Sample records for 1842676957299765latent class cluster

  1. 1842676957299765Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities

    Meghani Salimah


    Full Text Available Abstract Background Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction. Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals' preferences for health states given similar treatments and clinical risks. Methods Using latent class mixture model (LCA, we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups. Results The sample (N = 244 included men with prostate cancer (n = 188 and men at-risk for disease (n = 56. The sample was predominantly white (77%, with mean age of 60 years (SD ± 9.5. Most (85.9% were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC, substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of < .001. The three identified clusters were named high-traders (n = 31, low-traders (n = 116, and no-traders (n = 97. High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment. Low-traders were less likely to trade survival time and accepted risks of treatment. The no-traders were likely to make no trade-offs in any direction favouring the status quo. There was significant difference among the clusters in the importance of sexual activity (Pearson's χ2 = 16.55, P = 0.002; Goodman and Kruskal tau = 0.039, P < 0.001. In

  2. Context-sensitive intra-class clustering

    Yu, Yingwei


    This paper describes a new semi-supervised learning algorithm for intra-class clustering (ICC). ICC partitions each class into sub-classes in order to minimize overlap across clusters from different classes. This is achieved by allowing partitioning of a certain class to be assisted by data points from other classes in a context-dependent fashion. The result is that overlap across sub-classes (both within- and across class) is greatly reduced. ICC is particularly useful when combined with algorithms that assume that each class has a unimodal Gaussian distribution (e.g., Linear Discriminant Analysis (LDA), quadratic classifiers), an assumption that is not always true in many real-world situations. ICC can help partition non-Gaussian, multimodal distributions to overcome such a problem. In this sense, ICC works as a preprocessor. Experiments with our ICC algorithm on synthetic data sets and real-world data sets indicated that it can significantly improve the performance of LDA and quadratic classifiers. We expect our approach to be applicable to a broader class of pattern recognition problems where class-conditional densities are significantly non-Gaussian or multi-modal. © 2013 Elsevier Ltd. All rights reserved.

  3. Mutation classes of finite type cluster algebras with principal coefficients

    Seven, Ahmet


    In this paper, we prove Conjecture 4.8 of "Cluster algebras IV" by S. Fomin and A. Zelevinsky, stating that the mutation classes of rectangular matrices associated with cluster algebras of finite type are precisely those classes which are finite.

  4. Arabic web pages clustering and annotation using semantic class features

    Hanan M. Alghamdi


    Full Text Available To effectively manage the great amount of data on Arabic web pages and to enable the classification of relevant information are very important research problems. Studies on sentiment text mining have been very limited in the Arabic language because they need to involve deep semantic processing. Therefore, in this paper, we aim to retrieve machine-understandable data with the help of a Web content mining technique to detect covert knowledge within these data. We propose an approach to achieve clustering with semantic similarities. This approach comprises integrating k-means document clustering with semantic feature extraction and document vectorization to group Arabic web pages according to semantic similarities and then show the semantic annotation. The document vectorization helps to transform text documents into a semantic class probability distribution or semantic class density. To reach semantic similarities, the approach extracts the semantic class features and integrates them into the similarity weighting schema. The quality of the clustering result has evaluated the use of the purity and the mean intra-cluster distance (MICD evaluation measures. We have evaluated the proposed approach on a set of common Arabic news web pages. We have acquired favorable clustering results that are effective in minimizing the MICD, expanding the purity and lowering the runtime.

  5. Investigating Subtypes of Child Development: A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

    DiStefano, Christine; Kamphaus, R. W.


    Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures…

  6. Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis

    Rita Ismayilova; Emilya Nasirova; Colleen Hanou; Rivard, Robert G.; Bautista, Christian T.


    Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent class cluster (LCC) analysis on symptoms to determine clusters of brucellosis cases. A total of 454 cases reported between July 2011 and July 2013 were analyzed. LCC identified a two-cluster mo...

  7. Parallel unstructured AMR and gigabit networking for Beowulf-class clusters

    Norton, C. D.; Cwik, T. A.


    The impact of gigabit networking with Myrinet 2000 hardware and MPICH-GM software on a 2-way SMP Beowulf-class cluster for parallel unstructured adaptive mesh refinement using the PYRAMID library is described.

  8. A Beowulf-class computing cluster for the Monte Carlo production of the LHCb experiment

    Avoni, G; Bertin, A; Bruschi, M; Capponi, M; Carbone, A; Collamati, A; De Castro, S; Fabbri, Franco Luigi; Faccioli, P; Galli, D; Giacobbe, B; Lax, I; Marconi, U; Massa, I; Piccinini, M; Poli, M; Semprini-Cesari, N; Spighi, R; Vagnoni, V M; Vecchi, S; Villa, M; Vitale, A; Zoccoli, A


    The computing cluster built at Bologna to provide the LHCb Collaboration with a powerful Monte Carlo production tool is presented. It is a performance oriented Beowulf-class cluster, made of rack mounted commodity components, designed to minimize operational support requirements and to provide full and continuous availability of the computing resources. In this paper we describe the architecture of the cluster, and discuss the technical solutions adopted for each specialized sub-system.

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

    Landfors Mattias


    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

  10. Mini-Cluster on Teaching about the 1%, the Rich, the Upper Class, the Ruling Class

    Marcial González


    Full Text Available Marcial González, Greg Meyerson, and Richard Ohmann worked together on these three articles. We spoke on a panel organized by the Radical Caucus of the Modern Language Association for MLA's 2014 convention. Our topic was “Teaching About the 1%, the Rich, the Upper Class, the Ruling Class . . . . " As that list suggests, we meant to explore common ways of conceptualizing the wealthiest people in the U. S., and in capitalist society generally. We argued that the best way is to see them structurally, as integral to a class system. And we sketched out ways for teachers to do that.

  11. A dense micro-cluster of Class 0 protostars in NGC 2264 D-MM1

    Teixeira, Paula S; Lada, Charles J


    We present sensitive and high angular resolution (~1") 1.3 mm continuum observations of the dusty core D-MM1 in the Spokes cluster in NGC 2264 using the Submillimeter Array. A dense micro-cluster of seven Class 0 sources was detected in a 20" x 20" region with masses between 0.4 to 1.2 solar masses and deconvolved sizes of about 600 AU. We interpret the 1.3 mm emission as arising from the envelopes of the Class 0 protostellar sources. The mean separation of the 11 known sources (SMA Class 0 and previously known infrared sources) within D-MM1 is considerably smaller than the characteristic spacing between sources in the larger Spokes cluster and is consistent with hierarchical thermal fragmentation of the dense molecular gas in this region.

  12. Cyclist–motorist crash patterns in Denmark: A latent class clustering approach

    Kaplan, Sigal; Prato, Carlo Giacomo


    Objective: The current study aimed at uncovering patterns of cyclist–motorist crashes in Denmark and investigating their prevalence and severity. The importance of implementing clustering techniques for providing a holistic overview of vulnerable road users’ crash patterns derives from the need...... to prioritize safety issues and to devise efficient preventive measures. Method: The current study focused on cyclist–motorist crashes that occurred in Denmark during the period between 2007 and 2011. To uncover crash patterns, the current analysis applied latent class clustering, an unsupervised probabilistic...... clustering approach that relies on the statistical concept of likelihood and allows partial overlap across clusters. Results: The analysis yielded 13 distinguishable cyclist–motorist latent classes. Specific crash patterns for urban and rural areas were revealed. Prevalent features that allowed...

  13. Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis

    Rita Ismayilova


    Full Text Available Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent class cluster (LCC analysis on symptoms to determine clusters of brucellosis cases. A total of 454 cases reported between July 2011 and July 2013 were analyzed. LCC identified a two-cluster model and the Vuong-Lo-Mendell-Rubin likelihood ratio supported the cluster model. Brucellosis cases in the second cluster (19% reported higher percentages of poly-lymphadenopathy, hepatomegaly, arthritis, myositis, and neuritis and changes in liver function tests compared to cases of the first cluster. Patients in the second cluster had a severe brucellosis disease course and were associated with longer delay in seeking medical attention. Moreover, most of them were from Beylagan, a region focused on sheep and goat livestock production in south-central Azerbaijan. Patients in cluster 2 accounted for one-quarter of brucellosis cases and had a more severe clinical presentation. Delay in seeking medical care may explain severe illness. Future work needs to determine the factors that influence brucellosis case seeking and identify brucellosis species, particularly among cases from Beylagan.

  14. Structural variation of the ribosomal gene cluster within the class Insecta

    Mukha, D.V.; Sidorenko, A.P.; Lazebnaya, I.V. [Vavilov Institute of General Genetics, Moscow (Russian Federation)] [and others


    General estimation of ribosomal DNA variation within the class Insecta is presented. It is shown that, using blot-hybridization, one can detect differences in the structure of the ribosomal gene cluster not only between genera within an order, but also between species within a genera, including sibling species. Structure of the ribosomal gene cluster of the Coccinellidae family (ladybirds) is analyzed. It is shown that cloned highly conservative regions of ribosomal DNA of Tetrahymena pyriformis can be used as probes for analyzing ribosomal genes in insects. 24 refs., 4 figs.

  15. Fatal and serious road crashes involving young New Zealand drivers: a latent class clustering approach

    Weiss, Harold B.; Kaplan, Sigal; Prato, Carlo Giacomo


    classification that revealed how the identified clusters contain mostly crashes of a particular class and all the crashes of that class. The results raised three major safety concerns for young drivers that should be addressed: (1) reckless driving and traffic law violations; (2) inattention, error, and hazard......The over-representation of young drivers in road crashes remains an important concern worldwide. Cluster analysis has been applied to young driver sub-groups, but its application by analysing crash occurrence is just emerging. We present a classification analysis that advances the field through...... a holistic overview of crash patterns useful for designing youth-targeted road safety programmes. We compiled a database of 8644 New Zealand crashes from 2002 to 2011 involving at least one 15–24-year-old driver and a fatal or serious injury for at least one road user. We considered crash location...

  16. Global Clustering Quality Coefficient Assessing the Efficiency of PCA Class Assignment

    Mirela Praisler


    Full Text Available An essential factor influencing the efficiency of the predictive models built with principal component analysis (PCA is the quality of the data clustering revealed by the score plots. The sensitivity and selectivity of the class assignment are strongly influenced by the relative position of the clusters and by their dispersion. We are proposing a set of indicators inspired from analytical geometry that may be used for an objective quantitative assessment of the data clustering quality as well as a global clustering quality coefficient (GCQC that is a measure of the overall predictive power of the PCA models. The use of these indicators for evaluating the efficiency of the PCA class assignment is illustrated by a comparative study performed for the identification of the preprocessing function that is generating the most efficient PCA system screening for amphetamines based on their GC-FTIR spectra. The GCQC ranking of the tested feature weights is explained based on estimated density distributions and validated by using quadratic discriminant analysis (QDA.

  17. A class of spherical, truncated, anisotropic models for application to globular clusters

    de Vita, Ruggero; Bertin, Giuseppe; Zocchi, Alice


    Recently, a class of non-truncated, radially anisotropic models (the so-called f(ν)-models), originally constructed in the context of violent relaxation and modelling of elliptical galaxies, has been found to possess interesting qualities in relation to observed and simulated globular clusters. In view of new applications to globular clusters, we improve this class of models along two directions. To make them more suitable for the description of small stellar systems hosted by galaxies, we introduce a "tidal" truncation by means of a procedure that guarantees full continuity of the distribution function. The new fT(ν)-models are shown to provide a better fit to the observed photometric and spectroscopic profiles for a sample of 13 globular clusters studied earlier by means of non-truncated models; interestingly, the best-fit models also perform better with respect to the radial-orbit instability. Then, we design a flexible but simple two-component family of truncated models to study the separate issues of mass segregation and multiple populations. We do not aim at a fully realistic description of globular clusters to compete with the description currently obtained by means of dedicated simulations. The goal here is to try to identify the simplest models, that is, those with the smallest number of free parameters, but still have the capacity to provide a reasonable description for clusters that are evidently beyond the reach of one-component models. With this tool, we aim at identifying the key factors that characterize mass segregation or the presence of multiple populations. To reduce the relevant parameter space, we formulate a few physical arguments based on recent observations and simulations. A first application to two well-studied globular clusters is briefly described and discussed.

  18. Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks.

    de Oña, Juan; López, Griselda; Mujalli, Randa; Calvo, Francisco J


    One of the principal objectives of traffic accident analyses is to identify key factors that affect the severity of an accident. However, with the presence of heterogeneity in the raw data used, the analysis of traffic accidents becomes difficult. In this paper, Latent Class Cluster (LCC) is used as a preliminary tool for segmentation of 3229 accidents on rural highways in Granada (Spain) between 2005 and 2008. Next, Bayesian Networks (BNs) are used to identify the main factors involved in accident severity for both, the entire database (EDB) and the clusters previously obtained by LCC. The results of these cluster-based analyses are compared with the results of a full-data analysis. The results show that the combined use of both techniques is very interesting as it reveals further information that would not have been obtained without prior segmentation of the data. BN inference is used to obtain the variables that best identify accidents with killed or seriously injured. Accident type and sight distance have been identify in all the cases analysed; other variables such as time, occupant involved or age are identified in EDB and only in one cluster; whereas variables vehicles involved, number of injuries, atmospheric factors, pavement markings and pavement width are identified only in one cluster.

  19. Incremental multi-class semi-supervised clustering regularized by Kalman filtering.

    Mehrkanoon, Siamak; Agudelo, Oscar Mauricio; Suykens, Johan A K


    This paper introduces an on-line semi-supervised learning algorithm formulated as a regularized kernel spectral clustering (KSC) approach. We consider the case where new data arrive sequentially but only a small fraction of it is labeled. The available labeled data act as prototypes and help to improve the performance of the algorithm to estimate the labels of the unlabeled data points. We adopt a recently proposed multi-class semi-supervised KSC based algorithm (MSS-KSC) and make it applicable for on-line data clustering. Given a few user-labeled data points the initial model is learned and then the class membership of the remaining data points in the current and subsequent time instants are estimated and propagated in an on-line fashion. The update of the memberships is carried out mainly using the out-of-sample extension property of the model. Initially the algorithm is tested on computer-generated data sets, then we show that video segmentation can be cast as a semi-supervised learning problem. Furthermore we show how the tracking capabilities of the Kalman filter can be used to provide the labels of objects in motion and thus regularizing the solution obtained by the MSS-KSC algorithm. In the experiments, we demonstrate the performance of the proposed method on synthetic data sets and real-life videos where the clusters evolve in a smooth fashion over time.

  20. Clustering Educational Digital Library Usage Data: A Comparison of Latent Class Analysis and K-Means Algorithms

    Xu, Beijie; Recker, Mimi; Qi, Xiaojun; Flann, Nicholas; Ye, Lei


    This article examines clustering as an educational data mining method. In particular, two clustering algorithms, the widely used K-means and the model-based Latent Class Analysis, are compared, using usage data from an educational digital library service, the Instructional Architect ( Using a multi-faceted approach and multiple data…

  1. Organo-Zintl Clusters [P7R4]: A New Class of Superalkalis.

    Giri, Santanab; Reddy, G N; Jena, Puru


    Zintl ions composed of Group 13, 14, and 15 elements are multiply charged cluster anions that form the building blocks of the Zintl phase. Superalkalis, on the other hand, are cationic clusters that mimic the chemistry of the alkali atoms. It is, therefore, counterintuitive to expect that Zintl anions can be used as a core to construct superalkalis. In this paper, using density functional theory, we show that this is indeed possible. The results are compared with calculations at the MP2 level of theory. A systematic study of a P7(3-) Zintl core decorated with organic ligands [R = Me, CH2Me, CH(Me)2 and C(Me)3] shows that the ionization energies of some of the P7R4 species are smaller than those of the alkali atoms and hence can be classified as superalkalis. This opens the door to the design and synthesis of a new class of superalkali moieties apart from the traditional ones composed of only inorganic elements.

  2. A conserved cluster of three PRD-class homeobox genes (homeobrain, rx and orthopedia in the Cnidaria and Protostomia

    Mazza Maureen E


    Full Text Available Abstract Background Homeobox genes are a superclass of transcription factors with diverse developmental regulatory functions, which are found in plants, fungi and animals. In animals, several Antennapedia (ANTP-class homeobox genes reside in extremely ancient gene clusters (for example, the Hox, ParaHox, and NKL clusters and the evolution of these clusters has been implicated in the morphological diversification of animal bodyplans. By contrast, similarly ancient gene clusters have not been reported among the other classes of homeobox genes (that is, the LIM, POU, PRD and SIX classes. Results Using a combination of in silico queries and phylogenetic analyses, we found that a cluster of three PRD-class homeobox genes (Homeobrain (hbn, Rax (rx and Orthopedia (otp is present in cnidarians, insects and mollusks (a partial cluster comprising hbn and rx is present in the placozoan Trichoplax adhaerens. We failed to identify this 'HRO' cluster in deuterostomes; in fact, the Homeobrain gene appears to be missing from the chordate genomes we examined, although it is present in hemichordates and echinoderms. To illuminate the ancestral organization and function of this ancient cluster, we mapped the constituent genes against the assembled genome of a model cnidarian, the sea anemone Nematostella vectensis, and characterized their spatiotemporal expression using in situ hybridization. In N. vectensis, these genes reside in a span of 33 kb with the same gene order as previously reported in insects. Comparisons of genomic sequences and expressed sequence tags revealed the presence of alternative transcripts of Nv-otp and two highly unusual protein-coding polymorphisms in the terminal helix of the Nv-rx homeodomain. A population genetic survey revealed the Rx polymorphisms to be widespread in natural populations. During larval development, all three genes are expressed in the ectoderm, in non-overlapping territories along the oral-aboral axis, with distinct

  3. Impacts of fast food and food retail environment on overweight and obesity in China: a multilevel latent class cluster approach

    Zhang XiaoYong, Xiaoyong; Lans, van der I.A.; Dagevos, H.


    Objective To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. Design A multilevel latent class cluster model was applied to

  4. Transition-Metal Planar Boron Clusters: a New Class of Aromatic Compounds with High Coordination

    Wang, Lai-Sheng


    Photoelectron spectroscopy in combination with computational studies over the past decade has shown that boron clusters possess planar or quasi-planar structures, in contrast to that of bulk boron, which is dominated by three-dimensional cage-like building blocks. All planar or quasi-planar boron clusters are observed to consist of a monocyclic circumference with one or more interior atoms. The propensity for planarity has been found to be due to both σ and π electron delocalization throughout the molecular plane, giving rise to concepts of σ and π double aromaticity. We have found further that the central boron atoms can be substituted by transition metal atoms to form a new class of aromatic compounds, which consist of a central metal atom and a monocyclic boron ring (M B_n). Eight-, nine-, and ten-membered rings of boron have been observed, giving rise to octa-, ennea-, and deca-coordinated aromatic transition metal compounds [1-3]. References: [1] ``Aromatic Metal-Centered Monocyclic Boron Rings: Co B_9^- and Ru B_9^-" (Constantin Romanescu, Timur R. Galeev, Wei-Li Li, A. I. Boldyrev, and L. S. Wang), Angew. Chem. Int. Ed. {50}, 9334-9337 (2011). [2] ``Transition-Metal-Centered Nine-Membered Boron Rings: M B_9 and M B_9^- (M = Rh, Ir)" (Wei-Li Li, Constantin Romanescu, Timur R. Galeev, Zachary Piazza, A. I. Boldyrev, and L. S. Wang), J. Am. Chem. Soc. {134}, 165-168 (2012). [3] ``Observation of the Highest Coordination Number in Planar Species: Decacoordinated Ta B10^- and Nb B_9^- Anions" (Timur R. Galeev, Constantin Romanescu, Wei-Li Li, L. S. Wang, and A. I. Boldyrev), Angew. Chem. Int. Ed. {51}, 2101-2105 (2012).

  5. Three classes of plasmid (47-63 kb) carry the type B neurotoxin gene cluster of group II Clostridium botulinum.

    Carter, Andrew T; Austin, John W; Weedmark, Kelly A; Corbett, Cindi; Peck, Michael W


    Pulsed-field gel electrophoresis and DNA sequence analysis of 26 strains of Group II (nonproteolytic) Clostridium botulinum type B4 showed that 23 strains carried their neurotoxin gene cluster on a 47-63 kb plasmid (three strains lacked any hybridization signal for the neurotoxin gene, presumably having lost their plasmid). Unexpectedly, no neurotoxin genes were found on the chromosome. This apparent constraint on neurotoxin gene transfer to the chromosome stands in marked contrast to Group I C. botulinum, in which neurotoxin gene clusters are routinely found in both locations. The three main classes of type B4 plasmid identified in this study shared different regions of homology, but were unrelated to any Group I or Group III plasmid. An important evolutionary aspect firmly links plasmid class to geographical origin, with one class apparently dominant in marine environments, whereas a second class is dominant in European terrestrial environments. A third class of plasmid is a hybrid between the other two other classes, providing evidence for contact between these seemingly geographically separated populations. Mobility via conjugation has been previously demonstrated for the type B4 plasmid of strain Eklund 17B, and similar genes associated with conjugation are present in all type B4 plasmids now described. A plasmid toxin-antitoxin system pemI gene located close to the neurotoxin gene cluster and conserved in each type B4 plasmid class may be important in understanding the mechanism which regulates this unique and unexpected bias toward plasmid-borne neurotoxin genes in Group II C. botulinum type B4.

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

    Jarman Andrew P


    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.

  7. Genetic Algorithms Applied to Multi-Class Clustering for Gene Expression Data

    Haiyan Pan; Jun Zhu; Danfu Han


    A hybrid GA (genetic algorithm)-based clustering (HGACLUS) schema, combining merits of the Simulated Annealing, was described for finding an optimal or near-optimal set of medoids. This schema maximized the clustering success by achieving internal cluster cohesion and external cluster isolation. The performance of HGACLUS and other methods was compared by using simulated data and open microarray gene-expression datasets. HGACLUS was generally found to be more accurate and robust than other methods discussed in this paper by the exact validation strategy and the explicit cluster number.

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

    Simpson, T. Ian; Armstrong, J. Douglas; Jarman, Andrew P.


    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

  9. Genomic sequence analysis of the 238-kb swine segment with a cluster of TRIM and olfactory receptor genes located, but with no class I genes, at the distal end of the SLA class I region.

    Ando, Asako; Shigenari, Atsuko; Kulski, Jerzy K; Renard, Christine; Chardon, Patrick; Shiina, Takashi; Inoko, Hidetoshi


    Continuous genomic sequence has been previously determined for the swine leukocyte antigen (SLA) class I region from the TNF gene cluster at the border between the major histocompatibility complex (MHC) class III and class I regions to the UBD gene at the telomeric end of the classical class I gene cluster (SLA-1 to SLA-5, SLA-9, SLA-11). To complete the genomic sequence of the entire SLA class I genomic region, we have analyzed the genomic sequences of two BAC clones carrying a continuous 237,633-bp-long segment spanning from the TRIM15 gene to the UBD gene located on the telomeric side of the classical SLA class I gene cluster. Fifteen non-class I genes, including the zinc finger and the tripartite motif (TRIM) ring-finger-related family genes and olfactory receptor genes, were identified in the 238-kilobase (kb) segment, and their location in the segment was similar to their apparent human homologs. In contrast, a human segment (alpha block) spanning about 375 kb from the gene ETF1P1 and from the HLA-J to HLA-F genes was absent from the 238-kb swine segment. We conclude that the gene organization of the MHC non-class I genes located in the telomeric side of the classical SLA class I gene cluster is remarkably similar between the swine and the human segments, although the swine lacks a 375-kb segment corresponding to the human alpha block.


    D. A. Viattchenin


    Full Text Available A method for constructing a subset of labeled objects which is used in a heuristic algorithm of possible  clusterization with partial  training is proposed in the  paper.  The  method  is  based  on  data preprocessing by the heuristic algorithm of possible clusterization using a transitive closure of a fuzzy tolerance. Method efficiency is demonstrated by way of an illustrative example.

  11. Interactive exploration of uncertainty in fuzzy classifications by isosurface visualization of class clusters

    Lucieer, A.; Veen, L.E.


    Uncertainty and vagueness are important concepts when dealing with transition zones between vegetation communities or land-cover classes. In this study, classification uncertainty is quantified by applying a supervised fuzzy classification algorithm. New visualization techniques are proposed and pre

  12. Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering



    Full Text Available Transferring the brain computer interface (BCI from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG signal reasons us to look toward evolutionary algorithm (EA. Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA and particle swarm optimization (PSO based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD and desynchronization (ERD feature vector is formed.

  13. Semi Supervised Weighted K-Means Clustering for Multi Class Data Classification

    Vijaya Geeta Dharmavaram


    Full Text Available Supervised Learning techniques require large number of labeled examples to train a classifier model. Research on Semi Supervised Learning is motivated by the availability of unlabeled examples in abundance even in domains with limited number of labeled examples. In such domains semi supervised classifier uses the results of clustering for classifier development since clustering does not rely only on labeled examples as it groups the objects based on their similarities. In this paper, the authors propose a new algorithm for semi supervised classification namely Semi Supervised Weighted K-Means (SSWKM. In this algorithm, the authors suggest the usage of weighted Euclidean distance metric designed as per the purpose of clustering for estimating the proximity between a pair of points and used it for building semi supervised classifier. The authors propose a new approach for estimating the weights of features by appropriately adopting the results of multiple discriminant analysis. The proposed method was then tested on benchmark datasets from UCI repository with varied percentage of labeled examples and found to be consistent and promising.

  14. Clustering and combining pattern of metabolic syndrome components among Iranian population with latent class analysis

    Abbasi-Ghahramanloo, Abbas; Soltani, Sepideh; Gholami, Ali; Erfani, Mohammadreza; Yosaee, Somayeh


    Background: Metabolic syndrome (MetS), a combination of coronary heart disease and diabetes mellitus risk factor, refer to one of the most challenging public health issues in worldwide. The aim of this study was to identify the subgroups of participants in a study on the basis of MetS components. Methods: The cross-sectional study took place in the districts related to Tehran University of Medical Sciences. The randomly selected sample consists of 415 subjects. All participants provided written informed consent. Latent class analysis was performed to achieve the study’s objectives. Analyses were conducted by using proc LCA in SAS 9.2 software. Results: Except systolic and diastolic blood pressure, the prevalence of all MetS components is common in female than male. Four latent classes were identified: (a) non MetS, (b) low risk, (c) high risk, and (d) MetS. Notably, 24.2% and 1.3% of the subjects were in the high risk and MetS classes respectively. Conclusion: Most of the study participants were identified as high risk and MetS. Design and implementation of preventive interventions for this segment of the population are necessary. PMID:28210610

  15. Interaction of Fanaroff-Riley class II jets with a magnetised intra-cluster medium

    Huarte-Espinosa, Martín; Alexander, Paul


    We present 3-D MHD and synthetic numerical simulations to follow the evolution of randomly magnetized intra-cluster medium plasma under the effects of powerful, light, hypersonic and bipolar jets. We prescribe the cluster magnetic field (CMF) as a Gaussian random field with power law energy spectrum tuned to the expectation for Kolmogorov turbulence. We investigate the power of jets and the viewing angle used for the synthetic Rotation Measure (RM) observations. We find the model radio sources introduce and amplify fluctuations on the RM statistical properties; the average RM and the RM standard deviation are increased by the action of the jets. This may lead to overestimations of the CMFs' strength up to 70%. The effect correlates with the jet power. Jets distort and amplify CMFs especially near the edges of the lobes and the jets' heads. Thus the RM structure functions are flattened at scales comparable to the source size. Jet-produced RM enhancements depend on the orientation of the jet axis to the line of...

  16. Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes

    Cannistraci, Carlo


    Motivation: Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. Methods: \\'Minimum Curvilinearity\\' (MC) is a principle that-for small datasets-suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Results: Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. Conclusion: MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. © The Author(s) 2010. Published by Oxford University Press.

  17. Interaction of Fanaroff-Riley class II radio jets with a randomly magnetised intra-cluster medium

    Huarte-Espinosa, Martín; Alexander, Paul


    A combination of three-dimensional (3D) magnetohydrodynamics (MHD) and synthetic numerical simulations are presented to follow the evolution of a randomly magnetised plasma that models the intra-cluster medium (ICM), under the isolated effects of powerful, light, hypersonic and bipolar Fanaroff-Riley class II (FR II) jets. We prescribe the cluster magnetic field (CMF) as a Gaussian random field with a Kolmogorov-like energy spectrum. Both the power of the jets and the viewing angle that is used for the synthetic Rotation Measure (RM) observations are investigated. We find the model radio sources introduce and amplify fluctuations on the RM statistical properties which we analyse as a function of time as well as the viewing angle. The average RM and the RM standard deviation are increased by the action of the jets. Energetics, RM statistics and magnetic power spectral analysis consistently show that the effects also correlate with the jets' power, and that the lightest, fastest jets produce the strongest chang...

  18. Stellar variability in open clusters. I. A new class of variable stars in NGC 3766

    Mowlavi, N; Saesen, S; Eyer, L


    Aims. We analyze the population of periodic variable stars in the open cluster NGC 3766 based on a 7-year multi-band monitoring campaign conducted on the 1.2 m Swiss Euler telescope at La Silla, Chili. Methods. The data reduction, light curve cleaning and period search procedures, combined with the long observation time line, allow us to detect variability amplitudes down to the milli-magnitude level. The variability properties are complemented with the positions in the color-magnitude and color-color diagrams to classify periodic variable stars into distinct variability types. Results. We find a large population (36 stars) of new variable stars between the red edge of slowly pulsating B (SPB) stars and the blue edge of delta Sct stars, a region in the Hertzsprung-Russell (HR) diagram where no pulsation is predicted to occur based on standard stellar models. The bulk of their periods ranges from 0.1 to 0.7 d, with amplitudes between 1 and 4 mmag for the majority of them. About 20% of stars in that region of t...


    孟海东; 唐旋


    传统的聚类算法在考虑类与类之间的连通性特征和近似性特征上往往顾此失彼.首先给出类边界点和类轮廓的基本定义以及寻求方法,然后基于类间连通性特征和近似性特征的综合考虑,拟定一些类间相似性度量标准和方法,最后提出一种基于类轮廓的层次聚类算法.该算法能够有效处理任意形状的簇,且能够区分孤立点和噪声数据.通过对图像数据集和Iris标准数据集的聚类分析,验证了该算法的可行性和有效性.%Traditional clustering algorithms are often incapable of roundly considering the connectivity and similarity characteristics among classes. The thesis firstly presents the fundamental definition of class boundary point and class profile; secondly, with comprehensive consideration based on connectivity characteristics and similarity characteristics among classes, defines some standards and methods for inter class similarity measurement; thirdly, proposes a class-profile-based hierarchical clustering algorithm, which is able to effectively process arbitrary shaped clusters and distinguish isolated points from noise data. The feasibility and effectiveness of the algorithm is validated through clustering analysis on image data sets and Iris standard data sets.

  20. Natural product proteomining, a quantitative proteomics platform, allows rapid discovery of biosynthetic gene clusters for different classes of natural products.

    Gubbens, Jacob; Zhu, Hua; Girard, Geneviève; Song, Lijiang; Florea, Bogdan I; Aston, Philip; Ichinose, Koji; Filippov, Dmitri V; Choi, Young H; Overkleeft, Herman S; Challis, Gregory L; van Wezel, Gilles P


    Information on gene clusters for natural product biosynthesis is accumulating rapidly because of the current boom of available genome sequencing data. However, linking a natural product to a specific gene cluster remains challenging. Here, we present a widely applicable strategy for the identification of gene clusters for specific natural products, which we name natural product proteomining. The method is based on using fluctuating growth conditions that ensure differential biosynthesis of the bioactivity of interest. Subsequent combination of metabolomics and quantitative proteomics establishes correlations between abundance of natural products and concomitant changes in the protein pool, which allows identification of the relevant biosynthetic gene cluster. We used this approach to elucidate gene clusters for different natural products in Bacillus and Streptomyces, including a novel juglomycin-type antibiotic. Natural product proteomining does not require prior knowledge of the gene cluster or secondary metabolite and therefore represents a general strategy for identification of all types of gene clusters.

  1. Differences in the expressed HLA class I alleles effect the differential clustering of HIV type 1-specific T cell responses in infected Chinese and Caucasians

    Yu,XG; Addo,MM; Perkins,BA; Wej,FL; Rathod,A; Geer,SC; Parta,M; Cohen,D; Stone,DR; Russell,CJ; Tanzi,G; Mei,S; Wureel,AG; Frahm,N; Lichterfeld,M; Heath,L; Mullins,JI; Marincola,F; Goulder,PJR; Brander,C; Allen,T; Cao,YZ; Walker,BD; Altfeld,M


    China is a region of the world with a rapidly spreading HIV-1 epidemic. Studies providing insights into HIV-1 pathogenesis in infected Chinese are urgently needed to support the design and testing of an effective HIV-1 vaccine for this population. HIV-1-specific T cell responses were characterized in 32 HIV-1-infected individuals of Chinese origin and compared to 34 infected caucasians using 410 overlapping peptides spanning the entire HIV-1 clade B consensus sequence in an IFN-gamma ELISpot assay. All HIV-1 proteins were targeted with similar frequency in both populations and all study subjects recognized at least one overlapping peptide. HIV-1-specific T cell responses clustered in seven different regions of the HIV-1 genome in the Chinese cohort and in nine different regions in the caucasian cohort. The dominant HLA class I alleles expressed in the two populations differed significantly, and differences in epitope clustering pattern were shown to be influenced by differences in class I alleles that restrict immunodominant epitopes. These studies demonstrate that the clustering of HIV-1-specific T cell responses is influenced by the genetic HLA class I background in the study populations. The design and testing of candidate vaccines to fight the rapidly growing HIV-1 epidemic must therefore take the HLA genetics of the population into account as specific regions of the virus can be expected to be differentially targeted in ethnically diverse populations.

  2. Multi-class clustering of cancer subtypes through SVM based ensemble of pareto-optimal solutions for gene marker identification.

    Anirban Mukhopadhyay

    Full Text Available With the advancement of microarray technology, it is now possible to study the expression profiles of thousands of genes across different experimental conditions or tissue samples simultaneously. Microarray cancer datasets, organized as samples versus genes fashion, are being used for classification of tissue samples into benign and malignant or their subtypes. They are also useful for identifying potential gene markers for each cancer subtype, which helps in successful diagnosis of particular cancer types. In this article, we have presented an unsupervised cancer classification technique based on multiobjective genetic clustering of the tissue samples. In this regard, a real-coded encoding of the cluster centers is used and cluster compactness and separation are simultaneously optimized. The resultant set of near-Pareto-optimal solutions contains a number of non-dominated solutions. A novel approach to combine the clustering information possessed by the non-dominated solutions through Support Vector Machine (SVM classifier has been proposed. Final clustering is obtained by consensus among the clusterings yielded by different kernel functions. The performance of the proposed multiobjective clustering method has been compared with that of several other microarray clustering algorithms for three publicly available benchmark cancer datasets. Moreover, statistical significance tests have been conducted to establish the statistical superiority of the proposed clustering method. Furthermore, relevant gene markers have been identified using the clustering result produced by the proposed clustering method and demonstrated visually. Biological relationships among the gene markers are also studied based on gene ontology. The results obtained are found to be promising and can possibly have important impact in the area of unsupervised cancer classification as well as gene marker identification for multiple cancer subtypes.

  3. Stellar variability in open clusters. II. Discovery of a new period-luminosity relation in a class of fast-rotating pulsating stars in NGC 3766

    Mowlavi, N; Semaan, T; Eggenberger, P; Barblan, F; Eyer, L; Ekström, S; Georgy, C


    $Context.$ Pulsating stars are windows to the physics of stars enabling us to see glimpses of their interior. Not all stars pulsate, however. On the main sequence, pulsating stars form an almost continuous sequence in brightness, except for a magnitude range between $\\delta$ Scuti and slowly pulsating B stars. Against all expectations, 36 periodic variables were discovered in 2013 in this luminosity range in the open cluster NGC 3766, the origins of which was a mystery. $Aims.$ We investigate the properties of those new variability class candidates in relation to their stellar rotation rates and stellar multiplicity. $Methods.$ We took multi-epoch spectra over three consecutive nights using ESO's Very Large Telescope. $Results.$ We find that the majority of the new variability class candidates are fast-rotating pulsators that obey a new period-luminosity relation. We argue that the new relation discovered here has a different physical origin to the period-luminosity relations observed for Cepheids. $Conclusio...

  4. Cluster-cluster clustering

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.


    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.

  5. Cluster-cluster clustering

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.


    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.

  6. [Medicen Paris Région: A world-class ''competitiveness cluster'' in the Paris region incorporating a neuroscience ''subcluster''].

    Canet, Emmanuel


    The French public-private partnerships known as "competitive clusters" [pôles de compétitivité (PdC)] are intended to be novel and ambitious engines of regional growth, employment and biomedical innovation. Partly funded by government and local councils, they aim to capitalize on regional expertise by bringing together basic scientists, clinicians, innovative entrepreneurs and local decision-makers around specific themes that have become too costly and complex for any of these actors to tackle alone. Clusters provide the critical mass required both to underpin innovation potential and to authenticate regional claims to international competitiveness. Medicen is a biomedicine and therapeutics cluster comprising 120 partners from four broad "colleges" in the greater Paris region: major industry, small and medium-sized businesses, teaching hospitals/State research bodies, and local councils. Chief among its cooperative R&D projects is the neuroscience subcluster, in which "TransAl" the neurodegenerative disease project, counts Sanofi-Aventis, Servier and the French Atomic Energy Commission [Commissariat à l'Energie Atomique (CEA)] as key partners. One main aim is to develop an experimental model in rhesus monkeys in which a putative cause of Alzheimer's disease, intracerebral accumulation of b-amyloid peptide, is generated by impairing the peptide's clearance. The other aim, in which the nuclear medicine expertise of the CEA will be crucial, is to identify, characterize and validate markers for magnetic resonance and positron emission tomography imaging, and to source biomarkers from cerebrospinal fluid proteomics. A human biological resource centre (DNA and tissue banks) project dedicated to neurological and psychiatric disease should be up and running in 2007. Only through fundamental restructuring of resources on such a large cooperative scale are solutions likely to be found to the major problems of modern medicine, bringing healthcare and regional

  7. Fuzzy Clustering

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


    and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c....... A symptom may belong to more than one class. For instance to the class of very severe disease and to the class of failure of awareness of the own disturbance. The description of language failures by c-mean classification of analyzed factors correspond in many but not in all cases to the traditional......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  8. Can galaxy clusters, type Ia supernovae and cosmic microwave background ruled out a class of modified gravity theories?

    Holanda, R F L


    In this paper we study cosmological signatures of modified gravity theories that can be written as a coupling between a extra scalar field and the electromagnetic part of the usual Lagrangian for the matter fields. In these frameworks all the electromagnetic sector of the theory is affected and variations of fundamental constants, of the cosmic distance duality relation and of the evolution law of the cosmic microwave background radiation (CMB) are expected and are related each other. In order to search these variations we perform jointly analyses with angular diameter distances of galaxy clusters, luminosity distances of type Ia supernovae and $T_{CMB}(z)$ measurements. We obtain tight constraints with no indication of violation of the standard framework.

  9. Stellar variability in open clusters . II. Discovery of a new period-luminosity relation in a class of fast-rotating pulsating stars in NGC 3766

    Mowlavi, N.; Saesen, S.; Semaan, T.; Eggenberger, P.; Barblan, F.; Eyer, L.; Ekström, S.; Georgy, C.


    Context. Pulsating stars are windows to the physics of stars enabling us to see glimpses of their interior. Not all stars pulsate, however. On the main sequence, pulsating stars form an almost continuous sequence in brightness, except for a magnitude range between δ Scuti and slowly pulsating B stars. Against all expectations, 36 periodic variables were discovered in 2013 in this luminosity range in the open cluster NGC 3766, the origins of which was a mystery. Aims: We investigate the properties of those new variability class candidates in relation to their stellar rotation rates and stellar multiplicity. Methods: We took multi-epoch spectra over three consecutive nights using ESO's Very Large Telescope. Results: We find that the majority of the new variability class candidates are fast-rotating pulsators that obey a new period-luminosity relation. We argue that the new relation discovered here has a different physical origin to the period-luminosity relations observed for Cepheids. Conclusions: We anticipate that our discovery will boost the relatively new field of stellar pulsation in fast-rotating stars, will open new doors for asteroseismology, and will potentially offer a new tool to estimate stellar ages or cosmic distances. Based on observations made with the FLAMES instruments on the VLT/UT2 telescope at the Paranal Observatory, Chile, under the program ID 69.A-0123(A).

  10. A cluster randomized-controlled trial of a classroom-based drama workshop program to improve mental health outcomes among immigrant and refugee youth in special classes.

    Cécile Rousseau

    Full Text Available The aim of this cluster randomized trial was to evaluate the effectiveness of a school-based theatre intervention program for immigrant and refugee youth in special classes for improving mental health and academic outcomes. The primary hypothesis was that students in the theatre intervention group would report a greater reduction in impairment from symptoms compared to students in the control and tutoring groups.Special classrooms in five multiethnic high schools were randomly assigned to theater intervention (n = 10, tutoring (n = 10 or control status (n = 9, for a total of 477 participants. Students and teachers were non-blinded to group assignment. The primary outcome was impairment from emotional and behavioural symptoms assessed by the Impact Supplement of the Strengths and Difficulties Questionnaire (SDQ completed by the adolescents. The secondary outcomes were the SDQ global scores (teacher and youth reports, impairment assessed by teachers and school performance. The effect of the interventions was assessed through linear mixed effect models which incorporate the correlation between students in the same class, due to the nature of the randomization of the interventions by classroom.The theatre intervention was not associated with a greater reduction in self-reported impairment and symptoms in youth placed in special class because of learning, emotional and behavioural difficulties than a tutoring intervention or a non-active control group. The estimates of the different models show a non-significant decrease in both self-reported and impairment scores in the theatre intervention group for the overall group, but the impairment score decreased significantly for first generation adolescents while it increased for second generation adolescents.The difference between the population of immigrant and refugee youth newcomers studied previously and the sample of this trial may explain some of the differences in the observed impact of

  11. Scalable classification by clustering: Hybrid can be better than Pure

    Deng Shengchun; He Zengyou; Xu Xiaofei


    The problem of scalable classification by clustering in large databases was discussed. Clustering based classification method first generates clusters using clustering algorithms . To classify new coming data points , it finds the k nearest clusters of the data point as neighbors , and assign each data point to the dominant class of these neighbors . Existing algorithms incorporated class information in making clustering decisions and produced pure clusters (each cluster associated with only one class) . We presented hybrid cluster based algorithms , which produce clusters by unsupervised clustering and allow each cluster associated with multiple classes . Experimental results show that hybrid cluster based algorithms outperform pure ones in both classification accuracy and training speed.

  12. Deep observations of the Super-CLASS super-cluster at 325 MHz with the GMRT: the low-frequency source catalogue

    Riseley, C J; Hales, C A; Harrison, I; Birkinshaw, M; Battye, R A; Beswick, R J; Brown, M L; Casey, C M; Chapman, S C; Demetroullas, C; Hung, C -L; Jackson, N J; Muxlow, T; Watson, B


    We present the results of 325 MHz GMRT observations of a super-cluster field, known to contain five Abell clusters at redshift $z \\sim 0.2$. We achieve a nominal sensitivity of $34\\,\\mu$Jy beam$^{-1}$ toward the phase centre. We compile a catalogue of 3257 sources with flux densities in the range $183\\,\\mu\\rm{Jy}\\,-\\,1.5\\,\\rm{Jy}$ within the entire $\\sim 6.5$ square degree field of view. Subsequently, we use available survey data at other frequencies to derive the spectral index distribution for a sub-sample of these sources, recovering two distinct populations -- a dominant population which exhibit spectral index trends typical of steep-spectrum synchrotron emission, and a smaller population of sources with typically flat or rising spectra. We identify a number of sources with ultra-steep spectra or rising spectra for further analysis, finding two candidate high-redshift radio galaxies and three gigahertz-peaked-spectrum radio sources. Finally, we derive the Euclidean-normalised differential source counts us...

  13. Cluster-lensing: A Python Package for Galaxy Clusters & Miscentering

    Ford, Jes; VanderPlas, Jake


    We describe a new open source package for calculating properties of galaxy clusters, including NFW halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density $\\Sigma(R)$ and differential surface mass density $\\Delta\\Sigma(R)$...

  14. Clustering Approach to Stock Market Prediction

    M.Suresh Babu


    Full Text Available Clustering is an adaptive procedure in which objects are clustered or grouped together, based on the principle of maximizing the intra-class similarity and minimizing the inter-class similarity. Various clustering algorithms have been developed which results to a good performance on datasets for cluster formation. This paper analyze the major clustering algorithms: K-Means, Hierarchical clustering algorithm and reverse K means and compare the performance of these three major clustering algorithms on the aspect of correctly class wise cluster building ability of algorithm. An effective clustering method, HRK (Hierarchical agglomerative and Recursive K-means clustering is proposed, to predict the short-term stock price movements after the release of financial reports. The proposed method consists of three phases. First, we convert each financial report into a feature vector and use the hierarchical agglomerative clustering method to divide the converted feature vectors into clusters. Second, for each cluster, we recursively apply the K-means clustering method to partition each cluster into sub-clusters so that most feature vectors in each subcluster belong to the same class. Then, for each sub cluster, we choose its centroid as the representative feature vector. Finally, we employ the representative feature vectors to predict the stock price movements. The experimental results show the proposed method outperforms SVM in terms of accuracy and average profits.

  15. Online Correlation Clustering

    Mathieu, Claire; Schudy, Warren


    We study the online clustering problem where data items arrive in an online fashion. The algorithm maintains a clustering of data items into similarity classes. Upon arrival of v, the relation between v and previously arrived items is revealed, so that for each u we are told whether v is similar to u. The algorithm can create a new cluster for v and merge existing clusters. When the objective is to minimize disagreements between the clustering and the input, we prove that a natural greedy algorithm is O(n)-competitive, and this is optimal. When the objective is to maximize agreements between the clustering and the input, we prove that the greedy algorithm is .5-competitive; that no online algorithm can be better than .834-competitive; we prove that it is possible to get better than 1/2, by exhibiting a randomized algorithm with competitive ratio .5+c for a small positive fixed constant c.

  16. "Racializing" Class

    Hatt-Echeverria, Beth; Urrieta, Luis, Jr.


    In an effort to explore how racial and class oppressions intersect, the authors use their autobiographical narratives to depict cultural and experiential continuity and discontinuity in growing up white working class versus Chicano working class. They specifically focus on "racializing class" due to the ways class is often used as a copout by…

  17. Cluster headache

    Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... A cluster headache begins as a severe, sudden headache. The headache commonly strikes 2 to 3 hours after you fall ...

  18. Cluster Forests

    Yan, Donghui; Jordan, Michael I


    Inspired by Random Forests (RF) in the context of classification, we propose a new clustering ensemble method---Cluster Forests (CF). Geometrically, CF randomly probes a high-dimensional data cloud to obtain "good local clusterings" and then aggregates via spectral clustering to obtain cluster assignments for the whole dataset. The search for good local clusterings is guided by a cluster quality measure $\\kappa$. CF progressively improves each local clustering in a fashion that resembles the tree growth in RF. Empirical studies on several real-world datasets under two different performance metrics show that CF compares favorably to its competitors. Theoretical analysis shows that the $\\kappa$ criterion is shown to grow each local clustering in a desirable way---it is "noise-resistant." A closed-form expression is obtained for the mis-clustering rate of spectral clustering under a perturbation model, which yields new insights into some aspects of spectral clustering.

  19. Study on One-class Classification with Multi Hyper-spheres Based on Maximal Tree Clustering and Its Applications%基于最大树聚类的多超球体一类分类算法及其应用研究

    刘丽娟; 陈果


    An one-class Classification with multi hyper-spheres based on maximal tree clustering algorithm was presented herein.The training samples were firstly clustered into several sub-classes by the maximal tree clustering algorithm,and then,the sub-classes data were trained separately using one-class SVM(OC-SVM) and the multi hyper-spheres classifying models were established.The new method was applied to the instances of the simulation data set,UCI data sets and the rotor faults diagnosis,and the results show the effectiveness of the new method.%提出了一种基于最大树聚类的多超球体一类分类算法。首先应用最大树聚类算法将训练样本聚为多个子类,再对各子类分别进行一类支持向量机(one-class SVM,OC-SVM)分类器训练,得到由各子类对应的超球体形成的多超球体一类分类模型。分别将该方法应用于仿真数据、UCI标准数据集以及转子故障诊断三个实例中,结果表明了该方法的有效性。

  20. 基于谱聚类与类间可分性因子的高光谱波段选择%Hyperspectral Band Selection Based on Spectral Clustering and Inter-Class Separability Factor

    秦方普; 张爱武; 王书民; 孟宪刚; 胡少兴; 孙卫东


    With the development of remote sensing technology and imaging spectrometer ,the resolution of hyperspectral remote sensing image has been continually improved ,its vast amount of data not only improves the ability of the remote sensing detec-tion but also brings great difficulties for analyzing and processing at the same time .Band selection of hyperspectral imagery can effectively reduce data redundancy and improve classification accuracy and efficiency .So how to select the optimum band combi-nation from hundreds of bands of hyperspectral images is a key issue .In order to solve these problems ,we use spectral cluste-ring algorithm based on graph theory .Firstly ,taking of the original hyperspectral image bands as data points to be clustered , mutual information between every two bands is calculated to generate the similarity matrix .Then according to the graph partition theory ,spectral decomposition of the non-normalized Laplacian matrix generated by the similarity matrix is used to get the clus-ters ,which the similarity between is small and the similarity within is large .In order to achieve the purpose of dimensionality re-duction ,the inter-class separability factor of feature types on each band is calculated ,which is as the reference index to choose the representative bands in the clusters furthermore .Finally ,the support vector machine and minimum distance classification methods are employed to classify the hyperspectral image after band selection .The method in this paper is different from the tra-ditional unsupervised clustering method ,we employ spectral clustering algorithm based on graph theory and compute the inter-class separability factor based on a priori knowledge to select bands .Comparing with traditional adaptive band selection algo-rithm and band index based on automatically subspace divided algorithm ,the two sets of experiments results show that the over-all accuracy of SVM is about 94.08% and 94.24% and the overall accuracy of MDC is

  1. Star Clusters

    Gieles, M.


    Star clusters are observed in almost every galaxy. In this thesis we address several fundamental problems concerning the formation, evolution and disruption of star clusters. From observations of (young) star clusters in the interacting galaxy M51, we found that clusters are formed in complexes of stars and star clusters. These complexes share similar properties with giant molecular clouds, from which they are formed. Many (70%) of the young clusters will not survive the fist 10 Myr, due to t...

  2. Dependent Classes

    Gasiunas, Vaidas; Mezini, Mira; Ostermann, Klaus


    Virtual classes allow nested classes to be refined in subclasses. In this way nested classes can be seen as dependent abstractions of the objects of the enclosing classes. Expressing dependency via nesting, however, has two limitations: Abstractions that depend on more than one object cannot...... be modeled and a class must know all classes that depend on its objects. This paper presents dependent classes, a generalization of virtual classes that expresses similar semantics by parameterization rather than by nesting. This increases expressivity of class variations as well as the flexibility...... of their modularization. Besides, dependent classes complement multi-methods in scenarios where multi-dispatched abstractions rather than multi-dispatched method are needed. They can also be used to express more precise signatures of multi-methods and even extend their dispatch semantics. We present a formal semantics...

  3. Tune Your Brown Clustering, Please

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


    unexplored. Accordingly, we present information for practitioners on the behaviour of Brown clustering in order to assist hyper-parametre tuning, in the form of a theoretical model of Brown clustering utility. This model is then evaluated empirically in two sequence labelling tasks over two text types. We...... explore the dynamic between the input corpus size, chosen number of classes, and quality of the resulting clusters, which has an impact for any approach using Brown clustering. In every scenario that we examine, our results reveal that the values most commonly used for the clustering are sub-optimal....

  4. Class II Microcins

    Vassiliadis, Gaëlle; Destoumieux-Garzón, Delphine; Peduzzi, Jean

    Class II microcins are 4.9- to 8.9-kDa polypeptides produced by and active against enterobacteria. They are classified into two subfamilies according to their structure and their gene cluster arrangement. While class IIa microcins undergo no posttranslational modification, class IIb microcins show a conserved C-terminal sequence that carries a salmochelin-like siderophore motif as a posttranslational modification. Aside from this C-terminal end, which is the signature of class IIb microcins, some sequence similarities can be observed within and between class II subclasses, suggesting the existence of common ancestors. Their mechanisms of action are still under investigation, but several class II microcins use inner membrane proteins as cellular targets, and some of them are membrane-active. Like group B colicins, many, if not all, class II microcins are TonB- and energy-dependent and use catecholate siderophore receptors for recognition/­translocation across the outer membrane. In that context, class IIb microcins are considered to have developed molecular mimicry to increase their affinity for their outer membrane receptors through their salmochelin-like posttranslational modification.

  5. Learning regularized LDA by clustering.

    Pang, Yanwei; Wang, Shuang; Yuan, Yuan


    As a supervised dimensionality reduction technique, linear discriminant analysis has a serious overfitting problem when the number of training samples per class is small. The main reason is that the between- and within-class scatter matrices computed from the limited number of training samples deviate greatly from the underlying ones. To overcome the problem without increasing the number of training samples, we propose making use of the structure of the given training data to regularize the between- and within-class scatter matrices by between- and within-cluster scatter matrices, respectively, and simultaneously. The within- and between-cluster matrices are computed from unsupervised clustered data. The within-cluster scatter matrix contributes to encoding the possible variations in intraclasses and the between-cluster scatter matrix is useful for separating extra classes. The contributions are inversely proportional to the number of training samples per class. The advantages of the proposed method become more remarkable as the number of training samples per class decreases. Experimental results on the AR and Feret face databases demonstrate the effectiveness of the proposed method.

  6. Properties of $\\gamma$-Ray Burst Classes

    Hakkila, J; Roiger, R J; Mallozzi, R S; Pendleton, G N; Meegan, C A; Hakkila, Jon; Haglin, David J.; Roiger, Richard J.; Mallozzi, Robert S.; Pendleton, Geoffrey N.; Meegan, Charles A.


    The three gamma-ray burst (GRB) classes identified by statistical clustering analysis (Mukherjee et al. 1998) are examined using the pattern recognition algorithm C4.5 (Quinlan 1986). Although the statistical existence of Class 3 (intermediate duration, intermediate fluence, soft) is supported, the properties of this class do not need to arise from a distinct source population. Class 3 properties can easily be produced from Class 1 (long, high fluence, intermediate hardness) by a combination of measurement error, hardness/intensity correlation, and a newly-identified BATSE bias (the fluence duration bias). Class 2 (short, low fluence, hard) does not appear to be related to Class 1.

  7. Meaningful Clusters

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


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

  8. Word classes

    Rijkhoff, Jan


    This article provides an overview of recent literature and research on word classes, focusing in particular on typological approaches to word classification. The cross-linguistic classification of word class systems (or parts-of-speech systems) presented in this article is based on statements found...... – Adverb, because they have properties that are strongly associated with at least two of these four traditional word classes (e.g. Adjective and Adverb). Finally, this article discusses some of the ways in which word class distinctions interact with other grammatical domains, such as syntax and morphology....

  9. Weighted Clustering

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


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

  10. Organizing MHC Class II Presentation

    David R Fooksman


    Full Text Available Major histocompatibility complex (MHC class II molecules are ligands for CD4+ T cells and are critical for initiating the adaptive immune response. This review is focused on what is currently known about MHC class II organization at the plasma membrane of antigen presenting cells and how this affects antigen presentation to T cells. The organization and diffusion of class II molecules have been measured by a variety of biochemical and microscopic techniques. Membrane lipids and other proteins have been implicated in MHC class II organization and function. However, when compared with the organization of MHC class I or TCR complexes, much less is known about MHC class II. Since clustering of T cell receptors occurs during activation, the organization of MHC molecules prior to recognition and during synapse formation may be critical for antigen presentation.

  11. Cluster Lenses

    Kneib, Jean-Paul; 10.1007/s00159-011-0047-3


    Clusters of galaxies are the most recently assembled, massive, bound structures in the Universe. As predicted by General Relativity, given their masses, clusters strongly deform space-time in their vicinity. Clusters act as some of the most powerful gravitational lenses in the Universe. Light rays traversing through clusters from distant sources are hence deflected, and the resulting images of these distant objects therefore appear distorted and magnified. Lensing by clusters occurs in two regimes, each with unique observational signatures. The strong lensing regime is characterized by effects readily seen by eye, namely, the production of giant arcs, multiple-images, and arclets. The weak lensing regime is characterized by small deformations in the shapes of background galaxies only detectable statistically. Cluster lenses have been exploited successfully to address several important current questions in cosmology: (i) the study of the lens(es) - understanding cluster mass distributions and issues pertaining...

  12. Cluster functional renormalization group

    Reuther, Johannes; Thomale, Ronny


    Functional renormalization group (FRG) has become a diverse and powerful tool to derive effective low-energy scattering vertices of interacting many-body systems. Starting from a free expansion point of the action, the flow of the RG parameter Λ allows us to trace the evolution of the effective one- and two-particle vertices towards low energies by taking into account the vertex corrections between all parquet channels in an unbiased fashion. In this work, we generalize the expansion point at which the diagrammatic resummation procedure is initiated from a free UV limit to a cluster product state. We formulate a cluster FRG scheme where the noninteracting building blocks (i.e., decoupled spin clusters) are treated exactly, and the intercluster couplings are addressed via RG. As a benchmark study, we apply our cluster FRG scheme to the spin-1/2 bilayer Heisenberg model (BHM) on a square lattice where the neighboring sites in the two layers form the individual two-site clusters. Comparing with existing numerical evidence for the BHM, we obtain reasonable findings for the spin susceptibility, the spin-triplet excitation energy, and quasiparticle weight even in coupling regimes close to antiferromagnetic order. The concept of cluster FRG promises applications to a large class of interacting electron systems.

  13. Kaempferol suppresses lipid accumulation in macrophages through the downregulation of cluster of differentiation 36 and the upregulation of scavenger receptor class B type I and ATP-binding cassette transporters A1 and G1.

    Li, Xiu-Ying; Kong, Ling-Xi; Li, Juan; He, Hai-Xia; Zhou, Yuan-Da


    The accumulation of foam cells in atherosclerotic lesions is a hallmark of early-stage atherosclerosis. Kaempferol has been shown to inhibit oxidized low-density lipoprotein (oxLDL) uptake by macrophages; however, the underlying molecular mechanisms are not yet fully investigated. In this study, we shown that treatment with kaempferol markedly suppresses oxLDL-induced macrophage foam cell formation, which occurs due to a decrease in lipid accumulation and an increase in cholesterol efflux from THP-1-derived macrophages. Additionally, the kaempferol treatment of macrophages led to the downregulation of cluster of differentiation 36 (CD36) protein levels, the upregulation of ATP-binding cassette (ABC) transporter A1 (ABCA1), scavenger receptor class B type I (SR-BI) and ABCG1 protein levels, while no effects on scavenger receptor A (SR-A) expression were observed. Kaempferol had similar effects on the mRNA and protein expression of ABCA1, SR-BI, SR-A, CD36 and ABCG1. The reduced CD36 expression following kaempferol treatment involved the inhibition of c-Jun-activator protein-1 (AP-1) nuclear translocation. The inhibition of AP-1 using the inhibitor, SP600125, confirmed this involvement, as the AP-1 inhibition significantly augmented the kaempferol-induced reduction in CD36 expression. Accordingly, the kaempferol-mediated suppression of lipid accumulation in macrophages was also augmented by SP600125. The increased expression of ABCA1, SR-BI and ABCG1 following kaempferol treatment was accompanied by the enhanced protein expression of heme oxygenase-1 (HO-1). This increase was reversed following the knockdown of the HO-1 gene using small hairpin RNA (shRNA). Moreover, the kaempferol-mediated attenuation of lipid accumulation and the promotion of cholesterol efflux was also inhibited by HO-1 shRNA. In conclusion, the c-Jun-AP‑1-dependent downregulation of CD36 and the HO-1-dependent upregulation of ABCG1, SR-BI and ABCA1 may mediate the beneficial effects of

  14. Data Clustering

    Wagstaff, Kiri L.


    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

  15. Cluster Chemistry


    @@ Cansisting of eight scientists from the State Key Laboratory of Physical Chemistry of Solid Surfaces and Xiamen University, this creative research group is devoted to the research of cluster chemistry and creation of nanomaterials.After three-year hard work, the group scored a series of encouraging progresses in synthesis of clusters with special structures, including novel fullerenes, fullerene-like metal cluster compounds as well as other related nanomaterials, and their properties study.

  16. Class size versus class composition

    Jones, Sam

    Raising schooling quality in low-income countries is a pressing challenge. Substantial research has considered the impact of cutting class sizes on skills acquisition. Considerably less attention has been given to the extent to which peer effects, which refer to class composition, also may affect...... bias from omitted variables, the preferred IV results indicate considerable negative effects due to larger class sizes and larger numbers of overage-for-grade peers. The latter, driven by the highly prevalent practices of grade repetition and academic redshirting, should be considered an important...

  17. Clustered regression with unknown clusters

    Barman, Kishor


    We consider a collection of prediction experiments, which are clustered in the sense that groups of experiments ex- hibit similar relationship between the predictor and response variables. The experiment clusters as well as the regres- sion relationships are unknown. The regression relation- ships define the experiment clusters, and in general, the predictor and response variables may not exhibit any clus- tering. We call this prediction problem clustered regres- sion with unknown clusters (CRUC) and in this paper we focus on linear regression. We study and compare several methods for CRUC, demonstrate their applicability to the Yahoo Learning-to-rank Challenge (YLRC) dataset, and in- vestigate an associated mathematical model. CRUC is at the crossroads of many prior works and we study several prediction algorithms with diverse origins: an adaptation of the expectation-maximization algorithm, an approach in- spired by K-means clustering, the singular value threshold- ing approach to matrix rank minimization u...

  18. Finite mutation classes of coloured quivers

    Torkildsen, Hermund André


    We consider the general notion of coloured quiver mutation and show that the mutation class of a coloured quiver $Q$, arising from an $m$-cluster tilting object associated with $H$, is finite if and only if $H$ is of finite or tame representation type, or it has at most 2 simples. This generalizes a result known for 1-cluster categories.

  19. Subspace clustering through attribute clustering

    Kun NIU; Shubo ZHANG; Junliang CHEN


    Many recently proposed subspace clustering methods suffer from two severe problems. First, the algorithms typically scale exponentially with the data dimensionality or the subspace dimensionality of clusters. Second, the clustering results are often sensitive to input parameters. In this paper, a fast algorithm of subspace clustering using attribute clustering is proposed to over-come these limitations. This algorithm first filters out redundant attributes by computing the Gini coefficient. To evaluate the correlation of every two non-redundant attributes, the relation matrix of non-redundant attributes is constructed based on the relation function of two dimensional united Gini coefficients. After applying an overlapping clustering algorithm on the relation matrix, the candidate of all interesting subspaces is achieved. Finally, all subspace clusters can be derived by clustering on interesting subspaces. Experiments on both synthesis and real datasets show that the new algorithm not only achieves a significant gain of runtime and quality to find subspace clusters, but also is insensitive to input parameters.

  20. Clustering by Pattern Similarity

    Hai-xun Wang; Jian Pei


    The task of clustering is to identify classes of similar objects among a set of objects. The definition of similarity varies from one clustering model to another. However, in most of these models the concept of similarity is often based on such metrics as Manhattan distance, Euclidean distance or other Lp distances. In other words, similar objects must have close values in at least a set of dimensions. In this paper, we explore a more general type of similarity. Under the pCluster model we proposed, two objects are similar if they exhibit a coherent pattern on a subset of dimensions. The new similarity concept models a wide range of applications. For instance, in DNA microarray analysis, the expression levels of two genes may rise and fall synchronously in response to a set of environmental stimuli. Although the magnitude of their expression levels may not be close, the patterns they exhibit can be very much alike. Discovery of such clusters of genes is essential in revealing significant connections in gene regulatory networks. E-commerce applications, such as collaborative filtering, can also benefit from the new model, because it is able to capture not only the closeness of values of certain leading indicators but also the closeness of (purchasing, browsing, etc.) patterns exhibited by the customers. In addition to the novel similarity model, this paper also introduces an effective and efficient algorithm to detect such clusters, and we perform tests on several real and synthetic data sets to show its performance.


    Satya Chaitanya Sripada


    Full Text Available Clustering is one the main area in data mining literature. There are various algorithms for clustering. The evaluation of the performance isdone by validation measures. The external validation measures are used to measure the extent to which cluster labels affirm with theexternally given class labels. The aim of this paper is to compare the for K-means and Fuzzy C means clustering using the Purity andEntropy. The data used for evaluating the external measures is medical data.

  2. Cluster editing

    Böcker, S.; Baumbach, Jan


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

  3. Cluster analysis

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


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

  4. Weighted Clustering

    Ackerman, Margareta; Branzei, Simina; Loker, David


    In this paper we investigate clustering in the weighted setting, in which every data point is assigned a real valued weight. We conduct a theoretical analysis on the influence of weighted data on standard clustering algorithms in each of the partitional and hierarchical settings, characterising the precise conditions under which such algorithms react to weights, and classifying clustering methods into three broad categories: weight-responsive, weight-considering, and weight-robust. Our analysis raises several interesting questions and can be directly mapped to the classical unweighted setting.

  5. Perceptual qualities and material classes.

    Fleming, Roland W; Wiebel, Christiane; Gegenfurtner, Karl


    Under typical viewing conditions, we can easily group materials into distinct classes (e.g., woods, plastics, textiles). Additionally, we can also make many other judgments about material properties (e.g., hardness, rigidity, colorfulness). Although these two types of judgment (classification and inferring material properties) have different requirements, they likely facilitate one another. We conducted two experiments to investigate the interactions between material classification and judgments of material qualities in both the visual and semantic domains. In Experiment 1, nine students viewed 130 images of materials from 10 different classes. For each image, they rated nine subjective properties (glossiness, transparency, colorfulness, roughness, hardness, coldness, fragility, naturalness, prettiness). In Experiment 2, 65 subjects were given the verbal names of six material classes, which they rated in terms of 42 adjectives describing material qualities. In both experiments, there was notable agreement between subjects, and a relatively small number of factors (weighted combinations of different qualities) were substantially independent of one another. Despite the difficulty of classifying materials from images (Liu, Sharan, Adelson, & Rosenholtz, 2010), the different classes were well clustered in the feature space defined by the subjective ratings. K-means clustering could correctly identify class membership for over 90% of the samples, based on the average ratings across subjects. We also found a high degree of consistency between the two tasks, suggesting subjects access similar information about materials whether judging their qualities visually or from memory. Together, these findings show that perceptual qualities are well defined, distinct, and systematically related to material class membership.

  6. Class size versus class composition

    Jones, Sam

    Raising schooling quality in low-income countries is a pressing challenge. Substantial research has considered the impact of cutting class sizes on skills acquisition. Considerably less attention has been given to the extent to which peer effects, which refer to class composition, also may affect...... outcomes. This study uses new microdata from East Africa, incorporating test score data for over 250,000 children, to compare the likely efficacy of these two types of interventions. Endogeneity bias is addressed via fixed effects and instrumental variables techniques. Although these may not fully mitigate...

  7. Attracting higher income class to public transport in socially clustered cities. The case of Caracas. / Atracción del mayor nivel de ingresos al transporte público en las ciudades socialmente segregadas. El caso de Caracas.

    Flórez, Josefina


    Full Text Available In Caracas, as in most socially clustered cities, modal split is highly related to income. High income population is mostly car dependant, while lower income people are captive of public transport. This typical situation is explained by world-wide social values and fashion but also by the fact that new, segregated residential areas for the upper social levels have been located in areas poorly served by public transport, creating a dependency on the private car. It is not surprising that, during the 1970's, a high proportion of Caracas's middle and high-income citizens were systematically using their car even in areas where there was a good offer of public transport. What is more unusual is to realise that, since 1983 when the metro system was inaugurated, there is a new pattern of travel behaviour. The metro has mainly attracted high-income people. Besides the few of them who have transferred from surface to underground public transport, many of the wealthier patrons seem to be regular car users that presently take the metro when it provides a good alternative. Currently, the transit system in Caracas is comprised of four main modes: the metro (since 1983; the "por puesto", which are minibus vehicles of 18 to 32 seats; the jeeps, which are dual traction vehicles of up to 12 seat (most of them serving hilly areas, basically slums; and the bus system, consisting of metro-bus and private operators. CA Metro operates the metro and, since 1987, metro-bus lines, which are bus feeder services to its heavy rail metro operation that extend the cover area of the system into the less central zones of the city. While the metro and metro-bus offer transit services to middle and high income users, the mini-buses and jeeps provide flexible transit service to low income groups. The metro and metro-bus services are more reliable and offer higher quality that mini-buses and jeeps. This higher quality service is one of the main attributes attracting the wealthier

  8. Class distinction

    White, M. Catherine

    Typical 101 courses discourage many students from pursuing higher level science and math courses. Introductory classes in science and math serve largely as a filter, screening out all but the most promising students, and leaving the majority of college graduates—including most prospective teachers—with little understanding of how science works, according to a study conducted for the National Science Foundation. Because few teachers, particularly at the elementary level, experience any collegiate science teaching that stresses skills of inquiry and investigation, they simply never learn to use those methods in their teaching, the report states.

  9. Tidally Induced Elongation and Alignments of Galaxy Clusters

    Salvador-Solé, E; Salvador-Sole, Eduard; Solanes, Jose M.


    We show that tidal interaction among galaxy clusters can account for their observed alignments and very marked elongation and, consequently, that these characteristics of clusters are actually consistent with them being formed in hierarchical clustering. The well-established distribution of projected axial ratios of clusters with richness class $R\\ge 0$ is recovered very satisfactorily by means of a simple model with no free parameters. The main perturbers are relatively rich ($R\\ge 1$) single clusters and/or groups of clusters (superclusters) of a wider richness class ($R\\ge 0$) located within a distance of about 65 $h^{-1}$ Mpc from the perturbed cluster. This makes the proposed scheme be also consistent with all reported alignment effects involving clusters. We find that this tidal interaction is typically in the saturate regime (\\ie the maximum elongation allowed for systems in equilibrium is reached), which explains the very similar intrinsic axial ratio shown by all clusters. Tides would therefore play ...

  10. M$_1$ - M* correlation in galaxy clusters

    Trevese, D; Appodia, B


    Photographic F band photometry of a sample of 36 Abell clusters has been used to study the relation between the magnitude M_1 of the brightest cluster member and the Schechter function parameter M^*. Clusters appear segregated in the M_1-M^* plane according to their Rood \\& Sastry class. We prove on a statistical basis that on average, going from early to late RS classes, M_1 becomes brighter while M^* becomes fainter. The result agrees with the predictions of galactic cannibalism models, never confirmed by previous analyses.

  11. Cluster-lensing: A Python Package for Galaxy Clusters & Miscentering

    Ford, Jes


    We describe a new open source package for calculating properties of galaxy clusters, including NFW halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density $\\Sigma(R)$ and differential surface mass density $\\Delta\\Sigma(R)$ profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo (Ford 2016). Full documenta...

  12. Validity Index and number of clusters

    Mohamed Fadhel Saad


    Full Text Available Clustering (or cluster analysis has been used widely in pattern recognition, image processing, and data analysis. It aims to organize a collection of data items into c clusters, such that items within a cluster are more similar to each other than they are items in the other clusters. The number of clusters c is the most important parameter, in the sense that the remaining parameters have less influence on the resulting partition. To determine the best number of classes several methods were made, and are called validity index. This paper presents a new validity index for fuzzy clustering called a Modified Partition Coefficient And Exponential Separation (MPCAES index. The efficiency of the proposed MPCAES index is compared with several popular validity indexes. More information about these indexes is acquired in series of numerical comparisons and also real data Iris.

  13. Document Clustering based on Topic Maps

    Rafi, Muhammad; Farooq, Amir; 10.5120/1640-2204


    Importance of document clustering is now widely acknowledged by researchers for better management, smart navigation, efficient filtering, and concise summarization of large collection of documents like World Wide Web (WWW). The next challenge lies in semantically performing clustering based on the semantic contents of the document. The problem of document clustering has two main components: (1) to represent the document in such a form that inherently captures semantics of the text. This may also help to reduce dimensionality of the document, and (2) to define a similarity measure based on the semantic representation such that it assigns higher numerical values to document pairs which have higher semantic relationship. Feature space of the documents can be very challenging for document clustering. A document may contain multiple topics, it may contain a large set of class-independent general-words, and a handful class-specific core-words. With these features in mind, traditional agglomerative clustering algori...

  14. Quotients of cluster categories

    Jorgensen, Peter


    Higher cluster categories were recently introduced as a generalization of cluster categories. This paper shows that in Dynkin types A and D, half of all higher cluster categories are actually just quotients of cluster categories. The other half can be obtained as quotients of 2-cluster categories, the "lowest" type of higher cluster categories. Hence, in Dynkin types A and D, all higher cluster phenomena are implicit in cluster categories and 2-cluster categories. In contrast, the same is not...

  15. Regional Innovation Clusters

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

  16. Cluster forcing

    Christensen, Thomas Budde

    -industrialism and the ‘liveable' region. In this paper the cluster strategies that have been applied to the automotive sector in Wales are analysed. The paper includes a theoretical discussion on how the cluster concept has been applied to industrial policies, along with an empirical analysis of the application of the concept...... automotive sector in Wales. The paper draws from a survey of Welsh automotive suppliers on the characteristics of the local business environment and innovation. On the basis of the survey it is concluded that the public sector has an important task ahead concerning the linkages between universities and local...... businesses. The universities were not considered by the participating companies to be important parts of the local business environment and inputs from universities did not appear to be an important source to access knowledge about new product development or new techniques in production, distribution...

  17. Knowledge based cluster ensemble for cancer discovery from biomolecular data.

    Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying


    The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.

  18. The Hierarchical Distribution of Young Stellar Clusters in Nearby Galaxies

    Grasha, Kathryn; Calzetti, Daniela


    We investigate the spatial distributions of young stellar clusters in six nearby galaxies to trace the large scale hierarchical star-forming structures. The six galaxies are drawn from the Legacy ExtraGalactic UV Survey (LEGUS). We quantify the strength of the clustering among stellar clusters as a function of spatial scale and age to establish the survival timescale of the substructures. We separate the clusters into different classes, compact (bound) clusters and associations (unbound), and compare the clustering among them. We find that younger star clusters are more strongly clustered over small spatial scales and that the clustering disappears rapidly for ages as young as a few tens of Myr, consistent with clusters slowly losing the fractal dimension inherited at birth from their natal molecular clouds.

  19. Applying Machine Learning to Star Cluster Classification

    Fedorenko, Kristina; Grasha, Kathryn; Calzetti, Daniela; Mahadevan, Sridhar


    Catalogs describing populations of star clusters are essential in investigating a range of important issues, from star formation to galaxy evolution. Star cluster catalogs are typically created in a two-step process: in the first step, a catalog of sources is automatically produced; in the second step, each of the extracted sources is visually inspected by 3-to-5 human classifiers and assigned a category. Classification by humans is labor-intensive and time consuming, thus it creates a bottleneck, and substantially slows down progress in star cluster research.We seek to automate the process of labeling star clusters (the second step) through applying supervised machine learning techniques. This will provide a fast, objective, and reproducible classification. Our data is HST (WFC3 and ACS) images of galaxies in the distance range of 3.5-12 Mpc, with a few thousand star clusters already classified by humans as a part of the LEGUS (Legacy ExtraGalactic UV Survey) project. The classification is based on 4 labels (Class 1 - symmetric, compact cluster; Class 2 - concentrated object with some degree of asymmetry; Class 3 - multiple peak system, diffuse; and Class 4 - spurious detection). We start by looking at basic machine learning methods such as decision trees. We then proceed to evaluate performance of more advanced techniques, focusing on convolutional neural networks and other Deep Learning methods. We analyze the results, and suggest several directions for further improvement.

  20. Evolution of homeobox gene clusters in animals: the Giga-cluster and primary versus secondary clustering.

    David Ellard Keith Ferrier


    Full Text Available The Hox gene cluster has been a major focus in evolutionary developmental biology. This is because of its key role in patterning animal development and widespread examples of changes in Hox genes being linked to the evolution of animal body plans and morphologies. Also, the distinctive organisation of the Hox genes into genomic clusters in which the order of the genes along the chromosome corresponds to the order of their activity along the embryo, or during a developmental process, has been a further source of great interest. This is known as Colinearity, and it provides a clear link between genome organisation and the regulation of genes during development, with distinctive changes marking evolutionary transitions. The Hox genes are not alone, however. The homeobox genes are a large super-class, of which the Hox genes are only a small subset, and an ever-increasing number of further gene clusters besides the Hox are being discovered. This is of great interest because of the potential for such gene clusters to help understand major evolutionary transitions, both in terms of changes to development and morphology as well as evolution of genome organisation. However, there is uncertainty in our understanding of homeobox gene cluster evolution at present. This relates to our still rudimentary understanding of the dynamics of genome rearrangements and evolution over the evolutionary timescales being considered when we compare lineages from across the animal kingdom. A major goal is to deduce whether particular instances of clustering are primary (conserved from ancient ancestral clusters or secondary (reassortment of genes into clusters in lineage-specific fashion. The following summary of the various instances of homeobox gene clusters in animals, and the hypotheses about their evolution, provides a framework for the future resolution of this uncertainty.

  1. Atomic clusters with addressable complexity

    Wales, David J.


    A general formulation for constructing addressable atomic clusters is introduced, based on one or more reference structures. By modifying the well depths in a given interatomic potential in favour of nearest-neighbour interactions that are defined in the reference(s), the potential energy landscape can be biased to make a particular permutational isomer the global minimum. The magnitude of the bias changes the resulting potential energy landscape systematically, providing a framework to produce clusters that should self-organise efficiently into the target structure. These features are illustrated for small systems, where all the relevant local minima and transition states can be identified, and for the low-energy regions of the landscape for larger clusters. For a 55-particle cluster, it is possible to design a target structure from a transition state of the original potential and to retain this structure in a doubly addressable landscape. Disconnectivity graphs based on local minima that have no direct connections to a lower minimum provide a helpful way to visualise the larger databases. These minima correspond to the termini of monotonic sequences, which always proceed downhill in terms of potential energy, and we identify them as a class of biminimum. Multiple copies of the target cluster are treated by adding a repulsive term between particles with the same address to maintain distinguishable targets upon aggregation. By tuning the magnitude of this term, it is possible to create assemblies of the target cluster corresponding to a variety of structures, including rings and chains.

  2. Where have all the cluster halos gone?

    Burns, Jack O.; Sulkanen, Martin E.; Gisler, Galen R.; Perley, Rick A.


    A new LF (330 MHz) VLA image of the Perseus cluster confirms the presence of a miniradio halo with diameter of about 430 kpc (H0 = 75 km/s Mpc) surrounding 3C 84. A careful comparison with the Coma cluster shows that there is no evidence for a similar, very extended halo in Perseus despite the large number of cluster radio galaxies which could power such a halo. These two clusters represent two classes of radio halos which differ by the absence (Coma) or presence (Perseus) of cooling inflows. It is argued that smaller halos as in Perseus result form insufficient clusterwide magnetic fields. A simple model is presented which suggests that cooling flows can suppress the diffusion of turbulently amplified B-fields outward from the cluster core. Such a suppression leads to the development of minihalos which are confined to the cores of cooling flow clusters.

  3. Clustering Analysis on E-commerce Transaction Based on K-means Clustering

    Xuan HUANG


    Full Text Available Based on the density, increment and grid etc, shortcomings like the bad elasticity, weak handling ability of high-dimensional data, sensitive to time sequence of data, bad independence of parameters and weak handling ability of noise are usually existed in clustering algorithm when facing a large number of high-dimensional transaction data. Making experiments by sampling data samples of the 300 mobile phones of Taobao, the following conclusions can be obtained: compared with Single-pass clustering algorithm, the K-means clustering algorithm has a high intra-class dissimilarity and inter-class similarity when analyzing e-commerce transaction. In addition, the K-means clustering algorithm has very high efficiency and strong elasticity when dealing with a large number of data items. However, clustering effects of this algorithm are affected by clustering number and initial positions of clustering center. Therefore, it is easy to show the local optimization for clustering results. Therefore, how to determine clustering number and initial positions of the clustering center of this algorithm is still the important job to be researched in the future.

  4. An Automatic Clustering Technique for Optimal Clusters

    Pavan, K Karteeka; Rao, A V Dattatreya; 10.5121/ijcsea.2011.1412


    This paper proposes a simple, automatic and efficient clustering algorithm, namely, Automatic Merging for Optimal Clusters (AMOC) which aims to generate nearly optimal clusters for the given datasets automatically. The AMOC is an extension to standard k-means with a two phase iterative procedure combining certain validation techniques in order to find optimal clusters with automation of merging of clusters. Experiments on both synthetic and real data have proved that the proposed algorithm finds nearly optimal clustering structures in terms of number of clusters, compactness and separation.

  5. The Georgi Algorithms of Jet Clustering

    Ge, Shao-Feng


    We reveal the direct link between the jet clustering algorithms recently proposed by Howard Georgi and parton shower kinematics, providing firm foundation from the theoretical side. The kinematics of this class of elegant algorithms is explored systematically for partons with arbitrary masses and the jet function is generalized to $J^{(n)}_\\beta$ with a jet function index $n$ in order to achieve more degrees of freedom. Based on three basic requirements that, the result of jet clustering is p...

  6. Exotic populations in Galactic Globular Clusters

    Ferraro, F R


    Recent high-resolution observations of the central region of Galactic globular clusters have shown the presence of a large variety of exotic stellar objects whose formation and evolution may be strongly affected by dynamical interactions. In this paper I review the main properties of two classes of exotic objects: the so-called Blue Stragglers stars and the recently identified optical companions to Millisecond pulsar. Both these class of objects are invaluable tools to investigate the binary evolution in very dense environments and are powerful tracers of the dynamical history of the parent cluster.

  7. Teachers in Class

    Van Galen, Jane


    In this article, I argue for a closer read of the daily "class work" of teachers, as posited by Reay, 1998. In developing exploratory class portraits of four teachers who occupy distinctive social positions (two from working-class homes now teaching upper-middle-class children and two from upper-middle-class homes now teaching poor children), I…

  8. Supermodel Analysis of Galaxy Clusters

    Fusco-Femiano, R; Lapi, A


    [abridged] We present the analysis of the X-ray brightness and temperature profiles for six clusters belonging to both the Cool Core and Non Cool Core classes, in terms of the Supermodel (SM) developed by Cavaliere, Lapi & Fusco-Femiano (2009). Based on the gravitational wells set by the dark matter halos, the SM straightforwardly expresses the equilibrium of the IntraCluster Plasma (ICP) modulated by the entropy deposited at the boundary by standing shocks from gravitational accretion, and injected at the center by outgoing blastwaves from mergers or from outbursts of Active Galactic Nuclei. The cluster set analyzed here highlights not only how simply the SM represents the main dichotomy Cool vs. Non Cool Core clusters in terms of a few ICP parameters governing the radial entropy run, but also how accurately it fits even complex brightness and temperature profiles. For Cool Core clusters like A2199 and A2597, the SM with a low level of central entropy straightforwardly yields the characteristic peaked pr...

  9. Cluster headache

    Ducros Anne


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

  10. Double-partition Quantum Cluster Algebras

    Jakobsen, Hans Plesner; Zhang, Hechun


    A family of quantum cluster algebras is introduced and studied. In general, these algebras are new, but sub-classes have been studied previously by other authors. The algebras are indexed by double parti- tions or double flag varieties. Equivalently, they are indexed by broken lines L. By grouping...... together neighboring mutations into quantum line mutations we can mutate from the cluster algebra of one broken line to another. Compatible pairs can be written down. The algebras are equal to their upper cluster algebras. The variables of the quantum seeds are given by elements of the dual canonical basis....

  11. Issues Challenges and Tools of Clustering Algorithms

    Parul Agarwal


    Full Text Available Clustering is an unsupervised technique of Data Mining. It means grouping similar objects together and separating the dissimilar ones. Each object in the data set is assigned a class label in the clustering process using a distance measure. This paper has captured the problems that are faced in real when clustering algorithms are implemented .It also considers the most extensively used tools which are readily available and support functions which ease the programming. Once algorithms have been implemented, they also need to be tested for its validity. There exist several validation indexes for testing the performance and accuracy which have also been discussed here.

  12. A Virtual Class Calculus

    Ernst, Erik; Ostermann, Klaus; Cook, William Randall


    Virtual classes are class-valued attributes of objects. Like virtual methods, virtual classes are defined in an object's class and may be redefined within subclasses. They resemble inner classes, which are also defined within a class, but virtual classes are accessed through object instances......, not as static components of a class. When used as types, virtual classes depend upon object identity - each object instance introduces a new family of virtual class types. Virtual classes support large scale program composition techniques, including higher-order hierarchies and family polymorphism. The original...... definition of virtual classes in BETA left open the question of static type safety, since some type errors were not caught until runtime. Later the languages Caesar and gbeta have used a more strict static analysis in order to ensure static type safety. However, the existence of a sound, statically typed...

  13. RxClass

    U.S. Department of Health & Human Services — The RxClass Browser is a web application for exploring and navigating through the class hierarchies to find the RxNorm drug members associated with each class....

  14. Brightest Cluster Galaxies in the Extended GMRT radio halo cluster sample. Radio properties and cluster dynamics

    Kale, Ruta; Cassano, Rossella; Giacintucci, Simona; Bardelli, sandro; Dallacasa, Daniele; Zucca, Elena


    Brightest Cluster Galaxies (BCGs) show exceptional properties over the whole electromagnetic spectrum. Their special location at the centres of galaxy clusters raises the question of the role of the environment on their radio properties. To decouple the effect of the galaxy mass and of the environment in their statistical radio properties, we investigate the possible dependence of the occurrence of radio loudness and of the fractional radio luminosity function on the dynamical state of the hosting cluster. We studied the radio properties of the BCGs in the Extended GMRT Radio Halo Survey (EGRHS). We obtained a statistical sample of 59 BCGs, which was divided into two classes, depending on the dynamical state of the host cluster, i.e. merging (M) and relaxed (R). Among the 59 BCGs, 28 are radio-loud, and 31 are radio--quiet. The radio-loud sources are located favourably located in relaxed clusters (71\\%), while the reverse is true for the radio-quiet BCGs, mostly located in merging systems (81\\%). The fraction...

  15. SACS: Spitzer Archival Cluster Survey

    Stern, Daniel

    by the MIR color selection targets a key epoch in cluster development, when star formation is shutting down and the galaxies are becoming passive. Massive clusters also distort space-time around them, creating powerful gravitational telescopes that lens the distant universe. This both allows detailed studies of the lensed objects with otherwise unachievable sensitivity, as well as provides a unique probe of the mass distribution in the lensing cluster. In terms of cosmology, clusters are the most massive structures in the universe, and their space density is sensitive to basic cosmological parameters. Clusters identified by this program will become a lasting legacy of Spitzer, providing exciting targets for Chandra, Hubble, James Webb Space Telescope (JWST), Astro-H, Athena, as well as future 30-m class ground-based telescopes (e.g., GMT, ELT, TMT). The upcoming large-scale, space-based surveys of eROSITA, Euclid, and WFIRST all have distant cluster studies as key scientific goals. Our proposed survey will provide new high redshift targets for those satellites, enabling unique, exciting multi-wavelength studies of the Spitzer-selected sample, as well as a training set to identify additional high-redshift clusters outside of the Spitzer footprint.


    HU Ruifei; YIN Guofu; TAN Ying; CAI Peng


    Based on the analysis of features of the grid-based clustering method-clustering in quest(CLIQUE) and density-based clustering method-density-based spatial clustering of applications with noise (DBSCAN), a new clustering algorithm named cooperative clustering based on grid and density(CLGRID) is presented. The new algorithm adopts an equivalent rule of regional inquiry and density unit identification. The central region of one class is calculated by the grid-based method and the margin region by a density-based method. By clustering in two phases and using only a small number of seed objects in representative units to expand the cluster, the frequency of region query can be decreased, and consequently the cost of time is reduced. The new algorithm retains positive features of both grid-based and density-based methods and avoids the difficulty of parameter searching. It can discover clusters of arbitrary shape with high efficiency and is not sensitive to noise. The application of CLGRID on test data sets demonstrates its validity and higher efficiency, which contrast with traditional DBSCAN with R* tree.

  17. Partitional clustering algorithms


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

  18. Clustering and Community Detection with Imbalanced Clusters

    Aksoylar, Cem; Qian, Jing; Saligrama, Venkatesh


    Spectral clustering methods which are frequently used in clustering and community detection applications are sensitive to the specific graph constructions particularly when imbalanced clusters are present. We show that ratio cut (RCut) or normalized cut (NCut) objectives are not tailored to imbalanced cluster sizes since they tend to emphasize cut sizes over cut values. We propose a graph partitioning problem that seeks minimum cut partitions under minimum size constraints on partitions to de...

  19. Search for cooling flows in southern X-ray clusters of galaxies

    Nesci, R.; Altamore, A.


    EFOSC spectroscopic observations of 20 galaxies belonging to 10 distant X-ray southern clusters, selected from the HEAO1-A1 catalogue, are presented. The redshifts derived for the observed clusters (z = 0.15) are systematically lower than expected from their Duus and Newell distance class, but in good agreement with the distance class reported in the southern clusters catalog by Abell, Corwin, and Olowin. In the central cluster galaxies, no emission lines typical of cooling flow clusters, with negative results have been found. The '4000 break' amplitudes also have values typical for normal elliptical galaxies. These findings suggest that the observed clusters are unlikely to have strong ongoing cooling flows.

  20. Clusters of galaxies associated with quasars. I. 3C 206

    Ellingson, E.; Yee, H.K.C.; Green, R.F.; Kinman, T.D. (Steward Observatory, Tucson, AZ (USA); Montreal Universite (Canada); Kitt Peak National Observatory, Tucson, AZ (USA))


    Multislit spectroscopy and three-color CCD photometry of the galaxies in the cluster associated with the quasar 3C 206 (PKS 0837-12) at z = 0.198 are presented. This cluster is the richest environment of any low-redshift quasar observed in an Abell richness class 1 cluster. The cluster has a very flattened structure and a very concentrated core about the quasar. Most of the galaxies in this field have colors and luminosities consistent with normal galaxies at this redshift. The background-corrected blue fraction of galaxies is consistent with values for other rich clusters. The existence of several blue galaxies in the concentrated cluster core is an anomaly for a region of such high galaxy density, however, suggesting the absence of a substantial intracluster medium. This claim is supported by the Fanaroff-Riley (1974) class II morphology of the radio source. The velocity dispersion calculated from 11 spectroscopically confirmed cluster members is 500 + or - 110 km/s, which is slightly lower than the average for Abell class 1 clusters. A high frequency of interaction between the quasar host galaxy and cluster core members at low relative velocities, and a low intracluster gas pressure, may comprise a favorable environment for quasar activity. The properties of the cluster of galaxies associated with 3C 206 are consistent with this model. 59 refs.

  1. Cluster headaches.

    Ryan, R E; Ryan, R E


    The patient with cluster headaches will be afflicted with the most severe type of pain that one will encounter. If the physician can do something to help this patient either by symptomatic or, more importantly, prophylactic treatment, he or she will have a most thankful patient. This type of headache is seen most frequently in men, and occurs in a cyclic manner. During an acute cycle, the patient will experience a daily type of pain that may occur many times per day. The pain is usually unilateral and may be accompanied by unilateral lacrimation, conjunctivitis, and clear rhinorrhea. Prednisone is the first treatment we employ. Patients are seen for follow-up approximately twice a week, and their medication is lowered in an appropriate manner, depending on their response to the treatment. Regulation of dosage has to be individualized, and when one reaches the lower dose such as 5 to 10 mg per day, the drug may have to be tapered more slowly, or even maintained at that level for a period of time to prevent further recurrence of symptoms. We frequently will use an intravenous histamine desensitization technique to prevent further attacks. We will give the patient an ergotamine preparation to use for symptomatic relief. As these patients often have headaches during the middle of the night, we will place the patient on a 2-mg ergotamine preparation to take prior to going to bed in the evening. This often works in a prophylactic nature, and prevents the nighttime occurrence of a headache. We believe that following these principles to make the accurate diagnosis and institute the proper therapy will help the practicing otolaryngologist recognize and treat patients suffering from this severe pain.

  2. Factorial PD-Clustering

    Tortora, Cristina; Summa, Mireille Gettler


    Factorial clustering methods have been developed in recent years thanks to the improving of computational power. These methods perform a linear transformation of data and a clustering on transformed data optimizing a common criterion. Factorial PD-clustering is based on Probabilistic Distance clustering (PD-clustering). PD-clustering is an iterative, distribution free, probabilistic, clustering method. Factorial PD-clustering make a linear transformation of original variables into a reduced number of orthogonal ones using a common criterion with PD-Clustering. It is demonstrated that Tucker 3 decomposition allows to obtain this transformation. Factorial PD-clustering makes alternatively a Tucker 3 decomposition and a PD-clustering on transformed data until convergence. This method could significantly improve the algorithm performance and allows to work with large dataset, to improve the stability and the robustness of the method.

  3. Possibilistic Exponential Fuzzy Clustering

    Kiatichai Treerattanapitak; Chuleerat Jaruskulchai


    Generally,abnormal points (noise and outliers) cause cluster analysis to produce low accuracy especially in fuzzy clustering.These data not only stay in clusters but also deviate the centroids from their true positions.Traditional fuzzy clustering like Fuzzy C-Means (FCM) always assigns data to all clusters which is not reasonable in some circumstances.By reformulating objective function in exponential equation,the algorithm aggressively selects data into the clusters.However noisy data and outliers cannot be properly handled by clustering process therefore they are forced to be included in a cluster because of a general probabilistic constraint that the sum of the membership degrees across all clusters is one.In order to improve this weakness,possibilistic approach relaxes this condition to improve membership assignment.Nevertheless,possibilistic clustering algorithms generally suffer from coincident clusters because their membership equations ignore the distance to other clusters.Although there are some possibilistic clustering approaches that do not generate coincident clusters,most of them require the right combination of multiple parameters for the algorithms to work.In this paper,we theoretically study Possibilistic Exponential Fuzzy Clustering (PXFCM) that integrates possibilistic approach with exponential fuzzy clustering.PXFCM has only one parameter and not only partitions the data but also filters noisy data or detects them as outliers.The comprehensive experiments show that PXFCM produces high accuracy in both clustering results and outlier detection without generating coincident problems.

  4. A Survey of Popular R Packages for Cluster Analysis

    Flynt, Abby; Dean, Nema


    Cluster analysis is a set of statistical methods for discovering new group/class structure when exploring data sets. This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA…

  5. DYNER: A DYNamic ClustER for Education and Research

    Kehagias, Dimitris; Grivas, Michael; Mamalis, Basilis; Pantziou, Grammati


    Purpose: The purpose of this paper is to evaluate the use of a non-expensive dynamic computing resource, consisting of a Beowulf class cluster and a NoW, as an educational and research infrastructure. Design/methodology/approach: Clusters, built using commodity-off-the-shelf (COTS) hardware components and free, or commonly used, software, provide…

  6. FarMon:An Extensible,Efficient Cluster Monitoring System

    YongFAN; MeiMA; 等


    This paper presents the design and implementation of FarMon-a flexible event monitoring system for computing cluster,Using several techniques including DCL (Dynamic Class Loading)technique,module publish/subacribe/unsubscribe protocol and directory service,we create a high efficient,high extensible and high portable cluster monitoring system.

  7. On differential characteristic classes

    Ho, Man-Ho


    In this paper we give explicit formulas of differential characteristic classes of principal $G$-bundles with connections and prove their expected properties. In particular, we obtain explicit formulas for differential Chern classes, differential Pontryagin classes and differential Euler class. Furthermore, we show that the differential Chern class is the unique natural transformation from (Simons-Sullivan) differential $K$-theory to (Cheeger-Simons) differential characters that is compatible ...

  8. Dissolution of Globular Clusters

    Baumgardt, Holger


    Globular clusters are among the oldest objects in galaxies, and understanding the details of their formation and evolution can bring valuable insight into the early history of galaxies. This review summarises the current knowledge about the dissolution of star clusters and discusses the implications of star cluster dissolution for the evolution of the mass function of star cluster systems in galaxies.

  9. Structures of Mn clusters

    Tina M Briere; Marcel H F Sluiter; Vijay Kumar; Yoshiyuki Kawazoe


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

  10. Contextualizing the Cluster

    Giacomin, Valeria

    This dissertation examines the case of the palm oil cluster in Malaysia and Indonesia, today one of the largest agricultural clusters in the world. My analysis focuses on the evolution of the cluster from the 1880s to the 1970s in order to understand how it helped these two countries to integrate......-researched topic in the cluster literature – the emergence of clusters, their governance and institutional change, and competition between rival cluster locations – through the case of the Southeast Asian palm oil cluster....

  11. Loosely coupled class families

    Ernst, Erik


    are expressed using virtual classes seem to be very tightly coupled internally. While clients have achieved the freedom to dynamically use one or the other family, it seems that any given family contains a xed set of classes and we will need to create an entire family of its own just in order to replace one......Families of mutually dependent classes that may be accessed polymor- phically provide an advanced tool for separation of concerns, in that it enables client code to use a group of instances of related classes safely without depending on the exact classes involved. However, class families which...... of the members with another class. This paper shows how to express class families in such a manner that the classes in these families can be used in many dierent combinations, still enabling family polymorphism and ensuring type safety....

  12. Clustering in analytical chemistry.

    Drab, Klaudia; Daszykowski, Michal


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

  13. RNA secondary structures, polygon dissections and clusters

    Marsh, Robert J


    We show that the notion of induction introduced by Cassaigne, Ferenczi and Zamboni for trees of relations arising in the context of interval exchange relations can be generalised to the case of an arbitrary number of possible edge labels. We prove that the equivalence classes of its transitive closure can still be characterised via a circular order on the trees of relations in this case. We compute the cardinalities of these equivalence classes and show that the sequence of cardinalities, for a fixed number of possible edge labels, is a convolution of a Fuss-Catalan sequence. As in the original case, the equivalence classes are in bijection with a set of pseudoknot-free secondary structures arising from the study of RNA; we show that a natural subset of this set is in bijection with a set of m-clusters (in the cluster algebra sense).

  14. Hierarchical modeling of cluster size in wildlife surveys

    Royle, J. Andrew


    Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

  15. Identification of rural landscape classes through a GIS clustering method

    Irene Diti


    Full Text Available The paper presents a methodology aimed at supporting the rural planning process. The analysis of the state of the art of local and regional policies focused on rural and suburban areas, and the study of the scientific literature in the field of spatial analysis methodologies, have allowed the definition of the basic concept of the research. The proposed method, developed in a GIS, is based on spatial metrics selected and defined to cover various agricultural, environmental, and socio-economic components. The specific goal of the proposed methodology is to identify homogeneous extra-urban areas through their objective characterization at different scales. Once areas with intermediate urban-rural characters have been identified, the analysis is then focused on the more detailed definition of periurban agricultural areas. The synthesis of the results of the analysis of the various landscape components is achieved through an original interpretative key which aims to quantify the potential impacts of rural areas on the urban system. This paper presents the general framework of the methodology and some of the main results of its first implementation through an Italian case study.

  16. Cool Core Clusters from Cosmological Simulations

    Rasia, E; Murante, G; Planelles, S; Beck, A M; Biffi, V; Ragone-Figueroa, C; Granato, G L; Steinborn, L K; Dolag, K


    We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core and non-cool-core clusters. Our simulations include the effects of stellar and AGN feedback and are based on an improved version of the Smoothed-Particle-Hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, our primary diagnostic to classify the degree of cool-coreness of clusters, and on the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of cool-core systems, to nearly flat core isentropic profiles, characteristic of non cool-core systems. Using observational criteria to distinguish between the two classes of...

  17. Class 1 Areas

    U.S. Environmental Protection Agency — A "Class 1" area is a geographic area recognized by the EPA as being of the highest environmental quality and requiring maximum protection. Class I areas are areas...

  18. PRCR Classes and Activities

    Town of Cary, North Carolina — This data is specific to Parks and Recreation classes, workshops, and activities within the course catalog. It contains an entry for upcoming classes.*This data set...

  19. What Makes Clusters Decline?

    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....... The longitudinal study on the high-tech cluster reveals that technological lock-in and exit of key firms have contributed to decline. Entrepreneurship has a positive effect on the cluster’s adaptive capabilities, while multinational companies have contradicting effects by bringing in new resources to the cluster...

  20. Education and Class.

    Van Galen, Jane A.


    The working class is nearly invisible in multicultural education literature. Examines the possibilities of a more careful foregrounding of the complexities of social class in shaping life chances, focusing on the educational experiences of working class students and discussing the poor in order to promote understanding of the potential of teacher…

  1. Coupled Two-Way Clustering Analysis of Breast Cancer and Colon Cancer Gene Expression Data

    Getz, G; Kela, I; Domany, E; Notterman, D A; Getz, Gad; Gal, Hilah; Kela, Itai; Domany, Eytan; Notterman, Dan A.


    We present and review Coupled Two Way Clustering, a method designed to mine gene expression data. The method identifies submatrices of the total expression matrix, whose clustering analysis reveals partitions of samples (and genes) into biologically relevant classes. We demonstrate, on data from colon and breast cancer, that we are able to identify partitions that elude standard clustering analysis.

  2. Clustering Algorithm Based on Crowding Niche%小生境排挤聚类算法

    业宁; 董逸生


    A new clustering algorithm is proposed in this paper, which is based on crowding niche. Homogeneityspontaneous to withstands heterogeneity when organisms are evolving. Contemporary, Individual in same class com-pete each other to strive for limited resource. Individual that has bad fitness will be eliminated. We propose a cluster-ing algorithm based on this idea. Experiment evaluation has proved its efficiency.

  3. Determining the Optimal Number of Clusters with the Clustergram

    Fluegemann, Joseph K.; Davies, Misty D.; Aguirre, Nathan D.


    Cluster analysis aids research in many different fields, from business to biology to aerospace. It consists of using statistical techniques to group objects in large sets of data into meaningful classes. However, this process of ordering data points presents much uncertainty because it involves several steps, many of which are subject to researcher judgment as well as inconsistencies depending on the specific data type and research goals. These steps include the method used to cluster the data, the variables on which the cluster analysis will be operating, the number of resulting clusters, and parts of the interpretation process. In most cases, the number of clusters must be guessed or estimated before employing the clustering method. Many remedies have been proposed, but none is unassailable and certainly not for all data types. Thus, the aim of current research for better techniques of determining the number of clusters is generally confined to demonstrating that the new technique excels other methods in performance for several disparate data types. Our research makes use of a new cluster-number-determination technique based on the clustergram: a graph that shows how the number of objects in the cluster and the cluster mean (the ordinate) change with the number of clusters (the abscissa). We use the features of the clustergram to make the best determination of the cluster-number.

  4. Class, Culture and Politics

    Harrits, Gitte Sommer


    Even though contemporary discussions of class have moved forward towards recognizing a multidimensional concept of class, empirical analyses tend to focus on cultural practices in a rather narrow sense, that is, as practices of cultural consumption or practices of education. As a result......, discussions within political sociology have not yet utilized the merits of a multidimensional conception of class. In light of this, the article suggests a comprehensive Bourdieusian framework for class analysis, integrating culture as both a structural phenomenon co-constitutive of class and as symbolic...

  5. Persian Preposition Classes

    Marina Pantcheva


    Full Text Available In this paper I present the prepositional system in Persian. I show that Persian prepositions can be divided into three classes (Class 1, Class 2a and Class 2b which exhibit distinct syntactic behavior. Then I examine the question of the categorial status of Class 2 prepositions and demonstrate that they are not to be regarded as nouns. Finally I present the extended PP projection of Persian spatial prepositions and argue for a feature-based analysis of the properties they manifest.

  6. The Cluster Substructure - Alignment Connection

    Plionis, Manolis


    Using the APM cluster data we investigate whether the dynamical status of clusters is related to the large-scale structure of the Universe. We find that cluster substructure is strongly correlated with the tendency of clusters to be aligned with their nearest neighbour and in general with the nearby clusters that belong to the same supercluster. Furthermore, dynamically young clusters are more clustered than the overall cluster population. These are strong indications that cluster develop in ...

  7. Nuclear Clusters in Astrophysics

    Kubono, S.; Binh, Dam N.; Hayakawa, S.; Hashimoto, H.; Kahl, D.; Wakabayashi, Y.; Yamaguchi, H. [Center for Nuclear Study (CNS), University of Tokyo, Wako Branch at RIKEN 2-1 Hirosawa, Wako, Saitama, 351-0198 (Japan); Teranishi, T. [Department of Physics, Kyushu University, Fukuoka, 812-8581 (Japan); Iwasa, N. [Department of Physics, Tohoku University, Sendai, 980-8578 (Japan); Komatsubara, T. [Department of Physics, Tsukuba University, Ibaraki, 305-8571 (Japan); Kato, S. [Department of Physics, Yamagata University, Yamagata, 990-8560 (Japan); Khiem, Le H. [Institute of Physics, Vietnam Academy for Science and Technology, Hanoi (Viet Nam)


    The role of nuclear clustering is discussed for nucleosynthesis in stellar evolution with Cluster Nucleosynthesis Diagram (CND) proposed before. Special emphasis is placed on alpha-induced stellar reactions together with molecular states for O and C burning.

  8. Niching method using clustering crowding

    GUO Guan-qi; GUI Wei-hua; WU Min; YU Shou-yi


    This study analyzes drift phenomena of deterministic crowding and probabilistic crowding by using equivalence class model and expectation proportion equations. It is proved that the replacement errors of deterministic crowding cause the population converging to a single individual, thus resulting in premature stagnation or losing optional optima. And probabilistic crowding can maintain equilibrium multiple subpopulations as the population size is adequate large. An improved niching method using clustering crowding is proposed. By analyzing topology of fitness landscape using hill valley function and extending the search space for similarity analysis, clustering crowding determines the locality of search space more accurately, thus greatly decreasing replacement errors of crowding. The integration of deterministic and probabilistic replacement increases the capacity of both parallel local hill climbing and maintaining multiple subpopulations. The experimental results optimizing various multimodal functions show that,the performances of clustering crowding, such as the number of effective peaks maintained, average peak ratio and global optimum ratio are uniformly superior to those of the evolutionary algorithms using fitness sharing, simple deterministic crowding and probabilistic crowding.

  9. [Pathophysiology of cluster headache].

    Donnet, Anne


    The aetiology of cluster headache is partially unknown. Three areas are involved in the pathogenesis of cluster headache: the trigeminal nociceptive pathways, the autonomic system and the hypothalamus. The cluster headache attack involves activation of the trigeminal autonomic reflex. A dysfunction located in posterior hypothalamic gray matter is probably pivotal in the process. There is a probable association between smoke exposure, a possible genetic predisposition and the development of cluster headache.

  10. Cluster Physics with Merging Galaxy Clusters

    Sandor M. Molnar


    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.

  11. The Durban Auto Cluster

    Lorentzen, Jochen; Robbins, Glen; Barnes, Justin


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

  12. Cluster-lensing: A Python Package for Galaxy Clusters and Miscentering

    Ford, Jes; VanderPlas, Jake


    We describe a new open source package for calculating properties of galaxy clusters, including Navarro, Frenk, and White halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density {{Σ }}(R) and differential surface mass density {{Δ }}{{Σ }}(R) profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo. Full documentation, source code, and installation instructions are available at

  13. Class Generation for Numerical Wind Atlases

    Cutler, N.J.; Jørgensen, B.H.; Ersbøll, Bjarne Kjær;


    A new optimised clustering method is presented for generating wind classes for mesoscale modelling to produce numerical wind atlases. It is compared with the existing method of dividing the data in 12 to 16 sectors, 3 to 7 wind-speed bins and dividing again according to the stability of the atmos......A new optimised clustering method is presented for generating wind classes for mesoscale modelling to produce numerical wind atlases. It is compared with the existing method of dividing the data in 12 to 16 sectors, 3 to 7 wind-speed bins and dividing again according to the stability...... of the atmosphere. Wind atlases are typically produced using many years of on-site wind observations at many locations. Numerical wind atlases are the result of mesoscale model integrations based on synoptic scale wind climates and can be produced in a number of hours of computation. 40 years of twice daily NCEP....../NCAR reanalysis geostrophic wind data (approximately 200 km resolution) are represented in typically around 150 classes, each with a frequency of occurrence. The mean wind-speed and direction in each class is used as input data to force the mesoscale model, which downscales the wind to a 5 km resolution while...

  14. Final Report of the Evaluation of the 1969-1970 Benjamin Franklin Cluster Program: Programs and Patterns for Disadvantaged High School Students. ESEA Title I.

    Hoffman, Louis J.

    The Cluster Program at Benjamin Franklin High School, funded under Title I of the 1965 Elementary Secondary Education Act, is designed to be a school within a school in which 249 ninth grade students attend classes in two separate clusters. Each cluster is formulated such that all students receive instruction from five teachers in classes whose…

  15. Simultaneous clustering of multiple gene expression and physical interaction datasets.

    Manikandan Narayanan


    Full Text Available Many genome-wide datasets are routinely generated to study different aspects of biological systems, but integrating them to obtain a coherent view of the underlying biology remains a challenge. We propose simultaneous clustering of multiple networks as a framework to integrate large-scale datasets on the interactions among and activities of cellular components. Specifically, we develop an algorithm JointCluster that finds sets of genes that cluster well in multiple networks of interest, such as coexpression networks summarizing correlations among the expression profiles of genes and physical networks describing protein-protein and protein-DNA interactions among genes or gene-products. Our algorithm provides an efficient solution to a well-defined problem of jointly clustering networks, using techniques that permit certain theoretical guarantees on the quality of the detected clustering relative to the optimal clustering. These guarantees coupled with an effective scaling heuristic and the flexibility to handle multiple heterogeneous networks make our method JointCluster an advance over earlier approaches. Simulation results showed JointCluster to be more robust than alternate methods in recovering clusters implanted in networks with high false positive rates. In systematic evaluation of JointCluster and some earlier approaches for combined analysis of the yeast physical network and two gene expression datasets under glucose and ethanol growth conditions, JointCluster discovers clusters that are more consistently enriched for various reference classes capturing different aspects of yeast biology or yield better coverage of the analysed genes. These robust clusters, which are supported across multiple genomic datasets and diverse reference classes, agree with known biology of yeast under these growth conditions, elucidate the genetic control of coordinated transcription, and enable functional predictions for a number of uncharacterized genes.

  16. Cluster analysis for applications

    Anderberg, Michael R


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

  17. Management of cluster headache

    Tfelt-Hansen, Peer C; Jensen, Rigmor H


    and agitation. Patients may have up to eight attacks per day. Episodic cluster headache (ECH) occurs in clusters of weeks to months duration, whereas chronic cluster headache (CCH) attacks occur for more than 1 year without remissions. Management of cluster headache is divided into acute attack treatment....... In drug-resistant CCH, neuromodulation with either occipital nerve stimulation or deep brain stimulation of the hypothalamus is an alternative treatment strategy. For most cluster headache patients there are fairly good treatment options both for acute attacks and for prophylaxis. The big problem...

  18. Cluster Decline and Resilience

    Østergaard, Christian Richter; Park, Eun Kyung

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

  19. Class network routing

    Bhanot, Gyan; Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.


    Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

  20. Clustering high dimensional data

    Assent, Ira


    to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...... that provide different cluster models and different algorithmic approaches for cluster detection. Common to all approaches is the fact that they require some underlying assessment of similarity between data objects. In this article, we provide an overview of the effects of high-dimensional spaces...

  1. Clusters in nuclei

    Beck, Christian

    Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This third volume follows the successful Lect. Notes Phys. 818 (Vol. 1) and 848 (Vol. 2), and comprises six extensive lectures covering the following topics:  - Gamma Rays and Molecular Structure - Faddeev Equation Approach for Three Cluster Nuclear Reactions - Tomography of the Cluster Structure of Light Nuclei Via Relativistic Dissociation - Clustering Effects Within the Dinuclear Model : From Light to Hyper-heavy Molecules in Dynamical Mean-field Approach - Clusterization in Ternary Fission - Clusters in Light N...

  2. Unconventional methods for clustering

    Kotyrba, Martin


    Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is the main task of exploratory data mining and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics. The topic of this paper is one of the modern methods of clustering namely SOM (Self Organising Map). The paper describes the theory needed to understand the principle of clustering and descriptions of algorithm used with clustering in our experiments.

  3. Spatial cluster modelling

    Lawson, Andrew B


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

  4. Fostering a Middle Class



    Though there is no official definition of "middle class" in China,the tag has become one few Chinese people believe they deserve anyway.In early August,the Chinese Academy of Social Sciences released a report on China's urban development,saying China had a middle-class population of 230 million in 2009,or 37 percent of its urban residents.It also forecast half of city dwellers in China would be part of the middle class by 2023.

  5. ABS 497 Complete Class



    ABS 497 Complete Class   To purchase this material click below link   For more classes visit   ABS 497 Week 1 Assignment Community Change ABS 497 Week 1 DQ 1 Fabian's Story ABS 497 Week 1 DQ 2 Doug's Story ABS 497 Week 2 DQ 1 Parenting Styles ABS 497 Week 2 DQ 2 Ethnicity and Learning Theory ABS 497 Week 3 ...

  6. CLEAN: CLustering Enrichment ANalysis

    Medvedovic Mario


    Full Text Available Abstract Background Integration of biological knowledge encoded in various lists of functionally related genes has become one of the most important aspects of analyzing genome-wide functional genomics data. In the context of cluster analysis, functional coherence of clusters established through such analyses have been used to identify biologically meaningful clusters, compare clustering algorithms and identify biological pathways associated with the biological process under investigation. Results We developed a computational framework for analytically and visually integrating knowledge-based functional categories with the cluster analysis of genomics data. The framework is based on the simple, conceptually appealing, and biologically interpretable gene-specific functional coherence score (CLEAN score. The score is derived by correlating the clustering structure as a whole with functional categories of interest. We directly demonstrate that integrating biological knowledge in this way improves the reproducibility of conclusions derived from cluster analysis. The CLEAN score differentiates between the levels of functional coherence for genes within the same cluster based on their membership in enriched functional categories. We show that this aspect results in higher reproducibility across independent datasets and produces more informative genes for distinguishing different sample types than the scores based on the traditional cluster-wide analysis. We also demonstrate the utility of the CLEAN framework in comparing clusterings produced by different algorithms. CLEAN was implemented as an add-on R package and can be downloaded at The package integrates routines for calculating gene specific functional coherence scores and the open source interactive Java-based viewer Functional TreeView (FTreeView. Conclusion Our results indicate that using the gene-specific functional coherence score improves the reproducibility of the

  7. Tailor-Made Classes.

    Schreirer, Barbara A.


    Adapted teaching materials and procedures were developed at Florida State University to help visually handicapped students in the public schools participate in a mainstreamed home economics class. (MF)

  8. A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

    Vera, J. Fernando; Macias, Rodrigo; Heiser, Willem J.


    In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of…

  9. A Novel Clustering Algorithm Inspired by Membrane Computing

    Hong Peng


    Full Text Available P systems are a class of distributed parallel computing models; this paper presents a novel clustering algorithm, which is inspired from mechanism of a tissue-like P system with a loop structure of cells, called membrane clustering algorithm. The objects of the cells express the candidate centers of clusters and are evolved by the evolution rules. Based on the loop membrane structure, the communication rules realize a local neighborhood topology, which helps the coevolution of the objects and improves the diversity of objects in the system. The tissue-like P system can effectively search for the optimal partitioning with the help of its parallel computing advantage. The proposed clustering algorithm is evaluated on four artificial data sets and six real-life data sets. Experimental results show that the proposed clustering algorithm is superior or competitive to k-means algorithm and several evolutionary clustering algorithms recently reported in the literature.

  10. A New Feature Selection Method for Text Clustering

    XU Junling; XU Baowen; ZHANG Weifeng; CUI Zifeng; ZHANG Wei


    Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this paper, a new feature selection method for text clustering based on expectation maximization and cluster validity is proposed. It uses supervised feature selection method on the intermediate clustering result which is generated during iterative clustering to do feature selection for text clustering; meanwhile, the Davies-Bouldin's index is used to evaluate the intermediate feature subsets indirectly. Then feature subsets are selected according to the curve of the DaviesBouldin's index. Experiment is carried out on several popular datasets and the results show the advantages of the proposed method.

  11. Electronic Structure and Geometries of Small Compound Metal Clusters



    During the tenure of the DOE grant DE-FG05-87EI145316 we have concentrated on equilibrium geometries, stability, and the electronic structure of transition metal-carbon clusters (met-cars), clusters designed to mimic the chemistry of atoms, and reactivity of homo-nuclear metal clusters and ions with various reactant molecules. It is difficult to describe all the research the authors have accomplished as they have published 38 papers. In this report, they outline briefly the salient features of their work on the following topics: (1) Designer Clusters: Building Blocks for a New Class of Solids; (2) Atomic Structure, Stability, and Electronic Properties of Metallo-Carbohedrenes; (3) Reactivity of Metal Clusters with H{sub 2} and NO; and (4) Anomalous Spectroscopy of Li{sub 4} Clusters.

  12. Loop groups, Clusters, Dimers and Integrable systems

    Fock, V V


    We describe a class of integrable systems on Poisson submanifolds of the affine Poisson-Lie groups $\\widehat{PGL}(N)$, which can be enumerated by cyclically irreducible elements the co-extended affine Weyl groups $(\\widehat{W}\\times \\widehat{W})^\\sharp$. Their phase spaces admit cluster coordinates, whereas the integrals of motion are cluster functions. We show, that this class of integrable systems coincides with the constructed by Goncharov and Kenyon out of dimer models on a two-dimensional torus and classified by the Newton polygons. We construct the correspondence between the Weyl group elements and polygons, demonstrating that each particular integrable model admits infinitely many realisations on the Poisson-Lie groups. We also discuss the particular examples, including the relativistic Toda chains and the Schwartz-Ovsienko-Tabachnikov pentagram map.

  13. Agricultural Clusters in the Netherlands

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


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

  14. Definition of supertypes for HLA molecules using clustering of specificity matrices

    Lund, Ole; Nielsen, Morten; Kesmir, Can;


    a novel method for clustering sequence motifs. We construct hidden Markov models for HLA class I molecules using a Gibbs sampling procedure and use the similarities among these to define clusters of specificities. These clusters are extensions of the previously suggested ones. We suggest splitting some...... report that the previously observed specificities of these class II molecules can be clustered into nine classes, which only partly correspond to the serological classification. We show that classification of HLA molecules may be done in a uniform and automated way. The definition of clusters allows......Major histocompatibility complex (MHC) proteins are encoded by extremely polymorphic genes and play a crucial role in immunity. However, not all genetically different MHC molecules are functionally different. Sette and Sidney (1999) have defined nine HLA class I supertypes and showed that with only...

  15. The Conversation Class

    Jackson, Acy L.


    The conversation class occupies a unique place in the process of learning English as a second or foreign language. From the author's own experience in conducting special conversation classes with Persian-speaking adults, he has drawn up a number of simple but important guidelines, some of which he hopes may provide helpful suggestions for the…

  16. Universality classes of inflation

    Roest, Diederik


    We investigate all single-field, slow-roll inflationary models whose slow-roll parameters scale as 1/N in the limit of a large number of e-folds N. We proof that all such models belong to two universality classes, characterised by a single parameter. One class contains small field models like hillto

  17. Cutting Class Harms Grades

    Taylor, Lewis A., III


    An accessible business school population of undergraduate students was investigated in three independent, but related studies to determine effects on grades due to cutting class and failing to take advantage of optional reviews and study quizzes. It was hypothesized that cutting classes harms exam scores, attending preexam reviews helps exam…



    Classifying the middle class remains controversial despite its alleged growth China’s cities housed more than 230 million middle-class residents in 2009 or 37 percent of the urban population,according to the 2011 Blue Book of Cities in China released on August 3.




    China's cities housed more than 230 million middle-class residents in 2009ot 37 percent of the urban population,according to the 2011 Blue Book of Cities in China released on August 3.In China's main urban centers,Beijing and Shanghai,the middle class accounted for 46 percent and 38 percent,respectively,of the local population.

  20. Generalized Fourier transforms classes

    Berntsen, Svend; Møller, Steen


    The Fourier class of integral transforms with kernels $B(\\omega r)$ has by definition inverse transforms with kernel $B(-\\omega r)$. The space of such transforms is explicitly constructed. A slightly more general class of generalized Fourier transforms are introduced. From the general theory...

  1. Teaching Social Class

    Tablante, Courtney B.; Fiske, Susan T.


    Discussing socioeconomic status in college classes can be challenging. Both teachers and students feel uncomfortable, yet social class matters more than ever. This is especially true, given increased income inequality in the United States and indications that higher education does not reduce this inequality as much as many people hope. Resources…


    Rasia, E.; Borgani, S.; Murante, G.; Planelles, S.; Biffi, V.; Granato, G. L. [INAF, Osservatorio Astronomico di Trieste, via Tiepolo 11, I-34131, Trieste (Italy); Beck, A. M.; Steinborn, L. K.; Dolag, K. [Universitäts-Sternwarte München, Scheinerstr.1, D-81679 München (Germany); Ragone-Figueroa, C., E-mail: [Instituto de Astronomá Teórica y Experimental (IATE), Consejo Nacional de Investigaciones Cientiíficas y Técnicas de la República Argentina (CONICET), Observatorio Astronómico, Universidad Nacional de Córdoba, Laprida 854, X5000BGR, Córdoba (Argentina)


    We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and active galactic nucleus (AGN) feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of CC systems, to nearly flat core isentropic profiles, characteristic of NCC systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and observations. Furthermore, we also find that simulated CC clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic CC structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.

  3. Mapping Cigarettes Similarities using Cluster Analysis Methods

    Lorentz Jäntschi


    Full Text Available The aim of the research was to investigate the relationship and/or occurrences in and between chemical composition information (tar, nicotine, carbon monoxide, market information (brand, manufacturer, price, and public health information (class, health warning as well as clustering of a sample of cigarette data. A number of thirty cigarette brands have been analyzed. Six categorical (cigarette brand, manufacturer, health warnings, class and four continuous (tar, nicotine, carbon monoxide concentrations and package price variables were collected for investigation of chemical composition, market information and public health information. Multiple linear regression and two clusterization techniques have been applied. The study revealed interesting remarks. The carbon monoxide concentration proved to be linked with tar and nicotine concentration. The applied clusterization methods identified groups of cigarette brands that shown similar characteristics. The tar and carbon monoxide concentrations were the main criteria used in clusterization. An analysis of a largest sample could reveal more relevant and useful information regarding the similarities between cigarette brands.

  4. Clustering Categorical Data:A Cluster Ensemble Approach

    He Zengyou(何增友); Xu Xiaofei; Deng Shengchun


    Clustering categorical data, an integral part of data mining,has attracted much attention recently. In this paper, the authors formally define the categorical data clustering problem as an optimization problem from the viewpoint of cluster ensemble, and apply cluster ensemble approach for clustering categorical data. Experimental results on real datasets show that better clustering accuracy can be obtained by comparing with existing categorical data clustering algorithms.

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

    Christiansen, Lasse Engbo; Andersen, Jens Strodl


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

  6. Disentangling Porterian Clusters

    Jagtfelt, Tue

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

  7. Melting of sodium clusters

    Reyes-Nava, J A; Beltran, M R; Michaelian, K


    Thermal stability properties and the melting-like transition of Na_n, n=13-147, clusters are studied through microcanonical molecular dynamics simulations. The metallic bonding in the sodium clusters is mimicked by a many-body Gupta potential based on the second moment approximation of a tight-binding Hamiltonian. The characteristics of the solid-to-liquid transition in the sodium clusters are analyzed by calculating physical quantities like caloric curves, heat capacities, and root-mean-square bond length fluctuations using simulation times of several nanoseconds. Distinct melting mechanisms are obtained for the sodium clusters in the size range investigated. The calculated melting temperatures show an irregular variation with the cluster size, in qualitative agreement with recent experimental results. However, the calculated melting point for the Na_55 cluster is about 40 % lower than the experimental value.

  8. Cosmology with cluster surveys

    Subhabrata Majumdar


    Surveys of clusters of galaxies provide us with a powerful probe of the density and nature of the dark energy. The red-shift distribution of detected clusters is highly sensitive to the dark energy equation of state parameter . Upcoming Sunyaev–Zel'dovich (SZ) surveys would provide us large yields of clusters to very high red-shifts. Self-calibration of cluster scaling relations, possible for such a huge sample, would be able to constrain systematic biases on mass estimators. Combining cluster red-shift abundance with limited mass follow-up and cluster mass power spectrum can then give constraints on , as well as on 8 and to a few per cents.

  9. CSR in Industrial Clusters

    Lund-Thomsen, Peter; Pillay, Renginee G.


    Purpose – The paper seeks to review the literature on CSR in industrial clusters in developing countries, identifying the main strengths, weaknesses, and gaps in this literature, pointing to future research directions and policy implications in the area of CSR and industrial cluster development...... in this field and their comments incorporated in the final version submitted to Corporate Governance. Findings – The article traces the origins of the debate on industrial clusters and CSR in developing countries back to the early 1990s when clusters began to be seen as an important vehicle for local economic...... development in the South. At the turn of the millennium the industrial cluster debate expanded as clusters were perceived as a potential source of poverty reduction, while their role in promoting CSR among small and medium-sized enterprises began to take shape from 2006 onwards. At present, there is still...

  10. Cluster Management Institutionalization

    Normann, Leo; Agger Nielsen, Jeppe


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

  11. Structures in Galaxy Clusters

    Escalera, E; Girardi, M; Giuricin, G; Mardirossian, F; Mazure, A; Mezzetti, M


    The analysis of the presence of substructures in 16 well-sampled clusters of galaxies suggests a stimulating hypothesis: Clusters could be classified as unimodal or bimodal, on the basis of to the sub-clump distribution in the {\\em 3-D} space of positions and velocities. The dynamic study of these clusters shows that their fundamental characteristics, in particular the virial masses, are not severely biased by the presence of subclustering if the system considered is bound.

  12. Clustering Techniques in Bioinformatics

    Muhammad Ali Masood


    Full Text Available Dealing with data means to group information into a set of categories either in order to learn new artifacts or understand new domains. For this purpose researchers have always looked for the hidden patterns in data that can be defined and compared with other known notions based on the similarity or dissimilarity of their attributes according to well-defined rules. Data mining, having the tools of data classification and data clustering, is one of the most powerful techniques to deal with data in such a manner that it can help researchers identify the required information. As a step forward to address this challenge, experts have utilized clustering techniques as a mean of exploring hidden structure and patterns in underlying data. Improved stability, robustness and accuracy of unsupervised data classification in many fields including pattern recognition, machine learning, information retrieval, image analysis and bioinformatics, clustering has proven itself as a reliable tool. To identify the clusters in datasets algorithm are utilized to partition data set into several groups based on the similarity within a group. There is no specific clustering algorithm, but various algorithms are utilized based on domain of data that constitutes a cluster and the level of efficiency required. Clustering techniques are categorized based upon different approaches. This paper is a survey of few clustering techniques out of many in data mining. For the purpose five of the most common clustering techniques out of many have been discussed. The clustering techniques which have been surveyed are: K-medoids, K-means, Fuzzy C-means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN and Self-Organizing Map (SOM clustering.

  13. Clustering of Absorbers

    Cristiani, S; D'Odorico, V; Fontana, A; Giallongo, E; Moscardini, L; Savaglio, S


    The observed clustering of Lyman-$\\alpha$ lines is reviewed and compared with the clustering of CIV systems. We argue that a continuity of properties exists between Lyman-$\\alpha$ and metal systems and show that the small-scale clustering of the absorbers is consistent with a scenario of gravitationally induced correlations. At large scales statistically significant over and under-densities (including voids) are found on scales of tens of Mpc.

  14. Galaxy Clusters with Chandra

    Forman, W; Markevitch, M L; Vikhlinin, A A; Churazov, E


    We discuss Chandra results related to 1) cluster mergers and cold fronts and 2) interactions between relativistic plasma and hot cluster atmospheres. We describe the properties of cold fronts using NGC1404 in the Fornax cluster and A3667 as examples. We discuss multiple surface brightness discontinuities in the cooling flow cluster ZW3146. We review the supersonic merger underway in CL0657. Finally, we summarize the interaction between plasma bubbles produced by AGN and hot gas using M87 and NGC507 as examples.

  15. Star Clusters within FIRE

    Perez, Adrianna; Moreno, Jorge; Naiman, Jill; Ramirez-Ruiz, Enrico; Hopkins, Philip F.


    In this work, we analyze the environments surrounding star clusters of simulated merging galaxies. Our framework employs Feedback In Realistic Environments (FIRE) model (Hopkins et al., 2014). The FIRE project is a high resolution cosmological simulation that resolves star forming regions and incorporates stellar feedback in a physically realistic way. The project focuses on analyzing the properties of the star clusters formed in merging galaxies. The locations of these star clusters are identified with, a publicly available dendrogram algorithm. Once star cluster properties are extracted, they will be used to create a sub-grid (smaller than the resolution scale of FIRE) of gas confinement in these clusters. Then, we can examine how the star clusters interact with these available gas reservoirs (either by accreting this mass or blowing it out via feedback), which will determine many properties of the cluster (star formation history, compact object accretion, etc). These simulations will further our understanding of star formation within stellar clusters during galaxy evolution. In the future, we aim to enhance sub-grid prescriptions for feedback specific to processes within star clusters; such as, interaction with stellar winds and gas accretion onto black holes and neutron stars.

  16. The Youngest Globular Clusters

    Beck, Sara


    It is likely that all stars are born in clusters, but most clusters are not bound and disperse. None of the many protoclusters in our Galaxy are likely to develop into long-lived bound clusters. The Super Star Clusters (SSCs) seen in starburst galaxies are more massive and compact and have better chances of survival. The birth and early development of SSCs takes place deep in molecular clouds, and during this crucial stage the embedded clusters are invisible to optical or UV observations but are studied via the radio-infared supernebulae (RISN) they excite. We review observations of embedded clusters and identify RISN within 10 Mpc whose exciting clusters have a million solar masses or more in volumes of a few cubic parsecs and which are likely to not only survive as bound clusters, but to evolve into objects as massive and compact as Galactic globulars. These clusters are distinguished by very high star formation efficiency eta, at least a factor of 10 higher than the few percent seen in the Galaxy, probably...

  17. 15th Cluster workshop

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


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

  18. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

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


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

  19. Improved water quality retrieval by identifying optically unique water classes

    Nazeer, Majid; Nichol, Janet E.


    Accurate remote sensing retrieval of water quality parameters in complex coastal environments is challenging due to variability of the coastal environment. For example, in the coastal waters of Hong Kong water quality varies from east to west. The currently existing water zones, defined by the Hong Kong Environmental Protection Department (EPD) are based on ease of access to sampling locations rather than on water quality alone. In this study an archive of fifty-seven Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and HJ-1 A/B Charged Couple Device (CCD) images over a 13-year period (January 2000-December 2012) was used to define optically distinct water classes by Fuzzy c-Means (FCM) clustering. The clustering was applied by combining the Surface Reflectance (SR) derived from the first four bands of Landsat and HJ-1 scenes with 240 insitu samples of Chlorophyll-a (Chl-a) and Suspended Solid (SS) concentrations collected within 2 h of image acquisition. The FCM clustering suggested the existence of five optically different water classes in the region. The significance of the defined water classes was tested in terms of the water SR behaviour in each band. The SR for Classes 1 and 2 in bands 1-3 was lower than in other classes, and band 4 showed the lowest reflectance, indicating that these classes represent a clearer type of water. Class 3 showed intermediate reflectance in all bands, while Classes 4 and 5 showed overall higher reflectance indicating high sediment contribution from the Pearl River Delta. Application of water quality retrievals within individual classes showed much greater confidence with Root Mean Square Error (RMSE) of 1.32 μg/l (1.21 mg/l) for Chl-a (SS) concentrations, compared with 5.97 μg/l (2.98 mg/l) when applied to the whole spectrum of different water types across the region.

  20. Document Clustering Based on Semi-Supervised Term Clustering

    Hamid Mahmoodi


    Full Text Available The study is conducted to propose a multi-step feature (term selection process and in semi-supervised fashion, provide initial centers for term clusters. Then utilize the fuzzy c-means (FCM clustering algorithm for clustering terms. Finally assign each of documents to closest associated term clusters. While most text clustering algorithms directly use documents for clustering, we propose to first group the terms using FCM algorithm and then cluster documents based on terms clusters. We evaluate effectiveness of our technique on several standard text collections and compare our results with the some classical text clustering algorithms.

  1. Semantic Analysis of Virtual Classes and Nested Classes

    Madsen, Ole Lehrmann


    Virtual classes and nested classes are distinguishing features of BETA. Nested classes originated from Simula, but until recently they have not been part of main stream object- oriented languages. C++ has a restricted form of nested classes and they were included in Java 1.1. Virtual classes...... the central elements of the semantic analysis used in the Mjølner BETA compiler....

  2. Social Class Dialogues and the Fostering of Class Consciousness

    Madden, Meredith


    How do critical pedagogies promote undergraduate students' awareness of social class, social class identity, and social class inequalities in education? How do undergraduate students experience class consciousness-raising in the intergroup dialogue classroom? This qualitative study explores undergraduate students' class consciousness-raising in an…

  3. Critical exponents from cluster coefficients

    Rotman, Z.; Eisenberg, E.


    For a large class of repulsive interaction models, the Mayer cluster integrals can be transformed into a tridiagonal real symmetric matrix Rmn , whose elements converge to two constants. This allows for an effective extrapolation of the equation of state for these models. Due to a nearby (nonphysical) singularity on the negative real z axis, standard methods (e.g., Padé approximants based on the cluster integrals expansion) fail to capture the behavior of these models near the ordering transition, and, in particular, do not detect the critical point. A recent work [E. Eisenberg and A. Baram, Proc. Natl. Acad. Sci. U.S.A. 104, 5755 (2007)] has shown that the critical exponents σ and σ' , characterizing the singularity of the density as a function of the activity, can be exactly calculated if the decay of the R matrix elements to their asymptotic constant follows a 1/n2 law. Here we employ renormalization group (RG) arguments to extend this result and analyze cases for which the asymptotic approach of the R matrix elements toward their limiting value is of a more general form. The relevant asymptotic correction terms (in RG sense) are identified, and we then present a corrected exact formula for the critical exponents. We identify the limits of usage of the formula and demonstrate one physical model, which is beyond its range of validity. The formula is validated numerically and then applied to analyze a number of concrete physical models.

  4. Cluster algebras of finite mutation type via unfoldings

    Felikson, Anna; Tumarkin, Pavel


    We complete classification of mutation-finite cluster algebras by extending the technique derived by Fomin, Shapiro, and Thurston to skew-symmetrizable case. We show that every mutation-finite skew-symmetrizable matrix admits an unfolding which embeds the mutation class of mutation-finite skew-symmetrizable matrix to the mutation class of some mutation-finite skew-symmetric matrix. In particular, this establishes a correspondence between almost all skew-symmetrizable mutation-finite cluster algebras and triangulated marked bordered surfaces.

  5. Class in disguise

    Faber, Stine Thidemann; Prieur, Annick

    This paper asks how class can have importance in one of the worlds’ most equal societies: Denmark. The answer is that class here appears in disguised forms. The field under study is a city, Aalborg, in the midst of transition from a stronghold of industrialism to a post industrial economy....... The paper picks out two sets of discourses from this city: on the one hand a newspapers discourses about the city’s brand and on the other interviews with female inhabitants about experiences and visions of social differences and divides. The analysis reveals indirect and euphemized forms of class divisions....... The paper also raises questions about how sociological discourses may contribute to the veiling of class....

  6. Classes of Heart Failure

    ... Disease Venous Thromboembolism Aortic Aneurysm More Classes of Heart Failure Updated:Sep 28,2016 Doctors usually classify patients' ... Blood Pressure Tracker Find additional helpful resources here Heart Failure • Home • About Heart Failure Introduction Types of Heart ...

  7. IELP Class Observation



    @@ As an exchange student majoring in English, I am curious about how English is taught to international students here in America. Therefore, I observed an IELP (Intensive English Learning Program) class in Central Connecticut State University where I study.

  8. Teaching Heterogeneous Classes.

    Millrood, Radislav


    Discusses an approach to teaching heterogeneous English-as-a-Second/Foreign-Language classes. Draws on classroom research data to describe the features of a success-building lesson context. (Author/VWL)

  9. Clustering Text Data Streams

    Yu-Bao Liu; Jia-Rong Cai; Jian Yin; Ada Wai-Chee Fu


    Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organization and topic detection and tracing etc. However, most methods are similarity-based approaches and only use the TF*IDF scheme to represent the semantics of text data and often lead to poor clustering quality. Recently, researchers argue that semantic smoothing model is more efficient than the existing TF.IDF scheme for improving text clustering quality. However, the existing semantic smoothing model is not suitable for dynamic text data context. In this paper, we extend the semantic smoothing model into text data streams context firstly. Based on the extended model, we then present two online clustering algorithms OCTS and OCTSM for the clustering of massive text data streams. In both algorithms, we also present a new cluster statistics structure named cluster profile which can capture the semantics of text data streams dynamically and at the same time speed up the clustering process. Some efficient implementations for our algorithms are also given. Finally, we present a series of experimental results illustrating the effectiveness of our technique.

  10. Neurostimulation in cluster headache

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


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

  11. Securing personal network clusters

    Jehangir, Assed; Heemstra de Groot, Sonia M.


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

  12. [Cluster headache differential diagnosis].

    Guégan-Massardier, Evelyne; Laubier, Cécile


    Cluster headache is characterized by disabling stereotyped headache. Early diagnosis allows appropriate treatment, unfortunately diagnostic errors are frequent. The main differential diagnoses are other primary or essential headaches. Migraine, more frequent and whose diagnosis is carried by excess, trigeminal neuralgia or other trigemino-autonomic cephalgia. Vascular or tumoral underlying condition can mimic cluster headache, neck and brain imaging is recommended, ideally MRI.

  13. Coma cluster of galaxies


    Atlas Image mosaic, covering 34' x 34' on the sky, of the Coma cluster, aka Abell 1656. This is a particularly rich cluster of individual galaxies (over 1000 members), most prominently the two giant ellipticals, NGC 4874 (right) and NGC 4889 (left). The remaining members are mostly smaller ellipticals, but spiral galaxies are also evident in the 2MASS image. The cluster is seen toward the constellation Coma Berenices, but is actually at a distance of about 100 Mpc (330 million light years, or a redshift of 0.023) from us. At this distance, the cluster is in what is known as the 'Hubble flow,' or the overall expansion of the Universe. As such, astronomers can measure the Hubble Constant, or the universal expansion rate, based on the distance to this cluster. Large, rich clusters, such as Coma, allow astronomers to measure the 'missing mass,' i.e., the matter in the cluster that we cannot see, since it gravitationally influences the motions of the member galaxies within the cluster. The near-infrared maps the overall luminous mass content of the member galaxies, since the light at these wavelengths is dominated by the more numerous older stellar populations. Galaxies, as seen by 2MASS, look fairly smooth and homogeneous, as can be seen from the Hubble 'tuning fork' diagram of near-infrared galaxy morphology. Image mosaic by S. Van Dyk (IPAC).

  14. Cluster Management Institutionalization

    Normann, Leo; Agger Nielsen, Jeppe


    This article explores a new management form – cluster management – in Danish public sector day care. Although cluster management has been widely adopted in Danish day care at the municipality level, it has attracted only sparse research attention. We use theoretical insights from Scandinavian ins...

  15. Cluster Synchronization Algorithms

    Xia, Weiguo; Cao, Ming


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

  16. Cost-Effective Clustering

    Gottlieb, S


    Small Beowulf clusters can effectively serve as personal or group supercomputers. In such an environment, a cluster can be optimally designed for a specific problem (or a small set of codes). We discuss how theoretical analysis of the code and benchmarking on similar hardware lead to optimal systems.

  17. Relevant Subspace Clustering

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan;


    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 c...

  18. MKT 438 Complete Class



      To purchase this material click below link   For more classes visit   MKT 438 Week 1 Individual Assignment Defining Public Relation Paper MKT 438 Week 2 Team Assignment Public Relations Campaign Overview Paper MKT 438 Week 3 Individual Assignment Functions of Public Relation Paper MKT 438 Week 3 Team Assignment Public Relations Campaig...

  19. A class in astrobiology

    Airieau, S. A.


    The goal of this class is to provide basic astrobiology knowledge to upper division science students. The scope is broad and in-depth coverage is not possible in this introductory course. Instead, science students from various branches of academia can acquire a broad basis and understanding of the other fields: astronomy, biology, geology, biochemistry, planetary and space sciences. The class is highly modular and allows instructors to concentrate on or eliminate topics according to their priorities and preferences.

  20. Nordic Walking Classes

    Fitness Club


    Four classes of one hour each are held on Tuesdays. RDV barracks parking at Entrance A, 10 minutes before class time. Spring Course 2015: 05.05/12.05/19.05/26.05 Prices 40 CHF per session + 10 CHF club membership 5 CHF/hour pole rental Check out our schedule and enroll at: Hope to see you among us!

  1. On TPC cluster reconstruction

    Dydak, F; Nefedov, Y; Wotschack, J; Zhemchugov, A


    For a bias-free momentum measurement of TPC tracks, the correct determination of cluster positions is mandatory. We argue in particular that (i) the reconstruction of the entire longitudinal signal shape in view of longitudinal diffusion, electronic pulse shaping, and track inclination is important both for the polar angle reconstruction and for optimum r phi resolution; and that (ii) self-crosstalk of pad signals calls for special measures for the reconstruction of the z coordinate. The problem of 'shadow clusters' is resolved. Algorithms are presented for accepting clusters as 'good' clusters, and for the reconstruction of the r phi and z cluster coordinates, including provisions for 'bad' pads and pads next to sector boundaries, respectively.

  2. Job Oriented Monitoring Clusters

    Vijayalaxmi Cigala,


    Full Text Available There has been a lot of development in the field of clusters and grids. Recently, the use of clusters has been on rise in every possible field. This paper proposes a system that monitors jobs onlarge computational clusters. Monitoring jobs is essential to understand how jobs are being executed. This helps us in understanding the complete life cycle of the jobs being executed on large clusters. Also, this paper describes how the information obtained by monitoring the jobs would help in increasing the overall throughput of clusters. Heuristics help in efficient job distribution among the computational nodes, thereby accomplishing fair job distribution policy. The proposed system would be capable of loadbalancing among the computational nodes, detecting failures, taking corrective actions after failure detection, job monitoring, system resource monitoring, etc.

  3. Neutrosophic Hierarchical Clustering Algoritms

    Rıdvan Şahin


    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.

  4. A Commodity Computing Cluster

    Teuben, P. J.; Wolfire, M. G.; Pound, M. W.; Mundy, L. G.

    We have assembled a cluster of Intel-Pentium based PCs running Linux to compute a large set of Photodissociation Region (PDR) and Dust Continuum models. For various reasons the cluster is heterogeneous, currently ranging from a single Pentium-II 333 MHz to dual Pentium-III 450 MHz CPU machines. Although this will be sufficient for our ``embarrassingly parallelizable problem'' it may present some challenges for as yet unplanned future use. In addition the cluster was used to construct a MIRIAD benchmark, and compared to equivalent Ultra-Sparc based workstations. Currently the cluster consists of 8 machines, 14 CPUs, 50GB of disk-space, and a total peak speed of 5.83 GHz, or about 1.5 Gflops. The total cost of this cluster has been about $12,000, including all cabling, networking equipment, rack, and a CD-R backup system. The URL for this project is

  5. Mathematical classification and clustering

    Mirkin, Boris


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

  6. Cool Cluster Correctly Correlated

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


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

  7. Concurrent conditional clustering of multiple networks: COCONETS.

    Sabrina Kleessen

    Full Text Available The accumulation of high-throughput data from different experiments has facilitated the extraction of condition-specific networks over the same set of biological entities. Comparing and contrasting of such multiple biological networks is in the center of differential network biology, aiming at determining general and condition-specific responses captured in the network structure (i.e., included associations between the network components. We provide a novel way for comparison of multiple networks based on determining network clustering (i.e., partition into communities which is optimal across the set of networks with respect to a given cluster quality measure. To this end, we formulate the optimization-based problem of concurrent conditional clustering of multiple networks, termed COCONETS, based on the modularity. The solution to this problem is a clustering which depends on all considered networks and pinpoints their preserved substructures. We present theoretical results for special classes of networks to demonstrate the implications of conditionality captured by the COCONETS formulation. As the problem can be shown to be intractable, we extend an existing efficient greedy heuristic and applied it to determine concurrent conditional clusters on coexpression networks extracted from publically available time-resolved transcriptomics data of Escherichia coli under five stresses as well as on metabolite correlation networks from metabolomics data set from Arabidopsis thaliana exposed to eight environmental conditions. We demonstrate that the investigation of the differences between the clustering based on all networks with that obtained from a subset of networks can be used to quantify the specificity of biological responses. While a comparison of the Escherichia coli coexpression networks based on seminal properties does not pinpoint biologically relevant differences, the common network substructures extracted by COCONETS are supported by

  8. On class visualisation for high dimensional data: Exploring scientific datasets

    Kaban, Ata; Raychaudhuri, S; Nolan, L; Kaban, Ata; Sun, Jianyong; Raychaudhury, Somak; Nolan, Louisa


    Parametric Embedding (PE) has recently been proposed as a general-purpose algorithm for class visualisation. It takes class posteriors produced by a mixture-based clustering algorithm and projects them in 2D for visualisation. However, although this fully modularised combination of objectives (clustering and projection) is attractive for its conceptual simplicity, in the case of high dimensional data, we show that a more optimal combination of these objectives can be achieved by integrating them both into a consistent probabilistic model. In this way, the projection step will fulfil a role of regularisation, guarding against the curse of dimensionality. As a result, the tradeoff between clustering and visualisation turns out to enhance the predictive abilities of the overall model. We present results on both synthetic data and two real-world high-dimensional data sets: observed spectra of early-type galaxies and gene expression arrays.




    In this paper we propose a novel method for identifying relevant subspaces using fuzzy entropy and perform clustering. This measure discriminates the real distribution better by using membership functions for measuring class match degrees. Hence the fuzzy entropy reflects more information in the actual disbution of patterns in the subspaces. We use a heuristic procedure based on the silhouette criterion to find the number of clusters. The presented theories and algorithms are evaluated through experiments on a collection of benchmark data sets. Empirical results have shown its favorable performance in comparison with several other clustering algorithms.

  10. Far-Infrared Spectroscopy of Weakly Bound Hydrated Cluster Molecules

    Andersen, Jonas

    -sized molecular clusters with water by means of far-infrared and terahertz neon matrix isolation spectroscopy. The embedding of non-covalent cluster molecules in solid cryogenic neon matrices at 2.8 K ensures a high sensitivity for direct spectroscopic observations of the large-amplitude intermolecular...... vibrational bands of the cluster molecules in the challenging far-infrared and terahertz spectral regions.A key parameter in the validation of the performance of theoretical predictions for weak non-covalent intermolecular interactions is the dissociation energy D0 that depends heavily on the class of large...

  11. Molecules based on M(v) (M=Mo, W) and Ni(II) ions: a new class of trigonal bipyramidal cluster and confirmation of SMM behavior for the pentadecanuclear molecule {NiII[NiII(tmphen)(MeOH)]6[Ni(H2O)3]2[micro-CN]30[WV(CN)3]6}.

    Hilfiger, Matthew G; Zhao, Hanhua; Prosvirin, Andrey; Wernsdorfer, Wolfgang; Dunbar, Kim R


    The preparation, single crystal X-ray crystallography, and magnetic properties are reported for four new clusters based on [M'V(CN)8]3- octacyanometallates (M'=Mo, W). Reactions of [M'V(CN)8]3- with mononuclear NiII ions in the presence of the tmphen blocking ligand (tmphen=3,4,7,8-tetramethyl-1,10-phenanthroline) in a 2:3:6 ratio, respectively, lead to the formation of the trigonal bipyramidal clusters [NiII(tmphen)2]3[M'V(CN)8]2. Analogous reactions with the same starting materials performed in a 2:3:2 ratio, respectively, produce pentadecanuclear clusters of the type {NiII[NiII(tmphen)(MeOH)]6[Ni(H2O)3]2[micro-CN]30[WV(CN)3]6}. The W2Ni3 (1) and Mo2Ni3(2) pentanuclear clusters and the W6Ni9 (3) and Mo6Ni9 (4) pentadecanuclear molecules are isostructural to each other and crystallize in the space groups P2(1)/c and R3 respectively. Magnetic measurements indicate that the ground states for the trigonal bipyamidal clusters are S=4 as a consequence of ferromagnetic coupling with JW-Ni=9.5 cm(-1), JMo-Ni=10 cm(-1). The pentadecanuclear clusters exhibit ferromagnetic coupling as well, which leads to S=12 ground states (JW-Ni=12 cm(-1), JMo-Ni=12.2 cm(-1)). Reduced magnetization studies on the W-Ni analogues support the conclusion that they exhibit a negative axial anisotropy term; the fits give D values of -0.24 cm(-1) for the W2Ni3 cluster and D=-0.04 cm(-1)for the W6Ni9 cluster. AC susceptibility measurements indicate the beginning of an out-of-phase signal for the W2Ni3 and the W6Ni9 compounds, but detailed low temperature studies on small crystals by the microSQUID technique indicate that only the pentadecanuclear cluster exhibits hysteresis in accord with SMM behavior. Neither Mo cluster reveals any evidence for slow paramagnetic relaxation at low temperatures.

  12. Assembly of MHC class I molecules within the endoplasmic reticulum.

    Zhang, Yinan; Williams, David B


    MHC class I molecules bind cytosolically derived peptides within the endoplasmic reticulum (ER) and present them at the cell surface to cytotoxic T cells. A major focus of our laboratory has been to understand the functions of the diverse proteins involved in the intracellular assembly of MHC class I molecules. These include the molecular chaperones calnexin and calreticulin, which enhance the proper folding and subunit assembly of class I molecules and also retain assembly intermediates within the ER; ERp57, a thiol oxidoreductase that promotes heavy chain disulfide formation and proper assembly of the peptide loading complex; tapasin, which recruits class I molecules to the TAP peptide transporter and enhances the loading of high affinity peptide ligands; and Bap31, which is involved in clustering assembled class I molecules at ER exit sites for export along the secretory pathway. This review describes our contributions to elucidating the functions of these proteins; the combined effort of many dedicated students and postdoctoral fellows.

  13. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

    Ntampaka, M; Sutherland, D J; Fromenteau, S; Poczos, B; Schneider, J


    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark's publicly-available N-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power law scaling relation to infer cluster mass from galaxy line of sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with width = 0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (width = 2.13). We employ the Support Distribution Machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to...

  14. The K-band Hubble diagram for brightest cluster galaxies in X-ray clusters

    Collins, C; Collins, Chris; Mann, Bob


    This paper concerns the K band Hubble diagram for the brightest cluster galaxies (BCGs) in a sample of X-ray clusters covering the redshift range $0.05 2.3 \\times 10^{44}$ erg s$^{-1}$ (in the 0.3 - 3.5 keV band) is no more than 0.22 mag, and is not significantly reduced by correcting for the BCG structure parameter, $\\alpha$, or for X-ray luminosity. This is the smallest scatter in the absolute magnitudes of any single class of galaxy and demonstrates the homogeneity of BCGs in high-$L_{\\rm X}$ clusters. By contrast, we find that the brightest members of low-$L_{\\rm X}$ systems display a wider dispersion ($\\sim 0.5$ mag) in absolute magnitude than commonly seen in previous studies, which arises from the inclusion, in X-ray flux-limited samples, of poor clusters and groups which are usually omitted from low redshift studies of BCGs in optically rich clusters....[abstract shortened].. The BCGs in our high-$L_{\\rm X}$ clusters yield a value of $\\Omega_{\\rm M}=0.28\\pm0.24$ if the cosmological constant with a 95 ...

  15. An X-ray survey of clusters of galaxies. IV - A survey of southern clusters and a compilation of upper limits for both Abell and southern clusters

    Kowalski, M. P.; Ulmer, M. P.; Cruddace, R. G.; Wood, K. S.


    The results of the HEAO 1 A-1 X-ray survey of galaxy clusters are reported. X-ray error boxes and intensities are presented for all clusters in the Abell catalog and for the catalog of southern clusters and groups compiled by Duus and Newell (1977). A correlation is derived on the basis of the X-ray luminosity function for 2-6 keV which may be used to calculate the contribution of clusters to the diffuse X-ray background at different energies. The cluster X-ray is estimated to be 9.3 percent (+ 1.9 or - 1.5 percent). Correlations between X-ray luminosity and other cluster properties are exmained, and it is found that the distribution of upper limits may be applied to obtaining a more precise estimate of the average X-ray luminosity of clusters. The Abell richness class and southern cluster concentrations were strongly correlated with X-ray luminosity. Correlations between optical x-ray luminosity and optical radius velocity dispersion, spiral fraction, and radio power are analyzed. The evidence for all these correlations was considered to be weak because of poor scatter in the data.

  16. Cluster knockout reactions

    Arun K Jain; B N Joshi


    Cluster knockout reactions are expected to reveal the amount of clustering (such as that of , d and even of heavier clusters such as 12C, 16O etc.) in the target nucleus. In simple terms, incident medium high-energy nuclear projectile interacts strongly with the cluster (present in the target nucleus) as if it were existing as a free entity. Theoretically, the relatively softer interactions of the two outgoing particles with the residual nucleus lead to optical distortions and are treated in terms of distorted wave (DW) formalism. The long-range projectile–cluster interaction is accounted for, in terms of the finite range (FR) direct reaction formalism, as against the more commonly adopted zero-range (ZR) distorted wave impulse approximation (DWIA) formalism. Comparison of the DWIA calculations with the observed data provide information about the momentum distribution and the clustering spectroscopic factor of the target nucleus. Interesting results and some recent advancements in the area of (, 2) reactions and heavy cluster knockout reactions are discussed. Importance of the finite-range vertex and the final-state interactions are brought out.

  17. Software-Defined Cluster

    聂华; 杨晓君; 刘淘英


    The cluster architecture has played an important role in high-end computing for the past 20 years. With the advent of Internet services, big data, and cloud computing, traditional clusters face three challenges: 1) providing flexible system balance among computing, memory, and I/O capabilities;2) reducing resource pooling overheads;and 3) addressing low performance-power efficiency. This position paper proposes a software-defined cluster (SDC) architecture to deal with these challenges. The SDC architecture inherits two features of traditional cluster: its architecture is multicomputer and it has loosely-coupled interconnect. SDC provides two new mechanisms: global I/O space (GIO) and hardware-supported native access (HNA) to remote devices. Application software can define a virtual cluster best suited to its needs from resources pools provided by a physical cluster, and traditional cluster ecosystems need no modification. We also discuss a prototype design and implementation of a 32-processor cloud server utilizing the SDC architecture.

  18. Spanning Tree Based Attribute Clustering

    Zeng, Yifeng; Jorge, Cordero Hernandez


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

  19. Textile Industrial Clusters in China


    "National Textile Industry Cluster Development Seminar" convened, held by China National Textile and Apparel Council, 23 cities and towns were awarded as China’s Textile Industry Cluster Pilot District. By far, China’s textile industrial clusters have grown

  20. Class IIc or Circular Bacteriocins

    Martin-Visscher, Leah A.; van Belkum, Marco J.; Vederas, John C.

    The circular bacteriocins produced by Gram-positive bacteria represent a diverse class of antimicrobial peptides. These bacteriocins display enhanced stability compared to linear bacteriocins, which arises from their characteristic circular backbone. Currently, eight unique circular bacteriocins have been identified, and analysis of their gene clusters indicates that they likely utilize complex mechanisms for maturation and secretion, as well as for immunity. These bacteriocins target the cytoplasmic membrane of sensitive cells, leading to pore formation that results in loss of ions, dissipation of membrane potential, and ultimately, cell death. Structural studies suggest that despite variation in their sequences, most of these bacteriocins likely adopt a common three-dimensional architecture, consisting of four or five tightly packed helices encompassing a hydrophobic core. There are many mysteries surrounding the biosynthesis of these peptides, particularly in regard to the mechanism by which they are cyclized. Elucidation of such a mechanism may provide exciting new approaches to the bioengineering of new, stable, and antimicrobially active circular peptides.

  1. Allodynia in Cluster Headache.

    Wilbrink, Leopoldine A; Louter, Mark A; Teernstra, Onno Pm; van Zwet, Erik W; Huygen, Frank Jpm; Haan, Joost; Ferrari, Michel D; Terwindt, Gisela M


    Cutaneous allodynia is an established marker for central sensitization in migraine. There is debate whether cutaneous allodynia may also occur in cluster headache, another episodic headache disorder. Here we examined the presence and severity of allodynia in a large well-defined nation-wide population of people with cluster headache.Using validated questionnaires we assessed, cross-sectionally, ictal allodynia and comorbid depression and migraine in the nation-wide "Leiden University Cluster headache neuro-Analysis" (LUCA) study. Participants with cluster headache were diagnosed according to the International Classification of Headache Disorders criteria. Multivariate regression models were used, with correction for demographic factors and cluster headache subtype (chronic vs. episodic; recent attacks cluster headache responded of whom 218/606 (36%) had allodynia during attacks. Female gender (OR 2.05, 95% CI 1.28-3.29), low age at onset (OR 0.98, 95% CI 0.96- 0.99), lifetime depression (OR 1.63; 95% CI 1.06-2.50), comorbid migraine (OR 1.96; 95% CI 1.02-3.79), and having recent attacks (OR 1.80; 95% CI 1.13-2.86), but not duration of attacks and chronic cluster headache, were independent risk factors for allodynia.The high prevalence of cutaneous allodynia with similar risk factors for allodynia as found for migraine suggests that central sensitization, like in migraine, also occurs in cluster headache. In clinical practice, awareness that people with cluster headache may suffer from allodynia can in the future be an important feature in treatment options.

  2. Introduction to cluster dynamics

    Reinhard, Paul-Gerhard


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

  3. ClusterAlive

    Caruso, G.; Arezzini, S.; Ciampa, A.; Formuso, A.; Mazzoni, E.


    INFN-Pisa Scientific Computing Center is working from many years both in GRID and HPC computing. The monitoring and managing tools have been key components of the center's successful operation. The lessons learned from the use of standard tools, such as Ganglia, have been starting points for the development of new tools specific for our infrastructure. In this note we will illustrate the integration of many different monitoring tools in one single platform called ClusterAlive. Aim of ClusterAlive is to increase the HPC cluster performance and simplify maintenance operations, possibly in a proactive approach.

  4. Raspberry Pi super cluster

    Dennis, Andrew K


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

  5. Cluster modular autocontenido


    Desde hace años es común en organizaciones educativas y de investigación el desarrollo de actividades que requieren grandes capacidades de cálculo. La solución más común a estas necesidades es la compra o construcción de un cluster HPC (High Performance Computing), pero construir un cluster acarrea problemas y costos inesperados problemas al momento de utilizarlo y mantenerlo en operaciones. Nuestro proyecto busca desarrollar y documentar técnicas para construir un cluster HPC que sea fácilme...

  6. Extending Beowulf Clusters

    Steinwand, Daniel R.; Maddox, Brian; Beckmann, Tim; Hamer, George


    Beowulf clusters can provide a cost-effective way to compute numerical models and process large amounts of remote sensing image data. Usually a Beowulf cluster is designed to accomplish a specific set of processing goals, and processing is very efficient when the problem remains inside the constraints of the original design. There are cases, however, when one might wish to compute a problem that is beyond the capacity of the local Beowulf system. In these cases, spreading the problem to multiple clusters or to other machines on the network may provide a cost-effective solution.

  7. Class II genes of miniature swine. II. Molecular identification and characterization of B (beta) genes from the SLAc haplotype.

    Pratt, K; Sachs, D H; Germana, S; el-Gamil, M; Hirsch, F; Gustafsson, K; LeGuern, C


    Genomic clones corresponding to class II beta genes of the SLAc haplotype of miniature swine have been isolated and characterized. These genes have been grouped into seven non-overlapping clusters on the basis of restriction mapping. Ordering of exons within each cluster was accomplished by hybridization of Southern blots of restriction fragments with exon-specific probes. The two clusters (clusters 2 and 3) encoding the DRB and DQB genes were identified on the basis of hybridization with locus-specific 3' untranslated cDNA probes. Cluster 4 contained exons of both DOB and DQB genes, the basis for which remains to be determined. The remaining four clusters (1, 5, 6, 7) were identified as containing DP, DR, and DO coding sequences, respectively, on the basis of sequence analysis. The porcine class II region appears very similar to that of man in number and nature of the class II genes identified and in the intron/exon organization of corresponding genes.

  8. Combining cluster number counts and galaxy clustering

    Lacasa, Fabien; Rosenfeld, Rogerio


    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.

  9. Talking Class in Tehroon

    Elling, Rasmus Christian; Rezakhani, Khodadad


    Persian, like any other language, is laced with references to class, both blatant and subtle. With idioms and metaphors, Iranians can identify and situate others, and thus themselves, within hierarchies of social status and privilege, both real and imagined. Some class-related terms can be traced...... back to medieval times, whereas others are of modern vintage, the linguistic legacy of television shows, pop songs, social media memes or street vernacular. Every day, it seems, an infectious set of phrases appears that make yesterday’s seem embarrassingly antiquated....

  10. BUSN 460 Complete Class



    BUSN 460 Complete Class Click Link Below To Buy:     Week 1 DQ 1 Selling your team’s services to CanGo  Week 1 DQ 2 Mission, Vision & Values  Week 2 DQ 1 Planning a Technological Solution  Week 2 DQ 2 Cost Benefit Analysis  Week 3 DQ 1 Flow Charting Processes  Week 3 DQ 2 Implementing Technology  Week 4 DQ 1 Group vs Team  Week  4 DQ 2 Matrixed Employee Environments  Week 5 DQ 1 Pe...


    Dr. K. Sravana Kumar


                The middle class is placed between labour and capital. It neither directly awns the means of production that pumps out the surplus generated by wage labour power, nor does it, by its own labour, produce the surplus which has use and exchange value. Broadly speaking, this class consists of the petty bourgeoisie and the white-collar workers. The former are either self-employed or involved in the distribution of commodities and t...

  12. NR 512 Entire Class



     NR 512 Entire Class   Click Link Below To Buy: Or Visit   NR512 Week 1 Discussion Latest 2017 Integration of Nursing Informatics Skills and Competencies (graded) • Reflect on your own practice. Discuss how informatics is used in your practice. What is your primary area where you would use informatics? NR512 Week 2 Discussion Latest 2017 Wisdom Versus Judgment (graded) How does the conc...

  13. Evolution of clustered storage

    CERN. Geneva; Van de Vyvre, Pierre


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

  14. An Improved Fuzzy c-Means Clustering Algorithm Based on Shadowed Sets and PSO

    Jian Zhang


    Full Text Available To organize the wide variety of data sets automatically and acquire accurate classification, this paper presents a modified fuzzy c-means algorithm (SP-FCM based on particle swarm optimization (PSO and shadowed sets to perform feature clustering. SP-FCM introduces the global search property of PSO to deal with the problem of premature convergence of conventional fuzzy clustering, utilizes vagueness balance property of shadowed sets to handle overlapping among clusters, and models uncertainty in class boundaries. This new method uses Xie-Beni index as cluster validity and automatically finds the optimal cluster number within a specific range with cluster partitions that provide compact and well-separated clusters. Experiments show that the proposed approach significantly improves the clustering effect.

  15. Chromosomal localization of the gene for the human Theta class glutathione transferase (GSTT1)

    Webb, G.; Vaska, V. [Queen Elizabeth Hospital, Adelaide (Australia); Goggan, M.; Board, P. [Australian National Univ., Canberra (Australia)


    Two loci encoding Theta class glutathione transferases (GSTs) have been identified in humans. In situ hybridization studies have localized the GSTT1 gene to 22q11.2. This is the same band to which we previously localized the GSTT2 gene. This finding confirms the trend for human GST genes to be found in class-specific clusters. 20 refs., 1 fig.

  16. Globular clusters with Gaia

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


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

  17. Magnetic cluster excitations

    Furrer, Albert; Waldmann, Oliver


    Magnetic clusters, i.e., assemblies of a finite number (between two or three and several hundred) of interacting spin centers which are magnetically decoupled from their environment, can be found in many materials ranging from inorganic compounds and magnetic molecules to artificial metal structures formed on surfaces and metalloproteins. Their magnetic excitation spectra are determined by the nature of the spin centers and of the magnetic interactions, and the particular arrangement of the mutual interaction paths between the spin centers. Small clusters of up to four magnetic ions are ideal model systems in which to examine the fundamental magnetic interactions, which are usually dominated by Heisenberg exchange, but often complemented by anisotropic and/or higher-order interactions. In large magnetic clusters, which may potentially deal with a dozen or more spin centers, there is the possibility of novel many-body quantum states and quantum phenomena. In this review the necessary theoretical concepts and experimental techniques to study the magnetic cluster excitations and the resulting characteristic magnetic properties are introduced, followed by examples of small clusters, demonstrating the enormous amount of detailed physical information that can be retrieved. The current understanding of the excitations and their physical interpretation in the molecular nanomagnets which represent large magnetic clusters is then presented, with a section devoted to the subclass of single-molecule magnets, distinguished by displaying quantum tunneling of the magnetization. Finally, there is a summary of some quantum many-body states which evolve in magnetic insulators characterized by built-in or field-induced magnetic clusters. The review concludes by addressing future perspectives in the field of magnetic cluster excitations.

  18. Cauchy cluster process

    Ghorbani, Mohammad


    In this paper we introduce an instance of the well-know Neyman–Scott cluster process model with clusters having a long tail behaviour. In our model the offspring points are distributed around the parent points according to a circular Cauchy distribution. Using a modified Cramér-von Misses test st...... statistic and the simulated pointwise envelopes it is shown that this model fits better than the Thomas process to the frequently analyzed long-leaf pine data-set....

  19. Parallel Wolff Cluster Algorithms

    Bae, S.; Ko, S. H.; Coddington, P. D.

    The Wolff single-cluster algorithm is the most efficient method known for Monte Carlo simulation of many spin models. Due to the irregular size, shape and position of the Wolff clusters, this method does not easily lend itself to efficient parallel implementation, so that simulations using this method have thus far been confined to workstations and vector machines. Here we present two parallel implementations of this algorithm, and show that one gives fairly good performance on a MIMD parallel computer.

  20. Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues.

    Pandis, Nikolaos; Walsh, Tanya; Polychronopoulou, Argy; Eliades, Theodore


    Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

  1. Galaxy cluster's rotation

    Manolopoulou, Maria


    We study the possible rotation of cluster galaxies, developing, testing and applying a novel algorithm which identifies rotation, if such does exits, as well as its rotational centre, its axis orientation, rotational velocity amplitude and, finally, the clockwise or counterclockwise direction of rotation on the plane of the sky. To validate our algorithms we construct realistic Monte-Carlo mock rotating clusters and confirm that our method provides robust indications of rotation. We then apply our methodology on a sample of Abell clusters with z<~0.1 with member galaxies selected from the SDSS DR10 spectroscopic database. We find that ~35% of our clusters are rotating when using a set of strict criteria, while loosening the criteria we find this fraction increasing to ~48%. We correlate our rotation indicators with the cluster dynamical state, provided either by their Bautz-Morgan type or by their X-ray isophotal shape and find for those clusters showing rotation that the significance and strength of their...

  2. Cluster bomb ocular injuries

    Ahmad M Mansour


    Full Text Available Purpose: To present the visual outcomes and ocular sequelae of victims of cluster bombs. Materials and Methods: This retrospective, multicenter case series of ocular injury due to cluster bombs was conducted for 3 years after the war in South Lebanon (July 2006. Data were gathered from the reports to the Information Management System for Mine Action. Results: There were 308 victims of clusters bombs; 36 individuals were killed, of which 2 received ocular lacerations and; 272 individuals were injured with 18 receiving ocular injury. These 18 surviving individuals were assessed by the authors. Ocular injury occurred in 6.5% (20/308 of cluster bomb victims. Trauma to multiple organs occurred in 12 of 18 cases (67% with ocular injury. Ocular findings included corneal or scleral lacerations (16 eyes, corneal foreign bodies (9 eyes, corneal decompensation (2 eyes, ruptured cataract (6 eyes, and intravitreal foreign bodies (10 eyes. The corneas of one patient had extreme attenuation of the endothelium. Conclusions: Ocular injury occurred in 6.5% of cluster bomb victims and 67% of the patients with ocular injury sustained trauma to multiple organs. Visual morbidity in civilians is an additional reason for a global ban on the use of cluster bombs.

  3. Determination of atomic cluster structure with cluster fusion algorithm

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


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

  4. Packing of protein structures in clusters with magic numbers

    Lindgård, Per-Anker; Bohr, Henrik


    Recently we have proposed a model for folding proteins into packed `clusters'. We have constructed a local homology measure for protein fold classes by projecting consecutively secondary structures onto a lattice. Taking into account hydrophobic forces we have found a mechanism for formation...

  5. Cluster bias: Testing measurement invariance in multilevel data

    Jak, S.


    In this thesis we presented methods and procedures to test and account for measurement bias in multilevel data. Multilevel data are data with a clustered structure, for instance data of children grouped in classrooms, or data of employees in teams. For example, with data of children in classes, we c

  6. Assessment of Rotationally-Invariant Clustering Using Streamlet Tractography

    Liptrot, Matthew George; Lauze, Francois Bernard

    We present a novel visualisation-based strategy for the assessment of a recently proposed clustering technique for raw DWI volumes which derives rotationally-invariant metrics to classify voxels. The validity of the division of all brain tissue voxels into such classes was assessed using...

  7. The coupled cluster method and entanglement in three fermion systems

    Lévay, Péter; Nagy, Szilvia; Pipek, János; Sárosi, Gábor


    The Coupled Cluster (CC) and full CI expansions are studied for three fermions with six and seven modes. Surprisingly the CC expansion is tailor made to characterize the usual stochastic local operations and classical communication (SLOCC) entanglement classes. It means that the notion of a SLOCC transformation shows up quite naturally as a one relating the CC and CI expansions, and going from the CI expansion to the CC one is equivalent to obtaining a form for the state where the structure of the entanglement classes is transparent. In this picture, entanglement is characterized by the parameters of the cluster operators describing transitions from occupied states to singles, doubles, and triples of non-occupied ones. Using the CC parametrization of states in the seven-mode case, we give a simple formula for the unique SLOCC invariant J . Then we consider a perturbation problem featuring a state from the unique SLOCC class characterized by J ≠ 0 . For this state with entanglement generated by doubles, we investigate the phenomenon of changing the entanglement type due to the perturbing effect of triples. We show that there are states with real amplitudes such that their entanglement encoded into configurations of clusters of doubles is protected from errors generated by triples. Finally we put forward a proposal to use the parameters of the cluster operator describing transitions to doubles for entanglement characterization. Compared to the usual SLOCC classes, this provides a coarse grained approach to fermionic entanglement.

  8. Transporter’s evolution and carbohydrate metabolic clusters

    Plantinga, Titia H.; Does, Chris van der; Driessen, Arnold J.M.


    The yiaQRS genes of Escherichia coli K-12 are involved in carbohydrate metabolism. Clustering of homologous genes was found throughout several unrelated bacteria. Strikingly, all four bacterial transport protein classes were found, conserving transport function but not mechanism. It appears that dur

  9. Fostering a Middle Class


    Though there is no official definition of "middle class" in China, the tag has become one few Chinese people believe they deserve anyway.In early August, the Chinese Academy of Social Sciences released a report on China’s urban development,

  10. Teaching Very Large Classes

    DeRogatis, Amy; Honerkamp, Kenneth; McDaniel, Justin; Medine, Carolyn; Nyitray, Vivian-Lee; Pearson, Thomas


    The editor of "Teaching Theology and Religion" facilitated this reflective conversation with five teachers who have extensive experience and success teaching extremely large classes (150 students or more). In the course of the conversation these professors exchange and analyze the effectiveness of several active learning strategies they…

  11. Class Actions in Denmark

    Werlauff, Erik


    The article deals with the relatively new Danish Act on Class Action (Danish: gruppesøgsmål) which was suggested by The Permanent Council on Civil procedure (Retsplejerådet) of which the article's author is a member. The operability of the new provisions is illustrated through some wellknown Danish...

  12. Class, Cultism, and Multiculturalism.

    McLaren, Peter; Farahmandpur, Ramin


    Globalization has hurt both developed and developing countries. Capitalism's relations of exploitation can hurt people of color in disabling ways. Discusses the relationships among race, gender, ethnic, and class identities in order to articulate a political framework that moves toward transnational ethnic alliances, abolishing the role of capital…

  13. Openers for Biology Classes.

    Gridley, C. Robert R.

    This teaching guide contains 200 activities that are suitable for openers and demonstrations in biology classes. Details are provided regarding the use of these activities. Some of the broad topics under which the activities are organized include algae, amphibians, bacteria, biologists, crustaceans, dinosaurs, ecology, evolution, flowering plants,…

  14. Communication, "Class," and Culture.

    Jeffres, Leo W.

    A study was conducted to examine the relationships among communication, social class, and ethnic heritage. Eleven of thirteen ethnic groups in a Midwestern metropolitan area who had been studied in 1976 were surveyed again in late 1980 and early 1981. Groups surveyed were Irish, Greek, Czech, Italian, Lebanese, Hungarian, Lithuanian, Polish,…

  15. Shrinking Your Class

    Herron-Thorpe, Farren L.; Olson, Jo Clay; Davis, Denny


    Toys in the classroom was the result of a National Science Foundation grant that brought two engineering graduate students to a middle school math class. The graduate students and teachers collaborated in an effort to enhance students' mathematical learning. An engineering context was theorized as a way to further develop students' understanding…

  16. IQ and Social Class.

    Fischbein, Siv


    Swedish longitudinal studies of twins support Scarr-Salapatek's explanation of nature-nurture influences on intelligence. This model predicts more genetic variance in test results for advantaged than disadvantaged groups. Jensen's work, however, suggests equal amounts of variance among different social classes. (Author/CP)

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

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


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

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

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


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

  19. A New Clustering Algorithm for Face Classification

    Shaker K. Ali


    Full Text Available In This paper, we proposed new clustering algorithm depend on other clustering algorithm ideas. The proposed algorithm idea is based on getting distance matrix, then the exclusion of the matrix points which will be clustered by saving the location (row, column of these points and determine the minimum distance of these points which will be belongs the group (class and keep the other points which are not clustering yet. The propose algorithm is applied to image data base of the human face with different environment (direction, angles... etc.. These data are collected from different resource (ORL site and real images collected from random sample of Thi_Qar city population in lraq. Our algorithm has been implemented on three types of distance to calculate the minimum distance between points (Euclidean, Correlation and Minkowski distance .The efficiency ratio of proposed algorithm has varied according to the data base and threshold, the efficiency of our algorithm is exceeded (96%. Matlab (2014 has been used in this work.

  20. Hidden Galaxies in the Fornax Cluster

    Drinkwater, M J; Webster, R L; Barnes, D G; Gregg, M D; Phillipps, S; Jones, J B


    We are using the Multibeam 21cm receiver on the Parkes Telescope combined with the optical Two degree Field spectrograph (2dF) of the Anglo-Australian Telescope to obtain the first complete spectroscopic sample of the Fornax cluster. In the optical the survey is unique in that all objects (both ``stars'' and ``galaxies'') within our magnitude limits (Bj=16.5 to 19.7) are measured, producing the most complete survey of cluster members irrespective of surface brightness. We have detected two new classes of high surface brightness dwarf galaxy in the cluster. With 2dF we have discovered a population of very low luminosity (Mb approx -12) objects which are unresolved from the ground and may be the stripped nuclei of dwarf galaxies; they are unlike any known galaxies. In a survey of the brighter (Bj=16.5 to 18) galaxies with the FLAIR-II spectrograph we have found a number of new high surface brightness dwarf galaxies and show that the fraction of star-forming dwarf galaxies in the cluster is about 30 per cent, ab...

  1. Evolution and comparative analysis of the MHC Class III inflammatory region

    Speed Terence P; Sims Sarah; Palmer Sophie; Coggill Penny; Cross Joseph GR; Belov Katherine; Papenfuss Anthony T; Deakin Janine E; Beck Stephan; Graves Jennifer


    Abstract Background The Major Histocompatibility Complex (MHC) is essential for immune function. Historically, it has been subdivided into three regions (Class I, II, and III), but a cluster of functionally related genes within the Class III region has also been referred to as the Class IV region or "inflammatory region". This group of genes is involved in the inflammatory response, and includes members of the tumour necrosis family. Here we report the sequencing, annotation and comparative a...

  2. Euclid - an ESA Medium Class Mission

    Joachimi, B.


    Euclid is an ESA Medium Class mission in the Cosmic Visions program to be launched in 2020. With its 1.2 m telescope, Euclid is going to survey 15,000 deg2 of extragalactic sky in a broad optical band with outstanding image quality fit for weak gravitational lensing measurements. It will also provide near-infrared slitless spectroscopy of more than 107 emission-line galaxies with the main goal of measuring galaxy clustering. Imaging in three near-infrared bands by Euclid will be complemented by ground-based follow-up in optical bands to supply high-quality photometric redshift estimates out to z=2. In combination, its primary cosmological science drivers, weak gravitational lensing and galaxy clustering, will yield unprecedented constraints on the properties of dark matter and dark energy, as well as the validity of Einstein gravity on large scales. Euclid's rich datasets will facilitate further cosmological probes such as statistics of galaxy clusters or the study of galactic dark matter haloes, and a vast array of legacy science. In the following a brief overview on the Euclid mission and its key science is provided.

  3. Subspace K-means clustering

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


    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 existi

  4. Coincidence classes in nonorientable manifolds


    Full Text Available We study Nielsen coincidence theory for maps between manifolds of same dimension regardless of orientation. We use the definition of semi-index of a class, review the definition of defective classes, and study the occurrence of defective root classes. We prove a semi-index product formula for lifting maps and give conditions for the defective coincidence classes to be the only essential classes.

  5. Cluster Implantation and Deposition Apparatus

    Hanif, Muhammad; Popok, Vladimir


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

  6. Stellar populations in star clusters

    Li, Chengyuan; Deng, Licai


    Stellar populations contain the most important information about star clus- ter formation and evolution. Until several decades ago, star clusters were believed to be ideal laboratories for studies of simple stellar populations (SSPs). However, discoveries of multiple stellar populations in Galactic globular clusters have expanded our view on stellar populations in star clusters. They have simultaneously generated a number of controversies, particularly as to whether young star clusters may have the same origin as old globular clusters. In addition, extensive studies have revealed that the SSP scenario does not seem to hold for some intermediate-age and young star clusters either, thus making the origin of multiple stellar populations in star clusters even more complicated. Stellar population anomalies in numerous star clusters are well-documented, implying that the notion of star clusters as true SSPs faces serious challenges. In this review, we focus on stellar populations in massive clusters with different ...

  7. Chemical evolution of star clusters

    van Loon, Jacco Th.


    I discuss the chemical evolution of star clusters, with emphasis on old globular clusters, in relation to their formation histories. Globular clusters clearly formed in a complex fashion, under markedly different conditions from any younger clusters presently known. Those special conditions must be linked to the early formation epoch of the Galaxy and must not have occurred since. While a link to the formation of globular clusters in dwarf galaxies has been suggested, present-day dwarf galaxi...

  8. Maximum-likelihood cluster recontruction

    Bartelmann, M; Seitz, S; Schneider, P J; Bartelmann, Matthias; Narayan, Ramesh; Seitz, Stella; Schneider, Peter


    We present a novel method to recontruct the mass distribution of galaxy clusters from their gravitational lens effect on background galaxies. The method is based on a least-chisquare fit of the two-dimensional gravitational cluster potential. The method combines information from shear and magnification by the cluster lens and is designed to easily incorporate possible additional information. We describe the technique and demonstrate its feasibility with simulated data. Both the cluster morphology and the total cluster mass are well reproduced.

  9. Single-Seed Cascades on Clustered Networks

    McSweeney, John K


    We consider a dynamic network cascade process developed by Watts applied to a random networks with a specified amount of clustering, belonging to a class of random networks developed by Newman. We adapt existing tree-based methods to formulate an appropriate two-type branching process to describe the spread of a cascade started with a single active node, and obtain a fixed-point equation to implicitly express the extinction probability of such a cascade. In so doing, we also recover a special case of a formula of Hackett et al. giving conditions for certain extinction of the cascade.

  10. The spatial structure of young stellar clusters

    Kuhn, Michael A.

    . This apparent contradiction may be evidence of more rapid dynamical evolution accelerated by the merger of subclusters. Overall, 142 subclusters of young stars are found in the 17 MSFRs using the statistical "finite-mixture model" cluster analysis method, and the intrinsic stellar populations for these clusters are inferred using "initial mass functions" and "X-ray luminosity functions." Four structural classes are seen in MSFR: linear chains of subclusters, clumpy structures, core-halo structures, and simple isolated clusters. The subclusters do follow the structure of the molecular clouds, but do not appear to be coeval with each other. There is strong evidence in the subcluster properties for gas expulsion and subcluster expansion (e.g., the density ~ radius and age ~ radius relations), and evidence that is consistent with subcluster mergers (e.g., the ellipticity distribution and the number ~ density relation). The cluster analysis provides evidence to support hierarchical models of stellar cluster formation, which have been theorized to explain mass segregation and dynamical relaxation in very young clusters. The ~1 Myr age spreads in the subclusters of a MSFR appear to require slower star-formation in giant molecular clouds with continually driven turbulence, rather than clouds with rapidly decaying turbulence. And, the diverse range of stellar surface density environment in MSFRs will have implications for models of cluster survival after gas removal.

  11. 集群资源模糊聚类划分模型%Fuzzy Clustering Partition Model of Cluster Resource



    A fuzzy clustering partition model of cluster resource is proposed in this paper. It quantizes and normalizes the computer resource parameters of CPU, memory, I/O, network adapter and net. It uses fuzzy clustering technique to realize the partition of the computing nodes in the computer clusters. By using of the vector of resource demand and the vector of lowest inaccuracy tolerance, it can divide the computer cluster into several classes and the performance of these computers in one class is more similar. Test results show that this model can effectively partition the computer cluster and it fits the resource schedule of cloud computing.%提出一种集群资源模糊聚类划分模型.对计算机集群中计算节点的CPU、内存、网络、I/O和网卡资源参数进行量化和规范化,运用模糊聚类技术,实现计算节点的聚类划分.引入任务资源需求向量和最低误差容忍向量,将计算机集群划分为若干个性能均衡的逻辑子群.测试结果表明,该模型能有效划分计算机集群,适用于云计算领域的资源调度.

  12. World Class Facilities Management

    Malmstrøm, Ole Emil; Jensen, Per Anker


    Alle der med entusiasme arbejder med Facilities Management drømmer om at levere World Class. DFM drømmer om at skabe rammer og baggrund for, at vi i Danmark kan bryste os at være blandt de førende på verdensplan. Her samles op på, hvor tæt vi er på at nå drømmemålet.......Alle der med entusiasme arbejder med Facilities Management drømmer om at levere World Class. DFM drømmer om at skabe rammer og baggrund for, at vi i Danmark kan bryste os at være blandt de førende på verdensplan. Her samles op på, hvor tæt vi er på at nå drømmemålet....

  13. Out about class.

    Walker, L; Sell, I


    ABSTRACT Lesbian activist Léonie Walker traces the evolution of her involvement in social change philanthropy and her work to bring together activists of diverse class and racial backgrounds. She shows how she was trained as an activist, discusses conscious and socially responsible ways to steward wealth, and gives voice to the seldom-heard experiences of LGBT people with inherited wealth. The co-founder of the Women Managing Wealth program at the Ms. Foundation and a board member of Astraea Lesbian Action Foundation, she has also developed and facilitated numerous Dismantling Classism workshops. In this article, she discusses the importance of, and ways of implementing, cross-class, cross-race dialogue that can further understanding among activists of different backgrounds.

  14. Flexible Word Classes


    a century, the phenomenon has not played a role in the development of linguistic typology or modern grammatical theory. The current volume aims to address this gap by offering detailed studies on flexible word classes, investigating their properties and what it means for the grammar of a language to have...... Indonesian, Santali, Sri Lanka Malay, Lushootseed, Gooniyandi, and Late Archaic Chinese. Readership: Linguists and students of linguistics and cognitive sciences, anthropologists, philosophers...

  15. Monothiol glutaredoxins and A-type proteins: partners in Fe-S cluster trafficking.

    Mapolelo, Daphne T; Zhang, Bo; Randeniya, Sajini; Albetel, Angela-Nadia; Li, Haoran; Couturier, Jérémy; Outten, Caryn E; Rouhier, Nicolas; Johnson, Michael K


    Monothiol glutaredoxins (Grxs) are proposed to function in Fe-S cluster storage and delivery, based on their ability to exist as apo monomeric forms and dimeric forms containing a subunit-bridging [Fe(2)S(2)](2+) cluster, and to accept [Fe(2)S(2)](2+) clusters from primary scaffold proteins. In addition yeast cytosolic monothiol Grxs interact with Fra2 (Fe repressor of activation-2), to form a heterodimeric complex with a bound [Fe(2)S(2)](2+) cluster that plays a key role in iron sensing and regulation of iron homeostasis. In this work, we report on in vitro UV-visible CD studies of cluster transfer between homodimeric monothiol Grxs and members of the ubiquitous A-type class of Fe-S cluster carrier proteins ((Nif)IscA and SufA). The results reveal rapid, unidirectional, intact and quantitative cluster transfer from the [Fe(2)S(2)](2+) cluster-bound forms of A. thaliana GrxS14, S. cerevisiae Grx3, and A. vinelandii Grx-nif homodimers to A. vinelandii(Nif)IscA and from A. thaliana GrxS14 to A. thaliana SufA1. Coupled with in vivo evidence for interaction between monothiol Grxs and A-type Fe-S cluster carrier proteins, the results indicate that these two classes of proteins work together in cellular Fe-S cluster trafficking. However, cluster transfer is reversed in the presence of Fra2, since the [Fe(2)S(2)](2+) cluster-bound heterodimeric Grx3-Fra2 complex can be formed by intact [Fe(2)S(2)](2+) cluster transfer from (Nif)IscA. The significance of these results for Fe-S cluster biogenesis or repair and the cellular regulation of the Fe-S cluster status are discussed.

  16. [Social classes and poverty].

    Benach, Joan; Amable, Marcelo


    Social classes and poverty are two key social determinants fundamental to understand how disease and health inequalities are produced. During the 90's in Spain there has been a notable oscillation in the inequality and poverty levels, with an increase in the middle of the decade when new forms of social exclusion, high levels of unemployment and great difficulties in accessing the labour market, especially for those workers with less resources, emerged. Today society is still characterized by a clear social stratification and the existence of social classes with a predominance of high levels of unemployment and precarious jobs, and where poverty is an endemic social problem much worse than the EU average. To diminish health inequalities and to improve the quality of life will depend very much on the reduction of the poverty levels and the improvement of equal opportunities and quality of employment. To increase understanding of how social class and poverty affect public health, there is a need to improve the quality of both information and research, and furthermore planners and political decision makers must take into account those determinants when undertaking disease prevention and health promotion.

  17. Clustering Game Behavior Data

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


    Recent years have seen a deluge of behavioral data from players hitting the game industry. Reasons for this data surge are many and include the introduction of new business models, technical innovations, the popularity of online games, and the increasing persistence of games. Irrespective...... of the causes, the proliferation of behavioral data poses the problem of how to derive insights therefrom. Behavioral data sets can be large, time-dependent and high-dimensional. Clustering offers a way to explore such data and to discover patterns that can reduce the overall complexity of the data. Clustering...... scientists and present a review and tutorial focusing on the application of clustering techniques to mine behavioral game data. Several algorithms are reviewed and examples of their application shown. Key topics such as feature normalization are discussed and open problems in the context of game analytics...

  18. The concept of cluster

    Laursen, Lea Louise Holst; Møller, Jørgen


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

  19. Clusters in Light Nuclei

    Beck, C; Zafra, A Sanchez i; Thummerer, S; Azaiez, F; Bednarczyk, P; Courtin, S; Curien, D; Dorvaux, O; Goasduff, A; ~Lebhertz, D; Nourreddine, A; ~Rousseau, M; Salsac, M -D; von Oertzen, W; Gebauer, B; Wheldon, C; Kokalova, Tz; Efimov, G; Zherebchevsky, V; Schulz, Ch; Bohlen, H G; Kamanin, D; de Angelis, G; Gadea, A; Lenzi, S; Napoli, D R; Szilner, S; Milin, M; Catford, W N; Jenkins, D G; Royer, G


    A great deal of research work has been undertaken in the alpha-clustering study since the pioneering discovery, half a century ago, of 12C+12C molecular resonances. Our knowledge of the field of the physics of nuclear molecules has increased considerably and nuclear clustering remains one of the most fruitful domains of nuclear physics, facing some of the greatest challenges and opportunities in the years ahead. In this work, the occurence of "exotic" shapes in light N=Z alpha-like nuclei is investigated. Various approaches of superdeformed and hyperdeformed bands associated with quasimolecular resonant structures are presented. Results on clustering aspects are also discussed for light neutron-rich Oxygen isotopes.

  20. South Asian Cluster

    Ionel Sergiu Pirju


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

  1. I Cluster geografici

    Maurizio Rosina


    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.

  2. Cluster-tilting theory

    Simões, Raquel Coelho Guardado


    Tese de mestado em Matemática (Álgebra, Lógica e Fundamentos) apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2008 Resumo alargado disponível em português The notion of Cluster Algebra first appeared in 2001, in a paper by S. Fomin and A. Zelevinsky, studying the dual canonical basis of the quantum group of a finite dimensional simple Lie algebra over the complex numbers, and also total positivity for algebraic groups. Cluster categories, introduced by A. Buan, R...

  3. Kinematics of Clustering

    Wang, Steven; Metcalfe, Guy; Wu, Jie


    The dynamical system for inertial particles in fluid flow has both attracting and repelling regions, the interplay of which can localize particles. In laminar flow experiments we find that particles, initially moving throughout the fluid domain, can undergo an instability and cluster into subdomains of the fluid when the flow Reynolds number exceeds a critical value that depends on particle and fluid inertia. We derive an expression for the instability boundary and for a universal curve that describes the clustering rate for all particles.

  4. An Emerge Approach in Inter Cluster Similarity for Quality Clusters

    H. Venkateswara Reddy


    Full Text Available Relationship between the datasets is one most important issue in recent years. The recent methods are based mostly on the numerical data, but these methods are not suitable for real time data such as web pages, business transactions etc., which are known as Categorical data. It is difficult to find relationship in categorical data. In this paper, a new approach is proposed for finding the relationshipbetween the categorical data, hence to find relationship between the clusters. The main aim is to identify the quality clusters based on the relationship between clusters. If there is no relationship between clusters then those clusters are treated as quality clusters.

  5. Higher-order structure and epidemic dynamics in clustered networks

    Ritchie, Martin; House, Thomas; Kiss, Istvan Z


    Clustering is typically measured by the ratio of triangles to all triples, open or closed. Generating clustered networks, and how clustering affects dynamics on networks, is reasonably well understood for certain classes of networks \\cite{vmclust, karrerclust2010}, e.g., networks composed of lines and non-overlapping triangles. In this paper we show that it is possible to generate networks which, despite having the same degree distribution and equal clustering, exhibit different higher-order structure, specifically, overlapping triangles and other order-four (a closed network motif composed of four nodes) structures. To distinguish and quantify these additional structural features, we develop a new network metric capable of measuring order-four structure which, when used alongside traditional network metrics, allows us to more accurately describe a network's topology. Three network generation algorithms are considered: a modified configuration model and two rewiring algorithms. By generating homogeneous netwo...

  6. Cluster-like coordinates in supersymmetric quantum field theory.

    Neitzke, Andrew


    Recently it has become apparent that N = 2 supersymmetric quantum field theory has something to do with cluster algebras. I review one aspect of the connection: supersymmetric quantum field theories have associated hyperkähler moduli spaces, and these moduli spaces carry a structure that looks like an extension of the notion of cluster variety. In particular, one encounters the usual variables and mutations of the cluster story, along with more exotic extra variables and generalized mutations. I focus on a class of examples where the underlying cluster varieties are moduli spaces of flat connections on surfaces, as considered by Fock and Goncharov [Fock V, Goncharov A (2006) Publ Math Inst Hautes Études Sci 103:1-211]. The work reviewed here is largely joint with Davide Gaiotto and Greg Moore.

  7. Achieving Order through CHAOS: the LLNL HPC Linux Cluster Experience

    Braby, R L; Garlick, J E; Goldstone, R J


    Since fall 2001, Livermore Computing at Lawrence Livermore National Laboratory has deployed 11 Intel IA-32-based Linux clusters ranging in size up to 1154 nodes. All provide a common programming model and implement a similar cluster architecture. Hardware components are carefully selected for performance, usability, manageability, and reliability and are then integrated and supported using a strategy that evolved from practical experience. Livermore Computing Linux clusters run a common software environment that is developed and maintained in-house while drawing components and additional support from the open source community and industrial partnerships. The environment is based on Red Hat Linux and adds kernel modifications, cluster system management, monitoring and failure detection, resource management, authentication and access control, development environment, and parallel file system. The overall strategy has been successful and demonstrates that world-class high-performance computing resources can be built and maintained using commodity off-the-shelf hardware and open source software.

  8. Combining cluster number counts and galaxy clustering

    Lacasa, Fabien


    We present a detailed modelling of the joint covariance matrix between cluster number counts and the galaxy angular power spectrum. To this end, we use a Halo Model framework complemented by a Halo Occupation Distribution model (HOD), and we work in full-sky. We demonstrate the importance of accounting for non-Gaussianity to produce accurate covariance predictions, as the Gaussian part of the covariance can in fact become subdominant in certain configurations. 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, and demonstrating interesting mathematical properties. 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 noticeable better constraints, in particular because the cross-covariance introduces a synergy between the probes on small scales....

  9. Localized attack on clustering networks

    Dong, Gaogao; Du, Ruijin; Shao, Shuai; Stanley, H Eugene; Shlomo, Havlin


    Clustering network is one of which complex network attracting plenty of scholars to discuss and study the structures and cascading process. We primarily analyzed the effect of clustering coefficient to other various of the single clustering network under localized attack. These network models including double clustering network and star-like NON with clustering and random regular (RR) NON of ER networks with clustering are made up of at least two networks among which exist interdependent relation among whose degree of dependence is measured by coupling strength. We show both analytically and numerically, how the coupling strength and clustering coefficient effect the percolation threshold, size of giant component, critical coupling point where the behavior of phase transition changes from second order to first order with the increase of coupling strength between the networks. Last, we study the two types of clustering network: one type is same with double clustering network in which each subnetwork satisfies ...

  10. Clustering of resting state networks.

    Megan H Lee

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

  11. All quiet in Globular Clusters

    Dobrotka, A; Menou, K; Dobrotka, Andrej; Lasota, Jean-Pierre; Menou, Kristen


    Cataclysmic Variables (CVs) should be present in large numbers in Globular Clusters (GCs). Numerous low-luminosity X-ray sources identified over the past few years as candidate CVs in GCs support this notion. Yet, very few "cataclysms," the characteristic feature of this class of objects in the field, have been observed in GCs. We address this discrepancy here, within the framework of the standard Disk Instability Model for CV outbursts. We argue that the paucity of outbursts in GCs is probably not a direct consequence of the donors' low metallicities. We present diagnostics based on outburst properties allowing tests of the hypothesis that rare cataclysms are entirely due to lower mass transfer rates in GCs relative to the field, and we argue against this explanation. Instead, we propose that a combination of low mass transfer rates (>~ 10^14-15 g/s) and moderately strong white dwarf magnetic moments (>~ 10^30 G cm^3) stabilize CV disks in GCs and thus prevent most of them from experiencing frequent outburst...

  12. An Analysis of Particle Swarm Optimization with Data Clustering-Technique for Optimization in Data Mining

    Amreen Khan,


    Full Text Available Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. Clustering aims at representing large datasets by a fewer number of prototypes or clusters. It brings simplicity in modeling data and thus plays a central role in the process of knowledge discovery and data mining. Data mining tasks require fast and accurate partitioning of huge datasets, which may come with a variety of attributes or features. This imposes severe computational requirements on the relevant clustering techniques. A family of bio-inspired algorithms, well-known as Swarm Intelligence (SI has recently emerged that meets these requirements and has successfully been applied to a number ofreal world clustering problems. This paper looks into the use ofParticle Swarm Optimization for cluster analysis. The effectiveness of Fuzzy C-means clustering provides enhanced performance and maintains more diversity in the swarm and also allows the particles to be robust to trace the changing environment.

  13. Class Action and Class Settlement in a European Perspective

    Werlauff, Erik


    The article analyses the options for introducing common European rules on class action lawsuits with an opt-out-model in individual cases. An analysis is made of how the risks of misuse of class actions can be prevented. The article considers the Dutch rules on class settlements (the WCAM procedure...

  14. Clustering via Kernel Decomposition

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


    Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain poste...

  15. Detecting alternative graph clusterings.

    Mandala, Supreet; Kumara, Soundar; Yao, Tao


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

  16. Extended Fuzzy Clustering Algorithms

    U. Kaymak (Uzay); M. Setnes


    textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applied successfully in various fields including finance and marketing. Despite the successful applications, there are a number of issues that must be dealt with in practical applications of fuz

  17. Cluster headaches simulating parasomnias.

    Isik, Ugur; D'Cruz, O 'Neill F


    Nocturnal episodes of agitated arousal in otherwise healthy young children are often related to nonrapid eye movement parasomnias (night terrors). However, in patients with acute onset or increased frequency of parasomnias, organic causes of discomfort must be excluded. We report four young children whose parasomnias were caused by nocturnal cluster headaches and who responded to indomethacin dramatically.

  18. Dettagli utilizzo cluster INTEL


    Dall'inizio dell'anno 2004 il CILEA ospita e gestisce un cluster di processori Intel a 32 bit denominato avogadro. Esso é costituito da 128 nodi biprocessori Intel Xeon 3.06 GHz. L'articolo intende presentare le problematiche relative all'utilizzo della macchina processore fornendo le istruzioni operative necessarie all'uso più efficace.

  19. Fuzzy clustering of mechanisms

    Amitabha Ghosh; Dilip Kumar Pratihar; M V V Amarnath; Guenter Dittrich; Jorg Mueller


    During the course of development of Mechanical Engineering, a large number of mechanisms (that is, linkages to perform various types of tasks) have been conceived and developed. Quite a few atlases and catalogues were prepared by the designers of machines and mechanical systems. However, often it is felt that a clustering technique for handling the list of large number of mechanisms can be very useful,if it is developed based on a scientific principle. In this paper, it has been shown that the concept of fuzzy sets can be conveniently used for this purpose, if an adequate number of properly chosen attributes (also called characteristics) are identified. Using two clustering techniques, the mechanisms have been classified in the present work and in future, it may be extended to develop an expert system, which can automate type synthesis phase of mechanical design. To the best of the authors’ knowledge, this type of clustering of mechanisms has not been attempted before. Thus, this is the first attempt to cluster the mechanisms based on some quantitative measures. It may help the engineers to carry out type synthesis of the mechanisms.

  20. Emergence of regional clusters

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


    The literature on regional clusters has increased considerably during the last decade. The emergence and growth patterns are usually explained by such factors as unique local culture, regional capabilities, tacit knowledge or the existence of location-specific externalities (knowledge spillovers,...

  1. PVM Support for Clusters

    Springer, P.


    The latest version of PVM (3.4.3) now contains support for a PC cluster running Linux, also known as a Beowulf system. A PVM user of a computer outside the Beowulf system can add the Beowulf as a single machine.

  2. Hybrid cluster identification

    Martín-Herrero, J.


    I present a hybrid method for the labelling of clusters in two-dimensional lattices, which combines the recursive approach with iterative scanning to reduce the stack size required by the pure recursive technique, while keeping its benefits: single pass and straightforward cluster characterization and percolation detection parallel to the labelling. While the capacity to hold the entire lattice in memory is usually regarded as the major constraint for the applicability of the recursive technique, the required stack size is the real limiting factor. Resorting to recursion only for the transverse direction greatly reduces the recursion depth and therefore the required stack. It also enhances the overall performance of the recursive technique, as is shown by results on a set of uniform random binary lattices and on a set of samples of the Ising model. I also show how this technique may replace the recursive technique in Wolff's cluster algorithm, decreasing the risk of stack overflow and increasing its speed, and the Hoshen-Kopelman algorithm in the Swendsen-Wang cluster algorithm, allowing effortless characterization during generation of the samples and increasing its speed.

  3. Resolved SZE Cluster Count

    Jia-Yu Tang; Zu-Hui Fan


    We study the counts of resolved SZE (Sunyaev-Zel'dovich effect) clus-ters expected from an interferometric survey in different cosmological models underdifferent conditions. The self-similar universal gas model and Press-Schechter massfunction are used. We take the observing frequency to be 90 GHz, and consider twodish diameters, 1.2 m and 2.5 m. We calculate the number density of the galaxyclusters dN/(dΩdz) at a high flux limit Slimv = 100mJy and at a relative lowSlimv = 10 mJy. The total numbers of SZE clusters N in two low-Ω0 models arecompared. The results show that the influence of the resolved effect depends notonly on D, but also on Slimv: at a given D, the effect is more significant for a highthan for a low Slim Also, the resolved effect for a flat universe is more impressivethan that for an open universe. For D = 1.2m and Slimv= 10mJy, the resolvedeffect is very weak. Considering the designed interferometers which will be used tosurvey SZE clusters, we find that the resolved effect is insignificant when estimatingthe expected yield of the SZE cluster surveys.

  4. Clustering under Perturbation Resilience

    Balcan, Maria Florina


    Recently, Bilu and Linial \\cite{BL} formalized an implicit assumption often made when choosing a clustering objective: that the optimum clustering to the objective should be preserved under small multiplicative perturbations to distances between points. They showed that for max-cut clustering it is possible to circumvent NP-hardness and obtain polynomial-time algorithms for instances resilient to large (factor $O(\\sqrt{n})$) perturbations, and subsequently Awasthi et al. \\cite{ABS10} considered center-based objectives, giving algorithms for instances resilient to O(1) factor perturbations. In this paper, we greatly advance this line of work. For the $k$-median objective, we present an algorithm that can optimally cluster instances resilient to $(1 + \\sqrt{2})$-factor perturbations, solving an open problem of Awasthi et al.\\cite{ABS10}. We additionally give algorithms for a more relaxed assumption in which we allow the optimal solution to change in a small $\\epsilon$ fraction of the points after perturbation. ...

  5. Data clustering algorithms and applications

    Aggarwal, Charu C


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

  6. Quartile Clustering: A quartile based technique for Generating Meaningful Clusters

    Goswami, Saptarsi


    Clustering is one of the main tasks in exploratory data analysis and descriptive statistics where the main objective is partitioning observations in groups. Clustering has a broad range of application in varied domains like climate, business, information retrieval, biology, psychology, to name a few. A variety of methods and algorithms have been developed for clustering tasks in the last few decades. We observe that most of these algorithms define a cluster in terms of value of the attributes, density, distance etc. However these definitions fail to attach a clear meaning/semantics to the generated clusters. We argue that clusters having understandable and distinct semantics defined in terms of quartiles/halves are more appealing to business analysts than the clusters defined by data boundaries or prototypes. On the samepremise, we propose our new algorithm named as quartile clustering technique. Through a series of experiments we establish efficacy of this algorithm. We demonstrate that the quartile clusteri...

  7. Anomalia de Classe III


    Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária Introdução: A anomalia de classe III, é uma má oclusão que afeta os indivíduos psicologicamente, pois hoje em dia, a estética é socialmente valorizada. Deste modo, o diagnóstico deve ser executado precocemente para que os indivíduos portadores desta anomalia, possam ser acompanhados desde criança, pelos profissionais área da Medicina...

  8. Fullerene Molecules and Other Clusters of III-V Compounds

    Hira, Ajit; Auxier, John, II; Lucero, Melinda


    The goal of the our work is to derive geometries of fullerene-like cages and other clusters of atoms from groups III and V of the periodic table. Our previous research focused on Carbon Fullerenes and on GanAsn clusters (n = 1 thru 12). Our research group has made an original discovery about GanAsn clusters. In our work on nanotechnology to date, we used the hybrid ab initio methods of quantum chemistry to derive the different geometries for the clusters of interest. We also calculated binding energies, bond-lengths, ionization potentials, electron affinities and HOMO-LUMO gaps, and IR spectra for these geometries. Of particular significance was the magic number for GaAs cluster stability that we found at n = 8. This is important because materials containing controlled III-V nanostructures provide the capability of preparing new classes of materials with enhanced optical, magnetic, chemical sensor and photo-catalytic properties. The second phase of the investigation will examine the effects of confinement on the optical properties the clusters. It will be interesting to observe novel linear as well as nonlinear optical processes in them. The third phase of the investigation will focus on the improved design of solar cells based on the optical properties of the clusters.

  9. The rotation of Galaxy Clusters

    Tovmassian, Hrant M


    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\\%, and clusters of BMI type with dominant cD galaxy, ~ 35%. 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 merging with other clusters and groups of galaxies, in the result of which the rotation has been prevented.

  10. Estimation and Model Selection for Model-Based Clustering with the Conditional Classification Likelihood

    Baudry, Jean-Patrick


    The Integrated Completed Likelihood (ICL) criterion has been proposed by Biernacki et al. (2000) in the model-based clustering framework to select a relevant number of classes and has been used by statisticians in various application areas. A theoretical study of this criterion is proposed. A contrast related to the clustering objective is introduced: the conditional classification likelihood. This yields an estimator and a model selection criteria class. The properties of these new procedures are studied and ICL is proved to be an approximation of one of these criteria. We oppose these results to the current leading point of view about ICL, that it would not be consistent. Moreover these results give insights into the class notion underlying ICL and feed a reflection on the class notion in clustering. General results on penalized minimum contrast criteria and on mixture models are derived, which are interesting in their own right.

  11. Photoionization of rare gas clusters

    Zhang, Huaizhen

    This thesis concentrates on the study of photoionization of van der Waals clusters with different cluster sizes. The goal of the experimental investigation is to understand the electronic structure of van der Waals clusters and the electronic dynamics. These studies are fundamental to understand the interaction between UV-X rays and clusters. The experiments were performed at the Advanced Light Source at Lawrence Berkeley National Laboratory. The experimental method employs angle-resolved time-of-flight photoelectron spectrometry, one of the most powerful methods for probing the electronic structure of atoms, molecules, clusters and solids. The van der Waals cluster photoionization studies are focused on probing the evolution of the photoelectron angular distribution parameter as a function of photon energy and cluster size. The angular distribution has been known to be a sensitive probe of the electronic structure in atoms and molecules. However, it has not been used in the case of van der Waals clusters. We carried out outer-valence levels, inner-valence levels and core-levels cluster photoionization experiments. Specifically, this work reports on the first quantitative measurements of the angular distribution parameters of rare gas clusters as a function of average cluster sizes. Our findings for xenon clusters is that the overall photon-energy-dependent behavior of the photoelectrons from the clusters is very similar to that of the corresponding free atoms. However, distinct differences in the angular distribution point at cluster-size-dependent effects were found. For krypton clusters, in the photon energy range where atomic photoelectrons have a high angular anisotropy, our measurements show considerably more isotropic angular distributions for the cluster photoelectrons, especially right above the 3d and 4p thresholds. For the valence electrons, a surprising difference between the two spin-orbit components was found. For argon clusters, we found that the

  12. VizieR Online Data Catalog: Southern Groups and Clusters of Galaxies (Duus, Newell 1977)

    Duus, A.; Newell, E. B.


    The catalog is the result of a survey of film copies of the ESO B plates for southern clusters of galaxies. Because of the varying quality of the ESO films and the scattered placement of the fields searched, the present survey is not intended for use in statistical studies. Nevertheless, the clusters and groups are listed from a representative sample of nearby to distant systems that is spread across the southern sky. The catalog contains cluster identification number based on a right ascension, declination numbering scheme; the ESO field number (see ADC catalog 6030); position of cluster center on plate (in mm); concentration class type of cluster; estimate of the number of galaxies; asterisk for uncertainty assignment previous value; distance class; and previous designations. (1 data file).

  13. The luminosity function of cluster galaxies relations among M$_{1}$, M* and the morphological type

    Trevese, D; Appodia, B


    A study of the luminosity function of 36 Abell clusters of galaxies has been carried out using photographic plates obtained with the Palomar 1.2 m Schmidt telescope. The relation between the magnitude M_1 of the brightest cluster member and the Schechter function parameter M* has been analyzed. A positive correlation between M* and M_1 is found. However clusters appear segregated in the M_1-M* plane according to their Rood & Sastry class in such a way that on average M_1 becomes brighter while M* becomes fainter going from late to early Rood & Sastry and also Bautz & Morgan classes. Also a partial correlation analysis involving the magnitude M_10 of the 10th brightest galaxy, shows a negative intrinsic correlation between M_1 and M*. These results agree with the cannibalism model for the formation of brightest cluster members, and provide new constraints for theories of cluster formation and evolution.

  14. Challenges and Opportunities for the Application of Boron Clusters in Drug Design.

    Leśnikowski, Zbigniew J


    There are two branches in boron medicinal chemistry: the first focuses on single boron atom compounds, and the second utilizes boron clusters. Boron clusters and their heteroatom counterparts belong to the family of cage compounds. A subset of this extensive class of compounds includes dicarbadodecaboranes, which have the general formula C2B10H12, and their metal biscarboranyl complexes, metallacarboranes, with the formula [M(C2B10H12)2(-2)]. The unique properties of boron clusters have resulted in their utilization in applications such as in pharmacophores, as scaffolds in molecular construction, and as modulators of bioactive compounds. This Perspective presents an overview of the properties of boron clusters that are pertinent for drug discovery, recent applications in the design of various classes of drugs, and the potential use of boron clusters in the construction of new pharmaceuticals.

  15. Reconciling Virtual Classes with Genericity

    Ernst, Erik


    classes. As a result, a kind of type parameters have been introduced, but they are simple and only used where they excel. Conversely, final definitions of virtual classes have been re- moved from the language, thus making virtual classes more flexible. The result- ing language presents a clearer and more...

  16. Team Learning in Large Classes.

    Roueche, Suanne D., Ed.


    Information and suggestions are provided on the use of team learning in large college classes. Introductory material discusses the negative cycle of student-teacher interaction that may be provoked by large classes, and the use of permanent, heterogeneous, six- or seven-member student learning groups as the central focus of class activity as a…

  17. Understanding Class in Contemporary Societies

    Harrits, Gitte Sommer


    In this paper, I argue that claims about the death of class and the coming of the classless society are premature. Such claims are seldom genuinely empirical, and the theoretical argument often refers to a simple and therefore easily dismissible concept of class. By rejecting the concept of class...

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

    Deng, Y.; Qian, X.; Blöte, H.W.J.


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

  19. Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

    Jeban Ganesalingam

    Full Text Available BACKGROUND: Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS: Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS: The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001. CONCLUSION: The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

  20. Merging Galaxy Cluster Abell 2255 in Mid-Infrared

    Shim, Hyunjin; Lee, Hyung Mok; Lee, Myung Gyoon; Kim, Seong Jin; Hwang, Ho Seong; Hwang, Narae; Ko, Jongwan; Lee, Jong Chul; Lim, Sungsoon; Matsuhara, Hideo; Seo, Hyunjong; Wada, Takehiko; Goto, Tomotsugu


    We present the mid-infrared (MIR) observation of a nearby galaxy cluster, Abell 2255 by the AKARI space telescope. Using the AKARI's continuous wavelength coverage between 3-24 micron and the wide field of view, we investigate the properties of cluster member galaxies to see how the infall of the galaxies, the cluster substructures, and the cluster-cluster merger influence their evolution. We show that the excess of MIR (11 micron) flux is a good indicator to discriminate galaxies at different evolutionary stages, and divide galaxies into three classes accordingly : strong MIR-excess (N3-S11>0.2) galaxies that include both unobscured and obscured star-forming galaxies, weak MIR-excess (-2.05 Gyr) galaxies where the MIR emission arises mainly from the circumstellar dust around AGB stars, and intermediate MIR-excess (-1.2classes that are less than a few Gyrs old past the prime star formation activity. With the MIR-excess diagnostics, we investigate how local and cl...

  1. Eclipsing binaries in open clusters

    Southworth, John; Clausen, J.V.


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

  2. Cluster Based Text Classification Model

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


    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...

  3. Chemical evolution of star clusters

    van Loon, Jacco Th


    I discuss the chemical evolution of star clusters, with emphasis on old globular clusters, in relation to their formation histories. Globular clusters clearly formed in a complex fashion, under markedly different conditions from any younger clusters presently known. Those special conditions must be linked to the early formation epoch of the Galaxy and must not have occurred since. While a link to the formation of globular clusters in dwarf galaxies has been suggested, present-day dwarf galaxies are not representative of the gravitational potential wells within which the globular clusters formed. Instead, a formation deep within the proto-Galaxy or within dark-matter minihaloes might be favoured. Not all globular clusters may have formed and evolved similarly. In particular, we may need to distinguish Galactic halo from Galactic bulge clusters.

  4. Nuclear Cluster Aspects in Astrophysics

    Kubono, Shigeru


    The role of nuclear clustering is discussed for nucleosynthesis in stellar evolution with Cluster Nucleosynthesis Diagram (CND) proposed before. Special emphasis is placed on α-induced stellar reactions together with molecular states for O and C burning.

  5. Radio observations of Planck clusters

    Kale, Ruta


    Recently, a number of new galaxy clusters have been detected by the ESA-Planck satellite, the South Pole Telescope and the Atacama Cosmology Telescope using the Sunyaev-Zeldovich effect. Several of the newly detected clusters are massive, merging systems with disturbed morphology in the X-ray surface brightness. Diffuse radio sources in clusters, called giant radio halos and relics, are direct probes of cosmic rays and magnetic fields in the intra-cluster medium. These radio sources are found to occur mainly in massive merging clusters. Thus, the new SZ-discovered clusters are good candidates to search for new radio halos and relics. We have initiated radio observations of the clusters detected by Planck with the Giant Metrewave Radio Telescope. These observations have already led to the detection of a radio halo in PLCKG171.9-40.7, the first giant halo discovered in one of the new Planck clusters.

  6. Hierarchical Formation of Galactic Clusters

    Elmegreen, B G


    Young stellar groupings and clusters have hierarchical patterns ranging from flocculent spiral arms and star complexes on the largest scale to OB associations, OB subgroups, small loose groups, clusters and cluster subclumps on the smallest scales. There is no obvious transition in morphology at the cluster boundary, suggesting that clusters are only the inner parts of the hierarchy where stars have had enough time to mix. The power-law cluster mass function follows from this hierarchical structure: n(M_cl) M_cl^-b for b~2. This value of b is independently required by the observation that the summed IMFs from many clusters in a galaxy equals approximately the IMF of each cluster.

  7. Observations of Distant Clusters

    Donahue, Megan


    The is the proceedings and papers supported by the LTSA grant: Homer, D. J.\\& Donahue, M. 2003, in "The Emergence of Cosmic Structure": 13'h Astrophysics Conference Proceedings, Vol. 666,3 1 1-3 14, (AIP). Baumgartner, W. H., Loewenstein, M., Horner, D. J., Mushotzky, R. F. 2003, HEAD- AAS, 35.3503. Homer, D. J. , Donahue, M., Voit G. M. 2003, HEAD-AAS, 35.1309. Nowak, M. A., Smith, B., Donahue, M., Stocke, J. 2003, HEAD-AAS, 35.1316. Scott, D., Borys, C., Chapman, S. C., Donahue, M., Fahlman, G. G., Halpem, M. Newbury, P. 2002, AAS, 128.01. Jones, L. R. et al. 2002, A new era in cosmology, ASP Conference Proceedings, Vol. 283, p. 223 Donahue, M., Daly, R. A., Homer, D. J. 2003, ApJ, 584, 643, Constraints on the Cluster Environments and Hotspot magnetic field strengths for radio sources 3280 and 3254. Donahue, M., et al. 2003, ApJ, 598, 190. The mass, baryonic fraction, and x-ray temperature of the luminous, high-redshift cluster of galaxies MS045 1.6-0305 Perlman, E. S. et al. 2002, ApJS, 140, 256. Smith, B. J., Nowak, M., Donahue, M., Stocke, J. 2003, AJ, 126, 1763. Chandra Observations of the Interacting NGC44 10 Group of Galaxies. Postman, M., Lauer, T. R., Oegerle, W., Donahue, M. 2002, ApJ, 579, 93. The KPNO/deep-range cluster survey I. The catalog and space density of intermediate-redshift clusters. Molnar, S. M., Hughes, J. P., Donahue, M., Joy, M. 2002, ApJ, 573, L91, Chandra Observations of Unresolved X-Ray Sources around Two Clusters of Galaxies. Donahue, M., Mack, J., 2002 NewAR, 46, 155, HST NIcmos and WFPC2 observations of molecular hydrogen and dust around cooling flows. Koekemoer, A. M. et al. 2002 NewAR, 46, 149, Interactions between the A2597 central radio source and dense gas host galaxy. Donahue, M. et al. 2002 ApJ, 569,689, Distant cluster hunting II.

  8. Endogenous Small RNA Clusters in Plants

    Yong-Xin Liu


    Full Text Available In plants, small RNAs (sRNAs usually refer to non-coding RNAs (ncRNAs with lengths of 20–24 nucleotides. sRNAs are involved in the regulation of many essential processes related to plant development and environmental responses. sRNAs in plants are mainly grouped into microRNAs (miRNAs and small interfering RNAs (siRNAs, and the latter can be further classified into trans-acting siRNAs (ta-siRNAs, repeat-associated siRNAs (ra-siRNAs, natural anti-sense siRNAs (nat-siRNAs, etc. Many sRNAs exhibit a clustered distribution pattern in the genome. Here, we summarize the features and functions of cluster-distributed sRNAs, aimed to not only provide a thorough picture of sRNA clusters (SRCs in plants, but also shed light on the identification of new classes of functional sRNAs.

  9. Internet Gamblers Differ on Social Variables: A Latent Class Analysis.

    Khazaal, Yasser; Chatton, Anne; Achab, Sophia; Monney, Gregoire; Thorens, Gabriel; Dufour, Magali; Zullino, Daniele; Rothen, Stephane


    Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression-Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression-Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

  10. Predicting the decision to pursue mediation in civil disputes: a hierarchical classes analysis.

    Reich, Warren A; Kressel, Kenneth; Scanlon, Kathleen M; Weiner, Gary A


    Clients (N = 185) involved in civil court cases completed the CPR Institute's Mediation Screen, which is designed to assist in making a decision about pursuing mediation. The authors modeled data using hierarchical classes analysis (HICLAS), a clustering algorithm that places clients into 1 set of classes and CPRMS items into another set of classes. HICLAS then links the sets of classes so that any class of clients can be identified in terms of the classes of items they endorsed. HICLAS-derived item classes reflected 2 underlying themes: (a) suitability of the dispute for a problem-solving process and (b) potential benefits of mediation. All clients who perceived that mediation would be beneficial also believed that the context of their conflict was favorable to mediation; however, not all clients who saw a favorable context believed they would benefit from mediation. The majority of clients who agreed to pursue mediation endorsed items reflecting both contextual suitability and perceived benefits of mediation.

  11. Practical Introduction to Clustering Data

    Hartmann, Alexander K


    Data clustering is an approach to seek for structure in sets of complex data, i.e., sets of "objects". The main objective is to identify groups of objects which are similar to each other, e.g., for classification. Here, an introduction to clustering is given and three basic approaches are introduced: the k-means algorithm, neighbour-based clustering, and an agglomerative clustering method. For all cases, C source code examples are given, allowing for an easy implementation.

  12. Textile Industrial Clusters in China

    Nie Ting


    @@ "National Textile Industry Cluster Development Seminar" convened,held by China National Textile and Apparel Council,23 cities and towns were awarded as China's Textile Industry Cluster Pilot District.By far,China's textile industrial clusters have grown to 164,which indicate a quick and gorgeous development.These textile industrial clusters have a great impact on the local economy and even the whole national textile industry's development.

  13. The Assembly of Galaxy Clusters

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


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

  14. Massive star clusters in galaxies

    Harris, William E


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

  15. Hirzebruch classes of complex hypersurfaces

    Cappell, Sylvain E; Schuermann, Joerg; Shaneson, Julius L


    The Milnor-Hirzebruch class of a locally complete intersection X in an algebraic manifold M measures the difference between the (Poincare dual of the) Hirzebruch class of the virtual tangent bundle of X and, respectively, the Brasselet-Schuermann-Yokura (homology) Hirzebruch class of X. In this note, we calculate the Milnor-Hirzebruch class of a globally defined algebraic hypersurface X in terms of the corresponding Hirzebruch invariants of singular strata in a Whitney stratification of X. Our approach is based on Schuermann's specialization property for the motivic Hirzebruch class transformation of Brasselet-Schuermann-Yokura.

  16. On clusters and clustering from atoms to fractals

    Reynolds, PJ


    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

  17. Uncertainties in the cluster-cluster correlation function

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


    The bootstrap resampling technique is applied to estimate sampling errors and significance levels of the two-point correlation functions determined for a subset of the CfA redshift survey of galaxies and a redshift sample of 104 Abell clusters. The angular correlation functions is also calculated for a sample of 1664 Abell clusters. The standard errors for the Abell data are found to be considerably larger than quoted 'Poisson errors'. The enhancement of cluster clustering over galaxy clustering is statistically significant in the presence of resampling errors.

  18. Assessment of Rotationally-Invariant Clustering Using Streamlet Tractography

    Liptrot, Matthew George; Lauze, François


    We present a novel visualisation-based strategy for the assessment of a recently proposed clustering technique for raw DWI volumes which derives rotationally-invariant metrics to classify voxels. The validity of the division of all brain tissue voxels into such classes was assessed using...... the recently developed streamlets visualisation technique, which aims to represent brain fibres by collections of many short streamlines. Under the assumption that streamlines seeded in a cluster should stay within it, we were able to assess how well perceptual tracing could occur across the boundaries...

  19. Cluster dynamics and universality of Ising lattice gases

    Heringa, J. R.; Blöte, H. W. J.

    Lattice gases with nearest-neighbour exclusion are studied by means of Monte Carlo simulations with an efficient cluster algorithm. The critical dynamics is consistent with a dynamical exponent z=0 in the case of Wolff-like cluster updates for square and simple-cubic lattices in the studied range of lattice sizes. We find the critical activity zc=0.72020(4) for the body-centred cubic lattice. The critical exponents yh=2.475(8) and yt=1.61(6) disagree with an earlier study, but they do agree with the known values for the three-dimensional Ising universality class.

  20. Recovery Rate of Clustering Algorithms

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


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

  1. Geographic Projection of Cluster Composites

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


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

  2. Privacy-preserving distributed clustering

    Erkin, Z.; Veugen, T.; Toft, T.; Lagendijk, R.L.


    Clustering is a very important tool in data mining and is widely used in on-line services for medical, financial and social environments. The main goal in clustering is to create sets of similar objects in a data set. The data set to be used for clustering can be owned by a single entity, or in some

  3. Stellar populations in star clusters

    Li, Cheng-Yuan; de Grijs, Richard; Deng, Li-Cai


    Stellar populations contain the most important information about star cluster formation and evolution. Until several decades ago, star clusters were believed to be ideal laboratories for studies of simple stellar populations (SSPs). However, discoveries of multiple stellar populations in Galactic globular clusters have expanded our view on stellar populations in star clusters. They have simultaneously generated a number of controversies, particularly as to whether young star clusters may have the same origin as old globular clusters. In addition, extensive studies have revealed that the SSP scenario does not seem to hold for some intermediate-age and young star clusters either, thus making the origin of multiple stellar populations in star clusters even more complicated. Stellar population anomalies in numerous star clusters are well-documented, implying that the notion of star clusters as true SSPs faces serious challenges. In this review, we focus on stellar populations in massive clusters with different ages. We present the history and progress of research in this active field, as well as some of the most recent improvements, including observational results and scenarios that have been proposed to explain the observations. Although our current ability to determine the origin of multiple stellar populations in star clusters is unsatisfactory, we propose a number of promising projects that may contribute to a significantly improved understanding of this subject.

  4. Clustering Objects from Multiple Collections

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


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

  5. Clustering objects from multiple collections

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


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

  6. Outskirts of Galaxy Clusters

    Reiprich, Thomas H; Ettori, Stefano; Israel, Holger; Lovisari, Lorenzo; Molendi, Silvano; Pointecouteau, Etienne; Roncarelli, Mauro


    Until recently, only about 10% of the total intracluster gas volume had been studied with high accuracy, leaving a vast region essentially unexplored. This is now changing and a wide area of hot gas physics and chemistry awaits discovery in galaxy cluster outskirts. Also, robust large-scale total mass profiles and maps are within reach. First observational and theoretical results in this emerging field have been achieved in recent years with sometimes surprising findings. Here, we summarize and illustrate the relevant underlying physical and chemical processes and review the recent progress in X-ray, Sunyaev--Zel'dovich, and weak gravitational lensing observations of cluster outskirts, including also brief discussions of technical challenges and possible future improvements.

  7. Refractory chronic cluster headache

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


    Chronic cluster headache (CCH) often resists to prophylactic pharmaceutical treatments resulting in patients' life damage. In this rare but pragmatic situation escalation to invasive management is needed but framing criteria are lacking. We aimed to reach a consensus for refractory CCH definition...... for clinical and research use. The preparation of the final consensus followed three stages. Internal between authors, a larger between all European Headache Federation members and finally an international one among all investigators that have published clinical studies on cluster headache the last five years....... Eighty-five investigators reached by email. Proposed criteria were in the format of the International Classification of Headache Disorders III-beta (description, criteria, notes, comments and references). Following this evaluation eight drafts were prepared before the final. Twenty-four (28...

  8. Are megaquakes clustered?

    Daub, Eric G; Guyer, Robert A; Johnson, Paul A


    We study statistical properties of the number of large earthquakes over the past century. We analyze the cumulative distribution of the number of earthquakes with magnitude larger than threshold M in time interval T, and quantify the statistical significance of these results by simulating a large number of synthetic random catalogs. We find that in general, the earthquake record cannot be distinguished from a process that is random in time. This conclusion holds whether aftershocks are removed or not, except at magnitudes below M = 7.3. At long time intervals (T = 2-5 years), we find that statistically significant clustering is present in the catalog for lower magnitude thresholds (M = 7-7.2). However, this clustering is due to a large number of earthquakes on record in the early part of the 20th century, when magnitudes are less certain.

  9. Class Discovery in Galaxy Classification

    Bazell, D; Bazell, David; Miller, David J.


    In recent years, automated, supervised classification techniques have been fruitfully applied to labeling and organizing large astronomical databases. These methods require off-line classifier training, based on labeled examples from each of the (known) object classes. In practice, only a small batch of labeled examples, hand-labeled by a human expert, may be available for training. Moreover, there may be no labeled examples for some classes present in the data, i.e. the database may contain several unknown classes. Unknown classes may be present due to 1) uncertainty in or lack of knowledge of the measurement process, 2) an inability to adequately ``survey'' a massive database to assess its content (classes), and/or 3) an incomplete scientific hypothesis. In recent work, new class discovery in mixed labeled/unlabeled data was formally posed, with a proposed solution based on mixture models. In this work we investigate this approach, propose a competing technique suitable for class discovery in neural network...

  10. Propagating Class and Method Combination

    Ernst, Erik


    This paper presents a mixin based class and method combination mechanism with block structure propagation. Traditionally, mixins can be composed to form new classes, possibly merging the implementations of methods (as in CLOS). In our approach, a class or method combination operation may cause any...... number of implicit combinations. For example, it is possible to specify separate aspects of a family of classes, and then combine several aspects into a full-fledged class family. The combination expressions would explicitly combine whole-family aspects, and by propagation implicitly combine the aspects...... for each member of the class family, and again by propagation implicitly compose each method from its aspects. As opposed to CLOS, this is type-checked statically; and as opposed to other systems for advanced class combination/ merging/weaving, it is integrated directly in the language, ensuring a clear...

  11. Merging Galaxy Cluster A2255 in Mid-infrared

    Shim, Hyunjin; Im, Myungshin; Lee, Hyung Mok; Lee, Myung Gyoon; Kim, Seong Jin; Hwang, Ho Seong; Hwang, Narae; Ko, Jongwan; Lee, Jong Chul; Lim, Sungsoon; Matsuhara, Hideo; Seo, Hyunjong; Wada, Takehiko; Goto, Tomotsugu


    We present the mid-infrared (MIR) observation of a nearby galaxy cluster, A2255, by the AKARI space telescope. Using AKARI's continuous wavelength coverage between 3 and 24 μm and the wide field of view, we investigate the properties of cluster member galaxies to see how the infall of the galaxies, the cluster substructures, and the cluster-cluster merger influence their evolution. We show that the excess of MIR (~11 μm) flux is a good indicator for discriminating galaxies at different evolutionary stages and for dividing galaxies into three classes accordingly: strong MIR-excess (N3 - S11>0.2) galaxies that include both unobscured and obscured star-forming galaxies; weak MIR-excess (-2.0 S11 5 Gyr) galaxies where the MIR emission arises mainly from the circumstellar dust around AGB stars; and intermediate MIR-excess (-1.2 S11 < 0.2) galaxies in between the two classes that are less than a few Gyr old past the prime star formation activity. With the MIR-excess diagnostics, we investigate how local and cluster-scale environments affect the individual galaxies. We derive the total star formation rate (SFR) and the specific SFR of A2255 using the strong MIR-excess galaxies. The dust-free, total SFR of A2255 is ~130 M sun yr-1, which is consistent with the SFRs of other clusters of galaxies at similar redshifts and with similar masses. We find no strong evidence that supports enhanced star formation either inside the cluster or in the substructure region, suggesting that the infall or the cluster merging activities tend to suppress star formation. The intermediate MIR-excess galaxies, representing galaxies in transition from star-forming galaxies to quiescent galaxies, are located preferentially at the medium density region or cluster substructures with higher surface density of galaxies. Our findings suggest that galaxies are being transformed from star-forming galaxies into red, quiescent galaxies from the infall region through near the core which can be explained

  12. Pseudo Class III malocclusion.

    Al-Hummayani, Fadia M


    The treatment of deep anterior crossbite is technically challenging due to the difficulty of placing traditional brackets with fixed appliances. This case report represents a none traditional treatment modality to treat deep anterior crossbite in an adult pseudo class III malocclusion complicated by severely retruded, supraerupted upper and lower incisors. Treatment was carried out in 2 phases. Phase I treatment was performed by removable appliance "modified Hawley appliance with inverted labial bow," some modifications were carried out to it to suit the presented case. Positive overbite and overjet was accomplished in one month, in this phase with minimal forces exerted on the lower incisors. Whereas, phase II treatment was performed with fixed appliances (braces) to align teeth and have proper over bite and overjet and to close posterior open bite, this phase was accomplished within 11 month.

  13. Anticancer properties of distinct antimalarial drug classes.

    Rob Hooft van Huijsduijnen

    Full Text Available We have tested five distinct classes of established and experimental antimalarial drugs for their anticancer potential, using a panel of 91 human cancer lines. Three classes of drugs: artemisinins, synthetic peroxides and DHFR (dihydrofolate reductase inhibitors effected potent inhibition of proliferation with IC50s in the nM- low µM range, whereas a DHODH (dihydroorotate dehydrogenase and a putative kinase inhibitor displayed no activity. Furthermore, significant synergies were identified with erlotinib, imatinib, cisplatin, dasatinib and vincristine. Cluster analysis of the antimalarials based on their differential inhibition of the various cancer lines clearly segregated the synthetic peroxides OZ277 and OZ439 from the artemisinin cluster that included artesunate, dihydroartemisinin and artemisone, and from the DHFR inhibitors pyrimethamine and P218 (a parasite DHFR inhibitor, emphasizing their shared mode of action. In order to further understand the basis of the selectivity of these compounds against different cancers, microarray-based gene expression data for 85 of the used cell lines were generated. For each compound, distinct sets of genes were identified whose expression significantly correlated with compound sensitivity. Several of the antimalarials tested in this study have well-established and excellent safety profiles with a plasma exposure, when conservatively used in malaria, that is well above the IC50s that we identified in this study. Given their unique mode of action and potential for unique synergies with established anticancer drugs, our results provide a strong basis to further explore the potential application of these compounds in cancer in pre-clinical or and clinical settings.

  14. Network class superposition analyses.

    Carl A B Pearson

    Full Text Available Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30 for the yeast cell cycle process, considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.

  15. Astrophysics of galaxy clusters

    Ettori, Stefano


    As the nodes of the cosmic web, clusters of galaxies trace the large-scale distribution of matter in the Universe. They are thus privileged sites in which to investigate the complex physics of structure formation. However, the complete story of how these structures grow, and how they dissipate the gravitational and non-thermal components of their energy budget over cosmic time, is still beyond our grasp. Most of the baryons gravitationally bound to the cluster's halo is in the form of a diffuse, hot, metal-enriched plasma that radiates primarily in the X-ray band. X-ray observations of the evolving cluster population provide a unique opportunity to address such fundamental open questions as: How do hot diffuse baryons accrete and dynamically evolve in dark matter potentials? How and when was the energy that we observe in the ICM generated and distributed? Where and when are heavy elements produced and how are they circulated? We will present the ongoing activities to define the strategy on how an X-ray observatory with large collecting area and an unprecedented combination of high spectral and angular resolution, such as Athena, can address these questions.

  16. Support Policies in Clusters: Prioritization of Support Needs by Cluster Members According to Cluster Life Cycle

    Gulcin Salıngan


    Full Text Available Economic development has always been a moving target. Both the national and local governments have been facing the challenge of implementing the effective and efficient economic policy and program in order to best utilize their limited resources. One of the recent approaches in this area is called cluster-based economic analysis and strategy development. This study reviews key literature and some of the cluster based economic policies adopted by different governments. Based on this review, it proposes “the cluster life cycle” as a determining factor to identify the support requirements of clusters. A survey, designed based on literature review of International Cluster support programs, was conducted with 30 participants from 3 clusters with different maturity stage. This paper discusses the results of this study conducted among the cluster members in Eskişehir- Bilecik-Kütahya Region in Turkey on the requirement of the support to foster the development of related clusters.

  17. Hipax Cluster PACS Server

    Ramin Payrovi


    Full Text Available Best Performace: With our Hipax Cluster PACS Server solution we are introducing the parallel computing concept as an extremely fast software system to the PACS world. In contrast to the common PACS servers, the Hipax Cluster PACS software is not only restricted to one or two computers, but can be used on a couple of servers controlling each other."nThus, the same services can be run simultaneously on different computers. The scalable system can also be expanded subsequently without lost of per-formance by adding further processors or Hipax server units, for example, if new clients or modalities are to be connected."nMaximum Failure Security: The Cluster Server concept offers high failure security. If one of the server PCs breaks down, the services can be assumed by another Hipax server unit, temporarily. If the overload of one of the server PCs is imminent, the services will be carried out by another Hipax unit (load balancing. To increase the security, e.g. against fire, the single Hipax servers can also be located separately. This concept offers maximum security, flexibility, performance, redundancy and scalability."nThe Hipax Cluster PACS Server is easy to be administrated using a web interface. In the case of a system failure (e.g. overloading, breakdown of a server PC the system administrator receives a mes-sage via Email and is so enabled to solve the problem."nFeatures"n• Based on SQL database"n• Different services running on separate PCs"n• The Hipax Server unis are coordinated and able to control each other"n• Exponentiates the power of a cluster server to the whole PACS (more processors"n• Scalable to the demands"n• Maximum performance"n• Load balancing for optimum efficiency"n• Maximum failure security because of expo-nentiated redundancy"n• Warning Email automatically sent to the system administrator in the case of failure"n• Web interface for system configuration"n• Maintenance without shut down the system

  18. Stellar Snowflake Cluster


    [figure removed for brevity, see original site] Figure 1 Stellar Snowflake Cluster Combined Image [figure removed for brevity, see original site] Figure 2 Infrared Array CameraFigure 3 Multiband Imaging Photometer Newborn stars, hidden behind thick dust, are revealed in this image of a section of the Christmas Tree cluster from NASA's Spitzer Space Telescope, created in joint effort between Spitzer's infrared array camera and multiband imaging photometer instruments. The newly revealed infant stars appear as pink and red specks toward the center of the combined image (fig. 1). The stars appear to have formed in regularly spaced intervals along linear structures in a configuration that resembles the spokes of a wheel or the pattern of a snowflake. Hence, astronomers have nicknamed this the 'Snowflake' cluster. Star-forming clouds like this one are dynamic and evolving structures. Since the stars trace the straight line pattern of spokes of a wheel, scientists believe that these are newborn stars, or 'protostars.' At a mere 100,000 years old, these infant structures have yet to 'crawl' away from their location of birth. Over time, the natural drifting motions of each star will break this order, and the snowflake design will be no more. While most of the visible-light stars that give the Christmas Tree cluster its name and triangular shape do not shine brightly in Spitzer's infrared eyes, all of the stars forming from this dusty cloud are considered part of the cluster. Like a dusty cosmic finger pointing up to the newborn clusters, Spitzer also illuminates the optically dark and dense Cone nebula, the tip of which can be seen towards the bottom left corner of each image. This combined image shows the presence of organic molecules mixed with dust as wisps of green, which have been illuminated by nearby star formation. The larger yellowish dots neighboring the baby red stars in the Snowflake Cluster are massive stellar infants forming from the same cloud. The blue dots

  19. Focused Crawling of the Deep Web Using Service Class Descriptions

    Rocco, D; Liu, L; Critchlow, T


    Dynamic Web data sources--sometimes known collectively as the Deep Web--increase the utility of the Web by providing intuitive access to data repositories anywhere that Web access is available. Deep Web services provide access to real-time information, like entertainment event listings, or present a Web interface to large databases or other data repositories. Recent studies suggest that the size and growth rate of the dynamic Web greatly exceed that of the static Web, yet dynamic content is often ignored by existing search engine indexers owing to the technical challenges that arise when attempting to search the Deep Web. To address these challenges, we present DynaBot, a service-centric crawler for discovering and clustering Deep Web sources offering dynamic content. DynaBot has three unique characteristics. First, DynaBot utilizes a service class model of the Web implemented through the construction of service class descriptions (SCDs). Second, DynaBot employs a modular, self-tuning system architecture for focused crawling of the DeepWeb using service class descriptions. Third, DynaBot incorporates methods and algorithms for efficient probing of the Deep Web and for discovering and clustering Deep Web sources and services through SCD-based service matching analysis. Our experimental results demonstrate the effectiveness of the service class discovery, probing, and matching algorithms and suggest techniques for efficiently managing service discovery in the face of the immense scale of the Deep Web.

  20. Detection and Analysis of Clones in UML Class Models

    Dhavleesh Rattan


    Full Text Available It is quite frequent to copy and paste code fragments in software development. The copied source code is called a software clone and the activity is referred to as code cloning. The presence of code clones hamper maintenance and may lead to bug propagation. Now-a-days, model driven development has become a standard industry practice. Duplicate parts in models i.e. model clones pose similar challenges as in source code. This paper presents an approach to detect clones in Unified Modeling Language class models. The core of our technique is the construction of a labeled, ranked tree corresponding to the UML class model where attributes with their data types and methods with their signatures are represented as subtrees. By grouping and clustering of repeating subtrees, the tool is able to detect duplications in a UML class model at different levels of granularity i.e. complete class diagram, attributes with their data types and methods with their signatures across the model and cluster of such attributes/methods. We propose a new classification of model clones with the objective of detecting exact and meaningful clones. Empirical evaluation of the tool using open source reverse engineered and forward designed models show some interesting and relevant clones which provide useful insights into software modeling practice.

  1. Detection and Analysis of Clones in UML Class Models

    Dhavleesh Rattan


    Full Text Available It is quite frequent to copy and paste code fragments in software development. The copied source code is called a software clone and the activity is referred to as code cloning. The presence of code clones hamper maintenance and may lead to bug propagation. Now-a-days, model driven development has become a standard industry practice. Duplicate parts in models i.e. model clones pose similar challenges as in source code. This paper presents an approach to detect clones in Unified Modeling Language class models. The core of our technique is the construction of a labeled, ranked tree corresponding to the UML class model where attributes with their data types and methods with their signatures are represented as subtrees. By grouping and clustering of repeating subtrees, the tool is able to detect duplications in a UML class model at different levels of granularity i.e. complete class diagram, attributes with their data types and methods with their signatures across the model and cluster of such attributes/methods. We propose a new classification of model clones with the objective of detecting exact and meaningful clones. Empirical evaluation of the tool using open source reverse engineered and forward designed models show some interesting and relevant clones which provide useful insights into software modeling practice.

  2. Clustering Methodologies for Software Engineering

    Mark Shtern


    Full Text Available The size and complexity of industrial strength software systems are constantly increasing. This means that the task of managing a large software project is becoming even more challenging, especially in light of high turnover of experienced personnel. Software clustering approaches can help with the task of understanding large, complex software systems by automatically decomposing them into smaller, easier-to-manage subsystems. The main objective of this paper is to identify important research directions in the area of software clustering that require further attention in order to develop more effective and efficient clustering methodologies for software engineering. To that end, we first present the state of the art in software clustering research. We discuss the clustering methods that have received the most attention from the research community and outline their strengths and weaknesses. Our paper describes each phase of a clustering algorithm separately. We also present the most important approaches for evaluating the effectiveness of software clustering.

  3. Optical radii of galaxy clusters

    Girardi, M; Giuricin, G; Mardirossian, F; Mezzetti, M; Girardi, M; Biviano, A; Giuricin, G; Mardirossian, F; Mezzetti, M


    We analyze the density profiles and virial radii for a sample of 90 nearby clusters, using galaxies with available redshifts and positions. Each cluster has at least 20 redshifts measured within an Abell radius, and all the results come from galaxy sets of at least 20 members. Most of the density profiles of our clusters are well fitted by hydrostatic-isothermal-like profiles. The slopes we find for many cluster density profiles are consistent with the hypothesis that the galaxies are in equilibrium with the binding cluster potential. The virial radii correlate with the core radii at a very high significance level. The observed relationship between the two size estimates is in agreement with the theoretical one computed by using the median values of the density profile parameters fitted on our clusters. After correcting for incompleteness in our cluster sample, we provide the universal distributions functions of core and virial radii (obtained within half an Abell radius).

  4. The Development of Nanotechnological Clusters as the Elements of Nanoindustrial Infrastructure: European Experience

    Beloglazova Svetlana Anatolyevna


    Full Text Available The international experience in managing innovative development of regions shows that at this level of global economic system there is an objective process of synthesis of scientific, industrial, economic and social policies in the form of peculiar entities, named clusters, which helps to create favorable environment for appearance and expansion of innovations. Development strategies of advanced countries embody the identification of key competencies of regions and creation of nanotechnological clusters in order to stimulate innovation. Such clusters are intended to develop the methods for nanotechnology application, create new types of business activities, and provide world-class quality. The importance of implementation of nanotechnological cluster policy being a factor of sustainable development of economic systems at micro-, meso- and macro- levels determines the necessity to consider the experience of successful nanotechnological clusters in Italy and France: the cluster of nanotechnologies in the Veneto region, which is the largest and most competitive cluster in Italy, generating up to 9.3 % of the Italy’s GDP, and the Minalogic cluster in the French region Grenoble, being included in the top 5 largest micro and nanotechnological clusters of the world while Grenoble is in the top 15 most innovative regions in the world. The author defines the largest cluster members, describes key areas and key measures of government and non-government support, analyzes economic performance of clusters and describes their impact on the economy of a region and a country as a whole.

  5. Web Fuzzy Clustering and a Case Study

    LIU Mao-fu; HE Jing; HE Yan-xiang; HU Hui-jun


    We combine the web usage mining and fuzzy clustering and give the concept of web fuzzy clustering, and then put forward the web fuzzy clustering processing model which is discussed in detail. Web fuzzy clustering can be used in the web users clustering and web pages clustering. In the end, a case study is given and the result has proved the feasibility of using web fuzzy clustering in web pages clustering.

  6. Digital Doping in Magic-Sized CdSe Clusters.

    Muckel, Franziska; Yang, Jiwoong; Lorenz, Severin; Baek, Woonhyuk; Chang, Hogeun; Hyeon, Taeghwan; Bacher, Gerd; Fainblat, Rachel


    Magic-sized semiconductor clusters represent an exciting class of materials located at the boundary between quantum dots and molecules. It is expected that replacing single atoms of the host crystal with individual dopants in a one-by-one fashion can lead to unique modifications of the material properties. Here, we demonstrate the dependence of the magneto-optical response of (CdSe)13 clusters on the discrete number of Mn(2+) ion dopants. Using time-of-flight mass spectrometry, we are able to distinguish undoped, monodoped, and bidoped cluster species, allowing for an extraction of the relative amount of each species for a specific average doping concentration. A giant magneto-optical response is observed up to room temperature with clear evidence that exclusively monodoped clusters are magneto-optically active, whereas the Mn(2+) ions in bidoped clusters couple antiferromagnetically and are magneto-optically passive. Mn(2+)-doped clusters therefore represent a system where magneto-optical functionality is caused by solitary dopants, which might be beneficial for future solotronic applications.

  7. Customized recommendations for production management clusters of North American automatic milking systems.

    Tremblay, Marlène; Hess, Justin P; Christenson, Brock M; McIntyre, Kolby K; Smink, Ben; van der Kamp, Arjen J; de Jong, Lisanne G; Döpfer, Dörte


    Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is

  8. CCABC: Cyclic Cellular Automata Based Clustering For Energy Conservation in Sensor Networks

    Banerjee, Indrajit; Rahaman, Hafizur


    Sensor network has been recognized as the most significant technology for next century. Despites of its potential application, wireless sensor network encounters resource restriction such as low power, reduced bandwidth and specially limited power sources. This work proposes an efficient technique for the conservation of energy in a wireless sensor network (WSN) by forming an effective cluster of the network nodes distributed over a wide range of geographical area. The clustering scheme is developed around a specified class of cellular automata (CA) referred to as the modified cyclic cellular automata (mCCA). It sets a number of nodes in stand-by mode at an instance of time without compromising the area of network coverage and thereby conserves the battery power. The proposed scheme also determines an effective cluster size where the inter-cluster and intra-cluster communication cost is minimum. The simulation results establish that the cyclic cellular automata based clustering for energy conservation in sens...

  9. Hadoop cluster deployment

    Zburivsky, Danil


    This book is a step-by-step tutorial filled with practical examples which will show you how to build and manage a Hadoop cluster along with its intricacies.This book is ideal for database administrators, data engineers, and system administrators, and it will act as an invaluable reference if you are planning to use the Hadoop platform in your organization. It is expected that you have basic Linux skills since all the examples in this book use this operating system. It is also useful if you have access to test hardware or virtual machines to be able to follow the examples in the book.

  10. Weil classes on abelian varieties

    Moonen, B J J; Zarhin, Yu. G.


    Consider a complex abelian variety X on which a field F acts. Generalizing a construction of A. Weil, one associates to this a subspace W_F of the cohomology of X, which we call the space of Weil classes w.r.t. F. The purpose of this paper is to answer the following two questions: Q1: under what conditions on F does the space W_F contain, or even consist of, Hodge classes?, Q2: if W_F contains Hodge classes, under what conditions on F are these exceptional? In case X is defined over a number field, we also answer the analogous questions for Tate classes.

  11. On uniqueness of characteristic classes

    Feliu, Elisenda


    We give an axiomatic characterization of maps from algebraic K-theory. The results apply to a large class of maps from algebraic K-theory to any suitable cohomology theory or to algebraic K-theory. In particular, we obtain comparison theorems for the Chern character and Chern classes and for the ......We give an axiomatic characterization of maps from algebraic K-theory. The results apply to a large class of maps from algebraic K-theory to any suitable cohomology theory or to algebraic K-theory. In particular, we obtain comparison theorems for the Chern character and Chern classes...

  12. Convex Decomposition Based Cluster Labeling Method for Support Vector Clustering

    Yuan Ping; Ying-Jie Tian; Ya-Jian Zhou; Yi-Xian Yang


    Support vector clustering (SVC) is an important boundary-based clustering algorithm in multiple applications for its capability of handling arbitrary cluster shapes. However,SVC's popularity is degraded by its highly intensive time complexity and poor label performance.To overcome such problems,we present a novel efficient and robust convex decomposition based cluster labeling (CDCL) method based on the topological property of dataset.The CDCL decomposes the implicit cluster into convex hulls and each one is comprised by a subset of support vectors (SVs).According to a robust algorithm applied in the nearest neighboring convex hulls,the adjacency matrix of convex hulls is built up for finding the connected components; and the remaining data points would be assigned the label of the nearest convex hull appropriately.The approach's validation is guaranteed by geometric proofs.Time complexity analysis and comparative experiments suggest that CDCL improves both the efficiency and clustering quality significantly.

  13. Type Families with Class, Type Classes with Family

    Serrano, Alejandro; Hage, Jurriaan; Bahr, Patrick


    Type classes and type families are key ingredients in Haskell programming. Type classes were introduced to deal with ad-hoc polymorphism, although with the introduction of functional dependencies, their use expanded to type-level programming. Type families also allow encoding type-level functions...

  14. The Latent Class Model as a Measurement Model for Situational Judgment Tests

    Frank Rijmen


    Full Text Available In a situational judgment test, it is often debatable what constitutes a correct answer to a situation. There is currently a multitude of scoring procedures. Establishing a measurement model can guide the selection of a scoring rule. It is argued that the latent class model is a good candidate for a measurement model. Two latent class models are applied to the Managing Emotions subtest of the Mayer, Salovey, Caruso Emotional Intelligence Test: a plain-vanilla latent class model, and a second-order latent class model that takes into account the clustering of several possible reactions within each hypothetical scenario of the situational judgment test. The results for both models indicated that there were three subgroups characterised by the degree to which differentiation occurred between possible reactions in terms of perceived effectiveness. Furthermore, the results for the second-order model indicated a moderate cluster effect.

  15. Ultracompact Generation of Continuous-Variable Cluster States

    Menicucci, N C; Pfister, O; Zaidi, H; Flammia, Steven T.; Menicucci, Nicolas C.; Pfister, Olivier; Zaidi, Hussain


    We show that any continuous-variable (CV) cluster state with a bipartite graph -- a class that includes computationally universal graphs -- can be generated with a single multimode squeezing Hamiltonian acting on the vacuum. Any such Hamiltonian can, in principle, be implemented optically using a single optical parametric oscillator (OPO) based on a multiply phasematched nonlinear crystal pumped by an O(N^2)-mode field. This is in contrast to the equally resource-efficient scheme proposed in quant-ph/0610119, which requires N single-mode OPOs plus a network of O(N^2) beam splitters. The method proposed here is an essential step toward the efficient experimental creation of large-scale CV cluster states. As an illustration, we detail the experimental creation of a four-mode square CV cluster state from a single OPO.


    Mário Mestria


    Full Text Available ABSTRACT This paper proposes a hybrid heuristic algorithm, based on the metaheuristics Greedy Randomized Adaptive Search Procedure, Iterated Local Search and Variable Neighborhood Descent, to solve the Clustered Traveling Salesman Problem (CTSP. Hybrid Heuristic algorithm uses several variable neighborhood structures combining the intensification (using local search operators and diversification (constructive heuristic and perturbation routine. In the CTSP, the vertices are partitioned into clusters and all vertices of each cluster have to be visited contiguously. The CTSP is -hard since it includes the well-known Traveling Salesman Problem (TSP as a special case. Our hybrid heuristic is compared with three heuristics from the literature and an exact method. Computational experiments are reported for different classes of instances. Experimental results show that the proposed hybrid heuristic obtains competitive results within reasonable computational time.

  17. Acupuncture for episodic cluster headache: a trigeminal approach.

    Hayhoe, Simon


    Following evidence that acupuncture is clinically feasible and cost-effective in the treatment of headache, the UK National Institute for Health and Care Excellence recommends acupuncture as prophylactic treatment for migraine and tension headache. There has thus been expectation that other forms of headache should benefit also. Unfortunately, acupuncture has not generally been successful for cluster headache. This may be due to acupuncturists approaching the problem as one of severe migraine. In fact, cluster headache is classed as a trigeminal autonomic cephalgia. In this case report, episodic cluster headache is treated in the same way as has been shown effective for trigeminal neuralgia. Acupuncture is applied to the contralateral side at points appropriate for stimulating branches of the trigeminal nerve. Thus, ST2 is used for the infraorbital nerve, BL2 and Yuyao for the supratrochlear and supraorbital nerves, and Taiyang for the temporal branch of the zygomatic nerve.

  18. Polymorphism in magic-sized Au144(SR)60 clusters

    Jensen, Kirsten M. Ø.; Juhas, Pavol; Tofanelli, Marcus A.; Heinecke, Christine L.; Vaughan, Gavin; Ackerson, Christopher J.; Billinge, Simon J. L.


    Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. Here we present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. The study reveals structural polymorphism in these archetypal nanoclusters. In addition to confirming the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. The discovery of polymorphism may open up a new dimension in nanoscale engineering.

  19. Brightest Cluster Galaxies and Core Gas Density in REXCESS Clusters

    Haarsma, D B; Donahue, M; Bruch, S; Boehringer, H; Croston, J H; Pratt, G W; Voit, G M; Arnaud, M; Pierini, D


    We investigate the relationship between brightest cluster galaxies (BCGs) and their host clusters using a sample of nearby galaxy clusters from the Representative XMM-Newton Cluster Structure Survey (REXCESS). The sample was imaged with the Southern Observatory for Astrophysical Research (SOAR) in R band to investigate the mass of the old stellar population. Using a metric radius of 12h^-1 kpc, we find that the BCG luminosity depends weakly on overall cluster mass as L_BCG \\propto M_cl^0.18+-0.07, consistent with previous work. We found that 90% of the BCGs are located within 0.035 R_500 of the peak of the X-ray emission, including all of the cool core (CC) clusters. We also found an unexpected correlation between the BCG metric luminosity and the core gas density for non-cool core (non-CC) clusters, following a power law of n_e \\propto L_BCG^2.7+-0.4 (where n_e is measured at 0.008 R_500). The correlation is not easily explained by star formation (which is weak in non-CC clusters) or overall cluster mass (wh...

  20. Query Results Clustering by Extending SPARQL with CLUSTER BY

    Ławrynowicz, Agnieszka

    The task of dynamic clustering of the search results proved to be useful in the Web context, where the user often does not know the granularity of the search results in advance. The goal of this paper is to provide a declarative way for invoking dynamic clustering of the results of queries submitted over Semantic Web data. To achieve this goal the paper proposes an approach that extends SPARQL by clustering abilities. The approach introduces a new statement, CLUSTER BY, into the SPARQL grammar and proposes semantics for such extension.

  1. A Gamblers Clustering Based on Their Favorite Gambling Activity.

    Challet-Bouju, Gaëlle; Hardouin, Jean-Benoit; Renard, Noëlle; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Gorsane, Mohamed-Ali; Vénisse, Jean-Luc; Grall-Bronnec, Marie


    The objective of this study was to identify profiles of gamblers to explain the choice of preferred gambling activity among both problem and non-problem gamblers. 628 non-problem and problem gamblers were assessed with a structured interview including "healthy" (sociodemographic characteristics, gambling habits and personality profile assessed with the Temperament and Character Inventory-125) and "pathological" [diagnosis of pathological gambling, gambling-related cognitions (GRCs) and psychiatric comorbidity] variables. We performed a two-step cluster analysis based solely on "healthy" variables to identify gamblers' profiles which typically reflect the choice of preferred gambling activity. The obtained classes were then described using both "healthy" and "pathological" variables, by comparing each class to the rest of the sample. Clusters were generated. Class 1 (Electronic Gaming Machines gamblers) showed high cooperativeness, a lower level of GRC about strategy and more depressive disorders. Class 2 (games with deferred results gamblers) were high novelty seekers and showed a higher level of GRC about strategy and more addictive disorders. Class 3 (roulette gamblers) were more often high rollers and showed a higher level of GRC about strategy and more manic or hypomanic episodes and more obsessive-compulsive disorders. Class 4 (instant lottery gamblers) showed a lower tendency to suicide attempts. Class 5 (scratch cards gamblers) were high harm avoiders and showed a lower overall level of GRC and more panic attacks and eating disorders. The preference for one particular gambling activity may concern different profiles of gamblers. This study highlights the importance of considering the pair gambler-game rather than one or the other separately, and may provide support for future research on gambling and preventive actions directed toward a particular game.

  2. A Clustering Method Based on the Maximum Entropy Principle

    Edwin Aldana-Bobadilla


    Full Text Available Clustering is an unsupervised process to determine which unlabeled objects in a set share interesting properties. The objects are grouped into k subsets (clusters whose elements optimize a proximity measure. Methods based on information theory have proven to be feasible alternatives. They are based on the assumption that a cluster is one subset with the minimal possible degree of “disorder”. They attempt to minimize the entropy of each cluster. We propose a clustering method based on the maximum entropy principle. Such a method explores the space of all possible probability distributions of the data to find one that maximizes the entropy subject to extra conditions based on prior information about the clusters. The prior information is based on the assumption that the elements of a cluster are “similar” to each other in accordance with some statistical measure. As a consequence of such a principle, those distributions of high entropy that satisfy the conditions are favored over others. Searching the space to find the optimal distribution of object in the clusters represents a hard combinatorial problem, which disallows the use of traditional optimization techniques. Genetic algorithms are a good alternative to solve this problem. We benchmark our method relative to the best theoretical performance, which is given by the Bayes classifier when data are normally distributed, and a multilayer perceptron network, which offers the best practical performance when data are not normal. In general, a supervised classification method will outperform a non-supervised one, since, in the first case, the elements of the classes are known a priori. In what follows, we show that our method’s effectiveness is comparable to a supervised one. This clearly exhibits the superiority of our method.

  3. Local clustering in scale-free networks with hidden variables

    van der Hofstad, Remco; Janssen, A. J. E. M.; van Leeuwaarden, Johan S. H.; Stegehuis, Clara


    We investigate the presence of triangles in a class of correlated random graphs in which hidden variables determine the pairwise connections between vertices. The class rules out self-loops and multiple edges. We focus on the regime where the hidden variables follow a power law with exponent τ ∈(2 ,3 ) , so that the degrees have infinite variance. The natural cutoff hc characterizes the largest degrees in the hidden variable models, and a structural cutoff hs introduces negative degree correlations (disassortative mixing) due to the infinite-variance degrees. We show that local clustering decreases with the hidden variable (or degree). We also determine how the average clustering coefficient C scales with the network size N , as a function of hs and hc. For scale-free networks with exponent 2 universality class at hand. We characterize the extremely slow decay of C when τ ≈2 and show that for τ =2.1 , say, clustering starts to vanish only for networks as large as N =109 .

  4. Condylar volume and condylar area in class I, class II and class III young adult subjects

    Saccucci Matteo; D’Attilio Michele; Rodolfino Daria; Festa Felice; Polimeni Antonella; Tecco Simona


    Abstract Aim Aim of this study was to compare the volume and the shape of mandibular condyles in a Caucasian young adult population, with different skeletal pattern. Material and methods 200 Caucasian patients (15–30 years old, 95 male and 105 females) were classified in three groups on the base of ANB angle: skeletal class I (65 patients), skeletal class II (70 patients) and skeletal class III (65 patients). Left and right TMJs of each subject were evaluated independently with CBCT (Iluma). ...

  5. Fuzzy support vector machines based on linear clustering

    Xiong, Shengwu; Liu, Hongbing; Niu, Xiaoxiao


    A new Fuzzy Support Vector Machines (FSVMs) based on linear clustering is proposed in this paper. Its concept comes from the idea of linear clustering, selecting the data points near to the preformed hyperplane, which is formed on the training set including one positive and one negative training samples respectively. The more important samples near to the preformed hyperplane are selected by linear clustering technique, and the new FSVMs are formed on the more important data set. It integrates the merit of two kinds of FSVMs. The membership functions are defined using the relative distance between the data points and the preformed hyperplane during the training process. The fuzzy membership decision functions of multi-class FSVMs adopt the minimal value of all the decision functions of two-class FSVMs. To demonstrate the superiority of our methods, the benchmark data sets of machines learning databases are selected to verify the proposed FSVMs. The experimental results indicate that the proposed FSVMs can reduce the training data and running time, and its recognition rate is greater than or equal to that of FSVMs through selecting a suitable linear clustering parameter.

  6. Applying Data Clustering Feature to Speed Up Ant Colony Optimization

    Chao-Yang Pang


    Full Text Available Ant colony optimization (ACO is often used to solve optimization problems, such as traveling salesman problem (TSP. When it is applied to TSP, its runtime is proportional to the squared size of problem N so as to look less efficient. The following statistical feature is observed during the authors’ long-term gene data analysis using ACO: when the data size N becomes big, local clustering appears frequently. That is, some data cluster tightly in a small area and form a class, and the correlation between different classes is weak. And this feature makes the idea of divide and rule feasible for the estimate of solution of TSP. In this paper an improved ACO algorithm is presented, which firstly divided all data into local clusters and calculated small TSP routes and then assembled a big TSP route with them. Simulation shows that the presented method improves the running speed of ACO by 200 factors under the condition that data set holds feature of local clustering.

  7. Active matter clusters at interfaces

    Copenhagen, Katherine


    Collective and directed motility or swarming is an emergent phenomenon displayed by many self-organized assemblies of active biological matter such as clusters of embryonic cells during tissue development, cancerous cells during tumor formation and metastasis, colonies of bacteria in a biofilm, or even flocks of birds and schools of fish at the macro-scale. Such clusters typically encounter very heterogeneous environments. What happens when a cluster encounters an interface between two different environments has implications for its function and fate. Here we study this problem by using a mathematical model of a cluster that treats it as a single cohesive unit that moves in two dimensions by exerting a force/torque per unit area whose magnitude depends on the nature of the local environment. We find that low speed (overdamped) clusters encountering an interface with a moderate difference in properties can lead to refraction or even total internal reflection of the cluster. For large speeds (underdamped), wher...

  8. Cluster synchronization in oscillatory networks

    Belykh, Vladimir N.; Osipov, Grigory V.; Petrov, Valentin S.; Suykens, Johan A. K.; Vandewalle, Joos


    Synchronous behavior in networks of coupled oscillators is a commonly observed phenomenon attracting a growing interest in physics, biology, communication, and other fields of science and technology. Besides global synchronization, one can also observe splitting of the full network into several clusters of mutually synchronized oscillators. In this paper, we study the conditions for such cluster partitioning into ensembles for the case of identical chaotic systems. We focus mainly on the existence and the stability of unique unconditional clusters whose rise does not depend on the origin of the other clusters. Also, conditional clusters in arrays of globally nonsymmetrically coupled identical chaotic oscillators are investigated. The design problem of organizing clusters into a given configuration is discussed.

  9. Making Large Classes More Interactive.

    Brenner, John


    Describes the method of using prompts to allow students to have more "voice" in a large class. The prompt assignment requires students to respond anonymously to a statement that concerns the chapter being discussed in the class. Discusses how the Internet has allowed more freedom with the prompts. Puts forth some student responses to the…

  10. Student Engagement and Marketing Classes

    Taylor, Steven A.; Hunter, Gary L.; Melton, Horace; Goodwin, Stephen A.


    A study is reported that investigates the goals underlying undergraduate students' engagement in their major classes, nonmajor classes, and in extracurricular activities. The qualitative study employs both focus groups and goal-mapping exercises. The results suggest that students tend to focus on utilitarian, attribute-level considerations mainly…

  11. Notes on absolute Hodge classes

    Charles, François


    We survey the theory of absolute Hodge classes. The notes include a full proof of Deligne's theorem on absolute Hodge classes on abelian varieties as well as a discussion of other topics, such as the field of definition of Hodge loci and the Kuga-Satake construction.

  12. Predicting Acoustics in Class Rooms

    Christensen, Claus Lynge; Rindel, Jens Holger


    Typical class rooms have fairly simple geometries, even so room acoustics in this type of room is difficult to predict using today's room acoustic computer modeling software. The reasons why acoustics of class rooms are harder to predict than acoustics of complicated concert halls might...

  13. The Paradox of Paperless Classes.

    Lackie, Paula


    Describes paperless classes developed at Carleton College that augment traditional classes by giving students and faculty the ability to share digital course-related materials via the campus computer network. Presents a case study of a managerial economics course, and includes problems with various aspects of the course and solutions. (LRW)

  14. Translanguaging in a Reading Class

    Vaish, Viniti; Subhan, Aidil


    Using translanguaging as a theoretical foundation, this paper analyses findings from a Grade 2 reading class for low achieving students, where Malay was used as a scaffold to teach English. Data come from one class in one school in Singapore and its Learning Support Programme (LSP), which is part of a larger research project on biliteracy. The LSP…

  15. Class, Identity, and Teacher Education

    Van Galen, Jane A.


    This paper explores the possibilities of working with White, working-class teacher education students to explore the "complex social trajectory" (Reay in Women's Stud Int Forum 20(2):225-233, 1997a, p. 19) of class border crossing as they progress through college. Through analysis of a course that I have developed, "Education and the American…

  16. Class Differences in Cohabitation Processes

    Sassler, Sharon; Miller, Amanda J.


    Despite the burgeoning cohabitation literature, research has failed to examine social class variation in processes of forming and advancing such unions. Drawing upon in-depth interviews with 122 working- and middle-class cohabitors, we examine the duration between dating and moving in together, reasons for cohabiting, and subsequent plans.…

  17. Ideas for Managing Large Classes.

    Kabel, Robert L.


    Describes management strategies used in a large kinetics/industrial chemistry course. Strategies are designed to make instruction in such classes more efficient and effective. Areas addressed include homework assignment, quizzes, final examination, grading and feedback, and rewards for conducting the class in the manner described. (JN)

  18. Relations among tautological classes revisited

    Randal-Williams, Oscar


    We give a simple generalisation of a theorem of Morita (1989) [10] and [11], which leads to a great number of relations among tautological classes on moduli spaces of Riemann surfaces......We give a simple generalisation of a theorem of Morita (1989) [10] and [11], which leads to a great number of relations among tautological classes on moduli spaces of Riemann surfaces...

  19. Tautological Classes on Projective Towers

    Negut, Andrei


    When one has a tower of projective bundles over an algebraic variety and wishes to compute the push-forward of any cohomology class down this tower, one needs to recursively compute the Segre classes corresponding to each level. In this paper, we give a closed combinatorial formula that encodes this recursive procedure.

  20. Connecting Remote Clusters with ATM

    Hu, T.C.; Wyckoff, P.S.


    Sandia's entry into utilizing clusters of networked workstations is called Computational Plant or CPlant for short. The design of CPlant uses Ethernet to boot the individual nodes, Myrinet to communicate within a node cluster, and ATM to connect between remote clusters. This SAND document covers the work done to enable the use of ATM on the CPlant nodes in the Fall of 1997.

  1. Searches for High Redshift Clusters

    Dickinson, M


    High redshift galaxy clusters have traditionally been a fruitful place to study galaxy evolution. I review various search strategies for finding clusters at z > 1. Most efforts to date have concentrated on the environments of distant AGN. I illustrate these with data on the cluster around 3C 324 (z=1.2) and other, more distant systems, and discuss possibilities for future surveys with large telescopes.

  2. Synchronization in complex clustered networks

    HUANG Liang; LAI Ying-Cheng; Kwangho PARK; WANG Xingang; LAI Choy Heng; Robert A. GATENBY


    Synchronization in complex networks has been an active area of research in recent years. While much effort has been devoted to networks with the small-world and scale-free topology, structurally they are often assumed to have a single, densely connected component. Recently it has also become apparent that many networks in social, biological, and tech-nological systems are clustered, as characterized by a number (or a hierarchy) of sparsely linked clusters, each with dense and complex internal connections. Synchronization is funda-mental to the dynamics and functions of complex clustered networks, but this problem has just begun to be addressed. This paper reviews some progress in this direction by focus-ing on the interplay between the clustered topology and net-work synchronizability. In particular, there are two parame-ters characterizing a clustered network: the intra-cluster and the inter-cluster link density. Our goal is to clarify the roles of these parameters in shaping network synchronizability. By using theoretical analysis and direct numerical simulations of oscillator networks, it is demonstrated that clustered net-works with random inter-cluster links are more synchroniz-able, and synchronization can be optimized when inter-cluster and intra-cluster links match. The latter result has one coun-terintuitive implication: more links, if placed improperly, can actually lead to destruction of synchronization, even though such links tend to decrease the average network distance. It is hoped that this review will help attract attention to the fun-damental problem of clustered structures/synchronization in network science.

  3. Chemical Reactions of Silicon Clusters

    Ramakrishna, Mushti V.; Pan, Jun


    Smalley and co-workers discovered that chemisorption reactivities of silicon clusters vary over three orders of magnitude as a function of cluster size. In particular, they found that \\Si{33}, \\Si{39}, and \\Si{45} clusters are least reactive towards various reagents compared to their immediate neighbors in size. We explain these observations based on our stuffed fullerene model. This structural model consists of bulk-like core of five atoms surrounded by fullerene-like surface. Reconstruction...

  4. Light cluster production at NICA

    Bastian, N -U; Blaschke, D; Danielewicz, P; Ivanov, Yu B; Karpenko, Iu; Röpke, G; Rogachevsky, O; Wolter, H H


    Light cluster production at the NICA accelerator complex offers unique possibilities to use these states as "rare probes" of in-medium characteristics such as phase space occupation and early flow. In order to explain this statement, in this contribution theoretical considerations from the nuclear statistical equilibrium model and from a quantum statistical model of cluster production are supplemented with a discussion of a transport model for light cluster formation and with results from hydrodynamic simulations combined with the coalescence model.

  5. Cluster banding heat source model

    Zhang Liguo; Ji Shude; Yang Jianguo; Fang Hongyuan; Li Yafan


    Concept of cluster banding heat source model is put forward for the problem of overmany increment steps in the process of numerical simulation of large welding structures, and expression of cluster banding heat source model is deduced based on energy conservation law.Because the expression of cluster banding heat source model deduced is suitable for random weld width, quantitative analysis of welding stress field for large welding structures which have regular welds can be made quickly.

  6. The SMART CLUSTER METHOD - adaptive earthquake cluster analysis and declustering

    Schaefer, Andreas; Daniell, James; Wenzel, Friedemann


    Earthquake declustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity with usual applications comprising of probabilistic seismic hazard assessments (PSHAs) and earthquake prediction methods. 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. Various methods have been developed to address this issue from other researchers. These have differing ranges of complexity ranging from rather simple statistical window methods to complex epidemic models. This study introduces the smart cluster method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal identification. Hereby, an adaptive search algorithm for data point clusters is adopted. It uses the earthquake density in the spatio-temporal neighbourhood of each event to adjust the search properties. The identified clusters are subsequently analysed to determine directional anisotropy, focussing on a strong correlation along the rupture plane 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 events, an adaptive classification procedure is applied to disassemble subsequent ruptures which may have been grouped into an individual cluster using near-field searches, support vector machines and temporal splitting. The steering parameters of the search behaviour are linked to local earthquake properties like magnitude of completeness, earthquake density and Gutenberg-Richter parameters. The method is capable of identifying and classifying earthquake clusters in space and time. It is tested and validated using earthquake data from California and New Zealand. As a result of the cluster identification process, each event in

  7. Brightest Cluster Galaxies and Core Gas Density in REXCESS Clusters

    Haarsma, Deborah B.; Leisman, Luke; Donahue, Megan; Bruch, Seth; Böhringer, Hans; Croston, Judith H.; Pratt, Gabriel W.; Voit, G. Mark; Arnaud, Monique; Pierini, Daniele


    We investigate the relationship between brightest cluster galaxies (BCGs) and their host clusters using a sample of nearby galaxy clusters from the Representative XMM-Newton Cluster Structure Survey. The sample was imaged with the Southern Observatory for Astrophysical Research in R band to investigate the mass of the old stellar population. Using a metric radius of 12 h -1 kpc, we found that the BCG luminosity depends weakly on overall cluster mass as L BCG vprop M 0.18±0.07 cl, consistent with previous work. We found that 90% of the BCGs are located within 0.035 r 500 of the peak of the X-ray emission, including all of the cool core (CC) clusters. We also found an unexpected correlation between the BCG metric luminosity and the core gas density for non-cool-core (non-CC) clusters, following a power law of ne vprop L 2.7±0.4 BCG (where ne is measured at 0.008 r 500). The correlation is not easily explained by star formation (which is weak in non-CC clusters) or overall cluster mass (which is not correlated with core gas density). The trend persists even when the BCG is not located near the peak of the X-ray emission, so proximity is not necessary. We suggest that, for non-CC clusters, this correlation implies that the same process that sets the central entropy of the cluster gas also determines the central stellar density of the BCG, and that this underlying physical process is likely to be mergers.

  8. Clustering and rule-based classifications of chemical structures evaluated in the biological activity space.

    Schuffenhauer, Ansgar; Brown, Nathan; Ertl, Peter; Jenkins, Jeremy L; Selzer, Paul; Hamon, Jacques


    Classification methods for data sets of molecules according to their chemical structure were evaluated for their biological relevance, including rule-based, scaffold-oriented classification methods and clustering based on molecular descriptors. Three data sets resulting from uniformly determined in vitro biological profiling experiments were classified according to their chemical structures, and the results were compared in a Pareto analysis with the number of classes and their average spread in the profile space as two concurrent objectives which were to be minimized. It has been found that no classification method is overall superior to all other studied methods, but there is a general trend that rule-based, scaffold-oriented methods are the better choice if classes with homogeneous biological activity are required, but a large number of clusters can be tolerated. On the other hand, clustering based on chemical fingerprints is superior if fewer and larger classes are required, and some loss of homogeneity in biological activity can be accepted.

  9. External Defect classification of Citrus Fruit Images using Linear Discriminant Analysis Clustering and ANN classifiers



    Full Text Available Linear Discriminant Analysis (LDA is one technique for transforming raw data into a new feature space in which classification can be carried out more robustly. It is useful where the within-class frequencies are unequal. This method maximizes the ratio of between-class variance to the within-class variance in any particular data set and the maximal separability is guaranteed. LDA clustering models are used to classify object into different category. This study makes use of LDA for clustering the features obtained for the citrus fruit images taken in five different domains. Sub-windows of size 40x40 are cropped from the citrus fruit images having defects such as pitting, splitting and stem end rot. Features are extracted in four domains such as statistical features, fourier transform based features, discrete wavelet transform based features and stationary wavelet transform based features. The results of clustering and classification using LDA and ANN classifiers are reported


    Alexandre Ribeiro Afonso


    Full Text Available This article reports the findings of an empirical study about Automated Text Clustering applied to scientific articles and newspaper texts in Brazilian Portuguese, the objective was to find the most effective computational method able to cluster the input of texts in their original groups. The study covered four experiments, each experiment had four procedures: 1. Corpus Selections (a set of texts is selected for clustering, 2. Word Class Selections (Nouns, Verbs and Adjectives are chosen from each text by using specific algorithms, 3. Filtering Algorithms (a set of terms is selected from the results of the preview stage, a semantic weight is also inserted for each term and an index is generated for each text, 4. Clustering Algorithms (the clustering algorithms Simple K-Means, sIB and EM are applied to the indexes. After those procedures, clustering correctness and clustering time statistical results were collected. The sIB clustering algorithm is the best choice for both scientific and newspaper corpus, under the condition that the sIB clustering algorithm asks for the number of clusters as input before running (for the newspaper corpus, 68.9% correctness in 1 minute and for the scientific corpus, 77.8% correctness in 1 minute. The EM clustering algorithm additionally guesses the number of clusters without user intervention, but its best case is less than 53% correctness. Considering the experiments carried out, the results of human text classification and automated clustering are distant; it was also observed that the clustering correctness results vary according to the number of input texts and their topics.

  11. Control Class Summaries and Control Class IV from April 1990

    Wu, J.; /Fermilab


    The D0 cryogenic control system is a complicated system with many facets. Because of the large number and variety of features in the system, a series of ongoing control system training seminars, or control classes, were created in order to keep people up to date on the operation of the system. As of the writing of this engineering note, there have been four classes. The original lecture notes from each class can be found in the cryogenic control room at the D0 Assembly Building, or in the Co-op office. This note provides a summary of the first three control classes, and it includes the entire set of notes from the fourth class, which was held in April of 1990. This class was taught by Jeff Wendlandt and Dan Markley. Dan should be consulted for more complete explanations than those given in the notes. The notes are, in fact, more of a reference for someone who has some experience with the system, than they are a training manual. Most of the pages include pictures and printouts of different menus and functions, useful for finding details without searching through the actual program. In general, this note serves as a pointer to the existence of the control class lecture notes, and as an explanation of their overall contents and purpose.

  12. Cluster Radioactivity in 127I

    K. Manimaran


    Full Text Available Using the preformation cluster model of Gupta and collaborators we have studied all the possible cluster decay modes of 127 I. The calculated half-lives are compared with recently measured lower limits of cluster decay half-lives (for the clusters like 24Ne, 28Mg, 30Mg, 32Si, 34Si, 48Ca and 49Sc of 127I. Our calculated half-life values lies well above the experimentally measured lower limits and the trend of the values also matches with experimental ones.

  13. Optical properties of cluster plasma

    Kishimoto, Yasuaki; Tajima, Toshiki [Japan Atomic Energy Research Inst., Neyagawa, Osaka (Japan). Kansai Research Establishment; Downer, M.C.


    It is shown that unlike a gas plasma or an electron plasma in a metal, an ionized clustered material (`cluster plasma`) permits propagation below the plasma cut-off of electromagnetic (EM) waves whose phase velocity is close to but below the speed of light. This results from the excitation of a plasma oscillation mode (and/or polarization mode) through the cluster surface which does not exist in usual gaseous plasma. The existence of this new optical mode, cluster mode, is confirmed via numerical simulation. (author)

  14. Relativistic Binaries in Globular Clusters

    Benacquista Matthew J.


    Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing 10^4 - 10^7 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker-Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  15. Relativistic Binaries in Globular Clusters

    Benacquista Matthew


    Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing $10^4 - 10^6$ stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct $N$-body integrations and Fokker--Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  16. Integrative cluster analysis in bioinformatics

    Abu-Jamous, Basel; Nandi, Asoke K


    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

  17. Active matter clusters at interfaces.

    Copenhagen, Katherine; Gopinathan, Ajay


    Collective and directed motility or swarming is an emergent phenomenon displayed by many self-organized assemblies of active biological matter such as clusters of embryonic cells during tissue development, cancerous cells during tumor formation and metastasis, colonies of bacteria in a biofilm, or even flocks of birds and schools of fish at the macro-scale. Such clusters typically encounter very heterogeneous environments. What happens when a cluster encounters an interface between two different environments has implications for its function and fate. Here we study this problem by using a mathematical model of a cluster that treats it as a single cohesive unit that moves in two dimensions by exerting a force/torque per unit area whose magnitude depends on the nature of the local environment. We find that low speed (overdamped) clusters encountering an interface with a moderate difference in properties can lead to refraction or even total internal reflection of the cluster. For large speeds (underdamped), where inertia dominates, the clusters show more complex behaviors crossing the interface multiple times and deviating from the predictable refraction and reflection for the low velocity clusters. We then present an extreme limit of the model in the absence of rotational damping where clusters can become stuck spiraling along the interface or move in large circular trajectories after leaving the interface. Our results show a wide range of behaviors that occur when collectively moving active biological matter moves across interfaces and these insights can be used to control motion by patterning environments.

  18. A Spitzer Survey of Young Stellar Clusters within One Kiloparsec of the Sun: Cluster Core Extraction and Basic Structural Analysis

    Gutermuth, R A; Myers, P C; Allen, L E; Pipher, J L; Fazio, G G


    We present a uniform mid-infrared imaging and photometric survey of 36 young, nearby, star-forming clusters and groups using {\\it Spitzer} IRAC and MIPS. We have confidently identified and classified 2548 young stellar objects using recently established mid-infrared color-based methods. We have devised and applied a new algorithm for the isolation of local surface density enhancements from point source distributions, enabling us to extract the overdense cores of the observed star forming regions for further analysis. We have compiled several basic structural measurements of these cluster cores from the data, such as mean surface densities of sources, cluster core radii, and aspect ratios, in order to characterize the ranges for these quantities. We find that a typical cluster core is 0.39 pc in radius, has 26 members with infrared excess in a ratio of Class II to Class I sources of 3.7, is embedded in a $A_K$=0.8 mag cloud clump, and has a surface density of 60 pc$^{-2}$. We examine the nearest neighbor dista...

  19. On Identifying Clusters Within the C-type Asteroids of the Sloan Digital Sky Survey

    Poole, Renae; Ziffer, J.; Harvell, T.


    We applied AutoClass, a data mining technique based upon Bayesian Classification, to C-group asteroid colors in the Sloan Digital Sky Survey (SDSS). Previous taxonomic studies relied mostly on Principal Component Analysis (PCA) to differentiate asteroids within the C-group (e.g. B, G, F, Ch, Cg and Cb). AutoClass's advantage is that it calculates the most probable classification for us, removing the human factor from this part of the analysis. In our results, AutoClass divided the C-groups into two large classes and six smaller classes. The two large classes (n=4974 and 2033, respectively) display distinct regions with some overlap in color-vs-color plots. Each cluster's average spectrum is compared to 'typical' spectra of the C-group subtypes as defined by Tholen (1989) and each cluster's members are evaluated for consistency with previous taxonomies. Of the 117 asteroids classified as B-type in previous taxonomies, only 12 were found with SDSS colors that matched our criteria of having less than 0.1 magnitude error in u and 0.05 magnitude error in g, r, i, and z colors. Although this is a relatively small group, 11 of the 12 B-types were placed by AutoClass in the same cluster. By determining the C-group sub-classifications in the large SDSS database, this research furthers our understanding of the stratigraphy and composition of the main-belt.

  20. Nanophase materials assembled from atomic clusters

    Siegel, R.W.


    The preparation of atomic clusters of metals and ceramics by means of the gas-condensation method, followed by their in situ consolidation under high-vacuum conditions, has recently led to the synthesis of a new class of ultrafine-grained materials for which their physics is intimately coupled with their application. These nanophase materials, with 2 to 20 nm grain sizes, appear to have properties that are often rather different from conventional materials, and also processing characteristics that are greatly improved. The nanophase synthesis method described here should enable the design of materials heretofore unavailable, with improved or unique properties, based upon an understanding of the physics of these new materials. 23 refs., 8 figs.

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

    Deng, Youjin; Qian, Xiaofeng; Blöte, Henk W. J.


    We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q -state Potts model to noninteger values q>1 . Its results for static quantities are in a satisfactory agreement with those of the existing Swendsen-Wang-Chayes-Machta (SWCM) algorithm, which involves a full-cluster decomposition of random-cluster configurations. We explore the critical dynamics of this algorithm for several two-dimensional Potts and random-cluster models. For integer q , the single-cluster algorithm can be reduced to the Wolff algorithm, for which case we find that the autocorrelation functions decay almost purely exponentially, with dynamic exponents zexp=0.07 (1), 0.521 (7), and 1.007 (9) for q=2 , 3, and 4, respectively. For noninteger q , the dynamical behavior of the single-cluster algorithm appears to be very dissimilar to that of the SWCM algorithm. For large critical systems, the autocorrelation function displays a range of power-law behavior as a function of time. The dynamic exponents are relatively large. We provide an explanation for this peculiar dynamic behavior.

  2. Sleep in cluster headache

    Barloese, M C J; Jennum, P J; Lund, N T


    BACKGROUND AND PURPOSE: Cluster headache (CH) is a primary headache disorder characterized by severe attacks of unilateral pain following a chronobiological pattern. There is a close connection with sleep as most attacks occur during sleep. Hypothalamic involvement and a particular association...... with rapid eye movement (REM) sleep have been suggested. Sleep in a large, well-characterized population of CH patients was investigated. METHODS: Polysomnography (PSG) was performed on two nights in 40 CH patients during active bout and one night in 25 age, sex and body mass index matched controls...... in hospital. Macrostructure and other features of sleep were analyzed and related to phenotype. Clinical headache characterization was obtained by semi-structured interview. RESULTS: Ninety-nine nights of PSG were analyzed. Findings included a reduced percentage of REM sleep (17.3% vs. 23.0%, P = 0...

  3. Astronomy from satellite clusters

    Stachnik, R.; Labeyrie, A.


    Attention is called to the accumulating evidence that giant space telescopes, comprising a number of separate mirrors on independent satellites, are a realistic prospect for providing research tools of extraordinary power. The ESA-sponsored group and its counterpart in the US have reached remarkably similar conclusions regarding the basic configuration of extremely large synthetic-aperture devices. Both share the basic view that a cluster of spacecraft is preferable to a single monolithic structure. The emphasis of the US group has been on a mission that sweeps across as many sources as possible in the minimum time; it is referred to as SAMSI (Spacecraft Array for Michelson Spatial Interferometry). The European group has placed more emphasis on obtaining two-dimensional images. Their system is referred to as TRIO because, at least initially, it involves three independent systems. Detailed descriptions are given of the two systems.

  4. The Confucian Asian cluster

    Ionel Sergiu Pirju


    Full Text Available The Confucian Asian cluster consists of China, Hong Kong, Japan, Singapore, South Korea, and Taiwan. Confucian tradition countries were defined by achieving a consistent performance in the global economy, they still representing the major competitors in the EU and North American countries. Their progress is defined by a great national management that was able to influence beneficial management systems applied in organizations, these rules characterized by authority; aims to ensure the confidence in business. This article will present the intercultural values characterizing it, the leadership style and also tracing major macroeconomic considerations. The research is synchronic, analysing the contemporary situation of these countries, and the analysis will be interdisciplinary exploratory, identifying specific regional cultural elements.

  5. Analyzing geographic clustered response

    Merrill, D.W.; Selvin, S.; Mohr, M.S.


    In the study of geographic disease clusters, an alternative to traditional methods based on rates is to analyze case locations on a transformed map in which population density is everywhere equal. Although the analyst's task is thereby simplified, the specification of the density equalizing map projection (DEMP) itself is not simple and continues to be the subject of considerable research. Here a new DEMP algorithm is described, which avoids some of the difficulties of earlier approaches. The new algorithm (a) avoids illegal overlapping of transformed polygons; (b) finds the unique solution that minimizes map distortion; (c) provides constant magnification over each map polygon; (d) defines a continuous transformation over the entire map domain; (e) defines an inverse transformation; (f) can accept optional constraints such as fixed boundaries; and (g) can use commercially supported minimization software. Work is continuing to improve computing efficiency and improve the algorithm. 21 refs., 15 figs., 2 tabs.


    Lynch, Ryan S. [Physics Department, McGill University, 3600 Rue University, Montreal, QC H3A 2T8 (Canada); Freire, Paulo C. C. [Max-Planck-Institut fuer Radioastronomie, Auf dem Huegel 69, D-53121 Bonn (Germany); Ransom, Scott M. [National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903-4325 (United States); Jacoby, Bryan A., E-mail:, E-mail:, E-mail:, E-mail: [Aerospace Corporation, 15049 Conference Center Drive, Chantilly, VA 20151-3824 (United States)


    We have used the Robert C. Byrd Green Bank Telescope to time nine previously known pulsars without published timing solutions in the globular clusters (GCs) M62, NGC 6544, and NGC 6624. We have full timing solutions that measure the spin, astrometric, and (where applicable) binary parameters for six of these pulsars. The remaining three pulsars (reported here for the first time) were not detected enough to establish solutions. We also report our timing solutions for five pulsars with previously published solutions, and find good agreement with other authors, except for PSR J1701-3006B in M62. Gas in this system is probably responsible for the discrepancy in orbital parameters, and we have been able to measure a change in the orbital period over the course of our observations. Among the pulsars with new solutions we find several binary pulsars with very low mass companions (members of the so-called 'black widow' class) and we are able to place constraints on the mass-to-light ratio in two clusters. We confirm that one of the pulsars in NGC 6624 is indeed a member of the rare class of non-recycled pulsars found in GCs. We have also measured the orbital precession and Shapiro delay for a relativistic binary in NGC 6544. If we assume that the orbital precession can be described entirely by general relativity, which is likely, we are able to measure the total system mass (2.57190(73) M{sub Sun }) and companion mass (1.2064(20) M{sub Sun }), from which we derive the orbital inclination (sin i = 0.9956(14)) and the pulsar mass (1.3655(21) M{sub Sun }), the most precise such measurement ever obtained for a millisecond pulsar. The companion is the most massive known around a fully recycled pulsar.

  7. Meaningful Clustered Forest: an Automatic and Robust Clustering Algorithm

    Tepper, Mariano; Almansa, Andrés


    We propose a new clustering method that can be regarded as a numerical method to compute the proximity gestalt. The method analyzes edge length statistics in the MST of the dataset and provides an a contrario cluster detection criterion. The approach is fully parametric on the chosen distance and can detect arbitrarily shaped clusters. The method is also automatic, in the sense that only a single parameter is left to the user. This parameter has an intuitive interpretation as it controls the expected number of false detections. We show that the iterative application of our method can (1) provide robustness to noise and (2) solve a masking phenomenon in which a highly populated and salient cluster dominates the scene and inhibits the detection of less-populated, but still salient, clusters.

  8. Herd Clustering: A synergistic data clustering approach using collective intelligence

    Wong, Kachun


    Traditional data mining methods emphasize on analytical abilities to decipher data, assuming that data are static during a mining process. We challenge this assumption, arguing that we can improve the analysis by vitalizing data. In this paper, this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances are represented by moving particles. Particles attract each other locally and form clusters by themselves as shown in the case studies reported. To demonstrate its effectiveness, the performance of HC is compared to other state-of-the art clustering methods on more than thirty datasets using four performance metrics. An application for DNA motif discovery is also conducted. The results support the effectiveness of HC and thus the underlying philosophy. © 2014 Elsevier B.V.

  9. The Timing of Nine Globular Cluster Pulsars

    Lynch, Ryan S; Ransom, Scott M; Jacoby, Bryan A


    We have used the Robert C. Byrd Green Bank Telescope to time nine previously known pulsars without published timing solutions in the globular clusters M62, NGC 6544, and NGC 6624. We have full timing solutions that measure the spin, astrometric, and (where applicable) binary parameters for six of these pulsars. The remaining three pulsars (reported here for the first time) were not detected enough to establish solutions. We also report our timing solutions for five pulsars with previously published solutions, and find good agreement with past authors, except for PSR J1701-3006B in M62. Gas in this system is probably responsible for the discrepancy in orbital parameters, and we have been able to measure a change in the orbital period over the course of our observations. Among the pulsars with new solutions we find several binary pulsars with very low mass companions (members of the so-called "black widow" class) and we are able to place constraints on the mass-to-light ratio in two clusters. We confirm that on...

  10. The Georgi algorithms of jet clustering

    Ge, Shao-Feng


    We reveal the direct link between the jet clustering algorithms recently proposed by Howard Georgi and parton shower kinematics, providing firm foundation from the theoretical side. The kinematics of this class of elegant algorithms is explored systematically for partons with arbitrary masses and the jet function is generalized to J {/β ( n)} with a jet function index n in order to achieve more degrees of freedom. Based on three basic requirements that, the result of jet clustering is process-independent and hence logically consistent, for softer subjets the inclusion cone is larger to conform with the fact that parton shower tends to emit softer partons at earlier stage with larger opening angle, and that the cone size cannot be too large in order to avoid mixing up neighbor jets, we derive constraints on the jet function parameter β and index n which are closely related to cone size cutoff. Finally, we discuss how jet function values can be made invariant under Lorentz boost.

  11. VizieR Online Data Catalog: Masses and Ages of Stars in 68 Open Clusters (Piskunov 1980)

    Piskunov, A.


    This catalog contains the evolutionary masses and ages of about 7000 stars in 68 open clusters, as derived from their positions in the theoretical HR diagram. Cluster ages range from 106 to some 109 years, and their population varies from 30 to 700 members. For each cluster we have a table with ages and masses of stars. The file, clusters.dat may include for each cluster, the name (or NGC/IC number), cluster class, assumed color index E(B-V), true distance modulus (V-MV)0, evolutionary tracks used for given cluster and reference to the source of UBV data. The data in data.dat consists of star serial number, color index, V magnitude, luminosity, effective temperature, and ages and masses of stars. (2 data files).

  12. Novel pseudo-divergence of Gaussian mixture models based speaker clustering method

    Wang Bo; Xu Yiqiong; Li Bicheng


    Serial structure is applied to speaker recognition to reduce the algorithm delay and computational complexity. The speech is first classified into speaker class, and then searches the most likely one inside the class.Difference between Gaussian Mixture Models (GMMs) is widely applied in speaker classification. The paper proposes a novel mean of pseudo-divergence, the ratio of Inter-Model dispersion to Intra-Model dispersion, to present the difference between GMMs, to perform speaker cluster. Weight, mean and variance, GMM's components, are involved in the dispersion. Experiments indicate that the measurement can well present the difference of GMMs and has improved performance of speaker clustering.

  13. Lipschitz classes on local fields

    Wei-yi SU; Guo-xiang CHEN


    The Lipschitz class Lipα on a local field K is defined in this note, and the equivalent relationship between the Lipschitz class Lipα and the Holder type space Cα (K) is proved. Then, those important characteristics on the Euclidean space Rn and the local field K are compared, so that one may interpret the essential differences between the analyses on Rn and K. Finally, the Cantor type fractal function (V)(x) is showed in the Lipschitz class Lip (m, K), m < ln2/ln3.

  14. Lipschitz classes on local fields


    The Lipschitz class Lipαon a local field K is defined in this note,and the equivalent relationship between the Lipschitz class Lipαand the Holder type space C~α(K)is proved.Then,those important characteristics on the Euclidean space R~n and the local field K are compared,so that one may interpret the essential differences between the analyses on R~n and K.Finally,the Cantor type fractal functionθ(x)is showed in the Lipschitz class Lip(m,K),m<(ln 2/ln 3).

  15. New Ramsey Classes from Old

    Bodirsky, Manuel


    Let C_1 and C_2 be strong amalgamation classes of finite structures, with disjoint finite signatures sigma and tau. Then C_1 wedge C_2 denotes the class of all finite (sigma cup tau)-structures whose sigma-reduct is from C_1 and whose tau-reduct is from C_2. We prove that when C_1 and C_2 are Ramsey, then C_1 wedge C_2 is also Ramsey. We also discuss variations of this statement, and give several examples of new Ramsey classes derived from those general results.

  16. Homogeneous products of conjugacy classes

    Adan-Bante, Edith


    Let $G$ be a finite group and $a\\in G$. Let $a^G=\\{g^{-1}ag\\mid g\\in G\\}$ be the conjugacy class of $a$ in $G$. Assume that $a^G$ and $b^G$ are conjugacy classes of $G$ with the property that ${\\bf C}_G(a)={\\bf C}_G(b)$. Then $a^G b^G$ is a conjugacy class if and only if $[a,G]=[b,G]=[ab,G]$ and $[ab,G]$ is a normal subgroup of $G$.

  17. The Relationship between Class I and Class II Methanol Masers

    Ellingsen, S P


    The Australia Telescope National Facility Mopra millimetre telescope has been used to search for 95.1-GHz class I methanol masers towards sixty-two 6.6-GHz class II methanol masers. A total of twenty-six 95.1-GHz masers were detected, eighteen of these being new discoveries. Combining the results of this search with observations reported in the literature, a near complete sample of sixty-six 6.6-GHz class II methanol masers has been searched in the 95.1-GHz transition, with detections towards 38 per cent (twenty-five detections ; not all of the sources studied in this paper qualify for the complete sample, and some of the sources in the sample were not observed in the present observations). There is no evidence of an anti-correlation between either the velocity range, or peak flux density of the class I and II transitions, contrary to suggestions from previous studies. The majority of class I methanol maser sources have a velocity range that partially overlaps with the class II maser transitions. The presence...

  18. Effective FCM noise clustering algorithms in medical images.

    Kannan, S R; Devi, R; Ramathilagam, S; Takezawa, K


    The main motivation of this paper is to introduce a class of robust non-Euclidean distance measures for the original data space to derive new objective function and thus clustering the non-Euclidean structures in data to enhance the robustness of the original clustering algorithms to reduce noise and outliers. The new objective functions of proposed algorithms are realized by incorporating the noise clustering concept into the entropy based fuzzy C-means algorithm with suitable noise distance which is employed to take the information about noisy data in the clustering process. This paper presents initial cluster prototypes using prototype initialization method, so that this work tries to obtain the final result with less number of iterations. To evaluate the performance of the proposed methods in reducing the noise level, experimental work has been carried out with a synthetic image which is corrupted by Gaussian noise. The superiority of the proposed methods has been examined through the experimental study on medical images. The experimental results show that the proposed algorithms perform significantly better than the standard existing algorithms. The accurate classification percentage of the proposed fuzzy C-means segmentation method is obtained using silhouette validity index.

  19. Clustering determines the dynamics of complex contagions in multiplex networks

    Zhuang, Yong; Arenas, Alex; Yaǧan, Osman


    We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.

  20. A discriminative approach for unsupervised clustering of DNA sequence motifs.

    Philip Stegmaier

    Full Text Available Algorithmic comparison of DNA sequence motifs is a problem in bioinformatics that has received increased attention during the last years. Its main applications concern characterization of potentially novel motifs and clustering of a motif collection in order to remove redundancy. Despite growing interest in motif clustering, the question which motif clusters to aim at has so far not been systematically addressed. Here we analyzed motif similarities in a comprehensive set of vertebrate transcription factor classes. For this we developed enhanced similarity scores by inclusion of the information coverage (IC criterion, which evaluates the fraction of information an alignment covers in aligned motifs. A network-based method enabled us to identify motif clusters with high correspondence to DNA-binding domain phylogenies and prior experimental findings. Based on this analysis we derived a set of motif families representing distinct binding specificities. These motif families were used to train a classifier which was further integrated into a novel algorithm for unsupervised motif clustering. Application of the new algorithm demonstrated its superiority to previously published methods and its ability to reproduce entrained motif families. As a result, our work proposes a probabilistic approach to decide whether two motifs represent common or distinct binding specificities.


    S. Anitha Elavarasi


    Full Text Available Learning is the process of generating useful information from a huge volume of data. Learning can be either supervised learning (e.g. classification or unsupervised learning (e.g. Clustering Clustering is the process of grouping a set of physical objects into classes of similar object. Objects in real world consist of both numerical and categorical data. Categorical data are not analyzed as numerical data because of the absence of inherit ordering. This paper describes about ten different clustering algorithms, its methodology and the factors influencing its performance. Each algorithm is evaluated using real world datasets and its pro and cons are specified. The various similarity / dissimilarity measure applied to categorical data and its performance is also discussed. The time complexity defines the amount of time taken by an algorithm to perform the elementary operation. The time complexity of various algorithms are discussed and its performance on real world data such as mushroom, zoo, soya bean, cancer, vote, car and iris are measured. In this survey Cluster Accuracy and Error rate for four different clustering algorithm (K-modes, fuzzy K-modes, ROCK and Squeezer, two different similarity measure (DISC and Overlap and DILCA applied for hierarchy and partition algorithm are evaluated.

  2. Are Nuclear Star Clusters the Precursors of Massive Black Holes?

    Nadine Neumayer


    Full Text Available We present new upper limits for black hole masses in extremely late type spiral galaxies. We confirm that this class of galaxies has black holes with masses less than 106M⊙, if any. We also derive new upper limits for nuclear star cluster masses in massive galaxies with previously determined black hole masses. We use the newly derived upper limits and a literature compilation to study the low mass end of the global-to-nucleus relations. We find the following. (1 The MBH-σ relation cannot flatten at low masses, but may steepen. (2 The MBH-Mbulge relation may well flatten in contrast. (3 The MBH-Sersic n relation is able to account for the large scatter in black hole masses in low-mass disk galaxies. Outliers in the MBH-Sersic n relation seem to be dwarf elliptical galaxies. When plotting MBH versus MNC we find three different regimes: (a nuclear cluster dominated nuclei, (b a transition region, and (c black hole-dominated nuclei. This is consistent with the picture, in which black holes form inside nuclear clusters with a very low-mass fraction. They subsequently grow much faster than the nuclear cluster, destroying it when the ratio MBH/MNC grows above 100. Nuclear star clusters may thus be the precursors of massive black holes in galaxy nuclei.

  3. Phase classification by mean shift clustering of multispectral materials images.

    Martins, Diego Schmaedech; Josa, Victor M Galván; Castellano, Gustavo; da Costa, José A T Borges


    A mean-shift clustering (MSC) algorithm is introduced as a valuable alternative to perform materials phase classification from multispectral images. As opposed to other multivariate statistical techniques, such as factor analysis or principal component analysis (PCA), clustering techniques directly assign a class label to each pixel, so that their outputs are phase segmented images, i.e., there is no need for an additional segmentation algorithm. On the other hand, as compared to other clustering procedures and classification methods, such as segmentation by thresholding of multiple spectral components, MSC has the advantages of not requiring previous knowledge of the number of data clusters and not assuming any shape for these clusters, i.e., neither the number nor the composition of the phases must be previously known. This makes MSC a particularly useful tool for exploratory research, assisting phase identification of unknown samples. Visualization and interpretation of the results are also simplified, since the information content of the output image does not depend on the particular choice of the content of the color channels.We applied MSC to the analysis of two sets of X-ray maps acquired in scanning electron microscopes equipped with energy-dispersive detection systems. Our results indicate that MSC is capable of detecting additional phases, not clearly identified through PCA or multiple thresholding, with a very low empirical reject rate.

  4. The Nordic Mobile Telecommunication Cluster

    Jørgensen, Ulrik


    A study of the historic role of the Nordic mobile telephone and telecommunications cluster and its background in both coordinated innovation policies and societal developments in Scandinavia.......A study of the historic role of the Nordic mobile telephone and telecommunications cluster and its background in both coordinated innovation policies and societal developments in Scandinavia....

  5. Management of Classes with Breaches of Discipline



    As an only child is pampered and spoiled by parents, the contemporary student easily breaches class discipline. Class management appears more concerned than ever because breaches of class discipline have great impact on teaching. The author clarifies the necessity to study the management of classes with breaches of class discipline, numerates the phenomena of breaches of class discipline, precisely analyzes the causes from teachers and students and especially submits several measures to effectively prevent breaches of class discipline.

  6. Assembling of hydrogenated aluminum clusters

    Duque, F.; Mananes, A. [Dept. de Fisica Moderna, Universidad de Cantabria, Santander (Spain); Molina, L.M.; Lopez, M.J.; Alonso, J.A. [Dept. de Fisica Teorica, Universidad de Valladolid (Spain)


    The electronic and atomic structure of Al{sub 13}H has been studied using Density Functional Theory. Al{sub 13}H has closed electronic shells. This makes the cluster very stable and suggests that it could be a candidate to form cluster assembled solids. The interaction between two Al{sub 13}H clusters was analyzed and we found that the two units preserve their identities in the dimer. A cubic-like solid phase assembled from Al{sub 13}H units was then modeled. In that solid the clusters retain much of their identity. Molecular dynamics runs show that the structure of the assembled solid is stable at least up to 150 K. A favorable relative orientation of the clusters with respect to their neighbors is critical for the stability of that solid. (orig.)

  7. The inner Galactic globular clusters

    Mateo M.


    Full Text Available Galactic globular clusters located towards the inner regions of the Milky Way have been historically neglected, mainly due to the difficulties caused by the presence of an elevated extinction by foreground dust, and high field star densities along the lines of sight where most of them lie. To overcome these difficulties we have developed a new method to map the differential extinction suffered by these clusters, which was successfully applied to a sample of moderately-extincted, luminous, extended, inner Galactic globular clusters observed in the optical, for which we have been able to determine more accurate physical parameters. For the most extincted inner Galactic globular clusters, near-infrared wavelengths provide a more suitable window for their study. The VVV survey, which is currently observing the central regions of the Milky Way at these wavelengths, will provide a comprehensive view, from the inner regions out to their tidal radii and beyond, of most of these globular clusters.

  8. An Exact Relaxation of Clustering

    Mørup, Morten; Hansen, Lars Kai


    of clustering problems such as the K-means objective and pairwise clustering as well as graph partition problems, e.g., for community detection in complex networks. In particular we show that a relaxation to the simplex can be given for which the extreme solutions are stable hard assignment solutions and vice......Continuous relaxation of hard assignment clustering problems can lead to better solutions than greedy iterative refinement algorithms. However, the validity of existing relaxations is contingent on problem specific fuzzy parameters that quantify the level of similarity between the original...... versa. Based on the new relaxation we derive the SR-clustering algorithm that has the same complexity as traditional greedy iterative refinement algorithms but leading to significantly better partitions of the data. A Matlab implementation of the SR-clustering algorithm is available for download....

  9. Research on the use of E-Class in the university class management



    As an information exchange platform for online class, E-Class has played an important role in class management since its foundation. Based on the analysis of the impact of the network to university class management, this paper studied the advantages and the disadvantages of the current E-Class in class management, and proposed suggestions of strengthening the E-Class management.

  10. Latent Class Analysis of Incomplete Data via an Entropy-Based Criterion.

    Larose, Chantal; Harel, Ofer; Kordas, Katarzyna; Dey, Dipak K


    Latent class analysis is used to group categorical data into classes via a probability model. Model selection criteria then judge how well the model fits the data. When addressing incomplete data, the current methodology restricts the imputation to a single, pre-specified number of classes. We seek to develop an entropy-based model selection criterion that does not restrict the imputation to one number of clusters. Simulations show the new criterion performing well against the current standards of AIC and BIC, while a family studies application demonstrates how the criterion provides more detailed and useful results than AIC and BIC.

  11. Semantic Based Cluster Content Discovery in Description First Clustering Algorithm



    Full Text Available In the field of data analytics grouping of like documents in textual data is a serious problem. A lot of work has been done in this field and many algorithms have purposed. One of them is a category of algorithms which firstly group the documents on the basis of similarity and then assign the meaningful labels to those groups. Description first clustering algorithm belong to the category in which the meaningful description is deduced first and then relevant documents are assigned to that description. LINGO (Label Induction Grouping Algorithm is the algorithm of description first clustering category which is used for the automatic grouping of documents obtained from search results. It uses LSI (Latent Semantic Indexing; an IR (Information Retrieval technique for induction of meaningful labels for clusters and VSM (Vector Space Model for cluster content discovery. In this paper we present the LINGO while it is using LSI during cluster label induction and cluster content discovery phase. Finally, we compare results obtained from the said algorithm while it uses VSM and Latent semantic analysis during cluster content discovery phase.

  12. Tidal stripping of globular clusters in a simulated galaxy cluster

    Ramos, Felipe; Muriel, Hernán; Abadi, Mario


    Using a cosmological N-body numerical simulation of the formation of a galaxy cluster- sized halo, we analyze the temporal evolution of its globular cluster population. We follow the dynamical evolution of 38 galactic dark matter halos orbiting in a galaxy cluster that at redshift z=0 has a virial mass of 1.71 * 10 ^14 Msol h^-1. In order to mimic both "blue" and "red" populations of globular clusters, for each galactic halo we select two different sets of particles at high redshift (z ~ 1), constrained by the condition that, at redshift z=0, their average radial density profiles are similar to the observed profiles. As expected, the general galaxy cluster tidal field removes a significant fraction of the globular cluster populations to feed the intracluster population. On average, halos lost approximately 16% and 29% of their initial red and blue globular cluster populations, respectively. Our results suggest that these fractions strongly depend on the orbital trajectory of the galactic halo, specifically on...

  13. Sequential clustering of star formations in IC 1396

    Ya-Fang Huang; Jin-Zeng Li


    We present a comprehensive study of the H Ⅱ region IC 1396 and its star forming activity,in which multi-wavelength data ranging from the optical to the nearand far-infrared were employed.The surface density distribution of all the 2MASS sources with a certain detection toward IC 1396 indicates the existence of a compact cluster spatially consistent with the position of the exciting source of the H Ⅱ region,HD 206267.The spatial distribution of the sources with excessive infrared emission,selected based on archived 2MASS data,reveals the existence of four sub-clusters in this region.One is associated with the open cluster Trumpler 37.The other three are found to be spatially coincident with the bright rims of the H Ⅱ region.All the sources with excessive emission in the near infrared are cross-identified with AKARI IRC data.An analysis of the spectral energy distributions (SEDs) of the resultant sample leads to the identification of eight CLASS I,15 CLASS Ⅱ and 15 CLASS Ⅲ sources in IC 1396.Optical identification of the sample sources with R magnitudes brighter than 17 mag corroborates the results from the SED analysis.Based on the spatial distribution of the infrared young stellar objects at different evolutionary stages,the surrounding sub-clusters located in the bright rims are believed to be younger than the central one.This is consistent with a scenario of sequential star formation in this region.Imaging data of a dark patch in IC 1396 by Herschel SPIRE,on the other hand,indicate the presence of two far-infrared cores in LDN 1111,which are likely to be a new generation of protostellar objects in formation.So we infer that the star formation process in this H Ⅱ region was not continuous but rather episodic.



    Introduction In China, some English teachers go to class with only a textbook and a teaching plan, nothing else. After a while, the students complain that their classes are becoming more and more boring. Teachers have tried many ways to make their classes more interesting, motivating and effective, but using pictures in the classroom to do this has not been a popular method. The world provides us with all kinds of beautiful pictures. There is no reason why we should not make better use of them in language learning and teaching. This article will discuss the reasons for using pictures, suggest ways of collecting pictures and ways of using pictures in reading, writing, listening and speaking classes.

  15. Condylar volume and condylar area in class I, class II and class III young adult subjects

    Saccucci Matteo


    Full Text Available Abstract Aim Aim of this study was to compare the volume and the shape of mandibular condyles in a Caucasian young adult population, with different skeletal pattern. Material and methods 200 Caucasian patients (15–30 years old, 95 male and 105 females were classified in three groups on the base of ANB angle: skeletal class I (65 patients, skeletal class II (70 patients and skeletal class III (65 patients. Left and right TMJs of each subject were evaluated independently with CBCT (Iluma. TMJ evaluation included: condylar volume; condylar area; morphological index (MI. Condylar volumes were calculated by using the Mimics software. The condylar volume, the area and the morphological index (MI were compared among the three groups, by using non-parametric tests. Results The Kruskal-Wallis test and the Mann Whitney test revealed that: no significant difference was observed in the whole sample between the right and the left condylar volume; subjects in skeletal class III showed a significantly higher condylar volume, respect to class I and class II subjects (p 3 in males and 663.5 ± 81.3 mm3 in females; p 2 in males and 389.76 ± 61.15 mm2 in females; p  Conclusion Skeletal class appeared to be associated to the mandibular condylar volume and to the mandibular condylar area in the Caucasian orthodontic population.

  16. A latent class distance association model for cross-classified data with a categorical response variable

    Vera, J.F.; Rooij, M. de; Heiser, W.J.


    In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single ou

  17. Divisive latent class modeling as a density estimation method for categorical data

    van der Palm, D.W.; van der Ark, L.A.; Vermunt, J.K.


    Traditionally latent class (LC) analysis is used by applied researchers as a tool for identifying substantively meaningful clusters. More recently, LC models have also been used as a density estimation tool for categorical variables. We introduce a divisive LC (DLC) model as a density estimation too

  18. The Relationship of Academic Self-Efficacy to Class Participation and Exam Performance

    Galyon, Charles E.; Blondin, Carolyn A.; Yaw, Jared S.; Nalls, Meagan L.; Williams, Robert L.


    This study examined the relationship of academic self-efficacy to engagement in class discussion and performance on major course exams among students (N = 165) in an undergraduate human development course. Cluster analysis was used to identify three levels of academic self-efficacy: high (n = 34), medium (n = 91), and low (n = 40). Results…

  19. Power and sample size computation for Wald tests in latent class models

    Gudicha, D.W.; Tekle, F.B.; Vermunt, J.K.


    Latent class (LC) analysis is used by social, behavioral, and medical science researchers among others as a tool for clustering (or unsupervised classification) with categorical response variables, for analyzing the agreement between multiple raters, for evaluating the sensitivity and specificity of

  20. Covering #SAE: A Mobile Reporting Class's Changing Patterns of Interaction on Twitter over Time

    Jones, Julie


    This study examined the social network that emerged on Twitter surrounding a mobile reporting class as they covered a national breaking news event. The work introduces pedagogical strategies that enhance students' learning opportunities. Through NodeXL and social network cluster analysis, six groups emerged from the Twitter interactions tied to…

  1. A Feature Mining Based Approach for the Classification of Text Documents into Disjoint Classes.

    Nieto Sanchez, Salvador; Triantaphyllou, Evangelos; Kraft, Donald


    Proposes a new approach for classifying text documents into two disjoint classes. Highlights include a brief overview of document clustering; a data mining approach called the One Clause at a Time (OCAT) algorithm which is based on mathematical logic; vector space model (VSM); and comparing the OCAT to the VSM. (Author/LRW)

  2. Star Clusters in the log Age vs. M_V plane

    Bellazzini, M; Galleti, S; Federici, L; Buzzoni, A; Pecci, F Fusi


    We introduce the log Age vs. integrated absolute magnitude (M_V) plane as a diagnostic plane to compare different classes of star clusters and/or star cluster populations of different galaxies. In this plane, the open clusters of the Milky Way form a well-defined band parallel to theoretical sequences decribing the passive evolution of Simple Stellar Populations and display a pretty sharp upper threshold in mass (M ~ 2X 10^4 M_{sun}) over a 4 dex range of ages.

  3. Inferring modules from human protein interactome classes

    Chaurasia Gautam


    Full Text Available Abstract Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features. Results We examined this issue based on the analysis of modules detected by network clustering methods applied to both integrated and individual (disaggregated data sources, which we call interactome classes. Due to class diversity, we deal with variable dependencies of data features arising from structural specificities and biases, but also from possible overlaps. Since highly connected regions of the human interactome may point to potential protein complexes, we have focused on the concept of modularity, and elucidated the detection power of module extraction algorithms by independent validations based on GO, MIPS and KEGG. From the combination of protein interactions with gene expressions, a confidence scoring scheme has been proposed before proceeding via GO with further classification in permanent and transient modules. Conclusions Disaggregated interactomes are shown to be informative for inferring modularity, thus contributing to perform an effective integrative analysis. Validation of the extracted modules by multiple annotation allows for the assessment of confidence measures assigned to the modules in a protein pathway context. Notably, the proposed multilayer confidence scheme can be used for network calibration by enabling a transition from unweighted to weighted interactomes based on biological evidence.

  4. Evolution of nonlinear optical properties: from gold atomic clusters to plasmonic nanocrystals.

    Philip, Reji; Chantharasupawong, Panit; Qian, Huifeng; Jin, Rongchao; Thomas, Jayan


    Atomic clusters of metals are an emerging class of extremely interesting materials occupying the intermediate size regime between atoms and nanoparticles. Here we report the nonlinear optical (NLO) characteristics of ultrasmall, atomically precise clusters of gold, which are smaller than the critical size for electronic energy quantization (∼2 nm). Our studies reveal remarkable features of the distinct evolution of the optical nonlinearity as the clusters progress in size from the nonplasmonic regime to the plasmonic regime. We ascertain that the smallest atomic clusters do not show saturable absorption at the surface plasmon wavelength of larger gold nanocrystals (>2 nm). Consequently, the third-order optical nonlinearity in these ultrasmall gold clusters exhibits a significantly lower threshold for optical power limiting. This limiting efficiency, which is superior to that of plasmonic nanocrystals, is highly beneficial for optical limiting applications.

  5. Active FEL-Klystrons As Formers of Femto-Second Clusters of Electromagnetic Field. General Description

    A.Ju. Brusnik


    Full Text Available A qualitative physical and technological substantiation of the creation possibility of a new class of Femto-second Free Electron Lasers (FFELs (active cluster FEL-klystrons is given in the article. The concept of “electromagnetic field” cluster is introduced. Apart from that, the main difference between the concepts “the electromagnetic cluster” and “the radio-pulse” (which is well-known in radio-physics is formulated. The concept of “cluster electromagnetic wave” is also discussed. A general approach to designing the proposed active cluster FEL-klystrons is formulated. The description of a principal design scheme of the active cluster FEL-klystrons and their key technological basis are discussed.

  6. Clustering of landforms using self-organizing maps (SOM) in the west of Fars province

    Mokarram, Marzieh; Sathyamoorthy, Dinesh


    The aim of this study is to cluster landforms in the west of the Fars province, Iran using self-organizing maps (SOM). In SOM, according to qualitative data, the clustering tendencies of landforms were investigated using six morphometric parameters, which were slope, profile, plan, elevation, curvature and aspect. First, topographic position index (TPI) was used to prepare the landform classification map. The results of SOM showed that there were five classes for landform classification in the study area. Cluster 5 corresponds to high slope, high elevation but with different of concavity and convexity that consist of ridge landforms. Cluster 3 corresponds to flat areas, possibly plantation areas, in medium elevation and almost flat terrain. Clusters 1, 2 and 4 correspond to channels with different slope conditions.

  7. EGRET upper limits on the high-energy gamma-ray emission of galaxy clusters

    Reimer, O; Sreekumar, P; Mattox, J R


    We report EGRET upper limits on the high-energy gamma-ray emission from clusters of galaxies. EGRET observations between 1991 and 2000 were analyzed at positions of 58 individual clusters from a flux-limited sample of nearby X-ray bright galaxy clusters. Subsequently, a coadded image from individual galaxy clusters has been analyzed using an adequately adapted diffuse gamma-ray foreground model. The resulting 2 sigma upper limit for the average cluster is \\~ 6 x 10^{-9} cm^{-2} s^{-1} for E > 100 MeV. Implications of the non--detection of prominent individual clusters and of the general inability to detect the X-ray brightest galaxy clusters as a class of gamma-ray emitters are discussed. We compare our results with model predictions on the high-energy gamma-ray emission from galaxy clusters as well as with recent claims of an association between unidentified or unresolved gamma-ray sources and Abell clusters of galaxies and find these contradictory.

  8. The Intersection between Out-of-class Language Learning Strategies and In-class Activities

    Noor Saazai Mat Saad


    Full Text Available Studies on out-of-class language learning strategies (OCLLSs are usually divorced from the activities in class. Thus, this study addresses the connection of the two entities. The participants in this study were nine international postgraduate students who were undergoing their English language proficiency course in an institution in Malaysia.  Data were gathered through their weekly online postings on Google + and interview during the course. The data from the students were triangulated with the information found in the pro forma of the modules and interview with the lecturers. Atlas ti was used to manage the data.  It was discovered that the type of assessment set by lecturers for the course determined the use of OCLLSs. Findings show that firstly, more OCLLS were used in completing assignments than preparing for quizzes/tests. Thus, from the 3 modules; it was found that students employed more strategies for oral communication and writing rather than for reading.  Secondly, the OCLLSs used could form a 'strategy chain or cluster' for the tasks of preparing for oral presentation and completing writing assignments. Lastly, there was evidence of technology dependency on some of the main OCLLSs.  

  9. Cosmology with Clusters of Galaxies

    Borgani, Stefano

    I reviewed in my talk recent results on the cosmological constraints that can be obtained by following the evolution of the population of galaxy clusters. Using extended samples of X-ray selected clusters, I have shown how they can be used to trace this evolution out to redshift z ~ 1. This evolution can be compared to model predictions and, therefore, to constrain cosmological parameters, such as the density parameter Omega_m and the shape and amplitude of the power spectrum of density perturbations. I have emphasized that the robustness of such constraints is quite sensitive to the relation between cluster collapsed mass and X-ray luminosity and temperature. This demonstrates that our ability to place significant constraints on cosmology using clusters of galaxies relies on our capability to understand the physical processes, which determine the properties of the intra-cluster medium (ICM). In this context, I have discussed how numerical simulations of cluster formation in cosmological context can play an important role in uderstanding the ICM physics. I have presented results from a very large cosmological simulation, which also includes the hydrodynamical description of the cosmic baryons, the processes of star formation and feedback from the stellar populations. The results from this simulation represent a unique baseline to describe the processes of formation and evolution of clusters of galaxies.

  10. Classes subalternas, lutas de classe e hegemonia: uma abordagem gramsciana Subaltern classes, class struggles and hegemony: a gramscian approach

    Ivete Simionatto


    Full Text Available O artigo procura resgatar, no pensamento de Antonio Gramsci, a concepção de classes subalternas e a sua relação com outras categorias, especialmente, o Estado, a sociedade civil e a hegemonia, como suportes da luta de classes na realidade contemporânea. Aborda, ainda, as relações entre classes subalternas, senso comum e ideologia, bem como as formas de superação tematizadas por Gramsci, através da cultura e da filosofia da práxis. Nesse sentido, num movimento de totalidade, busca recuperar a discussão das classes subalternas, a partir da original formulação gramsciana no âmbito do marxismo, mediante a interação dialética entre estrutura e superestrutura, economia e política. Além do resgate conceitual, apontam-se alguns elementos como subsídios à discussão das formas de subalternidade presentes na realidade contemporânea e as possibilidades de fortalecimento das lutas de tais camadas de classe, sobretudo em momentos de forte desmobilização da participação popular.This article sought to revive the concept of subaltern classes and their relation with other categories, particularly the State, civil society and hegemony in the thinking of Antonio Gramsci, as a support for contemporary class struggles. It also analyzes the relations between subaltern classes, common sense and ideology, as well as the forms of "overcoming" conceptualized by Gramsci, through the culture and philosophy of praxis. The paper revives the discussion of the subaltern classes, based on the original Gramscian formulation in the realm of Marxism, through the dialectic interaction between structure and superstructure, economy and politics. In addition to the conceptual revival, it indicates some elements that can support the discussion of the forms of subalternity found in contemporary reality and the possibilities for strengthening the struggles of these class layers, above all in moments of strong demobilization of popular participation.


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


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

  12. Herschel photometry of brightest cluster galaxies in cooling flow clusters

    Edge, A C; Mittal, R; Allen, S W; Baum, S A; Boehringer, H; Bregman, J N; Bremer, M N; Combes, F; Crawford, C S; Donahue, M; Egami, E; Fabian, A C; Hamer, S L; Hatch, N A; Jaffe, W; Johnstone, R M; McNamara, B R; O'Dea, C P; Popesso, P; Quillen, A C; Salome, P; Sarazin, C L; Voit, G M; Wilman, R J; Wise, M W


    The dust destruction timescales in the cores of clusters of galaxies are relatively short given their high central gas densities. However, substantial mid-infrared and sub-mm emission has been detected in many brightest cluster galaxies. In this letter we present Herschel PACS and SPIRE photometry of the brightest cluster galaxy in three strong cooling flow clusters, A1068, A2597 and Zw3146. This photometry indicates that a substantial mass of cold dust is present (>3 x 10^7 Mo) at temperatures significantly lower (20-28K) than previously thought based on limited MIR and/or sub-mm results. The mass and temperature of the dust appear to match those of the cold gas traced by CO with a gas-to-dust ratio of 80-120.

  13. MHC class I loci of the Bar-Headed goose (Anser indicus

    Qinglong Liang


    Full Text Available MHC class I proteins mediate functions in anti-pathogen defense. MHC diversity has already been investigated by many studies in model avian species, but here we chose the bar-headed goose, a worldwide migrant bird, as a non-model avian species. Sequences from exons encoding the peptide-binding region (PBR of MHC class I molecules were isolated from liver genomic DNA, to investigate variation in these genes. These are the first MHC class I partial sequences of the bar-headed goose to be reported. A preliminary analysis suggests the presence of at least four MHC class I genes, which share great similarity with those of the goose and duck. A phylogenetic analysis of bar-headed goose, goose and duck MHC class I sequences using the NJ method supports the idea that they all cluster within the anseriforms clade.

  14. AutoClass@IJM: a powerful tool for Bayesian classification of heterogeneous data in biology.

    Achcar, Fiona; Camadro, Jean-Michel; Mestivier, Denis


    Recently, several theoretical and applied studies have shown that unsupervised Bayesian classification systems are of particular relevance for biological studies. However, these systems have not yet fully reached the biological community mainly because there are few freely available dedicated computer programs, and Bayesian clustering algorithms are known to be time consuming, which limits their usefulness when using personal computers. To overcome these limitations, we developed AutoClass@IJM, a computational resource with a web interface to AutoClass, a powerful unsupervised Bayesian classification system developed by the Ames Research Center at N.A.S.A. AutoClass has many powerful features with broad applications in biological sciences: (i) it determines the number of classes automatically, (ii) it allows the user to mix discrete and real valued data, (iii) it handles missing values. End users upload their data sets through our web interface; computations are then queued in our cluster server. When the clustering is completed, an URL to the results is sent back to the user by e-mail. AutoClass@IJM is freely available at:

  15. FunGeneClusterS

    Vesth, Tammi Camilla; Brandl, Julian; Andersen, Mikael Rørdam


    and industrial biotechnology applications. We have previously published a method for accurate prediction of clusters from genome and transcriptome data, which could also suggest cross-chemistry, however, this method was limited both in the number of parameters which could be adjusted as well as in user......Secondary metabolites of fungi are receiving an increasing amount of interest due to their prolific bioactivities and the fact that fungal biosynthesis of secondary metabolites often occurs from co-regulated and co-located gene clusters. This makes the gene clusters attractive for synthetic biology...

  16. Cluster de ventiladores em Catanduva.

    Luciana M. Onusic


    Full Text Available Este trabalho apresenta os resultados de um levantamento feito na cidade de Catanduva sobre a indústria de ventiladores nela instalada. É, inicialmente, apresentado o conceito de cluster, para, em seguida, serem apresentadas as características do setor de ventiladores de Catanduva, fazendo uma comparação desse setor com o conceito de cluster. Diversos aspectos mostram o interesse em considerar o setor como um cluster e são feitas sugestões para seu aprimoramento.

  17. Dynamical Processes in Globular Clusters

    McMillan, Stephen L W


    Globular clusters are among the most congested stellar systems in the Universe. Internal dynamical evolution drives them toward states of high central density, while simultaneously concentrating the most massive stars and binary systems in their cores. As a result, these clusters are expected to be sites of frequent close encounters and physical collisions between stars and binaries, making them efficient factories for the production of interesting and observable astrophysical exotica. I describe some elements of the competition among stellar dynamics, stellar evolution, and other processes that control globular cluster dynamics, with particular emphasis on pathways that may lead to the formation of blue stragglers.


    Zhang Shunhua; Zhang Yuehui


    Let H be a finite-dimensional hereditary algebra over an algebraically closed field k and CFm be the repetitive cluster category of H with m ≥ 1.We investigate the properties of cluster tilting objects in CFm and the structure of repetitive clustertilted algebras.Moreover,we generalize Theorem 4.2 in [12](Buan A,Marsh R,Reiten I.Cluster-tilted algebra,Trans.Amer.Math.Soc.,359(1)(2007),323-332.) to the situation of CFm,and prove that the tilting graph KCFm of CFm is connected.

  19. New Territory SZ Cluster Surveys

    Bartlett, J G; Barbosa, D


    The potential of the Sunyaev-Zel'dovich (SZ) effect for cluster studies has long been appreciated, although not yet fully exploited. Recent technological advances and improvements in observing strategies have changed this, to the point where it is now possible to speak of this subject at a meeting devoted to may be called {\\em pointed surveys}, dedicated to pre-selected clusters, from the former type already have significant numbers of clusters with very good signal-to-noise images; surveys of the second type are currently possible, but as yet not undertaken. The discussion will focus on the kind of science that can be done in this ``new territory''.

  20. Light cluster production at NICA

    Bastian, N.U. [University of Wroclaw, Wroclaw (Poland); Batyuk, P.; Rogachevsky, O. [Joint Institute for Nuclear Research, Dubna (Russian Federation); Blaschke, D. [University of Wroclaw, Wroclaw (Poland); Joint Institute for Nuclear Research, Dubna (Russian Federation); National Research Nuclear University (MEPhI), Moscow (Russian Federation); Danielewicz, P. [Michigan State University, East Lansing, MI (United States); Ivanov, Yu.B. [National Research Nuclear University (MEPhI), Moscow (Russian Federation); National Research Centre ' ' Kurchatov Institute' ' , Moscow (Russian Federation); Karpenko, Iu. [Bogolyubov Institute for Theoretical Physics, Kiev (Ukraine); INFN, Sezione di Firenze, Sesto Fiorentino (Italy); Roepke, G. [National Research Nuclear University (MEPhI), Moscow (Russian Federation); University of Rostock, Rostock (Germany); Wolter, H.H. [Universitaet Muenchen, Garching (Germany)


    Light cluster production at the NICA accelerator complex offers unique possibilities to use these states as ''rare probes'' of in-medium characteristics such as phase space occupation and early flow. In order to explain this statement, in this contribution theoretical considerations from the nuclear statistical equilibrium model and from a quantum statistical model of cluster production are supplemented with a discussion of a transport model for light cluster formation and with results from hydrodynamic simulations combined with the coalescence model. (orig.)