Energy transfer and clustering of photosynthetic light-harvesting complexes in reconstituted lipid membranes

International Nuclear Information System (INIS)

Dewa, Takehisa; Sumino, Ayumi; Watanabe, Natsuko; Noji, Tomoyasu; Nango, Mamoru

2013-01-01

Highlights: ► Photosynthetic light-harvesting complexes were reconstituted into lipid membranes. ► Energy transfers between light-harvesting complexes were examined. ► Atomic force microscopy indicated cluster formation of light-harvesting complexes. ► Efficient energy transfer was observed for the clustered complexes in the membranes. - Abstract: In purple photosynthetic bacteria, light-harvesting complex 2 (LH2) and light harvesting/reaction centre core complex (LH1-RC) play the key roles of capturing and transferring light energy and subsequent charge separation. These photosynthetic apparatuses form a supramolecular assembly; however, how the assembly influences the efficiency of energy conversion is not yet clear. We addressed this issue by evaluating the energy transfer in reconstituted photosynthetic protein complexes LH2 and LH1-RC and studying the structures and the membrane environment of the LH2/LH1-RC assemblies, which had been embedded into various lipid bilayers. Thus, LH2 and LH1-RC from Rhodopseudomonas palustris 2.1.6 were reconstituted in phosphatidylglycerol (PG), phosphatidylcholine (PC), and phosphatidylethanolamine (PE)/PG/cardiolipin (CL). Efficient energy transfer from LH2 to LH1-RC was observed in the PC and PE/PG/CL membranes. Atomic force microscopy revealed that LH2 and LH1-RC were heterogeneously distributed to form clusters in the PC and PE/PG/CL membranes. The results indicated that the phospholipid species influenced the cluster formation of LH2 and LH1-RC as well as the energy transfer efficiency

Energy transfer and clustering of photosynthetic light-harvesting complexes in reconstituted lipid membranes

Energy Technology Data Exchange (ETDEWEB)

Dewa, Takehisa, E-mail: takedewa@nitech.ac.jp [Department of Frontier Materials, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555 (Japan); Japan Science and Technology, PRESTO, 4-1-8 Honcho Kawaguchi, Saitama 332-0012 (Japan); Sumino, Ayumi; Watanabe, Natsuko; Noji, Tomoyasu [Department of Frontier Materials, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555 (Japan); Nango, Mamoru, E-mail: nango@nitech.ac.jp [Department of Frontier Materials, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555 (Japan)

2013-06-20

Highlights: ► Photosynthetic light-harvesting complexes were reconstituted into lipid membranes. ► Energy transfers between light-harvesting complexes were examined. ► Atomic force microscopy indicated cluster formation of light-harvesting complexes. ► Efficient energy transfer was observed for the clustered complexes in the membranes. - Abstract: In purple photosynthetic bacteria, light-harvesting complex 2 (LH2) and light harvesting/reaction centre core complex (LH1-RC) play the key roles of capturing and transferring light energy and subsequent charge separation. These photosynthetic apparatuses form a supramolecular assembly; however, how the assembly influences the efficiency of energy conversion is not yet clear. We addressed this issue by evaluating the energy transfer in reconstituted photosynthetic protein complexes LH2 and LH1-RC and studying the structures and the membrane environment of the LH2/LH1-RC assemblies, which had been embedded into various lipid bilayers. Thus, LH2 and LH1-RC from Rhodopseudomonas palustris 2.1.6 were reconstituted in phosphatidylglycerol (PG), phosphatidylcholine (PC), and phosphatidylethanolamine (PE)/PG/cardiolipin (CL). Efficient energy transfer from LH2 to LH1-RC was observed in the PC and PE/PG/CL membranes. Atomic force microscopy revealed that LH2 and LH1-RC were heterogeneously distributed to form clusters in the PC and PE/PG/CL membranes. The results indicated that the phospholipid species influenced the cluster formation of LH2 and LH1-RC as well as the energy transfer efficiency.

Synthesis of molecular hexatechnetium clusters by means of dimensional reduction of their polymeric complexes

International Nuclear Information System (INIS)

Ikai, T.; Yoshimura, T.; Shinohara, A.; Takayama, T.; Sekine, T.

2006-01-01

Selenide capping hexatechnetium cluster complex [Tc 6 (μ 3 -Se) 8 CN 6 ] 4- (1) was prepared by the reactions of one-dimensional polymer complex [Tc 6 (μ 3 -Se) 8 Br 4 ] 2- and cyanides at high temperature. Similar reaction of sulfide capping hexatechnetium cluster complex, [Tc 6 (μ 3 -S) 8 Br 6 ] 4- with cyanide gave the terminal substituted complex [Tc 6 (μ 3 -S) 8 CN 6 ] 4- (2). The single-crystal X-ray analysis of 1 and 2, showed that the Tc-Tc bond lengths become longer with lager ionic radius of the face capping ligands in the order S -1 , and that of 2 showed it at 2119 cm -1 . Each of cyclic voltammogram of 1 and 2 showed a reversible one electron redox wave assignable to the Tc 6 III /Tc 5 III Tc IV process. These redox potentials shift to the positive about 0.4V compared to those of the Re cluster analogs. (author)

Directed clustering coefficient as a measure of systemic risk in complex banking networks

Science.gov (United States)

Tabak, Benjamin M.; Takami, Marcelo; Rocha, Jadson M. C.; Cajueiro, Daniel O.; Souza, Sergio R. S.

2014-01-01

Recent literature has focused on the study of systemic risk in complex networks. It is clear now, after the crisis of 2008, that the aggregate behavior of the interaction among agents is not straightforward and it is very difficult to predict. Contributing to this debate, this paper shows that the directed clustering coefficient may be used as a measure of systemic risk in complex networks. Furthermore, using data from the Brazilian interbank network, we show that the directed clustering coefficient is negatively correlated with domestic interest rates.

Looping and clustering model for the organization of protein-DNA complexes on the bacterial genome

Science.gov (United States)

Walter, Jean-Charles; Walliser, Nils-Ole; David, Gabriel; Dorignac, Jérôme; Geniet, Frédéric; Palmeri, John; Parmeggiani, Andrea; Wingreen, Ned S.; Broedersz, Chase P.

2018-03-01

The bacterial genome is organized by a variety of associated proteins inside a structure called the nucleoid. These proteins can form complexes on DNA that play a central role in various biological processes, including chromosome segregation. A prominent example is the large ParB-DNA complex, which forms an essential component of the segregation machinery in many bacteria. ChIP-Seq experiments show that ParB proteins localize around centromere-like parS sites on the DNA to which ParB binds specifically, and spreads from there over large sections of the chromosome. Recent theoretical and experimental studies suggest that DNA-bound ParB proteins can interact with each other to condense into a coherent 3D complex on the DNA. However, the structural organization of this protein-DNA complex remains unclear, and a predictive quantitative theory for the distribution of ParB proteins on DNA is lacking. Here, we propose the looping and clustering model, which employs a statistical physics approach to describe protein-DNA complexes. The looping and clustering model accounts for the extrusion of DNA loops from a cluster of interacting DNA-bound proteins that is organized around a single high-affinity binding site. Conceptually, the structure of the protein-DNA complex is determined by a competition between attractive protein interactions and loop closure entropy of this protein-DNA cluster on the one hand, and the positional entropy for placing loops within the cluster on the other. Indeed, we show that the protein interaction strength determines the ‘tightness’ of the loopy protein-DNA complex. Thus, our model provides a theoretical framework for quantitatively computing the binding profiles of ParB-like proteins around a cognate (parS) binding site.

Cell surface clustering of Cadherin adhesion complex induced by antibody coated beads

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

Cadherin receptors mediate cell-cell adhesion, signal transduction and assembly of cytoskeletons. How a single transmembrane molecule Cadherin can be involved in multiple functions through modulating its binding activities with many membrane adhesion molecules and cytoskeletal components is an unanswered question which can be elucidated by clues from bead experiments. Human lung cells expressing N-Cadherin were examined. After co-incubation with anti-N-Cadherin monoclonal antibody coated beads, cell surface clustering of N-Cadherin was induced. Immunofluorescent detection demonstrated that in addition to Cadherin, β-Catenin, α-Catenin, α-Actinin and Actin fluorescence also aggregated respectively at the membrane site of bead attachment. Myosin heavy chain (MHC), another major component of Actin cytoskeleton, did not aggregate at the membrane site of bead attachment. Adhesion unrelated protein Con A and polylysine conjugated beads did not induce the clustering of adhesion molecules. It is indicated that the Cadherin/Catenins/α-Actinin/Actin complex is formed at Cadherin mediated cell adherens junction; occupancy and cell surface clustering of Cadherin is crucial for the formation of Cadherin adhesion protein complexes.

Community detection in complex networks using proximate support vector clustering

Science.gov (United States)

Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

2018-03-01

Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.

Oligomeric rare-earth metal cluster complexes with endohedral transition metal atoms

Energy Technology Data Exchange (ETDEWEB)

Steinberg, Simon; Zimmermann, Sina; Brühmann, Matthias; Meyer, Eva; Rustige, Christian; Wolberg, Marike; Daub, Kathrin; Bell, Thomas; Meyer, Gerd, E-mail: gerd.meyer@uni-koeln.de

2014-11-15

Comproportionation reactions of rare-earth metal trihalides (RX{sub 3}) with the respective rare-earth metals (R) and transition metals (T) led to the formation of 22 oligomeric R cluster halides encapsulating T, in 19 cases for the first time. The structures of these compounds were determined by single-crystal X-ray diffraction and are composed of trimers ((T{sub 3}R{sub 11})X{sub 15}-type, P6{sub 3}/m), tetramers ((T{sub 4}R{sub 16})X{sub 28}(R{sub 4}) (P-43m), (T{sub 4}R{sub 16})X{sub 20} (P4{sub 2}/nnm), (T{sub 4}R{sub 16})X{sub 24}(RX{sub 3}){sub 4} (I4{sub 1}/a) and (T{sub 4}R{sub 16})X{sub 23} (C2/m) types of structure) and pentamers ((Ru{sub 5}La{sub 14}){sub 2}Br{sub 39}, Cc) of (TR{sub r}){sub n} (n=2–5) clusters. These oligomers are further enveloped by inner (X{sup i}) as well as outer (X{sup a}) halido ligands, which possess diverse functionalities and interconnect like oligomers through i–i, i–a and/or a–i bridges. The general features of the crystal structures for these new compounds are discussed and compared to literature entries as well as different structure types with oligomeric T centered R clusters. Dimers and tetramers originating from the aggregation of (TR{sub 6}) octahedra via common edges are more frequent than trimers and pentamers, in which the (TR{sub r}) clusters share common faces. - Graphical abstract: Rare earth-metal cluster complexes with endohedral transition metal atoms (TR{sub 6}) may connect via common edges or faces to form dimers, trimers, tetramers and pentamers of which the tetramers are the most prolific. Packing effects and electron counts play an important role. - Highlights: • Rare-earth metal cluster complexes encapsulate transition metal atoms. • Oligomers are built via connection of octahedral clusters via common edges or faces. • Dimers through pentamers with closed structures are known. • Tetramers including a tetrahedron of endohedral atoms are the most prolific.

Alignment and integration of complex networks by hypergraph-based spectral clustering

Science.gov (United States)

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Studies of the charge instabilities in the complex nano-objects: clusters and bio-molecular systems

International Nuclear Information System (INIS)

Manil, B.

2007-11-01

For the last 6 years, my main research works focused on i) the Coulomb instabilities and the fragmentation processes of fullerenes and clusters of fullerenes ii) the stability and the reactivity of complex bio-molecular systems. Concerning the clusters of fullerenes, which are van der Waals type clusters, we have shown that the multiply charged species, obtained in collisions with slow highly charged ions, keep their structural properties but become very good electric conductor. In another hand, with the aim to understand the role of the biologic environment at the molecular scale in the irradiation damage of complex biomolecules, we have studied the charge stabilities of clusters of small biomolecules and the dissociation processes of larger nano-hydrated biomolecules. Theses studies have shown that first, specific molecular recognition mechanisms continue to exist in gas phase and secondly, a small and very simple biochemical environment is enough to change the dynamics of instabilities. (author)

The E. coli monothiol glutaredoxin GrxD forms homodimeric and heterodimeric FeS cluster containing complexes.

Science.gov (United States)

Yeung, N; Gold, B; Liu, N L; Prathapam, R; Sterling, H J; Willams, E R; Butland, G

2011-10-18

Monothiol glutaredoxins (mono-Grx) represent a highly evolutionarily conserved class of proteins present in organisms ranging from prokaryotes to humans. Mono-Grxs have been implicated in iron sulfur (FeS) cluster biosynthesis as potential scaffold proteins and in iron homeostasis via an FeS-containing complex with Fra2p (homologue of E. coli BolA) in yeast and are linked to signal transduction in mammalian systems. However, the function of the mono-Grx in prokaryotes and the nature of an interaction with BolA-like proteins have not been established. Recent genome-wide screens for E. coli genetic interactions reported the synthetic lethality (combination of mutations leading to cell death; mutation of only one of these genes does not) of a grxD mutation when combined with strains defective in FeS cluster biosynthesis (isc operon) functions [Butland, G., et al. (2008) Nature Methods 5, 789-795]. These data connected the only E. coli mono-Grx, GrxD to a potential role in FeS cluster biosynthesis. We investigated GrxD to uncover the molecular basis of this synthetic lethality and observed that GrxD can form FeS-bound homodimeric and BolA containing heterodimeric complexes. These complexes display substantially different spectroscopic and functional properties, including the ability to act as scaffold proteins for intact FeS cluster transfer to the model [2Fe-2S] acceptor protein E. coli apo-ferredoxin (Fdx), with the homodimer being significantly more efficient. In this work, we functionally dissect the potential cellular roles of GrxD as a component of both homodimeric and heterodimeric complexes to ultimately uncover if either of these complexes performs functions linked to FeS cluster biosynthesis. © 2011 American Chemical Society

Discovery of Multiseeded Multimode Formation of Embedded Clusters in the Rosette Molecular Complex

Science.gov (United States)

Li, Jin Zeng; Smith, Michael D.

2005-02-01

An investigation based on data from the spatially complete Two Micron All Sky Survey (2MASS) reveals that a remarkable burst of clustered star formation is taking place throughout the southeast quadrant of the Rosette Molecular Cloud. Compact clusters are forming in a multiseeded mode, in parallel and at various places. In addition, sparse aggregates of embedded young stars are extensively distributed. In this study we report the primary results and implications for high-mass and clustered star formation in giant molecular clouds. In particular, we incorporate for the first time the birth of medium- to low-mass stars into the scenario of sequential formation of OB clusters. Following the emergence of the young OB cluster NGC 2244, a variety of manifestations of forming clusters of medium to high mass appears in the vicinity of the swept-up layer of the H II region as well as farther into the molecular cloud. The embedded clusters appear to form in a structured manner, which suggests they follow tracks laid out by the decay of macroturbulence. We address the possible origins of the turbulence. This leads us to propose a tree model to interpret the neat spatial distribution of clusters within a large section of the Rosette complex. Prominent new-generation OB clusters are identified at the root of the tree pattern.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

Science.gov (United States)

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

Community Clustering Algorithm in Complex Networks Based on Microcommunity Fusion

Directory of Open Access Journals (Sweden)

Jin Qi

2015-01-01

Full Text Available With the further research on physical meaning and digital features of the community structure in complex networks in recent years, the improvement of effectiveness and efficiency of the community mining algorithms in complex networks has become an important subject in this area. This paper puts forward a concept of the microcommunity and gets final mining results of communities through fusing different microcommunities. This paper starts with the basic definition of the network community and applies Expansion to the microcommunity clustering which provides prerequisites for the microcommunity fusion. The proposed algorithm is more efficient and has higher solution quality compared with other similar algorithms through the analysis of test results based on network data set.

STAR CLUSTER COMPLEXES AND THE HOST GALAXY IN THREE H II GALAXIES: Mrk 36, UM 408, AND UM 461

Energy Technology Data Exchange (ETDEWEB)

Lagos, P. [Centro de Astrofisica da Universidade do Porto, Rua das Estrelas, 4150-762 Porto (Portugal); Telles, E. [Observatorio Nacional, Rua Jose Cristino, 77, Rio de Janeiro 20921-400 (Brazil); Nigoche-Netro, A. [Instituto de Astrofisica de Andalucia (IAA), Glorieta de la Astronomia s/n, 18008 Granada (Spain); Carrasco, E. R., E-mail: plagos@astro.up.pt, E-mail: etelles@on.br, E-mail: nigoche@iaa.es, E-mail: rcarrasco@gemini.edu [Gemini Observatory/AURA, Southern Operations Center, Casilla 603, La Serena (Chile)

2011-11-15

We present a stellar population study of three H II galaxies (Mrk 36, UM 408, and UM 461) based on the analysis of new ground-based high-resolution near-infrared J, H, and K{sub p} broadband and Br{gamma} narrowband images obtained with Gemini/NIRI. We identify and determine the relative ages and masses of the elementary star clusters and/or star cluster complexes of the starburst regions in each of these galaxies by comparing the colors with evolutionary synthesis models that include the contribution of stellar continuum, nebular continuum, and emission lines. We found that the current star cluster formation efficiency in our sample of low-luminosity H II galaxies is {approx}10%. Therefore, most of the recent star formation is not in massive clusters. Our findings seem to indicate that the star formation mode in our sample of galaxies is clumpy, and that these complexes are formed by a few massive star clusters with masses {approx}>10{sup 4} M{sub Sun }. The age distribution of these star cluster complexes shows that the current burst started recently and likely simultaneously over short timescales in their host galaxies, triggered by some internal mechanism. Finally, the fraction of the total cluster mass with respect to the low surface brightness (or host galaxy) mass, considering our complete range in ages, is less than 1%.

Gene expression patterns of oxidative phosphorylation complex I subunits are organized in clusters.

Directory of Open Access Journals (Sweden)

Yael Garbian

Full Text Available After the radiation of eukaryotes, the NUO operon, controlling the transcription of the NADH dehydrogenase complex of the oxidative phosphorylation system (OXPHOS complex I, was broken down and genes encoding this protein complex were dispersed across the nuclear genome. Seven genes, however, were retained in the genome of the mitochondrion, the ancient symbiote of eukaryotes. This division, in combination with the three-fold increase in subunit number from bacteria (N = approximately 14 to man (N = 45, renders the transcription regulation of OXPHOS complex I a challenge. Recently bioinformatics analysis of the promoter regions of all OXPHOS genes in mammals supported patterns of co-regulation, suggesting that natural selection favored a mechanism facilitating the transcriptional regulatory control of genes encoding subunits of these large protein complexes. Here, using real time PCR of mitochondrial (mtDNA- and nuclear DNA (nDNA-encoded transcripts in a panel of 13 different human tissues, we show that the expression pattern of OXPHOS complex I genes is regulated in several clusters. Firstly, all mtDNA-encoded complex I subunits (N = 7 share a similar expression pattern, distinct from all tested nDNA-encoded subunits (N = 10. Secondly, two sub-clusters of nDNA-encoded transcripts with significantly different expression patterns were observed. Thirdly, the expression patterns of two nDNA-encoded genes, NDUFA4 and NDUFA5, notably diverged from the rest of the nDNA-encoded subunits, suggesting a certain degree of tissue specificity. Finally, the expression pattern of the mtDNA-encoded ND4L gene diverged from the rest of the tested mtDNA-encoded transcripts that are regulated by the same promoter, consistent with post-transcriptional regulation. These findings suggest, for the first time, that the regulation of complex I subunits expression in humans is complex rather than reflecting global co-regulation.

Irradiation characteristics of metal-cluster-complex ions containing diverse multi-elements with large mass differences

International Nuclear Information System (INIS)

Fujiwara, Yukio; Kondou, Kouji; Teranishi, Yoshikazu; Nonaka, Hidehiko; Saito, Naoaki; Fujimoto, Toshiyuki; Kurokawa, Akira; Ichimura, Shingo; Tomita, Mitsuhiro

2007-01-01

Tetrairidium dodecacarbonyl, Ir 4 (CO) 12 , is a metal cluster complex which has a molecular weight of 1104.9. Using a metal-cluster-complex ion source, the interaction between Ir 4 (CO) n + ions (n=0-12) and silicon substrates was studied at a beam energy ranging from 2keV to 10keV at normal incidence. By adjusting Wien-filter voltage, the influence of CO ligands was investigated. Experimental results showed that sputtering yield of silicon bombarded with Ir 4 (CO) n + ions at 10keV decreased with the number of CO ligands. In the case of 2keV, deposition tended to be suppressed by removing CO ligands from the impinging cluster ions. The influence of CO ligands was explained by considering changes in surface properties caused by the irradiation of Ir 4 (CO) n + ions. It was also found that the bombardment with Ir 4 (CO) 7 + ions at 2.5keV caused deposition on silicon target

Cluster as a Tool to Increase the Competitiveness and Innovative Activity of Enterprises of the Defense Industry Complex

Directory of Open Access Journals (Sweden)

Katrina B. Dobrova

2017-01-01

Full Text Available Purpose: the main goal of the publication is to make a comprehensive study of the possible application of the cluster approach to improve the competitiveness and innovation activity of enterprises of the defense industry complex.Methods: the methodology of the research is based on the collection and analysis of initial data and information, the article uses a systematic approach to the study of socio-economic processes and phenomena. The research is based on modern theory of competition, innovation, as well as the modern paradigm of cluster development of the economy. In preparing the study, practical materials from Corporation “Rostec”.Results: the article gives the notion of cluster, the prospects for the use of the cluster approach to enhance competitiveness and innovation enterprises of the military-industrial complex. It is noted that the activation of interaction with the “civil sector” is particularly relevant in the context of the reduction of the state defense order, and the theory and practice of cluster management offers a number of forms of cluster interaction between the enterprises of the defense industry and the civil sector. It is emphasized that the development of cluster mechanisms can solve a number of problems related to the insufficient financial stability of defense industry enterprises in the context of a reduction in the state defense order, low innovation activity and the lack of developed models of interaction with small innovative enterprises. Ultimately, the use of cluster mechanisms in the development of defense enterprises is intended to enhance the competitiveness of the complex, both nationally and globally. It is stated that the existing clusters are not able to fully solve a number of specific tasks related to the diversification of integrated defense industry structures. Attention is drawn to the fact that existing clusters are not able to fully solve a number of specific tasks related to the

Interdependence of laminin-mediated clustering of lipid rafts and the dystrophin complex in astrocytes.

Science.gov (United States)

Noël, Geoffroy; Tham, Daniel Kai Long; Moukhles, Hakima

2009-07-17

Astrocyte endfeet surrounding blood vessels are active domains involved in water and potassium ion transport crucial to the maintenance of water and potassium ion homeostasis in brain. A growing body of evidence points to a role for dystroglycan and its interaction with perivascular laminin in the targeting of the dystrophin complex and the water-permeable channel, aquaporin 4 (AQP4), at astrocyte endfeet. However, the mechanisms underlying such compartmentalization remain poorly understood. In the present study we found that AQP4 resided in Triton X-100-insoluble fraction, whereas dystroglycan was recovered in the soluble fraction in astrocytes. Cholesterol depletion resulted in the translocation of a pool of AQP4 to the soluble fraction indicating that its distribution is indeed associated with cholesterol-rich membrane domains. Upon laminin treatment AQP4 and the dystrophin complex, including dystroglycan, reorganized into laminin-associated clusters enriched for the lipid raft markers GM1 and flotillin-1 but not caveolin-1. Reduced diffusion rates of GM1 in the laminin-induced clusters were indicative of the reorganization of raft components in these domains. In addition, both cholesterol depletion and dystroglycan silencing reduced the number and area of laminin-induced clusters of GM1, AQP4, and dystroglycan. These findings demonstrate the interdependence between laminin binding to dystroglycan and GM1-containing lipid raft reorganization and provide novel insight into the dystrophin complex regulation of AQP4 polarization in astrocytes.

Clusters and how to make it work : Cluster Strategy Toolkit

NARCIS (Netherlands)

Manickam, Anu; van Berkel, Karel

2014-01-01

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

MASSIVE STARS IN THE Cl 1813-178 CLUSTER: AN EPISODE OF MASSIVE STAR FORMATION IN THE W33 COMPLEX

International Nuclear Information System (INIS)

Messineo, Maria; Davies, Ben; Figer, Donald F.; Trombley, Christine; Kudritzki, R. P.; Valenti, Elena; Najarro, F.; Michael Rich, R.

2011-01-01

Young massive (M > 10 4 M sun ) stellar clusters are a good laboratory to study the evolution of massive stars. Only a dozen of such clusters are known in the Galaxy. Here, we report about a new young massive stellar cluster in the Milky Way. Near-infrared medium-resolution spectroscopy with UIST on the UKIRT telescope and NIRSPEC on the Keck telescope, and X-ray observations with the Chandra and XMM satellites, of the Cl 1813-178 cluster confirm a large number of massive stars. We detected 1 red supergiant, 2 Wolf-Rayet stars, 1 candidate luminous blue variable, 2 OIf, and 19 OB stars. Among the latter, twelve are likely supergiants, four giants, and the faintest three dwarf stars. We detected post-main-sequence stars with masses between 25 and 100 M sun . A population with age of 4-4.5 Myr and a mass of ∼10, 000 M sun can reproduce such a mixture of massive evolved stars. This massive stellar cluster is the first detection of a cluster in the W33 complex. Six supernova remnants and several other candidate clusters are found in the direction of the same complex.

Segregation and Clustering Effects on Complex Boron Redistribution in Strongly Doped Polycrystalline-Silicon Layers

International Nuclear Information System (INIS)

Abadli, S.; Mansour, F.

2011-01-01

This work deals with the investigation of the complex phenomenon of boron (B) transient enhanced diffusion (TED) in strongly implanted silicon (Si) layers. It concerns the instantaneous influences of the strong B concentrations, the Si layers crystallization, the clustering and the B trapping/segregation during thermal post-implantation annealing. We have used Si thin layers obtained from disilane (Si2H6) by low pressure chemical vapor deposition (LPCVD) and then B implanted with a dose of 4 x 1015 atoms/cm2 at an energy of 15 keV. To avoid long redistributions, thermal annealing was carried out at relatively low-temperatures (700, 750 and 800 'deg'C) for various short-times ranging between 1 and 30 minutes. To investigate the experimental secondary ion mass spectroscopy (SIMS) doping profiles, a redistribution model well adapted to the particular structure of Si-LPCVD layers and to the effects of strong-concentrations has been established. The good adjustment of the simulated profiles with the experimental SIMS profiles allowed a fundamental understanding about the instantaneous physical phenomena giving and disturbing the TED process in strongly doped Si-LPCVD layers. It was found that boron TED is strongly affected by the simultaneous complex kinetics of clustering, crystallization, trapping and segregation during annealing. The fast formation of small Si-B clusters enhances the B diffusivity whereas the evolution of the clusters and segregation reduce this enhancement. (author)

Towards a methodology for cluster searching to provide conceptual and contextual "richness" for systematic reviews of complex interventions: case study (CLUSTER).

Science.gov (United States)

Booth, Andrew; Harris, Janet; Croot, Elizabeth; Springett, Jane; Campbell, Fiona; Wilkins, Emma

2013-09-28

Systematic review methodologies can be harnessed to help researchers to understand and explain how complex interventions may work. Typically, when reviewing complex interventions, a review team will seek to understand the theories that underpin an intervention and the specific context for that intervention. A single published report from a research project does not typically contain this required level of detail. A review team may find it more useful to examine a "study cluster"; a group of related papers that explore and explain various features of a single project and thus supply necessary detail relating to theory and/or context.We sought to conduct a preliminary investigation, from a single case study review, of techniques required to identify a cluster of related research reports, to document the yield from such methods, and to outline a systematic methodology for cluster searching. In a systematic review of community engagement we identified a relevant project - the Gay Men's Task Force. From a single "key pearl citation" we conducted a series of related searches to find contextually or theoretically proximate documents. We followed up Citations, traced Lead authors, identified Unpublished materials, searched Google Scholar, tracked Theories, undertook ancestry searching for Early examples and followed up Related projects (embodied in the CLUSTER mnemonic). Our structured, formalised procedure for cluster searching identified useful reports that are not typically identified from topic-based searches on bibliographic databases. Items previously rejected by an initial sift were subsequently found to inform our understanding of underpinning theory (for example Diffusion of Innovations Theory), context or both. Relevant material included book chapters, a Web-based process evaluation, and peer reviewed reports of projects sharing a common ancestry. We used these reports to understand the context for the intervention and to explore explanations for its relative

FRONTIER FIELDS CLUSTERS: DEEP CHANDRA OBSERVATIONS OF THE COMPLEX MERGER MACS J1149.6+2223

Energy Technology Data Exchange (ETDEWEB)

Ogrean, G. A.; Weeren, R. J. van; Jones, C.; Forman, W.; Andrade-Santos, F.; Murray, S. S.; Nulsen, P.; Bulbul, E.; Kraft, R.; Randall, S. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Dawson, W. A. [Lawrence Livermore National Lab, 7000 East Avenue, Livermore, CA 94550 (United States); Golovich, N. [University of California, One Shields Avenue, Davis, CA 95616 (United States); Roediger, E. [Astronomy and Astrophysics Section, Dublin Institute for Advanced Studies, 31 Fitzwilliam Place, Dublin 2 (Ireland); Zitrin, A.; Sayers, J. [Cahill Center for Astronomy and Astrophysics, California Institute of Technology, MC 249-17, Pasadena, CA 91125 (United States); Goulding, A. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States); Umetsu, K. [Institute of Astronomy and Astrophysics, Academia Sinica, P.O. Box 23-141, Taipei 10617, Taiwan (China); Mroczkowski, T. [U.S. Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, DC 20375 (United States); Bonafede, A. [Hamburger Sternwarte, Universität Hamburg, Gojenbergsweg 112, D-21029 Hamburg (Germany); Churazov, E., E-mail: gogrean@cfa.harvard.edu [Max Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, D-85741, Garching (Germany); and others

2016-03-10

The Hubble Space Telescope Frontier Fields cluster MACS J1149.6+2223 is one of the most complex merging clusters, believed to consist of four dark matter halos. We present results from deep (365 ks) Chandra observations of the cluster, which reveal the most distant cold front (z  =  0.544) discovered to date. In the cluster outskirts, we also detect hints of a surface brightness edge that could be the bow shock preceding the cold front. The substructure analysis of the cluster identified several components with large relative radial velocities, thus indicating that at least some collisions occur almost along the line of sight. The inclination of the mergers with respect to the plane of the sky poses significant observational challenges at X-ray wavelengths. MACS J1149.6+2223 possibly hosts a steep-spectrum radio halo. If the steepness of the radio halo is confirmed, then the radio spectrum, combined with the relatively regular ICM morphology, could indicate that MACS J1149.6+2223 is an old merging cluster.

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

Science.gov (United States)

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

2017-11-01

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

Clusters and how to make it work : toolkit for cluster strategy

NARCIS (Netherlands)

Manickam, Anu; van Berkel, Karel

2013-01-01

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

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

Science.gov (United States)

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

2015-03-01

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

Regulation of human Nfu activity in Fe-S cluster delivery-characterization of the interaction between Nfu and the HSPA9/Hsc20 chaperone complex.

Science.gov (United States)

Wachnowsky, Christine; Liu, Yushi; Yoon, Taejin; Cowan, J A

2018-01-01

Iron-sulfur cluster biogenesis is a complex, but highly regulated process that involves de novo cluster formation from iron and sulfide ions on a scaffold protein, and subsequent delivery to final targets via a series of Fe-S cluster-binding carrier proteins. The process of cluster release from the scaffold/carrier for transfer to the target proteins may be mediated by a dedicated Fe-S cluster chaperone system. In human cells, the chaperones include heat shock protein HSPA9 and the J-type chaperone Hsc20. While the role of chaperones has been somewhat clarified in yeast and bacterial systems, many questions remain over their functional roles in cluster delivery and interactions with a variety of human Fe-S cluster proteins. One such protein, Nfu, has recently been recognized as a potential interaction partner of the chaperone complex. Herein, we examined the ability of human Nfu to function as a carrier by interacting with the human chaperone complex. Human Nfu is shown to bind to both chaperone proteins with binding affinities similar to those observed for IscU binding to the homologous HSPA9 and Hsc20, while Nfu can also stimulate the ATPase activity of HSPA9. Additionally, the chaperone complex was able to promote Nfu function by enhancing the second-order rate constants for Fe-S cluster transfer to target proteins and providing directionality in cluster transfer from Nfu by eliminating promiscuous transfer reactions. Together, these data support a hypothesis in which Nfu can serve as an alternative carrier protein for chaperone-mediated cluster release and delivery in Fe-S cluster biogenesis and trafficking. © 2017 Federation of European Biochemical Societies.

Young stellar population and star formation history ofW4 HII region/Cluster Complex

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Panwar, Neelam

2018-04-01

The HII region/cluster complex has been a subject of numerous investigations to study the feedback effect of massive stars on their surroundings. Massive stars not only alter the morphology of the parental molecular clouds, but also influence star formation, circumstellar disks and the mass function of low-mass stars in their vicinity. However, most of the studies of low-mass stellar content of the HII regions are limited only to the nearby regions. We study the star formation in the W4 HII region using deep optical observations obtained with the archival data from Canada - France - Hawaii Telescope, Two-Micron All Sky Survey, Spitzer, Herschel and Chandra. We investigate the spatial distribution of young stellar objects in the region, their association with the remnant molecular clouds, and search for the clustering to establish the sites of recent star formation. Our analysis suggests that the influence of massive stars on circumstellar disks is significant only to thei! r immediate neighborhood. The spatial correlation of the young stars with the distribution of gas and dust of the complex indicate that the clusters would have formed in a large filamentary cloud. The observing facilities at the 3.6-m Devasthal Optical Telescope (DOT), providing high-resolution spectral and imaging capabilities, will fulfill the major objectives in the study of HII regions.

Text Clustering Algorithm Based on Random Cluster Core

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Huang Long-Jun

2016-01-01

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

Personalized PageRank Clustering: A graph clustering algorithm based on random walks

Science.gov (United States)

A. Tabrizi, Shayan; Shakery, Azadeh; Asadpour, Masoud; Abbasi, Maziar; Tavallaie, Mohammad Ali

2013-11-01

Graph clustering has been an essential part in many methods and thus its accuracy has a significant effect on many applications. In addition, exponential growth of real-world graphs such as social networks, biological networks and electrical circuits demands clustering algorithms with nearly-linear time and space complexity. In this paper we propose Personalized PageRank Clustering (PPC) that employs the inherent cluster exploratory property of random walks to reveal the clusters of a given graph. We combine random walks and modularity to precisely and efficiently reveal the clusters of a graph. PPC is a top-down algorithm so it can reveal inherent clusters of a graph more accurately than other nearly-linear approaches that are mainly bottom-up. It also gives a hierarchy of clusters that is useful in many applications. PPC has a linear time and space complexity and has been superior to most of the available clustering algorithms on many datasets. Furthermore, its top-down approach makes it a flexible solution for clustering problems with different requirements.

clusterMaker: a multi-algorithm clustering plugin for Cytoscape

Directory of Open Access Journals (Sweden)

Morris John H

2011-11-01

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

Adaptive capacity of geographical clusters: Complexity science and network theory approach

Science.gov (United States)

Albino, Vito; Carbonara, Nunzia; Giannoccaro, Ilaria

This paper deals with the adaptive capacity of geographical clusters (GCs), that is a relevant topic in the literature. To address this topic, GC is considered as a complex adaptive system (CAS). Three theoretical propositions concerning the GC adaptive capacity are formulated by using complexity theory. First, we identify three main properties of CAS s that affect the adaptive capacity, namely the interconnectivity, the heterogeneity, and the level of control, and define how the value of these properties influence the adaptive capacity. Then, we associate these properties with specific GC characteristics so obtaining the key conditions of GCs that give them the adaptive capacity so assuring their competitive advantage. To test these theoretical propositions, a case study on two real GCs is carried out. The considered GCs are modeled as networks where firms are nodes and inter-firms relationships are links. Heterogeneity, interconnectivity, and level of control are considered as network properties and thus measured by using the methods of the network theory.

CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

Science.gov (United States)

Franke, R.

2016-11-01

In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

CHEMICAL ABUNDANCES IN NGC 5053: A VERY METAL-POOR AND DYNAMICALLY COMPLEX GLOBULAR CLUSTER

Energy Technology Data Exchange (ETDEWEB)

Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico [Astronomy Department, Indiana University, Bloomington, IN 47405 (United States)

2015-05-10

NGC 5053 provides a rich environment to test our understanding of the complex evolution of globular clusters (GCs). Recent studies have found that this cluster has interesting morphological features beyond the typical spherical distribution of GCs, suggesting that external tidal effects have played an important role in its evolution and current properties. Additionally, simulations have shown that NGC 5053 could be a likely candidate to belong to the Sagittarius dwarf galaxy (Sgr dSph) stream. Using the Wisconsin–Indiana–Yale–NOAO–Hydra multi-object spectrograph, we have collected high quality (signal-to-noise ratio ∼ 75–90), medium-resolution spectra for red giant branch stars in NGC 5053. Using these spectra we have measured the Fe, Ca, Ti, Ni, Ba, Na, and O abundances in the cluster. We measure an average cluster [Fe/H] abundance of −2.45 with a standard deviation of 0.04 dex, making NGC 5053 one of the most metal-poor GCs in the Milky Way (MW). The [Ca/Fe], [Ti/Fe], and [Ba/Fe] we measure are consistent with the abundances of MW halo stars at a similar metallicity, with alpha-enhanced ratios and slightly depleted [Ba/Fe]. The Na and O abundances show the Na–O anti-correlation found in most GCs. From our abundance analysis it appears that NGC 5053 is at least chemically similar to other GCs found in the MW. This does not, however, rule out NGC 5053 being associated with the Sgr dSph stream.

Chemical Abundances in NGC 5053: A Very Metal-poor and Dynamically Complex Globular Cluster

Science.gov (United States)

Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico

2015-05-01

NGC 5053 provides a rich environment to test our understanding of the complex evolution of globular clusters (GCs). Recent studies have found that this cluster has interesting morphological features beyond the typical spherical distribution of GCs, suggesting that external tidal effects have played an important role in its evolution and current properties. Additionally, simulations have shown that NGC 5053 could be a likely candidate to belong to the Sagittarius dwarf galaxy (Sgr dSph) stream. Using the Wisconsin-Indiana-Yale-NOAO-Hydra multi-object spectrograph, we have collected high quality (signal-to-noise ratio ˜ 75-90), medium-resolution spectra for red giant branch stars in NGC 5053. Using these spectra we have measured the Fe, Ca, Ti, Ni, Ba, Na, and O abundances in the cluster. We measure an average cluster [Fe/H] abundance of -2.45 with a standard deviation of 0.04 dex, making NGC 5053 one of the most metal-poor GCs in the Milky Way (MW). The [Ca/Fe], [Ti/Fe], and [Ba/Fe] we measure are consistent with the abundances of MW halo stars at a similar metallicity, with alpha-enhanced ratios and slightly depleted [Ba/Fe]. The Na and O abundances show the Na-O anti-correlation found in most GCs. From our abundance analysis it appears that NGC 5053 is at least chemically similar to other GCs found in the MW. This does not, however, rule out NGC 5053 being associated with the Sgr dSph stream.

Deficiency of the iron-sulfur clusters of mitochondrial reduced nicotinamide-adenine dinucleotide-ubiquinone oxidoreductase (complex I) in an infant with congenital lactic acidosis.

Science.gov (United States)

Moreadith, R W; Batshaw, M L; Ohnishi, T; Kerr, D; Knox, B; Jackson, D; Hruban, R; Olson, J; Reynafarje, B; Lehninger, A L

1984-09-01

We report the case of an infant with hypoglycemia, progressive lactic acidosis, an increased serum lactate/pyruvate ratio, and elevated plasma alanine, who had a moderate to profound decrease in the ability of mitochondria from four organs to oxidize pyruvate, malate plus glutamate, citrate, and other NAD+-linked respiratory substrates. The capacity to oxidize the flavin adenine dinucleotide-linked substrate, succinate, was normal. The most pronounced deficiency was in skeletal muscle, the least in kidney mitochondria. Enzymatic assays on isolated mitochondria ruled out defects in complexes II, III, and IV of the respiratory chain. Further studies showed that the defect was localized in the inner membrane mitochondrial NADH-ubiquinone oxidoreductase (complex I). When ferricyanide was used as an artificial electron acceptor, complex I activity was normal, indicating that electrons from NADH could reduce the flavin mononucleotide cofactor. However, electron paramagnetic resonance spectroscopy performed on liver submitochondrial particles showed an almost total loss of the iron-sulfur clusters characteristic of complex I, whereas normal signals were noted for other mitochondrial iron-sulfur clusters. This infant is presented as the first reported case of congenital lactic acidosis caused by a deficiency of the iron-sulfur clusters of complex I of the mitochondrial electron transport chain.

NEW CONSTRAINTS ON A COMPLEX RELATION BETWEEN GLOBULAR CLUSTER COLORS AND ENVIRONMENT

Energy Technology Data Exchange (ETDEWEB)

Powalka, Mathieu; Lançon, Ariane [Observatoire Astronomique de Strasbourg, Université de Strasbourg, CNRS, UMR 7550, 11 rue de l’Université, F-67000 Strasbourg (France); Puzia, Thomas H.; Alamo-Martínez, Karla; Ángel, Simón [Institute of Astrophysics, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago (Chile); Peng, Eric W.; Lim, Sungsoon [Department of Astronomy, Peking University, Beijing 100871 (China); Schönebeck, Frederik; Grebel, Eva K. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstraße 12-14, D-69120 Heidelberg (Germany); Blakeslee, John P.; Côté, Patrick; Ferrarese, Laura; Gwyn, S. D. J. [Herzberg Institute of Astrophysics, National Research Council of Canada, Victoria, BC V9E 2E7 (Canada); Cuillandre, Jean-Charles; Duc, Pierre-Alain [AIM Paris Saclay, CNRS/INSU, CEA/Irfu, Université Paris Diderot, Orme des Merisiers, F-91191 Gif-sur-Yvette Cedex (France); Durrell, Patrick [Department of Physics and Astronomy, Youngstown State University, One University Plaza, Youngstown, OH 44555 (United States); Guhathakurta, Puragra [UCO/Lick Observatory, Department of Astronomy and Astrophysics, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064 (United States); Kuntschner, Harald, E-mail: mathieu.powalka@astro.unistra.fr [European Southern Observatory, Karl-Schwarzschild-Str. 2, D-85748 Garching (Germany); and others

2016-09-20

We present an analysis of high-quality photometry for globular clusters (GCs) in the Virgo cluster core region, based on data from the Next Generation Virgo Cluster Survey (NGVS) pilot field, and in the Milky Way (MW), based on Very Large Telescope/X-Shooter spectrophotometry. We find significant discrepancies in color–color diagrams between sub-samples from different environments, confirming that the environment has a strong influence on the integrated colors of GCs. GC color distributions along a single color are not sufficient to capture the differences we observe in color–color space. While the average photometric colors become bluer with increasing radial distance to the cD galaxy M87, we also find a relation between the environment and the slope and intercept of the color–color relations. A denser environment seems to produce a larger dynamic range in certain color indices. We argue that these results are not due solely to differential extinction, Initial Mass Function variations, calibration uncertainties, or overall age/metallicity variations. We therefore suggest that the relation between the environment and GC colors is, at least in part, due to chemical abundance variations, which affect stellar spectra and stellar evolution tracks. Our results demonstrate that stellar population diagnostics derived from model predictions which are calibrated on one particular sample of GCs may not be appropriate for all extragalactic GCs. These results advocate a more complex model of the assembly history of GC systems in massive galaxies that goes beyond the simple bimodality found in previous decades.

NEW CONSTRAINTS ON A COMPLEX RELATION BETWEEN GLOBULAR CLUSTER COLORS AND ENVIRONMENT

International Nuclear Information System (INIS)

Powalka, Mathieu; Lançon, Ariane; Puzia, Thomas H.; Alamo-Martínez, Karla; Ángel, Simón; Peng, Eric W.; Lim, Sungsoon; Schönebeck, Frederik; Grebel, Eva K.; Blakeslee, John P.; Côté, Patrick; Ferrarese, Laura; Gwyn, S. D. J.; Cuillandre, Jean-Charles; Duc, Pierre-Alain; Durrell, Patrick; Guhathakurta, Puragra; Kuntschner, Harald

2016-01-01

We present an analysis of high-quality photometry for globular clusters (GCs) in the Virgo cluster core region, based on data from the Next Generation Virgo Cluster Survey (NGVS) pilot field, and in the Milky Way (MW), based on Very Large Telescope/X-Shooter spectrophotometry. We find significant discrepancies in color–color diagrams between sub-samples from different environments, confirming that the environment has a strong influence on the integrated colors of GCs. GC color distributions along a single color are not sufficient to capture the differences we observe in color–color space. While the average photometric colors become bluer with increasing radial distance to the cD galaxy M87, we also find a relation between the environment and the slope and intercept of the color–color relations. A denser environment seems to produce a larger dynamic range in certain color indices. We argue that these results are not due solely to differential extinction, Initial Mass Function variations, calibration uncertainties, or overall age/metallicity variations. We therefore suggest that the relation between the environment and GC colors is, at least in part, due to chemical abundance variations, which affect stellar spectra and stellar evolution tracks. Our results demonstrate that stellar population diagnostics derived from model predictions which are calibrated on one particular sample of GCs may not be appropriate for all extragalactic GCs. These results advocate a more complex model of the assembly history of GC systems in massive galaxies that goes beyond the simple bimodality found in previous decades.

Photo-induced transformation process at gold clusters-semiconductor interface: Implications for the complexity of gold clusters-based photocatalysis

Science.gov (United States)

Liu, Siqi; Xu, Yi-Jun

2016-03-01

The recent thrust in utilizing atomically precise organic ligands protected gold clusters (Au clusters) as photosensitizer coupled with semiconductors for nano-catalysts has led to the claims of improved efficiency in photocatalysis. Nonetheless, the influence of photo-stability of organic ligands protected-Au clusters at the Au/semiconductor interface on the photocatalytic properties remains rather elusive. Taking Au clusters-TiO2 composites as a prototype, we for the first time demonstrate the photo-induced transformation of small molecular-like Au clusters to larger metallic Au nanoparticles under different illumination conditions, which leads to the diverse photocatalytic reaction mechanism. This transformation process undergoes a diffusion/aggregation mechanism accompanied with the onslaught of Au clusters by active oxygen species and holes resulting from photo-excited TiO2 and Au clusters. However, such Au clusters aggregation can be efficiently inhibited by tuning reaction conditions. This work would trigger rational structural design and fine condition control of organic ligands protected-metal clusters-semiconductor composites for diverse photocatalytic applications with long-term photo-stability.

Production of complex particles in low energy spallation and in fragmentation reactions by in-medium random clusterization

International Nuclear Information System (INIS)

Lacroix, D.; Durand, D.

2005-09-01

Rules for in-medium complex particle production in nuclear reactions are proposed. These rules have been implemented in two models to simulate nucleon-nucleus and nucleus-nucleus reactions around the Fermi energy. Our work emphasizes the effect of randomness in cluster formation, the importance of the nucleonic Fermi motion as well as the role of conservation laws. The concepts of total available phase-space and explored phase-space under constraint imposed by the reaction are clarified. The compatibility of experimental observations with a random clusterization is illustrated in a schematic scenario of a proton-nucleus collision. The role of randomness under constraint is also illustrated in the nucleus-nucleus case. (authors)

Generation of clusters in complex dynamical networks via pinning control

International Nuclear Information System (INIS)

Li Kezan; Fu Xinchu; Small, Michael

2008-01-01

Many real-world networks show community structure, i.e., groups (or clusters) of nodes that have a high density of links within them but with a lower density of links between them. In this paper, by applying feedback injections to a fraction of network nodes, various clusters are synchronized independently according to the community structure generated by the group partition of the network (cluster synchronization). This control is achieved by pinning (i.e. applying linear feedback control) to a subset of the network nodes. Those pinned nodes are selected not randomly but according to the topological structure of communities of a given network. Specifically, for a given group partition of a network, those nodes with direct connections between groups must be pinned in order to achieve cluster synchronization. Both the local stability and global stability of cluster synchronization are investigated. Taking the tree-shaped network and the most modular network as two particular examples, we illustrate in detail how the pinning strategy influences the generation of clusters. The simulations verify the efficiency of the pinning schemes used in this paper

The Limited Role of Number of Nested Syntactic Dependencies in Accounting for Processing Cost: Evidence from German Simplex and Complex Verbal Clusters

Directory of Open Access Journals (Sweden)

Markus Bader

2018-01-01

Full Text Available This paper presents three acceptability experiments investigating German verb-final clauses in order to explore possible sources of sentence complexity during human parsing. The point of departure was De Vries et al.'s (2011 generalization that sentences with three or more crossed or nested dependencies are too complex for being processed by the human parsing mechanism without difficulties. This generalization is partially based on findings from Bach et al. (1986 concerning the acceptability of complex verb clusters in German and Dutch. The first experiment tests this generalization by comparing two sentence types: (i sentences with three nested dependencies within a single clause that contains three verbs in a complex verb cluster; (ii sentences with four nested dependencies distributed across two embedded clauses, one center-embedded within the other, each containing a two-verb cluster. The results show that sentences with four nested dependencies are judged as acceptable as control sentences with only two nested dependencies, whereas sentences with three nested dependencies are judged as only marginally acceptable. This argues against De Vries et al.'s (2011 claim that the human parser can process no more than two nested dependencies. The results are used to refine the Verb-Cluster Complexity Hypothesis of Bader and Schmid (2009a. The second and the third experiment investigate sentences with four nested dependencies in more detail in order to explore alternative sources of sentence complexity: the number of predicted heads to be held in working memory (storage cost in terms of the Dependency Locality Theory [DLT], Gibson, 2000 and the length of the involved dependencies (integration cost in terms of the DLT. Experiment 2 investigates sentences for which storage cost and integration cost make conflicting predictions. The results show that storage cost outweighs integration cost. Experiment 3 shows that increasing integration cost in sentences

Uncovering and testing the fuzzy clusters based on lumped Markov chain in complex network.

Science.gov (United States)

Jing, Fan; Jianbin, Xie; Jinlong, Wang; Jinshuai, Qu

2013-01-01

Identifying clusters, namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. By means of a lumped Markov chain model of a random walker, we propose two novel ways of inferring the lumped markov transition matrix. Furthermore, some useful results are proposed based on the analysis of the properties of the lumped Markov process. To find the best partition of complex networks, a novel framework including two algorithms for network partition based on the optimal lumped Markovian dynamics is derived to solve this problem. The algorithms are constructed to minimize the objective function under this framework. It is demonstrated by the simulation experiments that our algorithms can efficiently determine the probabilities with which a node belongs to different clusters during the learning process and naturally supports the fuzzy partition. Moreover, they are successfully applied to real-world network, including the social interactions between members of a karate club.

Calcium EXAFS establishes the Mn-Ca cluster in the oxygen-evolving complex of Photosystem II

Energy Technology Data Exchange (ETDEWEB)

Cinco, Roehl M.; McFarlane Holman, Karen L.; Robblee, John H.; Yano, Junko; Pizarro, Shelly A.; Bellacchio, Emanuele; Sauer, Kenneth; Yachandra, Vittal K.

2002-08-02

The proximity of Ca to the Mn cluster of the photosynthetic water-oxidation complex is demonstrated by X-ray absorption spectroscopy. We have collected EXAFS data at the Ca K-edge using active PS II membrane samples that contain approximately 2 Ca per 4 Mn. These samples are much less perturbed than previously investigated Sr-substituted samples, which were prepared subsequent to Ca depletion. The new Ca EXAFS clearly shows backscattering from Mn at 3.4 angstroms, a distance that agrees with that surmised from previously recorded Mn EXAFS. This result is also consistent with earlier related experiments at the Sr K-edge, using samples that contained functional Sr, that show Mn is {approx}; 3.5 angstroms distant from Sr. The totality of the evidence clearly advances the notion that the catalytic center of oxygen evolution is a Mn-Ca heteronuclear cluster.

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

Science.gov (United States)

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

Determining characteristic principal clusters in the “cluster-plus-glue-atom” model

International Nuclear Information System (INIS)

Du, Jinglian; Wen, Bin; 2NeT Lab, Wilfrid Laurier University, Waterloo, 75 University Ave West, Ontario N2L 3C5 (Canada))" data-affiliation=" (M2NeT Lab, Wilfrid Laurier University, Waterloo, 75 University Ave West, Ontario N2L 3C5 (Canada))" >Melnik, Roderick; Kawazoe, Yoshiyuki

2014-01-01

The “cluster-plus-glue-atom” model can easily describe the structure of complex metallic alloy phases. However, the biggest obstacle limiting the application of this model is that it is difficult to determine the characteristic principal cluster. In the case when interatomic force constants (IFCs) inside the cluster lead to stronger interaction than the interaction between the clusters, a new rule for determining the characteristic principal cluster in the “cluster-plus-glue-atom” model has been proposed on the basis of IFCs. To verify this new rule, the alloy phases in Cu–Zr and Al–Ni–Zr systems have been tested, and our results indicate that the present new rule for determining characteristic principal clusters is effective and reliable

Interactions of iron-bound frataxin with ISCU and ferredoxin on the cysteine desulfurase complex leading to Fe-S cluster assembly.

Science.gov (United States)

Cai, Kai; Frederick, Ronnie O; Tonelli, Marco; Markley, John L

2018-06-01

Frataxin (FXN) is involved in mitochondrial iron‑sulfur (Fe-S) cluster biogenesis and serves to accelerate Fe-S cluster formation. FXN deficiency is associated with Friedreich ataxia, a neurodegenerative disease. We have used a combination of isothermal titration calorimetry and multinuclear NMR spectroscopy to investigate interactions among the components of the biological machine that carries out the assembly of iron‑sulfur clusters in human mitochondria. Our results show that FXN tightly binds a single Fe 2+ but not Fe 3+ . While FXN (with or without bound Fe 2+ ) does not bind the scaffold protein ISCU directly, the two proteins interact mutually when each is bound to the cysteine desulfurase complex ([NFS1] 2 :[ISD11] 2 :[Acp] 2 ), abbreviated as (NIA) 2 , where "N" represents the cysteine desulfurase (NFS1), "I" represents the accessory protein (ISD11), and "A" represents acyl carrier protein (Acp). FXN binds (NIA) 2 weakly in the absence of ISCU but more strongly in its presence. Fe 2+ -FXN binds to the (NIA) 2 -ISCU 2 complex without release of iron. However, upon the addition of both l-cysteine and a reductant (either reduced FDX2 or DTT), Fe 2+ is released from FXN as consistent with Fe 2+ -FXN being the proximal source of iron for Fe-S cluster assembly. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2016-12-01

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

Evolution of the C-Type Lectin-Like Receptor Genes of the DECTIN-1 Cluster in the NK Gene Complex

Directory of Open Access Journals (Sweden)

Susanne Sattler

2012-01-01

Full Text Available Pattern recognition receptors are crucial in initiating and shaping innate and adaptive immune responses and often belong to families of structurally and evolutionarily related proteins. The human C-type lectin-like receptors encoded in the DECTIN-1 cluster within the NK gene complex contain prominent receptors with pattern recognition function, such as DECTIN-1 and LOX-1. All members of this cluster share significant homology and are considered to have arisen from subsequent gene duplications. Recent developments in sequencing and the availability of comprehensive sequence data comprising many species showed that the receptors of the DECTIN-1 cluster are not only homologous to each other but also highly conserved between species. Even in Caenorhabditis elegans, genes displaying homology to the mammalian C-type lectin-like receptors have been detected. In this paper, we conduct a comprehensive phylogenetic survey and give an up-to-date overview of the currently available data on the evolutionary emergence of the DECTIN-1 cluster genes.

Complexes of DNA bases and Watson-Crick base pairs with small neutral gold clusters.

Science.gov (United States)

Kryachko, E S; Remacle, F

2005-12-08

The nature of the DNA-gold interaction determines and differentiates the affinity of the nucleobases (adenine, thymine, guanine, and cytosine) to gold. Our preliminary computational study [Kryachko, E. S.; Remacle, F. Nano Lett. 2005, 5, 735] demonstrates that two major bonding factors govern this interaction: the anchoring, either of the Au-N or Au-O type, and the nonconventional N-H...Au hydrogen bonding. In this paper, we offer insight into the nature of nucleobase-gold interactions and provide a detailed characterization of their different facets, i.e., geometrical, energetic, and spectroscopic aspects; the gold cluster size and gold coordination effects; proton affinity; and deprotonation energy. We then investigate how the Watson-Crick DNA pairing patterns are modulated by the nucleobase-gold interaction. We do so in terms of the proton affinities and deprotonation energies of those proton acceptors and proton donors which are involved in the interbase hydrogen bondings. A variety of properties of the most stable Watson-Crick [A x T]-Au3 and [G x C]-Au3 hybridized complexes are described and compared with the isolated Watson-Crick A x T and G x C ones. It is shown that enlarging the gold cluster size to Au6 results in a rather short gold-gold bond in the Watson-Crick interbase region of the [G x C]-Au6 complex that bridges the G x C pair and thus leads to a significant strengthening of G x C pairing.

Is the largest aqueous gold cluster a superatom complex? Electronic structure & optical response of the structurally determined Au146(p-MBA)57.

Science.gov (United States)

López-Lozano, Xóchitl; Plascencia-Villa, G; Calero, G; Whetten, R L; Weissker, Hans-Christian

2017-12-07

The new water-soluble gold cluster Au 146 (p-MBA) 57 , the structure of which has been recently determined at sub-atomic resolution by Vergara et al., is the largest aqueous gold cluster ever structurally determined and likewise the smallest cluster with a stacking fault. The core presents a twinned truncated octahedron, while additional peripheral gold atoms follow a C 2 rotational symmetry. According to the usual counting rules of the superatom complex (SAC) model, the compound attains a number of 92 SAC electrons if the overall net charge is 3- (three additional electrons). As this is the number of electrons required for a major shell closing, the question arises of whether Au 146 (p-MBA) 57 should be regarded as a superatom complex. Starting from the experimental coordinates we have analyzed the structure using density-functional theory. The optimized (relaxed) structure retains all the connectivity of the experimental coordinates, while removing much of its irregularities in interatomic distances, thereby enhancing the C 2 -symmetry feature. On analyzing the angular-momentum-projected states, we show that, despite a small gap, the electronic structure does not exhibit SAC model character. In addition, optical absorption spectra are found to be relatively smooth compared to the example of the Au 144 (SR) 60 cluster. The Au 146 (SR) 57 does not derive its stability from SAC character; it cannot be considered as a superatom complex.

Spanning Tree Based Attribute Clustering

DEFF Research Database (Denmark)

Zeng, Yifeng; Jorge, Cordero Hernandez

2009-01-01

Attribute clustering has been previously employed to detect statistical dependence between subsets of variables. We propose a novel attribute clustering algorithm motivated by research of complex networks, called the Star Discovery algorithm. The algorithm partitions and indirectly discards...... 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...

The Mystery of Globular Clusters: Uncovering the Complexities of Their Evolution

Science.gov (United States)

O'Malley, Erin Marie

In recent years, evidence has grown for the existence of multiple stellar populations in globular clusters (GCs). However, questions remain regarding the nature of these populations. Photometric observations clearly show discrete populations while spectroscopic observations seem to show a continuous spread. This dissertation provides steps to better understanding GCs and the complexities associated with their evolution. Calibration of stellar evolution models at low metallicity is necessary for comparison to GCs. Accurate abundances of metal-poor subdwarfs are determined and used in this calibration. A Monte Carlo analysis is then performed in order to determine accurate distances, absolute ages, and integrated orbital trajectories for 24 GCs. These results are of critical importance as they not only incorporate the observational uncertainty, but also the uncertainty incurred by the models themselves. Lastly, high resolution spectra of three GCs (NGC 6681, NGC 6584 and NGC 7099) are obtained for a detailed abundance analysis of red giant branch stars. The high resolution and signal-to-noise achieved in these observations allows for the discovery of a statistically significant Na-O anticorrelation in all three clusters, the populations of which agree with those from photometric observations. Although we cannot determine precisely the nature of the polluters that were the predecessors to the enhanced populations, we do know that both s-process and r-process mechanisms contributed to the evolution and these results can be used to help constrain future models of GC polluter candidates.

Data clustering algorithms and applications

CERN Document Server

Aggarwal, Charu C

2013-01-01

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

Metal Sulfide Cluster Complexes and their Biogeochemical Importance in the Environment

International Nuclear Information System (INIS)

Luther, George W.; Rickard, David T.

2005-01-01

Aqueous clusters of FeS, ZnS and CuS constitute a major fraction of the dissolved metal load in anoxic oceanic, sedimentary, freshwater and deep ocean vent environments. Their ubiquity explains how metals are transported in anoxic environmental systems. Thermodynamic and kinetic considerations show that they have high stability in oxic aqueous environments, and are also a significant fraction of the total metal load in oxic river waters. Molecular modeling indicates that the clusters are very similar to the basic structural elements of the first condensed phase forming from aqueous solutions in the Fe-S, Zn-S and Cu-S systems. The structure of the first condensed phase is determined by the structure of the cluster in solution. This provides an alternative explanation of Ostwald's Rule, where the most soluble, metastable phases form before the stable phases. For example, in the case of FeS, we showed that the first condensed phase is nanoparticulate, metastable mackinawite with a particle size of 2 nm consisting of about 150 FeS subunits, representing the end of a continuum between aqueous FeS clusters and condensed material. These metal sulfide clusters and nanoparticles are significant in biogeochemistry. Metal sulfide clusters reduce sulfide and metal toxicity and help drive ecology. FeS cluster formation drives vent ecology and AgS cluster formation detoxifies Ag in Daphnia magna neonates. We also note a new reaction between FeS and DNA and discuss the potential role of FeS clusters in denaturing DNA

Comparison of Degrees of Potential-Energy-Surface Anharmonicity for Complexes and Clusters with Hydrogen Bonds

Science.gov (United States)

Kozlovskaya, E. N.; Doroshenko, I. Yu.; Pogorelov, V. E.; Vaskivskyi, Ye. V.; Pitsevich, G. A.

2018-01-01

Previously calculated multidimensional potential-energy surfaces of the MeOH monomer and dimer, water dimer, malonaldehyde, formic acid dimer, free pyridine-N-oxide/trichloroacetic acid complex, and protonated water dimer were analyzed. The corresponding harmonic potential-energy surfaces near the global minima were constructed for series of clusters and complexes with hydrogen bonds of different strengths based on the behavior of the calculated multidimensional potential-energy surfaces. This enabled the introduction of an obvious anharmonicity parameter for the calculated potential-energy surfaces. The anharmonicity parameter was analyzed as functions of the size of the analyzed area near the energy minimum, the number of points over which energies were compared, and the dimensionality of the solved vibrational problem. Anharmonicity parameters for potential-energy surfaces in complexes with strong, medium, and weak H-bonds were calculated under identical conditions. The obtained anharmonicity parameters were compared with the corresponding diagonal anharmonicity constants for stretching vibrations of the bridging protons and the lengths of the hydrogen bridges.

Large-Scale Multi-Dimensional Document Clustering on GPU Clusters

Energy Technology Data Exchange (ETDEWEB)

Cui, Xiaohui [ORNL; Mueller, Frank [North Carolina State University; Zhang, Yongpeng [ORNL; Potok, Thomas E [ORNL

2010-01-01

Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulation resembling the flocking behavior of birds in nature. This method is superior to other clustering algorithms, including k-means, in the sense that the outcome is not sensitive to the initial state. One limitation of this approach is that the algorithmic complexity is inherently quadratic in the number of documents. As a result, execution time becomes a bottleneck with large number of documents. In this paper, we assess the benefits of exploiting the computational power of Beowulf-like clusters equipped with contemporary Graphics Processing Units (GPUs) as a means to significantly reduce the runtime of flocking-based document clustering. Our framework scales up to over one million documents processed simultaneously in a sixteennode GPU cluster. Results are also compared to a four-node cluster with higher-end GPUs. On these clusters, we observe 30X-50X speedups, which demonstrates the potential of GPU clusters to efficiently solve massive data mining problems. Such speedups combined with the scalability potential and accelerator-based parallelization are unique in the domain of document-based data mining, to the best of our knowledge.

Clustering biomolecular complexes by residue contacts similarity

NARCIS (Netherlands)

Garcia Lopes Maia Rodrigues, João; Trellet, Mikaël; Schmitz, Christophe; Kastritis, Panagiotis; Karaca, Ezgi; Melquiond, Adrien S J; Bonvin, Alexandre M J J; Garcia Lopes Maia Rodrigues, João

Inaccuracies in computational molecular modeling methods are often counterweighed by brute-force generation of a plethora of putative solutions. These are then typically sieved via structural clustering based on similarity measures such as the root mean square deviation (RMSD) of atomic positions.

The Sustainable Development of Industry Clusters: Emergent Knowledge Networks and Socio Complex Adaptive Systems

Directory of Open Access Journals (Sweden)

Susu Nousala

2009-10-01

Full Text Available In a highly competitive global economy the development of sustainable, innovative responses from Industry is now vital. Many industries globally need to respond rather than react to current economic climate through sustainable (economically and environmentally development. The steel industry is a critical player in the urban landscape. Like many industries, small, medium enterprises (SMEs are vital players within the steel industry supply chain. The Australian SME steel housing sector (based in rural and regional areas are still developing systemic capabilities with the aim of realizing its full potential. The question of an effective sustainable industry is much larger than any one player. This paper aims to present a proposed methodological approach for sustainable cluster development based on previous industry wide investigations. Through the lens of scalability of a socio complex adaptive system, SME development becomes arguably the most significant player with regards to industry cluster development. By starting with SME development it's possible to build an understanding of a simultaneous two layered approach, "bottom up – top down" whilst including a very diversified group.

Hyperspectral clustering and unmixing for studying the ecology of state formation and complex societies

Science.gov (United States)

Kwong, Justin D.; Messinger, David W.; Middleton, William D.

2009-08-01

This project is an application of hyperspectral classification and unmixing in support of an ongoing archaeological study. The study region is the Oaxaca Valley located in the state of Oaxaca, Mexico on the southern coast. This was the birthplace of the Zapotec civilization which grew into a complex state level society. Hyperion imagery is being collected over a 30,000 km2 area. Classification maps of regions of interest are generated using K-means clustering and a novel algorithm called Gradient Flow. Gradient Flow departs from conventional stochastic or deterministic approaches, using graph theory to cluster spectral data. Spectral unmixing is conducted using the RIT developed algorithm Max-D to automatically find end members. Stepwise unmixing is performed to better model the data using the end members found be Max-D. Data are efficiently shared between imaging scientists and archaeologists using Google Earth to stream images over the internet rather than downloading them. The overall goal of the project is to provide archaeologists with useful information maps without having to interpret the raw data.

Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

Energy Technology Data Exchange (ETDEWEB)

Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng [Jiangnan University, Wuxi (China)

2014-11-15

The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy.

Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

International Nuclear Information System (INIS)

Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng

2014-01-01

The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

Science.gov (United States)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

Gold cluster carbonyls: saturated adsorption of CO on gold cluster cations, vibrational spectroscopy, and implications for their structures.

Science.gov (United States)

Fielicke, André; von Helden, Gert; Meijer, Gerard; Pedersen, David B; Simard, Benoit; Rayner, David M

2005-06-15

We report on the interaction of carbon monoxide with cationic gold clusters in the gas phase. Successive adsorption of CO molecules on the Au(n)(+) clusters proceeds until a cluster size specific saturation coverage is reached. Structural information for the bare gold clusters is obtained by comparing the saturation stoichiometry with the number of available equivalent sites presented by candidate structures of Au(n)(+). Our findings are in agreement with the planar structures of the Au(n)(+) cluster cations with n < or = 7 that are suggested by ion mobility experiments [Gilb, S.; Weis, P.; Furche, F.; Ahlrichs, R.; Kappes, M. M. J. Chem. Phys. 2001, 116, 4094]. By inference we also establish the structure of the saturated Au(n)(CO)(m)(+) complexes. In certain cases we find evidence suggesting that successive adsorption of CO can distort the metal cluster framework. In addition, the vibrational spectra of the Au(n)(CO)(m)(+) complexes in both the CO stretching region and in the region of the Au-C stretch and the Au-C-O bend are measured using infrared photodepletion spectroscopy. The spectra further aid in the structure determination of Au(n)(+), provide information on the structure of the Au(n)(+)-CO complexes, and can be compared with spectra of CO adsorbates on deposited clusters or surfaces.

Survey of the numerical characterisation of 2-D complex clusters

NARCIS (Netherlands)

Maggi, F.

2003-01-01

The study of cluster format ion is common in many fields of science and technology (aerosols, colloidal suspensions, hetero-disperse particulate systems in general, growth processes far from equilibrium, etc.). The term "cluster" is a general word indicating an object consisting of a set of

Lipid clustering correlates with membrane curvature as revealed by molecular simulations of complex lipid bilayers.

Directory of Open Access Journals (Sweden)

Heidi Koldsø

2014-10-01

Full Text Available Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP2, in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP2, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins.

Clustering high dimensional data

DEFF Research Database (Denmark)

Assent, Ira

2012-01-01

High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... 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...

Clustervision: Visual Supervision of Unsupervised Clustering.

Science.gov (United States)

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

2018-01-01

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

The Complexities of Implementing Cluster Supply Chain - Case Study of JCH

Science.gov (United States)

Xue, Xiao; Zhang, Jibiao; Wang, Yang

As a new type of management pattern, "cluster supply chain" (CSC) can help SMEs to face the global challenges through all kinds of collaboration. However, a major challenge in implementing CSC is the gap between theory and practice in the field. In an effort to provide a better understanding of this emerging phenomenon, this paper presents the implementation process of CSC in the context of JingCheng Mechanical & Electrical Holding co., ltd.(JCH) as a case study. The cast study of JCH suggests that the key problems in the practice of cluster supply chain: How do small firms use cluster supply chain? Only after we clarify the problem, the actual construction and operation of cluster supply chain does show successful results as it should be.

Cation-Cation Complexes of Pentavalent Uranyl: From Disproportionation Intermediates to Stable Clusters

Energy Technology Data Exchange (ETDEWEB)

Mougel, Victor; Horeglad, Pawel; Nocton, Gregory; Pecaut, Jacques; Mazzanti, Marinella [CEA, INAC, SCIB, Laboratoire de Reconnaissance Ionique et Chimie de Coordination, CEA-Grenoble, 38054 GRENOBLE, Cedex 09 (France)

2010-07-01

Three new cation cation complexes of pentavalent uranyl, stable with respect to the disproportionation reaction, have been prepared from the reaction of the precursor [(UO{sub 2}py{sub 5})-(KI{sub 2}py{sub 2})]{sub n} (1) with the Schiff base ligands salen{sup 2-}, acacen{sup 2-}, and salophen{sup 2-} (H{sub 2}salen N, N'-ethylene-bis(salicylidene-imine), H{sub 2}acacen=-N, N'-ethylenebis(acetylacetone-imine), H{sub 2}salophen=N, N'-phenylene-bis(salicylidene-imine)). The preparation of stable complexes requires a careful choice of counter ions and reaction conditions. Notably the reaction of 1 with salophen{sup 2-} in pyridine leads to immediate disproportionation, but in the presence of [18]crown-6 ([18]C-6) a stable complex forms. The solid-state structure of the four tetra-nuclear complexes ([UO{sub 2}-(acacen)]{sub 4}[{mu}{sub 8}-]{sub 2}[K([18]C-6)(py)]{sub 2}) (3) and ([UO{sub 2}(acacen)](4)[{mu}{sub 8}-]).2[K([222])(py)] (4) ([UO{sub 2}(salophen)](4)[{mu}{sub 8}-K]{sub 2}[mu(5)-KI]{sub 2}[(K([18]C-6)]).2 [K([18]C-6)-(thf){sub 2}].2I (5), and ([UO{sub 2}(salen)(4)][{mu}{sub 8}-Rb]{sub 2}[Rb([18]C-6)]{sub 2}) (9) ([222] = [222]cryptand, py =pyridine), presenting a T-shaped cation cation interaction has been determined by X-ray crystallographic studies. NMR spectroscopic and UV/Vis studies show that the tetra-nuclear structure is maintained in pyridine solution for the salen and acacen complexes. Stable mononuclear complexes of pentavalent uranyl are also obtained by reduction of the hexavalent uranyl Schiff base complexes with cobaltocene in pyridine in the absence of coordinating cations. The reactivity of the complex [U{sup V}O{sub 2}(salen)(py)][Cp*{sub 2}Co] with different alkali ions demonstrates the crucial effect of coordinating cations on the stability of cation cation complexes. The nature of the cation plays a key role in the preparation of stable cation cation complexes. Stable tetra-nuclear complexes form in the presence of K

Properties of the open cluster system

International Nuclear Information System (INIS)

Janes, K.A.; Tilley, C.; Lynga, G.

1988-01-01

A system of weights corresponding to the precision of open cluster data is described. Using these weights, some properties of open clusters can be studied more accurately than was possible earlier. It is clear that there are three types of objects: unbound clusters, bound clusters in the thin disk, and older bound clusters. Galactic gradients of metallicity, longevity, and linear diameter are studied. Distributions at right angles to the galactic plane are discussed in the light of the different cluster types. The clumping of clusters in complexes is studied. An estimate of the selection effects influencing the present material of open cluster data is made in order to evaluate the role played by open clusters in the history of the galactic disk. 58 references

Complexes of DNA bases and Watson-Crick base pairs interaction with neutral silver Agn (n = 8, 10, 12) clusters: a DFT and TDDFT study.

Science.gov (United States)

Srivastava, Ruby

2018-03-01

We study the binding of the neutral Ag n (n = 8, 10, 12) to the DNA base-adenine (A), guanine (G) and Watson-Crick -adenine-thymine, guanine-cytosine pairs. Geometries of complexes were optimized at the DFT level using the hybrid B3LYP functional. LANL2DZ effective core potential was used for silver and 6-31 + G ** was used for all other atoms. NBO charges were analyzed using the Natural population analysis. The absorption properties of Ag n -A,G/WC complexes were also studied using time-dependent density functional theory. The absorption spectra for these complexes show wavelength in the visible region. It was revealed that silver clusters interact more strongly with WC pairs than with isolated DNA complexes. Furthermore, it was found that the electronic charge transferred from silver to isolated DNA clusters are less than the electronic charge transferred from silver to the Ag n -WC complexes. The vertical ionization potential, vertical electron affinity, hardness, and electrophilicity index of Ag n -DNA/WC complexes have also been discussed.

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

Science.gov (United States)

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

2017-07-01

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

Interaction between Nbp35 and Cfd1 proteins of cytosolic Fe-S cluster assembly reveals a stable complex formation in Entamoeba histolytica.

Directory of Open Access Journals (Sweden)

Shadab Anwar

Full Text Available Iron-Sulfur (Fe-S proteins are involved in many biological functions such as electron transport, photosynthesis, regulation of gene expression and enzymatic activities. Biosynthesis and transfer of Fe-S clusters depend on Fe-S clusters assembly processes such as ISC, SUF, NIF, and CIA systems. Unlike other eukaryotes which possess ISC and CIA systems, amitochondriate Entamoeba histolytica has retained NIF & CIA systems for Fe-S cluster assembly in the cytosol. In the present study, we have elucidated interaction between two proteins of E. histolytica CIA system, Cytosolic Fe-S cluster deficient 1 (Cfd1 protein and Nucleotide binding protein 35 (Nbp35. In-silico analysis showed that structural regions ranging from amino acid residues (P33-K35, G131-V135 and I147-E151 of Nbp35 and (G5-V6, M34-D39 and G46-A52 of Cfd1 are involved in the formation of protein-protein complex. Furthermore, Molecular dynamic (MD simulations study suggested that hydrophobic forces surpass over hydrophilic forces between Nbp35 and Cfd1 and Van-der-Waal interaction plays crucial role in the formation of stable complex. Both proteins were separately cloned, expressed as recombinant fusion proteins in E. coli and purified to homogeneity by affinity column chromatography. Physical interaction between Nbp35 and Cfd1 proteins was confirmed in vitro by co-purification of recombinant Nbp35 with thrombin digested Cfd1 and in vivo by pull down assay and immunoprecipitation. The insilico, in vitro as well as in vivo results prove a stable interaction between these two proteins, supporting the possibility of its involvement in Fe-S cluster transfer to target apo-proteins through CIA machinery in E. histolytica. Our study indicates that initial synthesis of a Fe-S precursor in mitochondria is not necessary for the formation of Cfd1-Nbp35 complex. Thus, Cfd1 and Nbp35 with the help of cytosolic NifS and NifU proteins can participate in the maturation of non-mitosomal Fe-S proteins

Ubiquitination-Linked Phosphorylation of the FANCI S/TQ Cluster Contributes to Activation of the Fanconi Anemia I/D2 Complex

Directory of Open Access Journals (Sweden)

Ronald S. Cheung

2017-06-01

Full Text Available Repair of interstrand crosslinks by the Fanconi anemia (FA pathway requires both monoubiquitination and de-ubiquitination of the FANCI/FANCD2 (FANCI/D2 complex. In the standing model, the phosphorylation of six sites in the FANCI S/TQ cluster domain occurs upstream of, and promotes, FANCI/D2 monoubiquitination. We generated phospho-specific antibodies against three different S/TQ cluster sites (serines 556, 559, and 565 on human FANCI and found that, in contrast to the standing model, distinct FANCI sites were phosphorylated either predominantly upstream (ubiquitination independent; serine 556 or downstream (ubiquitination-linked; serines 559 and 565 of FANCI/D2 monoubiquitination. Ubiquitination-linked FANCI phosphorylation inhibited FANCD2 de-ubiquitination and bypassed the need to de-ubiquitinate FANCD2 to achieve effective interstrand crosslink repair. USP1 depletion suppressed ubiquitination-linked FANCI phosphorylation despite increasing FANCI/D2 monoubiquitination, providing an explanation of why FANCD2 de-ubiquitination is important for function of the FA pathway. Our work results in a refined model of how FANCI phosphorylation activates the FANCI/D2 complex.

Complex open-framework germanate built by 8-coordinated Ge 10 clusters

KAUST Repository

Yue, Huijuan; Peskov, Maxim; Sun, Junliang; Zou, Xiaodong

2012-01-01

cluster building units can be concluded. The framework of SU-67 is based on an elaborate topological pattern of connected Ge 10 clusters forming intersecting 10- and 11-ring channels and has a low framework density (12.4 Ge atoms per 1000 ̊ 3). We have

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

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

2011-01-01

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

Architecture of the Yeast Mitochondrial Iron-Sulfur Cluster Assembly Machinery: THE SUB-COMPLEX FORMED BY THE IRON DONOR, Yfh1 PROTEIN, AND THE SCAFFOLD, Isu1 PROTEIN.

Science.gov (United States)

Ranatunga, Wasantha; Gakh, Oleksandr; Galeano, Belinda K; Smith, Douglas Y; Söderberg, Christopher A G; Al-Karadaghi, Salam; Thompson, James R; Isaya, Grazia

2016-05-06

The biosynthesis of Fe-S clusters is a vital process involving the delivery of elemental iron and sulfur to scaffold proteins via molecular interactions that are still poorly defined. We reconstituted a stable, functional complex consisting of the iron donor, Yfh1 (yeast frataxin homologue 1), and the Fe-S cluster scaffold, Isu1, with 1:1 stoichiometry, [Yfh1]24·[Isu1]24 Using negative staining transmission EM and single particle analysis, we obtained a three-dimensional reconstruction of this complex at a resolution of ∼17 Å. In addition, via chemical cross-linking, limited proteolysis, and mass spectrometry, we identified protein-protein interaction surfaces within the complex. The data together reveal that [Yfh1]24·[Isu1]24 is a roughly cubic macromolecule consisting of one symmetric Isu1 trimer binding on top of one symmetric Yfh1 trimer at each of its eight vertices. Furthermore, molecular modeling suggests that two subunits of the cysteine desulfurase, Nfs1, may bind symmetrically on top of two adjacent Isu1 trimers in a manner that creates two putative [2Fe-2S] cluster assembly centers. In each center, conserved amino acids known to be involved in sulfur and iron donation by Nfs1 and Yfh1, respectively, are in close proximity to the Fe-S cluster-coordinating residues of Isu1. We suggest that this architecture is suitable to ensure concerted and protected transfer of potentially toxic iron and sulfur atoms to Isu1 during Fe-S cluster assembly. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

STAR FORMATION ACROSS THE W3 COMPLEX

Energy Technology Data Exchange (ETDEWEB)

Román-Zúñiga, Carlos G.; Ybarra, Jason E.; Tapia, Mauricio [Instituto de Astronomía, Universidad Nacional Autónoma de México, Unidad Académica en Ensenada, Km 103 Carr. Tijuana–Ensenada, Ensenada 22860 (Mexico); Megías, Guillermo D. [Facultad de Física. Universidad de Sevilla. Dpto. Física Atómica, Molecular y Nuclear, Sevilla, E-41080 (Spain); Lada, Elizabeth A. [Astronomy Department, University of Florida, 211 Bryant Space Sciences Center, FL 32611 (United States); Alves, Joáo F. [Institute of Astronomy, University of Vienna, Türkenschanzstr. 17, A-1180 Vienna (Austria)

2015-09-15

We present a multi-wavelength analysis of the history of star formation in the W3 complex. Using deep, near-infrared ground-based images combined with images obtained with Spitzer and Chandra observatories, we identified and classified young embedded sources. We identified the principal clusters in the complex and determined their structure and extension. We constructed extinction-limited samples for five principal clusters and constructed K-band luminosity functions that we compare with those of artificial clusters with varying ages. This analysis provided mean ages and possible age spreads for the clusters. We found that IC 1795, the centermost cluster of the complex, still hosts a large fraction of young sources with circumstellar disks. This indicates that star formation was active in IC 1795 as recently as 2 Myr ago, simultaneous to the star-forming activity in the flanking embedded clusters, W3-Main and W3(OH). A comparison with carbon monoxide emission maps indicates strong velocity gradients in the gas clumps hosting W3-Main and W3(OH) and shows small receding clumps of gas at IC 1795, suggestive of rapid gas removal (faster than the T Tauri timescale) in the cluster-forming regions. We discuss one possible scenario for the progression of cluster formation in the W3 complex. We propose that early processes of gas collapse in the main structure of the complex could have defined the progression of cluster formation across the complex with relatively small age differences from one group to another. However, triggering effects could act as catalysts for enhanced efficiency of formation at a local level, in agreement with previous studies.

Iron-sulfur cluster biogenesis in mammalian cells: new insights into the molecular mechanisms of cluster delivery

Science.gov (United States)

Maio, Nunziata; Rouault, Tracey. A.

2014-01-01

Iron-sulfur (Fe-S) clusters are ancient, ubiquitous cofactors composed of iron and inorganic sulfur. The combination of the chemical reactivity of iron and sulfur, together with many variations of cluster composition, oxidation states and protein environments, enables Fe-S clusters to participate in numerous biological processes. Fe-S clusters are essential to redox catalysis in nitrogen fixation, mitochondrial respiration and photosynthesis, to regulatory sensing in key metabolic pathways (i. e. cellular iron homeostasis and oxidative stress response), and to the replication and maintenance of the nuclear genome. Fe-S cluster biogenesis is a multistep process that involves a complex sequence of catalyzed protein- protein interactions and coupled conformational changes between the components of several dedicated multimeric complexes. Intensive studies of the assembly process have clarified key points in the biogenesis of Fe-S proteins. However several critical questions still remain, such as: what is the role of frataxin? Why do some defects of Fe-S cluster biogenesis cause mitochondrial iron overload? How are specific Fe-S recipient proteins recognized in the process of Fe-S transfer? This review focuses on the basic steps of Fe-S cluster biogenesis, drawing attention to recent advances achieved on the identification of molecular features that guide selection of specific subsets of nascent Fe-S recipients by the cochaperone HSC20. Additionally, it outlines the distinctive phenotypes of human diseases due to mutations in the components of the basic pathway. PMID:25245479

Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

Science.gov (United States)

Hendrix, Val; Benjamin, Doug; Yao, Yushu

2012-12-01

Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

Clusters and exotic processes

International Nuclear Information System (INIS)

Schiffer, J.P.

1975-01-01

An attempt is made to present some data which may be construed as indicating that perhaps clusters play a role in high energy and exotic pion or kaon interactions with complex (A much greater than 16) nuclei. Also an attempt is made to summarize some very recent experimental work on pion interactions with nuclei which may or may not in the end support a picture in which clusters play an important role. (U.S.)

The contribution of cluster and discriminant analysis to the classification of complex aquifer systems.

Science.gov (United States)

Panagopoulos, G P; Angelopoulou, D; Tzirtzilakis, E E; Giannoulopoulos, P

2016-10-01

This paper presents an innovated method for the discrimination of groundwater samples in common groups representing the hydrogeological units from where they have been pumped. This method proved very efficient even in areas with complex hydrogeological regimes. The proposed method requires chemical analyses of water samples only for major ions, meaning that it is applicable to most of cases worldwide. Another benefit of the method is that it gives a further insight of the aquifer hydrogeochemistry as it provides the ions that are responsible for the discrimination of the group. The procedure begins with cluster analysis of the dataset in order to classify the samples in the corresponding hydrogeological unit. The feasibility of the method is proven from the fact that the samples of volcanic origin were separated into two different clusters, namely the lava units and the pyroclastic-ignimbritic aquifer. The second step is the discriminant analysis of the data which provides the functions that distinguish the groups from each other and the most significant variables that define the hydrochemical composition of the aquifer. The whole procedure was highly successful as the 94.7 % of the samples were classified to the correct aquifer system. Finally, the resulted functions can be safely used to categorize samples of either unknown or doubtful origin improving thus the quality and the size of existing hydrochemical databases.

Complex open-framework germanate built by 8-coordinated Ge 10 clusters

KAUST Repository

Yue, Huijuan

2012-11-19

A novel open-framework germanate |(C 5H 14N 2) 2(C 5H 12N 2) 0.5(H 2O) 2.5|[Ge 12.5O 26(OH) 2] with three-dimensional 10- and 11-ring channels, denoted as SU-67, has been synthesized under hydrothermal conditions using 2-methylpiperazine (MPP) as the structure-directing agent (SDA). The synthesis is intimately related to that of JLG-5, a tubular germanate built from Ge 7 clusters. The influences of synthesis parameters are discussed. A strong influence of the hydrofluoric acid quantity on the resulting cluster building units can be concluded. The framework of SU-67 is based on an elaborate topological pattern of connected Ge 10 clusters forming intersecting 10- and 11-ring channels and has a low framework density (12.4 Ge atoms per 1000 ̊ 3). We have discovered that the topology of SU-67 is a new 8-connected nce-8-I4 1/acd net. Strong hydrogen bonding among the organic SDAs, water molecules, and Ge 10 clusters resulted in helical networks in SU-67. © 2012 American Chemical Society.

Platinum clusters with precise numbers of atoms for preparative-scale catalysis.

Science.gov (United States)

Imaoka, Takane; Akanuma, Yuki; Haruta, Naoki; Tsuchiya, Shogo; Ishihara, Kentaro; Okayasu, Takeshi; Chun, Wang-Jae; Takahashi, Masaki; Yamamoto, Kimihisa

2017-09-25

Subnanometer noble metal clusters have enormous potential, mainly for catalytic applications. Because a difference of only one atom may cause significant changes in their reactivity, a preparation method with atomic-level precision is essential. Although such a precision with enough scalability has been achieved by gas-phase synthesis, large-scale preparation is still at the frontier, hampering practical applications. We now show the atom-precise and fully scalable synthesis of platinum clusters on a milligram scale from tiara-like platinum complexes with various ring numbers (n = 5-13). Low-temperature calcination of the complexes on a carbon support under hydrogen stream affords monodispersed platinum clusters, whose atomicity is equivalent to that of the precursor complex. One of the clusters (Pt 10 ) exhibits high catalytic activity in the hydrogenation of styrene compared to that of the other clusters. This method opens an avenue for the application of these clusters to preparative-scale catalysis.The catalytic activity of a noble metal nanocluster is tied to its atomicity. Here, the authors report an atom-precise, fully scalable synthesis of platinum clusters from molecular ring precursors, and show that a variation of only one atom can dramatically change a cluster's reactivity.

Bacillus cereus Fnr binds a [4Fe-4S] cluster and forms a ternary complex with ResD and PlcR

Directory of Open Access Journals (Sweden)

Esbelin Julia

2012-06-01

Full Text Available Abstract Background Bacillus cereus is a facultative anaerobe that causes diarrheal disease in humans. Diarrheal syndrome may result from the secretion of various virulence factors including hemolysin BL and nonhemolytic enterotoxin Nhe. Expression of genes encoding Hbl and Nhe is regulated by the two redox systems, ResDE and Fnr, and the virulence regulator PlcR. B. cereus Fnr is a member of the Crp/Fnr family of iron-sulfur (Fe-S proteins. Only its apo-form has so far been studied. A major goal in deciphering the Fnr-dependent regulation of enterotoxin genes is thus to obtain and characterize holoFnr. Results Fnr has been subjected to in vitro Fe-S cluster reconstitution under anoxic conditions. UV-visible and EPR spectroscopic analyses together with the chemical estimation of the iron content indicated that Fnr binds one [4Fe-4S]2+ cluster per monomer. Atmospheric O2 causes disassembly of the Fe-S cluster, which exhibited a half-life of 15 min in air. Holo- and apoFnr have similar affinities for the nhe and hbl promoter regions, while holoFnr has a higher affinity for fnr promoter region than apoFnr. Both the apo- and holo-form of Fnr interact with ResD and PlcR to form a ternary complex. Conclusions Overall, this work shows that incorporation of the [4Fe-4S]2+ cluster is not required for DNA binding of Fnr to promoter regions of hbl and nhe enterotoxin genes or for the formation of a ternary complex with ResD and PlcR. This points to some new unusual properties of Fnr that may have physiological relevance in the redox regulation of enterotoxin gene regulation.

Ligand assisted cleavage of uranium oxo-clusters

Energy Technology Data Exchange (ETDEWEB)

Nocton, Gregory; Pecaut, Jacques; Mazzanti, Marinella [Laboratoire de Reconnaissance Ionique et Chimie de Coordination, Service de Chimie Inorganique et Biologique, UMR-E 3 CEA-UJF, CEA/DSM/INAC, CEA-Grenoble, 38054 Grenoble, Cedex 09 (France); Filinchuk, Yaroslav [Swiss Norwegian Beam Lines (SNBL) at the European Synchrotron Radiation Facility (ESRF), rue Jules Horowitz, 38043 Grenoble (France)

2010-07-01

Dibenzoylmethanate replaces the bridging triflate ligands in uranium triflate poly-oxo-clusters and cleaves the U{sub 12}O{sub 20} core yielding the new [U{sub 6}O{sub 4}(OH){sub 4}({eta}-dbm){sub 12}] dibenzoylmethanate (dbm{sup -}) cluster which slowly dissociates into a monomeric complex. This reactivity demonstrates the importance of bridging ligands in stabilizing uranium poly-oxo-clusters. (authors)

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

Directory of Open Access Journals (Sweden)

Ashlock Daniel

2009-08-01

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

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

Science.gov (United States)

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

2009-08-22

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

Small-volume potentiometric titrations: EPR investigations of Fe-S cluster N2 in mitochondrial complex I.

Science.gov (United States)

Wright, John J; Salvadori, Enrico; Bridges, Hannah R; Hirst, Judy; Roessler, Maxie M

2016-09-01

EPR-based potentiometric titrations are a well-established method for determining the reduction potentials of cofactors in large and complex proteins with at least one EPR-active state. However, such titrations require large amounts of protein. Here, we report a new method that requires an order of magnitude less protein than previously described methods, and that provides EPR samples suitable for measurements at both X- and Q-band microwave frequencies. We demonstrate our method by determining the reduction potential of the terminal [4Fe-4S] cluster (N2) in the intramolecular electron-transfer relay in mammalian respiratory complex I. The value determined by our method, E m7 =-158mV, is precise, reproducible, and consistent with previously reported values. Our small-volume potentiometric titration method will facilitate detailed investigations of EPR-active centres in non-abundant and refractory proteins that can only be prepared in small quantities. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Cluster approach to realization of innovation development strategy for the agroindustrial complex of the region

Directory of Open Access Journals (Sweden)

Valentina Aleksandrovna Kundius

2011-12-01

Full Text Available This paper reviews cluster approach as an innovative management technology for the regional economy. The results of studying the theory and practice of clustering of the regional economy, the formation of agribusiness and food clusters in agribusiness are presented. Basic features and operation of the cluster systems are revealed and distinguished from other forms of cooperative and economic interactions between small and big business features, motivational components of integration into clusters. On the basis of scientific propositions, a model of regional economic clusters is formulated; specific territorial distribution and level of aggregation of clusters in the agricultural sector were distinguished. It is proposed to refer agroindustrial clusters to the clusters that represent the associations of organization of various fields in a single reproduction cycle from raw material to finished products sales including all stages of reproduction on the basis of innovation and investment activity. A structuring work on principles of agro-clusters was held, sustainable competitive advantage and the formation mechanisms of the development of agro-industrial clusters have been grounded.

Clustering of near clusters versus cluster compactness

International Nuclear Information System (INIS)

Yu Gao; Yipeng Jing

1989-01-01

The clustering properties of near Zwicky clusters are studied by using the two-point angular correlation function. The angular correlation functions for compact and medium compact clusters, for open clusters, and for all near Zwicky clusters are estimated. The results show much stronger clustering for compact and medium compact clusters than for open clusters, and that open clusters have nearly the same clustering strength as galaxies. A detailed study of the compactness-dependence of correlation function strength is worth investigating. (author)

Clustering Game Behavior Data

DEFF Research Database (Denmark)

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

2015-01-01

of the causes, the proliferation of behavioral data poses the problem of how to derive insights therefrom. Behavioral data sets can be large, time-dependent and high-dimensional. Clustering offers a way to explore such data and to discover patterns that can reduce the overall complexity of the data. Clustering...... and other techniques for player profiling and play style analysis have, therefore, become popular in the nascent field of game analytics. However, the proper use of clustering techniques requires expertise and an understanding of games is essential to evaluate results. With this paper, we address game data...... 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...

Identifying and ranking influential spreaders in complex networks by combining a local-degree sum and the clustering coefficient

Science.gov (United States)

Li, Mengtian; Zhang, Ruisheng; Hu, Rongjing; Yang, Fan; Yao, Yabing; Yuan, Yongna

2018-03-01

Identifying influential spreaders is a crucial problem that can help authorities to control the spreading process in complex networks. Based on the classical degree centrality (DC), several improved measures have been presented. However, these measures cannot rank spreaders accurately. In this paper, we first calculate the sum of the degrees of the nearest neighbors of a given node, and based on the calculated sum, a novel centrality named clustered local-degree (CLD) is proposed, which combines the sum and the clustering coefficients of nodes to rank spreaders. By assuming that the spreading process in networks follows the susceptible-infectious-recovered (SIR) model, we perform extensive simulations on a series of real networks to compare the performances between the CLD centrality and other six measures. The results show that the CLD centrality has a competitive performance in distinguishing the spreading ability of nodes, and exposes the best performance to identify influential spreaders accurately.

Clustering of low-valence particles: structure and kinetics.

Science.gov (United States)

Markova, Olga; Alberts, Jonathan; Munro, Edwin; Lenne, Pierre-François

2014-08-01

We compute the structure and kinetics of two systems of low-valence particles with three or six freely oriented bonds in two dimensions. The structure of clusters formed by trivalent particles is complex with loops and holes, while hexavalent particles self-organize into regular and compact structures. We identify the elementary structures which compose the clusters of trivalent particles. At initial stages of clustering, the clusters of trivalent particles grow with a power-law time dependence. Yet at longer times fusion and fission of clusters equilibrates and clusters form a heterogeneous phase with polydispersed sizes. These results emphasize the role of valence in the kinetics and stability of finite-size clusters.

Electronic Structure of Transition Metal Clusters, Actinide Complexes and Their Reactivities

Energy Technology Data Exchange (ETDEWEB)

Krishnan Balasubramanian

2009-07-18

methods with all-electron Douglas-Kroll relativistic methods. We have the capabilities for computing full CI extrapolations including spin-orbit effects and several one-electron properties and electron density maps including spin-orbit effects. We are continuously collaborating with several experimental groups around the country and at National Labs to carry out computational studies on the DOE-BES funded projects. The past work in the last 3 years was primarily motivated and driven by the concurrent or recent experimental studies on these systems. We were thus significantly benefited by coordinating our computational efforts with experimental studies. The interaction between theory and experiment has resulted in some unique and exciting opportunities. For example, for the very first time ever, the upper spin-orbit component of a heavy trimer such as Au{sub 3} was experimentally observed as a result of our accurate computational study on the upper electronic states of gold trimer. Likewise for the first time AuH{sub 2} could be observed and interpreted clearly due to our computed potential energy surfaces that revealed the existence of a large barrier to convert the isolated AuH{sub 2} back to Au and H{sub 2}. We have also worked on yet to be observed systems and have made predictions for future experiments. We have computed the spectroscopic and thermodynamic properties of transition metal carbides transition metal clusters and compared our electronic states to the anion photodetachment spectra of Lai Sheng Wang. Prof Mike Morse and coworkers(funded also by DOE-BES) and Prof Stimle and coworkers(also funded by DOE-BES) are working on the spectroscopic properties of transition metal carbides and nitrides. Our predictions on the excited states of transition metal clusters such as Hf{sub 3}, Nb{sub 2}{sup +} etc., have been confirmed experimentally by Prof. Lombardi and coworkers using resonance Raman spectroscopy. We have also been studying larger complexes critical to the

Electronic Structure of Transition Metal Clusters, Actinide Complexes and Their Reactivities

International Nuclear Information System (INIS)

Balasubramanian, Krishnan

2009-01-01

methods with all-electron Douglas-Kroll relativistic methods. We have the capabilities for computing full CI extrapolations including spin-orbit effects and several one-electron properties and electron density maps including spin-orbit effects. We are continuously collaborating with several experimental groups around the country and at National Labs to carry out computational studies on the DOE-BES funded projects. The past work in the last 3 years was primarily motivated and driven by the concurrent or recent experimental studies on these systems. We were thus significantly benefited by coordinating our computational efforts with experimental studies. The interaction between theory and experiment has resulted in some unique and exciting opportunities. For example, for the very first time ever, the upper spin-orbit component of a heavy trimer such as Au 3 was experimentally observed as a result of our accurate computational study on the upper electronic states of gold trimer. Likewise for the first time AuH 2 could be observed and interpreted clearly due to our computed potential energy surfaces that revealed the existence of a large barrier to convert the isolated AuH 2 back to Au and H 2 . We have also worked on yet to be observed systems and have made predictions for future experiments. We have computed the spectroscopic and thermodynamic properties of transition metal carbides transition metal clusters and compared our electronic states to the anion photodetachment spectra of Lai Sheng Wang. Prof Mike Morse and coworkers(funded also by DOE-BES) and Prof Stimle and coworkers(also funded by DOE-BES) are working on the spectroscopic properties of transition metal carbides and nitrides. Our predictions on the excited states of transition metal clusters such as Hf 3 , Nb 2 + etc., have been confirmed experimentally by Prof. Lombardi and coworkers using resonance Raman spectroscopy. We have also been studying larger complexes critical to the environmental management of high

Scientific Cluster Deployment and Recovery – Using puppet to simplify cluster management

International Nuclear Information System (INIS)

Hendrix, Val; Yao Yushu; Benjamin, Doug

2012-01-01

Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

CORECLUSTER: A Degeneracy Based Graph Clustering Framework

OpenAIRE

Giatsidis , Christos; Malliaros , Fragkiskos; Thilikos , Dimitrios M. ,; Vazirgiannis , Michalis

2014-01-01

International audience; Graph clustering or community detection constitutes an important task forinvestigating the internal structure of graphs, with a plethora of applications in several domains. Traditional tools for graph clustering, such asspectral methods, typically suffer from high time and space complexity. In thisarticle, we present \\textsc{CoreCluster}, an efficient graph clusteringframework based on the concept of graph degeneracy, that can be used along withany known graph clusteri...

Cluster-cluster clustering

International Nuclear Information System (INIS)

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

1985-01-01

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

Examination of Clustering in Eutectic Microstrcture

Directory of Open Access Journals (Sweden)

Bortnyik K.

2017-06-01

Full Text Available The eutectic microstructures are complex microstructures and a hard work to describe it with few numbers. The eutectics builds up eutectic cells. In the cells the phases are clustered. With the development of big databases the data mining also develops, and produces a lot of method to handling the large datasets, and earns information from the sets. One typical method is the clustering, which finds the groups in the datasets. In this article a partitioning and a hierarchical clustering is applied to eutectic structures to find the clusters. In the case of AlMn alloy the K-means algorithm work well, and find the eutectic cells. In the case of ductile cast iron the hierarchical clustering works better. With the combination of the partitioning and hierarchical clustering with the image transformation, an effective method is developed for clustering the objects in the microstructures.

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

Directory of Open Access Journals (Sweden)

Can Tolga

2009-09-01

Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

Human major histocompatibility complex contains a minimum of 19 genes between the complement cluster and HLA-B

International Nuclear Information System (INIS)

Spies, T.; Bresnahan, M.; Strominger, J.L.

1989-01-01

A 600-kilobase (kb) DNA segment from the human major histocompatibility complex (MHC) class III region was isolated by extension of a previous 435-kb chromosome walk. The contiguous series of cloned overlapping cosmids contains the entire 555-kb interval between C2 in the complement gene cluster and HLA-B. This region is known to encode the tumor necrosis factors (TNFs) α and β, B144, and the major heat shock protein HSP70. Moreover, a cluster of genes, BAT1-BAT5 (HLA-B-associated transcripts) have been localized in the vicinity of the genes for TNFα and TNFβ. An additional four genes were identified by isolation of corresponding cDNA clones with cosmid DNA probes. These genes for BAT6-BAT9 were mapped near the gene for C2 within a 120-kb region that includes a HSP70 gene pair. These results, together with complementary data from a similar recent study, indicated the presence of a minimum of 19 genes within the C2-HLA-B interval of the MHC class III region. Although the functional properties of most of these genes are yet unknown, they may be involved in some aspects of immunity. This idea is supported by the genetic mapping of the hematopoietic histocompatibility locus-1 (Hh-1) in recombinant mice between TNFα and H-2S, which is homologous to the complement gene cluster in humans

Atomic cluster physics: new challenges for theory and experiment

Energy Technology Data Exchange (ETDEWEB)

Greiner, Walter [Frankfurt Institute for Advanced Studies, Max-von-Laue Str. 1, Frankfurt am Main 60438 (Germany); Solov' yov, Andrey [Frankfurt Institute for Advanced Studies, Max-von-Laue Str. 1, Frankfurt am Main 60438 (Germany)

2005-08-01

A brief introduction to atomic cluster physics, the inter-disciplinary field, which developed fairly successfully during last years, is presented. A review of recent achievements in the detailed ab initio description of structure and properties of atomic clusters and complex molecules is given. The main trends of development in the field are discussed and some of its new focuses are outlined. Particular attention is devoted to the role of quantum and many-body phenomena in the formation of complex multi-atomic systems and the methods of theoretical investigation of their specific properties. The role of the simplified model approaches accurately developed from the fundamental physical principles is stressed. Various illustrations are made for sodium, magnesium clusters, fullerenes and clusters of noble gas atoms.

A Chemical Composition Survey of the Iron-complex Globular Cluster NGC 6273 (M19)

Energy Technology Data Exchange (ETDEWEB)

Johnson, Christian I.; Caldwell, Nelson [Harvard–Smithsonian Center for Astrophysics, 60 Garden Street, MS-15, Cambridge, MA 02138 (United States); Rich, R. Michael [Department of Physics and Astronomy, UCLA, 430 Portola Plaza, Box 951547, Los Angeles, CA 90095-1547 (United States); Mateo, Mario [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States); Bailey, John I. III [Leiden Observatory, Leiden University, P.O. Box 9513, 2300RA Leiden (Netherlands); Clarkson, William I. [Department of Natural Sciences, University of Michigan–Dearborn, 4901 Evergreen Road, Dearborn, MI 48128 (United States); Olszewski, Edward W. [Steward Observatory, The University of Arizona, 933 N. Cherry Avenue, Tucson, AZ 85721 (United States); Walker, Matthew G., E-mail: cjohnson@cfa.harvard.edu, E-mail: ncaldwell@cfa.harvard.edu, E-mail: rmr@astro.ucla.edu, E-mail: mmateo@umich.edu, E-mail: baileyji@strw.leidenuniv.nl, E-mail: wiclarks@umich.edu, E-mail: eolszewski@as.arizona.edu, E-mail: mgwalker@andrew.cmu.edu [McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States)

2017-02-20

Recent observations have shown that a growing number of the most massive Galactic globular clusters contain multiple populations of stars with different [Fe/H] and neutron-capture element abundances. NGC 6273 has only recently been recognized as a member of this “iron-complex” cluster class, and we provide here a chemical and kinematic analysis of >300 red giant branch and asymptotic giant branch member stars using high-resolution spectra obtained with the Magellan –M2FS and VLT–FLAMES instruments. Multiple lines of evidence indicate that NGC 6273 possesses an intrinsic metallicity spread that ranges from about [Fe/H] = −2 to −1 dex, and may include at least three populations with different [Fe/H] values. The three populations identified here contain separate first (Na/Al-poor) and second (Na/Al-rich) generation stars, but a Mg–Al anti-correlation may only be present in stars with [Fe/H] ≳ −1.65. The strong correlation between [La/Eu] and [Fe/H] suggests that the s-process must have dominated the heavy element enrichment at higher metallicities. A small group of stars with low [ α /Fe] is identified and may have been accreted from a former surrounding field star population. The cluster’s large abundance variations are coupled with a complex, extended, and multimodal blue horizontal branch (HB). The HB morphology and chemical abundances suggest that NGC 6273 may have an origin that is similar to ω Cen and M54.

A novel cluster of Mycobacterium abscessus complex revealed by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS).

Science.gov (United States)

Suzuki, Hiromichi; Yoshida, Shiomi; Yoshida, Atsushi; Okuzumi, Katsuko; Fukusima, Atsuhito; Hishinuma, Akira

2015-12-01

Mycobacterium abscessus complex is a rapidly growing mycobacterium consisting of 3 subspecies, M. abscessus, Mycobacterium massiliense, and Mycobacterium bolletii. However, rapid and accurate species identification is difficult. We first evaluated a suitable protocol of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for distinguishing these subspecies. Then, we studied spectral signals by MALDI-TOF MS in 59 M. abscessus, 42 M. massiliense, and 2 M. bolletii. Among several specific spectral signals, 4 signals clearly differentiate M. massiliense from the other 2 subspecies, M. abscessus and M. bolletii. Moreover, 6 of the 42 M. massiliense isolates showed a spectral pattern similar to M. abscessus. These isolates correspond to the distinctive class of M. massiliense (cluster D) which is closer to M. abscessus by the previous variable number tandem repeat analysis. These results indicate that MALDI-TOF MS is not only useful for the identification of 3 subspecies of M. abscessus complex but also capable of distinguishing clusters of M. massiliense. Copyright © 2015 Elsevier Inc. All rights reserved.

On the Disruption of Star Clusters in a Hierarchical Interstellar Medium

Science.gov (United States)

Elmegreen, Bruce G.; Hunter, Deidre A.

2010-03-01

The distribution of the number of clusters as a function of mass M and age T suggests that clusters get eroded or dispersed in a regular way over time, such that the cluster number decreases inversely as an approximate power law with T within each fixed interval of M. This power law is inconsistent with standard dispersal mechanisms such as cluster evaporation and cloud collisions. In the conventional interpretation, it requires the unlikely situation where diverse mechanisms stitch together over time in a way that is independent of environment or M. Here, we consider another model in which the large-scale distribution of gas in each star-forming region plays an important role. We note that star clusters form with positional and temporal correlations in giant cloud complexes, and suggest that these complexes dominate the tidal force and collisional influence on a cluster during its first several hundred million years. Because the cloud complex density decreases regularly with position from the cluster birth site, the harassment and collision rates between the cluster and the cloud pieces decrease regularly with age as the cluster drifts. This decrease is typically a power law of the form required to explain the mass-age distribution. We reproduce this distribution for a variety of cases, including rapid disruption, slow erosion, combinations of these two, cluster-cloud collisions, cluster disruption by hierarchical disassembly, and partial cluster disruption. We also consider apparent cluster mass loss by fading below the surface brightness limit of a survey. In all cases, the observed log M-log T diagram can be reproduced under reasonable assumptions.

ON THE DISRUPTION OF STAR CLUSTERS IN A HIERARCHICAL INTERSTELLAR MEDIUM

International Nuclear Information System (INIS)

Elmegreen, Bruce G.; Hunter, Deidre A.

2010-01-01

The distribution of the number of clusters as a function of mass M and age T suggests that clusters get eroded or dispersed in a regular way over time, such that the cluster number decreases inversely as an approximate power law with T within each fixed interval of M. This power law is inconsistent with standard dispersal mechanisms such as cluster evaporation and cloud collisions. In the conventional interpretation, it requires the unlikely situation where diverse mechanisms stitch together over time in a way that is independent of environment or M. Here, we consider another model in which the large-scale distribution of gas in each star-forming region plays an important role. We note that star clusters form with positional and temporal correlations in giant cloud complexes, and suggest that these complexes dominate the tidal force and collisional influence on a cluster during its first several hundred million years. Because the cloud complex density decreases regularly with position from the cluster birth site, the harassment and collision rates between the cluster and the cloud pieces decrease regularly with age as the cluster drifts. This decrease is typically a power law of the form required to explain the mass-age distribution. We reproduce this distribution for a variety of cases, including rapid disruption, slow erosion, combinations of these two, cluster-cloud collisions, cluster disruption by hierarchical disassembly, and partial cluster disruption. We also consider apparent cluster mass loss by fading below the surface brightness limit of a survey. In all cases, the observed log M-log T diagram can be reproduced under reasonable assumptions.

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

Science.gov (United States)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

Structural and Functional Characterization of an Archaeal Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-associated Complex for Antiviral Defense (CASCADE)

DEFF Research Database (Denmark)

Lintner, Nathanael G; Kerou, Melina; Brumfield, Susan K

2011-01-01

In response to viral infection, many prokaryotes incorporate fragments of virus-derived DNA into loci called clustered regularly interspaced short palindromic repeats (CRISPRs). The loci are then transcribed, and the processed CRISPR transcripts are used to target invading viral DNA and RNA....... The Escherichia coli "CRISPR-associated complex for antiviral defense" (CASCADE) is central in targeting invading DNA. Here we report the structural and functional characterization of an archaeal CASCADE (aCASCADE) from Sulfolobus solfataricus. Tagged Csa2 (Cas7) expressed in S. solfataricus co-purifies with Cas5......a-, Cas6-, Csa5-, and Cas6-processed CRISPR-RNA (crRNA). Csa2, the dominant protein in aCASCADE, forms a stable complex with Cas5a. Transmission electron microscopy reveals a helical complex of variable length, perhaps due to substoichiometric amounts of other CASCADE components. A recombinant Csa2...

Clustering Millions of Faces by Identity.

Science.gov (United States)

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

2018-02-01

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

Cluster processing for 16Mb DRAM production

International Nuclear Information System (INIS)

Bergendahl, A.; Horak, D.

1989-01-01

Multichamber and in-situ technology are used to meet the challenge of manufacturing 16-Mb cost/performance DRAMs. The 16-Mb fabrication process is more complex than earlier 1-Mb and 4-Mb chips. Clustering of sequential process steps effectively compensates for both manufacturing complexity and foreign-material (FM) related defect densities. The development time of clusters combining new processes and equipment in multiple automated steps is nearly as long as the product development cycle. This necessitates codevelopment of manufacturing process cluster with technology integration while addressing the factors influencing FM defect generation, processing turnaround time (TAT), manufacturing costs, yield and array cell and support device designs. The advantages of multichamber and in situ processing have resulted in their application throughout the entire 16-Mb DRAM process as appropriate equipment becomes available

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

Science.gov (United States)

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

2018-04-01

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

Time-resolved explosion of intense-laser-heated clusters.

Science.gov (United States)

Kim, K Y; Alexeev, I; Parra, E; Milchberg, H M

2003-01-17

We investigate the femtosecond explosive dynamics of intense laser-heated argon clusters by measuring the cluster complex transient polarizability. The time evolution of the polarizability is characteristic of competition in the optical response between supercritical and subcritical density regions of the expanding cluster. The results are consistent with time-resolved Rayleigh scattering measurements, and bear out the predictions of a recent laser-cluster interaction model [H. M. Milchberg, S. J. McNaught, and E. Parra, Phys. Rev. E 64, 056402 (2001)

Time-resolved explosion of intense-laser-heated clusters

International Nuclear Information System (INIS)

Kim, K.Y.; Alexeev, I.; Parra, E.; Milchberg, H.M.

2003-01-01

We investigate the femtosecond explosive dynamics of intense laser-heated argon clusters by measuring the cluster complex transient polarizability. The time evolution of the polarizability is characteristic of competition in the optical response between supercritical and subcritical density regions of the expanding cluster. The results are consistent with time-resolved Rayleigh scattering measurements, and bear out the predictions of a recent laser-cluster interaction model [H. M. Milchberg, S. J. McNaught, and E. Parra, Phys. Rev. E 64, 056402 (2001)

Clustering potential of agriculture in Lviv region

Directory of Open Access Journals (Sweden)

N.A. Tsymbalista

2015-03-01

Full Text Available The paper emphasizes the need to stimulate the development of integration processes in agro-industrial complex of Ukraine. The advantages of the cluster model of integration are shown: along with the growth of competitiveness of agricultural products, it helps to increase the efficiency of inventory management of material flows, as well as to expand opportunities to attract investment and to implement innovation in agricultural production. Clusters also help to reduce transaction costs by establishing an optimal cooperation between the contracting parties. The theoretical essentiality of agro-industrial clusters is studied and a conceptual model of that kind of clusters is shown. The preconditions of clustering of agriculture in Lviv region are analyzed and feasibility of specific methods of statistical analysis to identify localization areas of the potential members of cluster-forming blocks of regional food clusters is verified. Cluster analysis is carried out to identify potential cluster-forming areas in the region in various sectors of agricultural production.

Exotic cluster structures on

CERN Document Server

Gekhtman, M; Vainshtein, A

2017-01-01

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

Efficient clustering aggregation based on data fragments.

Science.gov (United States)

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

2012-06-01

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

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

Science.gov (United States)

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

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

PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA

Directory of Open Access Journals (Sweden)

Y. Z. Gu

2017-09-01

Full Text Available Massive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective in finding clusters, becomes an important clustering approaches in the trajectory data mining. However, the traditional spectral clustering lacks the temporal expansion on the algorithm and limited in its applicability to large-scale problems due to its high computational complexity. This paper presents a parallel spatiotemporal spectral clustering based on multiple acceleration solutions to make the algorithm more effective and efficient, the performance is proved due to the experiment carried out on the massive taxi trajectory dataset in Wuhan city, China.

A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis

Directory of Open Access Journals (Sweden)

Shaoning Li

2017-01-01

Full Text Available In the fields of geographic information systems (GIS and remote sensing (RS, the clustering algorithm has been widely used for image segmentation, pattern recognition, and cartographic generalization. Although clustering analysis plays a key role in geospatial modelling, traditional clustering methods are limited due to computational complexity, noise resistant ability and robustness. Furthermore, traditional methods are more focused on the adjacent spatial context, which makes it hard for the clustering methods to be applied to multi-density discrete objects. In this paper, a new method, cell-dividing hierarchical clustering (CDHC, is proposed based on convex hull retraction. The main steps are as follows. First, a convex hull structure is constructed to describe the global spatial context of geospatial objects. Then, the retracting structure of each borderline is established in sequence by setting the initial parameter. The objects are split into two clusters (i.e., “sub-clusters” if the retracting structure intersects with the borderlines. Finally, clusters are repeatedly split and the initial parameter is updated until the terminate condition is satisfied. The experimental results show that CDHC separates the multi-density objects from noise sufficiently and also reduces complexity compared to the traditional agglomerative hierarchical clustering algorithm.

An analysis of hospital brand mark clusters.

Science.gov (United States)

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

2010-07-01

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

Peeking Network States with Clustered Patterns

Energy Technology Data Exchange (ETDEWEB)

Kim, Jinoh [Texas A & M Univ., Commerce, TX (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-10-20

Network traffic monitoring has long been a core element for effec- tive network management and security. However, it is still a chal- lenging task with a high degree of complexity for comprehensive analysis when considering multiple variables and ever-increasing traffic volumes to monitor. For example, one of the widely con- sidered approaches is to scrutinize probabilistic distributions, but it poses a scalability concern and multivariate analysis is not gen- erally supported due to the exponential increase of the complexity. In this work, we propose a novel method for network traffic moni- toring based on clustering, one of the powerful deep-learning tech- niques. We show that the new approach enables us to recognize clustered results as patterns representing the network states, which can then be utilized to evaluate “similarity” of network states over time. In addition, we define a new quantitative measure for the similarity between two compared network states observed in dif- ferent time windows, as a supportive means for intuitive analysis. Finally, we demonstrate the clustering-based network monitoring with public traffic traces, and show that the proposed approach us- ing the clustering method has a great opportunity for feasible, cost- effective network monitoring.

Robustness and structure of complex networks

Science.gov (United States)

Shao, Shuai

This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks

Quick detection of QRS complexes and R-waves using a wavelet transform and K-means clustering.

Science.gov (United States)

Xia, Yong; Han, Junze; Wang, Kuanquan

2015-01-01

Based on the idea of telemedicine, 24-hour uninterrupted monitoring on electrocardiograms (ECG) has started to be implemented. To create an intelligent ECG monitoring system, an efficient and quick detection algorithm for the characteristic waveforms is needed. This paper aims to give a quick and effective method for detecting QRS-complexes and R-waves in ECGs. The real ECG signal from the MIT-BIH Arrhythmia Database is used for the performance evaluation. The method proposed combined a wavelet transform and the K-means clustering algorithm. A wavelet transform is adopted in the data analysis and preprocessing. Then, based on the slope information of the filtered data, a segmented K-means clustering method is adopted to detect the QRS region. Detection of the R-peak is based on comparing the local amplitudes in each QRS region, which is different from other approaches, and the time cost of R-wave detection is reduced. Of the tested 8 records (total 18201 beats) from the MIT-BIH Arrhythmia Database, an average R-peak detection sensitivity of 99.72 and a positive predictive value of 99.80% are gained; the average time consumed detecting a 30-min original signal is 5.78s, which is competitive with other methods.

Anomalous properties of technetium clusters

International Nuclear Information System (INIS)

Kryuchkov, S.V.

1985-01-01

On the basis of critical evaluation of literature data in the field of chemistry of technetium cluster compounds with ligands of a weak field a conclusion is made on specific, ''anomalous'' properties of technetium cluster complexes which consist in an increased ability of the given element to the formation of a series of binuclear and multinuclear clusters, similar in composition and structure and easily transforming in each other. The majority of technetium clusters unlike similar compounds of other elements are paramagnetic with one unpaired electron on ''metallic'' MO of loosening type. All theoretical conceptions known today on the electronic structure of technetium clusters are considered. It is pointed out, that the best results in the explanation of ''anomalous'' properties of technetium clusters can be obtained in the framework of nonempirical methods of self-consistent field taking into account configuration interactions. It is also shown, that certain properties of technetium clusters can be explained on the basis of qualitative model of Coulomb repulsion of metal atoms in clusters. The conclusion is made, that technetium position in the Periodic table, as well as recently detected technetium property to the decrease of effective charge on its atoms during M-M bond formation promote a high ability of the element to cluster formation both with weak field ligands and with strong field one

Experimental studies of the chemistry of metal clusters

International Nuclear Information System (INIS)

Parks, E.K.; Riley, S.J.

1988-01-01

The procedures for studying chemical reactions of metal clusters in a continuous-flow reactor are described, and examples of such studies are given. Experiments to be discussed include kinetics and thermodynamics measurements, and determination of the composition of clusters saturated with various adsorbate reagents. Specific systems to be covered include the reaction of iron clusters with ammonia and with hydrogen, the reaction of nickel clusters with hydrogen and with ammonia, and the reaction of platinum clusters with ethylene. The last two reactions are characterized by complex, multi-step processes that lead to adsorbate decomposition and hydrogen desorption from the clusters. Methods for probing these processes will be discussed. 26 refs., 8 figs

Computer simulations of dendrimer-polyelectrolyte complexes.

Science.gov (United States)

Pandav, Gunja; Ganesan, Venkat

2014-08-28

We carry out a systematic analysis of static properties of the clusters formed by complexation between charged dendrimers and linear polyelectrolyte (LPE) chains in a dilute solution under good solvent conditions. We use single chain in mean-field simulations and analyze the structure of the clusters through radial distribution functions of the dendrimer, cluster size, and charge distributions. The effects of LPE length, charge ratio between LPE and dendrimer, the influence of salt concentration, and the dendrimer generation number are examined. Systems with short LPEs showed a reduced propensity for aggregation with dendrimers, leading to formation of smaller clusters. In contrast, larger dendrimers and longer LPEs lead to larger clusters with significant bridging. Increasing salt concentration was seen to reduce aggregation between dendrimers as a result of screening of electrostatic interactions. Generally, maximum complexation was observed in systems with an equal amount of net dendrimer and LPE charges, whereas either excess LPE or dendrimer concentrations resulted in reduced clustering between dendrimers.

Statistical Issues in Galaxy Cluster Cosmology

Science.gov (United States)

Mantz, Adam

2013-01-01

The number and growth of massive galaxy clusters are sensitive probes of cosmological structure formation. Surveys at various wavelengths can detect clusters to high redshift, but the fact that cluster mass is not directly observable complicates matters, requiring us to simultaneously constrain scaling relations of observable signals with mass. The problem can be cast as one of regression, in which the data set is truncated, the (cosmology-dependent) underlying population must be modeled, and strong, complex correlations between measurements often exist. Simulations of cosmological structure formation provide a robust prediction for the number of clusters in the Universe as a function of mass and redshift (the mass function), but they cannot reliably predict the observables used to detect clusters in sky surveys (e.g. X-ray luminosity). Consequently, observers must constrain observable-mass scaling relations using additional data, and use the scaling relation model in conjunction with the mass function to predict the number of clusters as a function of redshift and luminosity.

Laval nozzles for cluster-jet targets

Energy Technology Data Exchange (ETDEWEB)

Grieser, Silke; Bonaventura, Daniel; Hergemoeller, Ann-Katrin; Hetz, Benjamin; Koehler, Esperanza; Lessmann, Lukas; Khoukaz, Alfons [Institut fuer Kernphysik, Westfaelische Wilhelms-Universitaet Muenster, 48149 Muenster (Germany)

2016-07-01

Cluster-jet targets are highly suited for storage ring experiments due to the fact that they provide high and constant beam densities. Therefore, a cluster-jet target is planned to be the first internal target for the PANDA experiment at FAIR. A cluster source generates a continuous flow of cryogenic solid clusters by the expansion of pre-cooled gases within fine Laval nozzles. For the production of clusters the geometry of the nozzle is crucial. The production of such nozzles with their complex inner geometry represents a major technical challenge. The possibility to produce new fine Laval nozzles ensures the operation of cluster-jet targets, e.g. for the PANDA experiment, and opens the way for future investigations on the cluster production process to match the required targets performance. Optimizations on the recently developed production process and the fabrication of new glass nozzles were done. Initial measurements of these nozzles at the PANDA cluster-jet target prototype and the investigation of the cluster beam origin within the nozzle will be presented and discussed. For the future more Laval nozzles with different geometries will be produced and additional measurements with these new nozzles at the PANDA cluster-jet target prototype towards higher performance will be realized.

Evaluation of clustering algorithms for protein-protein interaction networks

Directory of Open Access Journals (Sweden)

van Helden Jacques

2006-11-01

Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This

Twenty five years of clusters -- from Bochum to Strasbourg

International Nuclear Information System (INIS)

Betts, R.R.; Chicago Univ., IL

1994-01-01

Developments in the area of clustering aspects of nuclear structure and reactions over the past twenty-five years are reviewed. The viewpoint is that the nucleus is an assembly of clusters. The question is whether clusters actually exist in the nucleus. Although there is abundant evidence for this in light nuclei, the situation for more complex clusters in heavier nuclei is much worse. Differential cross sections for scattering of alpha particles and heavy ions are shown

The Raman and vibronic activity of intermolecular vibrations in aromatic-containing complexes and clusters

International Nuclear Information System (INIS)

Maxton, P.M.; Schaeffer, M.W.; Ohline, S.M.; Kim, W.; Venturo, V.A.; Felker, P.M.

1994-01-01

Theoretical and experimental results pertaining to the excitation of intermolecular vibrations in the Raman and vibronic spectra of aromatic-containing, weakly bound complexes and clusters are reported. The theoretical analysis of intermolecular Raman activity is based on the assumption that the polarizability tensor of a weakly bound species is given by the sum of the polarizability tensors of its constituent monomers. The analysis shows that the van der Waals bending fundamentals in aromatic--rare gas complexes may be expected to be strongly Raman active. More generally, it predicts strong Raman activity for intermolecular vibrations that involve the libration or internal rotation of monomer moieties having appreciable permanent polarizability anisotropies. The vibronic activity of intermolecular vibrations in aromatic-rare gas complexes is analyzed under the assumption that every vibronic band gains its strength from an aromatic-localized transition. It is found that intermolecular vibrational excitations can accompany aromatic-localized vibronic excitations by the usual Franck--Condon mechanism or by a mechanism dependent on the librational amplitude of the aromatic moiety during the course of the pertinent intermolecular vibration. The latter mechanism can impart appreciable intensity to bands that are forbidden by rigid-molecule symmetry selection rules. The applicability of such rules is therefore called into question. Finally, experimental spectra of intermolecular transitions, obtained by mass-selective, ionization-detected stimulated Raman spectroscopies, are reported for benzene--X (X=Ar, --Ar 2 , N 2 , HCl, CO 2 , and --fluorene), fluorobenzene--Ar and --Kr, aniline--Ar, and fluorene--Ar and --Ar 2 . The results support the conclusions of the theoretical analyses and provide further evidence for the value of Raman methods in characterizing intermolecular vibrational level structures

Lactobacillus plantarum gene clusters encoding putative cell-surface protein complexes for carbohydrate utilization are conserved in specific gram-positive bacteria

Directory of Open Access Journals (Sweden)

Muscariello Lidia

2006-05-01

Full Text Available Abstract Background Genomes of gram-positive bacteria encode many putative cell-surface proteins, of which the majority has no known function. From the rapidly increasing number of available genome sequences it has become apparent that many cell-surface proteins are conserved, and frequently encoded in gene clusters or operons, suggesting common functions, and interactions of multiple components. Results A novel gene cluster encoding exclusively cell-surface proteins was identified, which is conserved in a subgroup of gram-positive bacteria. Each gene cluster generally has one copy of four new gene families called cscA, cscB, cscC and cscD. Clusters encoding these cell-surface proteins were found only in complete genomes of Lactobacillus plantarum, Lactobacillus sakei, Enterococcus faecalis, Listeria innocua, Listeria monocytogenes, Lactococcus lactis ssp lactis and Bacillus cereus and in incomplete genomes of L. lactis ssp cremoris, Lactobacillus casei, Enterococcus faecium, Pediococcus pentosaceus, Lactobacillius brevis, Oenococcus oeni, Leuconostoc mesenteroides, and Bacillus thuringiensis. These genes are neither present in the genomes of streptococci, staphylococci and clostridia, nor in the Lactobacillus acidophilus group, suggesting a niche-specific distribution, possibly relating to association with plants. All encoded proteins have a signal peptide for secretion by the Sec-dependent pathway, while some have cell-surface anchors, novel WxL domains, and putative domains for sugar binding and degradation. Transcriptome analysis in L. plantarum shows that the cscA-D genes are co-expressed, supporting their operon organization. Many gene clusters are significantly up-regulated in a glucose-grown, ccpA-mutant derivative of L. plantarum, suggesting catabolite control. This is supported by the presence of predicted CRE-sites upstream or inside the up-regulated cscA-D gene clusters. Conclusion We propose that the CscA, CscB, CscC and Csc

Software refactoring at the package level using clustering techniques

KAUST Repository

Alkhalid, A.

2011-01-01

Enhancing, modifying or adapting the software to new requirements increases the internal software complexity. Software with high level of internal complexity is difficult to maintain. Software refactoring reduces software complexity and hence decreases the maintenance effort. However, software refactoring becomes quite challenging task as the software evolves. The authors use clustering as a pattern recognition technique to assist in software refactoring activities at the package level. The approach presents a computer aided support for identifying ill-structured packages and provides suggestions for software designer to balance between intra-package cohesion and inter-package coupling. A comparative study is conducted applying three different clustering techniques on different software systems. In addition, the application of refactoring at the package level using an adaptive k-nearest neighbour (A-KNN) algorithm is introduced. The authors compared A-KNN technique with the other clustering techniques (viz. single linkage algorithm, complete linkage algorithm and weighted pair-group method using arithmetic averages). The new technique shows competitive performance with lower computational complexity. © 2011 The Institution of Engineering and Technology.

Structural oxidation state studies of the manganese cluster in the oxygen evolving complex of photosystem II

Energy Technology Data Exchange (ETDEWEB)

Liang, Wenchuan [Univ. of California, Berkeley, CA (United States)

1994-11-01

X-ray absorption spectroscopy (XAS) was performed on Photosystem II (PSII)-enriched membranes prepared from spinach to explore: (1) the correlation between structure and magnetic spin state of the Mn cluster in the oxygen evolving complex (OEC) in the S₂ state; and (2) the oxidation state changes of the Mn cluster in the flash-induced S-states. The structure of the Mn cluster in the S₂ state with the g~4 electron paramagnetic resonance (EPR) signal (S₂-g4 state) was compared with that in the S₂ state with multiline signal (S₂-MLS state) and the S₁ state. The S₂-g4 state has a higher XAS inflection point energy than that of the S₁ state, indicating the oxidation of Mn in the advance from the S₁ to the S₂-g4 state. Differences in the edge shape and in the extended X-ray absorption fine structure (EXAFS) show that the structure of the Mn cluster in the S₂-g4 state is different from that in the S₂-MLS or the S₁ state. In the S₂-g4 state, the second shell of backscatterers from the Mn absorber contains two Mn-Mn distances of 2.73 Å and 2.85 Å. Very little distance disorder exists in the second shell of the S₁ or S₂-MLS states. The third shell of the S₂-g4 state at about 3.3 Å also contains increased heterogeneity relative to that of the S₂-MLS or the S₁ state. Various S-states were prepared at room-temperature by saturating, single-turnover flashes. The flash-dependent oscillation in the amplitude of the MLS was used to characterize the S-state composition and to construct "pure" S-state Mn K-edge spectra. The edge position shifts to higher energy by 1.8 eV upon the S₁ → S₂ transition.

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

Science.gov (United States)

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

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

Featured Image: New Detail in the Toothbrush Cluster

Science.gov (United States)

Kohler, Susanna

2018-01-01

This spectacular composite (click here for the full image) reveals the galaxy cluster 1RXS J0603.3+4214, known as the Toothbrush cluster due to the shape of its most prominent radio relic. Featured in a recent publication led by Kamlesh Rajpurohit (Thuringian State Observatory, Germany), this image contains new Very Large Array (VLA) 1.5-GHz observations (red) showing the radio emission within the cluster. This is composited with a Chandra view of the X-ray emitting gas of the cluster (blue) and an optical image of the background from Subaru data. The new deep VLA data totaling 26 hours of observations provides a detailed look at the complex structure within the Toothbrush relic, revealing enigmatic filaments and twists (see below). This new data will help us to explore the possible merger history of this cluster, which is theorized to have caused the unusual shapes we see today. For more information, check out the original article linked below.High resolution VLA 12 GHz image of the Toothbrush showing the complex, often filamentary structures. [Rajpurohit et al. 2018]CitationK. Rajpurohit et al 2018 ApJ 852 65. doi:10.3847/1538-4357/aa9f13

Rapid identification of Enterobacter hormaechei and Enterobacter cloacae genetic cluster III.

Science.gov (United States)

Ohad, S; Block, C; Kravitz, V; Farber, A; Pilo, S; Breuer, R; Rorman, E

2014-05-01

Enterobacter cloacae complex bacteria are of both clinical and environmental importance. Phenotypic methods are unable to distinguish between some of the species in this complex, which often renders their identification incomplete. The goal of this study was to develop molecular assays to identify Enterobacter hormaechei and Ent. cloacae genetic cluster III which are relatively frequently encountered in clinical material. The molecular assays developed in this study are qPCR technology based and served to identify both Ent. hormaechei and Ent. cloacae genetic cluster III. qPCR results were compared to hsp60 sequence analysis. Most clinical isolates were assigned to Ent. hormaechei subsp. steigerwaltii and Ent. cloacae genetic cluster III. The latter was proportionately more frequently isolated from bloodstream infections than from other material (P < 0·05). The qPCR assays detecting Ent. hormaechei and Ent. cloacae genetic cluster III demonstrated high sensitivity and specificity. The presented qPCR assays allow accurate and rapid identification of clinical isolates of the Ent. cloacae complex. The improved identifications obtained can specifically assist analysis of Ent. hormaechei and Ent. cloacae genetic cluster III in nosocomial outbreaks and can promote rapid environmental monitoring. An association was observed between Ent. cloacae cluster III and systemic infection that deserves further attention. © 2014 The Society for Applied Microbiology.

Dynamic multifactor clustering of financial networks

Science.gov (United States)

Ross, Gordon J.

2014-02-01

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

CTEx Beowulf cluster for MCNP performance

International Nuclear Information System (INIS)

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

2011-01-01

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

Projection-based curve clustering

International Nuclear Information System (INIS)

Auder, Benjamin; Fischer, Aurelie

2012-01-01

This paper focuses on unsupervised curve classification in the context of nuclear industry. At the Commissariat a l'Energie Atomique (CEA), Cadarache (France), the thermal-hydraulic computer code CATHARE is used to study the reliability of reactor vessels. The code inputs are physical parameters and the outputs are time evolution curves of a few other physical quantities. As the CATHARE code is quite complex and CPU time-consuming, it has to be approximated by a regression model. This regression process involves a clustering step. In the present paper, the CATHARE output curves are clustered using a k-means scheme, with a projection onto a lower dimensional space. We study the properties of the empirically optimal cluster centres found by the clustering method based on projections, compared with the 'true' ones. The choice of the projection basis is discussed, and an algorithm is implemented to select the best projection basis among a library of orthonormal bases. The approach is illustrated on a simulated example and then applied to the industrial problem. (authors)

Swarm controlled emergence for ant clustering

DEFF Research Database (Denmark)

Scheidler, Alexander; Merkle, Daniel; Middendorf, Martin

2013-01-01

.g. moving robots, and clustering algorithms. Design/methodology/approach: Different types of control agents for that ant clustering model are designed by introducing slight changes to the behavioural rules of the normal agents. The clustering behaviour of the resulting swarms is investigated by extensive...... for future research to investigate the application of the method in other swarm systems. Swarm controlled emergence might be applied to control emergent effects in computing systems that consist of many autonomous components which make decentralized decisions based on local information. Practical...... simulation studies. Findings: It is shown that complex behavior can emerge in systems with two types of agents (normal agents and control agents). For a particular behavior of the control agents, an interesting swarm size dependent effect was found. The behaviour prevents clustering when the number...

Architecture of the Human Mitochondrial Iron-Sulfur Cluster Assembly Machinery*

Science.gov (United States)

Gakh, Oleksandr; Ranatunga, Wasantha; Smith, Douglas Y.; Ahlgren, Eva-Christina; Al-Karadaghi, Salam; Thompson, James R.; Isaya, Grazia

2016-01-01

Fe-S clusters, essential cofactors needed for the activity of many different enzymes, are assembled by conserved protein machineries inside bacteria and mitochondria. As the architecture of the human machinery remains undefined, we co-expressed in Escherichia coli the following four proteins involved in the initial step of Fe-S cluster synthesis: FXN42–210 (iron donor); [NFS1]·[ISD11] (sulfur donor); and ISCU (scaffold upon which new clusters are assembled). We purified a stable, active complex consisting of all four proteins with 1:1:1:1 stoichiometry. Using negative staining transmission EM and single particle analysis, we obtained a three-dimensional model of the complex with ∼14 Å resolution. Molecular dynamics flexible fitting of protein structures docked into the EM map of the model revealed a [FXN42–210]24·[NFS1]24·[ISD11]24·[ISCU]24 complex, consistent with the measured 1:1:1:1 stoichiometry of its four components. The complex structure fulfills distance constraints obtained from chemical cross-linking of the complex at multiple recurring interfaces, involving hydrogen bonds, salt bridges, or hydrophobic interactions between conserved residues. The complex consists of a central roughly cubic [FXN42–210]24·[ISCU]24 sub-complex with one symmetric ISCU trimer bound on top of one symmetric FXN42–210 trimer at each of its eight vertices. Binding of 12 [NFS1]2·[ISD11]2 sub-complexes to the surface results in a globular macromolecule with a diameter of ∼15 nm and creates 24 Fe-S cluster assembly centers. The organization of each center recapitulates a previously proposed conserved mechanism for sulfur donation from NFS1 to ISCU and reveals, for the first time, a path for iron donation from FXN42–210 to ISCU. PMID:27519411

Implementing a complex intervention to support personal recovery: a qualitative study nested within a cluster randomised controlled trial.

Science.gov (United States)

Leamy, Mary; Clarke, Eleanor; Le Boutillier, Clair; Bird, Victoria; Janosik, Monika; Sabas, Kai; Riley, Genevieve; Williams, Julie; Slade, Mike

2014-01-01

To investigate staff and trainer perspectives on the barriers and facilitators to implementing a complex intervention to help staff support the recovery of service users with a primary diagnosis of psychosis in community mental health teams. Process evaluation nested within a cluster randomised controlled trial (RCT). 28 interviews with mental health care staff, 3 interviews with trainers, 4 focus groups with intervention teams and 28 written trainer reports. 14 community-based mental health teams in two UK sites (one urban, one semi-rural) who received the intervention. The factors influencing the implementation of the intervention can be organised under two over-arching themes: Organisational readiness for change and Training effectiveness. Organisational readiness for change comprised three sub-themes: NHS Trust readiness; Team readiness; and Practitioner readiness. Training effectiveness comprised three sub-themes: Engagement strategies; Delivery style and Modelling recovery principles. Three findings can inform future implementation and evaluation of complex interventions. First, the underlying intervention model predicted that three areas would be important for changing practice: staff skill development; intention to implement; and actual implementation behaviour. This study highlighted the importance of targeting the transition from practitioners' intent to implement to actual implementation behaviour, using experiential learning and target setting. Second, practitioners make inferences about organisational commitment by observing the allocation of resources, Knowledge Performance Indicators and service evaluation outcome measures. These need to be aligned with recovery values, principles and practice. Finally, we recommend the use of organisational readiness tools as an inclusion criteria for selecting both organisations and teams in cluster RCTs. We believe this would maximise the likelihood of adequate implementation and hence reduce waste in research

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

Science.gov (United States)

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Jinsong Gui

2016-09-01

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

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

Science.gov (United States)

Leon, Stéphane; Bergond, Gilles; Vallenari, Antonella

1999-04-01

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

A Data-Driven Bidding Model for a Cluster of Price-Responsive Consumers of Electricity

DEFF Research Database (Denmark)

Saez Gallego, Javier; Morales González, Juan Miguel; Zugno, Marco

2016-01-01

This paper deals with the market-bidding problem of a cluster of price-responsive consumers of electricity. We develop an inverse optimization scheme that, recast as a bilevel programming problem, uses price-consumption data to estimate the complex market bid that best captures the price......-response of the cluster. The complex market bid is defined as a series of marginal utility functions plus some constraints on demand, such as maximum pick-up and drop-off rates. The proposed modeling approach also leverages information on exogenous factors that may influence the consumption behavior of the cluster, e...... can be largely captured in the form of a complex market bid, so that this could be ultimately used for the cluster to participate in the wholesale electricity market....

Improved Ant Colony Clustering Algorithm and Its Performance Study

Science.gov (United States)

Gao, Wei

2016-01-01

Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533

A highly efficient nano-cluster artificial peroxidase and its direct electrochemistry on a nano complex modified glassy carbon electrode.

Science.gov (United States)

Hong, Jun; Wang, Wei; Huang, Kun; Yang, Wei-Yun; Zhao, Ying-Xue; Xiao, Bao-Lin; Gao, Yun-Fei; Moosavi-Movahedi, Zainab; Ghourchian, Hedayatollah; Moosavi-Movahedi, Ali Akbar

2012-01-01

A nano-cluster with highly efficient peroxide activity was constructed based on nafion (NF) and cytochrome c (Cyt c). UV-Vis spectrometry and transmission electron microscopy (TEM) methods were utilized for characterization of the nano-structured enzyme or artificial peroxidase (AP). The nano-cluster was composed of a Chain-Ball structure, with an average ball size of about 40 nm. The Michaelis-Menten (K(m)) and catalytic rate (k(cat)) constants of the AP were determined to be 2.5 ± 0.4 µM and 0.069 ± 0.001 s(-1), respectively, in 50 mM PBS at pH 7.0. The catalytic efficiency of the AP was evaluated to be 0.028 ± 0.005 µM(-1) s(-1), which was 39 ± 5% as efficient as the native horseradish peroxidase (HRP). The AP was also immobilized on a functional multi-wall carbon nanotube (MWNCTs)-gold colloid nanoparticles (AuNPs) nano-complex modified glassy carbon (GC) electrode. The cyclic voltammetry of AP on the nano complex modified GC electrode showed a pair of well-defined redox peaks with a formal potential (E°') of -45 ± 2 mV (vs. Ag/AgCl) at a scan rate of 0.05 V/s. The heterogeneous electron transfer rate constant (k(s)) was evaluated to be 0.65 s(-1). The surface concentration of electroactive AP on GC electrode (Γ) was 7 × 10(-10) mol cm(-2). The apparent Michaelis-Menten constant (K(m)(app)) was 0.23 nM.

Triggered cluster formation in the RMC

Science.gov (United States)

Li, Jin Zeng; Smith, Michael D.

An investigation based on data from the spatially complete 2MASS Survey reveals that a remarkable burst of clustered star formation is taking place throughout the south-east quadrant of the Rosette Molecular Cloud. Compact clusters are forming in a multi-seeded mode, in parallel and at various places. In addition, sparse aggregates of embedded young stars are extensively distributed. Here we present the primary results and implications for high-mass and clustered star formation in this giant molecular cloud. In particular, we incorporate for the first time the birth of medium to low-mass stars into the scenario of sequential formation of OB clusters. Following the emergence of the young OB cluster NGC 2244, a variety of manifestations of forming clusters of medium to high mass appear in the vicinity of the swept-up layer of the H II region as well as further into the molecular cloud. The embedded clusters appear to form in a structured manner, which suggests they follow tracks laid out by the decay of macroturbulence. We address the possible origins of the turbulence. This leads us to propose a tree model to interpret the neat spatial distribution of clusters within a large section of the Rosette complex. Prominent new generation OB clusters are identified at the root of the tree pattern.

Taxonomical analysis of the Cancer cluster of galaxies

International Nuclear Information System (INIS)

Perea, J.; Olmo, A. del; Moles, M.

1986-01-01

A description is presented of the Cancer cluster of galaxies, based on a taxonomical analysis in (α,delta, Vsub(r)) space. Earlier results by previous authors on the lack of dynamical entity of the cluster are confirmed. The present analysis points out the existence of a binary structure in the most populated region of the complex. (author)

Linked supramolecular building blocks for enhanced cluster formation

DEFF Research Database (Denmark)

McLellan, Ross; Palacios, Maria A.; Beavers, Christine M.

2015-01-01

the complex assembly process. The ability to covalently link calix[4]arenes at the methylene bridge provides significantly improved control over the introduction of different metal centres to resulting cluster motifs. Clusters assembled from bis-calix[4]-arenes and transition metal ions or 3d-4 f combinations......(Figure Presented). Methylene-bridged calix[4]arenes have emerged as extremely versatile ligand supports in the formation of new polymetallic clusters possessing fascinating magnetic properties. Metal ion binding rules established for this building block allow one to partially rationalise...

Characterization of Glutaredoxin Fe-S Cluster-Binding Interactions Using Circular Dichroism Spectroscopy.

Science.gov (United States)

Albetel, Angela-Nadia; Outten, Caryn E

2018-01-01

Monothiol glutaredoxins (Grxs) with a conserved Cys-Gly-Phe-Ser (CGFS) active site are iron-sulfur (Fe-S) cluster-binding proteins that interact with a variety of partner proteins and perform crucial roles in iron metabolism including Fe-S cluster transfer, Fe-S cluster repair, and iron signaling. Various analytical and spectroscopic methods are currently being used to monitor and characterize glutaredoxin Fe-S cluster-dependent interactions at the molecular level. The electronic, magnetic, and vibrational properties of the protein-bound Fe-S cluster provide a convenient handle to probe the structure, function, and coordination chemistry of Grx complexes. However, some limitations arise from sample preparation requirements, complexity of individual techniques, or the necessity for combining multiple methods in order to achieve a complete investigation. In this chapter, we focus on the use of UV-visible circular dichroism spectroscopy as a fast and simple initial approach for investigating glutaredoxin Fe-S cluster-dependent interactions. © 2018 Elsevier Inc. All rights reserved.

WESTERN CHARPATHIAN RURAL MOUNTAIN TOURISM MAPPING THROUGH CLUSTER METHODOLOGY

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Elena TOMA

2013-10-01

Full Text Available Rural tourism from Western Carpathian Mountain was characterized in the last years by a low occupancy rate and a decline in tourist arrivals, due, beside of the direct effects of economic crises, to the remote location of mountain villages and to the low quality of infrastructure. For this reason we consider that the implementation of complex and integrated products based on tour thematic circuits represents a real opportunity to develop local rural tourism industry. The aim of this paper is to identify which is the best networking solution, based on clustering analysis. The Multidimensional Scaling Method and Hierarchical Cluster Method permitted us to demonstrate and identify the best way of clustering, and, in this way, the best route for a potential tour touristic circuit. Reported to the counties from which the villages take part, the identified cluster concentrate 57.7% of rural touristic accommodations and 65.0% of tourist arrivals, but it has an occupancy rate of only 5.9%. By implementing new complex touristic products we consider that can be assured a rise of this touristic dimension of the cluster and we propose more in depth studies regarding the profile of the potential customers.

A CLUSTER IN THE MAKING: ALMA REVEALS THE INITIAL CONDITIONS FOR HIGH-MASS CLUSTER FORMATION

International Nuclear Information System (INIS)

Rathborne, J. M.; Contreras, Y.; Longmore, S. N.; Bastian, N.; Jackson, J. M.; Alves, J. F.; Bally, J.; Foster, J. B.; Garay, G.; Kruijssen, J. M. D.; Testi, L.; Walsh, A. J.

2015-01-01

G0.253+0.016 is a molecular clump that appears to be on the verge of forming a high-mass cluster: its extremely low dust temperature, high mass, and high density, combined with its lack of prevalent star formation, make it an excellent candidate for an Arches-like cluster in a very early stage of formation. Here we present new Atacama Large Millimeter/Sub-millimeter Array observations of its small-scale (∼0.07 pc) 3 mm dust continuum and molecular line emission from 17 different species that probe a range of distinct physical and chemical conditions. The data reveal a complex network of emission features with a complicated velocity structure: there is emission on all spatial scales, the morphology of which ranges from small, compact regions to extended, filamentary structures that are seen in both emission and absorption. The dust column density is well traced by molecules with higher excitation energies and critical densities, consistent with a clump that has a denser interior. A statistical analysis supports the idea that turbulence shapes the observed gas structure within G0.253+0.016. We find a clear break in the turbulent power spectrum derived from the optically thin dust continuum emission at a spatial scale of ∼0.1 pc, which may correspond to the spatial scale at which gravity has overcome the thermal pressure. We suggest that G0.253+0.016 is on the verge of forming a cluster from hierarchical, filamentary structures that arise from a highly turbulent medium. Although the stellar distribution within high-mass Arches-like clusters is compact, centrally condensed, and smooth, the observed gas distribution within G0.253+0.016 is extended, with no high-mass central concentration, and has a complex, hierarchical structure. If this clump gives rise to a high-mass cluster and its stars are formed from this initially hierarchical gas structure, then the resulting cluster must evolve into a centrally condensed structure via a dynamical process

Graphics Processing Unit Enhanced Parallel Document Flocking Clustering

Energy Technology Data Exchange (ETDEWEB)

Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL; ST Charles, Jesse Lee [ORNL

2010-01-01

Analyzing and clustering documents is a complex problem. One explored method of solving this problem borrows from nature, imitating the flocking behavior of birds. One limitation of this method of document clustering is its complexity O(n2). As the number of documents grows, it becomes increasingly difficult to generate results in a reasonable amount of time. In the last few years, the graphics processing unit (GPU) has received attention for its ability to solve highly-parallel and semi-parallel problems much faster than the traditional sequential processor. In this paper, we have conducted research to exploit this archi- tecture and apply its strengths to the flocking based document clustering problem. Using the CUDA platform from NVIDIA, we developed a doc- ument flocking implementation to be run on the NVIDIA GEFORCE GPU. Performance gains ranged from thirty-six to nearly sixty times improvement of the GPU over the CPU implementation.

Financial and economic aspects of strategic management of industrial cluster

Directory of Open Access Journals (Sweden)

Katrina B. Dobrova

2017-01-01

Full Text Available Purpose: the main purpose of the publication is to examine comprehensively the financial and economic aspects of the strategic management of the industrial cluster by the example of the clusters of the Corporation “Rostec” with the participation of enterprises of the defense industry complex. Methods: the methodology of the research is based on the collection and analysis of initial data and information, the article uses a systematic approach to the study of socio-economic processes and phenomena. The research is based on modern theory of competition, innovation, as well as the modern paradigm of cluster development of the economy. In preparing the study, practical materials from Corporation “Rostec”. Results: the article gives the notion of industrial cluster, outlines the the prospects for using the cluster approach in the implementation of import substitution programs. Industrial clusters are considered as a source of preservation of a unique engineering culture, the revival of the engineering class. The creation of clusters is very promising in the defense industry complex, where clusters are identified as the most important source of diversification of the complex. Separate financial and economic aspects of strategic management industrial cluster are discussed in more detail on the example of cluster initiatives of Corporation “Rosteс”. It is noted that for the development of “Rostec” industrial clusters, it is planned to form centers of key competencies by creating conditions for the development of highly effective cooperative and synergetic relationships among the cluster participants. Formed clusters will be able to demonstrate higher rates of economic growth. In addition, focused funding will allow more efficient distribution of federal budget funds, as well as investor funds, aimed at technological development of cluster participants. To achieve these goals, it was recommended to ensure proper selection of key

Electron-Poor Polar Intermetallics: Complex Structures, Novel Clusters, and Intriguing Bonding with Pronounced Electron Delocalization.

Science.gov (United States)

Lin, Qisheng; Miller, Gordon J

2018-01-16

complexity can be realized by small amounts of Li replacing Zn atoms in the parent binary compounds CaZn 2 , CaZn 3 , and CaZn 5 ; their phase formation and bonding schemes can be rationalized by Fermi surface-Brillouin zone interactions between nearly free-electron states. "Cation-rich", electron-poor polar intermetallics have emerged using rare earth metals as the electropositive ("cationic") component together metal/metalloid clusters that mimic the backbones of aromatic hydrocarbon molecules, which give evidence of extensive electronic delocalization and multicenter bonding. Thus, we can identify three distinct, valence electron-poor, polar intermetallic systems that have yielded unprecedented phases adopting novel structures containing complex clusters and intriguing bonding characteristics. In this Account, we summarize our recent specific progress in the developments of novel Au-rich BaAl 4 -type related structures, shown in the "gold-rich grid", lithiation-modulated Ca-Li-Zn phases stabilized by different bonding characteristics, and rare earth-rich polar intermetallics containing unprecedented hydrocarbon-like planar Co-Ge metal clusters and pronounced delocalized multicenter bonding. We will focus mainly on novel structural motifs, bonding analyses, and the role of valence electrons for phase stability.

Implementing a complex intervention to support personal recovery: a qualitative study nested within a cluster randomised controlled trial.

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Mary Leamy

Full Text Available OBJECTIVE: To investigate staff and trainer perspectives on the barriers and facilitators to implementing a complex intervention to help staff support the recovery of service users with a primary diagnosis of psychosis in community mental health teams. DESIGN: Process evaluation nested within a cluster randomised controlled trial (RCT. PARTICIPANTS: 28 interviews with mental health care staff, 3 interviews with trainers, 4 focus groups with intervention teams and 28 written trainer reports. SETTING: 14 community-based mental health teams in two UK sites (one urban, one semi-rural who received the intervention. RESULTS: The factors influencing the implementation of the intervention can be organised under two over-arching themes: Organisational readiness for change and Training effectiveness. Organisational readiness for change comprised three sub-themes: NHS Trust readiness; Team readiness; and Practitioner readiness. Training effectiveness comprised three sub-themes: Engagement strategies; Delivery style and Modelling recovery principles. CONCLUSIONS: Three findings can inform future implementation and evaluation of complex interventions. First, the underlying intervention model predicted that three areas would be important for changing practice: staff skill development; intention to implement; and actual implementation behaviour. This study highlighted the importance of targeting the transition from practitioners' intent to implement to actual implementation behaviour, using experiential learning and target setting. Second, practitioners make inferences about organisational commitment by observing the allocation of resources, Knowledge Performance Indicators and service evaluation outcome measures. These need to be aligned with recovery values, principles and practice. Finally, we recommend the use of organisational readiness tools as an inclusion criteria for selecting both organisations and teams in cluster RCTs. We believe this would

Tap and trill clusters in typical and protracted phonological development: Challenging segments in complex phonological environments. Introduction to the special issue.

Science.gov (United States)

Stemberger, Joseph Paul; Bernhardt, Barbara May

2018-01-01

The papers in this crosslinguistic issue address children's acquisition of word-initial rhotic clusters in languages with taps/trills, that is, the acquisition of challenging segments in complex environments. Several papers also include comparisons with singleton rhotics and/or /l/ as a singleton or in clusters. The studies are part of a larger investigation that uses similar methodologies across languages in order to enhance crosslinguistic comparability (Bernhardt and Stemberger, 2012, 2015). Participants for the current studies were monolingual preschoolers with typical or protracted phonological development who speak one of the following languages: Germanic (Icelandic/Swedish); Romance (Portuguese/Spanish); Slavic (Bulgarian/Slovenian) and Finno-Ugric (Hungarian). This introductory paper describes characteristics of taps/trills and general methodology across the studies, concluding with predicted patterns of acquisition. The seven papers that follow are in a sense the 'results' for this introduction. A concluding paper discusses major findings and their implications for theory, research and clinical practice.

Neurobiology and sleep disorders in cluster headache

DEFF Research Database (Denmark)

Barloese, Mads Christian Johannes

2015-01-01

Cluster headache is characterized by unilateral attacks of severe pain accompanied by cranial autonomic features. Apart from these there are also sleep-related complaints and strong chronobiological features. The interaction between sleep and headache is complex at any level and evidence suggests...... that it may be of critical importance in our understanding of primary headache disorders. In cluster headache several interactions between sleep and the severe pain attacks have already been proposed. Supported by endocrinological and radiological findings as well as the chronobiological features, predominant...... involvement of cardiac autonomic control. We conducted a questionnaire survey on 275 cluster headache patients and 145 controls as well an in-patient sleep study including 40 CH-patients and 25 healthy controls. The findings include: A distinct circannual connection between cluster occurrence and the amount...

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-03-01

. However, if we exclude clusters embedded in complex large-scale environments, we find that the velocity dispersion of the remaining clusters is as good an estimator of M{sub 200} as L{sub r}. The final C4 catalog will contain {approx_equal} 2500 clusters using the full SDSS data set and will represent one of the largest and most homogeneous samples of local clusters.

A Flocking Based algorithm for Document Clustering Analysis

Energy Technology Data Exchange (ETDEWEB)

Cui, Xiaohui [ORNL; Gao, Jinzhu [ORNL; Potok, Thomas E [ORNL

2006-01-01

Social animals or insects in nature often exhibit a form of emergent collective behavior known as flocking. In this paper, we present a novel Flocking based approach for document clustering analysis. Our Flocking clustering algorithm uses stochastic and heuristic principles discovered from observing bird flocks or fish schools. Unlike other partition clustering algorithm such as K-means, the Flocking based algorithm does not require initial partitional seeds. The algorithm generates a clustering of a given set of data through the embedding of the high-dimensional data items on a two-dimensional grid for easy clustering result retrieval and visualization. Inspired by the self-organized behavior of bird flocks, we represent each document object with a flock boid. The simple local rules followed by each flock boid result in the entire document flock generating complex global behaviors, which eventually result in a clustering of the documents. We evaluate the efficiency of our algorithm with both a synthetic dataset and a real document collection that includes 100 news articles collected from the Internet. Our results show that the Flocking clustering algorithm achieves better performance compared to the K- means and the Ant clustering algorithm for real document clustering.

Density functional study of carbon monoxide adsorption on small cationic, neutral, and anionic aluminum nitride clusters

Science.gov (United States)

Guo, Ling

CO adsorption on small cationic, neutral, and anionic (AlN)n (n = 1-6) clusters has been investigated using density functional theory in the generalized gradient approximation. Among various possible CO adsorption sites, an N on-top (onefold coordinated) site is found to be the most favorable one, irrespective of the charge state of the clusters. The adsorption energies of CO on the anionic (AlN)nCO (n = 2-4) clusters are greater than those on the neutral and cationic complexes. The adsorption energies on the cationic and neutral complexes reflect the odd-even oscillations, and the adsorption energies of CO on the cationic (AlN)nCO (n = 5, 6) clusters are greater than those on the neutral and anionic complexes. The adsorption energies for the different charge states decrease with increasing cluster size.

Reconstructing galaxy histories from globular clusters.

Science.gov (United States)

West, Michael J; Côté, Patrick; Marzke, Ronald O; Jordán, Andrés

2004-01-01

Nearly a century after the true nature of galaxies as distant 'island universes' was established, their origin and evolution remain great unsolved problems of modern astrophysics. One of the most promising ways to investigate galaxy formation is to study the ubiquitous globular star clusters that surround most galaxies. Globular clusters are compact groups of up to a few million stars. They generally formed early in the history of the Universe, but have survived the interactions and mergers that alter substantially their parent galaxies. Recent advances in our understanding of the globular cluster systems of the Milky Way and other galaxies point to a complex picture of galaxy genesis driven by cannibalism, collisions, bursts of star formation and other tumultuous events.

Cellular internalization and morphological analysis after intravenous injection of a highly hydrophilic octahedral rhenium cluster complex - a new promising X-ray contrast agent.

Science.gov (United States)

Krasilnikova, Anna A; Solovieva, Anastasiya O; Trifonova, Kristina E; Brylev, Konstantin A; Ivanov, Anton A; Kim, Sung-Jin; Shestopalov, Michael A; Fufaeva, Maria S; Shestopalov, Alexander M; Mironov, Yuri V; Poveshchenko, Alexander F; Shestopalova, Lidia V

2016-11-01

The octahedral cluster compound Na 2 H 8 [{Re 6 Se 8 }(P(C 2 H 4 CONH 2 )(C 2 H 4 COO) 2 ) 6 ] has been shown to be highly radio dense, thus becoming a promising X-ray contrast agent. It was also shown that this compound had low cytotoxic effect in vitro, low acute toxicity in vivo and was eliminated rapidly from the body through the urinary tract. The present contribution describes a more detailed cellular internalization assay and morphological analysis after intravenous injection of this hexarhenium cluster compound at different doses. The median lethal dose (LD 50 ) of intravenously administrated compound was calculated (4.67 ± 0.69 g/kg). Results of the study clearly indicated that the cluster complex H n [{Re 6 Se 8 }(P(C 2 H 4 CONH 2 )(C 2 H 4 COO) 2 ) 6 ] n-10 was not internalized into cells in vitro and induced only moderate morphological alterations of kidneys at high doses without any changes in morphology of liver, spleen, duodenum, or heart of mice. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Creation of a 3Mn/1Fe cluster in the oxygen-evolving complex of photosystem II and investigation of its functional activity.

Science.gov (United States)

Semin, B К; Davletshina, L N; Seibert, M; Rubin, A B

2018-01-01

Extraction of Mn cations from the oxygen-evolving complex (OEC) of Ca-depleted PSII membranes (PSII[-Ca,4Mn]) by reductants like hydroquinone (H 2 Q) occurs with lower efficiency at acidic pH (2Mn/reaction center [RC] are extracted at pH5.7) than at neutral pH (3Mn/RC are extracted at pH6.5) [Semin et al. Photosynth. Res. 125 (2015) 95]. Fe(II) also extracts Mn cations from PSII(-Ca,4Mn), but only 2Mn/RC at pH6.5, forming a heteronuclear 2Mn/2Fe cluster [Semin and Seibert, J. Bioenerg. Biomembr. 48 (2016) 227]. Here we investigated the efficiency of Mn extraction by Fe(II) at acidic pH and found that Fe(II) cations can extract only 1Mn/RC from PSII(-Ca,4Mn) membranes at pH 5.7, forming a 3Mn/1Fe cluster. Also we found that the presence of Fe cations in a heteronuclear cluster (2Mn/2Fe) increases the resistance of the remaining Mn cations to H 2 Q action, since H 2 Q can extract Mn cations from homonuclear Mn clusters of PSII(-Ca,4Mn) and PSII(-Ca,2Mn) membranes but not from the heteronuclear cluster in PSII(-Ca,2Mn,2Fe) membranes. H 2 Q also cannot extract Mn from PSII membranes obtained by incubation of PSII(-Ca,4Mn) membranes with Fe(II) cations at pH5.7, which suggests the formation of a heteronuclear 3Mn/1Fe cluster in the OEC. Functional activity of PSII with a 3Mn/1Fe cluster was investigated. PSII preparations with a 3Mn/1Fe cluster in the OEC are able to photoreduce the exogenous electron acceptor 2,6-dichlorophenolindophenol, possibly due to incomplete oxidation of water molecules as is the case with PSII(-Ca,2Mn,2Fe) samples. However, in the contrast to PSII(-Ca,2Mn,2Fe) samples PSII(-Ca,3Mn,1Fe) membranes can evolve O 2 at a low rate in the presence of exogenous Ca 2+ (at about 27% of the rate of O 2 evolution in native PSII membranes). The explanation for this phenomenon (either water splitting and production of molecular O 2 by the 3Mn/1Fe cluster or apparent O 2 evolution due to minor contamination of PSII(3Mn,1Fe) samples with PSII(-Ca,4Mn) membranes

Codebook Generation Using Partition and Agglomerative Clustering

Directory of Open Access Journals (Sweden)

CHANG, C.-T.

2011-08-01

Full Text Available In this paper, we present a codebook generation algorithm to produce a codebook with lower distortion. Our method combines a fast codebook generation algorithm (CGAUCD with doubling technique and fast agglomerative clustering algorithm (FACA to generate a codebook with less computing time and lower distortion. Instead of using FACA directly to divide training vectors into M clusters, our proposed method first generates qM clusters from these training vectors, where q>1 is an integer, and then applies FACA to merge these qM clusters into M cells. This is due to the computational complexity of CGAUCD with doubling technique is less than that of FACA. These M cluster centers are used as the initial codebook for CGAUCD. Using three real images as the training set, our method can reduce the MSE and computing time of FPNN+CGAUCD, which is the available best method to our knowledge, by 0.19 to 0.38 and 74.6% to 84.3%, respectively.

Positron lifetime in vacancy clusters. Application to the study of vacancy-impurity interactions

International Nuclear Information System (INIS)

Corbel, C.

1986-02-01

Positron lifetime measurements are used to study the vacancy recovery (77-650 K) in 20 K electron irradiated dilute gold or iron alloys in stainless steels. Positron lifetimes in clusters of various shapes and structures are calculated to precise the information obtained by measuring the positron lifetime in a vacancy cluster of unknown size and configuration. From the calculations, we have drawn the following conclusions: - the minimal size of an unknown cluster can be deduced from the measurement of the positron lifetime in the cluster; - a decrease of the positron lifetime when the structure of the cluster evolves, means either a decrease of the size of the cluster, or, the appearance of a relaxed configuration. - The positron lifetime is very useful to discriminate between a spatial planar or relaxed configuration and a tri-dimensional one. In AuGe, AuSb, AuTn alloys, vacancy clusters decorated by solute atoms appear at 250 K. Their configurations are different from those in pure Au. Mobile vacancy-solutes complexes are involved in the clustering process in AuGe, AuSb. The clusters are probably decorated by several solute atoms in AuGe and AuSb where the resistivity evidences a clustering of solute atoms. In AuFe, vacancy-single or multi-complexes stable up to 670 K prevent cluster formation. In FeTi, FeSb, FeAu, vacancy migration is hindered by the formation of vacancy-solute complexes up to 315 K (Ti), up to 670 K (Sb), up to 700 K (Au). In FeSi, FeCu, FeAg, tri-dimensional clusters grow less easily than Fe. This is likely due to the formation of several kinds of small decorated clusters with relaxed or planar configurations. They are peculiarly stable, surviving up to 700 K at least. In Si (resp. Ti) doped 59Fe25Ni16Cr, solute atoms retain the vacancies up to 300 K (resp. 320 K) [fr

A Multilevel Gamma-Clustering Layout Algorithm for Visualization of Biological Networks

Science.gov (United States)

Hruz, Tomas; Lucas, Christoph; Laule, Oliver; Zimmermann, Philip

2013-01-01

Visualization of large complex networks has become an indispensable part of systems biology, where organisms need to be considered as one complex system. The visualization of the corresponding network is challenging due to the size and density of edges. In many cases, the use of standard visualization algorithms can lead to high running times and poorly readable visualizations due to many edge crossings. We suggest an approach that analyzes the structure of the graph first and then generates a new graph which contains specific semantic symbols for regular substructures like dense clusters. We propose a multilevel gamma-clustering layout visualization algorithm (MLGA) which proceeds in three subsequent steps: (i) a multilevel γ-clustering is used to identify the structure of the underlying network, (ii) the network is transformed to a tree, and (iii) finally, the resulting tree which shows the network structure is drawn using a variation of a force-directed algorithm. The algorithm has a potential to visualize very large networks because it uses modern clustering heuristics which are optimized for large graphs. Moreover, most of the edges are removed from the visual representation which allows keeping the overview over complex graphs with dense subgraphs. PMID:23864855

Effect of clustering on attack vulnerability of interdependent scale-free networks

International Nuclear Information System (INIS)

Li, Rui-qi; Sun, Shi-wen; Ma, Yi-lin; Wang, Li; Xia, Cheng-yi

2015-01-01

In order to deeply understand the complex interdependent systems, it is of great concern to take clustering coefficient, which is an important feature of many real-world systems, into account. Previous study mainly focused on the impact of clustering on interdependent networks under random attacks, while we extend the study to the case of the more realistic attacking strategy, targeted attack. A system composed of two interdependent scale-free networks with tunable clustering is provided. The effects of coupling strength and coupling preference on attack vulnerability are explored. Numerical simulation results demonstrate that interdependent links between two networks make the entire system much more fragile to attacks. Also, it is found that clustering significantly increases the vulnerability of interdependent scale-free networks. Moreover, for fully coupled network, disassortative coupling is found to be most vulnerable to random attacks, while the random and assortative coupling have little difference. Additionally, enhancing coupling strength can greatly enhance the fragility of interdependent networks against targeted attacks. These results can not only improve the deep understanding of structural complexity of complex systems, but also provide insights into the guidance of designing resilient infrastructures.

The complex of measures on inclusion of small businesses in innovation clusters

Directory of Open Access Journals (Sweden)

A. V. Kupchinsky

2016-01-01

Full Text Available Modern practice of managing and its display in scientific publications demonstrate that development of world economy with all evidence proves the major role and the importance of sector of small business structures in national economy. In the modern world the national economy in many respects began to be determined by the balanced and sustainable development of the small business structures recognized now as conductors and creators of new opening and technologies, moreover, as the strategic instrument of the structural transformations of a modern economic system of the country often directed to high-quality increase in efficiency of reproduction process of regional economy. Now in Russia the level of development of an innovative entrepreneurship is very low. It is possible to state lack of properly created institutional environment for development of a small entrepreneurship in the innovative sphere. Clasterisation represents process of consolidation of a number of the organizations of various industries for increase in competitiveness, implementation of innovations, effective development and receipt of other benefits. According to separation of economy on real and virtual, the possibility of creation of both real, and virtual clusters increases. Creation and development of regional clusters will help to create the necessary level of activity of small business structures in innovative activities that will favorably affect increase in competitiveness of both regional, and national economy. The package of measures including measures for involvement of small business structures in clusters is developed for development of a cluster initiative and increase in innovative development of the region. Application of this program will allow to reach synergy effect at the expense of high degree of concentration and cooperation of small business structures and increase in effectiveness of their activities.

Issues of branch clusters development: from theory to practice

Directory of Open Access Journals (Sweden)

Bondarenko N. E.

2016-07-01

Full Text Available the article deals with objective preconditions of forming stable bases of the cluster theory and its specific features, the attention is paid to historical aspects of dialectical development of the cluster theory. The authors highlighted the main tasks, accomplishment of which is necessary for achieving an effective cluster policy in the system of the national economy. The opportunity of using the advantages and potential opportunities of clusters in respect of the agricultural sphere of the national economy is grounded. The model of agro-industrial clusters is considered as one of the ways to increase competitive advantage of the agro-industrial complex, to achieve reproduction on an enlarged scale and to solve tasks of the national victualling. An algorithm of analyzing factors of forming clusters in the agricultural sector of russian economy is proposed.

Dynamically allocated virtual clustering management system

Science.gov (United States)

Marcus, Kelvin; Cannata, Jess

2013-05-01

The U.S Army Research Laboratory (ARL) has built a "Wireless Emulation Lab" to support research in wireless mobile networks. In our current experimentation environment, our researchers need the capability to run clusters of heterogeneous nodes to model emulated wireless tactical networks where each node could contain a different operating system, application set, and physical hardware. To complicate matters, most experiments require the researcher to have root privileges. Our previous solution of using a single shared cluster of statically deployed virtual machines did not sufficiently separate each user's experiment due to undesirable network crosstalk, thus only one experiment could be run at a time. In addition, the cluster did not make efficient use of our servers and physical networks. To address these concerns, we created the Dynamically Allocated Virtual Clustering management system (DAVC). This system leverages existing open-source software to create private clusters of nodes that are either virtual or physical machines. These clusters can be utilized for software development, experimentation, and integration with existing hardware and software. The system uses the Grid Engine job scheduler to efficiently allocate virtual machines to idle systems and networks. The system deploys stateless nodes via network booting. The system uses 802.1Q Virtual LANs (VLANs) to prevent experimentation crosstalk and to allow for complex, private networks eliminating the need to map each virtual machine to a specific switch port. The system monitors the health of the clusters and the underlying physical servers and it maintains cluster usage statistics for historical trends. Users can start private clusters of heterogeneous nodes with root privileges for the duration of the experiment. Users also control when to shutdown their clusters.

Fibers in the NGC 1333 proto-cluster

Science.gov (United States)

Hacar, A.; Tafalla, M.; Alves, J.

2017-10-01

Are the initial conditions for clustered star formation the same as for non-clustered star formation? To investigate the initial gas properties in young proto-clusters we carried out a comprehensive and high-sensitivity study of the internal structure, density, temperature, and kinematics of the dense gas content of the NGC 1333 region in Perseus, one of the nearest and best studied embedded clusters. The analysis of the gas velocities in the position-position-velocity space reveals an intricate underlying gas organization both in space and velocity. We identified a total of 14 velocity-coherent, (tran-)sonic structures within NGC 1333, with similar physical and kinematic properties than those quiescent, star-forming (aka fertile) fibers previously identified in low-mass star-forming clouds. These fibers are arranged in a complex spatial network, build-up the observed total column density, and contain the dense cores and protostars in this cloud. Our results demonstrate that the presence of fibers is not restricted to low-mass clouds but can be extended to regions of increasing mass and complexity. We propose that the observational dichotomy between clustered and non-clustered star-forming regions might be naturally explained by the distinct spatial density of fertile fibers in these environments. Based on observations carried out under project number 169-11 with the IRAM 30 m Telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain).Based on observations with the 100-m telescope of the MPIfR (Max-Planck-Institut für Radioastronomie) at Effelsberg.Molecular line observations (spectral cubes) are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/606/A123

Quantum mechanical design and structures of hexanuclear sandwich complex and its multidecker sandwich clusters (Li6)n([18]annulene)n+1 (n = 1-3).

Science.gov (United States)

Wang, Shu-Jian; Li, Ying; Wu, Di; Wang, Yin-Feng; Li, Zhi-Ru

2012-09-13

By means of density functional theory, a hexanuclear sandwich complex [18]annulene-Li6-[18]annulene which consists of a central Li6 hexagon ring and large face-capping ligands, [18]annulene, is designed and investigated. The large interaction energy and HOMO-LUMO gap suggest that this novel charge-separated complex is highly stable and may be experimentally synthesized. In addition, the stability found in the [18]annulene-Li6-[18]annulene complex extends to multidecker sandwich clusters (Li6)n([18]annulene)n+1 (n = 2-3). The energy gain upon addition of a [18]annulene-Li6 unit to (Li6)n-1([18]annulene)n is pretty large (96.97-98.22 kcal/mol), indicating that even larger multideckers will also be very stable. Similar to ferrocene, such a hexanuclear sandwich complex could be considered as a versatile building block to find potential applications in different areas of chemistry, such as nanoscience and material science.

Progeny Clustering: A Method to Identify Biological Phenotypes

Science.gov (United States)

Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

2015-01-01

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

Investigation on the correlation between energy deposition and clustered DNA damage induced by low-energy electrons.

Science.gov (United States)

Liu, Wei; Tan, Zhenyu; Zhang, Liming; Champion, Christophe

2018-05-01

This study presents the correlation between energy deposition and clustered DNA damage, based on a Monte Carlo simulation of the spectrum of direct DNA damage induced by low-energy electrons including the dissociative electron attachment. Clustered DNA damage is classified as simple and complex in terms of the combination of single-strand breaks (SSBs) or double-strand breaks (DSBs) and adjacent base damage (BD). The results show that the energy depositions associated with about 90% of total clustered DNA damage are below 150 eV. The simple clustered DNA damage, which is constituted of the combination of SSBs and adjacent BD, is dominant, accounting for 90% of all clustered DNA damage, and the spectra of the energy depositions correlating with them are similar for different primary energies. One type of simple clustered DNA damage is the combination of a SSB and 1-5 BD, which is denoted as SSB + BD. The average contribution of SSB + BD to total simple clustered DNA damage reaches up to about 84% for the considered primary energies. In all forms of SSB + BD, the SSB + BD including only one base damage is dominant (above 80%). In addition, for the considered primary energies, there is no obvious difference between the average energy depositions for a fixed complexity of SSB + BD determined by the number of base damage, but average energy depositions increase with the complexity of SSB + BD. In the complex clustered DNA damage constituted by the combination of DSBs and BD around them, a relatively simple type is a DSB combining adjacent BD, marked as DSB + BD, and it is of substantial contribution (on average up to about 82%). The spectrum of DSB + BD is given mainly by the DSB in combination with different numbers of base damage, from 1 to 5. For the considered primary energies, the DSB combined with only one base damage contributes about 83% of total DSB + BD, and the average energy deposition is about 106 eV. However, the

Architecture of the Yeast Mitochondrial Iron-Sulfur Cluster Assembly Machinery

Science.gov (United States)

Ranatunga, Wasantha; Gakh, Oleksandr; Galeano, Belinda K.; Smith, Douglas Y.; Söderberg, Christopher A. G.; Al-Karadaghi, Salam; Thompson, James R.; Isaya, Grazia

2016-01-01

The biosynthesis of Fe-S clusters is a vital process involving the delivery of elemental iron and sulfur to scaffold proteins via molecular interactions that are still poorly defined. We reconstituted a stable, functional complex consisting of the iron donor, Yfh1 (yeast frataxin homologue 1), and the Fe-S cluster scaffold, Isu1, with 1:1 stoichiometry, [Yfh1]24·[Isu1]24. Using negative staining transmission EM and single particle analysis, we obtained a three-dimensional reconstruction of this complex at a resolution of ∼17 Å. In addition, via chemical cross-linking, limited proteolysis, and mass spectrometry, we identified protein-protein interaction surfaces within the complex. The data together reveal that [Yfh1]24·[Isu1]24 is a roughly cubic macromolecule consisting of one symmetric Isu1 trimer binding on top of one symmetric Yfh1 trimer at each of its eight vertices. Furthermore, molecular modeling suggests that two subunits of the cysteine desulfurase, Nfs1, may bind symmetrically on top of two adjacent Isu1 trimers in a manner that creates two putative [2Fe-2S] cluster assembly centers. In each center, conserved amino acids known to be involved in sulfur and iron donation by Nfs1 and Yfh1, respectively, are in close proximity to the Fe-S cluster-coordinating residues of Isu1. We suggest that this architecture is suitable to ensure concerted and protected transfer of potentially toxic iron and sulfur atoms to Isu1 during Fe-S cluster assembly. PMID:26941001

Structural and functional characterization of an archaeal clustered regularly interspaced short palindromic repeat (CRISPR)-associated complex for antiviral defense (CASCADE).

Science.gov (United States)

Lintner, Nathanael G; Kerou, Melina; Brumfield, Susan K; Graham, Shirley; Liu, Huanting; Naismith, James H; Sdano, Matthew; Peng, Nan; She, Qunxin; Copié, Valérie; Young, Mark J; White, Malcolm F; Lawrence, C Martin

2011-06-17

In response to viral infection, many prokaryotes incorporate fragments of virus-derived DNA into loci called clustered regularly interspaced short palindromic repeats (CRISPRs). The loci are then transcribed, and the processed CRISPR transcripts are used to target invading viral DNA and RNA. The Escherichia coli "CRISPR-associated complex for antiviral defense" (CASCADE) is central in targeting invading DNA. Here we report the structural and functional characterization of an archaeal CASCADE (aCASCADE) from Sulfolobus solfataricus. Tagged Csa2 (Cas7) expressed in S. solfataricus co-purifies with Cas5a-, Cas6-, Csa5-, and Cas6-processed CRISPR-RNA (crRNA). Csa2, the dominant protein in aCASCADE, forms a stable complex with Cas5a. Transmission electron microscopy reveals a helical complex of variable length, perhaps due to substoichiometric amounts of other CASCADE components. A recombinant Csa2-Cas5a complex is sufficient to bind crRNA and complementary ssDNA. The structure of Csa2 reveals a crescent-shaped structure unexpectedly composed of a modified RNA-recognition motif and two additional domains present as insertions in the RNA-recognition motif. Conserved residues indicate potential crRNA- and target DNA-binding sites, and the H160A variant shows significantly reduced affinity for crRNA. We propose a general subunit architecture for CASCADE in other bacteria and Archaea.

First-principles studies on graphene-supported transition metal clusters

International Nuclear Information System (INIS)

Sahoo, Sanjubala; Khanna, Shiv N.; Gruner, Markus E.; Entel, Peter

2014-01-01

Theoretical studies on the structure, stability, and magnetic properties of icosahedral TM 13 (TM = Fe, Co, Ni) clusters, deposited on pristine (defect free) and defective graphene sheet as well as graphene flakes, have been carried out within a gradient corrected density functional framework. The defects considered in our study include a carbon vacancy for the graphene sheet and a five-membered and a seven-membered ring structures for graphene flakes (finite graphene chunks). It is observed that the presence of defect in the substrate has a profound influence on the electronic structure and magnetic properties of graphene-transition metal complexes, thereby increasing the binding strength of the TM cluster on to the graphene substrate. Among TM 13 clusters, Co 13 is absorbed relatively more strongly on pristine and defective graphene as compared to Fe 13 and Ni 13 clusters. The adsorbed clusters show reduced magnetic moment compared to the free clusters

ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time.

Science.gov (United States)

Cai, Yunpeng; Zheng, Wei; Yao, Jin; Yang, Yujie; Mai, Volker; Mao, Qi; Sun, Yijun

2017-04-01

The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for this purpose. However, it is currently computationally expensive to perform hierarchical clustering of extremely large sequence datasets due to its quadratic time and space complexities. In this paper we developed a new algorithm called ESPRIT-Forest for parallel hierarchical clustering of sequences. The algorithm achieves subquadratic time and space complexity and maintains a high clustering accuracy comparable to the standard method. The basic idea is to organize sequences into a pseudo-metric based partitioning tree for sub-linear time searching of nearest neighbors, and then use a new multiple-pair merging criterion to construct clusters in parallel using multiple threads. The new algorithm was tested on the human microbiome project (HMP) dataset, currently one of the largest published microbial 16S rRNA sequence dataset. Our experiment demonstrated that with the power of parallel computing it is now compu- tationally feasible to perform hierarchical clustering analysis of tens of millions of sequences. The software is available at http://www.acsu.buffalo.edu/∼yijunsun/lab/ESPRIT-Forest.html.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Data Analysis and Visualization (IDAV) and the Department of Computer Science, University of California, Davis, One Shields Avenue, Davis CA 95616, USA,; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,' ' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA; Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA; Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA,; Computer Science Division,University of California, Berkeley, CA, USA,; Computer Science Department, University of California, Irvine, CA, USA,; All authors are with the Berkeley Drosophila Transcription Network Project, Lawrence Berkeley National Laboratory,; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Biggin, Mark D.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; Keranen, Soile V. E.; Eisen, Michael B.; Knowles, David W.; Malik, Jitendra; Hagen, Hans; Hamann, Bernd

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii) evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

A phosphorescent silver(I)-gold (I) cluster complex that specifically lights up the nucleolus of living cells with FLIM imaging.

Science.gov (United States)

Chen, Min; Lei, Zhen; Feng, Wei; Li, Chunyan; Wang, Quan-Ming; Li, Fuyou

2013-06-01

The phosphorescent silver(I)-gold(I) cluster complex [CAu6Ag2(dppy)6](BF4)4 (N1) selectively stains the nucleolus, with a much lower uptake in the nucleus and cytoplasm, and exhibits excellent photostability. This Ag-Au cluster, which has a photoluminescent lifetime of microseconds, is particularly attractive as a probe in applications of time-gated microscopy. Investigation of the pathway of cellular entry indicated that N1 permeates the outer membrane and nuclear membrane of living cells through an energy-dependent and non-endocytic route within 10 min. High concentrations of N1 in the nucleolus have been quantified by inductively coupled plasma atomic emission spectroscopy (ICP-AES) and transmission electron microscopy coupled with an energy dispersive X-ray analysis (TEM-EDXA), which also helped to elucidate the mechanism of the specific staining. Intracellular selective staining may be correlated with the microenvironment of the nucleolus, which is consistent with experiments conducted at different phases of the cell cycle. These results prove that N1 is a very attractive phosphorescent staining reagent for visualizing the nucleolus of living cells. Copyright © 2013 Elsevier Ltd. All rights reserved.

Tribological coatings for complex mechanical elements produced by supersonic cluster beam deposition of metal dichalcogenide nanoparticles

Science.gov (United States)

Piazzoni, C.; Buttery, M.; Hampson, M. R.; Roberts, E. W.; Ducati, C.; Lenardi, C.; Cavaliere, F.; Piseri, P.; Milani, P.

2015-07-01

Fullerene-like MoS2 and WS2 nanoparticles can be used as building blocks for the fabrication of fluid and solid lubricants. Metal dichalcogenide films have a very low friction coefficient in vacuum, therefore they have mostly been used as solid lubricants in space and vacuum applications. Unfortunately, their use is significantly hampered by the fact that in the presence of humidity, oxygen and moisture, the low-friction properties of these materials rapidly degrade due to oxidation. The use of closed-cage MoS2 and WS2 nanoparticles may eliminate this problem, although the fabrication of lubricant thin films starting from dichalcogenide nanoparticles is, to date, a difficult task. Here we demonstrate the use of supersonic cluster beam deposition for the coating of complex mechanical elements (angular contact ball bearings) with nanostructured MoS2 and WS2 thin films. We report structural and tribological characterization of the coatings in view of the optimization of tribological performances for aerospace applications.

Infrared Multiple Photon Dissociation Spectroscopy Of Metal Cluster-Adducts

Science.gov (United States)

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

1987-01-01

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

Graph-based clustering and data visualization algorithms

CERN Document Server

Vathy-Fogarassy, Ágnes

2013-01-01

This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on

Interaction of hydrogen with palladium clusters deposited on graphene

Energy Technology Data Exchange (ETDEWEB)

Alonso, Julio A.; Granja, Alejandra; Cabria, Iván; López, María J. [Departamento de Física Teórica, Atómica y Optica, Universidad de Valladolid, 47011 Valladolid (Spain)

2015-12-31

Hydrogen adsorption on nanoporous carbon materials is a promising technology for hydrogen storage. However, pure carbon materials do not meet the technological requirements due to the week binding of hydrogen to the pore walls. Experimental work has shown that doping with Pd atoms and clusters enhances the storage capacity of porous carbons. Therefore, we have investigated the role played by the Pd dopant on the enhancement mechanisms. By performing density functional calculations, we have found that hydrogen adsorbs on Pd clusters deposited on graphene following two channels, molecular adsorption and dissociative chemisorption. However, desorption of Pd-H complexes competes with desorption of hydrogen, and consequently desorption of Pd-H complexes would spoil the beneficial effect of the dopant. As a way to overcome this difficulty, Pd atoms and clusters can be anchored to defects of the graphene layer, like graphene vacancies. The competition between molecular adsorption and dissociative chemisorption of H{sub 2} on Pd{sub 6} anchored on a graphene vacancy has been studied in detail.

Interaction of hydrogen with palladium clusters deposited on graphene

Science.gov (United States)

Alonso, Julio A.; Granja, Alejandra; Cabria, Iván; López, María J.

2015-12-01

Hydrogen adsorption on nanoporous carbon materials is a promising technology for hydrogen storage. However, pure carbon materials do not meet the technological requirements due to the week binding of hydrogen to the pore walls. Experimental work has shown that doping with Pd atoms and clusters enhances the storage capacity of porous carbons. Therefore, we have investigated the role played by the Pd dopant on the enhancement mechanisms. By performing density functional calculations, we have found that hydrogen adsorbs on Pd clusters deposited on graphene following two channels, molecular adsorption and dissociative chemisorption. However, desorption of Pd-H complexes competes with desorption of hydrogen, and consequently desorption of Pd-H complexes would spoil the beneficial effect of the dopant. As a way to overcome this difficulty, Pd atoms and clusters can be anchored to defects of the graphene layer, like graphene vacancies. The competition between molecular adsorption and dissociative chemisorption of H2 on Pd6 anchored on a graphene vacancy has been studied in detail.

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

Directory of Open Access Journals (Sweden)

Meerim SYDYKOVA

2014-11-01

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

Performance assessment of the SIMFAP parallel cluster at IFIN-HH Bucharest

International Nuclear Information System (INIS)

Adam, Gh.; Adam, S.; Ayriyan, A.; Dushanov, E.; Hayryan, E.; Korenkov, V.; Lutsenko, A.; Mitsyn, V.; Sapozhnikova, T.; Sapozhnikov, A; Streltsova, O.; Buzatu, F.; Dulea, M.; Vasile, I.; Sima, A.; Visan, C.; Busa, J.; Pokorny, I.

2008-01-01

Performance assessment and case study outputs of the parallel SIMFAP cluster at IFIN-HH Bucharest point to its effective and reliable operation. A comparison with results on the supercomputing system in LIT-JINR Dubna adds insight on resource allocation for problem solving by parallel computing. The solution of models asking for very large numbers of knots in the discretization mesh needs the migration to high performance computing based on parallel cluster architectures. The acquisition of ready-to-use parallel computing facilities being beyond limited budgetary resources, the solution at IFIN-HH was to buy the hardware and the inter-processor network, and to implement by own efforts the open software concerning both the operating system and the parallel computing standard. The present paper provides a report demonstrating the successful solution of these tasks. The implementation of the well-known HPL (High Performance LINPACK) Benchmark points to the effective and reliable operation of the cluster. The comparison of HPL outputs obtained on parallel clusters of different magnitudes shows that there is an optimum range of the order N of the linear algebraic system over which a given parallel cluster provides optimum parallel solutions. For the SIMFAP cluster, this range can be inferred to correspond to about 1 to 2 x 10 4 linear algebraic equations. For an algorithm of polynomial complexity N α the task sharing among p processors within a parallel solution mainly follows an (N/p)α behaviour under peak performance achievement. Thus, while the problem complexity remains the same, a substantial decrease of the coefficient of the leading order of the polynomial complexity is achieved. (authors)

Exploitation of Clustering Techniques in Transactional Healthcare Data

Directory of Open Access Journals (Sweden)

Naeem Ahmad Mahoto

2014-03-01

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

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

OpenAIRE

Viederytė, Rasa; Didžiokas, Rimantas

2014-01-01

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

Pre-equilibrium complex particle emission

International Nuclear Information System (INIS)

Bĕták, E.

2002-01-01

Semi-classical (phenomenological) pre-equilibrium emission of clusters of nucleons (complex particles) such as deuterons, tritons, helions and α particles from reactions induced by light projectiles (nucleons to α’s) is addressed. The main attention is given to the hard components in the emission energetic spectra, which play an increasing role at incident energies above 20 MeV, and are currently attributed to a presence of some kind of pre-equilibrium processes. In addition, the mechanisms of cluster reactions show special features such as the competition between pickup and knockout processes and the contributions of several successive steps in the reaction. The main frame used here to illustrate the processes and interplays of the competing mechanisms of pre-equilibrium cluster formation and emission, namely the coalescence, pick-up and knock-out, is the pre-equilibrium exciton model. It obviously contains the process of clusterization itself as its organic part. The most important case of complex particles with the largest amount of experimental data is that of alpha emission, which therefore naturally attracts most of the attention and where the widest range of possible mechanisms is available on the market. The loosely bound ejectiles, on the other side, are usually not able to demonstrate all features of the whole spectrum of contributing mechanisms, but they are nevertheless an important link between the nucleon emission and the cluster one.

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-10-20

}, the latter values slightly lower than but consistent with those derived for individual galactic halos. Taken as a whole, our results show that the production of the complex structures in the unrelaxed Virgo cluster core (including the production of the diffuse intracluster light) is an ongoing and continuing process.

Titanium embedded cage structure formation in AlnTi+ clusters and their interaction with Ar

International Nuclear Information System (INIS)

Torres, M. B.; Vega, A.; Balbás, L. C.; Aguilera-Granja, F.

2014-01-01

Recently, Ar physisorption was used as a structural probe for the location of the Ti dopant atom in aluminium cluster cations, Al n Ti + [Lang et al., J. Am. Soc. Mass Spectrom. 22, 1508 (2011)]. As an experiment result, the lack of Ar complexes for n > n c determines the cluster size for which the Ti atom is located inside of an Al cage. To elucidate the decisive factors for the formation of endohedrally Al n Ti + , experimentalists proposed detailed computational studies as indispensable. In this work, we investigated, using the density functional theory, the structural and electronic properties of singly titanium doped cationic clusters, Al n Ti + (n = 16–21) as well as the adsorption of an Ar atom on them. The first endohedral doped cluster, with Ti encapsulated in a fcc-like cage skeleton, appears at n c = 21, which is the critical number consistent with the exohedral-endohedral transition experimentally observed. At this critical size the non-crystalline icosahedral growth pattern, related to the pure aluminium clusters, with the Ti atom in the surface, changes into a endohedral fcc-like pattern. The map of structural isomers, relative energy differences, second energy differences, and structural parameters were determined and analyzed. Moreover, we show the critical size depends on the net charge of the cluster, being different for the cationic clusters (n c = 21) and their neutral counterparts (n c = 20). For the Al n Ti + · Ar complexes, and for n n Ti + clusters keeps unaltered in the Ar-cluster complexes. This fact indicates that Ar adsorption does not influence the cluster structure, providing support to the experimental technique used. For n c = 21, the smallest size of endohedral Ti doped cationic clusters, the Ar binding energy decreases drastically, whereas the Ar-cluster distance increases substantially, point to Ar physisorption, as assumed by the experimentalists. Calculated Ar adsorption energies agree well with available experimental binding

JUSTIFICATION OF THE PRIORITIES OF THE CLUSTERING OF AGRO-INDUSTRIES OF THE VORONEZH REGION

Directory of Open Access Journals (Sweden)

Y. A. Salikov

2014-01-01

Full Text Available Currently, in many regions of the Russian Federation initiated a large-scale work on the development and implementation of cluster policy in accordance with Federal and regional socio-economic development until 2020. The analysis of the status of implementation adopted in 2012, the concept of cluster policy of the Voronezh region showed that the complex is made on the date of the event is mainly responsible for the informational and infrastructural nature. However, from the total number of promising clusters by 2014, formed in fact, only two-thirds, while among the uncreated shall apply the cluster processing of agricultural products having a high rating prospects. Given that the formation of the agro-industrial cluster corresponds to the requirements and conditions in this study developed a new methodological approach, which carried out the rationale for the priority of the formation of the meat cluster in the agro-industrial complex of the Voronezh region. The basis of this methodological approach is the algorithm for the identification of areas of clustering, developed by the authors using statistics Forsythe, represents an efficient tool for the formation of priorities to achieve a qualitatively new results in the field of economy, science and technology. The proposed algorithm includes the serial combination of the following methodological stages: the formation of the object of research, identifying sources of reliable information on the basis of expert assessments, identify areas clustering of industries (including analysis legal framework the study of statistical data on the level of localization of industries and analysis of the practice of implementation of the cluster policy regions-analogues, identification of areas for additional clustering of industries and their mapping, and de-termination of the priority directions of the additional clustering of industries by ranking. The results of the study, carried out in accordance with this

Phase behavior of the 38-atom Lennard-Jones cluster

International Nuclear Information System (INIS)

Sehgal, Ray M.; Maroudas, Dimitrios; Ford, David M.

2014-01-01

We have developed a coarse-grained description of the phase behavior of the isolated 38-atom Lennard-Jones cluster (LJ 38 ). The model captures both the solid-solid polymorphic transitions at low temperatures and the complex cluster breakup and melting transitions at higher temperatures. For this coarse model development, we employ the manifold learning technique of diffusion mapping. The outcome of the diffusion mapping analysis over a broad temperature range indicates that two order parameters are sufficient to describe the cluster's phase behavior; we have chosen two such appropriate order parameters that are metrics of condensation and overall crystallinity. In this well-justified coarse-variable space, we calculate the cluster's free energy landscape (FEL) as a function of temperature, employing Monte Carlo umbrella sampling. These FELs are used to quantify the phase behavior and onsets of phase transitions of the LJ 38 cluster

Massive fungal biodiversity data re-annotation with multi-level clustering

DEFF Research Database (Denmark)

Vu, D.; Szoke, S.; Wiwie, Christian

2014-01-01

With the availability of newer and cheaper sequencing methods, genomic data are being generated at an increasingly fast pace. In spite of the high degree of complexity of currently available search routines, the massive number of sequences available virtually prohibits quick and correct identific...... for clustering. An implementation of the algorithm allowed clustering of all 344,239 ITS (Internal Transcribed Spacer) fungal sequences from GenBank utilizing only a normal desktop computer within 22 CPU-hours whereas the greedy clustering method took up to 242 CPU-hours....

The Stormy Life of Galaxy Clusters

Science.gov (United States)

Rudnick, Lawrence

2018-01-01

Galaxy clusters, the largest gravitationally bound structures, hold the full history of their baryonic evolution, serve as important cosmological tools and allow us to probe unique physical regimes in their diffuse plasmas. With characteristic dynamical timescales of 107-109 years, these diffuse thermal and relativistic media continue to evolve, as dark matter drives major mergers and more gentle continuing accretion. The history of this assembly is encoded in the plasmas, and a wide range of observational and theoretical investigations are aimed at decoding their signatures. X-ray temperature and density variations, low Mach number shocks, and "cold front" discontinuities all illuminate clusters' continued evolution. Radio structures and spectra are passive indicators of merger shocks, while radio galaxy distortions reveal the complex motions in the intracluster medium. Deep in cluster cores, AGNs associated with brightest cluster galaxies provide ongoing energy, and perhaps even stabilize the intracluster medium. In this talk, we will recount this evolving picture of the stormy ICM, and suggest areas of likely advance in the coming years.

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Oriented cluster perforating technology and its application in horizontal wells

Directory of Open Access Journals (Sweden)

Huabin Chen

2016-11-01

Full Text Available An oriented cluster perforating technology, which integrates both advantages of cluster and oriented perforating, will help solve a series of technical complexities in horizontal well drilling. For realizing its better application in oil and gas development, a series of technologies were developed including perforator self-weight eccentricity, matching of the electronic selective module codes with the surface program control, axial centralized contact signal transmission, and post-perforation intercluster sealing insulation. In this way, the following functions could be realized, such as cable-transmission horizontal well perforator self-weight orientation, dynamic signal transmission, reliable addressing & selective perforation and post-perforation intercluster sealing. The combined perforation and bridge plug or the multi-cluster perforation can be fulfilled in one trip of perforation string. As a result, the horizontal-well oriented cluster perforating technology based on cable conveying was developed. This technology was successfully applied in unconventional gas reservoir exploitation, such as shale gas and coalbed methane, with accurate orientation, reliable selective perforation and satisfactory inter-cluster sealing. The horizontal-well oriented cluster perforating technology benefits the orientation of horizontal well drilling with a definite target and direction, which provides a powerful support for the subsequent reservoir stimulation. It also promotes the fracturing fluid to sweep the principal pay zones to the maximum extent. Moreover, it is conductive to the formation of complex fracture networks in the reservoirs, making quality and efficient development of unconventional gas reservoirs possible.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

Science.gov (United States)

De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Brightest Cluster Galaxies in REXCESS Clusters

Science.gov (United States)

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

2009-01-01

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

From virtual clustering analysis to self-consistent clustering analysis: a mathematical study

Science.gov (United States)

Tang, Shaoqiang; Zhang, Lei; Liu, Wing Kam

2018-03-01

In this paper, we propose a new homogenization algorithm, virtual clustering analysis (VCA), as well as provide a mathematical framework for the recently proposed self-consistent clustering analysis (SCA) (Liu et al. in Comput Methods Appl Mech Eng 306:319-341, 2016). In the mathematical theory, we clarify the key assumptions and ideas of VCA and SCA, and derive the continuous and discrete Lippmann-Schwinger equations. Based on a key postulation of "once response similarly, always response similarly", clustering is performed in an offline stage by machine learning techniques (k-means and SOM), and facilitates substantial reduction of computational complexity in an online predictive stage. The clear mathematical setup allows for the first time a convergence study of clustering refinement in one space dimension. Convergence is proved rigorously, and found to be of second order from numerical investigations. Furthermore, we propose to suitably enlarge the domain in VCA, such that the boundary terms may be neglected in the Lippmann-Schwinger equation, by virtue of the Saint-Venant's principle. In contrast, they were not obtained in the original SCA paper, and we discover these terms may well be responsible for the numerical dependency on the choice of reference material property. Since VCA enhances the accuracy by overcoming the modeling error, and reduce the numerical cost by avoiding an outer loop iteration for attaining the material property consistency in SCA, its efficiency is expected even higher than the recently proposed SCA algorithm.

The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies

Energy Technology Data Exchange (ETDEWEB)

Grasha, K.; Calzetti, D. [Astronomy Department, University of Massachusetts, Amherst, MA 01003 (United States); Adamo, A.; Messa, M. [Dept. of Astronomy, The Oskar Klein Centre, Stockholm University, Stockholm (Sweden); Kim, H. [Gemini Observatory, La Serena (Chile); Elmegreen, B. G. [IBM Research Division, T.J. Watson Research Center, Yorktown Hts., NY (United States); Gouliermis, D. A. [Zentrum für Astronomie der Universität Heidelberg, Institut für Theoretische Astrophysik, Albert-Ueberle-Str. 2, D-69120 Heidelberg (Germany); Dale, D. A. [Dept. of Physics and Astronomy, University of Wyoming, Laramie, WY (United States); Fumagalli, M. [Institute for Computational Cosmology and Centre for Extragalactic Astronomy, Durham University, Durham (United Kingdom); Grebel, E. K.; Shabani, F. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstr. 12-14, D-69120 Heidelberg (Germany); Johnson, K. E. [Dept. of Astronomy, University of Virginia, Charlottesville, VA (United States); Kahre, L. [Dept. of Astronomy, New Mexico State University, Las Cruces, NM (United States); Kennicutt, R. C. [Institute of Astronomy, University of Cambridge, Cambridge (United Kingdom); Pellerin, A. [Dept. of Physics and Astronomy, State University of New York at Geneseo, Geneseo NY (United States); Ryon, J. E.; Ubeda, L. [Space Telescope Science Institute, Baltimore, MD (United States); Smith, L. J. [European Space Agency/Space Telescope Science Institute, Baltimore, MD (United States); Thilker, D., E-mail: kgrasha@astro.umass.edu [Dept. of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD (United States)

2017-05-10

We present a study of the hierarchical clustering of the young stellar clusters in six local (3–15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ∼40–60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.

The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies

Science.gov (United States)

Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Dale, D. A.; Fumagalli, M.; Grebel, E. K.; Johnson, K. E.; Kahre, L.; Kennicutt, R. C.; Messa, M.; Pellerin, A.; Ryon, J. E.; Smith, L. J.; Shabani, F.; Thilker, D.; Ubeda, L.

2017-05-01

We present a study of the hierarchical clustering of the young stellar clusters in six local (3-15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ˜40-60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.

The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies

International Nuclear Information System (INIS)

Grasha, K.; Calzetti, D.; Adamo, A.; Messa, M.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Dale, D. A.; Fumagalli, M.; Grebel, E. K.; Shabani, F.; Johnson, K. E.; Kahre, L.; Kennicutt, R. C.; Pellerin, A.; Ryon, J. E.; Ubeda, L.; Smith, L. J.; Thilker, D.

2017-01-01

We present a study of the hierarchical clustering of the young stellar clusters in six local (3–15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ∼40–60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.

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

International Nuclear Information System (INIS)

Walther, B.

1988-01-01

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

Robust K-Median and K-Means Clustering Algorithms for Incomplete Data

Directory of Open Access Journals (Sweden)

Jinhua Li

2016-01-01

Full Text Available Incomplete data with missing feature values are prevalent in clustering problems. Traditional clustering methods first estimate the missing values by imputation and then apply the classical clustering algorithms for complete data, such as K-median and K-means. However, in practice, it is often hard to obtain accurate estimation of the missing values, which deteriorates the performance of clustering. To enhance the robustness of clustering algorithms, this paper represents the missing values by interval data and introduces the concept of robust cluster objective function. A minimax robust optimization (RO formulation is presented to provide clustering results, which are insensitive to estimation errors. To solve the proposed RO problem, we propose robust K-median and K-means clustering algorithms with low time and space complexity. Comparisons and analysis of experimental results on both artificially generated and real-world incomplete data sets validate the robustness and effectiveness of the proposed algorithms.

Neurobiology and sleep disorders in cluster headache

DEFF Research Database (Denmark)

Barloese, Mads Christian Johannes

2015-01-01

of daylight, substantially poorer sleep quality in patients compared to controls which was present not only inside the clusters but also outside, affected REM-sleep in patients without a particular temporal connection to nocturnal attacks, equal prevalence of sleep apnea in both patient and control groups......Cluster headache is characterized by unilateral attacks of severe pain accompanied by cranial autonomic features. Apart from these there are also sleep-related complaints and strong chronobiological features. The interaction between sleep and headache is complex at any level and evidence suggests...... that it may be of critical importance in our understanding of primary headache disorders. In cluster headache several interactions between sleep and the severe pain attacks have already been proposed. Supported by endocrinological and radiological findings as well as the chronobiological features, predominant...

Concept of the Ural pharmaceutical cluster formation

Directory of Open Access Journals (Sweden)

Aleksandr Petrovich Petrov

2011-06-01

cluster is made; it's impact on economic development of areas the of cluster participants location is estimated. Areas of the state and community support for clustered forms of business organization are designated. A complex of proposed actions was designed to meet the life cycle of a cluster. This positive experience of the formation and development of cluster structure in Sverdlovsk region can be implemented in other regions of Russia.

Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

Science.gov (United States)

Elangasinghe, M. A.; Singhal, N.; Dirks, K. N.; Salmond, J. A.; Samarasinghe, S.

2014-09-01

This paper uses artificial neural networks (ANN), combined with k-means clustering, to understand the complex time series of PM10 and PM2.5 concentrations at a coastal location of New Zealand based on data from a single site. Out of available meteorological parameters from the network (wind speed, wind direction, solar radiation, temperature, relative humidity), key factors governing the pattern of the time series concentrations were identified through input sensitivity analysis performed on the trained neural network model. The transport pathways of particulate matter under these key meteorological parameters were further analysed through bivariate concentration polar plots and k-means clustering techniques. The analysis shows that the external sources such as marine aerosols and local sources such as traffic and biomass burning contribute equally to the particulate matter concentrations at the study site. These results are in agreement with the results of receptor modelling by the Auckland Council based on Positive Matrix Factorization (PMF). Our findings also show that contrasting concentration-wind speed relationships exist between marine aerosols and local traffic sources resulting in very noisy and seemingly large random PM10 concentrations. The inclusion of cluster rankings as an input parameter to the ANN model showed a statistically significant (p advanced air dispersion models.

N-Heterocyclic Carbene Coinage Metal Complexes of the Germanium-Rich Metalloid Clusters [Ge9R3]− and [Ge9RI2]2− with R = Si(iPr3 and RI = Si(TMS3

Directory of Open Access Journals (Sweden)

Felix S. Geitner

2017-07-01

Full Text Available We report on the synthesis of novel coinage metal NHC (N-heterocyclic carbene compounds of the germanium-rich metalloid clusters [Ge9R3]− and [Ge9RI2]2− with R = Si(iPr3 and RI = Si(TMS3. NHCDippCu{η3Ge9R3} with R = Si(iPr3 (1 represents a less bulky silyl group-substituted derivative of the known analogous compounds with R = Si(iBu3 or Si(TMS3. The coordination of the [NHCDippCu]+ moiety to the cluster unit occurs via one triangular face of the tri-capped trigonal prismatic [Ge9] cluster. Furthermore, a series of novel Zintl cluster coinage metal NHC compounds of the type (NHCM2{η3Ge9RI2} (RI = Si(TMS3 M = Cu, Ag and Au; NHC = NHCDipp or NHCMes is presented. These novel compounds represent a new class of neutral dinuclear Zintl cluster coinage metal NHC compounds, which are obtained either by the stepwise reaction of a suspension of K12Ge17 with Si(TMS3Cl and the coinage metal carbene complexes NHCMCl (M = Cu, Ag, Au, or via a homogenous reaction using the preformed bis-silylated cluster K2[Ge9(Si(TMS32] and the corresponding NHCMCl (M = Cu, Ag, Au complex. The molecular structures of NHCDippCu{η3Ge9(Si(iPr33} (1 and (NHCDippCu2{η3-Ge9(Si(TMS32} (2 were determined by single crystal X-ray diffraction methods. In 2, the coordination of the [NHCDippCu]+ moieties to the cluster unit takes place via both open triangular faces of the [Ge9] entity. Furthermore, all compounds were characterized by means of NMR spectroscopy (1H, 13C, 29Si and ESI-MS.

Cluster Headache: Epidemiology, Pathophysiology, Clinical Features, and Diagnosis.

Science.gov (United States)

Wei, Diana Yi-Ting; Yuan Ong, Jonathan Jia; Goadsby, Peter James

2018-04-01

Cluster headache is a primary headache disorder affecting up to 0.1% of the population. Patients suffer from cluster headache attacks lasting from 15 to 180 min up to 8 times a day. The attacks are characterized by the severe unilateral pain mainly in the first division of the trigeminal nerve, with associated prominent unilateral cranial autonomic symptoms and a sense of agitation and restlessness during the attacks. The male-to-female ratio is approximately 2.5:1. Experimental, clinical, and neuroimaging studies have advanced our understanding of the pathogenesis of cluster headache. The pathophysiology involves activation of the trigeminovascular complex and the trigeminal-autonomic reflex and accounts for the unilateral severe headache, the prominent ipsilateral cranial autonomic symptoms. In addition, the circadian and circannual rhythmicity unique to this condition is postulated to involve the hypothalamus and suprachiasmatic nucleus. Although the clinical features are distinct, it may be misdiagnosed, with patients often presenting to the otolaryngologist or dentist with symptoms. The prognosis of cluster headache remains difficult to predict. Patients with episodic cluster headache can shift to chronic cluster headache and vice versa. Longitudinally, cluster headache tends to remit with age with less frequent bouts and more prolonged periods of remission in between bouts.

From clusters to biomolecules: electric dipole, structure and dynamics

International Nuclear Information System (INIS)

Broyer, M; Antoine, R; Compagnon, I; Rayane, D; Dugourd, P

2007-01-01

In this paper, it is demonstrated that the electric dipole of complex molecules or clusters can be measured by beam deviation in an inhomogeneous electric field. This measurement, associated to appropriate theoretical calculations and simulations, allows us to determine the geometry of these systems and their dynamical behaviour as a function of temperature. Selected examples for mixed clusters (metal-fullerene, metal-benzene, salt) and biomolecules (hydrogen bound amino acids and glycine based polypeptides) are discussed

Dissolution kinetics of B clusters in crystalline Si

International Nuclear Information System (INIS)

De Salvador, D.; Napolitani, E.; Bisognin, G.; Carnera, A.; Bruno, E.; Mirabella, S.; Impellizzeri, G.; Priolo, F.

2005-01-01

Boron (B) clustering in crystalline Si induced by interaction with Si self-interstitials is a widely studied phenomenon of fundamental importance for Si micro- and nano-electronic technology. The requested B activation increase brings the B concentration to a very high level and a detailed understanding of B clustering at high concentration is demanded. In the present work we present some recent results regarding the B clustering process starting from B concentration both below and above the B solubility limit. We show that B clusters, produced by self-interstitial interaction with substitutional B in crystalline Si, dissolve under annealing according to two distinct paths with very different characteristic times. The two regimes generally coexist, but while the faster dissolution path is predominant for clusters formed at low B concentration (1 x 10 19 B/cm 3 ), the slower one is characteristic of clusters formed above the solubility limit and dominates the dissolution process at high B concentration (2 x 10 2 B/cm 3 ). The activation energies of both processes are characterized and discussed. It is shown that the faster path can be connected to a direct emission of mobile B from small clusters, while the slower path is demonstrated not to be self-interstitial limited and it is probably related to a more complex cluster dissolution process

Hierarchical and Complex System Entropy Clustering Analysis Based Validation for Traditional Chinese Medicine Syndrome Patterns of Chronic Atrophic Gastritis.

Science.gov (United States)

Zhang, Yin; Liu, Yue; Li, Yannan; Zhao, Xia; Zhuo, Lin; Zhou, Ajian; Zhang, Li; Su, Zeqi; Chen, Cen; Du, Shiyu; Liu, Daming; Ding, Xia

2018-03-22

Chronic atrophic gastritis (CAG) is the precancerous stage of gastric carcinoma. Traditional Chinese Medicine (TCM) has been widely used in treating CAG. This study aimed to reveal core pathogenesis of CAG by validating the TCM syndrome patterns and provide evidence for optimization of treatment strategies. This is a cross-sectional study conducted in 4 hospitals in China. Hierarchical clustering analysis (HCA) and complex system entropy clustering analysis (CSECA) were performed, respectively, to achieve syndrome pattern validation. Based on HCA, 15 common factors were assigned to 6 syndrome patterns: liver depression and spleen deficiency and blood stasis in the stomach collateral, internal harassment of phlegm-heat and blood stasis in the stomach collateral, phlegm-turbidity internal obstruction, spleen yang deficiency, internal harassment of phlegm-heat and spleen deficiency, and spleen qi deficiency. By CSECA, 22 common factors were assigned to 7 syndrome patterns: qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency. Combination of qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency may play a crucial role in CAG pathogenesis. In accord with this, treatment strategies by TCM herbal prescriptions should be targeted to regulating qi, activating blood, resolving turbidity, clearing heat, removing toxin, nourishing yin, and warming yang. Further explorations are needed to verify and expand the current conclusions.

Merging K-means with hierarchical clustering for identifying general-shaped groups.

Science.gov (United States)

Peterson, Anna D; Ghosh, Arka P; Maitra, Ranjan

2018-01-01

Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and K -means clustering are two approaches but have different strengths and weaknesses. For instance, hierarchical clustering identifies groups in a tree-like structure but suffers from computational complexity in large datasets while K -means clustering is efficient but designed to identify homogeneous spherically-shaped clusters. We present a hybrid non-parametric clustering approach that amalgamates the two methods to identify general-shaped clusters and that can be applied to larger datasets. Specifically, we first partition the dataset into spherical groups using K -means. We next merge these groups using hierarchical methods with a data-driven distance measure as a stopping criterion. Our proposal has the potential to reveal groups with general shapes and structure in a dataset. We demonstrate good performance on several simulated and real datasets.

Role of Anions Associated with the Formation and Properties of Silver Clusters.

Science.gov (United States)

Wang, Quan-Ming; Lin, Yu-Mei; Liu, Kuan-Guan

2015-06-16

Metal clusters have been very attractive due to their aesthetic structures and fascinating properties. Different from nanoparticles, each cluster of a macroscopic sample has a well-defined structure with identical composition, size, and shape. As the disadvantages of polydispersity are ruled out, informative structure-property relationships of metal clusters can be established. The formation of a high-nuclearity metal cluster involves the organization of metal ions into a complex entity in an ordered way. To achieve controllable preparation of metal clusters, it is helpful to introduce a directing agent in the formation process of a cluster. To this end, anion templates have been used to direct the formation of high nuclearity clusters. In this Account, the role of anions played in the formation of a variety of silver clusters has been reviewed. Silver ions are positively charged, so anionic species could be utilized to control the formation of silver clusters on the basis of electrostatic interactions, and the size and shape of the resulted clusters can be dictated by the templating anions. In addition, since the anion is an integral component in the silver clusters described, the physical properties of the clusters can be modulated by functional anions. The templating effects of simple inorganic anions and polyoxometales are shown in silver alkynyl clusters and silver thiolate clusters. Intercluster compounds are also described regarding the importance of anions in determining the packing of the ion pairs and making contribution to electron communications between the positive and negative counterparts. The role of the anions is threefold: (a) an anion is advantageous in stabilizing a cluster via balancing local positive charges of the metal cations; (b) an anion template could help control the size and shape of a cluster product; (c) an anion can be a key factor in influencing the function of a cluster through bringing in its intrinsic properties. Properties

Deployment Strategies and Clustering Protocols Efficiency

Directory of Open Access Journals (Sweden)

Chérif Diallo

2017-06-01

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

PREFACE: Nuclear Cluster Conference; Cluster'07

Science.gov (United States)

Freer, Martin

2008-05-01

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

Intracluster age gradients in numerous young stellar clusters

Science.gov (United States)

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

2018-05-01

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

Autonomic Cluster Management System (ACMS): A Demonstration of Autonomic Principles at Work

Science.gov (United States)

Baldassari, James D.; Kopec, Christopher L.; Leshay, Eric S.; Truszkowski, Walt; Finkel, David

2005-01-01

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of achieving significant computational capabilities for high-performance computing applications, while simultaneously affording the ability to. increase that capability simply by adding more (inexpensive) processors. However, the task of manually managing and con.guring a cluster quickly becomes impossible as the cluster grows in size. Autonomic computing is a relatively new approach to managing complex systems that can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Automatic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management.

Inhomogeneity of epidemic spreading with entropy-based infected clusters.

Science.gov (United States)

Wen-Jie, Zhou; Xing-Yuan, Wang

2013-12-01

Considering the difference in the sizes of the infected clusters in the dynamic complex networks, the normalized entropy based on infected clusters (δ*) is proposed to characterize the inhomogeneity of epidemic spreading. δ* gives information on the variability of the infected clusters in the system. We investigate the variation in the inhomogeneity of the distribution of the epidemic with the absolute velocity v of moving agent, the infection density ρ, and the interaction radius r. By comparing δ* in the dynamic networks with δH* in homogeneous mode, the simulation experiments show that the inhomogeneity of epidemic spreading becomes smaller with the increase of v, ρ, r.

Complex Structure of Galaxy Cluster Abell 1689: Evidence for a Merger from X-Ray Data?

Energy Technology Data Exchange (ETDEWEB)

Andersson, K

2004-01-29

Abell 1689 is a galaxy cluster at z = 0:183 where previous measurements of its mass using various techniques gave discrepant results. We present a new detailed measurement of the mass with the data based on X-ray observations with the European Photon Imaging Camera aboard the XMM-Newton Observatory, determined by using an unparameterized deprojection technique. Fitting the total mass profile to a Navarro-Frenk-White model yields halo concentration c = 7.2{sub -2.4}{sup +1.6} and r{sub 200} = 1.13 {+-} 0.21 h{sup -1} Mpc, corresponding to a mass which is less than half of what is found from gravitational lensing. Adding to the evidence of substructure from optical observations, X-ray analysis shows a highly asymmetric temperature profile and a non-uniform redshift distribution implying large scale relative motion of the gas. A lower than expected gas mass fraction f{sub gas} = 0.072 {+-} 0.008 (for a flat {Lambda}CDM cosmology) suggests a complex spatial and/or dynamical structure. We also find no signs of any additional absorbing component previously reported on the basis of the Chandra data, confirming the XMM low energy response using data from ROSAT.

Young star clusters in nearby molecular clouds

Science.gov (United States)

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

2018-06-01

The SFiNCs (Star Formation in Nearby Clouds) project is an X-ray/infrared study of the young stellar populations in 22 star-forming regions with distances ≲ 1 kpc designed to extend our earlier MYStIX (Massive Young Star-Forming Complex Study in Infrared and X-ray) survey of more distant clusters. Our central goal is to give empirical constraints on cluster formation mechanisms. Using parametric mixture models applied homogeneously to the catalogue of SFiNCs young stars, we identify 52 SFiNCs clusters and 19 unclustered stellar structures. The procedure gives cluster properties including location, population, morphology, association with molecular clouds, absorption, age (AgeJX), and infrared spectral energy distribution (SED) slope. Absorption, SED slope, and AgeJX are age indicators. SFiNCs clusters are examined individually, and collectively with MYStIX clusters, to give the following results. (1) SFiNCs is dominated by smaller, younger, and more heavily obscured clusters than MYStIX. (2) SFiNCs cloud-associated clusters have the high ellipticities aligned with their host molecular filaments indicating morphology inherited from their parental clouds. (3) The effect of cluster expansion is evident from the radius-age, radius-absorption, and radius-SED correlations. Core radii increase dramatically from ˜0.08 to ˜0.9 pc over the age range 1-3.5 Myr. Inferred gas removal time-scales are longer than 1 Myr. (4) Rich, spatially distributed stellar populations are present in SFiNCs clouds representing early generations of star formation. An appendix compares the performance of the mixture models and non-parametric minimum spanning tree to identify clusters. This work is a foundation for future SFiNCs/MYStIX studies including disc longevity, age gradients, and dynamical modelling.

[Complex posttraumatic stress disorder].

Science.gov (United States)

Green, Tamar; Kotler, Moshe

2007-11-01

The characteristic symptoms resulting from exposure to an extreme trauma include three clusters of symptoms: persistent experience of the traumatic event, persistent avoidance of stimuli associated with the trauma and persistent symptoms of increased arousal. Beyond the accepted clusters of symptoms for posttraumatic stress disorder exists a formation of symptoms related to exposure to extreme or prolonged stress e.g. childhood abuse, physical violence, rape, and confinement within a concentration camp. With accumulated evidence of the existence of these symptoms began a trail to classify a more complex syndrome, which included, but was not confined to the symptoms of posttraumatic stress disorder. This review addresses several subjects for study in complex posttraumatic stress disorder, which is a complicated and controversial topic. Firstly, the concept of complex posttraumatic stress disorder is presented. Secondly, the professional literature relevant to this disturbance is reviewed and finally, the authors present the polemic being conducted between the researchers of posttraumatic disturbances regarding validity, reliability and the need for separate diagnosis for these symptoms.

Formation of stable products from cluster-cluster collisions

International Nuclear Information System (INIS)

Alamanova, Denitsa; Grigoryan, Valeri G; Springborg, Michael

2007-01-01

The formation of stable products from copper cluster-cluster collisions is investigated by using classical molecular-dynamics simulations in combination with an embedded-atom potential. The dependence of the product clusters on impact energy, relative orientation of the clusters, and size of the clusters is studied. The structures and total energies of the product clusters are analysed and compared with those of the colliding clusters before impact. These results, together with the internal temperature, are used in obtaining an increased understanding of cluster fusion processes

Atomistic studies of nucleation of He clusters and bubbles in bcc iron

International Nuclear Information System (INIS)

Yang, L.; Deng, H.Q.; Gao, F.; Heinisch, H.L.; Kurtz, R.J.; Hu, S.Y.; Li, Y.L.; Zu, X.T.

2013-01-01

Atomistic simulations of the nucleation of He clusters and bubbles in bcc iron at 800 K have been carried out using the newly developed Fe–Fe interatomic potential, along with Ackland potential for the Fe–Fe interactions. Microstructure changes were analyzed in detail. We found that a He cluster with four He atoms is able to push out an iron interstitial from the cluster, creating a Frenkel pair. Small He clusters and self-interstitial atom (SIA) can migrate in the matrix, but He-vacancy (He-V) clusters are immobile. Most SIAs form clusters, and only the dislocation loops with a Burgers vector of b = 1/2 appear in the simulations. SIA clusters (or loops) are attached to He-V clusters for He implantation up to 1372 appm, while the He-V cluster–loop complexes with more than one He-V cluster are formed at the He concentration of 2057 appm and larger

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

Science.gov (United States)

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

2009-12-22

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

Stable dissipative optical vortex clusters by inhomogeneous effective diffusion.

Science.gov (United States)

Li, Huishan; Lai, Shiquan; Qui, Yunli; Zhu, Xing; Xie, Jianing; Mihalache, Dumitru; He, Yingji

2017-10-30

We numerically show the generation of robust vortex clusters embedded in a two-dimensional beam propagating in a dissipative medium described by the generic cubic-quintic complex Ginzburg-Landau equation with an inhomogeneous effective diffusion term, which is asymmetrical in the two transverse directions and periodically modulated in the longitudinal direction. We show the generation of stable optical vortex clusters for different values of the winding number (topological charge) of the input optical beam. We have found that the number of individual vortex solitons that form the robust vortex cluster is equal to the winding number of the input beam. We have obtained the relationships between the amplitudes and oscillation periods of the inhomogeneous effective diffusion and the cubic gain and diffusion (viscosity) parameters, which depict the regions of existence and stability of vortex clusters. The obtained results offer a method to form robust vortex clusters embedded in two-dimensional optical beams, and we envisage potential applications in the area of structured light.

Subunit stoichiometry of the chloroplast photosystem I complex

International Nuclear Information System (INIS)

Bruce, B.D.; Malkin, R.

1988-01-01

A native photosystem I (PS I) complex and a PS I core complex depleted of antenna subunits has been isolated from the uniformly 14 C-labeled aquatic higher plant, Lemna. These complexes have been analyzed for their subunit stoichiometry by quantitative sodium dodecyl sulfate-polyacrylamide gel electrophoresis methods. The results for both preparations indicate that one copy of each high molecular mass subunit is present per PS I complex and that a single copy of most low molecular mass subunits is also present. These results suggest that iron-sulfur center X, an early PS I electron acceptor proposed to bind to the high molecular mass subunits, contains a single [4Fe-4S] cluster which is bound to a dimeric structure of high molecular mass subunits, each providing 2 cysteine residues to coordinate this cluster

Spin chain simulations with a meron cluster algorithm

International Nuclear Information System (INIS)

Boyer, T.; Bietenholz, W.; Deutsches Elektronen-Synchrotron; Wuilloud, J.; Geneve Univ.

2007-01-01

We apply a meron cluster algorithm to the XY spin chain, which describes a quantum rotor. This is a multi-cluster simulation supplemented by an improved estimator, which deals with objects of half-integer topological charge. This method is powerful enough to provide precise results for the model with a θ-term - it is therefore one of the rare examples, where a system with a complex action can be solved numerically. In particular we measure the correlation length, as well as the topological and magnetic susceptibility. We discuss the algorithmic efficiency in view of the critical slowing down. Due to the excellent performance that we observe, it is strongly motivated to work on new applications of meron cluster algorithms in higher dimensions. (orig.)

Plasmon enhanced silver quantum cluster fluorescence for biochemical applications

DEFF Research Database (Denmark)

Bernard, S.; Kutter, J.P.; Mogensen, Klaus Bo

2014-01-01

Fluorescence microscopy of individual silver quantum clusters on the surface of silver nanoparticles reveals strong photoactivated emission under blue light excitation [1-4]. In this work, silver nanoparticles are produced by annealing silver thin films deposited on a glass substrate and silver q...... purposes. It was found, that in presence of a strong nucleophile (such as CN-), silver quantum clusters are dissolved into non-fluorescing AgCN complexes, resulting in a fast and observable decrease of the fluorescent signal....

Phylogenetic Inference of HIV Transmission Clusters

Directory of Open Access Journals (Sweden)

Vlad Novitsky

2017-10-01

Full Text Available Better understanding the structure and dynamics of HIV transmission networks is essential for designing the most efficient interventions to prevent new HIV transmissions, and ultimately for gaining control of the HIV epidemic. The inference of phylogenetic relationships and the interpretation of results rely on the definition of the HIV transmission cluster. The definition of the HIV cluster is complex and dependent on multiple factors, including the design of sampling, accuracy of sequencing, precision of sequence alignment, evolutionary models, the phylogenetic method of inference, and specified thresholds for cluster support. While the majority of studies focus on clusters, non-clustered cases could also be highly informative. A new dimension in the analysis of the global and local HIV epidemics is the concept of phylogenetically distinct HIV sub-epidemics. The identification of active HIV sub-epidemics reveals spreading viral lineages and may help in the design of targeted interventions.HIVclustering can also be affected by sampling density. Obtaining a proper sampling density may increase statistical power and reduce sampling bias, so sampling density should be taken into account in study design and in interpretation of phylogenetic results. Finally, recent advances in long-range genotyping may enable more accurate inference of HIV transmission networks. If performed in real time, it could both inform public-health strategies and be clinically relevant (e.g., drug-resistance testing.

Nuclear clustering - a cluster core model study

International Nuclear Information System (INIS)

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

2015-01-01

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

The threshold bootstrap clustering: a new approach to find families or transmission clusters within molecular quasispecies.

Directory of Open Access Journals (Sweden)

Mattia C F Prosperi

2010-10-01

Full Text Available Phylogenetic methods produce hierarchies of molecular species, inferring knowledge about taxonomy and evolution. However, there is not yet a consensus methodology that provides a crisp partition of taxa, desirable when considering the problem of intra/inter-patient quasispecies classification or infection transmission event identification. We introduce the threshold bootstrap clustering (TBC, a new methodology for partitioning molecular sequences, that does not require a phylogenetic tree estimation.The TBC is an incremental partition algorithm, inspired by the stochastic Chinese restaurant process, and takes advantage of resampling techniques and models of sequence evolution. TBC uses as input a multiple alignment of molecular sequences and its output is a crisp partition of the taxa into an automatically determined number of clusters. By varying initial conditions, the algorithm can produce different partitions. We describe a procedure that selects a prime partition among a set of candidate ones and calculates a measure of cluster reliability. TBC was successfully tested for the identification of type-1 human immunodeficiency and hepatitis C virus subtypes, and compared with previously established methodologies. It was also evaluated in the problem of HIV-1 intra-patient quasispecies clustering, and for transmission cluster identification, using a set of sequences from patients with known transmission event histories.TBC has been shown to be effective for the subtyping of HIV and HCV, and for identifying intra-patient quasispecies. To some extent, the algorithm was able also to infer clusters corresponding to events of infection transmission. The computational complexity of TBC is quadratic in the number of taxa, lower than other established methods; in addition, TBC has been enhanced with a measure of cluster reliability. The TBC can be useful to characterise molecular quasipecies in a broad context.

The threshold bootstrap clustering: a new approach to find families or transmission clusters within molecular quasispecies.

Science.gov (United States)

Prosperi, Mattia C F; De Luca, Andrea; Di Giambenedetto, Simona; Bracciale, Laura; Fabbiani, Massimiliano; Cauda, Roberto; Salemi, Marco

2010-10-25

Phylogenetic methods produce hierarchies of molecular species, inferring knowledge about taxonomy and evolution. However, there is not yet a consensus methodology that provides a crisp partition of taxa, desirable when considering the problem of intra/inter-patient quasispecies classification or infection transmission event identification. We introduce the threshold bootstrap clustering (TBC), a new methodology for partitioning molecular sequences, that does not require a phylogenetic tree estimation. The TBC is an incremental partition algorithm, inspired by the stochastic Chinese restaurant process, and takes advantage of resampling techniques and models of sequence evolution. TBC uses as input a multiple alignment of molecular sequences and its output is a crisp partition of the taxa into an automatically determined number of clusters. By varying initial conditions, the algorithm can produce different partitions. We describe a procedure that selects a prime partition among a set of candidate ones and calculates a measure of cluster reliability. TBC was successfully tested for the identification of type-1 human immunodeficiency and hepatitis C virus subtypes, and compared with previously established methodologies. It was also evaluated in the problem of HIV-1 intra-patient quasispecies clustering, and for transmission cluster identification, using a set of sequences from patients with known transmission event histories. TBC has been shown to be effective for the subtyping of HIV and HCV, and for identifying intra-patient quasispecies. To some extent, the algorithm was able also to infer clusters corresponding to events of infection transmission. The computational complexity of TBC is quadratic in the number of taxa, lower than other established methods; in addition, TBC has been enhanced with a measure of cluster reliability. The TBC can be useful to characterise molecular quasipecies in a broad context.

Supervised maximum-likelihood weighting of composite protein networks for complex prediction

Directory of Open Access Journals (Sweden)

Yong Chern Han

2012-12-01

Full Text Available Abstract Background Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true complexes go undetected. Results We address these challenges by integrating PPI data with other heterogeneous data sources to construct a composite protein network, and using a supervised maximum-likelihood approach to weight each edge based on its posterior probability of belonging to a complex. We then use six different clustering algorithms, and an aggregative clustering strategy, to discover complexes in the weighted network. We test our method on Saccharomyces cerevisiae and Homo sapiens, and show that complex discovery is improved: compared to previously proposed supervised and unsupervised weighting approaches, our method recalls more known complexes, achieves higher precision at all recall levels, and generates novel complexes of greater functional similarity. Furthermore, our maximum-likelihood approach allows learned parameters to be used to visualize and evaluate the evidence of novel predictions, aiding human judgment of their credibility. Conclusions Our approach integrates multiple data sources with supervised learning to create a weighted composite protein network, and uses six clustering algorithms with an aggregative clustering strategy to

From globally coupled maps to complex-systems biology

Energy Technology Data Exchange (ETDEWEB)

Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp [Research Center for Complex Systems Biology, Graduate School of Arts and Sciences, The University of Tokyo 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902 (Japan)

2015-09-15

Studies of globally coupled maps, introduced as a network of chaotic dynamics, are briefly reviewed with an emphasis on novel concepts therein, which are universal in high-dimensional dynamical systems. They include clustering of synchronized oscillations, hierarchical clustering, chimera of synchronization and desynchronization, partition complexity, prevalence of Milnor attractors, chaotic itinerancy, and collective chaos. The degrees of freedom necessary for high dimensionality are proposed to equal the number in which the combinatorial exceeds the exponential. Future analysis of high-dimensional dynamical systems with regard to complex-systems biology is briefly discussed.

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

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

2006-01-01

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

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

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

2008-01-01

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

HotRegion: a database of predicted hot spot clusters.

Science.gov (United States)

Cukuroglu, Engin; Gursoy, Attila; Keskin, Ozlem

2012-01-01

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.

Gas expulsion in highly substructured embedded star clusters

Science.gov (United States)

Farias, J. P.; Fellhauer, M.; Smith, R.; Domínguez, R.; Dabringhausen, J.

2018-06-01

We investigate the response of initially substructured, young, embedded star clusters to instantaneous gas expulsion of their natal gas. We introduce primordial substructure to the stars and the gas by simplistically modelling the star formation process so as to obtain a variety of substructure distributed within our modelled star-forming regions. We show that, by measuring the virial ratio of the stars alone (disregarding the gas completely), we can estimate how much mass a star cluster will retain after gas expulsion to within 10 per cent accuracy, no matter how complex the background structure of the gas is, and we present a simple analytical recipe describing this behaviour. We show that the evolution of the star cluster while still embedded in the natal gas, and the behaviour of the gas before being expelled, is crucial process that affect the time-scale on which the cluster can evolve into a virialized spherical system. Embedded star clusters that have high levels of substructure are subvirial for longer times, enabling them to survive gas expulsion better than a virialized and spherical system. By using a more realistic treatment for the background gas than our previous studies, we find it very difficult to destroy the young clusters with instantaneous gas expulsion. We conclude that gas removal may not be the main culprit for the dissolution of young star clusters.

Recent development in clusters of rare earths and actinides. Chemistry and materials

Energy Technology Data Exchange (ETDEWEB)

Zheng, Zhiping (ed.) [Arizona Univ., Tucson, AZ (United States). Dept. of Chemistry and Biochemistry

2017-02-01

This book contains the following eight contributions: 1. Lanthanide Hydroxide Cluster Complexes via Ligand-Controlled Hydrolysis of the Lanthanide Ions (Zhonghao Zhang, Yanan Zhang, and Zhiping Zheng); 2. Synthesis and Structures of Lanthanide-Transition Metal Clusters (Xiu-Ying Zheng, Xiang-Jian Kong, and La-Sheng Long); 3. Hydrothermal Synthesis of Lanthanide and Lanthanide-Transition-Metal Cluster Organic Frameworks via Synergistic Coordination Strategy (Jian-Wen Cheng and Guo-Yu Yang); 4. Oxo Clusters of 5f Elements (Sarah Hickam and Peter C.); 5. Construction and Luminescence Properties of 4f and d-4f Clusters with Salen-Type Schiff Base Ligands (Xiaoping Yang, Shiqing Wang, Chengri Wang, Shaoming Huang, and Richard A.); 6. 4f-Clusters for Cryogenic Magnetic Cooling (Yan-Cong Chen, Jun-Liang Liu, and Ming-Liang Tong); 7. Lanthanide Clusters Toward Single-Molecule Magnets (Tian Han, You-Song Ding, and Yan-Zhen Zheng); 8. Molecular Rare Earth Hydride Clusters (Takanori Shima and Zhaomin Hou).

Recent development in clusters of rare earths and actinides. Chemistry and materials

International Nuclear Information System (INIS)

Zheng, Zhiping

2017-01-01

This book contains the following eight contributions: 1. Lanthanide Hydroxide Cluster Complexes via Ligand-Controlled Hydrolysis of the Lanthanide Ions (Zhonghao Zhang, Yanan Zhang, and Zhiping Zheng); 2. Synthesis and Structures of Lanthanide-Transition Metal Clusters (Xiu-Ying Zheng, Xiang-Jian Kong, and La-Sheng Long); 3. Hydrothermal Synthesis of Lanthanide and Lanthanide-Transition-Metal Cluster Organic Frameworks via Synergistic Coordination Strategy (Jian-Wen Cheng and Guo-Yu Yang); 4. Oxo Clusters of 5f Elements (Sarah Hickam and Peter C.); 5. Construction and Luminescence Properties of 4f and d-4f Clusters with Salen-Type Schiff Base Ligands (Xiaoping Yang, Shiqing Wang, Chengri Wang, Shaoming Huang, and Richard A.); 6. 4f-Clusters for Cryogenic Magnetic Cooling (Yan-Cong Chen, Jun-Liang Liu, and Ming-Liang Tong); 7. Lanthanide Clusters Toward Single-Molecule Magnets (Tian Han, You-Song Ding, and Yan-Zhen Zheng); 8. Molecular Rare Earth Hydride Clusters (Takanori Shima and Zhaomin Hou).

Preconditions for Emergence of Lithuanian Clusters: from Informal Cooperation to Its Legitimation

Directory of Open Access Journals (Sweden)

Grumadaitė Kristina

2017-06-01

Full Text Available This paper reveals preconditions for the emergence of clusters as self-organisation based industrial systems in a context, in which cooperation traditions are insufficiently developed. These preconditions reflect the principles of the emergence of self-organising complex adaptive systems that are analysed in the complexity theory. Those principles are based on the initiation of non-equilibrium and its purposeful direction into the creation of a new order. This paper highlights the main external and internal tensions that influence informal or formal clustering of enterprises, while various change agents perform different roles making self-organising processes to occur.

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-08-05

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

{Ni4O4} Cluster Complex to Enhance the Reductive Photocurrent Response on Silicon Nanowire Photocathodes

Directory of Open Access Journals (Sweden)

Yatin J. Mange

2017-02-01

Full Text Available Metal organic {Ni4O4} clusters, known oxidation catalysts, have been shown to provide a valuable route in increasing the photocurrent response on silicon nanowire (SiNW photocathodes. {Ni4O4} clusters have been paired with SiNWs to form a new photocathode composite for water splitting. Under AM1.5 conditions, the combination of {Ni4O4} clusters with SiNWs gave a current density of −16 mA/cm2, which corresponds to an increase in current density of 60% when compared to bare SiNWs. The composite electrode was fully characterised and shown to be an efficient and stable photocathode for water splitting.

Investigation of Carbon Monoxide Adsorption on Cationic Gold- Palladium Clusters

Science.gov (United States)

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

2013-11-01

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

A conformal mapping approach to a root-clustering problem

International Nuclear Information System (INIS)

Melnikov, Gennady I; Dudarenko, Nataly A; Melnikov, Vitaly G

2014-01-01

This paper presents a new approach for matrix root-clustering in sophisticated and multiply-connected regions of the complex plane. The parametric sweeping method and a concept of the closed forbidden region covered by a set of modified three-parametrical Cassini regions are used. A conformal mapping approach was applied to formulate the main results of the paper. An application of the developed method to the problem of matrix root-clustering in a multiply connected region is shown for illustration

Inelastic neutron scattering from clusters

International Nuclear Information System (INIS)

Gudel, H.U.

1985-01-01

Magnetic excitations in clusters of paramagnetic ions have non-vanishing cross-sections for inelastic neutron scattering (INS). Exchange splittings can be determined, the temperature dependence of exchange can be studied, intra- and intercluster effects can be separated and magnetic form factors determined. INS provides a more direct access to the molecular properties than bulk techniques. Its application is restricted to complexes with no or few (< 10%) hydrogen atoms

ESPRIT-Tree: hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time.

Science.gov (United States)

Cai, Yunpeng; Sun, Yijun

2011-08-01

Taxonomy-independent analysis plays an essential role in microbial community analysis. Hierarchical clustering is one of the most widely employed approaches to finding operational taxonomic units, the basis for many downstream analyses. Most existing algorithms have quadratic space and computational complexities, and thus can be used only for small or medium-scale problems. We propose a new online learning-based algorithm that simultaneously addresses the space and computational issues of prior work. The basic idea is to partition a sequence space into a set of subspaces using a partition tree constructed using a pseudometric, then recursively refine a clustering structure in these subspaces. The technique relies on new methods for fast closest-pair searching and efficient dynamic insertion and deletion of tree nodes. To avoid exhaustive computation of pairwise distances between clusters, we represent each cluster of sequences as a probabilistic sequence, and define a set of operations to align these probabilistic sequences and compute genetic distances between them. We present analyses of space and computational complexity, and demonstrate the effectiveness of our new algorithm using a human gut microbiota data set with over one million sequences. The new algorithm exhibits a quasilinear time and space complexity comparable to greedy heuristic clustering algorithms, while achieving a similar accuracy to the standard hierarchical clustering algorithm.

Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks.

Science.gov (United States)

Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L; Carr, Lincoln D

2017-12-01

We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z_{2}, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.

Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks

Science.gov (United States)

Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L.; Carr, Lincoln D.

2017-12-01

We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z2, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.

Exploring biological network structure with clustered random networks

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Bansal Shweta

2009-12-01

Full Text Available Abstract Background Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions and the extent of clustering (the tendency for a set of three nodes to be interconnected are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics. Results Here we develop and implement a new Markov chain simulation algorithm to generate simple, connected random graphs that have a specified degree sequence and level of clustering, but are random in all other respects. The implementation of the algorithm (ClustRNet: Clustered Random Networks provides the generation of random graphs optimized according to a local or global, and relative or absolute measure of clustering. We compare our algorithm to other similar methods and show that ours more successfully produces desired network characteristics. Finding appropriate null models is crucial in bioinformatics research, and is often difficult, particularly for biological networks. As we demonstrate, the networks generated by ClustRNet can serve as random controls when investigating the impacts of complex network features beyond the byproduct of degree and clustering in empirical networks. Conclusion ClustRNet generates ensembles of graphs of specified edge structure and clustering. These graphs allow for systematic study of the impacts of connectivity and redundancies on network function and dynamics. This process is a key step in

Comprehensive cluster analysis with Transitivity Clustering.

Science.gov (United States)

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

2011-03-01

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

Spontaneous brain network activity: Analysis of its temporal complexity

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Mangor Pedersen

2017-06-01

Full Text Available The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node and participation coefficients (the between-module connectivity of a node were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1 Entropy is higher for the participation coefficient than for the clustering coefficient. (2 The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3 The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient and integration (the participation coefficient are temporally complex

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects

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Dreyhaupt, Jens

2017-05-01

Full Text Available An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called “cluster randomization”. Compared with studies with individual randomization, studies with cluster randomization normally require (significantly larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies.Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies.

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects.

Science.gov (United States)

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called "cluster randomization"). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies.

Cluster-cluster correlations and constraints on the correlation hierarchy

Science.gov (United States)

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

1988-01-01

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Molecular-dynamics analysis of mobile helium cluster reactions near surfaces of plasma-exposed tungsten

Energy Technology Data Exchange (ETDEWEB)

Hu, Lin; Maroudas, Dimitrios, E-mail: maroudas@ecs.umass.edu [Department of Chemical Engineering, University of Massachusetts, Amherst, Massachusetts 01003-9303 (United States); Hammond, Karl D. [Department of Chemical Engineering, University of Missouri, Columbia, Missouri 65211 (United States); Wirth, Brian D. [Department of Nuclear Engineering, University of Tennessee, Knoxville, Tennessee 37996 (United States)

2015-10-28

We report the results of a systematic atomic-scale analysis of the reactions of small mobile helium clusters (He{sub n}, 4 ≤ n ≤ 7) near low-Miller-index tungsten (W) surfaces, aiming at a fundamental understanding of the near-surface dynamics of helium-carrying species in plasma-exposed tungsten. These small mobile helium clusters are attracted to the surface and migrate to the surface by Fickian diffusion and drift due to the thermodynamic driving force for surface segregation. As the clusters migrate toward the surface, trap mutation (TM) and cluster dissociation reactions are activated at rates higher than in the bulk. TM produces W adatoms and immobile complexes of helium clusters surrounding W vacancies located within the lattice planes at a short distance from the surface. These reactions are identified and characterized in detail based on the analysis of a large number of molecular-dynamics trajectories for each such mobile cluster near W(100), W(110), and W(111) surfaces. TM is found to be the dominant cluster reaction for all cluster and surface combinations, except for the He{sub 4} and He{sub 5} clusters near W(100) where cluster partial dissociation following TM dominates. We find that there exists a critical cluster size, n = 4 near W(100) and W(111) and n = 5 near W(110), beyond which the formation of multiple W adatoms and vacancies in the TM reactions is observed. The identified cluster reactions are responsible for important structural, morphological, and compositional features in the plasma-exposed tungsten, including surface adatom populations, near-surface immobile helium-vacancy complexes, and retained helium content, which are expected to influence the amount of hydrogen re-cycling and tritium retention in fusion tokamaks.

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Science.gov (United States)

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

2015-01-01

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

Protein complex prediction via dense subgraphs and false positive analysis.

Directory of Open Access Journals (Sweden)

Cecilia Hernandez

Full Text Available Many proteins work together with others in groups called complexes in order to achieve a specific function. Discovering protein complexes is important for understanding biological processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI networks, which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some approaches are topology-based, where highly connected proteins are predicted to be complexes; some propose different clustering algorithms using partitioning, overlaps among clusters for networks modeled with unweighted or weighted graphs; and others use density of clusters and information based on protein functionality. However, some schemes still require much processing time or the quality of their results can be improved. Furthermore, most of the results obtained with computational tools are not accompanied by an analysis of false positives. We propose an effective and efficient mining algorithm for discovering highly connected subgraphs, which is our base for defining protein complexes. Our representation is based on transforming the PPI network into a directed acyclic graph that reduces the number of represented edges and the search space for discovering subgraphs. Our approach considers weighted and unweighted PPI networks. We compare our best alternative using PPI networks from Saccharomyces cerevisiae (yeast and Homo sapiens (human with state-of-the-art approaches in terms of clustering, biological metrics and execution times, as well as three gold standards for yeast and two for human. Furthermore, we analyze false positive predicted complexes searching the PDBe (Protein Data Bank in Europe database in order to identify matching protein complexes that have been purified and structurally characterized. Our analysis shows

Extensive polycistronism and antisense transcription in the mammalian Hox clusters.

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Gaëll Mainguy

Full Text Available The Hox clusters play a crucial role in body patterning during animal development. They encode both Hox transcription factor and micro-RNA genes that are activated in a precise temporal and spatial sequence that follows their chromosomal order. These remarkable collinear properties confer functional unit status for Hox clusters. We developed the TranscriptView platform to establish high resolution transcriptional profiling and report here that transcription in the Hox clusters is far more complex than previously described in both human and mouse. Unannotated transcripts can represent up to 60% of the total transcriptional output of a cluster. In particular, we identified 14 non-coding Transcriptional Units antisense to Hox genes, 10 of which (70% have a detectable mouse homolog. Most of these Transcriptional Units in both human and mouse present conserved sizeable sequences (>40 bp overlapping Hox transcripts, suggesting that these Hox antisense transcripts are functional. Hox clusters also display at least seven polycistronic clusters, i.e., different genes being co-transcribed on long isoforms (up to 30 kb. This work provides a reevaluated framework for understanding Hox gene function and dys-function. Such extensive transcriptions may provide a structural explanation for Hox clustering.

Analyzing Dynamic Probabilistic Risk Assessment Data through Topology-Based Clustering

Energy Technology Data Exchange (ETDEWEB)

Diego Mandelli; Dan Maljovec; BeiWang; Valerio Pascucci; Peer-Timo Bremer

2013-09-01

We investigate the use of a topology-based clustering technique on the data generated by dynamic event tree methodologies. The clustering technique we utilizes focuses on a domain-partitioning algorithm based on topological structures known as the Morse-Smale complex, which partitions the data points into clusters based on their uniform gradient flow behavior. We perform both end state analysis and transient analysis to classify the set of nuclear scenarios. We demonstrate our methodology on a dataset generated for a sodium-cooled fast reactor during an aircraft crash scenario. The simulation tracks the temperature of the reactor as well as the time for a recovery team to fix the passive cooling system. Combined with clustering results obtained previously through mean shift methodology, we present the user with complementary views of the data that help illuminate key features that may be otherwise hidden using a single methodology. By clustering the data, the number of relevant test cases to be selected for further analysis can be drastically reduced by selecting a representative from each cluster. Identifying the similarities of simulations within a cluster can also aid in the drawing of important conclusions with respect to safety analysis.

K-AP: Generating specified K clusters by efficient Affinity Propagation

KAUST Repository

Zhang, Xiangliang

2010-12-01

The Affinity Propagation (AP) clustering algorithm proposed by Frey and Dueck (2007) provides an understandable, nearly optimal summary of a data set. However, it suffers two major shortcomings: i) the number of clusters is vague with the user-defined parameter called self-confidence, and ii) the quadratic computational complexity. When aiming at a given number of clusters due to prior knowledge, AP has to be launched many times until an appropriate setting of self-confidence is found. The re-launched AP increases the computational cost by one order of magnitude. In this paper, we propose an algorithm, called K-AP, to exploit the immediate results of K clusters by introducing a constraint in the process of message passing. Through theoretical analysis and experimental validation, K-AP was shown to be able to directly generate K clusters as user defined, with a negligible increase of computational cost compared to AP. In the meanwhile, K-AP preserves the clustering quality as AP in terms of the distortion. K-AP is more effective than k-medoids w.r.t. the distortion minimization and higher clustering purity. © 2010 IEEE.

Message Passing Framework for Globally Interconnected Clusters

International Nuclear Information System (INIS)

Hafeez, M; Riaz, N; Asghar, S; Malik, U A; Rehman, A

2011-01-01

In prevailing technology trends it is apparent that the network requirements and technologies will advance in future. Therefore the need of High Performance Computing (HPC) based implementation for interconnecting clusters is comprehensible for scalability of clusters. Grid computing provides global infrastructure of interconnecting clusters consisting of dispersed computing resources over Internet. On the other hand the leading model for HPC programming is Message Passing Interface (MPI). As compared to Grid computing, MPI is better suited for solving most of the complex computational problems. MPI itself is restricted to a single cluster. It does not support message passing over the internet to use the computing resources of different clusters in an optimal way. We propose a model that provides message passing capabilities between parallel applications over the internet. The proposed model is based on Architecture for Java Universal Message Passing (A-JUMP) framework and Enterprise Service Bus (ESB) named as High Performance Computing Bus. The HPC Bus is built using ActiveMQ. HPC Bus is responsible for communication and message passing in an asynchronous manner. Asynchronous mode of communication offers an assurance for message delivery as well as a fault tolerance mechanism for message passing. The idea presented in this paper effectively utilizes wide-area intercluster networks. It also provides scheduling, dynamic resource discovery and allocation, and sub-clustering of resources for different jobs. Performance analysis and comparison study of the proposed framework with P2P-MPI are also presented in this paper.

Bond percolation on a class of correlated and clustered random graphs

International Nuclear Information System (INIS)

Allard, A; Hébert-Dufresne, L; Noël, P-A; Marceau, V; Dubé, L J

2012-01-01

We introduce a formalism for computing bond percolation properties of a class of correlated and clustered random graphs. This class of graphs is a generalization of the configuration model where nodes of different types are connected via different types of hyperedges, edges that can link more than two nodes. We argue that the multitype approach coupled with the use of clustered hyperedges can reproduce a wide spectrum of complex patterns, and thus enhances our capability to model real complex networks. As an illustration of this claim, we use our formalism to highlight unusual behaviours of the size and composition of the components (small and giant) in a synthetic, albeit realistic, social network. (paper)

Physical-depth architectural requirements for generating universal photonic cluster states

Science.gov (United States)

Morley-Short, Sam; Bartolucci, Sara; Gimeno-Segovia, Mercedes; Shadbolt, Pete; Cable, Hugo; Rudolph, Terry

2018-01-01

Most leading proposals for linear-optical quantum computing (LOQC) use cluster states, which act as a universal resource for measurement-based (one-way) quantum computation. In ballistic approaches to LOQC, cluster states are generated passively from small entangled resource states using so-called fusion operations. Results from percolation theory have previously been used to argue that universal cluster states can be generated in the ballistic approach using schemes which exceed the critical threshold for percolation, but these results consider cluster states with unbounded size. Here we consider how successful percolation can be maintained using a physical architecture with fixed physical depth, assuming that the cluster state is continuously generated and measured, and therefore that only a finite portion of it is visible at any one point in time. We show that universal LOQC can be implemented using a constant-size device with modest physical depth, and that percolation can be exploited using simple pathfinding strategies without the need for high-complexity algorithms.

Diffusion of He interstitial and di-He cluster at grain boundaries in α-Fe

International Nuclear Information System (INIS)

Gao, F.; Heinisch, H.L.; Kurtz, R.J.

2007-01-01

A systematic molecular dynamics study of the diffusion mechanisms of He interstitial and di-He cluster at two representative interfaces has been carried out in α-Fe. The diffusion coefficient of a He interstitial and the effective migration energies were determined. The He atom diffuses along the Σ11 grain boundary one-dimensionally along specific directions, while it migrates two-dimensionally at low temperatures, and three-dimensionally at higher temperatures, in the Σ3 grain boundary. The di-He interstitial cluster can migrate rapidly along the Σ3 interface at low temperatures, but not at the Σ11 interface. It has been observed that a di-He interstitial cluster can kick out a self interstitial atom (SIA) at high temperatures, forming a He 2 V complex. The SIA migrates rapidly near interfaces, whereas the He 2 V complex is immobile at the temperatures considered. This small cluster may serve as the smallest nucleation for the formation of helium bubbles at interfaces

Formation of Compact Ellipticals in the merging star cluster scenario

Science.gov (United States)

Urrutia Zapata, Fernanda Cecilia; Theory and star formation group

2018-01-01

In the last years, extended old stellar clusters have been observed. They are like globular clusters (GCs) but with larger sizes(a limit of Re=10 pc is currently seen as reasonable). These extended objects (EOs) cover a huge range of mass. Objects at the low mass end with masses comparable to normal globular clusters are called extended clusters or faint fuzzies Larsen & Brodie (2000) and objects at the high-mass end are called ultra compact dwarf galaxies (UCDs). Ultra compact dwarf galaxies are compact object with luminositys above the brigtest known GCs. UCDs are more compact than typical dwarf galaxies but with comparable luminosities. Usually, a lower mass limit of 2 × 10^6 Solar masses is applied.Fellhauer & Kroupa (2002a,b) demostrated that object like ECs, FFs and UCDs can be the remnants of the merger of star clusters complexes, this scenario is called the Merging Star Cluster Scenario. Amore concise study was performed by Bruens et al. (2009, 2011).Our work tries to explain the formation of compact elliptical(cE). These objects are a comparatively rare class of spheroidal galaxies, possessing very small Re and high central surface brightnesses (Faber 1973). cEs have the same parameters as extended objects but they are slightly larger than 100 pc and the luminosities are in the range of -11 to -12 Mag.The standard formation sceanrio of these systems proposes a galaxy origin. CEs are the result of tidal stripping and truncation of nucleated larger systems. Or they could be a natural extension of the class of elliptical galaxies to lower luminosities and smaller sizes.We want to propose a completely new formation scenario for cEs. In our project we try to model cEs in a similar way that UCDs using the merging star cluster scenario extended to much higher masses and sizes. We think that in the early Universe we might have produced sufficiently strong star bursts to form cluster complexes which merge into cEs. So far it is observationally unknown if cEs are

PROSPECTS OF THE REGIONAL INTEGRATION POLICY BASED ON CLUSTER FORMATION

Directory of Open Access Journals (Sweden)

Elena Tsepilova

2018-01-01

Full Text Available The purpose of this article is to develop the theoretical foundations of regional integration policy and to determine its prospects on the basis of cluster formation. The authors use such research methods as systematization, comparative and complex analysis, synthesis, statistical method. Within the framework of the research, the concept of regional integration policy is specified, and its integration core – cluster – is allocated. The authors work out an algorithm of regional clustering, which will ensure the growth of economy and tax income. Measures have been proposed to optimize the organizational mechanism of interaction between the participants of the territorial cluster and the authorities that allow to ensure the effective functioning of clusters, including taxation clusters. Based on the results of studying the existing methods for assessing the effectiveness of cluster policy, the authors propose their own approach to evaluating the consequences of implementing the regional integration policy, according to which the list of quantitative and qualitative indicators is defined. The present article systematizes the experience and results of the cluster policy of certain European countries, that made it possible to determine the prospects and synergetic effect from the development of clusters as an integration foundation of regional policy in the Russian Federation. The authors carry out the analysis of activity of cluster formations using the example of the Rostov region – a leader in the formation of conditions for the cluster policy development in the Southern Federal District. 11 clusters and cluster initiatives are developing in this region. As a result, the authors propose measures for support of the already existing clusters and creation of the new ones.

Metal interactions with boron clusters

International Nuclear Information System (INIS)

Grimes, R.N.

1982-01-01

This book presents information on the following topics: the structural and bonding features of metallaboranes and metallacarboranes; transition-metal derivatives of nido-boranes and some related species; interactions of metal groups with the octahydrotriborate (1-) anion, B 3 H 8 ; metallaboron cage compounds of the main group metals; closo-carborane-metal complexes containing metal-carbon and metal-boron omega-bonds; electrochemistry of metallaboron cage compounds; and boron clusters with transition metal-hydrogen bonds

Cluster management.

Science.gov (United States)

Katz, R

1992-11-01

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

A Starburst in the Core of a Galaxy Cluster: the Dwarf Irregular NGC 1427A in Fornax

Science.gov (United States)

Mora, Marcelo D.; Chanamé, Julio; Puzia, Thomas H.

2015-09-01

Gas-rich galaxies in dense environments such as galaxy clusters and massive groups are affected by a number of possible types of interactions with the cluster environment, which make their evolution radically different than that of field galaxies. The dwarf irregular galaxy NGC 1427A, presently infalling toward the core of the Fornax galaxy cluster for the first time, offers a unique opportunity to study those processes at a level of detail not possible to achieve for galaxies at higher redshifts, when galaxy-scale interactions were more common. Using the spatial resolution of the Hubble Space Telescope/Advanced Camera for Surveys and auxiliary Very Large Telescope/FORS1 ground-based observations, we study the properties of the most recent episodes of star formation in this gas-rich galaxy, the only one of its type near the core of the Fornax cluster. We study the structural and photometric properties of young star cluster complexes in NGC 1427A, identifying 12 bright such complexes with exceptionally blue colors. The comparison of our broadband near-UV/optical photometry with simple stellar population models yields ages below ˜ 4× {10}6 years and stellar masses from a few 1000 up to ˜ 3× {10}4{M}⊙ , slightly dependent on the assumption of cluster metallicity and initial mass function. Their grouping is consistent with hierarchical and fractal star cluster formation. We use deep Hα imaging data to determine the current star formation rate in NGC 1427A and estimate the ratio, Γ, of star formation occurring in these star cluster complexes to that in the entire galaxy. We find Γ to be among the largest such values available in the literature, consistent with starburst galaxies. Thus a large fraction of the current star formation in NGC 1427A is occurring in star clusters, with the peculiar spatial arrangement of such complexes strongly hinting at the possibility that the starburst is being triggered by the passage of the galaxy through the cluster environment

Emergent and multiplicative effect in a cluster

Directory of Open Access Journals (Sweden)

I. V. Linev

2016-01-01

Full Text Available The concept “Cluster” of domestic and foreign literature traditionally is considered as administrative and organizational education. At the same time he represents the social and economic object created for life support of the person. The cluster is considered as system object. The main signs are defined and his life cycle is considered. Cluster self-organization takes place stages: growth of organizational weight and effects, market threats and restrictions interfering growth of organizational weight. Development of clusters requires the state support in various forms which is offered to be carried out at various stages depending on his type. The cluster is considered as the economic system possessing an emergent which dynamic aspect is the synergy, the receiving multiplicative effect causing an opportunity. The quantitative assessment of size of the listed effects represents rather complex challenge, at the same time there is a number of the factors which are with her in directly proportional dependence. The synergy which is present at a cluster allows to gain social and economic effect of his functioning by means of integration of effects of all structural elements bigger, than their simple sum. The emergent in a cluster causes increase of productivity at the expense of innovations in technological and organizational spheres and stimulations of the birth of new businesses. The multiplicative effect arising in a cluster provides incremental nature of economic results. It is possible to refer the following to the main economic results received from creation and development of clusters: decrease in transactional and transformational expenses and costs of formation and further use of infrastructure, economy of costs of introduction and development of the high and innovative technologies, optimization of logistic and information expenses, increase of business reputation and investment appeal.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review.

Science.gov (United States)

Leech, Rebecca M; McNaughton, Sarah A; Timperio, Anna

2014-01-22

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5-18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥ 9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is

Accelerated EM-based clustering of large data sets

NARCIS (Netherlands)

Verbeek, J.J.; Nunnink, J.R.J.; Vlassis, N.

2006-01-01

Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms like k-means, we derive an accelerated variant of the EM algorithm for Gaussian mixtures that: (1) offers speedups that

Reactions of ruthenium and osmium cluster carbonyls with heteroatom-substituted and functionalized alkynes

International Nuclear Information System (INIS)

Koridze, A.A.

2000-01-01

The results of studies of the reactions of ruthenium and osmium cluster carbonyls with metal (M = Re, Mn, Fe) alkynes, silylalkynes, propargyl alcohols and their derivatives, diynes, enynes, and ferrocenylacetylene are summarized. Intramolecular rearrangements in the cluster complexes including migrations of carbonyl, hydride, and hydrocarbon ligands and the metal core reorganization are considered [ru

2012 Gordon Research Conference On Molecular And Ionic Clusters

International Nuclear Information System (INIS)

McCoy, Anne

2012-01-01

The Gordon Research Conference on 'Molecular and Ionic Clusters' focuses on clusters, which are the initial molecular species found in gases when condensation begins to occur. Condensation can take place solely from molecules interacting with each other, mostly at low temperatures, or when molecules condense around charged particles (electrons, protons, metal cations, molecular ions), producing ion molecule clusters. These clusters provide models for solvation, allow a pristine look at geometric as well as electronic structures of molecular complexes or matter in general, their interaction with radiation, their reactivity, their thermodynamic properties and, in particular, the related dynamics. This conference focuses on new ways to make clusters composed of different kinds of molecules, new experimental techniques to investigate the properties of the clusters and new theoretical methods with which to calculate the structures, dynamical motions and energetics of the clusters. Some of the main experimental methods employed include molecular beams, mass spectrometry, laser spectroscopy (from infrared to XUV; in the frequency as well as the time domain) and photoelectron spectroscopy. Techniques include laser absorption spectroscopy, laser induced fluorescence, resonance enhanced photoionization, mass-selected photodissociation, photofragment imaging, ZEKE photoelectron spectroscopy, etc. From the theoretical side, this conference highlights work on potential surfaces and measurable properties of the clusters. The close ties between experiment, theory and computation have been a hallmark of the Gordon Research Conference on Molecular and Ionic Clusters. In the 2012 meeting, we plan to have sessions that will focus on topics including: (1) The use of cluster studies to probe fundamental phenomena; (2) Finite size effects on structure and thermodynamics; (3) Intermolecular forces and cooperative effects; (4) Molecular clusters as models for solvation; and (5) Studies of

Scalability analysis of the synchronizability for ring or chain networks with dense clusters

International Nuclear Information System (INIS)

Lu, Jun-An; Zhang, Yong; Chen, Juan; Lü, Jinhu

2014-01-01

It is well known that most real-world complex networks, such as the Internet and the World Wide Web, are evolving networks. An interesting fundamental question is: how do some important functions or dynamical behaviors of complex networks evolve with increasing network scale? This paper aims at investigating the scalability of the synchronizability for ring or chain networks with dense clusters as the network size increases. We discover some interesting phenomena as follows: (i) the synchronizability of ring or chain networks with clusters decreases with increasing network scale regardless of the inner structures of all communities; (ii) for the same network scale, the network synchronizability decreases more quickly with increasing number of cluster blocks than with increasing number of nodes within the cluster block; (iii) the number of rings or chains has a much more significant influence on the network synchronizability than the size of the rings or chains. Our results indicate that network synchronizability can be maintained with increasing network scale by avoiding ring and chain structures. (paper)

CO dissociation on magnetic Fen clusters

KAUST Repository

Jedidi, Abdesslem

2014-01-01

This work theoretically investigates the CO dissociation on Fen nanoparticles, for n in the range of 1-65, focusing on size dependence in the context of the initial step of the Fischer-Tropsch reaction. CO adsorbs molecularly through its C-end on a triangular facet of the nanoparticle. Dissociation becomes easier when the cluster size increases. Then, the C atom is bonded to a square facet that is generated as a result of the adsorption if it does not yet exist in the bare cluster, while the O atom is adsorbed on a triangular facet. In the most stable situation, the two adsorbed atoms remain close together, both having in common one shared first-neighbor iron atom. There is a partial spin quenching of the neighboring Fe atoms, which become more positively charged than the other Fe atoms. The shared surface iron atom resembles a metal-cation from a complex. Despite the small size of the iron cluster considered, fluctuations due to specific configurations do not influence properties for n > 25 and global trends seem significant.

Lifting to cluster-tilting objects in higher cluster categories

OpenAIRE

Liu, Pin

2008-01-01

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

Clustered DNA lesion repair in eukaryotes: Relevance to mutagenesis and cell survival

Energy Technology Data Exchange (ETDEWEB)

Sage, Evelyne [Institut Curie, Bat. 110, Centre Universitaire, 91405 Orsay (France); CNRS UMR3348, Bat. 110, Centre Universitaire, 91405 Orsay (France); Harrison, Lynn, E-mail: lclary@lsuhsc.edu [Department of Molecular and Cellular Physiology, LSUHSC-S, 1501 Kings Highway, Shreveport, LA 71130 (United States)

2011-06-03

A clustered DNA lesion, also known as a multiply damaged site, is defined as {>=}2 damages in the DNA within 1-2 helical turns. Only ionizing radiation and certain chemicals introduce DNA damage in the genome in this non-random way. What is now clear is that the lethality of a damaging agent is not just related to the types of DNA lesions introduced, but also to how the damage is distributed in the DNA. Clustered DNA lesions were first hypothesized to exist in the 1990s, and work has progressed where these complex lesions have been characterized and measured in irradiated as well as in non-irradiated cells. A clustered lesion can consist of single as well as double strand breaks, base damage and abasic sites, and the damages can be situated on the same strand or opposing strands. They include tandem lesions, double strand break (DSB) clusters and non-DSB clusters, and base excision repair as well as the DSB repair pathways can be required to remove these complex lesions. Due to the plethora of oxidative damage induced by ionizing radiation, and the repair proteins involved in their removal from the DNA, it has been necessary to study how repair systems handle these lesions using synthetic DNA damage. This review focuses on the repair process and mutagenic consequences of clustered lesions in yeast and mammalian cells. By examining the studies on synthetic clustered lesions, and the effects of low vs high LET radiation on mammalian cells or tissues, it is possible to extrapolate the potential biological relevance of these clustered lesions to the killing of tumor cells by radiotherapy and chemotherapy, and to the risk of cancer in non-tumor cells, and this will be discussed.

Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

Science.gov (United States)

Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

2017-09-01

Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

Data Clustering

Science.gov (United States)

Wagstaff, Kiri L.

2012-03-01

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

Dense Fe cluster-assembled films by energetic cluster deposition

International Nuclear Information System (INIS)

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

2004-01-01

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

Cluster Physics with Merging Galaxy Clusters

Directory of Open Access Journals (Sweden)

Sandor M. Molnar

2016-02-01

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

Completion Report for Well Cluster ER-6-1

Energy Technology Data Exchange (ETDEWEB)

Bechtel Nevada

2004-10-01

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

A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm

Directory of Open Access Journals (Sweden)

Wenping Zou

2010-01-01

Full Text Available Artificial Bee Colony (ABC is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper presents an extended ABC algorithm, namely, the Cooperative Article Bee Colony (CABC, which significantly improves the original ABC in solving complex optimization problems. Clustering is a popular data analysis and data mining technique; therefore, the CABC could be used for solving clustering problems. In this work, first the CABC algorithm is used for optimizing six widely used benchmark functions and the comparative results produced by ABC, Particle Swarm Optimization (PSO, and its cooperative version (CPSO are studied. Second, the CABC algorithm is used for data clustering on several benchmark data sets. The performance of CABC algorithm is compared with PSO, CPSO, and ABC algorithms on clustering problems. The simulation results show that the proposed CABC outperforms the other three algorithms in terms of accuracy, robustness, and convergence speed.

A SPECTROSCOPIC ANALYSIS OF THE GALACTIC GLOBULAR CLUSTER NGC 6273 (M19)

Energy Technology Data Exchange (ETDEWEB)

Johnson, Christian I.; Caldwell, Nelson [Harvard–Smithsonian Center for Astrophysics, 60 Garden Street, MS-15, Cambridge, MA 02138 (United States); Rich, R. Michael [Department of Physics and Astronomy, UCLA, 430 Portola Plaza, Box 951547, Los Angeles, CA 90095-1547 (United States); Pilachowski, Catherine A. [Astronomy Department, Indiana University Bloomington, Swain West 319, 727 East 3rd Street, Bloomington, IN 47405-7105 (United States); Mateo, Mario; Bailey, John I. III [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States); Crane, Jeffrey D., E-mail: cjohnson@cfa.harvard.edu, E-mail: ncaldwell@cfa.harvard.edu, E-mail: rmr@astro.ucla.edu, E-mail: catyp@astro.indiana.edu, E-mail: mmateo@umich.edu, E-mail: baileyji@umich.edu, E-mail: crane@obs.carnegiescience.edu [The Observatories of the Carnegie Institution for Science, Pasadena, CA 91101 (United States)

2015-08-15

A combined effort utilizing spectroscopy and photometry has revealed the existence of a new globular cluster class. These “anomalous” clusters, which we refer to as “iron-complex” clusters, are differentiated from normal clusters by exhibiting large (≳0.10 dex) intrinsic metallicity dispersions, complex sub-giant branches, and correlated [Fe/H] and s-process enhancements. In order to further investigate this phenomenon, we have measured radial velocities and chemical abundances for red giant branch stars in the massive, but scarcely studied, globular cluster NGC 6273. The velocities and abundances were determined using high resolution (R ∼ 27,000) spectra obtained with the Michigan/Magellan Fiber System (M2FS) and MSpec spectrograph on the Magellan–Clay 6.5 m telescope at Las Campanas Observatory. We find that NGC 6273 has an average heliocentric radial velocity of +144.49 km s{sup −1} (σ = 9.64 km s{sup −1}) and an extended metallicity distribution ([Fe/H] = −1.80 to −1.30) composed of at least two distinct stellar populations. Although the two dominant populations have similar [Na/Fe], [Al/Fe], and [α/Fe] abundance patterns, the more metal-rich stars exhibit significant [La/Fe] enhancements. The [La/Eu] data indicate that the increase in [La/Fe] is due to almost pure s-process enrichment. A third more metal-rich population with low [X/Fe] ratios may also be present. Therefore, NGC 6273 joins clusters such as ω Centauri, M2, M22, and NGC 5286 as a new class of iron-complex clusters exhibiting complicated star formation histories.

Cluster analysis of rural, urban, and curbside atmospheric particle size data.

Science.gov (United States)

Beddows, David C S; Dall'Osto, Manuel; Harrison, Roy M

2009-07-01

Particle size is a key determinant of the hazard posed by airborne particles. Continuous multivariate particle size data have been collected using aerosol particle size spectrometers sited at four locations within the UK: Harwell (Oxfordshire); Regents Park (London); British Telecom Tower (London); and Marylebone Road (London). These data have been analyzed using k-means cluster analysis, deduced to be the preferred cluster analysis technique, selected from an option of four partitional cluster packages, namelythe following: Fuzzy; k-means; k-median; and Model-Based clustering. Using cluster validation indices k-means clustering was shown to produce clusters with the smallest size, furthest separation, and importantly the highest degree of similarity between the elements within each partition. Using k-means clustering, the complexity of the data set is reduced allowing characterization of the data according to the temporal and spatial trends of the clusters. At Harwell, the rural background measurement site, the cluster analysis showed that the spectra may be differentiated by their modal-diameters and average temporal trends showing either high counts during the day-time or night-time hours. Likewise for the urban sites, the cluster analysis differentiated the spectra into a small number of size distributions according their modal-diameter, the location of the measurement site, and time of day. The responsible aerosol emission, formation, and dynamic processes can be inferred according to the cluster characteristics and correlation to concurrently measured meteorological, gas phase, and particle phase measurements.

p-tert-Butylcalix[8]arene: an extremely versatile platform for cluster formation.

Science.gov (United States)

Taylor, Stephanie M; Sanz, Sergio; McIntosh, Ruaraidh D; Beavers, Christine M; Teat, Simon J; Brechin, Euan K; Dalgarno, Scott J

2012-12-07

p-tert-Butylcalix[4]arene is a bowl-shaped molecule capable of forming a range of polynuclear metal clusters under different experimental conditions. p-tert-Butylcalix[8]arene (TBC[8]) is a significantly more flexible analogue that has previously been shown to form mono- and binuclear lanthanide (Ln) metal complexes. The latter (cluster) motif is commonly observed and involves the calixarene adopting a near double-cone conformation, features of which suggested that it may be exploited as a type of assembly node in the formation of larger polynuclear lanthanide clusters. Variation in the experimental conditions employed for this system provides access to Ln(1), Ln(2), Ln(4), Ln(5), Ln(6), Ln(7) and Ln(8) complexes, with all polymetallic clusters containing the common binuclear lanthanide fragment. Closer inspection of the structures of the polymetallic clusters reveals that all but one (Ln(8)) are in fact based on metal octahedra or the building blocks of octahedra, with the identity and size of the final product dependent upon the basicity of the solution and the deprotonation level of the TBC[8] ligand. This demonstrates both the versatility of the ligand towards incorporation of additional metal centres, and the associated implications for tailoring the magnetic properties of the resulting assemblies in which lanthanide centres may be interchanged. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Investigating the synthesis of ligated metal clusters in solution using a flow reactor and electrospray ionization mass spectrometry.

Science.gov (United States)

Olivares, Astrid; Laskin, Julia; Johnson, Grant E

2014-09-18

The scalable synthesis of ligated subnanometer metal clusters containing an exact number of atoms is of interest due to the highly size-dependent catalytic, electronic, and optical properties of these species. While significant research has been conducted on the batch preparation of clusters through reduction synthesis in solution, the processes of metal complex reduction as well as cluster nucleation, growth, and postreduction etching are still not well understood. Herein, we demonstrate a prototype temperature-controlled flow reactor for qualitatively studying cluster formation in solution at steady-state conditions. Employing this technique, methanol solutions of a chloro(triphenylphosphine)gold precursor, 1,4-bis(diphenylphosphino)butane capping ligand, and borane-tert-butylamine reducing agent were combined in a mixing tee and introduced into a heated capillary with a known length. In this manner, the temperature dependence of the relative abundance of different ionic reactants, intermediates, and products synthesized in real time was characterized qualitatively using online mass spectrometry. A wide distribution of doubly and triply charged cationic gold clusters was observed as well as smaller singly charged organometallic complexes. The results demonstrate that temperature plays a crucial role in determining the relative population of cationic gold clusters and, in general, that higher temperature promotes the formation of doubly charged clusters and singly charged organometallic complexes while reducing the abundance of triply charged species. Moreover, the distribution of clusters observed at elevated temperatures is found to be consistent with that obtained at longer reaction times at room temperature, thereby demonstrating that heating may be used to access cluster distributions characteristic of different stages of batch reduction synthesis in solution.

User and Document Group Approach of Clustering in Tagging Systems

DEFF Research Database (Denmark)

Pan, Rong; Xu, Guandong; Dolog, Peter

2010-01-01

In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optim...... amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group....

Performance of networks of artificial neurons: The role of clustering

International Nuclear Information System (INIS)

Kim, Beom Jun

2004-01-01

The performance of the Hopfield neural network model is numerically studied on various complex networks, such as the Watts-Strogatz network, the Barabasi-Albert network, and the neuronal network of Caenorhabditis elegans. Through the use of a systematic way of controlling the clustering coefficient, with the degree of each neuron kept unchanged, we find that the networks with the lower clustering exhibit much better performance. The results are discussed in the practical viewpoint of application, and the biological implications are also suggested

Polygons, Stars, and Clusters; an Investigation of Polygon Displays

Science.gov (United States)

1988-01-01

variables were chosen, nine in each case , to give reasonably complex polygons without being too complex. I have seen no reported studies of the relation...Pont. Catalina C Datsun 210, Toyota Corolla, Dodge Colt, Honda Civic, Mazda GLC, Subaru, Ford Fiesta, Plym. Champ Figure 6. Clusters on the basis of...Merc. Marquis, Pont. Catalina, Pont. Grand Prix C Datsun 210, Toyota Corolla, Dodge Colt, Honda Civic, Mazda GLC, Subaru, Ford Fiesta, Plym. Champ

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

Science.gov (United States)

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

2014-11-01

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

Clustered DNA damages induced in human hematopoietic cells by low doses of ionizing radiation

Science.gov (United States)

Sutherland, Betsy M.; Bennett, Paula V.; Cintron-Torres, Nela; Hada, Megumi; Trunk, John; Monteleone, Denise; Sutherland, John C.; Laval, Jacques; Stanislaus, Marisha; Gewirtz, Alan

2002-01-01

Ionizing radiation induces clusters of DNA damages--oxidized bases, abasic sites and strand breaks--on opposing strands within a few helical turns. Such damages have been postulated to be difficult to repair, as are double strand breaks (one type of cluster). We have shown that low doses of low and high linear energy transfer (LET) radiation induce such damage clusters in human cells. In human cells, DSB are about 30% of the total of complex damages, and the levels of DSBs and oxidized pyrimidine clusters are similar. The dose responses for cluster induction in cells can be described by a linear relationship, implying that even low doses of ionizing radiation can produce clustered damages. Studies are in progress to determine whether clusters can be produced by mechanisms other than ionizing radiation, as well as the levels of various cluster types formed by low and high LET radiation.

Constructing a graph of connections in clustering algorithm of complex objects

Directory of Open Access Journals (Sweden)

Татьяна Шатовская

2015-05-01

Full Text Available The article describes the results of modifying the algorithm Chameleon. Hierarchical multi-level algorithm consists of several phases: the construction of the count, coarsening, the separation and recovery. Each phase can be used various approaches and algorithms. The main aim of the work is to study the quality of the clustering of different sets of data using a set of algorithms combinations at different stages of the algorithm and improve the stage of construction by the optimization algorithm of k choice in the graph construction of k of nearest neighbors

Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs

Directory of Open Access Journals (Sweden)

Theis Fabian J

2010-10-01

Full Text Available Abstract Background Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the interpretation of these networks. While most research focuses on the unipartite or bipartite case, we address the more general but common situation of k-partite graphs. These graphs contain k different node types and links are only allowed between nodes of different types. In order to reveal their structural organization and describe the contained information in a more coarse-grained fashion, we ask how to detect clusters within each node type. Results Since entities in biological networks regularly have more than one function and hence participate in more than one cluster, we developed a k-partite graph partitioning algorithm that allows for overlapping (fuzzy clusters. It determines for each node a degree of membership to each cluster. Moreover, the algorithm estimates a weighted k-partite graph that connects the extracted clusters. Our method is fast and efficient, mimicking the multiplicative update rules commonly employed in algorithms for non-negative matrix factorization. It facilitates the decomposition of networks on a chosen scale and therefore allows for analysis and interpretation of structures on various resolution levels. Applying our algorithm to a tripartite disease-gene-protein complex network, we were able to structure this graph on a large scale into clusters that are functionally correlated and biologically meaningful. Locally, smaller clusters enabled reclassification or annotation of the clusters' elements. We exemplified this for the transcription factor MECP2. Conclusions In order to cope with the overwhelming amount of information available from biomedical literature, we need to tackle the challenge of finding structures in large networks with nodes of multiple types. To this end, we presented a novel fuzzy k-partite graph partitioning

Validating clustering of molecular dynamics simulations using polymer models

Directory of Open Access Journals (Sweden)

Phillips Joshua L

2011-11-01

Full Text Available Abstract Background Molecular dynamics (MD simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our

Cluster dynamics at different cluster size and incident laser wavelengths

International Nuclear Information System (INIS)

Desai, Tara; Bernardinello, Andrea

2002-01-01

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

Zinc(II) complexes of carboxamide derivatives: Crystal structures ...

Indian Academy of Sciences (India)

can form complexes with a variety of metal ions. Recently, bi- ... tural analyses of both ligands and complex 1 by single crystal X-ray ..... software over a Red Hat Linux IBM cluster using den- .... Change in the relative viscosity (η/ηo)1/3 of CT-.

NGC 346: Looking in the Cradle of a Massive Star Cluster

Science.gov (United States)

Gouliermis, Dimitrios A.; Hony, Sacha

2017-03-01

How does a star cluster of more than few 10,000 solar masses form? We present the case of the cluster NGC 346 in the Small Magellanic Cloud, still embedded in its natal star-forming region N66, and we propose a scenario for its formation, based on observations of the rich stellar populations in the region. Young massive clusters host a high fraction of early-type stars, indicating an extremely high star formation efficiency. The Milky Way galaxy hosts several young massive clusters that fill the gap between young low-mass open clusters and old massive globular clusters. Only a handful, though, are young enough to study their formation. Moreover, the investigation of their gaseous natal environments suffers from contamination by the Galactic disk. Young massive clusters are very abundant in distant starburst and interacting galaxies, but the distance of their hosting galaxies do not also allow a detailed analysis of their formation. The Magellanic Clouds, on the other hand, host young massive clusters in a wide range of ages with the youngest being still embedded in their giant HII regions. Hubble Space Telescope imaging of such star-forming complexes provide a stellar sampling with a high dynamic range in stellar masses, allowing the detailed study of star formation at scales typical for molecular clouds. Our cluster analysis on the distribution of newly-born stars in N66 shows that star formation in the region proceeds in a clumpy hierarchical fashion, leading to the formation of both a dominant young massive cluster, hosting about half of the observed pre-main-sequence population, and a self-similar dispersed distribution of the remaining stars. We investigate the correlation between stellar surface density (and star formation rate derived from star-counts) and molecular gas surface density (derived from dust column density) in order to unravel the physical conditions that gave birth to NGC 346. A power law fit to the data yields a steep correlation between these

Reduced-dimension power allocation over clustered channels in cognitive radios system under co-channel interference

KAUST Repository

Ben Ghorbel, Mahdi

2014-05-12

The objective of this paper is to propose a reduceddimension resource allocation scheme in the context of cognitive radio system in presence of co-channel interference between users. We assume a multicarrier transmission for both the primary and secondary systems. Instead of optimizing the powers over all sub-carriers, the sub-carriers are grouped into clusters of sub-carriers, where the power of each sub-carrier is directly related to the power of the correspondent cluster. The power optimization is done only over the set of clusters instead of all sub-carriers which can significantly reduce the complexity of the resource allocation problem. The performance loss of the reduced dimension solution with respect to the optimal solution, where the optimization is carried over all active sub-carriers, allows trading-off complexity versus performance. Numerical evaluation indeed revealed that a limited performance loss occurs by optimizing over a reduced set of clusters instead of the full optimization in the context of cognitive radio systems.

On clusters and clustering from atoms to fractals

CERN Document Server

Reynolds, PJ

1993-01-01

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

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

Science.gov (United States)

Koslovsky, Matthew; Arellano, John; Schaefer, Caroline; Feiveson, Alan; Young, Millennia; Lee, Stuart

2017-01-01

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.

Particular Distribution of Enterobacter cloacae Strains Isolated from Urinary Tract Infection within Clonal Complexes.

Science.gov (United States)

Akbari, Majid; Bakhshi, Bita; Najar Peerayeh, Shahin

2016-01-01

Based on biochemical properties, Enterobacter cloacae represents a large complex of at least 13 variant species, subspecies, and genotypes that progressively identified as the most species causing hospital-acquired infections. The aim of this study was to determine the relevance between phylogenetically related strains within the E. cloacae complex and the frequency of urinary tract infection caused by them. A 268-bp fragment was obtained from hsp60 gene for 50 clinical E. cloacae isolates from urine cultures of inpatients that admitted to six hospitals in Tehran, Iran during December 2012 to November 2013. The 107 nucleotide sequences were analyzed and the evolutionary distances of sequences were computed and neighbor-joining tree was calculated. It showed that all of the genetic clusters have not an equal involvement in pathogenesis of urinary tract infections. Three superior clusters were found, together representing more than two third (80%) of the isolates (cluster VI with 25 members; clusters III and VIII with 9 and 6 members, respectively) and some genetic clusters were absent (IV, X, XII, and xiii), some of which are supposed to be associated with plants and no human infection has been reported. This study, for the first time, reports the unequal contribution of E. cloacae complex subspecies and clusters in urinary tract infections in Iran and together with studies from other countries suggest that the subspecies of E.hormaechei subsp. Oharae is the most prevalent E. cloacae complex subspecies regardless of country under study.

NP-hardness of the cluster minimization problem revisited

Science.gov (United States)

Adib, Artur B.

2005-10-01

The computational complexity of the 'cluster minimization problem' is revisited (Wille and Vennik 1985 J. Phys. A: Math. Gen. 18 L419). It is argued that the original NP-hardness proof does not apply to pairwise potentials of physical interest, such as those that depend on the geometric distance between the particles. A geometric analogue of the original problem is formulated, and a new proof for such potentials is provided by polynomial time transformation from the independent set problem for unit disk graphs. Limitations of this formulation are pointed out, and new subproblems that bear more direct consequences to the numerical study of clusters are suggested.

NP-hardness of the cluster minimization problem revisited

International Nuclear Information System (INIS)

Adib, Artur B

2005-01-01

The computational complexity of the 'cluster minimization problem' is revisited (Wille and Vennik 1985 J. Phys. A: Math. Gen. 18 L419). It is argued that the original NP-hardness proof does not apply to pairwise potentials of physical interest, such as those that depend on the geometric distance between the particles. A geometric analogue of the original problem is formulated, and a new proof for such potentials is provided by polynomial time transformation from the independent set problem for unit disk graphs. Limitations of this formulation are pointed out, and new subproblems that bear more direct consequences to the numerical study of clusters are suggested

NP-hardness of the cluster minimization problem revisited

Energy Technology Data Exchange (ETDEWEB)

Adib, Artur B [Physics Department, Brown University, Providence, RI 02912 (United States)

2005-10-07

The computational complexity of the 'cluster minimization problem' is revisited (Wille and Vennik 1985 J. Phys. A: Math. Gen. 18 L419). It is argued that the original NP-hardness proof does not apply to pairwise potentials of physical interest, such as those that depend on the geometric distance between the particles. A geometric analogue of the original problem is formulated, and a new proof for such potentials is provided by polynomial time transformation from the independent set problem for unit disk graphs. Limitations of this formulation are pointed out, and new subproblems that bear more direct consequences to the numerical study of clusters are suggested.

GLOBULAR CLUSTERS AND SPUR CLUSTERS IN NGC 4921, THE BRIGHTEST SPIRAL GALAXY IN THE COMA CLUSTER

International Nuclear Information System (INIS)

Lee, Myung Gyoon; Jang, In Sung

2016-01-01

We resolve a significant fraction of globular clusters (GCs) in NGC 4921, the brightest spiral galaxy in the Coma cluster. We also find a number of extended bright star clusters (star complexes) in the spur region of the arms. The latter are much brighter and bluer than those in the normal star-forming region, being as massive as 3 × 10 5 M ⊙ . The color distribution of the GCs in this galaxy is found to be bimodal. The turnover magnitudes of the luminosity functions of the blue (metal-poor) GCs (0.70 < (V − I) ≤ 1.05) in the halo are estimated V(max) = 27.11 ± 0.09 mag and I(max) = 26.21 ± 0.11 mag. We obtain similar values for NGC 4923, a companion S0 galaxy, and two Coma cD galaxies (NGC 4874 and NGC 4889). The mean value for the turnover magnitudes of these four galaxies is I(max) = 26.25 ± 0.03 mag. Adopting M I (max) = −8.56 ± 0.09 mag for the metal-poor GCs, we determine the mean distance to the four Coma galaxies to be 91 ± 4 Mpc. Combining this with the Coma radial velocity, we derive a value of the Hubble constant, H 0  = 77.9 ± 3.6 km s −1 Mpc −1 . We estimate the GC specific frequency of NGC 4921 to be S N  = 1.29 ± 0.25, close to the values for early-type galaxies. This indicates that NGC 4921 is in the transition phase to S0s

GLOBULAR CLUSTERS AND SPUR CLUSTERS IN NGC 4921, THE BRIGHTEST SPIRAL GALAXY IN THE COMA CLUSTER

Energy Technology Data Exchange (ETDEWEB)

Lee, Myung Gyoon; Jang, In Sung, E-mail: mglee@astro.snu.ac.kr, E-mail: isjang@astro.snu.ac.kr [Astronomy Program, Department of Physics and Astronomy, Seoul National University, Gwanak-gu, Seoul 151-742 (Korea, Republic of)

2016-03-01

We resolve a significant fraction of globular clusters (GCs) in NGC 4921, the brightest spiral galaxy in the Coma cluster. We also find a number of extended bright star clusters (star complexes) in the spur region of the arms. The latter are much brighter and bluer than those in the normal star-forming region, being as massive as 3 × 10{sup 5} M{sub ⊙}. The color distribution of the GCs in this galaxy is found to be bimodal. The turnover magnitudes of the luminosity functions of the blue (metal-poor) GCs (0.70 < (V − I) ≤ 1.05) in the halo are estimated V(max) = 27.11 ± 0.09 mag and I(max) = 26.21 ± 0.11 mag. We obtain similar values for NGC 4923, a companion S0 galaxy, and two Coma cD galaxies (NGC 4874 and NGC 4889). The mean value for the turnover magnitudes of these four galaxies is I(max) = 26.25 ± 0.03 mag. Adopting M{sub I} (max) = −8.56 ± 0.09 mag for the metal-poor GCs, we determine the mean distance to the four Coma galaxies to be 91 ± 4 Mpc. Combining this with the Coma radial velocity, we derive a value of the Hubble constant, H{sub 0} = 77.9 ± 3.6 km s{sup −1} Mpc{sup −1}. We estimate the GC specific frequency of NGC 4921 to be S{sub N} = 1.29 ± 0.25, close to the values for early-type galaxies. This indicates that NGC 4921 is in the transition phase to S0s.

Non-extensive statistical aspects of clustering and nuclear multi-fragmentation

International Nuclear Information System (INIS)

Calboreanu, A.

2002-01-01

Recent developments concerning an application of the non-extensive Tsalis statistics to describe clustering phenomena is briefly presented. Cluster formation is a common feature of a large number of physical phenomena encountered in molecular and nuclear physics, astrophysics, condensed matter and biophysics. Common to all these is the large number of degrees of freedom, thus justifying a statistical approach. However the conventional statistical mechanics paradigm seems to fail in dealing with clustering. Whether this is due to the prevalence of complex dynamical constrains, or it is a manifestation of new statistics is a subject of considerable interest, which was intensively debated during the last few years. Tsalis conjecture has proved extremely appealing due to its rather elegant and transparent basic arguments. We present here evidence for its adequacy for the study of a large class of physical phenomena related to cluster formation. An application to nuclear multi-fragmentation is presented. (author)

Health-related fitness profiles in adolescents with complex congenital heart disease

DEFF Research Database (Denmark)

Klausen, Susanne Hwiid; Wetterslev, Jørn; Søndergaard, Lars

2015-01-01

PURPOSE: This study investigates whether subgroups of different health-related fitness (HrF) profiles exist among girls and boys with complex congenital heart disease (ConHD) and how these are associated with lifestyle behaviors. METHODS: We measured the cardiorespiratory fitness, muscle strength...... in the Robust clusters reported leading a physically active lifestyle and participants in the Less robust cluster reported leading a sedentary lifestyle. Diagnoses were evenly distributed between clusters. CONCLUSIONS: The cluster analysis attributed some of the variability in cardiorespiratory fitness among...

GibbsCluster: unsupervised clustering and alignment of peptide sequences

DEFF Research Database (Denmark)

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-01-01

motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large......-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0....

Priority Directions of The Regional Food Complex Effectiveness Increase

Directory of Open Access Journals (Sweden)

Dmitry Andreyevich Karkh

2015-06-01

Full Text Available In the article, the modern trends of management integration as a solution of food and sectoral problems are considered. On the basis of national and foreign experience of development of integration, the classification of integration in economic systems is developed. On the basis of the given classification, the concept of integration is conducted. In the article, much attention is given to the food problem solution, which depends more on the agro-industrial complex based on metaintegration. The leading place of a food complex in the system of agro-industrial complex is caused by a role of food and food raw materials in life of the population of the country. The ratio of the sectors participating in the food production and consumer goods makes the sectoral structure of agro-industrial complex. In the conditions of the resource limitation necessary for the production and food delivery to the domestic market, the role of trade will increase not only in agro-industrial complex, but in all national economy. Also, in this article, the phenomenon of clusters is studied. The attention to clusters as to innovation systems reflects a rising tide of interest of economic science to the questions of economics functioning in regional level and understanding of a role of specific local resources in stimulation of innovative opportunities and competitiveness of small and medium business. Creating a cluster, participants develop the spatial and organizational integrated structure, in interaction of legal entities the status is saved and cooperation provides competitive advantages with other business entities. The role of the state in integration of cluster formations in the Russian Federation is more significant, than in any other country. The state represented by regional authorities actively participates in decision-making process by the business located in its catchment area not only through membership in governing bodies of large joint stock companies.

A redox-switchable Au8-cluster sensor.

Science.gov (United States)

Wu, Te-Haw; Hsu, Yu-Yen; Lin, Shu-Yi

2012-07-09

The proof of concept of a simple sensing platform based on the fluorescence of a gold cluster consisting of eight atoms, which is easily manipulated by reduction and oxidation of a specific molecule in the absence of chemical linkers, is demonstrated. Without using any coupling reagents to arrange the distance of the donor-acceptor pair, the fluorescence of the Au(8) -cluster is immediately switched off in the presence of 2-pyridinethiol (2-PyT) quencher. Through an upward-curving Stern-Volmer plot, the system shows complex fluorescence quenching with a combination of static and dynamic quenching processes. To analyze the static quenching constant (V) by a "sphere of action" model, the collisional encounter between the Au(8) -cluster and 2-PyT presents a quenching radius (r) ≈5.8 nm, which is larger than the sum of the radii of the Au(8) -cluster and 2-PyT. This implies that fluorescence quenching can occur even though the Au(8) -cluster and 2-PyT are not very close to each other. The quenching pathway may be derived from a photoinduced electron-transfer process of the encounter pair between the Au(8) -cluster (as an electron donor) and 2-PyT (as an electron acceptor) to allow efficient fluorescence quenching in the absence of coupling reagents. Interestingly, the fluorescence is restored by oxidation of 2-PyT to form the corresponding disulfide compound and then quenched again after the reduction of the disulfide. This redox-switchable fluorescent Au(8) -cluster platform is a novel discovery, and its utility as a promising sensor for detecting H(2) O(2) -generating enzymatic transformations is demonstrated. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Diametrical clustering for identifying anti-correlated gene clusters.

Science.gov (United States)

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

2003-09-01

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

Partitional clustering algorithms

CERN Document Server

2015-01-01

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

Shaping Globular Clusters with Black Holes

Science.gov (United States)

Kohler, Susanna

2018-03-01

How many black holes lurk within the dense environments of globular clusters, and how do these powerful objects shape the properties of the cluster around them? One such cluster, NGC 3201, is now helping us to answer these questions.Hunting Stellar-Mass Black HolesSince the detection of merging black-hole binaries by the Laser Interferometer Gravitational-Wave Observatory (LIGO), the dense environments of globular clusters have received increasing attention as potential birthplaces of these compact binary systems.The central region of the globular star cluster NGC 3201, as viewed by Hubble. The black hole is in orbit with the star marked by the blue circle. [NASA/ESA]In addition, more and more stellar-mass black-hole candidates have been observed within globular clusters, lurking in binary pairs with luminous, non-compact companions. The most recent of these detections, found in the globular cluster NGC 3201, stands alone as the first stellar-mass black hole candidate discovered via radial velocity observations: the black holes main-sequence companion gave away its presence via a telltale wobble.Now a team of scientists led by Kyle Kremer (CIERA and Northwestern University) is using models of this system to better understand the impact that black holes might have on their host clusters.A Model ClusterThe relationship between black holes and their host clusters is complicated. Though the cluster environment can determine the dynamical evolution of the black holes, the retention rate of black holes in a globular cluster (i.e., how many remain in the cluster when they are born as supernovae, rather than being kicked out during the explosion) influences how the host cluster evolves.Kremer and collaborators track this complex relationship by modeling the evolution of a cluster similar to NGC 3201 with a Monte Carlo code. The code incorporates physics relevant to the evolution of black holes and black-hole binaries in globular clusters, such as two-body relaxation

THE STRUCTURAL EVOLUTION OF FORMING AND EARLY STAGE STAR CLUSTERS

International Nuclear Information System (INIS)

Jaehnig, Karl O.; Da Rio, Nicola; Tan, Jonathan C.

2015-01-01

We study the degree of angular substructure in the stellar position distribution of young members of Galactic star-forming regions, looking for correlations with distance from cluster center, surface number density of stars, and local dynamical age. To this end we adopt the catalog of members in 18 young (∼1-3 Myr) clusters from the Massive Young Star-Forming Complex Study in Infrared and X-ray Survey and the statistical analysis of the angular dispersion parameter, δ ADP, N . We find statistically significant correlation between δ ADP, N and physical projected distance from the center of the clusters, with the centers appearing smoother than the outskirts, consistent with more rapid dynamical processing on local dynamical, free-fall or orbital timescales. Similarly, smoother distributions are seen in regions of higher surface density, or older dynamical ages. These results indicate that dynamical processing that erases substructure is already well-advanced in young, sometimes still-forming, clusters. Such observations of the dissipation of substructure have the potential to constrain theoretical models of the dynamical evolution of young and forming clusters

Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis

Directory of Open Access Journals (Sweden)

Sen Zhang

2015-01-01

Full Text Available One heuristic evolutionary algorithm recently proposed is the grey wolf optimizer (GWO, inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature. This paper presents an extended GWO algorithm based on Powell local optimization method, and we call it PGWO. PGWO algorithm significantly improves the original GWO in solving complex optimization problems. Clustering is a popular data analysis and data mining technique. Hence, the PGWO could be applied in solving clustering problems. In this study, first the PGWO algorithm is tested on seven benchmark functions. Second, the PGWO algorithm is used for data clustering on nine data sets. Compared to other state-of-the-art evolutionary algorithms, the results of benchmark and data clustering demonstrate the superior performance of PGWO algorithm.

Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

Directory of Open Access Journals (Sweden)

Yimei Wang

2018-04-01

Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

Identifying Clusters of Complex Urban–Rural Issues as Part of Policy Making Process Using a Network Analysis Approach: A Case Study in Bahía de Los Ángeles, Mexico

Directory of Open Access Journals (Sweden)

Javier Sandoval

2017-06-01

Full Text Available Improving human settlements diagnosis is a key factor in effective urban planning and the design of efficient policy making. In this paper, we illustrate how network theory concepts can be applied to reveal the topological structure of functional relationships in a network of heterogeneous urban–rural issues. This mapping is done using clustering algorithms and centrality value techniques. By analyzing emergent groups of urban–rural related issues, our methodology was applied to a rural community, considering in this exercise environmental matters and real estate interests as a way to better understand the structure of salient issues in the context of its urban development program design. Results show clusters that arrange themselves not by an obvious similarity in their constituent components, but by relations observed in urban–rural settings that hint on the issues that the urban development program must focus. Due to its complex nature, the classification of these emerging clusters and how they must be treated in traditional planning instruments is a new challenge that this novel methodology reveals.

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

Directory of Open Access Journals (Sweden)

Susan Worner

2013-09-01

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

A Deep Chandra Observation of the Distant Galaxy Cluster MS 1137.5+6625

Science.gov (United States)

Grego, Laura; Vrtilek, J. M.; Van Speybroeck, Leon; David, Laurence P.; Forman, William; Carlstrom, John E.; Reese, Erik D.; Joy, Marshall K.

2004-06-01

We present results from a deep Chandra observation of MS 1137.5+66, a distant (z=0.783) and massive cluster of galaxies. Only a few similarly massive clusters are currently known at such high redshifts; accordingly, this observation provides much needed information on the dynamical state of these rare systems. The cluster appears both regular and symmetric in the X-ray image. However, our analysis of the spectral and spatial X-ray data in conjunction with interferometric Sunyaev-Zel'dovich effect data and published deep optical imaging suggests that the cluster has a fairly complex structure. The angular diameter distance we calculate from the Chandra and Sunyaev-Zel'dovich effect data assuming an isothermal, spherically symmetric cluster implies a low value for the Hubble constant for which we explore possible explanations.

Cluster-based analysis of multi-model climate ensembles

Science.gov (United States)

Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

2018-06-01

Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

Improving estimation of kinetic parameters in dynamic force spectroscopy using cluster analysis

Science.gov (United States)

Yen, Chi-Fu; Sivasankar, Sanjeevi

2018-03-01

Dynamic Force Spectroscopy (DFS) is a widely used technique to characterize the dissociation kinetics and interaction energy landscape of receptor-ligand complexes with single-molecule resolution. In an Atomic Force Microscope (AFM)-based DFS experiment, receptor-ligand complexes, sandwiched between an AFM tip and substrate, are ruptured at different stress rates by varying the speed at which the AFM-tip and substrate are pulled away from each other. The rupture events are grouped according to their pulling speeds, and the mean force and loading rate of each group are calculated. These data are subsequently fit to established models, and energy landscape parameters such as the intrinsic off-rate (koff) and the width of the potential energy barrier (xβ) are extracted. However, due to large uncertainties in determining mean forces and loading rates of the groups, errors in the estimated koff and xβ can be substantial. Here, we demonstrate that the accuracy of fitted parameters in a DFS experiment can be dramatically improved by sorting rupture events into groups using cluster analysis instead of sorting them according to their pulling speeds. We test different clustering algorithms including Gaussian mixture, logistic regression, and K-means clustering, under conditions that closely mimic DFS experiments. Using Monte Carlo simulations, we benchmark the performance of these clustering algorithms over a wide range of koff and xβ, under different levels of thermal noise, and as a function of both the number of unbinding events and the number of pulling speeds. Our results demonstrate that cluster analysis, particularly K-means clustering, is very effective in improving the accuracy of parameter estimation, particularly when the number of unbinding events are limited and not well separated into distinct groups. Cluster analysis is easy to implement, and our performance benchmarks serve as a guide in choosing an appropriate method for DFS data analysis.

Identification of Protein Complexes Using Weighted PageRank-Nibble Algorithm and Core-Attachment Structure.

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Peng, Wei; Wang, Jianxin; Zhao, Bihai; Wang, Lusheng

2015-01-01

Protein complexes play a significant role in understanding the underlying mechanism of most cellular functions. Recently, many researchers have explored computational methods to identify protein complexes from protein-protein interaction (PPI) networks. One group of researchers focus on detecting local dense subgraphs which correspond to protein complexes by considering local neighbors. The drawback of this kind of approach is that the global information of the networks is ignored. Some methods such as Markov Clustering algorithm (MCL), PageRank-Nibble are proposed to find protein complexes based on random walk technique which can exploit the global structure of networks. However, these methods ignore the inherent core-attachment structure of protein complexes and treat adjacent node equally. In this paper, we design a weighted PageRank-Nibble algorithm which assigns each adjacent node with different probability, and propose a novel method named WPNCA to detect protein complex from PPI networks by using weighted PageRank-Nibble algorithm and core-attachment structure. Firstly, WPNCA partitions the PPI networks into multiple dense clusters by using weighted PageRank-Nibble algorithm. Then the cores of these clusters are detected and the rest of proteins in the clusters will be selected as attachments to form the final predicted protein complexes. The experiments on yeast data show that WPNCA outperforms the existing methods in terms of both accuracy and p-value. The software for WPNCA is available at "http://netlab.csu.edu.cn/bioinfomatics/weipeng/WPNCA/download.html".

Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

Energy Technology Data Exchange (ETDEWEB)

Simmhan, Yogesh; Noor, Muhammad Usman

2013-10-09

Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 data points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review

Science.gov (United States)

2014-01-01

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5–18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research

Performance Analysis of Cluster Formation in Wireless Sensor Networks.

Science.gov (United States)

Montiel, Edgar Romo; Rivero-Angeles, Mario E; Rubino, Gerardo; Molina-Lozano, Heron; Menchaca-Mendez, Rolando; Menchaca-Mendez, Ricardo

2017-12-13

Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN) use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes.

Performance Analysis of Cluster Formation in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Edgar Romo Montiel

2017-12-01

Full Text Available Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes.

A priori data-driven multi-clustered reservoir generation algorithm for echo state network.

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Xiumin Li

Full Text Available Echo state networks (ESNs with multi-clustered reservoir topology perform better in reservoir computing and robustness than those with random reservoir topology. However, these ESNs have a complex reservoir topology, which leads to difficulties in reservoir generation. This study focuses on the reservoir generation problem when ESN is used in environments with sufficient priori data available. Accordingly, a priori data-driven multi-cluster reservoir generation algorithm is proposed. The priori data in the proposed algorithm are used to evaluate reservoirs by calculating the precision and standard deviation of ESNs. The reservoirs are produced using the clustering method; only the reservoir with a better evaluation performance takes the place of a previous one. The final reservoir is obtained when its evaluation score reaches the preset requirement. The prediction experiment results obtained using the Mackey-Glass chaotic time series show that the proposed reservoir generation algorithm provides ESNs with extra prediction precision and increases the structure complexity of the network. Further experiments also reveal the appropriate values of the number of clusters and time window size to obtain optimal performance. The information entropy of the reservoir reaches the maximum when ESN gains the greatest precision.

MANAGING THE DEVELOPMENT OF AGRO-INDUSTRIAL CLUSTERS

Directory of Open Access Journals (Sweden)

D. V. Zavyalov

2018-01-01

relevant strategy of agrarian and industrial complex, imperfection of methodology of formation of clusters and lack of motives of consolidation of subjects of small and medium business in this sphere; backwardness of production, logistic and innovative infrastructure; and also the low level of commercialization of scientific research in the agro-industrial sector. As one of the measures capable to refract a similar negative situation, development of the concept of management of agro-industrial clusters formed on the basis of an information system of "a digital cluster" which includes algorithms and methods of optimization of information, material and financial flows for achievement of desirable indicators of economic activity by all participants of cluster structure is recommended. At the conceptual level mechanisms and instruments of management of development of agro-industrial clusters are also offered.

Cluster Matters

DEFF Research Database (Denmark)

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

2018-01-01

sell their products successfully in international markets, but there is also an increasingly large consumer base within India. Indeed, Indian industrial clusters have contributed to a substantial part of this growth process, and there are several hundred registered clusters within the country...... of this handbook, which focuses on the role of CSR in MSMEs. Hence we contribute to the literature on CSR in industrial clusters and specifically CSR in Indian industrial clusters by investigating the drivers of CSR in India’s industrial clusters....

Weighted Clustering

DEFF Research Database (Denmark)

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

2012-01-01

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

THE ROLE OF RAM PRESSURE STRIPPING IN THE QUENCHING OF CLUSTER STAR FORMATION

International Nuclear Information System (INIS)

Book, Laura G.; Benson, Andrew J.

2010-01-01

Recent observations of galaxy clusters have shown that environmental effects apparently associated with the cluster begin to lower the star formation rates of galaxies at distances as great as three times the cluster virial radius. These observations may indicate preprocessing of cluster galaxies in groups or in the cluster core for galaxies on highly elliptical orbits, but may also imply that the environmental effects due to the cluster are directly affecting galaxies on their first infall. To explore these issues, we investigate different models of ram pressure stripping (RPS) as it acts on satellite galaxies in clusters and compare to observations of the radial star formation gradient in clusters. We calculate the location of the accretion shock around model clusters and use this as the radius of onset of RPS in the GALFORM semi-analytic model of galaxy formation. Comparison of the results of our model and previously considered, simpler ram pressure models with recent observations indicates that current data are unable to strongly discriminate between models of RPS due to the complex interplay of preprocessing effects at work. However, future observations of a larger sample of clusters will likely be able to place stronger constraints on the process of RPS and its role in shaping radial trends in and around clusters.

Estimation of Economic Efficiency of Regional Touristic Complex

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Kurchenkov Vladimir Viktorovich

2015-09-01

Full Text Available The article describes the features of the development of the regional touristic complex in modern conditions and determines the direction of realizing the potential of the regional market of tourist services. The authors reveal the multiplicative interrelation for analyzing the interaction of the primary and secondary sectors of the regional market of tourist services. The key indicators of efficiency are outlined, the extent of their relevance for assessing the potential of international tourism in the region is revealed. The authors calculate the relative indicators reflecting the dynamics of incomes from inbound, outbound and domestic tourism in relation to the total income from tourism activities in the region during the reporting period, usually for one calendar year. On the basis of these parameters, the classification of the regions of the Southern Federal District in terms of tourist attraction is carried out. The authors determine the reasons of the low tourist attractiveness of the Volgograd region in comparison with other regions of the Southern Federal District. It is substantiated that the potential of expanding tourism activity is not fully realized today in the Volgograd region. The technique of analysis and evaluation of the effectiveness of regional touristic complex on the basis of cluster approach is suggested. For analyzing the effectiveness of regional tourism cluster the authors propose to use indicators that reflect the overall performance of the regional tourism cluster, characterizing the impact of cluster development of the area, or the regional market, as well as evaluating the performance of each of the companies cooperating in the framework of the cluster. The article contains recommendations to the regional authorities on improving the efficiency of regional touristic complex in the short- and long-term prospects.

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

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Gulcin Salıngan

2012-07-01

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

Polar localization of Escherichia coli chemoreceptors requires an intact Tol–Pal complex

Science.gov (United States)

Santos, Thiago M. A.; Lin, Ti-Yu; Rajendran, Madhusudan; Anderson, Samantha M.; Weibel, Douglas B.

2014-01-01

Summary Subcellular biomolecular localization is critical for the metabolic and structural properties of the cell. The functional implications of the spatiotemporal distribution of protein complexes during the bacterial cell cycle have long been acknowledged; however, the molecular mechanisms for generating and maintaining their dynamic localization in bacteria are not completely understood. Here we demonstrate that the trans-envelope Tol–Pal complex, a widely conserved component of the cell envelope of Gram-negative bacteria, is required to maintain the polar positioning of chemoreceptor clusters in Escherichia coli. Localization of the chemoreceptors was independent of phospholipid composition of the membrane and the curvature of the cell wall. Instead, our data indicate that chemoreceptors interact with components of the Tol–Pal complex and that this interaction is required to polarly localize chemoreceptor clusters. We found that disruption of the Tol–Pal complex perturbs the polar localization of chemoreceptors, alters cell motility, and affects chemotaxis. We propose that the E. coli Tol–Pal complex restricts mobility of the chemoreceptor clusters at the cell poles and may be involved in regulatory mechanisms that co-ordinate cell division and segregation of the chemosensory machinery. PMID:24720726

Satellite cluster flight using on-off cyclic control

Science.gov (United States)

Zhang, Hao; Gurfil, Pini

2015-01-01

Nano-satellite clusters and disaggregated satellites are new concepts in the realm of distributed satellite systems, which require complex cluster management - mainly regulating the maximal and minimal inter-satellite distances on time scales of years - while utilizing simple on-off propulsion systems. The simple actuators and long time scales require judicious astrodynamical modeling coupled with specialized orbit control. This paper offers a satellite cluster orbit control law which works for long time scales in a perturbed environment while utilizing fixed-magnitude thrusters. The main idea is to design a distributed controller which balances the fuel consumption among the satellites, thus mitigating the effect of differential drag perturbations. The underlying methodology utilizes a cyclic control algorithm based on a mean orbital elements feedback. Stability properties of the closed-loop cyclic control system do not adhere to the classical Lyapunov stability theory, so an effort is made to define and implement a suitable stability theory of noncompact equilibria sets. A state selection scheme is proposed for efficiently establishing a low Earth orbit cluster. Several simulations, including a real mission study, and several comparative investigations, are performed to show the strengths of the proposed control law.

Weighted community detection and data clustering using message passing

Science.gov (United States)

Shi, Cheng; Liu, Yanchen; Zhang, Pan

2018-03-01

Grouping objects into clusters based on the similarities or weights between them is one of the most important problems in science and engineering. In this work, by extending message-passing algorithms and spectral algorithms proposed for an unweighted community detection problem, we develop a non-parametric method based on statistical physics, by mapping the problem to the Potts model at the critical temperature of spin-glass transition and applying belief propagation to solve the marginals corresponding to the Boltzmann distribution. Our algorithm is robust to over-fitting and gives a principled way to determine whether there are significant clusters in the data and how many clusters there are. We apply our method to different clustering tasks. In the community detection problem in weighted and directed networks, we show that our algorithm significantly outperforms existing algorithms. In the clustering problem, where the data were generated by mixture models in the sparse regime, we show that our method works all the way down to the theoretical limit of detectability and gives accuracy very close to that of the optimal Bayesian inference. In the semi-supervised clustering problem, our method only needs several labels to work perfectly in classic datasets. Finally, we further develop Thouless-Anderson-Palmer equations which heavily reduce the computation complexity in dense networks but give almost the same performance as belief propagation.

MiR-17-92 cluster and immunity.

Science.gov (United States)

Kuo, George; Wu, Chao-Yi; Yang, Huang-Yu

2018-05-29

MicroRNAs (MiR, MiRNA) are small single-stranded non-coding RNAs that play an important role in the regulation of gene expression. MircoRNAs exert their effect by binding to complementary nucleotide sequences of the targeted messenger RNA, thus forming an RNA-induced silencing complex. The mircoRNA-17-92 cluster encoded by the miR-17-92 host gene is first found in malignant B-cell lymphoma. Recent research identifies the miR-17-92 cluster as a crucial player in the development of the immune system, the heart, the lung, and oncogenic events. In light of the miR-17-92 cluster's increasing role in regulating the immune system, our review will discuss the latest knowledge regarding its involvement in cells of both innate and adaptive immunity, including B cells, subsets of T cells such as Th1, Th2, T follicular helper cells, regulatory T cells, monocytes/macrophages, NK cells, and dendritic cells, and the possible targets that are regulated by its members. Copyright © 2018. Published by Elsevier B.V.

Unraveling the hidden heterogeneities of breast cancer based on functional miRNA cluster.

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Li Li

Full Text Available It has become increasingly clear that the current taxonomy of clinical phenotypes is mixed with molecular heterogeneity, which potentially affects the treatment effect for involved patients. Defining the hidden molecular-distinct diseases using modern large-scale genomic approaches is therefore useful for refining clinical practice and improving intervention strategies. Given that microRNA expression profiling has provided a powerful way to dissect hidden genetic heterogeneity for complex diseases, the aim of the study was to develop a bioinformatics approach that identifies microRNA features leading to the hidden subtyping of complex clinical phenotypes. The basic strategy of the proposed method was to identify optimal miRNA clusters by iteratively partitioning the sample and feature space using the two-ways super-paramagnetic clustering technique. We evaluated the obtained optimal miRNA cluster by determining the consistency of co-expression and the chromosome location among the within-cluster microRNAs, and concluded that the optimal miRNA cluster could lead to a natural partition of disease samples. We applied the proposed method to a publicly available microarray dataset of breast cancer patients that have notoriously heterogeneous phenotypes. We obtained a feature subset of 13 microRNAs that could classify the 71 breast cancer patients into five subtypes with significantly different five-year overall survival rates (45%, 82.4%, 70.6%, 100% and 60% respectively; p = 0.008. By building a multivariate Cox proportional-hazards prediction model for the feature subset, we identified has-miR-146b as one of the most significant predictor (p = 0.045; hazard ratios = 0.39. The proposed algorithm is a promising computational strategy for dissecting hidden genetic heterogeneity for complex diseases, and will be of value for improving cancer diagnosis and treatment.

Energy and charge transfer in ionized argon coated water clusters

International Nuclear Information System (INIS)

Kočišek, J.; Lengyel, J.; Fárník, M.; Slavíček, P.

2013-01-01

We investigate the electron ionization of clusters generated in mixed Ar-water expansions. The electron energy dependent ion yields reveal the neutral cluster composition and structure: water clusters fully covered with the Ar solvation shell are formed under certain expansion conditions. The argon atoms shield the embedded (H 2 O) n clusters resulting in the ionization threshold above ≈15 eV for all fragments. The argon atoms also mediate more complex reactions in the clusters: e.g., the charge transfer between Ar + and water occurs above the threshold; at higher electron energies above ∼28 eV, an excitonic transfer process between Ar + * and water opens leading to new products Ar n H + and (H 2 O) n H + . On the other hand, the excitonic transfer from the neutral Ar* state at lower energies is not observed although this resonant process was demonstrated previously in a photoionization experiment. Doubly charged fragments (H 2 O) n H 2 2+ and (H 2 O) n 2+ ions are observed and Intermolecular Coulomb decay (ICD) processes are invoked to explain their thresholds. The Coulomb explosion of the doubly charged cluster formed within the ICD process is prevented by the stabilization effect of the argon solvent

Determination of atomic cluster structure with cluster fusion algorithm

DEFF Research Database (Denmark)

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

2005-01-01

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

Membership determination of open clusters based on a spectral clustering method

Science.gov (United States)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

Observing the real time formation of phosphine-ligated gold clusters by electrospray ionization mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Ligare, Marshall R.; Johnson, Grant E.; Laskin, Julia

2017-01-01

Early stages of the reduction and nucleation of solution-phase gold clusters are largely unknown. This is due, in part, to the high reaction rates and the complexity of the cluster synthesis process. Through the addition of a diphosphine ligand, 1-4,Bis(diphenylphosphino)butane (L4) to the gold precursor, chloro(triphenylphosphine) gold(I) (Au(PPh3)Cl), in methanol organometallic complexes of the type, [Au(L4)x(L4O)y(PPh3)z]+, are formed. These complexes lower the rate of reduction so that the reaction can be directly monitored from 1 min to over an hour using on-line electrospray ionization mass spectrometry (ESI-MS). Our results indicate that the formation of Au8(L4)42+, Au9(L4)4H2+ and Au10(L4)52+ cationic clusters occurs through different reaction pathways that may be kinetically controlled either through the reducing agent concentration or the extent of oxidation of L4. Through comparison of selected ion chronograms our results indicate that Au2(L4)2H+ may be an intermediate in the formation of Au8(L4)42+and Au10(L4)52+ while a variety of chlorinated clusters are involved in the formation of Au9(L4)4H2+. Additionally, high-resolution mass spectrometry was employed to identify 53 gold containing species produced under highly oxidative conditions. New intermediate species are identified which help understand how different gold cluster nuclearities can be stabilized during the growth process.

Cluster headache

Science.gov (United States)

Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... Doctors do not know exactly what causes cluster headaches. They ... (chemical in the body released during an allergic response) or ...

Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

Science.gov (United States)

Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

2017-07-01

Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

Visualization of complex DNA damage along accelerated ions tracks

Science.gov (United States)

Kulikova, Elena; Boreyko, Alla; Bulanova, Tatiana; Ježková, Lucie; Zadneprianetc, Mariia; Smirnova, Elena

2018-04-01

The most deleterious DNA lesions induced by ionizing radiation are clustered DNA double-strand breaks (DSB). Clustered or complex DNA damage is a combination of a few simple lesions (single-strand breaks, base damage etc.) within one or two DNA helix turns. It is known that yield of complex DNA lesions increases with increasing linear energy transfer (LET) of radiation. For investigation of the induction and repair of complex DNA lesions, human fibroblasts were irradiated with high-LET 15N ions (LET = 183.3 keV/μm, E = 13MeV/n) and low-LET 60Co γ-rays (LET ≈ 0.3 keV/μm) radiation. DNA DSBs (γH2AX and 53BP1) and base damage (OGG1) markers were visualized by immunofluorecence staining and high-resolution microscopy. The obtained results showed slower repair kinetics of induced DSBs in cells irradiated with accelerated ions compared to 60Co γ-rays, indicating induction of more complex DNA damage. Confirming previous assumptions, detailed 3D analysis of γH2AX/53BP1 foci in 15N ions tracks revealed more complicated structure of the foci in contrast to γ-rays. It was shown that proteins 53BP1 and OGG1 involved in repair of DNA DSBs and modified bases, respectively, were colocalized in tracks of 15N ions and thus represented clustered DNA DSBs.

Recent developments of the quantum chemical cluster approach for modeling enzyme reactions.

Science.gov (United States)

Siegbahn, Per E M; Himo, Fahmi

2009-06-01

The quantum chemical cluster approach for modeling enzyme reactions is reviewed. Recent applications have used cluster models much larger than before which have given new modeling insights. One important and rather surprising feature is the fast convergence with cluster size of the energetics of the reactions. Even for reactions with significant charge separation it has in some cases been possible to obtain full convergence in the sense that dielectric cavity effects from outside the cluster do not contribute to any significant extent. Direct comparisons between quantum mechanics (QM)-only and QM/molecular mechanics (MM) calculations for quite large clusters in a case where the results differ significantly have shown that care has to be taken when using the QM/MM approach where there is strong charge polarization. Insights from the methods used, generally hybrid density functional methods, have also led to possibilities to give reasonable error limits for the results. Examples are finally given from the most extensive study using the cluster model, the one of oxygen formation at the oxygen-evolving complex in photosystem II.

Sleep stages identification in patients with sleep disorder using k-means clustering

Science.gov (United States)

Fadhlullah, M. U.; Resahya, A.; Nugraha, D. F.; Yulita, I. N.

2018-05-01

Data mining is a computational intelligence discipline where a large dataset processed using a certain method to look for patterns within the large dataset. This pattern then used for real time application or to develop some certain knowledge. This is a valuable tool to solve a complex problem, discover new knowledge, data analysis and decision making. To be able to get the pattern that lies inside the large dataset, clustering method is used to get the pattern. Clustering is basically grouping data that looks similar so a certain pattern can be seen in the large data set. Clustering itself has several algorithms to group the data into the corresponding cluster. This research used data from patients who suffer sleep disorders and aims to help people in the medical world to reduce the time required to classify the sleep stages from a patient who suffers from sleep disorders. This study used K-Means algorithm and silhouette evaluation to find out that 3 clusters are the optimal cluster for this dataset which means can be divided to 3 sleep stages.

Transport, dissociation and rotation of small self-interstitial atom clusters in tungsten

International Nuclear Information System (INIS)

Zhou, W.H.; Zhang, C.G.; Li, Y.G.; Zeng, Z.

2014-01-01

Numerical calculations have been performed to study the thermal motion of self-interstitial atom (SIA) clusters in tungsten (W). Molecular dynamics simulations show that SIA clusters exhibit a fast one-dimensional (1D) motion along the close packed 〈1 1 1〉 direction accompanied by a significant mass transport in this direction. A low frequency vibration mode is identified and considered to assist the motion of SIAs. The migration energy of SIA clusters are weakly dependent on their size in the average value of 0.019 eV, which is due to the strong interaction between SIAs revealed by calculating the potential energy curve of artificially moving the SIAs along 〈1 1 1〉 direction as well as nudged elastic band (NEB) method. The rotation process of SIA cluster is studied by activation–relaxation technique and the results show that SIA cluster presents complex rotation process. Our results on the motion SIA cluster may provide updated understanding on the performance decay of materials related to SIA defects

Photoionization cross section by Stieltjes imaging applied to coupled cluster Lanczos pseudo-spectra

Science.gov (United States)

Cukras, Janusz; Coriani, Sonia; Decleva, Piero; Christiansen, Ove; Norman, Patrick

2013-09-01

A recently implemented asymmetric Lanczos algorithm for computing (complex) linear response functions within the coupled cluster singles (CCS), coupled cluster singles and iterative approximate doubles (CC2), and coupled cluster singles and doubles (CCSD) is coupled to a Stieltjes imaging technique in order to describe the photoionization cross section of atoms and molecules, in the spirit of a similar procedure recently proposed by Averbukh and co-workers within the Algebraic Diagrammatic Construction approach. Pilot results are reported for the atoms He, Ne, and Ar and for the molecules H2, H2O, NH3, HF, CO, and CO2.

Photoionization cross section by Stieltjes imaging applied to coupled cluster Lanczos pseudo-spectra

International Nuclear Information System (INIS)

Cukras, Janusz; Coriani, Sonia; Decleva, Piero; Christiansen, Ove; Norman, Patrick

2013-01-01

A recently implemented asymmetric Lanczos algorithm for computing (complex) linear response functions within the coupled cluster singles (CCS), coupled cluster singles and iterative approximate doubles (CC2), and coupled cluster singles and doubles (CCSD) is coupled to a Stieltjes imaging technique in order to describe the photoionization cross section of atoms and molecules, in the spirit of a similar procedure recently proposed by Averbukh and co-workers within the Algebraic Diagrammatic Construction approach. Pilot results are reported for the atoms He, Ne, and Ar and for the molecules H 2 , H 2 O, NH 3 , HF, CO, and CO 2

Alkali metal cation complexation and solvent interactions by robust chromium(III) fluoride complexes

DEFF Research Database (Denmark)

Birk, T.; Magnussen, M.J.; Piligkos, Stergios

2010-01-01

)] have been synthesized from mer-[CrF3(py)(3)] and shown to precipitate sodium salts from solution, of which 3[CrF3(Me(3-)tacn)]center dot 2Na(Bph(4)).solv and 6[CrF3(terpy)]center dot 4Na(Bph(4)).solv have been crystallographically characterized. In these clusters, the neutral fluoride complexes bring...

A 'quick-look' report on the THETIS 80% blocked cluster forced reflood experiments

International Nuclear Information System (INIS)

Cooper, C.A.; Pearson, K.G.

1984-01-01

A brief selection of results of forced reflooding experiments with the THETIS 80 percent blocked cluster is presented. A description of the THETIS blocked cluster test assemblies, and details of the test conditions, are given. The two forced reflooding experiments have been the subject of a blind calculation exercise with the BART code, and the results of these experiments are compared with the results from corresponding experiments with the 90 percent blocked cluster test assembly. Some general observations are made, arising from the comparison of these two series of experiments, and a qualitative explanation for the relatively complex variation of the heat transfer within the THETIS blockages is advanced. A full report on the 80 percent blocked cluster forced reflooding experiments will be available later. (U.K.)

Dynamics and molecular determinants of cytoplasmic lipid droplet clustering and dispersion.

Directory of Open Access Journals (Sweden)

David J Orlicky

Full Text Available Perilipin-1 (Plin1, a prominent cytoplasmic lipid droplet (CLD binding phosphoprotein and key physiological regulator of triglyceride storage and lipolysis in adipocytes, is thought to regulate the fragmentation and dispersion of CLD that occurs in response to β-adrenergic activation of adenylate cyclase. Here we investigate the dynamics and molecular determinants of these processes using cell lines stably expressing recombinant forms of Plin1 and/or other members of the perilipin family. Plin1 and a C-terminal CLD-binding fragment of Plin1 (Plin1CT induced formation of single dense CLD clusters near the microtubule organizing center, whereas neither an N-terminal CLD-binding fragment of Plin1, nor Plin2 or Plin3 induced clustering. Clustered CLD coated by Plin1, or Plin1CT, dispersed in response to isoproterenol, or other agents that activate adenylate cyclase, in a process inhibited by the protein kinase A inhibitor, H89, and blocked by microtubule disruption. Isoproterenol-stimulated phosphorylation of CLD-associated Plin1 on serine 492 preceded their dispersion, and live cell imaging showed that cluster dispersion involved initial fragmentation of tight clusters into multiple smaller clusters, which then fragmented into well-dispersed individual CLD. siRNA knockdown of the cortical actin binding protein, moesin, induced disaggregation of tight clusters into multiple smaller clusters, and inhibited the reaggregation of dispersed CLD into tight clusters. Together these data suggest that the clustering and dispersion processes involve a complex orchestration of phosphorylation-dependent, microtubule-dependent and independent, and microfilament dependent steps.

Dynamics and molecular determinants of cytoplasmic lipid droplet clustering and dispersion.

Science.gov (United States)

Orlicky, David J; Monks, Jenifer; Stefanski, Adrianne L; McManaman, James L

2013-01-01

Perilipin-1 (Plin1), a prominent cytoplasmic lipid droplet (CLD) binding phosphoprotein and key physiological regulator of triglyceride storage and lipolysis in adipocytes, is thought to regulate the fragmentation and dispersion of CLD that occurs in response to β-adrenergic activation of adenylate cyclase. Here we investigate the dynamics and molecular determinants of these processes using cell lines stably expressing recombinant forms of Plin1 and/or other members of the perilipin family. Plin1 and a C-terminal CLD-binding fragment of Plin1 (Plin1CT) induced formation of single dense CLD clusters near the microtubule organizing center, whereas neither an N-terminal CLD-binding fragment of Plin1, nor Plin2 or Plin3 induced clustering. Clustered CLD coated by Plin1, or Plin1CT, dispersed in response to isoproterenol, or other agents that activate adenylate cyclase, in a process inhibited by the protein kinase A inhibitor, H89, and blocked by microtubule disruption. Isoproterenol-stimulated phosphorylation of CLD-associated Plin1 on serine 492 preceded their dispersion, and live cell imaging showed that cluster dispersion involved initial fragmentation of tight clusters into multiple smaller clusters, which then fragmented into well-dispersed individual CLD. siRNA knockdown of the cortical actin binding protein, moesin, induced disaggregation of tight clusters into multiple smaller clusters, and inhibited the reaggregation of dispersed CLD into tight clusters. Together these data suggest that the clustering and dispersion processes involve a complex orchestration of phosphorylation-dependent, microtubule-dependent and independent, and microfilament dependent steps.

Single-cluster dynamics for the random-cluster model

NARCIS (Netherlands)

Deng, Y.; Qian, X.; Blöte, H.W.J.

2009-01-01

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

Hox gene clusters in the Indonesian coelacanth, Latimeria menadoensis

Science.gov (United States)

Koh, Esther G. L.; Lam, Kevin; Christoffels, Alan; Erdmann, Mark V.; Brenner, Sydney; Venkatesh, Byrappa

2003-01-01

The Hox genes encode transcription factors that play a key role in specifying body plans of metazoans. They are organized into clusters that contain up to 13 paralogue group members. The complex morphology of vertebrates has been attributed to the duplication of Hox clusters during vertebrate evolution. In contrast to the single Hox cluster in the amphioxus (Branchiostoma floridae), an invertebrate-chordate, mammals have four clusters containing 39 Hox genes. Ray-finned fishes (Actinopterygii) such as zebrafish and fugu possess more than four Hox clusters. The coelacanth occupies a basal phylogenetic position among lobe-finned fishes (Sarcopterygii), which gave rise to the tetrapod lineage. The lobe fins of sarcopterygians are considered to be the evolutionary precursors of tetrapod limbs. Thus, the characterization of Hox genes in the coelacanth should provide insights into the origin of tetrapod limbs. We have cloned the complete second exon of 33 Hox genes from the Indonesian coelacanth, Latimeria menadoensis, by extensive PCR survey and genome walking. Phylogenetic analysis shows that 32 of these genes have orthologs in the four mammalian HOX clusters, including three genes (HoxA6, D1, and D8) that are absent in ray-finned fishes. The remaining coelacanth gene is an ortholog of hoxc1 found in zebrafish but absent in mammals. Our results suggest that coelacanths have four Hox clusters bearing a gene complement more similar to mammals than to ray-finned fishes, but with an additional gene, HoxC1, which has been lost during the evolution of mammals from lobe-finned fishes. PMID:12547909

Hemoglobin–Albumin Cluster Incorporating a Pt Nanoparticle: Artificial O2 Carrier with Antioxidant Activities

Science.gov (United States)

Hosaka, Hitomi; Haruki, Risa; Yamada, Kana; Böttcher, Christoph; Komatsu, Teruyuki

2014-01-01

A covalent core–shell structured protein cluster composed of hemoglobin (Hb) at the center and human serum albumins (HSA) at the periphery, Hb-HSAm, is an artificial O2 carrier that can function as a red blood cell substitute. Here we described the preparation of a novel Hb-HSA3 cluster with antioxidant activities and its O2 complex stable in aqueous H2O2 solution. We used an approach of incorporating a Pt nanoparticle (PtNP) into the exterior HSA unit of the cluster. A citrate reduced PtNP (1.8 nm diameter) was bound tightly within the cleft of free HSA with a binding constant (K) of 1.1×107 M−1, generating a stable HSA-PtNP complex. This platinated protein showed high catalytic activities for dismutations of superoxide radical anions (O2 •–) and hydrogen peroxide (H2O2), i.e., superoxide dismutase and catalase activities. Also, Hb-HSA3 captured PtNP into the external albumin unit (K = 1.1×107 M−1), yielding an Hb-HSA3(PtNP) cluster. The association of PtNP caused no alteration of the protein surface net charge and O2 binding affinity. The peripheral HSA-PtNP shell prevents oxidation of the core Hb, which enables the formation of an extremely stable O2 complex, even in H2O2 solution. PMID:25310133

Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles

Science.gov (United States)

Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F.; Perez, Danny

2017-10-01

Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.

Parents' personality clusters and eating disordered daughters' personality and psychopathology.

Science.gov (United States)

Amianto, Federico; Ercole, Roberta; Marzola, Enrica; Abbate Daga, Giovanni; Fassino, Secondo

2015-11-30

The present study explores how parents' personality clusters relate to their eating disordered daughters' personality and psychopathology. Mothers and fathers were tested with the Temperament Character Inventory. Their daughters were assessed with the following: Temperament and Character Inventory, Eating Disorder Inventory-2, Symptom Checklist-90, Parental Bonding Instrument, Attachment Style Questionnaire, and Family Assessment Device. Daughters' personality traits and psychopathology scores were compared between clusters. Daughters' features were related to those of their parents. Explosive/adventurous mothers were found to relate to their daughters' borderline personality profile and more severe interoceptive awareness. Mothers' immaturity was correlated to their daughters' higher character immaturity, inadequacy, and depressive feelings. Fathers who were explosive/methodic correlated with their daughters' character immaturity, severe eating, and general psychopathology. Fathers' character immaturity only marginally related to their daughters' specific features. Both parents' temperament clusters and mothers' character clusters related to patients' personality and eating psychopathology. The cluster approach to personality-related dynamics of families with an individual affected by an eating disorder expands the knowledge on the relationship between parents' characteristics and daughters' illness, suggesting complex and unique relationships correlating parents' personality traits to their daughters' disorder. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Formation process of the poly-oxo cluster U{sub 38}

Energy Technology Data Exchange (ETDEWEB)

Henning, Christoph [Helmholtz-Zentrum Dresden-Rossendorf e.V., Dresden (Germany). Div. Molecular Structures; Falaise, C.; Volkringer, Christoph; Loiseau, T. [Lille Univ., Villeneuve d' Ascq (France). Unite de Catalyse et Chimie du Solide

2016-07-01

Recently, a new poly-oxo cluster with 38 uranium atoms, U{sub 38}O{sub 56}Cl{sub 18}(THF){sub 8}(bz){sub 24}.8THF, (U{sub 38}), has been synthesized [1]. We studied ex situ the reaction kinetics of this complex [2].

A Cluster Analysis of Tic Symptoms in Children and Adults with Tourette Syndrome: Clinical Correlates and Treatment Outcome

Science.gov (United States)

McGuire, Joseph F.; Nyirabahizi, Epiphanie; Kircanski, Katharina; Piacentini, John; Peterson, Alan L.; Woods, Douglas W.; Wilhelm, Sabine; Walkup, John T.; Scahill, Lawrence

2013-01-01

Cluster analytic methods have examined the symptom presentation of chronic tic disorders (CTDs), with limited agreement across studies. The present study investigated patterns, clinical correlates, and treatment outcome of tic symptoms. 239 youth and adults with CTDs completed a battery of assessments at baseline to determine diagnoses, tic severity, and clinical characteristics. Participants were randomly assigned to receive either a comprehensive behavioral intervention for tics (CBIT) or psychoeducation and supportive therapy (PST). A cluster analysis was conducted on the baseline Yale Global Tic Severity Scale (YGTSS) symptom checklist to identify the constellations of tic symptoms. Four tic clusters were identified: Impulse Control and Complex Phonic Tics; Complex Motor Tics; Simple Head Motor/Vocal Tics; and Primarily Simple Motor Tics. Frequencies of tic symptoms showed few differences across youth and adults. Tic clusters had small associations with clinical characteristics and showed no associations to the presence of coexisting psychiatric conditions. Cluster membership scores did not predict treatment response to CBIT or tic severity reductions. Tic symptoms distinctly cluster with few difference across youth and adults, or coexisting conditions. This study, which is the first to examine tic clusters in relation to treatment, suggested that tic symptom profiles respond equally well to CBIT. PMID:24144615

A complex of Cas proteins 5, 6, and 7 is required for the biogenesis and stability of clustered regularly interspaced short palindromic repeats (crispr)-derived rnas (crrnas) in Haloferax volcanii.

Science.gov (United States)

Brendel, Jutta; Stoll, Britta; Lange, Sita J; Sharma, Kundan; Lenz, Christof; Stachler, Aris-Edda; Maier, Lisa-Katharina; Richter, Hagen; Nickel, Lisa; Schmitz, Ruth A; Randau, Lennart; Allers, Thorsten; Urlaub, Henning; Backofen, Rolf; Marchfelder, Anita

2014-03-07

The clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR-Cas) system is a prokaryotic defense mechanism against foreign genetic elements. A plethora of CRISPR-Cas versions exist, with more than 40 different Cas protein families and several different molecular approaches to fight the invading DNA. One of the key players in the system is the CRISPR-derived RNA (crRNA), which directs the invader-degrading Cas protein complex to the invader. The CRISPR-Cas types I and III use the Cas6 protein to generate mature crRNAs. Here, we show that the Cas6 protein is necessary for crRNA production but that additional Cas proteins that form a CRISPR-associated complex for antiviral defense (Cascade)-like complex are needed for crRNA stability in the CRISPR-Cas type I-B system in Haloferax volcanii in vivo. Deletion of the cas6 gene results in the loss of mature crRNAs and interference. However, cells that have the complete cas gene cluster (cas1-8b) removed and are transformed with the cas6 gene are not able to produce and stably maintain mature crRNAs. crRNA production and stability is rescued only if cas5, -6, and -7 are present. Mutational analysis of the cas6 gene reveals three amino acids (His-41, Gly-256, and Gly-258) that are essential for pre-crRNA cleavage, whereas the mutation of two amino acids (Ser-115 and Ser-224) leads to an increase of crRNA amounts. This is the first systematic in vivo analysis of Cas6 protein variants. In addition, we show that the H. volcanii I-B system contains a Cascade-like complex with a Cas7, Cas5, and Cas6 core that protects the crRNA.

Titanium embedded cage structure formation in Al{sub n}Ti{sup +} clusters and their interaction with Ar

Energy Technology Data Exchange (ETDEWEB)

Torres, M. B., E-mail: begonia@ubu.es [Departamento de Matemáticas y Computación, Universidad de Burgos, 09006 Burgos (Spain); Vega, A.; Balbás, L. C. [Departamento de Física Teórica, Universidad de Valladolid, 47011 Valladolid (Spain); Aguilera-Granja, F. [Instituto de Física, Universidad de San Luis Potosí, 78000 San Luis de Potosí (Mexico)

2014-05-07

Recently, Ar physisorption was used as a structural probe for the location of the Ti dopant atom in aluminium cluster cations, Al{sub n}Ti{sup +} [Lang et al., J. Am. Soc. Mass Spectrom. 22, 1508 (2011)]. As an experiment result, the lack of Ar complexes for n > n{sub c} determines the cluster size for which the Ti atom is located inside of an Al cage. To elucidate the decisive factors for the formation of endohedrally Al{sub n}Ti{sup +}, experimentalists proposed detailed computational studies as indispensable. In this work, we investigated, using the density functional theory, the structural and electronic properties of singly titanium doped cationic clusters, Al{sub n}Ti{sup +} (n = 16–21) as well as the adsorption of an Ar atom on them. The first endohedral doped cluster, with Ti encapsulated in a fcc-like cage skeleton, appears at n{sub c} = 21, which is the critical number consistent with the exohedral-endohedral transition experimentally observed. At this critical size the non-crystalline icosahedral growth pattern, related to the pure aluminium clusters, with the Ti atom in the surface, changes into a endohedral fcc-like pattern. The map of structural isomers, relative energy differences, second energy differences, and structural parameters were determined and analyzed. Moreover, we show the critical size depends on the net charge of the cluster, being different for the cationic clusters (n{sub c} = 21) and their neutral counterparts (n{sub c} = 20). For the Al {sub n} Ti {sup +} · Ar complexes, and for n < 21, the preferred Ar adsorption site is on top of the exohedral Ti atom, with adsorption energy in very good agreement with the experimental value. Instead, for n = 21, the Ar adsorption occurs on the top an Al atom with very low absorption energy. For all sizes the geometry of the Al{sub n}Ti{sup +} clusters keeps unaltered in the Ar-cluster complexes. This fact indicates that Ar adsorption does not influence the cluster structure, providing support

Relevant Subspace Clustering

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

2009-01-01

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

Advanced analysis of forest fire clustering

Science.gov (United States)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index

Horticultural cluster

OpenAIRE

SHERSTIUK S.V.; POSYLAYEVA K.I.

2013-01-01

In the article there are the theoretical and methodological approaches to the nature and existence of the cluster. The cluster differences from other kinds of cooperative and integration associations. Was develop by scientific-practical recommendations for forming a competitive horticultur cluster.