What Makes Clusters Decline?

DEFF Research Database (Denmark)

Østergaard, Christian Richter; Park, Eun Kyung

2015-01-01

Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark. The longit...... but being quick to withdraw in times of crisis....

Radiobiological analyse based on cell cluster models

International Nuclear Information System (INIS)

Lin Hui; Jing Jia; Meng Damin; Xu Yuanying; Xu Liangfeng

2010-01-01

The influence of cell cluster dimension on EUD and TCP for targeted radionuclide therapy was studied using the radiobiological method. The radiobiological features of tumor with activity-lack in core were evaluated and analyzed by associating EUD, TCP and SF.The results show that EUD will increase with the increase of tumor dimension under the activity homogeneous distribution. If the extra-cellular activity was taken into consideration, the EUD will increase 47%. Under the activity-lack in tumor center and the requirement of TCP=0.90, the α cross-fire influence of 211 At could make up the maximum(48 μm)3 activity-lack for Nucleus source, but(72 μm)3 for Cytoplasm, Cell Surface, Cell and Voxel sources. In clinic,the physician could prefer the suggested dose of Cell Surface source in case of the future of local tumor control for under-dose. Generally TCP could well exhibit the effect difference between under-dose and due-dose, but not between due-dose and over-dose, which makes TCP more suitable for the therapy plan choice. EUD could well exhibit the difference between different models and activity distributions,which makes it more suitable for the research work. When the user uses EUD to study the influence of activity inhomogeneous distribution, one should keep the consistency of the configuration and volume of the former and the latter models. (authors)

Electron impact ionization of large krypton clusters

Institute of Scientific and Technical Information of China (English)

Li Shao-Hui; Li Ru-Xin; Ni Guo-Quan; Xu Zhi-Zhan

2004-01-01

We show that the detection of ionization of very large van der Waals clusters in a pulsed jet or a beam can be realized by using a fast ion gauge. Rapid positive feedback electron impact ionization and fragmentation processes,which are initially ignited by electron impact ionization of the krypton clusters with the electron current of the ion gauge, result in the appearance of a progressional oscillation-like ion spectrum, or just of a single fast event under critical conditions. Each line in the spectrum represents a correlated explosion or avalanche ionization of the clusters.The phenomena have been analysed qualitatively along with a Rayleigh scattering experiment of the corresponding cluster jet.

Non-Hierarchical Clustering as a method to analyse an open-ended ...

African Journals Online (AJOL)

Apple

Keywords: algebraic thinking; cluster analysis; mathematics education; quantitative analysis. Introduction. Extensive ..... C1, C2 and C3 represent the three centroids of the three clusters formed. .... 6ALd. All these strategies are algebraic and 'high- ... 1995), of the didactical aspects related to teaching .... Brazil, 18-23 July.

Novel Method To Identify Source-Associated Phylogenetic Clustering Shows that Listeria monocytogenes Includes Niche-Adapted Clonal Groups with Distinct Ecological Preferences

DEFF Research Database (Denmark)

Nightingale, K. K.; Lyles, K.; Ayodele, M.

2006-01-01

population are identified (TreeStats test). Analysis of sequence data for 120 L. monocytogenes isolates revealed evidence of clustering between isolates from the same source, based on the phylogenies inferred from actA and inlA (P = 0.02 and P = 0.07, respectively; SourceCluster test). Overall, the Tree...... are biologically valid. Overall, our data show that (i) the SourceCluster and TreeStats tests can identify biologically meaningful source-associated phylogenetic clusters and (ii) L. monocytogenes includes clonal groups that have adapted to infect specific host species or colonize nonhost environments......., including humans, animals, and food. If the null hypothesis that the genetic distances for isolates within and between source populations are identical can be rejected (SourceCluster test), then particular clades in the phylogenetic tree with significant overrepresentation of sequences from a given source...

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

Science.gov (United States)

2014-01-01

Background There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. To illustrate this, we focus on the issue of cluster merging, considering the impact on the design, analysis and interpretation of trial outcomes. Methods We explored the effects of merging clusters on study power using standard methods of power calculation. We assessed the potential impacts on study findings of both homogeneous cluster merges (involving clusters randomised to the same arm of a trial) and heterogeneous merges (involving clusters randomised to different arms of a trial) by simulation. To determine the impact on bias and precision of treatment effect estimates, we applied standard methods of analysis to different populations under analysis. Results Cluster merging produced a systematic reduction in study power. This effect depended on the number of merges and was most pronounced when variability in cluster size was at its greatest. Simulations demonstrate that the impact on analysis was minimal when cluster merges were homogeneous, with impact on study power being balanced by a change in observed intracluster correlation coefficient (ICC). We found a decrease in study power when cluster merges were heterogeneous, and the estimate of treatment effect was attenuated. Conclusions Examples of cluster merges found in previously published reports of cluster randomised trials were typically homogeneous rather than heterogeneous. Simulations demonstrated that trial findings in such cases would be unbiased. However, simulations also showed that any heterogeneous cluster merges would introduce bias that would be hard to quantify, as well as having negative impacts on the precision of estimates obtained. Further methodological development is warranted to better determine how to analyse such trials appropriately. Interim recommendations

Intracluster age gradients in numerous young stellar clusters

Science.gov (United States)

Getman, K. V.; Feigelson, E. D.; Kuhn, M. A.; Bate, M. R.; Broos, P. S.; Garmire, G. P.

2018-05-01

The pace and pattern of star formation leading to rich young stellar clusters is quite uncertain. In this context, we analyse the spatial distribution of ages within 19 young (median t ≲ 3 Myr on the Siess et al. time-scale), morphologically simple, isolated, and relatively rich stellar clusters. Our analysis is based on young stellar object (YSO) samples from the Massive Young Star-Forming Complex Study in Infrared and X-ray and Star Formation in Nearby Clouds surveys, and a new estimator of pre-main sequence (PMS) stellar ages, AgeJX, derived from X-ray and near-infrared photometric data. Median cluster ages are computed within four annular subregions of the clusters. We confirm and extend the earlier result of Getman et al. (2014): 80 per cent of the clusters show age trends where stars in cluster cores are younger than in outer regions. Our cluster stacking analyses establish the existence of an age gradient to high statistical significance in several ways. Time-scales vary with the choice of PMS evolutionary model; the inferred median age gradient across the studied clusters ranges from 0.75 to 1.5 Myr pc-1. The empirical finding reported in the present study - late or continuing formation of stars in the cores of star clusters with older stars dispersed in the outer regions - has a strong foundation with other observational studies and with the astrophysical models like the global hierarchical collapse model of Vázquez-Semadeni et al.

Analysing the spatial patterns of livestock anthrax in Kazakhstan in relation to environmental factors: a comparison of local (Gi* and morphology cluster statistics

Directory of Open Access Journals (Sweden)

Ian T. Kracalik

2012-11-01

Full Text Available We compared a local clustering and a cluster morphology statistic using anthrax outbreaks in large (cattle and small (sheep and goats domestic ruminants across Kazakhstan. The Getis-Ord (Gi* statistic and a multidirectional optimal ecotope algorithm (AMOEBA were compared using 1st, 2nd and 3rd order Rook contiguity matrices. Multivariate statistical tests were used to evaluate the environmental signatures between clusters and non-clusters from the AMOEBA and Gi* tests. A logistic regression was used to define a risk surface for anthrax outbreaks and to compare agreement between clustering methodologies. Tests revealed differences in the spatial distribution of clusters as well as the total number of clusters in large ruminants for AMOEBA (n = 149 and for small ruminants (n = 9. In contrast, Gi* revealed fewer large ruminant clusters (n = 122 and more small ruminant clusters (n = 61. Significant environmental differences were found between groups using the Kruskall-Wallis and Mann- Whitney U tests. Logistic regression was used to model the presence/absence of anthrax outbreaks and define a risk surface for large ruminants to compare with cluster analyses. The model predicted 32.2% of the landscape as high risk. Approximately 75% of AMOEBA clusters corresponded to predicted high risk, compared with ~64% of Gi* clusters. In general, AMOEBA predicted more irregularly shaped clusters of outbreaks in both livestock groups, while Gi* tended to predict larger, circular clusters. Here we provide an evaluation of both tests and a discussion of the use of each to detect environmental conditions associated with anthrax outbreak clusters in domestic livestock. These findings illustrate important differences in spatial statistical methods for defining local clusters and highlight the importance of selecting appropriate levels of data aggregation.

Merged consensus clustering to assess and improve class discovery with microarray data

Directory of Open Access Journals (Sweden)

Jarman Andrew P

2010-12-01

Full Text Available Abstract Background One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a large number of methods available to perform clustering, but it is often unclear which method is best suited to the data and how to quantify the quality of the classifications produced. Results Here we describe an R package containing methods to analyse the consistency of clustering results from any number of different clustering methods using resampling statistics. These methods allow the identification of the the best supported clusters and additionally rank cluster members by their fidelity within the cluster. These metrics allow us to compare the performance of different clustering algorithms under different experimental conditions and to select those that produce the most reliable clustering structures. We show the application of this method to simulated data, canonical gene expression experiments and our own novel analysis of genes involved in the specification of the peripheral nervous system in the fruitfly, Drosophila melanogaster. Conclusions Our package enables users to apply the merged consensus clustering methodology conveniently within the R programming environment, providing both analysis and graphical display functions for exploring clustering approaches. It extends the basic principle of consensus clustering by allowing the merging of results between different methods to provide an averaged clustering robustness. We show that this extension is useful in correcting for the tendency of clustering algorithms to treat outliers differently within datasets. The R package, clusterCons, is freely available at CRAN and sourceforge under the GNU public licence.

Mouse Nkrp1-Clr gene cluster sequence and expression analyses reveal conservation of tissue-specific MHC-independent immunosurveillance.

Directory of Open Access Journals (Sweden)

Qiang Zhang

Full Text Available The Nkrp1 (Klrb1-Clr (Clec2 genes encode a receptor-ligand system utilized by NK cells as an MHC-independent immunosurveillance strategy for innate immune responses. The related Ly49 family of MHC-I receptors displays extreme allelic polymorphism and haplotype plasticity. In contrast, previous BAC-mapping and aCGH studies in the mouse suggest the neighboring and related Nkrp1-Clr cluster is evolutionarily stable. To definitively compare the relative evolutionary rate of Nkrp1-Clr vs. Ly49 gene clusters, the Nkrp1-Clr gene clusters from two Ly49 haplotype-disparate inbred mouse strains, BALB/c and 129S6, were sequenced. Both Nkrp1-Clr gene cluster sequences are highly similar to the C57BL/6 reference sequence, displaying the same gene numbers and order, complete pseudogenes, and gene fragments. The Nkrp1-Clr clusters contain a strikingly dissimilar proportion of repetitive elements compared to the Ly49 clusters, suggesting that certain elements may be partly responsible for the highly disparate Ly49 vs. Nkrp1 evolutionary rate. Focused allelic polymorphisms were found within the Nkrp1b/d (Klrb1b, Nkrp1c (Klrb1c, and Clr-c (Clec2f genes, suggestive of possible immune selection. Cell-type specific transcription of Nkrp1-Clr genes in a large panel of tissues/organs was determined. Clr-b (Clec2d and Clr-g (Clec2i showed wide expression, while other Clr genes showed more tissue-specific expression patterns. In situ hybridization revealed specific expression of various members of the Clr family in leukocytes/hematopoietic cells of immune organs, various tissue-restricted epithelial cells (including intestinal, kidney tubular, lung, and corneal progenitor epithelial cells, as well as myocytes. In summary, the Nkrp1-Clr gene cluster appears to evolve more slowly relative to the related Ly49 cluster, and likely regulates innate immunosurveillance in a tissue-specific manner.

Alpha-cluster preformation factor within cluster-formation model for odd-A and odd-odd heavy nuclei

Science.gov (United States)

Saleh Ahmed, Saad M.

2017-06-01

The alpha-cluster probability that represents the preformation of alpha particle in alpha-decay nuclei was determined for high-intensity alpha-decay mode odd-A and odd-odd heavy nuclei, 82 CSR) and the hypothesised cluster-formation model (CFM) as in our previous work. Our previous successful determination of phenomenological values of alpha-cluster preformation factors for even-even nuclei motivated us to expand the work to cover other types of nuclei. The formation energy of interior alpha cluster needed to be derived for the different nuclear systems with considering the unpaired-nucleon effect. The results showed the phenomenological value of alpha preformation probability and reflected the unpaired nucleon effect and the magic and sub-magic effects in nuclei. These results and their analyses presented are very useful for future work concerning the calculation of the alpha decay constants and the progress of its theory.

Time Clustered Sampling Can Inflate the Inferred Substitution Rate in Foot-And-Mouth Disease Virus Analyses.

Science.gov (United States)

Pedersen, Casper-Emil T; Frandsen, Peter; Wekesa, Sabenzia N; Heller, Rasmus; Sangula, Abraham K; Wadsworth, Jemma; Knowles, Nick J; Muwanika, Vincent B; Siegismund, Hans R

2015-01-01

With the emergence of analytical software for the inference of viral evolution, a number of studies have focused on estimating important parameters such as the substitution rate and the time to the most recent common ancestor (tMRCA) for rapidly evolving viruses. Coupled with an increasing abundance of sequence data sampled under widely different schemes, an effort to keep results consistent and comparable is needed. This study emphasizes commonly disregarded problems in the inference of evolutionary rates in viral sequence data when sampling is unevenly distributed on a temporal scale through a study of the foot-and-mouth (FMD) disease virus serotypes SAT 1 and SAT 2. Our study shows that clustered temporal sampling in phylogenetic analyses of FMD viruses will strongly bias the inferences of substitution rates and tMRCA because the inferred rates in such data sets reflect a rate closer to the mutation rate rather than the substitution rate. Estimating evolutionary parameters from viral sequences should be performed with due consideration of the differences in short-term and longer-term evolutionary processes occurring within sets of temporally sampled viruses, and studies should carefully consider how samples are combined.

Analyses on the formation of atmospheric particles and stabilized sulphuric acid clusters

Energy Technology Data Exchange (ETDEWEB)

Paasonen, P.

2012-11-01

Aerosol particles have various effects on our life. They affect the visibility and have diverse health effects, but are also applied in various applications, from drug inhalators to pesticides. Additionally, aerosol particles have manifold effects on the Earths' radiation budget and thus on the climate. The strength of the aerosol climate effect is one of the factors causing major uncertainties in the global climate models predicting the future climate change. Aerosol particles are emitted to atmosphere from various anthropogenic and biogenic sources, but they are also formed from precursor vapours in many parts of the world in a process called atmospheric new particle formation (NPF). The uncertainties in aerosol climate effect are partly due to the current lack of knowledge of the mechanisms governing the atmospheric NPF. It is known that gas phase sulphuric acid most certainly plays an important role in atmospheric NPF. However, also other vapours are needed in NPF, but the exact roles or even identities of these vapours are currently not exactly known. In this thesis I present some of the recent advancements in understanding of the atmospheric NPF in terms of the roles of the participating vapours and the meteorological conditions. Since direct measurements of new particle formation rate in the initial size scale of the formed particles (below 2 nm) are so far infrequent in both spatial and temporal scales, indirect methods are needed. The work presented on the following pages approaches the NPF from two directions: by analysing the observed formation rates of particles after they have grown to sizes measurable with widely applied instruments (2 nm or larger), and by measuring and modelling the initial sulphuric acid cluster formation. The obtained results can be summarized as follows. (1) The observed atmospheric new particle formation rates are typically connected with sulphuric acid concentration to the power close to two. (2) Also other compounds, most

Chin Shan analyses show advantages of whole pool multi-rack approach

International Nuclear Information System (INIS)

Singh, K.P.; Soler, A.I.

1991-01-01

Nuclear fuel storage racks are essentially thin-walled, cellular structures of prismatic cross-section. Although the details of design vary from one supplier to another, certain key physical attributes are common to all designs. For example, all racks feature square cells of sufficient opening size and height to enable insertion and withdrawal of the fuel assembly. The array of cells is positioned in a vertical orientation and is supported off the pool slab surface by four or more support legs. The spent fuel pool is filled with the individual fuel racks. The plenum created by the support legs is essential for proper cooling of the fuel assemblies stored in the rack, which relies on natural convective cooling to extract the heat emitted by the spent fuel. However, it has the insalutary effect of making it kinematically less stable. Regulatory authorities require careful and comprehensive analysis of the response of the racks under the seismic motions postulated for the pool slab. Results from whole pool multi-rack (WPMR) analyses at the Chin Shan and Oyster Creek nuclear plants point up the potential inadequacies of single rack 3D analyses, and show just how important it is to carry out WPMR simulations, despite their abstruseness and high cost. (author)

Cluster Decline and Resilience

DEFF Research Database (Denmark)

Østergaard, Christian Richter; Park, Eun Kyung

Most studies on regional clusters focus on identifying factors and processes that make clusters grow. However, sometimes technologies and market conditions suddenly shift, and clusters decline. This paper analyses the process of decline of the wireless communication cluster in Denmark, 1963......-2011. Our longitudinal study reveals that technological lock-in and exit of key firms have contributed to impairment of the cluster’s resilience in adapting to disruptions. Entrepreneurship has a positive effect on cluster resilience, while multinational companies have contradicting effects by bringing...... in new resources to the cluster but being quick to withdraw in times of crisis....

Cluster Physics with Merging Galaxy Clusters

Directory of Open Access Journals (Sweden)

Sandor M. Molnar

2016-02-01

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

Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster

Science.gov (United States)

Syakur, M. A.; Khotimah, B. K.; Rochman, E. M. S.; Satoto, B. D.

2018-04-01

Clustering is a data mining technique used to analyse data that has variations and the number of lots. Clustering was process of grouping data into a cluster, so they contained data that is as similar as possible and different from other cluster objects. SMEs Indonesia has a variety of customers, but SMEs do not have the mapping of these customers so they did not know which customers are loyal or otherwise. Customer mapping is a grouping of customer profiling to facilitate analysis and policy of SMEs in the production of goods, especially batik sales. Researchers will use a combination of K-Means method with elbow to improve efficient and effective k-means performance in processing large amounts of data. K-Means Clustering is a localized optimization method that is sensitive to the selection of the starting position from the midpoint of the cluster. So choosing the starting position from the midpoint of a bad cluster will result in K-Means Clustering algorithm resulting in high errors and poor cluster results. The K-means algorithm has problems in determining the best number of clusters. So Elbow looks for the best number of clusters on the K-means method. Based on the results obtained from the process in determining the best number of clusters with elbow method can produce the same number of clusters K on the amount of different data. The result of determining the best number of clusters with elbow method will be the default for characteristic process based on case study. Measurement of k-means value of k-means has resulted in the best clusters based on SSE values on 500 clusters of batik visitors. The result shows the cluster has a sharp decrease is at K = 3, so K as the cut-off point as the best cluster.

Ethical implications of excessive cluster sizes in cluster randomised trials.

Science.gov (United States)

Hemming, Karla; Taljaard, Monica; Forbes, Gordon; Eldridge, Sandra M; Weijer, Charles

2018-02-20

The cluster randomised trial (CRT) is commonly used in healthcare research. It is the gold-standard study design for evaluating healthcare policy interventions. A key characteristic of this design is that as more participants are included, in a fixed number of clusters, the increase in achievable power will level off. CRTs with cluster sizes that exceed the point of levelling-off will have excessive numbers of participants, even if they do not achieve nominal levels of power. Excessively large cluster sizes may have ethical implications due to exposing trial participants unnecessarily to the burdens of both participating in the trial and the potential risks of harm associated with the intervention. We explore these issues through the use of two case studies. Where data are routinely collected, available at minimum cost and the intervention poses low risk, the ethical implications of excessively large cluster sizes are likely to be low (case study 1). However, to maximise the social benefit of the study, identification of excessive cluster sizes can allow for prespecified and fully powered secondary analyses. In the second case study, while there is no burden through trial participation (because the outcome data are routinely collected and non-identifiable), the intervention might be considered to pose some indirect risk to patients and risks to the healthcare workers. In this case study it is therefore important that the inclusion of excessively large cluster sizes is justifiable on other grounds (perhaps to show sustainability). In any randomised controlled trial, including evaluations of health policy interventions, it is important to minimise the burdens and risks to participants. Funders, researchers and research ethics committees should be aware of the ethical issues of excessively large cluster sizes in cluster trials. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is

Genesis of cluster associations of enterprises

Directory of Open Access Journals (Sweden)

Pulina Tetyana V.

2013-03-01

Full Text Available The goal of the article is the study of genesis of creation of cluster associations of enterprises. It considers genesis of cluster definitions. It shows and analyses components that define the “cluster” concept. Researchers from many countries offer a significant number of definitions of the “cluster” term specifically in the economic direction, but there is no single generally accepted definition as of today. This fact is the result of a significant diversity of cluster structures. The article conducts a comparative analysis of classifications of cluster associations of enterprises. It identifies advantages and shortcomings of the cluster approach both from the position of an enterprise and from the position of a regional economy administration. The article marks out specific features of the life cycle of cluster associations of enterprises, which consists of the preparatory stage and stage of commercialisation. Majority of studies consider the preparatory stage and the stage of commercialisation, which consists of the following stages: entering market with a common brand, growth, maturity and crisis – is, practically, not considered. Taking into account the fact that the main result of cluster activity is the synergetic effect from mutually beneficial co-operation and activity results facilitate ensuring competitiveness of cluster enterprises, regional and national economies, the author gives own definition of a cluster.

Exploring spatial evolution of economic clusters: A case study of Beijing

Science.gov (United States)

Yang, Zhenshan; Sliuzas, Richard; Cai, Jianming; Ottens, Henk F. L.

2012-10-01

An identification of economic clusters and analysing their changing spatial patterns is important for understanding urban economic space dynamics. Previous studies, however, suffer from limitations as a consequence of using fixed geographically areas and not combining functional and spatial dynamics. The paper presents an approach, based on local spatial statistics and the case of Beijing to understand the spatial clustering of industries that are functionally interconnected by common or complementary patterns of demand or supply relations. Using register data of business establishments, it identifies economic clusters and analyses their pattern based on postcodes at different time slices during the period 1983-2002. The study shows how the advanced services occupy the urban centre and key sub centres. The Information and Communication Technology (ICT) cluster is mainly concentrated in the north part of the city and circles the urban centre, and the main manufacturing clusters are evolved in the key sub centers. This type of outcomes improves understanding of urban-economic dynamics, which can support spatial and economic planning.

Mechanistic study on lowering the sensitivity of positive atmospheric pressure photoionization mass spectrometric analyses: size-dependent reactivity of solvent clusters.

Science.gov (United States)

Ahmed, Arif; Choi, Cheol Ho; Kim, Sunghwan

2015-11-15

Understanding the mechanism of atmospheric pressure photoionization (APPI) is important for studies employing APPI liquid chromatography/mass spectrometry (LC/MS). In this study, the APPI mechanism for polyaromatic hydrocarbon (PAH) compounds dissolved in toluene and methanol or water mixture was investigated by use of MS analysis and quantum mechanical simulation. In particular, four different mechanisms that could contribute to the signal reduction were considered based on a combination of MS data and quantum mechanical calculations. The APPI mechanism is clarified by combining MS data and density functional theory (DFT) calculations. To obtain MS data, a positive-mode (+) APPI Q Exactive Orbitrap mass spectrometer was used to analyze each solution. DFT calculations were performed using the general atomic and molecular electronic structure system (GAMESS). The experimental results indicated that methanol significantly reduced the signal in (+) APPI, but no significative signal reduction was observed when water was used as a co-solvent with toluene. The signal reduction is more significant especially for molecular ions than for protonated ions. Therefore, important information about the mechanism of methanol-induced signal reduction in (+) APPI-MS can be gained due its negative impact on APPI efficiency. The size-dependent reactivity of methanol clusters ((CH3 OH)n , n = 1-8) is an important factor in determining the sensitivity of (+) APPI-MS analyses. Clusters can compete with toluene radical ions for electrons. The reactivity increases as the sizes of the methanol clusters increase and this effect can be caused by the size-dependent ionization energy of the solvent clusters. The resulting increase in cluster reactivity explains the flow rate and temperature-dependent signal reduction observed in the analytes. Based on the results presented here, minimizing the sizes of methanol clusters can improve the sensitivity of LC/(+)-APPI-MS. Copyright © 2015 John

Photometric analyses of abundances in dwarf spheroidal galaxies and globular clusters

International Nuclear Information System (INIS)

Light, R.M.

1988-01-01

This study investigated the abundance characteristics of several dwarf spheroidal galaxies. The chemical properties of stars in these galaxies are tracers of the origin and evolution of their stellar populations, and thus can provide constraints on the theories of their formation. To derive this abundance information, photometric observations of stars in a sample of globular clusters, covering a large range in metallicity, were analyzed. Parameters describing the position of the red giant branch were found to correlate very well with cluster metallicity over a large range in abundance. These measurements, made in the Thuan-Gunn photometry system, provide ranking schemes which are, with accurate photometry, more sensitive to changes in metallicity than similar broadband BV parameters. The relations were used to derive an improved estimate of the metallicity of cluster NGC 5053. These metallicity relations were used to analyze the Thuan-Gunn system photometry produced for the Sculptor, Ursa Minor, and Carina galaxies. The excellent agreement between their metallicities and those from other previous studies indicates that globular cluster red giant branch parameters are very useful in ranking dwarf spheroidal populations by metallicity. Together with other galaxian data, strong correlations can be seen between the mean metallicities and dispersions in metallicity and the luminosities of the dwarf spheroidal galaxies. These trends also seem to apply to members of the dwarf elliptical class of galaxies. The ramifications that these correlations and the existence of a metallicity gradient in Sculptor have on the formation of the dwarf spheroidals are discussed

Lifting to cluster-tilting objects in higher cluster categories

OpenAIRE

Liu, Pin

2008-01-01

In this note, we consider the $d$-cluster-tilted algebras, the endomorphism algebras of $d$-cluster-tilting objects in $d$-cluster categories. We show that a tilting module over such an algebra lifts to a $d$-cluster-tilting object in this $d$-cluster category.

A Data-origin Authentication Protocol Based on ONOS Cluster

Directory of Open Access Journals (Sweden)

Qin Hua

2016-01-01

Full Text Available This paper is aim to propose a data-origin authentication protocol based on ONOS cluster. ONOS is a SDN controller which can work under a distributed environment. However, the security of an ONOS cluster is seldom considered, and the communication in an ONOS cluster may suffer from lots of security threats. In this paper, we used a two-tier self-renewable hash chain for identity authentication and data-origin authentication. We analyse the security and overhead of our proposal and made a comparison with current security measure. It showed that with the help of our proposal, communication in an ONOS cluster could be protected from identity forging, replay attacks, data tampering, MITM attacks and repudiation, also the computational overhead would decrease apparently.

Is sibling rivalry fatal?: siblings and mortality clustering.

Science.gov (United States)

Kippen, Rebecca; Walters, Sarah

2012-01-01

Evidence drawn from nineteenth-century Belgian population registers shows that the presence of similarly aged siblings competing for resources within a household increases the probability of death for children younger than five, even when controlling for the preceding birth interval and multiple births. Furthermore, in this period of Belgian history, such mortality tended to cluster in certain families. The findings suggest the importance of segmenting the mortality of siblings younger than five by age group, of considering the presence of siblings as a time-varying covariate, and of factoring mortality clustering into analyses.

Application of cluster and discriminant analyses to diagnose lithological heterogeneity of the parent material according to its particle-size distribution

Science.gov (United States)

Giniyatullin, K. G.; Valeeva, A. A.; Smirnova, E. V.

2017-08-01

Particle-size distribution in soddy-podzolic and light gray forest soils of the Botanical Garden of Kazan Federal University has been studied. The cluster analysis of data on the samples from genetic soil horizons attests to the lithological heterogeneity of the profiles of all the studied soils. It is probable that they are developed from the two-layered sediments with the upper colluvial layer underlain by the alluvial layer. According to the discriminant analysis, the major contribution to the discrimination of colluvial and alluvial layers is that of the fraction >0.25 mm. The results of canonical analysis show that there is only one significant discriminant function that separates alluvial and colluvial sediments on the investigated territory. The discriminant function correlates with the contents of fractions 0.05-0.01, 0.25-0.05, and >0.25 mm. Classification functions making it possible to distinguish between alluvial and colluvial sediments have been calculated. Statistical assessment of particle-size distribution data obtained for the plow horizons on ten plowed fields within the garden indicates that this horizon is formed from colluvial sediments. We conclude that the contents of separate fractions and their ratios cannot be used as a universal criterion of the lithological heterogeneity. However, adequate combination of the cluster and discriminant analyses makes it possible to give a comprehensive assessment of the lithology of soil samples from data on the contents of sand and silt fractions, which considerably increases the information value and reliability of the results.

The ergot alkaloid gene cluster: Functional analyses and evolutionary aspects

Czech Academy of Sciences Publication Activity Database

Lorenz, N.; Haarmann, T.; Pažoutová, Sylvie; Jung, M.; Tudzynski, P.

2009-01-01

Roč. 70, 15-16 (2009), s. 1822-1832 ISSN 0031-9422 Institutional research plan: CEZ:AV0Z50200510 Keywords : Claviceps purpurea * Ergot fungus * Ergot alkaloid gene cluster Subject RIV: EE - Microbiology, Virology Impact factor: 3.104, year: 2009

Modulated modularity clustering as an exploratory tool for functional genomic inference.

Directory of Open Access Journals (Sweden)

Eric A Stone

2009-05-01

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

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

Science.gov (United States)

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Mental State Talk Structure in Children’s Narratives: A Cluster Analysis

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Giuliana Pinto

2017-01-01

Full Text Available This study analysed children’s Theory of Mind (ToM as assessed by mental state talk in oral narratives. We hypothesized that the children’s mental state talk in narratives has an underlying structure, with specific terms organized in clusters. Ninety-eight children attending the last year of kindergarten were asked to tell a story twice, at the beginning and at the end of the school year. Mental state talk was analysed by identifying terms and expressions referring to perceptual, physiological, emotional, willingness, cognitive, moral, and sociorelational states. The cluster analysis showed that children’s mental state talk is organized in two main clusters: perceptual states and affective states. Results from the study confirm the feasibility of narratives as an outlet to inquire mental state talk and offer a more fine-grained analysis of mental state talk structure.

Structure and Sequence Analyses of Clustered Protocadherins Reveal Antiparallel Interactions that Mediate Homophilic Specificity.

Science.gov (United States)

Nicoludis, John M; Lau, Sze-Yi; Schärfe, Charlotta P I; Marks, Debora S; Weihofen, Wilhelm A; Gaudet, Rachelle

2015-11-03

Clustered protocadherin (Pcdh) proteins mediate dendritic self-avoidance in neurons via specific homophilic interactions in their extracellular cadherin (EC) domains. We determined crystal structures of EC1-EC3, containing the homophilic specificity-determining region, of two mouse clustered Pcdh isoforms (PcdhγA1 and PcdhγC3) to investigate the nature of the homophilic interaction. Within the crystal lattices, we observe antiparallel interfaces consistent with a role in trans cell-cell contact. Antiparallel dimerization is supported by evolutionary correlations. Two interfaces, located primarily on EC2-EC3, involve distinctive clustered Pcdh structure and sequence motifs, lack predicted glycosylation sites, and contain residues highly conserved in orthologs but not paralogs, pointing toward their biological significance as homophilic interaction interfaces. These two interfaces are similar yet distinct, reflecting a possible difference in interaction architecture between clustered Pcdh subfamilies. These structures initiate a molecular understanding of clustered Pcdh assemblies that are required to produce functional neuronal networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

Science.gov (United States)

Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

2014-11-01

Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Co-clustering models, algorithms and applications

CERN Document Server

Govaert, Gérard

2013-01-01

Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach. Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixture

The Evolution of cluster concept in Catalonia : the case of Cork Cluster – AECORK

OpenAIRE

Serarols Tarrés, Joyce

2015-01-01

The aim of this final degree project is two-fold: first, to introduce the evolutionary concept of the cluster in Catalonia from a strategic perspective and, second, to analyse the case of the Catalan Cork cluster located in the province of Girona, that is, the northeast of Spain

Integrative cluster analysis in bioinformatics

CERN Document Server

Abu-Jamous, Basel; Nandi, Asoke K

2015-01-01

Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o

Diametrical clustering for identifying anti-correlated gene clusters.

Science.gov (United States)

Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

2003-09-01

Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

X-ray aspects of the DAFT/FADA clusters

Science.gov (United States)

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

2012-12-01

We have undertaken the DAFT/FADA survey with the aim of applying constraints on dark energy based on weak lensing tomography as well as obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range [0.4,0.9] for which there are HST archive data. We have analysed the XMM-Newton data available for 42 of these clusters to derive their X-ray temperatures and luminosities and search for substructures. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. We present preliminary results on the coupled X-ray and dynamical analyses of these clusters.

Cluster-cluster correlations in the two-dimensional stationary Ising-model

International Nuclear Information System (INIS)

Klassmann, A.

1997-01-01

In numerical integration of the Cahn-Hillard equation, which describes Oswald rising in a two-phase matrix, N. Masbaum showed that spatial correlations between clusters scale with respect to the mean cluster size (itself a function of time). T. B. Liverpool showed by Monte Carlo simulations for the Ising model that the analogous correlations have a similar form. Both demonstrated that immediately around each cluster there is some depletion area followed by something like a ring of clusters of the same size as the original one. More precisely, it has been shown that the distribution of clusters around a given cluster looks like a sinus-curve decaying exponentially with respect to the distance to a constant value

Clusters of galaxies as tools in observational cosmology : results from x-ray analysis

International Nuclear Information System (INIS)

Weratschnig, J.M.

2009-01-01

Clusters of galaxies are the largest gravitationally bound structures in the universe. They can be used as ideal tools to study large scale structure formation (e.g. when studying merger clusters) and provide highly interesting environments to analyse several characteristic interaction processes (like ram pressure stripping of galaxies, magnetic fields). In this dissertation thesis, we have studied several clusters of galaxies using X-ray observations. To obtain scientific results, we have applied different data reduction and analysis methods. With a combination of morphological and spectral analysis, the merger cluster Abell 514 was studied in much detail. It has a highly interesting morphology and shows signs for an ongoing merger as well as a shock. using a new method to detect substructure, we have analysed several clusters to determine whether any substructure is present in the X-ray image. This hints towards a real structure in the distribution of the intra-cluster medium (ICM) and is evidence for ongoing mergers. The results from this analysis are extensively used with the cluster of galaxies Abell S1136. Here, we study the ICM distribution and compare its structure with the spatial distribution of star forming galaxies. Cluster magnetic fields are another important topic of my thesis. They can be studied in Radio observations, which can be put into relation with results from X-ray observations. using observational data from several clusters, we could support the theory that cluster magnetic fields are frozen into the ICM. (author)

Applications of Cluster Analysis to the Creation of Perfectionism Profiles: A Comparison of two Clustering Approaches

Directory of Open Access Journals (Sweden)

Jocelyn H Bolin

2014-04-01

Full Text Available Although traditional clustering methods (e.g., K-means have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches.

Science.gov (United States)

Bolin, Jocelyn H; Edwards, Julianne M; Finch, W Holmes; Cassady, Jerrell C

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Cluster development in the SA tooling industry

Directory of Open Access Journals (Sweden)

Von Leipzig, Konrad

2015-11-01

Full Text Available This paper explores the concept of clustering in general, analysing research and experiences in different countries and regions, and summarising factors leading to success or contributing to failure of specific cluster initiatives. Based on this, requirements for the establishment of clusters are summarised. Next, initiatives especially in the South African tool and die making (TDM industry are considered. Through a benchmarking approach, the strengths and weaknesses of individual local tool rooms are analysed, and conclusions are drawn particularly about South African characteristics of the industry. From these results, and from structured interviews with individual tool room owners, difficulties in the establishment of a South African tooling cluster are explored, and specific areas of concern are pointed out.

How do childhood diagnoses of type 1 diabetes cluster in time?

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Colin R Muirhead

Full Text Available BACKGROUND: Previous studies have indicated that type 1 diabetes may have an infectious origin. The presence of temporal clustering-an irregular temporal distribution of cases--would provide additional evidence that occurrence may be linked with an agent that displays epidemicity. We tested for the presence and form of temporal clustering using population- based data from northeast England. MATERIALS AND METHODS: The study analysed data on children aged 0-14 years diagnosed with type 1 diabetes during the period 1990-2007 and resident in a defined geographical region of northeast England (Northumberland, Newcastle upon Tyne, and North Tyneside. Tests for temporal clustering by time of diagnosis were applied using a modified version of the Potthoff-Whittinghill method. RESULTS: The study analysed 468 cases of children diagnosed with type 1 diabetes. There was highly statistically significant evidence of temporal clustering over periods of a few months and over longer time intervals (p<0.001. The clustering within years did not show a consistent seasonal pattern. CONCLUSIONS: The study adds to the growing body of literature that supports the involvement of infectious agents in the aetiology of type 1 diabetes in children. Specifically it suggests that the precipitating agent or agents involved might be an infection that occurs in "mini-epidemics".

Properties of an ionised-cluster beam from a vaporised-cluster ion source

International Nuclear Information System (INIS)

Takagi, T.; Yamada, I.; Sasaki, A.

1978-01-01

A new type of ion source vaporised-metal cluster ion source, has been developed for deposition and epitaxy. A cluster consisting of 10 2 to 10 3 atoms coupled loosely together is formed by adiabatic expansion ejecting the vapour of materials into a high-vacuum region through the nozzle of a heated crucible. The clusters are ionised by electron bombardment and accelerated with neutral clusters toward a substrate. In this paper, mechanisms of cluster formation experimental results of the cluster size (atoms/cluster) and its distribution, and characteristics of the cluster ion beams are reported. The size is calculated from the kinetic equation E = (1/2)mNVsub(ej) 2 , where E is the cluster beam energy, Vsub(ej) is the ejection velocity, m is the mass of atom and N is the cluster size. The energy and the velocity of the cluster are measured by an electrostatic 127 0 energy analyser and a rotating disc system, respectively. The cluster size obtained for Ag is about 5 x 10 2 to 2 x 10 3 atoms. The retarding potential method is used to confirm the results for Ag. The same dependence on cluster size for metals such as Ag, Cu and Pb has been obtained in previous experiments. In the cluster state the cluster ion beam is easily produced by electron bombardment. About 50% of ionised clusters are obtained under typical operation conditions, because of the large ionisation cross sections of the clusters. To obtain a uniform spatial distribution, the ionising electrode system is also discussed. The new techniques are termed ionised-cluster beam deposition (ICBD) and epitaxy (ICBE). (author)

Prioritizing the risk of plant pests by clustering methods; self-organising maps, k-means and hierarchical clustering

Directory of Open Access Journals (Sweden)

Susan Worner

2013-09-01

Full Text Available For greater preparedness, pest risk assessors are required to prioritise long lists of pest species with potential to establish and cause significant impact in an endangered area. Such prioritization is often qualitative, subjective, and sometimes biased, relying mostly on expert and stakeholder consultation. In recent years, cluster based analyses have been used to investigate regional pest species assemblages or pest profiles to indicate the risk of new organism establishment. Such an approach is based on the premise that the co-occurrence of well-known global invasive pest species in a region is not random, and that the pest species profile or assemblage integrates complex functional relationships that are difficult to tease apart. In other words, the assemblage can help identify and prioritise species that pose a threat in a target region. A computational intelligence method called a Kohonen self-organizing map (SOM, a type of artificial neural network, was the first clustering method applied to analyse assemblages of invasive pests. The SOM is a well known dimension reduction and visualization method especially useful for high dimensional data that more conventional clustering methods may not analyse suitably. Like all clustering algorithms, the SOM can give details of clusters that identify regions with similar pest assemblages, possible donor and recipient regions. More important, however SOM connection weights that result from the analysis can be used to rank the strength of association of each species within each regional assemblage. Species with high weights that are not already established in the target region are identified as high risk. However, the SOM analysis is only the first step in a process to assess risk to be used alongside or incorporated within other measures. Here we illustrate the application of SOM analyses in a range of contexts in invasive species risk assessment, and discuss other clustering methods such as k

Properties of ammonium ion-water clusters: analyses of structure evolution, noncovalent interactions, and temperature and humidity effects.

Science.gov (United States)

Pei, Shi-Tu; Jiang, Shuai; Liu, Yi-Rong; Huang, Teng; Xu, Kang-Ming; Wen, Hui; Zhu, Yu-Peng; Huang, Wei

2015-03-26

Although ammonium ion-water clusters are abundant in the biosphere, some information regarding these clusters, such as their growth route, the influence of temperature and humidity, and the concentrations of various hydrated clusters, is lacking. In this study, theoretical calculations are performed on ammonium ion-water clusters. These theoretical calculations are focused on determining the following characteristics: (1) the pattern of cluster growth; (2) the percentages of clusters of the same size at different temperatures and humidities; (3) the distributions of different isomers for the same size clusters at different temperatures; (4) the relative strengths of the noncovalent interactions for clusters of different sizes. The results suggest that the dipole moment may be very significant for the ammonium ion-water system, and some new stable isomers were found. The nucleation of ammonium ions and water molecules is favorable at low temperatures; thus, the clusters observed at high altitudes might not be present at low altitudes. High humidity can contribute to the formation of large ammonium ion-water clusters, whereas the formation of small clusters may be favorable under low-humidity conditions. The potential energy surfaces (PES) of these different sized clusters are complicated and differ according to the distribution of isomers at different temperatures. Some similar structures are observed between NH4(+)(H2O)n and M(H2O)n (where M represents an alkali metal ion or water molecule); when n = 8, the clusters begin to form the closed-cage geometry. As the cluster size increases, these interactions become progressively weaker. The successive binding energy at the DF-MP2-F12/VDZ-F12 level is better than that at the PW91PW91/6-311++G(3df, 3pd) level and is consistent with the experimentally determined values.

Cluster dynamics at different cluster size and incident laser wavelengths

International Nuclear Information System (INIS)

Desai, Tara; Bernardinello, Andrea

2002-01-01

X-ray emission spectra from aluminum clusters of diameter -0.4 μm and gold clusters of dia. ∼1.25 μm are experimentally studied by irradiating the cluster foil targets with 1.06 μm laser, 10 ns (FWHM) at an intensity ∼10 12 W/cm 2 . Aluminum clusters show a different spectra compared to bulk material whereas gold cluster evolve towards bulk gold. Experimental data are analyzed on the basis of cluster dimension, laser wavelength and pulse duration. PIC simulations are performed to study the behavior of clusters at higher intensity I≥10 17 W/cm 2 for different size of the clusters irradiated at different laser wavelengths. Results indicate the dependence of cluster dynamics on cluster size and incident laser wavelength

Emulating galaxy clustering and galaxy-galaxy lensing into the deeply nonlinear regime: methodology, information, and forecasts

OpenAIRE

Wibking, Benjamin D.; Salcedo, Andrés N.; Weinberg, David H.; Garrison, Lehman H.; Ferrer, Douglas; Tinker, Jeremy; Eisenstein, Daniel; Metchnik, Marc; Pinto, Philip

2017-01-01

The combination of galaxy-galaxy lensing (GGL) with galaxy clustering is one of the most promising routes to determining the amplitude of matter clustering at low redshifts. We show that extending clustering+GGL analyses from the linear regime down to $\\sim 0.5 \\, h^{-1}$ Mpc scales increases their constraining power considerably, even after marginalizing over a flexible model of non-linear galaxy bias. Using a grid of cosmological N-body simulations, we construct a Taylor-expansion emulator ...

Improving clustering with metabolic pathway data.

Science.gov (United States)

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

2014-04-10

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

75 FR 53667 - Space Coast Regional Innovation Cluster Competition

Science.gov (United States)

2010-09-01

... Coast Regional Innovation Cluster Competition AGENCY: Economic Development Administration (EDA... upcoming availability of funding for the Space Coast Regional Innovation Cluster (RIC) Competition under... economic development initiatives aligned with regional cluster and competitiveness analyses to sustain the...

Spatial and space-time clustering of tuberculosis in Gurage Zone, Southern Ethiopia.

Science.gov (United States)

Tadesse, Sebsibe; Enqueselassie, Fikre; Hagos, Seifu

2018-01-01

Spatial targeting is advocated as an effective method that contributes for achieving tuberculosis control in high-burden countries. However, there is a paucity of studies clarifying the spatial nature of the disease in these countries. This study aims to identify the location, size and risk of purely spatial and space-time clusters for high occurrence of tuberculosis in Gurage Zone, Southern Ethiopia during 2007 to 2016. A total of 15,805 patient data that were retrieved from unit TB registers were included in the final analyses. The spatial and space-time cluster analyses were performed using the global Moran's I, Getis-Ord [Formula: see text] and Kulldorff's scan statistics. Eleven purely spatial and three space-time clusters were detected (P <0.001).The clusters were concentrated in border areas of the Gurage Zone. There were considerable spatial variations in the risk of tuberculosis by year during the study period. This study showed that tuberculosis clusters were mainly concentrated at border areas of the Gurage Zone during the study period, suggesting that there has been sustained transmission of the disease within these locations. The findings may help intensify the implementation of tuberculosis control activities in these locations. Further study is warranted to explore the roles of various ecological factors on the observed spatial distribution of tuberculosis.

The Business Cluster's Distribution e-Channels

OpenAIRE

Milan Davidovic

2011-01-01

The business cluster cooperative potential and business capability improvement are dependent on e-business implementation and business model change dynamics in cluster and his members based in new and existing distribution channels, customer relationships management and supplychain integration. In this work analyse cluster’s e-business models, e-commerce forms and distribution e-channels for three business cases: when cluster members are oriented on own business, on cooperative’s project or c...

Structures, stabilities, and electronic properties for rare-earth lanthanum doped gold clusters

International Nuclear Information System (INIS)

Zhao, Ya-Ru

2015-01-01

The structures, stabilities, and electronic properties of rare-earth lanthanum doped gold La 2 Au n (n = 1-9) and pure gold Au n (n ≤ 11) clusters have been investigated by using density functional theory. The optimized geometries show that the lowest energy structures of La 2 Au n clusters favour the 3D structure at n ≥ 3. The lanthanum atoms can strongly enhance the stabilities of gold clusters and tend to occupy the most highly coordinated position. By analysing the gap, vertical ionization potential, and chemical hardness, it is found that the La 2 Au 6 isomer possesses higher stability for small-sized La 2 Au n clusters (n = 1-9). The charges in the La 2 Au n clusters transfer from La atoms to the Au n host. In addition, Wiberg bond indices analysis reveals that the intensity of different bonds of La 2 Au n clusters exhibits a sequence of La-La bond > La-Au bond > Au-Au bond.

Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means

Science.gov (United States)

Saharan, S.; Baragona, R.; Nor, M. E.; Salleh, R. M.; Asrah, N. M.

2018-04-01

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.

Supersymmetry for nuclear cluster systems

International Nuclear Information System (INIS)

Levai, G.; Cseh, J.; Van Isacker, P.

2001-01-01

A supersymmetry scheme is proposed for nuclear cluster systems. The bosonic sector of the superalgebra describes the relative motion of the clusters, while its fermionic sector is associated with their internal structure. An example of core+α configurations is discussed in which the core is a p-shell nucleus and the underlying superalgebra is U(4/12). The α-cluster states of the nuclei 20 Ne and 19 F are analysed and correlations between their spectra, electric quadrupole transitions, and one-nucleon transfer reactions are interpreted in terms of U(4/12) supersymmetry. (author)

Relevant Subspace Clustering

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

2009-01-01

Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace...... clusters. Their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. In this work, we propose a novel model for relevant subspace clustering (RESCU). We present a global optimization which detects the most interesting non-redundant subspace clusters...... achieves top clustering quality while competing approaches show greatly varying performance....

Duplicated Gephyrin Genes Showing Distinct Tissue Distribution and Alternative Splicing Patterns Mediate Molybdenum Cofactor Biosynthesis, Glycine Receptor Clustering, and Escape Behavior in Zebrafish*

Science.gov (United States)

Ogino, Kazutoyo; Ramsden, Sarah L.; Keib, Natalie; Schwarz, Günter; Harvey, Robert J.; Hirata, Hiromi

2011-01-01

Gephyrin mediates the postsynaptic clustering of glycine receptors (GlyRs) and GABAA receptors at inhibitory synapses and molybdenum-dependent enzyme (molybdoenzyme) activity in non-neuronal tissues. Gephyrin knock-out mice show a phenotype resembling both defective glycinergic transmission and molybdenum cofactor (Moco) deficiency and die within 1 day of birth due to starvation and dyspnea resulting from deficits in motor and respiratory networks, respectively. To address whether gephyrin function is conserved among vertebrates and whether gephyrin deficiency affects molybdoenzyme activity and motor development, we cloned and characterized zebrafish gephyrin genes. We report here that zebrafish have two gephyrin genes, gphna and gphnb. The former is expressed in all tissues and has both C3 and C4 cassette exons, and the latter is expressed predominantly in the brain and spinal cord and harbors only C4 cassette exons. We confirmed that all of the gphna and gphnb splicing isoforms have Moco synthetic activity. Antisense morpholino knockdown of either gphna or gphnb alone did not disturb synaptic clusters of GlyRs in the spinal cord and did not affect touch-evoked escape behaviors. However, on knockdown of both gphna and gphnb, embryos showed impairments in GlyR clustering in the spinal cord and, as a consequence, demonstrated touch-evoked startle response behavior by contracting antagonistic muscles simultaneously, instead of displaying early coiling and late swimming behaviors, which are executed by side-to-side muscle contractions. These data indicate that duplicated gephyrin genes mediate Moco biosynthesis and control postsynaptic clustering of GlyRs, thereby mediating key escape behaviors in zebrafish. PMID:20843816

clusterMaker: a multi-algorithm clustering plugin for Cytoscape

Directory of Open Access Journals (Sweden)

Morris John H

2011-11-01

Full Text Available Abstract Background In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view, k-means, k-medoid, SCPS, AutoSOME, and native (Java MCL. Results Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. Conclusions The Cytoscape plugin cluster

Subspace K-means clustering.

Science.gov (United States)

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

2013-12-01

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

Elemental abundance and analyses with coadded DAO spectrograms

International Nuclear Information System (INIS)

Adelman, S.J.

1987-01-01

One can improve the quality of elemental abundance analyses by using higher signal-to-noise data than has been the practice at high resolution. The procedures developed at the Dominion Astrophysical Observatory to coadd high-dispersion coude spectrograms are used with a minimum of 10 6.5 A mm -1 IIa-O spectrograms of each of three field horizontal-branch (FHB)A stars to increase the signal-to-noise ratio of the photographic data over a considerable wavelength region. Fine analyses of the sharp-lined prototype FHB stars HD 109995 and 161817 show an internal consistency which justifies this effort. Their photospheric elemental abundances are similar to those of Population II globular cluster giants. (author)

The X-ray spectra of clusters of galaxies and their relationship to other cluster properties

International Nuclear Information System (INIS)

Mitchell, R.J.; Dickens, R.J.; Burnell, S.J.B.; Culhane, J.L.

1979-01-01

New observations with the MSSL proportional counter spectrometer on the Ariel V satellite of the X-ray spectra of 20 candidate clusters of galaxies are reported. The data are compared with the results from the OSO-8 satellite and the combined sample of some 30 cluster X-ray spectra are analysed. The present study finds generally larger values of Lsub(X) than do Uhuru or the SSI, which, because of the larger field of view, may indicate significant amounts of hot gas away from the cluster centres. The validity of all X-ray cluster identifications has been examined, and sources have been classified according to certainty of identification. The incidence of X-ray line emission from the clusters has been investigated and temperatures, kTsub(X), have been derived on the basis of an isothermal model. Relationships between X-ray, optical and radio properties of the clusters have been studied. The more massive, centrally condensed clusters generally contain higher temperature gas and have a greater luminosity than the less massive, more irregular clusters. (author)

Mobility of hydrogen-helium clusters in tungsten studied by molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Grigorev, Petr, E-mail: grigorievpit@gmail.com [SCK-CEN, Nuclear Materials Science Institute, Boeretang 200, Mol, 2400 (Belgium); Ghent University, Applied Physics EA17 FUSION-DC, St.Pietersnieuwstraat, 41 B4, B-9000, Gent (Belgium); Department of Experimental Nuclear Physics K-89, Institute of Physics, Nanotechnologies, and Telecommunications, Peter the Great St.Petersburg Polytechnic University, St. Petersburg (Russian Federation); Terentyev, Dmitry; Bonny, Giovanni [SCK-CEN, Nuclear Materials Science Institute, Boeretang 200, Mol, 2400 (Belgium); Zhurkin, Evgeny E. [Department of Experimental Nuclear Physics K-89, Institute of Physics, Nanotechnologies, and Telecommunications, Peter the Great St.Petersburg Polytechnic University, St. Petersburg (Russian Federation); Oost, Guido van [Ghent University, Applied Physics EA17 FUSION-DC, St.Pietersnieuwstraat, 41 B4, B-9000, Gent (Belgium); Noterdaeme, Jean-Marie [Ghent University, Applied Physics EA17 FUSION-DC, St.Pietersnieuwstraat, 41 B4, B-9000, Gent (Belgium); Max-Planck-Institut für Plasmaphysik, Garching (Germany)

2016-06-15

Tungsten is a primary candidate material for plasma facing components in fusion reactors. Interaction of plasma components with the material is unavoidable and will lead to degradation of the performance and the lifetime of the in-vessel components. In order to gain better understanding the mechanisms driving the material degradation at atomic level, atomistic simulations are employed. In this work we study migration, stability and self-trapping properties of pure helium and mixed helium-hydrogen clusters in tungsten by means of molecular dynamics simulations. We test two versions of an embedded atom model interatomic potential by comparing it with ab initio data regarding the binding properties of He clusters. By analysing the trajectories of the clusters during molecular dynamics simulations at finite temperatures we obtain the diffusion parameters. The results show that the diffusivity of mixed clusters is significantly lower, than that of pure helium clusters. The latter suggest that the formation of mixed clusters during mixed hydrogen helium plasma exposure will affect the helium diffusivity in the material.

Rearrangement of cluster structure during fission processes

DEFF Research Database (Denmark)

Lyalin, Andrey G.; Obolensky, Oleg I.; Solov'yov, Andrey V.

2004-01-01

Results of molecular dynamics simulations of fission reactions $Na_10^2+ -->Na_7^++ Na_3^+ and Na_18^2+--> 2Na_9^+ are presented. The dependence of the fission barriers on the isomer structure of the parent cluster is analysed. It is demonstrated that the energy necessary for removing homothetic...... groups of atoms from the parent cluster is largely independent of the isomer form of the parent cluster. The importance of rearrangement of the cluster structure during the fission process is elucidated. This rearrangement may include transition to another isomer state of the parent cluster before actual...

A hot X-ray filament associated with A3017 galaxy cluster

Science.gov (United States)

Parekh, V.; Durret, F.; Padmanabh, P.; Pandge, M. B.

2017-09-01

Recent simulations and observations have shown large-scale filaments in the cosmic web connecting nodes, with accreting materials (baryonic and dark matter) flowing through them. Current high-sensitivity observations also show that the propagation of shocks through filaments can heat them up and make filaments visible between two or more galaxy clusters or around massive clusters, based on optical and/or X-ray observations. We are reporting here the special case of the cluster A3017 associated with a hot filament. The temperature of the filament is 3.4^{-0.77}_{+1.30} keV and its length is ∼1 Mpc. We have analysed its archival Chandra data and report various properties. We also analysed GMRT 235/610 MHz radio data. Radio observations have revealed symmetric two-sided lobes that fill cavities in the A3017 cluster core region, associated with central active galactic nucleus. In the radio map, we also noticed a peculiar linear vertical radio structure in the X-ray filament region which might be associated with a cosmic filament shock. This radio structure could be a radio phoenix or old plasma where an old relativistic population is re-accelerated by shock propagation. Finally, we put an upper limit on the radio luminosity of the filament region.

THE SLOAN DIGITAL SKY SURVEY CO-ADD: CROSS-CORRELATION WEAK LENSING AND TOMOGRAPHY OF GALAXY CLUSTERS

International Nuclear Information System (INIS)

Simet, Melanie; Dodelson, Scott; Kubo, Jeffrey M.; Annis, James T.; Hao Jiangang; Johnston, David; Lin, Huan; Soares-Santos, Marcelle; Reis, Ribamar R. R.; Seo, Hee-Jong

2012-01-01

The shapes of distant galaxies are sheared by intervening galaxy clusters. We examine this effect in Stripe 82, a 275 deg 2 region observed multiple times in the Sloan Digital Sky Survey (SDSS) and co-added to achieve greater depth. We obtain a mass-richness calibration that is similar to other SDSS analyses, demonstrating that the co-addition process did not adversely affect the lensing signal. We also propose a new parameterization of the effect of tomography on the cluster lensing signal which does not require binning in redshift, and we show that using this parameterization we can detect tomography for stacked clusters at varying redshifts. Finally, due to the sensitivity of the tomographic detection to accurately marginalize over the effect of the cluster mass, we show that tomography at low redshift (where dependence on exact cosmological models is weak) can be used to constrain mass profiles in clusters.

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

Science.gov (United States)

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

2013-04-01

We have undertaken the DAFT/FADA survey with the double aim of setting constraints on dark energy based on weak lensing tomography and of obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range 0.4-0.9 for which there were HST archive data. We have analysed the XMM-Newton data available for 42 of these clusters to derive their X-ray temperatures and luminosities and search for substructures. Out of these, a spatial analysis was possible for 30 clusters, but only 23 had deep enough X-ray data for a really robust analysis. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. Altogether, the X-ray sample of 23 clusters and the optical sample of 26 clusters have 14 clusters in common. We present preliminary results on the coupled X-ray and dynamical analyses of these 14 clusters.

Clustering of dietary intake and sedentary behavior in 2-year-old children.

Science.gov (United States)

Gubbels, Jessica S; Kremers, Stef P J; Stafleu, Annette; Dagnelie, Pieter C; de Vries, Sanne I; de Vries, Nanne K; Thijs, Carel

2009-08-01

To examine clustering of energy balance-related behaviors (EBRBs) in young children. This is crucial because lifestyle habits are formed at an early age and track in later life. This study is the first to examine EBRB clustering in children as young as 2 years. Cross-sectional data originated from the Child, Parent and Health: Lifestyle and Genetic Constitution (KOALA) Birth Cohort Study. Parents of 2578 2-year-old children completed a questionnaire. Correlation analyses, principal component analyses, and linear regression analyses were performed to examine clustering of EBRBs. We found modest but consistent correlations in EBRBs. Two clusters emerged: a "sedentary-snacking cluster" and a "fiber cluster." Television viewing clustered with computer use and unhealthy dietary behaviors. Children who frequently consumed vegetables also consumed fruit and brown bread more often and white bread less often. Lower maternal education and maternal obesity were associated with high scores on the sedentary-snacking cluster, whereas higher educational level was associated with high fiber cluster scores. Obesity-prone behavioral clusters are already visible in 2-year-old children and are related to maternal characteristics. The findings suggest that obesity prevention should apply an integrated approach to physical activity and dietary intake in early childhood.

Hedgehog signaling pathway is active in GBM with GLI1 mRNA expression showing a single continuous distribution rather than discrete high/low clusters.

Science.gov (United States)

Chandra, Vikas; Das, Tapojyoti; Gulati, Puneet; Biswas, Nidhan K; Rote, Sarang; Chatterjee, Uttara; Ghosh, Samarendra N; Deb, Sumit; Saha, Suniti K; Chowdhury, Anup K; Ghosh, Subhashish; Rudin, Charles M; Mukherjee, Ankur; Basu, Analabha; Dhara, Surajit

2015-01-01

Hedgehog (Hh) signaling pathway is a valid therapeutic target in a wide range of malignancies. We focus here on glioblastoma multiforme (GBM), a lethal malignancy of the central nervous system (CNS). By analyzing RNA-sequencing based transcriptomics data on 149 clinical cases of TCGA-GBM database we show here a strong correlation (r = 0.7) between GLI1 and PTCH1 mRNA expression--as a hallmark of the canonical Hh-pathway activity in this malignancy. GLI1 mRNA expression varied in 3 orders of magnitude among the GBM patients of the same cohort showing a single continuous distribution-unlike the discrete high/low-GLI1 mRNA expressing clusters of medulloblastoma (MB). When compared with MB as a reference, the median GLI1 mRNA expression in GBM appeared 14.8 fold lower than that of the "high-Hh" cluster of MB but 5.6 fold higher than that of the "low-Hh" cluster of MB. Next, we demonstrated statistically significant up- and down-regulation of GLI1 mRNA expressions in GBM patient-derived low-passage neurospheres in vitro by sonic hedgehog ligand-enriched conditioned media (shh-CM) and by Hh-inhibitor drug vismodegib respectively. We also showed clinically achievable dose (50 μM) of vismodegib alone to be sufficient to induce apoptosis and cell cycle arrest in these low-passage GBM neurospheres in vitro. Vismodegib showed an effect on the neurospheres, both by down-regulating GLI1 mRNA expression and by inducing apoptosis/cell cycle arrest, irrespective of their relative endogenous levels of GLI1 mRNA expression. We conclude from our study that this single continuous distribution pattern of GLI1 mRNA expression technically puts almost all GBM patients in a single group rather than discrete high- or low-clusters in terms of Hh-pathway activity. That is suggestive of therapies with Hh-pathway inhibitor drugs in this malignancy without a need for further stratification of patients on the basis of relative levels of Hh-pathway activity among them.

EFFECT OF HELIUM SEDIMENTATION ON X-RAY MEASUREMENTS OF GALAXY CLUSTERS

International Nuclear Information System (INIS)

Peng Fang; Nagai, Daisuke

2009-01-01

The uniformity of the helium-to-hydrogen (He-to-H) abundance ratio in the X-ray emitting intracluster medium (ICM) is one of the commonly adopted assumptions in X-ray analyses of galaxy clusters and cosmological constraints derived from these measurements. In this paper, we investigate the effect of He sedimentation on X-ray measurements of galaxy clusters in order to assess this assumption and associated systematic uncertainties. By solving a set of flow equations for a H-He plasma, we show that the He-to-H mass ratio is significantly enhanced in the inner regions of clusters. The effect of He sedimentation, if not accounted for, introduces systematic biases in observable properties of clusters derived using X-ray observations. We show that these biases also introduce an apparent evolution in the observed gas mass fractions of X-ray luminous, dynamically relaxed clusters and hence biases in observational constraints on the dark energy equation of state parameter, w, derived from the cluster distance-redshift relation. The Hubble parameter derived from the combination of X-ray and Sunyaev-Zel'dovich effect measurements is affected by the He sedimentation process as well. Future measurements aiming to constrain w or H 0 to better than 10% may need to take into account the effect of He sedimentation. We propose that the evolution of gas mass fraction in the inner regions of clusters should provide unique observational diagnostics of the He sedimentation process.

Cluster-cluster clustering

International Nuclear Information System (INIS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

Manipulating cluster size of polyanion-stabilized Fe3O4 magnetic nanoparticle clusters via electrostatic-mediated assembly for tunable magnetophoresis behavior

International Nuclear Information System (INIS)

Yeap, Swee Pin; Ahmad, Abdul Latif; Ooi, Boon Seng; Lim, JitKang

2015-01-01

We report in this article an approach for manipulating the size of magnetic nanoparticle clusters (MNCs) via electrostatic-mediated assembly technique using an electrolyte as a clustering agent. The clusters were surface-tethered with poly(sodium 4-styrenesulfonate) (PSS) through electrostatic compensation to enhance their colloidal stability. Dynamic light scattering was employed to trace the evolution of cluster size. Simultaneously, electrophoretic mobility and Fourier transform infrared spectroscopy analyses were conducted to investigate the possible schemes involved in both cluster formation and PSS grafting. Results showed that the average hydrodynamic cluster size of the PSS/MNCs and their corresponding size distributions were successfully shifted by means of manipulating the suspension pH, the ionic nature of the electrolyte, and the electrolyte concentration. More specifically, the electrokinetic behavior of the particles upon interaction with the electrolyte plays a profound role in the formation of the PSS/MNCs. Nonetheless, the solubility of the polymer in electrolyte solution and the purification of the particles from residual ions should not be omitted in determining the effectiveness of this clustering approach. The PSS adlayer makes the resultant entities highly water-dispersible and provides electrosteric stabilization to shield the PSS/MNCs from aggregation. In this study, the experimental observations were analyzed and discussed on the basis of existing fundamental colloidal theories. The strategy of cluster size manipulation proposed here is simple and convenient to implement. Furthermore, manipulating the size of the MNCs also facilitates the tuning of magnetophoresis kinetics on exposure to low magnetic field gradient, which makes this nano-entity useful for engineering applications, specifically in separation processes.

Factor-cluster analysis and enrichment study of Mangrove sediments - An example from Mengkabong, Sabah

International Nuclear Information System (INIS)

Praveena, S.M.; Ahmed, A.; Radojevic, M.; Mohd Harun Abdullah; Aris, A.Z.

2007-01-01

This paper examines the tidal effects in the sediment of Mengkabong mangrove forest, Sabah. Generally, all the studied parameters showed high value at high tide compared to low tide. Factor-cluster analyses were adopted to allow the identification of controlling factors at high and low tides. Factor analysis extracted six controlling factors at high tide and seven controlling factors at low tide. Cluster analysis extracted two district clusters at high and low tides. The study showed that factor-cluster analysis application is a useful tool to single out the controlling factors at high and low tides. this will provide a basis for describing the tidal effects in the mangrove sediment. The salinity and electrical conductivity clusters as well as component loadings at high and low tide explained the tidal process where there is high contribution of seawater to mangrove sediments that controls the sediment chemistry. The geo accumulation index (T geo ) values suggest the mangrove sediments are having background concentrations for Al, Cu, Fe and Zn and unpolluted for Pb. (author)

Comparing clustering models in bank customers: Based on Fuzzy relational clustering approach

Directory of Open Access Journals (Sweden)

Ayad Hendalianpour

2016-11-01

Full Text Available Clustering is absolutely useful information to explore data structures and has been employed in many places. It organizes a set of objects into similar groups called clusters, and the objects within one cluster are both highly similar and dissimilar with the objects in other clusters. The K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms are the most popular clustering algorithms for their easy implementation and fast work, but in some cases we cannot use these algorithms. Regarding this, in this paper, a hybrid model for customer clustering is presented that is applicable in five banks of Fars Province, Shiraz, Iran. In this way, the fuzzy relation among customers is defined by using their features described in linguistic and quantitative variables. As follows, the customers of banks are grouped according to K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms and the proposed Fuzzy Relation Clustering (FRC algorithm. The aim of this paper is to show how to choose the best clustering algorithms based on density-based clustering and present a new clustering algorithm for both crisp and fuzzy variables. Finally, we apply the proposed approach to five datasets of customer's segmentation in banks. The result of the FCR shows the accuracy and high performance of FRC compared other clustering methods.

INFRARED HIGH-RESOLUTION INTEGRATED LIGHT SPECTRAL ANALYSES OF M31 GLOBULAR CLUSTERS FROM APOGEE

Energy Technology Data Exchange (ETDEWEB)

Sakari, Charli M. [Department of Astronomy, University of Washington, Seattle WA 98195-1580 (United States); Shetrone, Matthew D. [McDonald Observatory, University of Texas at Austin, HC75 Box 1337-MCD, Fort Davis, TX 79734 (United States); Schiavon, Ricardo P. [Gemini Observatory, 670 N. A’Ohoku Place, Hilo, HI 96720 (United States); Bizyaev, Dmitry; Pan, Kaike [Apache Point Observatory and New Mexico State University, P.O. Box 59, Sunspot, NM, 88349-0059 (United States); Prieto, Carlos Allende; García-Hernández, Domingo Aníbal [Instituto de Astrofísica de Canarias (IAC), Va Lactea s/n, E-38205 La Laguna, Tenerife (Spain); Beers, Timothy C. [Department of Physics and JINA Center for the Evolution of the Elements, University of Notre Dame, Notre Dame, IN 46556 (United States); Caldwell, Nelson [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Lucatello, Sara [INAF Osservatorio Astronomico di Padova, Vicolo dellOsservatorio 5, I-35122 Padova (Italy); Majewski, Steven; O’Connell, Robert W. [Dept. of Astronomy, University of Virginia, Charlottesville, VA 22904-4325 (United States); Strader, Jay, E-mail: sakaricm@u.washington.edu [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States)

2016-10-01

Chemical abundances are presented for 25 M31 globular clusters (GCs), based on moderately high resolution ( R = 22,500) H -band integrated light (IL) spectra from the Apache Point Observatory Galactic Evolution Experiment (APOGEE). Infrared (IR) spectra offer lines from new elements, lines of different strengths, and lines at higher excitation potentials compared to the optical. Integrated abundances of C, N, and O are derived from CO, CN, and OH molecular features, while Fe, Na, Mg, Al, Si, K, Ca, and Ti abundances are derived from atomic features. These abundances are compared to previous results from the optical, demonstrating the validity and value of IR IL analyses. The CNO abundances are consistent with typical tip of the red giant branch stellar abundances but are systematically offset from optical Lick index abundances. With a few exceptions, the other abundances agree between the optical and the IR within the 1 σ uncertainties. The first integrated K abundances are also presented and demonstrate that K tracks the α elements. The combination of IR and optical abundances allows better determinations of GC properties and enables probes of the multiple populations in extragalactic GCs. In particular, the integrated effects of the Na/O anticorrelation can be directly examined for the first time.

Deletion and Gene Expression Analyses Define the Paxilline Biosynthetic Gene Cluster in Penicillium paxilli

Directory of Open Access Journals (Sweden)

Emily J. Parker

2013-08-01

Full Text Available The indole-diterpene paxilline is an abundant secondary metabolite synthesized by Penicillium paxilli. In total, 21 genes have been identified at the PAX locus of which six have been previously confirmed to have a functional role in paxilline biosynthesis. A combination of bioinformatics, gene expression and targeted gene replacement analyses were used to define the boundaries of the PAX gene cluster. Targeted gene replacement identified seven genes, paxG, paxA, paxM, paxB, paxC, paxP and paxQ that were all required for paxilline production, with one additional gene, paxD, required for regular prenylation of the indole ring post paxilline synthesis. The two putative transcription factors, PP104 and PP105, were not co-regulated with the pax genes and based on targeted gene replacement, including the double knockout, did not have a role in paxilline production. The relationship of indole dimethylallyl transferases involved in prenylation of indole-diterpenes such as paxilline or lolitrem B, can be found as two disparate clades, not supported by prenylation type (e.g., regular or reverse. This paper provides insight into the P. paxilli indole-diterpene locus and reviews the recent advances identified in paxilline biosynthesis.

Group analyses of connectivity-based cortical parcellation using repeated k-means clustering

NARCIS (Netherlands)

Nanetti, Luca; Cerliani, Leonardo; Gazzola, Valeria; Renken, Remco; Keysers, Christian

2009-01-01

K-means clustering has become a popular tool for connectivity-based cortical segmentation using Diffusion Weighted Imaging (DWI) data. A sometimes ignored issue is, however, that the output of the algorithm depends on the initial placement of starting points, and that different sets of starting

Group sequential designs for stepped-wedge cluster randomised trials.

Science.gov (United States)

Grayling, Michael J; Wason, James Ms; Mander, Adrian P

2017-10-01

The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial's type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into

Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management Paramétrage et analyse d’observabilité de clusters de batteries de taille variable pour une gestion thermique embarquée

Directory of Open Access Journals (Sweden)

Lin Xinfan

2013-03-01

paramétrage en ligne et un observateur adaptatif sont conçus pour une batterie cylindrique. Le modèle thermique à une seule cellule est ensuite agrandi afin de créer un modèle de cluster de batteries dans le but d’étudier le schéma de température du cluster. Les interconnexions thermiques modélisées entre les cellules incluent la conduction de chaleur de cellule à cellule et la convection au flux du liquide de refroidissement environnant. Une analyse d’observabilité est effectuée sur le cluster avant la conception, pour le pack, d’un observateur en boucle fermée. Sur la base de l’analyse, les lignes directrices permettant la détermination du nombre minimal de sondes requises et leurs positionnements exacts sont déduites permettant d’assurer l’observabilité de tous les états thermiques.

A Web service substitution method based on service cluster nets

Science.gov (United States)

Du, YuYue; Gai, JunJing; Zhou, MengChu

2017-11-01

Service substitution is an important research topic in the fields of Web services and service-oriented computing. This work presents a novel method to analyse and substitute Web services. A new concept, called a Service Cluster Net Unit, is proposed based on Web service clusters. A service cluster is converted into a Service Cluster Net Unit. Then it is used to analyse whether the services in the cluster can satisfy some service requests. Meanwhile, the substitution methods of an atomic service and a composite service are proposed. The correctness of the proposed method is proved, and the effectiveness is shown and compared with the state-of-the-art method via an experiment. It can be readily applied to e-commerce service substitution to meet the business automation needs.

A New Swarm Intelligence Approach for Clustering Based on Krill Herd with Elitism Strategy

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Zhi-Yong Li

2015-10-01

Full Text Available As one of the most popular and well-recognized clustering methods, fuzzy C-means (FCM clustering algorithm is the basis of other fuzzy clustering analysis methods in theory and application respects. However, FCM algorithm is essentially a local search optimization algorithm. Therefore, sometimes, it may fail to find the global optimum. For the purpose of getting over the disadvantages of FCM algorithm, a new version of the krill herd (KH algorithm with elitism strategy, called KHE, is proposed to solve the clustering problem. Elitism tragedy has a strong ability of preventing the krill population from degrading. In addition, the well-selected parameters are used in the KHE method instead of originating from nature. Through an array of simulation experiments, the results show that the KHE is indeed a good choice for solving general benchmark problems and fuzzy clustering analyses.

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

Directory of Open Access Journals (Sweden)

Landfors Mattias

2010-10-01

Full Text Available Abstract 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

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

Science.gov (United States)

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

Physicochemical properties of different corn varieties by principal components analysis and cluster analysis

International Nuclear Information System (INIS)

Zeng, J.; Li, G.; Sun, J.

2013-01-01

Principal components analysis and cluster analysis were used to investigate the properties of different corn varieties. The chemical compositions and some properties of corn flour which processed by drying milling were determined. The results showed that the chemical compositions and physicochemical properties were significantly different among twenty six corn varieties. The quality of corn flour was concerned with five principal components from principal component analysis and the contribution rate of starch pasting properties was important, which could account for 48.90%. Twenty six corn varieties could be classified into four groups by cluster analysis. The consistency between principal components analysis and cluster analysis indicated that multivariate analyses were feasible in the study of corn variety properties. (author)

CONSTRAINING CLUSTER PHYSICS WITH THE SHAPE OF X-RAY CLUSTERS: COMPARISON OF LOCAL X-RAY CLUSTERS VERSUS ΛCDM CLUSTERS

International Nuclear Information System (INIS)

Lau, Erwin T.; Nagai, Daisuke; Kravtsov, Andrey V.; Vikhlinin, Alexey; Zentner, Andrew R.

2012-01-01

Recent simulations of cluster formation have demonstrated that condensation of baryons into central galaxies during cluster formation can drive the shape of the gas distribution in galaxy clusters significantly rounder out to their virial radius. These simulations generally predict stellar fractions within cluster virial radii that are ∼2-3 times larger than the stellar masses deduced from observations. In this paper, we compare ellipticity profiles of simulated clusters performed with varying input physics (radiative cooling, star formation, and supernova feedback) to the cluster ellipticity profiles derived from Chandra and ROSAT observations, in an effort to constrain the fraction of gas that cools and condenses into the central galaxies within clusters. We find that local relaxed clusters have an average ellipticity of ε = 0.18 ± 0.05 in the radial range of 0.04 ≤ r/r 500 ≤ 1. At larger radii r > 0.1r 500 , the observed ellipticity profiles agree well with the predictions of non-radiative simulations. In contrast, the ellipticity profiles of simulated clusters that include dissipative gas physics deviate significantly from the observed ellipticity profiles at all radii. The dissipative simulations overpredict (underpredict) ellipticity in the inner (outer) regions of galaxy clusters. By comparing simulations with and without dissipative gas physics, we show that gas cooling causes the gas distribution to be more oblate in the central regions, but makes the outer gas distribution more spherical. We find that late-time gas cooling and star formation are responsible for the significantly oblate gas distributions in cluster cores, but the gas shapes outside of cluster cores are set primarily by baryon dissipation at high redshift (z ≥ 2). Our results indicate that the shapes of X-ray emitting gas in galaxy clusters, especially at large radii, can be used to place constraints on cluster gas physics, making it potential probes of the history of baryonic

Electron: Cluster interactions

International Nuclear Information System (INIS)

Scheidemann, A.A.; Knight, W.D.

1994-02-01

Beam depletion spectroscopy has been used to measure absolute total inelastic electron-sodium cluster collision cross sections in the energy range from E ∼ 0.1 to E ∼ 6 eV. The investigation focused on the closed shell clusters Na 8 , Na 20 , Na 40 . The measured cross sections show an increase for the lowest collision energies where electron attachment is the primary scattering channel. The electron attachment cross section can be understood in terms of Langevin scattering, connecting this measurement with the polarizability of the cluster. For energies above the dissociation energy the measured electron-cluster cross section is energy independent, thus defining an electron-cluster interaction range. This interaction range increases with the cluster size

On-line learning from clustered input examples

NARCIS (Netherlands)

Riegler, Peter; Biehl, Michael; Solla, Sara A.; Marangi, Carmela; Marinaro, Maria; Tagliaferri, Roberto

1996-01-01

We analyse on-line learning of a linearly separable rule with a simple perceptron. Example inputs are taken from two overlapping clusters of data and the rule is defined through a teacher vector which is in general not aligned with the connection line of the cluster centers. We find that the Hebb

Cluster Ion Implantation in Graphite and Diamond

DEFF Research Database (Denmark)

Popok, Vladimir

2014-01-01

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

Cluster analysis of autoantibodies in 852 patients with systemic lupus erythematosus from a single center.

Science.gov (United States)

Artim-Esen, Bahar; Çene, Erhan; Şahinkaya, Yasemin; Ertan, Semra; Pehlivan, Özlem; Kamali, Sevil; Gül, Ahmet; Öcal, Lale; Aral, Orhan; Inanç, Murat

2014-07-01

Associations between autoantibodies and clinical features have been described in systemic lupus erythematosus (SLE). Herein, we aimed to define autoantibody clusters and their clinical correlations in a large cohort of patients with SLE. We analyzed 852 patients with SLE who attended our clinic. Seven autoantibodies were selected for cluster analysis: anti-DNA, anti-Sm, anti-RNP, anticardiolipin (aCL) immunoglobulin (Ig)G or IgM, lupus anticoagulant (LAC), anti-Ro, and anti-La. Two-step clustering and Kaplan-Meier survival analyses were used. Five clusters were identified. A cluster consisted of patients with only anti-dsDNA antibodies, a cluster of anti-Sm and anti-RNP, a cluster of aCL IgG/M and LAC, and a cluster of anti-Ro and anti-La antibodies. Analysis revealed 1 more cluster that consisted of patients who did not belong to any of the clusters formed by antibodies chosen for cluster analysis. Sm/RNP cluster had significantly higher incidence of pulmonary hypertension and Raynaud phenomenon. DsDNA cluster had the highest incidence of renal involvement. In the aCL/LAC cluster, there were significantly more patients with neuropsychiatric involvement, antiphospholipid syndrome, autoimmune hemolytic anemia, and thrombocytopenia. According to the Systemic Lupus International Collaborating Clinics damage index, the highest frequency of damage was in the aCL/LAC cluster. Comparison of 10 and 20 years survival showed reduced survival in the aCL/LAC cluster. This study supports the existence of autoantibody clusters with distinct clinical features in SLE and shows that forming clinical subsets according to autoantibody clusters may be useful in predicting the outcome of the disease. Autoantibody clusters in SLE may exhibit differences according to the clinical setting or population.

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

Science.gov (United States)

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

2017-07-01

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

Interplay between experiments and calculations for organometallic clusters and caged clusters

International Nuclear Information System (INIS)

Nakajima, Atsushi

2015-01-01

Clusters consisting of 10-1000 atoms exhibit size-dependent electronic and geometric properties. In particular, composite clusters consisting of several elements and/or components provide a promising way for a bottom-up approach for designing functional advanced materials, because the functionality of the composite clusters can be optimized not only by the cluster size but also by their compositions. In the formation of composite clusters, their geometric symmetry and dimensionality are emphasized to control the physical and chemical properties, because selective and anisotropic enhancements for optical, chemical, and magnetic properties can be expected. Organometallic clusters and caged clusters are demonstrated as a representative example of designing the functionality of the composite clusters. Organometallic vanadium-benzene forms a one dimensional sandwich structure showing ferromagnetic behaviors and anomalously large HOMO-LUMO gap differences of two spin orbitals, which can be regarded as spin-filter components for cluster-based spintronic devices. Caged clusters of aluminum (Al) are well stabilized both geometrically and electronically at Al 12 X, behaving as a “superatom”

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

International Nuclear Information System (INIS)

Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

2013-01-01

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

Science.gov (United States)

Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

2013-12-01

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.

Manipulating cluster size of polyanion-stabilized Fe{sub 3}O{sub 4} magnetic nanoparticle clusters via electrostatic-mediated assembly for tunable magnetophoresis behavior

Energy Technology Data Exchange (ETDEWEB)

Yeap, Swee Pin, E-mail: sweepin0727@hotmail.com; Ahmad, Abdul Latif; Ooi, Boon Seng; Lim, JitKang, E-mail: chjitkangl@usm.my [Universiti Sains Malaysia, School of Chemical Engineering (Malaysia)

2015-10-15

We report in this article an approach for manipulating the size of magnetic nanoparticle clusters (MNCs) via electrostatic-mediated assembly technique using an electrolyte as a clustering agent. The clusters were surface-tethered with poly(sodium 4-styrenesulfonate) (PSS) through electrostatic compensation to enhance their colloidal stability. Dynamic light scattering was employed to trace the evolution of cluster size. Simultaneously, electrophoretic mobility and Fourier transform infrared spectroscopy analyses were conducted to investigate the possible schemes involved in both cluster formation and PSS grafting. Results showed that the average hydrodynamic cluster size of the PSS/MNCs and their corresponding size distributions were successfully shifted by means of manipulating the suspension pH, the ionic nature of the electrolyte, and the electrolyte concentration. More specifically, the electrokinetic behavior of the particles upon interaction with the electrolyte plays a profound role in the formation of the PSS/MNCs. Nonetheless, the solubility of the polymer in electrolyte solution and the purification of the particles from residual ions should not be omitted in determining the effectiveness of this clustering approach. The PSS adlayer makes the resultant entities highly water-dispersible and provides electrosteric stabilization to shield the PSS/MNCs from aggregation. In this study, the experimental observations were analyzed and discussed on the basis of existing fundamental colloidal theories. The strategy of cluster size manipulation proposed here is simple and convenient to implement. Furthermore, manipulating the size of the MNCs also facilitates the tuning of magnetophoresis kinetics on exposure to low magnetic field gradient, which makes this nano-entity useful for engineering applications, specifically in separation processes.

Clustering at high redshifts

International Nuclear Information System (INIS)

Shaver, P.A.

1986-01-01

Evidence for clustering of and with high-redshift QSOs is discussed. QSOs of different redshifts show no clustering, but QSOs of similar redshifts appear to be clustered on a scale comparable to that of galaxies at the present epoch. In addition, spectroscopic studies of close pairs of QSOs indicate that QSOs are surrounded by a relatively high density of absorbing matter, possibly clusters of galaxies

The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

Science.gov (United States)

Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

2017-07-01

Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

Combined analyses of bacterial, fungal and nematode communities in andosolic agricultural soils in Japan.

Science.gov (United States)

Bao, Zhihua; Ikunaga, Yoko; Matsushita, Yuko; Morimoto, Sho; Takada-Hoshino, Yuko; Okada, Hiroaki; Oba, Hirosuke; Takemoto, Shuhei; Niwa, Shigeru; Ohigashi, Kentaro; Suzuki, Chika; Nagaoka, Kazunari; Takenaka, Makoto; Urashima, Yasufumi; Sekiguchi, Hiroyuki; Kushida, Atsuhiko; Toyota, Koki; Saito, Masanori; Tsushima, Seiya

2012-01-01

We simultaneously examined the bacteria, fungi and nematode communities in Andosols from four agro-geographical sites in Japan using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and statistical analyses to test the effects of environmental factors including soil properties on these communities depending on geographical sites. Statistical analyses such as Principal component analysis (PCA) and Redundancy analysis (RDA) revealed that the compositions of the three soil biota communities were strongly affected by geographical sites, which were in turn strongly associated with soil characteristics such as total C (TC), total N (TN), C/N ratio and annual mean soil temperature (ST). In particular, the TC, TN and C/N ratio had stronger effects on bacterial and fungal communities than on the nematode community. Additionally, two-way cluster analysis using the combined DGGE profile also indicated that all soil samples were classified into four clusters corresponding to the four sites, showing high site specificity of soil samples, and all DNA bands were classified into four clusters, showing the coexistence of specific DGGE bands of bacteria, fungi and nematodes in Andosol fields. The results of this study suggest that geography relative to soil properties has a simultaneous impact on soil microbial and nematode community compositions. This is the first combined profile analysis of bacteria, fungi and nematodes at different sites with agricultural Andosols.

The correlation functions for the clustering of galaxies and Abell clusters

International Nuclear Information System (INIS)

Jones, B.J.T.; Jones, J.E.; Copenhagen Univ.

1985-01-01

The difference in amplitudes between the galaxy-galaxy correlation function and the correlation function between Abell clusters is a consequence of two facts. Firstly, most Abell clusters with z<0.08 lie in a relatively small volume of the sampled space, and secondly, the fraction of galaxies lying in Abell clusters differs considerably inside and outside of this volume. (The Abell clusters are confined to a smaller volume of space than are the galaxies.) We discuss the implications of this interpretation of the clustering correlation functions and present a simple model showing how such a situation may arise quite naturally in standard theories for galaxy formation. (orig.)

Performance Evaluation of Incremental K-means Clustering Algorithm

OpenAIRE

Chakraborty, Sanjay; Nagwani, N. K.

2014-01-01

The incremental K-means clustering algorithm has already been proposed and analysed in paper [Chakraborty and Nagwani, 2011]. It is a very innovative approach which is applicable in periodically incremental environment and dealing with a bulk of updates. In this paper the performance evaluation is done for this incremental K-means clustering algorithm using air pollution database. This paper also describes the comparison on the performance evaluations between existing K-means clustering and i...

Multiple-scattering and DV-Xα analyses of a Cl-passivated Ge(111) surface

International Nuclear Information System (INIS)

Cao, S; Tang, J-C; Shen, S-L

2003-01-01

The multiple-scattering cluster and DV-Xα methods have been employed to analyse the chlorine 1s near edge x-ray absorption fine structure (NEXAFS) of a Cl-passivated Ge(111) surface. Our detailed analysis demonstrates how the chlorine atoms form a perfect monochloride structure with Cl bonding to the topmost Ge atom. Our calculation reveals the interaction in the chlorine layer is multipolar electrostatic forces. Furthermore, the DV-Xα cluster calculation shows that the orbital contour of the sharp Cl-Ge resonance exhibits a global symmetry, which confirms it to be σ * -like. The above studies are found to enrich previous experimental NEXAFS investigations

Cluster in the Auroral Acceleration Region

Science.gov (United States)

Pickett, Jolene S.; Fazakerley, Andrew N.; Marklund, Gorun; Dandouras, Iannis; Christopher, Ivar W.; Kistler, Lynn; Lucek, Elizabeth; Masson, Arnaud; Taylor, Matthew G.; Mutel, Robert L.;

Clustering of Pan- and Core-genome of Lactobacillus provides Novel Evolutionary Insights for Differentiation.

Science.gov (United States)

Inglin, Raffael C; Meile, Leo; Stevens, Marc J A

2018-04-24

Bacterial taxonomy aims to classify bacteria based on true evolutionary events and relies on a polyphasic approach that includes phenotypic, genotypic and chemotaxonomic analyses. Until now, complete genomes are largely ignored in taxonomy. The genus Lactobacillus consists of 173 species and many genomes are available to study taxonomy and evolutionary events. We analyzed and clustered 98 completely sequenced genomes of the genus Lactobacillus and 234 draft genomes of 5 different Lactobacillus species, i.e. L. reuteri, L. delbrueckii, L. plantarum, L. rhamnosus and L. helveticus. The core-genome of the genus Lactobacillus contains 266 genes and the pan-genome 20'800 genes. Clustering of the Lactobacillus pan- and core-genome resulted in two highly similar trees. This shows that evolutionary history is traceable in the core-genome and that clustering of the core-genome is sufficient to explore relationships. Clustering of core- and pan-genomes at species' level resulted in similar trees as well. Detailed analyses of the core-genomes showed that the functional class "genetic information processing" is conserved in the core-genome but that "signaling and cellular processes" is not. The latter class encodes functions that are involved in environmental interactions. Evolution of lactobacilli seems therefore directed by the environment. The type species L. delbrueckii was analyzed in detail and its pan-genome based tree contained two major clades whose members contained different genes yet identical functions. In addition, evidence for horizontal gene transfer between strains of L. delbrueckii, L. plantarum, and L. rhamnosus, and between species of the genus Lactobacillus is presented. Our data provide evidence for evolution of some lactobacilli according to a parapatric-like model for species differentiation. Core-genome trees are useful to detect evolutionary relationships in lactobacilli and might be useful in taxonomic analyses. Lactobacillus' evolution is directed

Information Clustering Based on Fuzzy Multisets.

Science.gov (United States)

Miyamoto, Sadaaki

2003-01-01

Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…

Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method

DEFF Research Database (Denmark)

Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

2014-01-01

The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probabi......The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models...... the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace...... method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous...

Estimation of cluster stability using the theory of electron density functional

International Nuclear Information System (INIS)

Borisov, Yu.A.

1985-01-01

Prospects of using simple versions of the electron density functional for studying the energy characteristics of cluster compounds Was discussed. These types of cluster compounds were considered: clusters of Cs, Be, B, Sr, Cd, Sc, In, V, Tl, I elements as intermediate form between molecule and solid body, metalloorganic Mo, W, Tc, Re, Rn clusters and elementoorganic compounds of nido-cluster type. The problem concerning changes in the binding energy of homoatomic clusters depending on their size and three-dimensional structure was analysed

Identifying Patient Attitudinal Clusters Associated with Asthma Control: The European REALISE Survey.

Science.gov (United States)

van der Molen, Thys; Fletcher, Monica; Price, David

Asthma is a highly heterogeneous disease that can be classified into different clinical phenotypes, and treatment may be tailored accordingly. However, factors beyond purely clinical traits, such as patient attitudes and behaviors, can also have a marked impact on treatment outcomes. The objective of this study was to further analyze data from the REcognise Asthma and LInk to Symptoms and Experience (REALISE) Europe survey, to identify distinct patient groups sharing common attitudes toward asthma and its management. Factor analysis of respondent data (N = 7,930) from the REALISE Europe survey consolidated the 34 attitudinal variables provided by the study population into a set of 8 summary factors. Cluster analyses were used to identify patient clusters that showed similar attitudes and behaviors toward each of the 8 summary factors. Five distinct patient clusters were identified and named according to the key characteristics comprising that cluster: "Confident and self-managing," "Confident and accepting of their asthma," "Confident but dependent on others," "Concerned but confident in their health care professional (HCP)," and "Not confident in themselves or their HCP." Clusters showed clear variability in attributes such as degree of confidence in managing their asthma, use of reliever and preventer medication, and level of asthma control. The 5 patient clusters identified in this analysis displayed distinctly different personal attitudes that would require different approaches in the consultation room certainly for asthma but probably also for other chronic diseases. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Implicit Priors in Galaxy Cluster Mass and Scaling Relation Determinations

Science.gov (United States)

Mantz, A.; Allen, S. W.

2011-01-01

Deriving the total masses of galaxy clusters from observations of the intracluster medium (ICM) generally requires some prior information, in addition to the assumptions of hydrostatic equilibrium and spherical symmetry. Often, this information takes the form of particular parametrized functions used to describe the cluster gas density and temperature profiles. In this paper, we investigate the implicit priors on hydrostatic masses that result from this fully parametric approach, and the implications of such priors for scaling relations formed from those masses. We show that the application of such fully parametric models of the ICM naturally imposes a prior on the slopes of the derived scaling relations, favoring the self-similar model, and argue that this prior may be influential in practice. In contrast, this bias does not exist for techniques which adopt an explicit prior on the form of the mass profile but describe the ICM non-parametrically. Constraints on the slope of the cluster mass-temperature relation in the literature show a separation based the approach employed, with the results from fully parametric ICM modeling clustering nearer the self-similar value. Given that a primary goal of scaling relation analyses is to test the self-similar model, the application of methods subject to strong, implicit priors should be avoided. Alternative methods and best practices are discussed.

Controlled AFM detachments and movement of nanoparticles: gold clusters on HOPG at different temperatures.

Science.gov (United States)

Tripathi, Manoj; Paolicelli, Guido; D'Addato, Sergio; Valeri, Sergio

2012-06-22

The effect of temperature on the onset of movement of gold nanoclusters (diameter 27 nm) deposited on highly oriented pyrolytic graphite (HOPG) has been studied by atomic force microscopy (AFM) techniques. Using the AFM with amplitude modulation (tapping mode AFM) we have stimulated and controlled the movement of individual clusters. We show how, at room temperature, controlled detachments and smooth movements can be obtained for clusters having dimensions comparable to or smaller than the tip radius. Displacement is practically visible in real time and it can be started and stopped easily by adjusting only one parameter, the tip amplitude oscillation. Analysing the energy dissipation signal at the onset of nanocluster sliding we evaluated a detachment threshold energy as a function of temperature in the range 300-413 K. We also analysed single cluster thermal induced displacement and combining this delicate procedure with AFM forced movement behaviour we conclude that detachment threshold energy is directly related to the activation energy of nanocluster diffusion and it scales linearly with temperature as expected for a single-particle thermally activated process.

Splitting Strip Detector Clusters in Dense Environments

CERN Document Server

Nachman, Benjamin Philip; The ATLAS collaboration

2018-01-01

Tracking in high density environments, particularly in high energy jets, plays an important role in many physics analyses at the LHC. In such environments, there is significant degradation of track reconstruction performance. Between runs 1 and 2, ATLAS implemented an algorithm that splits pixel clusters originating from multiple charged particles, using charge information, resulting in the recovery of much of the lost efficiency. However, no attempt was made in prior work to split merged clusters in the Semi Conductor Tracker (SCT), which does not measure charge information. In spite of the lack of charge information in SCT, a cluster-splitting algorithm has been developed in this work. It is based primarily on the difference between the observed cluster width and the expected cluster width, which is derived from track incidence angle. The performance of this algorithm is found to be competitive with the existing pixel cluster splitting based on track information.

X-ray cluster Abell 744

International Nuclear Information System (INIS)

Kurtz, M.J.; Huchra, J.P.; Beers, T.C.; Geller, M.J.; Gioia, I.M.

1985-01-01

X-ray and optical observations of the cluster of galaxies Abell 744 are presented. The X-ray flux (assuming H(0) = 100 km/s per Mpc) is about 9 x 10 to the 42nd erg/s. The X-ray source is extended, but shows no other structure. Photographic photometry (in Kron-Cousins R), calibrated by deep CCD frames, is presented for all galaxies brighter than 19th magnitude within 0.75 Mpc of the cluster center. The luminosity function is normal, and the isopleths show little evidence of substructure near the cluster center. The cluster has a dominant central galaxy, which is classified as a normal brightest-cluster elliptical on the basis of its luminosity profile. New redshifts were obtained for 26 galaxies in the vicinity of the cluster center; 20 appear to be cluster members. The spatial distribution of redshifts is peculiar; the dispersion within the 150 kpc core radius is much greater than outside. Abell 744 is similar to the nearby cluster Abell 1060. 31 references

Feature-Space Clustering for fMRI Meta-Analysis

DEFF Research Database (Denmark)

Goutte, Cyril; Hansen, Lars Kai; Liptrot, Mathew G.

2001-01-01

MRI sequences containing several hundreds of images, it is sometimes necessary to invoke feature extraction to reduce the dimensionality of the data space. A second interesting application is in the meta-analysis of fMRI experiment, where features are obtained from a possibly large number of single......-voxel analyses. In particular this allows the checking of the differences and agreements between different methods of analysis. Both approaches are illustrated on a fMRI data set involving visual stimulation, and we show that the feature space clustering approach yields nontrivial results and, in particular......, shows interesting differences between individual voxel analysis performed with traditional methods. © 2001 Wiley-Liss, Inc....

How can design be a platform for the development of a regional cluster in the Region of Southern Denmark

DEFF Research Database (Denmark)

Jensen, Susanne; Christensen, Poul Rind

2013-01-01

Analyses of key factors for the emergence of a cluster and the formation of a design cluster in the region of Southern Denmark......Analyses of key factors for the emergence of a cluster and the formation of a design cluster in the region of Southern Denmark...

Clustering structures of large proteins using multifractal analyses based on a 6-letter model and hydrophobicity scale of amino acids

International Nuclear Information System (INIS)

Yang Jianyi; Yu Zuguo; Anh, Vo

2009-01-01

The Schneider and Wrede hydrophobicity scale of amino acids and the 6-letter model of protein are proposed to study the relationship between the primary structure and the secondary structural classification of proteins. Two kinds of multifractal analyses are performed on the two measures obtained from these two kinds of data on large proteins. Nine parameters from the multifractal analyses are considered to construct the parameter spaces. Each protein is represented by one point in these spaces. A procedure is proposed to separate large proteins in the α, β, α + β and α/β structural classes in these parameter spaces. Fisher's linear discriminant algorithm is used to assess our clustering accuracy on the 49 selected large proteins. Numerical results indicate that the discriminant accuracies are satisfactory. In particular, they reach 100.00% and 84.21% in separating the α proteins from the {β, α + β, α/β} proteins in a parameter space; 92.86% and 86.96% in separating the β proteins from the {α + β, α/β} proteins in another parameter space; 91.67% and 83.33% in separating the α/β proteins from the α + β proteins in the last parameter space.

Cluster size matters: Size-driven performance of subnanometer clusters in catalysis, electrocatalysis and Li-air batteries

Science.gov (United States)

Vajda, Stefan

2015-03-01

This paper discusses the strongly size-dependent performance of subnanometer cluster based catalysts in 1) heterogeneous catalysis, 2) electrocatalysis and 3) Li-air batteries. The experimental studies are based on I. fabrication of ultrasmall clusters with atomic precision control of particle size and their deposition on oxide and carbon based supports; II. test of performance, III. in situand ex situ X-ray characterization of cluster size, shape and oxidation state; and IV.electron microscopies. Heterogeneous catalysis. The pronounced effect of cluster size and support on the performance of the catalyst (catalyst activity and the yield of Cn products) will be illustrated on the example of nickel and cobalt clusters in Fischer-Tropsch reaction. Electrocatalysis. The study of the oxygen evolution reaction (OER) on size-selected palladium clusters supported on ultrananocrystalline diamond show pronounced size effects. While Pd4 clusters show no reaction, Pd6 and Pd17 clusters are among the most active catalysts known (in in terms of turnover rate per Pd atom). The system (soft-landed Pd4, Pd6, or Pd17 clusters on an UNCD Si coated electrode) shows stable electrochemical potentials over several cycles, and the characterization of the electrodes show no evidence for evolution or dissolution of either the support Theoretical calculations suggest that this striking difference may be a demonstration that bridging Pd-Pd sites, which are only present in three-dimensional clusters, are active for the oxygen evolution reaction in Pd6O6. Li-air batteries. The studies show that sub-nm silver clusters have dramatic size-dependent effect on the lowering of the overpotential, charge capacity, morphology of the discharge products, as well as on the morphology of the nm size building blocks of the discharge products. The results suggest that by precise control of the active surface sites on the cathode, the performance of Li-air cells can be significantly improved

A Test for Cluster Bias: Detecting Violations of Measurement Invariance across Clusters in Multilevel Data

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Jak, Suzanne; Oort, Frans J.; Dolan, Conor V.

2013-01-01

We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings…

Cluster-assembled overlayers and high-temperature superconductors

International Nuclear Information System (INIS)

Ohno, T.R.; Yang, Y.; Kroll, G.H.; Krause, K.; Schmidt, L.D.; Weaver, J.H.; Kimachi, Y.; Hidaka, Y.; Pan, S.H.; de Lozanne, A.L.

1991-01-01

X-ray photoemission results for interfaces prepared by cluster assembly with nanometer-size clusters deposited on high-T c superconductors (HTS's) show a reduction in reactivity because atom interactions with the surface are replaced by cluster interactions. Results for conventional atom deposition show the formation of overlayer oxides that are related to oxygen depletion and disruption of the near-surface region of the HTS's. For cluster assembly of Cr and Cu, there is a very thin reacted region on single-crystal Bi 2 Sr 2 CaCu 2 O 8 . Reduced reactivity is observed for Cr cluster deposition on single-crystal YBa 2 Cu 3 O 7 -based interfaces. There is no evidence of chemical modification of the surface for Ge and Au cluster assembly on Bi 2 Sr 2 CaCu 2 O 8 (100). The overlayer grown by Au cluster assembly on Bi 2 Sr 2 CaCu 2 O 8 covers the surface at low temperature but roughening occurs upon warming to 300 K. Scanning-tunneling-microscopy results for the Au(cluster)/Bi 2 Sr 2 CaCu 2 O 8 system warmed to 300 K shows individual clusters that have coalesced into large clusters. These results offer insight into the role of surface energies and cluster interactions in determining the overlayer morphology. Transmission-electron-microscopy results for Cu cluster assembly on silica show isolated irregularly shaped clusters that do not interact at low coverage. Sintering and labyrinth formation is observed at intermediate coverage and, ultimately, a continuous film is achieved at high coverage. Silica surface wetting by Cu clusters demonstrates that dispersive force are important for these small clusters

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

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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

Galaxy clusters in the cosmic web

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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 0.4DAFT/FADA survey, which combines deep large field multi-band imaging and spectroscopic data, in order to detect filaments and/or structures around these clusters. Based on colour-magnitude diagrams, we have selected the galaxies likely to be in the cluster redshift range and studied their spatial distribution. We detect a number of structures and filaments around several clusters, proving that colour-magnitude diagrams are a reliable method to detect filaments around galaxy clusters. Since this method excludes blue (spiral) galaxies at the cluster redshift, we also apply the LePhare software to compute photometric redshifts from BVRIZ images to select galaxy cluster members and study their spatial distribution. We then find that, if only galaxies classified as early-type by LePhare are considered, we obtain the same distribution than with a red sequence selection, while taking into account late-type galaxies just pollutes the background level and deteriorates our detections. The photometric redshift based method therefore does not provide any additional information.

Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

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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.

Clusters in simple fluids

International Nuclear Information System (INIS)

Sator, N.

2003-01-01

This article concerns the correspondence between thermodynamics and the morphology of simple fluids in terms of clusters. Definitions of clusters providing a geometric interpretation of the liquid-gas phase transition are reviewed with an eye to establishing their physical relevance. The author emphasizes their main features and basic hypotheses, and shows how these definitions lead to a recent approach based on self-bound clusters. Although theoretical, this tutorial review is also addressed to readers interested in experimental aspects of clustering in simple fluids

A hybrid clustering approach to recognition of protein families in 114 microbial genomes

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Gogarten J Peter

2004-04-01

Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

Comprehensive Genomic Analyses of the OM43 Clade, Including a Novel Species from the Red Sea, Indicate Ecotype Differentiation among Marine Methylotrophs

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Jimenez-Infante, Francy; Ngugi, David Kamanda; Vinu, Manikandan; Alam, Intikhab; Kamau, Allan Anthony; Blom, Jochen; Bajic, Vladimir B.

2015-01-01

The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs that play important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (here designated MBRS-H7) from the ultraoligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species that forms a distinct cluster together with isolate KB13 from Hawaii (Hawaii-Red Sea [H-RS] cluster) that is separate from the cluster represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S-23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low-chlorophyll and/or high-temperature provinces for the H-RS cluster but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of the H-RS cluster include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely, the existence of the NADH:quinone oxidoreductase complex I (NUO) system in the H-RS cluster and the nonhomologous NADH:quinone oxidoreductase (NQR) system in the HTCC2181 cluster, which might have implications for their overall energetic yields. PMID:26655752

Voting-based consensus clustering for combining multiple clusterings of chemical structures

Directory of Open Access Journals (Sweden)

Saeed Faisal

2012-12-01

Full Text Available Abstract Background Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster. Results The cumulative voting-based aggregation algorithm (CVAA, cluster-based similarity partitioning algorithm (CSPA and hyper-graph partitioning algorithm (HGPA were examined. The F-measure and Quality Partition Index method (QPI were used to evaluate the clusterings and the results were compared to the Ward’s clustering method. The MDL Drug Data Report (MDDR dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward’s method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward’s method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria. Conclusions The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA was the method of choice among consensus clustering methods.

4C radio sources in clusters of galaxies

International Nuclear Information System (INIS)

McHardy, I.M.

1979-01-01

Observations of a complete sample of 4C and 4CT radio sources in Abell clusters with the Cambridge One-Mile telescope are analysed. It is concluded that radio sources are strongly concentrated towards the cluster centres and are equally likely to be found in clusters of any richness. The probability of a galaxy of a given absolute magnitude producing a source above a given luminosity does not depend on cluster membership. 4C and 4CT radio sources in clusters, selected at 178 MHz, occur preferentially in Bautz-Morgan (BM) class 1 clusters, whereas those selected at 1.4 GHz do not. The most powerful radio source in the cluster is almost always associated with the optically brightest galaxy. The average spectrum of 4C sources in the range 408 to 1407 MHz is steeper in BM class 1 than in other classes. Spectra also steepen with cluster richness. the morphology of 4C sources in clusters depends strongly on BM class and, in particular, radio-trail sources occur only in BM classes II, II-III and III. (author)

Indium clustering in a-plane InGaN quantum wells as evidenced by atom probe tomography

International Nuclear Information System (INIS)

Tang, Fengzai; Zhu, Tongtong; Oehler, Fabrice; Fu, Wai Yuen; Griffiths, James T.; Massabuau, Fabien C.-P.; Kappers, Menno J.; Oliver, Rachel A.; Martin, Tomas L.; Bagot, Paul A. J.; Moody, Michael P.

2015-01-01

Atom probe tomography (APT) has been used to characterize the distribution of In atoms within non-polar a-plane InGaN quantum wells (QWs) grown on a GaN pseudo-substrate produced using epitaxial lateral overgrowth. Application of the focused ion beam microscope enabled APT needles to be prepared from the low defect density regions of the grown sample. A complementary analysis was also undertaken on QWs having comparable In contents grown on polar c-plane sample pseudo-substrates. Both frequency distribution and modified nearest neighbor analyses indicate a statistically non-randomized In distribution in the a-plane QWs, but a random distribution in the c-plane QWs. This work not only provides insights into the structure of non-polar a-plane QWs but also shows that APT is capable of detecting as-grown nanoscale clustering in InGaN and thus validates the reliability of earlier APT analyses of the In distribution in c-plane InGaN QWs which show no such clustering

Indium clustering in a-plane InGaN quantum wells as evidenced by atom probe tomography

Energy Technology Data Exchange (ETDEWEB)

Tang, Fengzai; Zhu, Tongtong; Oehler, Fabrice; Fu, Wai Yuen; Griffiths, James T.; Massabuau, Fabien C.-P.; Kappers, Menno J.; Oliver, Rachel A., E-mail: rao28@cam.ac.uk [Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS (United Kingdom); Martin, Tomas L.; Bagot, Paul A. J.; Moody, Michael P., E-mail: michael.moody@materials.ox.ac.uk [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom)

2015-02-16

Atom probe tomography (APT) has been used to characterize the distribution of In atoms within non-polar a-plane InGaN quantum wells (QWs) grown on a GaN pseudo-substrate produced using epitaxial lateral overgrowth. Application of the focused ion beam microscope enabled APT needles to be prepared from the low defect density regions of the grown sample. A complementary analysis was also undertaken on QWs having comparable In contents grown on polar c-plane sample pseudo-substrates. Both frequency distribution and modified nearest neighbor analyses indicate a statistically non-randomized In distribution in the a-plane QWs, but a random distribution in the c-plane QWs. This work not only provides insights into the structure of non-polar a-plane QWs but also shows that APT is capable of detecting as-grown nanoscale clustering in InGaN and thus validates the reliability of earlier APT analyses of the In distribution in c-plane InGaN QWs which show no such clustering.

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

Science.gov (United States)

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).

Relationship between damage clustering and mortality in systemic lupus erythematosus in early and late stages of the disease: cluster analyses in a large cohort from the Spanish Society of Rheumatology Lupus Registry.

Science.gov (United States)

Pego-Reigosa, José María; Lois-Iglesias, Ana; Rúa-Figueroa, Íñigo; Galindo, María; Calvo-Alén, Jaime; de Uña-Álvarez, Jacobo; Balboa-Barreiro, Vanessa; Ibáñez Ruan, Jesús; Olivé, Alejandro; Rodríguez-Gómez, Manuel; Fernández Nebro, Antonio; Andrés, Mariano; Erausquin, Celia; Tomero, Eva; Horcada Rubio, Loreto; Uriarte Isacelaya, Esther; Freire, Mercedes; Montilla, Carlos; Sánchez-Atrio, Ana I; Santos-Soler, Gregorio; Zea, Antonio; Díez, Elvira; Narváez, Javier; Blanco-Alonso, Ricardo; Silva-Fernández, Lucía; Ruiz-Lucea, María Esther; Fernández-Castro, Mónica; Hernández-Beriain, José Ángel; Gantes-Mora, Marian; Hernández-Cruz, Blanca; Pérez-Venegas, José; Pecondón-Español, Ángela; Marras Fernández-Cid, Carlos; Ibáñez-Barcelo, Mónica; Bonilla, Gema; Torrente-Segarra, Vicenç; Castellví, Iván; Alegre, Juan José; Calvet, Joan; Marenco de la Fuente, José Luis; Raya, Enrique; Vázquez-Rodríguez, Tomás Ramón; Quevedo-Vila, Víctor; Muñoz-Fernández, Santiago; Otón, Teresa; Rahman, Anisur; López-Longo, Francisco Javier

2016-07-01

To identify patterns (clusters) of damage manifestations within a large cohort of SLE patients and evaluate the potential association of these clusters with a higher risk of mortality. This is a multicentre, descriptive, cross-sectional study of a cohort of 3656 SLE patients from the Spanish Society of Rheumatology Lupus Registry. Organ damage was ascertained using the Systemic Lupus International Collaborating Clinics Damage Index. Using cluster analysis, groups of patients with similar patterns of damage manifestations were identified. Then, overall clusters were compared as well as the subgroup of patients within every cluster with disease duration shorter than 5 years. Three damage clusters were identified. Cluster 1 (80.6% of patients) presented a lower amount of individuals with damage (23.2 vs 100% in clusters 2 and 3, P Cluster 2 (11.4% of patients) was characterized by musculoskeletal damage in all patients. Cluster 3 (8.0% of patients) was the only group with cardiovascular damage, and this was present in all patients. The overall mortality rate of patients in clusters 2 and 3 was higher than that in cluster 1 (P clusters. Both in early and late stages of the disease, there was a significant association of these clusters with an increased risk of mortality. Physicians should pay special attention to the early prevention of damage in these two systems. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

First evidence of diffuse ultra-steep-spectrum radio emission surrounding the cool core of a cluster

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Savini, F.; Bonafede, A.; Brüggen, M.; van Weeren, R.; Brunetti, G.; Intema, H.; Botteon, A.; Shimwell, T.; Wilber, A.; Rafferty, D.; Giacintucci, S.; Cassano, R.; Cuciti, V.; de Gasperin, F.; Röttgering, H.; Hoeft, M.; White, G.

2018-05-01

Diffuse synchrotron radio emission from cosmic-ray electrons is observed at the center of a number of galaxy clusters. These sources can be classified either as giant radio halos, which occur in merging clusters, or as mini halos, which are found only in cool-core clusters. In this paper, we present the first discovery of a cool-core cluster with an associated mini halo that also shows ultra-steep-spectrum emission extending well beyond the core that resembles radio halo emission. The large-scale component is discovered thanks to LOFAR observations at 144 MHz. We also analyse GMRT observations at 610 MHz to characterise the spectrum of the radio emission. An X-ray analysis reveals that the cluster is slightly disturbed, and we suggest that the steep-spectrum radio emission outside the core could be produced by a minor merger that powers electron re-acceleration without disrupting the cool core. This discovery suggests that, under particular circumstances, both a mini and giant halo could co-exist in a single cluster, opening new perspectives for particle acceleration mechanisms in galaxy clusters.

Spatial clustering of childhood cancer in Great Britain during the period 1969-1993.

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McNally, Richard J Q; Alexander, Freda E; Vincent, Tim J; Murphy, Michael F G

2009-02-15

The aetiology of childhood cancer is poorly understood. Both genetic and environmental factors are likely to be involved. The presence of spatial clustering is indicative of a very localized environmental component to aetiology. Spatial clustering is present when there are a small number of areas with greatly increased incidence or a large number of areas with moderately increased incidence. To determine whether localized environmental factors may play a part in childhood cancer aetiology, we analyzed for spatial clustering using a large set of national population-based data from Great Britain diagnosed 1969-1993. The Potthoff-Whittinghill method was used to test for extra-Poisson variation (EPV). Thirty-two thousand three hundred and twenty-three cases were allocated to 10,444 wards using diagnosis addresses. Analyses showed statistically significant evidence of clustering for acute lymphoblastic leukaemia (ALL) over the whole age range (estimate of EPV = 0.05, p = 0.002) and for ages 1-4 years (estimate of EPV = 0.03, p = 0.015). Soft-tissue sarcoma (estimate of EPV = 0.03, p = 0.04) and Wilms tumours (estimate of EPV = 0.04, p = 0.007) also showed significant clustering. Clustering tended to persist across different time periods for cases of ALL (estimate of between-time period EPV = 0.04, p =0.003). In conclusion, we observed low level spatial clustering that is attributable to a limited number of cases. This suggests that environmental factors, which in some locations display localized clustering, may be important aetiological agents in these diseases. For ALL and soft tissue sarcoma, but not Wilms tumour, common infectious agents may be likely candidates.

CC_TRS: Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life

Directory of Open Access Journals (Sweden)

Musaab Riyadh

2017-01-01

Full Text Available The rapid spreading of positioning devices leads to the generation of massive spatiotemporal trajectories data. In some scenarios, spatiotemporal data are received in stream manner. Clustering of stream data is beneficial for different applications such as traffic management and weather forecasting. In this article, an algorithm for Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life is proposed. The algorithm consists of two phases. There is the online phase where temporal micro clusters are used to store summarized spatiotemporal information for each group of similar segments. The clustering task in online phase is based on temporal micro cluster lifetime instead of time window technique which divides stream data into time bins and clusters each bin separately. For offline phase, a density based clustering approach is used to generate macro clusters depending on temporal micro clusters. The evaluation of the proposed algorithm on real data sets shows the efficiency and the effectiveness of the proposed algorithm and proved it is efficient alternative to time window technique.

Profiling physical activity motivation based on self-determination theory: a cluster analysis approach.

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Friederichs, Stijn Ah; Bolman, Catherine; Oenema, Anke; Lechner, Lilian

2015-01-01

In order to promote physical activity uptake and maintenance in individuals who do not comply with physical activity guidelines, it is important to increase our understanding of physical activity motivation among this group. The present study aimed to examine motivational profiles in a large sample of adults who do not comply with physical activity guidelines. The sample for this study consisted of 2473 individuals (31.4% male; age 44.6 ± 12.9). In order to generate motivational profiles based on motivational regulation, a cluster analysis was conducted. One-way analyses of variance were then used to compare the clusters in terms of demographics, physical activity level, motivation to be active and subjective experience while being active. Three motivational clusters were derived based on motivational regulation scores: a low motivation cluster, a controlled motivation cluster and an autonomous motivation cluster. These clusters differed significantly from each other with respect to physical activity behavior, motivation to be active and subjective experience while being active. Overall, the autonomous motivation cluster displayed more favorable characteristics compared to the other two clusters. The results of this study provide additional support for the importance of autonomous motivation in the context of physical activity behavior. The three derived clusters may be relevant in the context of physical activity interventions as individuals within the different clusters might benefit most from different intervention approaches. In addition, this study shows that cluster analysis is a useful method for differentiating between motivational profiles in large groups of individuals who do not comply with physical activity guidelines.

Star cluster formation history along the minor axis of the Large Magellanic Cloud

Science.gov (United States)

Piatti, Andrés E.; Cole, Andrew A.; Emptage, Bryn

2018-01-01

We analysed Washington CMT1 photometry of star clusters located along the minor axis of the Large Magellanic Cloud (LMC), from the LMC optical centre up to ∼39° outwards to the North-West. The data base was exploited in order to search for new star cluster candidates, to produce cluster CMDs cleaned from field star contamination and to derive age estimates for a statistically complete cluster sample. We confirmed that 146 star cluster candidates are genuine physical systems, and concluded that an overall ∼30 per cent of catalogued clusters in the surveyed regions are unlikely to be true physical systems. We did not find any new cluster candidates in the outskirts of the LMC (deprojected distance ≳ 8°). The derived ages of the studied clusters are in the range 7.2 < log(t yr-1) ≤ 9.4, with the sole exception of the globular cluster NGC 1786 (log(t yr-1) = 10.10). We also calculated the cluster frequency for each region, from which we confirmed previously proposed outside-in formation scenarios. In addition, we found that the outer LMC fields show a sudden episode of cluster formation (log(t yr-1) ∼7.8-7.9) which continued until log(t yr-1) ∼7.3 only in the outermost LMC region. We link these features to the first pericentre passage of the LMC to the Milky Way (MW), which could have triggered cluster formation due to ram pressure interaction between the LMC and MW halo.

Concomitant formation of different nature clusters and hardening in reactor pressure vessel steels irradiated by heavy ions

Energy Technology Data Exchange (ETDEWEB)

Fujii, K., E-mail: fujiik@inss.co.jp [Institute of Nuclear Safety System, Inc., Mihama 919-1205 (Japan); Fukuya, K. [Institute of Nuclear Safety System, Inc., Mihama 919-1205 (Japan); Hojo, T. [Japan Nuclear Energy Safety Organization, Toranomon, Minato-ku, Tokyo 105-0001 (Japan)

2013-11-15

Specimens of A533B steels containing 0.04, 0.09 and 0.21 wt%Cu were irradiated at 290 °C to 3 dpa with 3 MeV Fe ions and subjected to atom probe analyses, transmission electron microscopy observations and hardness measurements. The atom probe analysis results showed that two types of solute clusters were formed: Cu-enriched clusters containing Mn, Ni and Si atoms as irradiation-enhanced solute atom clusters and Mn/Ni/Si-enriched clusters as irradiation-induced solute atom clusters. Both cluster types occurred in the highest Cu-content steel and the ratio of Mn/Ni/Si-enriched clusters to Cu-enriched clusters increased with irradiation doses. It was confirmed that the cluster formation was a key factor in the microstructure evolution until the high dose irradiation was reached even in the low Cu content steels though the dislocation loops with much lower density than that of the clusters were observed as matrix damage. The difference in the hardening efficiency due to the difference in the nature of the clusters was small. The irradiation-induced clustering of undersized Si atoms suggested that a clustering driving force other than vacancy-driven diffusion, probably an interstitial mechanism, may become important at higher dose rates.

Concomitant formation of different nature clusters and hardening in reactor pressure vessel steels irradiated by heavy ions

International Nuclear Information System (INIS)

Fujii, K.; Fukuya, K.; Hojo, T.

2013-01-01

Specimens of A533B steels containing 0.04, 0.09 and 0.21 wt%Cu were irradiated at 290 °C to 3 dpa with 3 MeV Fe ions and subjected to atom probe analyses, transmission electron microscopy observations and hardness measurements. The atom probe analysis results showed that two types of solute clusters were formed: Cu-enriched clusters containing Mn, Ni and Si atoms as irradiation-enhanced solute atom clusters and Mn/Ni/Si-enriched clusters as irradiation-induced solute atom clusters. Both cluster types occurred in the highest Cu-content steel and the ratio of Mn/Ni/Si-enriched clusters to Cu-enriched clusters increased with irradiation doses. It was confirmed that the cluster formation was a key factor in the microstructure evolution until the high dose irradiation was reached even in the low Cu content steels though the dislocation loops with much lower density than that of the clusters were observed as matrix damage. The difference in the hardening efficiency due to the difference in the nature of the clusters was small. The irradiation-induced clustering of undersized Si atoms suggested that a clustering driving force other than vacancy-driven diffusion, probably an interstitial mechanism, may become important at higher dose rates

The Centaurus cluster of galaxies. I. The data

International Nuclear Information System (INIS)

Dickens, R.J.; Currie, M.J.; Lucey, J.R.

1985-07-01

The observations obtained from an extensive study of the Centaurus cluster of galaxies (α = 12sup(h) 47, σ = -41 0 ) are reported and described. An extensive catalogue is presented of galaxies in the region giving positions, magnitudes, morphological types, redshifts and other parameters. The data in the catalogue will be used in subsequent papers which analyse various aspects of the cluster. (author)

Where is the value of cluster associations for SMEs?

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Xabier De La Maza-Y-Aramburu

2012-06-01

Full Text Available Purpose: To explore the role played by policies for co-operation and networking, such as cluster initiatives. We empirically examine not only the direct effect of cluster initiatives on firms’ innovation performance, but also potential moderation and mediation effects with regards effort in other internal innovation activities.Methodology: We analyze the case of the long-running and stable Basque Cluster policy. We built using SABI an extensive sample of 1779 industrial SMEs, 132 of which are members of cluster associations. Findings: The results show that cluster associates do not have more innovation than non-cluster associates. It also rejects the moderation role of other innovation activities (such as technology management, environmental management or R&D activities. However, the results give support to the mediation role of cluster associations in enhancing the value of innovation activities. Practical implications: The results presented are relevant both for policy-makers seeking to achieve an optimal mix of ‘general cooperation’ and ‘activity-specific’ policies, as well as for the managers of firms who may accelerate the impacts of their innovation efforts by being members of cooperation networks.Research limitations: There are two main limitations to the empirical analysis. Firstly, the impossibility of identifying the year in which cluster associates formally register to the cluster association through secondary sources could entail a degree of endogeneity in the direct and moderation models. Secondly, we measure innovation as labour productivity growth, which is acknowledged as only a partial measure of innovation. More generally we acknowledge that evaluations of soft policies such as that reported in this paper should be combined with complementary qualitative analysis. Originality: Few empirical analyses have been conducted to empirically assess the efficiency of the Basque cluster policy. The research does not support

GLACE: freezing the environment of line--emitting cluster galaxies

Science.gov (United States)

Pintos--Castro, I.; Sánchez--Portal, M.; Cepa, J.; Povi, M.; Santos, J.; Altieri, B.; Bongiovanni, A.; Ederoclite, A.; Oteo, I.; Pérez García, A.; Pérez--Martínez, R.; Polednikova, J.; Ramón--Pérez, M.

2015-05-01

GLACE is performing a survey of emission-line galaxies in clusters with the main aim of studying the effect of the environment in the star formation activity. The innovation of this work is the use of tunable filters in scan mode to obtain low resolution spectra of the desired emission lines. Although the survey is in its initial stage, we have analysed two line datasets in two different clusters: Hα in Cl0024 at z=0.4 and [O II] in RXJ1257 at z = 0.9. The first is a well known intermediate redshift cluster that has been used to test the observational strategy. We reached the planned SFRs and we could deblend the [N II] component, thus being able to discriminate the AGN population from the star-forming galaxies. Also the spectral resolution is allowing us to exploit the data for dynamical analysis. The second target is a recently discovered cluster, that we have studied regarding its FIR and [O II] emission. The [O II] observations are revealing a fainter and less massive sample, when compared with the FIR emitters, showing two different populations of star-forming galaxies. The cluster emitters have shown that no evident correlation exist between the SFR (or sSFR) and the environment. Nevertheless, we have found that both samples, FIR- and [O II]-emitters, are concentrated in the areas of intermediate to even high local density. Additionally, we explored the morphological properties of the cluster galaxies using the non-parametric galSVM code.

Cosmology with clusters in the CMB

International Nuclear Information System (INIS)

Majumdar, Subhabrata

2008-01-01

Ever since the seminal work by Sunyaev and Zel'dovich describing the distortion of the CMB spectrum, due to photons passing through the hot inter cluster gas on its way to us from the surface of last scattering (the so called Sunyaev-Zel'dovich effect (SZE)), small scale distortions of the CMB by clusters has been used to detect clusters as well as to do cosmology with clusters. Cosmology with clusters in the CMB can be divided into three distinct regimes: a) when the clusters are completely unresolved and contribute to the secondary CMB distortions power spectrum at small angular scales; b) when we can just about resolve the clusters so as to detect the clusters through its total SZE flux such that the clusters can be tagged and counted for doing cosmology and c) when we can completely resolve the clusters so as to measure their sizes and other cluster structural properties and their evolution with redshift. In this article, we take a look at these three aspects of SZE cluster studies and their implication for using clusters as cosmological probes. We show that clusters can be used as effective probes of cosmology, when in all of these three cases, one explores the synergy between cluster physics and cosmology as well take clues about cluster physics from the latest high precision cluster observations (for example, from Chandra and XMM - Newton). As a specific case, we show how an observationally motivated cluster SZ template can explain the CBI-excess without the need for a high σ 8 . We also briefly discuss 'self-calibration' in cluster surveys and the prospect of using clusters as an ensemble of cosmic rulers to break degeneracies arising in cluster cosmology.

Thermodynamically accessible titanium clusters TiN, N = 2-32.

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Lazauskas, Tomas; Sokol, Alexey A; Buckeridge, John; Catlow, C Richard A; Escher, Susanne G E T; Farrow, Matthew R; Mora-Fonz, David; Blum, Volker W; Phaahla, Tshegofatso M; Chauke, Hasani R; Ngoepe, Phuti E; Woodley, Scott M

2018-05-10

We have performed a genetic algorithm search on the tight-binding interatomic potential energy surface (PES) for small TiN (N = 2-32) clusters. The low energy candidate clusters were further refined using density functional theory (DFT) calculations with the PBEsol exchange-correlation functional and evaluated with the PBEsol0 hybrid functional. The resulting clusters were analysed in terms of their structural features, growth mechanism and surface area. The results suggest a growth mechanism that is based on forming coordination centres by interpenetrating icosahedra, icositetrahedra and Frank-Kasper polyhedra. We identify centres of coordination, which act as centres of bulk nucleation in medium sized clusters and determine the morphological features of the cluster.

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

Science.gov (United States)

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.;

Phenotypes of asthma in low-income children and adolescents: cluster analysis

Directory of Open Access Journals (Sweden)

Anna Lucia Barros Cabral

Full Text Available ABSTRACT Objective: 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. Methods: 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. Results: 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. Conclusions: 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.

On the absence of radio haloes in clusters with double relics

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Bonafede, A.; Cassano, R.; Brüggen, M.; Ogrean, G. A.; Riseley, C. J.; Cuciti, V.; de Gasperin, F.; Golovich, N.; Kale, R.; Venturi, T.; van Weeren, R. J.; Wik, D. R.; Wittman, D.

2017-09-01

Pairs of radio relics are believed to form during cluster mergers, and are best observed when the merger occurs in the plane of the sky. Mergers can also produce radio haloes, through complex processes likely linked to turbulent re-acceleration of cosmic ray electrons. However, only some clusters with double relics also show a radio halo. Here, we present a novel method to derive upper limits on the radio halo emission, and analyse archival X-ray Chandra data, as well as galaxy velocity dispersions and lensing data, in order to understand the key parameter that switches on radio halo emission. We place upper limits on the halo power below the P1.4 GHz-M500 correlation for some clusters, confirming that clusters with double relics have different radio properties. Computing X-ray morphological indicators, we find that clusters with double relics are associated with the most disturbed clusters. We also investigate the role of different mass-ratios and time-since-merger. Data do not indicate that the merger mass-ratio has an impact on the presence or absence of radio haloes (the null hypothesis that the clusters belong to the same group cannot be rejected). However, the data suggest that the absence of radio haloes could be associated with early and late mergers, but the sample is too small to perform a statistical test. Our study is limited by the small number of clusters with double relics. Future surveys with LOFAR, ASKAP, MeerKat and SKA will provide larger samples to better address this issue.

Scalable Density-Based Subspace Clustering

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

2011-01-01

For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering...... method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real...... and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well....

The rotation of galaxy clusters

International Nuclear Information System (INIS)

Tovmassian, H.M.

2015-01-01

The method for detection of the galaxy cluster rotation based on the study of distribution of member galaxies with velocities lower and higher of the cluster mean velocity over the cluster image is proposed. The search for rotation is made for flat clusters with a/b> 1.8 and BMI type clusters which are expected to be rotating. For comparison there were studied also round clusters and clusters of NBMI type, the second by brightness galaxy in which does not differ significantly from the cluster cD galaxy. Seventeen out of studied 65 clusters are found to be rotating. It was found that the detection rate is sufficiently high for flat clusters, over 60 per cent, and clusters of BMI type with dominant cD galaxy, ≈ 35 per cent. The obtained results show that clusters were formed from the huge primordial gas clouds and preserved the rotation of the primordial clouds, unless they did not have mergings with other clusters and groups of galaxies, in the result of which the rotation has been prevented

a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

Science.gov (United States)

Huang, W.; Li, S.; Xu, S.

2016-06-01

How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the

Observations of CO and OI in stars in globular clusters

International Nuclear Information System (INIS)

Wallerstein, G.; Pilachowski, C.

1978-01-01

Since studies at classification dispersion and early analyses of high dispersion spectra have yielded little quantitative data on the abundances of C, N, and O in globular clusters the authors have been endeavoring to establish their abundances in stars in several clusters. The problem has been approached in two ways, by observing the 2.3 micron CO bands and the 6300 A [OI] line in individual stars in globular clusters. (Auth.)

Comparative genomics of chondrichthyan Hoxa clusters

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Zhong Ying-Fu

2009-09-01

Full Text Available Abstract Background The chondrichthyan or cartilaginous fish (chimeras, sharks, skates and rays occupy an important phylogenetic position as the sister group to all other jawed vertebrates and as an early lineage to diverge from the vertebrate lineage following two whole genome duplication events in vertebrate evolution. There have been few comparative genomic analyses incorporating data from chondrichthyan fish and none comparing genomic information from within the group. We have sequenced the complete Hoxa cluster of the Little Skate (Leucoraja erinacea and compared to the published Hoxa cluster of the Horn Shark (Heterodontus francisci and to available data from the Elephant Shark (Callorhinchus milii genome project. Results A BAC clone containing the full Little Skate Hoxa cluster was fully sequenced and assembled. Analyses of coding sequences and conserved non-coding elements reveal a strikingly high level of conservation across the cartilaginous fish, with twenty ultraconserved elements (100%,100 bp found between Skate and Horn Shark, compared to three between human and marsupials. We have also identified novel potential non-coding RNAs in the Skate BAC clone, some of which are conserved to other species. Conclusion We find that the Little Skate Hoxa cluster is remarkably similar to the previously published Horn Shark Hoxa cluster with respect to sequence identity, gene size and intergenic distance despite over 180 million years of separation between the two lineages. We suggest that the genomes of cartilaginous fish are more highly conserved than those of tetrapods or teleost fish and so are more likely to have retained ancestral non-coding elements. While useful for isolating homologous DNA, this complicates bioinformatic approaches to identify chondrichthyan-specific non-coding DNA elements

The cluster bootstrap consistency in generalized estimating equations

KAUST Repository

Cheng, Guang

2013-03-01

The cluster bootstrap resamples clusters or subjects instead of individual observations in order to preserve the dependence within each cluster or subject. In this paper, we provide a theoretical justification of using the cluster bootstrap for the inferences of the generalized estimating equations (GEE) for clustered/longitudinal data. Under the general exchangeable bootstrap weights, we show that the cluster bootstrap yields a consistent approximation of the distribution of the regression estimate, and a consistent approximation of the confidence sets. We also show that a computationally more efficient one-step version of the cluster bootstrap provides asymptotically equivalent inference. © 2012.

Gene cluster statistics with gene families.

Science.gov (United States)

Raghupathy, Narayanan; Durand, Dannie

2009-05-01

Identifying genomic regions that descended from a common ancestor is important for understanding the function and evolution of genomes. In distantly related genomes, clusters of homologous gene pairs are evidence of candidate homologous regions. Demonstrating the statistical significance of such "gene clusters" is an essential component of comparative genomic analyses. However, currently there are no practical statistical tests for gene clusters that model the influence of the number of homologs in each gene family on cluster significance. In this work, we demonstrate empirically that failure to incorporate gene family size in gene cluster statistics results in overestimation of significance, leading to incorrect conclusions. We further present novel analytical methods for estimating gene cluster significance that take gene family size into account. Our methods do not require complete genome data and are suitable for testing individual clusters found in local regions, such as contigs in an unfinished assembly. We consider pairs of regions drawn from the same genome (paralogous clusters), as well as regions drawn from two different genomes (orthologous clusters). Determining cluster significance under general models of gene family size is computationally intractable. By assuming that all gene families are of equal size, we obtain analytical expressions that allow fast approximation of cluster probabilities. We evaluate the accuracy of this approximation by comparing the resulting gene cluster probabilities with cluster probabilities obtained by simulating a realistic, power-law distributed model of gene family size, with parameters inferred from genomic data. Surprisingly, despite the simplicity of the underlying assumption, our method accurately approximates the true cluster probabilities. It slightly overestimates these probabilities, yielding a conservative test. We present additional simulation results indicating the best choice of parameter values for data

Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach

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Sami Ullah

2017-11-01

Full Text Available Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square scanning windows to discover disease clusters. In certain situations, where the disease occurrences tend to cluster in very irregularly shaped areas, these algorithms are not feasible in practise for the detection of space-time clusters. To address this problem, a new algorithm is proposed, which uses a co-clustering strategy to detect prospective and retrospective space-time disease clusters with no restriction on shape and size. The proposed method detects space-time disease clusters by tracking the changes in space–time occurrence structure instead of an in-depth search over space. This method was utilised to detect potential clusters in the annual and monthly malaria data in Khyber Pakhtunkhwa Province, Pakistan from 2012 to 2016 visualising the results on a heat map. The results of the annual data analysis showed that the most likely hotspot emerged in three sub-regions in the years 2013-2014. The most likely hotspots in monthly data appeared in the month of July to October in each year and showed a strong periodic trend.

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

Science.gov (United States)

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

2011-05-01

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

THE YOUNG OPEN CLUSTER BERKELEY 55

Energy Technology Data Exchange (ETDEWEB)

Negueruela, Ignacio; Marco, Amparo, E-mail: ignacio.negueruela@ua.es, E-mail: amparo.marco@ua.es [Departamento de Fisica, Ingenieria de Sistemas y Teoria de la Senal, Universidad de Alicante, Apdo. 99, E-03080 Alicante (Spain)

2012-02-15

We present UBV photometry of the highly reddened and poorly studied open cluster Berkeley 55, revealing an important population of B-type stars and several evolved stars of high luminosity. Intermediate-resolution far-red spectra of several candidate members confirm the presence of one F-type supergiant and six late supergiants or bright giants. The brightest blue stars are mid-B giants. Spectroscopic and photometric analyses indicate an age 50 {+-} 10 Myr. The cluster is located at a distance d Almost-Equal-To 4 kpc, consistent with other tracers of the Perseus Arm in this direction. Berkeley 55 is thus a moderately young open cluster with a sizable population of candidate red (super)giant members, which can provide valuable information about the evolution of intermediate-mass stars.

Performance quantification of clustering algorithms for false positive removal in fMRI by ROC curves

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André Salles Cunha Peres

Full Text Available Abstract Introduction Functional magnetic resonance imaging (fMRI is a non-invasive technique that allows the detection of specific cerebral functions in humans based on hemodynamic changes. The contrast changes are about 5%, making visual inspection impossible. Thus, statistic strategies are applied to infer which brain region is engaged in a task. However, the traditional methods like general linear model and cross-correlation utilize voxel-wise calculation, introducing a lot of false-positive data. So, in this work we tested post-processing cluster algorithms to diminish the false-positives. Methods In this study, three clustering algorithms (the hierarchical cluster, k-means and self-organizing maps were tested and compared for false-positive removal in the post-processing of cross-correlation analyses. Results Our results showed that the hierarchical cluster presented the best performance to remove the false positives in fMRI, being 2.3 times more accurate than k-means, and 1.9 times more accurate than self-organizing maps. Conclusion The hierarchical cluster presented the best performance in false-positive removal because it uses the inconsistency coefficient threshold, while k-means and self-organizing maps utilize a priori cluster number (centroids and neurons number; thus, the hierarchical cluster avoids clustering scattered voxels, as the inconsistency coefficient threshold allows only the voxels to be clustered that are at a minimum distance to some cluster.

Blue straggler stars beyond the Milky Way: a non-segregated population in the Large Magellanic Cloud cluster NGC 2213

Science.gov (United States)

Li, Chengyuan; Hong, Jongsuk

2018-06-01

Using the high-resolution observations obtained by the Hubble Space Telescope, we analysed the blue straggler stars (BSSs) in the Large Magellanic Cloud cluster NGC 2213. We found that the radial distribution of BSSs is consistent with that of the normal giant stars in NGC 2213, showing no evidence of mass segregation. However, an analytic calculation carried out for these BSSs shows that they are already dynamically old, because the estimated half-mass relaxation time for these BSSs is significantly shorter than the isochronal age of the cluster. We also performed direct N-body simulations for an NGC 2213-like cluster to understand the dynamical processes that lead to this non-segregated radial distribution of BSSs. Our numerical simulation shows that the presence of black hole subsystems inside the cluster centre can significantly affect the dynamical evolution of BSSs. The combined effects of the delayed segregation, binary disruption, and exchange interactions of BSS progenitor binaries may result in this non-segregated radial distribution of BSSs in NGC 2213.

Evolution of rotating stellar clusters at the stage of inelastic collisions

International Nuclear Information System (INIS)

Romanova, M.M.

1985-01-01

The dynamics of a gas-stellar disk in a dense stellar cluster of small ellipticity (epsilon or approximately 0.2-0.3. Possible existence of a thin stellar disk in a dense stellar cluster is analysed. With epsilon in the above range, collisions between cluster and disk stars are shown to have no effect on the evolution of the disk up to the instability time, provided that the ratio of disk stellar mass to the cluster stellar mass > or approximately 0.04

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

Science.gov (United States)

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

2014-10-02

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

Neutrosophic Hierarchical Clustering Algoritms

Directory of Open Access Journals (Sweden)

Rıdvan Şahin

2014-03-01

Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

Structure and bonding in clusters

International Nuclear Information System (INIS)

Kumar, V.

1991-10-01

We review here the recent progress made in the understanding of the electronic and atomic structure of small clusters of s-p bonded materials using the density functional molecular dynamics technique within the local density approximation. Starting with a brief description of the method, results are presented for alkali metal clusters, clusters of divalent metals such as Mg and Be which show a transition from van der Waals or weak chemical bonding to metallic behaviour as the cluster size grows and clusters of Al, Sn and Sb. In the case of semiconductors, we discuss results for Si, Ge and GaAs clusters. Clusters of other materials such as P, C, S, and Se are also briefly discussed. From these and other available results we suggest the possibility of unique structures for the magic clusters. (author). 69 refs, 7 figs, 1 tab

The next generation Virgo cluster survey. VIII. The spatial distribution of globular clusters in the Virgo cluster

Energy Technology Data Exchange (ETDEWEB)

Durrell, Patrick R.; Accetta, Katharine [Department of Physics and Astronomy, Youngstown State University, Youngstown, OH 44555 (United States); Côté, Patrick; Blakeslee, John P.; Ferrarese, Laura; McConnachie, Alan; Gwyn, Stephen [Herzberg Astronomy and Astrophysics, National Research Council, 5071 West Saanich Road, Victoria, BC V9E 2E7 (Canada); Peng, Eric W.; Zhang, Hongxin [Department of Astronomy, Peking University, Beijing 100871 (China); Mihos, J. Christopher [Department of Astronomy, Case Western Reserve University, Cleveland, OH 44106 (United States); Puzia, Thomas H.; Jordán, Andrés [Institute of Astrophysics, Pontificia Universidad Catolica, Av. Vicu' a Mackenna 4860, Macul 7820436, Santiago (Chile); Lançon, Ariane [Observatoire astronomique de Strasbourg, Université de Strasbourg, CNRS, UMR 7550, 11 rue de l' Université, F-67000 Strasbourg (France); Liu, Chengze [Center for Astronomy and Astrophysics, Department of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240 (China); Cuillandre, Jean-Charles [Canada-France-Hawaii Telescope Corporation, Kamuela, HI 96743 (United States); Boissier, Samuel; Boselli, Alessandro [Aix Marseille Université, CNRS, LAM (Laboratoire d' Astrophysique de Marseille) UMR 7326, F-13388 Marseille (France); Courteau, Stéphane [Department of Physics, Engineering Physics and Astronomy, Queen' s University, Kingston, ON K7L 3N6 (Canada); Duc, Pierre-Alain [AIM Paris Saclay, CNRS/INSU, CEA/Irfu, Université Paris Diderot, Orme des Merisiers, F-91191 Gif sur Yvette cedex (France); Emsellem, Eric [Université de Lyon 1, CRAL, Observatoire de Lyon, 9 av. Charles André, F-69230 Saint-Genis Laval (France); CNRS, UMR 5574, ENS de Lyon (France); and others

2014-10-20

We report on a large-scale study of the distribution of globular clusters (GCs) throughout the Virgo cluster, based on photometry from the Next Generation Virgo Cluster Survey (NGVS), a large imaging survey covering Virgo's primary subclusters (Virgo A = M87 and Virgo B = M49) out to their virial radii. Using the g{sub o}{sup ′}, (g' – i') {sub o} color-magnitude diagram of unresolved and marginally resolved sources within the NGVS, we have constructed two-dimensional maps of the (irregular) GC distribution over 100 deg{sup 2} to a depth of g{sub o}{sup ′} = 24. We present the clearest evidence to date showing the difference in concentration between red and blue GCs over the full extent of the cluster, where the red (more metal-rich) GCs are largely located around the massive early-type galaxies in Virgo, while the blue (metal-poor) GCs have a much more extended spatial distribution with significant populations still present beyond 83' (∼215 kpc) along the major axes of both M49 and M87. A comparison of our GC maps to the diffuse light in the outermost regions of M49 and M87 show remarkable agreement in the shape, ellipticity, and boxiness of both luminous systems. We also find evidence for spatial enhancements of GCs surrounding M87 that may be indicative of recent interactions or an ongoing merger history. We compare the GC map to that of the locations of Virgo galaxies and the X-ray intracluster gas, and find generally good agreement between these various baryonic structures. We calculate the Virgo cluster contains a total population of N {sub GC} = 67, 300 ± 14, 400, of which 35% are located in M87 and M49 alone. For the first time, we compute a cluster-wide specific frequency S {sub N,} {sub CL} = 2.8 ± 0.7, after correcting for Virgo's diffuse light. We also find a GC-to-baryonic mass fraction ε {sub b} = 5.7 ± 1.1 × 10{sup –4} and a GC-to-total cluster mass formation efficiency ε {sub t} = 2.9 ± 0.5 × 10{sup –5

Red giants and yellow stragglers in the young open cluster NGC 2447

Science.gov (United States)

da Silveira, M. D.; Pereira, C. B.; Drake, N. A.

2018-06-01

In this work we analysed, using high-resolution spectroscopy, a sample of 12 single and 4 spectroscopic binary stars of the open cluster NGC 2447. For the single stars, we obtained atmospheric parameters and chemical abundances of Li, C, N, O, Na, Mg, Al, Ca, Si, Ti, Ni, Cr, Y, Zr, La, Ce, Nd, Eu. Rotational velocities were obtained for all the stars. The abundances of the light elements and Eu and the rotational velocities were derived using spectral synthesis technique. We obtained a mean metallicity of [Fe/H] = -0.17 ± 0.05. We found that the abundances of all elements are similar to field giants and/or giants of open clusters, even for the s-process elements, which are enhanced as in other young open clusters. We show that the spectroscopic binaries NGC 2447-26, 38, and 42 are yellow-straggler stars, of which the primary is a giant star and the secondary a main-sequence A-type star.

Random matrix improved subspace clustering

KAUST Repository

Couillet, Romain; Kammoun, Abla

2017-01-01

This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show

Interacting star clusters in the Large Magellanic Cloud. Overmerging problem solved by cluster group formation

Science.gov (United States)

Leon, Stéphane; Bergond, Gilles; Vallenari, Antonella

1999-04-01

We present the tidal tail distributions of a sample of candidate binary clusters located in the bar of the Large Magellanic Cloud (LMC). One isolated cluster, SL 268, is presented in order to study the effect of the LMC tidal field. All the candidate binary clusters show tidal tails, confirming that the pairs are formed by physically linked objects. The stellar mass in the tails covers a large range, from 1.8x 10(3) to 3x 10(4) \\msun. We derive a total mass estimate for SL 268 and SL 356. At large radii, the projected density profiles of SL 268 and SL 356 fall off as r(-gamma ) , with gamma = 2.27 and gamma =3.44, respectively. Out of 4 pairs or multiple systems, 2 are older than the theoretical survival time of binary clusters (going from a few 10(6) years to 10(8) years). A pair shows too large age difference between the components to be consistent with classical theoretical models of binary cluster formation (Fujimoto & Kumai \\cite{fujimoto97}). We refer to this as the ``overmerging'' problem. A different scenario is proposed: the formation proceeds in large molecular complexes giving birth to groups of clusters over a few 10(7) years. In these groups the expected cluster encounter rate is larger, and tidal capture has higher probability. Cluster pairs are not born together through the splitting of the parent cloud, but formed later by tidal capture. For 3 pairs, we tentatively identify the star cluster group (SCG) memberships. The SCG formation, through the recent cluster starburst triggered by the LMC-SMC encounter, in contrast with the quiescent open cluster formation in the Milky Way can be an explanation to the paucity of binary clusters observed in our Galaxy. Based on observations collected at the European Southern Observatory, La Silla, Chile}

Variation in the fumonisin biosynthetic gene cluster in fumonisin-producing and nonproducing black aspergilli.

Science.gov (United States)

Susca, Antonia; Proctor, Robert H; Butchko, Robert A E; Haidukowski, Miriam; Stea, Gaetano; Logrieco, Antonio; Moretti, Antonio

2014-12-01

The ability to produce fumonisin mycotoxins varies among members of the black aspergilli. Previously, analyses of selected genes in the fumonisin biosynthetic gene (fum) cluster in black aspergilli from California grapes indicated that fumonisin-nonproducing isolates of Aspergillus welwitschiae lack six fum genes, but nonproducing isolates of Aspergillus niger do not. In the current study, analyses of black aspergilli from grapes from the Mediterranean Basin indicate that the genomic context of the fum cluster is the same in isolates of A. niger and A. welwitschiae regardless of fumonisin-production ability and that full-length clusters occur in producing isolates of both species and nonproducing isolates of A. niger. In contrast, the cluster has undergone an eight-gene deletion in fumonisin-nonproducing isolates of A. welwitschiae. Phylogenetic analyses suggest each species consists of a mixed population of fumonisin-producing and nonproducing individuals, and that existence of both production phenotypes may provide a selective advantage to these species. Differences in gene content of fum cluster homologues and phylogenetic relationships of fum genes suggest that the mutation(s) responsible for the nonproduction phenotype differs, and therefore arose independently, in the two species. Partial fum cluster homologues were also identified in genome sequences of four other black Aspergillus species. Gene content of these partial clusters and phylogenetic relationships of fum sequences indicate that non-random partial deletion of the cluster has occurred multiple times among the species. This in turn suggests that an intact cluster and fumonisin production were once more widespread among black aspergilli. Copyright © 2014 Elsevier Inc. All rights reserved.

A THREE-STEP SPATIAL-TEMPORAL-SEMANTIC CLUSTERING METHOD FOR HUMAN ACTIVITY PATTERN ANALYSIS

Directory of Open Access Journals (Sweden)

W. Huang

2016-06-01

Full Text Available How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time to four dimensions (space, time and semantics. More specifically, not only a location and time that people stay and spend are collected, but also what people “say” for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The

Irritable bowel syndrome and upper dyspepsia among the elderly: a study of symptom clusters in a random 70 year old population

DEFF Research Database (Denmark)

Kay, L; Jørgensen, Torben; Schultz-Larsen, K

1996-01-01

. Heartburn/acid regurgitation did not show a consistent association to any other symptoms and may be considered as a cluster of it own. Pain characteristics traditionally related to upper dyspepsia did not specifically relate to any cluster. It is concluded that, in this 70-year-old population abdominal......With the aim to assess the clustering of abdominal symptoms in a random population, data from a cohort study of a 70 year old Danish population were analysed. The cohort comprised 1,119 subjects of which 72% participated in a primary study and 91% of the survivors in a similar study five years...

Clustering methods for the optimization of atomic cluster structure

Science.gov (United States)

Bagattini, Francesco; Schoen, Fabio; Tigli, Luca

2018-04-01

In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

Science.gov (United States)

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-03-01

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

An evaluation of centrality measures used in cluster analysis

Science.gov (United States)

Engström, Christopher; Silvestrov, Sergei

2014-12-01

Clustering of data into groups of similar objects plays an important part when analysing many types of data, especially when the datasets are large as they often are in for example bioinformatics, social networks and computational linguistics. Many clustering algorithms such as K-means and some types of hierarchical clustering need a number of centroids representing the 'center' of the clusters. The choice of centroids for the initial clusters often plays an important role in the quality of the clusters. Since a data point with a high centrality supposedly lies close to the 'center' of some cluster, this can be used to assign centroids rather than through some other method such as picking them at random. Some work have been done to evaluate the use of centrality measures such as degree, betweenness and eigenvector centrality in clustering algorithms. The aim of this article is to compare and evaluate the usefulness of a number of common centrality measures such as the above mentioned and others such as PageRank and related measures.

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

Science.gov (United States)

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

2015-12-01

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

POTENTIAL CLUSTERS IN BANAT AND THEIR ROLE IN REGIONAL ECONOMIC DEVELOPMENT

Directory of Open Access Journals (Sweden)

Ramona IŞFĂNESCU

2010-06-01

Full Text Available The interest in the study of clusters and their role in the economic development of certain regions has constantly grown in the past years. This interest has also been emphasized by the emergence of successful clusters in many regions; these are clusters that have visibly and they have determined the increase in competitiveness of those particular regions. Clusters are geographic gatherings of firms and institutions, connected to each other and specialized in certain fields of activity. In Romania, due to the low cooperation level among enterprises we cannot say that proper clusters exists, but just some “spatial gatherings” of firms activating in certain domains, connected by the need of using certain natural resources and the existence of a specialized workforce in that particular domain. Natural “clusters” can be identified by means of quantitative analyses, these indicating the possibility to identify certain spatial assemblies of firms in a certain economic sector. Starting from these quantitative analyses, for Banat region have been identified some important spatial gatherings of firms activating in certain domains which could represent potential clusters in this area. As clusters function on the principle of cooperation among enterprises, a strong point of the region is the presence of foreign investors which promoted the model of enterprise cooperation through sub-contracting local enterprises. Among these, we mention the Italian investors which brought to Banat, especially to Timiş County the Italian cluster model. Are there in Banat premises for the emergence of clusters? Which are the fields of activity in which these clusters can emerge? What role will these clusters play in the economic development of the region? These are just some of the questions that we aim answering to through this study.

A Novel Cluster Head Selection Algorithm Based on Fuzzy Clustering and Particle Swarm Optimization.

Science.gov (United States)

Ni, Qingjian; Pan, Qianqian; Du, Huimin; Cao, Cen; Zhai, Yuqing

2017-01-01

An important objective of wireless sensor network is to prolong the network life cycle, and topology control is of great significance for extending the network life cycle. Based on previous work, for cluster head selection in hierarchical topology control, we propose a solution based on fuzzy clustering preprocessing and particle swarm optimization. More specifically, first, fuzzy clustering algorithm is used to initial clustering for sensor nodes according to geographical locations, where a sensor node belongs to a cluster with a determined probability, and the number of initial clusters is analyzed and discussed. Furthermore, the fitness function is designed considering both the energy consumption and distance factors of wireless sensor network. Finally, the cluster head nodes in hierarchical topology are determined based on the improved particle swarm optimization. Experimental results show that, compared with traditional methods, the proposed method achieved the purpose of reducing the mortality rate of nodes and extending the network life cycle.

Cluster Synchronization of Diffusively Coupled Nonlinear Systems: A Contraction-Based Approach

Science.gov (United States)

Aminzare, Zahra; Dey, Biswadip; Davison, Elizabeth N.; Leonard, Naomi Ehrich

2018-04-01

Finding the conditions that foster synchronization in networked nonlinear systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in nonlinear systems with linear coupling, such as has been used to model neuronal networks, are in general not strict enough to accurately determine the system behavior. We leverage contraction theory to derive new sufficient conditions for cluster synchronization in terms of the network structure, for a network where the intrinsic nonlinear dynamics of each node may differ. Our result requires that network connections satisfy a cluster-input-equivalence condition, and we explore the influence of this requirement on network dynamics. For application to networks of nodes with FitzHugh-Nagumo dynamics, we show that our new sufficient condition is tighter than those found in previous analyses that used smooth or nonsmooth Lyapunov functions. Improving the analytical conditions for when cluster synchronization will occur based on network configuration is a significant step toward facilitating understanding and control of complex networked systems.

Cluster infall in the concordance LCDM model

OpenAIRE

Pivato, Maximiliano C.; Padilla, Nelson D.; Lambas, Diego G.

2005-01-01

We perform statistical analyses of the infall of dark-matter onto clusters in numerical simulations within the concordance LCDM model. By studying the infall profile around clusters of different mass, we find a linear relation between the maximum infall velocity and mass which reach 900km/s for the most massive groups. The maximum infall velocity and the group mass follow a suitable power law fit of the form, V_{inf}^{max} = (M/m_0)^{gamma}. By comparing the measured infall velocity to the li...

First multispacecraft ion measurements in and near the Earth’s magnetosphere with the identical Cluster ion spectrometry (CIS experiment

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H. Rème

2001-09-01

Full Text Available On board the four Cluster spacecraft, the Cluster Ion Spectrometry (CIS experiment measures the full, three-dimensional ion distribution of the major magnetospheric ions (H+, He+, He++, and O+ from the thermal energies to about 40 keV/e. The experiment consists of two different instruments: a COmposition and DIstribution Function analyser (CIS1/CODIF, giving the mass per charge composition with medium (22.5° angular resolution, and a Hot Ion Analyser (CIS2/HIA, which does not offer mass resolution but has a better angular resolution (5.6° that is adequate for ion beam and solar wind measurements. Each analyser has two different sensitivities in order to increase the dynamic range. First tests of the instruments (commissioning activities were achieved from early September 2000 to mid January 2001, and the operation phase began on 1 February 2001. In this paper, first results of the CIS instruments are presented showing the high level performances and capabilities of the instruments. Good examples of data were obtained in the central plasma sheet, magnetopause crossings, magnetosheath, solar wind and cusp measurements. Observations in the auroral regions could also be obtained with the Cluster spacecraft at radial distances of 4–6 Earth radii. These results show the tremendous interest of multispacecraft measurements with identical instruments and open a new area in magnetospheric and solar wind-magnetosphere interaction physics.Key words. Magnetospheric physics (magnetopause, cusp and boundary layers; magnetopheric configuration and dynamics; solar wind - magnetosphere interactions

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

Science.gov (United States)

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure

Preferential site occupancy observed in coexpanded argon-krypton clusters

International Nuclear Information System (INIS)

Lundwall, M.; Bergersen, H.; Lindblad, A.; Oehrwall, G.; Svensson, S.; Bjoerneholm, O.; Tchaplyguine, M.

2006-01-01

Free heterogeneous argon-krypton clusters have been produced by coexpansion and investigated by means of x-ray photoelectron spectroscopy. By examining cluster surface and bulk binding energy shifts, relative intensities, and peak widths, we show that in the mixed argon-krypton clusters the krypton atoms favor the bulk and argon atoms are pushed to the surface. Furthermore, we show that krypton atoms in the surface layer occupy high-coordination sites and that heterogeneous argon-krypton clusters produced by coexpansion show the same surface structure as argon host clusters doped with krypton. These observations are supported by site-dependent calculations of chemical shifts

Binding energies of cluster ions

International Nuclear Information System (INIS)

Parajuli, R.; Matt, S.; Scheier, P.; Echt, O.; Stamatovic, A.; Maerk, T.D.

2002-01-01

The binding energy of charged clusters may be measured by analyzing the kinetic energy released in the metastable decay of mass selected parent ions. Using finite heat bath theory to determine the binding energies of argon, neon, krypton, oxygen and nitrogen from their respective average kinetic energy released were carried out. A high-resolution double focussing two-sector mass spectrometer of reversed Nier-Johnson type geometry was used. MIKE ( mass-analysed ion kinetic energy) were measured to investigate decay reactions of mass-selected ions. For the inert gases neon (Ne n + ), argon (Ar n + ) and krypton (Kr n + ), it is found that the binding energies initially decrease with increasing size n and then level off at a value above the enthalpy of vaporization of the condensed phase. Oxygen cluster ions shown a characteristic dependence on cluster size (U-shape) indicating a change in the metastable fragmentation mechanism when going from the dimer to the decamer ion. (nevyjel)

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

REGIONAL DEVELOPMENT BASED ON CLUSTER IN LIVESTOCK DEVELOPMENT. CLUSTER IN LIVESTOCK SECTOR IN THE KYRGYZ REPUBLIC

Directory of Open Access Journals (Sweden)

Meerim SYDYKOVA

2014-11-01

Full Text Available In most developing countries, where agriculture is the main economical source, clusters have been found as a booster to develop their economy. The Asian countries are now starting to implement agro-food clusters into the mainstream of changes in agriculture, farming and food industry. The long-term growth of meat production in the Kyrgyz Republic during the last decade, as well as the fact that agriculture has become one of the prioritized sectors of the economy, proved the importance of livestock sector in the economy of the Kyrgyz Republic. The research question is “Does the Kyrgyz Republic has strong economic opportunities and prerequisites in agriculture in order to implement an effective agro cluster in the livestock sector?” Paper focuses on describing the prerequisites of the Kyrgyz Republic in agriculture to implement livestock cluster. The main objective of the paper is to analyse the livestock sector of the Kyrgyz Republic and observe the capacity of this sector to implement agro-cluster. The study focuses on investigating livestock sector and a complex S.W.O.T. The analysis was carried out based on local and regional database and official studies. The results of research demonstrate the importance of livestock cluster for national economy. It can be concluded that cluster implementation could provide to its all members with benefits if they could build strong collaborative relationship in order to facilitate the access to the labour market and implicitly, the access to exchange of good practices. Their ability of potential cluster members to act as a convergence pole is critical for acquiring practical skills necessary for the future development of the livestock sector.

Exploitation of Clustering Techniques in Transactional Healthcare Data

Directory of Open Access Journals (Sweden)

Naeem Ahmad Mahoto

2014-03-01

Full Text Available Healthcare service centres equipped with electronic health systems have improved their resources as well as treatment processes. The dynamic nature of healthcare data of each individual makes it complex and difficult for physicians to manually mediate them; therefore, automatic techniques are essential to manage the quality and standardization of treatment procedures. Exploratory data analysis, patternanalysis and grouping of data is managed using clustering techniques, which work as an unsupervised classification. A number of healthcare applications are developed that use several data mining techniques for classification, clustering and extracting useful information from healthcare data. The challenging issue in this domain is to select adequate data mining algorithm for optimal results. This paper exploits three different clustering algorithms: DBSCAN (Density-Based Clustering, agglomerative hierarchical and k-means in real transactional healthcare data of diabetic patients (taken as case study to analyse their performance in large and dispersed healthcare data. The best solution of cluster sets among the exploited algorithms is evaluated using clustering quality indexes and is selected to identify the possible subgroups of patients having similar treatment patterns

Cluster models, factors and characteristics for the competitive advantage of Lithuanian Maritime sector

OpenAIRE

Viederytė, Rasa; Didžiokas, Rimantas

2014-01-01

Paper analyses several cluster models on the basis of competitiveness: Nine-factor model, Double diamond model, Funnel model of cluster determinants, Destination Competitiveness and sustainability models, which are related to Porter’s Diamond model and concentrate to the classical one - adopt M. Porter’s Diamond model methodology to the evaluation of Lithuanian Maritime sector’s clustering on the basis of competitiveness. Despite the advances in cluster research, this model remains a complex ...

Adaptive Scaling of Cluster Boundaries for Large-Scale Social Media Data Clustering.

Science.gov (United States)

Meng, Lei; Tan, Ah-Hwee; Wunsch, Donald C

2016-12-01

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the clustering mechanism of Fuzzy ART, and discover the vigilance region (VR) that essentially determines how a cluster in the Fuzzy ART system recognizes similar patterns in the feature space. The VR gives an intrinsic interpretation of the clustering mechanism and limitations of Fuzzy ART. Second, we introduce the idea of allowing different clusters in the Fuzzy ART system to have different vigilance levels in order to meet the diverse nature of the pattern distribution of social media data. To this end, we propose three vigilance adaptation methods, namely, the activation maximization (AM) rule, the confliction minimization (CM) rule, and the hybrid integration (HI) rule. With an initial vigilance value, the resulting clustering algorithms, namely, the AM-ART, CM-ART, and HI-ART, can automatically adapt the vigilance values of all clusters during the learning epochs in order to produce better cluster boundaries. Experiments on four social media data sets show that AM-ART, CM-ART, and HI-ART are more robust than Fuzzy ART to the initial vigilance value, and they usually achieve better or comparable performance and much faster speed than the state-of-the-art clustering algorithms that also do not require a predefined number of clusters.

Random matrix improved subspace clustering

KAUST Repository

Couillet, Romain

2017-03-06

This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based on vector channel observations in the context of massive MIMO wireless communication networks is provided.

Small gold clusters on graphene, their mobility and clustering: a DFT study

International Nuclear Information System (INIS)

Amft, Martin; Sanyal, Biplab; Eriksson, Olle; Skorodumova, Natalia V

2011-01-01

Motivated by the experimentally observed high mobility of gold atoms on graphene and their tendency to form nanometer-sized clusters, we present a density functional theory study of the ground state structures of small gold clusters on graphene, their mobility and clustering. Our detailed analysis of the electronic structures identifies the opportunity to form strong gold-gold bonds and the graphene-mediated interaction of the pre-adsorbed fragments as the driving forces behind gold's tendency to aggregate on graphene. While clusters containing up to three gold atoms have one unambiguous ground state structure, both gas phase isomers of a cluster with four gold atoms can be found on graphene. In the gas phase the diamond-shaped Au 4 D cluster is the ground state structure, whereas the Y-shaped Au 4 Y becomes the actual ground state when adsorbed on graphene. As we show, both clusters can be produced on graphene by two distinct clustering processes. We also studied in detail the stepwise formation of a gold dimer out of two pre-adsorbed adatoms, as well as the formation of Au 3 . All reactions are exothermic and no further activation barriers, apart from the diffusion barriers, were found. The diffusion barriers of all studied clusters range from 4 to 36 meV only, and are substantially exceeded by the adsorption energies of - 0.1 to - 0.59 eV. This explains the high mobility of Au 1-4 on graphene along the C-C bonds.

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.

Science.gov (United States)

Emmons, Scott; Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms-Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters.

The young star cluster population of M51 with LEGUS - II. Testing environmental dependences

Science.gov (United States)

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.

Cognitive Clusters in Specific Learning Disorder.

Science.gov (United States)

Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo

The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The introduction of the single overarching diagnostic category of specific learning disorder (SLD) could underemphasize interindividual clinical differences regarding intracategory cognitive functioning and learning proficiency, according to current models of multiple cognitive deficits at the basis of neurodevelopmental disorders. The characterization of specific cognitive profiles associated with an already manifest SLD could help identify possible early cognitive markers of SLD risk and distinct trajectories of atypical cognitive development leading to SLD. In this perspective, we applied a cluster analysis to identify groups of children with a Diagnostic and Statistical Manual-based diagnosis of SLD with similar cognitive profiles and to describe the association between clusters and SLD subtypes. A sample of 205 children with a diagnosis of SLD were enrolled. Cluster analyses (agglomerative hierarchical and nonhierarchical iterative clustering technique) were used successively on 10 core subtests of the Wechsler Intelligence Scale for Children-Fourth Edition. The 4-cluster solution was adopted, and external validation found differences in terms of SLD subtype frequencies and learning proficiency among clusters. Clinical implications of these findings are discussed, tracing directions for further studies.

Micro-Raman and SEM-EDS analyses to evaluate the nature of salt clusters present in secondary marine aerosol.

Science.gov (United States)

Morillas, Héctor; Marcaida, Iker; García-Florentino, Cristina; Maguregui, Maite; Arana, Gorka; Madariaga, Juan Manuel

2018-02-15

Marine aerosol is a complex inorganic and organic chemistry system which contains several salts, mainly forming different type of salt clusters. Different meteorological parameters have a key role in the formation of these aggregates. The relative humidity (%RH), temperature, CO, SO 2 and NO x levels and even the O 3 levels can promote different chemical reactions giving rise to salt clusters with different morphology and sizes. Sulfates, nitrates and chlorides and even mixed chlorosulfates or nitrosulfates are the final compounds which can be found in environments with a direct influence of marine aerosol. In order to collect and analyze these types of compounds, the use of adequate samplers is crucial. In this work, salt clusters were collected thanks to the use of a self-made passive sampler (SMPS) installed in a 20th century historic building (Punta Begoña Galleries, Getxo, Basque Country, Spain) which is surrounded by a beach and a sportive port. These salt clusters were finally analyzed directly by micro-Raman spectroscopy and Scanning Electron microscopy coupled to Energy Dispersive X-ray spectrometry (SEM-EDS). Copyright © 2017 Elsevier B.V. All rights reserved.

Switching Monopolar Radiofrequency Ablation Using a Separable Cluster Electrode in Patients with Hepatocellular Carcinoma: A Prospective Study.

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Jin Woo Choi

Full Text Available This study was conducted to evaluate the outcomes of multi-channel switching RFA using a separable cluster electrode in patients with HCC.From November 2011 to July 2013, 79 patients with 98 HCCs < 5 cm were enrolled and treated with RFA using a multi-channel switching radiofrequency system and a separable cluster electrode under the guidance of a real-time fusion imaging system. The primary and secondary endpoints were the 3-year local tumor progression (LTP rate and recurrence-free survival (RFS rate, respectively. For post hoc analyses, LTP, RFS, and major complication rates were retrospectively compared with a historical control group treated with RFA using the same radiofrequency system but with multiple internally-cooled electrodes.The technique success rate of the 98 tumors was 100%. Cumulative 1-year, 2-year, and 3-year LTP rates were 3.4%, 6.9%, and 12.4%, respectively. For patient-level data, cumulative 1-year, 2-year, and 3-year RFS rates were 83.9%, 68.6%, and 45.4%, respectively. On post hoc analyses, none of the baseline characteristics showed a significant difference between the separable cluster electrode and multiple internally-cooled electrodes group. Cumulative LTP and RFS rates of the two groups also showed no significant difference (p = 0.401 and p = 0.881, respectively. Finally, major complication rates of the separable cluster electrode group (5.0%, 4/79 and multiple internally-cooled electrodes group (5.9%, 4/74 were also comparable (p = 1.000.Switching monopolar RFA using a separable cluster electrode is a feasible and efficient technique for the treatment of HCCs smaller than 5 cm, providing comparable local tumor control to multiple internally-cooled electrodes.ClinicalTrials.gov NCT02745483.

Monoatomic and cluster beam effect on ToF-SIMS spectra of self-assembled monolayers on gold

Energy Technology Data Exchange (ETDEWEB)

Tuccitto, N. [Dipartimento di Scienze Chimiche Universita degli Studi di Catania, v.le A. Doria 6, 95125, Catania (Italy)], E-mail: n.tuccitto@unict.it; Torrisi, V.; Delfanti, I.; Licciardello, A. [Dipartimento di Scienze Chimiche Universita degli Studi di Catania, v.le A. Doria 6, 95125, Catania (Italy)

2008-12-15

Self-assembled monolayers represent well-defined systems that is a good model surface to study the effect of primary ion beams used in secondary ion mass spectrometry. The effect of polyatomic primary beams on both aliphatic and aromatic self-assembled monolayers has been studied. In particular, we analysed the variation of the relative secondary ion yield of both substrate metal-cluster (Au{sub n}{sup -}) in comparison with the molecular ions (M{sup -}) and clusters (M{sub x}Au{sub y}{sup -}) by using Bi{sup +}, Bi{sub 3}{sup +}, Bi{sub 5}{sup +} beams. Moreover, the differences in the secondary ion generation efficiency are discussed. The main effect of the cluster beams is related to an increased formation of low-mass fragments and to the enhancement of the substrate related gold-clusters. The results show that, at variance of many other cases, the static SIMS of self-assembled monolayers does not benefit of the use of polyatomic primary ions.

Clustering of Helium Atoms at a ½

NARCIS (Netherlands)

Berg, F. v.d.; Heugten, W. v.; Caspers, L.M.; Veen, A. v.; Hosson, J.Th.M. de

1977-01-01

Atomistic calculations on a ½<111>{110} edge dislocation show a restricted tendency of clustering of helium atom along this dislocation. Clusters with up to 4 helium atoms have been studied. A cluster with 3 helium proved to be most stable.

Cluster Analysis of Maize Inbred Lines

Directory of Open Access Journals (Sweden)

Jiban Shrestha

2016-12-01

Full Text Available The determination of diversity among inbred lines is important for heterosis breeding. Sixty maize inbred lines were evaluated for their eight agro morphological traits during winter season of 2011 to analyze their genetic diversity. Clustering was done by average linkage method. The inbred lines were grouped into six clusters. Inbred lines grouped into Clusters II had taller plants with maximum number of leaves. The cluster III was characterized with shorter plants with minimum number of leaves. The inbred lines categorized into cluster V had early flowering whereas the group into cluster VI had late flowering time. The inbred lines grouped into the cluster III were characterized by higher value of anthesis silking interval (ASI and those of cluster VI had lower value of ASI. These results showed that the inbred lines having widely divergent clusters can be utilized in hybrid breeding programme.

Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells.

Science.gov (United States)

Tait, Luke; Wedgwood, Kyle; Tsaneva-Atanasova, Krasimira; Brown, Jon T; Goodfellow, Marc

2018-07-14

The entorhinal cortex is a crucial component of our memory and spatial navigation systems and is one of the first areas to be affected in dementias featuring tau pathology, such as Alzheimer's disease and frontotemporal dementia. Electrophysiological recordings from principle cells of medial entorhinal cortex (layer II stellate cells, mEC-SCs) demonstrate a number of key identifying properties including subthreshold oscillations in the theta (4-12 Hz) range and clustered action potential firing. These single cell properties are correlated with network activity such as grid firing and coupling between theta and gamma rhythms, suggesting they are important for spatial memory. As such, experimental models of dementia have revealed disruption of organised dorsoventral gradients in clustered action potential firing. To better understand the mechanisms underpinning these different dynamics, we study a conductance based model of mEC-SCs. We demonstrate that the model, driven by extrinsic noise, can capture quantitative differences in clustered action potential firing patterns recorded from experimental models of tau pathology and healthy animals. The differential equation formulation of our model allows us to perform numerical bifurcation analyses in order to uncover the dynamic mechanisms underlying these patterns. We show that clustered dynamics can be understood as subcritical Hopf/homoclinic bursting in a fast-slow system where the slow sub-system is governed by activation of the persistent sodium current and inactivation of the slow A-type potassium current. In the full system, we demonstrate that clustered firing arises via flip bifurcations as conductance parameters are varied. Our model analyses confirm the experimentally suggested hypothesis that the breakdown of clustered dynamics in disease occurs via increases in AHP conductance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Advanced Behavioral Analyses Show that the Presence of Food Causes Subtle Changes in C. elegans Movement.

Science.gov (United States)

Angstman, Nicholas B; Frank, Hans-Georg; Schmitz, Christoph

2016-01-01

As a widely used and studied model organism, Caenorhabditis elegans worms offer the ability to investigate implications of behavioral change. Although, investigation of C. elegans behavioral traits has been shown, analysis is often narrowed down to measurements based off a single point, and thus cannot pick up on subtle behavioral and morphological changes. In the present study videos were captured of four different C. elegans strains grown in liquid cultures and transferred to NGM-agar plates with an E. coli lawn or with no lawn. Using an advanced software, WormLab, the full skeleton and outline of worms were tracked to determine whether the presence of food affects behavioral traits. In all seven investigated parameters, statistically significant differences were found in worm behavior between those moving on NGM-agar plates with an E. coli lawn and NGM-agar plates with no lawn. Furthermore, multiple test groups showed differences in interaction between variables as the parameters that significantly correlated statistically with speed of locomotion varied. In the present study, we demonstrate the validity of a model to analyze C. elegans behavior beyond simple speed of locomotion. The need to account for a nested design while performing statistical analyses in similar studies is also demonstrated. With extended analyses, C. elegans behavioral change can be investigated with greater sensitivity, which could have wide utility in fields such as, but not limited to, toxicology, drug discovery, and RNAi screening.

Advanced behavioral analyses show that the presence of food causes subtle changes in C. elegans movement

Directory of Open Access Journals (Sweden)

Nicholas eAngstman

2016-03-01

Full Text Available As a widely used and studied model organism, C. elegans worms offer the ability to investigate implications of behavioral change. Although investigation of C. elegans behavioral traits has been shown, analysis is often narrowed down to measurements based off a single point, and thus cannot pick up on subtle behavioral and morphological changes. In the present study videos were captured of four different C. elegans strains grown in liquid cultures and transferred to NGM-agar plates with an E. coli lawn or with no lawn. Using an advanced software, WormLab, the full skeleton and outline of worms were tracked to determine whether the presence of food affects behavioral traits. In all seven investigated parameters, statistically significant differences were found in worm behavior between those moving on NGM-agar plates with an E. coli lawn and NGM-agar plates with no lawn. Furthermore, multiple test groups showed differences in interaction between variables as the parameters that significantly correlated statistically with speed of locomotion varied. In the present study, we demonstrate the validity of a model to analyze C. elegans behavior beyond simple speed of locomotion. The need to account for a nested design while performing statistical analyses in similar studies is also demonstrated. With extended analyses, C. elegans behavioral change can be investigated with greater sensitivity, which could have wide utility in fields such as, but not limited to, toxicology, drug discovery, and RNAi screening.

Clustering Coefficients for Correlation Networks

Directory of Open Access Journals (Sweden)

Naoki Masuda

2018-03-01

Full Text Available Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients

Clustering Coefficients for Correlation Networks.

Science.gov (United States)

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

Clustering Coefficients for Correlation Networks

Science.gov (United States)

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

Persistence drives gene clustering in bacterial genomes

Directory of Open Access Journals (Sweden)

Rocha Eduardo PC

2008-01-01

Full Text Available Abstract Background Gene clustering plays an important role in the organization of the bacterial chromosome and several mechanisms have been proposed to explain its extent. However, the controversies raised about the validity of each of these mechanisms remind us that the cause of this gene organization remains an open question. Models proposed to explain clustering did not take into account the function of the gene products nor the likely presence or absence of a given gene in a genome. However, genomes harbor two very different categories of genes: those genes present in a majority of organisms – persistent genes – and those present in very few organisms – rare genes. Results We show that two classes of genes are significantly clustered in bacterial genomes: the highly persistent and the rare genes. The clustering of rare genes is readily explained by the selfish operon theory. Yet, genes persistently present in bacterial genomes are also clustered and we try to understand why. We propose a model accounting specifically for such clustering, and show that indispensability in a genome with frequent gene deletion and insertion leads to the transient clustering of these genes. The model describes how clusters are created via the gene flux that continuously introduces new genes while deleting others. We then test if known selective processes, such as co-transcription, physical interaction or functional neighborhood, account for the stabilization of these clusters. Conclusion We show that the strong selective pressure acting on the function of persistent genes, in a permanent state of flux of genes in bacterial genomes, maintaining their size fairly constant, that drives persistent genes clustering. A further selective stabilization process might contribute to maintaining the clustering.

Facilitating Cluster Evolution in Peripheral Regions

DEFF Research Database (Denmark)

Christensen, Jesper Lindgaard; Stoerring, Dagmara

2012-01-01

This paper discusses the feasibility and dilemmas in stimulating high-tech clusters in peripheral regions. In recent years innovation and cluster policy to a large extend has been focused upon stimulating collective learning processes and building social capital. This has in turn accentuated a need...... to focus on the carriers of the cluster policy. Despite this importance of the role of policy actors, research in cluster development and even cluster policy has generally not emphasized a more precise specification of this role. This paper contributes to this debate by substantiating the concept...... of “clusterpreneurs” defined as important actors in cluster formation. We illustrate the role of clusterpreneurs by the example of a biomedical technology cluster initiative in North Jutland, Denmark and point to the presence of different types of dilemmas connected with cluster policy. We show how the presence...

THE DYNAMICAL STATE OF BRIGHTEST CLUSTER GALAXIES AND THE FORMATION OF CLUSTERS

International Nuclear Information System (INIS)

Coziol, R.; Andernach, H.; Caretta, C. A.; Alamo-MartInez, K. A.; Tago, E.

2009-01-01

A large sample of Abell clusters of galaxies, selected for the likely presence of a dominant galaxy, is used to study the dynamical properties of the brightest cluster members (BCMs). From visual inspection of Digitized Sky Survey images combined with redshift information we identify 1426 candidate BCMs located in 1221 different redshift components associated with 1169 different Abell clusters. This is the largest sample published so far of such galaxies. From our own morphological classification we find that ∼92% of the BCMs in our sample are early-type galaxies and 48% are of cD type. We confirm what was previously observed based on much smaller samples, namely, that a large fraction of BCMs have significant peculiar velocities. From a subsample of 452 clusters having at least 10 measured radial velocities, we estimate a median BCM peculiar velocity of 32% of their host clusters' radial velocity dispersion. This suggests that most BCMs are not at rest in the potential well of their clusters. This phenomenon is common to galaxy clusters in our sample, and not a special trait of clusters hosting cD galaxies. We show that the peculiar velocity of the BCM is independent of cluster richness and only slightly dependent on the Bautz-Morgan type. We also find a weak trend for the peculiar velocity to rise with the cluster velocity dispersion. The strongest dependence is with the morphological type of the BCM: cD galaxies tend to have lower relative peculiar velocities than elliptical galaxies. This result points to a connection between the formation of the BCMs and that of their clusters. Our data are qualitatively consistent with the merging-groups scenario, where BCMs in clusters formed first in smaller subsystems comparable to compact groups of galaxies. In this scenario, clusters would have formed recently from the mergers of many such groups and would still be in a dynamically unrelaxed state.

Canonical PSO Based K-Means Clustering Approach for Real Datasets.

Science.gov (United States)

Dey, Lopamudra; Chakraborty, Sanjay

2014-01-01

"Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.

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

Science.gov (United States)

van Uitert, Edo; Joachimi, Benjamin

2017-07-01

We measure the alignment of the shapes of galaxy clusters, as traced by their satellite distributions, with the matter density field using the public redMaPPer catalogue based on Sloan Digital Sky Survey-Data Release 8 (SDSS-DR8), which contains 26 111 clusters up to z ˜ 0.6. The clusters are split into nine redshift and richness samples; in each of them, we detect a positive alignment, showing that clusters point towards density peaks. We interpret the measurements within the tidal alignment paradigm, allowing for a richness and redshift dependence. The intrinsic alignment (IA) amplitude at the pivot redshift z = 0.3 and pivot richness λ = 30 is A_IA^gen=12.6_{-1.2}^{+1.5}. We obtain tentative evidence that the signal increases towards higher richness and lower redshift. Our measurements agree well with results of maxBCG clusters and with dark-matter-only simulations. Comparing our results to the IA measurements of luminous red galaxies, we find that the IA amplitude of galaxy clusters forms a smooth extension towards higher mass. This suggests that these systems share a common alignment mechanism, which can be exploited to improve our physical understanding of IA.

TURBULENCE AND DYNAMO IN GALAXY CLUSTER MEDIUM: IMPLICATIONS ON THE ORIGIN OF CLUSTER MAGNETIC FIELDS

International Nuclear Information System (INIS)

Xu Hao; Collins, David C.; Norman, Michael L.; Li Hui; Li Shengtai

2009-01-01

We present self-consistent cosmological magnetohydrodynamic (MHD) simulations that simultaneously follow the formation of a galaxy cluster and the magnetic field ejection by an active galactic nucleus (AGN). We find that the magnetic fields ejected by the AGNs, though initially distributed in relatively small volumes, can be transported throughout the cluster and be further amplified by the intracluster medium (ICM) turbulence during the cluster formation process. The ICM turbulence is shown to be generated and sustained by the frequent mergers of smaller halos. Furthermore, a cluster-wide dynamo process is shown to exist in the ICM and amplify the magnetic field energy and flux. The total magnetic energy in the cluster can reach ∼10 61 erg while micro Gauss (μG) fields can distribute over ∼ Mpc scales throughout the whole cluster. This finding shows that magnetic fields from AGNs, being further amplified by the ICM turbulence through small-scale dynamo processes, can be the origin of cluster-wide magnetic fields.

Brightest Cluster Galaxies in REXCESS Clusters

Science.gov (United States)

Haarsma, Deborah B.; Leisman, L.; Bruch, S.; Donahue, M.

2009-01-01

Most galaxy clusters contain a Brightest Cluster Galaxy (BCG) which is larger than the other cluster ellipticals and has a more extended profile. In the hierarchical model, the BCG forms through many galaxy mergers in the crowded center of the cluster, and thus its properties give insight into the assembly of the cluster as a whole. In this project, we are working with the Representative XMM-Newton Cluster Structure Survey (REXCESS) team (Boehringer et al 2007) to study BCGs in 33 X-ray luminous galaxy clusters, 0.055 < z < 0.183. We are imaging the BCGs in R band at the Southern Observatory for Astrophysical Research (SOAR) in Chile. In this poster, we discuss our methods and give preliminary measurements of the BCG magnitudes, morphology, and stellar mass. We compare these BCG properties with the properties of their host clusters, particularly of the X-ray emitting gas.

Orbit Clustering Based on Transfer Cost

Science.gov (United States)

Gustafson, Eric D.; Arrieta-Camacho, Juan J.; Petropoulos, Anastassios E.

2013-01-01

We propose using cluster analysis to perform quick screening for combinatorial global optimization problems. The key missing component currently preventing cluster analysis from use in this context is the lack of a useable metric function that defines the cost to transfer between two orbits. We study several proposed metrics and clustering algorithms, including k-means and the expectation maximization algorithm. We also show that proven heuristic methods such as the Q-law can be modified to work with cluster analysis.

Quantifying Shapes: Mathematical Techniques for Analysing Visual Representations of Sound and Music

Directory of Open Access Journals (Sweden)

Genevieve L. Noyce

2013-12-01

Full Text Available Research on auditory-visual correspondences has a long tradition but innovative experimental paradigms and analytic tools are sparse. In this study, we explore different ways of analysing real-time visual representations of sound and music drawn by both musically-trained and untrained individuals. To that end, participants' drawing responses captured by an electronic graphics tablet were analysed using various regression, clustering, and classification techniques. Results revealed that a Gaussian process (GP regression model with a linear plus squared-exponential covariance function was able to model the data sufficiently, whereas a simpler GP was not a good fit. Spectral clustering analysis was the best of a variety of clustering techniques, though no strong groupings are apparent in these data. This was confirmed by variational Bayes analysis, which only fitted one Gaussian over the dataset. Slight trends in the optimised hyperparameters between musically-trained and untrained individuals allowed for the building of a successful GP classifier that differentiated between these two groups. In conclusion, this set of techniques provides useful mathematical tools for analysing real-time visualisations of sound and can be applied to similar datasets as well.

Seniority-based coupled cluster theory

International Nuclear Information System (INIS)

Henderson, Thomas M.; Scuseria, Gustavo E.; Bulik, Ireneusz W.; Stein, Tamar

2014-01-01

Doubly occupied configuration interaction (DOCI) with optimized orbitals often accurately describes strong correlations while working in a Hilbert space much smaller than that needed for full configuration interaction. However, the scaling of such calculations remains combinatorial with system size. Pair coupled cluster doubles (pCCD) is very successful in reproducing DOCI energetically, but can do so with low polynomial scaling (N 3 , disregarding the two-electron integral transformation from atomic to molecular orbitals). We show here several examples illustrating the success of pCCD in reproducing both the DOCI energy and wave function and show how this success frequently comes about. What DOCI and pCCD lack are an effective treatment of dynamic correlations, which we here add by including higher-seniority cluster amplitudes which are excluded from pCCD. This frozen pair coupled cluster approach is comparable in cost to traditional closed-shell coupled cluster methods with results that are competitive for weakly correlated systems and often superior for the description of strongly correlated systems

Crystallographic and mutational analyses of cystathionine β-synthase in the H2 S-synthetic gene cluster in Lactobacillus plantarum.

Science.gov (United States)

Matoba, Yasuyuki; Yoshida, Tomoki; Izuhara-Kihara, Hisae; Noda, Masafumi; Sugiyama, Masanori

2017-04-01

Cystathionine β-synthase (CBS) catalyzes the formation of l-cystathionine from l-serine and l-homocysteine. The resulting l-cystathionine is decomposed into l-cysteine, ammonia, and α-ketobutylic acid by cystathionine γ-lyase (CGL). This reverse transsulfuration pathway, which is catalyzed by both enzymes, mainly occurs in eukaryotic cells. The eukaryotic CBS and CGL have recently been recognized as major physiological enzymes for the generation of hydrogen sulfide (H 2 S). In some bacteria, including the plant-derived lactic acid bacterium Lactobacillus plantarum, the CBS- and CGL-encoding genes form a cluster in their genomes. Inactivation of these enzymes has been reported to suppress H 2 S production in bacteria; interestingly, it has been shown that H 2 S suppression increases their susceptibility to various antibiotics. In the present study, we characterized the enzymatic properties of the L. plantarum CBS, whose amino acid sequence displays a similarity with those of O-acetyl-l-serine sulfhydrylase (OASS) that catalyzes the generation of l-cysteine from O-acetyl-l-serine (l-OAS) and H 2 S. The L. plantarum CBS shows l-OAS- and l-cysteine-dependent CBS activities together with OASS activity. Especially, it catalyzes the formation of H 2 S in the presence of l-cysteine and l-homocysteine, together with the formation of l-cystathionine. The high affinity toward l-cysteine as a first substrate and tendency to use l-homocysteine as a second substrate might be associated with its enzymatic ability to generate H 2 S. Crystallographic and mutational analyses of CBS indicate that the Ala70 and Glu223 residues at the substrate binding pocket are important for the H 2 S-generating activity. © 2017 The Protein Society.

Competitive cluster growth in complex networks.

Science.gov (United States)

Moreira, André A; Paula, Demétrius R; Costa Filho, Raimundo N; Andrade, José S

2006-06-01

In this work we propose an idealized model for competitive cluster growth in complex networks. Each cluster can be thought of as a fraction of a community that shares some common opinion. Our results show that the cluster size distribution depends on the particular choice for the topology of the network of contacts among the agents. As an application, we show that the cluster size distributions obtained when the growth process is performed on hierarchical networks, e.g., the Apollonian network, have a scaling form similar to what has been observed for the distribution of a number of votes in an electoral process. We suggest that this similarity may be due to the fact that social networks involved in the electoral process may also possess an underlining hierarchical structure.

THE EVOLUTION OF DUSTY STAR FORMATION IN GALAXY CLUSTERS TO z = 1: SPITZER INFRARED OBSERVATIONS OF THE FIRST RED-SEQUENCE CLUSTER SURVEY

International Nuclear Information System (INIS)

Webb, T. M. A.; O'Donnell, D.; Coppin, Kristen; Faloon, Ashley; Geach, James E.; Noble, Allison; Yee, H. K. C.; Gilbank, David; Ellingson, Erica; Gladders, Mike; Muzzin, Adam; Wilson, Gillian; Yan, Renbin

2013-01-01

We present the results of an infrared (IR) study of high-redshift galaxy clusters with the MIPS camera on board the Spitzer Space Telescope. We have assembled a sample of 42 clusters from the Red-Sequence Cluster Survey-1 over the redshift range 0.3 14-15 M ☉ . We statistically measure the number of IR-luminous galaxies in clusters above a fixed inferred IR luminosity of 2 × 10 11 M ☉ , assuming a star forming galaxy template, per unit cluster mass and find it increases to higher redshift. Fitting a simple power-law we measure evolution of (1 + z) 5.1±1.9 over the range 0.3 cluster ). The evolution is similar, with ΣSFR/M cluster ∼ (1 + z) 5.4±1.9 . We show that this can be accounted for by the evolution of the IR-bright field population over the same redshift range; that is, the evolution can be attributed entirely to the change in the in-falling field galaxy population. We show that the ΣSFR/M cluster (binned over all redshift) decreases with increasing cluster mass with a slope (ΣSFR/M cluster ∼M cluster -1.5±0.4 ) consistent with the dependence of the stellar-to-total mass per unit cluster mass seen locally. The inferred star formation seen here could produce ∼5%-10% of the total stellar mass in massive clusters at z = 0, but we cannot constrain the descendant population, nor how rapidly the star-formation must shut-down once the galaxies have entered the cluster environment. Finally, we show a clear decrease in the number of IR-bright galaxies per unit optical galaxy in the cluster cores, confirming star formation continues to avoid the highest density regions of the universe at z ∼ 0.75 (the average redshift of the high-redshift clusters). While several previous studies appear to show enhanced star formation in high-redshift clusters relative to the field we note that these papers have not accounted for the overall increase in galaxy or dark matter density at the location of clusters. Once this is done, clusters at z ∼ 0.75 have the same

A novel approach to dynamic livelihood clustering

DEFF Research Database (Denmark)

Walelign, Solomon Zena; Pouliot, Mariéve; Larsen, Helle Overgaard

-wave panel dataset from 427 households in three locations of Nepal, we proposed an approach that combines households’ income and assets to identify different livelihood strategy clusters. Based on a Latent Markov Model we identify seven distinct livelihood strategies and analyse households’ movements between...

STRATEGIES FOR DEVELOPING SUSTAINABLE AND COMPETITIVE CLUSTER FOR SHRIMP INDUSTRY

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Anas M. Fauzi

2012-09-01

Full Text Available Kampung Vannamei as shrimp cluster is being developed since 2004 by PT CP Prima, tbk Surabaya through Shrimp Culture Health Management transformation technology to several traditional farmers in Gresik, Lamongan, Tuban, and Madura areas. The research objectives aims to identify and mapping of stakeholder, to analyze interaction of stakeholders, to formulate strategy from internal and external environment factors and to set priority on strategy to develop sustainable and competitive shrimp cluster in the Kampung vannamei. Primary data was collected through stakeholders’ discussion forums, questionnaires, and interviews with relevant actors. Observations to the business unit also performed to determine the production and business conditions, particularly in capturing information about the threat and challenges. While the secondary data is used in policy documents national and local area statistics, and relevant literature. Analyses were performed by using the SRI International cluster pyramid, diamond porter’s analysis, SWOT and Matrix TOWS analysis, and analytical hierarchy process. Analyses were performed by the methods discussed in qualitative and descriptive. There are 7 strategies could be implemented to develop sustainable and competitive shrimp cluster. However, it is recommended to implement the strategy base on priority, which the first priority is strategy to improve linkages between businesses in the upstream and downstream industries into multi stakeholders’ platform in shrimp industry.Keywords: Shrimp, Cluster, Competitiveness, Diamond Porter, SWOT Analysis, AHP

Metal cluster compounds - chemistry and importance; clusters containing isolated main group element atoms, large metal cluster compounds, cluster fluxionality

International Nuclear Information System (INIS)

Walther, B.

1988-01-01

This part of the review on metal cluster compounds deals with clusters containing isolated main group element atoms, with high nuclearity clusters and metal cluster fluxionality. It will be obvious that main group element atoms strongly influence the geometry, stability and reactivity of the clusters. High nuclearity clusters are of interest in there own due to the diversity of the structures adopted, but their intermediate position between molecules and the metallic state makes them a fascinating research object too. These both sites of the metal cluster chemistry as well as the frequently observed ligand and core fluxionality are related to the cluster metal and surface analogy. (author)

IDENTIFICAÇÃO DE CLUSTERS INTERNACIONAIS COM BASE NAS DIMENSÕES CULTURAIS DE HOFSTEDE. / Identification of international clusters based on the hofstede’s cultural dimensions

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Valderí de Castro Alcântara1

2012-08-01

Full Text Available Haja vista que a cultura de um país influencia a cultura organizacional das empresas nele presente e ainda é fator determinante no processo de internacionalização, torna-se relevante compreender e mensurar as características culturais de cada país. Os estudos de Hofstede (1984 apresentam uma metodologia útil para comparação entre culturas. Tal metodologia leva em consideração as características deuma cultura que possibilita diferenciar um país de outro. Dessa forma, é possível observar que determinados países compartilham certos traços culturais e, assim, é possível agrupá-los segundo critérios pré-estabelecidos. O presente trabalho objetiva utilizar-se de procedimentos estatísticos multivariados Clusters Analyses, K-Means Cluster Analysis e Análise Discriminante para determinar e validar agrupamentos de países, com base nas dimensões culturais de Hofstede (Distance Index, Individualism, Masculinity e Uncertainty Avoidance Index. Os resultados determinaram quatro clusters: Cluster 1 - países com cultura masculina e individualista; Cluster 2 - cultura coletivista e aversa à incerteza; Cluster 3 - cultura feminina e com baixa distância hierárquica; e Cluster 4 - cultura com elevada distância hierárquica e propensão à incerteza./ Considering that the culture of a country influences the organizational culture of this company and it is still a determining factor in the internationalization process becomes important to understand and measure the cultural characteristics of each country. The studies of Hofstede (1984 present a useful methodology for comparing cultures, this methodology takes into account the characteristics of a culturethat allows to differentiate one from another country. Thus one can observe that certain countries share certain cultural traits and so it is possible grouping them according to predetermined criteria. The present work aims to utilize multivariate statistical procedures Cluster Analyses

Sizing the star cluster population of the Large Magellanic Cloud

Science.gov (United States)

Piatti, Andrés E.

2018-04-01

The number of star clusters that populate the Large Magellanic Cloud (LMC) at deprojected distances knowledge of the LMC cluster formation and dissolution histories, we closely revisited such a compilation of objects and found that only ˜35 per cent of the previously known catalogued clusters have been included. The remaining entries are likely related to stellar overdensities of the LMC composite star field, because there is a remarkable enhancement of objects with assigned ages older than log(t yr-1) ˜ 9.4, which contrasts with the existence of the LMC cluster age gap; the assumption of a cluster formation rate similar to that of the LMC star field does not help to conciliate so large amount of clusters either; and nearly 50 per cent of them come from cluster search procedures known to produce more than 90 per cent of false detections. The lack of further analyses to confirm the physical reality as genuine star clusters of the identified overdensities also glooms those results. We support that the actual size of the LMC main body cluster population is close to that previously known.

Family-based clusters of cognitive test performance in familial schizophrenia

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Partonen Timo

2004-07-01

Full Text Available Abstract Background Cognitive traits derived from neuropsychological test data are considered to be potential endophenotypes of schizophrenia. Previously, these traits have been found to form a valid basis for clustering samples of schizophrenia patients into homogeneous subgroups. We set out to identify such clusters, but apart from previous studies, we included both schizophrenia patients and family members into the cluster analysis. The aim of the study was to detect family clusters with similar cognitive test performance. Methods Test scores from 54 randomly selected families comprising at least two siblings with schizophrenia spectrum disorders, and at least two unaffected family members were included in a complete-linkage cluster analysis with interactive data visualization. Results A well-performing, an impaired, and an intermediate family cluster emerged from the analysis. While the neuropsychological test scores differed significantly between the clusters, only minor differences were observed in the clinical variables. Conclusions The visually aided clustering algorithm was successful in identifying family clusters comprising both schizophrenia patients and their relatives. The present classification method may serve as a basis for selecting phenotypically more homogeneous groups of families in subsequent genetic analyses.

A Combinatorial Formula for Certain Elements of Upper Cluster Algebras

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Lee, Kyungyong; Li, Li; Mills, Matthew R.

2015-06-01

We develop an elementary formula for certain non-trivial elements of upper cluster algebras. These elements have positive coefficients. We show that when the cluster algebra is acyclic these elements form a basis. Using this formula, we show that each non-acyclic skew-symmetric cluster algebra of rank 3 is properly contained in its upper cluster algebra.

Knowledge between communities of practice and firms in clusters

DEFF Research Database (Denmark)

Reinau, Kristian Hegner

. This paper presents a case study in which theory about knowledge, communities of practice and networks is used to understand how knowledge is developed in high-tech companies placed in a cluster. The case study illuminates how internal and external relations and factors affect the knowledge development...... which factors that affect the knowledge development process in communities in the case companies. By analysing the interplay between formal and informal relations utilized by the companies, the knowledge embedded in the persons constituting the communities as well as knowledge embedded in objects used......Currently there is growing focus on how cluster internal and cluster external relations affect the creation of knowledge in companies placed in clusters. However, the current theories on this topic are too simple and the interplay between internal and external relations is relatively unknown...

Energy band dispersion in photoemission spectra of argon clusters

International Nuclear Information System (INIS)

Foerstel, Marko; Mucke, Melanie; Arion, Tiberiu; Lischke, Toralf; Barth, Silko; Ulrich, Volker; Ohrwall, Gunnar; Bjoerneholm, Olle; Hergenhahn, Uwe; Bradshaw, Alex M.

2011-01-01

Using photoemission we have investigated free argon clusters from a supersonic nozzle expansion in the photon energy range from threshold up to 28 eV. Measurements were performed both at high resolution with a hemispherical electrostatic energy analyser and at lower resolution with a magnetic bottle device. The latter experiments were performed for various mean cluster sizes. In addition to the ∼1.5 eV broad 3p-derived valence band seen in previous work, there is a sharper feature at ∼15 eV binding energy. Surprisingly for non-oriented clusters, this peak shifts smoothly in binding energy over the narrow photon energy range 15.5-17.7 eV, indicating energy band dispersion. The onset of this bulk band-like behaviour could be determined from the cluster size dependence.

CLASH-VLT: constraints on f (R) gravity models with galaxy clusters using lensing and kinematic analyses

Energy Technology Data Exchange (ETDEWEB)

Pizzuti, L.; Sartoris, B.; Borgani, S.; Girardi, M., E-mail: pizzuti@oats.inaf.it, E-mail: sartoris@oats.inaf.it, E-mail: borgani@oats.inaf.it, E-mail: girardi@oats.inaf.it [Dipartimento di Fisica, Sezione di Astronomia, Università di Trieste, Via Tiepolo 11, I-34143 Trieste (Italy); and others

2017-07-01

We perform a maximum likelihood kinematic analysis of the two dynamically relaxed galaxy clusters MACS J1206.2-0847 at z =0.44 and RXC J2248.7-4431 at z =0.35 to determine the total mass profile in modified gravity models, using a modified version of the MAMPOSSt code of Mamon, Biviano and Bou and apos;e. Our work is based on the kinematic and lensing mass profiles derived using the data from the Cluster Lensing And Supernova survey with Hubble (hereafter CLASH) and the spectroscopic follow-up with the Very Large Telescope (hereafter CLASH-VLT). We assume a spherical Navarro-Frenk-White (NFW hereafter) profile in order to obtain a constraint on the fifth force interaction range λ for models in which the dependence of this parameter on the environment is negligible at the scale considered (i.e. λ= const ) and fixing the fifth force strength to the value predicted in f (R) gravity. We then use information from lensing analysis to put a prior on the other NFW free parameters. In the case of MACSJ 1206 the joint kinematic+lensing analysis leads to an upper limit on the effective interaction range λ≤1.61 mpc at Δχ{sup 2}=2.71 on the marginalized distribution. For RXJ 2248 instead a possible tension with the ΛCDM model appears when adding lensing information, with a lower limit λ≥0.14 mpc at Δχ{sup 2}=2.71. This is consequence of the slight difference between the lensing and kinematic data, appearing in GR for this cluster, that could in principle be explained in terms of modifications of gravity. We discuss the impact of systematics and the limits of our analysis as well as future improvements of the results obtained. This work has interesting implications in view of upcoming and future large imaging and spectroscopic surveys, that will deliver lensing and kinematic mass reconstruction for a large number of galaxy clusters.

Cluster analyses of 20th century growth patterns in high elevation Great Basin bristlecone pine in the Snake Mountain Range, Nevada, USA

Science.gov (United States)

Tran, T. J.; Bruening, J. M.; Bunn, A. G.; Salzer, M. W.; Weiss, S. B.

2015-12-01

Great Basin bristlecone pine (Pinus longaeva) is a useful climate proxy because of the species' long lifespan (up to 5000 years) and the climatic sensitivity of its annually-resolved rings. Past studies have shown that growth of individual trees can be limited by temperature, soil moisture, or a combination of the two depending on biophysical setting at the scale of tens of meters. We extend recent research suggesting that trees vary in their growth response depending on their position on the landscape to analyze how growth patterns vary over time. We used hierarchical cluster analysis to examine the growth of 52 bristlecone pine trees near the treeline of Mount Washington, Nevada, USA. We classified growth of individual trees over the instrumental climate record into one of two possible scenarios: trees belonging to a temperature-sensitive cluster and trees belonging to a precipitation-sensitive cluster. The number of trees in the precipitation-sensitive cluster outnumbered the number of trees in the temperature-sensitive cluster, with trees in colder locations belonging to the temperature-sensitive cluster. When we separated the temporal range into two sections (1895-1949 and 1950-2002) spanning the length of the instrumental climate record, we found that most of the 52 trees remained loyal to their cluster membership (e.g., trees in the temperature-sensitive cluster in 1895-1949 were also in the temperature sensitive cluster in 1950-2002), though not without exception. Of those trees that do not remain consistent in cluster membership, the majority changed from temperature-sensitive to precipitation-sensitive as time progressed. This could signal a switch from temperature limitation to water limitation with warming climate. We speculate that topographic complexity in high mountain environments like Mount Washington might allow for climate refugia where growth response could remain constant over the Holocene.

A possibilistic approach to clustering

Science.gov (United States)

Krishnapuram, Raghu; Keller, James M.

1993-01-01

Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Conformational Clusters of Phosphorylated Tyrosine.

Science.gov (United States)

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

2017-12-06

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

Identification of a large, fast-expanding HIV-1 subtype B transmission cluster among MSM in Valencia, Spain.

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Juan Ángel Patiño-Galindo

Full Text Available We describe and characterize an exceptionally large HIV-1 subtype B transmission cluster occurring in the Comunidad Valenciana (CV, Spain. A total of 1806 HIV-1 protease-reverse transcriptase (PR/RT sequences from different patients were obtained in the CV between 2004 and 2014. After subtyping and generating a phylogenetic tree with additional HIV-1 subtype B sequences, a very large transmission cluster which included almost exclusively sequences from the CV was detected (n = 143 patients. This cluster was then validated and characterized with further maximum-likelihood phylogenetic analyses and Bayesian coalescent reconstructions. With these analyses, the CV cluster was delimited to 113 patients, predominately men who have sex with men (MSM. Although it was significantly located in the city of Valencia (n = 105, phylogenetic analyses suggested this cluster derives from a larger HIV lineage affecting other Spanish localities (n = 194. Coalescent analyses estimated its expansion in Valencia to have started between 1998 and 2004. From 2004 to 2009, members of this cluster represented only 1.46% of the HIV-1 subtype B samples studied in Valencia (n = 5/143, whereas from 2010 onwards its prevalence raised to 12.64% (n = 100/791. In conclusion, we have detected a very large transmission cluster in the CV where it has experienced a very fast growth in the recent years in the city of Valencia, thus contributing significantly to the HIV epidemic in this locality. Its transmission efficiency evidences shortcomings in HIV control measures in Spain and particularly in Valencia.

Identification of a large, fast-expanding HIV-1 subtype B transmission cluster among MSM in Valencia, Spain.

Science.gov (United States)

Patiño-Galindo, Juan Ángel; Torres-Puente, Manoli; Bracho, María Alma; Alastrué, Ignacio; Juan, Amparo; Navarro, David; Galindo, María José; Gimeno, Concepción; Ortega, Enrique; González-Candelas, Fernando

2017-01-01

We describe and characterize an exceptionally large HIV-1 subtype B transmission cluster occurring in the Comunidad Valenciana (CV, Spain). A total of 1806 HIV-1 protease-reverse transcriptase (PR/RT) sequences from different patients were obtained in the CV between 2004 and 2014. After subtyping and generating a phylogenetic tree with additional HIV-1 subtype B sequences, a very large transmission cluster which included almost exclusively sequences from the CV was detected (n = 143 patients). This cluster was then validated and characterized with further maximum-likelihood phylogenetic analyses and Bayesian coalescent reconstructions. With these analyses, the CV cluster was delimited to 113 patients, predominately men who have sex with men (MSM). Although it was significantly located in the city of Valencia (n = 105), phylogenetic analyses suggested this cluster derives from a larger HIV lineage affecting other Spanish localities (n = 194). Coalescent analyses estimated its expansion in Valencia to have started between 1998 and 2004. From 2004 to 2009, members of this cluster represented only 1.46% of the HIV-1 subtype B samples studied in Valencia (n = 5/143), whereas from 2010 onwards its prevalence raised to 12.64% (n = 100/791). In conclusion, we have detected a very large transmission cluster in the CV where it has experienced a very fast growth in the recent years in the city of Valencia, thus contributing significantly to the HIV epidemic in this locality. Its transmission efficiency evidences shortcomings in HIV control measures in Spain and particularly in Valencia.

PREFACE: Nuclear Cluster Conference; Cluster'07

Science.gov (United States)

Freer, Martin

2008-05-01

The Cluster Conference is a long-running conference series dating back to the 1960's, the first being initiated by Wildermuth in Bochum, Germany, in 1969. The most recent meeting was held in Nara, Japan, in 2003, and in 2007 the 9th Cluster Conference was held in Stratford-upon-Avon, UK. As the name suggests the town of Stratford lies upon the River Avon, and shortly before the conference, due to unprecedented rainfall in the area (approximately 10 cm within half a day), lay in the River Avon! Stratford is the birthplace of the `Bard of Avon' William Shakespeare, and this formed an intriguing conference backdrop. The meeting was attended by some 90 delegates and the programme contained 65 70 oral presentations, and was opened by a historical perspective presented by Professor Brink (Oxford) and closed by Professor Horiuchi (RCNP) with an overview of the conference and future perspectives. In between, the conference covered aspects of clustering in exotic nuclei (both neutron and proton-rich), molecular structures in which valence neutrons are exchanged between cluster cores, condensates in nuclei, neutron-clusters, superheavy nuclei, clusters in nuclear astrophysical processes and exotic cluster decays such as 2p and ternary cluster decay. The field of nuclear clustering has become strongly influenced by the physics of radioactive beam facilities (reflected in the programme), and by the excitement that clustering may have an important impact on the structure of nuclei at the neutron drip-line. It was clear that since Nara the field had progressed substantially and that new themes had emerged and others had crystallized. Two particular topics resonated strongly condensates and nuclear molecules. These topics are thus likely to be central in the next cluster conference which will be held in 2011 in the Hungarian city of Debrechen. Martin Freer Participants and Cluster'07

Social and Symbolic Capital in Firm Clusters

DEFF Research Database (Denmark)

Gretzinger, Susanne; Royer, Susanne

Based on a relational perspective this paper analyses the case of the “Mechatronics Cluster” in Southern Jutland, Denmark. We found that cluster managers are not aware of the importance of social and symbolic capital. Cluster managers could have access to both but they are not aware...... of this resource and they don´t have any knowledge how to manage social and symbolic capital. Just to integrate social-capital-supporting initiatives in the day to day business would help to develop and to foster social and symbolic capital on a low cost level. And in our example just to integrate successful sub...

Deployment Strategies and Clustering Protocols Efficiency

Directory of Open Access Journals (Sweden)

Chérif Diallo

2017-06-01

Full Text Available Wireless sensor networks face significant design challenges due to limited computing and storage capacities and, most importantly, dependence on limited battery power. Energy is a critical resource and is often an important issue to the deployment of sensor applications that claim to be omnipresent in the world of future. Thus optimizing the deployment of sensors becomes a major constraint in the design and implementation of a WSN in order to ensure better network operations. In wireless networking, clustering techniques add scalability, reduce the computation complexity of routing protocols, allow data aggregation and then enhance the network performance. The well-known MaxMin clustering algorithm was previously generalized, corrected and validated. Then, in a previous work we have improved MaxMin by proposing a Single- node Cluster Reduction (SNCR mechanism which eliminates single-node clusters and then improve energy efficiency. In this paper, we show that MaxMin, because of its original pathological case, does not support the grid deployment topology, which is frequently used in WSN architectures. The unreliability feature of the wireless links could have negative impacts on Link Quality Indicator (LQI based clustering protocols. So, in the second part of this paper we show how our distributed Link Quality based d- Clustering Protocol (LQI-DCP has good performance in both stable and high unreliable link environments. Finally, performance evaluation results also show that LQI-DCP fully supports the grid deployment topology and is more energy efficient than MaxMin.

Clustering Millions of Faces by Identity.

Science.gov (United States)

Otto, Charles; Wang, Dayong; Jain, Anil K

2018-02-01

Given a large collection of unlabeled face images, we address the problem of clustering faces into an unknown number of identities. This problem is of interest in social media, law enforcement, and other applications, where the number of faces can be of the order of hundreds of million, while the number of identities (clusters) can range from a few thousand to millions. To address the challenges of run-time complexity and cluster quality, we present an approximate Rank-Order clustering algorithm that performs better than popular clustering algorithms (k-Means and Spectral). Our experiments include clustering up to 123 million face images into over 10 million clusters. Clustering results are analyzed in terms of external (known face labels) and internal (unknown face labels) quality measures, and run-time. Our algorithm achieves an F-measure of 0.87 on the LFW benchmark (13 K faces of 5,749 individuals), which drops to 0.27 on the largest dataset considered (13 K faces in LFW + 123M distractor images). Additionally, we show that frames in the YouTube benchmark can be clustered with an F-measure of 0.71. An internal per-cluster quality measure is developed to rank individual clusters for manual exploration of high quality clusters that are compact and isolated.

Clustering and segregation of small vacancy clusters near tungsten (0 0 1) surface

Science.gov (United States)

Duan, Guohua; Li, Xiangyan; Xu, Yichun; Zhang, Yange; Jiang, Yan; Hao, Congyu; Liu, C. S.; Fang, Q. F.; Chen, Jun-Ling; Luo, G.-N.; Wang, Zhiguang

2018-01-01

Nanoporous metals have been shown to exhibit radiation-tolerance due to the trapping of the defects by the surface. However, the behavior of vacancy clusters near the surface is not clear which involves the competition between the self-trapping and segregation of small vacancy clusters (Vn) nearby the surface. In this study, we investigated the energetic and kinetic properties of small vacancy clusters near tungsten (0 0 1) surface by combining molecular statics (MS) calculations and object Kinetic Monte Carlo (OKMC) simulations. Results show that vacancies could be clustered with the reduced formation energy and migration energy of the single vacancy around a cluster as the respective energetic and kinetic driving forces. The small cluster has a migration energy barrier comparable to that for the single vacancy; the migration energy barriers for V1-5 and V7 are 1.80, 1.94, 2.17, 2.78, 3.12 and 3.11 eV, respectively. Clusters and become unstable near surface (0 0 1) and tend to dissociate into the surface. At the operation temperature of 1000 K, the single vacancy, V2, 2 V 3 V3 and V4 were observed to segregate to the surface within a time of one hour. Meanwhile, larger clusters survived near the surface, which could serve as nucleating center for voids near the surface. Our results suggest that under a low radiation dose, surface (0 0 1) could act as a sink for small vacancy clusters, alleviating defect accumulation in the material under a low radiation dose. We also obtained several empirical expressions for the vacancy cluster formation energy, binding energy, and trapping radius as a function of the number of vacancies in the cluster.

MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters

Directory of Open Access Journals (Sweden)

Louw Abraham I

2008-02-01

Full Text Available Abstract Background Microarray technology makes it possible to identify changes in gene expression of an organism, under various conditions. Data mining is thus essential for deducing significant biological information such as the identification of new biological mechanisms or putative drug targets. While many algorithms and software have been developed for analysing gene expression, the extraction of relevant information from experimental data is still a substantial challenge, requiring significant time and skill. Description MADIBA (MicroArray Data Interface for Biological Annotation facilitates the assignment of biological meaning to gene expression clusters by automating the post-processing stage. A relational database has been designed to store the data from gene to pathway for Plasmodium, rice and Arabidopsis. Tools within the web interface allow rapid analyses for the identification of the Gene Ontology terms relevant to each cluster; visualising the metabolic pathways where the genes are implicated, their genomic localisations, putative common transcriptional regulatory elements in the upstream sequences, and an analysis specific to the organism being studied. Conclusion MADIBA is an integrated, online tool that will assist researchers in interpreting their results and understand the meaning of the co-expression of a cluster of genes. Functionality of MADIBA was validated by analysing a number of gene clusters from several published experiments – expression profiling of the Plasmodium life cycle, and salt stress treatments of Arabidopsis and rice. In most of the cases, the same conclusions found by the authors were quickly and easily obtained after analysing the gene clusters with MADIBA.

NOISY WEAK-LENSING CONVERGENCE PEAK STATISTICS NEAR CLUSTERS OF GALAXIES AND BEYOND

International Nuclear Information System (INIS)

Fan Zuhui; Shan Huanyuan; Liu Jiayi

2010-01-01

Taking into account noise from intrinsic ellipticities of source galaxies, in this paper, we study the peak statistics in weak-lensing convergence maps around clusters of galaxies and beyond. We emphasize how the noise peak statistics is affected by the density distribution of nearby clusters, and also how cluster-peak signals are changed by the existence of noise. These are the important aspects to be thoroughly understood in weak-lensing analyses for individual clusters as well as in cosmological applications of weak-lensing cluster statistics. We adopt Gaussian smoothing with the smoothing scale θ G = 0.5arcmin in our analyses. It is found that the noise peak distribution near a cluster of galaxies sensitively depends on the density profile of the cluster. For a cored isothermal cluster with the core radius R c , the inner region with R ≤ R c appears noisy containing on average ∼2.4 peaks with ν ≥ 5 for R c = 1.7arcmin and the true peak height of the cluster ν = 5.6, where ν denotes the convergence signal-to-noise ratio. For a Navarro-Frenk-White (NFW) cluster of the same mass and the same central ν, the average number of peaks with ν ≥ 5 within R ≤ R c is ∼1.6. Thus a high peak corresponding to the main cluster can be identified more cleanly in the NFW case. In the outer region with R c c , the number of high noise peaks is considerably enhanced in comparison with that of the pure noise case without the nearby cluster. For ν ≥ 4, depending on the treatment of the mass-sheet degeneracy in weak-lensing analyses, the enhancement factor f is in the range of ∼5 to ∼55 for both clusters as their outer density profiles are similar. The properties of the main-cluster-peak identified in convergence maps are also significantly affected by the presence of noise. Scatters as well as a systematic shift for the peak height are present. The height distribution is peaked at ν ∼ 6.6, rather than at ν = 5.6, corresponding to a shift of Δν ∼ 1

DCE: A Distributed Energy-Efficient Clustering Protocol for Wireless Sensor Network Based on Double-Phase Cluster-Head Election.

Science.gov (United States)

Han, Ruisong; Yang, Wei; Wang, Yipeng; You, Kaiming

2017-05-01

Clustering is an effective technique used to reduce energy consumption and extend the lifetime of wireless sensor network (WSN). The characteristic of energy heterogeneity of WSNs should be considered when designing clustering protocols. We propose and evaluate a novel distributed energy-efficient clustering protocol called DCE for heterogeneous wireless sensor networks, based on a Double-phase Cluster-head Election scheme. In DCE, the procedure of cluster head election is divided into two phases. In the first phase, tentative cluster heads are elected with the probabilities which are decided by the relative levels of initial and residual energy. Then, in the second phase, the tentative cluster heads are replaced by their cluster members to form the final set of cluster heads if any member in their cluster has more residual energy. Employing two phases for cluster-head election ensures that the nodes with more energy have a higher chance to be cluster heads. Energy consumption is well-distributed in the proposed protocol, and the simulation results show that DCE achieves longer stability periods than other typical clustering protocols in heterogeneous scenarios.

From collisions to clusters

DEFF Research Database (Denmark)

Loukonen, Ville; Bork, Nicolai; Vehkamaki, Hanna

2014-01-01

-principles molecular dynamics collision simulations of (sulphuric acid)1(water)0, 1 + (dimethylamine) → (sulphuric acid)1(dimethylamine)1(water)0, 1 cluster formation processes. The simulations indicate that the sticking factor in the collisions is unity: the interaction between the molecules is strong enough...... control. As a consequence, the clusters show very dynamic ion pair structure, which differs from both the static structure optimisation calculations and the equilibrium first-principles molecular dynamics simulations. In some of the simulation runs, water mediates the proton transfer by acting as a proton...... to overcome the possible initial non-optimal collision orientations. No post-collisional cluster break up is observed. The reasons for the efficient clustering are (i) the proton transfer reaction which takes place in each of the collision simulations and (ii) the subsequent competition over the proton...

Clustering of carboxylated magnetite nanoparticles through polyethylenimine: Covalent versus electrostatic approach

Energy Technology Data Exchange (ETDEWEB)

Tóth, Ildikó Y., E-mail: Ildiko.Toth@chem.u-szeged.hu [Department of Physical Chemistry and Materials Science, University of Szeged, Aradi vt. square 1, Szeged (Hungary); Nesztor, Dániel [Department of Physical Chemistry and Materials Science, University of Szeged, Aradi vt. square 1, Szeged (Hungary); Novák, Levente [Department of Colloid and Environmental Chemistry, University of Debrecen, Egyetem square 1, Debrecen (Hungary); Illés, Erzsébet; Szekeres, Márta; Szabó, Tamás [Department of Physical Chemistry and Materials Science, University of Szeged, Aradi vt. square 1, Szeged (Hungary); Tombácz, Etelka, E-mail: tombacz@chem.u-szeged.hu [Department of Physical Chemistry and Materials Science, University of Szeged, Aradi vt. square 1, Szeged (Hungary)

2017-04-01

Carboxylated magnetite nanoparticles (MNPs) are frequently used to develop materials with enhanced properties for MRI and hyperthermia. The controlled clustering of MNPs via covalent or electrostatic approaches provides opportunity to prepare high quality materials. MNPs were prepared by co-precipitation and coated by poly(acrylic acid-co-maleic acid) (PAM@MNP). The clusters were synthesized from purified PAM@MNPs and polyethylenimine (PEI) solution via electrostatic interaction and covalent bond formation (ES-cluster and CB-cluster, respectively). The electrostatic adhesion (–NH{sub 3}{sup +} and –COO{sup –}) and the formed amide bond were confirmed by ATR-FTIR. The averaged area of CB-clusters was about twice as large as that of ES-cluster, based on TEM. The SAXS results showed that the surface of MNPs was smooth and the nanoparticles were close packed in both clusters. The pH-dependent aggregation state and zeta potential of clusters were characterized by DLS and electrophoresis measurements, the clusters were colloidally stable at pH>5. In hyperthermia experiments, the values of SAR were about two times larger for the chemically bonded cluster. The MRI studies showed exceptionally high transversion relaxivities, the r{sub 2} values are 457 mM{sup −1} s{sup −1} and 691 mM{sup −1} s{sup −1} for ES-cluster and CB-cluster, respectively. Based on these results, the chemically clustered product shows greater potential for feasible biomedical applications. - Highlights: • Chemically bonded clusters (CB-cluster) were prepared from PEI and PAM-coated MNPs. • The electrostatically clustered units (ES-cluster) are smaller and more compact. • The electrostatic adhesion and the amide bond formation were confirmed by ATR-FTIR. • CB-cluster dispersions are colloidally stable under physiological conditions. • CB-cluster shows great potential for application in MRI and hyperthermia.

Reproducibility of Cognitive Profiles in Psychosis Using Cluster Analysis.

Science.gov (United States)

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

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).

Comprehensive genomic analyses of the OM43 clade including a novel species from Red Sea indicate ecotype differentiation among marine methylotrophs

KAUST Repository

Jimenez Infante, Francy M.; Ngugi, David; Vinu, Manikandan; Alam, Intikhab; Kamau, Allan; Blom, Jochen; Bajic, Vladimir B.; Stingl, Ulrich

2015-01-01

The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs playing important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (designated here as MBRS-H7) from the ultra-oligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species, which forms a distinct cluster together with isolate KB13 from Hawaii (H-RS cluster) that is separate from that represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S–23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low chlorophyll and/or high temperature provinces for the H-RS cluster, but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of H-RS include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely the existence of the NADH:quinone oxidoreductase NUO system in the H-RS and the non-homologous NQR system in HTCC2181, which might have implications on their overall energetic yields.

Comprehensive genomic analyses of the OM43 clade including a novel species from Red Sea indicate ecotype differentiation among marine methylotrophs

KAUST Repository

Jimenez Infante, Francy M.

2015-12-11

The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs playing important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (designated here as MBRS-H7) from the ultra-oligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species, which forms a distinct cluster together with isolate KB13 from Hawaii (H-RS cluster) that is separate from that represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S–23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low chlorophyll and/or high temperature provinces for the H-RS cluster, but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of H-RS include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely the existence of the NADH:quinone oxidoreductase NUO system in the H-RS and the non-homologous NQR system in HTCC2181, which might have implications on their overall energetic yields.

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

Science.gov (United States)

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

2009-12-22

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

Methodologies for Improved Tag Cloud Generation with Clustering

DEFF Research Database (Denmark)

Leginus, Martin; Dolog, Peter; Lage, Ricardo Gomes

2012-01-01

Tag clouds are useful means for navigation in the social web systems. Usually the systems implement the tag cloud generation based on tag popularity which is not always the best method. In this paper we propose methodologies on how to combine clustering into the tag cloud generation to improve...... coverage and overlap. We study several clustering algorithms to generate tag clouds. We show that by extending cloud generation based on tag popularity with clustering we slightly improve coverage. We also show that if the cloud is generated by clustering independently of the tag popularity baseline we...

Chemisorption on size-selected metal clusters: activation barriers and chemical reactions for deuterium and aluminum cluster ions

International Nuclear Information System (INIS)

Jarrold, M.F.; Bower, J.E.

1988-01-01

The authors describe a new approach to investigating chemisorption on size-selected metal clusters. This approach involves investigating the collision-energy dependence of chemisorption using low-energy ion beam techniques. The method provides a direct measure of the activation barrier for chemisorption and in some cases an estimate of the desorption energy as well. They describe the application of this technique to chemisorption of deuterium on size-selected aluminum clusters. The activation barriers increase with cluster size (from a little over 1 eV for Al 10 + to around 2 eV for Al 27 + ) and show significant odd-even oscillations. The activation barriers for the clusters with an odd number of atoms are larger than those for the even-numbered clusters. In addition to chemisorption of deuterium onto the clusters, chemical reactions were observed, often resulting in cluster fragmentation. The main products observed were Al/sub n-1/D + , Al/sub n-2/ + , and Al + for clusters with n + and Al/sub n-1/D + for the larger clusters

Cluster Characteristics in a MIMO Indoor Propagation Environment

DEFF Research Database (Denmark)

Czink, Nicolai; Yin, Xuefeng; Ozcelik, Huseyin

2007-01-01

, strong (obstructed-)line-of-sight clusters show Rician fading, corresponding to few dominant propagation paths, whereas most clusters exhibit Rayleigh fading, corresponding to many paths with approximately equal powers and uncorrelated phases. Root-mean-square cluster azimuth spreads (CASs) were...

Star formation and substructure in galaxy clusters

International Nuclear Information System (INIS)

Cohen, Seth A.; Hickox, Ryan C.; Wegner, Gary A.; Einasto, Maret; Vennik, Jaan

2014-01-01

We investigate the relationship between star formation (SF) and substructure in a sample of 107 nearby galaxy clusters using data from the Sloan Digital Sky Survey. Several past studies of individual galaxy clusters have suggested that cluster mergers enhance cluster SF, while others find no such relationship. The SF fraction in multi-component clusters (0.228 ± 0.007) is higher than that in single-component clusters (0.175 ± 0.016) for galaxies with M r 0.1 <−20.5. In both single- and multi-component clusters, the fraction of star-forming galaxies increases with clustercentric distance and decreases with local galaxy number density, and multi-component clusters show a higher SF fraction than single-component clusters at almost all clustercentric distances and local densities. Comparing the SF fraction in individual clusters to several statistical measures of substructure, we find weak, but in most cases significant at greater than 2σ, correlations between substructure and SF fraction. These results could indicate that cluster mergers may cause weak but significant SF enhancement in clusters, or unrelaxed clusters exhibit slightly stronger SF due to their less evolved states relative to relaxed clusters.

Gravitational Waves and Intermediate-mass Black Hole Retention in Globular Clusters

Science.gov (United States)

Fragione, Giacomo; Ginsburg, Idan; Kocsis, Bence

2018-04-01

The recent discovery of gravitational waves (GWs) has opened new horizons for physics. Current and upcoming missions, such as LIGO, VIRGO, KAGRA, and LISA, promise to shed light on black holes of every size from stellar mass (SBH) sizes up to supermassive black holes. The intermediate-mass black hole (IMBH) family has not been detected beyond any reasonable doubt. Recent analyses suggest observational evidence for the presence of IMBHs in the centers of two Galactic globular clusters (GCs). In this paper, we investigate the possibility that GCs were born with a central IMBH, which undergoes repeated merger events with SBHs in the cluster core. By means of a semi-analytical method, we follow the evolution of the primordial cluster population in the galactic potential and the mergers of the binary IMBH-SBH systems. Our models predict ≈1000 IMBHs within 1 kpc from the galactic center and show that the IMBH-SBH merger rate density changes from { \\mathcal R }≈ 1000 Gpc‑3 yr‑1 beyond z ≈ 2 to { \\mathcal R }≈ 1{--}10 Gpc‑3 yr‑1 at z ≈ 0. The rates at low redshifts may be significantly higher if young massive star clusters host IMBHs. The merger rates are dominated by IMBHs with masses between 103 and 104 M ⊙. Currently, there are no LIGO/VIRGO upper limits for GW sources in this mass range, but our results show that at design sensitivity, these instruments will detect IMBH-SBH mergers in the coming years. LISA and the Einstein Telescope will be best suited to detect these events. The inspirals of IMBH-SBH systems may also generate an unresolved GW background.

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

Directory of Open Access Journals (Sweden)

Ujjwal Maulik

Full Text Available Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request.sarkar@labri.fr.

Detection of protein complex from protein-protein interaction network using Markov clustering

International Nuclear Information System (INIS)

Ochieng, P J; Kusuma, W A; Haryanto, T

2017-01-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

MANNER OF STOCKS SORTING USING CLUSTER ANALYSIS METHODS

Directory of Open Access Journals (Sweden)

Jana Halčinová

2014-06-01

Full Text Available The aim of the present article is to show the possibility of using the methods of cluster analysis in classification of stocks of finished products. Cluster analysis creates groups (clusters of finished products according to similarity in demand i.e. customer requirements for each product. Manner stocks sorting of finished products by clusters is described a practical example. The resultants clusters are incorporated into the draft layout of the distribution warehouse.

The molecular epidemiology of HIV-1 in the Comunidad Valenciana (Spain): analysis of transmission clusters.

Science.gov (United States)

Patiño-Galindo, Juan Ángel; Torres-Puente, Manoli; Bracho, María Alma; Alastrué, Ignacio; Juan, Amparo; Navarro, David; Galindo, María José; Ocete, Dolores; Ortega, Enrique; Gimeno, Concepción; Belda, Josefina; Domínguez, Victoria; Moreno, Rosario; González-Candelas, Fernando

2017-09-14

HIV infections are still a very serious concern for public heath worldwide. We have applied molecular evolution methods to study the HIV-1 epidemics in the Comunidad Valenciana (CV, Spain) from a public health surveillance perspective. For this, we analysed 1804 HIV-1 sequences comprising protease and reverse transcriptase (PR/RT) coding regions, sampled between 2004 and 2014. These sequences were subtyped and subjected to phylogenetic analyses in order to detect transmission clusters. In addition, univariate and multinomial comparisons were performed to detect epidemiological differences between HIV-1 subtypes, and risk groups. The HIV epidemic in the CV is dominated by subtype B infections among local men who have sex with men (MSM). 270 transmission clusters were identified (>57% of the dataset), 12 of which included ≥10 patients; 11 of subtype B (9 affecting MSMs) and one (n = 21) of CRF14, affecting predominately intravenous drug users (IDUs). Dated phylogenies revealed these large clusters to have originated from the mid-80s to the early 00 s. Subtype B is more likely to form transmission clusters than non-B variants and MSMs to cluster than other risk groups. Multinomial analyses revealed an association between non-B variants, which are not established in the local population yet, and different foreign groups.

Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data.

Directory of Open Access Journals (Sweden)

Manal Helal

Full Text Available BACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52% corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra

THE EVOLUTION OF DUSTY STAR FORMATION IN GALAXY CLUSTERS TO z = 1: SPITZER INFRARED OBSERVATIONS OF THE FIRST RED-SEQUENCE CLUSTER SURVEY

Energy Technology Data Exchange (ETDEWEB)

Webb, T. M. A.; O' Donnell, D.; Coppin, Kristen; Faloon, Ashley; Geach, James E.; Noble, Allison [McGill University, 3600 rue University, Montreal, QC, H3A 2T8 (Canada); Yee, H. K. C. [Department of Astronomy and Astrophysics, University of Toronto, 50 St. George St., Toronto, ON, M5S 3H4 (Canada); Gilbank, David [South African Astronomical Observatory, P.O. Box 9, Observatory, 7935 (South Africa); Ellingson, Erica [Department of Astrophysical and Planetary Sciences, University of Colorado at Boulder, Boulder, CO 80309 (United States); Gladders, Mike [Department of Astronomy and Astrophysics, University of Chicago, 5640 S. Ellis Ave., Chicago, IL 60637 (United States); Muzzin, Adam [Leiden Observatory, University of Leiden, Niels Bohrweg 2, NL-2333 CA, Leiden (Netherlands); Wilson, Gillian [Department of Physics and Astronomy, University of California at Riverside, 900 University Avenue, Riverside, CA 92521 (United States); Yan, Renbin [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States)

2013-10-01

We present the results of an infrared (IR) study of high-redshift galaxy clusters with the MIPS camera on board the Spitzer Space Telescope. We have assembled a sample of 42 clusters from the Red-Sequence Cluster Survey-1 over the redshift range 0.3 < z < 1.0 and spanning an approximate range in mass of 10{sup 14-15} M {sub ☉}. We statistically measure the number of IR-luminous galaxies in clusters above a fixed inferred IR luminosity of 2 × 10{sup 11} M {sub ☉}, assuming a star forming galaxy template, per unit cluster mass and find it increases to higher redshift. Fitting a simple power-law we measure evolution of (1 + z){sup 5.1±1.9} over the range 0.3 < z < 1.0. These results are tied to the adoption of a single star forming galaxy template; the presence of active galactic nuclei, and an evolution in their relative contribution to the mid-IR galaxy emission, will alter the overall number counts per cluster and their rate of evolution. Under the star formation assumption we infer the approximate total star formation rate per unit cluster mass (ΣSFR/M {sub cluster}). The evolution is similar, with ΣSFR/M {sub cluster} ∼ (1 + z){sup 5.4±1.9}. We show that this can be accounted for by the evolution of the IR-bright field population over the same redshift range; that is, the evolution can be attributed entirely to the change in the in-falling field galaxy population. We show that the ΣSFR/M {sub cluster} (binned over all redshift) decreases with increasing cluster mass with a slope (ΣSFR/M{sub cluster}∼M{sub cluster}{sup -1.5±0.4}) consistent with the dependence of the stellar-to-total mass per unit cluster mass seen locally. The inferred star formation seen here could produce ∼5%-10% of the total stellar mass in massive clusters at z = 0, but we cannot constrain the descendant population, nor how rapidly the star-formation must shut-down once the galaxies have entered the cluster environment. Finally, we show a clear decrease in the number of IR

Horizontal transfer of a nitrate assimilation gene cluster and ecological transitions in fungi: a phylogenetic study.

Directory of Open Access Journals (Sweden)

Jason C Slot

Full Text Available High affinity nitrate assimilation genes in fungi occur in a cluster (fHANT-AC that can be coordinately regulated. The clustered genes include nrt2, which codes for a high affinity nitrate transporter; euknr, which codes for nitrate reductase; and NAD(PH-nir, which codes for nitrite reductase. Homologs of genes in the fHANT-AC occur in other eukaryotes and prokaryotes, but they have only been found clustered in the oomycete Phytophthora (heterokonts. We performed independent and concatenated phylogenetic analyses of homologs of all three genes in the fHANT-AC. Phylogenetic analyses limited to fungal sequences suggest that the fHANT-AC has been transferred horizontally from a basidiomycete (mushrooms and smuts to an ancestor of the ascomycetous mold Trichoderma reesei. Phylogenetic analyses of sequences from diverse eukaryotes and eubacteria, and cluster structure, are consistent with a hypothesis that the fHANT-AC was assembled in a lineage leading to the oomycetes and was subsequently transferred to the Dikarya (Ascomycota+Basidiomycota, which is a derived fungal clade that includes the vast majority of terrestrial fungi. We propose that the acquisition of high affinity nitrate assimilation contributed to the success of Dikarya on land by allowing exploitation of nitrate in aerobic soils, and the subsequent transfer of a complete assimilation cluster improved the fitness of T. reesei in a new niche. Horizontal transmission of this cluster of functionally integrated genes supports the "selfish operon" hypothesis for maintenance of gene clusters.

Nonthermal emission from clusters of galaxies

International Nuclear Information System (INIS)

Kushnir, Doron; Waxman, Eli

2009-01-01

We show that the spectral and radial distribution of the nonthermal emission of massive, M ∼> 10 14.5 M ☉ , galaxy clusters may be approximately described by simple analytic expressions, which depend on the cluster thermal X-ray properties and on two model parameter, β core and η e . β core is the ratio of the cosmic-ray (CR) energy density (within a logarithmic CR energy interval) and the thermal energy density at the cluster core, and η e(p) is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of intra-cluster medium CRs, which are produced by accretion shocks, we find that β core ≅ η p /200, nearly independent of cluster mass and with a scatter Δln β core ≅ 1 between clusters of given mass. We show that the hard X-ray (HXR) and γ-ray luminosities produced by inverse Compton scattering of CMB photons by electrons accelerated in accretion shocks (primary electrons) exceed the luminosities produced by secondary particles (generated in hadronic interactions within the cluster) by factors ≅ 500(η e /η p )(T/10 keV) −1/2 and ≅ 150(η e /η p )(T/10 keV) −1/2 respectively, where T is the cluster temperature. Secondary particle emission may dominate at the radio and very high energy (∼> 1 TeV) γ-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and γ-ray emission from clusters of galaxies are extended, since the emission is dominated at these energies by primary (rather than by secondary) electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for η p ∼ η e ∼ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. In particular, we identify the clusters which are the best candidates for detection in �

Nonthermal emission from clusters of galaxies

Science.gov (United States)

Kushnir, Doron; Waxman, Eli

2009-08-01

We show that the spectral and radial distribution of the nonthermal emission of massive, M gtrsim 1014.5Msun, galaxy clusters may be approximately described by simple analytic expressions, which depend on the cluster thermal X-ray properties and on two model parameter, βcore and ηe. βcore is the ratio of the cosmic-ray (CR) energy density (within a logarithmic CR energy interval) and the thermal energy density at the cluster core, and ηe(p) is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of intra-cluster medium CRs, which are produced by accretion shocks, we find that βcore simeq ηp/200, nearly independent of cluster mass and with a scatter Δln βcore simeq 1 between clusters of given mass. We show that the hard X-ray (HXR) and γ-ray luminosities produced by inverse Compton scattering of CMB photons by electrons accelerated in accretion shocks (primary electrons) exceed the luminosities produced by secondary particles (generated in hadronic interactions within the cluster) by factors simeq 500(ηe/ηp)(T/10 keV)-1/2 and simeq 150(ηe/ηp)(T/10 keV)-1/2 respectively, where T is the cluster temperature. Secondary particle emission may dominate at the radio and very high energy (gtrsim 1 TeV) γ-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and γ-ray emission from clusters of galaxies are extended, since the emission is dominated at these energies by primary (rather than by secondary) electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for ηp ~ ηe ~ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. In particular, we identify the clusters which are the best candidates for detection in γ-rays. Finally, we show

Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

Science.gov (United States)

Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

2017-09-01

Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

Gaussian mixture clustering and imputation of microarray data.

Science.gov (United States)

Ouyang, Ming; Welsh, William J; Georgopoulos, Panos

2004-04-12

In microarray experiments, missing entries arise from blemishes on the chips. In large-scale studies, virtually every chip contains some missing entries and more than 90% of the genes are affected. Many analysis methods require a full set of data. Either those genes with missing entries are excluded, or the missing entries are filled with estimates prior to the analyses. This study compares methods of missing value estimation. Two evaluation metrics of imputation accuracy are employed. First, the root mean squared error measures the difference between the true values and the imputed values. Second, the number of mis-clustered genes measures the difference between clustering with true values and that with imputed values; it examines the bias introduced by imputation to clustering. The Gaussian mixture clustering with model averaging imputation is superior to all other imputation methods, according to both evaluation metrics, on both time-series (correlated) and non-time series (uncorrelated) data sets.

Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling

Energy Technology Data Exchange (ETDEWEB)

Peterson, John R.; Marshall, P.J.; /KIPAC, Menlo Park; Andersson, K.; /Stockholm U. /SLAC

2005-08-05

We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.

Nuclear clustering - a cluster core model study

International Nuclear Information System (INIS)

Paul Selvi, G.; Nandhini, N.; Balasubramaniam, M.

2015-01-01

Nuclear clustering, similar to other clustering phenomenon in nature is a much warranted study, since it would help us in understanding the nature of binding of the nucleons inside the nucleus, closed shell behaviour when the system is highly deformed, dynamics and structure at extremes. Several models account for the clustering phenomenon of nuclei. We present in this work, a cluster core model study of nuclear clustering in light mass nuclei

Defective functional connectivity between posterior hypothalamus and regions of the diencephalic-mesencephalic junction in chronic cluster headache.

Science.gov (United States)

Ferraro, Stefania; Nigri, Anna; Bruzzone, Maria Grazia; Brivio, Luca; Proietti Cecchini, Alberto; Verri, Mattia; Chiapparini, Luisa; Leone, Massimo

2018-01-01

Objective We tested the hypothesis of a defective functional connectivity between the posterior hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache based on: a) clinical and neuro-endocrinological findings in cluster headache patients; b) neuroimaging findings during cluster headache attacks; c) neuroimaging findings in drug-refractory chronic cluster headache patients improved after successful deep brain stimulation. Methods Resting state functional magnetic resonance imaging, associated with a seed-based approach, was employed to investigate the functional connectivity of the posterior hypothalamus in chronic cluster headache patients (n = 17) compared to age and sex-matched healthy subjects (n = 16). Random-effect analyses were performed to study differences between patients and controls in ipsilateral and contralateral-to-the-pain posterior hypothalamus functional connectivity. Results Cluster headache patients showed an increased functional connectivity between the ipsilateral posterior hypothalamus and a number of diencephalic-mesencephalic structures, comprising ventral tegmental area, dorsal nuclei of raphe, and bilateral substantia nigra, sub-thalamic nucleus, and red nucleus ( p cluster headache patients mainly involves structures that are part of (i.e. ventral tegmental area, substantia nigra) or modulate (dorsal nuclei of raphe, sub-thalamic nucleus) the midbrain dopaminergic systems. The midbrain dopaminergic systems could play a role in cluster headache pathophysiology and in particular in the chronicization process. Future studies are needed to better clarify if this finding is specific to cluster headache or if it represents an unspecific response to chronic pain.

Global survey of star clusters in the Milky Way. VI. Age distribution and cluster formation history

Science.gov (United States)

Piskunov, A. E.; Just, A.; Kharchenko, N. V.; Berczik, P.; Scholz, R.-D.; Reffert, S.; Yen, S. X.

2018-06-01

Context. The all-sky Milky Way Star Clusters (MWSC) survey provides uniform and precise ages, along with other relevant parameters, for a wide variety of clusters in the extended solar neighbourhood. Aims: In this study we aim to construct the cluster age distribution, investigate its spatial variations, and discuss constraints on cluster formation scenarios of the Galactic disk during the last 5 Gyrs. Methods: Due to the spatial extent of the MWSC, we have considered spatial variations of the age distribution along galactocentric radius RG, and along Z-axis. For the analysis of the age distribution we used 2242 clusters, which all lie within roughly 2.5 kpc of the Sun. To connect the observed age distribution to the cluster formation history we built an analytical model based on simple assumptions on the cluster initial mass function and on the cluster mass-lifetime relation, fit it to the observations, and determined the parameters of the cluster formation law. Results: Comparison with the literature shows that earlier results strongly underestimated the number of evolved clusters with ages t ≳ 100 Myr. Recent studies based on all-sky catalogues agree better with our data, but still lack the oldest clusters with ages t ≳ 1 Gyr. We do not observe a strong variation in the age distribution along RG, though we find an enhanced fraction of older clusters (t > 1 Gyr) in the inner disk. In contrast, the distribution strongly varies along Z. The high altitude distribution practically does not contain clusters with t < 1 Gyr. With simple assumptions on the cluster formation history, the cluster initial mass function and the cluster lifetime we can reproduce the observations. The cluster formation rate and the cluster lifetime are strongly degenerate, which does not allow us to disentangle different formation scenarios. In all cases the cluster formation rate is strongly declining with time, and the cluster initial mass function is very shallow at the high mass end.

Nuclear thermal rocket clustering: 1, A summary of previous work and relevant issues

International Nuclear Information System (INIS)

Buksa, J.J.; Houts, M.G.

1991-01-01

A general review of the technical merits of nuclear thermal rocket clustering is presented. A summary of previous analyses performed during the Rover program is presented and used to assess clustering in the context of projected Space Exploration Initiative missions. A number of technical issues are discussed including cluster reliability, engine-out operation, neutronic coupling, shutdown core power generation, shutdown reactivity requirements, reactor kinetics, and radiation shielding. 7 refs., 3 figs., 2 tabs

A Model-Based Cluster Analysis of Maternal Emotion Regulation and Relations to Parenting Behavior.

Science.gov (United States)

Shaffer, Anne; Whitehead, Monica; Davis, Molly; Morelen, Diana; Suveg, Cynthia

2017-10-15

In a diverse community sample of mothers (N = 108) and their preschool-aged children (M age  = 3.50 years), this study conducted person-oriented analyses of maternal emotion regulation (ER) based on a multimethod assessment incorporating physiological, observational, and self-report indicators. A model-based cluster analysis was applied to five indicators of maternal ER: maternal self-report, observed negative affect in a parent-child interaction, baseline respiratory sinus arrhythmia (RSA), and RSA suppression across two laboratory tasks. Model-based cluster analyses revealed four maternal ER profiles, including a group of mothers with average ER functioning, characterized by socioeconomic advantage and more positive parenting behavior. A dysregulated cluster demonstrated the greatest challenges with parenting and dyadic interactions. Two clusters of intermediate dysregulation were also identified. Implications for assessment and applications to parenting interventions are discussed. © 2017 Family Process Institute.

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

Science.gov (United States)

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.

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

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

2006-01-01

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

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

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

2008-01-01

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

Fission of Polyanionic Metal Clusters

Science.gov (United States)

König, S.; Jankowski, A.; Marx, G.; Schweikhard, L.; Wolfram, M.

2018-04-01

Size-selected dianionic lead clusters Pbn2 -, n =34 - 56 , are stored in a Penning trap and studied with respect to their decay products upon photoexcitation. Contrary to the decay of other dianionic metal clusters, these lead clusters show a variety of decay channels. The mass spectra of the fragments are compared to the corresponding spectra of the monoanionic precursors. This comparison leads to the conclusion that, in the cluster size region below about n =48 , the fission reaction Pbn2 -→Pbn-10 -+Pb10- is the major decay process. Its disappearance at larger cluster sizes may be an indication of a nonmetal to metal transition. Recently, the pair of Pb10- and Pbn-10 - were observed as pronounced fragments in electron-attachment studies [S. König et al., Int. J. Mass Spectrom. 421, 129 (2017), 10.1016/j.ijms.2017.06.009]. The present findings suggest that this combination is the fingerprint of the decay of doubly charged lead clusters. With this assumption, the dianion clusters have been traced down to Pb212 -, whereas the smallest size for the direct observation was as high as n =28 .

Efficient clustering aggregation based on data fragments.

Science.gov (United States)

Wu, Ou; Hu, Weiming; Maybank, Stephen J; Zhu, Mingliang; Li, Bing

2012-06-01

Clustering aggregation, known as clustering ensembles, has emerged as a powerful technique for combining different clustering results to obtain a single better clustering. Existing clustering aggregation algorithms are applied directly to data points, in what is referred to as the point-based approach. The algorithms are inefficient if the number of data points is large. We define an efficient approach for clustering aggregation based on data fragments. In this fragment-based approach, a data fragment is any subset of the data that is not split by any of the clustering results. To establish the theoretical bases of the proposed approach, we prove that clustering aggregation can be performed directly on data fragments under two widely used goodness measures for clustering aggregation taken from the literature. Three new clustering aggregation algorithms are described. The experimental results obtained using several public data sets show that the new algorithms have lower computational complexity than three well-known existing point-based clustering aggregation algorithms (Agglomerative, Furthest, and LocalSearch); nevertheless, the new algorithms do not sacrifice the accuracy.

Study of Cluster-size Effect on Damage Formation

International Nuclear Information System (INIS)

Aoki, Takaaki; Seki, Toshio; Nakai, Atsuko; Matsuo, Jiro; Takaoka, Gikan

2003-01-01

Computer simulation and experiments were performed in order to understand the effect of cluster size on damage formation. Results of molecular dynamics simulations of cluster impact on solid targets derived the model function, which explains the relationship among cluster size, incident energy and number of displacements. On the other hand, time of flight mass measurement system was installed a cluster irradiation system, so that cluster ion beam which cluster size distribution is well known can be irradiated on the target. The damage properties under various cluster irradiation conditions were examined using RBS. The results from computer simulations and experiments showed good agreements with each other, which suggests that irradiation damage by cluster ion beam can be controlled by selecting cluster size distribution and incident energy

Investigation of Carbon Monoxide Adsorption on Cationic Gold- Palladium Clusters

Science.gov (United States)

Chen, Yang-Mei; Kuang, Xiao-Yu; Sheng, Xiao-Wei; Wang, Huai-Qian; Shao, Peng; Zhong, Min-Ming

2013-11-01

Density functional calculations have been performed for the carbon monoxide molecule adsorption on AunPd+m(n+m ≤ 6) clusters. In the process of CO adsorption, small Au clusters and Pd clusters tend to be an Au atom and three Pd atoms adsorption, respectively. For the mixed Au-Pd clusters, an Au atom, a Pd atom, two atoms consisted of an Au atom and a Pd atom, two Pd atoms, and three Pd atoms adsorption structures are displayed. The highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gaps and natural bond orbital charge population are calculated. Moreover, CO adsorption energy, CO stretching frequency, and CO bond length (upon adsorption) are also analysed in detail. The results predict that the adsorption strength of Au clusters with CO and the C-O vibration strength is enhanced and reduced after doping of Pd in the AunPdmCO+ complexes, respectively

DMINDA: an integrated web server for DNA motif identification and analyses.

Science.gov (United States)

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-07-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

Science.gov (United States)

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal

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

Science.gov (United States)

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.

Lithium formate ion clusters formation during electrospray ionization: Evidence of magic number clusters by mass spectrometry and ab initio calculations

International Nuclear Information System (INIS)

Shukla, Anil; Bogdanov, Bogdan

2015-01-01

Small cationic and anionic clusters of lithium formate were generated by electrospray ionization and their fragmentations were studied by tandem mass spectrometry (collision-induced dissociation with N 2 ). Singly as well as multiply charged clusters were formed in both positive and negative ion modes with the general formulae, (HCOOLi) n Li + , (HCOOLi) n Li m m+ , (HCOOLi) n HCOO − , and (HCOOLi) n (HCOO) m m− . Several magic number cluster (MNC) ions were observed in both the positive and negative ion modes although more predominant in the positive ion mode with (HCOOLi) 3 Li + being the most abundant and stable cluster ion. Fragmentations of singly charged positive clusters proceed first by the loss of a dimer unit ((HCOOLi) 2 ) followed by the loss of monomer units (HCOOLi) although the former remains the dominant dissociation process. In the case of positive cluster ions, all fragmentations lead to the magic cluster (HCOOLi) 3 Li + as the most abundant fragment ion at higher collision energies which then fragments further to dimer and monomer ions at lower abundances. In the negative ion mode, however, singly charged clusters dissociated via sequential loss of monomer units. Multiply charged clusters in both positive and negative ion modes dissociated mainly via Coulomb repulsion. Quantum chemical calculations performed for smaller cluster ions showed that the trimer ion has a closed ring structure similar to the phenalenylium structure with three closed rings connected to the central lithium ion. Further additions of monomer units result in similar symmetric structures for hexamer and nonamer cluster ions. Thermochemical calculations show that trimer cluster ion is relatively more stable than neighboring cluster ions, supporting the experimental observation of a magic number cluster with enhanced stability

Altered spinal microRNA-146a and the microRNA-183 cluster contribute to osteoarthritic pain in knee joints.

Science.gov (United States)

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 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

Mass functions for eight galactic clusters in the solar neighborhood

International Nuclear Information System (INIS)

Francic, S.P.

1989-01-01

Mass functions for eight galactic clusters in the solar neighborhood have been obtained. The mass functions have been determined from proper motion membership probabilities and unlike similar investigations, corrected for outlying cluster stars. The membership probabilities have been determined from the joint proper motion and surface density distributions for the field and clusters stars. They have also been corrected for any magnitude dependences. Comparison of the mass functions with the Salpeter IMF shows that the older clusters tend to be deficient in the number of low mass stars, while the younger clusters tend to have more. Analysis of the relaxation times shows that the deficiency of faint stars in the older clusters is likely due to their evaporation from the cluster. The combined mass function for six of the cluster results in a power law with a power law index of -1.97 ± 0.17 for 1.1 < M/Mass of sun < 2.5. This agrees with a recent determination of the field star IMF where the power law index is -2.00 ± 0.18 for 0.8 < M/Mass of sun < 18. If the older clusters are not considered, then comparison of the combined mass function with the individual cluster mass functions shows that the universality hypothesis cannot be denied

Analysis of genetic diversity of Sclerotinia sclerotiorum from eggplant by mycelial compatibility, random amplification of polymorphic DNA (RAPD and simple sequence repeat (SSR analyses

Directory of Open Access Journals (Sweden)

Fatih Mehmet Tok

2016-09-01

Full Text Available The genetic diversity and pathogenicity/virulence among 60 eggplant Sclerotinia sclerotiorum isolates collected from six different geographic regions of Turkey were analysed using mycelial compatibility groupings (MCGs, random amplified polymorphic DNA (RAPD and simple sequence repeat (SSR polymorphism. By MCG tests, the isolates were classified into 22 groups. Out of 22 MCGs, 36% were represented each by a single isolate. The isolates showed great variability for virulence regardless of MCG and geographic origin. Based on the results of RAPD and SSR analyses, 60 S. sclerotiorum isolates representing 22 MCGs were grouped in 2 and 3 distinct clusters, respectively. Analyses using RAPD and SSR markers illustrated that cluster groupings or genetic distance of S. sclerotiorum populations from eggplant were not distinctly relative to the MCG, geographical origin and virulence diversity. The patterns obtained revealed a high heterogeneity of genetic composition and suggested the occurrence of clonal and sexual reproduction of S. sclerotiorum on eggplant in the areas surveyed.

Properties of liquid clusters in large-scale molecular dynamics nucleation simulations

International Nuclear Information System (INIS)

Angélil, Raymond; Diemand, Jürg; Tanaka, Kyoko K.; Tanaka, Hidekazu

2014-01-01

We have performed large-scale Lennard-Jones molecular dynamics simulations of homogeneous vapor-to-liquid nucleation, with 10 9 atoms. This large number allows us to resolve extremely low nucleation rates, and also provides excellent statistics for cluster properties over a wide range of cluster sizes. The nucleation rates, cluster growth rates, and size distributions are presented in Diemand et al. [J. Chem. Phys. 139, 74309 (2013)], while this paper analyses the properties of the clusters. We explore the cluster temperatures, density profiles, potential energies, and shapes. A thorough understanding of the properties of the clusters is crucial to the formulation of nucleation models. Significant latent heat is retained by stable clusters, by as much as ΔkT = 0.1ε for clusters with size i = 100. We find that the clusters deviate remarkably from spherical—with ellipsoidal axis ratios for critical cluster sizes typically within b/c = 0.7 ± 0.05 and a/c = 0.5 ± 0.05. We examine cluster spin angular momentum, and find that it plays a negligible role in the cluster dynamics. The interfaces of large, stable clusters are thinner than planar equilibrium interfaces by 10%−30%. At the critical cluster size, the cluster central densities are between 5% and 30% lower than the bulk liquid expectations. These lower densities imply larger-than-expected surface areas, which increase the energy cost to form a surface, which lowers nucleation rates

Stabilities of protonated water-ammonia clusters

Science.gov (United States)

Sundén, A. E. K.; Støchkel, K.; Hvelplund, P.; Brøndsted Nielsen, S.; Dynefors, B.; Hansen, K.

2018-05-01

Branching ratios of water and ammonia evaporation have been measured for spontaneous evaporation from protonated mixed clusters H+(H2O)n(NH3)m in the size range 0 ≤ n ≤ 11 and 0 ≤ m ≤ 7. Mixed clusters evaporate water except for clusters containing six or more ammonia molecules, indicating the formation of a stable core of one ammonium ion surrounded by four ammonia molecules and a second shell consisting predominantly of water. We relate evaporative branching ratios to free energy differences between the products of competing channels and determine the free energy differences for clusters with up to seven ammonia molecules. Clusters containing up to five ammonia molecules show a very strong scaling of these free energy differences.

Multi-wavelength study of young and massive galaxy clusters

International Nuclear Information System (INIS)

Lemonon, Ludovic

1999-01-01

Clusters of galaxies are the most massive objects gravitationally bound observed. They are the consequence of the evolution of most important perturbations in the cosmological microwave background. Their formation depends strongly of the cosmology, so they represent key objects to understand the Universe. The aim of this thesis is to study the processes of formation in clusters of galaxies well far away than previous studies clone, by high-resolution observations obtained by using most powerful telescope in each studied wavelength: X-ray, visible, infrared and radio. After data reductions of 12 clusters located at 0.1; z; 0.3, I was able to classified them in three categories: dynamically perturbed clusters, with substructures in their X-ray/optical image or velocity distribution of galaxies; cooling flows clusters, more relaxed than previous, with huge amount of gas cooling in their center; AGN contaminated, where the central dominant galaxy is an AGN which contaminate considerably the X-ray emission. I have obtained a measurement of the baryonic fraction of the Universe mass, and an estimation of the Universe matter density parameter at the mega-parsec scale, claiming for a low density universe. The ISOCAM data showed the effect of the ICM interactions on the star formation in cluster galaxies, and demonstrated that optical and mid-IR deduced star-formation are not basically compatible. They also showed how IR-emitting galaxies distribute in clusters, most noticeably how 15 um galaxies are located preferably on the edge of clusters. X-ray and radio data showed that clusters at z 0.25 could be find in several dynamical state, similarly with nearby ones, from relaxed to severely perturbed. All clusters present signs of past or present merging, in agreement with hierarchical structure formation scenario. This clusters database is an excellent starting point to study process of merging in clusters since they showed different aspect of this evolution. (author) [fr

The SUMO project I. A survey of multiple populations in globular clusters

Science.gov (United States)

Monelli, M.; Milone, A. P.; Stetson, P. B.; Marino, A. F.; Cassisi, S.; del Pino Molina, A.; Salaris, M.; Aparicio, A.; Asplund, M.; Grundahl, F.; Piotto, G.; Weiss, A.; Carrera, R.; Cebrián, M.; Murabito, S.; Pietrinferni, A.; Sbordone, L.

2013-05-01

We present a general overview and the first results of the SUMO project (a SUrvey of Multiple pOpulations in Globular Clusters). The objective of this survey is the study of multiple stellar populations in the largest sample of globular clusters homogeneously analysed to date. To this aim we obtained high signal-to-noise (S/N > 50) photometry for main sequence stars with mass down to ˜0.5 M⊙ in a large sample of clusters using both archival and proprietary U, B, V and I data from ground-based telescopes. In this paper, we focus on the occurrence of multiple stellar populations in 23 clusters. We define a new photometric index, cU, B, I = (U - B) - (B - I), which turns out to be very effective for identifying multiple sequences along the red giant branch (RGB). We found that in the V-cU, B, I diagram all clusters presented in this paper show broadened or multimodal RGBs, with the presence of two or more components. We found a direct connection with the chemical properties of different sequences, which display different abundances of light elements (O, Na, C, N and Al). The cU, B, I index is also a powerful tool for identifying distinct sequences of stars along the horizontal branch and, for the first time in the case of NGC 104 (47 Tuc), along the asymptotic giant branch. Our results demonstrate that (i) the presence of more than two stellar populations is a common feature amongst globular clusters, as already highlighted in previous work; (ii) multiple sequences with different chemical contents can be easily identified by using standard Johnson photometry obtained with ground-based facilities; (iii) in the study of globular cluster multiple stellar populations the cU, B, I index is an alternative to spectroscopy, and has the advantage of larger statistics.

Whisper, a resonance sounder and wave analyser: Performances and perspectives for the Cluster mission

DEFF Research Database (Denmark)

Decreau, P.M.E.; Fergeau, P.; KrannoselsKikh, V.

1997-01-01

The WHISPER sounder on the Cluster spacecraft is primarily designed to provide an absolute measurement of the total plasma density within the range 0.2-80 cm(-3). This is achieved by means of a resonance sounding technique which has already proved successful in the regions to be explored. The wav...... in the electron foreshock and solar wind, to investigations about small-scale structures via density and high-frequency emission signatures, and to the analysis of the non-thermal continuum in the magnetosphere....

Atomically precise arrays of fluorescent silver clusters: a modular approach for metal cluster photonics on DNA nanostructures.

Science.gov (United States)

Copp, Stacy M; Schultz, Danielle E; Swasey, Steven; Gwinn, Elisabeth G

2015-03-24

The remarkable precision that DNA scaffolds provide for arraying nanoscale optical elements enables optical phenomena that arise from interactions of metal nanoparticles, dye molecules, and quantum dots placed at nanoscale separations. However, control of ensemble optical properties has been limited by the difficulty of achieving uniform particle sizes and shapes. Ligand-stabilized metal clusters offer a route to atomically precise arrays that combine desirable attributes of both metals and molecules. Exploiting the unique advantages of the cluster regime requires techniques to realize controlled nanoscale placement of select cluster structures. Here we show that atomically monodisperse arrays of fluorescent, DNA-stabilized silver clusters can be realized on a prototypical scaffold, a DNA nanotube, with attachment sites separated by <10 nm. Cluster attachment is mediated by designed DNA linkers that enable isolation of specific clusters prior to assembly on nanotubes and preserve cluster structure and spectral purity after assembly. The modularity of this approach generalizes to silver clusters of diverse sizes and DNA scaffolds of many types. Thus, these silver cluster nano-optical elements, which themselves have colors selected by their particular DNA templating oligomer, bring unique dimensions of control and flexibility to the rapidly expanding field of nano-optics.

The Genome of Tolypocladium inflatum: Evolution, Organization, and Expression of the Cyclosporin Biosynthetic Gene Cluster

Science.gov (United States)

Bushley, Kathryn E.; Raja, Rajani; Jaiswal, Pankaj; Cumbie, Jason S.; Nonogaki, Mariko; Boyd, Alexander E.; Owensby, C. Alisha; Knaus, Brian J.; Elser, Justin; Miller, Daniel; Di, Yanming; McPhail, Kerry L.; Spatafora, Joseph W.

2013-01-01

The ascomycete fungus Tolypocladium inflatum, a pathogen of beetle larvae, is best known as the producer of the immunosuppressant drug cyclosporin. The draft genome of T. inflatum strain NRRL 8044 (ATCC 34921), the isolate from which cyclosporin was first isolated, is presented along with comparative analyses of the biosynthesis of cyclosporin and other secondary metabolites in T. inflatum and related taxa. Phylogenomic analyses reveal previously undetected and complex patterns of homology between the nonribosomal peptide synthetase (NRPS) that encodes for cyclosporin synthetase (simA) and those of other secondary metabolites with activities against insects (e.g., beauvericin, destruxins, etc.), and demonstrate the roles of module duplication and gene fusion in diversification of NRPSs. The secondary metabolite gene cluster responsible for cyclosporin biosynthesis is described. In addition to genes necessary for cyclosporin biosynthesis, it harbors a gene for a cyclophilin, which is a member of a family of immunophilins known to bind cyclosporin. Comparative analyses support a lineage specific origin of the cyclosporin gene cluster rather than horizontal gene transfer from bacteria or other fungi. RNA-Seq transcriptome analyses in a cyclosporin-inducing medium delineate the boundaries of the cyclosporin cluster and reveal high levels of expression of the gene cluster cyclophilin. In medium containing insect hemolymph, weaker but significant upregulation of several genes within the cyclosporin cluster, including the highly expressed cyclophilin gene, was observed. T. inflatum also represents the first reference draft genome of Ophiocordycipitaceae, a third family of insect pathogenic fungi within the fungal order Hypocreales, and supports parallel and qualitatively distinct radiations of insect pathogens. The T. inflatum genome provides additional insight into the evolution and biosynthesis of cyclosporin and lays a foundation for further investigations of the role

The Problem of Hipparcos Distances to Open Clusters. II. Constraints from Nearby Field Theory. Report 2; ClustersConstraints from nearly Field Stars

Science.gov (United States)

Soderblom, David R.; King, Jeremy R.; Hanson, Robert B.; Jones, Burton F.; Fischer, Debra; Stauffer, John R.; Pinsonneault, Marc H.

1998-01-01

This paper examines the discrepancy between distances to nearby open clusters as determined by parallaxes from Hipparcos compared to traditional main-sequence fitting. The biggest difference is seen for the Pleiades, and our hypothesis is that if the Hipparcos distance to the Pleiades is correct, then similar subluminous zero-age main-sequence (ZAMS) stars should exist elsewhere, including in the immediate solar neighborhood. We examine a color-magnitude diagram of very young and nearby solar-type stars and show that none of them lie below the traditional ZAMS, despite the fact that the Hipparcos Pleiades parallax would place its members 0.3 mag below that ZAMS. We also present analyses and observations of solar-type stars that do lie below the ZAMS, and we show that they are subluminous because of low metallicity and that they have the kinematics of old stars.

Comprehensive cluster analysis with Transitivity Clustering.

Science.gov (United States)

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

2011-03-01

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

Structure of small rare earth clusters

International Nuclear Information System (INIS)

Rayane, D.; Benamar, A.; Tribollet, B.; Broyer, M.; Melinon, P.

1991-01-01

Rare earth clusters are produced by the inert gas condensation technique. The observed size distribution shows large peaks at n=13, 19, 23, 26, 29, 32, 34, 37, 39, 45, .... The beginning of this sequence (up to 34) has been already observed in argon clusters and recently by our group in barium clusters; this sequence may be interpreted in terms of icosahedral structures corresponding to the addition of caps on a core icosahedron of 13 atoms. (orig.)

Giant light enhancement in atomic clusters

International Nuclear Information System (INIS)

Gadomsky, O. N.; Gadomskaya, I. V.; Altunin, K. K.

2009-01-01

We show that the polarizing effect of the atoms in an atomic cluster can lead to full compensation of the radiative damping of excited atomic states, a change in the sign of the dispersion of the atomic polarizability, and giant light enhancement by the atomic cluster.

Molecular dynamics simulation of nanoscale surface diffusion of heterogeneous adatoms clusters

International Nuclear Information System (INIS)

Imran, Muhammad; Hussain, Fayyaz; Ullah, Hafeez; Ahmad, Ejaz; Rashid, Muhammad; Ismail, Muhammad; Cai, Yongqing; Javid, M Arshad; Ahmad, S A

2016-01-01

Molecular dynamics simulation employing the embedded atom method potential is utilized to investigate nanoscale surface diffusion mechanisms of binary heterogeneous adatoms clusters at 300 K, 500 K, and 700 K. Surface diffusion of heterogeneous adatoms clusters can be vital for the binary island growth on the surface and can be useful for the formation of alloy-based thin film surface through atomic exchange process. The results of the diffusion process show that at 300 K, the diffusion of small adatoms clusters shows hopping, sliding, and shear motion; whereas for large adatoms clusters (hexamer and above), the diffusion is negligible. At 500 K, small adatoms clusters, i.e., dimer, show almost all possible diffusion mechanisms including the atomic exchange process; however no such exchange is observed for adatoms clusters greater than dimer. At 700 K, the exchange mechanism dominates for all types of clusters, where Zr adatoms show maximum tendency and Ag adatoms show minimum or no tendency toward the exchange process. Separation and recombination of one or more adatoms are also observed at 500 K and 700 K. The Ag adatoms also occupy pop-up positions over the adatoms clusters for short intervals. At 700 K, the vacancies are also generated in the vicinity of the adatoms cluster, vacancy formation, filling, and shifting can be observed from the results. (paper)

Factors influencing the quality of life of haemodialysis patients according to symptom cluster.

Science.gov (United States)

Shim, Hye Yeung; Cho, Mi-Kyoung

2018-05-01

To identify the characteristics in each symptom cluster and factors influencing the quality of life of haemodialysis patients in Korea according to cluster. Despite developments in renal replacement therapy, haemodialysis still restricts the activities of daily living due to pain and impairs physical functioning induced by the disease and its complications. Descriptive survey. Two hundred and thirty dialysis patients aged >18 years. They completed self-administered questionnaires of Dialysis Symptom Index and Kidney Disease Quality of Life instrument-Short Form 1.3. To determine the optimal number of clusters, the collected data were analysed using polytomous variable latent class analysis in R software (poLCA) to estimate the latent class models and the latent class regression models for polytomous outcome variables. Differences in characteristics, symptoms and QOL according to the symptom cluster of haemodialysis patients were analysed using the independent t test and chi-square test. The factors influencing the QOL according to symptom cluster were identified using hierarchical multiple regression analysis. Physical and emotional symptoms were significantly more severe, and the QOL was significantly worse in Cluster 1 than in Cluster 2. The factors influencing the QOL were spouse, job, insurance type and physical and emotional symptoms in Cluster 1, with these variables having an explanatory power of 60.9%. Physical and emotional symptoms were the only influencing factors in Cluster 2, and they had an explanatory power of 37.4%. Mitigating the symptoms experienced by haemodialysis patients and improving their QOL require educational and therapeutic symptom management interventions that are tailored according to the characteristics and symptoms in each cluster. The findings of this study are expected to lead to practical guidelines for addressing the symptoms experienced by haemodialysis patients, and they provide basic information for developing nursing

Cluster-cluster correlations and constraints on the correlation hierarchy

Science.gov (United States)

Hamilton, A. J. S.; Gott, J. R., III

1988-01-01

The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.

The affective discourse dynamics of metaphor clustering The affective discourse dynamics of metaphor clustering

Directory of Open Access Journals (Sweden)

Lynne Cameron

2010-05-01

Full Text Available

Metaphor is examined in the very different iscourse contexts of the classroom and of reconciliation talk to highlight the neglected affective dimension. The distribution of metaphors across discourse shows clustering at certain points, often where speakers are engaged in critical interpersonal discourse activity. Clusters in classroom talk co-occur with sequences of agenda management where teachers prepare students for upcoming lessons and with giving feedback to students, both of which require careful management of interpersonal and affective issues. Clusters in reconciliation talk co-occur with discourse management and with two situations with significant affective dynamics: appropriation of metaphor and exploration of alternative scenarios.

Metaphor is examined in the very different iscourse contexts of the classroom and of reconciliation talk to highlight the neglected affective dimension. The distribution of metaphors across discourse shows clustering at certain points, often where speakers are engaged in critical interpersonal discourse activity. Clusters in classroom talk co-occur with sequences of agenda management where teachers prepare students for upcoming lessons and with giving feedback to students, both of which require careful management of interpersonal and affective issues. Clusters in reconciliation talk co-occur with discourse management and with two situations with significant affective dynamics: appropriation of metaphor and exploration of alternative scenarios.

Evaluation of gene-expression clustering via mutual information distance measure

Directory of Open Access Journals (Sweden)

Maimon Oded

2007-03-01

Full Text Available Abstract Background The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI measure versus the use of the well known Euclidean distance and Pearson correlation coefficient. Results Relying on several public gene expression datasets, we evaluate the homogeneity and separation scores of different clustering solutions. It was found that the use of the MI measure yields a more significant differentiation among erroneous clustering solutions. The proposed measure was also used to analyze the performance of several known clustering algorithms. A comparative study of these algorithms reveals that their "best solutions" are ranked almost oppositely when using different distance measures, despite the found correspondence between these measures when analysing the averaged scores of groups of solutions. Conclusion In view of the results, further attention should be paid to the selection of a proper distance measure for analyzing the clustering of gene expression data.

The Impact of Clustering on the Innovativeness Of Furniture Industry

Directory of Open Access Journals (Sweden)

Grzegorzewska Emilia

2014-06-01

Full Text Available The furniture industry in Poland is a rapidly growing area of the economy. The level of innovation strongly influences furniture enterprises competitive position on the market. To support innovation, small and medium furniture industry businesses are affiliate in cluster initiatives. It supports the area of R&D, joint promotional campaigns and financing of new ventures. The paper presents selected furniture industry cluster initiatives that implement policies to support innovation activities of enterprises affiliated to them. In Poland, more and more furniture industry businesses brings together in cluster initiatives that aim to improve their market competitiveness and increase the level of innovation. Taken studies allow to analyse the direction of innovative activities undertaken by companies of the furniture industry with particular emphasis on the ones associated in clusters. Thus the aim of the article is to investigate the interest of Polish furniture enterprises (especially SMEs, in participation in clusters. Moreover the benefits of that choice and its impact on Polish furniture manufacturers innovativeness are evaluated.

Race, deprivation, and immigrant isolation: The spatial demography of air-toxic clusters in the continental United States.

Science.gov (United States)

Liévanos, Raoul S

2015-11-01

This article contributes to environmental inequality outcomes research on the spatial and demographic factors associated with cumulative air-toxic health risks at multiple geographic scales across the United States. It employs a rigorous spatial cluster analysis of census tract-level 2005 estimated lifetime cancer risk (LCR) of ambient air-toxic emissions from stationary (e.g., facility) and mobile (e.g., vehicular) sources to locate spatial clusters of air-toxic LCR risk in the continental United States. It then tests intersectional environmental inequality hypotheses on the predictors of tract presence in air-toxic LCR clusters with tract-level principal component factor measures of economic deprivation by race and immigrant status. Logistic regression analyses show that net of controls, isolated Latino immigrant-economic deprivation is the strongest positive demographic predictor of tract presence in air-toxic LCR clusters, followed by black-economic deprivation and isolated Asian/Pacific Islander immigrant-economic deprivation. Findings suggest scholarly and practical implications for future research, advocacy, and policy. Copyright © 2015 Elsevier Inc. All rights reserved.

Massive Star Clusters in Ongoing Galaxy Interactions: Clues to Cluster Formation

Science.gov (United States)

Keel, William C.; Borne, Kirk D.

2003-09-01

We present HST WFPC2 observations, supplemented by ground-based Hα data, of the star-cluster populations in two pairs of interacting galaxies selected for being in very different kinds of encounters seen at different stages. Dynamical information and n-body simulations provide the details of encounter geometry, mass ratio, and timing. In NGC 5752/4 we are seeing a weak encounter, well past closest approach, after about 2.5×108 yr. The large spiral NGC 5754 has a normal population of disk clusters, while the fainter companion NGC 5752 exhibits a rich population of luminous clusters with a flatter luminosity function. The strong, ongoing encounter in NGC 6621/2, seen about 1.0×108 yr past closest approach between roughly equal-mass galaxies, has produced an extensive population of luminous clusters, particularly young and luminous in a small region between the two nuclei. This region is dynamically interesting, with such a strong perturbation in the velocity field that the rotation curve reverses sign. From these results, in comparison with other strongly interacting systems discussed in the literature, cluster formation requires a threshold level of perturbation, with stage of the interaction a less important factor. The location of the most active star formation in NGC 6621/2 draws attention to a possible role for the Toomre stability threshold in shaping star formation in interacting galaxies. The rich cluster populations in NGC 5752 and NGC 6621 show that direct contact between gas-rich galaxy disks is not a requirement to form luminous clusters and that they can be triggered by processes happening within a single galaxy disk (albeit triggered by external perturbations). Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

Projected coupled cluster theory.

Science.gov (United States)

Qiu, Yiheng; Henderson, Thomas M; Zhao, Jinmo; Scuseria, Gustavo E

2017-08-14

Coupled cluster theory is the method of choice for weakly correlated systems. But in the strongly correlated regime, it faces a symmetry dilemma, where it either completely fails to describe the system or has to artificially break certain symmetries. On the other hand, projected Hartree-Fock theory captures the essential physics of many kinds of strong correlations via symmetry breaking and restoration. In this work, we combine and try to retain the merits of these two methods by applying symmetry projection to broken symmetry coupled cluster wave functions. The non-orthogonal nature of states resulting from the application of symmetry projection operators furnishes particle-hole excitations to all orders, thus creating an obstacle for the exact evaluation of overlaps. Here we provide a solution via a disentanglement framework theory that can be approximated rigorously and systematically. Results of projected coupled cluster theory are presented for molecules and the Hubbard model, showing that spin projection significantly improves unrestricted coupled cluster theory while restoring good quantum numbers. The energy of projected coupled cluster theory reduces to the unprojected one in the thermodynamic limit, albeit at a much slower rate than projected Hartree-Fock.

I Cluster geografici

Directory of Open Access Journals (Sweden)

Maurizio Rosina

2010-03-01

Full Text Available Geographic ClustersOver the past decade, public alphanumeric database have been growing at exceptional rate. Most of data can be georeferenced, so that is possible gaining new knowledge from such databases. The contribution of this paper is two-fold. We first present a model of geographic clusters, which uses only geographic and functionally data properties. The model is useful to process huge amount of public/government data, even daily upgrading. After that, we merge the model into the framework GEOPOI (GEOcoding Points Of Interest, and show some graphic map results.

I Cluster geografici

Directory of Open Access Journals (Sweden)

Maurizio Rosina

2010-03-01

Full Text Available Geographic Clusters Over the past decade, public alphanumeric database have been growing at exceptional rate. Most of data can be georeferenced, so that is possible gaining new knowledge from such databases. The contribution of this paper is two-fold. We first present a model of geographic clusters, which uses only geographic and functionally data properties. The model is useful to process huge amount of public/government data, even daily upgrading. After that, we merge the model into the framework GEOPOI (GEOcoding Points Of Interest, and show some graphic map results.

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Science.gov (United States)

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

2015-01-01

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

Nonthermal emission from clusters of galaxies

Energy Technology Data Exchange (ETDEWEB)

Kushnir, Doron; Waxman, Eli, E-mail: doron.kushnir@weizmann.ac.il, E-mail: eli.waxman@weizmann.ac.il [Physics Faculty, Weizmann Institute of Science, PO Box 26, Rehovot (Israel)

2009-08-01

We show that the spectral and radial distribution of the nonthermal emission of massive, M ∼> 10{sup 14.5}M{sub ☉}, galaxy clusters may be approximately described by simple analytic expressions, which depend on the cluster thermal X-ray properties and on two model parameter, β{sub core} and η{sub e}. β{sub core} is the ratio of the cosmic-ray (CR) energy density (within a logarithmic CR energy interval) and the thermal energy density at the cluster core, and η{sub e(p)} is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of intra-cluster medium CRs, which are produced by accretion shocks, we find that β{sub core} ≅ η{sub p}/200, nearly independent of cluster mass and with a scatter Δln β{sub core} ≅ 1 between clusters of given mass. We show that the hard X-ray (HXR) and γ-ray luminosities produced by inverse Compton scattering of CMB photons by electrons accelerated in accretion shocks (primary electrons) exceed the luminosities produced by secondary particles (generated in hadronic interactions within the cluster) by factors ≅ 500(η{sub e}/η{sub p})(T/10 keV){sup −1/2} and ≅ 150(η{sub e}/η{sub p})(T/10 keV){sup −1/2} respectively, where T is the cluster temperature. Secondary particle emission may dominate at the radio and very high energy (∼> 1 TeV) γ-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and γ-ray emission from clusters of galaxies are extended, since the emission is dominated at these energies by primary (rather than by secondary) electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for η{sub p} ∼ η{sub e} ∼ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. In particular

Robust MST-Based Clustering Algorithm.

Science.gov (United States)

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

Interaction of intense ultrashort pulse lasers with clusters

International Nuclear Information System (INIS)

Petrov, G. M.; Davis, J.

2008-01-01

The dynamics of clusters composed of different material irradiated by a high-intensity ultrashort pulse laser was studied using a fully relativistic three-dimensional molecular dynamics model. Key parameters of the cluster evolution such as particle positions, energy absorption, and cluster explosion were simulated. By a direct comparison of these parameters for clusters of equal initial radius but made of different material (deuterium, neon, argon, and xenon), the main stages and attributes of cluster evolution were elucidated. The simulations showed that clusters made of different material act alike, especially those of heavy elements. Clusters made of heavy elements (neon, argon, and xenon) differentiate from clusters made of light elements (deuterium) by the magnitude of the absorbed energy per cluster and the final mean energy of exploding ions. What most distinguishes clusters composed of different material is the amount of emitted radiation and its spectral range

Clustering Moving Objects Using Segments Slopes

OpenAIRE

Mohamed E. El-Sharkawi; Hoda M. O. Mokhtar; Omnia Ossama

2011-01-01

Given a set of moving object trajectories, we show how to cluster them using k-meansclustering approach. Our proposed clustering algorithm is competitive with the k-means clusteringbecause it specifies the value of “k” based on the segment’s slope of the moving object trajectories. Theadvantage of this approach is that it overcomes the known drawbacks of the k-means algorithm, namely,the dependence on the number of clusters (k), and the dependence on the initial choice of the clusters’centroi...

Fuzzy C-means method for clustering microarray data.

Science.gov (United States)

Dembélé, Doulaye; Kastner, Philippe

2003-05-22

Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes. A major problem in applying the FCM method for clustering microarray data is the choice of the fuzziness parameter m. We show that the commonly used value m = 2 is not appropriate for some data sets, and that optimal values for m vary widely from one data set to another. We propose an empirical method, based on the distribution of distances between genes in a given data set, to determine an adequate value for m. By setting threshold levels for the membership values, genes which are tigthly associated to a given cluster can be selected. Using a yeast cell cycle data set as an example, we show that this selection increases the overall biological significance of the genes within the cluster. Supplementary text and Matlab functions are available at http://www-igbmc.u-strasbg.fr/fcm/

Infrared study of new star cluster candidates associated to dusty globules

Science.gov (United States)

Soto King, P.; Barbá, R.; Roman-Lopes, A.; Jaque, M.; Firpo, V.; Nilo, J. L.; Soto, M.; Minniti, D.

2014-10-01

We present results from a study of a sample of small star clusters associated to dusty globules and bright-rimmed clouds that have been observed under ESO/Chile public infrared survey Vista Variables in the Vía Láctea (VVV). In this short communication, we analyse the near-infrared properties of a set of four small clusters candidates associated to dark clouds. This sample of clusters associated to dusty globules are selected from the new VVV stellar cluster candidates developed by members of La Serena VVV Group (Barbá et al. 2014). Firstly, we are producing color-color and color-magnitude diagrams for both, cluster candidates and surrounding areas for comparison through PSF photometry. The cluster positions are determined from the morphology on the images and also from the comparison of the observed luminosity function for the cluster candidates and the surrounding star fields. Now, we are working in the procedures to establish the full sample of clusters to be analyzed and methods for subtraction of the star field contamination. These clusters associated to dusty globules are simple laboratories to study the star formation relatively free of the influence of large star-forming regions and populous clusters, and they will be compared with those clusters associated to bright-rimmed globules, which are influenced by the energetic action of nearby O and B massive stars.

Quasi-free experiments as a tool for the study of 6Li cluster structure

International Nuclear Information System (INIS)

Lattuada, M.; Riggi, F.; Spitaleri, C.; Vinciguerra, D.

1984-01-01

The value of the α-d clustering probability in 6 Li deduced from quasi-free experiments may be influenced by the choice of the inter-cluster wave function. Several functional forms usually taken to describe the relative motion of the two clusters have been examined. The effect of the choice of the intercluster wave function on the information deduced by analysing quasi-free data in the plane-wave impulse approximation was investigated

Role of shell corrections in the phenomenon of cluster radioactivity

Science.gov (United States)

Kaur, Mandeep; Singh, Bir Bikram; Sharma, Manoj K.

2018-05-01

The detailed investigation has been carried out to explore the role of shell corrections in the decay of various radioactive parent nuclei in trans-lead region, specifically, which lead to doubly magic 208Pb daughter nucleus through emission of clusters such as 14C, 18,20O, 22,24,26Ne, 28,30 Mg and 34S i. The fragmentation potential comprises of binding energies (BE), Coulomb potential (Vc) and nuclear or proximity potential (VP) of the decaying fragments (or clusters). It is relevant to mention here that the contributions of VLDM (T=0) and δU (T=0) in the BE have been analysed within the Strutinsky renormanlization procedure. In the framework of quantum mechanical fragmentation theory (QMFT), we have investigated the above mentioned cluster decays with and without inclusion of shell corrections in the fragmentation potential for spherical as well as non-compact oriented nuclei. We find that the experimentally observed clusters 14C, 18,20O, 22,24,26 Ne, 28,30 Mg and 34Si having doubly magic 208 Pb daughter nucleus are not strongly minimized, they do so only after the inclusion of shell corrections in the fragmentation potential. The nuclear structure information carried by the shell corrections have been explored via these calculations, within the collective clusterisation process of QMFT, in the study of ground state decay of radioactive nuclei. The role of different parts of fragmentation potentials such as VLDM, δU, Vc and Vp is dually analysed for better understanding of radioactive cluster decay.

Cluster management.

Science.gov (United States)

Katz, R

1992-11-01

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

Forming clusters within clusters: how 30 Doradus recollapsed and gave birth again

Science.gov (United States)

Rahner, Daniel; Pellegrini, Eric W.; Glover, Simon C. O.; Klessen, Ralf S.

2018-01-01

The 30 Doradus nebula in the Large Magellanic Cloud (LMC) contains the massive starburst cluster NGC 2070 with a massive and probably younger stellar sub clump at its centre: R136. It is not clear how such a massive inner cluster could form several million years after the older stars in NGC 2070, given that stellar feedback is usually thought to expel gas and inhibit further star formation. Using the recently developed 1D feedback scheme WARPFIELD to scan a large range of cloud and cluster properties, we show that an age offset of several million years between the stellar populations is in fact to be expected given the interplay between feedback and gravity in a giant molecular cloud with a density ≳500 cm-3 due to re-accretion of gas on to the older stellar population. Neither capture of field stars nor gas retention inside the cluster have to be invoked in order to explain the observed age offset in NGC 2070 as well as the structure of the interstellar medium around it.

Substructures in DAFT/FADA survey clusters based on XMM and optical data

Science.gov (United States)

Durret, F.; DAFT/FADA Team

2014-07-01

The DAFT/FADA survey was initiated to perform weak lensing tomography on a sample of 90 massive clusters in the redshift range [0.4,0.9] with HST imaging available. The complementary deep multiband imaging constitutes a high quality imaging data base for these clusters. In X-rays, we have analysed the XMM-Newton and/or Chandra data available for 32 clusters, and for 23 clusters we fit the X-ray emissivity with a beta-model and subtract it to search for substructures in the X-ray gas. This study was coupled with a dynamical analysis for the 18 clusters with at least 15 spectroscopic galaxy redshifts in the cluster range, based on a Serna & Gerbal (SG) analysis. We detected ten substructures in eight clusters by both methods (X-rays and SG). The percentage of mass included in substructures is found to be roughly constant with redshift, with values of 5-15%. Most of the substructures detected both in X-rays and with the SG method are found to be relatively recent infalls, probably at their first cluster pericenter approach.

Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis.

Science.gov (United States)

Fukuoka, Yoshimi; Zhou, Mo; Vittinghoff, Eric; Haskell, William; Goldberg, Ken; Aswani, Anil

2018-02-01

Determining patterns of physical activity throughout the day could assist in developing more personalized interventions or physical activity guidelines in general and, in particular, for women who are less likely to be physically active than men. The aims of this report are to identify clusters of women based on accelerometer-measured baseline raw metabolic equivalent of task (MET) values and a normalized version of the METs ≥3 data, and to compare sociodemographic and cardiometabolic risks among these identified clusters. A total of 215 women who were enrolled in the Mobile Phone Based Physical Activity Education (mPED) trial and wore an accelerometer for at least 8 hours per day for the 7 days prior to the randomization visit were analyzed. The k-means clustering method and the Lloyd algorithm were used on the data. We used the elbow method to choose the number of clusters, looking at the percentage of variance explained as a function of the number of clusters. The results of the k-means cluster analyses of raw METs revealed three different clusters. The unengaged group (n=102) had the highest depressive symptoms score compared with the afternoon engaged (n=65) and morning engaged (n=48) groups (overall Pcluster groups using a large national dataset. ClinicalTrials.gov NCT01280812; https://clinicaltrials.gov/ct2/show/NCT01280812 (Archived by WebCite at http://www.webcitation.org/6vVyLzwft). ©Yoshimi Fukuoka, Mo Zhou, Eric Vittinghoff, William Haskell, Ken Goldberg, Anil Aswani. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 01.02.2018.

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

Science.gov (United States)

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

2015-07-14

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

Completion Report for Well Cluster ER-6-1

Energy Technology Data Exchange (ETDEWEB)

Bechtel Nevada

2004-10-01

Well Cluster ER-6-1 was constructed for the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office in support of the Nevada Environmental Restoration Division at the Nevada Test Site, Nye County, Nevada. This work was initiated as part of the Groundwater Characterization Project, now known as the Underground Test Area Project. The well cluster is located in southeastern Yucca Flat. Detailed lithologic descriptions with stratigraphic assignments for Well Cluster ER-6-1 are included in this report. These are based on composite drill cuttings collected every 3 meters and conventional core samples taken below 639 meters, supplemented by geophysical log data. Detailed petrographic, chemical, and mineralogical studies of rock samples were conducted on 11 samples to resolve complex interrelationships between several of the Tertiary tuff units. Additionally, paleontological analyses by the U.S. Geological Survey confirmed the stratigraphic assignments below 539 meters within the Paleozoic sedimentary section. All three wells in the Well ER-6-1 cluster were drilled within the Quaternary and Tertiary alluvium section, the Tertiary volcanic section, and into the Paleozoic sedimentary section.

Data Clustering

Science.gov (United States)

Wagstaff, Kiri L.

2012-03-01

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

ELEMENTAL ABUNDANCE RATIOS IN STARS OF THE OUTER GALACTIC DISK. IV. A NEW SAMPLE OF OPEN CLUSTERS

International Nuclear Information System (INIS)

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

2012-01-01

We present radial velocities and chemical abundances for nine stars in the old, distant open clusters Be18, Be21, Be22, Be32, and PWM4. For Be18 and PWM4, these are the first chemical abundance measurements. Combining our data with literature results produces a compilation of some 68 chemical abundance measurements in 49 unique clusters. For this combined sample, we study the chemical abundances of open clusters as a function of distance, age, and metallicity. We confirm that the metallicity gradient in the outer disk is flatter than the gradient in the vicinity of the solar neighborhood. We also confirm that the open clusters in the outer disk are metal-poor with enhancements in the ratios [α/Fe] and perhaps [Eu/Fe]. All elements show negligible or small trends between [X/Fe] and distance ( –1 ), but for some elements, there is a hint that the local (R GC GC > 13 kpc) samples may have different trends with distance. There is no evidence for significant abundance trends versus age ( –1 ). We measure the linear relation between [X/Fe] and metallicity, [Fe/H], and find that the scatter about the mean trend is comparable to the measurement uncertainties. Comparison with solar neighborhood field giants shows that the open clusters share similar abundance ratios [X/Fe] at a given metallicity. While the flattening of the metallicity gradient and enhanced [α/Fe] ratios in the outer disk suggest a chemical enrichment history different from that of the solar neighborhood, we echo the sentiments expressed by Friel et al. that definitive conclusions await homogeneous analyses of larger samples of stars in larger numbers of clusters. Arguably, our understanding of the evolution of the outer disk from open clusters is currently limited by systematic abundance differences between various studies.

Dense Fe cluster-assembled films by energetic cluster deposition

International Nuclear Information System (INIS)

Peng, D.L.; Yamada, H.; Hihara, T.; Uchida, T.; Sumiyama, K.

2004-01-01

High-density Fe cluster-assembled films were produced at room temperature by an energetic cluster deposition. Though cluster-assemblies are usually sooty and porous, the present Fe cluster-assembled films are lustrous and dense, revealing a soft magnetic behavior. Size-monodispersed Fe clusters with the mean cluster size d=9 nm were synthesized using a plasma-gas-condensation technique. Ionized clusters are accelerated electrically and deposited onto the substrate together with neutral clusters from the same cluster source. Packing fraction and saturation magnetic flux density increase rapidly and magnetic coercivity decreases remarkably with increasing acceleration voltage. The Fe cluster-assembled film obtained at the acceleration voltage of -20 kV has a packing fraction of 0.86±0.03, saturation magnetic flux density of 1.78±0.05 Wb/m 2 , and coercivity value smaller than 80 A/m. The resistivity at room temperature is ten times larger than that of bulk Fe metal

clubber: removing the bioinformatics bottleneck in big data analyses

Science.gov (United States)

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2018-01-01

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment. PMID:28609295

clubber: removing the bioinformatics bottleneck in big data analyses.

Science.gov (United States)

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2017-06-13

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these "big data" analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber's goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment.

clubber: removing the bioinformatics bottleneck in big data analyses

Directory of Open Access Journals (Sweden)

Miller Maximilian

2017-06-01

Full Text Available With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min clearly illustrate the importance of clubber in the everyday computational biology environment.

Noninvasive neuromodulation in cluster headache

DEFF Research Database (Denmark)

Láinez, Miguel J A; Jensen, Rigmor

2015-01-01

PURPOSE OF REVIEW: Neuromodulation is an alternative in the management of medically intractable cluster headache patients. Most of the techniques are invasive, but in the last 2 years, some studies using a noninvasive device have been presented. The objective of this article is to review the data...... using this approach. RECENT FINDINGS: Techniques as occipital nerve stimulation or sphenopalatine ganglion stimulation are recommended as first-line therapy in refractory cluster patients, but they are invasive and maybe associated with complications. Noninvasive vagal nerve stimulation with an external...... device has been tried in cluster patients. Results from clinical practice and a single randomized clinical trial have been presented showing a reduction of the number of cluster attacks/week in the patients treated with the device. The rate of adverse events was low and most of them were mild. SUMMARY...

Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.

Directory of Open Access Journals (Sweden)

Geoffrey M Jacquez

Full Text Available In case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses regarding disease causation.Global, local and focused Q-statistics are applied to data from a population-based case-control study of 11 southeast Michigan counties. Analyses were conducted using both year- and age-based measures of time. The analyses were adjusted for arsenic exposure, education, smoking, family history of bladder cancer, occupational exposure to bladder cancer carcinogens, age, gender, and race.Significant global clustering of cases was not found. Such a finding would indicate large-scale clustering of cases relative to controls through time. However, highly significant local clusters were found in Ingham County near Lansing, in Oakland County, and in the City of Jackson, Michigan. The Jackson City cluster was observed in working-ages and is thus consistent with occupational causes. The Ingham County cluster persists over time, suggesting a broad-based geographically defined exposure. Focused clusters were found for 20 industrial sites engaged in manufacturing activities associated with known or suspected bladder cancer carcinogens. Set-based tests that adjusted for multiple testing were not significant, although local clusters persisted through time and temporal trends in probability of local tests were observed.Q analyses provide a powerful tool for unpacking unexplained disease risk from case-control studies. This is particularly useful when the effect of risk factors varies spatially, through time, or through both space and time. For bladder cancer in Michigan, the next step is to investigate causal hypotheses that may explain the excess bladder cancer risk localized to areas of

MOCCA-SURVEY Database I: Is NGC 6535 a dark star cluster harbouring an IMBH?

Science.gov (United States)

Askar, Abbas; Bianchini, Paolo; de Vita, Ruggero; Giersz, Mirek; Hypki, Arkadiusz; Kamann, Sebastian

2017-01-01

We describe the dynamical evolution of a unique type of dark star cluster model in which the majority of the cluster mass at Hubble time is dominated by an intermediate-mass black hole (IMBH). We analysed results from about 2000 star cluster models (Survey Database I) simulated using the Monte Carlo code MOnte Carlo Cluster simulAtor and identified these dark star cluster models. Taking one of these models, we apply the method of simulating realistic `mock observations' by utilizing the Cluster simulatiOn Comparison with ObservAtions (COCOA) and Simulating Stellar Cluster Observation (SISCO) codes to obtain the photometric and kinematic observational properties of the dark star cluster model at 12 Gyr. We find that the perplexing Galactic globular cluster NGC 6535 closely matches the observational photometric and kinematic properties of the dark star cluster model presented in this paper. Based on our analysis and currently observed properties of NGC 6535, we suggest that this globular cluster could potentially harbour an IMBH. If it exists, the presence of this IMBH can be detected robustly with proposed kinematic observations of NGC 6535.

Application of a clustering-based peak alignment algorithm to analyze various DNA fingerprinting data.

Science.gov (United States)

Ishii, Satoshi; Kadota, Koji; Senoo, Keishi

2009-09-01

DNA fingerprinting analysis such as amplified ribosomal DNA restriction analysis (ARDRA), repetitive extragenic palindromic PCR (rep-PCR), ribosomal intergenic spacer analysis (RISA), and denaturing gradient gel electrophoresis (DGGE) are frequently used in various fields of microbiology. The major difficulty in DNA fingerprinting data analysis is the alignment of multiple peak sets. We report here an R program for a clustering-based peak alignment algorithm, and its application to analyze various DNA fingerprinting data, such as ARDRA, rep-PCR, RISA, and DGGE data. The results obtained by our clustering algorithm and by BioNumerics software showed high similarity. Since several R packages have been established to statistically analyze various biological data, the distance matrix obtained by our R program can be used for subsequent statistical analyses, some of which were not previously performed but are useful in DNA fingerprinting studies.

Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry

Directory of Open Access Journals (Sweden)

Manuel Llorca

2014-03-01

Full Text Available In this paper we advocate using the latent class model (LCM approach to control for technological differences in traditional efficiency analysis of regulated electricity networks. Our proposal relies on the fact that latent class models are designed to cluster firms by uncovering differences in technology parameters. Moreover, it can be viewed as a supervised method for clustering data that takes into account the same (production or cost relationship that is analysed later, often using nonparametric frontier techniques. The simulation exercises show that the proposed approach outperforms other sample selection procedures. The proposed methodology is illustrated with an application to a sample of US electricity transmission firms for the period 2001–2009.

The Dual Role of Multinational Corporations in Cluster Evolution

DEFF Research Database (Denmark)

Østergaard, Christian Richter; Reinau, Kristian Hegner; Park, Eun Kyung

2017-01-01

This chapter shows that multinational corporations play a dual role in cluster evolution through the case of the wireless communications cluster in Northern Denmark. On the one hand, they bring in resources to the cluster, such as financial resources, technology, knowledge, innovation networks, a...

A MULTIVARIATE APPROACH TO ANALYSE NATIVE FOREST TREE SPECIE SEEDS

Directory of Open Access Journals (Sweden)

Alessandro Dal Col Lúcio

2006-03-01

Full Text Available This work grouped, by species, the most similar seed tree, using the variables observed in exotic forest species of theBrazilian flora of seeds collected in the Forest Research and Soil Conservation Center of Santa Maria, Rio Grande do Sul, analyzedfrom January, 1997, to march, 2003. For the cluster analysis, all the species that possessed four or more analyses per lot wereanalyzed by the hierarchical Clustering method, of the standardized Euclidian medium distance, being also a principal componentanalysis technique for reducing the number of variables. The species Callistemon speciosus, Cassia fistula, Eucalyptus grandis,Eucalyptus robusta, Eucalyptus saligna, Eucalyptus tereticornis, Delonix regia, Jacaranda mimosaefolia e Pinus elliottii presentedmore than four analyses per lot, in which the third and fourth main components explained 80% of the total variation. The clusteranalysis was efficient in the separation of the groups of all tested species, as well as the method of the main components.

Color Gradient in the King Type Globular Cluster NGC 7089

Directory of Open Access Journals (Sweden)

Young-Jong Sohn

1999-12-01

Full Text Available We use BV CCD images to investigate the reality of the color gradient within a King type globular cluster NGC 7089. Surface photometry shows that there is a strong radial color gradient in the central region of the cluster in the sense of bluer center with the amplitude of -0.39 +/- 0.07 mag/arcsec2 in (B - V. In the outer region of the cluster, however, the radial color gradient shows a reverse case, i.e., redder toward the center. (B - V color profile which was derived from resolved stars in VGC 7089 field also shows a significant color gradient in the central region of the clusters, indicating that lights from the combination of red giant stars and blue horizontal branch stars cause the radial color gradient. Color gradient of the outer region of NGC 7089 may be due to the unresolved background of the cluster. Similar color gradients in the central area of clusters have been previously observed exserved exclusively in highly concentrated systems classified as post core collapse clusters. We caution, however, to confirm the reality of the color gradient from resolved stars, we need more accurate imaging data of the cluster with exceptional seeing condition because the effect of completeness correlates with local density of stars.

Detecting space-time cancer clusters using residential histories

Science.gov (United States)

Jacquez, Geoffrey M.; Meliker, Jaymie R.

2007-04-01

Methods for analyzing geographic clusters of disease typically ignore the space-time variability inherent in epidemiologic datasets, do not adequately account for known risk factors (e.g., smoking and education) or covariates (e.g., age, gender, and race), and do not permit investigation of the latency window between exposure and disease. Our research group recently developed Q-statistics for evaluating space-time clustering in cancer case-control studies with residential histories. This technique relies on time-dependent nearest neighbor relationships to examine clustering at any moment in the life-course of the residential histories of cases relative to that of controls. In addition, in place of the widely used null hypothesis of spatial randomness, each individual's probability of being a case is instead based on his/her risk factors and covariates. Case-control clusters will be presented using residential histories of 220 bladder cancer cases and 440 controls in Michigan. In preliminary analyses of this dataset, smoking, age, gender, race and education were sufficient to explain the majority of the clustering of residential histories of the cases. Clusters of unexplained risk, however, were identified surrounding the business address histories of 10 industries that emit known or suspected bladder cancer carcinogens. The clustering of 5 of these industries began in the 1970's and persisted through the 1990's. This systematic approach for evaluating space-time clustering has the potential to generate novel hypotheses about environmental risk factors. These methods may be extended to detect differences in space-time patterns of any two groups of people, making them valuable for security intelligence and surveillance operations.

Signatures for quark clustering in nuclei

International Nuclear Information System (INIS)

Carlson, C.E.; Lassila, K.E.

1994-01-01

As a signature for the presence of quark clusters in nuclei, the authors suggest studying backward protons produced by electron scattering off deuterons and suggest a ratio that cancels out much of the detailed properties of deuterons or 6-quark clusters. The test may be viewed as a test that the short range part of the deuteron is still a 2-nucleon system. They make estimates to show how it fails in characteristic and significant ways if the two nucleons at short range coalesce into a kneaded 6-quark cluster

Signatures for quark clustering in nuclei

Energy Technology Data Exchange (ETDEWEB)

Carlson, C.E. [College of William and Mary, Williamsburg, VA (United States); Lassila, K.E. [Iowa State Univ., Ames, IA (United States)

1994-04-01

As a signature for the presence of quark clusters in nuclei, the authors suggest studying backward protons produced by electron scattering off deuterons and suggest a ratio that cancels out much of the detailed properties of deuterons or 6-quark clusters. The test may be viewed as a test that the short range part of the deuteron is still a 2-nucleon system. They make estimates to show how it fails in characteristic and significant ways if the two nucleons at short range coalesce into a kneaded 6-quark cluster.

Survey of quasi-free cluster knockout

International Nuclear Information System (INIS)

Roos, P.G.; Chant, N.S.

1975-01-01

The investigation of quasi-free knockout reactions has been proceeding for many years now, since the first experiments studying (p,2p) reactions on light nuclei. These experiments clearly showed the dominance of quasi-free proton knockout, and have provided information on the proton holes states in nuclei. From very early in the game people extended these studies to the knock-out of clusters, in an attempt to obtain nuclear structure information about clustering in nuclei. These cluster knockout reactions, excluding the nucleon knockout work, are examined. 20 figures, 16 references

MOCK OBSERVATIONS OF BLUE STRAGGLERS IN GLOBULAR CLUSTER MODELS

International Nuclear Information System (INIS)

Sills, Alison; Glebbeek, Evert; Chatterjee, Sourav; Rasio, Frederic A.

2013-01-01

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 are 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

Self-selection in size and structure in argon clusters formed on amorphous carbon

Energy Technology Data Exchange (ETDEWEB)

Krainyukova, Nina V.; Waal, Benjamin W. van de

2004-07-01

Argon clusters formed on an amorphous carbon substrate as deposited from the vapor phase were studied by means of transmission high energy electron diffraction using the liquid helium cryostat. Electron diffractograms were analysed on the basis of assumption that there exist a cluster size distribution in samples formed on substrate and multi-shell structures such as icosahedra, decahedra, fcc and hcp were probed for different sizes up to {approx}15 000 atoms. The experimental data were considered as a result of a superposition of diffracted intensities from clusters of different sizes and structures. The comparative analysis was based on the R-factor minimization that was found to be equal to 0.014 for the best fit between experiment and modelling. The total size and structure distribution function shows the presence of 'non-crystallographic' structures such as icosahedra and decahedra with five-fold symmetry that was found to prevail and a smaller amount of fcc and hcp structures. Possible growth mechanisms as well as observed general tendency to self-selection in sizes and structures are presumably governed by confined pore-like geometry in an amorphous carbon substrate.

An analysis of hospital brand mark clusters.

Science.gov (United States)

Vollmers, Stacy M; Miller, Darryl W; Kilic, Ozcan

2010-07-01

This study analyzed brand mark clusters (i.e., various types of brand marks displayed in combination) used by hospitals in the United States. The brand marks were assessed against several normative criteria for creating brand marks that are memorable and that elicit positive affect. Overall, results show a reasonably high level of adherence to many of these normative criteria. Many of the clusters exhibited pictorial elements that reflected benefits and that were conceptually consistent with the verbal content of the cluster. Also, many clusters featured icons that were balanced and moderately complex. However, only a few contained interactive imagery or taglines communicating benefits.

Combining cluster number counts and galaxy clustering

Energy Technology Data Exchange (ETDEWEB)

Lacasa, Fabien; Rosenfeld, Rogerio, E-mail: fabien@ift.unesp.br, E-mail: rosenfel@ift.unesp.br [ICTP South American Institute for Fundamental Research, Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo (Brazil)

2016-08-01

The abundance of clusters and the clustering of galaxies are two of the important cosmological probes for current and future large scale surveys of galaxies, such as the Dark Energy Survey. In order to combine them one has to account for the fact that they are not independent quantities, since they probe the same density field. It is important to develop a good understanding of their correlation in order to extract parameter constraints. We present a detailed modelling of the joint covariance matrix between cluster number counts and the galaxy angular power spectrum. We employ the framework of the halo model complemented by a Halo Occupation Distribution model (HOD). We demonstrate the importance of accounting for non-Gaussianity to produce accurate covariance predictions. Indeed, we show that the non-Gaussian covariance becomes dominant at small scales, low redshifts or high cluster masses. We discuss in particular the case of the super-sample covariance (SSC), including the effects of galaxy shot-noise, halo second order bias and non-local bias. We demonstrate that the SSC obeys mathematical inequalities and positivity. Using the joint covariance matrix and a Fisher matrix methodology, we examine the prospects of combining these two probes to constrain cosmological and HOD parameters. We find that the combination indeed results in noticeably better constraints, with improvements of order 20% on cosmological parameters compared to the best single probe, and even greater improvement on HOD parameters, with reduction of error bars by a factor 1.4-4.8. This happens in particular because the cross-covariance introduces a synergy between the probes on small scales. We conclude that accounting for non-Gaussian effects is required for the joint analysis of these observables in galaxy surveys.

Mapping Dark Matter in Simulated Galaxy Clusters

Science.gov (United States)

Bowyer, Rachel

2018-01-01

Galaxy clusters are the most massive bound objects in the Universe with most of their mass being dark matter. Cosmological simulations of structure formation show that clusters are embedded in a cosmic web of dark matter filaments and large scale structure. It is thought that these filaments are found preferentially close to the long axes of clusters. We extract galaxy clusters from the simulations "cosmo-OWLS" in order to study their properties directly and also to infer their properties from weak gravitational lensing signatures. We investigate various stacking procedures to enhance the signal of the filaments and large scale structure surrounding the clusters to better understand how the filaments of the cosmic web connect with galaxy clusters. This project was supported in part by the NSF REU grant AST-1358980 and by the Nantucket Maria Mitchell Association.

Toward understanding environmental effects in SDSS clusters

Energy Technology Data Exchange (ETDEWEB)

Einasto, Jaan; Tago, E.; Einasto, M.; Saar, E.; Suhhonenko, I.; /Tartu Observ.; Heinamaki, P.; /Tartu Observ. /Tuorla Observ.; Hutsi, G.; /Tartu Observ. /Garching, Max; Tucker, D.L.; /Fermilab

2004-11-01

We find clusters and superclusters of galaxies using the Data Release 1 of the Sloan Digital Sky Survey. We determine the luminosity function of clusters and find that clusters in a high-density environment have a luminosity a factor of {approx}5 higher than in a low-density environment. We also study clusters and superclusters in numerical simulations. Simulated clusters in a high-density environment are also more massive than those in a low-density environment. Comparison of the density distribution at various epochs in simulations shows that in large low-density regions (voids) dynamical evolution is very slow and stops at an early epoch. In contrast, in large regions of higher density (superclusters) dynamical evolution starts early and continues until the present; here particles cluster early, and by merging of smaller groups very rich systems of galaxies form.

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

Science.gov (United States)

LaCon, Genevieve; Morrison, Amy C; Astete, Helvio; Stoddard, Steven T; Paz-Soldan, Valerie A; Elder, John P; Halsey, Eric S; Scott, Thomas W; Kitron, Uriel; Vazquez-Prokopec, Gonzalo M

2014-08-01

Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels. Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [pentomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study. Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots.

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

Directory of Open Access Journals (Sweden)

Genevieve LaCon

2014-08-01

Full Text Available Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1 quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2 determine overlap between clusters, (3 quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4 quantify the extent of clustering at the household and neighborhood levels.Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study.Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than

Rapid identification and classification of bacteria by 16S rDNA restriction fragment melting curve analyses (RFMCA).

Science.gov (United States)

Rudi, Knut; Kleiberg, Gro H; Heiberg, Ragnhild; Rosnes, Jan T

2007-08-01

The aim of this work was to evaluate restriction fragment melting curve analyses (RFMCA) as a novel approach for rapid classification of bacteria during food production. RFMCA was evaluated for bacteria isolated from sous vide food products, and raw materials used for sous vide production. We identified four major bacterial groups in the material analysed (cluster I-Streptococcus, cluster II-Carnobacterium/Bacillus, cluster III-Staphylococcus and cluster IV-Actinomycetales). The accuracy of RFMCA was evaluated by comparison with 16S rDNA sequencing. The strains satisfying the RFMCA quality filtering criteria (73%, n=57), with both 16S rDNA sequence information and RFMCA data (n=45) gave identical group assignments with the two methods. RFMCA enabled rapid and accurate classification of bacteria that is database compatible. Potential application of RFMCA in the food or pharmaceutical industry will include development of classification models for the bacteria expected in a given product, and then to build an RFMCA database as a part of the product quality control.

Medium Resolution Spectroscopy and Chemical Composition of Galactic Globular Clusters

Directory of Open Access Journals (Sweden)

Khamidullina D. A.

2014-12-01

Full Text Available We used integrated-light medium-resolution spectra of six Galactic globular clusters and model stellar atmospheres to carry out population synthesis and to derive chemical composition and age of the clusters. We used medium-resolution spectra of globular clusters published by Schiavon et al. (2005, as well as our long-slit observations with the 1.93 m telescope of the Haute Provence Observatory. The observed spectra were fitted to the theoretical ones interactively. As an initial approach, we used masses, radii and log g of stars in the clusters corresponding to the best fitting isochrones in the observed color-magnitude diagrams. The computed synthetic blanketed spectra of stars were summed according to the Chabrier mass function. To improve the determination of age and helium content, the shape and depth of the Balmer absorption lines was analysed. The abundances of Mg, Ca, C and several other elements were derived. A reasonable agreement with the literature data both in chemical composition and in age of the clusters is found. Our method might be useful for the development of stellar population models and for a better understanding of extragalactic star clusters.

Medium resolution spectroscopy and chemical composition of Galactic globular clusters

Science.gov (United States)

Khamidullina, D. A.; Sharina, M. E.; Shimansky, V. V.; Davoust, E.

We used integrated-light medium-resolution spectra of six Galactic globular clusters and model stellar atmospheres to carry out population synthesis and to derive chemical composition and age of the clusters. We used medium-resolution spectra of globular clusters published by Schiavon et al. (2005), as well as our long-slit observations with the 1.93 m telescope of the Haute Provence Observatory. The observed spectra were fitted to the theoretical ones interactively. As an initial approach, we used masses, radii and log g of stars in the clusters corresponding to the best fitting isochrones in the observed color-magnitude diagrams. The computed synthetic blanketed spectra of stars were summed according to the Chabrier mass function. To improve the determination of age and helium content, the shape and depth of the Balmer absorption lines was analysed. The abundances of Mg, Ca, C and several other elements were derived. A reasonable agreement with the literature data both in chemical composition and in age of the clusters is found. Our method might be useful for the development of stellar population models and for a better understanding of extragalactic star clusters.

Clustering disaggregated load profiles using a Dirichlet process mixture model

International Nuclear Information System (INIS)

Granell, Ramon; Axon, Colin J.; Wallom, David C.H.

2015-01-01

Highlights: • We show that the Dirichlet process mixture model is scaleable. • Our model does not require the number of clusters as an input. • Our model creates clusters only by the features of the demand profiles. • We have used both residential and commercial data sets. - Abstract: The increasing availability of substantial quantities of power-use data in both the residential and commercial sectors raises the possibility of mining the data to the advantage of both consumers and network operations. We present a Bayesian non-parametric model to cluster load profiles from households and business premises. Evaluators show that our model performs as well as other popular clustering methods, but unlike most other methods it does not require the number of clusters to be predetermined by the user. We used the so-called ‘Chinese restaurant process’ method to solve the model, making use of the Dirichlet-multinomial distribution. The number of clusters grew logarithmically with the quantity of data, making the technique suitable for scaling to large data sets. We were able to show that the model could distinguish features such as the nationality, household size, and type of dwelling between the cluster memberships

Clusters and how to make it work : Cluster Strategy Toolkit

NARCIS (Netherlands)

Manickam, Anu; van Berkel, Karel

2014-01-01

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

Opportunistic usage of the CMS online cluster using a cloud overlay

CERN Document Server

Chaze, Olivier; Andronidis, Anastasios; Behrens, Ulf; Branson, James; Brummer, Philipp; Contescu, Alexandru-Cristian; Cittolin, Sergio; Craigs, Benjamin; Darlea, Georgiana-Lavinia; Deldicque, Christian; Demiragli, Zeynep; Dobson, M; Doualot, Nicolas; Erhan, Samim; Fulcher, Jonathan Richard; Gigi, Dominique; Glege, Frank; Gomez-Ceballos, Guillelmo; Hegeman, Jeroen; Holzner, Andre Georg; Jimenez-Estupiñán, Raul; Masetti, Lorenzo; Meijers, Frans; Meschi, Emilio; Mommsen, Remigius; Morovic, Srecko; O'Dell, Vivian; Orsini, Luciano; Paus, Christoph; Pieri, Marco; Racz, Attila; Sakulin, Hannes; Schwick, Christoph; Reis, Thomas; Simelevicius, Dainius; Zejdl, Petr

2016-01-01

After two years of maintenance and upgrade, the Large Hadron Collider (LHC), the largest and most powerful particle accelerator in the world, has started its second three year run. Around 1500 computers make up the CMS (Compact Muon Solenoid) Online cluster. This cluster is used for Data Acquisition of the CMS experiment at CERN, selecting and sending to storage around 20 TBytes of data per day that are then analysed by the Worldwide LHC Computing Grid (WLCG) infrastructure that links hundreds of data centres worldwide. 3000 CMS physicists can access and process data, and are always seeking more computing power and data. The backbone of the CMS Online cluster is composed of 16000 cores which provide as much computing power as all CMS WLCG Tier1 sites (352K HEP-SPEC-06 score in the CMS cluster versus 300K across CMS Tier1 sites). The computing power available in the CMS cluster can significantly speed up the processing of data, so an effort has been made to allocate the resources of the CMS Online cluster to t...

The use of hierarchical clustering for the design of optimized monitoring networks

Science.gov (United States)

Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji

2018-05-01

Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different

Text Clustering Algorithm Based on Random Cluster Core

Directory of Open Access Journals (Sweden)

Huang Long-Jun

2016-01-01

Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

A Clustering Routing Protocol for Mobile Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Jinke Huang

2016-01-01

Full Text Available The dynamic topology of a mobile ad hoc network poses a real challenge in the design of hierarchical routing protocol, which combines proactive with reactive routing protocols and takes advantages of both. And as an essential technique of hierarchical routing protocol, clustering of nodes provides an efficient method of establishing a hierarchical structure in mobile ad hoc networks. In this paper, we designed a novel clustering algorithm and a corresponding hierarchical routing protocol for large-scale mobile ad hoc networks. Each cluster is composed of a cluster head, several cluster gateway nodes, several cluster guest nodes, and other cluster members. The proposed routing protocol uses proactive protocol between nodes within individual clusters and reactive protocol between clusters. Simulation results show that the proposed clustering algorithm and hierarchical routing protocol provide superior performance with several advantages over existing clustering algorithm and routing protocol, respectively.

Renewable energy clusters recurring barriers to cluster development in eleven countries

CERN Document Server

Jaegersberg, Gudrun

2017-01-01

Taking eleven countries in Europe, Canada, South Africa, America, Latin America and Australia, this book discusses recurring barriers to cluster development in the renewable energy sector. The authors look at the real-world dynamics and tensions between stakeholders on the ground, with a particular focus on the relationships between SMEs and other actors. This trans-regional study is unique in its scale and scope, drawing on a decade of field research to show how by learning from the successes and failures of other clusters, costs and risk can be reduced. The book fills a significant gap in the literature for policymakers, managers and economic developers in a key market.

Einstein observations of the Hydra A cluster and the efficiency of galaxy formation in groups and clusters

Science.gov (United States)

David, L. P.; Arnaud, K. A.; Forman, W.; Jones, C.

1990-01-01

The Einstein imaging proportional counter observations of the poor cluster of galaxies centered on the radio galaxy Hydra A are examined. From the surface brightness profile, it is found that the X-ray-emitting gas in the Hydra A cluster must be condensing out of the intracluster medium at a rate of 600 solar masses/yr. This is one of the largest mass deposition rates observed in a cluster of galaxies. The ratio of gas mass to stellar mass is compared for a variety of systems, showing that this ratio correlates with the gas temperature.

Subtypes of autism by cluster analysis based on structural MRI data.

Science.gov (United States)

Hrdlicka, Michal; Dudova, Iva; Beranova, Irena; Lisy, Jiri; Belsan, Tomas; Neuwirth, Jiri; Komarek, Vladimir; Faladova, Ludvika; Havlovicova, Marketa; Sedlacek, Zdenek; Blatny, Marek; Urbanek, Tomas

2005-05-01

The aim of our study was to subcategorize Autistic Spectrum Disorders (ASD) using a multidisciplinary approach. Sixty four autistic patients (mean age 9.4+/-5.6 years) were entered into a cluster analysis. The clustering analysis was based on MRI data. The clusters obtained did not differ significantly in the overall severity of autistic symptomatology as measured by the total score on the Childhood Autism Rating Scale (CARS). The clusters could be characterized as showing significant differences: Cluster 1: showed the largest sizes of the genu and splenium of the corpus callosum (CC), the lowest pregnancy order and the lowest frequency of facial dysmorphic features. Cluster 2: showed the largest sizes of the amygdala and hippocampus (HPC), the least abnormal visual response on the CARS, the lowest frequency of epilepsy and the least frequent abnormal psychomotor development during the first year of life. Cluster 3: showed the largest sizes of the caput of the nucleus caudatus (NC), the smallest sizes of the HPC and facial dysmorphic features were always present. Cluster 4: showed the smallest sizes of the genu and splenium of the CC, as well as the amygdala, and caput of the NC, the most abnormal visual response on the CARS, the highest frequency of epilepsy, the highest pregnancy order, abnormal psychomotor development during the first year of life was always present and facial dysmorphic features were always present. This multidisciplinary approach seems to be a promising method for subtyping autism.

Efficient similarity-based data clustering by optimal object to cluster reallocation.

Science.gov (United States)

Rossignol, Mathias; Lagrange, Mathieu; Cont, Arshia

2018-01-01

We present an iterative flat hard clustering algorithm designed to operate on arbitrary similarity matrices, with the only constraint that these matrices be symmetrical. Although functionally very close to kernel k-means, our proposal performs a maximization of average intra-class similarity, instead of a squared distance minimization, in order to remain closer to the semantics of similarities. We show that this approach permits the relaxing of some conditions on usable affinity matrices like semi-positiveness, as well as opening possibilities for computational optimization required for large datasets. Systematic evaluation on a variety of data sets shows that compared with kernel k-means and the spectral clustering methods, the proposed approach gives equivalent or better performance, while running much faster. Most notably, it significantly reduces memory access, which makes it a good choice for large data collections. Material enabling the reproducibility of the results is made available online.

Persistent Spatial Clusters of Prescribed Antimicrobials among Danish Pig Farms - A Register-Based Study

DEFF Research Database (Denmark)

Fertner, Mette Ely; Sanchez, Javier; Boklund, Anette

2015-01-01

The emergence of pathogens resistant to antimicrobials has prompted political initiatives targeting a reduction in the use of veterinary antimicrobials in Denmark, especially for pigs. This study elucidates the tendency of pig farms with a significantly higher antimicrobial use to remain...... in clusters in certain geographical regions of Denmark. Animal Daily Doses/100 pigs/day were calculated for all three age groups of pigs (weaners, finishers and sows) for each quarter during 2012-13 in 6,143 commercial indoor pig producing farms. The data were split into four time periods of six months....... Repeated spatial cluster analyses were performed to identify persistent clusters, i.e. areas included in a significant cluster throughout all four time periods. Antimicrobials prescribed for weaners did not result in any persistent clusters. In contrast, antimicrobial use in finishers clustered...

Dynamic multifactor clustering of financial networks

Science.gov (United States)

Ross, Gordon J.

2014-02-01

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

Exact WKB analysis and cluster algebras

International Nuclear Information System (INIS)

Iwaki, Kohei; Nakanishi, Tomoki

2014-01-01

We develop the mutation theory in the exact WKB analysis using the framework of cluster algebras. Under a continuous deformation of the potential of the Schrödinger equation on a compact Riemann surface, the Stokes graph may change the topology. We call this phenomenon the mutation of Stokes graphs. Along the mutation of Stokes graphs, the Voros symbols, which are monodromy data of the equation, also mutate due to the Stokes phenomenon. We show that the Voros symbols mutate as variables of a cluster algebra with surface realization. As an application, we obtain the identities of Stokes automorphisms associated with periods of cluster algebras. The paper also includes an extensive introduction of the exact WKB analysis and the surface realization of cluster algebras for nonexperts. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Cluster algebras in mathematical physics’. (paper)

The old open cluster Melotte 66

International Nuclear Information System (INIS)

Hawarden, T.G.

1976-01-01

Photoelectric and photographic photometry of the open cluster Melotte 66 is presented. The colour-magnitude (CM) diagram shows most of the characteristics of an old cluster. The giant branch is broad with its blue edge populated preferentially by stars from the outer parts of the cluster. There is no detectable horizontal subgiant sequence. The main sequence turn-off colour, two-colour diagram and the colour difference between the turn-off and the subgiants are used to estimate the age and composition. Melotte 66 appears to have reddening E(B-V) = 0sup(m).17 and ultraviolet excess delta(U-B) approximately 0sup(m).1. The cluster is probably between 6 and 7 x 10 9 yr old. A distance modulus (m-M) 0 =12sup(m).4 is derived, which implies that the cluster lies about 750 pc from the galactic plane. (author)

CTEx Beowulf cluster for MCNP performance

International Nuclear Information System (INIS)

Gonzaga, Roberto N.; Amorim, Aneuri S. de; Balthar, Mario Cesar V.

2011-01-01

This work is an introduction to the CTEx Nuclear Defense Department's Beowulf Cluster. Building a Beowulf Cluster is a complex learning process that greatly depends upon your hardware and software requirements. The feasibility and efficiency of performing MCNP5 calculations with a small, heterogeneous computing cluster built in Red Hat's Fedora Linux operating system personal computers (PC) are explored. The performance increases that may be expected with such clusters are estimated for cases that typify general radiation transport calculations. Our results show that the speed increase from additional slave PCs is nearly linear up to 10 processors. The pre compiled parallel binary version of MCNP uses the Message-Passing Interface (MPI) protocol. The use of this pre compiled parallel version of MCNP5 with the MPI protocol on a small, heterogeneous computing cluster built from Red Hat's Fedora Linux operating system PCs is the subject of this work. (author)

Electronic shell structure in multiply charged silver clusters

International Nuclear Information System (INIS)

Kandler, O.; Athanassenas, K.; Echt, O.; Kreisle, D.; Leisner, T.; Recknagel, E.

1991-01-01

Silver clusters are generated by standard laser vaporization technique and ionized via multiphoton ionization. Time-of-flight mass spectrometry reveals singly, doubly and triply charged clusters, Ag n z+ (z=1, 2, 3). The spectra show, for all charge states, intensity variations, indicating enhanced stabilities for cluster sizes with closed electronic configurations in accord with the spherical jellium model. (orig.)

On clusters and clustering from atoms to fractals

CERN Document Server

Reynolds, PJ

1993-01-01

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

Anisotropy: an estimable alloy in the study of point defect clustering

International Nuclear Information System (INIS)

Weinberg, C.; Quere, Y.

1986-09-01

Crystal anisotropy forces vacancies and interstitials, in irradiated uranium, to cluster into two distinct families of dislocation loops. A consequence of this fortunate circumstance, the irradiation ''growth'', is easily observed by length measurements performed under neutron irradiation at ≅ 30-40 K. These experiments are analysed in a way which allows to detect two distinct modes of clustering for interstitials and vacancies. The same analysis is applied to previous experiments performed at ≅ 4K [1-2

Searches for 3.5 keV Absorption Features in Cluster AGN Spectra

Science.gov (United States)

Conlon, Joseph P.

2018-06-01

We investigate possible evidence for a spectral dip around 3.5 keV in central cluster AGNs, motivated by previous results for archival Chandra observations of the Perseus cluster and the general interest in novel spectral features around 3.5 keV that may arise from dark matter physics. We use two deep Chandra observations of the Perseus and Virgo clusters that have recently been made public. In both cases, mild improvements in the fit (Δχ2 = 4.2 and Δχ2 = 2.5) are found by including such a dip at 3.5 keV into the spectrum. A comparable result (Δχ2 = 6.5) is found re-analysing archival on-axis Chandra ACIS-S observations of the centre of the Perseus cluster.