmed cluster member galaxies. Our redshift catalogue has a high spectroscopic completeness (˜94 per cent) for rpetro ≤ 19.4 and cluster-centric distances R < 2R200. We use the confirmed cluster member positions and redshifts to determine cluster velocity dispersion, R200, virial and caustic masses, as well as cluster structure. The clusters have virial masses 14.25 ≤ log(M200/M⊙) ≤ 15.19. The cluster sample exhibits a range of dynamical states, from relatively relaxed-appearing systems, to clusters with strong indications of merger-related substructure. Aperture- and point spread function matched photometry are derived from Sloan Digital Sky Survey and VLT Survey Telescope/ATLAS imaging and used to estimate stellar masses. These estimates, in combination with the redshifts, are used to define the input target catalogue for the cluster portion of the SAMI-GS. The primary SAMI-GS cluster targets have R

On the X-ray spectrum of the volume emissivity arising from Abell clusters

NASA Technical Reports Server (NTRS)

Stottlemyer, A. R.; Boldt, E. A.

1984-01-01

HEAO 1 A-2 X-ray spectra (2-15 keV) for an optically selected sample of Abell clusters of galaxies with z less than 0.1 have been analyzed to determine the energy dependence of the cosmological X-ray volume emissivity arising from such clusters. This spectrum is well fitted by an isothermal-bremsstrahlung model with kT = 7.4 + or - 1.5 KeV. This result is a test of the isothermal-volume-emissivity spectrum to be inferred from the conjecture that all contributing clusters may be characterized by kT = 7 keV, as assumed by McKee et al. (1980) in estimating the underlying luminosity function for the same sample. Although satisfied at the statistical level indicated, the analysis of a low-luminosity subsample suggests that this assumption of identical isothermal spectra would lead to a systematic error for a more statistically precise determination of the luminosity function's form.

Simulating star clusters with the AMUSE software framework. I. Dependence of cluster lifetimes on model assumptions and cluster dissolution modes

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

Whitehead, Alfred J.; McMillan, Stephen L. W.; Vesperini, Enrico

2013-12-01

We perform a series of simulations of evolving star clusters using the Astrophysical Multipurpose Software Environment (AMUSE), a new community-based multi-physics simulation package, and compare our results to existing work. These simulations model a star cluster beginning with a King model distribution and a selection of power-law initial mass functions and contain a tidal cutoff. They are evolved using collisional stellar dynamics and include mass loss due to stellar evolution. After studying and understanding that the differences between AMUSE results and results from previous studies are understood, we explored the variation in cluster lifetimes due to the random realization noisemore » introduced by transforming a King model to specific initial conditions. This random realization noise can affect the lifetime of a simulated star cluster by up to 30%. Two modes of star cluster dissolution were identified: a mass evolution curve that contains a runaway cluster dissolution with a sudden loss of mass, and a dissolution mode that does not contain this feature. We refer to these dissolution modes as 'dynamical' and 'relaxation' dominated, respectively. For Salpeter-like initial mass functions, we determined the boundary between these two modes in terms of the dynamical and relaxation timescales.« less

Towards Tunable Consensus Clustering for Studying Functional Brain Connectivity During Affective Processing.

PubMed

Liu, Chao; Abu-Jamous, Basel; Brattico, Elvira; Nandi, Asoke K

2017-03-01

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package "UNCLES" available on http://cran.r-project.org/web/packages/UNCLES/index.html .

Distinguishing Functional DNA Words; A Method for Measuring Clustering Levels

NASA Astrophysics Data System (ADS)

Moghaddasi, Hanieh; Khalifeh, Khosrow; Darooneh, Amir Hossein

2017-01-01

Functional DNA sub-sequences and genome elements are spatially clustered through the genome just as keywords in literary texts. Therefore, some of the methods for ranking words in texts can also be used to compare different DNA sub-sequences. In analogy with the literary texts, here we claim that the distribution of distances between the successive sub-sequences (words) is q-exponential which is the distribution function in non-extensive statistical mechanics. Thus the q-parameter can be used as a measure of words clustering levels. Here, we analyzed the distribution of distances between consecutive occurrences of 16 possible dinucleotides in human chromosomes to obtain their corresponding q-parameters. We found that CG as a biologically important two-letter word concerning its methylation, has the highest clustering level. This finding shows the predicting ability of the method in biology. We also proposed that chromosome 18 with the largest value of q-parameter for promoters of genes is more sensitive to dietary and lifestyle. We extended our study to compare the genome of some selected organisms and concluded that the clustering level of CGs increases in higher evolutionary organisms compared to lower ones.

VLA observations of a complete sample of extragalactic X-ray sources. II

NASA Technical Reports Server (NTRS)

Schild, R.; Zamorani, G.; Gioia, I. M.; Feigelson, E. D.; Maccacaro, T.

1983-01-01

A complete sample of 35 X-ray selected sources found with the Einstein Observatory has been observed with the Very Large Array at 6 cm to investigate the relationship between radio and X-ray emission in extragalactic objects. Detections include three active galactic nuclei (AGNs), two clusters or groups of galaxies, two individual galaxies, and two BL Lac objects. The frequency of radio emission in X-ray selected AGNs is compared with that of optically selected quasars using the integral radio-optical luminosity function. The result suggests that the probability for X-ray selected quasars to be radio sources is higher than for those optically selected. No obvious correlation is found in the sample between the richness of X-ray luminosity of the cluster and the presence of a galaxy with radio luminosity at 5 GHz larger than 10 to the 30th ergs/s/Hz.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Matilda: A mass filtered nanocluster source

NASA Astrophysics Data System (ADS)

Kwon, Gihan

Cluster science provides a good model system for the study of the size dependence of electronic properties, chemical reactivity, as well as magnetic properties of materials. One of the main interests in cluster science is the nanoscale understanding of chemical reactions and selectivity in catalysis. Therefore, a new cluster system was constructed to study catalysts for applications in renewable energy. Matilda, a nanocluster source, consists of a cluster source and a Retarding Field Analyzer (RFA). A moveable AJA A310 Series 1"-diameter magnetron sputtering gun enclosed in a water cooled aggregation tube served as the cluster source. A silver coin was used for the sputtering target. The sputtering pressure in the aggregation tube was controlled, ranging from 0.07 to 1torr, using a mass flow controller. The mean cluster size was found to be a function of relative partial pressure (He/Ar), sputtering power, and aggregation length. The kinetic energy distribution of ionized clusters was measured with the RFA. The maximum ion energy distribution was 2.9 eV/atom at a zero pressure ratio. At high Ar flow rates, the mean cluster size was 20 ˜ 80nm, and at a 9.5 partial pressure ratio, the mean cluster size was reduced to 1.6nm. Our results showed that the He gas pressure can be optimized to reduce the cluster size variations. Results from SIMION, which is an electron optics simulation package, supported the basic function of an RFA, a three-element lens and the magnetic sector mass filter. These simulated results agreed with experimental data. For the size selection experiment, the channeltron electron multiplier collected ionized cluster signal at different positions during Ag deposition on a TEM grid for four and half hours. The cluster signal was high at the position for neutral clusters, which was not bent by a magnetic field, and the signal decreased rapidly far away from the neutral cluster region. For cluster separation according to mass to charge ratio in a magnetic sector mass filter, the ion energy of the cluster and its distribution must be precisely controlled by acceleration or deceleration. To verify the size separation, a high resolution microscope was required. Matilda provided narrow particle sized distribution from atomic scale to 4nm in size with different pressure ratio without additional mass filter. It is very economical way to produce relatively narrow particle size distribution.

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction.

PubMed

Akhter, Nasrin; Shehu, Amarda

2018-01-19

Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

A Fine-Scale Functional Logic to Convergence from Retina to Thalamus.

PubMed

Liang, Liang; Fratzl, Alex; Goldey, Glenn; Ramesh, Rohan N; Sugden, Arthur U; Morgan, Josh L; Chen, Chinfei; Andermann, Mark L

2018-05-31

Numerous well-defined classes of retinal ganglion cells innervate the thalamus to guide image-forming vision, yet the rules governing their convergence and divergence remain unknown. Using two-photon calcium imaging in awake mouse thalamus, we observed a functional arrangement of retinal ganglion cell axonal boutons in which coarse-scale retinotopic ordering gives way to fine-scale organization based on shared preferences for other visual features. Specifically, at the ∼6 μm scale, clusters of boutons from different axons often showed similar preferences for either one or multiple features, including axis and direction of motion, spatial frequency, and changes in luminance. Conversely, individual axons could "de-multiplex" information channels by participating in multiple, functionally distinct bouton clusters. Finally, ultrastructural analyses demonstrated that retinal axonal boutons in a local cluster often target the same dendritic domain. These data suggest that functionally specific convergence and divergence of retinal axons may impart diverse, robust, and often novel feature selectivity to visual thalamus. Copyright © 2018 Elsevier Inc. All rights reserved.

Non-specific filtering of beta-distributed data.

PubMed

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

2014-06-19

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

Neuropsychological phenotypes among men with and without HIV disease in the multicenter AIDS cohort study.

PubMed

Molsberry, Samantha A; Cheng, Yu; Kingsley, Lawrence; Jacobson, Lisa; Levine, Andrew J; Martin, Eileen; Miller, Eric N; Munro, Cynthia A; Ragin, Ann; Sacktor, Ned; Becker, James T

2018-05-11

Mild forms of HIV-associated neurocognitive disorder (HAND) remain prevalent in the combination anti-retroviral therapy (cART) era. This study's objective was to identify neuropsychological subgroups within the Multicenter AIDS Cohort Study (MACS) based on the participant-based latent structure of cognitive function and to identify factors associated with subgroups. The MACS is a four-site longitudinal study of the natural and treated history of HIV disease among gay and bisexual men. Using neuropsychological domain scores we used a cluster variable selection algorithm to identify the optimal subset of domains with cluster information. Latent profile analysis was applied using scores from identified domains. Exploratory and post-hoc analyses were conducted to identify factors associated with cluster membership and the drivers of the observed associations. Cluster variable selection identified all domains as containing cluster information except for Working Memory. A three-profile solution produced the best fit for the data. Profile 1 performed below average on all domains, Profile 2 performed average on executive functioning, motor, and speed and below average on learning and memory, Profile 3 performed at or above average across all domains. Several demographic, cognitive, and social factors were associated with profile membership; these associations were driven by differences between Profile 1 and the other profiles. There is an identifiable pattern of neuropsychological performance among MACS members determined by all domains except Working Memory. Neither HIV nor HIV-related biomarkers were related with cluster membership, consistent with other findings that cognitive performance patterns do not map directly onto HIV serostatus.

Melting of size-selected gallium clusters with 60-183 atoms.

PubMed

Pyfer, Katheryne L; Kafader, Jared O; Yalamanchali, Anirudh; Jarrold, Martin F

2014-07-10

Heat capacities have been measured as a function of temperature for size-selected gallium cluster cations with between 60 and 183 atoms. Almost all clusters studied show a single peak in the heat capacity that is attributed to a melting transition. The peaks can be fit by a two-state model incorporating only fully solid-like and fully liquid-like species, and hence no partially melted intermediates. The exceptions are Ga90(+), which does not show a peak, and Ga80(+) and Ga81(+), which show two peaks. For the clusters with two peaks, the lower temperature peak is attributed to a structural transition. The melting temperatures for clusters with less than 50 atoms have previously been shown to be hundreds of degrees above the bulk melting point. For clusters with more than 60 atoms the melting temperatures decrease, approaching the bulk value (303 K) at around 95 atoms, and then show several small upward excursions with increasing cluster size. A plot of the latent heat against the entropy change for melting reveals two groups of clusters: the latent heats and entropy changes for clusters with less than 94 atoms are distinct from those for clusters with more than 93 atoms. This observation suggests that a significant change in the nature of the bonding or the structure of the clusters occurs at 93-94 atoms. Even though the melting temperatures are close to the bulk value for the larger clusters studied here, the latent heats and entropies of melting are still far from the bulk values.

Robust watermarking scheme for binary images using a slice-based large-cluster algorithm with a Hamming Code

NASA Astrophysics Data System (ADS)

Chen, Wen-Yuan; Liu, Chen-Chung

2006-01-01

The problems with binary watermarking schemes are that they have only a small amount of embeddable space and are not robust enough. We develop a slice-based large-cluster algorithm (SBLCA) to construct a robust watermarking scheme for binary images. In SBLCA, a small-amount cluster selection (SACS) strategy is used to search for a feasible slice in a large-cluster flappable-pixel decision (LCFPD) method, which is used to search for the best location for concealing a secret bit from a selected slice. This method has four major advantages over the others: (a) SBLCA has a simple and effective decision function to select appropriate concealment locations, (b) SBLCA utilizes a blind watermarking scheme without the original image in the watermark extracting process, (c) SBLCA uses slice-based shuffling capability to transfer the regular image into a hash state without remembering the state before shuffling, and finally, (d) SBLCA has enough embeddable space that every 64 pixels could accommodate a secret bit of the binary image. Furthermore, empirical results on test images reveal that our approach is a robust watermarking scheme for binary images.

MMPI-2: Cluster Analysis of Personality Profiles in Perinatal Depression—Preliminary Evidence

PubMed Central

Grillo, Alessandra; Lauriola, Marco; Giacchetti, Nicoletta

2014-01-01

Background. To assess personality characteristics of women who develop perinatal depression. Methods. The study started with a screening of a sample of 453 women in their third trimester of pregnancy, to which was administered a survey data form, the Edinburgh Postnatal Depression Scale (EPDS) and the Minnesota Multiphasic Personality Inventory 2 (MMPI-2). A clinical group of subjects with perinatal depression (PND, 55 subjects) was selected; clinical and validity scales of MMPI-2 were used as predictors in hierarchical cluster analysis carried out. Results. The analysis identified three clusters of personality profile: two “clinical” clusters (1 and 3) and an “apparently common” one (cluster 2). The first cluster (39.5%) collects structures of personality with prevalent obsessive or dependent functioning tending to develop a “psychasthenic” depression; the third cluster (13.95%) includes women with prevalent borderline functioning tending to develop “dysphoric” depression; the second cluster (46.5%) shows a normal profile with a “defensive” attitude, probably due to the presence of defense mechanisms or to the fear of stigma. Conclusion. Characteristics of personality have a key role in clinical manifestations of perinatal depression; it is important to detect them to identify mothers at risk and to plan targeted therapeutic interventions. PMID:25574499

Ortholog-based screening and identification of genes related to intracellular survival.

PubMed

Yang, Xiaowen; Wang, Jiawei; Bing, Guoxia; Bie, Pengfei; De, Yanyan; Lyu, Yanli; Wu, Qingmin

2018-04-20

Bioinformatics and comparative genomics analysis methods were used to predict unknown pathogen genes based on homology with identified or functionally clustered genes. In this study, the genes of common pathogens were analyzed to screen and identify genes associated with intracellular survival through sequence similarity, phylogenetic tree analysis and the λ-Red recombination system test method. The total 38,952 protein-coding genes of common pathogens were divided into 19,775 clusters. As demonstrated through a COG analysis, information storage and processing genes might play an important role intracellular survival. Only 19 clusters were present in facultative intracellular pathogens, and not all were present in extracellular pathogens. Construction of a phylogenetic tree selected 18 of these 19 clusters. Comparisons with the DEG database and previous research revealed that seven other clusters are considered essential gene clusters and that seven other clusters are associated with intracellular survival. Moreover, this study confirmed that clusters screened by orthologs with similar function could be replaced with an approved uvrY gene and its orthologs, and the results revealed that the usg gene is associated with intracellular survival. The study improves the current understanding of intracellular pathogens characteristics and allows further exploration of the intracellular survival-related gene modules in these pathogens. Copyright © 2018. Published by Elsevier B.V.

Infrared spectroscopy of phenol-(H2O)(n>10): structural strains in hydrogen bond networks of neutral water clusters.

PubMed

Mizuse, Kenta; Hamashima, Toru; Fujii, Asuka

2009-11-05

To investigate hydrogen bond network structures of tens of water molecules, we report infrared spectra of moderately size (n)-selected phenol-(H2O)n (approximately 10 < or = n < or = approximately 50), which have essentially the same network structures as (H2O)(n+1). The phenyl group in phenol-(H2O)(n) allows us to apply photoionization-based size selection and infrared-ultraviolet double resonance spectroscopy. The spectra show a clear low-frequency shift of the free OH stretching band with increasing n. Detailed analyses with density functional theory calculations indicate that this shift is accounted for by the hydrogen bond network development from highly strained ones in the small (n < approximately 10) clusters to more relaxed ones in the larger clusters, in addition to the cooperativity of hydrogen bonds.

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

Magnetism, structures and stabilities of cluster assembled TM@Si nanotubes (TM = Cr, Mn and Fe): a density functional study.

PubMed

Dhaka, Kapil; Bandyopadhyay, Debashis

2016-08-02

The present study reports transition metal (TM = Cr, Mn and Fe) doped silicon nanotubes with tunable band structures and magnetic properties by careful selection of cluster assemblies as building blocks using the first-principles density functional theory. We found that the transition metal doping and in addition, the hydrogen termination process can stabilize the pure silicon nanoclusters or cluster assemblies and then it could be extended as magnetic nanotubes with finite magnetic moments. Study of the band structures and density of states (DOS) of different empty and TM doped nanotubes (Type 1 to Type 4) show that these nanotubes are useful as metals, semiconductors, semi-metals and half-metals. These designer magnetic materials could be useful in spintronics and magnetic devices of nanoscale order.

Structural study of gold clusters.

PubMed

Xiao, Li; Tollberg, Bethany; Hu, Xiankui; Wang, Lichang

2006-03-21

Density functional theory (DFT) calculations were carried out to study gold clusters of up to 55 atoms. Between the linear and zigzag monoatomic Au nanowires, the zigzag nanowires were found to be more stable. Furthermore, the linear Au nanowires of up to 2 nm are formed by slightly stretched Au dimers. These suggest that a substantial Peierls distortion exists in those structures. Planar geometries of Au clusters were found to be the global minima till the cluster size of 13. A quantitative correlation is provided between various properties of Au clusters and the structure and size. The relative stability of selected clusters was also estimated by the Sutton-Chen potential, and the result disagrees with that obtained from the DFT calculations. This suggests that a modification of the Sutton-Chen potential has to be made, such as obtaining new parameters, in order to use it to search the global minima for bigger Au clusters.

Synergistic selection between ecological niche and mate preference primes diversification.

PubMed

Boughman, Janette W; Svanbäck, Richard

2017-01-01

The ecological niche and mate preferences have independently been shown to be important for the process of speciation. Here, we articulate a novel mechanism by which ecological niche use and mate preference can be linked to promote speciation. The degree to which individual niches are narrow and clustered affects the strength of divergent natural selection and population splitting. Similarly, the degree to which individual mate preferences are narrow and clustered affects the strength of divergent sexual selection and assortative mating between diverging forms. This novel perspective is inspired by the literature on ecological niches; it also explores mate preferences and how they may contribute to speciation. Unlike much comparative work, we do not search for evolutionary patterns using proxies for adaptation and sexual selection, but rather we elucidate how ideas from niche theory relate to mate preference, and how this relationship can foster speciation. Recognizing that individual and population niches are conceptually and ecologically linked to individual and population mate preference functions will significantly increase our understanding of rapid evolutionary diversification in nature. It has potential to help solve the difficult challenge of testing the role of sexual selection in the speciation process. We also identify ecological factors that are likely to affect individual niche and individual mate preference in synergistic ways and as a consequence to promote speciation. The ecological niche an individual occupies can directly affect its mate preference. Clusters of individuals with narrow, differentiated niches are likely to have narrow, differentiated mate preference functions. Our approach integrates ecological and sexual selection research to further our understanding of diversification processes. Such integration may be necessary for progress because these processes seem inextricably linked in the natural world. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Toward An Understanding of Cluster Evolution: A Deep X-Ray Selected Cluster Catalog from ROSAT

NASA Technical Reports Server (NTRS)

Jones, Christine; Oliversen, Ronald (Technical Monitor)

2002-01-01

In the past year, we have focussed on studying individual clusters found in this sample with Chandra, as well as using Chandra to measure the luminosity-temperature relation for a sample of distant clusters identified through the ROSAT study, and finally we are continuing our study of fossil groups. For the luminosity-temperature study, we compared a sample of nearby clusters with a sample of distant clusters and, for the first time, measured a significant change in the relation as a function of redshift (Vikhlinin et al. in final preparation for submission to Cape). We also used our ROSAT analysis to select and propose for Chandra observations of individual clusters. We are now analyzing the Chandra observations of the distant cluster A520, which appears to have undergone a recent merger. Finally, we have completed the analysis of the fossil groups identified in ROM observations. In the past few months, we have derived X-ray fluxes and luminosities as well as X-ray extents for an initial sample of 89 objects. Based on the X-ray extents and the lack of bright galaxies, we have identified 16 fossil groups. We are comparing their X-ray and optical properties with those of optically rich groups. A paper is being readied for submission (Jones, Forman, and Vikhlinin in preparation).

HICOSMO - cosmology with a complete sample of galaxy clusters - I. Data analysis, sample selection and luminosity-mass scaling relation

NASA Astrophysics Data System (ADS)

Schellenberger, G.; Reiprich, T. H.

2017-08-01

The X-ray regime, where the most massive visible component of galaxy clusters, the intracluster medium, is visible, offers directly measured quantities, like the luminosity, and derived quantities, like the total mass, to characterize these objects. The aim of this project is to analyse a complete sample of galaxy clusters in detail and constrain cosmological parameters, like the matter density, Ωm, or the amplitude of initial density fluctuations, σ8. The purely X-ray flux-limited sample (HIFLUGCS) consists of the 64 X-ray brightest galaxy clusters, which are excellent targets to study the systematic effects, that can bias results. We analysed in total 196 Chandra observations of the 64 HIFLUGCS clusters, with a total exposure time of 7.7 Ms. Here, we present our data analysis procedure (including an automated substructure detection and an energy band optimization for surface brightness profile analysis) that gives individually determined, robust total mass estimates. These masses are tested against dynamical and Planck Sunyaev-Zeldovich (SZ) derived masses of the same clusters, where good overall agreement is found with the dynamical masses. The Planck SZ masses seem to show a mass-dependent bias to our hydrostatic masses; possible biases in this mass-mass comparison are discussed including the Planck selection function. Furthermore, we show the results for the (0.1-2.4) keV luminosity versus mass scaling relation. The overall slope of the sample (1.34) is in agreement with expectations and values from literature. Splitting the sample into galaxy groups and clusters reveals, even after a selection bias correction, that galaxy groups exhibit a significantly steeper slope (1.88) compared to clusters (1.06).

Galaxy Evolution Viewed as Functions of Environment and Mass

NASA Astrophysics Data System (ADS)

Kodama, Tadayuki; Tanaka, Masayuki; Tanaka, Ichi; Kajisawa, Masaru

We present two large surveys of distant clusters currently being carried out with Subaru, making use of its great capability of wide-field study both in the optical and in the near-infrared. The optical surveys, called PISCES, have mapped out large scale structures in and around 8 distant clusters at 0.4 < z <1.3, composed of multiple filaments and clumps extended over 15-30 Mpc scale. From the photometric and spectroscopic properties of galaxies over a wide range in environment, we find that the truncation of galaxies is seen in the outskirts of clusters rather than in the cluster cores.We also see a clear environmental dependence of the down-sizing (progressively later quenching of star formation in smaller galaxies). The near-infrared surveys are being conducted with a new wide-field instrument targeting proto-clusters around high-zradio-loud galaxies up to z ~4. Most of these field are known to show a large number of Lyαand/or Hαemitters at the same redshifts of the radio galaxies. We see a clear excess of near-infrared selected galaxies (JHK s -selected galaxies as well as DRG) in these fields, and they are indeed proto-clusters with not only young emitters but also evolved populations. Spatial distribution of such NIR selected galaxies is filamentary and track similar structures traced by the emitters. There is an hint that the bright-end of the red sequence first appeared between z= 3 and 2.

Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps

PubMed Central

2011-01-01

Background Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering. Results The conformational dynamics of the α-spectrin SH3 protein domain and six single mutants were analysed by MD simulations. The Cα's Cartesian coordinates of conformations sampled in the essential space were used as input data vectors for SOM training, then complete linkage clustering was performed on the SOM prototype vectors. A specific protocol to optimize a SOM for structural ensembles was proposed: the optimal SOM was selected by means of a Taguchi experimental design plan applied to different data sets, and the optimal sampling rate of the MD trajectory was selected. The proposed two-level approach was applied to single trajectories of the SH3 domain independently as well as to groups of them at the same time. The results demonstrated the potential of this approach in the analysis of large ensembles of molecular structures: the possibility of producing a topological mapping of the conformational space in a simple 2D visualisation, as well as of effectively highlighting differences in the conformational dynamics directly related to biological functions. Conclusions The use of a two-level approach combining SOMs and hierarchical clustering for conformational analysis of structural ensembles of proteins was proposed. It can easily be extended to other study cases and to conformational ensembles from other sources. PMID:21569575

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

PubMed

Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C; Morris, John H; Ferrin, Thomas E; Poole, Leslie B; Fetrow, Jacquelyn S

2017-02-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins

PubMed Central

Babbitt, Patricia C.; Ferrin, Thomas E.

2017-01-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially—MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method’s novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences. PMID:28187133

Extrinsic Sources of Scatter in the Richness-mass Relation of Galaxy Clusters

NASA Astrophysics Data System (ADS)

Rozo, Eduardo; Rykoff, Eli; Koester, Benjamin; Nord, Brian; Wu, Hao-Yi; Evrard, August; Wechsler, Risa

2011-10-01

Maximizing the utility of upcoming photometric cluster surveys requires a thorough understanding of the richness-mass relation of galaxy clusters. We use Monte Carlo simulations to study the impact of various sources of observational scatter on this relation. Cluster ellipticity, photometric errors, photometric redshift errors, and cluster-to-cluster variations in the properties of red-sequence galaxies contribute negligible noise. Miscentering, however, can be important, and likely contributes to the scatter in the richness-mass relation of galaxy maxBCG clusters at the low-mass end, where centering is more difficult. We also investigate the impact of projection effects under several empirically motivated assumptions about cluster environments. Using Sloan Digital Sky Survey data and the maxBCG cluster catalog, we demonstrate that variations in cluster environments can rarely (≈1%-5% of the time) result in significant richness boosts. Due to the steepness of the mass/richness function, the corresponding fraction of optically selected clusters that suffer from these projection effects is ≈5%-15%. We expect these numbers to be generic in magnitude, but a precise determination requires detailed, survey-specific modeling.

Partially oxidized iridium clusters within dendrimers: size-controlled synthesis and selective hydrogenation of 2-nitrobenzaldehyde

NASA Astrophysics Data System (ADS)

Higaki, Tatsuya; Kitazawa, Hirokazu; Yamazoe, Seiji; Tsukuda, Tatsuya

2016-06-01

Iridium clusters nominally composed of 15, 30 or 60 atoms were size-selectively synthesized within OH-terminated poly(amidoamine) dendrimers of generation 6. Spectroscopic characterization revealed that the Ir clusters were partially oxidized. All the Ir clusters efficiently converted 2-nitrobenzaldehyde to anthranil and 2-aminobenzaldehyde under atmospheric hydrogen at room temperature in toluene via selective hydrogenation of the NO2 group. The selectivity toward 2-aminobenzaldehyde over anthranil was improved with the reduction of the cluster size. The improved selectivity is ascribed to more efficient reduction than intramolecular heterocyclization of a hydroxylamine intermediate on smaller clusters that have a higher Ir(0)-phase population on the surface.Iridium clusters nominally composed of 15, 30 or 60 atoms were size-selectively synthesized within OH-terminated poly(amidoamine) dendrimers of generation 6. Spectroscopic characterization revealed that the Ir clusters were partially oxidized. All the Ir clusters efficiently converted 2-nitrobenzaldehyde to anthranil and 2-aminobenzaldehyde under atmospheric hydrogen at room temperature in toluene via selective hydrogenation of the NO2 group. The selectivity toward 2-aminobenzaldehyde over anthranil was improved with the reduction of the cluster size. The improved selectivity is ascribed to more efficient reduction than intramolecular heterocyclization of a hydroxylamine intermediate on smaller clusters that have a higher Ir(0)-phase population on the surface. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01460g

Electronic Interactions of Size-Selected Oxide Clusters on Metallic and Thin Film Oxide Supports

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

Xue, Meng; Nakayama, Miki; Liu, Ping

The interfacial electronic structure of various size-selected metal oxide nanoclusters (M 3O x; M = Mo, Nb, Ti) on Cu(111) and a thin film of Cu 2O supports were investigated in this paper by a combination of experimental methods and density functional theory (DFT). These systems explore electron transfer at the metal–metal oxide interface which can modify surface structure, metal oxidation states, and catalytic activity. Electron transfer was probed by measurements of surface dipoles derived from coverage dependent work function measurements using two-photon photoemission (2PPE) and metal core level binding energy spectra from X-ray photoelectron spectroscopy (XPS). The measured surfacemore » dipoles are negative for all clusters on Cu(111) and Cu 2O/Cu(111), but those on the Cu 2O surface are much larger in magnitude. In addition, sub-stoichiometric or “reduced” clusters exhibit smaller surface dipoles on both the Cu(111) and Cu 2O surfaces. Negative surface dipoles for clusters on Cu(111) suggest Cu → cluster electron transfer, which is generally supported by DFT-calculated Bader charge distributions. For Cu 2O/Cu(111), calculations of the surface electrostatic potentials show that the charge distributions associated with cluster adsorption structures or distortions at the cluster–Cu 2O–Cu(111) interface are largely responsible for the observed negative surface dipoles. Changes observed in the XPS spectra for the Mo 3d, Nb 3d, and Ti 2p core levels of the clusters on Cu(111) and Cu 2O/Cu(111) are interpreted with help from the calculated Bader charges and cluster adsorption structures, the latter providing information about the presence of inequivalent cation sites. Finally, the results presented in this work illustrate how the combined use of different experimental probes along with theoretical calculations can result in a more realistic picture of cluster–support interactions and bonding.« less

Electronic Interactions of Size-Selected Oxide Clusters on Metallic and Thin Film Oxide Supports

DOE PAGES

Xue, Meng; Nakayama, Miki; Liu, Ping; ...

2017-09-13

The interfacial electronic structure of various size-selected metal oxide nanoclusters (M 3O x; M = Mo, Nb, Ti) on Cu(111) and a thin film of Cu 2O supports were investigated in this paper by a combination of experimental methods and density functional theory (DFT). These systems explore electron transfer at the metal–metal oxide interface which can modify surface structure, metal oxidation states, and catalytic activity. Electron transfer was probed by measurements of surface dipoles derived from coverage dependent work function measurements using two-photon photoemission (2PPE) and metal core level binding energy spectra from X-ray photoelectron spectroscopy (XPS). The measured surfacemore » dipoles are negative for all clusters on Cu(111) and Cu 2O/Cu(111), but those on the Cu 2O surface are much larger in magnitude. In addition, sub-stoichiometric or “reduced” clusters exhibit smaller surface dipoles on both the Cu(111) and Cu 2O surfaces. Negative surface dipoles for clusters on Cu(111) suggest Cu → cluster electron transfer, which is generally supported by DFT-calculated Bader charge distributions. For Cu 2O/Cu(111), calculations of the surface electrostatic potentials show that the charge distributions associated with cluster adsorption structures or distortions at the cluster–Cu 2O–Cu(111) interface are largely responsible for the observed negative surface dipoles. Changes observed in the XPS spectra for the Mo 3d, Nb 3d, and Ti 2p core levels of the clusters on Cu(111) and Cu 2O/Cu(111) are interpreted with help from the calculated Bader charges and cluster adsorption structures, the latter providing information about the presence of inequivalent cation sites. Finally, the results presented in this work illustrate how the combined use of different experimental probes along with theoretical calculations can result in a more realistic picture of cluster–support interactions and bonding.« less

Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering.

PubMed

Boari de Lima, Elisa; Meira, Wagner; Melo-Minardi, Raquel Cardoso de

2016-06-01

As increasingly more genomes are sequenced, the vast majority of proteins may only be annotated computationally, given experimental investigation is extremely costly. This highlights the need for computational methods to determine protein functions quickly and reliably. We believe dividing a protein family into subtypes which share specific functions uncommon to the whole family reduces the function annotation problem's complexity. Hence, this work's purpose is to detect isofunctional subfamilies inside a family of unknown function, while identifying differentiating residues. Similarity between protein pairs according to various properties is interpreted as functional similarity evidence. Data are integrated using genetic programming and provided to a spectral clustering algorithm, which creates clusters of similar proteins. The proposed framework was applied to well-known protein families and to a family of unknown function, then compared to ASMC. Results showed our fully automated technique obtained better clusters than ASMC for two families, besides equivalent results for other two, including one whose clusters were manually defined. Clusters produced by our framework showed great correspondence with the known subfamilies, besides being more contrasting than those produced by ASMC. Additionally, for the families whose specificity determining positions are known, such residues were among those our technique considered most important to differentiate a given group. When run with the crotonase and enolase SFLD superfamilies, the results showed great agreement with this gold-standard. Best results consistently involved multiple data types, thus confirming our hypothesis that similarities according to different knowledge domains may be used as functional similarity evidence. Our main contributions are the proposed strategy for selecting and integrating data types, along with the ability to work with noisy and incomplete data; domain knowledge usage for detecting subfamilies in a family with different specificities, thus reducing the complexity of the experimental function characterization problem; and the identification of residues responsible for specificity.

Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering

PubMed Central

Boari de Lima, Elisa; Meira, Wagner; de Melo-Minardi, Raquel Cardoso

2016-01-01

As increasingly more genomes are sequenced, the vast majority of proteins may only be annotated computationally, given experimental investigation is extremely costly. This highlights the need for computational methods to determine protein functions quickly and reliably. We believe dividing a protein family into subtypes which share specific functions uncommon to the whole family reduces the function annotation problem’s complexity. Hence, this work’s purpose is to detect isofunctional subfamilies inside a family of unknown function, while identifying differentiating residues. Similarity between protein pairs according to various properties is interpreted as functional similarity evidence. Data are integrated using genetic programming and provided to a spectral clustering algorithm, which creates clusters of similar proteins. The proposed framework was applied to well-known protein families and to a family of unknown function, then compared to ASMC. Results showed our fully automated technique obtained better clusters than ASMC for two families, besides equivalent results for other two, including one whose clusters were manually defined. Clusters produced by our framework showed great correspondence with the known subfamilies, besides being more contrasting than those produced by ASMC. Additionally, for the families whose specificity determining positions are known, such residues were among those our technique considered most important to differentiate a given group. When run with the crotonase and enolase SFLD superfamilies, the results showed great agreement with this gold-standard. Best results consistently involved multiple data types, thus confirming our hypothesis that similarities according to different knowledge domains may be used as functional similarity evidence. Our main contributions are the proposed strategy for selecting and integrating data types, along with the ability to work with noisy and incomplete data; domain knowledge usage for detecting subfamilies in a family with different specificities, thus reducing the complexity of the experimental function characterization problem; and the identification of residues responsible for specificity. PMID:27348631

Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

Vathsala, H.; Koolagudi, Shashidhar G.

2017-01-01

In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good.

Gold atoms and dimers on amorphous SiO(2): calculation of optical properties and cavity ringdown spectroscopy measurements.

PubMed

Del Vitto, Annalisa; Pacchioni, Gianfranco; Lim, Kok Hwa; Rösch, Notker; Antonietti, Jean-Marie; Michalski, Marcin; Heiz, Ulrich; Jones, Harold

2005-10-27

We report on the optical absorption spectra of gold atoms and dimers deposited on amorphous silica in size-selected fashion. Experimental spectra were obtained by cavity ringdown spectroscopy. Issues on soft-landing, fragmentation, and thermal diffusion are discussed on the basis of the experimental results. In parallel, cluster and periodic supercell density functional theory (DFT) calculations were performed to model atoms and dimers trapped on various defect sites of amorphous silica. Optically allowed electronic transitions were calculated, and comparisons with the experimental spectra show that silicon dangling bonds [[triple bond]Si(.-)], nonbridging oxygen [[triple bond]Si-O(.-)], and the silanolate group [[triple bond]Si-O(-)] act as trapping centers for the gold particles. The results are not only important for understanding the chemical bonding of atoms and clusters on oxide surfaces, but they will also be of fundamental interest for photochemical studies of size-selected clusters on surfaces.

Golgi sorting regulates organization and activity of GPI-proteins at apical membranes

PubMed Central

Tivodar, Simona; Formiggini, Fabio; Ossato, Giulia; Gratton, Enrico; Tramier, Marc; Coppey-Moisan, Maïté; Zurzolo, Chiara

2014-01-01

Here, we combined classical biochemistry with novel biophysical approaches to study with high spatial and temporal resolution the organization of GPI-anchored proteins (GPI-APs) at the plasma membrane of polarized epithelial cells. We show that in polarized MDCK cells, following sorting in the Golgi, each GPI-AP reaches the apical surface in homo-clusters. Golgi-derived homo-clusters are required for their subsequent plasma membrane organization into cholesterol-dependent hetero-clusters. By contrast, in non-polarized MDCK cells GPI-APs are delivered to the surface as monomers in an unpolarized manner and are not able to form hetero-clusters. We further demonstrate that this GPI-AP organization is regulated by the content of cholesterol in the Golgi apparatus and is required to maintain the functional state of the protein at the apical membrane. Thus, different from fibroblasts, in polarized epithelial cells a selective cholesterol-dependent sorting mechanism in the Golgi regulates both the organization and the function of GPI-APs at the apical surface. PMID:24681536

Wobbled electronic properties of lithium clusters: Deterministic approach through first principles

NASA Astrophysics Data System (ADS)

Kushwaha, Anoop Kumar; Nayak, Saroj Kumar

2018-03-01

The innate tendency to form dendritic growth promoted through cluster formation leading to the failure of a Li-ion battery system have drawn significant attention of the researchers towards the effective destabilization of the cluster growth through selective implementation of electrolytic media such as acetonitrile (MeCN). In the present work, using first principles density functional theory and continuum dielectric model, we have investigated the origin of oscillatory nature of binding energy per atom of Lin (n ≤ 8) under the influence of MeCN. In the gas phase, we found that static mean polarizability is strongly correlated with binding energy and shows oscillatory nature with cluster size due to the open shell of Lin cluster. However, in acetonitrile medium, the binding energy has been correlated with electrostatic Lin -MeCN interaction and it has been found that both of them possess wobbled behavior characterized by the cluster size.

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

PubMed Central

Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

Improved optical mass tracer for galaxy clusters calibrated using weak lensing measurements

NASA Astrophysics Data System (ADS)

Reyes, R.; Mandelbaum, R.; Hirata, C.; Bahcall, N.; Seljak, U.

2008-11-01

We develop an improved mass tracer for clusters of galaxies from optically observed parameters, and calibrate the mass relation using weak gravitational lensing measurements. We employ a sample of ~13000 optically selected clusters from the Sloan Digital Sky Survey (SDSS) maxBCG catalogue, with photometric redshifts in the range 0.1-0.3. The optical tracers we consider are cluster richness, cluster luminosity, luminosity of the brightest cluster galaxy (BCG) and combinations of these parameters. We measure the weak lensing signal around stacked clusters as a function of the various tracers, and use it to determine the tracer with the least amount of scatter. We further use the weak lensing data to calibrate the mass normalization. We find that the best mass estimator for massive clusters is a combination of cluster richness, N200, and the luminosity of the BCG, LBCG: , where is the observed mean BCG luminosity at a given richness. This improved mass tracer will enable the use of galaxy clusters as a more powerful tool for constraining cosmological parameters.

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Inactivation of iron-sulfur cluster biogenesis regulator SufR in Synechocystis sp. PCC 6803 induces unique iron-dependent protein-level responses.

PubMed

Vuorijoki, Linda; Tiwari, Arjun; Kallio, Pauli; Aro, Eva-Mari

2017-05-01

Iron-sulfur (Fe-S) clusters are protein-bound cofactors associated with cellular electron transport and redox sensing, with multiple specific functions in oxygen-evolving photosynthetic cyanobacteria. The aim here was to elucidate protein-level effects of the transcriptional repressor SufR involved in the regulation of Fe-S cluster biogenesis in the cyanobacterium Synechocystis sp. PCC 6803. The approach was to quantitate 94 pre-selected target proteins associated with various metabolic functions using SRM in Synechocystis. The evaluation was conducted in response to sufR deletion under different iron conditions, and complemented with EPR analysis on the functionality of the photosystems I and II as well as with RT-qPCR to verify the effects of SufR also on transcript level. The results on both protein and transcript levels show that SufR acts not only as a repressor of the suf operon when iron is available but also has other direct and indirect functions in the cell, including maintenance of the expression of pyruvate:ferredoxin oxidoreductase NifJ and other Fe-S cluster proteins under iron sufficient conditions. Furthermore, the results imply that in the absence of iron the suf operon is repressed by some additional regulatory mechanism independent of SufR. The study demonstrates that Fe-S cluster metabolism in Synechocystis is stringently regulated, and has complex interactions with multiple primary functions in the cell, including photosynthesis and central carbon metabolism. The study provides new insight into the regulation of Fe-S cluster biogenesis via suf operon, and the associated wide-ranging protein-level changes in photosynthetic cyanobacteria. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

High degree of genetic differentiation in marine three-spined sticklebacks (Gasterosteus aculeatus).

PubMed

Defaveri, Jacquelin; Shikano, Takahito; Shimada, Yukinori; Merilä, Juha

2013-09-01

Populations of widespread marine organisms are typically characterized by a low degree of genetic differentiation in neutral genetic markers, but much less is known about differentiation in genes whose functional roles are associated with specific selection regimes. To uncover possible adaptive population divergence and heterogeneous genomic differentiation in marine three-spined sticklebacks (Gasterosteus aculeatus), we used a candidate gene-based genome-scan approach to analyse variability in 138 microsatellite loci located within/close to (<6 kb) functionally important genes in samples collected from ten geographic locations. The degree of genetic differentiation in markers classified as neutral or under balancing selection-as determined with several outlier detection methods-was low (F(ST) = 0.033 or 0.011, respectively), whereas average FST for directionally selected markers was significantly higher (F(ST) = 0.097). Clustering analyses provided support for genomic and geographic heterogeneity in selection: six genetic clusters were identified based on allele frequency differences in the directionally selected loci, whereas four were identified with the neutral loci. Allelic variation in several loci exhibited significant associations with environmental variables, supporting the conjecture that temperature and salinity, but not optic conditions, are important drivers of adaptive divergence among populations. In general, these results suggest that in spite of the high degree of physical connectivity and gene flow as inferred from neutral marker genes, marine stickleback populations are strongly genetically structured in loci associated with functionally relevant genes. © 2013 John Wiley & Sons Ltd.

Receptive field optimisation and supervision of a fuzzy spiking neural network.

PubMed

Glackin, Cornelius; Maguire, Liam; McDaid, Liam; Sayers, Heather

2011-04-01

This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train firing rates and behave in a similar manner as fuzzy membership functions. The connectivity of the hidden and output layers in the fuzzy spiking neural network (FSNN) is representative of a fuzzy rule base. Fuzzy C-Means clustering is utilised to produce clusters that represent the antecedent part of the fuzzy rule base that aid classification of the feature data. Suitable cluster widths are determined using two strategies; subjective thresholding and evolutionary thresholding respectively. The former technique typically results in compact solutions in terms of the number of neurons, and is shown to be particularly suited to small data sets. In the latter technique a pool of cluster candidates is generated using Fuzzy C-Means clustering and then a genetic algorithm is employed to select the most suitable clusters and to specify cluster widths. In both scenarios, the network is supervised but learning only occurs locally as in the biological case. The advantages and disadvantages of the network topology for the Fisher Iris and Wisconsin Breast Cancer benchmark classification tasks are demonstrated and directions of current and future work are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

Boredom-proneness, loneliness, social engagement and depression and their association with cognitive function in older people: a population study.

PubMed

Conroy, Ronan M; Golden, Jeannette; Jeffares, Isabelle; O'Neill, Desmond; McGee, Hannah

2010-08-01

In this study, we use data from a population survey of persons aged 65 and over living in the Irish Republic to examine the relationship of cognitive impairment, assessed using the Abbreviated Mental Test, with loneliness, boredom-proneness, social relations, and depression. Participants were randomly selected community-dwelling Irish people aged 65+ years. An Abbreviated Mental Test score of 8 or 9 out of 10 was classified as 'low normal', and a score of less than 8 as 'possible cognitive impairment'. We used clustering around latent variables analysis (CLV) to identify families of variables associated with reduced cognitive function. The overall prevalence of possible cognitive impairment was 14.7% (95% CI 12.4-17.3%). Low normal scores had a prevalence of 30.5% (95% CI 27.2-33.7%). CLV analysis identified three groups of predictors: 'Low social support' (widowed, living alone, low social support), 'personal cognitive reserve' (low social activity, no leisure exercise, never having married, loneliness and boredom-proneness), and 'sociodemographic cognitive reserve' (primary education, rural domicile). In multivariate analysis, both cognitive reserve clusters, but not social support, were independently associated with cognitive function. Loneliness and boredom-proneness are associated with reduced cognitive function in older age, and cluster with other factors associated with cognitive reserve. Both may have a common underlying mechanism in the failure to select and maintain attention on particular features of the social environment (loneliness) or the non-social environment (boredom-proneness).

Multiple relaxations of the cluster surface diffusion in a homoepitaxial SrTiO3 layer

NASA Astrophysics Data System (ADS)

Woo, Chang-Su; Chu, Kanghyun; Song, Jong-Hyun; Yang, Chan-Ho

2018-03-01

We examine the surface diffusion process of adatomic clusters on a (001)-oriented SrTiO3 single crystal using reflection high energy electron diffraction (RHEED). We find that the recovery curve of the RHEED intensity acquired after a homoepitaxial half-layer growth can be accurately fit into a double exponential function, indicating the existence of two dominant relaxation mechanisms. The characteristic relaxation times at selected growth temperatures are investigated to determine the diffusion activation barriers of 0.67 eV and 0.91 eV, respectively. The Monte Carlo simulation of the cluster hopping model suggests that the decrease in the number of dimeric and trimeric clusters during surface diffusion is the origin of the observed relaxation phenomena.

Widespread signatures of local mRNA folding structure selection in four Dengue virus serotypes

PubMed Central

2015-01-01

Background It is known that mRNA folding can affect and regulate various gene expression steps both in living organisms and in viruses. Previous studies have recognized functional RNA structures in the genome of the Dengue virus. However, these studies usually focused either on the viral untranslated regions or on very specific and limited regions at the beginning of the coding sequences, in a limited number of strains, and without considering evolutionary selection. Results Here we performed the first large scale comprehensive genomics analysis of selection for local mRNA folding strength in the Dengue virus coding sequences, based on a total of 1,670 genomes and 4 serotypes. Our analysis identified clusters of positions along the coding regions that may undergo a conserved evolutionary selection for strong or weak local folding maintained across different viral variants. Specifically, 53-66 clusters for strong folding and 49-73 clusters for weak folding (depending on serotype) aggregated of positions with a significant conservation of folding energy signals (related to partially overlapping local genomic regions) were recognized. In addition, up to 7% of these positions were found to be conserved in more than 90% of the viral genomes. Although some of the identified positions undergo frequent synonymous / non-synonymous substitutions, the selection for folding strength therein is preserved, and thus cannot be trivially explained based on sequence conservation alone. Conclusions The fact that many of the positions with significant folding related signals are conserved among different Dengue variants suggests that a better understanding of the mRNA structures in the corresponding regions may promote the development of prospective anti- Dengue vaccination strategies. The comparative genomics approach described here can be employed in the future for detecting functional regions in other pathogens with very high mutations rates. PMID:26449467

Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic.

PubMed

Ma, Yue; Yin, Fei; Zhang, Tao; Zhou, Xiaohua Andrew; Li, Xiaosong

2016-01-01

Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set-proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters.

Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic

PubMed Central

Ma, Yue; Yin, Fei; Zhang, Tao; Zhou, Xiaohua Andrew; Li, Xiaosong

2016-01-01

Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set–proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters. PMID:26820646

A path-based measurement for human miRNA functional similarities using miRNA-disease associations

NASA Astrophysics Data System (ADS)

Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

2016-09-01

Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

Homosexual Fellatio: Erect Penis Licking between Male Bonin Flying Foxes Pteropus pselaphon.

PubMed

Sugita, Norimasa

2016-01-01

A recent focus of interest has been on the functional significance of genital licking (fellatio and cunnilingus) in relation to sexual selection in Pteropodid bats. In the present paper, a form of fellatio in wild Bonin flying foxes, Pteropus pselaphon, performed between adult males has been reported. During the mating season, adult flying foxes roost in same-sex groups, forming ball-shaped clusters which provide warmth. The female clusters may also contain a few males. Unassociated with allogrooming, same-sex genital licking occurred among males in the all male clusters. As such, male-male fellatio can be considered as homosexual behavior, two functional explanations could account for this behavior; the social bonding and the social tension regulation hypotheses suggested in a previous review. Given that neither the simpler alternative that in all male groups such fellatio may represent misdirected sexual behavior, nor the two previously proposed functional hypotheses were supported by the data, I propose another functional hypothesis. Homosexual fellatio in this species could help males solve inconsistent situations in the roost when there are conflicts between cooperative behavior for social thermoregulation and competition for mating.

Uniform deposition of size-selected clusters using Lissajous scanning

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

Beniya, Atsushi; Watanabe, Yoshihide, E-mail: e0827@mosk.tytlabs.co.jp; Hirata, Hirohito

2016-05-15

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

The metallicity of the intracluster medium over cosmic time: further evidence for early enrichment

NASA Astrophysics Data System (ADS)

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn; Simionescu, Aurora; Urban, Ondrej; Werner, Norbert; Zhuravleva, Irina

2017-12-01

We use Chandra X-ray data to measure the metallicity of the intracluster medium (ICM) in 245 massive galaxy clusters selected from X-ray and Sunyaev-Zel'dovich (SZ) effect surveys, spanning redshifts 0 < z < 1.2. Metallicities were measured in three different radial ranges, spanning cluster cores through their outskirts. We explore trends in these measurements as a function of cluster redshift, temperature and surface brightness 'peakiness' (a proxy for gas cooling efficiency in cluster centres). The data at large radii (0.5-1 r500) are consistent with a constant metallicity, while at intermediate radii (0.1-0.5 r500) we see a late-time increase in enrichment, consistent with the expected production and mixing of metals in cluster cores. In cluster centres, there are strong trends of metallicity with temperature and peakiness, reflecting enhanced metal production in the lowest entropy gas. Within the cool-core/sharply peaked cluster population, there is a large intrinsic scatter in central metallicity and no overall evolution, indicating significant astrophysical variations in the efficiency of enrichment. The central metallicity in clusters with flat surface brightness profiles is lower, with a smaller intrinsic scatter, but increases towards lower redshifts. Our results are consistent with other recent measurements of ICM metallicity as a function of redshift. They reinforce the picture implied by observations of uniform metal distributions in the outskirts of nearby clusters, in which most of the enrichment of the ICM takes place before cluster formation, with significant later enrichment taking place only in cluster centres, as the stellar populations of the central galaxies evolve.

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

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn

Here, we use Chandra X-ray data to measure the metallicity of the intracluster medium (ICM) in 245 massive galaxy clusters selected from X-ray and Sunyaev–Zel'dovich (SZ) effect surveys, spanning redshifts 0 < z < 1.2. Metallicities were measured in three different radial ranges, spanning cluster cores through their outskirts. We explore trends in these measurements as a function of cluster redshift, temperature and surface brightness ‘peakiness’ (a proxy for gas cooling efficiency in cluster centres). The data at large radii (0.5–1 r500) are consistent with a constant metallicity, while at intermediate radii (0.1–0.5 r500) we see a late-time increase inmore » enrichment, consistent with the expected production and mixing of metals in cluster cores. In cluster centres, there are strong trends of metallicity with temperature and peakiness, reflecting enhanced metal production in the lowest entropy gas. Within the cool-core/sharply peaked cluster population, there is a large intrinsic scatter in central metallicity and no overall evolution, indicating significant astrophysical variations in the efficiency of enrichment. The central metallicity in clusters with flat surface brightness profiles is lower, with a smaller intrinsic scatter, but increases towards lower redshifts. Our results are consistent with other recent measurements of ICM metallicity as a function of redshift. They reinforce the picture implied by observations of uniform metal distributions in the outskirts of nearby clusters, in which most of the enrichment of the ICM takes place before cluster formation, with significant later enrichment taking place only in cluster centres, as the stellar populations of the central galaxies evolve.« less

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

PubMed

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

PubMed Central

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

Formation of young massive clusters from turbulent molecular clouds

NASA Astrophysics Data System (ADS)

Fujii, Michiko; Portegies Zwart, Simon

2015-08-01

We simulate the formation and evolution of young star clusters using smoothed-particle hydrodynamics (SPH) and direct N-body methods. We start by performing SPH simulations of the giant molecular cloud with a turbulent velocity field, a mass of 10^4 to 10^6 M_sun, and a density between 17 and 1700 cm^-3. We continue the SPH simulations for a free-fall time scale, and analyze the resulting structure of the collapsed cloud. We subsequently replace a density-selected subset of SPH particles with stars. As a consequence, the local star formation efficiency exceeds 30 per cent, whereas globally only a few per cent of the gas is converted to stars. The stellar distribution is very clumpy with typically a dozen bound conglomerates that consist of 100 to 10000 stars. We continue to evolve the stars dynamically using the collisional N-body method, which accurately treats all pairwise interactions, stellar collisions and stellar evolution. We analyze the results of the N-body simulations at 2 Myr and 10 Myr. From dense massive molecular clouds, massive clusters grow via hierarchical merging of smaller clusters. The shape of the cluster mass function that originates from an individual molecular cloud is consistent with a Schechter function with a power-law slope of beta = -1.73 at 2 Myr and beta = -1.67 at 10 Myr, which fits to observed cluster mass function of the Carina region. The superposition of mass functions have a power-law slope of < -2, which fits the observed mass function of star clusters in the Milky Way, M31 and M83. We further find that the mass of the most massive cluster formed in a single molecular cloud with a mass of M_g scales with 6.1 M_g^0.51 which also agrees with recent observation in M51. The molecular clouds which can form massive clusters are much denser than those typical in the Milky Way. The velocity dispersion of such molecular clouds reaches 20 km/s and it is consistent with the relative velocity of the molecular clouds observed near NGC 3603 and Westerlund 2, for which a triggered star formation by cloud-cloud collisions is suggested.

X-ray versus infrared selection of distant galaxy clusters: A case study using the XMM-LSS and SpARCS cluster samples

NASA Astrophysics Data System (ADS)

Willis, J. P.; Ramos-Ceja, M. E.; Muzzin, A.; Pacaud, F.; Yee, H. K. C.; Wilson, G.

2018-04-01

We present a comparison of two samples of z > 0.8 galaxy clusters selected using different wavelength-dependent techniques and examine the physical differences between them. We consider 18 clusters from the X-ray selected XMM-LSS distant cluster survey and 92 clusters from the optical-MIR selected SpARCS cluster survey. Both samples are selected from the same approximately 9 square degree sky area and we examine them using common XMM-Newton, Spitzer-SWIRE and CFHT Legacy Survey data. Clusters from each sample are compared employing aperture measures of X-ray and MIR emission. We divide the SpARCS distant cluster sample into three sub-samples: a) X-ray bright, b) X-ray faint, MIR bright, and c) X-ray faint, MIR faint clusters. We determine that X-ray and MIR selected clusters display very similar surface brightness distributions of galaxy MIR light. In addition, the average location and amplitude of the galaxy red sequence as measured from stacked colour histograms is very similar in the X-ray and MIR-selected samples. The sub-sample of X-ray faint, MIR bright clusters displays a distribution of BCG-barycentre position offsets which extends to higher values than all other samples. This observation indicates that such clusters may exist in a more disturbed state compared to the majority of the distant cluster population sampled by XMM-LSS and SpARCS. This conclusion is supported by stacked X-ray images for the X-ray faint, MIR bright cluster sub-sample that display weak, centrally-concentrated X-ray emission, consistent with a population of growing clusters accreting from an extended envelope of material.

Measuring the Mass Distribution in Z is Approximately 0.2 Cluster Lenses with XMM, HST and CFHT

NASA Technical Reports Server (NTRS)

2004-01-01

Being the most massive gravitationally bound objects in the Universe, clusters of galaxies are prime targets for studies of structure formation and evolution. Specifically the comoving space density of virialized clusters of a given mass (or X-ray temperature), but also the frequency and degree of substructure, as well as the shape of the cluster mass profile are quantities whose current values and evolution as a function of lookback time can provide important constraints on the cosmological and physical parameters of structure formation theories. The project funded by NASA grant NAG 5-10041 intended to take such studies to a new level by combining observations of a well-selected cluster sample by three state-of-the-art telescopes: HST, to accurately measure the mass distribution in the cluster core (approx. 0.5 h(sup -1)(sub 50) Mpc) via strong gravitational lensing; CFHT, to measure the large scale mass distribution out to approx. 3 Mpc via weak lensing; and XMM, to measure the gas density and temperature distribution accurately on intermediate scales < 1.5 Mpc. XMM plays a pivotal role in this context as the calibration of X-ray mass measurements through accurate, spatially resolved X-ray temperature measurements (particularly in the cosmologically most sensitive range of kT> 5 keV) is central to the questions outlined above. This set of observations promised to yield the best cluster mass measurements obtained so far for a representative sample, thus allowing us to: 1) Measure the high-mass end of the local cluster mass function; 2) Test predictions of a universal cluster mass profile; 3) calibrate the mass-temperature and temperature-luminosity relations for clusters and the scatter around these relations, which is vital for studies of cluster evolution using the X-ray temperature and X-ray luminosity functions.

Methane Oxidation to Methanol Catalyzed by Cu-Oxo Clusters Stabilized in NU-1000 Metal-Organic Framework.

PubMed

Ikuno, Takaaki; Zheng, Jian; Vjunov, Aleksei; Sanchez-Sanchez, Maricruz; Ortuño, Manuel A; Pahls, Dale R; Fulton, John L; Camaioni, Donald M; Li, Zhanyong; Ray, Debmalya; Mehdi, B Layla; Browning, Nigel D; Farha, Omar K; Hupp, Joseph T; Cramer, Christopher J; Gagliardi, Laura; Lercher, Johannes A

2017-08-02

Copper oxide clusters synthesized via atomic layer deposition on the nodes of the metal-organic framework (MOF) NU-1000 are active for oxidation of methane to methanol under mild reaction conditions. Analysis of chemical reactivity, in situ X-ray absorption spectroscopy, and density functional theory calculations are used to determine structure/activity relations in the Cu-NU-1000 catalytic system. The Cu-loaded MOF contained Cu-oxo clusters of a few Cu atoms. The Cu was present under ambient conditions as a mixture of ∼15% Cu + and ∼85% Cu 2+ . The oxidation of methane on Cu-NU-1000 was accompanied by the reduction of 9% of the Cu in the catalyst from Cu 2+ to Cu + . The products, methanol, dimethyl ether, and CO 2 , were desorbed with the passage of 10% water/He at 135 °C, giving a carbon selectivity for methane to methanol of 45-60%. Cu oxo clusters stabilized in NU-1000 provide an active, first generation MOF-based, selective methane oxidation catalyst.

Weak lensing magnification of SpARCS galaxy clusters

NASA Astrophysics Data System (ADS)

Tudorica, A.; Hildebrandt, H.; Tewes, M.; Hoekstra, H.; Morrison, C. B.; Muzzin, A.; Wilson, G.; Yee, H. K. C.; Lidman, C.; Hicks, A.; Nantais, J.; Erben, T.; van der Burg, R. F. J.; Demarco, R.

2017-12-01

Context. Measuring and calibrating relations between cluster observables is critical for resource-limited studies. The mass-richness relation of clusters offers an observationally inexpensive way of estimating masses. Its calibration is essential for cluster and cosmological studies, especially for high-redshift clusters. Weak gravitational lensing magnification is a promising and complementary method to shear studies, that can be applied at higher redshifts. Aims: We aim to employ the weak lensing magnification method to calibrate the mass-richness relation up to a redshift of 1.4. We used the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS) galaxy cluster candidates (0.2 < z < 1.4) and optical data from the Canada France Hawaii Telescope (CFHT) to test whether magnification can be effectively used to constrain the mass of high-redshift clusters. Methods: Lyman-break galaxies (LBGs) selected using the u-band dropout technique and their colours were used as a background sample of sources. LBG positions were cross-correlated with the centres of the sample of SpARCS clusters to estimate the magnification signal, which was optimally-weighted using an externally-calibrated LBG luminosity function. The signal was measured for cluster sub-samples, binned in both redshift and richness. Results: We measured the cross-correlation between the positions of galaxy cluster candidates and LBGs and detected a weak lensing magnification signal for all bins at a detection significance of 2.6-5.5σ. In particular, the significance of the measurement for clusters with z> 1.0 is 4.1σ; for the entire cluster sample we obtained an average M200 of 1.28 -0.21+0.23 × 1014 M⊙. Conclusions: Our measurements demonstrated the feasibility of using weak lensing magnification as a viable tool for determining the average halo masses for samples of high redshift galaxy clusters. The results also established the success of using galaxy over-densities to select massive clusters at z > 1. Additional studies are necessary for further modelling of the various systematic effects we discussed.

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

The Extended Northern ROSAT Galaxy Cluster Survey (NORAS II). I. Survey Construction and First Results

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

Böhringer, Hans; Chon, Gayoung; Trümper, Joachim

As the largest, clearly defined building blocks of our universe, galaxy clusters are interesting astrophysical laboratories and important probes for cosmology. X-ray surveys for galaxy clusters provide one of the best ways to characterize the population of galaxy clusters. We provide a description of the construction of the NORAS II galaxy cluster survey based on X-ray data from the northern part of the ROSAT All-Sky Survey. NORAS II extends the NORAS survey down to a flux limit of 1.8 × 10{sup −12} erg s{sup −1} cm{sup −2} (0.1–2.4 keV), increasing the sample size by about a factor of two. The NORAS IImore » cluster survey now reaches the same quality and depth as its counterpart, the southern REFLEX II survey, allowing us to combine the two complementary surveys. The paper provides information on the determination of the cluster X-ray parameters, the identification process of the X-ray sources, the statistics of the survey, and the construction of the survey selection function, which we provide in numerical format. Currently NORAS II contains 860 clusters with a median redshift of z  = 0.102. We provide a number of statistical functions, including the log N –log S and the X-ray luminosity function and compare these to the results from the complementary REFLEX II survey. Using the NORAS II sample to constrain the cosmological parameters, σ {sub 8} and Ω{sub m}, yields results perfectly consistent with those of REFLEX II. Overall, the results show that the two hemisphere samples, NORAS II and REFLEX II, can be combined without problems into an all-sky sample, just excluding the zone of avoidance.« less

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

NASA Astrophysics Data System (ADS)

Brown, Aidan; Rutenberg, Andrew

2015-03-01

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

X-ray versus infrared selection of distant galaxy clusters: a case study using the XMM-LSS and SpARCS cluster samples

NASA Astrophysics Data System (ADS)

Willis, J. P.; Ramos-Ceja, M. E.; Muzzin, A.; Pacaud, F.; Yee, H. K. C.; Wilson, G.

2018-07-01

We present a comparison of two samples of z> 0.8 galaxy clusters selected using different wavelength-dependent techniques and examine the physical differences between them. We consider 18 clusters from the X-ray-selected XMM Large Scale Structure (LSS) distant cluster survey and 92 clusters from the optical-mid-infrared (MIR)-selected Spitzer Adaptation of the Red Sequence Cluster survey (SpARCS) cluster survey. Both samples are selected from the same approximately 9 sq deg sky area and we examine them using common XMM-Newton, Spitizer Wide-Area Infrared Extra-galactic (SWIRE) survey, and Canada-France-Hawaii Telescope Legacy Survey data. Clusters from each sample are compared employing aperture measures of X-ray and MIR emission. We divide the SpARCS distant cluster sample into three sub-samples: (i) X-ray bright, (ii) X-ray faint, MIR bright, and (iii) X-ray faint, MIR faint clusters. We determine that X-ray- and MIR-selected clusters display very similar surface brightness distributions of galaxy MIR light. In addition, the average location and amplitude of the galaxy red sequence as measured from stacked colour histograms is very similar in the X-ray- and MIR-selected samples. The sub-sample of X-ray faint, MIR bright clusters displays a distribution of brightest cluster galaxy-barycentre position offsets which extends to higher values than all other samples. This observation indicates that such clusters may exist in a more disturbed state compared to the majority of the distant cluster population sampled by XMM-LSS and SpARCS. This conclusion is supported by stacked X-ray images for the X-ray faint, MIR bright cluster sub-sample that display weak, centrally concentrated X-ray emission, consistent with a population of growing clusters accreting from an extended envelope of material.

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-08-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics |*| the infamous |*|gastrophysics|*| in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-09-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics -- the infamous ``gastrophysics''-- in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

Neurobiological indicators of disinhibition in posttraumatic stress disorder.

PubMed

Sadeh, Naomi; Spielberg, Jeffrey M; Miller, Mark W; Milberg, William P; Salat, David H; Amick, Melissa M; Fortier, Catherine B; McGlinchey, Regina E

2015-08-01

Deficits in impulse control are increasingly recognized in association with posttraumatic stress disorder (PTSD). To our further understanding of the neurobiology of PTSD-related disinhibition, we examined alterations in brain morphology and network connectivity associated with response inhibition failures and PTSD severity. The sample consisted of 189 trauma-exposed Operation Enduring Freedom/Operation Iraqi Freedom veterans (89% male, ages 19-62) presenting with a range of current PTSD severity. Disinhibition was measured using commission errors on a Go/No-Go (GNG) task with emotional stimuli, and PTSD was assessed using a measure of current symptom severity. Whole-brain vertex-wise analyses of cortical thickness revealed two clusters associated with PTSD-related disinhibition (Monte Carlo cluster corrected P < 0.05). The first cluster included portions of right inferior and middle frontal gyri and frontal pole. The second cluster spanned portions of left medial orbital frontal, rostral anterior cingulate, and superior frontal gyrus. In both clusters, commission errors were associated with reduced cortical thickness at higher (but not lower) levels of PTSD symptoms. Resting-state functional magnetic resonance imaging analyses revealed alterations in the functional connectivity of the right frontal cluster. Together, study findings suggest that reductions in cortical thickness in regions involved in flexible decision-making, emotion regulation, and response inhibition contribute to impulse control deficits in PTSD. Furthermore, aberrant coupling between frontal regions and networks involved in selective attention, memory/learning, and response preparation suggest disruptions in functional connectivity may also play a role. © 2015 Wiley Periodicals, Inc.

Exhaustive comparison and classification of ligand-binding surfaces in proteins

PubMed Central

Murakami, Yoichi; Kinoshita, Kengo; Kinjo, Akira R; Nakamura, Haruki

2013-01-01

Many proteins function by interacting with other small molecules (ligands). Identification of ligand-binding sites (LBS) in proteins can therefore help to infer their molecular functions. A comprehensive comparison among local structures of LBSs was previously performed, in order to understand their relationships and to classify their structural motifs. However, similar exhaustive comparison among local surfaces of LBSs (patches) has never been performed, due to computational complexity. To enhance our understanding of LBSs, it is worth performing such comparisons among patches and classifying them based on similarities of their surface configurations and electrostatic potentials. In this study, we first developed a rapid method to compare two patches. We then clustered patches corresponding to the same PDB chemical component identifier for a ligand, and selected a representative patch from each cluster. We subsequently exhaustively as compared the representative patches and clustered them using similarity score, PatSim. Finally, the resultant PatSim scores were compared with similarities of atomic structures of the LBSs and those of the ligand-binding protein sequences and functions. Consequently, we classified the patches into ∼2000 well-characterized clusters. We found that about 63% of these clusters are used in identical protein folds, although about 25% of the clusters are conserved in distantly related proteins and even in proteins with cross-fold similarity. Furthermore, we showed that patches with higher PatSim score have potential to be involved in similar biological processes. PMID:23934772

Mutiple Stellar Populations in Blanco DECam Bulge Survey Globular Clusters

NASA Astrophysics Data System (ADS)

Miller, Doryan; Pilachowski, C. A.; Johnson, C. I.; Rich, R. Michael; Clarkson, William I.; Young, M.; Michael, S.

2018-01-01

Preliminary SDSS ugrizY photometric observations of globular cluster stars included in the Blanco DECam Bulge Survey (BDBS) were examined to determine the suitability of these data to characterize stellar populations within clusters. The BDBS fields include around two dozen globular clusters, including the iron-complex cluster M22 and the pulsar-rich cluster Terzan 5. Many globular clusters show evidence for multiple stellar populations as a spread in the u-g color of stars in a given phase of stellar evolution, and in some clusters, the populations have different radial distributions. BDBS clusters with low and/or non-variable reddening and long dynamical mixing time scales were selected for study, and photometry for RGB and main sequence stars within two half-light radii from the center of each cluster was extracted from the BDBS preliminary catalog. Field contamination was reduced in each candidate cluster by removing all stars more than a tenth of a magnitude from the best-fit fiducial curves following the g-r vs r color-magnitude diagram. The remaining stars were split into separate populations based on u-g color, and effective cumulative distribution functions vs. half-light radius were compared to identify differences in the populations’ radial distributions.

Effects of levomilnacipran ER on noradrenergic symptoms, anxiety symptoms, and functional impairment in adults with major depressive disorder: Post hoc analysis of 5 clinical trials.

PubMed

Blier, Pierre; Gommoll, Carl; Chen, Changzheng; Kramer, Kenneth

2017-03-01

To evaluate the effects of levomilnacipran extended-release (LVM-ER; 40-120mg/day) on noradrenergic (NA) and anxiety-related symptoms in adults with major depressive disorder (MDD) and explore the relationship between these symptoms and functional impairment. Data were pooled from 5 randomized, double-blind, placebo-controlled trials (N=2598). Anxiety and NA Cluster scores were developed by adding selected item scores from the Montgomery-Åsberg Depression Rating Scale (MADRS) and 17-item Hamilton Depression Rating Scale (HAMD 17 ). A path analysis was conducted to estimate the direct effects of LVM-ER on functional impairment (Sheehan Disability Scale [SDS] total score) and the indirect effects through changes in NA and Anxiety Cluster scores. Mean improvements from baseline in NA and Anxiety Cluster scores were significantly greater with LVM-ER versus placebo (both P<0.001), as were the response rates (≥50% score improvement): NA Cluster (44% vs 34%; odds ratio=1.56; P<0.0001); Anxiety Cluster (39% vs 36%; odds ratio=1.19; P=0.041). Mean improvement in SDS total score was also significantly greater with LVM-ER versus placebo (-7.3 vs -5.6; P<0.0001). LVM-ER had an indirect effect on change in SDS total score that was mediated more strongly through NA Cluster score change (86%) than Anxiety Cluster score change (18%); the direct effect was negligible. NA and Anxiety Cluster scores, developed based on the face validity of individual MADRS and HAMD 17 items, were not predefined as efficacy outcomes in any of the studies. In adults with MDD, LVM-ER indirectly improved functional impairment mainly through improvements in NA symptoms and less so via anxiety symptoms. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Constraints on the Energy Content of the Universe from a Combination of Galaxy Cluster Observables

NASA Technical Reports Server (NTRS)

Molnar, Sandor M.; Haiman, Zoltan; Birkinshaw, Mark; Mushotzky, Richard F.

2003-01-01

We demonstrate that constraints on cosmological parameters from the distribution of clusters as a function of redshift (dN/dz) are complementary to accurate angular diameter distance (D(sub A)) measurements to clusters, and their combination significantly tightens constraints on the energy density content of the Universe. The number counts can be obtained from X-ray and/or SZ (Sunyaev-Ze'dovich effect) surveys, and the angular diameter distances can be determined from deep observations of the intra-cluster gas using their thermal bremsstrahlung X-ray emission and the SZ effect. We combine constraints from simulated cluster number counts expected from a 12 deg(sup 2) SZ cluster survey and constraints from simulated angular diameter distance measurements based on the X-ray/SZ method assuming a statistical accuracy of 10% in the angular diameter distance determination of 100 clusters with redshifts less than 1.5. We find that Omega(sub m), can be determined within about 25%, Omega(sub lambda) within 20% and w within 16%. We show that combined dN/dz+(sub lambda) constraints can be used to constrain the different energy densities in the Universe even in the presence of a few percent redshift dependent systematic error in D(sub lambda). We also address the question of how best to select clusters of galaxies for accurate diameter distance determinations. We show that the joint dN/dz+ D(lambda) constraints on cosmological parameters for a fixed target accuracy in the energy density parameters are optimized by selecting clusters with redshift upper cut-offs in the range 0.55 approx. less than 1. Subject headings: cosmological parameters - cosmology: theory - galaxies:clusters: general

CODEX weak lensing: concentration of galaxy clusters at z ~ 0.5

DOE PAGES

Cibirka, N.; Cypriano, E. S.; Brimioulle, F.; ...

2017-03-04

Here, we present a stacked weak-lensing analysis of 27 richness selected galaxy clusters at 0.40 ≤ z ≤ 0.62 in the COnstrain Dark Energy with X-ray galaxy clusters (CODEX) survey. The fields were observed in five bands with the Canada–France–Hawaii Telescope (CFHT). We measure the stacked surface mass density profile with a 14σ significance in the radial range 0.1 < RMpch -1 < 2.5. The profile is well described by the halo model, with the main halo term following a Navarro–Frenk–White profile (NFW) profile and including the off-centring effect. We select the background sample using a conservative colour–magnitude method to reduce the potential systematic errors and contamination by cluster member galaxies. We perform a Bayesian analysis for the stacked profile and constrain the best-fitting NFW parameters M 200c=6.6more » $$+1.0\\atop{-0.8}$$×10 14h -1 M⊙ and c 200c=3.7$$+0.7\\atop{-0.6}$$. The off-centring effect was modelled based on previous observational results found for redMaPPer Sloan Digital Sky Survey clusters. Our constraints on M200c and c200c allow us to investigate the consistency with numerical predictions and select a concentration–mass relation to describe the high richness CODEX sample. Comparing our best-fitting values for M200c and c200c with other observational surveys at different redshifts, we find no evidence for evolution in the concentration–mass relation, though it could be mitigated by particular selection functions. Similar to previous studies investigating the X-ray luminosity–mass relation, our data suggest a lower evolution than expected from self-similarity.« less

The galaxy luminosity function around groups

NASA Astrophysics Data System (ADS)

González, R. E.; Padilla, N. D.; Galaz, G.; Infante, L.

2005-11-01

We present a study on the variations of the luminosity function of galaxies around clusters in a numerical simulation with semi-analytic galaxies, attempting to detect these variations in the 2dF Galaxy Redshift Survey. We subdivide the simulation box into equal-density regions around clusters, which we assume can be achieved by selecting objects at a given normalized distance (r/rrms, where rrms is an estimate of the halo radius) from the group centre. The semi-analytic model predicts important variations in the luminosity function out to r/rrms~= 5. In brief, variations in the mass function of haloes around clusters (large dark matter haloes with M > 1012h-1Msolar) lead to cluster central regions that present a high abundance of bright galaxies (high M* values) as well as low-luminosity galaxies (high α) at r/rrms~= 3 there is a lack of bright galaxies, which shows the depletion of galaxies in the regions surrounding clusters (minimum in M* and α), and a tendency to constant luminosity function parameters at larger cluster-centric distances. We take into account the observational biases present in the real data by reproducing the peculiar velocity effect on the redshifts of galaxies in the simulation box, and also by producing mock catalogues. We find that excluding from the analysis galaxies which in projection are close to the centres of the groups provides results that are qualitatively consistent with the full simulation box results. When we apply this method to mock catalogues of the 2dF Galaxy Redshift Survey (2dFGRS) and the 2PIGG catalogue of groups, we find that the variations in the luminosity function are almost completely erased by the Finger of God effect; only a lack of bright galaxies at r/rrms~= 3 can be marginally detected in the mock catalogues. The results from the real 2dFGRS data show a clearer detection of a dip in M* and α for r/rrms= 3, consistent with the semi-analytic predictions.

Random Walk Quantum Clustering Algorithm Based on Space

NASA Astrophysics Data System (ADS)

Xiao, Shufen; Dong, Yumin; Ma, Hongyang

2018-01-01

In the random quantum walk, which is a quantum simulation of the classical walk, data points interacted when selecting the appropriate walk strategy by taking advantage of quantum-entanglement features; thus, the results obtained when the quantum walk is used are different from those when the classical walk is adopted. A new quantum walk clustering algorithm based on space is proposed by applying the quantum walk to clustering analysis. In this algorithm, data points are viewed as walking participants, and similar data points are clustered using the walk function in the pay-off matrix according to a certain rule. The walk process is simplified by implementing a space-combining rule. The proposed algorithm is validated by a simulation test and is proved superior to existing clustering algorithms, namely, Kmeans, PCA + Kmeans, and LDA-Km. The effects of some of the parameters in the proposed algorithm on its performance are also analyzed and discussed. Specific suggestions are provided.

Ligand-protected gold clusters: the structure, synthesis and applications

NASA Astrophysics Data System (ADS)

Pichugina, D. A.; Kuz'menko, N. E.; Shestakov, A. F.

2015-11-01

Modern concepts of the structure and properties of atomic gold clusters protected by thiolate, selenolate, phosphine and phenylacetylene ligands are analyzed. Within the framework of the superatom theory, the 'divide and protect' approach and the structure rule, the stability and composition of a cluster are determined by the structure of the cluster core, the type of ligands and the total number of valence electrons. Methods of selective synthesis of gold clusters in solution and on the surface of inorganic composites based, in particular, on the reaction of Aun with RS, RSe, PhC≡C, Hal ligands or functional groups of proteins, on stabilization of clusters in cavities of the α-, β and γ-cyclodextrin molecules (Au15 and Au25) and on anchorage to a support surface (Au25/SiO2, Au20/C, Au10/FeOx) are reviewed. Problems in this field are also discussed. Among the methods for cluster structure prediction, particular attention is given to the theoretical approaches based on the density functional theory (DFT). The structures of a number of synthesized clusters are described using the results obtained by X-ray diffraction analysis and DFT calculations. A possible mechanism of formation of the SR(AuSR)n 'staple' units in the cluster shell is proposed. The structure and properties of bimetallic clusters MxAunLm (M=Pd, Pt, Ag, Cu) are discussed. The Pd or Pt atom is located at the centre of the cluster, whereas Ag and Cu atoms form bimetallic compounds in which the heteroatom is located on the surface of the cluster core or in the 'staple' units. The optical properties, fluorescence and luminescence of ligand-protected gold clusters originate from the quantum effects of the Au atoms in the cluster core and in the oligomeric SR(AuSR)x units in the cluster shell. Homogeneous and heterogeneous reactions catalyzed by atomic gold clusters are discussed in the context of the reaction mechanism and the nature of the active sites. The bibliography includes 345 references.

Automatic insertion of simulated microcalcification clusters in a software breast phantom

NASA Astrophysics Data System (ADS)

Shankla, Varsha; Pokrajac, David D.; Weinstein, Susan P.; DeLeo, Michael; Tuite, Catherine; Roth, Robyn; Conant, Emily F.; Maidment, Andrew D.; Bakic, Predrag R.

2014-03-01

An automated method has been developed to insert realistic clusters of simulated microcalcifications (MCs) into computer models of breast anatomy. This algorithm has been developed as part of a virtual clinical trial (VCT) software pipeline, which includes the simulation of breast anatomy, mechanical compression, image acquisition, image processing, display and interpretation. An automated insertion method has value in VCTs involving large numbers of images. The insertion method was designed to support various insertion placement strategies, governed by probability distribution functions (pdf). The pdf can be predicated on histological or biological models of tumor growth, or estimated from the locations of actual calcification clusters. To validate the automated insertion method, a 2-AFC observer study was designed to compare two placement strategies, undirected and directed. The undirected strategy could place a MC cluster anywhere within the phantom volume. The directed strategy placed MC clusters within fibroglandular tissue on the assumption that calcifications originate from epithelial breast tissue. Three radiologists were asked to select between two simulated phantom images, one from each placement strategy. Furthermore, questions were posed to probe the rationale behind the observer's selection. The radiologists found the resulting cluster placement to be realistic in 92% of cases, validating the automated insertion method. There was a significant preference for the cluster to be positioned on a background of adipose or mixed adipose/fibroglandular tissues. Based upon these results, this automated lesion placement method will be included in our VCT simulation pipeline.

Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

NASA Astrophysics Data System (ADS)

Hoomod, Haider K.; Kareem Jebur, Tuka

2018-05-01

Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

Fuzzy Subspace Clustering

NASA Astrophysics Data System (ADS)

Borgelt, Christian

In clustering we often face the situation that only a subset of the available attributes is relevant for forming clusters, even though this may not be known beforehand. In such cases it is desirable to have a clustering algorithm that automatically weights attributes or even selects a proper subset. In this paper I study such an approach for fuzzy clustering, which is based on the idea to transfer an alternative to the fuzzifier (Klawonn and Höppner, What is fuzzy about fuzzy clustering? Understanding and improving the concept of the fuzzifier, In: Proc. 5th Int. Symp. on Intelligent Data Analysis, 254-264, Springer, Berlin, 2003) to attribute weighting fuzzy clustering (Keller and Klawonn, Int J Uncertain Fuzziness Knowl Based Syst 8:735-746, 2000). In addition, by reformulating Gustafson-Kessel fuzzy clustering, a scheme for weighting and selecting principal axes can be obtained. While in Borgelt (Feature weighting and feature selection in fuzzy clustering, In: Proc. 17th IEEE Int. Conf. on Fuzzy Systems, IEEE Press, Piscataway, NJ, 2008) I already presented such an approach for a global selection of attributes and principal axes, this paper extends it to a cluster-specific selection, thus arriving at a fuzzy subspace clustering algorithm (Parsons, Haque, and Liu, 2004).

The enhancement of rapidly quenched galaxies in distant clusters at 0.5 < z < 1.0

NASA Astrophysics Data System (ADS)

Socolovsky, Miguel; Almaini, Omar; Hatch, Nina A.; Wild, Vivienne; Maltby, David T.; Hartley, William G.; Simpson, Chris

2018-05-01

We investigate the relationship between environment and galaxy evolution in the redshift range 0.5 < z < 1.0. Galaxy overdensities are selected using a friends-of-friends algorithm, applied to deep photometric data in the Ultra-Deep Survey field. A study of the resulting stellar mass functions reveals clear differences between cluster and field environments, with a strong excess of low-mass rapidly quenched galaxies in cluster environments compared to the field. Cluster environments also show a corresponding deficit of young, low-mass star-forming galaxies, which show a sharp radial decline towards cluster centres. By comparing mass functions and radial distributions, we conclude that young star-forming galaxies are rapidly quenched as they enter overdense environments, becoming post-starburst galaxies before joining the red sequence. Our results also point to the existence of two environmental quenching pathways operating in galaxy clusters, operating on different time-scales. Fast quenching acts on galaxies with high specific star formation rates, operating on time-scales shorter than the cluster dynamical time (<1 Gyr). In contrast, slow quenching affects galaxies with moderate specific star formation rates, regardless of their stellar mass, and acts on longer time-scales (≳ 1 Gyr). Of the cluster galaxies in the stellar mass range 9.0 < log (M/M⊙) < 10.5 quenched during this epoch, we find that 73 per cent were transformed through fast quenching, while the remaining 27 per cent followed the slow quenching route.

Pattern Genes Suggest Functional Connectivity of Organs

NASA Astrophysics Data System (ADS)

Qin, Yangmei; Pan, Jianbo; Cai, Meichun; Yao, Lixia; Ji, Zhiliang

2016-05-01

Human organ, as the basic structural and functional unit in human body, is made of a large community of different cell types that organically bound together. Each organ usually exerts highly specified physiological function; while several related organs work smartly together to perform complicated body functions. In this study, we present a computational effort to understand the roles of genes in building functional connection between organs. More specifically, we mined multiple transcriptome datasets sampled from 36 human organs and tissues, and quantitatively identified 3,149 genes whose expressions showed consensus modularly patterns: specific to one organ/tissue, selectively expressed in several functionally related tissues and ubiquitously expressed. These pattern genes imply intrinsic connections between organs. According to the expression abundance of the 766 selective genes, we consistently cluster the 36 human organs/tissues into seven functional groups: adipose & gland, brain, muscle, immune, metabolism, mucoid and nerve conduction. The organs and tissues in each group either work together to form organ systems or coordinate to perform particular body functions. The particular roles of specific genes and selective genes suggest that they could not only be used to mechanistically explore organ functions, but also be designed for selective biomarkers and therapeutic targets.

The metallicity of the intracluster medium over cosmic time: further evidence for early enrichment

DOE PAGES

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn; ...

2017-08-26

Here, we use Chandra X-ray data to measure the metallicity of the intracluster medium (ICM) in 245 massive galaxy clusters selected from X-ray and Sunyaev–Zel'dovich (SZ) effect surveys, spanning redshifts 0 < z < 1.2. Metallicities were measured in three different radial ranges, spanning cluster cores through their outskirts. We explore trends in these measurements as a function of cluster redshift, temperature and surface brightness ‘peakiness’ (a proxy for gas cooling efficiency in cluster centres). The data at large radii (0.5–1 r500) are consistent with a constant metallicity, while at intermediate radii (0.1–0.5 r500) we see a late-time increase inmore » enrichment, consistent with the expected production and mixing of metals in cluster cores. In cluster centres, there are strong trends of metallicity with temperature and peakiness, reflecting enhanced metal production in the lowest entropy gas. Within the cool-core/sharply peaked cluster population, there is a large intrinsic scatter in central metallicity and no overall evolution, indicating significant astrophysical variations in the efficiency of enrichment. The central metallicity in clusters with flat surface brightness profiles is lower, with a smaller intrinsic scatter, but increases towards lower redshifts. Our results are consistent with other recent measurements of ICM metallicity as a function of redshift. They reinforce the picture implied by observations of uniform metal distributions in the outskirts of nearby clusters, in which most of the enrichment of the ICM takes place before cluster formation, with significant later enrichment taking place only in cluster centres, as the stellar populations of the central galaxies evolve.« less

Interplay between oxygen and Fe-S cluster biogenesis: insights from the Suf pathway.

PubMed

Boyd, Eric S; Thomas, Khaleh M; Dai, Yuyuan; Boyd, Jeff M; Outten, F Wayne

2014-09-23

Iron-sulfur (Fe-S) cluster metalloproteins conduct essential functions in nearly all contemporary forms of life. The nearly ubiquitous presence of Fe-S clusters and the fundamental requirement for Fe-S clusters in both aerobic and anaerobic Archaea, Bacteria, and Eukarya suggest that these clusters were likely integrated into central metabolic pathways early in the evolution of life prior to the widespread oxidation of Earth's atmosphere. Intriguingly, Fe-S cluster-dependent metabolism is sensitive to disruption by oxygen because of the decreased bioavailability of ferric iron as well as direct oxidation of sulfur trafficking intermediates and Fe-S clusters by reactive oxygen species. This fact, coupled with the ubiquity of Fe-S clusters in aerobic organisms, suggests that organisms evolved with mechanisms that facilitate the biogenesis and use of these essential cofactors in the presence of oxygen, which gradually began to accumulate around 2.5 billion years ago as oxygenic photosynthesis proliferated and reduced minerals that buffered against oxidation were depleted. This review highlights the most ancient of the Fe-S cluster biogenesis pathways, the Suf system, which likely was present in early anaerobic forms of life. Herein, we use the evolution of the Suf pathway to assess the relationships between the biochemical functions and physiological roles of Suf proteins, with an emphasis on the selective pressure of oxygen toxicity. Our analysis suggests that diversification into oxygen-containing environments disrupted iron and sulfur metabolism and was a main driving force in the acquisition of accessory Suf proteins (such as SufD, SufE, and SufS) by the core SufB-SufC scaffold complex. This analysis provides a new framework for the study of Fe-S cluster biogenesis pathways and Fe-S cluster-containing metalloenzymes and their complicated patterns of divergence in response to oxygen.

EVIDENCE FOR THE UNIVERSALITY OF PROPERTIES OF RED-SEQUENCE GALAXIES IN X-RAY- AND RED-SEQUENCE-SELECTED CLUSTERS AT z ∼ 1

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

Foltz, R.; Wilson, G.; DeGroot, A.

We study the slope, intercept, and scatter of the color–magnitude and color–mass relations for a sample of 10 infrared red-sequence-selected clusters at z ∼ 1. The quiescent galaxies in these clusters formed the bulk of their stars above z ≳ 3 with an age spread Δt ≳ 1 Gyr. We compare UVJ color–color and spectroscopic-based galaxy selection techniques, and find a 15% difference in the galaxy populations classified as quiescent by these methods. We compare the color–magnitude relations from our red-sequence selected sample with X-ray- and photometric-redshift-selected cluster samples of similar mass and redshift. Within uncertainties, we are unable tomore » detect any difference in the ages and star formation histories of quiescent cluster members in clusters selected by different methods, suggesting that the dominant quenching mechanism is insensitive to cluster baryon partitioning at z ∼ 1.« less

Cluster model studies of anion and molecular specificities via electrospray ionization photoelectron spectroscopy

DOE PAGES

Wang, Xue -Bin

2017-01-06

Ion specificity, a widely observed macroscopic phenomenon in condensed phases and at interfaces, is essentially a fundamental chemical physical issue. We have been investigating such effects using cluster models in an “atom-by-atom” and “molecule-by-molecule” fashion not possible with condensed-phase methods. We use electrospray ionization (ESI) to generate molecular and ionic clusters to simulate key molecular entities involved in local binding regions, and characterize them employing negative ion photoelectron spectroscopy (NIPES). Inter- and intramolecular interactions and binding configurations are directly obtained as functions of cluster size and composition, providing insightful molecular-level description and characterization over the local active sites that playmore » crucial roles in determining solution chemistry and condensed phase phenomena. Finally, the topics covered in this article are relevant to a wide scope of research fields ranging from ion specific effects in electrolyte solutions, ion selectivity/recognition in normal functioning of life, to molecular specificity in aerosol particle formation, as well as in rational material design and synthesis.« less

Structural and magnetic properties of FeGen-/0 (n = 3-12) clusters: Mass-selected anion photoelectron spectroscopy and density functional theory calculations

NASA Astrophysics Data System (ADS)

Deng, Xiao-Jiao; Kong, Xiang-Yu; Liang, Xiaoqing; Yang, Bin; Xu, Hong-Guang; Xu, Xi-Ling; Feng, Gang; Zheng, Wei-Jun

2017-12-01

The structural, electronic, and magnetic properties of FeGen-/0 (n = 3-12) clusters were investigated by using anion photoelectron spectroscopy in combination with density functional theory calculations. For both anionic and neutral FeGen (n = 3-12) clusters with n ≤ 7, the dominant structures are exohedral. The FeGe8-/0 clusters have half-encapsulated boat-shaped structures, and the opening of the boat-shaped structure is gradually covered by the additional Ge atoms to form Gen cage from n = 9 to 11. The structures of FeGe10-/0 can be viewed as two Ge atoms symmetrically capping the opening of the boat-shaped structure of FeGe8, and those of FeGe12-/0 are distorted hexagonal prisms with the Fe atom at the center. Natural population analysis shows that there is an electron transfer from the Ge atoms to the Fe atom at n = 8-12. The total magnetic moment of FeGen-/0 and local magnetic moment of the Fe atom have not been quenched.

Infrared spectroscopy of protonated trimethylamine-(benzene)(n) (n = 1-4) as model clusters of the quaternary ammonium-aromatic ring interaction.

PubMed

Shishido, Ryunosuke; Kawai, Yuki; Fujii, Asuka

2014-09-04

The essence of the molecular recognition of the neurotransmitter acetylcholine has been attributed to the attractive interaction between a quaternary ammonium and aromatic rings. We employed protonated trimethylamine-(benzene)n clusters (n = 1-4) in the gas phase as a model to study the recognition mechanism of acetylcholine at the microscopic level. We applied size-selective infrared spectroscopy to the clusters and observed the NH and CH stretching vibrational regions. We also performed density functional theory calculations of stable structures, charge distributions, and infrared spectra of the clusters. It was shown that the methyl groups of protonated trimethylamine are solvated by benzene one at a time in the n > 1 clusters, and the validity of these clusters as a model system of the acetylcholine recognition was demonstrated. The nature of the interactions between a quaternary ammonium and aromatic rings is discussed on the basis of the observed infrared spectra and the theoretical calculations.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

PubMed

Sammond, Deanne W; Kastelowitz, Noah; Himmel, Michael E; Yin, Hang; Crowley, Michael F; Bomble, Yannick J

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms

PubMed Central

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.; Yin, Hang; Crowley, Michael F.; Bomble, Yannick J.

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions. PMID:26741367

Autophagy selectivity through receptor clustering

NASA Astrophysics Data System (ADS)

Rutenberg, Andrew; Brown, Aidan

Substrate selectivity in autophagy requires an all-or-none cellular response. We focus on peroxisomes, for which autophagy receptor proteins NBR1 and p62 are well characterized. Using computational models, we explore the hypothesis that physical clustering of autophagy receptor proteins on the peroxisome surface provides an appropriate all-or-none response. We find that larger peroxisomes nucleate NBR1 clusters first, and lose them due to competitive coarsening last, resulting in significant size-selectivity. We then consider a secondary hypothesis that p62 inhibits NBR1 cluster formation. We find that p62 inhibition enhances size-selectivity enough that, even if there is no change of the pexophagy rate, the volume of remaining peroxisomes can significantly decrease. We find that enhanced ubiquitin levels suppress size-selectivity, and that this effect is more pronounced for individual peroxisomes. Sufficient ubiquitin allows receptor clusters to form on even the smallest peroxisomes. We conclude that NBR1 cluster formation provides a viable physical mechanism for all-or-none substrate selectivity in pexophagy. We predict that cluster formation is associated with significant size-selectivity. Now at Simon Fraser University.

Nuclear structure studies performed using the (18O,16O) two-neutron transfer reactions

NASA Astrophysics Data System (ADS)

Carbone, D.; Agodi, C.; Cappuzzello, F.; Cavallaro, M.; Ferreira, J. L.; Foti, A.; Gargano, A.; Lenzi, S. M.; Linares, R.; Lubian, J.; Santagati, G.

2018-02-01

Excitation energy spectra and absolute cross section angular distributions were measured for the 13C(18O,16O)15C two-neutron transfer reaction at 84 MeV incident energy. This reaction selectively populates two-neutron configurations in the states of the residual nucleus. Exact finite-range coupled reaction channel calculations are used to analyse the data. Two approaches are discussed: the extreme cluster and the newly introduced microscopic cluster. The latter makes use of spectroscopic amplitudes in the centre of mass reference frame, derived from shell-model calculations using the Moshinsky transformation brackets. The results describe well the experimental cross section and highlight cluster configurations in the involved wave functions.

From Head to Sword: The Clustering Properties of Stars in Orion

NASA Astrophysics Data System (ADS)

Gomez, Mercedes; Lada, Charles J.

1998-04-01

We investigate the structure in the spatial distributions of optically selected samples of young stars in the Head (lambda Orionis) and in the Sword (Orion A) regions of the constellation of Orion with the aid of stellar surface density maps and the two-point angular correlation function. The distributions of young stars in both regions are found to be nonrandom and highly clustered. Stellar surface density maps reveal three distinct clusters in the lambda Ori region. The two-point correlation function displays significant features at angular scales that correspond to the radii and separations of the three clusters identified in the surface density maps. Most young stars in the lambda Ori region (~80%) are presently found within these three clusters, consistent with the idea that the majority of young stars in this region were formed in dense protostellar clusters that have significantly expanded since their formation. Over a scale of ~0.05d-0.5d the correlation function is well described by a single power law that increases smoothly with decreasing angular scale. This suggests that, within the clusters, the stars either are themselves hierarchically clustered or have a volume density distribution that falls steeply with radius. The relative lack of Hα emission-line stars in the one cluster in this region that contains OB stars suggests a timescale for emission-line activity of less than 4 Myr around late-type stars in the cluster and may indicate that the lifetimes of protoplanetary disks around young stellar objects are reduced in clusters containing O stars. The spatial distribution of young stars in the Orion A region is considerably more complex. The angular correlation function of the OB stars (which are mostly foreground to the Orion A molecular cloud) is very similar to that of the Hα stars (which are located mostly within the molecular cloud) and significantly different from that of the young stars in the lambda Ori region. This suggests that, although spatially separated, both populations in the Orion A region may have originated from a similar fragmentation process. Stellar surface density maps and modeling of the angular correlation function suggest that somewhat less than half of the OB and Hα stars in the Orion A cloud are presently within well-defined stellar clusters. Although all the OB stars could have originated in rich clusters, a significant fraction of the Hα stars appear to have formed outside such clusters in a more spatially dispersed manner. The close similarity of the angular correlation functions of the OB and Hα stars toward the molecular cloud, in conjunction with the earlier indications of a relatively high star formation rate and high gas pressure in this cloud, is consistent with the idea that older, foreground OB stars triggered the current episode of star formation in the Orion A cloud. One of the OB clusters (Upper Sword) that is foreground to the cloud does not appear to be associated with any of the clusterings of emission-line stars, again suggesting a timescale (<4 Myr) for emission-line activity and disk lifetimes around late-type stars born in OB clusters.

NEW CONSTRAINTS ON MASS-DEPENDENT DISRUPTION OF STAR CLUSTERS IN M51

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

Chandar, Rupali; Whitmore, Bradley C.; Regan, Michael

2011-02-01

We use UBVI H{alpha} images of the Whirlpool galaxy, M51, taken with the Advanced Camera for Surveys and WFPC2 cameras on the Hubble Space Telescope (HST) to select star clusters, and to estimate their masses and ages by comparing their observed colors with predictions from population synthesis models. We construct the mass function of intermediate-age (1-4 x 10{sup 8} yr) clusters, and find that it is well described by a power law, {psi}(M) {proportional_to} M{sup {beta}}, with {beta} = -2.1 {+-} 0.2, for clusters more massive than M {approx} 6 x 10{sup 3} M{sub sun}. This extends the mass functionmore » of intermediate-age clusters in M51 to masses lower by nearly a factor of five over previous determinations. The mass function does not show evidence for curvature at either the high or low mass end. This shape indicates that there is no evidence for the earlier disruption of lower mass clusters compared with their higher mass counterparts (i.e., no mass-dependent disruption) over the observed range of masses and ages, or for a physical upper mass limit M{sub C} with which clusters in M51 can form. These conclusions differ from previous suggestions based on poorer-quality HST observations. We discuss their implications for the formation and disruption of the clusters. Ages of clusters in two 'feathers', stellar features extending from the outer portion of a spiral arm, show that the feather with a larger pitch angle formed earlier, and over a longer period, than the other.« less

Cold dark energy constraints from the abundance of galaxy clusters

DOE PAGES

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

2017-10-05

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

Cold dark energy constraints from the abundance of galaxy clusters

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

Heneka, Caroline; Rapetti, David; Cataneo, Matteo

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

Photometric redshifts as a tool for studying the Coma cluster galaxy populations

NASA Astrophysics Data System (ADS)

Adami, C.; Ilbert, O.; Pelló, R.; Cuillandre, J. C.; Durret, F.; Mazure, A.; Picat, J. P.; Ulmer, M. P.

2008-12-01

Aims: We apply photometric redshift techniques to an investigation of the Coma cluster galaxy luminosity function (GLF) at faint magnitudes, in particular in the u* band where basically no studies are presently available at these magnitudes. Methods: Cluster members were selected based on probability distribution function from photometric redshift calculations applied to deep u^*, B, V, R, I images covering a region of almost 1 deg2 (completeness limit R ~ 24). In the area covered only by the u* image, the GLF was also derived after a statistical background subtraction. Results: Global and local GLFs in the B, V, R, and I bands obtained with photometric redshift selection are consistent with our previous results based on a statistical background subtraction. The GLF in the u* band shows an increase in the faint end slope towards the outer regions of the cluster. The analysis of the multicolor type spatial distribution reveals that late type galaxies are distributed in clumps in the cluster outskirts, where X-ray substructures are also detected and where the GLF in the u* band is steeper. Conclusions: We can reproduce the GLFs computed with classical statistical subtraction methods by applying a photometric redshift technique. The u* GLF slope is steeper in the cluster outskirts, varying from α ~ -1 in the cluster center to α ~ -2 in the cluster periphery. The concentrations of faint late type galaxies in the cluster outskirts could explain these very steep slopes, assuming a short burst of star formation in these galaxies when entering the cluster. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is also partly based on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. Also based on data from W. M. Keck Observatory which is operated as a scientific partnership between the California Institute of Technology, the University of California, and NASA. It was made possible by the generous financial support of the W. M. Keck Foundation.

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

PubMed Central

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

Spitzer Imaging of Planck-Herschel Dusty Proto-Clusters at z=2-3

NASA Astrophysics Data System (ADS)

Cooray, Asantha; Ma, Jingzhe; Greenslade, Joshua; Kubo, Mariko; Nayyeri, Hooshang; Clements, David; Cheng, Tai-An

2018-05-01

We have recently introduced a new proto-cluster selection technique by combing Herschel/SPIRE imaging data and Planck/HFIk all-sky survey point source catalog. These sources are identified as Planck point sources with clumps of Herschel source over-densities with far-IR colors comparable to z=0 ULIRGS redshifted to z=2 to 3. The selection is sensitive to dusty starbursts and obscured QSOs and we have recovered couple of the known proto-clusters and close to 30 new proto-clusters. The candidate proto-clusters selected from this technique have far-IR flux densities several times higher than those that are optically selected, such as using LBG selection, implying that the member galaxies are in a special phase of heightened dusty starburst and dusty QSO activity. This far-IR luminous phase may be short but likely to be necessary piece to understand the whole stellar mass assembly history of clusters. Moreover, our photo-clusters are missed in optical selections, suggesting that optically selected proto-clusters alone do not provide adequate statistics and a comparison of the far-IR and optical selected clusters may reveal the importance of the dusty stellar mass assembly. Here, we propose IRAC observations of six of the highest priority new proto-clusters, to establish the validity of the technique and to determine the total stellar mass through SED models. For a modest observing time the science program will have a substantial impact on an upcoming science topic in cosmology with implications for observations with JWST and WFIRST to understand the mass assembly in the universe.

Homosexual Fellatio: Erect Penis Licking between Male Bonin Flying Foxes Pteropus pselaphon

PubMed Central

Sugita, Norimasa

2016-01-01

A recent focus of interest has been on the functional significance of genital licking (fellatio and cunnilingus) in relation to sexual selection in Pteropodid bats. In the present paper, a form of fellatio in wild Bonin flying foxes, Pteropus pselaphon, performed between adult males has been reported. During the mating season, adult flying foxes roost in same-sex groups, forming ball-shaped clusters which provide warmth. The female clusters may also contain a few males. Unassociated with allogrooming, same-sex genital licking occurred among males in the all male clusters. As such, male-male fellatio can be considered as homosexual behavior, two functional explanations could account for this behavior; the social bonding and the social tension regulation hypotheses suggested in a previous review. Given that neither the simpler alternative that in all male groups such fellatio may represent misdirected sexual behavior, nor the two previously proposed functional hypotheses were supported by the data, I propose another functional hypothesis. Homosexual fellatio in this species could help males solve inconsistent situations in the roost when there are conflicts between cooperative behavior for social thermoregulation and competition for mating. PMID:27824953

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.

A cost-function approach to rival penalized competitive learning (RPCL).

PubMed

Ma, Jinwen; Wang, Taijun

2006-08-01

Rival penalized competitive learning (RPCL) has been shown to be a useful tool for clustering on a set of sample data in which the number of clusters is unknown. However, the RPCL algorithm was proposed heuristically and is still in lack of a mathematical theory to describe its convergence behavior. In order to solve the convergence problem, we investigate it via a cost-function approach. By theoretical analysis, we prove that a general form of RPCL, called distance-sensitive RPCL (DSRPCL), is associated with the minimization of a cost function on the weight vectors of a competitive learning network. As a DSRPCL process decreases the cost to a local minimum, a number of weight vectors eventually fall into a hypersphere surrounding the sample data, while the other weight vectors diverge to infinity. Moreover, it is shown by the theoretical analysis and simulation experiments that if the cost reduces into the global minimum, a correct number of weight vectors is automatically selected and located around the centers of the actual clusters, respectively. Finally, we apply the DSRPCL algorithms to unsupervised color image segmentation and classification of the wine data.

Structure function and splice site analysis of the synaptogenic activity of the neurexin-1 beta LNS domain.

PubMed

Graf, Ethan R; Kang, Yunhee; Hauner, Anna M; Craig, Ann Marie

2006-04-19

Recent findings suggest that the neurexin-neuroligin link promotes both GABAergic and glutamatergic synaptogenesis, but the mechanism by which neurexins influence the clustering of appropriate neuroligins and postsynaptic differentiation remains unclear. Previous studies suggested that the presence or absence of alternatively spliced residues at splice site 4 (S4) in the neurexin LNS domain may regulate neurexin function. We demonstrate that addition of the S4 insert selectively reduces the ability of neurexin-1beta to cluster neuroligin-1/3/4 and glutamatergic postsynaptic proteins, although clustering of neuroligin-2 and GABAergic postsynaptic proteins remain strong. Furthermore, addition of the S4 insert decreases the binding affinity of neurexin-1beta to neuroligins-1 and -4 but has little effect on binding to neuroligins-2 and -3. Additional structure-function studies reveal the neurexin binding interface mediating synaptogenic activity to be composed primarily of residues in the beta2beta3, beta6beta7, and beta10beta11 loops on one rim of the LNS domain beta sandwich. Mutation of two predicted Ca(2+)-binding residues disrupts postsynaptic protein clustering and binding to neuroligins, consistent with previous findings that neurexin-neuroligin binding is Ca2+ dependent. Glutamatergic postsynaptic clustering was more readily disrupted by the mutagenesis than GABAergic postsynaptic protein clustering. Perhaps neurexins-neuroligins, or neurexin-1beta at least, is most important for GABA synapse formation or controlling the balance of GABA and glutamate synapses. These results suggest that differential neurexin-neuroligin binding affinities and splice variations may play an instructive role in postsynaptic differentiation.

Galactic cannibalism. III. The morphological evolution of galaxies and clusters

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

Hausman, M.A.; Ostriker, J.P.

1978-09-01

We present a numerical simulation for the evolution of massive cluster galaxies due to the accretion of other galaxies, finding that after several accretions a bright ''normal'' galaxy begins to resemble a cD giant, with a bright core and large core radius. Observable quantities such as color, scale size, and logarithmic intensity gradient ..cap alpha.. are calculated and are consistent with observations. The multiple nuclei sometimes found in cD galaxies may be understood as the undigested remnants of cannibalized companions. A cluster's bright galaxies are selectively depleted, an effect which can transform the cluster's luminosity function from a power lawmore » to the observed form with a steep high-luminosity falloff and which pushes the turnover point to lower luminosities with time. We suggest that these effects may account for apparent nonstatistical features observed in the luminosity distribution of bright cluster galaxies, and that the sequence of cluster types discovered by Bautz and Morgan and Oemler is essentially one of increasing dynamical evolution, the rate of evolution depending inversely on the cluster's central relaxation time.« less

Hydrogen-bonded ring closing and opening of protonated methanol clusters H(+)(CH3OH)(n) (n = 4-8) with the inert gas tagging.

PubMed

Li, Ying-Cheng; Hamashima, Toru; Yamazaki, Ryoko; Kobayashi, Tomohiro; Suzuki, Yuta; Mizuse, Kenta; Fujii, Asuka; Kuo, Jer-Lai

2015-09-14

The preferential hydrogen bond (H-bond) structures of protonated methanol clusters, H(+)(MeOH)n, in the size range of n = 4-8, were studied by size-selective infrared (IR) spectroscopy in conjunction with density functional theory calculations. The IR spectra of bare clusters were compared with those with the inert gas tagging by Ar, Ne, and N2, and remarkable changes in the isomer distribution with the tagging were found for clusters with n≥ 5. The temperature dependence of the isomer distribution of the clusters was calculated by the quantum harmonic superposition approach. The observed spectral changes with the tagging were well interpreted by the fall of the cluster temperature with the tagging, which causes the transfer of the isomer distribution from the open and flexible H-bond network types to the closed and rigid ones. Anomalous isomer distribution with the tagging, which has been recently found for protonated water clusters, was also found for H(+)(MeOH)5. The origin of the anomaly was examined by the experiments on its carrier gas dependence.

Genetic characterization of the hemagglutinin genes of wild-type measles virus circulating in china, 1993-2009.

PubMed

Xu, Songtao; Zhang, Yan; Zhu, Zhen; Liu, Chunyu; Mao, Naiying; Ji, Yixin; Wang, Huiling; Jiang, Xiaohong; Li, Chongshan; Tang, Wei; Feng, Daxing; Wang, Changyin; Zheng, Lei; Lei, Yue; Ling, Hua; Zhao, Chunfang; Ma, Yan; He, Jilan; Wang, Yan; Li, Ping; Guan, Ronghui; Zhou, Shujie; Zhou, Jianhui; Wang, Shuang; Zhang, Hong; Zheng, Huanying; Liu, Leng; Ma, Hemuti; Guan, Jing; Lu, Peishan; Feng, Yan; Zhang, Yanjun; Zhou, Shunde; Xiong, Ying; Ba, Zhuoma; Chen, Hui; Yang, Xiuhui; Bo, Fang; Ma, Yujie; Liang, Yong; Lei, Yake; Gu, Suyi; Liu, Wei; Chen, Meng; Featherstone, David; Jee, Youngmee; Bellini, William J; Rota, Paul A; Xu, Wenbo

2013-01-01

China experienced several large measles outbreaks in the past two decades, and a series of enhanced control measures were implemented to achieve the goal of measles elimination. Molecular epidemiologic surveillance of wild-type measles viruses (MeV) provides valuable information about the viral transmission patterns. Since 1993, virologic surveillnace has confirmed that a single endemic genotype H1 viruses have been predominantly circulating in China. A component of molecular surveillance is to monitor the genetic characteristics of the hemagglutinin (H) gene of MeV, the major target for virus neutralizing antibodies. Analysis of the sequences of the complete H gene from 56 representative wild-type MeV strains circulating in China during 1993-2009 showed that the H gene sequences were clustered into 2 groups, cluster 1 and cluster 2. Cluster1 strains were the most frequently detected cluster and had a widespread distribution in China after 2000. The predicted amino acid sequences of the H protein were relatively conserved at most of the functionally significant amino acid positions. However, most of the genotype H1 cluster1 viruses had an amino acid substitution (Ser240Asn), which removed a predicted N-linked glycosylation site. In addition, the substitution of Pro397Leu in the hemagglutinin noose epitope (HNE) was identified in 23 of 56 strains. The evolutionary rate of the H gene of the genotype H1 viruses was estimated to be approximately 0.76×10(-3) substitutions per site per year, and the ratio of dN to dS (dN/dS) was <1 indicating the absence of selective pressure. Although H genes of the genotype H1 strains were conserved and not subjected to selective pressure, several amino acid substitutions were observed in functionally important positions. Therefore the antigenic and genetic properties of H genes of wild-type MeVs should be monitored as part of routine molecular surveillance for measles in China.

Subaru Weak-lensing Survey of Dark Matter Subhalos in the Coma Cluster: Subhalo Mass Function and Statistical Properties

NASA Astrophysics Data System (ADS)

Okabe, Nobuhiro; Futamase, Toshifumi; Kajisawa, Masaru; Kuroshima, Risa

2014-04-01

We present a 4 deg2 weak gravitational lensing survey of subhalos in the very nearby Coma cluster using the Subaru/Suprime-Cam. The large apparent size of cluster subhalos allows us to measure the mass of 32 subhalos detected in a model-independent manner, down to the order of 10-3 of the virial mass of the cluster. Weak-lensing mass measurements of these shear-selected subhalos enable us to investigate subhalo properties and the correlation between subhalo masses and galaxy luminosities for the first time. The mean distortion profiles stacked over subhalos show a sharply truncated feature which is well-fitted by a Navarro-Frenk-White (NFW) mass model with the truncation radius, as expected due to tidal destruction by the main cluster. We also found that subhalo masses, truncation radii, and mass-to-light ratios decrease toward the cluster center. The subhalo mass function, dn/dln M sub, in the range of 2 orders of magnitude in mass, is well described by a single power law or a Schechter function. Best-fit power indices of 1.09^{+0.42}_{-0.32} for the former model and 0.99_{-0.23}^{+0.34} for the latter, are in remarkable agreement with slopes of ~0.9-1.0 predicted by the cold dark matter paradigm. The tangential distortion signals in the radial range of 0.02-2 h -1 Mpc from the cluster center show a complex structure which is well described by a composition of three mass components of subhalos, the NFW mass distribution as a smooth component of the main cluster, and a lensing model from a large scale structure behind the cluster. Although the lensing signals are 1 order of magnitude lower than those for clusters at z ~ 0.2, the total signal-to-noise ratio, S/N = 13.3, is comparable, or higher, because the enormous number of background source galaxies compensates for the low lensing efficiency of the nearby cluster. Based on data collected from the Subaru Telescope and obtained from SMOKA, operated by the Astronomy Data Center, National Astronomical Observatory of Japan.

Assessment of personality functioning: validity of the operationalized psychodynamic diagnosis axis IV (structure).

PubMed

Doering, Stephan; Burgmer, Markus; Heuft, Gereon; Menke, Dina; Bäumer, Brigitta; Lübking, Margit; Feldmann, Marcus; Schneider, Gudrun

2014-01-01

The assessment of personality functioning has recently become a focus of psychiatric diagnostics. The interview-based Operationalized Psychodynamic Diagnosis (OPD-2) provides a 'structure axis' for the assessment of personality functioning. One hundred twenty-four psychiatric patients were diagnosed by means of the Structured Clinical Interviews for DSM-IV (SCID-I and SCID-II), underwent OPD-2 interviews, and completed 9 questionnaires. The OPD-2 structure axis shows good interrater reliability (intraclass correlation = 0.793). Correlations between the OPD-2 structure axis domains and a priori selected questionnaire scales were of medium size and significant. Patients with a personality disorder (PD) showed significantly worse personality functioning than those without. In cluster B PD, personality functioning was more severely impaired than in cluster C PD. The OPD-2 structure axis shows good reliability as well as concurrent and discriminant validity and can be recommended for clinical use and research purposes. © 2013 S. Karger AG, Basel.

Diffuse Optical Light in Galaxy Clusters. II. Correlations with Cluster Properties

NASA Astrophysics Data System (ADS)

Krick, J. E.; Bernstein, R. A.

2007-08-01

We have measured the flux, profile, color, and substructure in the diffuse intracluster light (ICL) in a sample of 10 galaxy clusters with a range of mass, morphology, redshift, and density. Deep, wide-field observations for this project were made in two bands at the 1 m Swope and 2.5 m du Pont telescopes at Las Campanas Observatory. Careful attention in reduction and analysis was paid to the illumination correction, background subtraction, point-spread function determination, and galaxy subtraction. ICL flux is detected in both bands in all 10 clusters ranging from 7.6×1010 to 7.0×1011 h-170 Lsolar in r and 1.4×1010 to 1.2×1011 h-170 Lsolar in the B band. These fluxes account for 6%-22% of the total cluster light within one-quarter of the virial radius in r and 4%-21% in the B band. Average ICL B-r colors range from 1.5 to 2.8 mag when k- and evolution corrected to the present epoch. In several clusters we also detect ICL in group environments near the cluster center and up to 1 h-170 Mpc distant from the cluster center. Our sample, having been selected from the Abell sample, is incomplete in that it does not include high-redshift clusters with low density, low flux, or low mass, and it does not include low-redshift clusters with high flux, high mass, or high density. This bias makes it difficult to interpret correlations between ICL flux and cluster properties. Despite this selection bias, we do find that the presence of a cD galaxy corresponds to both centrally concentrated galaxy profiles and centrally concentrated ICL profiles. This is consistent with ICL either forming from galaxy interactions at the center or forming at earlier times in groups and later combining in the center.

Stellar-to-halo mass relation of cluster galaxies

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

Niemiec, Anna; Jullo, Eric; Limousin, Marceau

In the formation of galaxy groups and clusters, the dark matter haloes containing satellite galaxies are expected to be tidally stripped in gravitational interactions with the host. We use galaxy-galaxy weak lensing to measure the average mass of dark matter haloes of satellite galaxies as a function of projected distance to the centre of the host, since stripping is expected to be greater for satellites closer to the centre of the cluster. We further classify the satellites according to their stellar mass: assuming that the stellar component of the galaxy is less disrupted by tidal stripping, stellar mass can bemore » used as a proxy of the infall mass. We study the stellar to halo mass relation of satellites as a function of the cluster-centric distance to measure tidal stripping. We use the shear catalogues of the DES science veri cation archive, the CFHTLenS and the CFHT Stripe 82 surveys, and we select satellites from the redMaPPer catalogue of clusters. For galaxies located in the outskirts of clusters, we nd a stellar to halo mass relation in good agreement with the theoretical expectations from Moster, Naab & White (2013) for central galaxies. In the centre of the cluster, we nd that this relation is shifted to smaller halo mass for a given stellar mass. We interpret this nding as further evidence for tidal stripping of dark matter haloes in high density environments.« less

Stellar-to-halo mass relation of cluster galaxies

DOE PAGES

Niemiec, Anna; Jullo, Eric; Limousin, Marceau; ...

2017-07-04

In the formation of galaxy groups and clusters, the dark matter haloes containing satellite galaxies are expected to be tidally stripped in gravitational interactions with the host. We use galaxy-galaxy weak lensing to measure the average mass of dark matter haloes of satellite galaxies as a function of projected distance to the centre of the host, since stripping is expected to be greater for satellites closer to the centre of the cluster. We further classify the satellites according to their stellar mass: assuming that the stellar component of the galaxy is less disrupted by tidal stripping, stellar mass can bemore » used as a proxy of the infall mass. We study the stellar to halo mass relation of satellites as a function of the cluster-centric distance to measure tidal stripping. We use the shear catalogues of the DES science veri cation archive, the CFHTLenS and the CFHT Stripe 82 surveys, and we select satellites from the redMaPPer catalogue of clusters. For galaxies located in the outskirts of clusters, we nd a stellar to halo mass relation in good agreement with the theoretical expectations from Moster, Naab & White (2013) for central galaxies. In the centre of the cluster, we nd that this relation is shifted to smaller halo mass for a given stellar mass. We interpret this nding as further evidence for tidal stripping of dark matter haloes in high density environments.« less

Clustering of quasars in SDSS-IV eBOSS: study of potential systematics and bias determination

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

Laurent, Pierre; Goff, Jean-Marc Le; Burtin, Etienne

2017-07-01

We study the first year of the eBOSS quasar sample in the redshift range 0.9< z <2.2 which includes 68,772 homogeneously selected quasars. We show that the main source of systematics in the evaluation of the correlation function arises from inhomogeneities in the quasar target selection, particularly related to the extinction and depth of the imaging data used for targeting. We propose a weighting scheme that mitigates these systematics. We measure the quasar correlation function and provide the most accurate measurement to date of the quasar bias in this redshift range, b {sub Q} = 2.45 ± 0.05 at z-barmore » =1.55, together with its evolution with redshift. We use this information to determine the minimum mass of the halo hosting the quasars and the characteristic halo mass, which we find to be both independent of redshift within statistical error. Using a recently-measured quasar-luminosity-function we also determine the quasar duty cycle. The size of this first year sample is insufficient to detect any luminosity dependence to quasar clustering and this issue should be further studied with the final ∼500,000 eBOSS quasar sample.« less

Clustering of quasars in SDSS-IV eBOSS: study of potential systematics and bias determination

NASA Astrophysics Data System (ADS)

Laurent, Pierre; Eftekharzadeh, Sarah; Le Goff, Jean-Marc; Myers, Adam; Burtin, Etienne; White, Martin; Ross, Ashley J.; Tinker, Jeremy; Tojeiro, Rita; Bautista, Julian; Brinkmann, Jonathan; Comparat, Johan; Dawson, Kyle; du Mas des Bourboux, Hélion; Kneib, Jean-Paul; McGreer, Ian D.; Palanque-Delabrouille, Nathalie; Percival, Will J.; Prada, Francisco; Rossi, Graziano; Schneider, Donald P.; Weinberg, David; Yèche, Christophe; Zarrouk, Pauline; Zhao, Gong-Bo

2017-07-01

We study the first year of the eBOSS quasar sample in the redshift range 0.9

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

NASA Astrophysics Data System (ADS)

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-04-01

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra.

PubMed

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-03-13

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

"A Richness Study of 14 Distant X-Ray Clusters from the 160 Square Degree Survey"

NASA Technical Reports Server (NTRS)

Jones, Christine; West, Donald (Technical Monitor)

2001-01-01

We have measured the surface density of galaxies toward 14 X-ray-selected cluster candidates at redshifts z(sub i) 0.46, and we show that they are associated with rich galaxy concentrations. These clusters, having X-ray luminosities of Lx(0.5-2 keV) approx. (0.5 - 2.6) x 10(exp 44) ergs/ sec are among the most distant and luminous in our 160 deg(exp 2) ROSAT Position Sensitive Proportional Counter cluster survey. We find that the clusters range between Abell richness classes 0 and 2 and have a most probable richness class of 1. We compare the richness distribution of our distant clusters to those for three samples of nearby clusters with similar X-ray luminosities. We find that the nearby and distant samples have similar richness distributions, which shows that clusters have apparently not evolved substantially in richness since redshift z=0.5. There is, however, a marginal tendency for the distant clusters to be slightly poorer than nearby clusters, although deeper multicolor data for a large sample would be required to confirm this trend. We compare the distribution of distant X-ray clusters in the L(sub X)-richness plane to the distribution of optically selected clusters from the Palomar Distant Cluster Survey. The optically selected clusters appear overly rich for their X-ray luminosities, when compared to X-ray-selected clusters. Apparently, X-ray and optical surveys do not necessarily sample identical mass concentrations at large redshifts. This may indicate the existence of a population of optically rich clusters with anomalously low X-ray emission, More likely, however, it reflects the tendency for optical surveys to select unvirialized mass concentrations, as might be expected when peering along large-scale filaments.

Star clusters in the Magellanic Clouds - I. Parametrization and classification of 1072 clusters in the LMC

NASA Astrophysics Data System (ADS)

Nayak, P. K.; Subramaniam, A.; Choudhury, S.; Indu, G.; Sagar, Ram

2016-12-01

We have introduced a semi-automated quantitative method to estimate the age and reddening of 1072 star clusters in the Large Magellanic Cloud (LMC) using the Optical Gravitational Lensing Experiment III survey data. This study brings out 308 newly parametrized clusters. In a first of its kind, the LMC clusters are classified into groups based on richness/mass as very poor, poor, moderate and rich clusters, similar to the classification scheme of open clusters in the Galaxy. A major cluster formation episode is found to happen at 125 ± 25 Myr in the inner LMC. The bar region of the LMC appears prominently in the age range 60-250 Myr and is found to have a relatively higher concentration of poor and moderate clusters. The eastern and the western ends of the bar are found to form clusters initially, which later propagates to the central part. We demonstrate that there is a significant difference in the distribution of clusters as a function of mass, using a movie based on the propagation (in space and time) of cluster formation in various groups. The importance of including the low-mass clusters in the cluster formation history is demonstrated. The catalogue with parameters, classification, and cleaned and isochrone fitted colour-magnitude diagrams of 1072 clusters, which are available as online material, can be further used to understand the hierarchical formation of clusters in selected regions of the LMC.

Galaxy Cluster Mass Reconstruction Project - II. Quantifying scatter and bias using contrasting mock catalogues

DOE PAGES

Old, L.; Wojtak, R.; Mamon, G. A.; ...

2015-03-26

Our paper is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilize the positions, velocities and colours of galaxies. Our aim is to quantify the scatter, systematic bias and completeness of cluster masses derived from a diverse set of 25 galaxy-based methods using two contrasting mock galaxy catalogues based on a sophisticated halo occupation model and a semi-analytic model. Analysing 968 clusters, we find a wide range in the rms errors in log M200c delivered by the different methods (0.18–1.08 dex, i.e. a factor of ~1.5–12), with abundance-matchingmore » and richness methods providing the best results, irrespective of the input model assumptions. In addition, certain methods produce a significant number of catastrophic cases where the mass is under- or overestimated by a factor greater than 10. Given the steeply falling high-mass end of the cluster mass function, we recommend that richness- or abundance-matching-based methods are used in conjunction with these methods as a sanity check for studies selecting high-mass clusters. We also see a stronger correlation of the recovered to input number of galaxies for both catalogues in comparison with the group/cluster mass, however, this does not guarantee that the correct member galaxies are being selected. Finally, we did not observe significantly higher scatter for either mock galaxy catalogues. These results have implications for cosmological analyses that utilize the masses, richnesses, or abundances of clusters, which have different uncertainties when different methods are used.« less

CLASH: A census of magnified star-forming galaxies at z ∼ 6-8

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

Bradley, L. D.; Coe, D.; Postman, M.

2014-09-01

We utilize 16 band Hubble Space Telescope (HST) observations of 18 lensing clusters obtained as part of the Cluster Lensing And Supernova survey with Hubble (CLASH) Multi-Cycle Treasury program to search for z ∼ 6-8 galaxies. We report the discovery of 204, 45, and 13 Lyman-break galaxy candidates at z ∼ 6, z ∼ 7, and z ∼ 8, respectively, identified from purely photometric redshift selections. This large sample, representing nearly an order of magnitude increase in the number of magnified star-forming galaxies at z ∼ 6-8 presented to date, is unique in that we have observations in four WFC3/UVISmore » UV, seven ACS/WFC optical, and all five WFC3/IR broadband filters, which enable very accurate photometric redshift selections. We construct detailed lensing models for 17 of the 18 clusters to estimate object magnifications and to identify two new multiply lensed z ≳ 6 candidates. The median magnifications over the 17 clusters are 4, 4, and 5 for the z ∼ 6, z ∼ 7, and z ∼ 8 samples, respectively, over an average area of 4.5 arcmin{sup 2} per cluster. We compare our observed number counts with expectations based on convolving 'blank' field UV luminosity functions through our cluster lens models and find rough agreement down to ∼27 mag, where we begin to suffer significant incompleteness. In all three redshift bins, we find a higher number density at brighter observed magnitudes than the field predictions, empirically demonstrating for the first time the enhanced efficiency of lensing clusters over field surveys. Our number counts also are in general agreement with the lensed expectations from the cluster models, especially at z ∼ 6, where we have the best statistics.« less

The MUSIC of CLASH: Predictions on the Concentration-Mass Relation

NASA Astrophysics Data System (ADS)

Meneghetti, M.; Rasia, E.; Vega, J.; Merten, J.; Postman, M.; Yepes, G.; Sembolini, F.; Donahue, M.; Ettori, S.; Umetsu, K.; Balestra, I.; Bartelmann, M.; Benítez, N.; Biviano, A.; Bouwens, R.; Bradley, L.; Broadhurst, T.; Coe, D.; Czakon, N.; De Petris, M.; Ford, H.; Giocoli, C.; Gottlöber, S.; Grillo, C.; Infante, L.; Jouvel, S.; Kelson, D.; Koekemoer, A.; Lahav, O.; Lemze, D.; Medezinski, E.; Melchior, P.; Mercurio, A.; Molino, A.; Moscardini, L.; Monna, A.; Moustakas, J.; Moustakas, L. A.; Nonino, M.; Rhodes, J.; Rosati, P.; Sayers, J.; Seitz, S.; Zheng, W.; Zitrin, A.

2014-12-01

We present an analysis of the MUSIC-2 N-body/hydrodynamical simulations aimed at estimating the expected concentration-mass relation for the CLASH (Cluster Lensing and Supernova Survey with Hubble) cluster sample. We study nearly 1,400 halos simulated at high spatial and mass resolution. We study the shape of both their density and surface-density profiles and fit them with a variety of radial functions, including the Navarro-Frenk-White (NFW), the generalized NFW, and the Einasto density profiles. We derive concentrations and masses from these fits. We produce simulated Chandra observations of the halos, and we use them to identify objects resembling the X-ray morphologies and masses of the clusters in the CLASH X-ray-selected sample. We also derive a concentration-mass relation for strong-lensing clusters. We find that the sample of simulated halos that resembles the X-ray morphology of the CLASH clusters is composed mainly of relaxed halos, but it also contains a significant fraction of unrelaxed systems. For such a heterogeneous sample we measure an average two-dimensional concentration that is ~11% higher than is found for the full sample of simulated halos. After accounting for projection and selection effects, the average NFW concentrations of CLASH clusters are expected to be intermediate between those predicted in three dimensions for relaxed and super-relaxed halos. Matching the simulations to the individual CLASH clusters on the basis of the X-ray morphology, we expect that the NFW concentrations recovered from the lensing analysis of the CLASH clusters are in the range [3-6], with an average value of 3.87 and a standard deviation of 0.61.

The music of clash: predictions on the concentration-mass relation

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

Meneghetti, M.; Rasia, E.; Vega, J.

We present an analysis of the MUSIC-2 N-body/hydrodynamical simulations aimed at estimating the expected concentration-mass relation for the CLASH (Cluster Lensing and Supernova Survey with Hubble) cluster sample. We study nearly 1,400 halos simulated at high spatial and mass resolution. We study the shape of both their density and surface-density profiles and fit them with a variety of radial functions, including the Navarro-Frenk-White (NFW), the generalized NFW, and the Einasto density profiles. We derive concentrations and masses from these fits. We produce simulated Chandra observations of the halos, and we use them to identify objects resembling the X-ray morphologies andmore » masses of the clusters in the CLASH X-ray-selected sample. We also derive a concentration-mass relation for strong-lensing clusters. We find that the sample of simulated halos that resembles the X-ray morphology of the CLASH clusters is composed mainly of relaxed halos, but it also contains a significant fraction of unrelaxed systems. For such a heterogeneous sample we measure an average two-dimensional concentration that is ∼11% higher than is found for the full sample of simulated halos. After accounting for projection and selection effects, the average NFW concentrations of CLASH clusters are expected to be intermediate between those predicted in three dimensions for relaxed and super-relaxed halos. Matching the simulations to the individual CLASH clusters on the basis of the X-ray morphology, we expect that the NFW concentrations recovered from the lensing analysis of the CLASH clusters are in the range [3-6], with an average value of 3.87 and a standard deviation of 0.61.« less

Method of precisely modifying predetermined surface layers of a workpiece by cluster ion impact therewith

DOEpatents

Friedman, L.; Beuhler, R.J.; Matthew, M.W.; Ledbetter, M.

1984-06-25

A method of precisely modifying a selected area of a workpiece by producing a beam of charged cluster ions that is narrowly mass selected to a predetermined mean size of cluster ions within a range of 25 to 10/sup 6/ atoms per cluster ion, and accelerated in a beam to a critical velocity. The accelerated beam is used to impact a selected area of an outer surface of the workpiece at a preselected rate of impacts of cluster ions/cm/sup 2//sec in order to effect a precise modification in that selected area of the workpiece.

Method of precisely modifying predetermined surface layers of a workpiece by cluster ion impact therewith

DOEpatents

Friedman, Lewis; Buehler, Robert J.; Matthew, Michael W.; Ledbetter, Myron

1985-01-01

A method of precisely modifying a selected area of a workpiece by producing a beam of charged cluster ions that is narrowly mass selected to a predetermined mean size of cluster ions within a range of 25 to 10.sup.6 atoms per cluster ion, and accelerated in a beam to a critical velocity. The accelerated beam is used to impact a selected area of an outer surface of the workpiece at a preselected rate of impacts of cluster ions/cm.sup.2 /sec. in order to effect a precise modification in that selected area of the workpiece.

Clustering mechanism of oxocarboxylic acids involving hydration reaction: Implications for the atmospheric models

NASA Astrophysics Data System (ADS)

Liu, Ling; Kupiainen-Määttä, Oona; Zhang, Haijie; Li, Hao; Zhong, Jie; Kurtén, Theo; Vehkamäki, Hanna; Zhang, Shaowen; Zhang, Yunhong; Ge, Maofa; Zhang, Xiuhui; Li, Zesheng

2018-06-01

The formation of atmospheric aerosol particles from condensable gases is a dominant source of particulate matter in the boundary layer, but the mechanism is still ambiguous. During the clustering process, precursors with different reactivities can induce various chemical reactions in addition to the formation of hydrogen bonds. However, the clustering mechanism involving chemical reactions is rarely considered in most of the nucleation process models. Oxocarboxylic acids are common compositions of secondary organic aerosol, but the role of oxocarboxylic acids in secondary organic aerosol formation is still not fully understood. In this paper, glyoxylic acid, the simplest and the most abundant atmospheric oxocarboxylic acid, has been selected as a representative example of oxocarboxylic acids in order to study the clustering mechanism involving hydration reactions using density functional theory combined with the Atmospheric Clusters Dynamic Code. The hydration reaction of glyoxylic acid can occur either in the gas phase or during the clustering process. Under atmospheric conditions, the total conversion ratio of glyoxylic acid to its hydration reaction product (2,2-dihydroxyacetic acid) in both gas phase and clusters can be up to 85%, and the product can further participate in the clustering process. The differences in cluster structures and properties induced by the hydration reaction lead to significant differences in cluster formation rates and pathways at relatively low temperatures.

A high-significance measurement of correlation between unresolved IRAS sources and optically-selected galaxy clusters

NASA Astrophysics Data System (ADS)

Hincks, Adam D.; Hajian, Amir; Addison, Graeme E.

2013-05-01

We cross-correlate the 100 μm Improved Reprocessing of the IRAS Survey (IRIS) map and galaxy clusters at 0.1 < z < 0.3 in the maxBCG catalogue taken from the Sloan Digital Sky Survey, measuring an angular cross-power spectrum over multipole moments 150 < l < 3000 at a total significance of over 40σ. The cross-spectrum, which arises from the spatial correlation between unresolved dusty galaxies that make up the cosmic infrared background (CIB) in the IRIS map and the galaxy clusters, is well-fit by a single power law with an index of -1.28±0.12, similar to the clustering of unresolved galaxies from cross-correlating far-infrared and submillimetre maps at longer wavelengths. Using a recent, phenomenological model for the spectral and clustering properties of the IRIS galaxies, we constrain the large-scale bias of the maxBCG clusters to be 2.6±1.4, consistent with existing analyses of the real-space cluster correlation function. The success of our method suggests that future CIB-optical cross-correlations using Planck and Herschel data will significantly improve our understanding of the clustering and redshift distribution of the faint CIB sources.

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

PubMed

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

2014-06-01

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

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

PubMed Central

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

2013-01-01

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

Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

PubMed

Reynolds, Hannah T; Slot, Jason C; Divon, Hege H; Lysøe, Erik; Proctor, Robert H; Brown, Daren W

2017-08-01

In fungi, distribution of secondary metabolite (SM) gene clusters is often associated with host- or environment-specific benefits provided by SMs. In the plant pathogen Alternaria brassicicola (Dothideomycetes), the DEP cluster confers an ability to synthesize the SM depudecin, a histone deacetylase inhibitor that contributes weakly to virulence. The DEP cluster includes genes encoding enzymes, a transporter, and a transcription regulator. We investigated the distribution and evolution of the DEP cluster in 585 fungal genomes and found a wide but sporadic distribution among Dothideomycetes, Sordariomycetes, and Eurotiomycetes. We confirmed DEP gene expression and depudecin production in one fungus, Fusarium langsethiae. Phylogenetic analyses suggested 6-10 horizontal gene transfers (HGTs) of the cluster, including a transfer that led to the presence of closely related cluster homologs in Alternaria and Fusarium. The analyses also indicated that HGTs were frequently followed by loss/pseudogenization of one or more DEP genes. Independent cluster inactivation was inferred in at least four fungal classes. Analyses of transitions among functional, pseudogenized, and absent states of DEP genes among Fusarium species suggest enzyme-encoding genes are lost at higher rates than the transporter (DEP3) and regulatory (DEP6) genes. The phenotype of an experimentally-induced DEP3 mutant of Fusarium did not support the hypothesis that selective retention of DEP3 and DEP6 protects fungi from exogenous depudecin. Together, the results suggest that HGT and gene loss have contributed significantly to DEP cluster distribution, and that some DEP genes provide a greater fitness benefit possibly due to a differential tendency to form network connections. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2017. This work is written by US Government employees and is in the public domain in the US.

The cosmological analysis of X-ray cluster surveys - I. A new method for interpreting number counts

NASA Astrophysics Data System (ADS)

Clerc, N.; Pierre, M.; Pacaud, F.; Sadibekova, T.

2012-07-01

We present a new method aimed at simplifying the cosmological analysis of X-ray cluster surveys. It is based on purely instrumental observable quantities considered in a two-dimensional X-ray colour-magnitude diagram (hardness ratio versus count rate). The basic principle is that even in rather shallow surveys, substantial information on cluster redshift and temperature is present in the raw X-ray data and can be statistically extracted; in parallel, such diagrams can be readily predicted from an ab initio cosmological modelling. We illustrate the methodology for the case of a 100-deg2XMM survey having a sensitivity of ˜10-14 erg s-1 cm-2 and fit at the same time, the survey selection function, the cluster evolutionary scaling relations and the cosmology; our sole assumption - driven by the limited size of the sample considered in the case study - is that the local cluster scaling relations are known. We devote special attention to the realistic modelling of the count-rate measurement uncertainties and evaluate the potential of the method via a Fisher analysis. In the absence of individual cluster redshifts, the count rate and hardness ratio (CR-HR) method appears to be much more efficient than the traditional approach based on cluster counts (i.e. dn/dz, requiring redshifts). In the case where redshifts are available, our method performs similar to the traditional mass function (dn/dM/dz) for the purely cosmological parameters, but constrains better parameters defining the cluster scaling relations and their evolution. A further practical advantage of the CR-HR method is its simplicity: this fully top-down approach totally bypasses the tedious steps consisting in deriving cluster masses from X-ray temperature measurements.

The linkage between ribosomal crystallography, metal ions, heteropolytungstates and functional flexibility

PubMed Central

Bashan, Anat; Yonath, Ada

2009-01-01

Crystallography of ribosomes, the universal cell nucleoprotein assemblies facilitating the translation of the genetic-code into proteins, met with severe problems owing to their large size, complex structure, inherent flexibility and high conformational variability. For the case of the small ribosomal subunit, which caused extreme difficulties, post crystallization treatment by minute amounts of a heteropolytungstate cluster allowed structure determination at atomic resolution. This cluster played a dual role in ribosomal crystallography: providing anomalous phasing power and dramatically increased the resolution, by stabilization of a selected functional conformation. Thus, four out of the fourteen clusters that bind to each of the crystallized small subunits are attached to a specific ribosomal protein in a fashion that may control a significant component of the subunit internal flexibility, by “gluing” symmetrical related subunits. Here we highlight basic issues in the relationship between metal ions and macromolecules and present common traits controlling in the interactions between polymetalates and various macromolecules, which may be extended towards the exploitation of polymetalates for therapeutical treatment. PMID:19915655

X-ray insights into star and planet formation.

PubMed

Feigelson, Eric D

2010-04-20

Although stars and planets form in cold environments, X-rays are produced in abundance by young stars. This review examines the implications of stellar X-rays for star and planet formation studies, highlighting the contributions of NASA's (National Aeronautics and Space Administration) Chandra X-ray Observatory. Seven topics are covered: X-rays from protostellar outflow shocks, X-rays from the youngest protostars, the stellar initial mass function, the structure of young stellar clusters, the fate of massive stellar winds, X-ray irradiation of protoplanetary disks, and X-ray flare effects on ancient meteorites. Chandra observations of star-forming regions often show dramatic star clusters, powerful magnetic reconnection flares, and parsec-scale diffuse plasma. X-ray selected samples of premain sequence stars significantly advance studies of star cluster formation, the stellar initial mass function, triggered star-formation processes, and protoplanetary disk evolution. Although X-rays themselves may not play a critical role in the physics of star formation, they likely have important effects on protoplanetary disks by heating and ionizing disk gases.

X-ray insights into star and planet formation

PubMed Central

Feigelson, Eric D.

2010-01-01

Although stars and planets form in cold environments, X-rays are produced in abundance by young stars. This review examines the implications of stellar X-rays for star and planet formation studies, highlighting the contributions of NASA’s (National Aeronautics and Space Administration) Chandra X-ray Observatory. Seven topics are covered: X-rays from protostellar outflow shocks, X-rays from the youngest protostars, the stellar initial mass function, the structure of young stellar clusters, the fate of massive stellar winds, X-ray irradiation of protoplanetary disks, and X-ray flare effects on ancient meteorites. Chandra observations of star-forming regions often show dramatic star clusters, powerful magnetic reconnection flares, and parsec-scale diffuse plasma. X-ray selected samples of premain sequence stars significantly advance studies of star cluster formation, the stellar initial mass function, triggered star-formation processes, and protoplanetary disk evolution. Although X-rays themselves may not play a critical role in the physics of star formation, they likely have important effects on protoplanetary disks by heating and ionizing disk gases. PMID:20404197

The Spatial Distribution of the Young Stellar Clusters in the Star-forming Galaxy NGC 628

NASA Astrophysics Data System (ADS)

Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Aloisi, A.; Bright, S. N.; Christian, C.; Cignoni, M.; Dale, D. A.; Dobbs, C.; Elmegreen, D. M.; Fumagalli, M.; Gallagher, J. S., III; Grebel, E. K.; Johnson, K. E.; Lee, J. C.; Messa, M.; Smith, L. J.; Ryon, J. E.; Thilker, D.; Ubeda, L.; Wofford, A.

2015-12-01

We present a study of the spatial distribution of the stellar cluster populations in the star-forming galaxy NGC 628. Using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey), we have identified 1392 potential young (≲ 100 Myr) stellar clusters within the galaxy using a combination of visual inspection and automatic selection. We investigate the clustering of these young stellar clusters and quantify the strength and change of clustering strength with scale using the two-point correlation function. We also investigate how image boundary conditions and dust lanes affect the observed clustering. The distribution of the clusters is well fit by a broken power law with negative exponent α. We recover a weighted mean index of α ∼ -0.8 for all spatial scales below the break at 3.″3 (158 pc at a distance of 9.9 Mpc) and an index of α ∼ -0.18 above 158 pc for the accumulation of all cluster types. The strength of the clustering increases with decreasing age and clusters older than 40 Myr lose their clustered structure very rapidly and tend to be randomly distributed in this galaxy, whereas the mass of the star cluster has little effect on the clustering strength. This is consistent with results from other studies that the morphological hierarchy in stellar clustering resembles the same hierarchy as the turbulent interstellar medium.

Sinter-Resistant Platinum Catalyst Supported by Metal-Organic Framework.

PubMed

Kim, In Soo; Li, Zhanyong; Zheng, Jian; Platero-Prats, Ana E; Mavrandonakis, Andreas; Pellizzeri, Steven; Ferrandon, Magali; Vjunov, Aleksei; Gallington, Leighanne C; Webber, Thomas E; Vermeulen, Nicolaas A; Penn, R Lee; Getman, Rachel B; Cramer, Christopher J; Chapman, Karena W; Camaioni, Donald M; Fulton, John L; Lercher, Johannes A; Farha, Omar K; Hupp, Joseph T; Martinson, Alex B F

2018-01-22

Single atoms and few-atom clusters of platinum are uniformly installed on the zirconia nodes of a metal-organic framework (MOF) NU-1000 via targeted vapor-phase synthesis. The catalytic Pt clusters, site-isolated by organic linkers, are shown to exhibit high catalytic activity for ethylene hydrogenation while exhibiting resistance to sintering up to 200 °C. In situ IR spectroscopy reveals the presence of both single atoms and few-atom clusters that depend upon synthesis conditions. Operando X-ray absorption spectroscopy and X-ray pair distribution analyses reveal unique changes in chemical bonding environment and cluster size stability while on stream. Density functional theory calculations elucidate a favorable reaction pathway for ethylene hydrogenation with the novel catalyst. These results provide evidence that atomic layer deposition (ALD) in MOFs is a versatile approach to the rational synthesis of size-selected clusters, including noble metals, on a high surface area support. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

NASA Astrophysics Data System (ADS)

Podestà, Alessandro; Borghi, Francesca; Indrieri, Marco; Bovio, Simone; Piazzoni, Claudio; Milani, Paolo

2015-12-01

Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO2) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility.

Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

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

Podestà, Alessandro, E-mail: alessandro.podesta@mi.infn.it, E-mail: pmilani@mi.infn.it; Borghi, Francesca; Indrieri, Marco

Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO{sub 2}) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevantmore » interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility.« less

Screening and expression of selected taxonomically conserved and unique hypothetical proteins in Burkholderia pseudomallei K96243

NASA Astrophysics Data System (ADS)

Akhir, Nor Azurah Mat; Nadzirin, Nurul; Mohamed, Rahmah; Firdaus-Raih, Mohd

2015-09-01

Hypothetical proteins of bacterial pathogens represent a large numbers of novel biological mechanisms which could belong to essential pathways in the bacteria. They lack functional characterizations mainly due to the inability of sequence homology based methods to detect functional relationships in the absence of detectable sequence similarity. The dataset derived from this study showed 550 candidates conserved in genomes that has pathogenicity information and only present in the Burkholderiales order. The dataset has been narrowed down to taxonomic clusters. Ten proteins were selected for ORF amplification, seven of them were successfully amplified, and only four proteins were successfully expressed. These proteins will be great candidates in determining the true function via structural biology.

Non-Gaussian shape discrimination with spectroscopic galaxy surveys

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

Byun, Joyce; Bean, Rachel, E-mail: byun@astro.cornell.edu, E-mail: rbean@astro.cornell.edu

2015-03-01

We consider how galaxy clustering data, from Mpc to Gpc scales, from upcoming large scale structure surveys, such as Euclid and DESI, can provide discriminating information about the bispectrum shape arising from a variety of inflationary scenarios. Through exploring in detail the weighting of shape properties in the calculation of the halo bias and halo mass function we show how they probe a broad range of configurations, beyond those in the squeezed limit, that can help distinguish between shapes with similar large scale bias behaviors. We assess the impact, on constraints for a diverse set of non-Gaussian shapes, of galaxymore » clustering information in the mildly non-linear regime, and surveys that span multiple redshifts and employ different galactic tracers of the dark matter distribution. Fisher forecasts are presented for a Euclid-like spectroscopic survey of Hα-selected emission line galaxies (ELGs), and a DESI-like survey, of luminous red galaxies (LRGs) and [O-II] doublet-selected ELGs, in combination with Planck-like CMB temperature and polarization data.While ELG samples provide better probes of shapes that are divergent in the squeezed limit, LRG constraints, centered below z<1, yield stronger constraints on shapes with scale-independent large-scale halo biases, such as the equilateral template. The ELG and LRG samples provide complementary degeneracy directions for distinguishing between different shapes. For Hα-selected galaxies, we note that recent revisions of the expected Hα luminosity function reduce the halo bias constraints on the local shape, relative to the CMB. For galaxy clustering constraints to be comparable to those from the CMB, additional information about the Gaussian galaxy bias is needed, such as can be determined from the galaxy clustering bispectrum or probing the halo power spectrum directly through weak lensing. If the Gaussian galaxy bias is constrained to better than a percent level then the LSS and CMB data could provide complementary constraints that will enable differentiation of bispectrum with distinct theoretical origins but with similar large scale, squeezed-limit properties.« less

Academic Clustering and Major Selection of Intercollegiate Student-Athletes

ERIC Educational Resources Information Center

Schneider, Ray G.; Ross, Sally R.; Fisher, Morgan

2010-01-01

Although journalists and reporters have written about academic clustering among college student-athletes, there has been a dearth of scholarly analysis devoted to the subject. This study explored football players' academic major selections to determine if academic clustering actually existed. The seasons 1996, 2001, and 2006 were selected for…

The Impact of Multipollutant Clusters on the Association Between Fine Particulate Air Pollution and Microvascular Function.

PubMed

Ljungman, Petter L; Wilker, Elissa H; Rice, Mary B; Austin, Elena; Schwartz, Joel; Gold, Diane R; Koutrakis, Petros; Benjamin, Emelia J; Vita, Joseph A; Mitchell, Gary F; Vasan, Ramachandran S; Hamburg, Naomi M; Mittleman, Murray A

2016-03-01

Prior studies including the Framingham Heart Study have suggested associations between single components of air pollution and vascular function; however, underlying mixtures of air pollution may have distinct associations with vascular function. We used a k-means approach to construct five distinct pollution mixtures from elemental analyses of particle filters, air pollution monitoring data, and meteorology. Exposure was modeled as an interaction between fine particle mass (PM2.5), and concurrent pollution cluster. Outcome variables were two measures of microvascular function in the fingertip in the Framingham Offspring and Third Generation cohorts from 2003 to 2008. In 1,720 participants, associations between PM2.5 and baseline pulse amplitude tonometry differed by air pollution cluster (interaction P value 0.009). Higher PM2.5 on days with low mass concentrations but high proportion of ultrafine particles from traffic was associated with 18% (95% confidence interval: 4.6%, 33%) higher baseline pulse amplitude per 5 μg/m and days with high contributions of oil and wood combustion with 16% (95% confidence interval: 0.2%, 34%) higher baseline pulse amplitude. We observed no variation in associations of PM2.5 with hyperemic response to ischemia observed across air pollution clusters. PM2.5 exposure from air pollution mixtures with large contributions of local ultrafine particles from traffic, heating oil, and wood combustion was associated with higher baseline pulse amplitude but not hyperemic response. Our findings suggest little association between acute exposure to air pollution clusters reflective of select sources and hyperemic response to ischemia, but possible associations with excessive small artery pulsatility with potentially deleterious microvascular consequences.

The Impact of Multi-pollutant Clusters on the Association between Fine Particulate Air Pollution and Microvascular Function

PubMed Central

Ljungman, Petter L.; Wilker, Elissa H.; Rice, Mary B.; Austin, Elena; Schwartz, Joel; Gold, Diane R.; Koutrakis, Petros; Benjamin, Emelia J.; Vita, Joseph A.; Mitchell, Gary F.; Vasan, Ramachandran S.

2016-01-01

Background Prior studies including the Framingham Heart Study have suggested associations between single components of air pollution and vascular function; however, underlying mixtures of air pollution may have distinct associations with vascular function. Methods We used a k-means approach to construct five distinct pollution mixtures from elemental analyses of particle filters, air pollution monitoring data, and meteorology. Exposure was modeled as an interaction between fine particle mass (PM2.5), and concurrent pollution cluster. Outcome variables were two measures of microvascular function in the fingertip in the Framingham Offspring and Third Generation cohorts from 2003-2008. Results In 1,720 participants, associations between PM2.5 and baseline pulse amplitude tonometry differed by air pollution cluster (interaction p value 0.009). Higher PM2.5 on days with low mass concentrations but high proportion of ultrafine particles from traffic was associated with 18% (95% CI 4.6%; 33%) higher baseline pulse amplitude per 5 μg/m3 and days with high contributions of oil and wood combustion with 16% (95% CI 0.2%; 34%) higher baseline pulse amplitude. We observed no variation in associations of PM2.5 with hyperemic response to ischemia observed across air pollution clusters. Conclusions PM2.5 exposure from air pollution mixtures with large contributions of local ultrafine particles from traffic, heating oil and wood combustion was associated with higher baseline pulse amplitude but not PAT ratio. Our findings suggest little association between acute exposure to air pollution clusters reflective of select sources and hyperemic response to ischemia, but possible associations with excessive small artery pulsatility with potentially deleterious microvascular consequences. PMID:26562062

Sinter-Resistant Platinum Catalyst Supported by Metal-Organic Framework

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

Kim, In Soo; Li, Zhanyong; Zheng, Jian

Installed on the zirconia nodes of a metal-organic framework (MOF) NU-1000 via targeted vapor-phase synthesis. The catalytic Pt clusters, site-isolated by organic linkers, are shown to exhibit high catalytic activity for ethylene hydrogenation while exhibiting resistance to sintering up to 200 degrees C. In situ IR spectroscopy reveals the presence of both single atoms and few-atom clusters that depend upon synthesis conditions. Operando X-ray absorption spectroscopy and Xray pair distribution analyses reveal unique changes in chemical bonding environment and cluster size stability while on stream. Density functional theory calculations elucidate a favorable reaction pathway for ethylene hydrogenation with the novelmore » catalyst. These results provide evidence that atomic layer deposition (ALD) in MOFs is a versatile approach to the rational synthesis of size-selected clusters, including noble metals, on a high surface area support.« less

Predicting the random drift of MEMS gyroscope based on K-means clustering and OLS RBF Neural Network

NASA Astrophysics Data System (ADS)

Wang, Zhen-yu; Zhang, Li-jie

2017-10-01

Measure error of the sensor can be effectively compensated with prediction. Aiming at large random drift error of MEMS(Micro Electro Mechanical System))gyroscope, an improved learning algorithm of Radial Basis Function(RBF) Neural Network(NN) based on K-means clustering and Orthogonal Least-Squares (OLS) is proposed in this paper. The algorithm selects the typical samples as the initial cluster centers of RBF NN firstly, candidates centers with K-means algorithm secondly, and optimizes the candidate centers with OLS algorithm thirdly, which makes the network structure simpler and makes the prediction performance better. Experimental results show that the proposed K-means clustering OLS learning algorithm can predict the random drift of MEMS gyroscope effectively, the prediction error of which is 9.8019e-007°/s and the prediction time of which is 2.4169e-006s

Melting and Freezing of Metal Clusters

NASA Astrophysics Data System (ADS)

Aguado, Andrés; Jarrold, Martin F.

2011-05-01

Recent developments allow heat capacities to be measured for size-selected clusters isolated in the gas phase. For clusters with tens to hundreds of atoms, the heat capacities determined as a function of temperature usually have a single peak attributed to a melting transition. The melting temperatures and latent heats show large size-dependent fluctuations. In some cases, the melting temperatures change by hundreds of degrees with the addition of a single atom. Theory has played a critical role in understanding the origin of the size-dependent fluctuations, and in understanding the properties of the liquid-like and solid-like states. In some cases, the heat capacities have extra features (an additional peak or a dip) that reveal a more complex behavior than simple melting. In this article we provide a description of the methods used to measure the heat capacities and provide an overview of the experimental and theoretical results obtained for sodium and aluminum clusters.

Physical linkage of metabolic genes in fungi is an adaptation against the accumulation of toxic intermediate compounds.

PubMed

McGary, Kriston L; Slot, Jason C; Rokas, Antonis

2013-07-09

Genomic analyses have proliferated without being tied to tangible phenotypes. For example, although coordination of both gene expression and genetic linkage have been offered as genetic mechanisms for the frequently observed clustering of genes participating in fungal metabolic pathways, elucidation of the phenotype(s) favored by selection, resulting in cluster formation and maintenance, has not been forthcoming. We noted that the cause of certain well-studied human metabolic disorders is the accumulation of toxic intermediate compounds (ICs), which occurs when the product of an enzyme is not used as a substrate by a downstream neighbor in the metabolic network. This raises the hypothesis that the phenotype favored by selection to drive gene clustering is the mitigation of IC toxicity. To test this, we examined 100 diverse fungal genomes for the simplest type of cluster, gene pairs that are both metabolic neighbors and chromosomal neighbors immediately adjacent to each other, which we refer to as "double neighbor gene pairs" (DNGPs). Examination of the toxicity of their corresponding ICs shows that, compared with chromosomally nonadjacent metabolic neighbors, DNGPs are enriched for ICs that have acutely toxic LD50 doses or reactive functional groups. Furthermore, DNGPs are significantly more likely to be divergently oriented on the chromosome; remarkably, ∼40% of these DNGPs have ICs known to be toxic. We submit that the structure of synteny in metabolic pathways of fungi is a signature of selection for protection against the accumulation of toxic metabolic intermediates.

Physical linkage of metabolic genes in fungi is an adaptation against the accumulation of toxic intermediate compounds

PubMed Central

McGary, Kriston L.; Slot, Jason C.; Rokas, Antonis

2013-01-01

Genomic analyses have proliferated without being tied to tangible phenotypes. For example, although coordination of both gene expression and genetic linkage have been offered as genetic mechanisms for the frequently observed clustering of genes participating in fungal metabolic pathways, elucidation of the phenotype(s) favored by selection, resulting in cluster formation and maintenance, has not been forthcoming. We noted that the cause of certain well-studied human metabolic disorders is the accumulation of toxic intermediate compounds (ICs), which occurs when the product of an enzyme is not used as a substrate by a downstream neighbor in the metabolic network. This raises the hypothesis that the phenotype favored by selection to drive gene clustering is the mitigation of IC toxicity. To test this, we examined 100 diverse fungal genomes for the simplest type of cluster, gene pairs that are both metabolic neighbors and chromosomal neighbors immediately adjacent to each other, which we refer to as “double neighbor gene pairs” (DNGPs). Examination of the toxicity of their corresponding ICs shows that, compared with chromosomally nonadjacent metabolic neighbors, DNGPs are enriched for ICs that have acutely toxic LD50 doses or reactive functional groups. Furthermore, DNGPs are significantly more likely to be divergently oriented on the chromosome; remarkably, ∼40% of these DNGPs have ICs known to be toxic. We submit that the structure of synteny in metabolic pathways of fungi is a signature of selection for protection against the accumulation of toxic metabolic intermediates. PMID:23798424

MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma

PubMed Central

Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S.; Theis, Fabian J.

2015-01-01

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method “miRlastic”, which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic. PMID:26694379

MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma.

PubMed

Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S; Theis, Fabian J

2015-12-18

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method "miRlastic", which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic.

Molecular evolution and functional divergence of the cytochrome P450 3 (CYP3) Family in Actinopterygii (ray-finned fish).

PubMed

Yan, Jun; Cai, Zhonghua

2010-12-10

The cytochrome P450 (CYP) superfamily is a multifunctional hemethiolate enzyme that is widely distributed from Bacteria to Eukarya. The CYP3 family contains mainly the four subfamilies CYP3A, CYP3B, CYP3C and CYP3D in vertebrates; however, only the Actinopterygii (ray-finned fish) have all four subfamilies and detailed understanding of the evolutionary relationship of Actinopterygii CYP3 family members would be valuable. Phylogenetic relationships were constructed to trace the evolutionary history of the Actinopterygii CYP3 family genes. Selection analysis, relative rate tests and functional divergence analysis were combined to interpret the relationship of the site-specific evolution and functional divergence in the Actinopterygii CYP3 family. The results showed that the four CYP3 subfamilies in Actinopterygii might be formed by gene duplication. The first gene duplication event was responsible for divergence of the CYP3B/C clusters from ancient CYP3 before the origin of the Actinopterygii, which corresponded to the fish-specific whole genome duplication (WGD). Tandem repeat duplication in each of the homologue clusters produced stable CYP3B, CYP3C, CYP3A and CYP3D subfamilies. Acceleration of asymmetric evolutionary rates and purifying selection together were the main force for the production of new subfamilies and functional divergence in the new subset after gene duplication, whereas positive selection was detected only in the retained CYP3A subfamily. Furthermore, nearly half of the functional divergence sites appear to be related to substrate recognition, which suggests that site-specific evolution is closely related with functional divergence in the Actinopterygii CYP3 family. The split of fish-specific CYP3 subfamilies was related to the fish-specific WGD, and site-specific acceleration of asymmetric evolutionary rates and purifying selection was the main force for the origin of the new subfamilies and functional divergence in the new subset after gene duplication. Site-specific evolution in substrate recognition was related to functional divergence in the Actinopterygii CYP3 family.

Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms

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

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research.more » Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. As a result, the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.« less

The environment of young massive clusters

NASA Astrophysics Data System (ADS)

Vanzi, L.; Sauvage, M.

2006-06-01

We observed a sample of Blue Dwarf Galaxies in the Ks (2.2 μm) and Lα (3.7 μm) IR bands at the ESO VLT with ISAAC. The purpose of the observations was to study the population of young massive clusters and the conditions under which they are formed. The sample galaxies included: Tol 1924-416, Tol 35, Pox 36, UM 462, He 2-10, II Zw 40, Tol 3, NGC 1705, NGC 5408, IC 4662, NGC 5253. They were selected to have evidence for star formation and firm detection by IRAS. All galaxies observed turned to be very rich of young massive clusters in Ks. Only few clusters, about 8%, showed counterparts in Lα. Most L' sources can be associated to radio thermal sources, with the only exception of the NGC 1705's one. For two galaxies, NGC 5408 and IC 4662, we derived the cluster luminosity functions finding them consistent with a power law of index about -2. We compared the numbers and luminosities of the clusters with the star formation rate of the host galaxy and could not find any evidence of a relation.

Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms

DOE PAGES

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.; ...

2016-01-07

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research.more » Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. As a result, the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.« less

Kernel spectral clustering with memory effect

NASA Astrophysics Data System (ADS)

Langone, Rocco; Alzate, Carlos; Suykens, Johan A. K.

2013-05-01

Evolving graphs describe many natural phenomena changing over time, such as social relationships, trade markets, metabolic networks etc. In this framework, performing community detection and analyzing the cluster evolution represents a critical task. Here we propose a new model for this purpose, where the smoothness of the clustering results over time can be considered as a valid prior knowledge. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness. The latter allows the model to cluster the current data well and to be consistent with the recent history. We also propose new model selection criteria in order to carefully choose the hyper-parameters of our model, which is a crucial issue to achieve good performances. We successfully test the model on four toy problems and on a real world network. We also compare our model with Evolutionary Spectral Clustering, which is a state-of-the-art algorithm for community detection of evolving networks, illustrating that the kernel spectral clustering with memory effect can achieve better or equal performances.

R package to estimate intracluster correlation coefficient with confidence interval for binary data.

PubMed

Chakraborty, Hrishikesh; Hossain, Akhtar

2018-03-01

The Intracluster Correlation Coefficient (ICC) is a major parameter of interest in cluster randomized trials that measures the degree to which responses within the same cluster are correlated. There are several types of ICC estimators and its confidence intervals (CI) suggested in the literature for binary data. Studies have compared relative weaknesses and advantages of ICC estimators as well as its CI for binary data and suggested situations where one is advantageous in practical research. The commonly used statistical computing systems currently facilitate estimation of only a very few variants of ICC and its CI. To address the limitations of current statistical packages, we developed an R package, ICCbin, to facilitate estimating ICC and its CI for binary responses using different methods. The ICCbin package is designed to provide estimates of ICC in 16 different ways including analysis of variance methods, moments based estimation, direct probabilistic methods, correlation based estimation, and resampling method. CI of ICC is estimated using 5 different methods. It also generates cluster binary data using exchangeable correlation structure. ICCbin package provides two functions for users. The function rcbin() generates cluster binary data and the function iccbin() estimates ICC and it's CI. The users can choose appropriate ICC and its CI estimate from the wide selection of estimates from the outputs. The R package ICCbin presents very flexible and easy to use ways to generate cluster binary data and to estimate ICC and it's CI for binary response using different methods. The package ICCbin is freely available for use with R from the CRAN repository (https://cran.r-project.org/package=ICCbin). We believe that this package can be a very useful tool for researchers to design cluster randomized trials with binary outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Creating Quasi Two-Dimensional Cluster-Assembled Materials through Self-Assembly of a Janus Polyoxometalate-Silsesquioxane Co-Cluster.

PubMed

Wu, Han; Zhang, Yu-Qi; Hu, Min-Biao; Ren, Li-Jun; Lin, Yue; Wang, Wei

2017-05-30

Clusters are an important class of nanoscale molecules or superatoms that exhibit an amazing diversity in structure, chemical composition, shape, and functionality. Assembling two types of clusters is creating emerging cluster-assembled materials (CAMs). In this paper, we report an effective approach to produce quasi two-dimensional (2D) CAMs of two types of spherelike clusters, polyhedral oligomeric silsesquioxanes (POSS), and polyoxometalates (POM). To avoid macrophase separation between the two clusters, they are covalently linked to form a POM-POSS cocluster with Janus characteristics and a dumbbell shape. This Janus characteristics enables the cocluster to self-assemble into diverse nanoaggregates, as conventional amphiphilic molecules and macromolecules do, in selective solvents. In our study, we obtained micelles, vesicles, nanosheets, and nanoribbons by tuning the n-hexane content in mixed solvents of acetone and n-hexane. Ordered packing of clusters in the nanosheets and nanoribbons were directly visualized using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) technique. We infer that the increase of packing order results in the vesicle-to-sheet transition and the change in packing mode causes the sheet-to-ribbon transitions. Our findings have verified the effectivity of creating quasi 2D cluster-assembled materials though the cocluster self-assembly as a new approach to produce novel CAMs.

Photothermal and photoacoustic processes of laser activated nano-thermolysis of cells

NASA Astrophysics Data System (ADS)

Lapotko, Dmitri; Lukianova, Ekaterina; Mitskevich, Pavel; Smolnikova, Victoria; Potapnev, Michail; Konopleva, Marina; Andreeff, Michael; Oraevsky, Alexander

2007-02-01

Laser Activated Nano-Thermolysis was recently proposed for selective damage of individual target (cancer) cells by pulsed laser induced microbubbles around superheated clusters of optically absorbing nanoparticles (NP). One of the clinical applications of this technology is the elimination of residual tumor cells from human blood and bone marrow. Clinical standards for the safety and efficacy of such procedure require the development and verification of highly selective and controllable mechanisms of cell killing. Our previous experiments showed that laser-induced microbubble is the main damaging factor in the case cell irradiation by short laser pulses above the threshold. Our current aim was to study the cell damage mechanisms and analyze selectivity and efficacy of cell damage as a function of NP parameters, NP-cell interaction conditions, and conditions of bubble generation around NP and NP clusters in cells. Generation of laser-induced bubbles around gold NP with diameters 10-250 nm was studied in Acute Myeloblast Leukemia (AML) cultures, normal stem and model K562 human cells. Short laser pulses (10 ns, 532 nm) were applied to those cells in vitro and the processes in cells were investigated with photothermal, fluorescent and atomic force microscopies and also with fluorescence flow cytometry. We have found that the best selectivity of cell damage is achieved by (1) forming large clusters of optically absorbing NP in target cells and (2) irradiating the cells with single laser pulses with the lowest fluence that can generate microbubble only around large clusters but not around single NP. Laser microbubbles with the lifetime from 20 ns to 2000 ns generated in individual cells caused damage and lysis of the cellular membrane and consequently cell death. Laser microbubbles did not damage normal cells around the damaged target (tumor) cell. Laser irradiation with equal fluence did not cause any damage of cells without accumulated NP clusters.

The properties of small Ag clusters bound to DNA bases.

PubMed

Soto-Verdugo, Víctor; Metiu, Horia; Gwinn, Elisabeth

2010-05-21

We study the binding of neutral silver clusters, Ag(n) (n=1-6), to the DNA bases adenine (A), cytosine (C), guanine (G), and thymine (T) and the absorption spectra of the silver cluster-base complexes. Using density functional theory (DFT), we find that the clusters prefer to bind to the doubly bonded ring nitrogens and that binding to T is generally much weaker than to C, G, and A. Ag(3) and Ag(4) make the stronger bonds. Bader charge analysis indicates a mild electron transfer from the base to the clusters for all bases, except T. The donor bases (C, G, and A) bind to the sites on the cluster where the lowest unoccupied molecular orbital has a pronounced protrusion. The site where cluster binds to the base is controlled by the shape of the higher occupied states of the base. Time-dependent DFT calculations show that different base-cluster isomers may have very different absorption spectra. In particular, we find new excitations in base-cluster molecules, at energies well below those of the isolated components, and with strengths that depend strongly on the orientations of planar clusters with respect to the base planes. Our results suggest that geometric constraints on binding, imposed by designed DNA structures, may be a feasible route to engineering the selection of specific cluster-base assemblies.

Estimating and Identifying Unspecified Correlation Structure for Longitudinal Data

PubMed Central

Hu, Jianhua; Wang, Peng; Qu, Annie

2014-01-01

Identifying correlation structure is important to achieving estimation efficiency in analyzing longitudinal data, and is also crucial for drawing valid statistical inference for large size clustered data. In this paper, we propose a nonparametric method to estimate the correlation structure, which is applicable for discrete longitudinal data. We utilize eigenvector-based basis matrices to approximate the inverse of the empirical correlation matrix and determine the number of basis matrices via model selection. A penalized objective function based on the difference between the empirical and model approximation of the correlation matrices is adopted to select an informative structure for the correlation matrix. The eigenvector representation of the correlation estimation is capable of reducing the risk of model misspecification, and also provides useful information on the specific within-cluster correlation pattern of the data. We show that the proposed method possesses the oracle property and selects the true correlation structure consistently. The proposed method is illustrated through simulations and two data examples on air pollution and sonar signal studies. PMID:26361433

Rigid-Cluster Models of Conformational Transitions in Macromolecular Machines and Assemblies

PubMed Central

Kim, Moon K.; Jernigan, Robert L.; Chirikjian, Gregory S.

2005-01-01

We present a rigid-body-based technique (called rigid-cluster elastic network interpolation) to generate feasible transition pathways between two distinct conformations of a macromolecular assembly. Many biological molecules and assemblies consist of domains which act more or less as rigid bodies during large conformational changes. These collective motions are thought to be strongly related with the functions of a system. This fact encourages us to simply model a macromolecule or assembly as a set of rigid bodies which are interconnected with distance constraints. In previous articles, we developed coarse-grained elastic network interpolation (ENI) in which, for example, only Cα atoms are selected as representatives in each residue of a protein. We interpolate distance differences of two conformations in ENI by using a simple quadratic cost function, and the feasible conformations are generated without steric conflicts. Rigid-cluster interpolation is an extension of the ENI method with rigid-clusters replacing point masses. Now the intermediate conformations in an anharmonic pathway can be determined by the translational and rotational displacements of large clusters in such a way that distance constraints are observed. We present the derivation of the rigid-cluster model and apply it to a variety of macromolecular assemblies. Rigid-cluster ENI is then modified for a hybrid model represented by a mixture of rigid clusters and point masses. Simulation results show that both rigid-cluster and hybrid ENI methods generate sterically feasible pathways of large systems in a very short time. For example, the HK97 virus capsid is an icosahedral symmetric assembly composed of 60 identical asymmetric units. Its original Hessian matrix size for a Cα coarse-grained model is >(300,000)2. However, it reduces to (84)2 when we apply the rigid-cluster model with icosahedral symmetry constraints. The computational cost of the interpolation no longer scales heavily with the size of structures; instead, it depends strongly on the minimal number of rigid clusters into which the system can be decomposed. PMID:15833998

Interplay between Oxygen and Fe–S Cluster Biogenesis: Insights from the Suf Pathway

PubMed Central

2015-01-01

Iron–sulfur (Fe–S) cluster metalloproteins conduct essential functions in nearly all contemporary forms of life. The nearly ubiquitous presence of Fe–S clusters and the fundamental requirement for Fe–S clusters in both aerobic and anaerobic Archaea, Bacteria, and Eukarya suggest that these clusters were likely integrated into central metabolic pathways early in the evolution of life prior to the widespread oxidation of Earth’s atmosphere. Intriguingly, Fe–S cluster-dependent metabolism is sensitive to disruption by oxygen because of the decreased bioavailability of ferric iron as well as direct oxidation of sulfur trafficking intermediates and Fe–S clusters by reactive oxygen species. This fact, coupled with the ubiquity of Fe–S clusters in aerobic organisms, suggests that organisms evolved with mechanisms that facilitate the biogenesis and use of these essential cofactors in the presence of oxygen, which gradually began to accumulate around 2.5 billion years ago as oxygenic photosynthesis proliferated and reduced minerals that buffered against oxidation were depleted. This review highlights the most ancient of the Fe–S cluster biogenesis pathways, the Suf system, which likely was present in early anaerobic forms of life. Herein, we use the evolution of the Suf pathway to assess the relationships between the biochemical functions and physiological roles of Suf proteins, with an emphasis on the selective pressure of oxygen toxicity. Our analysis suggests that diversification into oxygen-containing environments disrupted iron and sulfur metabolism and was a main driving force in the acquisition of accessory Suf proteins (such as SufD, SufE, and SufS) by the core SufB–SufC scaffold complex. This analysis provides a new framework for the study of Fe–S cluster biogenesis pathways and Fe–S cluster-containing metalloenzymes and their complicated patterns of divergence in response to oxygen. PMID:25153801

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

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Baryon content of massive galaxy clusters at 0.57 < z < 1.33

DOE PAGES

Chiu, I.; Mohr, J.; McDonald, M.; ...

2015-11-02

Here, we study the stellar, Brightest Cluster Galaxy (BCG) and intracluster medium (ICM) masses of 14 South Pole Telescope (SPT) selected galaxy clusters with median redshift z = 0.9 and median mass M 500 = 6 x 10 14M ⊙. We estimate stellar masses for each cluster and BCG using six photometric bands spanning the range from the ultraviolet to the near-infrared observed with the VLT, HST and Spitzer. The ICM masses are derived from Chandra and XMM-Newton X-ray observations, and the virial masses are derived from the SPT Sunyaev-Zel'dovich Effect signature. At z = 0.9 the BCG mass Mmore » * BCG constitutes 0.12 ± 0.01% of the halo mass for a 6 x 10 14M ⊙ cluster, and this fraction falls as M 500 -0.58±0.007. The cluster stellar mass function has a characteristic mass M 0 = 10 11.0±0.1M ⊙, and the number of galaxies per unit mass in clusters is larger than in the field by a factor 1.65 ± 0.2. Both results are consistent with measurements on group scales and at lower redshift.« less

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

PubMed Central

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-01-01

Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR).

PubMed

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-06-01

Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.

Fischer–Tropsch Synthesis at a Low Pressure on Subnanometer Cobalt Oxide Clusters: The Effect of Cluster Size and Support on Activity and Selectivity

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

Lee, Sungsik; Lee, Byeongdu; Seifert, Sönke

2015-05-21

In this study, the catalytic activity and changes in the oxidation state during the Fischer Tropsch (FT) reaction was investigated on subnanometer size-selected cobalt clusters deposited on oxide (Al2O3, MgO) and carbon-based (ultrananocrystalline diamond UNCD) supports by temperature programmed reaction (TPRx) combined with in-situ grazing-incidence X-ray absorption characterization (GIXAS). The activity and selectivity of ultrasmall cobalt clusters exhibits a very strong dependence on cluster size and support. The evolution of the oxidation state of metal cluster during the reaction reveals that metal-support interaction plays a key role in the reaction.

Neurobiological Indicators of Disinhibition in Posttraumatic Stress Disorder

PubMed Central

Sadeh, Naomi; Spielberg, Jeffrey M.; Miller, Mark W.; Milberg, William P.; Salat, David H.; Amick, Melissa M.; Fortier, Catherine B.; McGlinchey, Regina E.

2015-01-01

Deficits in impulse control are increasingly recognized in association with posttraumatic stress disorder (PTSD). To further our understanding of the neurobiology of PTSD-related disinhibition, we examined alterations in brain morphology and network connectivity associated with response inhibition failures and PTSD severity. The sample consisted of 189 trauma-exposed Operation Enduring Freedom/Operation Iraqi Freedom veterans (89% male, ages 19–62) presenting with a range of current PTSD severity. Disinhibition was measured using commission errors on a Go/No-Go task with emotional stimuli, and PTSD was assessed using a measure of current symptom severity. Whole-brain vertex-wise analyses of cortical thickness revealed two clusters associated with PTSD-related disinhibition (Monte Carlo cluster corrected p< .05). The first cluster included portions of right inferior and middle frontal gyri and frontal pole. The second cluster spanned portions of left medial orbital frontal, rostral anterior cingulate, and superior frontal gyrus. In both clusters, commission errors were associated with reduced cortical thickness at higher (but not lower) levels of PTSD symptoms. Resting-state fMRI analyses revealed alterations in the functional connectivity of the right frontal cluster. Together, study findings suggest that reductions in cortical thickness in regions involved in flexible decision-making, emotion regulation, and response inhibition contribute to impulse control deficits in PTSD. Further, aberrant coupling between frontal regions and networks involved in selective attention, memory/learning, and response preparation suggest disruptions in functional connectivity may also play a role. PMID:25959594

Gene signatures and expression of miRNAs associated with efficacy of panitumumab in a head and neck cancer phase II trial.

PubMed

Siano, Marco; Espeli, Vittoria; Mach, Nicolas; Bossi, Paolo; Licitra, Lisa; Ghielmini, Michele; Frattini, Milo; Canevari, Silvana; De Cecco, Loris

2018-07-01

Platinum-based chemotherapy plus the anti-EGFR monoclonal antibody (mAb) cetuximab is used to treat recurrent/metastatic (RM) head-neck squamous cell carcinoma (HNSCC). Recently, we defined Cluster3 gene-expression signature as a potential predictor of favorable progression-free survival (PFS) in cetuximab-treated RM-HNSCC patients and predictor of partial metabolic FDG-PET response in an afatinib window-of-opportunity trial. Another anti-EGFR-mAb (panitumumab) was used as the treatment agent in RM-HNSCC patients in the phase II PANI01trial. PANI01 tumor samples were analyzed using functional genomics to explore response predictors to anti-EGFR therapy. Whole-gene expression and real-time PCR analyses were applied to pre-treatment samples from 25 PANI01 patients. Three gene signatures (Cluster3 score, RAS onco-signature, microenvironment score) and seven selected miRNAs were separately analyzed for association with panitumumab efficacy. Cluster3 expression levels had a profile with a significant bimodal separation of samples (P =  3.08 E-13). Higher RAS activation, microenvironment score, and miRNA expression were associated with low-Cluster3 patients. The same biomarkers were separately associated with PFS. Patients with high-Cluster3 had significantly longer PFS than patients with low-Cluster3 (median PFS: 174 versus 51 days; log-rank P = 0.0021). ROC analysis demonstrated accuracy in predicting PFS (AUC = 0.877). Despite differences in clinical settings and anti-EGFR inhibitors used for treatment, response prediction by the Cluster3 signature and selected miRNAs was essentially the same. Translation into a useful clinical assay requires validation in a broader setting. Copyright © 2018 Elsevier Ltd. All rights reserved.

Measuring Disability in Population Based Surveys: The Interrelationship between Clinical Impairments and Reported Functional Limitations in Cameroon and India

PubMed Central

2016-01-01

Purpose To investigate the relationship between two distinct measures of disability: self-reported functional limitations and objectively-screened clinical impairments. Methods We undertook an all age population-based survey of disability in two areas: North-West Cameroon (August/October 2013) and Telangana State, India (Feb/April 2014). Participants were selected for inclusion via two-stage cluster randomised sampling (probability proportionate to size cluster selection and compact segment sampling within clusters). Disability was defined as the presence of self-reported functional limitations across eight domains, or presence of moderate or greater clinical impairments. Clinical impairment screening comprised of visual acuity testing for vision impairment, pure tone audiometry for hearing impairment, musculoskeletal functioning assessment for musculoskeletal impairment, reported seizure history for epilepsy and reported symptoms of clinical depression (depression adults only). Information was collected using structured questionnaires, observations and examinations. Results Self-reported disability prevalence was 5.9% (95% CI 4.7–7.4) and 7.5% (5.9–9.4) in Cameroon and India respectively. The prevalence of moderate or greater clinical impairments in the same populations were 8.4% (7.5–9.4) in Cameroon and 10.5% (9.4–11.7) in India. Overall disability prevalence (self-report and/or screened positive to a moderate or greater clinical impairment) was 10.5% in Cameroon and 12.2% in India, with limited overlap between the sub-populations identified using the two types of tools. 33% of participants in Cameroon identified to have a disability, and 45% in India, both reported functional limitations and screened positive to objectively-screened impairments, whilst the remainder were identified via one or other tool only. A large proportion of people with moderate or severe clinical impairments did not self-report functional difficulties despite reporting participation restrictions. Conclusion Tools to assess reported functional limitation alone are insufficient to identify all persons with participation restrictions and moderate or severe clinical impairments. A self-reported functional limitation tool followed by clinical screening of all those who report any level of difficulty would identify 94% of people with disabilities in Cameroon and 95% in India, meeting the study criteria. PMID:27741320

Measuring Disability in Population Based Surveys: The Interrelationship between Clinical Impairments and Reported Functional Limitations in Cameroon and India.

PubMed

Mactaggart, Islay; Kuper, Hannah; Murthy, G V S; Oye, Joseph; Polack, Sarah

2016-01-01

To investigate the relationship between two distinct measures of disability: self-reported functional limitations and objectively-screened clinical impairments. We undertook an all age population-based survey of disability in two areas: North-West Cameroon (August/October 2013) and Telangana State, India (Feb/April 2014). Participants were selected for inclusion via two-stage cluster randomised sampling (probability proportionate to size cluster selection and compact segment sampling within clusters). Disability was defined as the presence of self-reported functional limitations across eight domains, or presence of moderate or greater clinical impairments. Clinical impairment screening comprised of visual acuity testing for vision impairment, pure tone audiometry for hearing impairment, musculoskeletal functioning assessment for musculoskeletal impairment, reported seizure history for epilepsy and reported symptoms of clinical depression (depression adults only). Information was collected using structured questionnaires, observations and examinations. Self-reported disability prevalence was 5.9% (95% CI 4.7-7.4) and 7.5% (5.9-9.4) in Cameroon and India respectively. The prevalence of moderate or greater clinical impairments in the same populations were 8.4% (7.5-9.4) in Cameroon and 10.5% (9.4-11.7) in India. Overall disability prevalence (self-report and/or screened positive to a moderate or greater clinical impairment) was 10.5% in Cameroon and 12.2% in India, with limited overlap between the sub-populations identified using the two types of tools. 33% of participants in Cameroon identified to have a disability, and 45% in India, both reported functional limitations and screened positive to objectively-screened impairments, whilst the remainder were identified via one or other tool only. A large proportion of people with moderate or severe clinical impairments did not self-report functional difficulties despite reporting participation restrictions. Tools to assess reported functional limitation alone are insufficient to identify all persons with participation restrictions and moderate or severe clinical impairments. A self-reported functional limitation tool followed by clinical screening of all those who report any level of difficulty would identify 94% of people with disabilities in Cameroon and 95% in India, meeting the study criteria.

Hybrid fuzzy cluster ensemble framework for tumor clustering from biomolecular data.

PubMed

Yu, Zhiwen; Chen, Hantao; You, Jane; Han, Guoqiang; Li, Le

2013-01-01

Cancer class discovery using biomolecular data is one of the most important tasks for cancer diagnosis and treatment. Tumor clustering from gene expression data provides a new way to perform cancer class discovery. Most of the existing research works adopt single-clustering algorithms to perform tumor clustering is from biomolecular data that lack robustness, stability, and accuracy. To further improve the performance of tumor clustering from biomolecular data, we introduce the fuzzy theory into the cluster ensemble framework for tumor clustering from biomolecular data, and propose four kinds of hybrid fuzzy cluster ensemble frameworks (HFCEF), named as HFCEF-I, HFCEF-II, HFCEF-III, and HFCEF-IV, respectively, to identify samples that belong to different types of cancers. The difference between HFCEF-I and HFCEF-II is that they adopt different ensemble generator approaches to generate a set of fuzzy matrices in the ensemble. Specifically, HFCEF-I applies the affinity propagation algorithm (AP) to perform clustering on the sample dimension and generates a set of fuzzy matrices in the ensemble based on the fuzzy membership function and base samples selected by AP. HFCEF-II adopts AP to perform clustering on the attribute dimension, generates a set of subspaces, and obtains a set of fuzzy matrices in the ensemble by performing fuzzy c-means on subspaces. Compared with HFCEF-I and HFCEF-II, HFCEF-III and HFCEF-IV consider the characteristics of HFCEF-I and HFCEF-II. HFCEF-III combines HFCEF-I and HFCEF-II in a serial way, while HFCEF-IV integrates HFCEF-I and HFCEF-II in a concurrent way. HFCEFs adopt suitable consensus functions, such as the fuzzy c-means algorithm or the normalized cut algorithm (Ncut), to summarize generated fuzzy matrices, and obtain the final results. The experiments on real data sets from UCI machine learning repository and cancer gene expression profiles illustrate that 1) the proposed hybrid fuzzy cluster ensemble frameworks work well on real data sets, especially biomolecular data, and 2) the proposed approaches are able to provide more robust, stable, and accurate results when compared with the state-of-the-art single clustering algorithms and traditional cluster ensemble approaches.

Subcellular Relocalization and Positive Selection Play Key Roles in the Retention of Duplicate Genes of Populus Class III Peroxidase Family[W][OPEN

PubMed Central

Ren, Lin-Ling; Liu, Yan-Jing; Liu, Hai-Jing; Qian, Ting-Ting; Qi, Li-Wang; Wang, Xiao-Ru; Zeng, Qing-Yin

2014-01-01

Gene duplication is the primary source of new genes and novel functions. Over the course of evolution, many duplicate genes lose their function and are eventually removed by deletion. However, some duplicates have persisted and evolved diverse functions. A particular challenge is to understand how this diversity arises and whether positive selection plays a role. In this study, we reconstructed the evolutionary history of the class III peroxidase (PRX) genes from the Populus trichocarpa genome. PRXs are plant-specific enzymes that play important roles in cell wall metabolism and in response to biotic and abiotic stresses. We found that two large tandem-arrayed clusters of PRXs evolved from an ancestral cell wall type PRX to vacuole type, followed by tandem duplications and subsequent functional specification. Substitution models identified seven positively selected sites in the vacuole PRXs. These positively selected sites showed significant effects on the biochemical functions of the enzymes. We also found that positive selection acts more frequently on residues adjacent to, rather than directly at, a critical active site of the enzyme, and on flexible regions rather than on rigid structural elements of the protein. Our study provides new insights into the adaptive molecular evolution of plant enzyme families. PMID:24934172

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

PubMed Central

Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel

2018-01-01

Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102

Selective memory generalization by spatial patterning of protein synthesis

PubMed Central

O’Donnell, Cian; Sejnowski, Terrence J.

2014-01-01

Summary Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings we proposed a novel two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. PMID:24742462

Selective memory generalization by spatial patterning of protein synthesis.

PubMed

O'Donnell, Cian; Sejnowski, Terrence J

2014-04-16

Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings, we proposed a two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

VizieR Online Data Catalog: XXL Survey: First results (Pierre+, 2016)

NASA Astrophysics Data System (ADS)

Pierre, M.; Pacaud, F.; Adami, C.; Alis, S.; Altieri, B.; Baran, B.; Benoist, C.; Birkinshaw, M.; Bongiorno, A.; Bremer, M. N.; Brusa, M.; Butler, A.; Ciliegi, P.; Chiappetti, L.; Clerc, N.; Corasaniti, P. S.; Coupon, J.; De Breuck, C.; Democles, J.; Desai, S.; Delhaize, J.; Devriendt, J.; Dubois, Y.; Eckert, D.; Elyiv, A.; Ettori, S.; Evrard, A.; Faccioli, L.; Farahi, A.; Ferrari, C.; Finet, F.; Fotopoulou, S.; Fourmanoit, N.; Gandhi, P.; Gastaldello, F.; Gastaud, R.; Georgantopoulos, I.; Giles, P.; Guennou, L.; Guglielmo, V.; Horellou, C.; Husband, K.; Huynh, M.; Iovino, A.; Kilbinger, M.; Koulouridis, E.; Lavoie, S.; Le Brun, A. M. C.; Lefevre, J. P.; Lidman, C.; Lieu, M.; Lin, C. A.; Mantz, A.; Maughan, B. J.; Maurogordato, S.; McCarthy, I. G.; McGee, S.; Melin, J. B.; Melnyk, O.; Menanteau, F.; Novak, M.; Paltani, S.; Plionis, M.; Poggianti, B. M.; Pomarede, D.; Pompei, E.; Ponman, T. J.; Ramos-Ceja, M. E.; Ranalli, P.; Rapetti, D.; Raychaudury, S.; Reiprich, T. H.; Rottgering, H.; Rozo, E.; Ryko, E.; Sadibekova, T.; Santos, J.; Sauvageot, J. L.; Schimd, C.; Sereno, M.; Smith, G. P.; Smolcic, V.; Snowden, S.; Spergel, D.; Stanford, S.; Surdej, J.; Valageas, P.; Valotti, A.; Valtchanov, I.; Vignali, C.; Willis, J.; Ziparo, F.

2016-03-01

Paper I. Scientific motivations - XMM-Newton observing plan. Follow-up observations and simulation programme. The table xxlpoint.dat is a list of all XMM survey-type observations (<=AO-10) in the XXL fields, providing the match between the internal naming and the ESA XXM log,the coordinates and useful exposure times of the XMM pointings, their quality and ancillary information. Paper II. The bright cluster sample: catalogue and luminosity function. Paper III. Luminosity-temperature relation of the bright cluster sample. Paper IV. Mass-temperature relation of the bright cluster sample. This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of 3*10-14erg/cm2/s on the source flux within a 1' aperture. The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. The bright cluster sample consists of systems with masses between M500=7*10+14 and 3*10+14Mȯ, mostly located between z=0.1 and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the prediction from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of σ8 and/or ΩM appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to z~1. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters. We provide the XXL-100-GC catalogue (xxl100gc.dat), the master catalogue of the 100 brightest galaxy clusters from the XXL Survey. This catalogue summarizes all the information published on this sample by the XXL collaboration, which were initially distributed over several articles. It contains the sources positions, redshifts, fluxes and mass estimates published in Appendix D of paper II, combined with luminosities and temperatures from Table 1 of paper III, as well as gas masses from Table A.1 of paper XIII. Paper VI. The 1000 brightest X-ray point sources. We provide the XXL1000AGN catalogue (xxl1000a.dat), the first catalogue release of the XXL point source catalog, detected in the 2-10keV energy band. The catalogue contains the 1000 brightest sources, at the flux limit of F[2-10 keV]=4.8 10-14erg/s/cm2. We provide derived X-ray spectral parameters, and counterpart properties including four optical magnitudes, photometric and spectroscopic redshift estimates. We also provide the best photometric redshift class based on machine learning classification and the probability for a source to be a star or a photometric redshift outlier. Paper IX. Optical overdensity and radio continuum analysis of a supercluster at z=0.43. The table xxl_vla.dat contains the full source catalogue of all 155 radio sources detected with S/N>=6 in the Very Large Array 3GHz continuum survey of the XXL-North field. The observations covered the 0.7x0.7 square degrees subarea of the 25 square degree XXL-North field. The radio data has an angular resolution of 3.2x1.9 square arcsec and a mean rms of 20uJy per beam. There are 25 resolved sources, of which 8 are multicomponent objects. Paper XI. ATCA 2.1 GHz continuum observations. The table xxl_atca.dat contains the full source catalogue of all 1389 radio sources detected with S/N>=5 in the Australia Telescope Compact Array 2.1GHz continuum pilot survey of the XXL-South field. The observations covered the inner 6.5 square degrees of the 25 square degree XXL-South field. The radio data has an angular resolution of 4.7x4.2 square arcsec and a median rms of 50uJy per beam. There are 305 resolved sources, of which 77 are multicomponent objects. The table contains various observed parameters of the radio sources, such as position, peak flux density and signal-to-noise ratio. Paper XIV. AAOmega redshifts for the southern XXL field. We present a catalogue (xxlaaoz.dat) containing the redshifts of 3660 X-ray selected targets in the XXL southern field. The redshifts were obtained with the AAOmega spectrograph and 2dF fibre positioner on the Anglo-Australian Telescope. The catalogue contains 1515 broad line AGN, 528 stars, and redshifts for 41 out of the 49 brightest X-ray selected clusters in the XXL southern field. Paper XV. Evidence for dry merger driven BCG growth in XXL-100-GC X-ray clusters Given the availability of good quality multiband photometry together with photometric and spectroscopic redshifts to z<1, a simple set of criteria can be used to identify BCGs. For the present work, we define a BCG as: - the brightest galaxy in z-band, - within 0.5xr500 of the cluster X-ray centroid, - with a redshift that is consistent with that of the cluster as determined from all the redshifts available around the X-ray centroid. Our final sample (xxl100bc.dat) consists of 85 clusters, 45 of which are in the Northern field and 40 in the Southern field. (9 data files).

Association between Physical Activity Levels and Physiological Factors Underlying Mobility in Young, Middle-Aged and Older Individuals Living in a City District

PubMed Central

Laudani, Luca; Vannozzi, Giuseppe; Sawacha, Zimi; della Croce, Ugo; Cereatti, Andrea; Macaluso, Andrea

2013-01-01

Maintaining adequate levels of physical activity is known to preserve health status and functional independence as individuals grow older. However, the relationship between determinants of physical activity (volume and intensity) and physiological factors underlying mobility (cardio-respiratory fitness, neuromuscular function and functional abilities) is still unclear. The aim of this study was to investigate the association between objectively quantified physical activity and a spectrum of physiological factors underlying mobility in young, middle-aged and older individuals living in a city district. Experiments were carried out on 24 young (28±2 years), 24 middle-aged (48±2 years) and 24 older (70±3 years) gender-matched volunteers. Physical activity was monitored by a wearable activity monitor to quantify volume and intensity of overall physical activity and selected habitual activities over 24 hours. Ventilatory threshold was assessed during an incremental cycling test. Torque, muscle fiber conduction velocity and agonist-antagonist coactivation were measured during maximal voluntary contraction of knee extensors and flexors. Ground reaction forces were measured during sit-to-stand and counter-movement jump. K-means cluster analysis was used to classify the participants’ physical activity levels based on parameters of volume and intensity. Two clusters of physical activity volume (i.e., high and low volume) and three clusters of physical activity intensity (i.e. high, medium and low intensity) were identified in all participants. Cardio-respiratory fitness was associated with volume of overall physical activity as well as lying, sitting, standing, walking and stair climbing. On the other hand, neuromuscular function and functional abilities showed a significant association with intensity of overall physical activity as well as postural transition, walking and stair climbing. As a practical application, the relative role played by volume and intensity of overall physical activity and selected habitual activities should be taken into account in the design of preventative training interventions to preserve mobility as individuals grow older. PMID:24040209

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.

Absorption line indices in the UV. I. Empirical and theoretical stellar population models

NASA Astrophysics Data System (ADS)

Maraston, C.; Nieves Colmenárez, L.; Bender, R.; Thomas, D.

2009-01-01

Aims: Stellar absorption lines in the optical (e.g. the Lick system) have been extensively studied and constitute an important stellar population diagnostic for galaxies in the local universe and up to moderate redshifts. Proceeding towards higher look-back times, galaxies are younger and the ultraviolet becomes the relevant spectral region where the dominant stellar populations shine. A comprehensive study of ultraviolet absorption lines of stellar population models is however still lacking. With this in mind, we study absorption line indices in the far and mid-ultraviolet in order to determine age and metallicity indicators for UV-bright stellar populations in the local universe as well as at high redshift. Methods: We explore empirical and theoretical spectral libraries and use evolutionary population synthesis to compute synthetic line indices of stellar population models. From the empirical side, we exploit the IUE-low resolution library of stellar spectra and system of absorption lines, from which we derive analytical functions (fitting functions) describing the strength of stellar line indices as a function of gravity, temperature and metallicity. The fitting functions are entered into an evolutionary population synthesis code in order to compute the integrated line indices of stellar populations models. The same line indices are also directly evaluated on theoretical spectral energy distributions of stellar population models based on Kurucz high-resolution synthetic spectra, In order to select indices that can be used as age and/or metallicity indicators for distant galaxies and globular clusters, we compare the models to data of template globular clusters from the Magellanic Clouds with independently known ages and metallicities. Results: We provide synthetic line indices in the wavelength range ~1200 Å to ~3000 Å for stellar populations of various ages and metallicities.This adds several new indices to the already well-studied CIV and SiIV absorptions. Based on the comparison with globular cluster data, we select a set of 11 indices blueward of the 2000 Å rest-frame that allows us to recover well the ages and the metallicities of the clusters. These indices are ideal to study ages and metallicities of young galaxies at high redshift. We also provide the synthetic high-resolution stellar population SEDs.

YOUNG STELLAR CLUSTERS CONTAINING MASSIVE YOUNG STELLAR OBJECTS IN THE VVV SURVEY

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

Borissova, J.; Alegría, S. Ramírez; Kurtev, R.

The purpose of this research is to study the connections of the global properties of eight young stellar clusters projected in the Vista Variables in the Via Lactea (VVV) ESO Large Public Survey disk area and their young stellar object (YSO) populations. The analysis is based on the combination of spectroscopic parallax-based reddening and distance determinations with main-sequence and pre-main-sequence ishochrone fitting to determine the basic parameters (reddening, age, distance) of the sample clusters. The lower mass limit estimations show that all clusters are low or intermediate mass (between 110 and 1800  M {sub ⊙}), the slope Γ of themore » obtained present-day mass functions of the clusters is close to the Kroupa initial mass function. The YSOs in the cluster’s surrounding fields are classified using low resolution spectra, spectral energy distribution fits with theoretical predictions, and variability, taking advantage of multi-epoch VVV observations. All spectroscopically confirmed YSOs (except one) are found to be massive (more than 8 M {sub ⊙}). Using VVV and GLIMPSE color–color cuts we have selected a large number of new YSO candidates, which are checked for variability and 57% are found to show at least low-amplitude variations. In few cases it was possible to distinguish between YSO and AGB classifications on the basis of light curves.« less

A populous intermediate-age open cluster and evidence of an embedded cluster among the FSR globular cluster candidates

NASA Astrophysics Data System (ADS)

Bica, E.; Bonatto, C.

2008-03-01

We study the nature of the globular cluster (GC) candidates FSR 1603 and FSR1755 selected from the catalogue of Froebrich, Scholz & Raftery. Their properties are investigated with Two-Micron All-Sky Survey field-star decontaminated photometry, which is used to build colour-magnitude diagrams (CMDs) and stellar radial density profiles. FSR1603 has the open cluster Ruprecht 101 as optical counterpart, and we show it to be a massive intermediate-age cluster. Relevant parameters of FSR1603 are the age ~1Gyr, distance from the Sun dsolar ~ 2.7kpc, Galactocentric distance RGC ~ 6.4kpc, core radius RC ~ 1.1pc, mass function slope χ ~ 1.8, observed stellar mass (for stars with mass in the range 1.27 <= m <= 2.03Msolar) Mobs ~ 500Msolar and a total (extrapolated to m = 0.08Msolar) stellar mass Mtot ~ 2300Msolar. FSR1755, on the other hand, is not a populous cluster. It may be a sparse young cluster embedded in the HII region Sh2-3, subject to an absorption AV ~ 4.1, located at dsolar ~ 1.3kpc. Important field-star contamination, spatially variable heavy dust obscuration, even in Ks, and gas emission characterize its field. A nearly vertical, sparse blue stellar sequence shows up in the CMDs.

Cluster-guided imaging-based CFD analysis of airflow and particle deposition in asthmatic human lungs

NASA Astrophysics Data System (ADS)

Choi, Jiwoong; Leblanc, Lawrence; Choi, Sanghun; Haghighi, Babak; Hoffman, Eric; Lin, Ching-Long

2017-11-01

The goal of this study is to assess inter-subject variability in delivery of orally inhaled drug products to small airways in asthmatic lungs. A recent multiscale imaging-based cluster analysis (MICA) of computed tomography (CT) lung images in an asthmatic cohort identified four clusters with statistically distinct structural and functional phenotypes associating with unique clinical biomarkers. Thus, we aimed to address inter-subject variability via inter-cluster variability. We selected a representative subject from each of the 4 asthma clusters as well as 1 male and 1 female healthy controls, and performed computational fluid and particle simulations on CT-based airway models of these subjects. The results from one severe and one non-severe asthmatic cluster subjects characterized by segmental airway constriction had increased particle deposition efficiency, as compared with the other two cluster subjects (one non-severe and one severe asthmatics) without airway constriction. Constriction-induced jets impinging on distal bifurcations led to excessive particle deposition. The results emphasize the impact of airway constriction on regional particle deposition rather than disease severity, demonstrating the potential of using cluster membership to tailor drug delivery. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837. XSEDE.

Domain Selectivity in the Parahippocampal Gyrus Is Predicted by the Same Structural Connectivity Patterns in Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; He, Chenxi; Peelen, Marius V; Zhong, Suyu; Gong, Gaolang; Caramazza, Alfonso; Bi, Yanchao

2017-05-03

Human ventral occipital temporal cortex contains clusters of neurons that show domain-preferring responses during visual perception. Recent studies have reported that some of these clusters show surprisingly similar domain selectivity in congenitally blind participants performing nonvisual tasks. An important open question is whether these functional similarities are driven by similar innate connections in blind and sighted groups. Here we addressed this question focusing on the parahippocampal gyrus (PHG), a region that is selective for large objects and scenes. Based on the assumption that patterns of long-range connectivity shape local computation, we examined whether domain selectivity in PHG is driven by similar structural connectivity patterns in the two populations. Multiple regression models were built to predict the selectivity of PHG voxels for large human-made objects from white matter (WM) connectivity patterns in both groups. These models were then tested using independent data from participants with similar visual experience (two sighted groups) and using data from participants with different visual experience (blind and sighted groups). Strikingly, the WM-based predictions between blind and sighted groups were as successful as predictions between two independent sighted groups. That is, the functional selectivity for large objects of a PHG voxel in a blind participant could be accurately predicted by its WM pattern using the connection-to-function model built from the sighted group data, and vice versa. Regions that significantly predicted PHG selectivity were located in temporal and frontal cortices in both sighted and blind populations. These results show that the large-scale network driving domain selectivity in PHG is independent of vision. SIGNIFICANCE STATEMENT Recent studies have reported intriguingly similar domain selectivity in sighted and congenitally blind individuals in regions within the ventral visual cortex. To examine whether these similarities originate from similar innate connectional roots, we investigated whether the domain selectivity in one population could be predicted by the structural connectivity pattern of the other. We found that the selectivity for large objects of a PHG voxel in a blind participant could be predicted by its structural connectivity pattern using the connection-to-function model built from the sighted group data, and vice versa. These results reveal that the structural connectivity underlying domain selectivity in the PHG is independent of visual experience, providing evidence for nonvisual representations in this region. Copyright © 2017 the authors 0270-6474/17/374706-12$15.00/0.

X-Ray Temperatures, Luminosities, and Masses from XMM-Newton Follow-up of the First Shear-selected Galaxy Cluster Sample

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

Deshpande, Amruta J.; Hughes, John P.; Wittman, David, E-mail: amrejd@physics.rutgers.edu, E-mail: jph@physics.rutgers.edu, E-mail: dwittman@physics.ucdavis.edu

We continue the study of the first sample of shear-selected clusters from the initial 8.6 square degrees of the Deep Lens Survey (DLS); a sample with well-defined selection criteria corresponding to the highest ranked shear peaks in the survey area. We aim to characterize the weak lensing selection by examining the sample’s X-ray properties. There are multiple X-ray clusters associated with nearly all the shear peaks: 14 X-ray clusters corresponding to seven DLS shear peaks. An additional three X-ray clusters cannot be definitively associated with shear peaks, mainly due to large positional offsets between the X-ray centroid and the shearmore » peak. Here we report on the XMM-Newton properties of the 17 X-ray clusters. The X-ray clusters display a wide range of luminosities and temperatures; the L {sub X} − T {sub X} relation we determine for the shear-associated X-ray clusters is consistent with X-ray cluster samples selected without regard to dynamical state, while it is inconsistent with self-similarity. For a subset of the sample, we measure X-ray masses using temperature as a proxy, and compare to weak lensing masses determined by the DLS team. The resulting mass comparison is consistent with equality. The X-ray and weak lensing masses show considerable intrinsic scatter (∼48%), which is consistent with X-ray selected samples when their X-ray and weak lensing masses are independently determined.« less

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

PubMed

Ballante, Flavio; Marshall, Garland R

2016-01-25

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.

Tagging of Endogenous BK Channels with a Fluorogen-Activating Peptide Reveals β4-Mediated Control of Channel Clustering in Cerebellum

PubMed Central

Pratt, Christopher P.; Kuljis, Dika A.; Homanics, Gregg E.; He, Jianjun; Kolodieznyi, Dmytro; Dudem, Srikanth; Hollywood, Mark A.; Barth, Alison L.; Bruchez, Marcel P.

2017-01-01

BK channels are critical regulators of neuronal activity, controlling firing, neurotransmitter release, cerebellar function, and BK channel mutations have been linked to seizure disorders. Modulation of BK channel gating is well characterized, regulated by accessory subunit interactions, intracellular signaling pathways, and membrane potential. In contrast, the role of intracellular trafficking mechanisms in controlling BK channel function, especially in live cells, has been less studied. Fluorogen-activating peptides (FAPs) are well-suited for trafficking and physiological studies due to the binding of malachite green (MG)-based dyes with sub-nanomolar affinity to the FAP, resulting in bright, photostable, far-red fluorescence. Cell-excluded MG dyes enable the selective tagging of surface protein and tracking through endocytic pathways. We used CRISPR to insert the FAP at the extracellular N-terminus of BKα in the first exon of its native locus, enabling regulation by the native promoter elements and tag incorporation into multiple splice isoforms. Motor coordination was found to be normal; however, BK channel expression seems to be reduced in some locations. Alternate start site selection or post-translational proteolytic processing resulted in incomplete FAP tagging of the BKα proteins in brain tissues. In Purkinje cell somata, FAP revealed BK channel clustering previously only observed by electron microscopy. Measurement of these clusters in β4+/- and β4-/- mice showed that puncta number and cluster fluorescence intensity on the soma are reduced in β4-/- knockout animals. This novel mouse line provides a versatile fluorescent platform for studying endogenous BK channels in living and fixed tissues. Future studies could apply this line to ex vivo neuronal cultures to study live-cell channel trafficking. PMID:29163049

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

PubMed

Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

2018-01-01

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

The Incomplete Conditional Stellar Mass Function: Unveiling the Stellar Mass Functions of Galaxies at 0.1 < Z < 0.8 from BOSS Observations

NASA Astrophysics Data System (ADS)

Guo, Hong; Yang, Xiaohu; Lu, Yi

2018-05-01

We propose a novel method to constrain the missing fraction of galaxies using galaxy clustering measurements in the galaxy conditional stellar mass function (CSMF) framework, which is applicable to surveys that suffer significantly from sample selection effects. The clustering measurements, which are not sensitive to the random sampling (missing fraction) of galaxies, are widely used to constrain the stellar–halo mass relation (SHMR). By incorporating a missing fraction (incompleteness) component into the CSMF model (ICSMF), we use the incomplete stellar mass function and galaxy clustering to simultaneously constrain the missing fractions and the SHMRs. Tests based on mock galaxy catalogs with a few typical missing fraction models show that this method can accurately recover the missing fraction and the galaxy SHMR, hence providing us with reliable measurements of the galaxy stellar mass functions. We then apply it to the Baryon Oscillation Spectroscopic Survey (BOSS) over the redshift range of 0.1 < z < 0.8 for galaxies of M * > 1011 M ⊙. We find that the sample completeness for BOSS is over 80% at z < 0.6 but decreases at higher redshifts to about 30%. After taking these completeness factors into account, we provide accurate measurements of the stellar mass functions for galaxies with {10}11 {M}ȯ < {M}* < {10}12 {M}ȯ , as well as the SHMRs, over the redshift range 0.1 < z < 0.8 in this largest galaxy redshift survey.

Exploring the effect of oxygen-containing functional groups on the water-holding capacity of lignite.

PubMed

Liu, Jie; Jiang, Xiangang; Cao, Yu; Zhang, Chen; Zhao, Guangyao; Zhao, Maoshuang; Feng, Li

2018-05-07

Graphene oxide with different degrees of oxidation was prepared and selected as a model compound of lignite to study quantitatively, using both experiment and theoretical calculation methods, the effect on water-holding capacity of oxygen-containing functional groups. The experimental results showed that graphite can be oxidized, and forms epoxy groups most easily, followed by hydroxyl and carboxyl groups. The prepared graphene oxide forms a membrane-state as a single layer structure, with an irregular surface. The water-holding capacity of lignite increased with the content of oxygen-containing functional groups. The influence on the configuration of water molecule clusters and binding energy of water molecules of different oxygen-containing functional groups was calculated by density functional theory. The calculation results indicated that the configuration of water molecule clusters was totally changed by oxygen-containing functional groups. The order of binding energy produced by oxygen-containing functional groups and water molecules was as follows: carboxyl > edge phenol hydroxyl >epoxy group. Finally, it can be concluded that the potential to form more hydrogen bonds is the key factor influencing the interaction energy between model compounds and water molecules.

Cluster size selectivity in the product distribution of ethene dehydrogenation on niobium clusters.

PubMed

Parnis, J Mark; Escobar-Cabrera, Eric; Thompson, Matthew G K; Jacula, J Paul; Lafleur, Rick D; Guevara-García, Alfredo; Martínez, Ana; Rayner, David M

2005-08-18

Ethene reactions with niobium atoms and clusters containing up to 25 constituent atoms have been studied in a fast-flow metal cluster reactor. The clusters react with ethene at about the gas-kinetic collision rate, indicating a barrierless association process as the cluster removal step. Exceptions are Nb8 and Nb10, for which a significantly diminished rate is observed, reflecting some cluster size selectivity. Analysis of the experimental primary product masses indicates dehydrogenation of ethene for all clusters save Nb10, yielding either Nb(n)C2H2 or Nb(n)C2. Over the range Nb-Nb6, the extent of dehydrogenation increases with cluster size, then decreases for larger clusters. For many clusters, secondary and tertiary product masses are also observed, showing varying degrees of dehydrogenation corresponding to net addition of C2H4, C2H2, or C2. With Nb atoms and several small clusters, formal addition of at least six ethene molecules is observed, suggesting a polymerization process may be active. Kinetic analysis of the Nb atom and several Nb(n) cluster reactions with ethene shows that the process is consistent with sequential addition of ethene units at rates corresponding approximately to the gas-kinetic collision frequency for several consecutive reacting ethene molecules. Some variation in the rate of ethene pick up is found, which likely reflects small energy barriers or steric constraints associated with individual mechanistic steps. Density functional calculations of structures of Nb clusters up to Nb(6), and the reaction products Nb(n)C2H2 and Nb(n)C2 (n = 1...6) are presented. Investigation of the thermochemistry for the dehydrogenation of ethene to form molecular hydrogen, for the Nb atom and clusters up to Nb6, demonstrates that the exergonicity of the formation of Nb(n)C2 species increases with cluster size over this range, which supports the proposal that the extent of dehydrogenation is determined primarily by thermodynamic constraints. Analysis of the structural variations present in the cluster species studied shows an increase in C-H bond lengths with cluster size that closely correlates with the increased thermodynamic drive to full dehydrogenation. This correlation strongly suggests that all steps in the reaction are barrierless, and that weakening of the C-H bonds is directly reflected in the thermodynamics of the overall dehydrogenation process. It is also demonstrated that reaction exergonicity in the initial partial dehydrogenation step must be carried through as excess internal energy into the second dehydrogenation step.

Genetic Characterization of the Hemagglutinin Genes of Wild-Type Measles Virus Circulating in China, 1993–2009

PubMed Central

Zhu, Zhen; Liu, Chunyu; Mao, Naiying; Ji, Yixin; Wang, Huiling; Jiang, Xiaohong; Li, Chongshan; Tang, Wei; Feng, Daxing; Wang, Changyin; Zheng, Lei; Lei, Yue; Ling, Hua; Zhao, Chunfang; Ma, Yan; He, Jilan; Wang, Yan; Li, Ping; Guan, Ronghui; Zhou, Shujie; Zhou, Jianhui; Wang, Shuang; Zhang, Hong; Zheng, Huanying; Liu, Leng; Ma, Hemuti; Guan, Jing; Lu, Peishan; Feng, Yan; Zhang, Yanjun; Zhou, Shunde; Xiong, Ying; Ba, Zhuoma; Chen, Hui; Yang, Xiuhui; Bo, Fang; Ma, Yujie; Liang, Yong; Lei, Yake; Gu, Suyi; Liu, Wei; Chen, Meng; Featherstone, David; Jee, Youngmee; Bellini, William J.; Rota, Paul A.; Xu, Wenbo

2013-01-01

Background China experienced several large measles outbreaks in the past two decades, and a series of enhanced control measures were implemented to achieve the goal of measles elimination. Molecular epidemiologic surveillance of wild-type measles viruses (MeV) provides valuable information about the viral transmission patterns. Since 1993, virologic surveillnace has confirmed that a single endemic genotype H1 viruses have been predominantly circulating in China. A component of molecular surveillance is to monitor the genetic characteristics of the hemagglutinin (H) gene of MeV, the major target for virus neutralizing antibodies. Principal Findings Analysis of the sequences of the complete H gene from 56 representative wild-type MeV strains circulating in China during 1993–2009 showed that the H gene sequences were clustered into 2 groups, cluster 1 and cluster 2. Cluster1 strains were the most frequently detected cluster and had a widespread distribution in China after 2000. The predicted amino acid sequences of the H protein were relatively conserved at most of the functionally significant amino acid positions. However, most of the genotype H1 cluster1 viruses had an amino acid substitution (Ser240Asn), which removed a predicted N-linked glycosylation site. In addition, the substitution of Pro397Leu in the hemagglutinin noose epitope (HNE) was identified in 23 of 56 strains. The evolutionary rate of the H gene of the genotype H1 viruses was estimated to be approximately 0.76×10−3 substitutions per site per year, and the ratio of dN to dS (dN/dS) was <1 indicating the absence of selective pressure. Conclusions Although H genes of the genotype H1 strains were conserved and not subjected to selective pressure, several amino acid substitutions were observed in functionally important positions. Therefore the antigenic and genetic properties of H genes of wild-type MeVs should be monitored as part of routine molecular surveillance for measles in China. PMID:24073194

Do X-ray dark or underluminous galaxy clusters exist?

NASA Astrophysics Data System (ADS)

Andreon, S.; Moretti, A.

2011-12-01

We study the X-ray properties of a color-selected sample of clusters at 0.1 < z < 0.3, to quantify the real aboundance of the population of X-ray dark or underluminous clusters and at the same time the spurious detection contamination level of color-selected cluster catalogs. Starting from a local sample of color-selected clusters, we restrict our attention to those with sufficiently deep X-ray observations to probe their X-ray luminosity down to very faint values and without introducing any X-ray bias. This allowed us to have an X-ray- unbiased sample of 33 clusters to measure the LX-richness relation. Swift 1.4 Ms X-ray observations show that at least 89% of the color-detected clusters are real objects with a potential well deep enough to heat and retain an intracluster medium. The percentage rises to 94% when one includes the single spectroscopically confirmed color-selected cluster whose X-ray emission is not secured. Looking at our results from the opposite perspective, the percentage of X-ray dark clusters among color-selected clusters is very low: at most about 11 per cent (at 90% confidence). Supplementing our data with those from literature, we conclude that X-ray- and color- cluster surveys sample the same population and consequently that in this regard we can safely use clusters selected with any of the two methods for cosmological purposes. This is an essential and promising piece of information for upcoming surveys in both the optical/IR (DES, EUCLID) and X-ray (eRosita). Richness correlates with X-ray luminosity with a large scatter, 0.51 ± 0.08 (0.44 ± 0.07) dex in lgLX at a given richness, when Lx is measured in a 500 (1070) kpc aperture. We release data and software to estimate the X-ray flux, or its upper limit, of a source with over-Poisson background fluctuations (found in this work to be ~20% on cluster angular scales) and to fit X-ray luminosity vs richness if there is an intrinsic scatter. These Bayesian applications rigorously account for boundaries (e.g., the X-ray luminosity and the richness cannot be negative).

Evolution of the real-space correlation function from next generation cluster surveys. Recovering the real-space correlation function from photometric redshifts

NASA Astrophysics Data System (ADS)

Sridhar, Srivatsan; Maurogordato, Sophie; Benoist, Christophe; Cappi, Alberto; Marulli, Federico

2017-04-01

Context. The next generation of galaxy surveys will provide cluster catalogues probing an unprecedented range of scales, redshifts, and masses with large statistics. Their analysis should therefore enable us to probe the spatial distribution of clusters with high accuracy and derive tighter constraints on the cosmological parameters and the dark energy equation of state. However, for the majority of these surveys, redshifts of individual galaxies will be mostly estimated by multiband photometry which implies non-negligible errors in redshift resulting in potential difficulties in recovering the real-space clustering. Aims: We investigate to which accuracy it is possible to recover the real-space two-point correlation function of galaxy clusters from cluster catalogues based on photometric redshifts, and test our ability to detect and measure the redshift and mass evolution of the correlation length r0 and of the bias parameter b(M,z) as a function of the uncertainty on the cluster redshift estimate. Methods: We calculate the correlation function for cluster sub-samples covering various mass and redshift bins selected from a 500 deg2 light-cone limited to H < 24. In order to simulate the distribution of clusters in photometric redshift space, we assign to each cluster a redshift randomly extracted from a Gaussian distribution having a mean equal to the cluster cosmological redshift and a dispersion equal to σz. The dispersion is varied in the range σ(z=0)=\\frac{σz{1+z_c} = 0.005,0.010,0.030} and 0.050, in order to cover the typical values expected in forthcoming surveys. The correlation function in real-space is then computed through estimation and deprojection of wp(rp). Four mass ranges (from Mhalo > 2 × 1013h-1M⊙ to Mhalo > 2 × 1014h-1M⊙) and six redshift slices covering the redshift range [0, 2] are investigated, first using cosmological redshifts and then for the four photometric redshift configurations. Results: From the analysis of the light-cone in cosmological redshifts we find a clear increase of the correlation amplitude as a function of redshift and mass. The evolution of the derived bias parameter b(M,z) is in fair agreement with theoretical expectations. We calculate the r0-d relation up to our highest mass, highest redshift sample tested (z = 2,Mhalo > 2 × 1014h-1M⊙). From our pilot sample limited to Mhalo > 5 × 1013h-1M⊙(0.4 < z < 0.7), we find that the real-space correlation function can be recovered by deprojection of wp(rp) within an accuracy of 5% for σz = 0.001 × (1 + zc) and within 10% for σz = 0.03 × (1 + zc). For higher dispersions (besides σz > 0.05 × (1 + zc)), the recovery becomes noisy and difficult. The evolution of the correlation in redshift and mass is clearly detected for all σz tested, but requires a large binning in redshift to be detected significantly between individual redshift slices when increasing σz. The best-fit parameters (r0 and γ) as well as the bias obtained from the deprojection method for all σz are within the 1σ uncertainty of the zc sample.

Semisupervised Clustering by Iterative Partition and Regression with Neuroscience Applications

PubMed Central

Qian, Guoqi; Wu, Yuehua; Ferrari, Davide; Qiao, Puxue; Hollande, Frédéric

2016-01-01

Regression clustering is a mixture of unsupervised and supervised statistical learning and data mining method which is found in a wide range of applications including artificial intelligence and neuroscience. It performs unsupervised learning when it clusters the data according to their respective unobserved regression hyperplanes. The method also performs supervised learning when it fits regression hyperplanes to the corresponding data clusters. Applying regression clustering in practice requires means of determining the underlying number of clusters in the data, finding the cluster label of each data point, and estimating the regression coefficients of the model. In this paper, we review the estimation and selection issues in regression clustering with regard to the least squares and robust statistical methods. We also provide a model selection based technique to determine the number of regression clusters underlying the data. We further develop a computing procedure for regression clustering estimation and selection. Finally, simulation studies are presented for assessing the procedure, together with analyzing a real data set on RGB cell marking in neuroscience to illustrate and interpret the method. PMID:27212939

Morphology of size-selected Ptn clusters on CeO2(111)

NASA Astrophysics Data System (ADS)

Shahed, Syed Mohammad Fakruddin; Beniya, Atsushi; Hirata, Hirohito; Watanabe, Yoshihide

2018-03-01

Supported Pt catalysts and ceria are well known for their application in automotive exhaust catalysts. Size-selected Pt clusters supported on a CeO2(111) surface exhibit distinct physical and chemical properties. We investigated the morphology of the size-selected Ptn (n = 5-13) clusters on a CeO2(111) surface using scanning tunneling microscopy at room temperature. Ptn clusters prefer a two-dimensional morphology for n = 5 and a three-dimensional (3D) morphology for n ≥ 6. We further observed the preference for a 3D tri-layer structure when n ≥ 10. For each cluster size, we quantitatively estimated the relative fraction of the clusters for each type of morphology. Size-dependent morphology of the Ptn clusters on the CeO2(111) surface was attributed to the Pt-Pt interaction in the cluster and the Pt-O interaction between the cluster and CeO2(111) surface. The results obtained herein provide a clear understanding of the size-dependent morphology of the Ptn clusters on a CeO2(111) surface.

Morphology of size-selected Ptn clusters on CeO2(111).

PubMed

Shahed, Syed Mohammad Fakruddin; Beniya, Atsushi; Hirata, Hirohito; Watanabe, Yoshihide

2018-03-21

Supported Pt catalysts and ceria are well known for their application in automotive exhaust catalysts. Size-selected Pt clusters supported on a CeO 2 (111) surface exhibit distinct physical and chemical properties. We investigated the morphology of the size-selected Pt n (n = 5-13) clusters on a CeO 2 (111) surface using scanning tunneling microscopy at room temperature. Pt n clusters prefer a two-dimensional morphology for n = 5 and a three-dimensional (3D) morphology for n ≥ 6. We further observed the preference for a 3D tri-layer structure when n ≥ 10. For each cluster size, we quantitatively estimated the relative fraction of the clusters for each type of morphology. Size-dependent morphology of the Pt n clusters on the CeO 2 (111) surface was attributed to the Pt-Pt interaction in the cluster and the Pt-O interaction between the cluster and CeO 2 (111) surface. The results obtained herein provide a clear understanding of the size-dependent morphology of the Pt n clusters on a CeO 2 (111) surface.

Analytical network process based optimum cluster head selection in wireless sensor network.

PubMed

Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.

Analytical network process based optimum cluster head selection in wireless sensor network

PubMed Central

Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process. PMID:28719616

A tripartite clustering analysis on microRNA, gene and disease model.

PubMed

Shen, Chengcheng; Liu, Ying

2012-02-01

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

A WISE Selection of MIR AGN in Different Environments

NASA Astrophysics Data System (ADS)

Cheeseboro, Belinda D.; Norman, Dara J.

2015-01-01

This study was undertaken to understand the role of large scale environment in the evolution of MIR-selected AGN. In this study we examine AGN candidates in two types of environments: 7 clusters and 6 blank fields. Two types of clusters were studied in this project: 3 virialized and 4 non-virialized. The redshift of the clusters ranged 0.22≤z≤0.28. We used the mid-infrared WISE All-Sky database to identify AGN, applying various methods to refine our AGN candidate selection. To ascertain if there is an excess or deficit of MIR AGN in galaxy clusters vs. blank fields, we compared the AGN candidate distributions in virialized vs. non-virialized clusters to the blank fields. After close examination and comparison of the results to X-ray selected AGN from the Gilmour et al. (2009) study, we concluded that we do not detect an excess or deficit of MIR AGN in our clusters whether the cluster was virialized or non-virialized. This contrasted the conclusion of the Gilmour et al. (2009) study where there was an excess of X-Ray selected AGN in clusters.We also note an interesting feature in our WISE color-color plots that might be used for further investigation.Cheeseboro was supported by the NOAO/KPNO ResearchExperiences for Undergraduates (REU) Program which is funded by theNational Science Foundation Research Experiences for UndergraduatesProgram (AST-1262829).

Statistical analysis of ALFALFA galaxies: Insights in galaxy formation & near-field cosmology

NASA Astrophysics Data System (ADS)

Papastergis, Emmanouil

2013-03-01

The Arecibo Legacy Fast ALFA (ALFALFA) survey is a blind, extragalactic survey in the 21cm emission line of atomic hydrogen (HI). Presently, sources have been cataloged over ≈4,000 deg2 of sky (~60% of its final area), resulting in the largest HI-selected sample to date. We use the rich ALFALFA dataset to measure the statistical properties of HI-bearing galaxies, such as their mass distribution and clustering characteristics. These statistical distributions are determined by the properties of darkmatter on galactic scales, and by the complex baryonic processes through which galaxies form over cosmic time. As a result, detailed studies of these distributions can lead to important insights in galaxy formation & evolution and near-field cosmology. In particular, we measure the space density of HI-bearing galaxies as a function of the width of their HI profile (i.e. the velocity width function of galaxies), and find substantial disagreement with the distribution expected in a lambda cold dark matter (ΛCDM) universe. In particular, the number of galaxies with maximum rotational velocities upsilonrot ≈ 35 kms--1 (as judged by their HI velocity width) is about an order of magnitude lower than what predicted based on populating ΛCDM halos with modeled galaxies. We identify two possible solutions to the discrepancy: First, an alternative dark matter scenario in which the formation of low-mass halos is heavily suppressed (e.g. a warm dark matter universe with keV-scale dark matter particles). Secondly, we consider the possibility that rotational velocitites of dwarf galaxies derived from HI velocity widths may systematically underestimate the true mass of the host halo, due to the shape of their rotation curves. In this latter scenario, quantitative predictions for the internal kinematics of dwarf galaxies can be made, which can be checked in the future to probe the nature of dark matter. Furthermore, we take advantage of the overlap of ALFALFA with the Sloan Digital Sky Survey (SDSS), to measure the number density of galaxies as a function of their "baryonic" mass (stars + atomic gas). In the context of a ΛCDM cosmological model, the measured distribution reveals that low-mass halos are heavily "baryon depleted", i.e. their baryonic-to-dark mass ratio is much lower than the cosmological value. These baryon deficits are usually attributed to stellar feedback (e.g. supernova-driven gas outflows), but the efficiency implied by our measurement is extremely high. Whether such efficient feedback can be accommodated in a consistent picture of galaxy formation is an open question, and remains one of the principle scientific drivers for hydrodynamic simulations of galaxy formation. Lastly, we measure the clustering properties of HI-selected samples, through the two-point correlation function of ALFALFA galaxies. We find no compelling evidence for a dependence of clustering on HI mass, suggesting that the relationship between galactic gas mass and host halo mass is not tight. We furthermore find that HI galaxies cluster more weakly than optically selected ones, when no color selection is applied. However, SDSS galaxies with blue colors have very similar clustering characteristics with ALFALFA galaxies, both in real as well as in redshift space. On the other hand, HI galaxies cluster much more weakly than optical galaxies with red colors, and in fact "avoid" being located within ≈3 Mpc from the latter. By considering the clustering properties of ΛCDM halos, we confirm our previous intuition for an MHI-Mh relation with large scatter, and find that spin parameter may be a key halo property related to the gas content of present-day galaxies.

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

Sills, Alison; Glebbeek, Evert; Chatterjee, Sourav

We created artificial color-magnitude diagrams of Monte Carlo dynamical models of globular clusters and then used observational methods to determine the number of blue stragglers in those clusters. We compared these blue stragglers to various cluster properties, mimicking work that has been done for blue stragglers in Milky Way globular clusters to determine the dominant formation mechanism(s) of this unusual stellar population. We find that a mass-based prescription for selecting blue stragglers will select approximately twice as many blue stragglers than a selection criterion that was developed for observations of real clusters. However, the two numbers of blue stragglers aremore » well-correlated, so either selection criterion can be used to characterize the blue straggler population of a cluster. We confirm previous results that the simplified prescription for the evolution of a collision or merger product in the BSE code overestimates their lifetimes. We show that our model blue stragglers follow similar trends with cluster properties (core mass, binary fraction, total mass, collision rate) as the true Milky Way blue stragglers as long as we restrict ourselves to model clusters with an initial binary fraction higher than 5%. We also show that, in contrast to earlier work, the number of blue stragglers in the cluster core does have a weak dependence on the collisional parameter Γ in both our models and in Milky Way globular clusters.« less

The stabilization mechanism of titanium cluster

NASA Astrophysics Data System (ADS)

Sun, Houqian; Ren, Yun; Hao, Yuhua; Wu, Zhaofeng; Xu, Ning

2015-05-01

A systematic and comparative theoretical study on the stabilization mechanism of titanium cluster has been performed by selecting the clusters Tin (n=3, 4, 5, 7, 13, 15 and 19) as representatives in the framework of density-functional theory. For small clusters Tin (n=3, 4 and 5), the binding energy gain due to spin polarization is substantially larger than that due to structural distortion. For medium clusters Ti13 and Ti15, both have about the same contribution. For Tin (n=4, 5, 13 and 15), when the undistorted high symmetric structure with spin-polarization is changed into the lowest energy structure, the energy level spelling due to distortion fails to reverse the level order of occupied and unoccupied molecular orbital (MO) of two type spin states, the spin configuration remains unchanged. In spin restricted and undistorted high symmetric structure, d orbitals participate in the hybridization in MOs, usually by way of a less distorted manner, and weak bonds are formed. In contrast, d orbitals take part in the formation of MOs in the ground state structure, usually in a distorted manner, and strong covalent metallic bonds are formed.

The Atacama Cosmology Telescope (ACT): Beam Profiles and First SZ Cluster Maps

NASA Technical Reports Server (NTRS)

Hincks, A. D.; Acquaviva, V.; Ade, P. A.; Aguirre, P.; Amiri, M.; Appel, J. W.; Barrientos, L. F.; Battistelli, E. S.; Bond, J. R.; Brown, B.;

A clustering algorithm for sample data based on environmental pollution characteristics

NASA Astrophysics Data System (ADS)

Chen, Mei; Wang, Pengfei; Chen, Qiang; Wu, Jiadong; Chen, Xiaoyun

2015-04-01

Environmental pollution has become an issue of serious international concern in recent years. Among the receptor-oriented pollution models, CMB, PMF, UNMIX, and PCA are widely used as source apportionment models. To improve the accuracy of source apportionment and classify the sample data for these models, this study proposes an easy-to-use, high-dimensional EPC algorithm that not only organizes all of the sample data into different groups according to the similarities in pollution characteristics such as pollution sources and concentrations but also simultaneously detects outliers. The main clustering process consists of selecting the first unlabelled point as the cluster centre, then assigning each data point in the sample dataset to its most similar cluster centre according to both the user-defined threshold and the value of similarity function in each iteration, and finally modifying the clusters using a method similar to k-Means. The validity and accuracy of the algorithm are tested using both real and synthetic datasets, which makes the EPC algorithm practical and effective for appropriately classifying sample data for source apportionment models and helpful for better understanding and interpreting the sources of pollution.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Solubilization of a membrane protein by combinatorial supercharging.

PubMed

Hajduczki, Agnes; Majumdar, Sudipta; Fricke, Marie; Brown, Isola A M; Weiss, Gregory A

2011-04-15

Hydrophobic and aggregation-prone, membrane proteins often prove too insoluble for conventional in vitro biochemical studies. To engineer soluble variants of human caveolin-1, a phage-displayed library of caveolin variants targeted the hydrophobic intramembrane domain with substitutions to charged residues. Anti-selections for insolubility removed hydrophobic variants, and positive selections for binding to the known caveolin ligand HIV gp41 isolated functional, folded variants. Assays with several caveolin binding partners demonstrated the successful folding and functionality by a solubilized, full-length caveolin variant selected from the library. This caveolin variant allowed assay of the direct interaction between caveolin and cavin. Clustered along one face of a putative helix, the solubilizing mutations suggest a structural model for the intramembrane domain of caveolin. The approach provides a potentially general method for solubilization and engineering of membrane-associated proteins by phage display.

A survey for low-mass stellar and substellar members of the Hyades open cluster

NASA Astrophysics Data System (ADS)

Melnikov, Stanislav; Eislöffel, Jochen

2018-03-01

Context. Unlike young open clusters (with ages < 250 Myr), the Hyades cluster (age 600 Myr) has a clear deficit of very low-mass stars (VLM) and brown dwarfs (BD). Since this open cluster has a low stellar density and covers several tens of square degrees on the sky, extended surveys are required to improve the statistics of the VLM/BD objects in the cluster. Aim. We search for new VLM stars and BD candidates in the Hyades cluster to improve the present-day cluster mass function down to substellar masses. Methods: An imaging survey of the Hyades with a completeness limit of 21.m5 in the R band and 20.m5 in the I band was carried out with the 2k × 2k CCD Schmidt camera at the 2 m Alfred Jensch Telescope in Tautenburg. We performed a photometric selection of the cluster member candidates by combining results of our survey with 2MASS JHKs photometry Results: We present a photometric and proper motion survey covering 23.4 deg2 in the Hyades cluster core region. Using optical/IR colour-magnitude diagrams, we identify 66 photometric cluster member candidates in the magnitude range 14.m7 < I < 20.m5. The proper motion measurements are based on several all-sky surveys with an epoch difference of 60-70 yr for the bright objects. The proper motions allowed us to discriminate the cluster members from field objects and resulted in 14 proper motion members of the Hyades. We rediscover Hy 6 as a proper motion member and classify it as a substellar object candidate (BD) based on the comparison of the observed colour-magnitude diagram with theoretical model isochrones. Conclusions: With our results, the mass function of the Hyades continues to be shallow below 0.15 M⊙ indicating that the Hyades have probably lost their lowest mass members by means of dynamical evolution. We conclude that the Hyades core represents the "VLM/BD desert" and that most of the substeller objects may have already left the volume of the cluster.

SEARCHING FOR COOLING SIGNATURES IN STRONG LENSING GALAXY CLUSTERS: EVIDENCE AGAINST BARYONS SHAPING THE MATTER DISTRIBUTION IN CLUSTER CORES

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

Blanchard, Peter K.; Bayliss, Matthew B.; McDonald, Michael

2013-07-20

The process by which the mass density profile of certain galaxy clusters becomes centrally concentrated enough to produce high strong lensing (SL) cross-sections is not well understood. It has been suggested that the baryonic condensation of the intracluster medium (ICM) due to cooling may drag dark matter to the cores and thus steepen the profile. In this work, we search for evidence of ongoing ICM cooling in the first large, well-defined sample of SL selected galaxy clusters in the range 0.1 < z < 0.6. Based on known correlations between the ICM cooling rate and both optical emission line luminositymore » and star formation, we measure, for a sample of 89 SL clusters, the fraction of clusters that have [O II]{lambda}{lambda}3727 emission in their brightest cluster galaxy (BCG). We find that the fraction of line-emitting BCGs is constant as a function of redshift for z > 0.2 and shows no statistically significant deviation from the total cluster population. Specific star formation rates, as traced by the strength of the 4000 A break, D{sub 4000}, are also consistent with the general cluster population. Finally, we use optical imaging of the SL clusters to measure the angular separation, R{sub arc}, between the arc and the center of mass of each lensing cluster in our sample and test for evidence of changing [O II] emission and D{sub 4000} as a function of R{sub arc}, a proxy observable for SL cross-sections. D{sub 4000} is constant with all values of R{sub arc}, and the [O II] emission fractions show no dependence on R{sub arc} for R{sub arc} > 10'' and only very marginal evidence of increased weak [O II] emission for systems with R{sub arc} < 10''. These results argue against the ability of baryonic cooling associated with cool core activity in the cores of galaxy clusters to strongly modify the underlying dark matter potential, leading to an increase in SL cross-sections.« less

Laser ablation synthesis of arsenic-phosphide Asm Pn clusters from As-P mixtures. Laser desorption ionisation with quadrupole ion trap time-of-flight mass spectrometry: The mass spectrometer as a synthesizer.

PubMed

Kubáček, Pavel; Prokeš, Lubomír; Pamreddy, Annapurna; Peña-Méndez, Eladia María; Conde, José Elias; Alberti, Milan; Havel, Josef

2018-05-30

Only a few arsenic phosphides are known. A high potential for the generation of new compounds is offered by Laser Ablation Synthesis (LAS) and when Laser Desorption Ionization (LDI) is coupled with simultaneous Time-Of-Flight Mass Spectrometry (TOFMS), immediate identification of the clusters can be achieved. LAS was used for the generation of arsenic phosphides via laser ablation of phosphorus-arsenic mixtures while quadrupole ion trap time-of-flight mass spectrometry (QIT-TOFMS) was used to acquire the mass spectra. Many new As m P n ± clusters (479 binary and 369 mono-elemental) not yet described in the literature were generated in the gas phase and their stoichiometry determined. The likely structures for some of the observed clusters arbitrary selected (20) were computed by density functional theory (DFT) optimization. LAS is an advantageous approach for the generation of new As m P n clusters, while mass spectrometry was found to be an efficient technique for the determination of cluster stoichiometry. The results achieved might inspire the synthesis of new materials. Copyright © 2018 John Wiley & Sons, Ltd.

Continuous-variable quantum computing in optical time-frequency modes using quantum memories.

PubMed

Humphreys, Peter C; Kolthammer, W Steven; Nunn, Joshua; Barbieri, Marco; Datta, Animesh; Walmsley, Ian A

2014-09-26

We develop a scheme for time-frequency encoded continuous-variable cluster-state quantum computing using quantum memories. In particular, we propose a method to produce, manipulate, and measure two-dimensional cluster states in a single spatial mode by exploiting the intrinsic time-frequency selectivity of Raman quantum memories. Time-frequency encoding enables the scheme to be extremely compact, requiring a number of memories that are a linear function of only the number of different frequencies in which the computational state is encoded, independent of its temporal duration. We therefore show that quantum memories can be a powerful component for scalable photonic quantum information processing architectures.

Oxide dispersion strengthened ferritic steels: a basic research joint program in France

NASA Astrophysics Data System (ADS)

Boutard, J.-L.; Badjeck, V.; Barguet, L.; Barouh, C.; Bhattacharya, A.; Colignon, Y.; Hatzoglou, C.; Loyer-Prost, M.; Rouffié, A. L.; Sallez, N.; Salmon-Legagneur, H.; Schuler, T.

2014-12-01

AREVA, CEA, CNRS, EDF and Mécachrome are funding a joint program of basic research on Oxide Dispersion Strengthened Steels (ODISSEE), in support to the development of oxide dispersion strengthened 9-14% Cr ferritic-martensitic steels for the fuel element cladding of future Sodium-cooled fast neutron reactors. The selected objectives and the results obtained so far will be presented concerning (i) physical-chemical characterisation of the nano-clusters as a function of ball-milling process, metallurgical conditions and irradiation, (ii) meso-scale understanding of failure mechanisms under dynamic loading and creep, and, (iii) kinetic modelling of nano-clusters nucleation and α/α‧ unmixing.

Clustering of quasars in a wide luminosity range at redshift 4 with Subaru Hyper Suprime-Cam Wide-field imaging

NASA Astrophysics Data System (ADS)

He, Wanqiu; Akiyama, Masayuki; Bosch, James; Enoki, Motohiro; Harikane, Yuichi; Ikeda, Hiroyuki; Kashikawa, Nobunari; Kawaguchi, Toshihiro; Komiyama, Yutaka; Lee, Chien-Hsiu; Matsuoka, Yoshiki; Miyazaki, Satoshi; Nagao, Tohru; Nagashima, Masahiro; Niida, Mana; Nishizawa, Atsushi J.; Oguri, Masamune; Onoue, Masafusa; Oogi, Taira; Ouchi, Masami; Schulze, Andreas; Shirasaki, Yuji; Silverman, John D.; Tanaka, Manobu M.; Tanaka, Masayuki; Toba, Yoshiki; Uchiyama, Hisakazu; Yamashita, Takuji

2018-01-01

We examine the clustering of quasars over a wide luminosity range, by utilizing 901 quasars at \\overline{z}_phot˜ 3.8 with -24.73 < M1450 < -22.23 photometrically selected from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) S16A Wide2 date release and 342 more luminous quasars at 3.4 < zspec < 4.6 with -28.0 < M1450 < -23.95 from the Sloan Digital Sky Survey that fall in the HSC survey fields. We measure the bias factors of two quasar samples by evaluating the cross-correlation functions (CCFs) between the quasar samples and 25790 bright z ˜ 4 Lyman break galaxies in M1450 < -21.25 photometrically selected from the HSC dataset. Over an angular scale of 10.0" to 1000.0", the bias factors are 5.93+1.34-1.43 and 2.73+2.44-2.55 for the low- and high-luminosity quasars, respectively, indicating no significant luminosity dependence of quasar clustering at z ˜ 4. It is noted that the bias factor of the luminous quasars estimated by the CCF is smaller than that estimated by the auto-correlation function over a similar redshift range, especially on scales below 40.0". Moreover, the bias factor of the less-luminous quasars implies the minimal mass of their host dark matter halos is 0.3-2 × 1012 h-1 M⊙, corresponding to a quasar duty cycle of 0.001-0.06.

The cluster-cluster correlation function. [of galaxies

NASA Technical Reports Server (NTRS)

Postman, M.; Geller, M. J.; Huchra, J. P.

1986-01-01

The clustering properties of the Abell and Zwicky cluster catalogs are studied using the two-point angular and spatial correlation functions. The catalogs are divided into eight subsamples to determine the dependence of the correlation function on distance, richness, and the method of cluster identification. It is found that the Corona Borealis supercluster contributes significant power to the spatial correlation function to the Abell cluster sample with distance class of four or less. The distance-limited catalog of 152 Abell clusters, which is not greatly affected by a single system, has a spatial correlation function consistent with the power law Xi(r) = 300r exp -1.8. In both the distance class four or less and distance-limited samples the signal in the spatial correlation function is a power law detectable out to 60/h Mpc. The amplitude of Xi(r) for clusters of richness class two is about three times that for richness class one clusters. The two-point spatial correlation function is sensitive to the use of estimated redshifts.

The Role of Large-Scale Structure and Assembly in the Quenching of Star Formation in Cluster Galaxies at z 0.2

NASA Astrophysics Data System (ADS)

Moran, Sean; Smith, G.; Haines, C.; Egami, E.; Hardegree-Ullman, E.; Heckman, T.

2010-01-01

We present results from LoCuSS, the Local Cluster Substructure Survey, on the distribution and abundance of cluster galaxies showing signatures of recently quenched star formation, within a sample of 15 z 0.2 clusters. Combining LoCuSS' wide-field UV through NIR photometry with weak-lensing derived mass maps for these clusters, we identify passive galaxies that have undergone recent quenching via both rapid (100Myr) and slow (1Gyr) mechanisms. By studying their abundance in a statistically significant sample of z 0.2 clusters, we explore how the effectiveness of environmental quenching of star formation varies as a function of the level of cluster substructure, in addition to global cluster characteristics such as mass or X-ray luminosity and temperature, with the aim of understanding the role that pre-processing of galaxies within groups and filaments plays in the overall buildup of the morphology-density and SFR-density relations. We find that clusters with large levels of substructure indicative of recent assembly or cluster-cluster mergers host a higher fraction of galaxies with signs of recent ram-pressure stripping by the hot intra-cluster gas. In addition, we find that the fraction of post-starburst galaxies increases with cluster mass (M500), but fractions of optically-selected AGN and GALEX-defined "Green Valley" galaxies show the opposite trend, being most abundant in rather low-mass clusters. These trends suggest a picture where quenching of star formation occurs most vigorously in actively assembling structures, with comparatively little activity in the most massive structures where most of the nearby large-scale structure has already been accreted and Virialized into the main cluster body.

Influence of gravity on inertial particle clustering in turbulence

NASA Astrophysics Data System (ADS)

Lu, J.; Nordsiek, H.; Saw, E. W.; Fugal, J. P.; Shaw, R. A.

2008-11-01

We report results from experiments aimed at studying inertial particles in homogeneous, isotropic turbulence, under the influence of gravitational settling. Conditions are selected to investigate the transition from negligible role of gravity to gravitationally dominated, as is expected to occur in atmospheric clouds. We measure droplet clustering, relative velocities, and the distribution of collision angles in this range. The experiments are carried out in a laboratory chamber with nearly homogeneous, isotropic turbulence. The turbulence is characterized using LDV and 2-frame holographic particle tracking velocimetry. We seed the flow with particles of various Stokes and Froude numbers and use digital holography to obtain 3D particle positions and velocities. From particle positions, we investigate the impact of gravity on inertial clustering through the calculation of the radial distribution function and we compare to computational results and other recent experiments.

Clustering of disulfide-rich peptides provides scaffolds for hit discovery by phage display: application to interleukin-23.

PubMed

Barkan, David T; Cheng, Xiao-Li; Celino, Herodion; Tran, Tran T; Bhandari, Ashok; Craik, Charles S; Sali, Andrej; Smythe, Mark L

2016-11-23

Disulfide-rich peptides (DRPs) are found throughout nature. They are suitable scaffolds for drug development due to their small cores, whose disulfide bonds impart extraordinary chemical and biological stability. A challenge in developing a DRP therapeutic is to engineer binding to a specific target. This challenge can be overcome by (i) sampling the large sequence space of a given scaffold through a phage display library and by (ii) panning multiple libraries encoding structurally distinct scaffolds. Here, we implement a protocol for defining these diverse scaffolds, based on clustering structurally defined DRPs according to their conformational similarity. We developed and applied a hierarchical clustering protocol based on DRP structural similarity, followed by two post-processing steps, to classify 806 unique DRP structures into 81 clusters. The 20 most populated clusters comprised 85% of all DRPs. Representative scaffolds were selected from each of these clusters; the representatives were structurally distinct from one another, but similar to other DRPs in their respective clusters. To demonstrate the utility of the clusters, phage libraries were constructed for three of the representative scaffolds and panned against interleukin-23. One library produced a peptide that bound to this target with an IC 50 of 3.3 μM. Most DRP clusters contained members that were diverse in sequence, host organism, and interacting proteins, indicating that cluster members were functionally diverse despite having similar structure. Only 20 peptide scaffolds accounted for most of the natural DRP structural diversity, providing suitable starting points for seeding phage display experiments. Through selection of the scaffold surface to vary in phage display, libraries can be designed that present sequence diversity in architecturally distinct, biologically relevant combinations of secondary structures. We supported this hypothesis with a proof-of-concept experiment in which three phage libraries were constructed and panned against the IL-23 target, resulting in a single-digit μM hit and suggesting that a collection of libraries based on the full set of 20 scaffolds increases the potential to identify efficiently peptide binders to a protein target in a drug discovery program.

Genome-wide evidence for divergent selection between populations of a major agricultural pathogen.

PubMed

Hartmann, Fanny E; McDonald, Bruce A; Croll, Daniel

2018-06-01

The genetic and environmental homogeneity in agricultural ecosystems is thought to impose strong and uniform selection pressures. However, the impact of this selection on plant pathogen genomes remains largely unknown. We aimed to identify the proportion of the genome and the specific gene functions under positive selection in populations of the fungal wheat pathogen Zymoseptoria tritici. First, we performed genome scans in four field populations that were sampled from different continents and on distinct wheat cultivars to test which genomic regions are under recent selection. Based on extended haplotype homozygosity and composite likelihood ratio tests, we identified 384 and 81 selective sweeps affecting 4% and 0.5% of the 35 Mb core genome, respectively. We found differences both in the number and the position of selective sweeps across the genome between populations. Using a XtX-based outlier detection approach, we identified 51 extremely divergent genomic regions between the allopatric populations, suggesting that divergent selection led to locally adapted pathogen populations. We performed an outlier detection analysis between two sympatric populations infecting two different wheat cultivars to identify evidence for host-driven selection. Selective sweep regions harboured genes that are likely to play a role in successfully establishing host infections. We also identified secondary metabolite gene clusters and an enrichment in genes encoding transporter and protein localization functions. The latter gene functions mediate responses to environmental stress, including interactions with the host. The distinct gene functions under selection indicate that both local host genotypes and abiotic factors contributed to local adaptation. © 2018 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

Influence of Cr doping on the stability and structure of small cobalt oxide clusters.

PubMed

Tung, Nguyen Thanh; Tam, Nguyen Minh; Nguyen, Minh Tho; Lievens, Peter; Janssens, Ewald

2014-07-28

The stability of mass-selected pure cobalt oxide and chromium doped cobalt oxide cluster cations, ConO+m and Con-1CrO+m (n = 2, 3; m = 2-6 and n = 4; m = 3-8), has been investigated using photodissociation mass spectrometry. Oxygen-rich ConO+m clusters (m ≥ n + 1 for n = 2, 4 and m ≥ n + 2 for n = 3) prefer to photodissociate via the loss of an oxygen molecule, whereas oxygen poorer clusters favor the evaporation of oxygen atoms. Substituting a single Co atom by a single Cr atom alters the dissociation behavior. All investigated Con-1 CrO+m clusters, except CoCrO+2 and CoCrO+3, prefer to decay by eliminating a neutral oxygen molecule. Co2O+2, Co4O+3, Co4O+4, and CoCrO+2 are found to be relatively difficult to dissociate and appear as fragmentation product of several larger clusters, suggesting that they are particularly stable. The geometric structures of pure and Cr doped cobalt oxide species are studied using density functional theory calculations. Dissociation energies for different evaporation channels are calculated and compared with the experimental observations. The influence of the dopant atom on the structure and the stability of the clusters is discussed.

Engineering Redox Potential of Lithium Clusters for Electrode Material in Lithium-Ion Batteries

DOE PAGES

Kushwaha, Anoop Kumar; Sahoo, Mihir Ranjan; Nanda, Jagjit; ...

2017-07-01

Low negative electrode potential and high reactivity makes lithium (Li) ideal candidate for obtaining highest possible energy density among other materials. Here, we show a novel route with which the overall electrode potential could significantly be enhanced through selection of cluster size. In using first principles density functional theory and continuum dielectric model, we studied free energy and redox potential as well as investigated relative stability of Li n (n ≤ 8) clusters in both gas phase and solution. We found that Li 3 has the lowest negative redox potential (thereby highest overall electrode potential) suggesting that cluster based approachmore » could provide a novel way of engineering the next generation battery technology. The microscopic origin of Li 3 cluster’s superior performance is related to two major factors: gas phase ionization and difference between solvation free energy for neutral and positive ion. Taken together, our study provides insight into the engineering of redox potential in battery and could stimulate further work in this direction.« less

Engineering Redox Potential of Lithium Clusters for Electrode Material in Lithium-Ion Batteries

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

Kushwaha, Anoop Kumar; Sahoo, Mihir Ranjan; Nanda, Jagjit

Low negative electrode potential and high reactivity makes lithium (Li) ideal candidate for obtaining highest possible energy density among other materials. Here, we show a novel route with which the overall electrode potential could significantly be enhanced through selection of cluster size. In using first principles density functional theory and continuum dielectric model, we studied free energy and redox potential as well as investigated relative stability of Li n (n ≤ 8) clusters in both gas phase and solution. We found that Li 3 has the lowest negative redox potential (thereby highest overall electrode potential) suggesting that cluster based approachmore » could provide a novel way of engineering the next generation battery technology. The microscopic origin of Li 3 cluster’s superior performance is related to two major factors: gas phase ionization and difference between solvation free energy for neutral and positive ion. Taken together, our study provides insight into the engineering of redox potential in battery and could stimulate further work in this direction.« less

ON THE CLUSTERING OF SUBMILLIMETER GALAXIES

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

Williams, Christina C.; Giavalisco, Mauro; Yun, Min S.

2011-06-01

We measure the angular two-point correlation function of submillimeter galaxies (SMGs) from 1.1 mm imaging of the COSMOS field with the AzTEC camera and ASTE 10 m telescope. These data yield one of the largest contiguous samples of SMGs to date, covering an area of 0.72 deg{sup 2} down to a 1.26 mJy beam{sup -1} (1{sigma}) limit, including 189 (328) sources with S/N {>=}3.5 (3). We can only set upper limits to the correlation length r{sub 0}, modeling the correlation function as a power law with pre-assigned slope. Assuming existing redshift distributions, we derive 68.3% confidence level upper limits ofmore » r{sub 0} {approx}< 6-8h{sup -1} Mpc at 3.7 mJy and r{sub 0} {approx}< 11-12 h{sup -1} Mpc at 4.2 mJy. Although consistent with most previous estimates, these upper limits imply that the real r{sub 0} is likely smaller. This casts doubts on the robustness of claims that SMGs are characterized by significantly stronger spatial clustering (and thus larger mass) than differently selected galaxies at high redshift. Using Monte Carlo simulations we show that even strongly clustered distributions of galaxies can appear unclustered when sampled with limited sensitivity and coarse angular resolution common to current submillimeter surveys. The simulations, however, also show that unclustered distributions can appear strongly clustered under these circumstances. From the simulations, we predict that at our survey depth, a mapped area of 2 deg{sup 2} is needed to reconstruct the correlation function, assuming smaller beam sizes of future surveys (e.g., the Large Millimeter Telescope's 6'' beam size). At present, robust measures of the clustering strength of bright SMGs appear to be below the reach of most observations.« less

Behavioral and anatomical consequences of early versus late symbol training in macaques.

PubMed

Srihasam, Krishna; Mandeville, Joseph B; Morocz, Istvan A; Sullivan, Kevin J; Livingstone, Margaret S

2012-02-09

Distinct brain regions, reproducible from one person to the next, are specialized for processing different kinds of human expertise, such as face recognition and reading. Here, we explore the relationship between age of learning, learning ability, and specialized brain structures. Specifically, we ask whether the existence of reproducible cortical domains necessarily means that certain abilities are innate, or innately easily learned, or whether reproducible domains can be formed, or refined, by interactions between genetic programs and common early experience. Functional MRI showed that intensive early, but not late, experience caused the formation of category-selective regions in macaque temporal lobe for stimuli never naturally encountered by monkeys. And behaviorally, early training produced more fluent processing of these stimuli than the same training in adults. One explanation for these results is that in higher cortical areas, as in early sensory areas, experience drives functional clustering and functional clustering determines how that information is processed. Copyright © 2012 Elsevier Inc. All rights reserved.

Refining a complex diagnostic construct: subtyping Dysthymia with the Shedler-Westen Assessment Procedure-II.

PubMed

Huprich, Steven K; Defife, Jared; Westen, Drew

2014-01-01

We sought to determine whether meaningful subtypes of Dysthymic patients could be identified when grouping them by similar personality profiles. A random, national sample of psychiatrists and clinical psychologists (n=1201) described a randomly selected current patient with personality pathology using the descriptors in the Shedler-Westen Assessment Procedure-II (SWAP-II), completed assessments of patients' adaptive functioning, and provided DSM-IV Axis I and II diagnoses. We applied Q-factor cluster analyses to those patients diagnosed with Dysthymic Disorder. Four clusters were identified-High Functioning, Anxious/Dysphoric, Emotionally Dysregulated, and Narcissistic. These factor scores corresponded with a priori hypotheses regarding diagnostic comorbidity and level of adaptive functioning. We compared these groups to diagnostic constructs described and empirically identified in the past literature. The results converge with past and current ideas about the ways in which chronic depression and personality are related and offer an enhanced means by which to understand a heterogeneous diagnostic category that is empirically grounded and clinically useful. © 2013 Published by Elsevier B.V.

Combining Mixture Components for Clustering*

PubMed Central

Baudry, Jean-Patrick; Raftery, Adrian E.; Celeux, Gilles; Lo, Kenneth; Gottardo, Raphaël

2010-01-01

Model-based clustering consists of fitting a mixture model to data and identifying each cluster with one of its components. Multivariate normal distributions are typically used. The number of clusters is usually determined from the data, often using BIC. In practice, however, individual clusters can be poorly fitted by Gaussian distributions, and in that case model-based clustering tends to represent one non-Gaussian cluster by a mixture of two or more Gaussian distributions. If the number of mixture components is interpreted as the number of clusters, this can lead to overestimation of the number of clusters. This is because BIC selects the number of mixture components needed to provide a good approximation to the density, rather than the number of clusters as such. We propose first selecting the total number of Gaussian mixture components, K, using BIC and then combining them hierarchically according to an entropy criterion. This yields a unique soft clustering for each number of clusters less than or equal to K. These clusterings can be compared on substantive grounds, and we also describe an automatic way of selecting the number of clusters via a piecewise linear regression fit to the rescaled entropy plot. We illustrate the method with simulated data and a flow cytometry dataset. Supplemental Materials are available on the journal Web site and described at the end of the paper. PMID:20953302

A Variable-Selection Heuristic for K-Means Clustering.

ERIC Educational Resources Information Center

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Intra-cluster Globular Clusters in a Simulated Galaxy Cluster

NASA Astrophysics Data System (ADS)

Ramos-Almendares, Felipe; Abadi, Mario; Muriel, Hernán; Coenda, Valeria

2018-01-01

Using a cosmological dark matter simulation of a galaxy-cluster halo, we follow the temporal evolution of its globular cluster population. To mimic the red and blue globular cluster populations, we select at high redshift (z∼ 1) two sets of particles from individual galactic halos constrained by the fact that, at redshift z = 0, they have density profiles similar to observed ones. At redshift z = 0, approximately 60% of our selected globular clusters were removed from their original halos building up the intra-cluster globular cluster population, while the remaining 40% are still gravitationally bound to their original galactic halos. As the blue population is more extended than the red one, the intra-cluster globular cluster population is dominated by blue globular clusters, with a relative fraction that grows from 60% at redshift z = 0 up to 83% for redshift z∼ 2. In agreement with observational results for the Virgo galaxy cluster, the blue intra-cluster globular cluster population is more spatially extended than the red one, pointing to a tidally disrupted origin.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Bridging Zirconia Nodes within a Metal–Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires

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

Platero-Prats, Ana E.; League, Aaron B.; Bernales, Varinia

Metal-organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. Notably, atomic layer deposition (ALD) in MOFs has recently emerged as a versatile approach to functionalize MOF surfaces with a wide variety of catalytic metal-oxo species. Understanding the structure of newly deposited species and how they are tethered within the MOF is critical to understanding how these components couple to govern the active material properties. By combining local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis and differencemore » envelope density analysis, with electron microscopy imag-ing and computational modeling, we resolve the precise atomic structure of metal-oxo species deposited in the MOF NU-1000 through ALD. These analyses demonstrate that deposition of NiO xH y clusters occurs selectively within the smallest pores of NU-1000, between the zirconia nodes, serving to connect these nodes along the c-direction to yield hetero-bimetallic metal-oxo nanowires. Finally, this bridging motif perturbs the NU-1000 framework structure, drawing the zirconia nodes closer together, and also underlies the sintering-resistance of these clusters during the hydrogenation of light olefins.« less

Bridging Zirconia Nodes within a Metal-Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires.

PubMed

Platero-Prats, Ana E; League, Aaron B; Bernales, Varinia; Ye, Jingyun; Gallington, Leighanne C; Vjunov, Aleksei; Schweitzer, Neil M; Li, Zhanyong; Zheng, Jian; Mehdi, B Layla; Stevens, Andrew J; Dohnalkova, Alice; Balasubramanian, Mahalingam; Farha, Omar K; Hupp, Joseph T; Browning, Nigel D; Fulton, John L; Camaioni, Donald M; Lercher, Johannes A; Truhlar, Donald G; Gagliardi, Laura; Cramer, Christopher J; Chapman, Karena W

2017-08-02

Metal-organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. Notably, atomic layer deposition (ALD) in MOFs has recently emerged as a versatile approach to functionalize MOF surfaces with a wide variety of catalytic metal-oxo species. Understanding the structure of newly deposited species and how they are tethered within the MOF is critical to understanding how these components couple to govern the active material properties. By combining local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis, and difference envelope density analysis, with electron microscopy imaging and computational modeling, we resolve the precise atomic structure of metal-oxo species deposited in the MOF NU-1000 through ALD. These analyses demonstrate that deposition of NiO x H y clusters occurs selectively within the smallest pores of NU-1000, between the zirconia nodes, serving to connect these nodes along the c-direction to yield heterobimetallic metal-oxo nanowires. This bridging motif perturbs the NU-1000 framework structure, drawing the zirconia nodes closer together, and also underlies the sintering resistance of these clusters during the hydrogenation of light olefins.

High-redshift Luminous Red Galaxies clustering analysis in SDSS Stripe82

NASA Astrophysics Data System (ADS)

Nikoloudakis, N.

2012-01-01

We have measured the clustering of Luminous Red Galaxies in Stripe 82 using the angular correlation function. We have selected 130000 LRGs via colour cuts in R-I:I-K with the K band data coming from UKIDSS LAS. We have used the cross-correlation technique of Newman (2008) to establish the redshift distribution of the LRGs as a function of colour cut, cross-correlating the LRGs with SDSS QSOs, DEEP2 and VVDS galaxies. We also used the AUS LRG redshift survey to establish the n(z) at z<1. We then compare the w(theta) results to the results of Sawangwit et al (2010) from 3 samples of SDSS LRGs at lower redshift to measure the dependence of clustering on redshift and LRG luminosity. We have compared the results for luminosity-matched LRG samples with simple evolutionary models, such as those expected from long-lived, passive models for LRGs and for the HOD models of Wake et al (2009) and find that the long-lived model may be a poorer fit than at lower redshifts. We find some evidence for evolution in the LRG correlation function slope in that the 2-halo term appears to flatten in slope at z>1. We present arguments that this is not caused by systematics.

Bridging Zirconia Nodes within a Metal–Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires

DOE PAGES

Platero-Prats, Ana E.; League, Aaron B.; Bernales, Varinia; ...

2017-07-11

Metal-organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. Notably, atomic layer deposition (ALD) in MOFs has recently emerged as a versatile approach to functionalize MOF surfaces with a wide variety of catalytic metal-oxo species. Understanding the structure of newly deposited species and how they are tethered within the MOF is critical to understanding how these components couple to govern the active material properties. By combining local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis and differencemore » envelope density analysis, with electron microscopy imag-ing and computational modeling, we resolve the precise atomic structure of metal-oxo species deposited in the MOF NU-1000 through ALD. These analyses demonstrate that deposition of NiO xH y clusters occurs selectively within the smallest pores of NU-1000, between the zirconia nodes, serving to connect these nodes along the c-direction to yield hetero-bimetallic metal-oxo nanowires. Finally, this bridging motif perturbs the NU-1000 framework structure, drawing the zirconia nodes closer together, and also underlies the sintering-resistance of these clusters during the hydrogenation of light olefins.« less

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.

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.

Temporal Clustering of Regional-Scale Extreme Precipitation Events in Southern Switzerland

NASA Astrophysics Data System (ADS)

Barton, Yannick; Giannakaki, Paraskevi; Von Waldow, Harald; Chevalier, Clément; Pfhal, Stephan; Martius, Olivia

2017-04-01

Temporal clustering of extreme precipitation events on subseasonal time scales is a form of compound extremes and is of crucial importance for the formation of large-scale flood events. Here, the temporal clustering of regional-scale extreme precipitation events in southern Switzerland is studied. These precipitation events are relevant for the flooding of lakes in southern Switzerland and northern Italy. This research determines whether temporal clustering is present and then identifies the dynamics that are responsible for the clustering. An observation-based gridded precipitation dataset of Swiss daily rainfall sums and ECMWF reanalysis datasets are used. To analyze the clustering in the precipitation time series a modified version of Ripley's K function is used. It determines the average number of extreme events in a time period, to characterize temporal clustering on subseasonal time scales and to determine the statistical significance of the clustering. Significant clustering of regional-scale precipitation extremes is found on subseasonal time scales during the fall season. Four high-impact clustering episodes are then selected and the dynamics responsible for the clustering are examined. During the four clustering episodes, all heavy precipitation events were associated with an upperlevel breaking Rossby wave over western Europe and in most cases strong diabatic processes upstream over the Atlantic played a role in the amplification of these breaking waves. Atmospheric blocking downstream over eastern Europe supported this wave breaking during two of the clustering episodes. During one of the clustering periods, several extratropical transitions of tropical cyclones in the Atlantic contributed to the formation of high-amplitude ridges over the Atlantic basin and downstream wave breaking. During another event, blocking over Alaska assisted the phase locking of the Rossby waves downstream over the Atlantic.

The x-ray luminous galaxy cluster population at 0.9 < z ≲ 1.6 as revealed by the XMM-Newton Distant Cluster Project

NASA Astrophysics Data System (ADS)

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

2011-12-01

We present the largest sample to date of spectroscopically confirmed x-ray luminous high-redshift galaxy clusters comprising 22 systems in the range 0.9 as part of the XMM-Newton Distant Cluster Project (XDCP). All systems were initially selected as extended x-ray sources over 76.1 deg2 of non-contiguous deep archival XMM-Newton coverage, of which 49.4 deg2 are part of the core survey with a quantifiable selection function and 17.7 deg2 are classified as ‘gold’ coverage as the starting point for upcoming cosmological applications. Distant cluster candidates were followed up with moderately deep optical and near-infrared imaging in at least two bands to photometrically identify the cluster galaxy populations and obtain redshift estimates based on the colors of simple stellar population models. We test and calibrate the most promising redshift estimation techniques based on the R-z and z-H colors for efficient distant cluster identifications and find a good redshift accuracy performance of the z-H color out to at least z ˜ 1.5, while the redshift evolution of the R-z color leads to increasingly large uncertainties at z ≳ 0.9. Photometrically identified high-z systems are spectroscopically confirmed with VLT/FORS 2 with a minimum of three concordant cluster member redshifts. We present first details of two newly identified clusters, XDCP J0338.5+0029 at z = 0.916 and XDCP J0027.2+1714 at z = 0.959, and investigate the x-ray properties of SpARCS J003550-431224 at z = 1.335, which shows evidence for ongoing major merger activity along the line-of-sight. We provide x-ray properties and luminosity-based total mass estimates for the full sample of 22 high-z clusters, of which 17 are at z ⩾ 1.0 and seven populate the highest redshift bin at z > 1.3. The median system mass of the sample is M200 ≃ 2 × 1014 M⊙, while the probed mass range for the distant clusters spans approximately (0.7-7) × 1014 M⊙. The majority (>70%) of the x-ray selected clusters show rather regular x-ray morphologies, albeit in most cases with a discernible elongation along one axis. In contrast to local clusters, the z > 0.9 systems mostly do not harbor central dominant galaxies coincident with the x-ray centroid position, but rather exhibit significant brightest cluster galaxy (BCG) offsets from the x-ray center with a median value of about 50 kpc in projection and a smaller median luminosity gap to the second-ranked galaxy of Δm12 ≃ 0.3 mag. We estimate a fraction of cluster-associated NVSS 1.4 GHz radio sources of about 30%, preferentially located within 1‧ from the x-ray center. This value suggests an increase of the fraction of very luminous cluster-associated radio sources by about a factor of 2.5-5 relative to low-z systems. The galaxy populations in z ≳ 1.5 cluster environments show first evidence for drastic changes on the high-mass end of galaxies and signs of a gradual disappearance of a well-defined cluster red-sequence as strong star formation activity is observed in an increasing fraction of massive galaxies down to the densest core regions. The presented XDCP high-z sample will allow first detailed studies of the cluster population during the critical cosmic epoch at lookback times of 7.3-9.5 Gyr on the aggregation and evolution of baryons in the cold and hot phases as a function of redshift and system mass. Based on observations under program IDs 079.A-0634 and 085.A-0647 collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile, and 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).

MASGOMAS PROJECT, New automatic-tool for cluster search on IR photometric surveys

NASA Astrophysics Data System (ADS)

Rübke, K.; Herrero, A.; Borissova, J.; Ramirez-Alegria, S.; García, M.; Marin-Franch, A.

2015-05-01

The Milky Way is expected to contain a large number of young massive (few x 1000 solar masses) stellar clusters, borne in dense cores of gas and dust. Yet, their known number remains small. We have started a programme to search for such clusters, MASGOMAS (MAssive Stars in Galactic Obscured MAssive clusterS). Initially, we selected promising candidates by means of visual inspection of infrared images. In a second phase of the project we have presented a semi-automatic method to search for obscured massive clusters that resulted in the identification of new massive clusters, like MASGOMAS-1 (with more than 10,000 solar masses) and MASGOMAS-4 (a double-cored association of about 3,000 solar masses). We have now developped a new automatic tool for MASGOMAS that allows the identification of a large number of massive cluster candidates from the 2MASS and VVV catalogues. Cluster candidates fulfilling criteria appropriated for massive OB stars are thus selected in an efficient and objective way. We present the results from this tool and the observations of the first selected cluster, and discuss the implications for the Milky Way structure.

X-Ray Morphological Analysis of the Planck ESZ Clusters

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

X-Ray Morphological Analysis of the Planck ESZ Clusters

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

Lovisari, Lorenzo; Forman, William R.; Jones, Christine

2017-09-01

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

A model of autophagy size selectivity by receptor clustering on peroxisomes

NASA Astrophysics Data System (ADS)

Brown, Aidan I.; Rutenberg, Andrew D.

2017-05-01

Selective autophagy must not only select the correct type of organelle, but also must discriminate between individual organelles of the same kind so that some but not all of the organelles are removed. We propose that physical clustering of autophagy receptor proteins on the organelle surface can provide an appropriate all-or-none signal for organelle degradation. We explore this proposal using a computational model restricted to peroxisomes and the relatively well characterized pexophagy receptor proteins NBR1 and p62. We find that larger peroxisomes nucleate NBR1 clusters first and lose them last through competitive coarsening. This results in significant size-selectivity that favors large peroxisomes, and can explain the increased catalase signal that results from siRNA inhibition of p62. Excess ubiquitin, resulting from damaged organelles, suppresses size-selectivity but not cluster formation. Our proposed selectivity mechanism thus allows all damaged organelles to be degraded, while otherwise selecting only a portion of organelles for degradation.

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

Model selection for semiparametric marginal mean regression accounting for within-cluster subsampling variability and informative cluster size.

PubMed

Shen, Chung-Wei; Chen, Yi-Hau

2018-03-13

We propose a model selection criterion for semiparametric marginal mean regression based on generalized estimating equations. The work is motivated by a longitudinal study on the physical frailty outcome in the elderly, where the cluster size, that is, the number of the observed outcomes in each subject, is "informative" in the sense that it is related to the frailty outcome itself. The new proposal, called Resampling Cluster Information Criterion (RCIC), is based on the resampling idea utilized in the within-cluster resampling method (Hoffman, Sen, and Weinberg, 2001, Biometrika 88, 1121-1134) and accommodates informative cluster size. The implementation of RCIC, however, is free of performing actual resampling of the data and hence is computationally convenient. Compared with the existing model selection methods for marginal mean regression, the RCIC method incorporates an additional component accounting for variability of the model over within-cluster subsampling, and leads to remarkable improvements in selecting the correct model, regardless of whether the cluster size is informative or not. Applying the RCIC method to the longitudinal frailty study, we identify being female, old age, low income and life satisfaction, and chronic health conditions as significant risk factors for physical frailty in the elderly. © 2018, The International Biometric Society.

Charge Retention by Monodisperse Gold Clusters on Surfaces Prepared Using Soft Landing of Mass Selected Ions

NASA Astrophysics Data System (ADS)

Johnson, Grant; Priest, Thomas; Laskin, Julia

2012-02-01

Monodisperse gold clusters have been prepared on surfaces in different charge states through soft landing of mass-selected ions. Gold clusters were synthesized in methanol solution by reduction of a gold precursor with a weak reducing agent in the presence of a diphosphine capping ligand. Electrospray ionization was used to introduce the clusters into the gas-phase and mass-selection was employed to isolate a single ionic cluster species which was delivered to surfaces at well controlled kinetic energies. Using in-situ time of flight secondary ion mass spectrometry (SIMS) it is demonstrated that the cluster retains its 3+ charge state when soft landed onto the surface of a fluorinated self assembled monolayer on gold. In contrast, when deposited onto carboxylic acid terminated and conventional alkyl thiol surfaces on gold the clusters exhibit larger relative abundances of the 2+ and 1+ charge states, respectively. The kinetics of charge reduction on the surface have been investigated using in-situ Fourier Transform Ion Cyclotron Resonance SIMS. It is shown that an extremely slow interfacial charge reduction occurs on the fluorinated monolayer surface while an almost instantaneous neutralization takes place on the surface of the alkyl thiol monolayer. Our results demonstrate that the size and charge state of small gold clusters on surfaces, both of which exert a dramatic influence on their chemical and physical properties, may be tuned through soft landing of mass-selected ions onto selected substrates.

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

PubMed

Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

Finding optimal inputs for a multiple-input, single-output system is taxing for a system operator. Population-based optimization is used to create sets of functions that produce a locally optimal input based on a desired output. An operator or higher level planner could use one of the functions in real time. For the optimization, each agent in the population uses the cost and output gradients to take steps lowering the cost while maintaining their current output. When an agent reaches an optimal input for its current output, additional agents are generated in the output gradient directions. The new agents then settle to the local optima for the new output values. The set of associated optimal points forms an inverse function, via spline interpolation, from a desired output to an optimal input. In this manner, multiple locally optimal functions can be created. These functions are naturally clustered in input and output spaces allowing for a continuous inverse function. The operator selects the best cluster over the anticipated range of desired outputs and adjusts the set point (desired output) while maintaining optimality. This reduces the demand from controlling multiple inputs, to controlling a single set point with no loss in performance. Results are demonstrated on a sample set of functions and on a robot control problem.

The Evolution of Globular Cluster Systems In Early-Type Galaxies

NASA Astrophysics Data System (ADS)

Grillmair, Carl

1999-07-01

We will measure structural parameters {core radii and concentrations} of globular clusters in three early-type galaxies using deep, four-point dithered observations. We have chosen globular cluster systems which have young, medium-age and old cluster populations, as indicated by cluster colors and luminosities. Our primary goal is to test the hypothesis that globular cluster luminosity functions evolve towards a ``universal'' form. Previous observations have shown that young cluster systems have exponential luminosity functions rather than the characteristic log-normal luminosity function of old cluster systems. We will test to see whether such young system exhibits a wider range of structural parameters than an old systems, and whether and at what rate plausible disruption mechanisms will cause the luminosity function to evolve towards a log-normal form. A simple observational comparison of structural parameters between different age cluster populations and between diff er ent sub-populations within the same galaxy will also provide clues concerning both the formation and destruction mechanisms of star clusters, the distinction between open and globular clusters, and the advisability of using globular cluster luminosity functions as distance indicators.

Identification of atypical flight patterns

NASA Technical Reports Server (NTRS)

Statler, Irving C. (Inventor); Ferryman, Thomas A. (Inventor); Amidan, Brett G. (Inventor); Whitney, Paul D. (Inventor); White, Amanda M. (Inventor); Willse, Alan R. (Inventor); Cooley, Scott K. (Inventor); Jay, Joseph Griffith (Inventor); Lawrence, Robert E. (Inventor); Mosbrucker, Chris (Inventor)

2005-01-01

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

Protein-protein interface detection using the energy centrality relationship (ECR) characteristic of proteins.

PubMed

Sudarshan, Sanjana; Kodathala, Sasi B; Mahadik, Amruta C; Mehta, Isha; Beck, Brian W

2014-01-01

Specific protein interactions are responsible for most biological functions. Distinguishing Functionally Linked Interfaces of Proteins (FLIPs), from Functionally uncorrelated Contacts (FunCs), is therefore important to characterizing these interactions. To achieve this goal, we have created a database of protein structures called FLIPdb, containing proteins belonging to various functional sub-categories. Here, we use geometric features coupled with Kortemme and Baker's computational alanine scanning method to calculate the energetic sensitivity of each amino acid at the interface to substitution, identify hotspots, and identify other factors that may contribute towards an interface being FLIP or FunC. Using Principal Component Analysis and K-means clustering on a training set of 160 interfaces, we could distinguish FLIPs from FunCs with an accuracy of 76%. When these methods were applied to two test sets of 18 and 170 interfaces, we achieved similar accuracies of 78% and 80%. We have identified that FLIP interfaces have a stronger central organizing tendency than FunCs, due, we suggest, to greater specificity. We also observe that certain functional sub-categories, such as enzymes, antibody-heavy-light, antibody-antigen, and enzyme-inhibitors form distinct sub-clusters. The antibody-antigen and enzyme-inhibitors interfaces have patterns of physical characteristics similar to those of FunCs, which is in agreement with the fact that the selection pressures of these interfaces is differently evolutionarily driven. As such, our ECR model also successfully describes the impact of evolution and natural selection on protein-protein interfaces. Finally, we indicate how our ECR method may be of use in reducing the false positive rate of docking calculations.

Protein-Protein Interface Detection Using the Energy Centrality Relationship (ECR) Characteristic of Proteins

PubMed Central

Sudarshan, Sanjana; Kodathala, Sasi B.; Mahadik, Amruta C.; Mehta, Isha; Beck, Brian W.

2014-01-01

Specific protein interactions are responsible for most biological functions. Distinguishing Functionally Linked Interfaces of Proteins (FLIPs), from Functionally uncorrelated Contacts (FunCs), is therefore important to characterizing these interactions. To achieve this goal, we have created a database of protein structures called FLIPdb, containing proteins belonging to various functional sub-categories. Here, we use geometric features coupled with Kortemme and Baker's computational alanine scanning method to calculate the energetic sensitivity of each amino acid at the interface to substitution, identify hotspots, and identify other factors that may contribute towards an interface being FLIP or FunC. Using Principal Component Analysis and K-means clustering on a training set of 160 interfaces, we could distinguish FLIPs from FunCs with an accuracy of 76%. When these methods were applied to two test sets of 18 and 170 interfaces, we achieved similar accuracies of 78% and 80%. We have identified that FLIP interfaces have a stronger central organizing tendency than FunCs, due, we suggest, to greater specificity. We also observe that certain functional sub-categories, such as enzymes, antibody-heavy-light, antibody-antigen, and enzyme-inhibitors form distinct sub-clusters. The antibody-antigen and enzyme-inhibitors interfaces have patterns of physical characteristics similar to those of FunCs, which is in agreement with the fact that the selection pressures of these interfaces is differently evolutionarily driven. As such, our ECR model also successfully describes the impact of evolution and natural selection on protein-protein interfaces. Finally, we indicate how our ECR method may be of use in reducing the false positive rate of docking calculations. PMID:24830938

The Abundance of Low-Luminosity Lyα Emitters at High Redshift

NASA Astrophysics Data System (ADS)

Santos, Michael R.; Ellis, Richard S.; Kneib, Jean-Paul; Richard, Johan; Kuijken, Konrad

2004-05-01

We derive the luminosity function of high-redshift Lyα-emitting sources from a deep, blind, spectroscopic survey that utilized strong-lensing magnification by intermediate-redshift clusters of galaxies. We observed carefully selected regions near nine clusters, consistent with magnification factors generally greater than 10 for the redshift range 4.5L)~L-1 over 1041-1042.5 ergs s-1. When combined with the results of other surveys, limited at higher luminosities, our results suggest evidence for the suppression of star formation in low-mass halos, as predicted in popular models of galaxy formation. Data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Benchmark CCSD(T) and DFT study of binding energies in Be7 - 12: in search of reliable DFT functional for beryllium clusters

NASA Astrophysics Data System (ADS)

Labanc, Daniel; Šulka, Martin; Pitoňák, Michal; Černušák, Ivan; Urban, Miroslav; Neogrády, Pavel

2018-05-01

We present a computational study of the stability of small homonuclear beryllium clusters Be7 - 12 in singlet electronic states. Our predictions are based on highly correlated CCSD(T) coupled cluster calculations. Basis set convergence towards the complete basis set limit as well as the role of the 1s core electron correlation are carefully examined. Our CCSD(T) data for binding energies of Be7 - 12 clusters serve as a benchmark for performance assessment of several density functional theory (DFT) methods frequently used in beryllium cluster chemistry. We observe that, from Be10 clusters on, the deviation from CCSD(T) benchmarks is stable with respect to size, and fluctuating within 0.02 eV error bar for most examined functionals. This opens up the possibility of scaling the DFT binding energies for large Be clusters using CCSD(T) benchmark values for smaller clusters. We also tried to find analogies between the performance of DFT functionals for Be clusters and for the valence-isoelectronic Mg clusters investigated recently in Truhlar's group. We conclude that it is difficult to find DFT functionals that perform reasonably well for both beryllium and magnesium clusters. Out of 12 functionals examined, only the M06-2X functional gives reasonably accurate and balanced binding energies for both Be and Mg clusters.

Large-scale clustering measurements with photometric redshifts: comparing the dark matter haloes of X-ray AGN, star-forming and passive galaxies at z ≈ 1

NASA Astrophysics Data System (ADS)

Georgakakis, A.; Mountrichas, G.; Salvato, M.; Rosario, D.; Pérez-González, P. G.; Lutz, D.; Nandra, K.; Coil, A.; Cooper, M. C.; Newman, J. A.; Berta, S.; Magnelli, B.; Popesso, P.; Pozzi, F.

2014-10-01

We combine multi-wavelength data in the AEGIS-XD and C-COSMOS surveys to measure the typical dark matter halo mass of X-ray selected active galactic nuclei (AGN) [LX(2-10 keV) > 1042 erg s- 1] in comparison with far-infrared selected star-forming galaxies detected in the Herschel/PEP survey (PACS Evolutionary Probe; LIR > 1011 L⊙) and quiescent systems at z ≈ 1. We develop a novel method to measure the clustering of extragalactic populations that uses photometric redshift probability distribution functions in addition to any spectroscopy. This is advantageous in that all sources in the sample are used in the clustering analysis, not just the subset with secure spectroscopy. The method works best for large samples. The loss of accuracy because of the lack of spectroscopy is balanced by increasing the number of sources used to measure the clustering. We find that X-ray AGN, far-infrared selected star-forming galaxies and passive systems in the redshift interval 0.6 < z < 1.4 are found in haloes of similar mass, log MDMH/(M⊙ h-1) ≈ 13.0. We argue that this is because the galaxies in all three samples (AGN, star-forming, passive) have similar stellar mass distributions, approximated by the J-band luminosity. Therefore, all galaxies that can potentially host X-ray AGN, because they have stellar masses in the appropriate range, live in dark matter haloes of log MDMH/(M⊙ h-1) ≈ 13.0 independent of their star formation rates. This suggests that the stellar mass of X-ray AGN hosts is driving the observed clustering properties of this population. We also speculate that trends between AGN properties (e.g. luminosity, level of obscuration) and large-scale environment may be related to differences in the stellar mass of the host galaxies.

Adaptive Evolution as a Predictor of Species-Specific Innate Immune Response.

PubMed

Webb, Andrew E; Gerek, Z Nevin; Morgan, Claire C; Walsh, Thomas A; Loscher, Christine E; Edwards, Scott V; O'Connell, Mary J

2015-07-01

It has been proposed that positive selection may be associated with protein functional change. For example, human and macaque have different outcomes to HIV infection and it has been shown that residues under positive selection in the macaque TRIM5α receptor locate to the region known to influence species-specific response to HIV. In general, however, the relationship between sequence and function has proven difficult to fully elucidate, and it is the role of large-scale studies to help bridge this gap in our understanding by revealing major patterns in the data that correlate genotype with function or phenotype. In this study, we investigate the level of species-specific positive selection in innate immune genes from human and mouse. In total, we analyzed 456 innate immune genes using codon-based models of evolution, comparing human, mouse, and 19 other vertebrate species to identify putative species-specific positive selection. Then we used population genomic data from the recently completed Neanderthal genome project, the 1000 human genomes project, and the 17 laboratory mouse genomes project to determine whether the residues that were putatively positively selected are fixed or variable in these populations. We find evidence of species-specific positive selection on both the human and the mouse branches and we show that the classes of genes under positive selection cluster by function and by interaction. Data from this study provide us with targets to test the relationship between positive selection and protein function and ultimately to test the relationship between positive selection and discordant phenotypes. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genetic similarities between tobacco use disorder and related comorbidities: an exploratory study

PubMed Central

2014-01-01

Background Tobacco use disorder (TUD), defined as the use of tobacco to the detriment of a person’s health or social functioning, is associated with various disorders. We hypothesized that mutual variation in genes may partly explain this link. The aims of this study were to make a non-exhaustive inventory of the disorders using (partially) the same genetic pathways as TUD, and to describe the genetic similarities between TUD and the selected disorders. Methods We developed a 3 stage approach: (i) selection of genes influencing TUD using Gene2Mesh and Ingenuity Pathway Analysis (IPA), (ii) selection of disorders associated with the selected genes using IPA and (iii) genetic similarities between disorders associated with TUD using Jaccard distance and cluster analyses. Results Fourteen disorders and thirty-two genes met our inclusion criteria. The Jaccard distance between pairs of disorders ranged from 0.00 (e.g. oesophageal cancer and malignant hypertension) to 0.45 (e.g. bladder cancer and addiction). A lower number in the Jaccard distance indicates a higher similarity between the two disorders. Two main clusters of genetically similar disorders were observed, one including coexisting disorders (e.g. addiction and alcoholism) and the other one with the side-effects of smoking (e.g. gastric cancer and malignant hypertension). Conclusions This exploratory study partly explains the potential genetic components linking TUD to other disorders. Two principle clusters of disorders were observed (i) coexisting disorders of TUD and (ii) side-effects of TUD disorders. A further deepening of this observation in a real life study should allow strengthening this hypothesis. PMID:25060307

Electronic Structure of the [Cu 3 (μ-O) 3] 2+ Cluster in Mordenite Zeolite and Its Effects on the Methane to Methanol Oxidation

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

Vogiatzis, Konstantinos D.; Li, Guanna; Hensen, Emiel J. M.

Identifying Cu-exchanged zeolites able to activate C–H bonds and selectively convert methane to methanol is a challenge in the field of biomimetic heterogeneous catalysis. Recent experiments point to the importance of trinuclear [Cu 3(μ-O) 3] 2+ complexes inside the micropores of mordenite (MOR) zeolite for selective oxo-functionalization of methane. The electronic structures of these species, namely, the oxidation state of Cu ions and the reactive character of the oxygen centers, are not yet fully understood. In this study, we performed a detailed analysis of the electronic structure of the [Cu 3(μ-O) 3] 2+ site using multiconfigurational wave-function-based methods and densitymore » functional theory. The calculations reveal that all Cu sites in the cluster are predominantly present in the Cu(II) formal oxidation state with a minor contribution from Cu(III), whereas two out of three oxygen anions possess a radical character. These electronic properties, along with the high accessibility of the out-of-plane oxygen center, make this oxygen the preferred site for the homolytic C–H activation of methane by [Cu 3(μ-O) 3] 2+. These new insights aid in the construction of a theoretical framework for the design of novel catalysts for oxyfunctionalization of natural gas and suggest further spectroscopic examination.« less

Electronic Structure of the [Cu 3 (μ-O) 3] 2+ Cluster in Mordenite Zeolite and Its Effects on the Methane to Methanol Oxidation

DOE PAGES

Vogiatzis, Konstantinos D.; Li, Guanna; Hensen, Emiel J. M.; ...

2017-09-28

Identifying Cu-exchanged zeolites able to activate C–H bonds and selectively convert methane to methanol is a challenge in the field of biomimetic heterogeneous catalysis. Recent experiments point to the importance of trinuclear [Cu 3(μ-O) 3] 2+ complexes inside the micropores of mordenite (MOR) zeolite for selective oxo-functionalization of methane. The electronic structures of these species, namely, the oxidation state of Cu ions and the reactive character of the oxygen centers, are not yet fully understood. In this study, we performed a detailed analysis of the electronic structure of the [Cu 3(μ-O) 3] 2+ site using multiconfigurational wave-function-based methods and densitymore » functional theory. The calculations reveal that all Cu sites in the cluster are predominantly present in the Cu(II) formal oxidation state with a minor contribution from Cu(III), whereas two out of three oxygen anions possess a radical character. These electronic properties, along with the high accessibility of the out-of-plane oxygen center, make this oxygen the preferred site for the homolytic C–H activation of methane by [Cu 3(μ-O) 3] 2+. These new insights aid in the construction of a theoretical framework for the design of novel catalysts for oxyfunctionalization of natural gas and suggest further spectroscopic examination.« less

Improving hot region prediction by parameter optimization of density clustering in PPI.

PubMed

Hu, Jing; Zhang, Xiaolong

2016-11-01

This paper proposed an optimized algorithm which combines density clustering of parameter selection with feature-based classification for hot region prediction. First, all the residues are classified by SVM to remove non-hot spot residues, then density clustering of parameter selection is used to find hot regions. In the density clustering, this paper studies how to select input parameters. There are two parameters radius and density in density-based incremental clustering. We firstly fix density and enumerate radius to find a pair of parameters which leads to maximum number of clusters, and then we fix radius and enumerate density to find another pair of parameters which leads to maximum number of clusters. Experiment results show that the proposed method using both two pairs of parameters provides better prediction performance than the other method, and compare these two predictive results, the result by fixing radius and enumerating density have slightly higher prediction accuracy than that by fixing density and enumerating radius. Copyright © 2016. Published by Elsevier Inc.

Defining clusters in APT reconstructions of ODS steels.

PubMed

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

2013-09-01

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

Brighter galaxy bias: underestimating the velocity dispersions of galaxy clusters

NASA Astrophysics Data System (ADS)

Old, L.; Gray, M. E.; Pearce, F. R.

2013-09-01

We study the systematic bias introduced when selecting the spectroscopic redshifts of brighter cluster galaxies to estimate the velocity dispersion of galaxy clusters from both simulated and observational galaxy catalogues. We select clusters with Ngal ≥ 50 at five low-redshift snapshots from the publicly available De Lucia & Blaziot semi-analytic model galaxy catalogue. Clusters are also selected from the Tempel Sloan Digital Sky Survey Data Release 8 groups and clusters catalogue across the redshift range 0.021 ≤ z ≤ 0.098. We employ various selection techniques to explore whether the velocity dispersion bias is simply due to a lack of dynamical information or is the result of an underlying physical process occurring in the cluster, for example, dynamical friction experienced by the brighter cluster members. The velocity dispersions of the parent dark matter (DM) haloes are compared to the galaxy cluster dispersions and the stacked distribution of DM particle velocities is examined alongside the corresponding galaxy velocity distribution. We find a clear bias between the halo and the semi-analytic galaxy cluster velocity dispersion on the order of σgal/σDM ˜ 0.87-0.95 and a distinct difference in the stacked galaxy and DM particle velocities distribution. We identify a systematic underestimation of the velocity dispersions when imposing increasing absolute I-band magnitude limits. This underestimation is enhanced when using only the brighter cluster members for dynamical analysis on the order of 5-35 per cent, indicating that dynamical friction is a serious source of bias when using galaxy velocities as tracers of the underlying gravitational potential. In contrast to the literature we find that the resulting bias is not only halo mass dependent but also that the nature of the dependence changes according to the galaxy selection strategy. We make a recommendation that, in the realistic case of limited availability of spectral observations, a strictly magnitude-limited sample should be avoided to ensure an unbiased estimate of the velocity dispersion.

Community detection using Kernel Spectral Clustering with memory

NASA Astrophysics Data System (ADS)

Langone, Rocco; Suykens, Johan A. K.

2013-02-01

This work is related to the problem of community detection in dynamic scenarios, which for instance arises in the segmentation of moving objects, clustering of telephone traffic data, time-series micro-array data etc. A desirable feature of a clustering model which has to capture the evolution of communities over time is the temporal smoothness between clusters in successive time-steps. In this way the model is able to track the long-term trend and in the same time it smooths out short-term variation due to noise. We use the Kernel Spectral Clustering with Memory effect (MKSC) which allows to predict cluster memberships of new nodes via out-of-sample extension and has a proper model selection scheme. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness as a valid prior knowledge. The latter, in fact, allows the model to cluster the current data well and to be consistent with the recent history. Here we propose a generalization of the MKSC model with an arbitrary memory, not only one time-step in the past. The experiments conducted on toy problems confirm our expectations: the more memory we add to the model, the smoother over time are the clustering results. We also compare with the Evolutionary Spectral Clustering (ESC) algorithm which is a state-of-the art method, and we obtain comparable or better results.

Catalysis by clusters with precise numbers of atoms

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

Tyo, Eric C.; Vajda, Stefan

2015-07-03

Clusters that contain only a small number of atoms can exhibit unique and often unexpected properties. The clusters are of particular interest in catalysis because they can act as individual active sites, and minor changes in size and composition – such as the addition or removal of a single atom – can have a substantial influence on the activity and selectivity of a reaction. Here we review recent progress in the synthesis, characterization and catalysis of well-defined sub-nanometre clusters. We examine work on size-selected supported clusters in ultra-high vacuum environments and under realistic reaction conditions, and explore the use ofmore » computational methods to provide a mechanistic understanding of their catalytic properties. We also highlight the potential of size-selected clusters to provide insights into important catalytic processes and their use in the development of novel catalytic systems.« less

The mass function and dynamical mass of young star clusters: why their initial crossing-time matters crucially

NASA Astrophysics Data System (ADS)

Parmentier, Geneviève; Baumgardt, Holger

2012-12-01

We highlight the impact of cluster-mass-dependent evolutionary rates upon the evolution of the cluster mass function during violent relaxation, that is, while clusters dynamically respond to the expulsion of their residual star-forming gas. Mass-dependent evolutionary rates arise when the mean volume density of cluster-forming regions is mass-dependent. In that case, even if the initial conditions are such that the cluster mass function at the end of violent relaxation has the same shape as the embedded-cluster mass function (i.e. infant weight-loss is mass-independent), the shape of the cluster mass function does change transiently during violent relaxation. In contrast, for cluster-forming regions of constant mean volume density, the cluster mass function shape is preserved all through violent relaxation since all clusters then evolve at the same mass-independent rate. On the scale of individual clusters, we model the evolution of the ratio of the dynamical mass to luminous mass of a cluster after gas expulsion. Specifically, we map the radial dependence of the time-scale for a star cluster to return to equilibrium. We stress that fields of view a few pc in size only, typical of compact clusters with rapid evolutionary rates, are likely to reveal cluster regions which have returned to equilibrium even if the cluster experienced a major gas expulsion episode a few Myr earlier. We provide models with the aperture and time expressed in units of the initial half-mass radius and initial crossing-time, respectively, so that our results can be applied to clusters with initial densities, sizes, and apertures different from ours.

GEMINI/GMOS SPECTROSCOPY OF 26 STRONG-LENSING-SELECTED GALAXY CLUSTER CORES

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

Bayliss, Matthew B.; Gladders, Michael D.; Koester, Benjamin P.

2011-03-15

We present results from a spectroscopic program targeting 26 strong-lensing cluster cores that were visually identified in the Sloan Digital Sky Survey (SDSS) and the Second Red-Sequence Cluster Survey (RCS-2). The 26 galaxy cluster lenses span a redshift range of 0.2 < z < 0.65, and our spectroscopy reveals 69 unique background sources with redshifts as high as z = 5.200. We also identify redshifts for 262 cluster member galaxies and measure the velocity dispersions and dynamical masses for 18 clusters where we have redshifts for N {>=} 10 cluster member galaxies. We account for the expected biases in dynamicalmore » masses of strong-lensing-selected clusters as predicted by results from numerical simulations and discuss possible sources of bias in our observations. The median dynamical mass of the 18 clusters with N {>=} 10 spectroscopic cluster members is M {sub Vir} = 7.84 x 10{sup 14} M {sub sun} h {sup -1} {sub 0.7}, which is somewhat higher than predictions for strong-lensing-selected clusters in simulations. The disagreement is not significant considering the large uncertainty in our dynamical data, systematic uncertainties in the velocity dispersion calibration, and limitations of the theoretical modeling. Nevertheless our study represents an important first step toward characterizing large samples of clusters that are identified in a systematic way as systems exhibiting dramatic strong-lensing features.« less

Jellyfish: Observational Properties of Extreme Ram-Pressure Stripping Events in Massive Galaxy Clusters

NASA Astrophysics Data System (ADS)

Conor, McPartland; Ebeling, Harald; Roediger, Elke

2015-08-01

We investigate the physical origin and observational signatures of extreme ram-pressure stripping (RPS) in 63 massive galaxy clusters at z=0.3-0.7, based on data in the F606W passband obtained with the Advanced Camera for Surveys aboard the Hubble Space Telescope. Using a training set of a dozen ``jellyfish" galaxies identified earlier in the same imaging data, we define quantitative morphological criteria to select candidate galaxies which are similar to known cases of RPS. Considering a sample of 16 ``jellyfish" galaxies (10 of which we present for the first time), we visually derive estimates of the projected direction of motion based on dynamical features such as apparent compression shocks and debris trails. Our findings suggest that the observed events occur primarily at large distances from the cluster core and involve infall trajectories featuring high impact parameters. Simple models of cluster growth show that such trajectories are consistent with two scenarios: 1) galaxy infall along filaments; and 2) infall at high velocities (≥1000 km/s) characteristic of cluster mergers. The observed distribution of events is best described by timescales of ˜few Myr in agreement with recent numerical simulations of RPS. The broader areal coverage of the Hubble Frontier Fields should provide an even larger sample of RPS events to determine the relative contributions of infall and cluster mergers. Prompted by the discovery of several jellyfish galaxies whose brightness in the F606W passband rivals or exceeds that of the respective brightest cluster galaxy, we attempt to constrain the luminosity function of galaxies undergoing RPS. The observed significant excess at the bright end compared to the luminosity functions of blue cluster members strongly suggests enhanced star formation, thus challenging theoretical and numerical studies according to which RPS merely displaces existing star-forming regions. In-depth studies of individual objects will help test our conclusions and allow a quantitative comparison with predictions of theoretical and numerical models of ram-pressure stripping.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Technical Reports Server (NTRS)

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

Galaxy clusters in the cosmic web

NASA Astrophysics Data System (ADS)

Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

2014-12-01

Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4

A very large ( θ E ≳ 40") strong gravitational lens selected with the Sunyaev–Zel’dovich effect: PLCK G287.0+32.9 ( z = 0.38)

DOE PAGES

Zitrin, Adi; Seitz, Stella; Monna, Anna; ...

2017-04-10

Since galaxy clusters sit at the high end of the mass function, the number of galaxy clusters both massive and concentrated enough to yield particularly large Einstein radii poses useful constraints on cosmological and structure formation models. To date, less than a handful of clusters are known to have Einstein radii exceedingmore » $$\\sim 40^{\\prime\\prime} $$ (for a source at $${z}_{s}\\simeq 2$$, nominally). Here, we report an addition to that list of the Sunyaev–Zel'dovich (SZ) selected cluster, PLCK G287.0+32.9 (z = 0.38), the second-highest SZ-mass (M 500) cluster from the Planck catalog. We present the first strong-lensing analysis of the cluster, identifying 20 sets of multiply imaged galaxies and candidates in new Hubble Space Telescope ( HST) data, including a long, $$l\\sim 22^{\\prime\\prime} $$ giant arc, as well as a quadruply imaged, apparently bright (magnified to $${J}_{{\\rm{F}}110{\\rm{W}}}=25.3$$ AB), likely high-redshift dropout galaxy at $${z}_{\\mathrm{phot}}=6.90$$ [6.13–8.43] (95% C.I.). Our analysis reveals a very large critical area (1.55 arcmin2, $${z}_{s}\\simeq 2$$), corresponding to an effective Einstein radius of $${\\theta }_{{\\rm{E}}}\\sim 42^{\\prime\\prime} $$. Furthermore, the model suggests the critical area will expand to 2.58 arcmin2 ($${\\theta }_{{\\rm{E}}}\\sim 54^{\\prime\\prime} $$) for sources at $${z}_{s}\\sim 10$$. Our work adds to recent efforts to model very massive clusters toward the launch of the James Webb Space Telescope, in order to identify the most useful cosmic lenses for studying the early universe. Spectroscopic redshifts for the multiply imaged galaxies and additional HST data will be necessary for refining the lens model and verifying the nature of the $$z\\sim 7$$ dropout.« less

Automatic Approach to Morphological Classification of Galaxies With Analysis of Galaxy Populations in Clusters

NASA Astrophysics Data System (ADS)

Sultanova, Madina; Barkhouse, Wayne; Rude, Cody

2018-01-01

The classification of galaxies based on their morphology is a field in astrophysics that aims to understand galaxy formation and evolution based on their physical differences. Whether structural differences are due to internal factors or a result of local environment, the dominate mechanism that determines galaxy type needs to be robustly quantified in order to have a thorough grasp of the origin of the different types of galaxies. The main subject of my Ph.D. dissertation is to explore the use of computers to automatically classify and analyze large numbers of galaxies according to their morphology, and to analyze sub-samples of galaxies selected by type to understand galaxy formation in various environments. I have developed a computer code to classify galaxies by measuring five parameters from their images in FITS format. The code was trained and tested using visually classified SDSS galaxies from Galaxy Zoo and the EFIGI data set. I apply my morphology software to numerous galaxies from diverse data sets. Among the data analyzed are the 15 Abell galaxy clusters (0.03 < z < 0.184) from Rude et al. 2017 (in preparation), which were observed by the Canada-France-Hawaii Telescope. Additionally, I studied 57 galaxy clusters from Barkhouse et al. (2007), 77 clusters from the WINGS survey (Fasano et al. 2006), and the six Hubble Space Telescope (HST) Frontier Field galaxy clusters. The high resolution of HST allows me to compare distant clusters with those nearby to look for evolutionary changes in the galaxy cluster population. I use the results from the software to examine the properties (e.g. luminosity functions, radial dependencies, star formation rates) of selected galaxies. Due to the large amount of data that will be available from wide-area surveys in the future, the use of computer software to classify and analyze the morphology of galaxies will be extremely important in terms of efficiency. This research aims to contribute to the solution of this problem.

A very large ( θ E ≳ 40") strong gravitational lens selected with the Sunyaev–Zel’dovich effect: PLCK G287.0+32.9 ( z = 0.38)

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

Zitrin, Adi; Seitz, Stella; Monna, Anna

Since galaxy clusters sit at the high end of the mass function, the number of galaxy clusters both massive and concentrated enough to yield particularly large Einstein radii poses useful constraints on cosmological and structure formation models. To date, less than a handful of clusters are known to have Einstein radii exceedingmore » $$\\sim 40^{\\prime\\prime} $$ (for a source at $${z}_{s}\\simeq 2$$, nominally). Here, we report an addition to that list of the Sunyaev–Zel'dovich (SZ) selected cluster, PLCK G287.0+32.9 (z = 0.38), the second-highest SZ-mass (M 500) cluster from the Planck catalog. We present the first strong-lensing analysis of the cluster, identifying 20 sets of multiply imaged galaxies and candidates in new Hubble Space Telescope ( HST) data, including a long, $$l\\sim 22^{\\prime\\prime} $$ giant arc, as well as a quadruply imaged, apparently bright (magnified to $${J}_{{\\rm{F}}110{\\rm{W}}}=25.3$$ AB), likely high-redshift dropout galaxy at $${z}_{\\mathrm{phot}}=6.90$$ [6.13–8.43] (95% C.I.). Our analysis reveals a very large critical area (1.55 arcmin2, $${z}_{s}\\simeq 2$$), corresponding to an effective Einstein radius of $${\\theta }_{{\\rm{E}}}\\sim 42^{\\prime\\prime} $$. Furthermore, the model suggests the critical area will expand to 2.58 arcmin2 ($${\\theta }_{{\\rm{E}}}\\sim 54^{\\prime\\prime} $$) for sources at $${z}_{s}\\sim 10$$. Our work adds to recent efforts to model very massive clusters toward the launch of the James Webb Space Telescope, in order to identify the most useful cosmic lenses for studying the early universe. Spectroscopic redshifts for the multiply imaged galaxies and additional HST data will be necessary for refining the lens model and verifying the nature of the $$z\\sim 7$$ dropout.« less

Infrared spectroscopy of hydrated naphthalene cluster anions.

PubMed

Knurr, Benjamin J; Adams, Christopher L; Weber, J Mathias

2012-09-14

We present infrared spectra of mass-selected C(10)H(8)(-)·(H(2)O)(n)·Ar(m) cluster anions (n = 1-6) obtained by Ar predissociation spectroscopy. The experimental spectra are compared with predicted spectra from density functional theory calculations. The OH groups of the water ligands are involved in H-bonds to other water molecules or to the π system of the naphthalene anion, which accommodates the excess electron. The interactions in the water network are generally found to be more important than those between water molecules and the ion. For 2 ≤ n ≤ 4 the water molecules form single layer water networks on one side of the naphthalene anion, while for n = 5 and 6, cage and multilayer structures become more energetically favorable. For cluster sizes with more than 3 water molecules, multiple conformers are likely to be responsible for the experimental spectra.

The Geometry of Selected U.S. Tidal Inlets.

DTIC Science & Technology

1980-05-01

wrong cluster. Table 6. Descriminant analysis results for three variables (DCC, EM2, and EM3). a. Coefficients for di i iminant functions based on three...47.95/ 3 07.72 0.975, 4,1 0 .310. 1 C1297 0,)1r, 55,94 o, D, C 24.07: 1. C5, 75 Iable-9. Descriminant analysis results for six variables (DMX, DMA, W

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

Jacobson, Heather R.; Pilachowski, Catherine A.; Friel, Eileen D., E-mail: jacob189@msu.edu, E-mail: catyp@astro.indiana.edu, E-mail: edfriel@mac.com

We present a detailed chemical abundance study of evolved stars in 10 open clusters based on Hydra multi-object echelle spectra obtained with the WIYN 3.5 m telescope. From an analysis of both equivalent widths and spectrum synthesis, abundances have been determined for the elements Fe, Na, O, Mg, Si, Ca, Ti, Ni, Zr, and for two of the 10 clusters, Al and Cr. To our knowledge, this is the first detailed abundance analysis for clusters NGC 1245, NGC 2194, NGC 2355, and NGC 2425. These 10 clusters were selected for analysis because they span a Galactocentric distance range R{sub gc}more » {approx} 9-13 kpc, the approximate location of the transition between the inner and outer disks. Combined with cluster samples from our previous work and those of other studies in the literature, we explore abundance trends as a function of cluster R{sub gc}, age, and [Fe/H]. As found previously by us and other studies, the [Fe/H] distribution appears to decrease with increasing R{sub gc} to a distance of {approx}12 kpc and then flattens to a roughly constant value in the outer disk. Cluster average element [X/Fe] ratios appear to be independent of R{sub gc}, although the picture for [O/Fe] is more complicated with a clear trend of [O/Fe] with [Fe/H] and sample incompleteness. Other than oxygen, no other element [X/Fe] exhibits a clear trend with [Fe/H]; likewise, there does not appear to be any strong correlation between abundance and cluster age. We divided clusters into different age bins to explore temporal variations in the radial element distributions. The radial metallicity gradient appears to have flattened slightly as a function of time, as found by other studies. There is also some indication that the transition from the inner disk metallicity gradient to the {approx}constant [Fe/H] distribution of the outer disk occurs at different Galactocentric radii for different age bins. However, interpretation of the time evolution of radial abundance distributions is complicated by the unequal R{sub gc} and [Fe/H] ranges spanned by clusters in different age bins.« less

Reexamine structures and relative stability of medium-sized silicon clusters: Low-lying endohedral fullerene-like clusters Si 30-Si 38

NASA Astrophysics Data System (ADS)

Yoo, Soohaeng; Shao, Nan; Zeng, X. C.

2009-10-01

We report improved results of lowest-lying silicon clusters Si 30-Si 38. A large population of low-energy clusters are collected from previous searches by several research groups and the binding energies of these clusters are computed using density-functional theory (DFT) methods. Best candidates (isomers with high binding energies) are identified from the screening calculations. Additional constrained search is then performed for the best candidates using the basin-hopping method combined with DFT geometry optimization. The obtained low-lying clusters are classified according to binding energies computed using either the Perdew-Burke-Ernzerhof (PBE) functional or the Becke exchange and Lee-Yang-Parr correlation (BLYP) functional. We propose to rank low-lying clusters according to the mean PBE/BLYP binding energies in view that the PBE functional tends to give greater binding energies for more compact clusters whereas the BLYP functional tends to give greater binding energies for less compact clusters or clusters composed of small-sized magic-number clusters. Except for Si 30, the new search confirms again that medium-size silicon clusters Si 31-Si 38 constructed with proper fullerene cage motifs are most promising to be the lowest-energy structures.

Clustering and visualizing similarity networks of membrane proteins.

PubMed

Hu, Geng-Ming; Mai, Te-Lun; Chen, Chi-Ming

2015-08-01

We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. © 2015 Wiley Periodicals, Inc.

The XMM Cluster Survey: X-ray analysis methodology

NASA Astrophysics Data System (ADS)

Lloyd-Davies, E. J.; Romer, A. Kathy; Mehrtens, Nicola; Hosmer, Mark; Davidson, Michael; Sabirli, Kivanc; Mann, Robert G.; Hilton, Matt; Liddle, Andrew R.; Viana, Pedro T. P.; Campbell, Heather C.; Collins, Chris A.; Dubois, E. Naomi; Freeman, Peter; Harrison, Craig D.; Hoyle, Ben; Kay, Scott T.; Kuwertz, Emma; Miller, Christopher J.; Nichol, Robert C.; Sahlén, Martin; Stanford, S. A.; Stott, John P.

2011-11-01

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 describe the data processing methodology applied to the 5776 XMM observations used to construct the current XCS source catalogue. A total of 3675 > 4σ cluster candidates with >50 background-subtracted X-ray counts are extracted from a total non-overlapping area suitable for cluster searching of 410 deg2. Of these, 993 candidates are detected with >300 background-subtracted X-ray photon counts, and we demonstrate that robust temperature measurements can be obtained down to this count limit. We describe in detail the automated pipelines used to perform the spectral and surface brightness fitting for these candidates, as well as to estimate redshifts from the X-ray data alone. A total of 587 (122) X-ray temperatures to a typical accuracy of <40 (<10) per cent have been measured to date. We also present the methodology adopted for determining the selection function of the survey, and show that the extended source detection algorithm is robust to a range of cluster morphologies by inserting mock clusters derived from hydrodynamical simulations into real XMMimages. These tests show that the simple isothermal β-profiles is sufficient to capture the essential details of the cluster population detected in the archival XMM observations. The redshift follow-up of the XCS cluster sample is presented in a companion paper, together with a first data release of 503 optically confirmed clusters.

Bottom-up strategies for the assembling of magnetic systems using nanoclusters

NASA Astrophysics Data System (ADS)

Dupuis, V.; Hillion, A.; Robert, A.; Loiselet, O.; Khadra, G.; Capiod, P.; Albin, C.; Boisron, O.; Le Roy, D.; Bardotti, L.; Tournus, F.; Tamion, A.

2018-05-01

In the frame of the 20th Anniversary of the Journal of Nanoparticle Research (JNR), our aim is to start from the historical context 20 years ago and to give some recent results and perspectives concerning nanomagnets prepared from clusters preformed in the gas phase using the low-energy cluster beam deposition (LECBD) technique. In this paper, we focus our attention on the typical case of Co clusters embedded in various matrices to study interface magnetic anisotropy and magnetic interactions as a function of volume concentrations, and on still current and perspectives through two examples of binary metallic 3d-5d TM (namely CoPt and FeAu) cluster assemblies to illustrate size-related and nanoalloy phenomena on magnetic properties in well-defined mass-selected clusters. The structural and magnetic properties of these cluster assemblies were investigated using various experimental techniques that include high-resolution transmission electron microscopy (HRTEM), superconducting quantum interference device (SQUID) magnetometry, and synchrotron techniques such as extended X-ray absorption fine structure (EXAFS) and X-ray magnetic circular dichroism (XMCD). Depending on the chemical nature of both NPs and matrix, we observe different magnetic responses compared to their bulk counterparts. In particular, we show how finite size effects (size reduction) enhance their magnetic moment and how specific relaxation in nanoalloys can impact their magnetic anisotropy.

Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

Eight different variable selection techniques for model-based and non-model-based clustering are evaluated across a wide range of cluster structures. It is shown that several methods have difficulties when non-informative variables (i.e., random noise) are included in the model. Furthermore, the distribution of the random noise greatly impacts the…

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.

Phylogenetic continuum indicates "galaxies" in the protein universe: preliminary results on the natural group structures of proteins.

PubMed

Ladunga, I

1992-04-01

The markedly nonuniform, even systematic distribution of sequences in the protein "universe" has been analyzed by methods of protein taxonomy. Mapping of the natural hierarchical system of proteins has revealed some dense cores, i.e., well-defined clusterings of proteins that seem to be natural structural groupings, possibly seeds for a future protein taxonomy. The aim was not to force proteins into more or less man-made categories by discriminant analysis, but to find structurally similar groups, possibly of common evolutionary origin. Single-valued distance measures between pairs of superfamilies from the Protein Identification Resource were defined by two chi 2-like methods on tripeptide frequencies and the variable-length subsequence identity method derived from dot-matrix comparisons. Distance matrices were processed by several methods of cluster analysis to detect phylogenetic continuum between highly divergent proteins. Only well-defined clusters characterized by relatively unique structural, intracellular environmental, organismal, and functional attribute states were selected as major protein groups, including subsets of viral and Escherichia coli proteins, hormones, inhibitors, plant, ribosomal, serum and structural proteins, amino acid synthases, and clusters dominated by certain oxidoreductases and apolar and DNA-associated enzymes. The limited repertoire of functional patterns due to small genome size, the high rate of recombination, specific features of the bacterial membranes, or of the virus cycle canalize certain proteins of viruses and Gram-negative bacteria, respectively, to organismal groups.

Final Report for "Non-Accelerator Physics – Research in High Energy Physics: Dark Energy Research on DES"

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

Ritz, Steve; Jeltema, Tesla

One of the greatest mysteries in modern cosmology is the fact that the expansion of the universe is observed to be accelerating. This acceleration may stem from dark energy, an additional energy component of the universe, or may indicate that the theory of general relativity is incomplete on cosmological scales. The growth rate of large-scale structure in the universe and particularly the largest collapsed structures, clusters of galaxies, is highly sensitive to the underlying cosmology. Clusters will provide one of the single most precise methods of constraining dark energy with the ongoing Dark Energy Survey (DES). The accuracy of themore » cosmological constraints derived from DES clusters necessarily depends on having an optimized and well-calibrated algorithm for selecting clusters as well as an optical richness estimator whose mean relation and scatter compared to cluster mass are precisely known. Calibrating the galaxy cluster richness-mass relation and its scatter was the focus of the funded work. Specifically, we employ X-ray observations and optical spectroscopy with the Keck telescopes of optically-selected clusters to calibrate the relationship between optical richness (the number of galaxies in a cluster) and underlying mass. This work also probes aspects of cluster selection like the accuracy of cluster centering which are critical to weak lensing cluster studies.« less

A deep view on the Virgo cluster core

NASA Astrophysics Data System (ADS)

Lieder, S.; Lisker, T.; Hilker, M.; Misgeld, I.; Durrell, P.

2012-02-01

Studies of dwarf spheroidal (dSph) galaxies with statistically significant sample sizes are still rare beyond the Local Group, since these low surface brightness objects can only be identified with deep imaging data. In galaxy clusters, where they constitute the dominant population in terms of number, they represent the faint end slope of the galaxy luminosity function and provide important insight on the interplay between galaxy mass and environment. In this study we investigate the optical photometric properties of early-type galaxies (dwarf ellipticals (dEs) and dSphs) in the Virgo cluster core region, by analysing their location on the colour magnitude relation (CMR) and the structural scaling relations down to faint magnitudes, and by constructing the luminosity function to compare it with theoretical expectations. Our work is based on deep CFHT V- and I-band data covering several square degrees of the Virgo cluster core that were obtained in 1999 using the CFH12K instrument. We visually select potential cluster members based on morphology and angular size, excluding spiral galaxies. A photometric analysis has been carried out for 295 galaxies, using surface brightness profile shape and colour as further criteria to identify probable background contaminants. 216 galaxies are considered to be certain or probable Virgo cluster members. Our study reveals 77 galaxies not catalogued in the VCC (with 13 of them already found in previous studies) that are very likely Virgo cluster members because they follow the Virgo CMR and exhibit low Sérsic indices. Those galaxies reach MV = -8.7 mag. The CMR shows a clear change in slope from dEs to dSphs, while the scatter of the CMR in the dSph regime does not increase significantly. Our sample might, however, be somewhat biased towards redder colours. The scaling relations given by the dEs appear to be continued by the dSphs indicating a similar origin. The observed change in the CMR slope may mark the point at which gas loss prevented significant metal enrichment. The almost constant scatter around the CMR possibly indicates a short formation period, resulting in similar stellar populations. The luminosity function shows a Schechter function's faint end slope of α = -1.50 ± 0.17, implying a lack of galaxies related to the expected number of low-mass dark matter haloes from theoretical models. Our findings could be explained by suppressed star formation in low-mass dark matter halos or by tidal disruption of dwarfs in the dense core region of the cluster. Tables 3 and 4 are available in electronic form at http://www.aanda.org

Compressive Sensing Cluster Expansion Studies of Lithium Intercalation and Phase Transformation in MoS2 for Energy Storage

NASA Astrophysics Data System (ADS)

Liu, Chi-Ping; Zhou, Fei; Ozolins, Vidvuds; University of California, Los Angeles Collaboration; Lawrence livermore national laboratory Collaboration

2015-03-01

Bulk molybdenum disulfide (MoS2) is a good electrode material candidate for energy storage applications, such as lithium ion batteries and supercapacitors due to its high theoretical energy and power density. First-principles density-functional theory (DFT) calculations combined with cluster expansion are an effective method to study thermodynamic and kinetic properties of electrode materials. In order to construct accurate models for cluster expansion, it is important to effectively choose clusters with significant contributions. In this work, we employ a compressive sensing based technique to select relevant clusters in order to build an accurate Hamiltonian for cluster expansion, enabling the study of Li intercalation in MoS2. We find that the 2H MoS2 structure is only stable at low Li content while 1T MoS2 is the preferred phase at high Li content. The results show that the 2H MoS2 phase transforms into the disordered 1T phase and the disordered 1T structure remains after the first Li insertion/deinsertion cycle suggesting that disordered 1T MoS2 is stable even at dilute Li content. This work also highlights that cluster expansion treated with compressive sensing is an effective and powerful tool for model construction and can be applied to advanced battery and supercapacitor electrode materials.

Thermodynamics of Small Alkali Metal Halide Cluster Ions: Comparison of Classical Molecular Simulations with Experiment and Quantum Chemistry

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

Vlcek, Lukas; Uhlik, Filip; Moucka, Filip

We evaluate the ability of selected classical molecular models to describe the thermodynamic and structural aspects of gas-phase hydration of alkali halide ions and the formation of small water clusters. To understand the effect of many-body interactions (polarization) and charge penetration effects on the accuracy of a force field, we perform Monte Carlo simulations with three rigid water models using different functional forms to account for these effects: (i) point charge non-polarizable SPC/E, (ii) Drude point charge polarizable SWM4- DP, and (iii) Drude Gaussian charge polarizable BK3. Model predictions are compared with experimental Gibbs free energies and enthalpies of ionmore » hydration, and with microscopic structural properties obtained from quantum DFT calculations. We find that all three models provide comparable predictions for pure water clusters and cation hydration, but differ significantly in their description of anion hydration. None of the investigated classical force fields can consistently and quantitatively reproduce the experimental gas phase hydration thermodynamics. The outcome of this study highlights the relation between the functional form that describes the effective intermolecular interactions and the accuracy of the resulting ion hydration properties.« less

Application of B{sub 12}N{sub 12} and B{sub 12}P{sub 12} as two fullerene-like semiconductors for adsorption of halomethane: Density functional theory study

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

Rad, Ali Shokuhi, E-mail: a.shokuhi@gmail.com

We examined and discussed the interaction of two halomethanes (mono-chloromethane (MCM), and mono-fluoromethane (MFM)) with B{sub 12}N{sub 12} and B{sub 12}P{sub 12} fullerene-like nanocages as semiconductor based on density functional theory (DFT). We calculated adsorption energies and followed the changes in the electronic structure of semiconductors upon adsorption of MCM and MFM. We found that the adsorption on the B{sub 12}N{sub 12} nano-cluster is energetically more favorable compared to B{sub 12}P{sub 12} nano-cluster. Also for both systems we found higher values of adsorption energy for MFM than for MCM. We found that upon adsorption of above-mentioned species on these twomore » fullerene-like semiconductors, the HOMO–LUMO distributions and also the gap energy for each system did not change significantly, which correspond to the physisorption process. As a result, B{sub 12}N{sub 12} is a more appropriate nano-cluster to be used as a selective sensor for halomethanes, especially for MFM.« less

Altered spinal microRNA-146a and the microRNA-183 cluster contribute to osteoarthritic pain in knee joints.

PubMed

Li, Xin; Kroin, Jeffrey S; Kc, Ranjan; Gibson, Gary; Chen, Di; Corbett, Grant T; Pahan, Kalipada; Fayyaz, Sana; Kim, Jae-Sung; van Wijnen, Andre J; Suh, Joon; Kim, Su-Gwan; Im, Hee-Jeong

2013-12-01

The objective of this study was to examine whether altered expression of microRNAs in central nervous system components is pathologically linked to chronic knee joint pain in osteoarthritis. A surgical animal model for knee joint OA was generated by medial meniscus transection in rats followed by behavioral pain tests. Relationships between pathological changes in knee joint and development of chronic joint pain were examined by histology and imaging analyses. Alterations in microRNAs associated with OA-evoked pain sensation were determined in bilateral lumbar dorsal root ganglia (DRG) and the spinal dorsal horn by microRNA array followed by individual microRNA analyses. Gain- and loss-of-function studies of selected microRNAs (miR-146a and miR-183 cluster) were conducted to identify target pain mediators regulated by these selective microRNAs in glial cells. The ipsilateral hind leg displayed significantly increased hyperalgesia after 4 weeks of surgery, and sensitivity was sustained for the remainder of the 8-week experimental period (F = 341, p < 0.001). The development of OA-induced chronic pain was correlated with pathological changes in the knee joints as assessed by histological and imaging analyses. MicroRNA analyses showed that miR-146a and the miR-183 cluster were markedly reduced in the sensory neurons in DRG (L4/L5) and spinal cord from animals experiencing knee joint OA pain. The downregulation of miR-146a and/or the miR-183 cluster in the central compartments (DRG and spinal cord) are closely associated with the upregulation of inflammatory pain mediators. The corroboration between decreases in these signature microRNAs and their specific target pain mediators were further confirmed by gain- and loss-of-function analyses in glia, the major cellular component of the central nervous system (CNS). MicroRNA therapy using miR-146a and the miR-183 cluster could be powerful therapeutic intervention for OA in alleviating joint pain and concomitantly regenerating peripheral knee joint cartilage. © 2013 American Society for Bone and Mineral Research.

Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

Deep near-infrared adaptive-optics observations of a young embedded cluster at the edge of the RCW 41 H II region

NASA Astrophysics Data System (ADS)

Neichel, B.; Samal, M. R.; Plana, H.; Zavagno, A.; Bernard, A.; Fusco, T.

2015-04-01

Aims: We investigate the star formation activity in a young star forming cluster embedded at the edge of the RCW 41 H ii region. As a complementary goal, we aim to demonstrate the gain provided by wide-field adaptive optics (WFAO) instruments to study young clusters. Methods: We used deep, JHKs images from the newly commissioned Gemini-GeMS/GSAOI instrument, complemented with Spitzer IRAC observations, in order to study the photometric properties of the young stellar cluster. GeMS is a WFAO instrument that delivers almost diffraction-limited images over a field of ~2' across. The exquisite angular resolution allows us to reach a limiting magnitude of J ~ 22 for 98% completeness. The combination of the IRAC photometry with our JHKs catalog is used to build color-color diagrams, and select young stellar object (YSO) candidates. The JHKs photometry is also used in conjunction with pre-main sequence evolutionary models to infer masses and ages. The K-band luminosity function is derived, and then used to build the initial mass function (IMF) of the cluster. Results: We detect the presence of 80 YSO candidates. Those YSOs are used to infer the cluster age, which is found to be in the range 1 to 5 Myr. More precisely, we find that 1/3 of the YSOs are in a range between 3 to 5 Myr, while 2/3 of the YSO are ≤3 Myr. When looking at the spatial distribution of these two populations, we find evidence of a potential age gradient across the field that suggests sequential star formation. We construct the IMF and show that we can sample the mass distribution well into the brown dwarf regime (down to ~0.01 M⊙). The logarithmic mass function rises to peak at ~0.3 M⊙, before turning over and declining into the brown dwarf regime. The total cluster mass derived is estimated to be 78 ± 18 M⊙, while the ratio derived of brown dwarfs to star is 18 ± 5%. When comparing it with other young clusters, we find that the IMF shape of the young cluster embedded within RCW 41 is consistent with those of Trapezium, IC 348, or Chamaeleon I, except for the IMF peak, which happens to be at higher mass. This characteristic is also seen in clusters like NGC 6611 or even Taurus. These results suggest that the medium-to-low mass end of the IMF possibly depends on environment.

Breakup of a homeobox cluster after genome duplication in teleosts

PubMed Central

Mulley, John F.; Chiu, Chi-hua; Holland, Peter W. H.

2006-01-01

Several families of homeobox genes are arranged in genomic clusters in metazoan genomes, including the Hox, ParaHox, NK, Rhox, and Iroquois gene clusters. The selective pressures responsible for maintenance of these gene clusters are poorly understood. The ParaHox gene cluster is evolutionarily conserved between amphioxus and human but is fragmented in teleost fishes. We show that two basal ray-finned fish, Polypterus and Amia, each possess an intact ParaHox cluster; this implies that the selective pressure maintaining clustering was lost after whole-genome duplication in teleosts. Cluster breakup is because of gene loss, not transposition or inversion, and the total number of ParaHox genes is the same in teleosts, human, mouse, and frog. We propose that this homeobox gene cluster is held together in chordates by the existence of interdigitated control regions that could be separated after locus duplication in the teleost fish. PMID:16801555

The complexity of selection at the major primate beta-defensin locus.

PubMed

Semple, Colin A M; Maxwell, Alison; Gautier, Philippe; Kilanowski, Fiona M; Eastwood, Hayden; Barran, Perdita E; Dorin, Julia R

2005-05-18

We have examined the evolution of the genes at the major human beta-defensin locus and the orthologous loci in a range of other primates and mouse. For the first time these data allow us to examine selective episodes in the more recent evolutionary history of this locus as well as the ancient past. We have used a combination of maximum likelihood based tests and a maximum parsimony based sliding window approach to give a detailed view of the varying modes of selection operating at this locus. We provide evidence for strong positive selection soon after the duplication of these genes within an ancestral mammalian genome. Consequently variable selective pressures have acted on beta-defensin genes in different evolutionary lineages, with episodes both of negative, and more rarely positive selection, during the divergence of primates. Positive selection appears to have been more common in the rodent lineage, accompanying the birth of novel, rodent-specific beta-defensin genes. These observations allow a fuller understanding of the evolution of mammalian innate immunity. In both the rodent and primate lineages, sites in the second exon have been subject to positive selection and by implication are important in functional diversity. A small number of sites in the mature human peptides were found to have undergone repeated episodes of selection in different primate lineages. Particular sites were consistently implicated by multiple methods at positions throughout the mature peptides. These sites are clustered at positions predicted to be important for the specificity of the antimicrobial or chemoattractant properties of beta-defensins. Surprisingly, sites within the prepropeptide region were also implicated as being subject to significant positive selection, suggesting previously unappreciated functional significance for this region. Identification of these putatively functional sites has important implications for our understanding of beta-defensin function and for novel antibiotic design.

First Selection, Then Influence: Developmental Differences in Friendship Dynamics Regarding Academic Achievement

ERIC Educational Resources Information Center

Gremmen, Mariola Claudia; Dijkstra, Jan Kornelis; Steglich, Christian; Veenstra, René

2017-01-01

This study concerns peer selection and influence dynamics in early adolescents' friendships regarding academic achievement. Using longitudinal social network analysis (RSiena), both selection and influence processes were investigated for students' average grades and their cluster-specific grades (i.e., language, exact, and social cluster). Data…

The hierarchical brain network for face recognition.

PubMed

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

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

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE PAGES

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; ...

2013-01-01

Background . The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective . To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods . The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expertmore » knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results . The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions . Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

PubMed Central

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

2013-01-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification. PMID:24223463

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

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

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.

2013-10-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integratedmore » into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Neuropsychiatric symptom clusters and functional disability in cognitively-impaired-not-demented individuals.

PubMed

Peters, Kevin R; Rockwood, Kenneth; Black, Sandra E; Hogan, David B; Gauthier, Serge G; Loy-English, Inge; Hsiung, Ging-Yuek R; Jacova, Claudia; Kertesz, Andrew; Feldman, Howard H

2008-02-01

Previous research has shown that cognitively-impaired-not-demented (CIND) individuals with at least one neuropsychiatric symptom (NPS) have more functional disability than individuals without any NPSs. The objectives of the present study were to determine whether there are consistent clusters of NPS in CIND individuals and whether certain NPS clusters are more strongly associated with measures of functional disability than other NPS clusters in this population. This was a cross-sectional baseline study of NPS using the Neuropsychiatric Inventory (NPI) in a national clinic-based observational cohort study (the Canadian Cohort Study of Cognitive Impairment and Related Dementias study). The present investigation focuses on a subset of CIND subjects (73%) whose informant endorsed the presence of at least one NPI item. A hierarchical cluster analysis identified two NPS clusters. One consisted of mood factors (i.e., depression, anxiety, apathy, irritability, and problems with sleep) and the other cluster captured frontal symptoms (i.e., aberrant motor behavior, disinhibition, agitation, and problems with appetite). NPSs grouped within the mood cluster were more common than the frontal cluster (95% of subjects had at least one NPS within the mood cluster versus 53% in the frontal cluster). However, the frontal cluster was more strongly associated with functional disability measures even after controlling for cognitive status (i.e., the Mini-Mental State Exam) and the mood cluster score. The frontal cluster of NPSs was more strongly associated with functional disability than the mood cluster.

Active Galactic Nucleus Feedback with the Square Kilometre Array and Implications for Cluster Physics and Cosmology

NASA Astrophysics Data System (ADS)

Iqbal, Asif; Kale, Ruta; Majumdar, Subhabrata; Nath, Biman B.; Pandge, Mahadev; Sharma, Prateek; Malik, Manzoor A.; Raychaudhury, Somak

2017-12-01

Active Galactic Nuclei (AGN) feedback is regarded as an important non-gravitational process in galaxy clusters, providing useful constraints on large-scale structure formation. It modifies the structure and energetics of the intra-cluster medium (ICM) and hence its understanding is crucially needed in order to use clusters as high precision cosmological probes. In this context, particularly keeping in mind the upcoming high quality radio data expected from radio surveys like Square Kilometre Array (SKA) with its higher sensitivity, high spatial and spectral resolutions, we review our current understanding of AGN feedback, its cosmological implications and the impact that SKA can have in revolutionizing our understanding of AGN feedback in large-scale structures. Recent developments regarding the AGN outbursts and its possible contribution to excess entropy in the hot atmospheres of groups and clusters, its correlation with the feedback energy in ICM, quenching of cooling flows and the possible connection between cool core clusters and radio mini-halos, are discussed. We describe current major issues regarding modeling of AGN feedback and its impact on the surrounding medium. With regard to the future of AGN feedback studies, we examine the possible breakthroughs that can be expected from SKA observations. In the context of cluster cosmology, for example, we point out the importance of SKA observations for cluster mass calibration by noting that most of z>1 clusters discovered by eROSITA X-ray mission can be expected to be followed up through a 1000 hour SKA1-mid programme. Moreover, approximately 1000 radio mini halos and ˜ 2500 radio halos at z<0.6 can be potentially detected by SKA1 and SKA2 and used as tracers of galaxy clusters and determination of cluster selection function.

SPT-GMOS: A GEMINI/GMOS-SOUTH SPECTROSCOPIC SURVEY OF GALAXY CLUSTERS IN THE SPT-SZ SURVEY

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

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.

We present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg{sup 2} of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goal ofmore » these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W , of [O ii] λλ 3727, 3729 and H- δ , and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m {sup ⋆}). Finally, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ∼20% of the full SPT-SZ sample.« less

SPT-GMOS: A Gemini/GMOS-South Spectroscopic survey of galaxy clusters in the SPT-SZ survey

DOE PAGES

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.; ...

2016-11-01

Here, we present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg 2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goalmore » of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W, of [O II] λλ3727, 3729 and H-δ, and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m*). Lastly, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ~20% of the full SPT-SZ sample.« less

SPT-GMOS: A Gemini/GMOS-South Spectroscopic survey of galaxy clusters in the SPT-SZ survey

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

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.

Here, we present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg 2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goalmore » of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W, of [O II] λλ3727, 3729 and H-δ, and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m*). Lastly, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ~20% of the full SPT-SZ sample.« less

The [(AI 2O 3) 2] - Anion Cluster: Electron Localization-Delocalization Isomerism

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

Sierka, Marek; Dobler, Jens; Sauer, Joachim

2009-10-05

Three-dimensional bulk alumina and its two-dimensional thin films show great structural diversity, posing considerable challenges to their experimental structural characterization and computational modeling. Recently, structural diversity has also been demonstrated for zerodimensional gas phase aluminum oxide clusters. Mass-selected clusters not only make systematic studies of the structural and electronic properties as a function of size possible, but lately have also emerged as powerful molecular models of complex surfaces and solid catalysts. In particular, the [(Al 2O 3) 3-5] + clusters were the first example of polynuclear maingroup metal oxide cluster that are able to thermally activate CH 4. Over themore » past decades gas phase aluminum oxide clusters have been extensively studied both experimentally and computationally, but definitive structural assignments were made for only a handful of them: the planar [Al 3O 3] - and [Al 5O 4] - cluster anions, and the [(Al 2O 3) 1-4(AlO)] + cluster cations. For stoichiometric clusters only the atomic structures of [(Al 2O 3) 4] +/0 have been nambiguously resolved. Here we report on the structures of the [(Al 2O 3) 2] -/0 clusters combining photoelectron spectroscopy (PES) and quantum chemical calculations employing a genetic algorithm as a global optimization technique. The [(Al 2O 3) 2] - cluster anion show energetically close lying but structurally distinct cage and sheet-like isomers which differ by delocalization/localization of the extra electron. The experimental results are crucial for benchmarking the different computational methods applied with respect to a proper description of electron localization and the relative energies for the isomers which will be of considerable value for future computational studies of aluminum oxide and related systems.« less

Clustering by neurocognition for fine-mapping of the schizophrenia susceptibility loci on chromosome 6p

PubMed Central

Lin, Sheng-Hsiang; Liu, Chih-Min; Liu, Yu-Li; Fann, Cathy Shen-Jang; Hsiao, Po-Chang; Wu, Jer-Yuarn; Hung, Shuen-Iu; Chen, Chun-Houh; Wu, Han-Ming; Jou, Yuh-Shan; Liu, Shi K.; Hwang, Tzung J.; Hsieh, Ming H.; Chang, Chien-Ching; Yang, Wei-Chih; Lin, Jin-Jia; Chou, Frank Huang-Chih; Faraone, Stephen V.; Tsuang, Ming T.; Hwu, Hai-Gwo; Chen, Wei J.

2009-01-01

Chromosome 6p is one of the most commonly implicated regions in the genome-wide linkage scans of schizophrenia, whereas further association studies for markers in this region were inconsistent likely due to heterogeneity. This study aimed to identify more homogeneous subgroups of families for fine mapping on regions around markers D6S296 and D6S309 (both in 6p24.3) as well as D6S274 (in 6p22.3) by means of similarity in neurocognitive functioning. A total of 160 families of patients with schizophrenia comprising at least two affected siblings who had data for 8 neurocognitive test variables of the Continuous Performance Test (CPT) and the Wisconsin Card Sorting Test (WCST) were subjected to cluster analysis with data visualization using the test scores of both affected siblings. Family clusters derived were then used separately in family-based association tests for 64 single nucleotide polymorphisms covering the region of 6p24.3 and 6p22.3. Three clusters were derived from the family-based clustering, with deficit cluster 1 representing deficit on the CPT, deficit cluster 2 representing deficit on both the CPT and the WCST, and a third cluster of non-deficit. After adjustment using false discovery rate for multiple testing, SNP rs13873 and haplotype rs1225934-rs13873 on BMP6-TXNDC5 genes were significantly associated with schizophrenia for the deficit cluster 1 but not for the deficit cluster 2 or non-deficit cluster. Our results provide further evidence that the BMP6-TXNDC5 locus on 6p24.3 may play a role in the selective impairments on sustained attention of schizophrenia. PMID:19694819

SPT-GMOS: A Gemini/GMOS-South Spectroscopic Survey of Galaxy Clusters in the SPT-SZ Survey

NASA Astrophysics Data System (ADS)

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.; Allen, S. W.; Applegate, D. E.; Ashby, M. L. N.; Bautz, M.; Benson, B. A.; Bleem, L. E.; Bocquet, S.; Brodwin, M.; Capasso, R.; Carlstrom, J. E.; Chang, C. L.; Chiu, I.; Cho, H.-M.; Clocchiatti, A.; Crawford, T. M.; Crites, A. T.; de Haan, T.; Desai, S.; Dietrich, J. P.; Dobbs, M. A.; Doucouliagos, A. N.; Foley, R. J.; Forman, W. R.; Garmire, G. P.; George, E. M.; Gladders, M. D.; Gonzalez, A. H.; Gupta, N.; Halverson, N. W.; Hlavacek-Larrondo, J.; Hoekstra, H.; Holder, G. P.; Holzapfel, W. L.; Hou, Z.; Hrubes, J. D.; Huang, N.; Jones, C.; Keisler, R.; Knox, L.; Lee, A. T.; Leitch, E. M.; von der Linden, A.; Luong-Van, D.; Mantz, A.; Marrone, D. P.; McDonald, M.; McMahon, J. J.; Meyer, S. S.; Mocanu, L. M.; Mohr, J. J.; Murray, S. S.; Padin, S.; Pryke, C.; Rapetti, D.; Reichardt, C. L.; Rest, A.; Ruhl, J. E.; Saliwanchik, B. R.; Saro, A.; Sayre, J. T.; Schaffer, K. K.; Schrabback, T.; Shirokoff, E.; Song, J.; Spieler, H. G.; Stalder, B.; Stanford, S. A.; Staniszewski, Z.; Stark, A. A.; Story, K. T.; Vanderlinde, K.; Vieira, J. D.; Vikhlinin, A.; Williamson, R.; Zenteno, A.

2016-11-01

We present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goal of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W, of [O II] λλ3727, 3729 and H-δ, and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m⋆). Finally, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ∼20% of the full SPT-SZ sample.

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling.

PubMed

Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

2015-09-18

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling

PubMed Central

Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

2015-01-01

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols. PMID:26393608

A cluster-based approach to selecting representative stimuli from the International Affective Picture System (IAPS) database.

PubMed

Constantinescu, Alexandra C; Wolters, Maria; Moore, Adam; MacPherson, Sarah E

2017-06-01

The International Affective Picture System (IAPS; Lang, Bradley, & Cuthbert, 2008) is a stimulus database that is frequently used to investigate various aspects of emotional processing. Despite its extensive use, selecting IAPS stimuli for a research project is not usually done according to an established strategy, but rather is tailored to individual studies. Here we propose a standard, replicable method for stimulus selection based on cluster analysis, which re-creates the group structure that is most likely to have produced the valence arousal, and dominance norms associated with the IAPS images. Our method includes screening the database for outliers, identifying a suitable clustering solution, and then extracting the desired number of stimuli on the basis of their level of certainty of belonging to the cluster they were assigned to. Our method preserves statistical power in studies by maximizing the likelihood that the stimuli belong to the cluster structure fitted to them, and by filtering stimuli according to their certainty of cluster membership. In addition, although our cluster-based method is illustrated using the IAPS, it can be extended to other stimulus databases.

R-CMap-An open-source software for concept mapping.

PubMed

Bar, Haim; Mentch, Lucas

2017-02-01

Planning and evaluating projects often involves input from many stakeholders. Fusing and organizing many different ideas, opinions, and interpretations into a coherent and acceptable plan or project evaluation is challenging. This is especially true when seeking contributions from a large number of participants, especially when not all can participate in group discussions, or when some prefer to contribute their perspectives anonymously. One of the major breakthroughs in the area of evaluation and program planning has been the use of graphical tools to represent the brainstorming process. This provides a quantitative framework for organizing ideas and general concepts into simple-to-interpret graphs. We developed a new, open-source concept mapping software called R-CMap, which is implemented in R. This software provides a graphical user interface to guide users through the analytical process of concept mapping. The R-CMap software allows users to generate a variety of plots, including cluster maps, point rating and cluster rating maps, as well as pattern matching and go-zone plots. Additionally, R-CMap is capable of generating detailed reports that contain useful statistical summaries of the data. The plots and reports can be embedded in Microsoft Office tools such as Word and PowerPoint, where users may manually adjust various plot and table features to achieve the best visual results in their presentations and official reports. The graphical user interface of R-CMap allows users to define cluster names, change the number of clusters, select rating variables for relevant plots, and importantly, select subsets of respondents by demographic criteria. The latter is particularly useful to project managers in order to identify different patterns of preferences by subpopulations. R-CMap is user-friendly, and does not require any programming experience. However, proficient R users can add to its functionality by directly accessing built-in functions in R and sharing new features with the concept mapping community. Copyright © 2016 Elsevier Ltd. All rights reserved.

Overdensities of SMGs around WISE-selected, ultraluminous, high-redshift AGNs

NASA Astrophysics Data System (ADS)

Jones, Suzy F.; Blain, Andrew W.; Assef, Roberto J.; Eisenhardt, Peter; Lonsdale, Carol; Condon, James; Farrah, Duncan; Tsai, Chao-Wei; Bridge, Carrie; Wu, Jingwen; Wright, Edward L.; Jarrett, Tom

2017-08-01

We investigate extremely luminous dusty galaxies in the environments around Wide-field Infrared Survey Explorer (WISE)-selected hot dust-obscured galaxies (Hot DOGs) and WISE/radio-selected active galactic nuclei (AGNs) at average redshifts of z = 2.7 and 1.7, respectively. Previous observations have detected overdensities of companion submillimetre-selected sources around 10 Hot DOGs and 30 WISE/radio AGNs, with overdensities of ˜2-3 and ˜5-6, respectively. We find that the space densities in both samples to be overdense compared to normal star-forming galaxies and submillimetre galaxies (SMGs) in the Submillimetre Common-User Bolometer Array 2 (SCUBA-2) Cosmology Legacy Survey (S2CLS). Both samples of companion sources have consistent mid-infrared (mid-IR) colours and mid-IR to submm ratios as SMGs. The brighter population around WISE/radio AGNs could be responsible for the higher overdensity reported. We also find that the star formation rate densities are higher than the field, but consistent with clusters of dusty galaxies. WISE-selected AGNs appear to be good signposts for protoclusters at high redshift on arcmin scales. The results reported here provide an upper limit to the strength of angular clustering using the two-point correlation function. Monte Carlo simulations show no angular correlation, which could indicate protoclusters on scales larger than the SCUBA-2 1.5-arcmin scale maps.

Angular correlation function of 1.5 million luminous red galaxies: clustering evolution and a search for baryon acoustic oscillations

NASA Astrophysics Data System (ADS)

Sawangwit, U.; Shanks, T.; Abdalla, F. B.; Cannon, R. D.; Croom, S. M.; Edge, A. C.; Ross, Nicholas P.; Wake, D. A.

2011-10-01

We present the angular correlation function measured from photometric samples comprising 1562 800 luminous red galaxies (LRGs). Three LRG samples were extracted from the Sloan Digital Sky Survey (SDSS) imaging data, based on colour-cut selections at redshifts, z≈ 0.35, 0.55 and 0.7 as calibrated by the spectroscopic surveys, SDSS-LRG, 2dF-SDSS LRG and QSO (quasi-stellar object) (2SLAQ) and the AAΩ-LRG survey. The galaxy samples cover ≈7600 deg2 of sky, probing a total cosmic volume of ≈5.5 h-3 Gpc3. The small- and intermediate-scale correlation functions generally show significant deviations from a single power-law fit with a well-detected break at ≈1 h-1 Mpc, consistent with the transition scale between the one- and two-halo terms in halo occupation models. For galaxy separations 1-20 h-1 Mpc and at fixed luminosity, we see virtually no evolution of the clustering with redshift and the data are consistent with a simple high peaks biasing model where the comoving LRG space density is constant with z. At fixed z, the LRG clustering amplitude increases with luminosity in accordance with the simple high peaks model, with a typical LRG dark matter halo mass 1013-1014 h-1 M⊙. For r < 1 h-1 Mpc, the evolution is slightly faster and the clustering decreases towards high redshift consistent with a virialized clustering model. However, assuming the halo occupation distribution (HOD) and Λ cold dark matter (ΛCDM) halo merger frameworks, ˜2-3 per cent/Gyr of the LRGs are required to merge in order to explain the small scales clustering evolution, consistent with previous results. At large scales, our result shows good agreement with the SDSS-LRG result of Eisenstein et al. but we find an apparent excess clustering signal beyond the baryon acoustic oscillations (BAO) scale. Angular power spectrum analyses of similar LRG samples also detect a similar apparent large-scale clustering excess but more data are required to check for this feature in independent galaxy data sets. Certainly, if the ΛCDM model were correct then we would have to conclude that this excess was caused by systematics at the level of Δw≈ 0.001-0.0015 in the photometric AAΩ-LRG sample.

The emergence of the galactic stellar mass function from a non-universal IMF in clusters

NASA Astrophysics Data System (ADS)

Dib, Sami; Basu, Shantanu

2018-06-01

We investigate the dependence of a single-generation galactic mass function (SGMF) on variations in the initial stellar mass functions (IMF) of stellar clusters. We show that cluster-to-cluster variations of the IMF lead to a multi-component SGMF where each component in a given mass range can be described by a distinct power-law function. We also show that a dispersion of ≈0.3 M⊙ in the characteristic mass of the IMF, as observed for young Galactic clusters, leads to a low-mass slope of the SGMF that matches the observed Galactic stellar mass function even when the IMFs in the low-mass end of individual clusters are much steeper.

Mass functions for globular cluster main sequences based on CCD photometry and stellar models

NASA Astrophysics Data System (ADS)

McClure, Robert D.; Vandenberg, Don A.; Smith, Graeme H.; Fahlman, Gregory G.; Richer, Harvey B.; Hesser, James E.; Harris, William E.; Stetson, Peter B.; Bell, R. A.

1986-08-01

Main-sequence luminosity functions constructed from CCD observations of globular clusters reveal a strong trend in slope with metal abundance. Theoretical luminosity functions constructed from VandenBerg and Bell's (1985) isochrones have been fitted to the observations and reveal a trend between x, the power-law index of the mass function, and metal abundance. The most metal-poor clusters require an index of about x = 2.5, whereas the most metal-rich clusters exhibit an index of x of roughly -0.5. The luminosity functions for two sparse clusters, E3 and Pal 5, are distinct from those of the more massive clusters, in that they show a turndown which is possibly a result of mass loss or tidal disruption.

Conditions for the Evolution of Gene Clusters in Bacterial Genomes

PubMed Central

Ballouz, Sara; Francis, Andrew R.; Lan, Ruiting; Tanaka, Mark M.

2010-01-01

Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters. PMID:20168992

Detection and clustering of features in aerial images by neuron network-based algorithm

NASA Astrophysics Data System (ADS)

Vozenilek, Vit

2015-12-01

The paper presents the algorithm for detection and clustering of feature in aerial photographs based on artificial neural networks. The presented approach is not focused on the detection of specific topographic features, but on the combination of general features analysis and their use for clustering and backward projection of clusters to aerial image. The basis of the algorithm is a calculation of the total error of the network and a change of weights of the network to minimize the error. A classic bipolar sigmoid was used for the activation function of the neurons and the basic method of backpropagation was used for learning. To verify that a set of features is able to represent the image content from the user's perspective, the web application was compiled (ASP.NET on the Microsoft .NET platform). The main achievements include the knowledge that man-made objects in aerial images can be successfully identified by detection of shapes and anomalies. It was also found that the appropriate combination of comprehensive features that describe the colors and selected shapes of individual areas can be useful for image analysis.

Design of Janus nanoparticles with atomic precision: tungsten-doped gold nanostructures.

PubMed

Sun, Qiang; Wang, Qian; Jena, Puru; Kawazoe, Yoshiyuki

2008-02-01

Janus nanoparticles, characterized by their anisotropic structure and interactions, have added a new dimension to nanoscience because of their potential applications in biomedicine, sensors, catalysis, and assembled materials. The technological applications of these nanoparticles, however, have been limited as the current chemical, physical, and biosynthetic methods lack sufficient size and shape selectivity. We report a technique where gold clusters doped with tungsten can serve as a seed that facilitates the natural growth of anisotropic nanostructures whose size and shape can be controlled with atomic precision. Using ab initio simulated annealing and molecular dynamics calculations on AunW (n > 12) clusters, we discovered that the W@Au12 cage cluster forms a very stable core with the remaining Au atoms forming patchy structures on its surface. The anisotropic geometry gives rise to anisotropies in vibrational spectra, charge distributions, electronic structures, and reactivity, thus making it useful to have dual functionalities. In particular, the core-patch structure is shown to possess a hydrophilic head and a hydrophobic tail. The W@Au12 clusters can also be used as building blocks of a nanoring with novel properties.

Finding and testing network communities by lumped Markov chains.

PubMed

Piccardi, Carlo

2011-01-01

Identifying communities (or clusters), namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. Yet, there is a lack of formal criteria for defining communities and for testing their significance. We propose a sharp definition that is based on a quality threshold. By means of a lumped Markov chain model of a random walker, a quality measure called "persistence probability" is associated to a cluster, which is then defined as an "α-community" if such a probability is not smaller than α. Consistently, a partition composed of α-communities is an "α-partition." These definitions turn out to be very effective for finding and testing communities. If a set of candidate partitions is available, setting the desired α-level allows one to immediately select the α-partition with the finest decomposition. Simultaneously, the persistence probabilities quantify the quality of each single community. Given its ability in individually assessing each single cluster, this approach can also disclose single well-defined communities even in networks that overall do not possess a definite clusterized structure.

Clustering analysis of proteins from microbial genomes at multiple levels of resolution.

PubMed

Zaslavsky, Leonid; Ciufo, Stacy; Fedorov, Boris; Tatusova, Tatiana

2016-08-31

Microbial genomes at the National Center for Biotechnology Information (NCBI) represent a large collection of more than 35,000 assemblies. There are several complexities associated with the data: a great variation in sampling density since human pathogens are densely sampled while other bacteria are less represented; different protein families occur in annotations with different frequencies; and the quality of genome annotation varies greatly. In order to extract useful information from these sophisticated data, the analysis needs to be performed at multiple levels of phylogenomic resolution and protein similarity, with an adequate sampling strategy. Protein clustering is used to construct meaningful and stable groups of similar proteins to be used for analysis and functional annotation. Our approach is to create protein clusters at three levels. First, tight clusters in groups of closely-related genomes (species-level clades) are constructed using a combined approach that takes into account both sequence similarity and genome context. Second, clustroids of conservative in-clade clusters are organized into seed global clusters. Finally, global protein clusters are built around the the seed clusters. We propose filtering strategies that allow limiting the protein set included in global clustering. The in-clade clustering procedure, subsequent selection of clustroids and organization into seed global clusters provides a robust representation and high rate of compression. Seed protein clusters are further extended by adding related proteins. Extended seed clusters include a significant part of the data and represent all major known cell machinery. The remaining part, coming from either non-conservative (unique) or rapidly evolving proteins, from rare genomes, or resulting from low-quality annotation, does not group together well. Processing these proteins requires significant computational resources and results in a large number of questionable clusters. The developed filtering strategies allow to identify and exclude such peripheral proteins limiting the protein dataset in global clustering. Overall, the proposed methodology allows the relevant data at different levels of details to be obtained and data redundancy eliminated while keeping biologically interesting variations.

Evaluation of familial aggregation, vegetable consumption, legumes consumption, and physical activity on functional constipation in families of children with functional constipation versus children without constipation.

PubMed

Dehghani, Seyed Mohsen; Moravej, Hossein; Rajaei, Elahe; Javaherizadeh, Hazhir

2015-01-01

Constipation is a frequent complication in paediatrics. Most of the constipation is functional. Functional constipation constitutes 25% of visits in paediatric gastroenterology clinics. Two studies were published regarding aggregation or clustering of functional constipation. Only one of these research projects was about a paediatric population. To elucidate the cluster pattern of constipation among the families of children with constipation. This case-control study was carried out on the families of 37 children < 18 years old with chronic functional constipation and the families of 37 healthy children as controls. Cases were enrolled in the study according to Rome III criteria for constipation. The control group was selected from children < 18 years old who visited the well baby clinic of the university. Parents and siblings were evaluated regarding constipation. Rome II and III were used for evaluation of constipation for adults and children, respectively. Data was analysed using SPSS (Chicago, IL, USA). The χ(2) and t-test were used for comparison. Physical activity and vegetable consumption were seen more frequently in the control group compared to the cases, but these differences were statistically insignificant. Constipation in mothers was significantly higher in the case group compared to the control group (p = 0.015). There was no significant difference between the two groups regarding exercise and vegetable consumption. The frequency of constipation among mothers was significantly higher in the case group compared to the control group. Another study is recommended in a larger population for evaluation of genetic background, diet, physical activity, and familial clustering among mothers of children with constipation.

New trial wave function for the nuclear cluster structure of nuclei

NASA Astrophysics Data System (ADS)

Zhou, Bo

2018-04-01

A new trial wave function is proposed for nuclear cluster physics, in which an exact solution to the long-standing center-of-mass problem is given. In the new approach, the widths of the single-nucleon Gaussian wave packets and the widths of the relative Gaussian wave functions describing correlations of nucleons or clusters are treated as variables in the explicit intrinsic wave function of the nuclear system. As an example, this new wave function was applied to study the typical {^{20}Ne} (α+{{^{16}}O}) cluster system. By removing exactly the spurious center-of-mass effect in a very simple way, the energy curve of {^{20}Ne} was obtained by variational calculations with the width of the α cluster, the width of the {{^{16}}O} cluster, and the size parameter of the nucleus. These are considered the three crucial variational variables in describing the {^{20}Ne} (α+{{^{16}}O}) cluster system. This shows that the new wave function can be a very interesting new tool for studying many-body and cluster effects in nuclear physics.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

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.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

Automated sample plan selection for OPC modeling

NASA Astrophysics Data System (ADS)

Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

2014-03-01

It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

PubMed

Comeau, Stephen R; Gatchell, David W; Vajda, Sandor; Camacho, Carlos J

2004-01-01

Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu

The cosmological analysis of X-ray cluster surveys. III. 4D X-ray observable diagrams

NASA Astrophysics Data System (ADS)

Pierre, M.; Valotti, A.; Faccioli, L.; Clerc, N.; Gastaud, R.; Koulouridis, E.; Pacaud, F.

2017-11-01

Context. Despite compelling theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties surrounding cluster-mass estimates. Aims: Our aim is to develop a fully self-consistent cosmological approach of X-ray cluster surveys, exclusively based on observable quantities rather than masses. This procedure is justified given the possibility to directly derive the cluster properties via ab initio modelling, either analytically or by using hydrodynamical simulations. In this third paper, we evaluate the method on cluster toy-catalogues. Methods: We model the population of detected clusters in the count-rate - hardness-ratio - angular size - redshift space and compare the corresponding four-dimensional diagram with theoretical predictions. The best cosmology+physics parameter configuration is determined using a simple minimisation procedure; errors on the parameters are estimated by averaging the results from ten independent survey realisations. The method allows a simultaneous fit of the cosmological parameters of the cluster evolutionary physics and of the selection effects. Results: When using information from the X-ray survey alone plus redshifts, this approach is shown to be as accurate as the modelling of the mass function for the cosmological parameters and to perform better for the cluster physics, for a similar level of assumptions on the scaling relations. It enables the identification of degenerate combinations of parameter values. Conclusions: Given the considerably shorter computer times involved for running the minimisation procedure in the observed parameter space, this method appears to clearly outperform traditional mass-based approaches when X-ray survey data alone are available.

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

Yu, Kuang; Libisch, Florian; Carter, Emily A., E-mail: eac@princeton.edu

We report a new implementation of the density functional embedding theory (DFET) in the VASP code, using the projector-augmented-wave (PAW) formalism. Newly developed algorithms allow us to efficiently perform optimized effective potential optimizations within PAW. The new algorithm generates robust and physically correct embedding potentials, as we verified using several test systems including a covalently bound molecule, a metal surface, and bulk semiconductors. We show that with the resulting embedding potential, embedded cluster models can reproduce the electronic structure of point defects in bulk semiconductors, thereby demonstrating the validity of DFET in semiconductors for the first time. Compared to ourmore » previous version, the new implementation of DFET within VASP affords use of all features of VASP (e.g., a systematic PAW library, a wide selection of functionals, a more flexible choice of U correction formalisms, and faster computational speed) with DFET. Furthermore, our results are fairly robust with respect to both plane-wave and Gaussian type orbital basis sets in the embedded cluster calculations. This suggests that the density functional embedding method is potentially an accurate and efficient way to study properties of isolated defects in semiconductors.« less

Performance Analysis of Cluster Formation in Wireless Sensor Networks.

PubMed

Montiel, Edgar Romo; Rivero-Angeles, Mario E; Rubino, Gerardo; Molina-Lozano, Heron; Menchaca-Mendez, Rolando; Menchaca-Mendez, Ricardo

2017-12-13

Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN) use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes.

Performance Analysis of Cluster Formation in Wireless Sensor Networks

PubMed Central

Montiel, Edgar Romo; Rivero-Angeles, Mario E.; Rubino, Gerardo; Molina-Lozano, Heron; Menchaca-Mendez, Rolando; Menchaca-Mendez, Ricardo

2017-01-01

Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN) use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes. PMID:29236065

Prokaryotic Gene Clusters: A Rich Toolbox for Synthetic Biology

PubMed Central

Fischbach, Michael; Voigt, Christopher A.

2014-01-01

Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be “mixed-and-matched” to create a designer organism. PMID:21154668

Highly active Au/δ-MoC and Au/β-Mo 2C catalysts for the low-temperature water gas shift reaction: effects of the carbide metal/carbon ratio on the catalyst performance

DOE PAGES

Posada-Pérez, Sergio; Gutiérrez, Ramón A.; Zuo, Zhijun; ...

2017-05-08

In this paper, the water gas shift (WGS) reaction catalyzed by orthorhombic β-Mo 2C and cubic δ-MoC surfaces with and without Au clusters supported thereon has been studied by means of a combination of sophisticated experiments and state-of-the-art computational modeling. Experiments evidence the importance of the metal/carbon ratio on the performance of these systems, where Au/δ-MoC is presented as a suitable catalyst for WGS at low temperatures owing to its high activity, selectivity (only CO 2 and H 2 are detected), and stability (oxycarbides are not observed). Periodic density functional theory-based calculations show that the supported Au clusters and themore » Au/δ-MoC interface do not take part directly in water dissociation but their presence is crucial to switch the reaction mechanism, drastically decreasing the effect of the reverse WGS reaction and favoring the WGS products desorption, thus leading to an increase in CO 2 and H 2 production. Finally, the present results clearly display the importance of the Mo/C ratio and the synergy with the admetal clusters in tuning the activity and selectivity of the carbide substrate.« less

Highly active Au/δ-MoC and Au/β-Mo 2C catalysts for the low-temperature water gas shift reaction: effects of the carbide metal/carbon ratio on the catalyst performance

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

Posada-Pérez, Sergio; Gutiérrez, Ramón A.; Zuo, Zhijun

In this paper, the water gas shift (WGS) reaction catalyzed by orthorhombic β-Mo 2C and cubic δ-MoC surfaces with and without Au clusters supported thereon has been studied by means of a combination of sophisticated experiments and state-of-the-art computational modeling. Experiments evidence the importance of the metal/carbon ratio on the performance of these systems, where Au/δ-MoC is presented as a suitable catalyst for WGS at low temperatures owing to its high activity, selectivity (only CO 2 and H 2 are detected), and stability (oxycarbides are not observed). Periodic density functional theory-based calculations show that the supported Au clusters and themore » Au/δ-MoC interface do not take part directly in water dissociation but their presence is crucial to switch the reaction mechanism, drastically decreasing the effect of the reverse WGS reaction and favoring the WGS products desorption, thus leading to an increase in CO 2 and H 2 production. Finally, the present results clearly display the importance of the Mo/C ratio and the synergy with the admetal clusters in tuning the activity and selectivity of the carbide substrate.« less

A two-stage cluster sampling method using gridded population data, a GIS, and Google Earth(TM) imagery in a population-based mortality survey in Iraq.

PubMed

Galway, Lp; Bell, Nathaniel; Sae, Al Shatari; Hagopian, Amy; Burnham, Gilbert; Flaxman, Abraham; Weiss, Wiliam M; Rajaratnam, Julie; Takaro, Tim K

2012-04-27

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

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

PubMed Central

2012-01-01

Background Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. Results We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS) to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Conclusion Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings. PMID:22540266

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

PubMed Central

2010-01-01

Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451

Redshift Evolution of Non-Gaussianity in Cosmic Large-Scale Structure

NASA Astrophysics Data System (ADS)

Sullivan, James; Wiegand, Alexander; Eisenstein, Daniel

2018-01-01

We probe the higher-order galaxy clustering in the final data release (DR12) of the Sloan Digital Sky Survey using germ-grain Minkowski Functionals (MFs). Our data selection contains 979,430 BOSS galaxies from both the northern and southern galactic caps over the redshift range 0.2 - 0.6. We extract the higher-order parts of the MFs and find deviations from the case without higher order MFs with chi-squared values of order 1000 for 24 degrees of freedom across the entire data selection. We show the MFs to be sensitive to contributions up to the five-point correlation function across the entire data selection. We measure significant redshift evolution in the higher-order functionals for the first time, with a percentage growth between redshift bins of approximately 20 % in both galactic caps. This is a nearly a factor of 2 greater than similar growth in the two-point correlation function and will allow for tests of non-linear structure growth by comparing the three-point and higher-order parts to their expected theoretical values. The SAO REU program is funded by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant AST-1659473, and by the Smithsonian Institution.

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

SU-G-TeP3-14: Three-Dimensional Cluster Model in Inhomogeneous Dose Distribution

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

Wei, J; Penagaricano, J; Narayanasamy, G

2016-06-15

Purpose: We aim to investigate 3D cluster formation in inhomogeneous dose distribution to search for new models predicting radiation tissue damage and further leading to new optimization paradigm for radiotherapy planning. Methods: The aggregation of higher dose in the organ at risk (OAR) than a preset threshold was chosen as the cluster whose connectivity dictates the cluster structure. Upon the selection of the dose threshold, the fractional density defined as the fraction of voxels in the organ eligible to be part of the cluster was determined according to the dose volume histogram (DVH). A Monte Carlo method was implemented tomore » establish a case pertinent to the corresponding DVH. Ones and zeros were randomly assigned to each OAR voxel with the sampling probability equal to the fractional density. Ten thousand samples were randomly generated to ensure a sufficient number of cluster sets. A recursive cluster searching algorithm was developed to analyze the cluster with various connectivity choices like 1-, 2-, and 3-connectivity. The mean size of the largest cluster (MSLC) from the Monte Carlo samples was taken to be a function of the fractional density. Various OARs from clinical plans were included in the study. Results: Intensive Monte Carlo study demonstrates the inverse relationship between the MSLC and the cluster connectivity as anticipated and the cluster size does not change with fractional density linearly regardless of the connectivity types. An initially-slow-increase to exponential growth transition of the MSLC from low to high density was observed. The cluster sizes were found to vary within a large range and are relatively independent of the OARs. Conclusion: The Monte Carlo study revealed that the cluster size could serve as a suitable index of the tissue damage (percolation cluster) and the clinical outcome of the same DVH might be potentially different.« less

Deposition of Size-Selected Cu Nanoparticles by Inert Gas Condensation

PubMed Central

2010-01-01

Nanometer size-selected Cu clusters in the size range of 1–5 nm have been produced by a plasma-gas-condensation-type cluster deposition apparatus, which combines a grow-discharge sputtering with an inert gas condensation technique. With this method, by controlling the experimental conditions, it was possible to produce nanoparticles with a strict control in size. The structure and size of Cu nanoparticles were determined by mass spectroscopy and confirmed by atomic force microscopy (AFM) and scanning electron transmission microscopy (STEM) measurements. In order to preserve the structural and morphological properties, the energy of cluster impact was controlled; the energy of acceleration of the nanoparticles was in near values at 0.1 ev/atom for being in soft landing regime. From SEM measurements developed in STEM-HAADF mode, we found that nanoparticles are near sized to those values fixed experimentally also confirmed by AFM observations. The results are relevant, since it demonstrates that proper optimization of operation conditions can lead to desired cluster sizes as well as desired cluster size distributions. It was also demonstrated the efficiency of the method to obtain size-selected Cu clusters films, as a random stacking of nanometer-size crystallites assembly. The deposition of size-selected metal clusters represents a novel method of preparing Cu nanostructures, with high potential in optical and catalytic applications. PMID:20652132

An approach to functionally relevant clustering of the protein universe: Active site profile‐based clustering of protein structures and sequences

PubMed Central

Knutson, Stacy T.; Westwood, Brian M.; Leuthaeuser, Janelle B.; Turner, Brandon E.; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D.; Harper, Angela F.; Brown, Shoshana D.; Morris, John H.; Ferrin, Thomas E.; Babbitt, Patricia C.

2017-01-01

Abstract Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification—amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two‐Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure‐Function Linkage Database, SFLD) self‐identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self‐identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well‐curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP‐identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F‐measure and performance analysis on the enolase search results and comparison to GEMMA and SCI‐PHY demonstrate that TuLIP avoids the over‐division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. PMID:28054422

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Exploring Connectivity in Sequence Space of Functional RNA

NASA Technical Reports Server (NTRS)

Wei, Chenyu; Pohorille, Andrzej; Popovic, Milena; Ditzler, Mark

2017-01-01

Emergence of replicable genetic molecules was one of the marking points in the origin of life, evolution of which can be conceptualized as a walk through the space of all possible sequences. A theoretical concept of fitness landscape helps to understand evolutionary processes through assigning a value of fitness to each genotype. Then, evolution of a phenotype is viewed as a series of consecutive, single-point mutations. Natural selection biases evolution toward peaks of high fitness and away from valleys of low fitness. whereas neutral drift occurs in the sequence space without direction as mutations are introduced at random. Large networks of neutral or near-neutral mutations on a fitness landscape, especially for sufficiently long genomes, are possible or even inevitable. Their detection in experiments, however, has been elusive. Although a few near-neutral evolutionary pathways have been found, recent experimental evidence indicates landscapes consist of largely isolated islands. The generality of these results, however, is not clear, as the genome length or the fraction of functional molecules in the genotypic space might have been insufficient for the emergence of large, neutral networks. Thorough investigation on the structure of the fitness landscape is essential to understand the mechanisms of evolution of early genomes. RNA molecules are commonly assumed to play the pivotal role in the origin of genetic systems. They are widely believed to be early, if not the earliest, genetic and catalytic molecules, with abundant biochemical activities as aptamers and ribozymes, i.e. RNA molecules capable, respectively, to bind small molecules or catalyze chemical reactions. Here, we present results of our recent studies on the structure of the sequence space of RNA ligase ribozymes selected through in vitro evolution. Several hundred thousands of sequences active to a different degree were obtained by way of deep sequencing. Analysis of these sequences revealed several large clusters defined such that every sequence in a cluster can be reached from any other sequence in the same cluster through a series of single point mutations. Sequences in a single cluster appear to adopt more than one secondary structure. The mechanism of refolding within a single cluster was examined. To shed light on possible evolutionary paths in the space of ribozymes, the connectivity between clusters was investigated. The effect of length of RNA molecules on the structure of the fitness landscape and possible evolutionary paths was examined by way of comparing functional sequences of 20 and 80 nucleobases in length. It was found that sequences of different lengths shared secondary structure motifs that were presumed responsible for catalytic activity, with increasing complexity and global structural rearrangements emerging in longer molecules.

CLASH: Joint analysis of strong-lensing, weak-lensing shear, and magnification data for 20 galaxy clusters*

DOE PAGES

Umetsu, Keiichi; Zitrin, Adi; Gruen, Daniel; ...

2016-04-20

Here, we present a comprehensive analysis of strong-lensing, weak-lensing shear and magnification data for a sample of 16 X-ray-regular and 4 high-magnification galaxy clusters atmore » $$0.19\\lesssim z\\lesssim 0.69$$ selected from Cluster Lensing And Supernova survey with Hubble (CLASH). Our analysis combines constraints from 16-band Hubble Space Telescope observations and wide-field multi-color imaging taken primarily with Suprime-Cam on the Subaru Telescope, spanning a wide range of cluster radii (10''–16'). We reconstruct surface mass density profiles of individual clusters from a joint analysis of the full lensing constraints, and determine masses and concentrations for all of the clusters. We find the internal consistency of the ensemble mass calibration to be ≤5% ± 6% in the one-halo regime (200–2000 kpc h –1) compared to the CLASH weak-lensing-only measurements of Umetsu et al. For the X-ray-selected subsample of 16 clusters, we examine the concentration–mass (c–M) relation and its intrinsic scatter using a Bayesian regression approach. Our model yields a mean concentration of $$c{| }_{z=0.34}=3.95\\pm 0.35$$ at M200c sime 14 × 1014 M⊙ and an intrinsic scatter of $$\\sigma (\\mathrm{ln}{c}_{200{\\rm{c}}})=0.13\\pm 0.06$$, which is in excellent agreement with Λ cold dark matter predictions when the CLASH selection function based on X-ray morphological regularity and the projection effects are taken into account. We also derive an ensemble-averaged surface mass density profile for the X-ray-selected subsample by stacking their individual profiles. The stacked lensing signal is detected at 33σ significance over the entire radial range ≤4000 kpc h –1, accounting for the effects of intrinsic profile variations and uncorrelated large-scale structure along the line of sight. The stacked mass profile is well described by a family of density profiles predicted for cuspy dark-matter-dominated halos in gravitational equilibrium, namely, the Navarro–Frenk–White (NFW), Einasto, and DARKexp models, whereas the single power-law, cored isothermal and Burkert density profiles are disfavored by the data. We show that cuspy halo models that include the large-scale two-halo term provide improved agreement with the data. For the NFW halo model, we measure a mean concentration of $${c}_{200{\\rm{c}}}={3.79}_{-0.28}^{+0.30}$$ at $${M}_{200{\\rm{c}}}={14.1}_{-1.0}^{+1.0}\\times {10}^{14}\\;{M}_{\\odot }$$, demonstrating consistency between the complementary analysis methods.« less

Specific Contributions of Ventromedial, Anterior Cingulate, and Lateral Prefrontal Cortex for Attentional Selection and Stimulus Valuation

PubMed Central

Kaping, Daniel; Vinck, Martin; Hutchison, R. Matthew; Everling, Stefan; Womelsdorf, Thilo

2011-01-01

Attentional control ensures that neuronal processes prioritize the most relevant stimulus in a given environment. Controlling which stimulus is attended thus originates from neurons encoding the relevance of stimuli, i.e. their expected value, in hand with neurons encoding contextual information about stimulus locations, features, and rules that guide the conditional allocation of attention. Here, we examined how these distinct processes are encoded and integrated in macaque prefrontal cortex (PFC) by mapping their functional topographies at the time of attentional stimulus selection. We find confined clusters of neurons in ventromedial PFC (vmPFC) that predominantly convey stimulus valuation information during attention shifts. These valuation signals were topographically largely separated from neurons predicting the stimulus location to which attention covertly shifted, and which were evident across the complete medial-to-lateral extent of the PFC, encompassing anterior cingulate cortex (ACC), and lateral PFC (LPFC). LPFC responses showed particularly early-onset selectivity and primarily facilitated attention shifts to contralateral targets. Spatial selectivity within ACC was delayed and heterogeneous, with similar proportions of facilitated and suppressed responses during contralateral attention shifts. The integration of spatial and valuation signals about attentional target stimuli was observed in a confined cluster of neurons at the intersection of vmPFC, ACC, and LPFC. These results suggest that valuation processes reflecting stimulus-specific outcome predictions are recruited during covert attentional control. Value predictions and the spatial identification of attentional targets were conveyed by largely separate neuronal populations, but were integrated locally at the intersection of three major prefrontal areas, which may constitute a functional hub within the larger attentional control network. PMID:22215982

GAtor: A First-Principles Genetic Algorithm for Molecular Crystal Structure Prediction.

PubMed

Curtis, Farren; Li, Xiayue; Rose, Timothy; Vázquez-Mayagoitia, Álvaro; Bhattacharya, Saswata; Ghiringhelli, Luca M; Marom, Noa

2018-04-10

We present the implementation of GAtor, a massively parallel, first-principles genetic algorithm (GA) for molecular crystal structure prediction. GAtor is written in Python and currently interfaces with the FHI-aims code to perform local optimizations and energy evaluations using dispersion-inclusive density functional theory (DFT). GAtor offers a variety of fitness evaluation, selection, crossover, and mutation schemes. Breeding operators designed specifically for molecular crystals provide a balance between exploration and exploitation. Evolutionary niching is implemented in GAtor by using machine learning to cluster the dynamically updated population by structural similarity and then employing a cluster-based fitness function. Evolutionary niching promotes uniform sampling of the potential energy surface by evolving several subpopulations, which helps overcome initial pool biases and selection biases (genetic drift). The various settings offered by GAtor increase the likelihood of locating numerous low-energy minima, including those located in disconnected, hard to reach regions of the potential energy landscape. The best structures generated are re-relaxed and re-ranked using a hierarchy of increasingly accurate DFT functionals and dispersion methods. GAtor is applied to a chemically diverse set of four past blind test targets, characterized by different types of intermolecular interactions. The experimentally observed structures and other low-energy structures are found for all four targets. In particular, for Target II, 5-cyano-3-hydroxythiophene, the top ranked putative crystal structure is a Z' = 2 structure with P1̅ symmetry and a scaffold packing motif, which has not been reported previously.

Statistical thermodynamics of clustered populations.

PubMed

Matsoukas, Themis

2014-08-01

We present a thermodynamic theory for a generic population of M individuals distributed into N groups (clusters). We construct the ensemble of all distributions with fixed M and N, introduce a selection functional that embodies the physics that governs the population, and obtain the distribution that emerges in the scaling limit as the most probable among all distributions consistent with the given physics. We develop the thermodynamics of the ensemble and establish a rigorous mapping to regular thermodynamics. We treat the emergence of a so-called giant component as a formal phase transition and show that the criteria for its emergence are entirely analogous to the equilibrium conditions in molecular systems. We demonstrate the theory by an analytic model and confirm the predictions by Monte Carlo simulation.

Selection of intracellular calcium patterns in a model with clustered Ca2+ release channels

NASA Astrophysics Data System (ADS)

Shuai, J. W.; Jung, P.

2003-03-01

A two-dimensional model is proposed for intracellular Ca2+ waves, which incorporates both the discrete nature of Ca2+ release sites in the endoplasmic reticulum membrane and the stochastic dynamics of the clustered inositol 1,4,5-triphosphate (IP3) receptors. Depending on the Ca2+ diffusion coefficient and concentration of IP3, various spontaneous Ca2+ patterns, such as calcium puffs, local waves, abortive waves, global oscillation, and tide waves, can be observed. We further investigate the speed of the global waves as a function of the IP3 concentration and the Ca2+ diffusion coefficient and under what conditions the spatially averaged Ca2+ response can be described by a simple set of ordinary differential equations.

X-Ray Properties of Lensing-Selected Clusters

NASA Astrophysics Data System (ADS)

Paterno-Mahler, Rachel; Sharon, Keren; Bayliss, Matthew; McDonald, Michael; Gladders, Michael; Johnson, Traci; Dahle, Hakon; Rigby, Jane R.; Whitaker, Katherine E.; Florian, Michael; Wuyts, Eva

2017-08-01

I will present preliminary results from the Michigan Swift X-ray observations of clusters from the Sloan Giant Arcs Survey (SGAS). These clusters were lensing selected based on the presence of a giant arc visible from SDSS. I will characterize the morphology of the intracluster medium (ICM) of the clusters in the sample, and discuss the offset between the X-ray centroid, the mass centroid as determined by strong lensing analysis, and the BCG position. I will also present early-stage work on the scaling relation between the lensing mass and the X-ray luminosity.

The ACS Survey of Galactic Globular Clusters. VIII. Effects of Environment on Globular Cluster Global Mass Functions

NASA Astrophysics Data System (ADS)

Paust, Nathaniel E. Q.; Reid, I. Neill; Piotto, Giampaolo; Aparicio, Antonio; Anderson, Jay; Sarajedini, Ata; Bedin, Luigi R.; Chaboyer, Brian; Dotter, Aaron; Hempel, Maren; Majewski, Steven; Marín-Franch, A.; Milone, Antonino; Rosenberg, Alfred; Siegel, Michael

2010-02-01

We have used observations obtained as part of the Hubble Space Telescope/ACS Survey of Galactic Globular Clusters to construct global present-day mass functions for 17 globular clusters utilizing multi-mass King models to extrapolate from our observations to the global cluster behavior. The global present-day mass functions for these clusters are well matched by power laws from the turnoff, ≈0.8 M sun, to 0.2-0.3 M sun on the lower main sequence. The slopes of those power-law fits, α, have been correlated with an extensive set of intrinsic and extrinsic cluster properties to investigate which parameters may influence the form of the present-day mass function. We do not confirm previous suggestions of correlations between α and either metallicity or Galactic location. However, we do find a strong statistical correlation with the related parameters central surface brightness, μ V , and inferred central density, ρ0. The correlation is such that clusters with denser cores (stronger binding energy) tend to have steeper mass functions (a higher proportion of low-mass stars), suggesting that dynamical evolution due to external interactions may have played a key role in determining α. Thus, the present-day mass function may owe more to nurture than to nature. Detailed modeling of external dynamical effects is therefore a requisite for determining the initial mass function for Galactic globular clusters.

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

NASA Technical Reports Server (NTRS)

Bahcall, Neta A.; Cen, Renyue

1992-01-01

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

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

Novel Rhizosphere Soil Alleles for the Enzyme 1-Aminocyclopropane-1-Carboxylate Deaminase Queried for Function with an In Vivo Competition Assay

PubMed Central

Jin, Zhao; Di Rienzi, Sara C.; Janzon, Anders; Werner, Jeff J.; Angenent, Largus T.; Dangl, Jeffrey L.; Fowler, Douglas M.

2015-01-01

Metagenomes derived from environmental microbiota encode a vast diversity of protein homologs. How this diversity impacts protein function can be explored through selection assays aimed to optimize function. While artificially generated gene sequence pools are typically used in selection assays, their usage may be limited because of technical or ethical reasons. Here, we investigate an alternative strategy, the use of soil microbial DNA as a starting point. We demonstrate this approach by optimizing the function of a widely occurring soil bacterial enzyme, 1-aminocyclopropane-1-carboxylate (ACC) deaminase. We identified a specific ACC deaminase domain region (ACCD-DR) that, when PCR amplified from the soil, produced a variant pool that we could swap into functional plasmids carrying ACC deaminase-encoding genes. Functional clones of ACC deaminase were selected for in a competition assay based on their capacity to provide nitrogen to Escherichia coli in vitro. The most successful ACCD-DR variants were identified after multiple rounds of selection by sequence analysis. We observed that previously identified essential active-site residues were fixed in the original unselected library and that additional residues went to fixation after selection. We identified a divergent essential residue whose presence hints at the possible use of alternative substrates and a cluster of neutral residues that did not influence ACCD performance. Using an artificial ACCD-DR variant library generated by DNA oligomer synthesis, we validated the same fixation patterns. Our study demonstrates that soil metagenomes are useful starting pools of protein-coding-gene diversity that can be utilized for protein optimization and functional characterization when synthetic libraries are not appropriate. PMID:26637602

Cluster Ion Spectrometry (CIS) Data Archiving in the CAA

NASA Astrophysics Data System (ADS)

Dandouras, I. S.; Barthe, A.; Penou, E.; Brunato, S.; Reme, H.; Kistler, L. M.; Blagau, A.; Facsko, G.; Kronberg, E.; Laakso, H. E.

2009-12-01

The Cluster Active Archive (CAA) aims at preserving the four Cluster spacecraft data, so that they are usable in the long-term by the scientific community as well as by the instrument team PIs and Co-Is. This implies that the data are filed together with the descriptive and documentary elements making it possible to select and interpret them. The CIS (Cluster Ion Spectrometry) experiment is a comprehensive ionic plasma spectrometry package onboard the four Cluster spacecraft, capable of obtaining full three-dimensional ion distributions (about 0 to 40 keV/e) with a time resolution of one spacecraft spin (4 sec) and with mass-per-charge composition determination. The CIS package consists of two different instruments, a Hot Ion Analyser (HIA) and a time-of-flight ion Composition Distribution Function (CODIF) analyser. For the archival of the CIS data a multi-level approach has been adopted. The CAA archival includes processed raw data (Level 1 data), moments of the ion distribution functions (Level 2 data), and calibrated high-resolution data in a variety of physical units (Level 3 data). The latter are 3-D ion distribution functions and 2-D pitch-angle distributions. In addition, a software package has been developed to allow the CAA user to interactively calculate partial or total moments of the ion distributions. Instrument cross-calibration has been an important activity in preparing the data for archival. The CIS data archive includes also experiment documentation, graphical products for browsing through the data, and data caveats. In addition, data quality indexes are under preparation, to help the user. Given the complexity of an ion spectrometer, and the variety of its operational modes, each one being optimised for a different magnetospheric region or measurement objective, consultation of the data caveats by the end user will always be a necessary step in the data analysis.

Slicing cluster mass functions with a Bayesian razor

NASA Astrophysics Data System (ADS)

Sealfon, C. D.

2010-08-01

We apply a Bayesian ``razor" to forecast Bayes factors between different parameterizations of the galaxy cluster mass function. To demonstrate this approach, we calculate the minimum size N-body simulation needed for strong evidence favoring a two-parameter mass function over one-parameter mass functions and visa versa, as a function of the minimum cluster mass.

VizieR Online Data Catalog: LAMOST survey of star clusters in M31. II. (Chen+, 2016)

NASA Astrophysics Data System (ADS)

Chen, B.; Liu, X.; Xiang, M.; Yuan, H.; Huang, Y.; Shi, J.; Fan, Z.; Huo, Z.; Wang, C.; Ren, J.; Tian, Z.; Zhang, H.; Liu, G.; Cao, Z.; Zhang, Y.; Hou, Y.; Wang, Y.

2016-09-01

We select a sample of 306 massive star clusters observed with the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) in the vicinity fields of M31 and M33. Massive clusters in our sample are all selected from the catalog presented in Paper I (Chen et al. 2015, Cat. J/other/RAA/15.1392), including five newly discovered clusters selected with the SDSS photometry, three newly confirmed, and 298 previously known clusters from Revised Bologna Catalogue (RBC; Galleti et al. 2012, Cat. V/143; http://www.bo.astro.it/M31/). Since then another two objects, B341 and B207, have also been observed with LAMOST, and they are included in the current analysis. The current sample does not include those listed in Paper I but is selected from Johnson et al. 2012 (Cat. J/ApJ/752/95) since most of them are young but not so massive. All objects are observed with LAMOST between 2011 September and 2014 June. Table1 lists the name, position, and radial velocity of all sample clusters analyzed in the current work. The LAMOST spectra cover the wavelength range 3700-9000Å at a resolving power of R~1800. Details about the observations and data reduction can be found in Paper I. The median signal-to-noise ratio (S/N) per pixel at 4750 and 7450Å of spectra of all clusters in the current sample are, respectively, 14 and 37. Essentially all spectra have S/N(4750Å)>5 except for the spectra of 18 clusters. The latter have S/N(7540Å)>10. Peacock et al. 2010 (Cat. J/MNRAS/402/803) retrieved images of M31 star clusters and candidates from the SDSS archive and extracted ugriz aperture photometric magnitudes from those objects using the SExtractor. They present a catalog containing homogeneous ugriz photometry of 572 star clusters and 373 candidates. Among them, 299 clusters are in our sample. (2 data files).

CLASH: Weak-lensing shear-and-magnification analysis of 20 galaxy clusters

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

Umetsu, Keiichi; Czakon, Nicole; Medezinski, Elinor

2014-11-10

We present a joint shear-and-magnification weak-lensing analysis of a sample of 16 X-ray-regular and 4 high-magnification galaxy clusters at 0.19 ≲ z ≲ 0.69 selected from the Cluster Lensing And Supernova survey with Hubble (CLASH). Our analysis uses wide-field multi-color imaging, taken primarily with Suprime-Cam on the Subaru Telescope. From a stacked-shear-only analysis of the X-ray-selected subsample, we detect the ensemble-averaged lensing signal with a total signal-to-noise ratio of ≅ 25 in the radial range of 200-3500 kpc h {sup –1}, providing integrated constraints on the halo profile shape and concentration-mass relation. The stacked tangential-shear signal is well described bymore » a family of standard density profiles predicted for dark-matter-dominated halos in gravitational equilibrium, namely, the Navarro-Frenk-White (NFW), truncated variants of NFW, and Einasto models. For the NFW model, we measure a mean concentration of c{sub 200c}=4.01{sub −0.32}{sup +0.35} at an effective halo mass of M{sub 200c}=1.34{sub −0.09}{sup +0.10}×10{sup 15} M{sub ⊙}. We show that this is in excellent agreement with Λ cold dark matter (ΛCDM) predictions when the CLASH X-ray selection function and projection effects are taken into account. The best-fit Einasto shape parameter is α{sub E}=0.191{sub −0.068}{sup +0.071}, which is consistent with the NFW-equivalent Einasto parameter of ∼0.18. We reconstruct projected mass density profiles of all CLASH clusters from a joint likelihood analysis of shear-and-magnification data and measure cluster masses at several characteristic radii assuming an NFW density profile. We also derive an ensemble-averaged total projected mass profile of the X-ray-selected subsample by stacking their individual mass profiles. The stacked total mass profile, constrained by the shear+magnification data, is shown to be consistent with our shear-based halo-model predictions, including the effects of surrounding large-scale structure as a two-halo term, establishing further consistency in the context of the ΛCDM model.« less

Description of an α-cluster tail in 8Be and 20Ne: Delocalization of the α cluster by quantum penetration

NASA Astrophysics Data System (ADS)

Kanada-En'yo, Yoshiko

2014-10-01

We analyze the α-cluster wave functions in cluster states of ^8Be and ^{20}Ne by comparing the exact relative wave function obtained by the generator coordinate method (GCM) with various types of trial functions. For the trial functions, we adopt the fixed range shifted Gaussian of the Brink-Bloch (BB) wave function, the spherical Gaussian with the adjustable range parameter of the spherical Tohsaki-Horiuchi-Schuck-Röpke (sTHSR), the deformed Gaussian of the deformed THSR (dTHSR), and a function with the Yukawa tail (YT). The quality of the description of the exact wave function with a trial function is judged by the squared overlap between the trial function and the GCM wave function. A better result is obtained with the sTHSR wave function than the BB wave function, and further improvement can be made with the dTHSR wave function because these wave functions can describe the outer tail better. The YT wave function gives almost an equal quality to or even better quality than the dTHSR wave function, indicating that the outer tail of α-cluster states is characterized by the Yukawa-like tail rather than the Gaussian tail. In weakly bound α-cluster states with small α separation energy and the low centrifugal and Coulomb barriers, the outer tail part is the slowly damping function described well by the quantum penetration through the effective barrier. This outer tail characterizes the almost zero-energy free α gas behavior, i.e., the delocalization of the cluster.

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

PubMed Central

Ahmed, Gulnaz; Zou, Jianhua; Zhao, Xi; Sadiq Fareed, Mian Muhammad

2017-01-01

The longer network lifetime of Wireless Sensor Networks (WSNs) is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs) selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED) clustering, Artificial Bee Colony (ABC), Zone Based Routing (ZBR), and Centralized Energy Efficient Clustering (CEEC) using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps) greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput. PMID:28241492

Single-site trinuclear copper oxygen clusters in mordenite for selective conversion of methane to methanol.

PubMed

Grundner, Sebastian; Markovits, Monica A C; Li, Guanna; Tromp, Moniek; Pidko, Evgeny A; Hensen, Emiel J M; Jentys, Andreas; Sanchez-Sanchez, Maricruz; Lercher, Johannes A

2015-06-25

Copper-exchanged zeolites with mordenite structure mimic the nuclearity and reactivity of active sites in particulate methane monooxygenase, which are enzymes able to selectively oxidize methane to methanol. Here we show that the mordenite micropores provide a perfect confined environment for the highly selective stabilization of trinuclear copper-oxo clusters that exhibit a high reactivity towards activation of carbon-hydrogen bonds in methane and its subsequent transformation to methanol. The similarity with the enzymatic systems is also implied from the similarity of the reversible rearrangements of the trinuclear clusters occurring during the selective transformations of methane along the reaction path towards methanol, in both the enzyme system and copper-exchanged mordenite.

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.

A regularized clustering approach to brain parcellation from functional MRI data

NASA Astrophysics Data System (ADS)

Dillon, Keith; Wang, Yu-Ping

2017-08-01

We consider a data-driven approach for the subdivision of an individual subject's functional Magnetic Resonance Imaging (fMRI) scan into regions of interest, i.e., brain parcellation. The approach is based on a computational technique for calculating resolution from inverse problem theory, which we apply to neighborhood selection for brain connectivity networks. This can be efficiently calculated even for very large images, and explicitly incorporates regularization in the form of spatial smoothing and a noise cutoff. We demonstrate the reproducibility of the method on multiple scans of the same subjects, as well as the variations between subjects.

On the universality of the two-point galaxy correlation function

NASA Technical Reports Server (NTRS)

Davis, Marc; Meiksin, Avery; Strauss, Michael A.; Da Costa, L. Nicolaci; Yahil, Amos

1988-01-01

The behavior of the two-point galaxy correlation function in volume-limited subsamples of three complete redshift surveys is investigated. The correlation length is shown to scale approximately as the square root of the distance limit in both the CfA and Southern Sky catalogs, but to be independent of the distance limit in the IRAS sample. This effect is found to be due to factors such as the large positive density fluctuations in the foreground of the optically selected catalogs biasing the correlation length estimate downward, and the brightest galaxies appearing to be more strongly clustered than the mean.

Efficacy of community-based physiotherapy networks for patients with Parkinson's disease: a cluster-randomised trial.

PubMed

Munneke, Marten; Nijkrake, Maarten J; Keus, Samyra Hj; Kwakkel, Gert; Berendse, Henk W; Roos, Raymund Ac; Borm, George F; Adang, Eddy M; Overeem, Sebastiaan; Bloem, Bastiaan R

2010-01-01

Many patients with Parkinson's disease are treated with physiotherapy. We have developed a community-based professional network (ParkinsonNet) that involves training of a selected number of expert physiotherapists to work according to evidence-based recommendations, and structured referrals to these trained physiotherapists to increase the numbers of patients they treat. We aimed to assess the efficacy of this approach for improving health-care outcomes. Between February, 2005, and August, 2007, we did a cluster-randomised trial with 16 clusters (defined as community hospitals and their catchment area). Clusters were randomly allocated by use of a variance minimisation algorithm to ParkinsonNet care (n=8) or usual care (n=8). Patients were assessed at baseline and at 8, 16, and 24 weeks of follow-up. The primary outcome was a patient preference disability score, the patient-specific index score, at 16 weeks. Health secondary outcomes were functional mobility, mobility-related quality of life, and total societal costs over 24 weeks. Analysis was by intention to treat. This trial is registered, number NCT00330694. We included 699 patients. Baseline characteristics of the patients were comparable between the ParkinsonNet clusters (n=358) and usual-care clusters (n=341). The primary endpoint was similar for patients within the ParkinsonNet clusters (mean 47.7, SD 21.9) and control clusters (48.3, 22.4). Health secondary endpoints were also similar for patients in both study groups. Total costs over 24 weeks were lower in ParkinsonNet clusters compared with usual-care clusters (difference euro727; 95% CI 56-1399). Implementation of ParkinsonNet networks did not change health outcomes for patients living in ParkinsonNet clusters. However, health-care costs were reduced in ParkinsonNet clusters compared with usual-care clusters. ZonMw; Netherlands Organisation for Scientific Research; Dutch Parkinson's Disease Society; National Parkinson Foundation; Stichting Robuust. Copyright 2010 Elsevier Ltd. All rights reserved.

Galaxy clustering dependence on the [O II] emission line luminosity in the local Universe

NASA Astrophysics Data System (ADS)

Favole, Ginevra; Rodríguez-Torres, Sergio A.; Comparat, Johan; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Montero-Dorta, Antonio D.

2017-11-01

We study the galaxy clustering dependence on the [O II] emission line luminosity in the SDSS DR7 Main galaxy sample at mean redshift z ∼ 0.1. We select volume-limited samples of galaxies with different [O II] luminosity thresholds and measure their projected, monopole and quadrupole two-point correlation functions. We model these observations using the 1 h-1 Gpc MultiDark-Planck cosmological simulation and generate light cones with the SUrvey GenerAtoR algorithm. To interpret our results, we adopt a modified (Sub)Halo Abundance Matching scheme, accounting for the stellar mass incompleteness of the emission line galaxies. The satellite fraction constitutes an extra parameter in this model and allows to optimize the clustering fit on both small and intermediate scales (i.e. rp ≲ 30 h-1 Mpc), with no need of any velocity bias correction. We find that, in the local Universe, the [O II] luminosity correlates with all the clustering statistics explored and with the galaxy bias. This latter quantity correlates more strongly with the SDSS r-band magnitude than [O II] luminosity. In conclusion, we propose a straightforward method to produce reliable clustering models, entirely built on the simulation products, which provides robust predictions of the typical ELG host halo masses and satellite fraction values. The SDSS galaxy data, MultiDark mock catalogues and clustering results are made publicly available.

A cluster-based strategy for assessing the overlap between large chemical libraries and its application to a recent acquisition.

PubMed

Engels, Michael F M; Gibbs, Alan C; Jaeger, Edward P; Verbinnen, Danny; Lobanov, Victor S; Agrafiotis, Dimitris K

2006-01-01

We report on the structural comparison of the corporate collections of Johnson & Johnson Pharmaceutical Research & Development (JNJPRD) and 3-Dimensional Pharmaceuticals (3DP), performed in the context of the recent acquisition of 3DP by JNJPRD. The main objective of the study was to assess the druglikeness of the 3DP library and the extent to which it enriched the chemical diversity of the JNJPRD corporate collection. The two databases, at the time of acquisition, collectively contained more than 1.1 million compounds with a clearly defined structural description. The analysis was based on a clustering approach and aimed at providing an intuitive quantitative estimate and visual representation of this enrichment. A novel hierarchical clustering algorithm called divisive k-means was employed in combination with Kelley's cluster-level selection method to partition the combined data set into clusters, and the diversity contribution of each library was evaluated as a function of the relative occupancy of these clusters. Typical 3DP chemotypes enriching the diversity of the JNJPRD collection were catalogued and visualized using a modified maximum common substructure algorithm. The joint collection of JNJPRD and 3DP compounds was also compared to other databases of known medicinally active or druglike compounds. The potential of the methodology for the analysis of very large chemical databases is discussed.

An ensemble framework for clustering protein-protein interaction networks.

PubMed

Asur, Sitaram; Ucar, Duygu; Parthasarathy, Srinivasan

2007-07-01

Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network. In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins. Supplementary data are available at Bioinformatics online.

Spectroscopic Confirmation of Two Massive Red-sequence-selected Galaxy Clusters at Z Approximately Equal to 1.2 in the Sparcs-North Cluster Survey

NASA Technical Reports Server (NTRS)

Muzzin, Adam; Wilson, Gillian; Yee, H.K.C.; Hoekstra, Henk; Gilbank, David; Surace, Jason; Lacy, Mark; Blindert, Kris; Majumdar, Subhabrata; Demarco, Ricardo;

Marine Microbial Secondary Metabolites: Pathways, Evolution and Physiological Roles.

PubMed

Giordano, Daniela; Coppola, Daniela; Russo, Roberta; Denaro, Renata; Giuliano, Laura; Lauro, Federico M; di Prisco, Guido; Verde, Cinzia

2015-01-01

Microbes produce a huge array of secondary metabolites endowed with important ecological functions. These molecules, which can be catalogued as natural products, have long been exploited in medical fields as antibiotics, anticancer and anti-infective agents. Recent years have seen considerable advances in elucidating natural-product biosynthesis and many drugs used today are natural products or natural-product derivatives. The major contribution to recent knowledge came from application of genomics to secondary metabolism and was facilitated by all relevant genes being organised in a contiguous DNA segment known as gene cluster. Clustering of genes regulating biosynthesis in bacteria is virtually universal. Modular gene clusters can be mixed and matched during evolution to generate structural diversity in natural products. Biosynthesis of many natural products requires the participation of complex molecular machines known as polyketide synthases and non-ribosomal peptide synthetases. Discovery of new evolutionary links between the polyketide synthase and fatty acid synthase pathways may help to understand the selective advantages that led to evolution of secondary-metabolite biosynthesis within bacteria. Secondary metabolites confer selective advantages, either as antibiotics or by providing a chemical language that allows communication among species, with other organisms and their environment. Herewith, we discuss these aspects focusing on the most clinically relevant bioactive molecules, the thiotemplated modular systems that include polyketide synthases, non-ribosomal peptide synthetases and fatty acid synthases. We begin by describing the evolutionary and physiological role of marine natural products, their structural/functional features, mechanisms of action and biosynthesis, then turn to genomic and metagenomic approaches, highlighting how the growing body of information on microbial natural products can be used to address fundamental problems in environmental evolution and biotechnology. © 2015 Elsevier Ltd. All rights reserved.

The ALHAMBRA survey: evolution of galaxy clustering since z ˜ 1

NASA Astrophysics Data System (ADS)

Arnalte-Mur, P.; Martínez, V. J.; Norberg, P.; Fernández-Soto, A.; Ascaso, B.; Merson, A. I.; Aguerri, J. A. L.; Castander, F. J.; Hurtado-Gil, L.; López-Sanjuan, C.; Molino, A.; Montero-Dorta, A. D.; Stefanon, M.; Alfaro, E.; Aparicio-Villegas, T.; Benítez, N.; Broadhurst, T.; Cabrera-Caño, J.; Cepa, J.; Cerviño, M.; Cristóbal-Hornillos, D.; del Olmo, A.; González Delgado, R. M.; Husillos, C.; Infante, L.; Márquez, I.; Masegosa, J.; Moles, M.; Perea, J.; Pović, M.; Prada, F.; Quintana, J. M.

2014-06-01

We study the clustering of galaxies as function of luminosity and redshift in the range 0.35 < z < 1.25 using data from the Advanced Large Homogeneous Area Medium-Band Redshift Astronomical (ALHAMBRA) survey. The ALHAMBRA data used in this work cover 2.38 deg2 in seven independent fields, after applying a detailed angular selection mask, with accurate photometric redshifts, σz ≲ 0.014(1 + z), down to IAB < 24. Given the depth of the survey, we select samples in B-band luminosity down to Lth ≃ 0.16L* at z = 0.9. We measure the real-space clustering using the projected correlation function, accounting for photometric redshifts uncertainties. We infer the galaxy bias, and study its evolution with luminosity. We study the effect of sample variance, and confirm earlier results that the Cosmic Evolution Survey (COSMOS) and European Large Area ISO Survey North 1 (ELAIS-N1) fields are dominated by the presence of large structures. For the intermediate and bright samples, Lmed ≳ 0.6L*, we obtain a strong dependence of bias on luminosity, in agreement with previous results at similar redshift. We are able to extend this study to fainter luminosities, where we obtain an almost flat relation, similar to that observed at low redshift. Regarding the evolution of bias with redshift, our results suggest that the different galaxy populations studied reside in haloes covering a range in mass between log10[Mh/( h-1 M⊙)] ≳ 11.5 for samples with Lmed ≃ 0.3L* and log10[Mh/( h-1 M⊙)] ≳ 13.0 for samples with Lmed ≃ 2L*, with typical occupation numbers in the range of ˜1-3 galaxies per halo.

1,003 reference genomes of bacterial and archaeal isolates expand coverage of the tree of life

DOE PAGES

Mukherjee, Supratim; Seshadri, Rekha; Varghese, Neha J.; ...

2017-06-12

We present 1,003 reference genomes that were sequenced as part of the Genomic Encyclopedia of Bacteria and Archaea (GEBA) initiative, selected to maximize sequence coverage of phylogenetic space. These genomes double the number of existing type strains and expand their overall phylogenetic diversity by 25%. Comparative analyses with previously available finished and draft genomes reveal a 10.5% increase in novel protein families as a function of phylogenetic diversity. The GEBA genomes recruit 25 million previously unassigned metagenomic proteins from 4,650 samples, improving their phylogenetic and functional interpretation. We identify numerous biosynthetic clusters and experimentally validate a divergent phenazine cluster withmore » potential new chemical structure and antimicrobial activity. This Resource is the largest single release of reference genomes to date. Bacterial and archaeal isolate sequence space is still far from saturated, and future endeavors in this direction will continue to be a valuable resource for scientific discovery.« less

1,003 reference genomes of bacterial and archaeal isolates expand coverage of the tree of life

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

Mukherjee, Supratim; Seshadri, Rekha; Varghese, Neha J.

We present 1,003 reference genomes that were sequenced as part of the Genomic Encyclopedia of Bacteria and Archaea (GEBA) initiative, selected to maximize sequence coverage of phylogenetic space. These genomes double the number of existing type strains and expand their overall phylogenetic diversity by 25%. Comparative analyses with previously available finished and draft genomes reveal a 10.5% increase in novel protein families as a function of phylogenetic diversity. The GEBA genomes recruit 25 million previously unassigned metagenomic proteins from 4,650 samples, improving their phylogenetic and functional interpretation. We identify numerous biosynthetic clusters and experimentally validate a divergent phenazine cluster withmore » potential new chemical structure and antimicrobial activity. This Resource is the largest single release of reference genomes to date. Bacterial and archaeal isolate sequence space is still far from saturated, and future endeavors in this direction will continue to be a valuable resource for scientific discovery.« less

An Overview on Indications and Chemical Composition of Aromatic Waters (Hydrosols) as Functional Beverages in Persian Nutrition Culture and Folk Medicine for Hyperlipidemia and Cardiovascular Conditions

PubMed Central

Hamedi, Azadeh; Moheimani, Seyed Mahmoud; Sakhteman, Amirhossein; Etemadfard, Hamed; Moein, Mahmoodreza

2017-01-01

Hydrosol beverages in Persian nutrition culture and ethnomedicine are the side products of essential oil industry that are used as delicious drinks or safe remedies. To investigate indications and chemical composition of hydrosol beverages for hyperlipidemia and cardiovascular conditions, Fars province was selected as the field of study. Ethnomedical data were gathered by questionnaires. The constituents of hydrosols were extracted with liquid/liquid extraction and analyzed by gas chromatography–mass spectrometry. Statistical analysis were used to cluster their constituents and find the relevance of their composition. A literature survey was also performed on plants used to prepare them. Thymol was the major or second major component of these beverages, except for wormwood and olive leaf hydrosols. Based on clustering methods, although some similarities could be found, composition of barberry, will fumitory, dill, and aloe hydrosols have more differences than others. These studies may help in developing some functional beverages or new therapeutics. PMID:29228785

Beyond the plane-parallel approximation for redshift surveys

NASA Astrophysics Data System (ADS)

Castorina, Emanuele; White, Martin

2018-06-01

Redshift -space distortions privilege the location of the observer in cosmological redshift surveys, breaking the translational symmetry of the underlying theory. This violation of statistical homogeneity has consequences for the modelling of clustering observables, leading to what are frequently called `wide-angle effects'. We study these effects analytically, computing their signature in the clustering of the multipoles in configuration and Fourier space. We take into account both physical wide-angle contributions as well as the terms generated by the galaxy selection function. Similar considerations also affect the way power spectrum estimators are constructed. We quantify in an analytical way the biases that enter and clarify the relation between what we measure and the underlying theoretical modelling. The presence of an angular window function is also discussed. Motivated by this analysis, we present new estimators for the three dimensional Cartesian power spectrum and bispectrum multipoles written in terms of spherical Fourier-Bessel coefficients. We show how the latter have several interesting properties, allowing in particular a clear separation between angular and radial modes.

Moderating effect of intrinsic religiosity on the relationship between depression and cognitive function among community-dwelling older adults.

PubMed

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah

2018-04-01

Research has found that depression in later life is associated with cognitive impairment. Thus, the mechanism to reduce the effect of depression on cognitive function is warranted. In this paper, we intend to examine whether intrinsic religiosity mediates the association between depression and cognitive function. The study included 2322 nationally representative community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, cognitive function, depression and intrinsic religiosity. A four-step moderated hierarchical regression analysis was employed to test the moderating effect. Statistical analyses were performed using SPSS (version 15.0). Bivariate analyses showed that both depression and intrinsic religiosity had significant relationships with cognitive function. In addition, four-step moderated hierarchical regression analysis revealed that the intrinsic religiosity moderated the association between depression and cognitive function, after controlling for selected socio-demographic characteristics. Intrinsic religiosity might reduce the negative effect of depression on cognitive function. Professionals who are working with depressed older adults should seek ways to improve their intrinsic religiosity as one of the strategies to prevent cognitive impairment.

The Reactivity and Structure of Size Selected VxO y Clusters on a TiO2 (110)-(1 X 1) Surface of Variable Oxidation State

NASA Astrophysics Data System (ADS)

Neilson, Hunter L.

The Reactivity and Structure of Size Selected VxOy Clusters on a TiO2 (110) Surface of Variable Oxidation State by Hunter L Neilson The selective oxidative dehydrogenation of methanol by vanadium oxide/TiO2 model systems has received a great deal of interest in the surface science community. Previous studies using temperature programmed desorption and reaction (TPD/R) to probe the oxidation of methanol to formaldehyde by vanadia/TiO2 model catalysts have shown that the activity of these systems vary considerably based on the way in which the model system is prepared with formaldehyde desorption temperatures observed anywhere from room temperature to 660 K. The principle reason for this variation is that the preparation of sub-monolayer films of vanadia on TiO2 produces clusters with a multitude of VxOy structures and a mixture of vanadium oxidation states. As a result the stoichiometry of the active vanadium oxide catalyst as well as the oxidation state of vanadium in the active catalyst remain unknown. To better understand this system, our group has probed the reactivity and structure of size-selected Vx, VOy and VxOy clusters on a reduced TiO2 (110) support in ultra-high vacuum (UHV) via TPD/R and scanning tunneling microscopy (STM). Ex situ preparation of these clusters in the gas phase prior to deposition has allowed us to systematically vary the stoichiometry of the vanadia clusters; a layer of control not available via the usual routes to vanadium oxide. The most active catalysts are shown to have (VO3)n stoichiometry in agreement with the theoretical models of the Metiu group. We have shown that both the activity and selectivity of V2O6 and V3O9 cluster catalysts depend sensitively on the oxidation state of the TiO2 (110) support. For example, V2O6 on a reduced surface is selective for the oxidation of methanol to formaldehyde while the selectivity shifts to favor methyl formate as the surface becomes increasingly oxidized. STM studies show that the structure of size-selected V2O6 clusters, upon adsorption to the surface, varies considerably with the oxidation state of the support, in good agreement with our reactivity studies. V 3O9 was shown to catalyze the oxidation of methanol to both formaldehyde and methyl formate on a reduced surface while STM suggests that, unlike V2O6, these clusters are prone to decomposition upon adsorption to the surface. Furthermore, TPD/R of size selected V 2O5 and V2O7 on TiO2 suggests that altering the stoichiometry of the (VO3)n clusters by a single oxygen atom significantly inhibits the activity of these catalysts.

EXPLORING FUNCTIONAL CONNECTIVITY IN FMRI VIA CLUSTERING.

PubMed

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

2009-04-01

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

Revisiting benzene cluster cations for the chemical ionization of dimethyl sulfide and select volatile organic compounds

DOE PAGES

Kim, Michelle J.; Zoerb, Matthew C.; Campbell, Nicole R.; ...

2016-04-05

Here, benzene cluster cations were revisited as a sensitive and selective reagent ion for the chemical ionization of dimethyl sulfide (DMS) and a select group of volatile organic compounds (VOCs). Laboratory characterization was performed using both a new set of compounds (i.e., DMS, β-caryophyllene) as well as previously studied VOCs (i.e., isoprene, α-pinene). Using a field deployable chemical-ionization time-of-flight mass spectrometer (CI-ToFMS), benzene cluster cations demonstrated high sensitivity (> 1 ncps ppt −1) to DMS, isoprene, and α-pinene standards. Parallel measurements conducted using a chemical-ionization quadrupole mass spectrometer, with a much weaker electric field, demonstrated that ion–molecule reactions likely proceed through amore » combination of ligand-switching and direct charge transfer mechanisms. Laboratory tests suggest that benzene cluster cations may be suitable for the selective ionization of sesquiterpenes, where minimal fragmentation (< 25 %) was observed for the detection of β-caryophyllene, a bicyclic sesquiterpene. The in-field stability of benzene cluster cations using CI-ToFMS was examined in the marine boundary layer during the High Wind Gas Exchange Study (HiWinGS). The use of benzene cluster cation chemistry for the selective detection of DMS was validated against an atmospheric pressure ionization mass spectrometer, where measurements from the two instruments were highly correlated ( R 2 > 0.95, 10 s averages) over a wide range of sampling conditions.« less

Functional Interference Clusters in Cancer Patients With Bone Metastases: A Secondary Analysis of RTOG 9714

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

Chow, Edward, E-mail: Edward.Chow@sunnybrook.c; James, Jennifer; Barsevick, Andrea

Purpose: To explore the relationships (clusters) among the functional interference items in the Brief Pain Inventory (BPI) in patients with bone metastases. Methods: Patients enrolled in the Radiation Therapy Oncology Group (RTOG) 9714 bone metastases study were eligible. Patients were assessed at baseline and 4, 8, and 12 weeks after randomization for the palliative radiotherapy with the BPI, which consists of seven functional items: general activity, mood, walking ability, normal work, relations with others, sleep, and enjoyment of life. Principal component analysis with varimax rotation was used to determine the clusters between the functional items at baseline and the follow-up.more » Cronbach's alpha was used to determine the consistency and reliability of each cluster at baseline and follow-up. Results: There were 448 male and 461 female patients, with a median age of 67 years. There were two functional interference clusters at baseline, which accounted for 71% of the total variance. The first cluster (physical interference) included normal work and walking ability, which accounted for 58% of the total variance. The second cluster (psychosocial interference) included relations with others and sleep, which accounted for 13% of the total variance. The Cronbach's alpha statistics were 0.83 and 0.80, respectively. The functional clusters changed at week 12 in responders but persisted through week 12 in nonresponders. Conclusion: Palliative radiotherapy is effective in reducing bone pain. Functional interference component clusters exist in patients treated for bone metastases. These clusters changed over time in this study, possibly attributable to treatment. Further research is needed to examine these effects.« less

Lensing is low: cosmology, galaxy formation or new physics?

NASA Astrophysics Data System (ADS)

Leauthaud, Alexie; Saito, Shun; Hilbert, Stefan; Barreira, Alexandre; More, Surhud; White, Martin; Alam, Shadab; Behroozi, Peter; Bundy, Kevin; Coupon, Jean; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Mandelbaum, Rachel; Miller, Lance; Moraes, Bruno; Pereira, Maria E. S.; Rodríguez-Torres, Sergio A.; Schmidt, Fabian; Shan, Huan-Yuan; Viel, Matteo; Villaescusa-Navarro, Francisco

2017-05-01

We present high signal-to-noise galaxy-galaxy lensing measurements of the Baryon Oscillation Spectroscopic Survey constant mass (CMASS) sample using 250 deg2 of weak-lensing data from Canada-France-Hawaii Telescope Lensing Survey and Canada-France-Hawaii Telescope Stripe 82 Survey. We compare this signal with predictions from mock catalogues trained to match observables including the stellar mass function and the projected and two-dimensional clustering of CMASS. We show that the clustering of CMASS, together with standard models of the galaxy-halo connection, robustly predicts a lensing signal that is 20-40 per cent larger than observed. Detailed tests show that our results are robust to a variety of systematic effects. Lowering the value of S_8=σ _8 \\sqrt{Ω _m/0.3} compared to Planck Collaboration XIII reconciles the lensing with clustering. However, given the scale of our measurement (r < 10 h-1 Mpc), other effects may also be at play and need to be taken into consideration. We explore the impact of baryon physics, assembly bias, massive neutrinos and modifications to general relativity on ΔΣ and show that several of these effects may be non-negligible given the precision of our measurement. Disentangling cosmological effects from the details of the galaxy-halo connection, the effect of baryons, and massive neutrinos, is the next challenge facing joint lensing and clustering analyses. This is especially true in the context of large galaxy samples from Baryon Acoustic Oscillation surveys with precise measurements but complex selection functions.

Principal component and clustering analysis on molecular dynamics data of the ribosomal L11·23S subdomain.

PubMed

Wolf, Antje; Kirschner, Karl N

2013-02-01

With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria's L11·23S ribosomal subdomain, which is a target of thiopeptide antibiotics. Clustering was performed, using K-means and average-linkage algorithms, on data involving the first two to the first five PC subspace dimensions. For the average-linkage algorithm we found that data-point membership, cluster shape, and cluster size depended on the selected PC subspace data. In contrast, K-means provided very consistent results regardless of the selected subspace. Since we present results on a single model system, generalization concerning the clustering of different PC subspaces of other molecular systems is currently premature. However, our hope is that this study illustrates a) the complexities in selecting the appropriate clustering algorithm, b) the complexities in interpreting and validating their results, and c) by combining PC analysis with subsequent clustering valuable dynamic and conformational information can be obtained.

Halo correlations in nonlinear cosmic density fields

NASA Astrophysics Data System (ADS)

Bernardeau, F.; Schaeffer, R.

1999-09-01

The question we address in this paper is the determination of the correlation properties of the dark matter halos appearing in cosmic density fields once they underwent a strongly nonlinear evolution induced by gravitational dynamics. A series of previous works have given indications that kind of non-Gaussian features are induced by nonlinear evolution in term of the high-order correlation functions. Assuming such patterns for the matter field, i.e. that the high-order correlation functions behave as products of two-body correlation functions, we derive the correlation properties of the halos, that are assumed to represent the correlation properties of galaxies or clusters. The hierarchical pattern originally induced by gravity is shown to be conserved for the halos. The strength of their correlations at any order varies, however, but is found to depend only on their internal properties, namely on the parameter x~ m/r(3-gamma ) where m is the mass of the halo, r its size and gamma is the power law index of the two-body correlation function. This internal parameter is seen to be close to the depth of the internal potential well of virialized objects. We were able to derive the explicit form of the generating function of the moments of the halo counts probability distribution function. In particular we show explicitly that, generically, S_P(x)-> P(P-2) in the rare halo limit. Various illustrations of our general results are presented. As a function of the properties of the underlying matter field, we construct the count probabilities for halos and in particular discuss the halo void probability. We evaluate the dependence of the halo mass function on the environment: within clusters, hierarchical clustering implies the higher masses are favored. These properties solely arise from what is a natural bias (ie, naturally induced by gravity) between the observed objects and the unseen matter field, and how it manifests itself depending on which selection effects are imposed.

Synergism of virtual screening and medicinal chemistry: identification and optimization of allosteric antagonists of metabotropic glutamate receptor 1.

PubMed

Noeske, Tobias; Trifanova, Dina; Kauss, Valerjans; Renner, Steffen; Parsons, Christopher G; Schneider, Gisbert; Weil, Tanja

2009-08-01

We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by virtual screening and subsequent hit optimization. For ligand-based virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC(50)=0.74+/-0.29 microM). Hit optimization yielded lead structure 16 with an affinity of K(i)=0.024+/-0.001 microM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.

Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

NASA Astrophysics Data System (ADS)

Lestari, A. W.; Rustam, Z.

2017-07-01

In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

The Vibrational Frequencies of CaO2, ScO2, and TiO2: A Comparison of Theoretical Methods

NASA Technical Reports Server (NTRS)

Rosi, Marzio; Bauschlicher, Charles W., Jr.; Chertihin, George V.; Andrews, Lester; Arnold, James O. (Technical Monitor)

1997-01-01

The vibrational frequencies of several states of CaO2, ScO2, and TiO2 are computed at using density functional theory (DFT), the Hatree-Fock approach, second order Moller-Plesset perturbation theory (MP2), and the complete-active-space self-consistent-field theory. Three different functionals are used in the DFT calculations, including two hybrid functionals. The coupled cluster singles and doubles approach including the effect of unlinked triples, determined using perturbation theory, is applied to selected states. The Becke-Perdew 86 functional appears to be the cost effective method of choice, although even this functional does not perform well for one state of CaO2. The MP2 approach is significantly inferior to the DFT approaches.

The clustering amplitude of X-ray-selected AGN at z ˜ 0.8: evidence for a negative dependence on accretion luminosity

NASA Astrophysics Data System (ADS)

Mountrichas, G.; Georgakakis, A.; Menzel, M.-L.; Fanidakis, N.; Merloni, A.; Liu, Z.; Salvato, M.; Nandra, K.

2016-04-01

The northern tile of the wide-area and shallow XMM-XXL X-ray survey field is used to estimate the average dark matter halo mass of relatively luminous X-ray-selected active galactic nucleus (AGN) [log {L}_X (2-10 keV)= 43.6^{+0.4}_{-0.4} erg s^{-1}] in the redshift interval z = 0.5-1.2. Spectroscopic follow-up observations of X-ray sources in the XMM-XXL field by the Sloan telescope are combined with the VIMOS Public Extragalactic Redshift Survey spectroscopic galaxy survey to determine the cross-correlation signal between X-ray-selected AGN (total of 318) and galaxies (about 20 000). We model the large scales (2-25 Mpc) of the correlation function to infer a mean dark matter halo mass of log M / (M_{{⊙}} h^{-1}) = 12.50 ^{+0.22} _{-0.30} for the X-ray-selected AGN sample. This measurement is about 0.5 dex lower compared to estimates in the literature of the mean dark matter halo masses of moderate-luminosity X-ray AGN [LX(2-10 keV) ≈ 1042-1043 erg s- 1] at similar redshifts. Our analysis also links the mean clustering properties of moderate-luminosity AGN with those of powerful ultraviolet/optically selected QSOs, which are typically found in haloes with masses few times 1012 M⊙. There is therefore evidence for a negative luminosity dependence of the AGN clustering. This is consistent with suggestions that AGN have a broad dark matter halo mass distribution with a high mass tail that becomes subdominant at high accretion luminosities. We further show that our results are in qualitative agreement with semi-analytic models of galaxy and AGN evolution, which attribute the wide range of dark matter halo masses among the AGN population to different triggering mechanisms and/or black hole fuelling modes.

Cherry-picking functionally relevant substates from long md trajectories using a stratified sampling approach.

PubMed

Chandramouli, Balasubramanian; Mancini, Giordano

2016-01-01

Classical Molecular Dynamics (MD) simulations can provide insights at the nanoscopic scale into protein dynamics. Currently, simulations of large proteins and complexes can be routinely carried out in the ns-μs time regime. Clustering of MD trajectories is often performed to identify selective conformations and to compare simulation and experimental data coming from different sources on closely related systems. However, clustering techniques are usually applied without a careful validation of results and benchmark studies involving the application of different algorithms to MD data often deal with relatively small peptides instead of average or large proteins; finally clustering is often applied as a means to analyze refined data and also as a way to simplify further analysis of trajectories. Herein, we propose a strategy to classify MD data while carefully benchmarking the performance of clustering algorithms and internal validation criteria for such methods. We demonstrate the method on two showcase systems with different features, and compare the classification of trajectories in real and PCA space. We posit that the prototype procedure adopted here could be highly fruitful in clustering large trajectories of multiple systems or that resulting especially from enhanced sampling techniques like replica exchange simulations. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.

Phenotypes of asthma in low-income children and adolescents: cluster analysis.

PubMed

Cabral, Anna Lucia Barros; Sousa, Andrey Wirgues; Mendes, Felipe Augusto Rodrigues; Carvalho, Celso Ricardo Fernandes de

2017-01-01

Studies characterizing asthma phenotypes have predominantly included adults or have involved children and adolescents in developed countries. Therefore, their applicability in other populations, such as those of developing countries, remains indeterminate. Our objective was to determine how low-income children and adolescents with asthma in Brazil are distributed across a cluster analysis. We included 306 children and adolescents (6-18 years of age) with a clinical diagnosis of asthma and under medical treatment for at least one year of follow-up. At enrollment, all the patients were clinically stable. For the cluster analysis, we selected 20 variables commonly measured in clinical practice and considered important in defining asthma phenotypes. Variables with high multicollinearity were excluded. A cluster analysis was applied using a twostep agglomerative test and log-likelihood distance measure. Three clusters were defined for our population. Cluster 1 (n = 94) included subjects with normal pulmonary function, mild eosinophil inflammation, few exacerbations, later age at asthma onset, and mild atopy. Cluster 2 (n = 87) included those with normal pulmonary function, a moderate number of exacerbations, early age at asthma onset, more severe eosinophil inflammation, and moderate atopy. Cluster 3 (n = 108) included those with poor pulmonary function, frequent exacerbations, severe eosinophil inflammation, and severe atopy. Asthma was characterized by the presence of atopy, number of exacerbations, and lung function in low-income children and adolescents in Brazil. The many similarities with previous cluster analyses of phenotypes indicate that this approach shows good generalizability. Estudos que caracterizam fenótipos de asma predominantemente incluem adultos ou foram realizados em crianças e adolescentes de países desenvolvidos; portanto, sua aplicabilidade em outras populações, tais como as de países em desenvolvimento, permanece indeterminada. Nosso objetivo foi determinar como crianças e adolescentes asmáticas de baixa renda no Brasil são distribuídos através de uma análise de clusters. Foram incluídos 306 crianças e adolescentes (6-18 anos de idade) com diagnóstico clínico de asma e sob tratamento médico por pelo menos um ano de acompanhamento. No momento da inclusão, todos os pacientes estavam clinicamente estáveis. Vinte variáveis comumente determinadas na prática clínica e consideradas importantes na definição dos fenótipos de asma foram selecionadas para a análise de clusters. As variáveis com alta multicolinearidade foram excluídas. Uma análise de clusters foi realizada utilizando-se um teste aglomerativo em duas etapas e log-likelihood distance measure. Três clusters foram definidos para nossa população. O cluster 1 (n = 94) incluiu indivíduos com função pulmonar normal, inflamação eosinofílica leve, poucas exacerbações, início mais tardio da asma e atopia leve. O cluster 2 (n = 87) incluiu pacientes com função pulmonar normal, número moderado de exacerbações, início precoce da asma, inflamação eosinofílica mais grave e atopia moderada. O cluster 3 (n = 108) incluiu pacientes com função pulmonar ruim, exacerbações frequentes, inflamação eosinofílica e atopia graves. A asma foi caracterizada por presença de atopia, número de exacerbações e função pulmonar em crianças e adolescentes de baixa renda no Brasil. As muitas semelhanças entre esta e outras análises de clusters de fenótipos indicam que essa abordagem apresenta boa generalização.

Reproducibility of Cognitive Profiles in Psychosis Using Cluster Analysis.

PubMed

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

2018-04-01

Cognitive dysfunction is a core symptom dimension that cuts across the psychoses. Recent findings support classification of patients along the cognitive dimension using cluster analysis; however, data-derived groupings may be highly determined by sampling characteristics and the measures used to derive the clusters, and so their interpretability must be established. We examined cognitive clusters in a cross-diagnostic sample of patients with psychosis and associations with clinical and functional outcomes. We then compared our findings to a previous report of cognitive clusters in a separate sample using a different cognitive battery. Participants with affective or non-affective psychosis (n=120) and healthy controls (n=31) were administered the MATRICS Consensus Cognitive Battery, and clinical and community functioning assessments. Cluster analyses were performed on cognitive variables, and clusters were compared on demographic, cognitive, and clinical measures. Results were compared to findings from our previous report. A four-cluster solution provided a good fit to the data; profiles included a neuropsychologically normal cluster, a globally impaired cluster, and two clusters of mixed profiles. Cognitive burden was associated with symptom severity and poorer community functioning. The patterns of cognitive performance by cluster were highly consistent with our previous findings. We found evidence of four cognitive subgroups of patients with psychosis, with cognitive profiles that map closely to those produced in our previous work. Clusters were associated with clinical and community variables and a measure of premorbid functioning, suggesting that they reflect meaningful groupings: replicable, and related to clinical presentation and functional outcomes. (JINS, 2018, 24, 382-390).

The young star cluster population of M51 with LEGUS - II. Testing environmental dependences

NASA Astrophysics Data System (ADS)

Messa, Matteo; Adamo, A.; Calzetti, D.; Reina-Campos, M.; Colombo, D.; Schinnerer, E.; Chandar, R.; Dale, D. A.; Gouliermis, D. A.; Grasha, K.; Grebel, E. K.; Elmegreen, B. G.; Fumagalli, M.; Johnson, K. E.; Kruijssen, J. M. D.; Östlin, G.; Shabani, F.; Smith, L. J.; Whitmore, B. C.

2018-06-01

It has recently been established that the properties of young star clusters (YSCs) can vary as a function of the galactic environment in which they are found. We use the cluster catalogue produced by the Legacy Extragalactic UV Survey (LEGUS) collaboration to investigate cluster properties in the spiral galaxy M51. We analyse the cluster population as a function of galactocentric distance and in arm and inter-arm regions. The cluster mass function exhibits a similar shape at all radial bins, described by a power law with a slope close to -2 and an exponential truncation around 105 M⊙. While the mass functions of the YSCs in the spiral arm and inter-arm regions have similar truncation masses, the inter-arm region mass function has a significantly steeper slope than the one in the arm region, a trend that is also observed in the giant molecular cloud mass function and predicted by simulations. The age distribution of clusters is dependent on the region considered, and is consistent with rapid disruption only in dense regions, while little disruption is observed at large galactocentric distances and in the inter-arm region. The fraction of stars forming in clusters does not show radial variations, despite the drop in the H2 surface density measured as a function of galactocentric distance. We suggest that the higher disruption rate observed in the inner part of the galaxy is likely at the origin of the observed flat cluster formation efficiency radial profile.

THE CLUSTER LENSING AND SUPERNOVA SURVEY WITH HUBBLE: AN OVERVIEW

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

Postman, Marc; Coe, Dan; Bradley, Larry

2012-04-01

The Cluster Lensing And Supernova survey with Hubble (CLASH) is a 524-orbit Multi-Cycle Treasury Program to use the gravitational lensing properties of 25 galaxy clusters to accurately constrain their mass distributions. The survey, described in detail in this paper, will definitively establish the degree of concentration of dark matter in the cluster cores, a key prediction of structure formation models. The CLASH cluster sample is larger and less biased than current samples of space-based imaging studies of clusters to similar depth, as we have minimized lensing-based selection that favors systems with overly dense cores. Specifically, 20 CLASH clusters are solelymore » X-ray selected. The X-ray-selected clusters are massive (kT > 5 keV) and, in most cases, dynamically relaxed. Five additional clusters are included for their lensing strength ({theta}{sub Ein} > 35'' at z{sub s} = 2) to optimize the likelihood of finding highly magnified high-z (z > 7) galaxies. A total of 16 broadband filters, spanning the near-UV to near-IR, are employed for each 20-orbit campaign on each cluster. These data are used to measure precise ({sigma}{sub z} {approx} 0.02(1 + z)) photometric redshifts for newly discovered arcs. Observations of each cluster are spread over eight epochs to enable a search for Type Ia supernovae at z > 1 to improve constraints on the time dependence of the dark energy equation of state and the evolution of supernovae. We present newly re-derived X-ray luminosities, temperatures, and Fe abundances for the CLASH clusters as well as a representative source list for MACS1149.6+2223 (z 0.544).« less

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

IUE observations of rapidly rotating low-mass stars in young clusters - The relation between chromospheric activity and rotation

NASA Technical Reports Server (NTRS)

Simon, Theodore

1990-01-01

If the rapid spindown of low-mass stars immediately following their arrival on the ZAMS results from magnetic braking by coronal winds, an equally sharp decline in their chromospheric emission may be expected. To search for evidence of this effect, the IUE spacecraft was used to observe the chromospheric Mg II emission lines of G-M dwarfs in the nearby IC 2391, Alpha Persei, Pleiades, and Hyades clusters. Similar observations were made of a group of X-ray-selected 'naked' T Tauri stars in Taurus-Auriga. The existence of a decline in activity cannot be confirmed from the resulting data. However, the strength of the chromospheric emission in the Mg II lines of the cluster stars is found to be correlated with rotation rate, being strongest for the stars with the shortest rotation periods and weakest for those with the longest periods. This provides indirect support for such an evolutionary change in activity. Chromospheric activity may thus be only an implicit function of age.

Reversing Conventional Reactivity of Mixed Oxo/Alkyl Rare-Earth Complexes: Non-Redox Oxygen Atom Transfer.

PubMed

Hong, Jianquan; Tian, Haiwen; Zhang, Lixin; Zhou, Xigeng; Del Rosal, Iker; Weng, Linhong; Maron, Laurent

2018-01-22

The preferential substitution of oxo ligands over alkyl ones of rare-earth complexes is commonly considered as "impossible" due to the high oxophilicity of metal centers. Now, it has been shown that simply assembling mixed methyl/oxo rare-earth complexes to a rigid trinuclear cluster framework cannot only enhance the activity of the Ln-oxo bond, but also protect the highly reactive Ln-alkyl bond, thus providing a previously unrecognized opportunity to selectively manipulate the oxo ligand in the presence of numerous reactive functionalities. Such trimetallic cluster has proved to be a suitable platform for developing the unprecedented non-redox rare-earth-mediated oxygen atom transfer from ketones to CS 2 and PhNCS. Controlled experiments and computational studies shed light on the driving force for these reactions, emphasizing the importance of the sterical accessibility and multimetallic effect of the cluster framework in promoting reversal of reactivity of rare-earth oxo complexes. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Energetics and solvation structure of a dihalogen dopant (I2) in (4)He clusters.

PubMed

Pérez de Tudela, Ricardo; Barragán, Patricia; Valdés, Álvaro; Prosmiti, Rita

2014-08-21

The energetics and structure of small HeNI2 clusters are analyzed as the size of the system changes, with N up to 38. The full interaction between the I2 molecule and the He atoms is based on analytical ab initio He-I2 potentials plus the He-He interaction, obtained from first-principle calculations. The most stable structures, as a function of the number of solvent He atoms, are obtained by employing an evolutionary algorithm and compared with CCSD(T) and MP2 ab initio computations. Further, the classical description is completed by explicitly including thermal corrections and quantum features, such as zero-point-energy values and spatial delocalization. From quantum PIMC calculations, the binding energies and radial/angular probability density distributions of the thermal equilibrium state for selected-size clusters are computed at a low temperature. The sequential formation of regular shell structures is analyzed and discussed for both classical and quantum treatments.

Computational clustering for viral reference proteomes

PubMed Central

Chen, Chuming; Huang, Hongzhan; Mazumder, Raja; Natale, Darren A.; McGarvey, Peter B.; Zhang, Jian; Polson, Shawn W.; Wang, Yuqi; Wu, Cathy H.

2016-01-01

Motivation: The enormous number of redundant sequenced genomes has hindered efforts to analyze and functionally annotate proteins. As the taxonomy of viruses is not uniformly defined, viral proteomes pose special challenges in this regard. Grouping viruses based on the similarity of their proteins at proteome scale can normalize against potential taxonomic nomenclature anomalies. Results: We present Viral Reference Proteomes (Viral RPs), which are computed from complete virus proteomes within UniProtKB. Viral RPs based on 95, 75, 55, 35 and 15% co-membership in proteome similarity based clusters are provided. Comparison of our computational Viral RPs with UniProt’s curator-selected Reference Proteomes indicates that the two sets are consistent and complementary. Furthermore, each Viral RP represents a cluster of virus proteomes that was consistent with virus or host taxonomy. We provide BLASTP search and FTP download of Viral RP protein sequences, and a browser to facilitate the visualization of Viral RPs. Availability and implementation: http://proteininformationresource.org/rps/viruses/ Contact: chenc@udel.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153712

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

NASA Astrophysics Data System (ADS)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

Dwarf elliptical galaxies

NASA Technical Reports Server (NTRS)

Ferguson, Henry C.; Binggeli, Bruno

1994-01-01

Dwarf elliptical (dE) galaxies, with blue absolute magnitudes typically fainter than M(sub B) = -16, are the most numerous type of galaxy in the nearby universe. Tremendous advances have been made over the past several years in delineating the properties of both Local Group satellite dE's and the large dE populations of nearby clusters. We review some of these advances, with particular attention to how well currently availiable data can constrain (a) models for the formation of dE's, (b) the physical and evolutionary connections between different types of galaxies that overlap in the same portion of the mass-spectrum of galaxies, (c) the contribution of dE's to the galaxy luminosity functions in clusters and the field, (d) the star-forming histories of dE's and their possible contribution to faint galaxy counts, and (e) the clustering properties of dE's. In addressing these issues, we highlight the extent to which selection effects temper these constraints, and outline areas where new data would be particularly valuable.

Strong Clustering of Lyman Break Galaxies around Luminous Quasars at Z ˜ 4

NASA Astrophysics Data System (ADS)

García-Vergara, Cristina; Hennawi, Joseph F.; Barrientos, L. Felipe; Rix, Hans-Walter

2017-10-01

In the standard picture of structure formation, the first massive galaxies are expected to form at the highest peaks of the density field, which constitute the cores of massive proto-clusters. Luminous quasars (QSOs) at z ˜ 4 are the most strongly clustered population known, and should thus reside in massive dark matter halos surrounded by large overdensities of galaxies, implying a strong QSO-galaxy cross-correlation function. We observed six z ˜ 4 QSO fields with VLT/FORS, exploiting a novel set of narrow-band filters custom designed to select Lyman Break Galaxies (LBGs) in a thin redshift slice of {{Δ }}z˜ 0.3, mitigating the projection effects that have limited the sensitivity of previous searches for galaxies around z≳ 4 QSOs. We find that LBGs are strongly clustered around QSOs, and present the first measurement of the QSO-LBG cross-correlation function at z ˜ 4, on scales of 0.1≲ R≲ 9 {h}-1 {Mpc} (comoving). Assuming a power-law form for the cross-correlation function ξ ={(r/{r}0{QG})}γ , we measure {r}0{QG}={8.83}-1.51+1.39 {h}-1 {Mpc} for a fixed slope of γ =2.0. This result is in agreement with the expected cross-correlation length deduced from measurements of the QSO and LBG auto-correlation function, and assuming a deterministic bias model. We also measure a strong auto-correlation of LBGs in our QSO fields, finding {r}0{GG}={21.59}-1.69+1.72 {h}-1 {Mpc} for a fixed slope of γ =1.5, which is ˜4 times larger than the LBG auto-correlation length in blank fields, providing further evidence that QSOs reside in overdensities of LBGs. Our results qualitatively support a picture where luminous QSOs inhabit exceptionally massive ({M}{halo}> {10}12 {M}⊙ ) dark matter halos at z ˜ 4.

A Granular Self-Organizing Map for Clustering and Gene Selection in Microarray Data.

PubMed

Ray, Shubhra Sankar; Ganivada, Avatharam; Pal, Sankar K

2016-09-01

A new granular self-organizing map (GSOM) is developed by integrating the concept of a fuzzy rough set with the SOM. While training the GSOM, the weights of a winning neuron and the neighborhood neurons are updated through a modified learning procedure. The neighborhood is newly defined using the fuzzy rough sets. The clusters (granules) evolved by the GSOM are presented to a decision table as its decision classes. Based on the decision table, a method of gene selection is developed. The effectiveness of the GSOM is shown in both clustering samples and developing an unsupervised fuzzy rough feature selection (UFRFS) method for gene selection in microarray data. While the superior results of the GSOM, as compared with the related clustering methods, are provided in terms of β -index, DB-index, Dunn-index, and fuzzy rough entropy, the genes selected by the UFRFS are not only better in terms of classification accuracy and a feature evaluation index, but also statistically more significant than the related unsupervised methods. The C-codes of the GSOM and UFRFS are available online at http://avatharamg.webs.com/software-code.

Minor digestive symptoms and their impact in the general population: a cluster analysis approach.

PubMed

L'Heureux-Bouron, Diane; Legrain-Raspaud, Sophie; Carruthers, Helen R; Whorwell, P J

2018-01-01

The classification and treatment of patients who do not meet the criteria for a functional gastrointestinal (GI) disorder has not been well established. This study aimed to record the prevalence of minor digestive symptoms (MDSs) in the general population attempting to divide them into symptom clusters as well as trying to assess their impact and the way sufferers cope with them. Following face-to-face interviews, a web-based, self-administered questionnaire was designed to capture a range of GI sensations using 34 questions and 12 images depicting abdominal symptoms. A randomly selected sample of 1515 women and 409 men representing the general population in France was studied. Cluster analysis was used to identify groups of respondents with naturally co-occurring symptoms. Data were also collected on other factors such as exacerbating and relieving strategies. MDSs were reported at least every 2 months in 66.5% of women and 47.7% of men. A total of 11 symptom clusters were identified: constipation-like, flatulence, abdominal pressure, abdominal swelling, acid reflux, diarrhoea-like, intestinal heaviness, intestinal pain, gurgling, burning and gastric pain. Despite being minor, these problems had a major impact on vitality and self-image as well as emotional, social and physical well-being. Respondents considered lifestyle, food and disordered function as the main factors responsible for MDSs. Physical measures and dietary modification were the most frequent strategies adopted to obtain relief. MDSs are common and improved methods of recognition are needed so that better management strategies can be developed for individuals with these symptoms. The definition of symptom clusters may offer one way of achieving this goal.

Cognitive variability in bipolar II disorder: who is cognitively impaired and who is preserved.

PubMed

Solé, Brisa; Jiménez, Esther; Torrent, Carla; Del Mar Bonnin, Caterina; Torres, Imma; Reinares, María; Priego, Ángel; Salamero, Manel; Colom, Francesc; Varo, Cristina; Vieta, Eduard; Martínez-Arán, Anabel

2016-05-01

Although it is well established that euthymic patients with bipolar disorder can have cognitive impairment, substantial heterogeneity exists and little is known about the extent and severity of impairment within the bipolar II disorder subtype. Therefore, the main aim of this study was to analyze cognitive variability in a sample of patients with bipolar II disorder. The neuropsychological performance of 116 subjects, including 64 euthymic patients with bipolar II disorder and 52 healthy control subjects, was examined and compared by means of a comprehensive neurocognitive battery. Neurocognitive data were analyzed using a cluster analysis to examine whether there were specific groups based on neurocognitive patterns. Subsequently, subjects from each cluster were compared on demographic, clinical, and functional variables. A three-cluster solution was identified with an intact neurocognitive group (n = 29, 48.3%), an intermediate or selectively impaired group (n = 24, 40.0%), and a globally impaired group (n = 7, 11.6%). Among the three clusters, statistically significant differences were observed in premorbid intelligence quotient (p = 0.002), global functional outcome (p = 0.021), and leisure activities (p = 0.001), with patients in the globally impaired cluster showing the lowest attainments. No differences in other clinical characteristics were found among the groups. These results confirm that neurocognitive variability is also present among patients with bipolar II disorder. Approximately one-half of the patients with bipolar II disorder were cognitively impaired, and among them 12% were severely and globally impaired. The identification of different cognitive profiles may help to develop cognitive remediation programs specifically tailored for each cognitive profile. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Method to Find Longevity-Selected Positions in the Mammalian Proteome

PubMed Central

Semeiks, Jeremy; Grishin, Nick V.

2012-01-01

Evolutionary theory suggests that the force of natural selection decreases with age. To explore the extent to which this prediction directly affects protein structure and function, we used multiple regression to find longevity-selected positions, defined as the columns of a sequence alignment conserved in long-lived but not short-lived mammal species. We analyzed 7,590 orthologous protein families in 33 mammalian species, accounting for body mass, phylogeny, and species-specific mutation rate. Overall, we found that the number of longevity-selected positions in the mammalian proteome is much higher than would be expected by chance. Further, these positions are enriched in domains of several proteins that interact with one another in inflammation and other aging-related processes, as well as in organismal development. We present as an example the kinase domain of anti-Müllerian hormone type-2 receptor (AMHR2). AMHR2 inhibits ovarian follicle recruitment and growth, and a homology model of the kinase domain shows that its longevity-selected positions cluster near a SNP associated with delayed human menopause. Distinct from its canonical role in development, this region of AMHR2 may function to regulate the protein’s activity in a lifespan-specific manner. PMID:22701678

The Hierarchical Brain Network for Face Recognition

PubMed Central

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level. PMID:23527282