WorldWideScience

Sample records for atomic clusters analysis

  1. Analysis of Radiation Damage in Light Water Reactors: Comparison of Cluster Analysis Methods for the Analysis of Atom Probe Data.

    Science.gov (United States)

    Hyde, Jonathan M; DaCosta, Gérald; Hatzoglou, Constantinos; Weekes, Hannah; Radiguet, Bertrand; Styman, Paul D; Vurpillot, Francois; Pareige, Cristelle; Etienne, Auriane; Bonny, Giovanni; Castin, Nicolas; Malerba, Lorenzo; Pareige, Philippe

    2017-04-01

    Irradiation of reactor pressure vessel (RPV) steels causes the formation of nanoscale microstructural features (termed radiation damage), which affect the mechanical properties of the vessel. A key tool for characterizing these nanoscale features is atom probe tomography (APT), due to its high spatial resolution and the ability to identify different chemical species in three dimensions. Microstructural observations using APT can underpin development of a mechanistic understanding of defect formation. However, with atom probe analyses there are currently multiple methods for analyzing the data. This can result in inconsistencies between results obtained from different researchers and unnecessary scatter when combining data from multiple sources. This makes interpretation of results more complex and calibration of radiation damage models challenging. In this work simulations of a range of different microstructures are used to directly compare different cluster analysis algorithms and identify their strengths and weaknesses.

  2. Structure and analysis of atomic vibrations in clusters of Cu n ( n ≤ 20)

    Science.gov (United States)

    Rusina, G. G.; Borisova, S. D.; Chulkov, E. V.

    2013-02-01

    The binding energy, equilibrium geometry, and vibration frequencies of free clusters Cu n (2 ≤ n ≤ 20) are calculated using the potentials of interatomic interactions found using the tight-binding approximation. The nonmonotonic dependence of the clusters' minimum vibration frequency on their sizes and the extreme values for the number of atoms in a cluster n = 4, 6, 13, and 19 is demonstrated. It is noted that this result agrees with the theoretical and experimental data on stable structures of small and medium metallic clusters.

  3. New techniques for the analysis of fine-scaled clustering phenomena within atom probe tomography (APT) data.

    Science.gov (United States)

    Stephenson, Leigh T; Moody, Michael P; Liddicoat, Peter V; Ringer, Simon P

    2007-12-01

    Nanoscale atomic clusters in atom probe tomographic data are not universally defined but instead are characterized by the clustering algorithm used and the parameter values controlling the algorithmic process. A new core-linkage clustering algorithm is developed, combining fundamental elements of the conventional maximum separation method with density-based analyses. A key improvement to the algorithm is the independence of algorithmic parameters inherently unified in previous techniques, enabling a more accurate analysis to be applied across a wider range of material systems. Further, an objective procedure for the selection of parameters based on approximating the data with a model of complete spatial randomness is developed and applied. The use of higher nearest neighbor distributions is highlighted to give insight into the nature of the clustering phenomena present in a system and to generalize the clustering algorithms used to analyze it. Maximum separation, density-based scanning, and the core linkage algorithm, developed within this study, were separately applied to the investigation of fine solute clustering of solute atoms in an Al-1.9Zn-1.7Mg (at.%) at two distinct states of early phase decomposition and the results of these analyses were evaluated.

  4. Statistical analysis of atom probe data: detecting the early stages of solute clustering and/or co-segregation.

    Science.gov (United States)

    Hyde, J M; Cerezo, A; Williams, T J

    2009-04-01

    Statistical analysis of atom probe data has improved dramatically in the last decade and it is now possible to determine the size, the number density and the composition of individual clusters or precipitates such as those formed in reactor pressure vessel (RPV) steels during irradiation. However, the characterisation of the onset of clustering or co-segregation is more difficult and has traditionally focused on the use of composition frequency distributions (for detecting clustering) and contingency tables (for detecting co-segregation). In this work, the authors investigate the possibility of directly examining the neighbourhood of each individual solute atom as a means of identifying the onset of solute clustering and/or co-segregation. The methodology involves comparing the mean observed composition around a particular type of solute with that expected from the overall composition of the material. The methodology has been applied to atom probe data obtained from several irradiated RPV steels. The results show that the new approach is more sensitive to fine scale clustering and co-segregation than that achievable using composition frequency distribution and contingency table analyses.

  5. Atomic clusters with addressable complexity

    Science.gov (United States)

    Wales, David J.

    2017-02-01

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

  6. 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....

  7. Cluster analysis

    CERN Document Server

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

    2011-01-01

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

  8. Organising Atoms, Clusters and Proteins on Surfaces

    Science.gov (United States)

    Palmer, Richard E.

    2008-10-01

    This talk will discuss new developments in the creation of nanoscale surface features and their applications in biomedicine. Electron-surface interactions and plasma methods play a crucial role in both the production and analysis of these ``atomic architectures.'' At the extreme limit, electron injection from the tip of a scanning tunnelling microscope (STM) enables bond-selective manipulation of individual polyatomic molecules [1]. On a more practical level, the controlled deposition of size-selected clusters [2], generated by magnetron sputtering and gas condensation followed by mass selection, represents a surprisingly efficient route to the fabrication of surface features of size 1-10 nm, the size scale of biological molecules such as proteins. STM and AFM measurements show the clusters can act as binding sites for individual protein molecules. For example, the pinning of size-selected AuN clusters (N = 1--2000) to the (hydrophobic) graphite surface presents bindings site for sulphur atoms and thus for the cysteine residues in protein molecules. Systematic studies of different proteins [3] provide ``ground rules'' for residue-specific protein immobilisation by clusters and have led to the development of a novel biochip for protein screening by a spin-off company. The 3D atomic structure of the clusters is highly relevant to such applications. We show that measurement of the scattered electron beam intensity - specifically, the high angle annular dark field (HAADF) signal - in the scanning transmission electron microscope (STEM) allows us (a) to count the number of atoms in a cluster on the surface and (b) to determine a 3D atom-density map of the cluster when an aberration-corrected STEM is used [4]. 1. P.A. Sloan and R.E. Palmer, Nature 434 367 (2005). 2. S. Pratontep, P. Preece, C. Xirouchaki, R.E. Palmer, C.F. Sanz-Navarro, S.D. Kenny and R. Smith, Phys. Rev. Lett. 90 055503 (2003). 3. R.E. Palmer, S. Pratontep and H.-G. Boyen, Nature Materials 2 443 (2003

  9. Quantum Monte Carlo methods and lithium cluster properties. [Atomic clusters

    Energy Technology Data Exchange (ETDEWEB)

    Owen, R.K.

    1990-12-01

    Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) (0.1981), 0.1895(9) (0.1874(4)), 0.1530(34) (0.1599(73)), 0.1664(37) (0.1724(110)), 0.1613(43) (0.1675(110)) Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) (0.0203(12)), 0.0188(10) (0.0220(21)), 0.0247(8) (0.0310(12)), 0.0253(8) (0.0351(8)) Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.

  10. Atomic mobility in energetic cluster deposition

    Institute of Scientific and Technical Information of China (English)

    PAN Zheng-Ying; WANG Yue-Xia; WEI Qi; LI Zhi-Jie; ZHOU Liang; ZHANG Liang-Kun

    2004-01-01

    This paper tries to outline the influence of atomic mobility on the initial fabrication of thin films formed by LECBD. Based on our recent studies on low-energy cluster beam deposition (LECBD) by molecular dynamics simulation, two examples, the deposition of small carbon clusters on Si and diamond surfaces and Al clusters on Ni substrate, were mainly discussed. The impact energy of the cluster ranges from 0.1 eV to 100 eV. In the former case,the mobility and the lateral migration of surface atoms, especially the recoil atoms, are enhanced with increasing the impact energy, which promote the film to be smoother and denser. For the latter case, the transverse kinetic energy of cluster atoms, caused mainly by the collision between moving cluster atoms, dominates the lateral spread of cluster atoms on the surface, which is contributive to layer-by-layer growth of thin films. Our result is consistent with the experimental observations that the film structure is strongly dependent on the impact energy. In addition, it elucidates that the atomic mobility takes a leading role in the structure characteristic of films formed by LECBD.

  11. Structural and electronic properties for atomic clusters

    Science.gov (United States)

    Sun, Yan

    We have studied the structural and electronic properties for different groups of atomic clusters by doing a global search on the potential energy surface using the Taboo Search in Descriptors Space (TSDS) method and calculating the energies with Kohn-Sham Density Functional Theory (KS-DFT). Our goal was to find the structural and electronic principles for predicting the structure and stability of clusters. For Ben (n = 3--20), we have found that the evolution of geometric and electronic properties with size reflects a change in the nature of the bonding from van der Waals to metallic and then bulk-like. The cluster sizes with extra stability agree well with the predictions of the jellium model. In the 4d series of transition metal (TM) clusters, as the d-type bonding becomes more important, the preferred geometric structure changes from icosahedral (Y, Zr), to distorted compact structures (Nb, Mo), and FCC or simple cubic crystal fragments (Tc, Ru, Rh) due to the localized nature of the d-type orbital. Analysis of relative isomer energies and their electronic density of states suggest that these clusters tend to follow a maximum hardness principle (MHP). For A4B12 clusters (A is divalent, B is monovalent), we found unusually large (on average 1.95 eV) HOMO-LUMO gap values. This shows the extra stability at an electronic closed shell (20 electrons) predicted by the jellium model. The importance of symmetry, closed electronic and ionic shells in stability is shown by the relative stability of homotops of Mg4Ag12 which also provides support for the hypothesis that clusters that satisfy more than one stability criterion ("double magic") should be particularly stable.

  12. 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

  13. Fusion and fission of atomic clusters: recent advances

    DEFF Research Database (Denmark)

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

    2005-01-01

    We review recent advances made by our group in finding optimized geometries of atomic clusters as well as in description of fission of charged small metal clusters. We base our approach to these problems on analysis of multidimensional potential energy surface. For the fusion process we have...... developed an effective scheme of adding new atoms to stable cluster geometries of larger clusters in an efficient way. We apply this algorithm to finding geometries of metal and noble gas clusters. For the fission process the analysis of the potential energy landscape calculated on the ab initio level...... of theory allowed us to obtain very detailed information on energetics and pathways of the different fission channels for the Na^2+_10 clusters....

  14. Fusion and fission of atomic clusters: recent advances

    DEFF Research Database (Denmark)

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

    2005-01-01

    developed an effective scheme of adding new atoms to stable cluster geometries of larger clusters in an efficient way. We apply this algorithm to finding geometries of metal and noble gas clusters. For the fission process the analysis of the potential energy landscape calculated on the ab initio level......We review recent advances made by our group in finding optimized geometries of atomic clusters as well as in description of fission of charged small metal clusters. We base our approach to these problems on analysis of multidimensional potential energy surface. For the fusion process we have...... of theory allowed us to obtain very detailed information on energetics and pathways of the different fission channels for the Na^2+_10 clusters....

  15. Assembling hierarchical cluster solids with atomic precision.

    Science.gov (United States)

    Turkiewicz, Ari; Paley, Daniel W; Besara, Tiglet; Elbaz, Giselle; Pinkard, Andrew; Siegrist, Theo; Roy, Xavier

    2014-11-12

    Hierarchical solids created from the binary assembly of cobalt chalcogenide and iron oxide molecular clusters are reported. Six different molecular clusters based on the octahedral Co6E8 (E = Se or Te) and the expanded cubane Fe8O4 units are used as superatomic building blocks to construct these crystals. The formation of the solid is driven by the transfer of charge between complementary electron-donating and electron-accepting clusters in solution that crystallize as binary ionic compounds. The hierarchical structures are investigated by single-crystal X-ray diffraction, providing atomic and superatomic resolution. We report two different superstructures: a superatomic relative of the CsCl lattice type and an unusual packing arrangement based on the double-hexagonal close-packed lattice. Within these superstructures, we demonstrate various compositions and orientations of the clusters.

  16. Beyond organic chemistry: aromaticity in atomic clusters.

    Science.gov (United States)

    Boldyrev, Alexander I; Wang, Lai-Sheng

    2016-04-28

    We describe joint experimental and theoretical studies carried out collaboratively in the authors' labs for understanding the structures and chemical bonding of novel atomic clusters, which exhibit aromaticity. The concept of aromaticity was first discovered to be useful in understanding the square-planar unit of Al4 in a series of MAl4(-) bimetallic clusters that led to discoveries of aromaticity in many metal cluster systems, including transition metals and similar cluster motifs in solid compounds. The concept of aromaticity has been found to be particularly powerful in understanding the stability and bonding in planar boron clusters, many of which have been shown to be analogous to polycyclic aromatic hydrocarbons in their π bonding. Stimulated by the multiple aromaticity in planar boron clusters, a design principle has been proposed for stable metal-cerntered aromatic molecular wheels of the general formula, M@Bn(k-). A series of such borometallic aromatic wheel complexes have been produced in supersonic cluster beams and characterized experimentally and theoretically, including Ta@B10(-) and Nb@B10(-), which exhibit the highest coordination number in two dimensions.

  17. Alpha-cluster model of atomic nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Sosin, Zbigniew; Kallunkathariyil, Jinesh [Jagiellonian University, M. Smoluchowski Institute of Physics, Krakow (Poland); Blocki, Jan [NCBJ, Theoretical Physics Division (BP2), Swierk (Poland); Lukasik, Jerzy; Pawlowski, Piotr [IFJ PAN, Krakow (Poland)

    2016-05-15

    The description of a nuclear system in its ground state and at low excitations based on the equation of state (EoS) around normal density is presented. In the expansion of the EoS around the saturation point, additional spin polarization terms are taken into account. These terms, together with the standard symmetry term, are responsible for the appearance of the α-like clusters in the ground-state configurations of the N=Z even-even nuclei. At the nuclear surface these clusters can be identified as alpha particles. A correction for the surface effects is introduced for atomic nuclei. Taking into account an additional interaction between clusters the binding energies and sizes of the considered nuclei are very accurately described. The limits of the EoS parameters are established from the properties of the α, {sup 3}He and t particles. (orig.)

  18. Clusters of atoms and molecules theory, experiment, and clusters of atoms

    CERN Document Server

    1994-01-01

    Clusters of Atoms and Molecules is devoted to theoretical concepts and experimental techniques important in the rapidly expanding field of cluster science. Cluster properties are dicussed for clusteres composed of alkali metals, semiconductors, transition metals, carbon, oxides and halides of alkali metals, rare gases, and neutral molecules. The book is composed of several well-integrated treatments all prepared by experts. Each contribution starts out as simple as possible and ends with the latest results so that the book can serve as a text for a course, an introduction into the field, or as a reference book for the expert.

  19. Cluster analysis for applications

    CERN Document Server

    Anderberg, Michael R

    1973-01-01

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

  20. Symmetrisation schemes for global optimisation of atomic clusters.

    Science.gov (United States)

    Oakley, Mark T; Johnston, Roy L; Wales, David J

    2013-03-21

    Locating the global minima of atomic and molecular clusters can be a difficult optimisation problem. Here we report benchmarks for procedures that exploit approximate symmetry. This strategy was implemented in the GMIN program following a theoretical analysis, which explained why high-symmetry structures are more likely to have particularly high or particularly low energy. The analysis, and the corresponding algorithms, allow for approximate point group symmetry, and can be combined with basin-hopping and genetic algorithms. We report results for 38-, 75-, and 98-atom Lennard-Jones clusters, which are all multiple-funnel systems. Exploiting approximate symmetry reduces the mean time taken to locate the global minimum by up to two orders of magnitude, with smaller improvements in efficiency for LJ(55) and LJ(74), which correspond to simpler single-funnel energy landscapes.

  1. Marketing research cluster analysis

    Directory of Open Access Journals (Sweden)

    Marić Nebojša

    2002-01-01

    Full Text Available One area of applications of cluster analysis in marketing is identification of groups of cities and towns with similar demographic profiles. This paper considers main aspects of cluster analysis by an example of clustering 12 cities with the use of Minitab software.

  2. Nanophase materials assembled from atomic clusters

    Energy Technology Data Exchange (ETDEWEB)

    Siegel, R.W.

    1989-09-01

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

  3. Cluster Correspondence Analysis

    NARCIS (Netherlands)

    M. van de Velden (Michel); A. Iodice D' Enza; F. Palumbo

    2014-01-01

    markdownabstract__Abstract__ A new method is proposed that combines dimension reduction and cluster analysis for categorical data. A least-squares objective function is formulated that approximates the cluster by variables cross-tabulation. Individual observations are assigned to clusters

  4. Detecting Clusters in Atom Probe Data with Gaussian Mixture Models.

    Science.gov (United States)

    Zelenty, Jennifer; Dahl, Andrew; Hyde, Jonathan; Smith, George D W; Moody, Michael P

    2017-04-01

    Accurately identifying and extracting clusters from atom probe tomography (APT) reconstructions is extremely challenging, yet critical to many applications. Currently, the most prevalent approach to detect clusters is the maximum separation method, a heuristic that relies heavily upon parameters manually chosen by the user. In this work, a new clustering algorithm, Gaussian mixture model Expectation Maximization Algorithm (GEMA), was developed. GEMA utilizes a Gaussian mixture model to probabilistically distinguish clusters from random fluctuations in the matrix. This machine learning approach maximizes the data likelihood via expectation maximization: given atomic positions, the algorithm learns the position, size, and width of each cluster. A key advantage of GEMA is that atoms are probabilistically assigned to clusters, thus reflecting scientifically meaningful uncertainty regarding atoms located near precipitate/matrix interfaces. GEMA outperforms the maximum separation method in cluster detection accuracy when applied to several realistically simulated data sets. Lastly, GEMA was successfully applied to real APT data.

  5. Atom trap trace analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Z.-T.; Bailey, K.; Chen, C.-Y.; Du, X.; Li, Y.-M.; O' Connor, T. P.; Young, L.

    2000-05-25

    A new method of ultrasensitive trace-isotope analysis has been developed based upon the technique of laser manipulation of neutral atoms. It has been used to count individual {sup 85}Kr and {sup 81}Kr atoms present in a natural krypton sample with isotopic abundances in the range of 10{sup {minus}11} and 10{sup {minus}13}, respectively. The atom counts are free of contamination from other isotopes, elements,or molecules. The method is applicable to other trace-isotopes that can be efficiently captured with a magneto-optical trap, and has a broad range of potential applications.

  6. Quantum fluctuation effects on nuclear fragment and atomic cluster formation

    Energy Technology Data Exchange (ETDEWEB)

    Ohnishi, Akira [Hokkaido Univ., Sapporo (Japan). Dept. of Physics; Randrup, J.

    1997-05-01

    We investigate the nuclear fragmentation and atomic cluster formation by means of the recently proposed quantal Langevin treatment. It is shown that the effect of the quantal fluctuation is in the opposite direction in nuclear fragment and atomic cluster size distribution. This tendency is understood through the effective classical temperature for the observables. (author)

  7. Ab initio calculations and modelling of atomic cluster structure

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Lyalin, Andrey G.; Greiner, Walter

    2004-01-01

    framework for modelling the fusion process of noble gas clusters is presented. We report the striking correspondence of the peaks in the experimentally measured abundance mass spectra with the peaks in the size-dependence of the second derivative of the binding energy per atom calculated for the chain...... of the noble gas clusters up to 150 atoms....

  8. CLEAN: CLustering Enrichment ANalysis

    Directory of Open Access Journals (Sweden)

    Medvedovic Mario

    2009-07-01

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

  9. Unraveling the atomic structure of ultrafine iron clusters

    KAUST Repository

    Wang, Hongtao

    2012-12-18

    Unraveling the atomic structures of ultrafine iron clusters is critical to understanding their size-dependent catalytic effects and electronic properties. Here, we describe the stable close-packed structure of ultrafine Fe clusters for the first time, thanks to the superior properties of graphene, including the monolayer thickness, chemical inertness, mechanical strength, electrical and thermal conductivity. These clusters prefer to take regular planar shapes with morphology changes by local atomic shuffling, as suggested by the early hypothesis of solid-solid transformation. Our observations differ from observations from earlier experimental study and theoretical model, such as icosahedron, decahedron or cuboctahedron. No interaction was observed between Fe atoms or clusters and pristine graphene. However, preferential carving, as observed by other research groups, can be realized only when Fe clusters are embedded in graphene. The techniques introduced here will be of use in investigations of other clusters or even single atoms or molecules.

  10. Cluster Correspondence Analysis.

    Science.gov (United States)

    van de Velden, M; D'Enza, A Iodice; Palumbo, F

    2017-03-01

    A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.

  11. A 3D-analysis of cluster formation and dynamics of the X(-)-benzene (X = F, Cl, Br, I) ionic dimer solvated by Ar atoms.

    Science.gov (United States)

    Albertí, Margarita; Huarte-Larrañaga, Fermín; Aguilar, Antonio; Lucas, José M; Pirani, Fernando

    2011-05-14

    The specific influence of X(-) ions (X = F,Cl, Br, I) in the solvation process of halide-benzene (X(-)-Bz) ionic heterodimers by Ar atoms is investigated by means of molecular dynamic (MD) simulations. The gradual evolution from cluster rearrangement to solvation dynamics is discussed by considering ensembles of n (n = 1-15 and n = 30) Ar atoms around the X(-)-Bz stable ionic dimers. The potential energy surfaces employed are based on an atom/ion-atom and atom/ion-bond decomposition, which has been developed previously by some of the authors. The outcome of the dynamics is analyzed by employing radial distribution functions (RDF) and tridimensional (3D) probability densities.

  12. Magnetic properties of supported metal atoms and clusters

    Science.gov (United States)

    Martins, Michael; Wurth, Wilfried

    2016-12-01

    Clusters are small systems ranging from a few atoms up to several thousand atoms. They are of high interest in basic research, but also for applications due to their specific electronic, magnetic or chemical properties depending on size and composition. For small clusters, quantum size effects play an important role and specific material properties might be tailored by choosing a special size or composition of the cluster. Here, we review the magnetic properties of adatoms and supported small mass-selected transition-metal clusters in the few-atom limit investigated by x-ray magnetic circular dichroism spectroscopy in the soft x-ray regime. The influence of cluster size, composition, the cluster-surface and intra-cluster interaction on the spin and orbital magnetic moments will be discussed.

  13. Structures of 38-atom gold-platinum nanoalloy clusters

    Energy Technology Data Exchange (ETDEWEB)

    Ong, Yee Pin; Yoon, Tiem Leong [School of Physics, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia); Lim, Thong Leng [Faculty of Engineering and Technology, Multimedia University, Melaka Campus, 75450 Melaka (Malaysia)

    2015-04-24

    Bimetallic nanoclusters, such as gold-platinum nanoclusters, are nanomaterials promising wide range of applications. We perform a numerical study of 38-atom gold-platinum nanoalloy clusters, Au{sub n}Pt{sub 38−n} (0 ≤ n ≤ 38), to elucidate the geometrical structures of these clusters. The lowest-energy structures of these bimetallic nanoclusters at the semi-empirical level are obtained via a global-minimum search algorithm known as parallel tempering multi-canonical basin hopping plus genetic algorithm (PTMBHGA), in which empirical Gupta many-body potential is used to describe the inter-atomic interactions among the constituent atoms. The structures of gold-platinum nanoalloy clusters are predicted to be core-shell segregated nanoclusters. Gold atoms are observed to preferentially occupy the surface of the clusters, while platinum atoms tend to occupy the core due to the slightly smaller atomic radius of platinum as compared to gold’s. The evolution of the geometrical structure of 38-atom Au-Pt clusters displays striking similarity with that of 38-atom Au-Cu nanoalloy clusters as reported in the literature.

  14. Detecting and extracting clusters in atom probe data: A simple, automated method using Voronoi cells

    Energy Technology Data Exchange (ETDEWEB)

    Felfer, P., E-mail: peter.felfer@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia); Ceguerra, A.V., E-mail: anna.ceguerra@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia); Ringer, S.P., E-mail: simon.ringer@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia); Cairney, J.M., E-mail: julie.cairney@sydney.edu.au [Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia)

    2015-03-15

    The analysis of the formation of clusters in solid solutions is one of the most common uses of atom probe tomography. Here, we present a method where we use the Voronoi tessellation of the solute atoms and its geometric dual, the Delaunay triangulation to test for spatial/chemical randomness of the solid solution as well as extracting the clusters themselves. We show how the parameters necessary for cluster extraction can be determined automatically, i.e. without user interaction, making it an ideal tool for the screening of datasets and the pre-filtering of structures for other spatial analysis techniques. Since the Voronoi volumes are closely related to atomic concentrations, the parameters resulting from this analysis can also be used for other concentration based methods such as iso-surfaces. - Highlights: • Cluster analysis of atom probe data can be significantly simplified by using the Voronoi cell volumes of the atomic distribution. • Concentration fields are defined on a single atomic basis using Voronoi cells. • All parameters for the analysis are determined by optimizing the separation probability of bulk atoms vs clustered atoms.

  15. A liquid drop model for embedded atom method cluster energies

    Science.gov (United States)

    Finley, C. W.; Abel, P. B.; Ferrante, J.

    1996-01-01

    Minimum energy configurations for homonuclear clusters containing from two to twenty-two atoms of six metals, Ag, Au, Cu, Ni, Pd, and Pt have been calculated using the Embedded Atom Method (EAM). The average energy per atom as a function of cluster size has been fit to a liquid drop model, giving estimates of the surface and curvature energies. The liquid drop model gives a good representation of the relationship between average energy and cluster size. As a test the resulting surface energies are compared to EAM surface energy calculations for various low-index crystal faces with reasonable agreement.

  16. Advanced Electrochemistry of Individual Metal Clusters Electrodeposited Atom by Atom to Nanometer by Nanometer.

    Science.gov (United States)

    Kim, Jiyeon; Dick, Jeffrey E; Bard, Allen J

    2016-11-15

    Metal clusters are very important as building blocks for nanoparticles (NPs) for electrocatalysis and electroanalysis in both fundamental and applied electrochemistry. Attention has been given to understanding of traditional nucleation and growth of metal clusters and to their catalytic activities for various electrochemical applications in energy harvesting as well as analytical sensing. Importantly, understanding the properties of these clusters, primarily the relationship between catalysis and morphology, is required to optimize catalytic function. This has been difficult due to the heterogeneities in the size, shape, and surface properties. Thus, methods that address these issues are necessary to begin understanding the reactivity of individual catalytic centers as opposed to ensemble measurements, where the effect of size and morphology on the catalysis is averaged out in the measurement. This Account introduces our advanced electrochemical approaches to focus on each isolated metal cluster, where we electrochemically fabricated clusters or NPs atom by atom to nanometer by nanometer and explored their electrochemistry for their kinetic and catalytic behavior. Such approaches expand the dimensions of analysis, to include the electrochemistry of (1) a discrete atomic cluster, (2) solely a single NP, or (3) individual NPs in the ensemble sample. Specifically, we studied the electrocatalysis of atomic metal clusters as a nascent electrocatalyst via direct electrodeposition on carbon ultramicroelectrode (C UME) in a femtomolar metal ion precursor. In addition, we developed tunneling ultramicroelectrodes (TUMEs) to study electron transfer (ET) kinetics of a redox probe at a single metal NP electrodeposited on this TUME. Owing to the small dimension of a NP as an active area of a TUME, extremely high mass transfer conditions yielded a remarkably high standard ET rate constant, k(0), of 36 cm/s for outer-sphere ET reaction. Most recently, we advanced nanoscale

  17. APROACHES TOWARDS CLUSTER ANALYSIS

    National Research Council Canada - National Science Library

    Manuela Tvaronaviciene; Kristina Razminiene; Leonardo Piccinetti

    2015-01-01

    .... The findings indicate that case study is used in many articles refering to cluster research. Other methods, such as analysis, interview, survey, research, equation and others are used to support case study...

  18. On metallic clusters squeezed in atomic cages

    CERN Document Server

    Apostol, M

    1996-01-01

    The stability of metallic clusters of sodium (Na) in the octahedral cages of Na-doped fullerites Na6C60 and Na11C60 is discussed within a Thomas-Fermi model. It is shown that the tetrahedral Na4-cluster in Na6C60 has an electric charge of cca. +2.7 (in electron charge units), while the body-centered cubic Na9-cluster in Na11C60 is almost electrically neutral.

  19. Atomic cluster collisions: ISACC-2015 (7th International Symposium)*

    Science.gov (United States)

    Prosmiti, Rita; Villarreal, Pablo; Delgado-Barrio, Gerardo; Solov'yov, Andey V.

    2017-02-01

    The ISACC 2015 brought together nearly a hundred scientists in the field of atomic and molecular cluster physics from around the world. We deliver the Editorial of a topical issue compiling/presenting original research results from some of the participants on both experimental and theoretical studies involving research areas from small clusters to extended molecular systems in the field.

  20. Thermodynamics of small clusters of atoms: A molecular dynamics simulation

    DEFF Research Database (Denmark)

    Damgaard Kristensen, W.; Jensen, E. J.; Cotterill, Rodney M J

    1974-01-01

    The thermodynamic properties of clusters containing 55, 135, and 429 atoms have been calculated using the molecular dynamics method. Structural and vibrational properties of the clusters were examined at different temperatures in both the solid and the liquid phase. The nature of the melting...

  1. Preparation of Cluster States for Many Atoms in Cavity QED

    Institute of Scientific and Technical Information of China (English)

    ZHAN Zhi-Ming

    2007-01-01

    We propose a scheme for the generation of the cluster states for many atoms in cavity QED. In our scheme,the atoms are sent through nonresonant cavity fields in the vacuum states. The cavity fields are only virtually excited and no quantum information will be transferred from the atoms to the cavity fields. The advantage is that the cavities are suppressed during the procedure. The scheme can also be generalized to the ion trap system.

  2. Long-Range Correlations in Small Atomic Clusters

    Science.gov (United States)

    Nayak, Saroj K.; Ramaswamy, R.

    We study the power spectrum of fluctuations in the potential energy of atoms in small rare-gas clusters. At temperatures when the cluster is in a liquid-like state the spectra have a “1/f” dependence over a wide range of frequency f. This behavior is distinctly different from both the solid phase of clusters or bulk liquid, and is indicative of long-range temporal correlations. The origins of this phenomenon is explored by studying the individual potential-energy distributions in pure and mixed rare-gas clusters, Xe55 and ArXe54, via molecular dynamics simulations. Substitution of atomic impurities acts as an effective probe of the dynamics, and we observe that long-lived memory effects have their origins in hierarchical relaxation processes arising in the motion of the atoms from the surface to the core and vice-versa.

  3. Coupled-cluster computations of atomic nuclei

    CERN Document Server

    Hagen, G; Hjorth-Jensen, M; Dean, D J

    2013-01-01

    In the past decade, coupled-cluster theory has seen a renaissance in nuclear physics, with computations of neutron-rich and medium-mass nuclei. The method is efficient for nuclei with product-state references, and it describes many aspects of weakly bound and unbound nuclei. This report reviews the technical and conceptual developments of this method in nuclear physics, and the results of coupled-cluster calculations for nucleonic matter, and for exotic isotopes of helium, oxygen, calcium, and some of their neighbors.

  4. Quantitative binomial distribution analyses of nanoscale like-solute atom clustering and segregation in atom probe tomography data.

    Science.gov (United States)

    Moody, Michael P; Stephenson, Leigh T; Ceguerra, Anna V; Ringer, Simon P

    2008-07-01

    The applicability of the binomial frequency distribution is outlined for the analysis of the evolution nanoscale atomic clustering of dilute solute in an alloy subject to thermal ageing in 3D atom probe data. The conventional chi(2) statistics and significance testing are demonstrated to be inappropriate for comparison of quantity of solute segregation present in two or more different sized system. Pearson coefficient, mu, is shown to normalize chi(2) with respect to sample size over an order of magnitude. A simple computer simulation is implemented to investigate the binomial analysis and infer meaning in the measured value of mu over a series of systems at different solute concentrations and degree of clustering. The simulations replicate the form of experimental data and demonstrate the effect of detector efficiency to significantly underestimate the measured segregation. The binomial analysis is applied to experimental atom probe data sets and complementary simulations are used to interpret the results.

  5. 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.

  6. Aerosol cluster impact and break-up : II. Atomic and Cluster Scale Models.

    Energy Technology Data Exchange (ETDEWEB)

    Lechman, Jeremy B.; Takato, Yoichi (State University of New York at Buffalo, Buffalo, NY)

    2010-09-01

    Understanding the interaction of aerosol particle clusters/flocs with surfaces is an area of interest for a number of processes in chemical, pharmaceutical, and powder manufacturing as well as in steam-tube rupture in nuclear power plants. Developing predictive capabilities for these applications involves coupled phenomena on multiple length and timescales from the process macroscopic scale ({approx}1m) to the multi-cluster interaction scale (1mm-0.1m) to the single cluster scale ({approx}1000 - 10000 particles) to the particle scale (10nm-10{micro}m) interactions, and on down to the sub-particle, atomic scale interactions. The focus of this report is on the single cluster scale; although work directed toward developing better models of particle-particle interactions by considering sub-particle scale interactions and phenomena is also described. In particular, results of mesoscale (i.e., particle to single cluster scale) discrete element method (DEM) simulations for aerosol cluster impact with rigid walls are presented. The particle-particle interaction model is based on JKR adhesion theory and is implemented as an enhancement to the granular package in the LAMMPS code. The theory behind the model is outlined and preliminary results are shown. Additionally, as mentioned, results from atomistic classical molecular dynamics simulations are also described as a means of developing higher fidelity models of particle-particle interactions. Ultimately, the results from these and other studies at various scales must be collated to provide systems level models with accurate 'sub-grid' information for design, analysis and control of the underlying systems processes.

  7. Protein-protected luminescent noble metal quantum clusters: an emerging trend in atomic cluster nanoscience

    OpenAIRE

    Paulrajpillai Xavier; Kamalesh Chaudhari; Ananya Baksi; Thalappil Pradeep

    2012-01-01

    Noble metal quantum clusters (NMQCs) are the missing link between isolated noble metal atoms and nanoparticles. NMQCs are sub-nanometer core sized clusters composed of a group of atoms, most often luminescent in the visible region, and possess intriguing photo-physical and chemical properties. A trend is observed in the use of ligands, ranging from phosphines to functional proteins, for the synthesis of NMQCs in the liquid phase. In this review, we briefly overview recent advancements in the ...

  8. Chemically induced magnetism in atomically precise gold clusters.

    Science.gov (United States)

    Krishna, Katla Sai; Tarakeshwar, Pilarisetty; Mujica, Vladimiro; Kumar, Challa S S R

    2014-03-12

    Comparative theoretical and experimental investigations are reported into chemically induced magnetism in atomically-precise, ligand-stabilized gold clusters Au25 , Au38 and Au55 . The results indicate that [Au25 (PPh3 )10 (SC12 H25 )5 Cl2 ](2+) and Au38 (SC12 H25 )24 are diamagnetic, Au25 (SC2 H4 Ph)18 is paramagnetic, and Au55 (PPh3 )12 Cl6 , is ferromagnetic at room temperature. Understanding the magnetic properties resulting from quantum size effects in such atomically precise gold clusters could lead to new fundamental discoveries and applications.

  9. Detecting and extracting clusters in atom probe data: a simple, automated method using Voronoi cells.

    Science.gov (United States)

    Felfer, P; Ceguerra, A V; Ringer, S P; Cairney, J M

    2015-03-01

    The analysis of the formation of clusters in solid solutions is one of the most common uses of atom probe tomography. Here, we present a method where we use the Voronoi tessellation of the solute atoms and its geometric dual, the Delaunay triangulation to test for spatial/chemical randomness of the solid solution as well as extracting the clusters themselves. We show how the parameters necessary for cluster extraction can be determined automatically, i.e. without user interaction, making it an ideal tool for the screening of datasets and the pre-filtering of structures for other spatial analysis techniques. Since the Voronoi volumes are closely related to atomic concentrations, the parameters resulting from this analysis can also be used for other concentration based methods such as iso-surfaces. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Origin of the size-dependence of the polarizability per atom in heterogeneous clusters: The case of AlP clusters.

    Science.gov (United States)

    Krishtal, Alisa; Senet, Patrick; Van Alsenoy, Christian

    2010-10-21

    An analysis of the atomic polarizabilities α in stoichiometric aluminum phosphide clusters, computed at the MP2 and density functional theory (DFT) levels, the latter using the B3LYP functional, and partitioned using the classic and iterative versions of the Hirshfeld method, is presented. Two sets of clusters are examined: the ground-state Al(n)P(n) clusters (n=2-9) and the prolate clusters (Al(2)P(2))(N) and (Al(3)P(3))(N) (N≤6). In the ground-state clusters, the mean polarizability per atom, i.e., α/2n, decreases with the cluster size but shows peaks at n=5 and at n=7. We demonstrate that these peaks can be explained by a large polarizability of the Al atoms and by a low polarizability of the P atoms in Al(5)P(5) and Al(7)P(7) due to the presence of homopolar bonds in these clusters. We show indeed that the polarizability of an atom within an Al(n)P(n) cluster depends on the cluster size and the heteropolarity of the bonds it forms within the cluster, i.e., on the charges of the atoms. The polarizabilities of the fragments Al(2)P(2) and Al(3)P(3) in the prolate clusters were found to depend mainly on their location within the cluster. Finally, we show that the iterative Hirshfeld method is more suitable than the classic Hirshfeld method for describing the atomic polarizabilities and the atomic charges in clusters with heteropolar bonds, although both versions of the Hirshfeld method lead to similar conclusions.

  11. [Cluster analysis in biomedical researches].

    Science.gov (United States)

    Akopov, A S; Moskovtsev, A A; Dolenko, S A; Savina, G D

    2013-01-01

    Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research.

  12. Adsorption of a single gold or silver atom on vanadium oxide clusters.

    Science.gov (United States)

    Ding, Xun-Lei; Wang, Dan; Li, Rui-Jie; Liao, Heng-Lu; Zhang, Yan; Zhang, Hua-Yong

    2016-04-14

    The bonding properties between a single atom and its support have a close relationship with the stability and reactivity of single-atom catalysts. As a model system, the structural and electronic properties of bimetallic oxide clusters MV3Oy(q) (M = Au or Ag, q = 0, ±1, and y = 6-8) are systematically studied using density functional theory. The single noble metal atom Au or Ag tends to be adsorbed on the periphery of the V oxide clusters. Au prefers V sites for oxygen-poor clusters and O sites for oxygen-rich clusters, while Ag prefers O sites for most cases. According to natural population analysis, Au may possess positive or negative charges in the bimetallic oxide clusters, while Ag usually possesses positive charges. The bonding between Au and V has relatively high covalent character according to the bond order analysis. This work may provide some clues for understanding the bonding properties of single noble metal atoms on the support in practical single-atom catalysts, and serve as a starting point for further theoretical studies on the reaction mechanisms of related catalytic systems.

  13. Model study in chemisorption: atomic hydrogen on beryllium clusters

    Energy Technology Data Exchange (ETDEWEB)

    Bauschlicher, C.W. Jr.

    1976-08-01

    The interaction between atomic hydrogen and the (0001) surface of Be metal has been studied by ab initio electronic structure theory. Self-consistent-field (SCF) calculations have been performed using minimum, optimized minimum, double zeta and mixed basis sets for clusters as large as 22 Be atoms. The binding energy and equilibrium geometry (the distance to the surface) were determined for 4 sites. Both spatially restricted (the wavefunction was constrained to transform as one of the irreducible representations of the molecular point group) and unrestricted SCF calculations were performed. Using only the optimized minimum basis set, clusters containing as many as 22 beryllium atoms have been investigated. From a variety of considerations, this cluster is seen to be nearly converged within the model used, providing the most reliable results for chemisorption. The site dependence of the frequency is shown to be a geometrical effect depending on the number and angle of the bonds. The diffusion of atomic hydrogen through a perfect beryllium crystal is predicted to be energetically unfavorable. The cohesive energy, the ionization energy and the singlet-triplet separation were computed for the clusters without hydrogen. These quantities can be seen as a measure of the total amount of edge effects. The chemisorptive properties are not related to the total amount of edge effects, but rather the edge effects felt by the adsorbate bonding berylliums. This lack of correlation with the total edge effects illustrates the local nature of the bonding, further strengthening the cluster model for chemisorption. A detailed discussion of the bonding and electronic structure is included. The remaining edge effects for the Be/sub 22/ cluster are discussed.

  14. Spin magnetic moments from single atoms to small Cr clusters

    Energy Technology Data Exchange (ETDEWEB)

    Boeglin, C.; Decker, R.; Bulou, H.; Scheurer, F.; Chado, I. [IPCMS-GSI - UMR 7504, 67037 Strasbourg Cedex (France); Ohresser, P. [LURE, 91405 Orsay (France); Dhesi, S.S. [ESRF, BP 220, 38043 Grenoble Cedex (France); Present permanent address: Diamond Light Source, Chilton, Didcot OX11 0QX (United Kingdom); Gaudry, E. [LMCP, 4, place Jussieu, 75252 Paris (France); Lazarovits, B. [CCMS, T.U. Vienna, Gumpendorfstr. 1a, 1060 Wien (Austria)

    2005-07-01

    Morphology studies at the first stages of the growth of Cr/Au(111) are reported and compared to the magnetic properties of the nanostructures. We analyze by Scanning Tunneling Microscopy and Low Energy Electron Diffraction the Cr clusters growth between 200 K and 300 K. In the early stages of the growth the morphology of the clusters shows monoatomic high islands located at the kinks of the herringbone reconstructed Au(111) surface. By X-ray Magnetic Circular Dichroism performed on the Cr L{sub 2,3} edges it is shown that the temperature dependent morphology strongly influences the magnetic properties of the Cr clusters. We show that in the sub-monolayer regime Cr clusters are antiferromagnetic and paramagnetic when the size reaches the atomic limit. (copyright 2005 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  15. Deposition of size-selected atomic clusters on surfaces

    CERN Document Server

    Carroll, S J

    1999-01-01

    implant into the surface. For Ag sub 2 sub 0 -Ag sub 2 sub 0 sub 0 clusters, the implantation depth is found to scale linearly with the impact energy and inversely with the cross-sectional area of the cluster, with an offset due to energy lost to the elastic compression of the surface (Paper VI). For smaller (Ag sub 3) clusters the orientation of the cluster with respect to the surface and the precise impact site play an important role; the impact energy has to be 'focused' in order for cluster implantation to occur (Paper VII). The application of deposited clusters for the creation of Si nanostructures by plasma etching is explored in Paper VIII. This dissertation presents technical developments and experimental and computational investigations concerned with the deposition of atomic clusters onto surfaces. It consists of a collection of papers, in which the main body of results are contained, and four chapters presenting a subject review, computational and experimental techniques and a summary of the result...

  16. Probabilistic Teleportation of Three-Atom State via Five-Atom Cluster State

    Institute of Scientific and Technical Information of China (English)

    YU Li-Zhi; WU Tao

    2013-01-01

    A scheme for probabilistic teleportation of an unknown three-atom entangled state via a five-atom nonmaximally entangled duster state as quantum channel is proposed.In this scheme,the sender performs two Bell state and a single-atom measurements on the atoms,the receiver can reconstruct the original state with a certain probability by introducing an auxiliary atom and operating appropriate unitary transformations and controlled-not (C-not) operations according to the sender Alice's measurement results.As a result,the probability of successful teleportation is determined by the smallest two of the coefficients' absolute values of the cluster state.The considerable advantage of our scheme is that we employ a non-maximally entangled cluster state as quantum channel in the scheme,which can greatly reduce the amount of entanglement resources and need less classical bits.If we employ a maximally entangled cluster state as quantum channei,the probabilistic teleportation scheme becomes usual teleportation,the successful probability being 100%.

  17. Electronically excited rubidium atom in a helium cluster or film

    Science.gov (United States)

    Leino, Markku; Viel, Alexandra; Zillich, Robert E.

    2008-11-01

    We present theoretical studies of helium droplets and films doped with one electronically excited rubidium atom Rb∗ (P2). Diffusion and path integral Monte Carlo approaches are used to investigate the energetics and the structure of clusters containing up to 14 helium atoms. The surface of large clusters is approximated by a helium film. The nonpair additive potential energy surface is modeled using a diatomic in molecule scheme. Calculations show that the stable structure of Rb∗Hen consists of a seven helium atom ring centered at the rubidium, surrounded by a tirelike second solvation shell. A very different structure is obtained when performing a "vertical Monte Carlo transition." In this approach, a path integral Monte Carlo equilibration starts from the stable configuration of a rubidium atom in the electronic ground state adsorbed to the helium surface after switching to the electronically excited surface. In this case, Rb∗Hen relaxes to a weakly bound metastable state in which Rb∗ sits in a shallow dimple. The interpretation of the results is consistent with the recent experimental observations [G. Auböck et al., Phys. Rev. Lett. 101, 035301 (2008)].

  18. Theory for the atomic shell structure of the cluster magnetic moment and magnetoresistance of a cluster ensemble

    Science.gov (United States)

    Jensen, P. J.; Bennemann, K. H.

    1995-12-01

    We present a simple theory for the cluster size dependence of the average cluster magnetic moment of transition metal clusters. Assuming a local environmental dependence of the atomic magnetic moments, the cluster magnetization exhibits a magnetic shell structure, reflecting the atomic structure of the cluster. Thus, the observed oscillations of the average cluster magnet moment may serve as a fingerprint of the cluster geometry. We also discuss the giant magnetoresistance (GMR) exhibited by an ensemble of magnetic clusters embedded in a metallic matrix. It is shown that the magnetic anisotropy affects strongly the magnetization of the cluster ensemble under certain conditions. Since the GMR depends on the cluster ensemble magnetization, it can be used to determine the cluster magnetic anisotropy energy.

  19. Integrative cluster analysis in bioinformatics

    CERN Document Server

    Abu-Jamous, Basel; Nandi, Asoke K

    2015-01-01

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

  20. Direct atomic imaging and density functional theory study of the Au24Pd1 cluster catalyst.

    Science.gov (United States)

    Bruma, A; Negreiros, F R; Xie, S; Tsukuda, T; Johnston, R L; Fortunelli, A; Li, Z Y

    2013-10-21

    In this study we report a direct, atomic-resolution imaging of calcined Au24Pd1 clusters supported on multiwall carbon nanotubes by employing aberration-corrected scanning transmission electron microscopy. Using gold atoms as mass standards, we confirm the cluster size to be 25 ± 2, in agreement with the Au24Pd1(SR)18 precursor used in the synthesis. Concurrently, a Density-Functional/Basin-Hopping computational algorithm is employed to locate the low-energy configurations of free Au24Pd1 cluster. Cage structures surrounding a single core atom are found to be favored, with a slight preference for Pd to occupy the core site. The cluster shows a tendency toward elongated arrangements, consistent with experimental data. The degree of electron transfer from the Pd dopant to Au is quantified through a Löwdin charge analysis, suggesting that Pd may act as an electron promoter to the surrounding Au atoms when they are involved in catalytic reactions.

  1. Clustered field evaporation of metallic glasses in atom probe tomography.

    Science.gov (United States)

    Zemp, J; Gerstl, S S A; Löffler, J F; Schönfeld, B

    2016-03-01

    Field evaporation of metallic glasses is a stochastic process combined with spatially and temporally correlated events, which are referred to as clustered evaporation (CE). This phenomenon is investigated by studying the distance between consecutive detector hits. CE is found to be a strongly localized phenomenon (up to 3nm in range) which also depends on the type of evaporating ions. While a similar effect in crystals is attributed to the evaporation of crystalline layers, CE of metallic glasses presumably has a different - as yet unknown - physical origin. The present work provides new perspectives on quantification methods for atom probe tomography of metallic glasses.

  2. Computer Simulation of Ordering and Atom Clustering in Aging Binary Al-Li Alloy

    Institute of Scientific and Technical Information of China (English)

    LI Xiao-ling; CHEN Zheng; WANG Yong-xin; HU Ming-juan

    2004-01-01

    Ordering and atom clustering in aging binary Al-Li alloy has been investigated by computer simulation through calculating the long range order (lro.) parameter and composition deviation order parameter from single-site occupation probabilities of Li atom. The results show that when the alloy lies in metastable region in the phase diagram ordering and atom clustering occur simultaneously. As the composition of the alloy increases ordering occurs earlier than atom clustering gradually. When the alloy lies in instable region atom clustering takes place after the congruent ordering completes. It has also been found that the incubation period of the phase transformation is shortened as the composition increases.

  3. Computer Simulation of Ordering and Atom Clustering in Aging Binary AI-Li Alloy

    Institute of Scientific and Technical Information of China (English)

    LIXiao-ling; CHENZheng; WANGYong-xin; HUMing-juan

    2004-01-01

    Ordering and atom clustering in aging binary Al-Li alloy has been investigated by computer simulation through calculating the long range order (lro.) parameter and composition deviation order parameter from single-site occupation probabilities of Li atom. The results show that when the alloy lies in metastable region in the phase diagram ordering and atom clustering occur simultaneously. As the composition of the alloy increases ordering occurs earlier than atom clustering gradually. When the alloy lies in instable region atom clustering takes place after the congruent ordering completes. It has also been found that the incubation period of the phase transformation is shortened as the composition increases.

  4. Protein-protected luminescent noble metal quantum clusters: an emerging trend in atomic cluster nanoscience.

    Science.gov (United States)

    Xavier, Paulrajpillai Lourdu; Chaudhari, Kamalesh; Baksi, Ananya; Pradeep, Thalappil

    2012-01-01

    Noble metal quantum clusters (NMQCs) are the missing link between isolated noble metal atoms and nanoparticles. NMQCs are sub-nanometer core sized clusters composed of a group of atoms, most often luminescent in the visible region, and possess intriguing photo-physical and chemical properties. A trend is observed in the use of ligands, ranging from phosphines to functional proteins, for the synthesis of NMQCs in the liquid phase. In this review, we briefly overview recent advancements in the synthesis of protein protected NMQCs with special emphasis on their structural and photo-physical properties. In view of the protein protection, coupled with direct synthesis and easy functionalization, this hybrid QC-protein system is expected to have numerous optical and bioimaging applications in the future, pointers in this direction are visible in the literature.

  5. Protein-protected luminescent noble metal quantum clusters: an emerging trend in atomic cluster nanoscience

    Directory of Open Access Journals (Sweden)

    Paulrajpillai Xavier

    2012-02-01

    Full Text Available Noble metal quantum clusters (NMQCs are the missing link between isolated noble metal atoms and nanoparticles. NMQCs are sub-nanometer core sized clusters composed of a group of atoms, most often luminescent in the visible region, and possess intriguing photo-physical and chemical properties. A trend is observed in the use of ligands, ranging from phosphines to functional proteins, for the synthesis of NMQCs in the liquid phase. In this review, we briefly overview recent advancements in the synthesis of protein protected NMQCs with special emphasis on their structural and photo-physical properties. In view of the protein protection, coupled with direct synthesis and easy functionalization, this hybrid QC-protein system is expected to have numerous optical and bioimaging applications in the future, pointers in this direction are visible in the literature.

  6. Clustering of Ions at Atomic-Dimensions in Quantum Plasmas

    CERN Document Server

    Shukla, P K

    2012-01-01

    By means of particle simulations of the equations of motion for ions interacting with the newly discovered Shukla-Eliasson (SE) force in a dense quantum plasma, we demonstrate that the SE force is powerful to bring ions closer at atomic dimensions. Specifically, we present simulation results on the dynamics of an ensemble of ions in the presence of the SE force without and with confining external potentials and collisions between the ions and degenerate electrons. Our particle simulations reveal that under the SE force, ions attract each other, come closer and form ionic clusters in the bath of degenerate electrons that shield the ions. Furthermore, an external confining potential produces robust ion clusters that can have cigar-like and ball-like shapes. The binding between the ions on account of the SE force may provide possibility of non-Coulombic explosions of ionic clusters for inertial confined fusion (ICF) schemes when high-energy density plasmas (density exceeding $10^{23}$ per cubic centimeters) are ...

  7. Structure and atomic vibrations in bimetallic Ni13 - n Al n clusters

    Science.gov (United States)

    Rusina, G. G.; Borisova, S. D.; Chulkov, E. V.

    2015-04-01

    The binding energy, equilibrium geometry, and vibration frequencies in bimetallic clusters Ni13 - n Al n ( n = 0-13) have been calculated using the embedded atom method potentials. It has been shown that the icosahedral structure is the most stable in monoatomic and bimetallic clusters. A tendency of Al atoms to segregate on the cluster surface has been revealed in agreement with the experimental data. The calculations of the atomic vibrations have shown the nonmonotonic dependence of the minimum and maximum vibration frequencies of cluster atoms on its composition and the coupling of their extreme values with the most stable atomic configuration. The increase in the number of Al atoms leads to the shift of the frequency spectrum and the substantial redistribution of the localization of vibrations on the cluster atoms.

  8. Toward the Atomic-Level Mass Analysis of Biomolecules by the Scanning Atom Probe.

    Science.gov (United States)

    Nishikawa, Osamu; Taniguchi, Masahiro

    2016-12-22

    In 1994, a new type of atom probe instrument, named the scanning atom probe (SAP), was proposed. The unique feature of the SAP is the introduction of a small extraction electrode, which scans over a specimen surface and confines the high field, required for field evaporation of surface atoms in a small space, between the specimen and the electrode. Thus, the SAP does not require a sharp specimen tip. This indicates that the SAP can mass analyze the specimens which are difficult to form in a sharp tip, such as organic materials and biomolecules. Clean single wall carbon nanotubes (CNT), made by high-pressure carbon monoxide process are found to be the best substrates for biomolecules. Various amino acids and dipeptide biomolecules were successfully mass analyzed, revealing characteristic clusters formed by strongly bound atoms in the specimens. The mass analysis indicates that SAP analysis of biomolecules is not only qualitative, but also quantitative.

  9. Reactivity Control of Rhodium Cluster Ions by Alloying with Tantalum Atoms.

    Science.gov (United States)

    Mafuné, Fumitaka; Tawaraya, Yuki; Kudoh, Satoshi

    2016-02-18

    Gas phase, bielement rhodium and tantalum clusters, RhnTam(+) (n + m = 6), were prepared by the double laser ablation of Rh and Ta rods in He carrier gas. The clusters were introduced into a reaction gas cell filled with nitric oxide (NO) diluted with He and were subjected to collisions with NO and He at room temperature. The product species were observed by mass spectrometry, demonstrating that the NO molecules were sequentially adsorbed on the RhnTam(+) clusters to form RhnTam(+)NxOx (x = 1, 2, 3, ...) species. In addition, oxide clusters, RhnTam(+)O2, were also observed, suggesting that the NO molecules were dissociatively adsorbed on the cluster, the N atoms migrated on the surface to form N2, and the N2 molecules were released from RhnTam(+)N2O2. The reactivity, leading to oxide formation, was composition dependent: oxide clusters were dominantly formed for the bielement clusters containing both Rh and Ta atoms, whereas such clusters were hardly formed for the single-element Rhn(+) and Tam(+) clusters. DFT calculations indicated that the Ta atoms induce dissociation of NO on the clusters by lowering the dissociation energy, whereas the Rh atoms enable release of N2 by lowering the binding energy of the N atoms on the clusters.

  10. Scoring methods used in cluster analysis

    OpenAIRE

    Sirota, Sergej

    2014-01-01

    The aim of the thesis is to compare methods of cluster analysis correctly classify objects in the dataset into groups, which are known. In the theoretical section first describes the steps needed to prepare a data file for cluster analysis. The next theoretical section is dedicated to the cluster analysis, which describes ways of measuring similarity of objects and clusters, and dedicated to description the methods of cluster analysis used in practical part of this thesis. In practical part a...

  11. Bubble growth from clustered hydrogen and helium atoms in tungsten under a fusion environment

    Science.gov (United States)

    You, Yu-Wei; Kong, Xiang-Shan; Wu, Xuebang; Liu, C. S.; Chen, J. L.; Luo, G.-N.

    2017-01-01

    Bubbles seriously degrade the mechanical properties of tungsten and thus threaten the safety of nuclear fusion devices, however, the underlying atomic mechanism of bubble growth from clustered hydrogen and helium atoms is still mysterious. In this work, first-principles calculations are therefore carried out to assess the stability of tungsten atoms around both hydrogen and helium clusters. We find that the closest vacancy-formation energies of interstitial hydrogen and helium clusters are substantially decreased. The first-nearest and second-nearest vacancy-formation energies close to vacancy-hydrogen clusters decrease in a step-like way to  ˜0, while those close to vacancy-helium clusters are reduced almost linearly to  ˜-5.46 eV when atom number reaches 10. The vacancy-formation energies closest to helium clusters are more significantly reduced than those nearest to hydrogen clusters, whatever the clusters are embedded at interstitial sites or vacancies. The reduction of vacancy-formation energies results in instability and thus emission of tungsten atoms close to interstitial helium and vacancy-helium clusters, which illustrates the experimental results, that the tungsten atoms can be emitted from the vicinity of vacancy-helium clusters. In addition, the emission of unstable tungsten atoms close to hydrogen clusters may become possible once they are disturbed by the environment. The emission of tungsten atoms facilitates the growth and evolution of hydrogen and helium clusters and ultimately the bubble formation. The results also explain the bubble formation even if no displacement damage is produced in tungsten exposed to low-energy hydrogen and helium plasma.

  12. Investigation of accelerated neutral atom beams created from gas cluster ion beams

    Energy Technology Data Exchange (ETDEWEB)

    Kirkpatrick, A., E-mail: akirkpatrick@exogenesis.us [Exogenesis Corporation, 20 Fortune Drive, Billerica, MA 01821 (United States); Kirkpatrick, S.; Walsh, M.; Chau, S.; Mack, M.; Harrison, S.; Svrluga, R.; Khoury, J. [Exogenesis Corporation, 20 Fortune Drive, Billerica, MA 01821 (United States)

    2013-07-15

    A new concept for ultra-shallow processing of surfaces known as accelerated neutral atom beam (ANAB) technique employs conversion of energetic gas cluster ions produced by the gas cluster ion beam (GCIB) method into intense collimated beams of coincident neutral gas atoms having controllable average energies from less than 10 eV per atom to beyond 100 eV per atom. A beam of accelerated gas cluster ions is first produced as is usual in GCIB, but conditions within the source ionizer and extraction regions are adjusted such that immediately after ionization and acceleration the clusters undergo collisions with non-ionized gas atoms. Energy transfer during these collisions causes the energetic cluster ions to release many of their constituent atoms. An electrostatic deflector is then used to eliminate charged species, leaving the released neutral atoms to still travel collectively at the same velocities they had as bonded components of their parent clusters. Upon target impact, the accelerated neutral atom beams produce effects similar to those normally associated with GCIB, but to shallower depths, with less surface damage and with superior subsurface interfaces. The paper discusses generation and characterization of the accelerated neutral atom beams, describes interactions of the beams with target surfaces, and presents examples of ongoing work on applications for biomedical devices.

  13. Investigation of accelerated neutral atom beams created from gas cluster ion beams

    Science.gov (United States)

    Kirkpatrick, A.; Kirkpatrick, S.; Walsh, M.; Chau, S.; Mack, M.; Harrison, S.; Svrluga, R.; Khoury, J.

    2013-07-01

    A new concept for ultra-shallow processing of surfaces known as accelerated neutral atom beam (ANAB) technique employs conversion of energetic gas cluster ions produced by the gas cluster ion beam (GCIB) method into intense collimated beams of coincident neutral gas atoms having controllable average energies from less than 10 eV per atom to beyond 100 eV per atom. A beam of accelerated gas cluster ions is first produced as is usual in GCIB, but conditions within the source ionizer and extraction regions are adjusted such that immediately after ionization and acceleration the clusters undergo collisions with non-ionized gas atoms. Energy transfer during these collisions causes the energetic cluster ions to release many of their constituent atoms. An electrostatic deflector is then used to eliminate charged species, leaving the released neutral atoms to still travel collectively at the same velocities they had as bonded components of their parent clusters. Upon target impact, the accelerated neutral atom beams produce effects similar to those normally associated with GCIB, but to shallower depths, with less surface damage and with superior subsurface interfaces. The paper discusses generation and characterization of the accelerated neutral atom beams, describes interactions of the beams with target surfaces, and presents examples of ongoing work on applications for biomedical devices.

  14. Nonlinear analysis of EAS clusters

    CERN Document Server

    Zotov, M Yu; Fomin, Y A; Fomin, Yu. A.

    2002-01-01

    We apply certain methods of nonlinear time series analysis to the extensive air shower clusters found earlier in the data set obtained with the EAS-1000 Prototype array. In particular, we use the Grassberger-Procaccia algorithm to compute the correlation dimension of samples in the vicinity of the clusters. The validity of the results is checked by surrogate data tests and some additional quantities. We compare our conclusions with the results of similar investigations performed by the EAS-TOP and LAAS groups.

  15. Supermodel Analysis of Galaxy Clusters

    CERN Document Server

    Fusco-Femiano, R; Lapi, A

    2009-01-01

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

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

    Science.gov (United States)

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

    2012-09-12

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

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

    Science.gov (United States)

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

    2014-07-10

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

  18. Efficient scheme of quantum SWAP gate and multi-atom cluster state via cavity QED

    Institute of Scientific and Technical Information of China (English)

    Jiang Chun-Lei; Fang Mao-Fa; Hu Yao-Hua

    2008-01-01

    In this paper,we propose a physical scheme to realize quantum SWAP gate by using a large-detuned single-mode cavity field and two identical Rydberg atoms.It is shown that the scheme can also be used to create multi-atom cluster state.During the interaction between atom and cavity,the cavity is only virtually excited and thus the scheme is insensitive to the cavity field states and cavity decay.With the help of our scheme it is very simple to prepare the N-atom cluster state with perfect fidelity and probability.The practical feasibility of this method is also discussed.

  19. Teleportation of arbitrary unknown two-atom state with Cluster state via thermal cavity

    Institute of Scientific and Technical Information of China (English)

    Zhang Wen; Liu Yi-Min; Liu Jun; Zhang Zhan-Jun

    2008-01-01

    This paper proposes a scheme for implementing the teleportation of an arbitrary unknown two-atom state by using a cluster state of four identical 2-level atoms as quantum channel in a thermal cavity.The two distinct advantages of the present scheme are:(i)The discrimination of 16 orthonormal cluster states in the standard teleportation protocol is transformed into the discrimination of single-atom states.Consequently,the discrimination difficulty of states is degraded.(ii)The scheme is insensitive to the cavity field state and the cavity decay for the thermal cavity is only virtually excited when atoms interact with it.Thus.the scheme is more feasible.

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

    Science.gov (United States)

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

    2015-03-24

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

  1. SPATIO-TEMPORAL CLUSTER ANALYSIS OF DISEASE

    Directory of Open Access Journals (Sweden)

    M. S. Abramovich

    2014-01-01

    Full Text Available The robust version of the spatial scanning statistics for clustering is proposed. Spatio-temporal cluster analysis algorithms were used for the cluster detection of incidence of thyroid carcinoma. Me-thods and algorithms of detection and building clusters for disease on studying territories are consi-dered.

  2. Endohedral beryllium atoms in germanium clusters with eight and fewer vertices: how small can a cluster be and still encapsulate a central atom?

    Science.gov (United States)

    Uţă, M M; King, R B

    2012-05-31

    Structures of the beryllium-centered germanium clusters Be@Ge(n)(z) (n = 8, 7, 6; z = -4, -2, 0, +2) have been investigated by density functional theory to provide some insight regarding the smallest metal cluster that can encapsulate an interstitial atom. The lowest energy structures of the eight-vertex Be@Ge(8)(z) clusters (z = -4, -2, 0, +2) all have the Be atom at the center of a closed polyhedron, namely, a D(4d) square antiprism for Be@Ge(8)(4-), a D(2d) bisdisphenoid for Be@Ge(8)(2-), an ideal O(h) cube for Be@Ge(8), and a C(2v) distorted cube for Be@Ge(8)(2+). The Be-centered cubic structures predicted for Be@Ge(8) and Be@Ge(8)(2+) differ from the previously predicted lowest energy structures for the isoelectronic Ge(8)(2-) and Ge(8). This appears to be related to the larger internal volume of the cube relative to other closed eight-vertex polyhedra. The lowest energy structures for the smaller seven- and six-vertex clusters Be@Ge(n)(z) (n = 7, 6; z = -4, -2, 0, +2) no longer have the Be atom at the center of a closed Ge(n) polyhedron. Instead, either the Ge(n) polyhedron has opened up to provide a larger volume for the Be atom or the Be atom has migrated to the surface of the polyhedron. However, higher energy structures are found in which the Be atom is located at the center of a Ge(n) (n = 7, 6) polyhedron. Examples of such structures are a centered C(2v) capped trigonal prismatic structure for Be@Ge(7)(2-), a centered D(5h) pentagonal bipyramidal structure for Be@Ge(7), a centered D(3h) trigonal prismatic structure for Be@Ge(6)(4-), and a centered octahedral structure for Be@Ge(6). Cluster buildup reactions of the type Be@Ge(n)(z) + Ge(2) → Be@Ge(n+2)(z) (n = 6, 8; z = -4, -2, 0, +2) are all predicted to be highly exothermic. This suggests that interstitial clusters having an endohedral atom inside a bare post transition element polyhedron with eight or fewer vertices are less than the optimum size. This is consistent with the experimental observation

  3. Hydrogen mimicking the properties of coinage metal atoms in Cu and Ag monohydride clusters.

    Science.gov (United States)

    Vetter, Karsten; Proch, Sebastian; Ganteför, Gerd F; Behera, Swayamprabha; Jena, Puru

    2013-12-28

    A systematic study of the electronic structure and equilibrium geometries of Cun, Cun-1H, Agn, and Agn-1H; n = 2-5 clusters is carried out using photoelectron spectroscopy (PES) experiments and density functional theory based calculations. Our objective is to see if the substitution of a coinage metal atom by hydrogen would retain the electronic structure of the parent metal cluster since both systems are isoelectronic. For clusters with n ≥ 3, we find that the measured PES and vertical detachment energies (VDEs) (i.e. energies necessary to remove an electron from the anionic Mn(-) (M = Cu, Ag) clusters without changing their geometries) are close to those of Mn-1H(-) clusters, suggesting that substitution of a metal atom with hydrogen does not perturb the electronic structure of the parent cluster anion significantly. Calculated VDEs agree very well with experiment validating the theoretical methods used as well as the geometries of the neutral and anionic clusters.

  4. Electron spectra and structure of atomic and molecular clusters

    Energy Technology Data Exchange (ETDEWEB)

    Dehmer, Patricia M.

    1980-01-01

    Changes in electronic structure that occur during the stepwise transition from gas phase monomers to large clusters which resemble the condensed phase were studied. This basic information on weakly bound clusters is critical to the understanding of such phenomena as nucleation, aerosol formation, catalysis, and gas-to-particle conversion, yet there exist almost no experimental data on neutral particle energy levels or binding energies as a function of cluster size. (GHT)

  5. Semiclassical Szego limit of resonance clusters for the hydrogen atom Stark Hamiltonian

    CERN Document Server

    Hislop, Peter D

    2011-01-01

    We study the weighted averages of resonance clusters for the hydrogen atom with a Stark electric field in the weak field limit. We prove a semiclassical Szego-type theorem for resonance clusters showing that the limiting distribution of the resonance shifts concentrates on the classical energy surface corresponding to a rescaled eigenvalue of the hydrogen atom Hamiltonian. This result extends Szego-type results on eigenvalue clusters to resonance clusters. There are two new features in this work: first, the study of resonance clusters requires the use of non self-adjoint operators, and second, the Stark perturbation is unbounded so control of the perturbation is achieved using localization properties of coherent states corresponding to hydrogen atom eigenvalues.

  6. Structure and Chemistry of Atomic Clusters from Supersonic Beams.

    Science.gov (United States)

    Yang, Shi-He.

    A tandem time-of-flight (TOF) apparatus was designed to study the structure and chemistry of cold transition metal cluster ions from supersonic beams. By means of a photodissociation laser fluence dependence technique, binding energies of Nb_{rm x }^{+} (x = 2 - 20), Co_{rm x}^{+ } (x = 4 - 20) and etc. were found to generally increase with cluster size. The desorption energies of Nb_{rm x}N _2^{+} (x = 2 - 17) and Nb_{rm x} CO^{+} (x = 2 - 10) also increase with cluster size with some oscillations similar to the size dependent reactivities of these clusters. Photodetachment studies revealed that electron affinities of copper clusters increase with cluster size with a sharp even/odd alternation. Unlike other noble metals, Ag_{rm x}^ {-} clusters display two competing processes: photodissociation and photodetachment. Relative reactivities of cluster ions of Nb, Co, Ag, and etc. have been measured using a fast flow cluster reactor, displaying a similar function of cluster size to that of the neutrals. In addition, preliminary photoelectron experiments have been performed on Cu_{ rm x}^{-} and Nb _{rm x}^{-}. A magnetic Time-of-flight ultraviolet photoelectron spectrometer (MTOFUPS) has been developed to study electronic structures of cold metal and semiconductor cluster anions prepared in supersonic beams. Application of this spectrometer to carbon clusters with a F_2 laser (7.9 eV) allowed their electron affinities and UPS patterns to be measured,demonstrating a remarkable structural evolution of these clusters: Chains (C_2^{ -}-C_9^{-} ) - Rings (C_{10}^ {-}-C_{29}^ {-}) - Cages (C_{38 }^{-}-C_{84 }^{-}). In particular, the UPS of C_{60}^{-} is in excellent agreement with the CNDO/S calculation, providing a striking spectral evidence for the highly symmetric icosahedral soccer ball structure--Buckminsterfullerene. For comparison, the UPS of Si_ {rm x}^{-} and Ge_{rm x}^{ -} are presented. Unlike carbon clusters which prefer structures of low dimensionality, these

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

    Science.gov (United States)

    Schaefer, Andreas; Daniell, James; Wenzel, Friedemann

    2016-04-01

    Earthquake declustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity with usual applications comprising of probabilistic seismic hazard assessments (PSHAs) and earthquake prediction methods. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation. Various methods have been developed to address this issue from other researchers. These have differing ranges of complexity ranging from rather simple statistical window methods to complex epidemic models. This study introduces the smart cluster method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal identification. Hereby, an adaptive search algorithm for data point clusters is adopted. It uses the earthquake density in the spatio-temporal neighbourhood of each event to adjust the search properties. The identified clusters are subsequently analysed to determine directional anisotropy, focussing on a strong correlation along the rupture plane and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010/2011 Darfield-Christchurch events, an adaptive classification procedure is applied to disassemble subsequent ruptures which may have been grouped into an individual cluster using near-field searches, support vector machines and temporal splitting. The steering parameters of the search behaviour are linked to local earthquake properties like magnitude of completeness, earthquake density and Gutenberg-Richter parameters. The method is capable of identifying and classifying earthquake clusters in space and time. It is tested and validated using earthquake data from California and New Zealand. As a result of the cluster identification process, each event in

  8. Small Al clusters on the Cu(111) surface: Atomic relaxation and vibrational properties

    Science.gov (United States)

    Rusina, G. G.; Borisova, S. D.; Chulkov, E. V.

    2010-11-01

    The relaxation and vibrational properties of both Al clusters and the (111) surface of a copper sub-strate were studied using the interatomic interaction potentials obtained in a tight-binding approximation. The presence of small aluminum clusters led to modification of the vibrational states of the substrate, a shift of the Rayleigh mode, and excitation of new Z-polarized modes. Hybridized modes localized on the cluster adatoms and the neighboring atoms of the substrate were found in the phonon spectrum. The localized dipole-active modes of the cluster and their strong hybridization with vibrations of the substrate points to desorption stability of the tri- and heptaatomic clusters.

  9. Cluster Analysis of Ranunculus Species

    Directory of Open Access Journals (Sweden)

    SURANTO

    2002-01-01

    Full Text Available The aim of the experiment was to examine whether the morphological characters of eleven species of Ranunculus collected from a number of populations were in agreement with the genetic data (isozyme. The method used in this study was polyacrilamide gel electrophoresis using peroxides, estarase, malate dehydrogenase, and acid phosphatase enzymes. The results showed that cluster analysis based on isozyme data have given a good support to classification of eleven species based on morphological groups. This study concluded that in certain species each morphological variation was profit to be genetically based.

  10. Atom Trap Trace Analysis of Ca Isotopes

    Energy Technology Data Exchange (ETDEWEB)

    Hoekstra, S., E-mail: hoekstra@fhi-berlin.mgp.de [Fritz-Haber Institut der Max-Planck Gesellschaft (Germany); Mollema, A. K.; Morgenstern, R.; Willmann, L.; Wilschut, H. W.; Hoekstra, R. [Rijksuniversiteit Groningen, Atomic Physics, KVI (Netherlands)

    2005-04-15

    In our experiment we aim at the detection of the rarest, naturally occuring calcium isotope 41Ca by means of atom trap trace analysis. On basis of single-atom detection of 46Ca our present sensitivity for 41Ca is estimated to be 1 atom per hour at an abundance of 10-12. To reach a sensitivity at the level of natural abundance, which is 10-14, we need to reduce atomic beam losses. To achieve this, optical compression of the atomic beam is a promising option. We use Monte Carlo Simulations to demonstrate that optical compression of the atomic beam increases throughput of the atomic beam as well as isotope selectivity.

  11. Anisotropy modeling of terahertz metamaterials: polarization dependent resonance manipulation by meta-atom cluster.

    Science.gov (United States)

    Jung, Hyunseung; In, Chihun; Choi, Hyunyong; Lee, Hojin

    2014-06-09

    Recently metamaterials have inspired worldwide researches due to their exotic properties in transmitting, reflecting, absorbing or refracting specific electromagnetic waves. Most metamaterials are known to have anisotropic properties, but existing anisotropy models are applicable only to a single meta-atom and its properties. Here we propose an anisotropy model for asymmetrical meta-atom clusters and their polarization dependency. The proposed anisotropic meta-atom clusters show a unique resonance property in which their frequencies can be altered for parallel polarization, but fixed to a single resonance frequency for perpendicular polarization. The proposed anisotropic metamaterials are expected to pave the way for novel optical systems.

  12. A symmetry adapted approach to vibrational excitations in atomic clusters

    CERN Document Server

    Frank, A I; Bijker, R; Lemus, R; Pérez-Bernal, F

    1998-01-01

    An algebraic method especially suited to describe strongly anharmonic vibrational spectra in molecules may be an appropriate framework to study vibrational spectra of Na$^+_n$ clusters, where nearly flat potential energy surfaces and the appearance of close lying isomers have been reported. As an illustration we describe the model and apply it to the Be$_4$, H$_3^+$, Be$_3$ and Na$_3^+$ clusters.

  13. Three-dimensional simulation on explosions of hydrogen atomic clusters irradiated by an intense femtosecond laser pulse

    Institute of Scientific and Technical Information of China (English)

    Xia Yong; Liu Jian-Sheng; Ni Guo-Quan; Xu Zhi-Zhan

    2004-01-01

    Using classic particle dynamics simulations, the interaction process between an intense femtosecond laser pulse and icosahedral hydrogen atomic clusters H13, H55 and H147 has been studied. It is revealed that with increasing number of atoms in the cluster, the kinetic energy of ions generated in the Coulomb explosion of the ionized hydrogen clusters increases. The expansion process of the clusters after laser irradiation has also been examined, showing that the expansion scale decreases with increasing cluster size.

  14. Self-diffusion dynamic behavior of atomic clusters on Re(0 0 0 1) surface

    Energy Technology Data Exchange (ETDEWEB)

    Liu Fusheng [Department of Applied Physics, Hunan University, Changsha 410082 (China); Hu Wangyu, E-mail: wangyuhu2001cn@yahoo.com.cn [Department of Applied Physics, Hunan University, Changsha 410082 (China); Deng Huiqiu; Luo Wenhua; Xiao Shifang [Department of Applied Physics, Hunan University, Changsha 410082 (China); Yang Jianyu [Department of Maths and Physics, Hunan Institute of Engineering, Xiangtan 411104 (China)

    2009-08-15

    Using molecular dynamics simulations and a modified analytic embedded atom potential, the self-diffusion dynamics of rhenium atomic clusters up to seven atoms on Re(0 0 0 1) surface have been studied in the temperature ranges from 600 K to 1900 K. The simulation time varies from 20 ns to 200 ns according to the cluster sizes and the temperature. The heptamer and trimer are more stable comparing to other neighboring non-compact clusters. The diffusion coefficients of clusters are derived from the mean square displacement of cluster's mass-center, and diffusion prefactors D{sub 0} and activation energies E{sub a} are derived from the Arrhenius relation. It is found that the Arrhenius relation of the adatom can be divided into two parts at different temperature range. The activation energy of clusters increases with the increasing of the atom number in clusters. The prefactor of the heptamer is 2-3 orders of magnitude higher than a usual prefactor because of a large number of nonequivalent diffusion processes. The trimer and heptamer are the nuclei at different temperature range according to the nucleation theory.

  15. Cluster Fusion: Face-Fused Nine-Atom Deltahedral Clusters in [Sn14 Ni(CO)](4.).

    Science.gov (United States)

    Perla, Luis G; Sevov, Slavi C

    2016-06-01

    The title anion was synthesized by heating dimethylformamide (DMF) solution of the known Ni-centered and Ni(CO)-capped tin clusters [Ni@Sn9 Ni(CO)](3-) . The new anion represents the first example of face-fused nine-atom molecular clusters. The two clusters are identical elongated tricapped trigonal prisms of nido-[Sn8 Ni(CO)](6-) with nickel at one of the capping positions. They are fused along a triangular face adjacent to a trigonal prismatic base and made of two Sn and one Ni atoms. The new anion is structurally characterized by single-crystal X-ray diffraction in the compound (K[222-crypt])4 [Sn14 Ni(CO)]⋅DMF. Its presence in solution is corroborated by electrospray mass spectrometry.

  16. Kr atoms and their clustering in zeolite A

    CERN Document Server

    Lim, W T; Jung, K J; Heo, N H

    2001-01-01

    The positions of Kr atoms encapsulated in the molecular-dimensioned cavities of fully dehydrated zeolite A of unit-cell composition Cs sub 3 Na sub 8 HSi sub 1 sub 2 Al sub 1 sub 2 O sub 4 sub 8 (Cs sub 3 -A) have been determined. Cs sub 3 -A was exposed to 1025 atm of krypton gas at 400 .deg. C for four days, followed by cooling at pressure to encapsulate Kr atoms. The resulting crystal structure of Cs sub 3 -A(6Kr) (a=12.247(2) A, R sub 1 =0.078, and R sub 2 =0.085) has been determined by single-crystal X-ray diffraction techniques in the cubic space group Pm3m at 21(1) .deg. C and 1 atm. In the crystal structure of Cs sub 3 -A(6Kr), six Kr atoms per unit cell are distributed over three crystallographically distinct positions: each unit cell contains one Kr atom at Kr(1) on a threefold axis in the sodalite unit, three at Kr(2) opposite four-rings in the large cavity , and two at Kr(3) on threefold axes in the large cavity . Relatively strong interactions of Kr atoms at Kr(1) and Kr(3) with Na sup + ions of ...

  17. M atom (M = Cu, Ag and Au) interaction with Ag and Au substrates: a first-principles study using cluster and slab models.

    Science.gov (United States)

    Nigam, Sandeep; Majumder, Chiranjib

    2010-11-03

    Using state-of-the-art first-principles calculations we report the interaction of M atoms (M = Cu, Ag and Au) with small Ag(n), Au(n) clusters (n = 3 and 6) and periodic Ag(111) and Au(111) surfaces. All calculations were performed using the plane wave pseudo-potential approach under the spin polarized version of the generalized gradient approximation scheme. The result shows that the equilibrium geometry of all MAg(3) and MAu(3) clusters favor a planar rhombus structure. From the charge distribution analysis of MAg(n)/MAu(n) clusters it is found that, while Cu and Ag donates electronic charge towards the host clusters, the Au atom acts as an acceptor, thus creating charge polarization in the system. The difference in orbital decomposed charges before and after the M interaction reveals that enhanced s-d hybridization is responsible for keeping the MAu(6) cluster planar, and increased p-orbital participation induces three-dimensional configurations in MAg(6) clusters. The optimization of M atom deposition on the Ag(111) and Au(111) surfaces shows that M atoms prefer to adsorb on the threefold fcc site over other well-defined sites. From the orbital decomposed charge analysis it is inferred that, although there is significant difference in the absolute magnitude of the interaction energy between M atoms and the Ag or Au substrates, the nature of chemical bonding is similar for the finite size clusters as well as in slab models.

  18. MD simulation of atomic displacement cascades near chromium-rich clusters in FeCr alloy

    Energy Technology Data Exchange (ETDEWEB)

    Tikhonchev, M., E-mail: tikhonchev@sv.ulsu.ru [Ulyanovsk State University, Research Institute of Technology, 42 Leo Tolstoy St., 432970 Ulyanovsk (Russian Federation); Svetukhin, V. [Ulyanovsk State University, Research Institute of Technology, 42 Leo Tolstoy St., 432970 Ulyanovsk (Russian Federation); Gaganidze, E. [Karlsruhe Institute of Technology, Institute for Applied Materials, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Karlsruhe (Germany)

    2013-11-15

    The paper reports simulation of cascades in Fe–9 at.%Cr binary alloy containing chromium-rich clusters. The simulation is performed by the molecular dynamics method at the initial temperature of 300 K and primary knock-on atom energy of 15 and 20 keV. Spherical clusters containing 95 at.% of Cr with diameter of 1–5 nm have been considered. The properties of cascade evolution in the presence of chromium-rich cluster are studied. It is shown that these clusters tend to dissolve in collision cascades. However, clusters with diameter of ⩾3 nm exhibit only slight modifications and can be considered stable. Parameters of small (1–2 nm) clusters can change significantly and, in some cases, a 1 nm cluster can be totally dissolved.

  19. Quantum Cloning of an Unknown 2-Atom State via Entangled Cluster States

    Science.gov (United States)

    Yu, L.-z.; Zhong, F.

    2016-06-01

    This paper presented a scheme for cloning a 2-atom state in the QED cavity with the help of Victor who is the state's preparer. The cloning scheme has two steps. In the first step, the scheme requires probabilistic teleportation of a 2-atom state that is unknown in advance, and uses a 4-atom cluster state as quantum channel. In the second step, perfect copies of the 2-atom entangled state may be realized with the assistance of Victor. The finding is that our scheme has two outstanding advantages: it is not sensitive to the cavity decay, and Bell state is easy to identify.

  20. Ab initio calculations and modelling of atomic cluster structure

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Lyalin, Andrey G.; Greiner, Walter

    2004-01-01

    The optimized structure and electronic properties of small sodium and magnesium clusters have been investigated using it ab initio theoretical methods based on density-functional theory and post-Hartree-Fock many-body perturbation theory accounting for all electrons in the system. A new theoretical...

  1. Cluster analysis in phenotyping a Portuguese population.

    Science.gov (United States)

    Loureiro, C C; Sa-Couto, P; Todo-Bom, A; Bousquet, J

    2015-09-03

    Unbiased cluster analysis using clinical parameters has identified asthma phenotypes. Adding inflammatory biomarkers to this analysis provided a better insight into the disease mechanisms. This approach has not yet been applied to asthmatic Portuguese patients. To identify phenotypes of asthma using cluster analysis in a Portuguese asthmatic population treated in secondary medical care. Consecutive patients with asthma were recruited from the outpatient clinic. Patients were optimally treated according to GINA guidelines and enrolled in the study. Procedures were performed according to a standard evaluation of asthma. Phenotypes were identified by cluster analysis using Ward's clustering method. Of the 72 patients enrolled, 57 had full data and were included for cluster analysis. Distribution was set in 5 clusters described as follows: cluster (C) 1, early onset mild allergic asthma; C2, moderate allergic asthma, with long evolution, female prevalence and mixed inflammation; C3, allergic brittle asthma in young females with early disease onset and no evidence of inflammation; C4, severe asthma in obese females with late disease onset, highly symptomatic despite low Th2 inflammation; C5, severe asthma with chronic airflow obstruction, late disease onset and eosinophilic inflammation. In our study population, the identified clusters were mainly coincident with other larger-scale cluster analysis. Variables such as age at disease onset, obesity, lung function, FeNO (Th2 biomarker) and disease severity were important for cluster distinction. Copyright © 2015. Published by Elsevier España, S.L.U.

  2. Optimum Metallic-Bond Scheme: A Quantitative Analysis of Mass Spectra of Sodium Clusters

    Institute of Scientific and Technical Information of China (English)

    苏长荣; 李家明

    2001-01-01

    Based on the results of the optimum metallic-bond scheme for sodium clusters, we present a quantitative analysis of the detailed features of the mass spectra of sodium clusters. We find that, in the generation of sodium clusters with various abundances, the quasi-steady processes through adding or losing a sodium atom dominate. The quasi-steady processes through adding or losing a sodium dimer are also important to understand the detailed features of mass spectra for small clusters.

  3. The applicability and effectiveness of cluster analysis

    Science.gov (United States)

    Ingram, D. S.; Actkinson, A. L.

    1973-01-01

    An insight into the characteristics which determine the performance of a clustering algorithm is presented. In order for the techniques which are examined to accurately cluster data, two conditions must be simultaneously satisfied. First the data must have a particular structure, and second the parameters chosen for the clustering algorithm must be correct. By examining the structure of the data from the Cl flight line, it is clear that no single set of parameters can be used to accurately cluster all the different crops. The effectiveness of either a noniterative or iterative clustering algorithm to accurately cluster data representative of the Cl flight line is questionable. Thus extensive a prior knowledge is required in order to use cluster analysis in its present form for applications like assisting in the definition of field boundaries and evaluating the homogeneity of a field. New or modified techniques are necessary for clustering to be a reliable tool.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ditmire, Todd [Univ. of Texas, Austin, TX (United States). Center for High Energy Density Science

    2016-10-12

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

  5. Fragmentation of neutral carbon clusters formed by high velocity atomic collision; Fragmentation d'agregats de carbone neutres formes par collision atomique a haute vitesse

    Energy Technology Data Exchange (ETDEWEB)

    Martinet, G

    2004-05-01

    The aim of this work is to understand the fragmentation of small neutral carbon clusters formed by high velocity atomic collision on atomic gas. In this experiment, the main way of deexcitation of neutral clusters formed by electron capture with ionic species is the fragmentation. To measure the channels of fragmentation, a new detection tool based on shape analysis of current pulse delivered by semiconductor detectors has been developed. For the first time, all branching ratios of neutral carbon clusters are measured in an unambiguous way for clusters size up to 10 atoms. The measurements have been compared to a statistical model in microcanonical ensemble (Microcanonical Metropolis Monte Carlo). In this model, various structural properties of carbon clusters are required. These data have been calculated with Density Functional Theory (DFT-B3LYP) to find the geometries of the clusters and then with Coupled Clusters (CCSD(T)) formalism to obtain dissociation energies and other quantities needed to compute fragmentation calculations. The experimental branching ratios have been compared to the fragmentation model which has allowed to find an energy distribution deposited in the collision. Finally, specific cluster effect has been found namely a large population of excited states. This behaviour is completely different of the atomic carbon case for which the electron capture in the ground states predominates. (author)

  6. Coupled-cluster calculations of properties of Boron atom as a monovalent system

    CERN Document Server

    Gharibnejad, H

    2015-01-01

    We present relativistic coupled-cluster (CC) calculations of energies, magnetic-dipole hyperfine constants, and electric-dipole transition amplitudes for low-lying states of atomic boron. The trivalent boron atom is computationally treated as a monovalent system. We explore performance of the CC method at various approximations. Our most complete treatment involves singles, doubles and the leading valence triples. The calculations are done using several approximations in the coupled-cluster (CC) method. The results are within 0.2-0.4% of the energy benchmarks. The hyperfine constants are reproduced with 1-2% accuracy.

  7. Mixed monolayer protected gold atom-oxide cluster synthesis and characterization

    Science.gov (United States)

    Nambiar, Sindhu R.; Aneesh, Padamadathil K.; Sukumar, Chinthu; Rao, Talasila P.

    2012-06-01

    Small atomic gold clusters in solution, Aun, stabilized by cetyl trimethylammonium bromide (CTAB) and cysteine, have been synthesized potentiodynamically in quiescent aqueous solutions. The electrodissolution of gold to gold ions during an anodic scan and subsequent cluster formation during a cathodic scan in underpotential (UPDD) and overpotential dissolution-deposition (OPDD) regions were studied. The experimental potentiodynamic I-E profiles and chronoamperometric i-t transients are fit into reported theoretical models of adsorption and electrocrystallization. The plausible application of clusters/cluster film to cysteine sensing based on fluorescence quenching and square wave stripping voltammetry is demonstrated.Small atomic gold clusters in solution, Aun, stabilized by cetyl trimethylammonium bromide (CTAB) and cysteine, have been synthesized potentiodynamically in quiescent aqueous solutions. The electrodissolution of gold to gold ions during an anodic scan and subsequent cluster formation during a cathodic scan in underpotential (UPDD) and overpotential dissolution-deposition (OPDD) regions were studied. The experimental potentiodynamic I-E profiles and chronoamperometric i-t transients are fit into reported theoretical models of adsorption and electrocrystallization. The plausible application of clusters/cluster film to cysteine sensing based on fluorescence quenching and square wave stripping voltammetry is demonstrated. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr30446e

  8. Atomic structure prediction of nanostructures, clusters and surfaces

    CERN Document Server

    Ciobanu, Cristian V; Ho, Kai-Ming

    2013-01-01

    This work fills the gap for a comprehensive reference conveying the developments in global optimization of atomic structures using genetic algorithms. Over the last few decades, such algorithms based on mimicking the processes of natural evolution have made their way from computer science disciplines to solid states physics and chemistry, where they have demonstrated their versatility and predictive power for many materials. Following an introduction and historical perspective, the text moves on to provide an in-depth description of the algorithm before describing its applications to crystal s

  9. Quantum chemical calculation of the equilibrium structures of small metal atom clusters

    Science.gov (United States)

    Kahn, L. R.

    1982-01-01

    Metal atom clusters are studied based on the application of ab initio quantum mechanical approaches. Because these large 'molecular' systems pose special practical computational problems in the application of the quantum mechanical methods, there is a special need to find simplifying techniques that do not compromise the reliability of the calculations. Research is therefore directed towards various aspects of the implementation of the effective core potential technique for the removal of the metal atom core electrons from the calculations.

  10. Time-dependent coupled-cluster method for atomic nuclei

    CERN Document Server

    Pigg, D A; Nam, H; Papenbrock, T

    2012-01-01

    We study time-dependent coupled-cluster theory in the framework of nuclear physics. Based on Kvaal's bi-variational formulation of this method [S. Kvaal, arXiv:1201.5548], we explicitly demonstrate that observables that commute with the Hamiltonian are conserved under time evolution. We explore the role of the energy and of the similarity-transformed Hamiltonian under real and imaginary time evolution and relate the latter to similarity renormalization group transformations. Proof-of-principle computations of He-4 and O-16 in small model spaces, and computations of the Lipkin model illustrate the capabilities of the method.

  11. The Ultraviolet Photoelectron Spectroscopy of Group IV 2-15 Atom Cluster Anions

    Science.gov (United States)

    Craycraft, Mary Jo.

    The ability to map valence electronic structure is the result of a recent advance in photoelectron spectroscopy; its union with cluster molecular beam technology. The task of interpreting the spectra is hampered by a serious lack of understanding of cluster electronic structure in general. Recently progress has been made in finding models for single s valence electron systems. Alkali and noble metal clusters can be treated as free electron systems and simple interatomic potentials can be used with rare gas clusters. Neither a smeared jellium background nor a simple interatomic potential is adequate to describe covalent bonding, however. The isoelectronic Group IV members have a valence configuration of ns^2 np^2. All readily form clusters, and the elements differ in both their atomic and bulk properties; thus the series provides an ideal system for studying electronic structure. The mass selected cluster ion beam is crossed with a beam (6.42 or 7.9eV) and the resulting photodetached electrons collected with the aid of judiciously arranged magnetic fields. The spectra are found to be unique for each size cluster. Some spectra show a significant gap between the two lowest binding energy features, indicating that the neutral cluster is a closed shell species. The clusters with such gaps are minima in a plot of EA as a function of cluster size. The UPS also vary with the cluster composition. Carbon is unique; an even -odd alternation in electron affinities switches from odd minima for clusters containing less than ten atoms to odd maxima for larger clusters. This corresponds with an alternation in singlet and triplet ground states and a switch from chain to ring structures previously predicted by theory (K. S. Pitzer, E. Clementi, J. Amer. Chem. Soc. 81 4477 (1958) and R. Hoffmann, Tetrahedron 22 521 (1965)). The spectra of the remaining group IV members are remarkably similar to each other for clusters of up to ten atoms, as is the trend in the electron affinities as

  12. 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.

  13. Structure and energetics of Ni clusters with up to 150 atoms

    CERN Document Server

    Grigoryan, V G

    2003-01-01

    We present a method (the Aufbau/Abbau method) for optimizing the structure of a whole series of clusters without making any assumptions on the structure. Subsequently, the method is combined with the embedded-atom method in determining the structure of the two energetically lowest isomers of Ni_N clusters with N up to 150. Finally, various analytical descriptors are introduced that are used in studying the overall shape of the clusters, their structure and stability, and possible growth and dissociation processes.

  14. Metal-carbon clusters: The origin of the delayed atomic ion

    Science.gov (United States)

    Davis, K. M.; Peppernick, S. J.; Castleman, A. W.

    2006-04-01

    Studies of the emission of electrons from excited metal-carbon cluster systems that include the Met-Car (M8C12, where M is Ti, Zr, and V) also have revealed the evolution of a delayed atomic ion. The source of the delayed atomic ion, which involves the emission of ionized atoms on the microsecond time scale, is the focus of this investigation. By studying the delayed ionization of mixed zirconium and titanium carbon complexes produced in a laser vaporization source coupled to a time-of-flight mass spectrometer, for the first time both the zirconium and titanium delayed atomic ions were observed to be emitted in the same experiment. These studies allowed a determination that the source of the delayed atomic ion is an excited metal dicarbide. A plausible mechanism involving the excitation of a high Rydberg state of the metal dicarbide prior to an excited ion pair separation is proposed.

  15. Atomic, electronic, and magnetic properties of bimetallic ZrCo clusters: A first-principles study

    Science.gov (United States)

    Chattaraj, D.; Bhattacharya, Saswata; Dash, Smruti; Majumder, C.

    2016-09-01

    Here, we report the atomic, electronic, and magnetic structures of small ZrmCon (m + n = 2, 4, 6, and 8) alloy clusters based on spin-polarized density functional theory under the plane wave based pseudo-potential approach. The ground state geometry and other low-lying stable isomers of each cluster have been identified using the cascade genetic algorithm scheme. On the basis of the relative energy, it is found that Zr2Co2 (for tetramer), Zr3Co3 (for hexamer), and Zr4Co4 (for octamer) are the most stable isomers than others. In order to underscore the hydrogen storage capacity of these small clusters, the hydrogen adsorption on the stable ZrmCon (m + n = 2, 4, 6, and 8) clusters has also been studied. The electronic structures of ZrmCon clusters with and without adsorbed hydrogen are described in terms of density of states spectra and charge density contours.

  16. Exchange-correlation interaction and AO-hybridization of alkali-metal atomic clusters.

    Science.gov (United States)

    Liu, Xuan; Ito, Haruhiko; Torikai, Eiko

    2013-09-19

    The structure of alkali-metal atomic clusters is optimized with B3P86 hybrid functional for the highest spin state as well as with B3LYP hybrid functional for the lowest spin state. A dramatic change from plane to solid occurs in the highest spin state when the number of constituent atoms is four. The binding, exchange, and correlation energies are evaluated for both the highest and lowest spin states. Next, we explore the dependence of the exchange and correlation energies on the binding energy. The exchange energy contributes to the formation of the highest spin clusters, whereas the correlation energy contributes to the formation of the lowest spin clusters. The highest spin clusters are most stable when the exchange energy is a minimum. Then, to see why the ferromagnetic bond among spin-aligned identical atoms arises against Pauli exclusion principle, we estimate the mixing ratio of p orbitals in molecular orbitals. The s-p hybridization increases the binding energy in absolute value due to the extensive overlap of molecular orbitals and leads to generation of the highest spin clusters.

  17. Robust cluster analysis and variable selection

    CERN Document Server

    Ritter, Gunter

    2014-01-01

    Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50 years. The author focuses on the robust clustering methods he found to be the most useful on simulated data and real-time applications. The book provides clear guidance for the varying needs of bot

  18. ASteCA - Automated Stellar Cluster Analysis

    CERN Document Server

    Perren, Gabriel I; Piatti, Andrés E

    2014-01-01

    We present ASteCA (Automated Stellar Cluster Analysis), a suit of tools designed to fully automatize the standard tests applied on stellar clusters to determine their basic parameters. The set of functions included in the code make use of positional and photometric data to obtain precise and objective values for a given cluster's center coordinates, radius, luminosity function and integrated color magnitude, as well as characterizing through a statistical estimator its probability of being a true physical cluster rather than a random overdensity of field stars. ASteCA incorporates a Bayesian field star decontamination algorithm capable of assigning membership probabilities using photometric data alone. An isochrone fitting process based on the generation of synthetic clusters from theoretical isochrones and selection of the best fit through a genetic algorithm is also present, which allows ASteCA to provide accurate estimates for a cluster's metallicity, age, extinction and distance values along with its unce...

  19. Cluster analysis for computer workload evaluation

    CERN Document Server

    Landau, K

    1976-01-01

    An introduction to computer workload analysis is given, showing its range of application in computer centre management, system and application programming. Cluster methods are discussed which can be used in conjunction with workload data and cluster algorithms are adapted to the specific set problem. Several samples of CDC 7600- accounting-data-collected at CERN, the European Organization for Nuclear Research-underwent a cluster analysis to determine job groups. The conclusions from resource usage of typical job groups in relation to computer workload analysis are discussed. (17 refs).

  20. Ab initio random structure search for 13-atom clusters of fcc elements.

    Science.gov (United States)

    Chou, J P; Hsing, C R; Wei, C M; Cheng, C; Chang, C M

    2013-03-27

    The 13-atom metal clusters of fcc elements (Al, Rh, Ir, Ni, Pd, Pt, Cu, Ag, Au) were studied by density functional theory calculations. The global minima were searched for by the ab initio random structure searching method. In addition to some new lowest-energy structures for Pd13 and Au13, we found that the effective coordination numbers of the lowest-energy clusters would increase with the ratio of the dimer-to-bulk bond length. This correlation, together with the electronic structures of the lowest-energy clusters, divides the 13-atom clusters of these fcc elements into two groups (except for Au13, which prefers a two-dimensional structure due to the relativistic effect). Compact-like clusters that are composed exclusively of triangular motifs are preferred for elements without d-electrons (Al) or with (nearly) filled d-band electrons (Ni, Pd, Cu, Ag). Non-compact clusters composed mainly of square motifs connected by some triangular motifs (Rh, Ir, Pt) are favored for elements with unfilled d-band electrons.

  1. Cluster analysis of multiple planetary flow regimes

    Science.gov (United States)

    Mo, Kingtse; Ghil, Michael

    1988-01-01

    A modified cluster analysis method developed for the classification of quasi-stationary events into a few planetary flow regimes and for the examination of transitions between these regimes is described. The method was applied first to a simple deterministic model and then to a 500-mbar data set for Northern Hemisphere (NH), for which cluster analysis was carried out in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters were found in the low-frequency band of more than 10 days, while transient clusters were found in the band-pass frequency window between 2.5 and 6 days. In the low-frequency band, three pairs of clusters determined EOFs 1, 2, and 3, respectively; they exhibited well-known regional features, such as blocking, the Pacific/North American pattern, and wave trains. Both model and low-pass data exhibited strong bimodality.

  2. [Cluster analysis and its application].

    Science.gov (United States)

    Půlpán, Zdenĕk

    2002-01-01

    The study exploits knowledge-oriented and context-based modification of well-known algorithms of (fuzzy) clustering. The role of fuzzy sets is inherently inclined towards coping with linguistic domain knowledge also. We try hard to obtain from rich diverse data and knowledge new information about enviroment that is being explored.

  3. Cluster Analysis of Adolescent Blogs

    Science.gov (United States)

    Liu, Eric Zhi-Feng; Lin, Chun-Hung; Chen, Feng-Yi; Peng, Ping-Chuan

    2012-01-01

    Emerging web applications and networking systems such as blogs have become popular, and they offer unique opportunities and environments for learners, especially for adolescent learners. This study attempts to explore the writing styles and genres used by adolescents in their blogs by employing content, factor, and cluster analyses. Factor…

  4. Atom probe analysis of titanium hydride precipitates.

    Science.gov (United States)

    Takahashi, J; Kawakami, K; Otsuka, H; Fujii, H

    2009-04-01

    It is expected that the three-dimensional atom probe (3DAP) will be used as a tool to visualize the atomic scale of hydrogen atoms in steel is expected, due to its high spatial resolution and very low detection limit. In this paper, the first 3DAP analysis of titanium hydride precipitates in metal titanium is reported in terms of the quantitative detection of hydrogen. FIB fabrication techniques using the lift-out method have enabled the production of needle tips of hydride precipitates, of several tens of microns in size, within a titanium matrix. The hydrogen concentration estimated from 3DAP analysis was slightly smaller than that of the hydride phase predicted from the phase diagram. We discuss the origin of the difference between the experimental and predicted values and the performance of 3DAP for the quantitative detection of hydrogen.

  5. Atom-by-atom analysis of global downhill protein folding

    Science.gov (United States)

    Sadqi, Mourad; Fushman, David; Muñoz, Victor

    2006-07-01

    Protein folding is an inherently complex process involving coordination of the intricate networks of weak interactions that stabilize native three-dimensional structures. In the conventional paradigm, simple protein structures are assumed to fold in an all-or-none process that is inaccessible to experiment. Existing experimental methods therefore probe folding mechanisms indirectly. A widely used approach interprets changes in protein stability and/or folding kinetics, induced by engineered mutations, in terms of the structure of the native protein. In addition to limitations in connecting energetics with structure, mutational methods have significant experimental uncertainties and are unable to map complex networks of interactions. In contrast, analytical theory predicts small barriers to folding and the possibility of downhill folding. These theoretical predictions have been confirmed experimentally in recent years, including the observation of global downhill folding. However, a key remaining question is whether downhill folding can indeed lead to the high-resolution analysis of protein folding processes. Here we show, with the use of nuclear magnetic resonance (NMR), that the downhill protein BBL from Escherichia coli unfolds atom by atom starting from a defined three-dimensional structure. Thermal unfolding data on 158 backbone and side-chain protons out of a total of 204 provide a detailed view of the structural events during folding. This view confirms the statistical nature of folding, and exposes the interplay between hydrogen bonding, hydrophobic forces, backbone conformation and side-chain entropy. From the data we also obtain a map of the interaction network in this protein, which reveals the source of folding cooperativity. Our approach can be extended to other proteins with marginal barriers (less than 3RT), providing a new tool for the study of protein folding.

  6. Formation of bimetallic clusters in superfluid helium nanodroplets analysed by atomic resolution electron tomography

    Science.gov (United States)

    Haberfehlner, Georg; Thaler, Philipp; Knez, Daniel; Volk, Alexander; Hofer, Ferdinand; Ernst, Wolfgang E.; Kothleitner, Gerald

    2015-10-01

    Structure, shape and composition are the basic parameters responsible for properties of nanoscale materials, distinguishing them from their bulk counterparts. To reveal these in three dimensions at the nanoscale, electron tomography is a powerful tool. Advancing electron tomography to atomic resolution in an aberration-corrected transmission electron microscope remains challenging and has been demonstrated only a few times using strong constraints or extensive filtering. Here we demonstrate atomic resolution electron tomography on silver/gold core/shell nanoclusters grown in superfluid helium nanodroplets. We reveal morphology and composition of a cluster identifying gold- and silver-rich regions in three dimensions and we estimate atomic positions without using any prior information and with minimal filtering. The ability to get full three-dimensional information down to the atomic scale allows understanding the growth and deposition process of the nanoclusters and demonstrates an approach that may be generally applicable to all types of nanoscale materials.

  7. Identifying low-coordinated atoms on oxide-supported Au clusters

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Xiao; Nilius, Niklas; Freund, Hans-Joachim [Fritz-Haber-Institut der MPG, Faradayweg 4-6, D-14195 Berlin (Germany); Koskinen, Pekka; Haekkinen, Hannu [Department of Physics, University of Jyvaeskylae, Finland (Finland)

    2010-07-01

    The outstanding chemical properties of small metal particles are partly governed by the perimeter atoms that are located at the boundary to the oxide support. Those edge and corner sites are unique due to their low coordination, a peculiar electronic structure and charge state. We have employed STM and DFT to characterize the perimeter atoms around planar Au clusters grown on a MgO/Ag(001) thin film. The atoms exhibit an enhanced state density with respect to the island center in conductance spectra taken around the Fermi level. Furthermore, they carry extra electrons resulting from a charge transfer from the MgO-Ag interface into the Au islands. Both effects render the perimeter atoms highly attractive for binding molecules, as demonstrated via CO adsorption experiments on the system.

  8. Cluster Analysis of the Malaysian Hipposideros

    Science.gov (United States)

    Sazali, Siti Nurlydia; Laman, Charlie J.; Abdullah, M. T.

    2008-01-01

    A preliminary study on the morphometric variations among species in the genus Hipposideros was conducted using voucher specimens from the Universiti Malaysia Sarawak (UNIMAS) Zoological Museum and the Department of Wildlife and National Park (DWNP) Kuala Lumpur. A total of 24 individuals from six species of this genus were morphologically studied where all related measurements of body, skull and dental were measured and recorded. The statistical data subjected to the cluster analysis shows that the genus Hipposideros is divided into two major clusters where each species was clearly separated. The cluster analysis among Hipposideros species is useful for aiding in species identification.

  9. Using cluster analysis to explore survey data.

    Science.gov (United States)

    Spencer, Llinos; Roberts, Gwerfyl; Irvine, Fiona; Jones, Peter; Baker, Colin

    2007-01-01

    Llinos Haf Spencer reports on the use of the cluster analysis statistical technique in nursing research and uses data from the Welsh Language Awareness in Healthcare Provision in Wales survey as an exemplar She concludes that cluster analysis is a valuable tool to tease out patterns in data that are not initially evident in bivariate analyses and thus should be considered as a viable option for nursing research.

  10. Nursing home care quality: a cluster analysis.

    Science.gov (United States)

    Grøndahl, Vigdis Abrahamsen; Fagerli, Liv Berit

    2017-02-13

    Purpose The purpose of this paper is to explore potential differences in how nursing home residents rate care quality and to explore cluster characteristics. Design/methodology/approach A cross-sectional design was used, with one questionnaire including questions from quality from patients' perspective and Big Five personality traits, together with questions related to socio-demographic aspects and health condition. Residents ( n=103) from four Norwegian nursing homes participated (74.1 per cent response rate). Hierarchical cluster analysis identified clusters with respect to care quality perceptions. χ(2) tests and one-way between-groups ANOVA were performed to characterise the clusters ( pclusters were identified; Cluster 1 residents (28.2 per cent) had the best care quality perceptions and Cluster 2 (67.0 per cent) had the worst perceptions. The clusters were statistically significant and characterised by personal-related conditions: gender, psychological well-being, preferences, admission, satisfaction with staying in the nursing home, emotional stability and agreeableness, and by external objective care conditions: healthcare personnel and registered nurses. Research limitations/implications Residents assessed as having no cognitive impairments were included, thus excluding the largest group. By choosing questionnaire design and structured interviews, the number able to participate may increase. Practical implications Findings may provide healthcare personnel and managers with increased knowledge on which to develop strategies to improve specific care quality perceptions. Originality/value Cluster analysis can be an effective tool for differentiating between nursing homes residents' care quality perceptions.

  11. Cluster Analysis and Clinical Asthma Phenotypes

    Science.gov (United States)

    Shaw, Dominic E.; Berry, Michael A.; Thomas, Michael; Brightling, Christopher E.; Wardlaw, Andrew J.

    2014-01-01

    Rationale Heterogeneity in asthma expression is multidimensional, including variability in clinical, physiologic, and pathologic parameters. Classification requires consideration of these disparate domains in a unified model. Objectives To explore the application of a multivariate mathematical technique, k-means cluster analysis, for identifying distinct phenotypic groups. Methods We performed k-means cluster analysis in three independent asthma populations. Clusters of a population managed in primary care (n = 184) with predominantly mild to moderate disease, were compared with a refractory asthma population managed in secondary care (n = 187). We then compared differences in asthma outcomes (exacerbation frequency and change in corticosteroid dose at 12 mo) between clusters in a third population of 68 subjects with predominantly refractory asthma, clustered at entry into a randomized trial comparing a strategy of minimizing eosinophilic inflammation (inflammation-guided strategy) with standard care. Measurements and Main Results Two clusters (early-onset atopic and obese, noneosinophilic) were common to both asthma populations. Two clusters characterized by marked discordance between symptom expression and eosinophilic airway inflammation (early-onset symptom predominant and late-onset inflammation predominant) were specific to refractory asthma. Inflammation-guided management was superior for both discordant subgroups leading to a reduction in exacerbation frequency in the inflammation-predominant cluster (3.53 [SD, 1.18] vs. 0.38 [SD, 0.13] exacerbation/patient/yr, P = 0.002) and a dose reduction of inhaled corticosteroid in the symptom-predominant cluster (mean difference, 1,829 μg beclomethasone equivalent/d [95% confidence interval, 307–3,349 μg]; P = 0.02). Conclusions Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms. PMID:18480428

  12. Performance Analysis of Hierarchical Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    K.Ranjini

    2011-07-01

    Full Text Available Clustering is the classification of objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters, so that the data in each subset (ideally share some common trait - often proximity according to some defined distance measure. Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. This paper explains the implementation of agglomerative and divisive clustering algorithms applied on various types of data. The details of the victims of Tsunami in Thailand during the year 2004, was taken as the test data. Visual programming is used for implementation and running time of the algorithms using different linkages (agglomerative to different types of data are taken for analysis.

  13. A cluster expansion model for predicting activation barrier of atomic processes

    Energy Technology Data Exchange (ETDEWEB)

    Rehman, Tafizur; Jaipal, M. [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016 (India); Chatterjee, Abhijit, E-mail: achatter@iitk.ac.in [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016 (India); Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400 076 (India)

    2013-06-15

    We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.

  14. Generation of atomic Greenberger-Horne-Zeilinger states and cluster states through cavity-assisted interaction

    Institute of Scientific and Technical Information of China (English)

    Huang Xiu-Hua; Lin Xiu-Min; Lin Gong-Wei; Chen Zhi-Hua; Tang Yao-Xiang

    2008-01-01

    This paper proposes a scalable scheme to generate n-atom GHZ states and cluster states by using the basic building block, i.e., a weak coherent optical pulse |α) being reflected successively from a single-atom cavity. In the schemes,coherent state of light is used instead of single photon source, homodyne measurement on coherent light is done instead of single photon detection, and no need for individually addressing keeps the schemes easy to implement from the experimental point of view. The successful probabilities of our protocols approach unity in the ideal ease.

  15. Trapping of hydrogen atoms inside small beryllium clusters and their ions

    Science.gov (United States)

    Naumkin, F. Y.; Wales, D. J.

    2016-08-01

    Structure, stability and electronic properties are evaluated computationally for small Ben (n = 5-9) cluster cages accommodating atomic H inside and forming core-shell species. These parameters are predicted to vary significantly upon insertion of H, for ionic derivatives, and with the system size. In particular, the energy barrier for H-atom exit from the cage changes significantly for ions compared to the neutral counterparts. The corresponding effects predicted for cage assemblies suggest the possibility of efficient charge-control of hydrogen release. This, together with a high capacity for storing hydrogen in extended such assemblies might indicate a possible way towards feasible hydrogen-storage solutions.

  16. Investigation of energy thresholds of atomic and cluster sputtering of some elements under ion bombardment

    CERN Document Server

    Atabaev, B G; Lifanova, L F

    2002-01-01

    Threshold energies of sputtering of negative cluster ions from the Si(111) surface were measured at bombardment by Cs sup + , Rb sup + , and Na sup + ions with energy of 0.1-3.0 keV. These results are compared with the calculations of the similar thresholds by Bohdansky etc. formulas (3) for clusters Si sub n sup - and Cu sub n sup - with n=(1-5) and also for B, C, Al, Si, Fe, Cu atoms. Threshold energies of sputtering for the above elements were also estimated using the data from (5). Satisfactory agreement between the experimental and theoretical results was obtained. (author)

  17. Atomic and electronic structure of gold clusters: understanding flakes, cages and superatoms from simple concepts.

    Science.gov (United States)

    Häkkinen, Hannu

    2008-09-01

    Atomic structure and electronic structure are intimately interrelated properties of nanoclusters and nanoparticles, defining their stability, electronic, optical and chemical properties, in other words, their usability as potential components for nanoscale devices. This tutorial review attempts to describe the development in understanding the structures of bare and ligand-protected gold clusters over the past decade, based on selected density-functional-theory calculations. This review should be of interest both to newcomers in the field and to an interdisciplinary community of researchers working in synthesis, characterization and utilization of ligand-protected gold clusters.

  18. Clustering analysis of telecommunication customers

    Institute of Scientific and Technical Information of China (English)

    REN Hong; ZHENG Yan; WU Ye-rong

    2009-01-01

    In this article, a clustering method based on genetic algorithm (GA) for telecommunication customer subdivision is presented. First, the features of telecommunication customers (such as the calling behavior and consuming behavior) are extracted. Second, the similarities between the multidimensional feature vectors of telecommunication customers are computed and mapped as the distance between samples on a two-dimensional plane. Finally, the distances are adjusted to approximate the similarities gradually by GA. One advantage of this method is the independent distribution of the sample space. The experiments demonstrate the feasibility of the proposed method.

  19. 2nd International Symposium "Atomic Cluster Collisions : Structure and Dynamics from the Nuclear to the Biological Scale"

    CERN Document Server

    Solov'yov, Andrey; ISACC 2007; Latest advances in atomic cluster collisions

    2008-01-01

    This book presents a 'snapshot' of the most recent and significant advances in the field of cluster physics. It is a comprehensive review based on contributions by the participants of the 2nd International Symposium on Atomic Cluster Collisions (ISACC 2007) held in July 19-23, 2007 at GSI, Darmstadt, Germany. The purpose of the Symposium is to promote the growth and exchange of scientific information on the structure and properties of nuclear, atomic, molecular, biological and complex cluster systems studied by means of photonic, electronic, heavy particle and atomic collisions. Particular attention is devoted to dynamic phenomena, many-body effects taking place in cluster systems of a different nature - these include problems of fusion and fission, fragmentation, collective electron excitations, phase transitions, etc.Both the experimental and theoretical aspects of cluster physics, uniquely placed between nuclear physics on the one hand and atomic, molecular and solid state physics on the other, are discuss...

  20. Bayesian data analysis tools for atomic physics

    CERN Document Server

    Trassinelli, Martino

    2016-01-01

    We present an introduction to some concepts of Bayesian data analysis in the context of atomic physics. Starting from basic rules of probability, we present the Bayes' theorem and its applications. In particular we discuss about how to calculate simple and joint probability distributions and the Bayesian evidence, a model dependent quantity that allows to assign probabilities to different hypotheses from the analysis of a same data set. To give some practical examples, these methods are applied to two concrete cases. In the first example, the presence or not of a satellite line in an atomic spectrum is investigated. In the second example, we determine the most probable model among a set of possible profiles from the analysis of a statistically poor spectrum. We show also how to calculate the probability distribution of the main spectral component without having to determine uniquely the spectrum modeling. For these two studies, we implement the program Nested fit to calculate the different probability distrib...

  1. Electric dipole polarizability of alkaline-Earth-metal atoms from perturbed relativistic coupled-cluster theory with triples

    CERN Document Server

    Chattopadhyay, S; Angom, D

    2014-01-01

    The perturbed relativistic coupled-cluster (PRCC) theory is applied to calculate the electric dipole polarizabilities of alkaline Earth metal atoms. The Dirac-Coulomb-Breit atomic Hamiltonian is used and we include the triple excitations in the relativistic coupled-cluster (RCC) theory. The theoretical issues related to the triple excitation cluster operators are described in detail and we also provide details on the computational implementation. The PRCC theory results are in good agreement with the experimental and previous theoretical results. We, then, highlight the importance of considering the Breit interaction for alkaline Earth metal atoms.

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

    Science.gov (United States)

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

    2014-10-01

    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 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 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, W.H.; Zhang, C.G.; Li, Y.G. [Key Laboratory for Materials Physics, Institute of Solid State Physics, Chinese Academy of Sciences, Hefei 230031 (China); Zeng, Z., E-mail: zzeng@theory.issp.ac.cn [Key Laboratory for Materials Physics, Institute of Solid State Physics, Chinese Academy of Sciences, Hefei 230031 (China); Department of Physics, University of Science and Technology of China, Hefei 230026 (China)

    2014-10-15

    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.

  4. Filtering Genes for Cluster and Network Analysis

    Directory of Open Access Journals (Sweden)

    Parkhomenko Elena

    2009-06-01

    Full Text Available Abstract Background Prior to cluster analysis or genetic network analysis it is customary to filter, or remove genes considered to be irrelevant from the set of genes to be analyzed. Often genes whose variation across samples is less than an arbitrary threshold value are deleted. This can improve interpretability and reduce bias. Results This paper introduces modular models for representing network structure in order to study the relative effects of different filtering methods. We show that cluster analysis and principal components are strongly affected by filtering. Filtering methods intended specifically for cluster and network analysis are introduced and compared by simulating modular networks with known statistical properties. To study more realistic situations, we analyze simulated "real" data based on well-characterized E. coli and S. cerevisiae regulatory networks. Conclusion The methods introduced apply very generally, to any similarity matrix describing gene expression. One of the proposed methods, SUMCOV, performed well for all models simulated.

  5. Comparative atomic charges on Na{sup +}-(H{sub 2}O){sub n} (n + 1 - 6) clusters

    Energy Technology Data Exchange (ETDEWEB)

    Uddin, Nizam; Choi, Cheol Ho [Dept. of Chemistry and Green-Nano Materials Research Center, College of Natural Sciences, Kyungpook National University, Daegu (Korea, Republic of)

    2015-03-15

    The performance of our mean gradient charge (MGC) concept was systematically investigated by adopting Na{sup +}-(H{sub 2}O){sub n} (n = 1–6) model clusters. The Mulliken charges are sensitive to the choice of theories and basis sets, and ChelpG charges abnormally behave with the system size. MGC and “atoms-in-molecules” (AIM) show small mean standard deviations (⁓0.02) with the choice of the theory and the basis set. However, an unpredictable value was found in AIM predictions. Both natural population analysis (NPA) and MGC yielded smooth and monotonic curves as a function of the system size. Therefore, MGC appears to have desirable properties in the consistent and reliable predictions of atomic charges.

  6. Creating fractional quantum Hall states with atomic clusters using light-assisted insertion of angular momentum

    Science.gov (United States)

    Zhang, Junyi; Beugnon, Jérôme; Nascimbene, Sylvain

    2016-10-01

    We describe a protocol to prepare clusters of ultracold bosonic atoms in strongly interacting states reminiscent of fractional quantum Hall states. Our scheme consists in injecting a controlled amount of angular momentum to an atomic gas using Raman transitions carrying orbital angular momentum. By injecting one unit of angular momentum per atom, one realizes a single-vortex state, which is well described by mean-field theory for large enough particle numbers. We also present schemes to realize fractional quantum Hall states, namely, the bosonic Laughlin and Moore-Read states. We investigate the requirements for adiabatic nucleation of such topological states, in particular comparing linear Landau-Zener ramps and arbitrary ramps obtained from optimized control methods. We also show that this protocol requires excellent control over the isotropic character of the trapping potential.

  7. Using Cluster Analysis to Examine Husband-Wife Decision Making

    Science.gov (United States)

    Bonds-Raacke, Jennifer M.

    2006-01-01

    Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

  8. Clustering analysis of seismicity and aftershock identification.

    Science.gov (United States)

    Zaliapin, Ilya; Gabrielov, Andrei; Keilis-Borok, Vladimir; Wong, Henry

    2008-07-01

    We introduce a statistical methodology for clustering analysis of seismicity in the time-space-energy domain and use it to establish the existence of two statistically distinct populations of earthquakes: clustered and nonclustered. This result can be used, in particular, for nonparametric aftershock identification. The proposed approach expands the analysis of Baiesi and Paczuski [Phys. Rev. E 69, 066106 (2004)10.1103/PhysRevE.69.066106] based on the space-time-magnitude nearest-neighbor distance eta between earthquakes. We show that for a homogeneous Poisson marked point field with exponential marks, the distance eta has the Weibull distribution, which bridges our results with classical correlation analysis for point fields. The joint 2D distribution of spatial and temporal components of eta is used to identify the clustered part of a point field. The proposed technique is applied to several seismicity models and to the observed seismicity of southern California.

  9. 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.

  10. 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.

  11. Can an Ising-like cluster expansion describe atomic relaxations in alloys?

    Science.gov (United States)

    Zunger, Alex; Wolverton, C.

    1996-03-01

    Ising-like lattice models are often described as ``fixed lattice'' models, incapable of describing the effects of structural relaxation. However, we have recently demonstrated^1 the ability of generalized k-space^2 Ising-like cluster expansions to describe the energetics and thermodynamics associated with large atomic displacements in alloys. Although the expansion is constructed only from the energies of a few (small-unit-cell) ordered structures, it provides accurate predictions of the atomically-relaxed energies of random, ordered, or partially ordered alloys, as compared with direct, large scale ( ~1000 atom) energy-minimizing simulations. Moreover, unlike molecular dynamics, here relaxed energies are obtained without having to compute relaxed geometries. Combination of the cluster expansion with Monte Carlo calculations is shown to provide a far more efficient means for calculating thermodynamic properties than explicit molecular dynamics or other structural minimization methods. [1] C. Wolverton and A. Zunger, Phys. Rev. Lett. 75, 3162 (1995). [2] D. B. Laks, L. G. Ferreira, S. Froyen, and A. Zunger, Phys. Rev. B 46, 12587 (1992). Supported by BES/OER/DMS under contract DE-AC36-83CH10093.

  12. Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

    Science.gov (United States)

    Steenbergen, K G; Gaston, N

    2014-02-14

    Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

  13. Cluster and constraint analysis in tetrahedron packings.

    Science.gov (United States)

    Jin, Weiwei; Lu, Peng; Liu, Lufeng; Li, Shuixiang

    2015-04-01

    The disordered packings of tetrahedra often show no obvious macroscopic orientational or positional order for a wide range of packing densities, and it has been found that the local order in particle clusters is the main order form of tetrahedron packings. Therefore, a cluster analysis is carried out to investigate the local structures and properties of tetrahedron packings in this work. We obtain a cluster distribution of differently sized clusters, and peaks are observed at two special clusters, i.e., dimer and wagon wheel. We then calculate the amounts of dimers and wagon wheels, which are observed to have linear or approximate linear correlations with packing density. Following our previous work, the amount of particles participating in dimers is used as an order metric to evaluate the order degree of the hierarchical packing structure of tetrahedra, and an order map is consequently depicted. Furthermore, a constraint analysis is performed to determine the isostatic or hyperstatic region in the order map. We employ a Monte Carlo algorithm to test jamming and then suggest a new maximally random jammed packing of hard tetrahedra from the order map with a packing density of 0.6337.

  14. Identifying Peer Institutions Using Cluster Analysis

    Science.gov (United States)

    Boronico, Jess; Choksi, Shail S.

    2012-01-01

    The New York Institute of Technology's (NYIT) School of Management (SOM) wishes to develop a list of peer institutions for the purpose of benchmarking and monitoring/improving performance against other business schools. The procedure utilizes relevant criteria for the purpose of establishing this peer group by way of a cluster analysis. The…

  15. [Visual field progression in glaucoma: cluster analysis].

    Science.gov (United States)

    Bresson-Dumont, H; Hatton, J; Foucher, J; Fonteneau, M

    2012-11-01

    Visual field progression analysis is one of the key points in glaucoma monitoring, but distinction between true progression and random fluctuation is sometimes difficult. There are several different algorithms but no real consensus for detecting visual field progression. The trend analysis of global indices (MD, sLV) may miss localized deficits or be affected by media opacities. Conversely, point-by-point analysis makes progression difficult to differentiate from physiological variability, particularly when the sensitivity of a point is already low. The goal of our study was to analyse visual field progression with the EyeSuite™ Octopus Perimetry Clusters algorithm in patients with no significant changes in global indices or worsening of the analysis of pointwise linear regression. We analyzed the visual fields of 162 eyes (100 patients - 58 women, 42 men, average age 66.8 ± 10.91) with ocular hypertension or glaucoma. For inclusion, at least six reliable visual fields per eye were required, and the trend analysis (EyeSuite™ Perimetry) of visual field global indices (MD and SLV), could show no significant progression. The analysis of changes in cluster mode was then performed. In a second step, eyes with statistically significant worsening of at least one of their clusters were analyzed point-by-point with the Octopus Field Analysis (OFA). Fifty four eyes (33.33%) had a significant worsening in some clusters, while their global indices remained stable over time. In this group of patients, more advanced glaucoma was present than in stable group (MD 6.41 dB vs. 2.87); 64.82% (35/54) of those eyes in which the clusters progressed, however, had no statistically significant change in the trend analysis by pointwise linear regression. Most software algorithms for analyzing visual field progression are essentially trend analyses of global indices, or point-by-point linear regression. This study shows the potential role of analysis by clusters trend. However, for best

  16. Lacunarity analysis of atomic configurations: Application to ethanol-water mixtures

    Science.gov (United States)

    Gereben, Orsolya

    2015-09-01

    Lacunarity analysis is a scale-dependent method quantifying the translational invariance in patterns. In this work it is used to characterize the distribution of several subsets of atoms in molecular systems. Binary clusters and one-component (ethanol or water) hydrogen-bonded clusters of ethanol-water mixtures with 0 -100 mol % ethanol content were analyzed. Molecular dynamics simulations created the configurations, and all were in good agreement with the respective experimental x-ray diffraction data. Lacunarity analysis revealed that the placement of the one-component clusters at low concentration can be described by a multifractal distribution, especially in the case of ethanol. Most of the cases these clusters are not isolated entities, but form islands in binary clusters.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-02-16

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

  18. Electronic and atomic structure of the AlnHn+2 clusters

    DEFF Research Database (Denmark)

    Martinez, Jose Ignacio; Alonso, J.A.

    2008-01-01

    occupied and the lowest unoccupied molecular orbitals (HOMO-LUMO) and, consequently, they are chemically very stable. The largest gap of 2.81 eV occurs for Al6H8. Five clusters of the family, Al4H6, Al5H7, Al6H8, Al7H9, and Al10H12, fulfill the Wade-Mingos rule. That is, in AlnHn+2, the Al matrix forms...... a polyhedron of n vertices and n H atoms form strong H-Al terminal bonds; one pair of electrons is involved in each of those bonds. The remaining n+1 electron pairs form a delocalized cloud over the surface of the Al cage. The clusters fulfilling the Wade-Mingos rule have wider HOMO-LUMO gaps...

  19. Linear scaling coupled cluster and perturbation theories in the atomic orbital basis

    Science.gov (United States)

    Scuseria, Gustavo E.; Ayala, Philippe Y.

    1999-11-01

    We present a reformulation of the coupled cluster equations in the atomic orbital (AO) basis that leads to a linear scaling algorithm for large molecules. Neglecting excitation amplitudes in a screening process designed to achieve a target energy accuracy, we obtain an AO coupled cluster method which is competitive in terms of number of amplitudes with the traditional molecular orbital (MO) solution, even for small molecules. For large molecules, the decay properties of integrals and excitation amplitudes becomes evident and our AO method yields a linear scaling algorithm with respect to molecular size. We present benchmark calculations to demonstrate that our AO reformulation of the many-body electron correlation problem defeats the "exponential scaling wall" that has characterized high-level MO quantum chemistry calculations for many years.

  20. Magnetism of Metals, Alloys and of Clusters of Transition Metal Atoms

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A condition for local moment formation in metals derived by Stoddart and March (Ann. Phys.NY 1972 64, 174) is first used to discuss the ferromagnetism of body-centred-cubic Fe. A less detailed discussion is also added on Ni and Co. This leads into a treatment of the nonlinear response of such 3d ferromagnets to dilute substitutional impurities. Antiferromagnets responding to local changes in the exchange field caused by such impurities are also studied, Mn in Cr being one such system discussed. The paper concludes with a brief summary of clusters of transition metal atoms, with most attention devoted to Cr and to Mn.

  1. Electron Impact Ionization and Fragmentation Dynamics of Small Atomic and Molecular Clusters

    Science.gov (United States)

    Dorn, Alexander

    2016-09-01

    New ionization and fragmentation reactions emerge if target atoms or molecules are embedded in an environment as it is the case in small clusters or in the condensed phase. These can be intermolecular energy and charge transfer processes or a completely modified fragmentation behavior of the molecular ions. Here we study low energy electron impact induced ionization with a multi-electron and ion imaging spectrometer (reaction microscope) and a supersonic gas jet target which can produce small clusters of various target species. Interatomic reactions are studied for the model system of weakly bound Ar2 dimers. Here, the coincident detection of three electrons and two ions gives detailed insight in interatomic Coulombic decay and radiative charge transfer processes. Such processes were also found in bio-relevant systems like water clusters. We studied pure and water-mixed clusters of tetrahydrofuran (C4H8O, THF) which is the simplest analog of deoxyribose in the DNA backbone. One observation is that ionization of the outermost valence orbital for the monomer leads to stable THF ions. In contrast if THF is bound to another THF or a water molecule the molecular ring breaks. In addition we identify intermolecular Coulombic decay induced by energy transfer from a water molecule ionized in the inner valence shell to the neighboring THF molecule.

  2. Cluster analysis of obesity and asthma phenotypes.

    Directory of Open Access Journals (Sweden)

    E Rand Sutherland

    Full Text Available BACKGROUND: Asthma is a heterogeneous disease with variability among patients in characteristics such as lung function, symptoms and control, body weight, markers of inflammation, and responsiveness to glucocorticoids (GC. Cluster analysis of well-characterized cohorts can advance understanding of disease subgroups in asthma and point to unsuspected disease mechanisms. We utilized an hypothesis-free cluster analytical approach to define the contribution of obesity and related variables to asthma phenotype. METHODOLOGY AND PRINCIPAL FINDINGS: In a cohort of clinical trial participants (n = 250, minimum-variance hierarchical clustering was used to identify clinical and inflammatory biomarkers important in determining disease cluster membership in mild and moderate persistent asthmatics. In a subset of participants, GC sensitivity was assessed via expression of GC receptor alpha (GCRα and induction of MAP kinase phosphatase-1 (MKP-1 expression by dexamethasone. Four asthma clusters were identified, with body mass index (BMI, kg/m(2 and severity of asthma symptoms (AEQ score the most significant determinants of cluster membership (F = 57.1, p<0.0001 and F = 44.8, p<0.0001, respectively. Two clusters were composed of predominantly obese individuals; these two obese asthma clusters differed from one another with regard to age of asthma onset, measures of asthma symptoms (AEQ and control (ACQ, exhaled nitric oxide concentration (F(ENO and airway hyperresponsiveness (methacholine PC(20 but were similar with regard to measures of lung function (FEV(1 (% and FEV(1/FVC, airway eosinophilia, IgE, leptin, adiponectin and C-reactive protein (hsCRP. Members of obese clusters demonstrated evidence of reduced expression of GCRα, a finding which was correlated with a reduced induction of MKP-1 expression by dexamethasone CONCLUSIONS AND SIGNIFICANCE: Obesity is an important determinant of asthma phenotype in adults. There is heterogeneity in

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

    Science.gov (United States)

    Corrigan, Neil; Bankart, Michael J G; Gray, Laura J; Smith, Karen L

    2014-05-24

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

  4. Semi-supervised consensus clustering for gene expression data analysis

    OpenAIRE

    Wang, Yunli; Pan, Youlian

    2014-01-01

    Background Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

  5. Energetics and self-diffusion behavior of Zr atomic clusters on a Zr(0 0 0 1) surface

    Energy Technology Data Exchange (ETDEWEB)

    Liu Fusheng [Department of Applied Physics, Hunan University, Changsha 410082 (China); Hu Wangyu [Department of Applied Physics, Hunan University, Changsha 410082 (China)], E-mail: wangyuhu2001cn@yahoo.com.cn; Deng Huiqiu; Luo Wenhua; Xiao Shifang [Department of Applied Physics, Hunan University, Changsha 410082 (China); Yang Jianyu [Department of Maths and Physics, Hunan Institute of Engineering, Xiangtan 411104 (China)

    2009-09-15

    Using a molecular dynamics method and a modified analytic embedded atom potential, the energetic and the self-diffusion dynamics of Zr atomic clusters up to eight atoms on {alpha}-Zr(0 0 0 1) surface have been studied. The simulation temperature ranges from 300 to 1100 K and the simulation time varies from 20 to 40 ns. It's found that the heptamer and trimer are more stable comparing to other neighboring non-compact clusters. The diffusion coefficients of clusters are derived from the mean square displacement of cluster's mass-center and the present diffusion coefficients for clusters exhibit an Arrhenius behavior. The Arrhenius relation of the single adatom can be divided into two parts in different temperature range because of their different diffusion mechanisms. The migration energies of clusters increase with increasing the number of atoms in cluster. The differences of the prefactors also come from the diverse diffusion mechanisms. On the facet of 60 nm, the heptamer can be the nuclei in the crystal growth below 370 K.

  6. Geographic atrophy phenotype identification by cluster analysis.

    Science.gov (United States)

    Monés, Jordi; Biarnés, Marc

    2017-07-20

    To identify ocular phenotypes in patients with geographic atrophy secondary to age-related macular degeneration (GA) using a data-driven cluster analysis. This was a retrospective analysis of data from a prospective, natural history study of patients with GA who were followed for ≥6 months. Cluster analysis was used to identify subgroups within the population based on the presence of several phenotypic features: soft drusen, reticular pseudodrusen (RPD), primary foveal atrophy, increased fundus autofluorescence (FAF), greyish FAF appearance and subfoveal choroidal thickness (SFCT). A comparison of features between the subgroups was conducted, and a qualitative description of the new phenotypes was proposed. The atrophy growth rate between phenotypes was then compared. Data were analysed from 77 eyes of 77 patients with GA. Cluster analysis identified three groups: phenotype 1 was characterised by high soft drusen load, foveal atrophy and slow growth; phenotype 3 showed high RPD load, extrafoveal and greyish FAF appearance and thin SFCT; the characteristics of phenotype 2 were midway between phenotypes 1 and 3. Phenotypes differed in all measured features (p≤0.013), with decreases in the presence of soft drusen, foveal atrophy and SFCT seen from phenotypes 1 to 3 and corresponding increases in high RPD load, high FAF and greyish FAF appearance. Atrophy growth rate differed between phenotypes 1, 2 and 3 (0.63, 1.91 and 1.73 mm(2)/year, respectively, p=0.0005). Cluster analysis identified three distinct phenotypes in GA. One of them showed a particularly slow growth pattern. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  7. Theoretical realization of cluster-assembled hydrogen storage materials based on terminated carbon atomic chains.

    Science.gov (United States)

    Liu, Chun-Sheng; An, Hui; Guo, Ling-Ju; Zeng, Zhi; Ju, Xin

    2011-01-14

    The capacity of carbon atomic chains with different terminations for hydrogen storage is studied using first-principles density functional theory calculations. Unlike the physisorption of H(2) on the H-terminated chain, we show that two Li (Na) atoms each capping one end of the odd- or even-numbered carbon chain can hold ten H(2) molecules with optimal binding energies for room temperature storage. The hybridization of the Li 2p states with the H(2)σ orbitals contributes to the H(2) adsorption. However, the binding mechanism of the H(2) molecules on Na arises only from the polarization interaction between the charged Na atom and the H(2). Interestingly, additional H(2) molecules can be bound to the carbon atoms at the chain ends due to the charge transfer between Li 2s2p (Na 3s) and C 2p states. More importantly, dimerization of these isolated metal-capped chains does not affect the hydrogen binding energy significantly. In addition, a single chain can be stabilized effectively by the C(60) fullerenes termination. With a hydrogen uptake of ∼10 wt.% on Li-coated C(60)-C(n)-C(60) (n = 5, 8), the Li(12)C(60)-C(n)-Li(12)C(60) complex, keeping the number of adsorbed H(2) molecules per Li and stabilizing the dispersion of individual Li atoms, can serve as better building blocks of polymers than the (Li(12)C(60))(2) dimer. These findings suggest a new route to design cluster-assembled hydrogen storage materials based on terminated sp carbon chains.

  8. Dynamics of atomic clusters in intense optical fields of ultrashort duration

    Indian Academy of Sciences (India)

    Deepak Mathur; Firoz A Rajgara

    2012-01-01

    Intense laser pulses have been generated that last for only 10 fs, long enough to accommodate only 3 optical cycles of 800 nm light. Upon focussing such pulses, intensities in the 1015 W cm−2 range are readily generated. At such intensities, the magnitude of the optical field begins to match intra-atomic Coulombic fields. Consequently, exposure of atoms and molecules to such intense pulses inevitably leads to single and multiple ionization. We report here results of experiments that we have conducted that involve irradiation of gas-phase Ar15,000 clusters by such intense, few-cycle laser pulses. The clusters become multiply ionized and undergo Coulomb explosion, giving rise to ejection of fast Ar-ions. Results show that the strong-field dynamics in the few-cycle domain differ significantly from those that occur in the longer pulse (> 30 fs) regime. Manifestations of these differences are presented in the form of angle-dependent ion energy and ion yield functions.

  9. Selective oxidation with dioxygen by gold nanoparticle catalysts derived from 55-atom clusters.

    Science.gov (United States)

    Turner, Mark; Golovko, Vladimir B; Vaughan, Owain P H; Abdulkin, Pavel; Berenguer-Murcia, Angel; Tikhov, Mintcho S; Johnson, Brian F G; Lambert, Richard M

    2008-08-21

    Supported gold nanoparticles have excited much interest owing to their unusual and somewhat unexpected catalytic properties, but the origin of the catalytic activity is still not fully understood. Experimental work on gold particles supported on a titanium dioxide (110) single-crystal surface has established a striking size threshold effect associated with a metal-to-insulator transition, with gold particles catalytically active only if their diameters fall below approximately 3.5 nm. However, the remarkable catalytic behaviour might also in part arise from strong electronic interaction between the gold and the titanium dioxide support. In the case of industrially important selective oxidation reactions, explanation of the effectiveness of gold nanoparticle catalysts is complicated by the need for additives to drive the reaction, and/or the presence of strong support interactions and incomplete understanding of their possible catalytic role. Here we show that very small gold entities ( approximately 1.4 nm) derived from 55-atom gold clusters and supported on inert materials are efficient and robust catalysts for the selective oxidation of styrene by dioxygen. We find a sharp size threshold in catalytic activity, in that particles with diameters of approximately 2 nm and above are completely inactive. Our observations suggest that catalytic activity arises from the altered electronic structure intrinsic to small gold nanoparticles, and that the use of 55-atom gold clusters may prove a viable route to the synthesis of robust gold catalysts suited to practical application.

  10. 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...... 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......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...

  11. 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...... 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......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...

  12. MANNER OF STOCKS SORTING USING CLUSTER ANALYSIS METHODS

    Directory of Open Access Journals (Sweden)

    Jana Halčinová

    2014-06-01

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

  13. AMOEBA clustering revisited. [cluster analysis, classification, and image display program

    Science.gov (United States)

    Bryant, Jack

    1990-01-01

    A description of the clustering, classification, and image display program AMOEBA is presented. Using a difficult high resolution aircraft-acquired MSS image, the steps the program takes in forming clusters are traced. A number of new features are described here for the first time. Usage of the program is discussed. The theoretical foundation (the underlying mathematical model) is briefly presented. The program can handle images of any size and dimensionality.

  14. Mapping Cigarettes Similarities using Cluster Analysis Methods

    Directory of Open Access Journals (Sweden)

    Lorentz Jäntschi

    2007-09-01

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

  15. Structural motifs, mixing, and segregation effects in 38-atom binary clusters

    Science.gov (United States)

    Paz-Borbón, Lauro Oliver; Johnston, Roy L.; Barcaro, Giovanni; Fortunelli, Alessandro

    2008-04-01

    Thirty eight-atom binary clusters composed of elements from groups 10 and 11 of the Periodic Table mixing a second-row with a third-row transition metal (TM) (i.e., clusters composed of the four pairs: Pd-Pt, Ag-Au, Pd-Au, and Ag-Pt) are studied through a combined empirical-potential (EP)/density functional (DF) method. A "system comparison" approach is adopted in order to analyze a wide diversity of structural motifs, and the energy competition among different structural motifs is studied at the DF level for these systems, mainly focusing on the composition 24-14 (the first number refers to the second-row TM atom) but also considering selected motifs with compositions 19-19 (of interest for investigating surface segregation effects) and 32-6 (also 14-24 and 6-32 for the Pd-Au pair). The results confirm the EP predictions about the stability of crystalline structures at this size for the Au-Pd pair but with decahedral or mixed fivefold-symmetric/closed-packed structures in close competition with fcc motifs for the Ag-Au or Ag-Pt and Pd-Pt pairs, respectively. Overall, the EP description is found to be reasonably accurate for the Pd-Pt and Au-Pd pairs, whereas it is less reliable for the Ag-Au and Ag-Pt pairs due to electronic structure (charge transfer or directionality) effects. The driving force to core-shell chemical ordering is put on a quantitative basis, and surface segregation of the most cohesive element into the core is confirmed, with the exception of the Ag-Au pair for which charge transfer effects favor the segregation of Au to the surface of the clusters.

  16. Significantly Enhanced Hydrogen Evolution Activity of Freestanding Pd-Ru Distorted Icosahedral Clusters with less than 600 Atoms.

    Science.gov (United States)

    Dai, Zhihui; Liu, Suli; Zhang, Qinghua; Bao, Jianchun; Li, Yafei; Gu, Lin

    2017-07-24

    Freestanding metal nanoclusters can tune, precisely and effectively, the Gibbs free energy (ΔGH) of atomic hydrogen on the surface of materials. This enables the enhancement of hydrogen evolution activity. In this paper, we report a study of freestanding Pd-Ru distorted icosahedral clusters (ico-clusters) with less than 600 atoms using a simple one-pot synthesis method. This Pd-Ru ico-cluster can be used as an efficient electrocatalyst for the hydrogen evolution reaction (HER) in acidic water, which is a promising alternative to Pt. The experimental and theoretical results suggest that the fcc freestanding Pd-Ru distorted ico-clusters with less than 600 atoms ensure increased active edges and distorted defect sites that reduce the coordination number for the atoms on the catalyst surface. Furthermore, Ru is a more effective hydrogen dissociation source, while Pd has a better hydrogen storage function. Pd-Ru can tune the ΔGH of atomic hydrogen adsorbed on a catalyst and reach an optimal equilibrium state that improves the HER performance. Our studies represent a robust approach towards the development of freestanding Pd-Ru distorted ico-clusters and advanced catalysts with non-Pt content for HER and many other heterogeneous reactions. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Structurally Well-Defined Sigmoidal Gold Clusters: Probing the Correlation between Metal Atom Arrangement and Chiroptical Response.

    Science.gov (United States)

    He, Xin; Wang, Yuechao; Jiang, Hong; Zhao, Liang

    2016-05-04

    Asymmetric arrangement of metal atoms is crucial for understanding the chirality origin of chiral metal nanoclusters and facilitating the design and development of new chiral catalysts and chiroptical devices. Here, we describe the construction of four asymmetric gold and gold-silver clusters by chirality transfer from diimido ligands. The acquired metal clusters show strong circular dichroism (CD) response with large anisotropy factors of up to 6 × 10(-3), larger than the values of most reported chiral gold nanoclusters. Regardless of the same absolute configuration of the applied three diimido ligands, sigmoidal and reverse-sigmoidal arrangements of gold atoms both can be achieved, which resultantly produce an opposite Cotton effect within a specific absorption range. On the basis of the detailed structural characterization via X-ray crystallography and contrast experiments, the chirality contribution of the imido ligand, the asymmetrically arranged metal cluster, and the chiral arrangement of aromatic rings of phosphine ligands have been qualitatively evaluated. Time-dependent DFT calculations reveal that the chiroptical property of the acquired metal clusters is mainly influenced by the asymmetrically arranged metal atoms. Correlation of asymmetric arrangements of metal atoms in clusters with their chiroptical response provides a viable means of fabricating a designable chiral surface of metal nanoclusters and opens a broader prospect for chiral cluster application.

  18. Real-time study of the adiabatic energy loss in an atomic collision with a metal cluster.

    Science.gov (United States)

    Baer, Roi; Siam, Nidal

    2004-10-01

    Gas-phase hydrogen atoms are accelerated towards metallic surfaces in their vicinity. As it approaches the surface, the velocity of an atom increases and this motion excites the metallic electrons, causing energy loss to the atom. This dissipative dynamics is frequently described as atomic motion under friction, where the friction coefficient is obtained from ab initio calculations assuming a weak interaction and slow atom. This paper tests the aforementioned approach by comparing to a real-time Ehrenfest molecular dynamics simulation of such a process. The electrons are treated realistically using standard approximations to time-dependent density functional theory. We find indeed that the electronic excitations produce a friction-like force on the atom. However, the friction coefficient strongly depends on the direction of the motion of the atom: it is large when the atom is moving towards the cluster and much smaller when the atom is moving away. It is concluded that a revision of the model for energy dissipation at metallic surfaces, at least for clusters, may be necessary.

  19. Photoelectron imaging, probe of the dynamics: from atoms... to clusters; Imagerie de photoelectrons, sonde de la dynamique: des atomes... aux agregats

    Energy Technology Data Exchange (ETDEWEB)

    Lepine, F

    2003-06-15

    This thesis concerns the study of the deexcitation of clusters and atoms by photoelectron imaging. The first part is dedicated to thermionic emission of a finite size system. A 3-dimensional imaging setup allows us to measure the time evolution of the kinetic energy spectrum of electrons emitted from different clusters (W{sub n}{sup -}, C{sub n}{sup -}, C{sub 60}). Then we have a direct access to the fundamental quantities which characterize this statistical emission: the temperature of the finite heat bath and the decay rate. The second part concerns the ionization of atomic Rydberg states placed in a static electric field. We performed the first experiment of photoionization microscopy which allows us to obtain a picture which is the macroscopic projection of the electronic wave function. Then we have access to the detail of the photoionization and particularly to the quantum properties of the electron usually confined at the atomic scale. (author)

  20. Monitoring the dissolution process of metals in the gas phase: reactions of nanoscale Al and Ga metal atom clusters and their relationship to similar metalloid clusters.

    Science.gov (United States)

    Burgert, Ralf; Schnöckel, Hansgeorg

    2008-05-14

    Formation and dissolution of metals are two of the oldest technical chemical processes. On the atomic scale, these processes are based on the formation and cleavage of metal-metal bonds. During the past 15 years we have studied intensively the intermediates during the formation process of metals, i.e. the formation of compounds containing many metal-metal bonds between naked metal atoms in the center and ligand-bearing metal atoms at the surface. We have called the clusters metalloid or, more generally, elementoid clusters. Via a retrosynthetic route, the many different Al and Ga metalloid clusters which have been structurally characterized allow us to understand also the dissolution process; i.e. the cleavage of metal-metal (M-M) bonds. However, this process can be detected much more directly by the reaction of single metal atom clusters in the gas phase under high vacuum conditions. A suitable tool to monitor the dissolution process of a metal cluster in the gas phase is FT-ICR (Fourier transform ion cyclotron resonance) mass spectrometry. Snapshots during these cleavage processes are possible because only every 1-10 s is there a contact between a cluster molecule and an oxidizing molecule (e.g. Cl2). This period is long, i.e. the formation of the primary product (a smaller metal atom cluster) is finished before the next collision happens. We have studied three different types of reaction:(1) Step-by-step fragmentation of a structurally known metalloid cluster allows us to understand the bonding principle of these clusters because in every step only the weakest bond is broken.(2) There are three oxidation reactions of an Al13(-) cluster molecule with Cl2, HCl and O2 central to this review. These three reactions represent three different reaction types, (a) an exothermic reaction (Cl2), (b) an endothermic reaction (HCl), and (c) a kinetically limited reaction based on spin conservation rules (O2).(3) Finally, we present the reaction of a metalloid cluster with Cl2

  1. Equivalent damage validation by variable cluster analysis

    Science.gov (United States)

    Drago, Carlo; Ferlito, Rachele; Zucconi, Maria

    2016-06-01

    The main aim of this work is to perform a clustering analysis on the damage relieved in the old center of L'Aquila after the earthquake occurred on April 6, 2009 and to validate an Indicator of Equivalent Damage ED that summarizes the information reported on the AeDES card regarding the level of damage and their extension on the surface of the buildings. In particular we used a sample of 13442 masonry buildings located in an area characterized by a Macroseismic Intensity equal to 8 [1]. The aim is to ensure the coherence between the clusters and its hierarchy identified in the data of damage detected and in the data of the ED elaborated.

  2. Structure and property of metal melt Ⅲ—Relationship between kinematic viscosity and size of atomic clusters

    Institute of Scientific and Technical Information of China (English)

    POPEL; P; S; KONSTANTINOVA; N; Yu

    2010-01-01

    The method of crucible rotating oscillation damping was employed to measure the kinematic viscosity of aluminum melt,and the curve of viscosity v versus temperature T from 935 to 1383 K was obtained.Besides,based on the calculation model of the evolution behavior of atomic clusters in liquid structure,the curve of atomic clusters size d versus temperature was obtained,and the calculated results are in good agreement with the experimental values.By analyzing experimental data,it was found that both the viscosity and the size of atomic clusters of aluminum melt are monodrome functions of temperature,and the relation between v(T) and d(T) is a linear function,i.e.,v = v 0 + K·d(T).This relation indirectly verifies the calculation model of the structural information of metal melt,which is of great significance for studying the relation between melt microstructure and macro-physical properties.

  3. Atomic Force Microscopy for Soil Analysis

    Science.gov (United States)

    gazze, andrea; doerr, stefan; dudley, ed; hallin, ingrid; matthews, peter; quinn, gerry; van keulen, geertje; francis, lewis

    2016-04-01

    Atomic Force Microscopy (AFM) is a high-resolution surface-sensitive technique, which provides 3-dimensional topographical information and material properties of both stiff and soft samples in their natural environments. Traditionally AFM has been applied to samples with low roughness: hence its use for soil analysis has been very limited so far. Here we report the optimization settings required for a standardization of high-resolution and artefact-free analysis of natural soil with AFM: soil immobilization, AFM probe selection, artefact recognition and minimization. Beyond topography, AFM can be used in a spectroscopic mode to evaluate nanomechanical properties, such as soil viscosity, stiffness, and deformation. In this regards, Bruker PeakForce-Quantitative NanoMechanical (QNM) AFM provides a fast and convenient way to extract physical properties from AFM force curves in real-time to obtain soil nanomechanical properties. Here we show for the first time the ability of AFM to describe the topography of natural soil at nanometre resolution, with observation of micro-components, such as clays, and of nano-structures, possibly of biotic origin, the visualization of which would prove difficult with other instrumentations. Finally, nanomechanical profiling has been applied to different wettability states in soil and the respective physical patterns are discussed.

  4. Atom column indexing: atomic resolution image analysis through a matrix representation.

    Science.gov (United States)

    Sang, Xiahan; Oni, Adedapo A; LeBeau, James M

    2014-12-01

    Here, we report the development of an approach to map atomic resolution images into a convenient matrix representation. Through the combination of two-dimensional Gaussian fitting and the projective standard deviation, atom column locations are projected onto two noncollinear reference lattice vectors that are used to assign each a unique (i, j) matrix index. By doing so, straightforward atomic resolution image analysis becomes possible. Using practical examples, we demonstrate that the matrix representation greatly simplifies categorizing atom columns to different sublattices. This enables a myriad of direct analyses, such as mapping atom column properties and correlating long-range atom column pairs. MATLAB source code can be downloaded from https://github.com/subangstrom/aci.

  5. Data Clustering Analysis Based on Wavelet Feature Extraction

    Institute of Scientific and Technical Information of China (English)

    QIANYuntao; TANGYuanyan

    2003-01-01

    A novel wavelet-based data clustering method is presented in this paper, which includes wavelet feature extraction and cluster growing algorithm. Wavelet transform can provide rich and diversified information for representing the global and local inherent structures of dataset. therefore, it is a very powerful tool for clustering feature extraction. As an unsupervised classification, the target of clustering analysis is dependent on the specific clustering criteria. Several criteria that should be con-sidered for general-purpose clustering algorithm are pro-posed. And the cluster growing algorithm is also con-structed to connect clustering criteria with wavelet fea-tures. Compared with other popular clustering methods,our clustering approach provides multi-resolution cluster-ing results,needs few prior parameters, correctly deals with irregularly shaped clusters, and is insensitive to noises and outliers. As this wavelet-based clustering method isaimed at solving two-dimensional data clustering prob-lem, for high-dimensional datasets, self-organizing mapand U-matrlx method are applied to transform them intotwo-dimensional Euclidean space, so that high-dimensional data clustering analysis,Results on some sim-ulated data and standard test data are reported to illus-trate the power of our method.

  6. Thermally Stable and Regenerable Platinum-Tin Clusters for Propane Dehydrogenation Prepared by Atom Trapping on Ceria

    Energy Technology Data Exchange (ETDEWEB)

    Xiong, Haifeng [Department of Chemical & Biological Engineering and Center for Microengineered Materials, University of New Mexico, Albuquerque NM 87131 USA; Lin, Sen [Research Institute of Photocatalysis, State Key Laboratory of Photocatalysis on Energy and Environment, Fuzhou University, Fuzhou 350002 China; Goetze, Joris [Inorganic Chemistry and Catalysis, Debye Institute for Nanomaterials Science, Utrecht University, Universiteitsweg 99 3584 CG Utrecht The Netherlands; Pletcher, Paul [Inorganic Chemistry and Catalysis, Debye Institute for Nanomaterials Science, Utrecht University, Universiteitsweg 99 3584 CG Utrecht The Netherlands; Guo, Hua [Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque NM 87131 USA; Kovarik, Libor [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland WA 99352 USA; Artyushkova, Kateryna [Department of Chemical & Biological Engineering and Center for Microengineered Materials, University of New Mexico, Albuquerque NM 87131 USA; Weckhuysen, Bert M. [Inorganic Chemistry and Catalysis, Debye Institute for Nanomaterials Science, Utrecht University, Universiteitsweg 99 3584 CG Utrecht The Netherlands; Datye, Abhaya K. [Department of Chemical & Biological Engineering and Center for Microengineered Materials, University of New Mexico, Albuquerque NM 87131 USA

    2017-06-28

    CeO2 supports are unique in their ability to trap ionic Pt, providing exceptional stability for isolated single atoms of Pt. Here, we explore the reactivity and stability of single atom Pt species for the industrially important reaction of light alkane dehydrogenation. The single atom Pt/CeO2 catalysts are stable during propane dehydrogenation, but we observe no selectivity towards propene. DFT calculations show strong adsorption of the olefin produced, leading to further unwanted reactions. In contrast, when Sn is added to ceria, the single atom Pt catalyst undergoes an activation phase where it transforms into Pt-Sn clusters under reaction conditions. Formation of small Pt-Sn clusters allows the catalyst to achieve high selectivity towards propene, due to facile desorption of the product. The CeO2-supported Pt-Sn clusters are very stable, even during extended reaction at 680 °C. By adding water vapor to the feed, coke formation can almost completely be suppressed. Furthermore, the Pt-Sn clusters can be readily transformed back to the atomically dispersed species on ceria via oxidation, making Pt-Sn/CeO2 a fully regenerable catalyst.

  7. Size-specific interaction of alkali metal ions in the solvation of M+-benzene clusters by Ar atoms.

    Science.gov (United States)

    Huarte-Larrañaga, F; Aguilar, A; Lucas, J M; Albertí, M

    2007-08-23

    The size-specific influence of the M+ alkali ion (M = Li, Na, K, Rb, and Cs) in the solvation process of the M+-benzene clusters by Ar atoms is investigated by means of molecular dynamic simulations. To fully understand the behavior observed in M+-bz-Ar(n) clusters, solvation is also studied in clusters containing either M+ or benzene only. The potential energy surfaces employed are based on a semiempirical bond-atom decomposition, which has been developed previously by some of the authors. The outcome of the dynamics is analyzed by employing radial distribution functions, studying the evolution of the distances between the Ar atoms and the alkali ion M+ or the benzene molecule for all M+-bz-Ar(n) clusters. For all members, in the M+-bz series, the benzene molecule (bz) is found to remain strongly bound to M+ even in the presence of solvent atoms. The radial distribution functions for the heavier clusters (K+-bz, Rb+-bz, and Cs+-bz), are found to be different than for the lighter (Na+-bz and Li+-bz) ones.

  8. Constructing storyboards based on hierarchical clustering analysis

    Science.gov (United States)

    Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

    2005-07-01

    There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

  9. Atoms

    Institute of Scientific and Technical Information of China (English)

    刘洪毓

    2007-01-01

    Atoms(原子)are all around us.They are something like the bricks (砖块)of which everything is made. The size of an atom is very,very small.In just one grain of salt are held millions of atoms. Atoms are very important.The way one object acts depends on what

  10. A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering

    CERN Document Server

    Seldin, Yevgeny

    2010-01-01

    We formulate weighted graph clustering as a prediction problem: given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. This formulation enables practical and theoretical comparison of different approaches to graph clustering as well as comparison of graph clustering with other possible ways to model the graph. We adapt the PAC-Bayesian analysis of co-clustering (Seldin and Tishby, 2008; Seldin, 2009) to derive a PAC-Bayesian generalization bound for graph clustering. The bound shows that graph clustering should optimize a trade-off between empirical data fit and the mutual information that clusters preserve on the graph nodes. A similar trade-off derived from information-theoretic considerations was already shown to produce state-of-the-art results in practice (Slonim et al., 2005; Yom-Tov and Slonim, 2009). This paper supports the empirical evidence by providing a better theoretical foundation, suggesting formal generalization guarantees, and offering...

  11. Photodissociation of pyrrole-ammonia clusters by velocity map imaging: mechanism for the H-atom transfer reaction.

    Science.gov (United States)

    Rubio-Lago, L; Amaral, G A; Oldani, A N; Rodríguez, J D; González, M G; Pino, G A; Bañares, L

    2011-01-21

    The photodissociation dynamics of pyrrole-ammonia clusters (PyH·(NH(3))(n), n = 2-6) has been studied using a combination of velocity map imaging and non-resonant detection of the NH(4)(NH(3))(n-1) products. The excited state hydrogen-atom transfer mechanism (ESHT) is evidenced through delayed ionization and presents a threshold around 236.6 nm, in agreement with previous reports. A high resolution determination of the kinetic energy distributions (KEDs) of the products reveals slow (∼0.15 eV) and structured distributions for all the ammonia cluster masses studied. The low values of the measured kinetic energy rule out the existence of a long-lived intermediate state, as it has been proposed previously. Instead, a direct N-H bond rupture, in the fashion of the photodissociation of bare pyrrole, is proposed. This assumption is supported by a careful analysis of the structure of the measured KEDs in terms of a discrete vibrational activity of the pyrrolyl co-fragment.

  12. Catalyst Architecture for Stable Single Atom Dispersion Enables Site-Specific Spectroscopic and Reactivity Measurements of CO Adsorbed to Pt Atoms, Oxidized Pt Clusters, and Metallic Pt Clusters on TiO2.

    Science.gov (United States)

    DeRita, Leo; Dai, Sheng; Lopez-Zepeda, Kimberly; Pham, Nicholas; Graham, George W; Pan, Xiaoqing; Christopher, Phillip

    2017-10-11

    Oxide-supported precious metal nanoparticles are widely used industrial catalysts. Due to expense and rarity, developing synthetic protocols that reduce precious metal nanoparticle size and stabilize dispersed species is essential. Supported atomically dispersed, single precious metal atoms represent the most efficient metal utilization geometry, although debate regarding the catalytic activity of supported single precious atom species has arisen from difficulty in synthesizing homogeneous and stable single atom dispersions, and a lack of site-specific characterization approaches. We propose a catalyst architecture and characterization approach to overcome these limitations, by depositing ∼1 precious metal atom per support particle and characterizing structures by correlating scanning transmission electron microscopy imaging and CO probe molecule infrared spectroscopy. This is demonstrated for Pt supported on anatase TiO2. In these structures, isolated Pt atoms, Ptiso, remain stable through various conditions, and spectroscopic evidence suggests Ptiso species exist in homogeneous local environments. Comparing Ptiso to ∼1 nm preoxidized (Ptox) and prereduced (Ptmetal) Pt clusters on TiO2, we identify unique spectroscopic signatures of CO bound to each site and find CO adsorption energy is ordered: Ptiso ≪ Ptmetal atoms bonded to TiO2 and that Ptiso exhibits optimal reactivity because every atom is exposed for catalysis and forms an interfacial site with TiO2. This approach should be generally useful for studying the behavior of supported precious metal atoms.

  13. Stochastic analysis/synthesis using sinusoidal atoms

    DEFF Research Database (Denmark)

    Jensen, Kristoffer

    2008-01-01

    This work proposes a method for re-synthesizing music for use in perceptual experiments regarding structural changes and in music creation. Atoms are estimated from music audio, modelled in a stochastic model, and re-synthesized from the model pa- rameters. The atoms are found by splitting...... sinusoids into short segments, and modelled into amplitude and envelope shape, frequency, time and duration. A simple model for creating envelopes with percussive, sustained or crescendo shape is presented. Single variable and joint probability density functions are created from the atom parameters and used...... to re-create sounds with the same distribution of the atoms parameters. A novel method for visualization music, the musigram, permits a better understanding of the re- synthesized sounds....

  14. Cluster-based exposure variation analysis.

    Science.gov (United States)

    Samani, Afshin; Mathiassen, Svend Erik; Madeleine, Pascal

    2013-04-04

    Static posture, repetitive movements and lack of physical variation are known risk factors for work-related musculoskeletal disorders, and thus needs to be properly assessed in occupational studies. The aims of this study were (i) to investigate the effectiveness of a conventional exposure variation analysis (EVA) in discriminating exposure time lines and (ii) to compare it with a new cluster-based method for analysis of exposure variation. For this purpose, we simulated a repeated cyclic exposure varying within each cycle between "low" and "high" exposure levels in a "near" or "far" range, and with "low" or "high" velocities (exposure change rates). The duration of each cycle was also manipulated by selecting a "small" or "large" standard deviation of the cycle time. Theses parameters reflected three dimensions of exposure variation, i.e. range, frequency and temporal similarity.Each simulation trace included two realizations of 100 concatenated cycles with either low (ρ = 0.1), medium (ρ = 0.5) or high (ρ = 0.9) correlation between the realizations. These traces were analyzed by conventional EVA, and a novel cluster-based EVA (C-EVA). Principal component analysis (PCA) was applied on the marginal distributions of 1) the EVA of each of the realizations (univariate approach), 2) a combination of the EVA of both realizations (multivariate approach) and 3) C-EVA. The least number of principal components describing more than 90% of variability in each case was selected and the projection of marginal distributions along the selected principal component was calculated. A linear classifier was then applied to these projections to discriminate between the simulated exposure patterns, and the accuracy of classified realizations was determined. C-EVA classified exposures more correctly than univariate and multivariate EVA approaches; classification accuracy was 49%, 47% and 52% for EVA (univariate and multivariate), and C-EVA, respectively (p analysis are the advantages

  15. Single-molecule atomic force microscopy reveals clustering of the yeast plasma-membrane sensor Wsc1.

    Science.gov (United States)

    Heinisch, Jürgen J; Dupres, Vincent; Wilk, Sabrina; Jendretzki, Arne; Dufrêne, Yves F

    2010-06-14

    Signalling is a key feature of living cells which frequently involves the local clustering of specific proteins in the plasma membrane. How such protein clustering is achieved within membrane microdomains ("rafts") is an important, yet largely unsolved problem in cell biology. The plasma membrane of yeast cells represents a good model to address this issue, since it features protein domains that are sufficiently large and stable to be observed by fluorescence microscopy. Here, we demonstrate the ability of single-molecule atomic force microscopy to resolve lateral clustering of the cell integrity sensor Wsc1 in living Saccharomyces cerevisiae cells. We first localize individual wild-type sensors on the cell surface, revealing that they form clusters of approximately 200 nm size. Analyses of three different mutants indicate that the cysteine-rich domain of Wsc1 has a crucial, not yet anticipated function in sensor clustering and signalling. Clustering of Wsc1 is strongly enhanced in deionized water or at elevated temperature, suggesting its relevance in proper stress response. Using in vivo GFP-localization, we also find that non-clustering mutant sensors accumulate in the vacuole, indicating that clustering may prevent endocytosis and sensor turnover. This study represents the first in vivo single-molecule demonstration for clustering of a transmembrane protein in S. cerevisiae. Our findings indicate that in yeast, like in higher eukaryotes, signalling is coupled to the localized enrichment of sensors and receptors within membrane patches.

  16. Single-molecule atomic force microscopy reveals clustering of the yeast plasma-membrane sensor Wsc1.

    Directory of Open Access Journals (Sweden)

    Jürgen J Heinisch

    Full Text Available Signalling is a key feature of living cells which frequently involves the local clustering of specific proteins in the plasma membrane. How such protein clustering is achieved within membrane microdomains ("rafts" is an important, yet largely unsolved problem in cell biology. The plasma membrane of yeast cells represents a good model to address this issue, since it features protein domains that are sufficiently large and stable to be observed by fluorescence microscopy. Here, we demonstrate the ability of single-molecule atomic force microscopy to resolve lateral clustering of the cell integrity sensor Wsc1 in living Saccharomyces cerevisiae cells. We first localize individual wild-type sensors on the cell surface, revealing that they form clusters of approximately 200 nm size. Analyses of three different mutants indicate that the cysteine-rich domain of Wsc1 has a crucial, not yet anticipated function in sensor clustering and signalling. Clustering of Wsc1 is strongly enhanced in deionized water or at elevated temperature, suggesting its relevance in proper stress response. Using in vivo GFP-localization, we also find that non-clustering mutant sensors accumulate in the vacuole, indicating that clustering may prevent endocytosis and sensor turnover. This study represents the first in vivo single-molecule demonstration for clustering of a transmembrane protein in S. cerevisiae. Our findings indicate that in yeast, like in higher eukaryotes, signalling is coupled to the localized enrichment of sensors and receptors within membrane patches.

  17. Multiple ionization of atom clusters by intense soft X-rays from a free-electron laser.

    Science.gov (United States)

    Wabnitz, H; Bittner, L; de Castro, A R B; Döhrmann, R; Gürtler, P; Laarmann, T; Laasch, W; Schulz, J; Swiderski, A; von Haeften, K; Möller, T; Faatz, B; Fateev, A; Feldhaus, J; Gerth, C; Hahn, U; Saldin, E; Schneidmiller, E; Sytchev, K; Tiedtke, K; Treusch, R; Yurkov, M

    2002-12-05

    Intense radiation from lasers has opened up many new areas of research in physics and chemistry, and has revolutionized optical technology. So far, most work in the field of nonlinear processes has been restricted to infrared, visible and ultraviolet light, although progress in the development of X-ray lasers has been made recently. With the advent of a free-electron laser in the soft-X-ray regime below 100 nm wavelength, a new light source is now available for experiments with intense, short-wavelength radiation that could be used to obtain deeper insights into the structure of matter. Other free-electron sources with even shorter wavelengths are planned for the future. Here we present initial results from a study of the interaction of soft X-ray radiation, generated by a free-electron laser, with Xe atoms and clusters. We find that, whereas Xe atoms become only singly ionized by the absorption of single photons, absorption in clusters is strongly enhanced. On average, each atom in large clusters absorbs up to 400 eV, corresponding to 30 photons. We suggest that the clusters are heated up and electrons are emitted after acquiring sufficient energy. The clusters finally disintegrate completely by Coulomb explosion.

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

    CERN Document Server

    Emmons, Scott; Gallant, Mike; Börner, Katy

    2016-01-01

    Notions of community quality underlie network clustering. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms -- Blondel, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 o...

  19. Cluster analysis of word frequency dynamics

    Science.gov (United States)

    Maslennikova, Yu S.; Bochkarev, V. V.; Belashova, I. A.

    2015-01-01

    This paper describes the analysis and modelling of word usage frequency time series. During one of previous studies, an assumption was put forward that all word usage frequencies have uniform dynamics approaching the shape of a Gaussian function. This assumption can be checked using the frequency dictionaries of the Google Books Ngram database. This database includes 5.2 million books published between 1500 and 2008. The corpus contains over 500 billion words in American English, British English, French, German, Spanish, Russian, Hebrew, and Chinese. We clustered time series of word usage frequencies using a Kohonen neural network. The similarity between input vectors was estimated using several algorithms. As a result of the neural network training procedure, more than ten different forms of time series were found. They describe the dynamics of word usage frequencies from birth to death of individual words. Different groups of word forms were found to have different dynamics of word usage frequency variations.

  20. Ab initio study of the structural, magnetic, and electronic properties of copper and silver clusters and their alloys with one palladium atom

    Directory of Open Access Journals (Sweden)

    S. J Hashemifar

    2015-01-01

    Full Text Available In this paper, the structural, magnetic, and electronic properties of two- to nine-atom copper and silver clusters and their alloys with one palladium atom are investigated by using full-potential all-electron density functional computations. After calculating minimized energy of several structural isomers of every nanocluster, it is argued that the small size nanoclusters (up to size of 6, ‎ prefer planar structures, while by increasing size a 2D-3D structural transformation is observed. The structural transformation of pure and copper-palladium clusters occurs in the size of seven and that of silver-palladium cluster in happens at the size of six. The calculated second difference and dissociation energies confirm that the two- and eight- atom pure clusters and three- and seven- atom alloyed clusters are magic clusters. The electronic and magnetic properties of stable isomers are calculated and considered after applying many body based GW correction.

  1. [Biological material sampling for atomic absorption analysis].

    Science.gov (United States)

    Makarenko, N P; Ganebnykh, E V

    2007-01-01

    The optimum conditions have been chosen for mineralization of biological material for the atomic absorption determination of toxic metals, by using a [Russian characters: see text]-01 laboratory furnace (Gefest) upon exposure to high temperature, pressure, and microwave field. The completeness of dissection of biological material by microwave mineralization is shown under the optimal conditions.

  2. Coupled-cluster singles, doubles and triples (CCSDT) calculations of atomization energies

    DEFF Research Database (Denmark)

    Bak, KL; Jorgensen, P; Olsen, Jeppe

    2000-01-01

    Atomization energies have been calculated for CO, H2O, F-2, HF, N-2 and CH2 (the (1)A(1) state) using the coupled-duster singles, doubles and triples (CCSDT) model as well as the coupled-cluster singles and doubles model with a perturbative correction for triples [CCSD(T)]. TheCCSD(T) model...... provides an excellent approximation to the CCSDT model; at the cc-pV5Z basis set level, the CCSDT valence triples contribution is underestimated by 9.1% (0.8 kJ/mol) for CH, and overestimated for the remaining molecules by as little as 4.3%(1.3 kJ/mol) for F-2,and as much as 8.4% (3.0 kJ/mol) for N-2....... At the CCSDT level, the agreement with experiment is not improved, suggesting that some cancellation of error occurs between the missing triples contributions at the CCSD(T) level and the contributions from the connected quadruples. (C) 2000 Elsevier Science B.V, All rights reserved....

  3. Atomic scale study of CU clustering and pseudo-homogeneous Fe–Si nanocrystallization in soft magnetic FeSiNbB(CU) alloys

    Energy Technology Data Exchange (ETDEWEB)

    Pradeep, K.G. [Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Str. 1, 40237 Düsseldorf (Germany); Materials Chemistry, RWTH Aachen University, Kopernikusstr. 10, 52074 Aachen (Germany); Herzer, G. [Vacuumschmelze GmbH & Co. KG, Grüner Weg 37, 63450 Hanau (Germany); Raabe, D. [Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Str. 1, 40237 Düsseldorf (Germany)

    2015-12-15

    A local electrode atom probe has been employed to trace the onset of Cu clustering followed by their coarsening and subsequent growth upon rapid (10 s) annealing of an amorphous Fe{sub 73.5}Si{sub 15.5}Cu{sub 1}Nb{sub 3}B{sub 7} alloy. It has been found that the clustering of Cu atoms introduces heterogeneities in the amorphous matrix, leading to the formation of Fe rich regions which crystallizes pseudo-homogeneously into Fe–Si nanocrystals upon annealing. In this paper, we present the data treatment method that allows for the visualization of these different phases and to understand their morphology while still quantifying them in terms of their size, number density and volume fraction. The crystallite size of Fe–Si nanocrystals as estimated from the atom probe data are found to be in good agreement with other complementary techniques like XRD and TEM, emphasizing the importance of this approach towards accurate structural analysis. In addition, a composition driven data segmentation approach has been attempted to determine and distinguish nanocrystalline regions from the remaining amorphous matrix. Such an analysis introduces the possibility of retrieving crystallographic information from extremely fine (2–4 nm sized) nanocrystalline regions of very low volume fraction (< 5 Vol%) thereby providing crucial in-sights into the chemical heterogeneity induced crystallization process of amorphous materials.

  4. Dopant-induced 2D-3D transition in small Au-containing clusters: DFT-global optimisation of 8-atom Au-Ag nanoalloys.

    Science.gov (United States)

    Heiles, Sven; Logsdail, Andrew J; Schäfer, Rolf; Johnston, Roy L

    2012-02-21

    A genetic algorithm (GA) coupled with density functional theory (DFT) calculations is used to perform global optimisations for all compositions of 8-atom Au-Ag bimetallic clusters. The performance of this novel GA-DFT approach for bimetallic nanoparticles is tested for structures reported in the literature. New global minimum structures for various compositions are predicted and the 2D-3D transition is located. Results are explained with the aid of an analysis of the electronic density of states. The chemical ordering of the predicted lowest energy isomers are explained via a detailed analysis of the charge separation and mixing energies of the bimetallic clusters. Finally, dielectric properties are computed and the composition and dimensionality dependence of the electronic polarizability and dipole moment is discussed, enabling predictions to be made for future electric beam deflection experiments.

  5. Chemical inhomogeneity in In{sub x}Ga{sub 1-x}N and ZnO. A HRTEM study on atomic scale clustering

    Energy Technology Data Exchange (ETDEWEB)

    Bartel, T.P.

    2008-10-08

    Nanostructuration as well as the nucleation and growth of nanoparticles pervades the development of modern materials and devices. Quantitative high resolution transmission electron microscopy (HRTEM) is currently being developed for a structural and chemical analysis at an atomic scale. It is used in this thesis to study the chemical inhomogeneity and clustering in In{sub x}Ga{sub 1-x}N, InN and ZnO. A methodology for reliable quantitative HRTEM is rst de ned: it necessitates a damage free sample, the avoidance of electron beam damage and the control of microscope instabilities. With these conditions satis ed, the reliability of quantitative HRTEM is demonstrated by an accurate measurement of lattice relaxation in a thin TEM sample. Clustering in an alloy can then be distinguished from a random distribution of atoms. In In{sub x}Ga{sub 1-x}N for instance, clustering is detected for concentrations x>0.1. The sensitivity is insufficient to determine whether clustering is present for lower concentrations. HRTEM allows to identify the amplitude and the spatial distribution of the decomposition which is attributed to a spinodal decomposition. In InN, nanometer scale metallic indium inclusions are detected. With decreasing size of the metallic clusters, the photoluminescence of the sample shifts towards the infrared. This indicates that the inclusions may be responsible for the infrared activity of InN. Finally, ZnO grown homoepitaxially on zinc-face and oxygen-face substrates is studied. The O-face epilayer is strained whereas the Zn-face epilayer is almost strain free and has a higher crystalline quality. Quantitative analysis of exit wave phases is in good agreement with simulations, but the signal to noise ratio needs to be improved for the detection of single point defects. (orig.)

  6. Somatotyping using 3D anthropometry: a cluster analysis.

    Science.gov (United States)

    Olds, Tim; Daniell, Nathan; Petkov, John; David Stewart, Arthur

    2013-01-01

    Somatotyping is the quantification of human body shape, independent of body size. Hitherto, somatotyping (including the most popular method, the Heath-Carter system) has been based on subjective visual ratings, sometimes supported by surface anthropometry. This study used data derived from three-dimensional (3D) whole-body scans as inputs for cluster analysis to objectively derive clusters of similar body shapes. Twenty-nine dimensions normalised for body size were measured on a purposive sample of 301 adults aged 17-56 years who had been scanned using a Vitus Smart laser scanner. K-means Cluster Analysis with v-fold cross-validation was used to determine shape clusters. Three male and three female clusters emerged, and were visualised using those scans closest to the cluster centroid and a caricature defined by doubling the difference between the average scan and the cluster centroid. The male clusters were decidedly endomorphic (high fatness), ectomorphic (high linearity), and endo-mesomorphic (a mixture of fatness and muscularity). The female clusters were clearly endomorphic, ectomorphic, and the ecto-mesomorphic (a mixture of linearity and muscularity). An objective shape quantification procedure combining 3D scanning and cluster analysis yielded shape clusters strikingly similar to traditional somatotyping.

  7. A hybrid monkey search algorithm for clustering analysis.

    Science.gov (United States)

    Chen, Xin; Zhou, Yongquan; Luo, Qifang

    2014-01-01

    Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to fall into local optimum solution. In view of the disadvantages of the k-means method, this paper proposed a hybrid monkey algorithm based on search operator of artificial bee colony algorithm for clustering analysis and experiment on synthetic and real life datasets to show that the algorithm has a good performance than that of the basic monkey algorithm for clustering analysis.

  8. A Hybrid Monkey Search Algorithm for Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Xin Chen

    2014-01-01

    Full Text Available Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to fall into local optimum solution. In view of the disadvantages of the k-means method, this paper proposed a hybrid monkey algorithm based on search operator of artificial bee colony algorithm for clustering analysis and experiment on synthetic and real life datasets to show that the algorithm has a good performance than that of the basic monkey algorithm for clustering analysis.

  9. Smartness and Italian Cities. A Cluster Analysis

    Directory of Open Access Journals (Sweden)

    Flavio Boscacci

    2014-05-01

    Full Text Available Smart cities have been recently recognized as the most pleasing and attractive places to live in; due to this, both scholars and policy-makers pay close attention to this topic. Specifically, urban “smartness” has been identified by plenty of characteristics that can be grouped into six dimensions (Giffinger et al. 2007: smart Economy (competitiveness, smart People (social and human capital, smart Governance (participation, smart Mobility (both ICTs and transport, smart Environment (natural resources, and smart Living (quality of life. According to this analytical framework, in the present paper the relation between urban attractiveness and the “smart” characteristics has been investigated in the 103 Italian NUTS3 province capitals in the year 2011. To this aim, a descriptive statistics has been followed by a regression analysis (OLS, where the dependent variable measuring the urban attractiveness has been proxied by housing market prices. Besides, a Cluster Analysis (CA has been developed in order to find differences and commonalities among the province capitals.The OLS results indicate that living, people and economy are the key drivers for achieving a better urban attractiveness. Environment, instead, keeps on playing a minor role. Besides, the CA groups the province capitals a

  10. Instantaneous normal mode analysis of melting of finite dust clusters.

    Science.gov (United States)

    Melzer, André; Schella, André; Schablinski, Jan; Block, Dietmar; Piel, Alexander

    2012-06-01

    The experimental melting transition of finite two-dimensional dust clusters in a dusty plasma is analyzed using the method of instantaneous normal modes. In the experiment, dust clusters are heated in a thermodynamic equilibrium from a solid to a liquid state using a four-axis laser manipulation system. The fluid properties of the dust cluster, such as the diffusion constant, are measured from the instantaneous normal mode analysis. Thereby, the phase transition of these finite clusters is approached from the liquid phase. From the diffusion constants, unique melting temperatures have been assigned to dust clusters of various sizes that very well reflect their dynamical stability properties.

  11. Cluster Analysis to Identify Possible Subgroups in Tinnitus Patients.

    Science.gov (United States)

    van den Berge, Minke J C; Free, Rolien H; Arnold, Rosemarie; de Kleine, Emile; Hofman, Rutger; van Dijk, J Marc C; van Dijk, Pim

    2017-01-01

    In tinnitus treatment, there is a tendency to shift from a "one size fits all" to a more individual, patient-tailored approach. Insight in the heterogeneity of the tinnitus spectrum might improve the management of tinnitus patients in terms of choice of treatment and identification of patients with severe mental distress. The goal of this study was to identify subgroups in a large group of tinnitus patients. Data were collected from patients with severe tinnitus complaints visiting our tertiary referral tinnitus care group at the University Medical Center Groningen. Patient-reported and physician-reported variables were collected during their visit to our clinic. Cluster analyses were used to characterize subgroups. For the selection of the right variables to enter in the cluster analysis, two approaches were used: (1) variable reduction with principle component analysis and (2) variable selection based on expert opinion. Various variables of 1,783 tinnitus patients were included in the analyses. Cluster analysis (1) included 976 patients and resulted in a four-cluster solution. The effect of external influences was the most discriminative between the groups, or clusters, of patients. The "silhouette measure" of the cluster outcome was low (0.2), indicating a "no substantial" cluster structure. Cluster analysis (2) included 761 patients and resulted in a three-cluster solution, comparable to the first analysis. Again, a "no substantial" cluster structure was found (0.2). Two cluster analyses on a large database of tinnitus patients revealed that clusters of patients are mostly formed by a different response of external influences on their disease. However, both cluster outcomes based on this dataset showed a poor stability, suggesting that our tinnitus population comprises a continuum rather than a number of clearly defined subgroups.

  12. PERFORMANCE ANALYSIS OF CLUSTERED RADIO INTERFEROMETRIC CALIBRATION

    NARCIS (Netherlands)

    Kazemi, S.; Yatawatta, S.; Zaroubi, S.

    2012-01-01

    Subtraction of compact, bright sources is essential to produce high quality images in radio astronomy. It is recently proposed that 'clustered' calibration can perform better in subtracting fainter background sources. This is due to the fact that the effective power of a source cluster is greater th

  13. The Psychology of Yoga Practitioners: A Cluster Analysis.

    Science.gov (United States)

    Genovese, Jeremy E C; Fondran, Kristine M

    2017-03-30

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

  14. Using Cluster Analysis for Data Mining in Educational Technology Research

    Science.gov (United States)

    Antonenko, Pavlo D.; Toy, Serkan; Niederhauser, Dale S.

    2012-01-01

    Cluster analysis is a group of statistical methods that has great potential for analyzing the vast amounts of web server-log data to understand student learning from hyperlinked information resources. In this methodological paper we provide an introduction to cluster analysis for educational technology researchers and illustrate its use through…

  15. A Survey of Popular R Packages for Cluster Analysis

    Science.gov (United States)

    Flynt, Abby; Dean, Nema

    2016-01-01

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

  16. Using Cluster Analysis for Data Mining in Educational Technology Research

    Science.gov (United States)

    Antonenko, Pavlo D.; Toy, Serkan; Niederhauser, Dale S.

    2012-01-01

    Cluster analysis is a group of statistical methods that has great potential for analyzing the vast amounts of web server-log data to understand student learning from hyperlinked information resources. In this methodological paper we provide an introduction to cluster analysis for educational technology researchers and illustrate its use through…

  17. A Survey of Popular R Packages for Cluster Analysis

    Science.gov (United States)

    Flynt, Abby; Dean, Nema

    2016-01-01

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

  18. Preparation and Analysis of Atom Probe Tips by Xenon Focused Ion Beam Milling.

    Science.gov (United States)

    Estivill, Robert; Audoit, Guillaume; Barnes, Jean-Paul; Grenier, Adeline; Blavette, Didier

    2016-06-01

    The damage and ion distribution induced in Si by an inductively coupled plasma Xe focused ion beam was investigated by atom probe tomography. By using predefined patterns it was possible to prepare the atom probe tips with a sub 50 nm end radius in the ion beam microscope. The atom probe reconstruction shows good agreement with simulated implantation profiles and interplanar distances extracted from spatial distribution maps. The elemental profiles of O and C indicate co-implantation during the milling process. The presence of small disc-shaped Xe clusters are also found in the three-dimensional reconstruction. These are attributed to the presence of Xe nanocrystals or bubbles that open during the evaporation process. The expected accumulated dose points to a loss of >95% of the Xe during analysis, which escapes undetected.

  19. Cluster analysis of the hot subdwarfs in the PG survey

    Science.gov (United States)

    Thejll, Peter; Charache, Darryl; Shipman, Harry L.

    1989-01-01

    Application of cluster analysis to the hot subdwarfs in the Palomar Green (PG) survey of faint blue high-Galactic-latitude objects is assessed, with emphasis on data noise and the number of clusters to subdivide the data into. The data used in the study are presented, and cluster analysis, using the CLUSTAN program, is applied to it. Distances are calculated using the Euclidean formula, and clustering is done by Ward's method. The results are discussed, and five groups representing natural divisions of the subdwarfs in the PG survey are presented.

  20. Carbon nanotubes randomly decorated with gold clusters: from nano{sup 2}hybrid atomic structures to gas sensing prototypes

    Energy Technology Data Exchange (ETDEWEB)

    Charlier, J-C; Zanolli, Z [Unite de Physico-Chimie et de Physique des Materiaux (PCPM), European Theoretical Spectroscopy Facility (ETSF), Universite Catholique de Louvain, Place Croix du Sud 1, B-1348 Louvain-la-Neuve (Belgium); Arnaud, L; Avilov, I V; Felten, A; Pireaux, J-J [Centre de Recherche en Physique de la Matiere et du Rayonnement (PMR-LISE), Facultes Universitaires Notre-Dame de la Paix, 61 Rue de Bruxelles, B-5000 Namur (Belgium); Delgado, M [Sensotran, s.l., Avenida Remolar 31, E-08820 El Prat de Llobregat, Barcelona (Spain); Demoisson, F; Reniers, F [Service de Chimie Analytique et Chimie des Interfaces (CHANI), Universite Libre de Bruxelles, Faculte des Sciences, CP255, Boulevard du Triomphe 2, B-1050 Bruxelles (Belgium); Espinosa, E H; Ionescu, R; Leghrib, R; Llobet, E [Department of Electronic Engineering, Universitat Rovira i Virgili, Avenida Paisos Catalans 26, E-43007 Tarragona (Spain); Ewels, C P; Suarez-Martinez, I [Institut des Materiaux Jean Rouxel (IMN), Universite de Nantes, 2 rue de la Houssiniere-BP 32229, F-44322 Nantes Cedex 3 (France); Guillot, J; Mansour, A; Migeon, H-N [Departement Science et Analyse des Materiaux, Centre de Recherche Public-Gabriel Lippmann, rue du Brill 41, L-4422 Belvaux (Luxembourg); Watson, G E, E-mail: jean-jacques.pireaux@fundp.ac.b [Vega Science Trust, Unit 118, Science Park SQ, Brighton, BN1 9SB (United Kingdom)

    2009-09-16

    Carbon nanotube surfaces, activated and randomly decorated with metal nanoclusters, have been studied in uniquely combined theoretical and experimental approaches as prototypes for molecular recognition. The key concept is to shape metallic clusters that donate or accept a fractional charge upon adsorption of a target molecule, and modify the electron transport in the nanotube. The present work focuses on a simple system, carbon nanotubes with gold clusters. The nature of the gold-nanotube interaction is studied using first-principles techniques. The numerical simulations predict the binding and diffusion energies of gold atoms at the tube surface, including realistic atomic models for defects potentially present at the nanotube surface. The atomic structure of the gold nanoclusters and their effect on the intrinsic electronic quantum transport properties of the nanotube are also predicted. Experimentally, multi-wall CNTs are decorated with gold clusters using (1) vacuum evaporation, after activation with an RF oxygen plasma and (2) colloid solution injected into an RF atmospheric plasma; the hybrid systems are accurately characterized using XPS and TEM techniques. The response of gas sensors based on these nano{sup 2}hybrids is quantified for the detection of toxic species like NO{sub 2}, CO, C{sub 2}H{sub 5}OH and C{sub 2}H{sub 4}.

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

    Science.gov (United States)

    DiStefano, Christine; Kamphaus, R. W.

    2006-01-01

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

  2. The application of cluster analysis in the intercomparison of loop structures in RNA.

    Science.gov (United States)

    Huang, Hung-Chung; Nagaswamy, Uma; Fox, George E

    2005-04-01

    We have developed a computational approach for the comparison and classification of RNA loop structures. Hairpin or interior loops identified in atomic resolution RNA structures were intercompared by conformational matching. The root-mean-square deviation (RMSD) values between all pairs of RNA fragments of interest, even if from different molecules, are calculated. Subsequently, cluster analysis is performed on the resulting matrix of RMSD distances using the unweighted pair group method with arithmetic mean (UPGMA). The cluster analysis objectively reveals groups of folds that resemble one another. To demonstrate the utility of the approach, a comprehensive analysis of all the terminal hairpin tetraloops that have been observed in 15 RNA structures that have been determined by X-ray crystallography was undertaken. The method found major clusters corresponding to the well-known GNRA and UNCG types. In addition, two tetraloops with the unusual primary sequence UMAC (M is A or C) were successfully assigned to the GNRA cluster. Larger loop structures were also examined and the clustering results confirmed the occurrence of variations of the GNRA and UNCG tetraloops in these loops and provided a systematic means for locating them. Nineteen examples of larger loops that closely resemble either the GNRA or UNCG tetraloop were found in the large ribosomal RNAs. When the clustering approach was extended to include all structures in the SCOR database, novel relationships were detected including one between the ANYA motif and a less common folding of the GAAA tetraloop sequence.

  3. Study of atomic clusters in neutron irradiated reactor pressure vessel surveillance samples by extended X-ray absorption fine structure spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Cammelli, S. [LWV, NES, Paul Scherrer Institute, 5232 Villigen PSI (Switzerland); Fachbereich C - Physik, Bergische Universitaet Wuppertal, Gauss-Str. 20, 42097 Wuppertal (Germany)], E-mail: Sebastiano.cammelli@psi.ch; Degueldre, C.; Kuri, G.; Bertsch, J. [LWV, NES, Paul Scherrer Institute, 5232 Villigen PSI (Switzerland); Luetzenkirchen-Hecht, D.; Frahm, R. [Fachbereich C - Physik, Bergische Universitaet Wuppertal, Gauss-Str. 20, 42097 Wuppertal (Germany)

    2009-03-31

    Copper and nickel impurities in nuclear reactor pressure vessel (RPV) steel can form nano-clusters, which have a strong impact on the ductile-brittle transition temperature of the material. Thus, for control purposes and simulation of long irradiation times, surveillance samples are submitted to enhanced neutron irradiation. In this work, surveillance samples from a Swiss nuclear power plant were investigated by extended X-ray absorption fine structure spectroscopy (EXAFS). The density of Cu and Ni atoms determined in the first and second shells around the absorber is affected by the irradiation and temperature. The comparison of the EXAFS data at Cu and Ni K-edges shows that these elements reside in arrangements similar to bcc Fe. However, the EXAFS analysis reveals local irradiation damage in the form of vacancy fractions, which can be determined with a precision of {approx}5%. There are indications that the formation of Cu and Ni clusters differs significantly.

  4. Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

    Science.gov (United States)

    Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

    2017-01-01

    Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

  5. Analysis of a free oscillation atom interferometer

    CERN Document Server

    Kafle, Rudra P; Zozulya, Alex A

    2011-01-01

    We analyze a Bose-Einstein condensate (BEC) - based free oscillation atom Michelson interferometer in a weakly confining harmonic magnetic trap. A BEC at the center of the trap is split into two harmonics by a laser standing wave. The harmonics move in opposite directions with equal speeds and turn back under the influence of the trapping potential at their classical turning points. The harmonics are allowed to pass through each other and a recombination pulse is applied when they overlap at the end of a cycle after they return for the second time. We derive an expression for the contrast of the interferometric fringes and obtain the fundamental limit of performance of the interferometer in the parameter space.

  6. Analysis of Stemming Algorithm for Text Clustering

    Directory of Open Access Journals (Sweden)

    N.Sandhya

    2011-09-01

    Full Text Available Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. In Bag of words representation of documents the words that appear in documents often have many morphological variants and in most cases, morphological variants of words have similar semantic interpretations and can be considered as equivalent for the purpose of clustering applications. For this reason, a number of stemming Algorithms, or stemmers, have been developed, which attempt to reduce a word to its stem or root form. Thus, the key terms of a document are represented by stems rather than by the original words. In this work we have studied the impact of stemming algorithm along with four popular similarity measures (Euclidean, cosine, Pearson correlation and extended Jaccard in conjunction with different types of vector representation (boolean, term frequency and term frequency and inverse document frequency on cluster quality. For Clustering documents we have used partitional based clustering technique K Means. Performance is measured against a human-imposed classification of Classic data set. We conducted a number of experiments and used entropy measure to assure statistical significance of results. Cosine, Pearson correlation and extended Jaccard similarities emerge as the best measures to capture human categorization behavior, while Euclidean measures perform poor. After applying the Stemming algorithm Euclidean measure shows little improvement.

  7. Toward optimal cluster power spectrum analysis

    CERN Document Server

    Smith, Robert E

    2014-01-01

    The power spectrum of galaxy clusters is an important probe of the cosmological model. In this paper we determine the optimal weighting scheme for maximizing the signal-to-noise ratio for such measurements. We find a closed form analytic expression for the optimal weights. Our expression takes into account: cluster mass, finite survey volume effects, survey masking, and a flux limit. The implementation of this weighting scheme requires knowledge of the measured cluster masses, and analytic models for the bias and space-density of clusters as a function of mass and redshift. Recent studies have suggested that the optimal method for reconstruction of the matter density field from a set of clusters is mass-weighting (Seljak et al 2009, Hamaus et al 2010, Cai et al 2011). We compare our optimal weighting scheme with this approach and also with the original power spectrum scheme of Feldman et al (1994). We show that our optimal weighting scheme outperforms these approaches for both volume- and flux-limited cluster...

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

    Science.gov (United States)

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

    2017-07-01

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

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

    Science.gov (United States)

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

    2017-03-01

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

  10. Three-Dimensional Assignment of the Structures of Atomic Clusters: an Example of Au8M (M=Si, Ge, Sn) Anion Clusters

    Science.gov (United States)

    Liu, Yi-Rong; Huang, Teng; Gai, Yan-Bo; Zhang, Yang; Feng, Ya-Juan; Huang, Wei

    2015-12-01

    Identification of different isomer structures of atomic and molecular clusters has long been a challenging task in the field of cluster science. Here we present a three-dimensional (3D) assignment method, combining the energy (1D) and simulated (2D) spectra to assure the assignment of the global minimum structure. This method is more accurate and convenient than traditional methods, which only consider the total energy and first vertical detachment energies (VDEs) of anion clusters. There are two prerequisites when the 3D assignment method is ultilized. First, a reliable global minimum search algorithm is necessary to explore enough valleys on the potential energy surface. Second, trustworthy simulated spectra are necessary, that is to say, spectra that are in quantitative agreement. In this paper, we demonstrate the validity of the 3D assignment method using Au8M- (M = Si, Ge, Sn) systems. Results from this study indicate that the global minimum structures of Au8Ge- and Au8Sn- clusters are different from those described in previous studies.

  11. Intelligent Hybrid Cluster Based Classification Algorithm for Social Network Analysis

    Directory of Open Access Journals (Sweden)

    S. Muthurajkumar

    2014-05-01

    Full Text Available In this paper, we propose an hybrid clustering based classification algorithm based on mean approach to effectively classify to mine the ordered sequences (paths from weblog data in order to perform social network analysis. In the system proposed in this work for social pattern analysis, the sequences of human activities are typically analyzed by switching behaviors, which are likely to produce overlapping clusters. In this proposed system, a robust Modified Boosting algorithm is proposed to hybrid clustering based classification for clustering the data. This work is useful to provide connection between the aggregated features from the network data and traditional indices used in social network analysis. Experimental results show that the proposed algorithm improves the decision results from data clustering when combined with the proposed classification algorithm and hence it is proved that of provides better classification accuracy when tested with Weblog dataset. In addition, this algorithm improves the predictive performance especially for multiclass datasets which can increases the accuracy.

  12. Bayesian model-based cluster analysis for predicting macrofaunal communities

    NARCIS (Netherlands)

    Braak, ter C.J.F.; Hoijtink, H.; Akkermans, W.; Verdonschot, P.F.M.

    2003-01-01

    To predict macrofaunal community composition from environmental data a two-step approach is often followed: (1) the water samples are clustered into groups on the basis of the macrofauna data and (2) the groups are related to the environmental data, e.g. by discriminant analysis. For the cluster ana

  13. Atom trap trace analysis of {sup 39}Ar

    Energy Technology Data Exchange (ETDEWEB)

    Welte, Joachim

    2011-12-14

    Detection of {sup 39}Ar in natural water samples can be employed for radiometric dating on a timescale of 50 to 1000 years before present. This experimental work comprises the setup of an atomic beam and trap apparatus that captures and detects {sup 39}Ar atoms by the laser-cooling technique ''Atom Trap Trace Analysis''. With this approach, the limitations of low-level counting, regarding sample size and measurement time, could be overcome. In the course of this work, the hyperfine structure spectrum of the cooling transition 1s{sub 5}-2p{sub 9} has been experimentally determined. A high intensity, optically collimated beam of slow metastable argon atoms has been set up and fluorescence detection of individual {sup 39}Ar atoms in a magneto-optical trap is realized. {sup 39}Ar count rates of 1 atom in about 4 hours have been achieved for atmospheric argon. Recent improvements further suggest that even higher count rates of 1 atom/hour are within reach.

  14. Cluster growing process and a sequence of magic numbers

    DEFF Research Database (Denmark)

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

    2003-01-01

    demonstrate that in this way all known global minimum structures of the Lennard-Jones (LJ) clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence for the clusters of noble gas atoms......We present a new theoretical framework for modeling the cluster growing process. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system, and absorbing its energy at each step, we find cluster growing paths up to the cluster sizes of more than 100 atoms. We...... and compare it with experimental observations....

  15. Atomic Beam Laser Spectrometer for In-field Isotopic Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Castro, Alonso [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Actinide Analytical Chemistry Group

    2016-06-22

    This is a powerpoint presentation for the DTRA quarterly program review that goes into detail about the atomic beam laser spectrometer for in-field isotopic analysis. The project goals are the following: analysis of post-detonation debris, determination of U and Pu isotopic composition, and fieldable prototype: < 2ft3, < 1000W.

  16. Hierarchical Cluster Analysis – Various Approaches to Data Preparation

    Directory of Open Access Journals (Sweden)

    Z. Pacáková

    2013-09-01

    Full Text Available The article deals with two various approaches to data preparation to avoid multicollinearity. The aim of the article is to find similarities among the e-communication level of EU states using hierarchical cluster analysis. The original set of fourteen indicators was first reduced on the basis of correlation analysis while in case of high correlation indicator of higher variability was included in further analysis. Secondly the data were transformed using principal component analysis while the principal components are poorly correlated. For further analysis five principal components explaining about 92% of variance were selected. Hierarchical cluster analysis was performed both based on the reduced data set and the principal component scores. Both times three clusters were assumed following Pseudo t-Squared and Pseudo F Statistic, but the final clusters were not identical. An important characteristic to compare the two results found was to look at the proportion of variance accounted for by the clusters which was about ten percent higher for the principal component scores (57.8% compared to 47%. Therefore it can be stated, that in case of using principal component scores as an input variables for cluster analysis with explained proportion high enough (about 92% for in our analysis, the loss of information is lower compared to data reduction on the basis of correlation analysis.

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

    Science.gov (United States)

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

    2016-01-01

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

  18. Formation of Exotic Networks of Water Clusters in Helium Droplets Facilitated by the Presence of Neon Atoms

    Energy Technology Data Exchange (ETDEWEB)

    Douberly, Gary E.; Miller, Roger E.; Xantheas, Sotiris S.

    2017-03-08

    Water clusters are formed in helium droplets via the sequential capture of monomers. One or two neon atoms are added to each droplet prior to the addition of water. The infrared spectrum of the droplet ensemble reveals several signatures of polar, water tetramer clusters having dipole moments between 2D and 3D. Comparison with ab initio computations supports the assignment of the cluster networks to noncyclic “3+1” clusters, which are ~5.3 kcal/mol less stable than the global minimum nonpolar cyclic tetramer. The (H2O)3Ne + H2O ring insertion barrier is sufficiently large, such that evaporative helium cooling is capable of kinetically quenching the nonequilibrium tetramer system prior to its rearrangement to the lower energy cyclic species. To this end, the reported process results in the formation of exotic water cluster networks that are either higher in energy than the most stable gas-phase analogs or not even stable in the gas phase.

  19. Formation of Exotic Networks of Water Clusters in Helium Droplets Facilitated by the Presence of Neon Atoms.

    Science.gov (United States)

    Douberly, Gary E; Miller, Roger E; Xantheas, Sotiris S

    2017-03-22

    Water clusters are formed in helium droplets via the sequential capture of monomers. One or two neon atoms are added to each droplet prior to the addition of water. The infrared spectrum of the droplet ensemble reveals several signatures of polar, water tetramer clusters having dipole moments between 2D and 3D. Comparison with ab initio computations supports the assignment of the cluster networks to noncyclic "3 + 1" clusters, which are ∼5.3 kcal/mol less stable than the global minimum nonpolar cyclic tetramer. The (H2O)3Ne + H2O ring insertion barrier is sufficiently large, such that evaporative helium cooling is capable of kinetically quenching the nonequilibrium tetramer system prior to its rearrangement to the lower energy cyclic species. To this end, the reported process results in the formation of exotic water cluster networks that are either higher in energy than the most stable gas-phase analogs or not even stable in the gas phase.

  20. Entropic Approach to Multiscale Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Antonio Insolia

    2012-05-01

    Full Text Available Recently, a novel method has been introduced to estimate the statistical significance of clustering in the direction distribution of objects. The method involves a multiscale procedure, based on the Kullback–Leibler divergence and the Gumbel statistics of extreme values, providing high discrimination power, even in presence of strong background isotropic contamination. It is shown that the method is: (i semi-analytical, drastically reducing computation time; (ii very sensitive to small, medium and large scale clustering; (iii not biased against the null hypothesis. Applications to the physics of ultra-high energy cosmic rays, as a cosmological probe, are presented and discussed.

  1. Obstructive Sleep Apnea: A Cluster Analysis at Time of Diagnosis

    Science.gov (United States)

    Grillet, Yves; Richard, Philippe; Stach, Bruno; Vivodtzev, Isabelle; Timsit, Jean-Francois; Lévy, Patrick; Tamisier, Renaud; Pépin, Jean-Louis

    2016-01-01

    Background The classification of obstructive sleep apnea is on the basis of sleep study criteria that may not adequately capture disease heterogeneity. Improved phenotyping may improve prognosis prediction and help select therapeutic strategies. Objectives: This study used cluster analysis to investigate the clinical clusters of obstructive sleep apnea. Methods An ascending hierarchical cluster analysis was performed on baseline symptoms, physical examination, risk factor exposure and co-morbidities from 18,263 participants in the OSFP (French national registry of sleep apnea). The probability for criteria to be associated with a given cluster was assessed using odds ratios, determined by univariate logistic regression. Results: Six clusters were identified, in which patients varied considerably in age, sex, symptoms, obesity, co-morbidities and environmental risk factors. The main significant differences between clusters were minimally symptomatic versus sleepy obstructive sleep apnea patients, lean versus obese, and among obese patients different combinations of co-morbidities and environmental risk factors. Conclusions Our cluster analysis identified six distinct clusters of obstructive sleep apnea. Our findings underscore the high degree of heterogeneity that exists within obstructive sleep apnea patients regarding clinical presentation, risk factors and consequences. This may help in both research and clinical practice for validating new prevention programs, in diagnosis and in decisions regarding therapeutic strategies. PMID:27314230

  2. Detection of Functional Change Using Cluster Trend Analysis in Glaucoma.

    Science.gov (United States)

    Gardiner, Stuart K; Mansberger, Steven L; Demirel, Shaban

    2017-05-01

    Global analyses using mean deviation (MD) assess visual field progression, but can miss localized changes. Pointwise analyses are more sensitive to localized progression, but more variable so require confirmation. This study assessed whether cluster trend analysis, averaging information across subsets of locations, could improve progression detection. A total of 133 test-retest eyes were tested 7 to 10 times. Rates of change and P values were calculated for possible re-orderings of these series to generate global analysis ("MD worsening faster than x dB/y with P cluster analyses ("n locations [or clusters] worsening faster than x dB/y with P cluster analysis criterion, and 4.1 years (95% CI, 4.0-4.5) for the best pointwise criterion. However, for pointwise analysis, only 38% of these changes were confirmed, compared with 61% for clusters and 76% for MD. The time until 25% of eyes showed subsequently confirmed deterioration was 6.3 years (95% CI, 6.0-7.2) for global, 6.3 years (95% CI, 6.0-7.0) for pointwise, and 6.0 years (95% CI, 5.3-6.6) for cluster analyses. Although the specificity is still suboptimal, cluster trend analysis detects subsequently confirmed deterioration sooner than either global or pointwise analyses.

  3. [On National Demonstration Areas: a cluster analysis].

    Science.gov (United States)

    Mao, F; Jiang, Y Y; Dong, W L; Ji, N; Dong, J Q

    2017-04-10

    Objective: To understand the 'backward' provinces and the relatively poor work among the construction of National Demonstration Area, so as to promote communication and future visions among different regions. Methods: Methods on Cluster analysis were used to compare the development of National Demonstration Area in different provinces, including the coverage of National Demonstration Area and the scores of non-communicable disease (NCDs) prevention and control work based on a standardized indicating system. Results: According to the results from the construction of National Demonstration Area, all the 29 provinces and the Xinjiang Production and Construction Corps (except Tibet and Qinghai) were classified into 6 categories: Shanghai; Beijing, Zhejiang, Chongqing; Tianjin, Shandong, Guangdong and Xinjiang Production and Construction Corps; Hebei, Fujian, Hubei, Jiangsu, Liaoning, Xinjiang, Hunan and Guangxi; Shanxi, Jilin, Henan, Hainan,Sichuan, Anhui and Jiangxi; Inner Mongolia, Shaanxi, Ningxia, Guizhou, Yunnan, Gansu and Heilongjiang. Based on the scores gathered from this study, 24 items that representing the achievements from the NCDs prevention and control endeavor were classified into 4 categories: Manpower, special day on NCD, information materials development, policy/strategy support, financial support, mass media, enabled environment, community fitness campaign, health promotion for children and teenage, institutional structure and patient self-management; healthy diet, risk factors on NCDs surveillance, tobacco control and community diagnosis; intervention of high-risk groups, identification of high-risk groups, reporting system on cardiovascular and cerebrovascular events, popularization of basic public health service, workplace intervention programs, construction of demonstration units and mortality surveillance; oral hygiene and tumor registration. Contents including oral hygiene, tumor registration, intervention on high-risk groups, identification of

  4. Collective properties of deformed atomic clusters described within a projected spherical basis

    OpenAIRE

    Raduta, A. A.; Raduta, Al. H.; Budaca, R.

    2011-01-01

    Several relevant properties of the Na clusters were studied by using a projected spherical single particle states.The proposed model is able to describe in an unified fashion the spherical and deformed clusters. Photoabsorbtion cross section is realistically explained within an RPA approach and a Shiff dipole moment as a transition operator

  5. Combining Theory and Experiment to Characterize the Atomic Structures of Surface-Deposited Au309 Clusters

    NARCIS (Netherlands)

    Curley, B.C.; Johnston, R.L.; Young, N.P.; Li, Z.; Di Vece, M.; Palmer, R.E.; Bleloch, A.l.

    2007-01-01

    Gold clusters with icosahedral, decahedral, and cuboctahedral shell structures, have been studied using the Gupta many-body potential, to aid in the structural characterization of surface-deposited Au309 clusters using high-angle annular dark field-scanning transmission electron microscopy (HAADF-ST

  6. Accurate van der Waals coefficients between fullerenes and fullerene-alkali atoms and clusters: Modified single-frequency approximation

    Science.gov (United States)

    Tao, Jianmin; Mo, Yuxiang; Tian, Guocai; Ruzsinszky, Adrienn

    2016-08-01

    Long-range van der Waals (vdW) interaction is critically important for intermolecular interactions in molecular complexes and solids. However, accurate modeling of vdW coefficients presents a great challenge for nanostructures, in particular for fullerene clusters, which have huge vdW coefficients but also display very strong nonadditivity. In this work, we calculate the coefficients between fullerenes, fullerene and sodium clusters, and fullerene and alkali atoms with the hollow-sphere model within the modified single-frequency approximation (MSFA). In the MSFA, we assume that the electron density is uniform in a molecule and that only valence electrons in the outmost subshell of atoms contribute. The input to the model is the static multipole polarizability, which provides a sharp cutoff for the plasmon contribution outside the effective vdW radius. We find that the model can generate C6 in excellent agreement with expensive wave-function-based ab initio calculations, with a mean absolute relative error of only 3 % , without suffering size-dependent error. We show that the nonadditivities of the coefficients C6 between fullerenes and C60 and sodium clusters Nan revealed by the model agree remarkably well with those based on the accurate reference values. The great flexibility, simplicity, and high accuracy make the model particularly suitable for the study of the nonadditivity of vdW coefficients between nanostructures, advancing the development of better vdW corrections to conventional density functional theory.

  7. Design and Analysis Considerations for Cluster Randomized Controlled Trials That Have a Small Number of Clusters.

    Science.gov (United States)

    Deke, John

    2016-10-25

    Cluster randomized controlled trials (CRCTs) often require a large number of clusters in order to detect small effects with high probability. However, there are contexts where it may be possible to design a CRCT with a much smaller number of clusters (10 or fewer) and still detect meaningful effects. The objective is to offer recommendations for best practices in design and analysis for small CRCTs. I use simulations to examine alternative design and analysis approaches. Specifically, I examine (1) which analytic approaches control Type I errors at the desired rate, (2) which design and analytic approaches yield the most power, (3) what is the design effect of spurious correlations, and (4) examples of specific scenarios under which impacts of different sizes can be detected with high probability. I find that (1) mixed effects modeling and using Ordinary Least Squares (OLS) on data aggregated to the cluster level both control the Type I error rate, (2) randomization within blocks is always recommended, but how best to account for blocking through covariate adjustment depends on whether the precision gains offset the degrees of freedom loss, (3) power calculations can be accurate when design effects from small sample, spurious correlations are taken into account, and (4) it is very difficult to detect small effects with just four clusters, but with six or more clusters, there are realistic circumstances under which small effects can be detected with high probability. © The Author(s) 2016.

  8. Visual verification and analysis of cluster detection for molecular dynamics.

    Science.gov (United States)

    Grottel, Sebastian; Reina, Guido; Vrabec, Jadran; Ertl, Thomas

    2007-01-01

    A current research topic in molecular thermodynamics is the condensation of vapor to liquid and the investigation of this process at the molecular level. Condensation is found in many physical phenomena, e.g. the formation of atmospheric clouds or the processes inside steam turbines, where a detailed knowledge of the dynamics of condensation processes will help to optimize energy efficiency and avoid problems with droplets of macroscopic size. The key properties of these processes are the nucleation rate and the critical cluster size. For the calculation of these properties it is essential to make use of a meaningful definition of molecular clusters, which currently is a not completely resolved issue. In this paper a framework capable of interactively visualizing molecular datasets of such nucleation simulations is presented, with an emphasis on the detected molecular clusters. To check the quality of the results of the cluster detection, our framework introduces the concept of flow groups to highlight potential cluster evolution over time which is not detected by the employed algorithm. To confirm the findings of the visual analysis, we coupled the rendering view with a schematic view of the clusters' evolution. This allows to rapidly assess the quality of the molecular cluster detection algorithm and to identify locations in the simulation data in space as well as in time where the cluster detection fails. Thus, thermodynamics researchers can eliminate weaknesses in their cluster detection algorithms. Several examples for the effective and efficient usage of our tool are presented.

  9. 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.

  10. Differences in Pedaling Technique in Cycling: A Cluster Analysis.

    Science.gov (United States)

    Lanferdini, Fábio J; Bini, Rodrigo R; Figueiredo, Pedro; Diefenthaeler, Fernando; Mota, Carlos B; Arndt, Anton; Vaz, Marco A

    2016-10-01

    To employ cluster analysis to assess if cyclists would opt for different strategies in terms of neuromuscular patterns when pedaling at the power output of their second ventilatory threshold (POVT2) compared with cycling at their maximal power output (POMAX). Twenty athletes performed an incremental cycling test to determine their power output (POMAX and POVT2; first session), and pedal forces, muscle activation, muscle-tendon unit length, and vastus lateralis architecture (fascicle length, pennation angle, and muscle thickness) were recorded (second session) in POMAX and POVT2. Athletes were assigned to 2 clusters based on the behavior of outcome variables at POVT2 and POMAX using cluster analysis. Clusters 1 (n = 14) and 2 (n = 6) showed similar power output and oxygen uptake. Cluster 1 presented larger increases in pedal force and knee power than cluster 2, without differences for the index of effectiveness. Cluster 1 presented less variation in knee angle, muscle-tendon unit length, pennation angle, and tendon length than cluster 2. However, clusters 1 and 2 showed similar muscle thickness, fascicle length, and muscle activation. When cycling at POVT2 vs POMAX, cyclists could opt for keeping a constant knee power and pedal-force production, associated with an increase in tendon excursion and a constant fascicle length. Increases in power output lead to greater variations in knee angle, muscle-tendon unit length, tendon length, and pennation angle of vastus lateralis for a similar knee-extensor activation and smaller pedal-force changes in cyclists from cluster 2 than in cluster 1.

  11. Logistics Enterprise Evaluation Model Based On Fuzzy Clustering Analysis

    Science.gov (United States)

    Fu, Pei-hua; Yin, Hong-bo

    In this thesis, we introduced an evaluation model based on fuzzy cluster algorithm of logistics enterprises. First of all,we present the evaluation index system which contains basic information, management level, technical strength, transport capacity,informatization level, market competition and customer service. We decided the index weight according to the grades, and evaluated integrate ability of the logistics enterprises using fuzzy cluster analysis method. In this thesis, we introduced the system evaluation module and cluster analysis module in detail and described how we achieved these two modules. At last, we gave the result of the system.

  12. Cancer incidence in men: a cluster analysis of spatial patterns

    Directory of Open Access Journals (Sweden)

    D'Alò Daniela

    2008-11-01

    Full Text Available Abstract Background Spatial clustering of different diseases has received much less attention than single disease mapping. Besides chance or artifact, clustering of different cancers in a given area may depend on exposure to a shared risk factor or to multiple correlated factors (e.g. cigarette smoking and obesity in a deprived area. Models developed so far to investigate co-occurrence of diseases are not well-suited for analyzing many cancers simultaneously. In this paper we propose a simple two-step exploratory method for screening clusters of different cancers in a population. Methods Cancer incidence data were derived from the regional cancer registry of Umbria, Italy. A cluster analysis was performed on smoothed and non-smoothed standardized incidence ratios (SIRs of the 13 most frequent cancers in males. The Besag, York and Mollie model (BYM and Poisson kriging were used to produce smoothed SIRs. Results Cluster analysis on non-smoothed SIRs was poorly informative in terms of clustering of different cancers, as only larynx and oral cavity were grouped, and of characteristic patterns of cancer incidence in specific geographical areas. On the other hand BYM and Poisson kriging gave similar results, showing cancers of the oral cavity, larynx, esophagus, stomach and liver formed a main cluster. Lung and urinary bladder cancers clustered together but not with the cancers mentioned above. Both methods, particularly the BYM model, identified distinct geographic clusters of adjacent areas. Conclusion As in single disease mapping, non-smoothed SIRs do not provide reliable estimates of cancer risks because of small area variability. The BYM model produces smooth risk surfaces which, when entered into a cluster analysis, identify well-defined geographical clusters of adjacent areas. It probably enhances or amplifies the signal arising from exposure of more areas (statistical units to shared risk factors that are associated with different cancers. In

  13. Assessment of cluster yield components by image analysis.

    Science.gov (United States)

    Diago, Maria P; Tardaguila, Javier; Aleixos, Nuria; Millan, Borja; Prats-Montalban, Jose M; Cubero, Sergio; Blasco, Jose

    2015-04-01

    Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way. Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R(2) between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%. The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods. © 2014 Society of Chemical Industry.

  14. CLUSTERING ANALYSIS OF DEBRIS-FLOW STREAMS

    Institute of Scientific and Technical Information of China (English)

    Yuan-Fan TSAI; Huai-Kuang TSAI; Cheng-Yan KAO

    2004-01-01

    The Chi-Chi earthquake in 1999 caused disastrous landslides, which triggered numerous debris flows and killed hundreds of people. A critical rainfall intensity line for each debris-flow stream is studied to prevent such a disaster. However, setting rainfall lines from incomplete data is difficult, so this study considered eight critical factors to group streams, such that streams within a cluster have similar rainfall lines. A genetic algorithm is applied to group 377 debris-flow streams selected from the center of an area affected by the Chi-Chi earthquake. These streams are grouped into seven clusters with different characteristics. The results reveal that the proposed method effectively groups debris-flow streams.

  15. Detection of early glaucomatous progression with octopus cluster trend analysis.

    Science.gov (United States)

    Naghizadeh, Farzaneh; Holló, Gábor

    2014-01-01

    To compare the ability of Corrected Cluster Trend Analysis (CCTA) and Cluster Trend Analysis (CTA) with event analysis of Octopus visual field series to detect early glaucomatous progression. One eye of 15 healthy, 19 ocular hypertensive, 20 preperimetric, and 51 perimetric glaucoma (PG) patients were investigated with Octopus normal G2 test at 6-month intervals for 1.5 to 3 years. Progression was defined with significant worsening in any of the 10 Octopus clusters with CCTA, and event analysis criteria, respectively. With event analysis, 9 PG eyes showed localized progression and 1 diffuse mean defect (MD) worsening. With CCTA, progression was indicated in 1 normal, 1 ocular hypertensive, and 1 preperimetric glaucoma eyes due to vitreous floaters, and 28 PG eyes including all 9 eyes with localized progression with event analysis. The locations of CCTA progression matched those found with event analysis in all 9 cases. In 17 of the remaining 19 eyes, progressing clusters matched the locations that were suspicious but not definitive for progression with event analysis. In the eye with diffuse MD worsening, CTA found significant progression for 7 clusters. For global MD progression rate, eyes worsened with CCTA only did not differ from the stable eyes but had significantly smaller progression rates than the eyes progressed with event analysis (P=0.0002). In PG, Octopus CCTA and CTA are clinically useful to identify early progression and areas suspicious for early progression. However, in some eyes with no glaucomatous visual field damage, vitreous floaters may cause progression artifacts.

  16. Cluster Analysis of Gene Expression Data

    CERN Document Server

    Domany, E

    2002-01-01

    The expression levels of many thousands of genes can be measured simultaneously by DNA microarrays (chips). This novel experimental tool has revolutionized research in molecular biology and generated considerable excitement. A typical experiment uses a few tens of such chips, each dedicated to a single sample - such as tissue extracted from a particular tumor. The results of such an experiment contain several hundred thousand numbers, that come in the form of a table, of several thousand rows (one for each gene) and 50 - 100 columns (one for each sample). We developed a clustering methodology to mine such data. In this review I provide a very basic introduction to the subject, aimed at a physics audience with no prior knowledge of either gene expression or clustering methods. I explain what genes are, what is gene expression and how it is measured by DNA chips. Next I explain what is meant by "clustering" and how we analyze the massive amounts of data from such experiments, and present results obtained from a...

  17. Production of intense beams of mass-selected water cluster ions and theoretical study of atom-water interactions

    CERN Document Server

    Wang, Z P; Reinhard, P -G; Suraud, E; Bruny, G; Montano, C; Feil, S; Eden, S; Abdoul-Carime, H; Farizon, B; Farizon, M; Ouaskit, S; Maerk, T D

    2009-01-01

    The influences of water molecules surrounding biological molecules during irradiation with heavy particles (atoms,ions) are currently a major subject in radiation science on a molecular level. In order to elucidate the underlying complex reaction mechanisms we have initiated a joint experimental and theoretical investigation with the aim to make direct comparisons between experimental and theoretical results. As a first step, studies of collisions of a water molecule with a neutral projectile (C atom) at high velocities (> 0.1 a.u.), and with a charged projectile (proton) at low velocities (< 0.1 a.u.) have been studied within the microscopic framework. In particular, time-dependent density functional theory (TDDFT) was applied to the valence electrons and coupled non-adiabatically to Molecular dynamics (MD) for ionic cores. Complementary experimental developments have been carried out to study projectile interactions with accelerated (< 10 keV) and mass-selected cluster ions. The first size distributio...

  18. Comparative analysis of genomic signal processing for microarray data clustering.

    Science.gov (United States)

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  19. Using cluster analysis to organize and explore regional GPS velocities

    Science.gov (United States)

    Simpson, Robert W.; Thatcher, Wayne; Savage, James C.

    2012-01-01

    Cluster analysis offers a simple visual exploratory tool for the initial investigation of regional Global Positioning System (GPS) velocity observations, which are providing increasingly precise mappings of actively deforming continental lithosphere. The deformation fields from dense regional GPS networks can often be concisely described in terms of relatively coherent blocks bounded by active faults, although the choice of blocks, their number and size, can be subjective and is often guided by the distribution of known faults. To illustrate our method, we apply cluster analysis to GPS velocities from the San Francisco Bay Region, California, to search for spatially coherent patterns of deformation, including evidence of block-like behavior. The clustering process identifies four robust groupings of velocities that we identify with four crustal blocks. Although the analysis uses no prior geologic information other than the GPS velocities, the cluster/block boundaries track three major faults, both locked and creeping.

  20. Equation-Of Coupled-Cluster Calculations of Photodetachment Cross Sections for Atomic Negative Ions across the Periodic Table

    Science.gov (United States)

    Ichino, Takatoshi; Cheng, Lan; Stanton, John F.

    2016-06-01

    The innovative application of the ion-trap technique by Wester and coworkers has yielded definitive experimental values of photodetachment cross sections for the atomic oxygen radical anion (Obullet -) [Hlavenka et al., J. Chem. Phys. 130, 061105 (2009)]. In the present study, equation-of-motion coupled-cluster (EOM-CC) calculations have been performed to derive theoretical values of photodetachment cross sections for the negative ions of atoms in the first two periods of the periodic table as well as of those which belong to the alkali metal and halogen groups. Two methods have been employed to derive the cross sections. One involves the Dyson orbitals obtained from EOM-CC calculations and plane wave functions for the detached electron in the transition dipole moment integrals. The other method utilizes the moment theory following EOM-CC calculations of transition dipole moments for a large number of pseudo-states. The cross sections so evaluated for Obullet - match the experimental values very well. Generally good agreement has been found between the theoretical and experimental values of the cross sections for the atoms in the first two periods, while the present calculations cast some doubt on reported experimental values for some atoms beyond the second period. Substantial relativistic effects on the cross section have been observed for heavy elements in the alkali metal and halogen groups.

  1. Adsorption of beryllium atoms and clusters both on graphene and in a bilayer of graphite investigated by DFT.

    Science.gov (United States)

    Ferro, Yves; Fernandez, Nicolas; Allouche, Alain; Linsmeier, Christian

    2013-01-09

    We herein investigate the interaction of beryllium with a graphene sheet and in a bilayer of graphite by means of periodic DFT calculations. In all cases, we find the beryllium atoms to be more weakly bonded on graphene than in the bilayer. Be(2) forms both magnetic and non-magnetic structures on graphene depending on the geometrical configuration of adsorption. We find that the stability of the Be/bilayer system increases with the size of the beryllium clusters inserted into the bilayer of graphite. We also find a charge transfer from beryllium to the graphite layers. All these results are analysed in terms of electronic structure.

  2. Formation of globular clusters in atomic-cooling halos via rapid gas condensation and fragmentation during the epoch of reionization

    CERN Document Server

    Kimm, Taysun; Rosdahl, Joakim; Yi, Sukyoung

    2015-01-01

    We investigate the formation of metal-poor globular clusters (GCs) at the center of two dark matter halos with $M_{halo}\\sim4\\times10^7\\,M_\\odot$ at $z>10$ using cosmological radiation-hydrodynamics simulations. We find that very compact ($\\lesssim$ 1 pc) and massive ($\\sim6\\times10^5\\,M_\\odot$) clusters form rapidly when pristine gas collapses isothermally with the aid of efficient Ly$\\alpha$ emission during the transition from molecular-cooling halos to atomic-cooling halos. Because the local free-fall time of dense star-forming gas is very short ($\\ll 1\\,{\\rm Myr}$), a large fraction of the collapsed gas is turned into stars before stellar feedback processes blow out the gas and shut down star formation. Although the early stage of star formation is limited to a small region of the central star-forming disk, we find that the disk quickly fragments due to metal enrichment from supernovae. Sub-clusters formed in the fragmented clouds eventually merge with the main cluster at the center. We estimate using a s...

  3. Intense deuterium nuclear fusion of pycnodeuterium-lumps coagulated locally within highly deuterated atom clusters

    CERN Document Server

    Yoshiaki, A; Zhang, Y C

    2002-01-01

    Embedded nano-Pd particles of 5 nm in size instantly abundant D-atoms more than 250% in the atomic ratio against Pd-atoms at room temperature when they are kept in D sub 2 gas pressurized to less than 10 atm. In such ultrahigh densities, 2-4 D-atoms can be coagulated inside each octahedral space of Pd lattice (pycnodeuterium-lump). When a stimulation energy such as latticequake causing by ultrasonic wave was supplied to those highly deuterated Pd particles, intense deuterium nuclear fusion (''solid fusion'') was generated there and both excess heat and sup 4 He gas were abundantly produced. Naturally, these facts can not be realized at all in bulk Pd. The results show that the nuclear fusion occurs without any hazardous rays in pycnodeuterium-lumps coagulated locally inside the each cell of the host metal lattice. These unit cells correspond to minimum unit of the solid fusion reactor as a ''Lattice Reactor''. (author)

  4. Mode conversion of Mie plasmons at the surface of metallic atomic clusters

    Science.gov (United States)

    El-Khawaldeh, A.; Kull, H.-J.

    2017-04-01

    The dynamics of the Mie plasmon is described in the framework of the self-consistent quantum Vlasov theory by a reduced single-state model. The single-state model is validated by many-electron calculations for Na clusters. In this framework, collisionless damping of the Mie plasmon can be investigated for a wide range of cluster parameters by linear perturbation theory. The characteristic scaling of the damping rate with the inverse cluster radius is demonstrated. The basic damping mechanism of the Mie plasmon can be explained by a conversion of surface modes into volume modes due to the scattering by the self-consistent potential of the electron-electron interaction at the cluster boundary.

  5. Encapsulation method for atom probe tomography analysis of nanoparticles

    NARCIS (Netherlands)

    Larson, D.J.; Giddings, A.D.; Wub, Y.; Verheijen, M.A.; Prosa, T.J.; Roozeboom, F.; Rice, K.P.; Kessels, W.M.M.; Geiser, B.P.; Kelly, T.F.

    2015-01-01

    Open-space nanomaterials are a widespread class of technologically important materials that are generally incompatible with analysis by atom probe tomography (APT) due to issues with specimen preparation, field evaporation and data reconstruction. The feasibility of encapsulating such non-compact ma

  6. Atomic Force Analysis of Elastic Deformations of CD

    Directory of Open Access Journals (Sweden)

    A. Kuzmenko

    2013-12-01

    Full Text Available The procedure for the determination of elastic parameters according to reference nanometer lithographic marks by atomic force microscopy on samples with up to microscopic sizes is proposed. Analysis of dynamic changes of elastic characteristics that makes it possible to establish the critical rotation velocity of a CD without plastic deformations has been made.

  7. Atomic scale modelling of Al and Ni(1 1 1) surface erosion under cluster impact

    CERN Document Server

    Zhurkin, E E

    2003-01-01

    We have studied sputtering of Al and Ni(1 1 1) surfaces under impact of Al sub N and Ni sub N clusters (1=13. The pronounced microcraters are formed in the impact region above a threshold cluster size of around N=13. As a sensitivity study, we show that interaction with electronic subsystem of the target has a strong influence on secondary emission, but almost does not affect the features of surface microstructure of irradiated target.

  8. 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.

  9. A Distributed Flocking Approach for Information Stream Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-01-01

    Intelligence analysts are currently overwhelmed with the amount of information streams generated everyday. There is a lack of comprehensive tool that can real-time analyze the information streams. Document clustering analysis plays an important role in improving the accuracy of information retrieval. However, most clustering technologies can only be applied for analyzing the static document collection because they normally require a large amount of computation resource and long time to get accurate result. It is very difficult to cluster a dynamic changed text information streams on an individual computer. Our early research has resulted in a dynamic reactive flock clustering algorithm which can continually refine the clustering result and quickly react to the change of document contents. This character makes the algorithm suitable for cluster analyzing dynamic changed document information, such as text information stream. Because of the decentralized character of this algorithm, a distributed approach is a very natural way to increase the clustering speed of the algorithm. In this paper, we present a distributed multi-agent flocking approach for the text information stream clustering and discuss the decentralized architectures and communication schemes for load balance and status information synchronization in this approach.

  10. Cluster analysis of WIBS single particle bioaerosol data

    Directory of Open Access Journals (Sweden)

    N. H. Robinson

    2012-09-01

    Full Text Available Hierarchical agglomerative cluster analysis was performed on single-particle multi-spatial datasets comprising optical diameter, asymmetry and three different fluorescence measurements, gathered using two dual Waveband Integrated Bioaerosol Sensor (WIBS. The technique is demonstrated on measurements of various fluorescent and non-fluorescent polystyrene latex spheres (PSL before being applied to two separate contemporaneous ambient WIBS datasets recorded in a forest site in Colorado, USA as part of the BEACHON-RoMBAS project. Cluster analysis results between both datasets are consistent. Clusters are tentatively interpreted by comparison of concentration time series and cluster average measurement values to the published literature (of which there is a paucity to represent: non-fluorescent accumulation mode aerosol; bacterial agglomerates; and fungal spores. To our knowledge, this is the first time cluster analysis has been applied to long term online PBAP measurements. The novel application of this clustering technique provides a means for routinely reducing WIBS data to discrete concentration time series which are more easily interpretable, without the need for any a priori assumptions concerning the expected aerosol types. It can reduce the level of subjectivity compared to the more standard analysis approaches, which are typically performed by simple inspection of various ensemble data products. It also has the advantage of potentially resolving less populous or subtly different particle types. This technique is likely to become more robust in the future as fluorescence-based aerosol instrumentation measurement precision, dynamic range and the number of available metrics is improved.

  11. Cluster analysis of WIBS single particle bioaerosol data

    Science.gov (United States)

    Robinson, N. H.; Allan, J. D.; Huffman, J. A.; Kaye, P. H.; Foot, V. E.; Gallagher, M.

    2012-09-01

    Hierarchical agglomerative cluster analysis was performed on single-particle multi-spatial datasets comprising optical diameter, asymmetry and three different fluorescence measurements, gathered using two dual Waveband Integrated Bioaerosol Sensor (WIBS). The technique is demonstrated on measurements of various fluorescent and non-fluorescent polystyrene latex spheres (PSL) before being applied to two separate contemporaneous ambient WIBS datasets recorded in a forest site in Colorado, USA as part of the BEACHON-RoMBAS project. Cluster analysis results between both datasets are consistent. Clusters are tentatively interpreted by comparison of concentration time series and cluster average measurement values to the published literature (of which there is a paucity) to represent: non-fluorescent accumulation mode aerosol; bacterial agglomerates; and fungal spores. To our knowledge, this is the first time cluster analysis has been applied to long term online PBAP measurements. The novel application of this clustering technique provides a means for routinely reducing WIBS data to discrete concentration time series which are more easily interpretable, without the need for any a priori assumptions concerning the expected aerosol types. It can reduce the level of subjectivity compared to the more standard analysis approaches, which are typically performed by simple inspection of various ensemble data products. It also has the advantage of potentially resolving less populous or subtly different particle types. This technique is likely to become more robust in the future as fluorescence-based aerosol instrumentation measurement precision, dynamic range and the number of available metrics is improved.

  12. Cluster analysis of clinical data identifies fibromyalgia subgroups.

    Directory of Open Access Journals (Sweden)

    Elisa Docampo

    Full Text Available INTRODUCTION: Fibromyalgia (FM is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. MATERIAL AND METHODS: 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. RESULTS: VARIABLES CLUSTERED INTO THREE INDEPENDENT DIMENSIONS: "symptomatology", "comorbidities" and "clinical scales". Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1, high symptomatology and comorbidities (Cluster 2, and high symptomatology but low comorbidities (Cluster 3, showing differences in measures of disease severity. CONCLUSIONS: We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment.

  13. Variable cluster analysis method for building neural network model

    Institute of Scientific and Technical Information of China (English)

    王海东; 刘元东

    2004-01-01

    To address the problems that input variables should be reduced as much as possible and explain output variables fully in building neural network model of complicated system, a variable selection method based on cluster analysis was investigated. Similarity coefficient which describes the mutual relation of variables was defined. The methods of the highest contribution rate, part replacing whole and variable replacement are put forwarded and deduced by information theory. The software of the neural network based on cluster analysis, which can provide many kinds of methods for defining variable similarity coefficient, clustering system variable and evaluating variable cluster, was developed and applied to build neural network forecast model of cement clinker quality. The results show that all the network scale, training time and prediction accuracy are perfect. The practical application demonstrates that the method of selecting variables for neural network is feasible and effective.

  14. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Årup; Frutiger, Sally A.

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing. Hum. Brain Mapping 15...

  15. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing...

  16. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing...

  17. Cluster analysis of Southeastern U.S. climate stations

    Science.gov (United States)

    Stooksbury, D. E.; Michaels, P. J.

    1991-09-01

    A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.

  18. Initial magnetization analysis of iron cluster assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Michele, Oliver; Hesse, Juergen; Bremers, Heiko [Technische Universitaet Braunschweig, Institut fuer Metallphysik und Nukleare Festkoerperphysik, Mendelssohnstrasse 3, 38106 Braunschweig (Germany); Peng, Dong-Lian; Sumiyama, Kenji; Hihara, Takehiko; Yamamuro, Saeki [Department of Materials Science and Engineering, Nagoya Institute of Technology, Nagoya 466-8555 (Japan)

    2004-12-01

    Nearly monodispersed oxide-coated Fe cluster assemblies were prepared using a plasma-gas-condensation style cluster beam deposition apparatus (D. L. Peng et al. J. Appl. Phys. 92 3075 (2002)). The characterization of such assemblies is presented using SQUID magnetometry. The aim of this contribution is the interpretation of the initial magnetization curves instead of the usual presentation of hysteresis loops and coercivities. The description of the initial magnetization is based on a proposed vector model valid for Stoner-Wohlfarth particles. The model includes the particles' anisotropy and possible interactions regarding these influences as equivalent magnetic fields. The model is an extension of the one described by Michele et al. (J. Phys.: Condens. Matter 16 427 (2004)) regarding the fact that in a completely demagnetized state, in the sample consisting of a very large number of particles always equal anisotropy fields of opposite signs are present. We measured the initial magnetization curves for different temperatures and present the temperature dependence of the model's parameters. (Abstract Copyright [2004], Wiley Periodicals, Inc.)

  19. Spatial Data Mining using Cluster Analysis

    Directory of Open Access Journals (Sweden)

    Ch.N.Santhosh Kumar

    2012-09-01

    Full Text Available Data mining, which is refers to as Knowledge Discovery in Databases(KDD, means a process of nontrivialexaction of implicit, previously useful and unknown information such as knowledge rules, descriptions,regularities, and major trends from large databases. Data mining is evolved in a multidisciplinary field ,including database technology, machine learning, artificial intelligence, neural network, informationretrieval, and so on. In principle data mining should be applicable to the different kind of data and databasesused in many different applications, including relational databases, transactional databases, datawarehouses, object- oriented databases, and special application- oriented databases such as spatialdatabases, temporal databases, multimedia databases, and time- series databases. Spatial data mining, alsocalled spatial mining, is data mining as applied to the spatial data or spatial databases. Spatial data are thedata that have spatial or location component, and they show the information, which is more complex thanclassical data. A spatial database stores spatial data represents by spatial data types and spatialrelationships and among data. Spatial data mining encompasses various tasks. These include spatialclassification, spatial association rule mining, spatial clustering, characteristic rules, discriminant rules,trend detection. This paper presents how spatial data mining is achieved using clustering.

  20. Comparison of the quantitative analysis performance between pulsed voltage atom probe and pulsed laser atom probe.

    Science.gov (United States)

    Takahashi, J; Kawakami, K; Raabe, D

    2017-01-31

    The difference in quantitative analysis performance between the voltage-mode and laser-mode of a local electrode atom probe (LEAP3000X HR) was investigated using a Fe-Cu binary model alloy. Solute copper atoms in ferritic iron preferentially field evaporate because of their significantly lower evaporation field than the matrix iron, and thus, the apparent concentration of solute copper tends to be lower than the actual concentration. However, in voltage-mode, the apparent concentration was higher than the actual concentration at 40K or less due to a detection loss of matrix iron, and the concentration decreased with increasing specimen temperature due to the preferential evaporation of solute copper. On the other hand, in laser-mode, the apparent concentration never exceeded the actual concentration, even at lower temperatures (20K), and this mode showed better quantitative performance over a wide range of specimen temperatures. These results indicate that the pulsed laser atom probe prevents both detection loss and preferential evaporation under a wide range of measurement conditions.

  1. Photoionization and Velocity Map Imaging spectroscopy of atoms, molecules and clusters with Synchrotron and Free Electron Laser radiation at Elettra

    Energy Technology Data Exchange (ETDEWEB)

    Di Fraia, M., E-mail: michele.di.fraia@desy.de [University of Trieste, Department of Physics, via Valerio 2, 34127 Trieste (Italy); Sergo, R.; Stebel, L.; Giuressi, D.; Cautero, G.; Tudor, M.; Callegari, C. [Elettra-Sincrotrone Trieste S.C.p.A., S.S. 14 – Km 163.5, 34149 Basovizza, Trieste (Italy); O’Keeffe, P. [CNR-ISM, Area della Ricerca di Roma 1, Monterotondo Scalo, 00015 Roma (Italy); Ovcharenko, Y. [Institut für Optik und Atomare Physik, Technische Universität Berlin, Berlin (Germany); Lyamayev, V. [European XFEL GmbH, Hamburg (Germany); Feyer, V.; Moise, A. [Elettra-Sincrotrone Trieste S.C.p.A., S.S. 14 – Km 163.5, 34149 Basovizza, Trieste (Italy); Devetta, M.; Piseri, P. [Dipartimento di Fisica, Universitá degli Studi di Milano, Milan (Italy); Grazioli, C. [Department of Chemical and Pharmaceutical Sciences, University of Trieste, 34127 Trieste (Italy); Coreno, M. [CNR-ISM, Area della Ricerca di Roma 1, Monterotondo Scalo, 00015 Roma (Italy)

    2015-12-01

    Advances in laser and Synchrotron Radiation instrumentation are continuously boosting fundamental research on the electronic structure of matter. At Elettra the collaboration between several groups active in the field of atomic, molecular and cluster physics and the Instrumentation and Detector Laboratory has resulted in an experimental set-up that successfully tackles the challenges posed by the investigation of the electronic structure of isolated species in the gas phase. The use of Synchrotron Radiation (SR) and Free Electron Laser (FEL) light, allows to cover a wide spectrum of targets from energetic to dynamics. We developed a Velocity Map Imaging (VMI) spectrometer that allows to perform as well SR as FEL experiments, just by changing part of the detection system. In SR experiments, at the Gasphase beamline of Elettra, a cross delay line detector is used, coupled to a 4-channel time-to-digital converter that reconstructs the position of the electrons. Simultaneously, a Time-of-Flight (TOF) mass spectrometer is used to acquire photoion spectra. Such a system allows PhotoElectron-PhotoIon-Coincidence (PEPICO) spectroscopy of atoms, molecules and clusters. In FEL experiments (notably differing from SR experiments in the much higher rate of events produced and detected, which forces one to forfeit coincidence detection), at the Low Density Matter (LDM) beamline of FERMI, a Micro Channel Plate (MCP) a phosphor screen and a CCD camera are used instead, capable of shot-by-shot collection of practically all events, albeit without time resolution.

  2. Multivariate analysis of the globular clusters in M87

    CERN Document Server

    Das, Sukanta; Davoust, Emmanuel

    2015-01-01

    An objective classification of 147 globular clusters in the inner region of the giant elliptical galaxy M87 is carried out with the help of two methods of multivariate analysis. First independent component analysis is used to determine a set of independent variables that are linear combinations of various observed parameters (mostly Lick indices) of the globular clusters. Next K-means cluster analysis is applied on the independent components, to find the optimum number of homogeneous groups having an underlying structure. The properties of the four groups of globular clusters thus uncovered are used to explain the formation mechanism of the host galaxy. It is suggested that M87 formed in two successive phases. First a monolithic collapse, which gave rise to an inner group of metal-rich clusters with little systematic rotation and an outer group of metal-poor clusters in eccentric orbits. In a second phase, the galaxy accreted low-mass satellites in a dissipationless fashion, from the gas of which the two othe...

  3. Identifying clinical course patterns in SMS data using cluster analysis

    DEFF Research Database (Denmark)

    Kent, Peter; Kongsted, Alice

    2012-01-01

    ABSTRACT: BACKGROUND: Recently, there has been interest in using the short message service (SMS or text messaging), to gather frequent information on the clinical course of individual patients. One possible role for identifying clinical course patterns is to assist in exploring clinically importa...... of cluster analysis. More research is needed, especially head-to-head studies, to identify which technique is best to use under what circumstances.......ABSTRACT: BACKGROUND: Recently, there has been interest in using the short message service (SMS or text messaging), to gather frequent information on the clinical course of individual patients. One possible role for identifying clinical course patterns is to assist in exploring clinically important...... by spline analysis. However, cluster analysis of SMS data in its original untransformed form may be simpler and offer other advantages. Therefore, the aim of this study was to determine whether cluster analysis could be used for identifying clinical course patterns distinct from the pattern of the whole...

  4. Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

    Energy Technology Data Exchange (ETDEWEB)

    Belianinov, Alex, E-mail: belianinova@ornl.gov; Ganesh, Panchapakesan; Lin, Wenzhi; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V. [Oak Ridge National Laboratory, Institute for Functional Imaging of Materials, Center for Nanophase Material Science, Oak Ridge, Tennessee 37922 (United States); Sales, Brian C.; Sefat, Athena S. [Oak Ridge National Laboratory, Materials Science and Technology Division, Oak Ridge, Tennessee 37922 (United States)

    2014-12-01

    Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe{sub 0.55}Se{sub 0.45} (T{sub c} = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe{sub 1−x}Se{sub x} structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

  5. Cluster analysis of undergraduate drinkers based on alcohol expectancy scores.

    Science.gov (United States)

    Leeman, Robert F; Kulesza, Magdalena; Stewart, Diana W; Copeland, Amy L

    2012-03-01

    Expectancies of alcohol's effects have been associated with problem drinking in undergraduates. If subgroups can be classified based on expectancies, this may facilitate identifying those at highest risk for problem drinking. Undergraduates (N = 612) from two state universities completed a web-based survey. Responses to the Comprehensive Effects of Alcohol scale were analyzed using k-means cluster analysis separately within each university sample. Hartigan's heuristic was used to determine that five was the optimal number of clusters in each sample. Clusters were distinguishable based on their overall magnitude of expectancy endorsement and by a tendency to endorse stronger positive than negative expectancies. Subsequent analyses were conducted to compare clusters on alcohol involvement and trait disinhibition. A cluster characterized by endorsement of positive and negative expectancies ("strong expectancy") was associated with a particularly problematic risk profile, specifically concerning difficulties with self-control (i.e., trait disinhibition and impaired control over alcohol use). A cluster with higher positive and lower negative expectancies reported frequent heavy drinking but appeared to be at lower risk than the strong expectancy cluster in a number of respects. Negative expectancy endorsement appeared to represent added risk above and beyond positive expectancies. Results suggest that both the magnitude and combination of expectancies endorsed by subgroups of undergraduate drinkers may relate to their risk level in terms of alcohol involvement and personality traits. These findings may have implications for interventions with young adult drinkers.

  6. Damage creation in silicon single crystals irradiated with 200 keV/atom Au{sub n}{sup +} clusters

    Energy Technology Data Exchange (ETDEWEB)

    Canut, B. E-mail: bruno.canut@dpmsun1.univ-lyon1.fr; Fallavier, M.; Marty, O.; Ramos, S.M.M

    2000-04-01

    Silicon wafers of (1 0 0) orientation were irradiated with Au{sub n} cluster beams (1{<=}n{<=}7) produced by the 2.5 MV Van de Graaff accelerator of the Institut de Physique Nucleaire de Lyon equipped with a liquid metal source. The incident energy was of 200 keV per gold atom, which corresponds to a slowing-down mainly governed by elastic processes (nuclear energy loss of Au{sup +} ions: 3 keV nm{sup -1}). All the irradiations were performed at room temperature with fluences up to 5x10{sup 14} Au (at. cm{sup -2}). The typical beam currents varied from 1.5 nA for Au{sup +} down to 20 pA for Au{sub 7}{sup +}. The radiation-induced disorder was measured by means of Rutherford backscattering spectrometry in channeling geometry (RBS-C), using a {sup 4}He{sup +} beam accelerated at 2 MV. From the fluence evolution of the lattice disorder at the target surface, we evidence that polyatomic projectiles produce more defects per incident atom than single Au{sup +} ions. As an example we measured damage cross-sections per incident Au atom of 12.5 and 2.7 nm{sup 2} for Au{sub 7}{sup +} and Au{sup +} projectiles, respectively. This cluster effect was ascribed to the high density of nuclear energy deposited within the cascade. Transmission electron microscopy (TEM) was performed on samples irradiated at low fluences (10{sup 9} at. cm{sup -2}) in order to visualize each projectile impact.

  7. Atomic layer deposition of platinum clusters on titania nanoparticles at atmospheric pressure

    NARCIS (Netherlands)

    Goulas, A.; Van Ommen, J.R.

    2013-01-01

    We report the fabrication of platinum nanoclusters with a narrow size distribution on TiO2 nanoparticles using atomic layer deposition. With MeCpPtMe3 and ozone as reactants, the deposition can be carried out at a relatively low temperature of 250 degrees C. Our approach of working with suspended na

  8. Bayesian Analysis of Two Stellar Populations in Galactic Globular Clusters III: Analysis of 30 Clusters

    CERN Document Server

    Wagner-Kaiser, R; Sarajedini, A; von Hippel, T; van Dyk, D A; Robinson, E; Stein, N; Jefferys, W H

    2016-01-01

    We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of 30 Galactic Globular Clusters to characterize two distinct stellar populations. A sophisticated Bayesian technique is employed to simultaneously sample the joint posterior distribution of age, distance, and extinction for each cluster, as well as unique helium values for two populations within each cluster and the relative proportion of those populations. We find the helium differences among the two populations in the clusters fall in the range of ~0.04 to 0.11. Because adequate models varying in CNO are not presently available, we view these spreads as upper limits and present them with statistical rather than observational uncertainties. Evidence supports previous studies suggesting an increase in helium content concurrent with increasing mass of the cluster and also find that the proportion of the first population of stars increases with mass as well. Our results are examined in the context of proposed g...

  9. Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

    Science.gov (United States)

    Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

    2016-01-01

    Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

  10. Cluster analysis of radionuclide concentrations in beach sand

    NARCIS (Netherlands)

    de Meijer, R.J.; James, I.; Jennings, P.J.; Keoyers, J.E.

    This paper presents a method in which natural radionuclide concentrations of beach sand minerals are traced along a stretch of coast by cluster analysis. This analysis yields two groups of mineral deposit with different origins. The method deviates from standard methods of following dispersal of

  11. Barrierless growth of precursor-free, ultrafast laser-fragmented noble metal nanoparticles by colloidal atom clusters - A kinetic in situ study.

    Science.gov (United States)

    Jendrzej, Sandra; Gökce, Bilal; Amendola, Vincenzo; Barcikowski, Stephan

    2016-02-01

    Unintended post-synthesis growth of noble metal colloids caused by excess amounts of reactants or highly reactive atom clusters represents a fundamental problem in colloidal chemistry, affecting product stability or purity. Hence, quantified kinetics could allow defining nanoparticle size determination in dependence of the time. Here, we investigate in situ the growth kinetics of ps pulsed laser-fragmented platinum nanoparticles in presence of naked atom clusters in water without any influence of reducing agents or surfactants. The nanoparticle growth is investigated for platinum covering a time scale of minutes to 50days after nanoparticle generation, it is also supplemented by results obtained from gold and palladium. Since a minimum atom cluster concentration is exceeded, a significant growth is determined by time resolved UV/Vis spectroscopy, analytical disc centrifugation, zeta potential measurement and transmission electron microscopy. We suggest a decrease of atom cluster concentration over time, since nanoparticles grow at the expense of atom clusters. The growth mechanism during early phase (<1day) of laser-synthesized colloid is kinetically modeled by rapid barrierless coalescence. The prolonged slow nanoparticle growth is kinetically modeled by a combination of coalescence and Lifshitz-Slyozov-Wagner kinetic for Ostwald ripening, validated experimentally by the temperature dependence of Pt nanoparticle size and growth quenching by Iodide anions.

  12. Extrapolated intermediate Hamiltonian coupled-cluster approach: theory and pilot application to electron affinities of alkali atoms.

    Science.gov (United States)

    Eliav, Ephraim; Vilkas, Marius J; Ishikawa, Yasuyuki; Kaldor, Uzi

    2005-06-08

    The intermediate Hamiltonian (IH) coupled-cluster method makes possible the use of very large model spaces in coupled-cluster calculations without running into intruder states. This is achieved at the cost of approximating some of the IH matrix elements, which are not taken at their rigorous effective Hamiltonian (EH) value. The extrapolated intermediate Hamiltonian (XIH) approach proposed here uses a parametrized IH and extrapolates it to the full EH, with model spaces larger by several orders of magnitude than those possible in EH coupled-cluster methods. The flexibility and resistance to intruders of the IH approach are thus combined with the accuracy of full EH. Various extrapolation schemes are described. A pilot application to the electron affinities (EAs) of alkali atoms is presented, where converged EH results are obtained by XIH for model spaces of approximately 20,000 determinants; direct EH calculations converge only for a one-dimensional model space. Including quantum electrodynamic effects, the average XIH error for the EAs is 0.6 meV and the largest error is 1.6 meV. A new reference estimate for the EA of Fr is proposed at 486+/-2 meV.

  13. Tuning optical properties of magic number cluster (SiO2)4O2H4 by substitutional bonding with gold atoms.

    Science.gov (United States)

    Cai, Xiulong; Zhang, Peng; Ma, Liuxue; Zhang, Wenxian; Ning, Xijing; Zhao, Li; Zhuang, Jun

    2009-04-30

    By bonding gold atoms to the magic number cluster (SiO(2))(4)O(2)H(4), two groups of Au-adsorbed shell-like clusters Au(n)(SiO(2))(4)O(2)H(4-n) (n = 1-4) and Au(n)(SiO(2))(4)O(2) (n = 5-8) were obtained, and their spectral properties were studied. The ground-state structures of these clusters were optimized by density functional theory, and the results show that in despite of the different numbers and types of the adsorbed Au atoms, the cluster core (SiO(2))(4)O(2) of T(d) point-group symmetry keeps almost unchanged. The absorption spectra were obtained by time-dependent density functional theory. From one group to the other, an extension of absorption wavelength from the UV-visible to the NIR region was observed, and in each group the absorption strengths vary linearly with the number of Au atoms. These features indicate their advantages for exploring novel materials with easily controlled tunable optical properties. Furthermore, due to the weak electronic charge transfer between the Au atoms, the clusters containing Au(2) dimers, especially Au(8)(SiO(2))(4)O(2), absorb strongly NIR light at 900 approximately 1200 nm. Such strong absorption suggests potential applications of these shell-like clusters in tumor cells thermal therapy, like the gold-coated silica nanoshells with larger sizes.

  14. Technology Clusters Exploration for Patent Portfolio through Patent Abstract Analysis

    Directory of Open Access Journals (Sweden)

    Gabjo Kim

    2016-12-01

    Full Text Available This study explores technology clusters through patent analysis. The aim of exploring technology clusters is to grasp competitors’ levels of sustainable research and development (R&D and establish a sustainable strategy for entering an industry. To achieve this, we first grouped the patent documents with similar technologies by applying affinity propagation (AP clustering, which is effective while grouping large amounts of data. Next, in order to define the technology clusters, we adopted the term frequency-inverse document frequency (TF-IDF weight, which lists the terms in order of importance. We collected the patent data of Korean electric car companies from the United States Patent and Trademark Office (USPTO to verify our proposed methodology. As a result, our proposed methodology presents more detailed information on the Korean electric car industry than previous studies.

  15. An Empirical Analysis of Rough Set Categorical Clustering Techniques

    Science.gov (United States)

    2017-01-01

    Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, many attentions have been put on categorical data clustering, where data objects are made up of non-numerical attributes. For categorical data clustering the rough set based approaches such as Maximum Dependency Attribute (MDA) and Maximum Significance Attribute (MSA) has outperformed their predecessor approaches like Bi-Clustering (BC), Total Roughness (TR) and Min-Min Roughness(MMR). This paper presents the limitations and issues of MDA and MSA techniques on special type of data sets where both techniques fails to select or faces difficulty in selecting their best clustering attribute. Therefore, this analysis motivates the need to come up with better and more generalize rough set theory approach that can cope the issues with MDA and MSA. Hence, an alternative technique named Maximum Indiscernible Attribute (MIA) for clustering categorical data using rough set indiscernible relations is proposed. The novelty of the proposed approach is that, unlike other rough set theory techniques, it uses the domain knowledge of the data set. It is based on the concept of indiscernibility relation combined with a number of clusters. To show the significance of proposed approach, the effect of number of clusters on rough accuracy, purity and entropy are described in the form of propositions. Moreover, ten different data sets from previously utilized research cases and UCI repository are used for experiments. The results produced in tabular and graphical forms shows that the proposed MIA technique provides better performance in selecting the clustering attribute in terms of purity, entropy, iterations, time, accuracy and rough accuracy. PMID:28068344

  16. An Empirical Analysis of Rough Set Categorical Clustering Techniques.

    Science.gov (United States)

    Uddin, Jamal; Ghazali, Rozaida; Deris, Mustafa Mat

    2017-01-01

    Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, many attentions have been put on categorical data clustering, where data objects are made up of non-numerical attributes. For categorical data clustering the rough set based approaches such as Maximum Dependency Attribute (MDA) and Maximum Significance Attribute (MSA) has outperformed their predecessor approaches like Bi-Clustering (BC), Total Roughness (TR) and Min-Min Roughness(MMR). This paper presents the limitations and issues of MDA and MSA techniques on special type of data sets where both techniques fails to select or faces difficulty in selecting their best clustering attribute. Therefore, this analysis motivates the need to come up with better and more generalize rough set theory approach that can cope the issues with MDA and MSA. Hence, an alternative technique named Maximum Indiscernible Attribute (MIA) for clustering categorical data using rough set indiscernible relations is proposed. The novelty of the proposed approach is that, unlike other rough set theory techniques, it uses the domain knowledge of the data set. It is based on the concept of indiscernibility relation combined with a number of clusters. To show the significance of proposed approach, the effect of number of clusters on rough accuracy, purity and entropy are described in the form of propositions. Moreover, ten different data sets from previously utilized research cases and UCI repository are used for experiments. The results produced in tabular and graphical forms shows that the proposed MIA technique provides better performance in selecting the clustering attribute in terms of purity, entropy, iterations, time, accuracy and rough accuracy.

  17. Visualization methods for statistical analysis of microarray clusters

    Directory of Open Access Journals (Sweden)

    Li Kai

    2005-05-01

    Full Text Available Abstract Background The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determine which clustering algorithm is most appropriate to apply, and it is difficult to verify the results of any algorithm due to the lack of a gold-standard. Appropriate data visualization tools can aid this analysis process, but existing visualization methods do not specifically address this issue. Results We present several visualization techniques that incorporate meaningful statistics that are noise-robust for the purpose of analyzing the results of clustering algorithms on microarray data. This includes a rank-based visualization method that is more robust to noise, a difference display method to aid assessments of cluster quality and detection of outliers, and a projection of high dimensional data into a three dimensional space in order to examine relationships between clusters. Our methods are interactive and are dynamically linked together for comprehensive analysis. Further, our approach applies to both protein and gene expression microarrays, and our architecture is scalable for use on both desktop/laptop screens and large-scale display devices. This methodology is implemented in GeneVAnD (Genomic Visual ANalysis of Datasets and is available at http://function.princeton.edu/GeneVAnD. Conclusion Incorporating relevant statistical information into data visualizations is key for analysis of large biological datasets, particularly because of high levels of noise and the lack of a gold-standard for comparisons. We developed several new visualization techniques and demonstrated their effectiveness for evaluating cluster quality and relationships between clusters.

  18. Cognitive analysis of multiple sclerosis utilizing fuzzy cluster means

    Directory of Open Access Journals (Sweden)

    Imianvan Anthony Agboizebeta

    2012-01-01

    Full Text Available Multiple sclerosis, often called MS, is a disease that affects the central nervous system (the brain and spinal cord. Myelin provides insulation for nerve cells improves the conduction of impulses along the nerves and is important for maintaining the health of the nerves. In multiple sclerosis, inflammation causes the myelin to disappear. Genetic factors, environmental issues and viral infection may also play a role in developing the disease. Ms is characterized by life threatening symptoms such as; loss of balance, hearing problem and depression. The application of Fuzzy Cluster Means (FCM or Fuzzy CMean analysis to the diagnosis of different forms of multiple sclerosis is the focal point of this paper. Application of cluster analysis involves a sequence of methodological and analytical decision steps that enhances the quality and meaning of the clusters produced. Uncertainties associated with analysis of multiple sclerosis test data are eliminated by the system

  19. Statistical analysis of bound companions in the Coma cluster

    Science.gov (United States)

    Mendelin, Martin; Binggeli, Bruno

    2017-08-01

    Aims: The rich and nearby Coma cluster of galaxies is known to have substructure. We aim to create a more detailed picture of this substructure by searching directly for bound companions around individual giant members. Methods: We have used two catalogs of Coma galaxies, one covering the cluster core for a detailed morphological analysis, another covering the outskirts. The separation limit between possible companions (secondaries) and giants (primaries) is chosen as MB = -19 and MR = -20, respectively for the two catalogs. We have created pseudo-clusters by shuffling positions or velocities of the primaries and search for significant over-densities of possible companions around giants by comparison with the data. This method was developed and applied first to the Virgo cluster. In a second approach we introduced a modified nearest neighbor analysis using several interaction parameters for all galaxies. Results: We find evidence for some excesses due to possible companions for both catalogs. Satellites are typically found among the faintest dwarfs (MB type giants (spirals) in the outskirts, which is expected in an infall scenario of cluster evolution. A rough estimate for an upper limit of bound galaxies within Coma is 2-4%, to be compared with 7% for Virgo. Conclusions: The results agree well with the expected low frequency of bound companions in a regular cluster such as Coma. To exploit the data more fully and reach more detailed insights into the physics of cluster evolution we suggest applying the method also to model clusters created by N-body simulations for comparison.

  20. H2 Molecular Clusters with Embedded Molecules and Atoms as the Source of the Diffuse Interstellar Bands

    Science.gov (United States)

    Bernstein, L. S.; Clark, F. O.; Lynch, D. K.

    2013-05-01

    We suggest that the diffuse interstellar bands (DIBs) arise from absorption lines of electronic transitions in molecular clusters primarily composed of a single molecule, atom, or ion ("seed"), embedded in a single-layer shell of H2 molecules. Less abundant variants of the cluster, including two seed molecules and/or a two-layer shell of H2 molecules, may also occur. The lines are broadened, blended, and wavelength-shifted by interactions between the seed and surrounding H2 shell. We refer to these clusters as contaminated H2 clusters (CHCs). We show that CHC spectroscopy matches the diversity of observed DIB spectral profiles and provides good fits to several DIB profiles based on a rotational temperature of 10 K. CHCs arise from ~centimeter-sized, dirty H2 ice balls, called contaminated H2 ice macro-particles (CHIMPs), formed in cold, dense, giant molecular clouds (GMCs), and later released into the interstellar medium (ISM) upon GMC disruption. Attractive interactions, arising from Van der Waals and ion-induced dipole potentials, between the seeds and H2 molecules enable CHIMPs to attain centimeter-sized dimensions. When an ultraviolet (UV) photon is absorbed in the outer layer of a CHIMP, it heats the icy matrix and expels CHCs into the ISM. While CHCs are quickly destroyed by absorbing UV photons, they are replenished by the slowly eroding CHIMPs. Since CHCs require UV photons for their release, they are most abundant at, but not limited to, the edges of UV-opaque molecular clouds, consistent with the observed, preferred location of DIBs. An inherent property of CHCs, which can be characterized as nanometer size, spinning, dipolar dust grains, is that they emit in the radio-frequency region. We also show that the CHCs offer a natural explanation for the anomalous microwave emission feature in the ~10-100 GHz spectral region.

  1. On the size and structure of helium snowballs formed around charged atoms and clusters of noble gases.

    Science.gov (United States)

    Bartl, Peter; Leidlmair, Christian; Denifl, Stephan; Scheier, Paul; Echt, Olof

    2014-09-18

    Helium nanodroplets doped with argon, krypton, or xenon are ionized by electrons and analyzed in a mass spectrometer. HenNgx(+) ions containing up to seven noble gas (Ng) atoms and dozens of helium atoms are identified; the high resolution of the mass spectrometer combined with advanced data analysis make it possible to unscramble contributions from isotopologues that have the same nominal mass but different numbers of helium or Ng atoms, such as the magic He20(84)Kr2(+) and the isobaric, nonmagic He41(84)Kr(+). Anomalies in these ion abundances reveal particularly stable ions; several intriguing patterns emerge. Perhaps most astounding are the results for HenAr(+), which show evidence for three distinct, solid-like solvation shells containing 12, 20, and 12 helium atoms. This observation runs counter to the common notion that only the first solvation shell is solid-like but agrees with calculations by Galli et al. for HenNa(+) [J. Phys. Chem. A 2011, 115, 7300] that reveal three shells of icosahedral symmetry. HenArx(+) (2 ≤ x ≤ 7) ions appear to be especially stable if they contain a total of n + x = 19 atoms. A sequence of anomalies in the abundance distribution of HenKrx(+) suggests that rings of six helium atoms are inserted into the solvation shell each time a krypton atom is added to the ionic core, from Kr(+) to Kr3(+). Previously reported strong anomalies at He12Kr2(+) and He12Kr3(+) [Kim , J. H.; et al. J. Chem. Phys. 2006, 124, 214301] are attributed to a contamination. Only minor local anomalies appear in the distributions of HenXex(+) (x ≤ 3). The distributions of HenKr(+) and HenXe(+) show strikingly similar, broad features that are absent from the distribution of HenAr(+); differences are tentatively ascribed to the very different fragmentation dynamics of these ions.

  2. Traffic Accident, System Model and Cluster Analysis in GIS

    Directory of Open Access Journals (Sweden)

    Veronika Vlčková

    2015-07-01

    Full Text Available One of the many often frequented topics as normal journalism, so the professional public, is the problem of traffic accidents. This article illustrates the orientation of considerations to a less known context of accidents, with the help of constructive systems theory and its methods, cluster analysis and geoinformation engineering. Traffic accident is reframing the space-time, and therefore it can be to study with tools of technology of geographic information systems. The application of system approach enabling the formulation of the system model, grabbed by tools of geoinformation engineering and multicriterial and cluster analysis.

  3. Robustness of "cut and splice" genetic algorithms in the structural optimization of atomic clusters

    OpenAIRE

    Froltsov, V.; Reuter, K.

    2009-01-01

    We return to the geometry optimization problem of Lennard-Jones clusters to analyze the performance dependence of 'cut and splice' genetic algorithms (GAs) on the employed population size. We generally find that admixing twinning mutation moves leads to an improved robustness of the algorithm efficiency with respect to this a priori unknown technical parameter. The resulting very stable performance of the corresponding mutation + mating GA implementation over a wide range of population sizes...

  4. Cluster Analysis of Metal Concentrations in River Kubanni Zaria, Nigeria

    Directory of Open Access Journals (Sweden)

    A.W. Butu

    2013-08-01

    Full Text Available The cluster analysis was used to assess the degree of association of the metal concentrations in river Kubanni Zaria, Nigeria. The main sources of data for the analysis were the sediment from four distinct locations along the long profile Kubanni River which were analyzed using Instrumental Nitrogen Activities Analysis (INAA techniques. The Nigerian Research Reactor-1(NIRR-1 which is Miniature Nitrogen Source Reactor (MNSR was used to analyze the data. The result of the laboratory analysis was subjected to cluster analysis. The analysis shows a stable clustering system where the metal concentrations in the four different locations were grouped into two main groups with one outlier. The level of concentration of elements that were sampled in the dry months were cluster in group I and those collected in the raining months were in group II. This strongly support that there is temporal variation in the levels of concentration of metal contaminants between wet and dry seasons in river Kubanni and also confirms the fact that the elements that were collected in the wet season are from the same source and those in the dry season are also from common source.

  5. Quantum Monte-Carlo programming for atoms, molecules, clusters, and solids

    Energy Technology Data Exchange (ETDEWEB)

    Schattke, Wolfgang [Kiel Univ. (Germany). Inst. of Theoretical Physics and Astrophysics; Ikerbasque Foundation/Donostia International Physics Center, San Sebastian (Spain); Diez Muino, Ricardo [Centro de Fisica de Materiales CSIC-UPV/EHU (Spain); Donostia International Physics Center, San Sebastian (Spain)

    2013-11-01

    This is a book that initiates the reader into the basic concepts and practical applications of Quantum Monte Carlo. Because of the simplicity of its theoretical concept, the authors focus on the variational Quantum Monte Carlo scheme. The reader is enabled to proceed from simple examples as the hydrogen atom to advanced ones as the Lithium solid. In between, several intermediate steps are introduced, including the Hydrogen molecule (2 electrons), the Lithium atom (3 electrons) and expanding to an arbitrary number of electrons to finally treat the three-dimensional periodic array of Lithium atoms in a crystal. The book is unique, because it provides both theory and numerical programs. It pedagogically explains how to transfer into computational tools what is usually described in a theoretical textbook. It also includes the detailed physical understanding of methodology that cannot be found in a code manual. The combination of both aspects allows the reader to assimilate the fundamentals of Quantum Monte Carlo not only by reading but also by practice.

  6. Application of microarray analysis on computer cluster and cloud platforms.

    Science.gov (United States)

    Bernau, C; Boulesteix, A-L; Knaus, J

    2013-01-01

    Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

  7. Bayesian analysis of two stellar populations in Galactic globular clusters- III. Analysis of 30 clusters

    Science.gov (United States)

    Wagner-Kaiser, R.; Stenning, D. C.; Sarajedini, A.; von Hippel, T.; van Dyk, D. A.; Robinson, E.; Stein, N.; Jefferys, W. H.

    2016-12-01

    We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of 30 Galactic globular clusters to characterize two distinct stellar populations. A sophisticated Bayesian technique is employed to simultaneously sample the joint posterior distribution of age, distance, and extinction for each cluster, as well as unique helium values for two populations within each cluster and the relative proportion of those populations. We find the helium differences among the two populations in the clusters fall in the range of ˜0.04 to 0.11. Because adequate models varying in carbon, nitrogen, and oxygen are not presently available, we view these spreads as upper limits and present them with statistical rather than observational uncertainties. Evidence supports previous studies suggesting an increase in helium content concurrent with increasing mass of the cluster and we also find that the proportion of the first population of stars increases with mass as well. Our results are examined in the context of proposed globular cluster formation scenarios. Additionally, we leverage our Bayesian technique to shed light on the inconsistencies between the theoretical models and the observed data.

  8. Hydrogen isotope dynamic effects on partially reduced paramagnetic six-atom Ag clusters in low-symmetry cage of zeolite A

    Directory of Open Access Journals (Sweden)

    Amgalanbaatar Baldansuren

    2016-12-01

    Full Text Available A well-defined, monodisperse Ag6+ cluster was prepared by mild chemical treatments including aqueous ion-exchange, dehydration, oxygen calcination at 673 K and hydrogen reduction 293 K, rather than autoreduction and irradiations with γ-ray and X-ray. H2 reduction was proved as a crucial step to form the nanosize cluster with six equivalent silver atoms. Hydrogen isotope exchange and dynamics were probed by EPR and HYSCORE to provide information relevant to the cluster geometry, size, charge state and spin state. Desorption experiments result in the deuterium desorption energy of 0.78 eV from the cluster, exceeding the experimental value of 0.38 eV for the single crystal Ag(111 surface. These experiments indicate that the EPR-active clusters are in delicate equilibrium with EPR-silent clusters.

  9. New possible properties of atomic nuclei investigated by non linear methods: Fractal and recurrence quantification analysis

    OpenAIRE

    Conte, Elio,; Khrennikov, Andrei Yu.; Zbilut, Joseph P.

    2007-01-01

    For the first time we apply the methodologies of nonlinear analysis to investigate atomic matter. We use these methods in the analysis of Atomic Weights and of Mass Number of atomic nuclei. Using the AutoCorrelation Function and Mutual Information we establish the presence of nonlinear effects in the mechanism of increasing mass of atomic nuclei considered as a function of the atomic number. We find that increasing mass is divergent, possibly chaotic. We also investigate the possible existenc...

  10. Examination of European Union economic cohesion: A cluster analysis approach

    Directory of Open Access Journals (Sweden)

    Jiri Mazurek

    2014-01-01

    Full Text Available In the past years majority of EU members experienced the highest economic decline in their modern history, but impacts of the global financial crisis were not distributed homogeneously across the continent. The aim of the paper is to examine a cohesion of European Union (plus Norway and Iceland in terms of an economic development of its members from the 1st of January 2008 to the 31st of December 2012. For the study five economic indicators were selected: GDP growth, unemployment, inflation, labour productivity and government debt. Annual data from Eurostat databases were averaged over the whole period and then used as an input for a cluster analysis. It was found that EU countries were divided into six different clusters. The most populated cluster with 14 countries covered Central and West Europe and reflected relative homogeneity of this part of Europe. Countries of Southern Europe (Greece, Portugal and Spain shared their own cluster of the most affected countries by the recent crisis as well as the Baltics and the Balkans states in another cluster. On the other hand Slovakia and Poland, only two countries that escaped a recession, were classified in their own cluster of the most successful countries

  11. Sun Protection Belief Clusters: Analysis of Amazon Mechanical Turk Data.

    Science.gov (United States)

    Santiago-Rivas, Marimer; Schnur, Julie B; Jandorf, Lina

    2016-12-01

    This study aimed (i) to determine whether people could be differentiated on the basis of their sun protection belief profiles and individual characteristics and (ii) explore the use of a crowdsourcing web service for the assessment of sun protection beliefs. A sample of 500 adults completed an online survey of sun protection belief items using Amazon Mechanical Turk. A two-phased cluster analysis (i.e., hierarchical and non-hierarchical K-means) was utilized to determine clusters of sun protection barriers and facilitators. Results yielded three distinct clusters of sun protection barriers and three distinct clusters of sun protection facilitators. Significant associations between gender, age, sun sensitivity, and cluster membership were identified. Results also showed an association between barrier and facilitator cluster membership. The results of this study provided a potential alternative approach to developing future sun protection promotion initiatives in the population. Findings add to our knowledge regarding individuals who support, oppose, or are ambivalent toward sun protection and inform intervention research by identifying distinct subtypes that may best benefit from (or have a higher need for) skin cancer prevention efforts.

  12. A Geometric Analysis of Subspace Clustering with Outliers

    CERN Document Server

    Soltanolkotabi, Mahdi

    2011-01-01

    This paper considers the problem of clustering a collection of unlabeled data points assumed to lie near a union of lower dimensional planes. As is common in computer vision or unsupervised learning applications, we do not know in advance how many subspaces there are nor do we have any information about their dimensions. We develop a novel geometric analysis of an algorithm named {\\em sparse subspace clustering} (SSC) \\cite{Elhamifar09}, which significantly broadens the range of problems where it is provably effective. For instance, we show that SSC can recover multiple subspaces, each of dimension comparable to the ambient dimension. We also prove that SSC can correctly cluster data points even when the subspaces of interest intersect. Further, we develop an extension of SSC that succeeds when the data set is corrupted with possibly overwhelmingly many outliers. Underlying our analysis are clear geometric insights, which may bear on other sparse recovery problems. A numerical study complements our theoretica...

  13. Cluster analysis of knowledge sources in standardized electrical engineering subfields

    Directory of Open Access Journals (Sweden)

    Blagojević Marija

    2016-01-01

    Full Text Available The paper presents a cluster analysis of innovation of knowledge sources based on the standards in the field of Electrical Engineering. Both local (SRPS and global (ISO knowledge sources have been analysed with the aim of innovating a Knowledge Base (KB. The results presented indicate a means/possibility of grouping the subfields within a cluster. They also point to a trend or intensity of knowledge source innovation for the purpose of innovating the KB that accompanies innovations. The study provides the possibility of predicting necessary financial resources in the forthcoming period by means of original mathematical relations. Furthermore, the cluster analysis facilitates the comparison of the innovation intensity in this and other (subfields. Future work relates to the monitoring of the knowledge source innovation by means of KB engineering and improvement of the methodology of prediction using neural networks.

  14. Rydberg Matter clusters of alkali metal atoms: the link between meteoritic matter, polar mesosphere summer echoes (PMSE), sporadic sodium layers, polar mesospheric clouds (PMCs, NLCs), and ion chemistry

    CERN Document Server

    Olofson, Frans; Holmlid, Leif

    2010-01-01

    A material exists which links together the influx of meteoritic matter from interplanetary space, the polar mesosphere summer echoes (PMSE), the sporadic sodium layers, the polar mesospheric clouds (PMCs, NLCs), and the observed ion chemistry in the mesosphere. The evidence in these research fields is here analyzed and found to agree well with the properties of Rydberg Matter (RM). This material has been studied with numerous methods in the laboratory. Alkali atoms, mainly Na, reach the mesosphere in the form of interplanetary (meteoritic, cometary) dust. The planar RM clusters NaN usually contain N = 19, 37 or 61 atoms, and have the density of air at 90 km altitude where they float. The diameters of the clusters are 10-100 nm from laboratory high precision radio frequency spectroscopic studies. Such experiments show that RM clusters interact strongly with radar frequencies: this explains the radio frequency heating and reflection studies of PMSE layers. The clusters give the low temperature in the mesosphere...

  15. Cluster analysis of WIBS single-particle bioaerosol data

    Science.gov (United States)

    Robinson, N. H.; Allan, J. D.; Huffman, J. A.; Kaye, P. H.; Foot, V. E.; Gallagher, M.

    2013-02-01

    Hierarchical agglomerative cluster analysis was performed on single-particle multi-spatial data sets comprising optical diameter, asymmetry and three different fluorescence measurements, gathered using two dual Wideband Integrated Bioaerosol Sensors (WIBSs). The technique is demonstrated on measurements of various fluorescent and non-fluorescent polystyrene latex spheres (PSL) before being applied to two separate contemporaneous ambient WIBS data sets recorded in a forest site in Colorado, USA, as part of the BEACHON-RoMBAS project. Cluster analysis results between both data sets are consistent. Clusters are tentatively interpreted by comparison of concentration time series and cluster average measurement values to the published literature (of which there is a paucity) to represent the following: non-fluorescent accumulation mode aerosol; bacterial agglomerates; and fungal spores. To our knowledge, this is the first time cluster analysis has been applied to long-term online primary biological aerosol particle (PBAP) measurements. The novel application of this clustering technique provides a means for routinely reducing WIBS data to discrete concentration time series which are more easily interpretable, without the need for any a priori assumptions concerning the expected aerosol types. It can reduce the level of subjectivity compared to the more standard analysis approaches, which are typically performed by simple inspection of various ensemble data products. It also has the advantage of potentially resolving less populous or subtly different particle types. This technique is likely to become more robust in the future as fluorescence-based aerosol instrumentation measurement precision, dynamic range and the number of available metrics are improved.

  16. Cluster analysis of WIBS single-particle bioaerosol data

    Directory of Open Access Journals (Sweden)

    N. H. Robinson

    2013-02-01

    Full Text Available Hierarchical agglomerative cluster analysis was performed on single-particle multi-spatial data sets comprising optical diameter, asymmetry and three different fluorescence measurements, gathered using two dual Wideband Integrated Bioaerosol Sensors (WIBSs. The technique is demonstrated on measurements of various fluorescent and non-fluorescent polystyrene latex spheres (PSL before being applied to two separate contemporaneous ambient WIBS data sets recorded in a forest site in Colorado, USA, as part of the BEACHON-RoMBAS project. Cluster analysis results between both data sets are consistent. Clusters are tentatively interpreted by comparison of concentration time series and cluster average measurement values to the published literature (of which there is a paucity to represent the following: non-fluorescent accumulation mode aerosol; bacterial agglomerates; and fungal spores. To our knowledge, this is the first time cluster analysis has been applied to long-term online primary biological aerosol particle (PBAP measurements. The novel application of this clustering technique provides a means for routinely reducing WIBS data to discrete concentration time series which are more easily interpretable, without the need for any a priori assumptions concerning the expected aerosol types. It can reduce the level of subjectivity compared to the more standard analysis approaches, which are typically performed by simple inspection of various ensemble data products. It also has the advantage of potentially resolving less populous or subtly different particle types. This technique is likely to become more robust in the future as fluorescence-based aerosol instrumentation measurement precision, dynamic range and the number of available metrics are improved.

  17. Joint Sequence Analysis: Association and Clustering

    Science.gov (United States)

    Piccarreta, Raffaella

    2017-01-01

    In its standard formulation, sequence analysis aims at finding typical patterns in a set of life courses represented as sequences. Recently, some proposals have been introduced to jointly analyze sequences defined on different domains (e.g., work career, partnership, and parental histories). We introduce measures to evaluate whether a set of…

  18. Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

    Science.gov (United States)

    Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

    2013-01-01

    Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

  19. Transcriptional analysis of ESAT-6 cluster 3 in Mycobacterium smegmatis

    Directory of Open Access Journals (Sweden)

    Riccardi Giovanna

    2009-03-01

    Full Text Available Abstract Background The ESAT-6 (early secreted antigenic target, 6 kDa family collects small mycobacterial proteins secreted by Mycobacterium tuberculosis, particularly in the early phase of growth. There are 23 ESAT-6 family members in M. tuberculosis H37Rv. In a previous work, we identified the Zur- dependent regulation of five proteins of the ESAT-6/CFP-10 family (esxG, esxH, esxQ, esxR, and esxS. esxG and esxH are part of ESAT-6 cluster 3, whose expression was already known to be induced by iron starvation. Results In this research, we performed EMSA experiments and transcriptional analysis of ESAT-6 cluster 3 in Mycobacterium smegmatis (msmeg0615-msmeg0625 and M. tuberculosis. In contrast to what we had observed in M. tuberculosis, we found that in M. smegmatis ESAT-6 cluster 3 responds only to iron and not to zinc. In both organisms we identified an internal promoter, a finding which suggests the presence of two transcriptional units and, by consequence, a differential expression of cluster 3 genes. We compared the expression of msmeg0615 and msmeg0620 in different growth and stress conditions by means of relative quantitative PCR. The expression of msmeg0615 and msmeg0620 genes was essentially similar; they appeared to be repressed in most of the tested conditions, with the exception of acid stress (pH 4.2 where msmeg0615 was about 4-fold induced, while msmeg0620 was repressed. Analysis revealed that in acid stress conditions M. tuberculosis rv0282 gene was 3-fold induced too, while rv0287 induction was almost insignificant. Conclusion In contrast with what has been reported for M. tuberculosis, our results suggest that in M. smegmatis only IdeR-dependent regulation is retained, while zinc has no effect on gene expression. The role of cluster 3 in M. tuberculosis virulence is still to be defined; however, iron- and zinc-dependent expression strongly suggests that cluster 3 is highly expressed in the infective process, and that the cluster

  20. On Monte Carlo and molecular dynamics methods inspired by Tsallis statistics: Methodology, optimization, and application to atomic clusters

    Science.gov (United States)

    Andricioaei, Ioan; Straub, John E.

    1997-12-01

    Generalized Monte Carlo and molecular dynamics algorithms which provide enhanced sampling of the phase space in the calculation of equilibrium thermodynamic properties is presented. The algorithm samples trial moves from a generalized statistical distribution derived from a modification of the Gibbs-Shannon entropy proposed by Tsallis. Results for a one-dimensional model potential demonstrate that the algorithm leads to a greatly enhanced rate of barrier crossing and convergence in the calculation of equilibrium averages. Comparison is made with standard Metropolis Monte Carlo and the J-walking algorithm of Franz, Freeman and Doll. Application to a 13-atom Lennard-Jones cluster demonstrates the ease with which the algorithm may be applied to complex molecular systems.

  1. Inter-channel effects in monosolvated atomic iodide cluster anion detachment: correlation of the anisotropy parameter with solvent dipole moment.

    Science.gov (United States)

    Mbaiwa, Foster; Dao, Diep; Holtgrewe, Nicholas; Lasinski, Joshua; Mabbs, Richard

    2012-03-21

    Photoelectron imaging results are presented for I(-)[middle dot]X cluster anions (X = CO(2), C(4)H(5)N [pyrrole], (CH(3))(2)CO, CH(3)NO(2)). The available detachment channels are labeled according to the neutral iodine atom states produced (channel I ≡ (2)P(3/2) and channel II ≡ (2)P(1/2)). At photon energies in the vicinity of the channel II threshold these data are compared to previously reported results for I(-)[middle dot]X (X = CH(3)CN, CH(3)Cl, CH(3)Br, and H(2)O). In particular, these results show a strong connection between the dipole moment of the solvent molecule and the behavior of the channel I photoelectron angular distributions in this region, which is consistent with an electronic autodetachment process. The evolution of the channel II:channel I branching ratios in this excitation regime supports this contention.

  2. Inter-channel effects in monosolvated atomic iodide cluster anion detachment: Correlation of the anisotropy parameter with solvent dipole moment

    Science.gov (United States)

    Mbaiwa, Foster; Dao, Diep; Holtgrewe, Nicholas; Lasinski, Joshua; Mabbs, Richard

    2012-03-01

    Photoelectron imaging results are presented for I-.X cluster anions (X = CO2, C4H5N [pyrrole], (CH3)2CO, CH3NO2). The available detachment channels are labeled according to the neutral iodine atom states produced (channel I ≡ 2P3/2 and channel II ≡ 2P1/2). At photon energies in the vicinity of the channel II threshold these data are compared to previously reported results for I-.X (X = CH3CN, CH3Cl, CH3Br, and H2O). In particular, these results show a strong connection between the dipole moment of the solvent molecule and the behavior of the channel I photoelectron angular distributions in this region, which is consistent with an electronic autodetachment process. The evolution of the channel II:channel I branching ratios in this excitation regime supports this contention.

  3. Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering

    Science.gov (United States)

    Yang, Bo; Fu, Xiao; Sidiropoulos, Nicholas D.

    2017-01-01

    Dimensionality reduction techniques play an essential role in data analytics, signal processing and machine learning. Dimensionality reduction is usually performed in a preprocessing stage that is separate from subsequent data analysis, such as clustering or classification. Finding reduced-dimension representations that are well-suited for the intended task is more appealing. This paper proposes a joint factor analysis and latent clustering framework, which aims at learning cluster-aware low-dimensional representations of matrix and tensor data. The proposed approach leverages matrix and tensor factorization models that produce essentially unique latent representations of the data to unravel latent cluster structure -- which is otherwise obscured because of the freedom to apply an oblique transformation in latent space. At the same time, latent cluster structure is used as prior information to enhance the performance of factorization. Specific contributions include several custom-built problem formulations, corresponding algorithms, and discussion of associated convergence properties. Besides extensive simulations, real-world datasets such as Reuters document data and MNIST image data are also employed to showcase the effectiveness of the proposed approaches.

  4. Isolation of atomically precise mixed ligand shell PdAu24 clusters

    Science.gov (United States)

    Sels, Annelies; Barrabés, Noelia; Knoppe, Stefan; Bürgi, Thomas

    2016-05-01

    Exposure of PdAu24(2-PET)18 (2-PET: 2-phenylethylthiolate) to BINAS (1,1-binaphthyl-2,2-dithiol) leads to species of composition PdAu24(2-PET)18-2x(BINAS)x due to ligand exchange reactions. The BINAS adsorbs in a specific mode that bridges the apex and one core site of two adjacent S(R)-Au-S(R)-Au-S(R) units. Species with different compositions of the ligand shell can be separated by HPLC. Furthermore, site isomers can be separated. For the cluster with exactly one BINAS in its ligand shell only one isomer is expected due to the symmetry of the cluster, which is confirmed by High-Performance Liquid Chromatography (HPLC). Addition of a second BINAS to the ligand shell leads to several isomers. In total six distinguishable isomers are possible for PdAu24(2-PET)14(BINAS)2 including two pairs of enantiomers concerning the adsorption pattern. At least four distinctive isomers are separated by HPLC. Calculations indicate that one of the six possibilities is energetically disfavoured. Interestingly, diastereomers, which have an enantiomeric relationship concerning the adsorption pattern of chiral BINAS, have significantly different stabilities. The relative intensity of the observed peaks in the HPLC does not reflect the statistical weight of the different isomers. This shows, as supported by the calculations, that the first adsorbed BINAS molecule influences the adsorption of the second incoming BINAS ligand. In addition, experiments with the corresponding Pt doped gold cluster reveal qualitatively the same behaviour, however with slightly different relative abundances of the corresponding isomers. This finding points towards the influence of electronic effects on the isomer distribution. Even for clusters containing more than two BINAS ligands a limited number of isomers were found, which is in contrast to the corresponding situation for monothiols, where the number of possible isomers is much larger.Exposure of PdAu24(2-PET)18 (2-PET: 2-phenylethylthiolate) to BINAS (1

  5. Encapsulation method for atom probe tomography analysis of nanoparticles.

    Science.gov (United States)

    Larson, D J; Giddings, A D; Wu, Y; Verheijen, M A; Prosa, T J; Roozeboom, F; Rice, K P; Kessels, W M M; Geiser, B P; Kelly, T F

    2015-12-01

    Open-space nanomaterials are a widespread class of technologically important materials that are generally incompatible with analysis by atom probe tomography (APT) due to issues with specimen preparation, field evaporation and data reconstruction. The feasibility of encapsulating such non-compact matter in a matrix to enable APT measurements is investigated using nanoparticles as an example. Simulations of field evaporation of a void, and the resulting artifacts in ion trajectory, underpin the requirement that no voids remain after encapsulation. The approach is demonstrated by encapsulating Pt nanoparticles in an ZnO:Al matrix created by atomic layer deposition, a growth technique which offers very high surface coverage and conformality. APT measurements of the Pt nanoparticles are correlated with transmission electron microscopy images and numerical simulations in order to evaluate the accuracy of the APT reconstruction.

  6. Characterization of population exposure to organochlorines: A cluster analysis application

    NARCIS (Netherlands)

    R.M. Guimarães (Raphael Mendonça); S. Asmus (Sven); A. Burdorf (Alex)

    2013-01-01

    textabstractThis study aimed to show the results from a cluster analysis application in the characterization of population exposure to organochlorines through variables related to time and exposure dose. Characteristics of 354 subjects in a population exposed to organochlorine pesticides residues

  7. Cluster analysis as a prediction tool for pregnancy outcomes.

    Science.gov (United States)

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  8. A Cluster Analysis of Personality Style in Adults with ADHD

    Science.gov (United States)

    Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

    2008-01-01

    Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

  9. A Cluster Analysis of Personality Style in Adults with ADHD

    Science.gov (United States)

    Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

    2008-01-01

    Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

  10. Language Learner Motivational Types: A Cluster Analysis Study

    Science.gov (United States)

    Papi, Mostafa; Teimouri, Yasser

    2014-01-01

    The study aimed to identify different second language (L2) learner motivational types drawing on the framework of the L2 motivational self system. A total of 1,278 secondary school students learning English in Iran completed a questionnaire survey. Cluster analysis yielded five different groups based on the strength of different variables within…

  11. Making Sense of Cluster Analysis: Revelations from Pakistani Science Classes

    Science.gov (United States)

    Pell, Tony; Hargreaves, Linda

    2011-01-01

    Cluster analysis has been applied to quantitative data in educational research over several decades and has been a feature of the Maurice Galton's research in primary and secondary classrooms. It has offered potentially useful insights for teaching yet its implications for practice are rarely implemented. It has been subject also to negative…

  12. Frailty phenotypes in the elderly based on cluster analysis

    DEFF Research Database (Denmark)

    Dato, Serena; Montesanto, Alberto; Lagani, Vincenzo

    2012-01-01

    genetic background on the frailty status is still questioned. We investigated the applicability of a cluster analysis approach based on specific geriatric parameters, previously set up and validated in a southern Italian population, to two large longitudinal Danish samples. In both cohorts, we identified...

  13. Herschel observations of extended atomic gas in the core of the Perseus cluster

    CERN Document Server

    Mittal, Rupal; Ferland, Gary J; Edge, Alastair C; O'Dea, Christopher P; Baum, Stefi A; Whelan, John T; Johnstone, Roderick M; Combes, Francoise; Salome, Philippe; Fabian, Andy C; Tremblay, Grant R; Donahue, Megan; Russell, Helen

    2012-01-01

    We present Herschel observations of the core of the Perseus cluster of galaxies. The brightest cluster galaxy, NGC 1275, is surrounded by a network of filaments previously imaged extensively in H{\\alpha} and CO. In this work, we report detections of FIR lines with Herschel. All but one of the lines are spatially extended, with the [CII] line emission extending up to 25 kpc from the core. There is spatial and kinematical correlation among [CII], H{\\alpha} and CO, which gives us confidence to model the different components of the gas with a common heating model. With the help of FIR continuum Herschel measurements, together with a suite of coeval radio, submm and infrared data, we performed a SED fitting of NGC 1275 using a model that contains contributions from dust emission as well as synchrotron AGN emission. The data indicate a low dust emissivity index, beta ~ 1, a total dust mass close to 10^7 solar mass, a cold dust component with temperature 38 \\pm 2 K and a warm dust component with temperature of 116 \\...

  14. Atom-by-Atom Analysis of Semiconductor Nanowires with Parts Per Million Sensitivity.

    Science.gov (United States)

    Koelling, S; Li, A; Cavalli, A; Assali, S; Car, D; Gazibegovic, S; Bakkers, E P A M; Koenraad, P M

    2017-02-08

    The functionality of semiconductor devices is determined by the incorporation of dopants at concentrations down to the parts per million (ppm) level and below. Optimization of intentional and unintentional impurity doping relies on methods to detect and map the level of impurities. Detecting such low concentrations of impurities in nanostructures is however challenging to date as on the one hand methods used for macroscopic samples cannot be applied due to the inherent small volumes or faceted surfaces and on the other hand conventional microscopic analysis techniques are not sufficiently sensitive. Here, we show that we can detect and map impurities at the ppm level in semiconductor nanowires using atom probe tomography. We develop a method applicable to a wide variety of nanowires relevant for electronic and optical devices. We expect that it will contribute significantly to the further optimization of the synthesis of nanowires, nanostructures and devices based on these structures.

  15. Photoelectron angular distributions for states of any mixed character: an experiment-friendly model for atomic, molecular, and cluster anions.

    Science.gov (United States)

    Khuseynov, Dmitry; Blackstone, Christopher C; Culberson, Lori M; Sanov, Andrei

    2014-09-28

    We present a model for laboratory-frame photoelectron angular distributions in direct photodetachment from (in principle) any molecular orbital using linearly polarized light. A transparent mathematical approach is used to generalize the Cooper-Zare central-potential model to anionic states of any mixed character. In the limit of atomic-anion photodetachment, the model reproduces the Cooper-Zare formula. In the case of an initial orbital described as a superposition of s and p-type functions, the model yields the previously obtained s-p mixing formula. The formalism is further advanced using the Hanstorp approximation, whereas the relative scaling of the partial-wave cross-sections is assumed to follow the Wigner threshold law. The resulting model describes the energy dependence of photoelectron anisotropy for any atomic, molecular, or cluster anions, usually without requiring a direct calculation of the transition dipole matrix elements. As a benchmark case, we apply the p-d variant of the model to the experimental results for NO(-) photodetachment and show that the observed anisotropy trend is described well using physically meaningful values of the model parameters. Overall, the presented formalism delivers insight into the photodetachment process and affords a new quantitative strategy for analyzing the photoelectron angular distributions and characterizing mixed-character molecular orbitals using photoelectron imaging spectroscopy of negative ions.

  16. Metals on graphene and carbon nanotube surfaces: From mobile atoms to atomtronics to bulk metals to clusters and catalysts

    KAUST Repository

    Sarkar, Santanu C.

    2014-01-14

    In this Perspective, we present an overview of recent fundamental studies on the nature of the interaction between individual metal atoms and metal clusters and the conjugated surfaces of graphene and carbon nanotube with a particular focus on the electronic structure and chemical bonding at the metal-graphene interface. We discuss the relevance of organometallic complexes of graphitic materials to the development of a fundamental understanding of these interactions and their application in atomtronics as atomic interconnects, high mobility organometallic transistor devices, high-frequency electronic devices, organometallic catalysis (hydrogen fuel generation by photocatalytic water splitting, fuel cells, hydrogenation), spintronics, memory devices, and the next generation energy devices. We touch on chemical vapor deposition (CVD) graphene grown on metals, the reactivity of its surface, and its use as a template for asymmetric graphene functionalization chemistry (ultrathin Janus discs). We highlight some of the latest advances in understanding the nature of interactions between metals and graphene surfaces from the standpoint of metal overlayers deposited on graphene and SWNT thin films. Finally, we comment on the major challenges facing the field and the opportunities for technological applications. © 2013 American Chemical Society.

  17. Star-forming dwarf galaxies in the Virgo cluster: the link between molecular gas, atomic gas, and dust

    CERN Document Server

    Grossi, M; Bizzocchi, L; Giovanardi, C; Bomans, D; Coelho, B; De Looze, I; Gonçalves, T S; Hunt, L K; Leonardo, E; Madden, S; Menéndez-Delmestre, K; Pappalardo, C; Riguccini, L

    2016-01-01

    We present $^{12}$CO(1-0) and $^{12}$CO(2-1) observations of a sample of 20 star-forming dwarfs selected from the Herschel Virgo Cluster Survey, with oxygen abundances ranging from 12 + log(O/H) ~ 8.1 to 8.8. CO emission is observed in ten galaxies and marginally detected in another one. CO fluxes correlate with the FIR 250 $\\mu$m emission, and the dwarfs follow the same linear relation that holds for more massive spiral galaxies extended to a wider dynamical range. We compare different methods to estimate H2 molecular masses, namely a metallicity-dependent CO-to-H2 conversion factor and one dependent on H-band luminosity. The molecular-to-stellar mass ratio remains nearly constant at stellar masses <~ 10$^9$ M$_{\\odot}$, contrary to the atomic hydrogen fraction, M$_{HI}$/M$_*$, which increases inversely with M$_*$. The flattening of the M$_{H_2}$/M$_*$ ratio at low stellar masses does not seem to be related to the effects of the cluster environment because it occurs for both HI-deficient and HI-normal dwa...

  18. Reappraisal of nuclear quadrupole moments of atomic halogens via relativistic coupled cluster linear response theory for the ionization process.

    Science.gov (United States)

    Chaudhuri, Rajat K; Chattopadhyay, Sudip; Mahapatra, Uttam Sinha

    2013-11-27

    The coupled cluster based linear response theory (CCLRT) with four-component relativistic spinors is employed to compute the electric field gradients (EFG) of (35)Cl, (79)Br, and (127)I nuclei. The EFGs resulting from these calculations are combined with experimental nuclear quadrupole coupling constants (NQCC) to determine the nuclear quadrupole moments (NQM), Q of the halide nuclei. Our estimated NQMs [(35)Cl = -81.12 mb, (79)Br = 307.98 mb, and (127)I = -688.22 mb] agree well with the new atomic values [(35)Cl = -81.1(1.2), (79)Br = 302(5), and (127)I = -680(10) mb] obtained via Fock space multireference coupled cluster method with the Dirac-Coulomb-Breit Hamiltonian. Although our estimated Q((79)Br) value deviates from the accepted reference value of 313(3) mb, it agrees well with the recently recommended value, Q((79)Br) = 308.7(20) mb. Good agreement with current reference data indicates the accuracy of the proposed value for these halogen nuclei and lends credence to the results obtained via CCLRT approach. The electron affinities yielded by this method with no extra cost are also in good agreement with experimental values, which bolster our belief that the NQMs values for halogen nuclei derived here are reliable.

  19. Selective electrodesorption based atomic layer deposition (SEBALD): a novel electrochemical route to deposit metal clusters on Ag(111).

    Science.gov (United States)

    Innocenti, M; Bellandi, S; Lastraioli, E; Loglio, F; Foresti, M L

    2011-09-20

    The possibility of synergic effects of some metals on the catalytic activity of silver led us to study the way to perform controlled deposition on silver. In fact, many metals of technological interest such as Co, Ni, and Fe cannot be deposited at underpotential on silver, and any attempt to control the deposition at overpotential, even at potentials slightly negative of the Nernst value, did not allow an effective control. However, due to the favorable energy gain involved in the formation of the corresponding sulfides, these metals can be deposited at underpotential on sulfur covered silver. The deposition is surface limited and the successive electrodesorption of sulfur leaves confined clusters of metals. The method can also be used to obtain metal clusters of different size. In fact, the alternate underpotential deposition of elements that form a compound is the basis of the electrochemical atomic layer epitaxy (ECALE), and the reiteration of the basic cycle allows us to obtain sulfide deposits whose thickness increases with the number of cycles. Therefore, the successive selective desorption of sulfur leaves increasing amounts of metals.

  20. Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

    Directory of Open Access Journals (Sweden)

    Tushar H Jaware

    2013-10-01

    Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

  1. Effect of hydrogen atoms on the structures of trinuclear metal carbonyl clusters: trinuclear manganese carbonyl hydrides.

    Science.gov (United States)

    Liu, Xian-mei; Wang, Chao-yang; Li, Qian-shu; Xie, Yaoming; King, R Bruce; Schaefer, Henry F

    2009-05-18

    The structures of the trinuclear manganese carbonyl hydrides H(3)Mn(3)(CO)(n) (n = 12, 11, 10, 9) have been investigated by density functional theory (DFT). Optimization of H(3)Mn(3)(CO)(12) gives the experimentally known structure in which all carbonyl groups are terminal and each edge of a central Mn(3) equilateral triangle is bridged by a single hydrogen atom. This structure establishes the canonical distance 3.11 A for the Mn-Mn single bond satisfying the 18-electron rule. The central triangular (mu-H)(3)Mn(3) unit is retained in the lowest energy structure of H(3)Mn(3)(CO)(11), which may thus be derived from the H(3)Mn(3)(CO)(12) structure by removal of a carbonyl group with concurrent conversion of one of the remaining carbonyl groups into a semibridging carbonyl group to fill the resulting hole. The potential energy surface of H(3)Mn(3)(CO)(10) is relatively complicated with six singlet and five triplet structures. One of the lower energy H(3)Mn(3)(CO)(10) structures has one of the hydrogen atoms bridging the entire Mn(3) triangle and the other two hydrogen atoms bridging Mn-Mn edges. This H(3)Mn(3)(CO)(10) structure achieves the favored 18-electron configuration with a very short MnMn triple bond of 2.36 A. The other low energy H(3)Mn(3)(CO)(10) structure retains the (mu-H)(3)Mn(3) core of H(3)Mn(3)(CO)(12) but has a unique six-electron donor eta(2)-mu(3) carbonyl group bridging the entire Mn(3) triangle similar to the unique carbonyl group in the known compound Cp(3)Nb(3)(CO)(6)(eta(2)-mu(3)-CO). For H(3)Mn(3)(CO)(9) a structure with a central (mu(3)-H)(2)Mn(3) trigonal bipyramid lies >20 kcal/mol below any of the other structures. Triplet structures were found for the unsaturated H(3)Mn(3)(CO)(n) (n = 11, 10, 9) systems but at significantly higher energies than the lowest lying singlet structures.

  2. Outcome-Driven Cluster Analysis with Application to Microarray Data.

    Directory of Open Access Journals (Sweden)

    Jessie J Hsu

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

  3. Improving Cluster Analysis with Automatic Variable Selection Based on Trees

    Science.gov (United States)

    2014-12-01

    ANALYSIS WITH AUTOMATIC VARIABLE SELECTION BASED ON TREES by Anton D. Orr December 2014 Thesis Advisor: Samuel E. Buttrey Second Reader...DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE IMPROVING CLUSTER ANALYSIS WITH AUTOMATIC VARIABLE SELECTION BASED ON TREES 5. FUNDING NUMBERS 6...2006 based on classification and regression trees to address problems with determining dissimilarity. Current algorithms do not simultaneously address

  4. Modeling optical properties of silicon clusters by first principles: From a few atoms to large nanocrystals

    Energy Technology Data Exchange (ETDEWEB)

    Nurbawono, Argo; Liu, Shuanglong [Department of Physics and the Centre for Advanced 2D Materials, National University of Singapore, 2 Science Drive 3 (Singapore); Zhang, Chun, E-mail: phyzc@nus.edu.sg [Department of Physics and the Centre for Advanced 2D Materials, National University of Singapore, 2 Science Drive 3 (Singapore); Department of Chemistry, National University of Singapore, 3 Science Drive 3 (Singapore)

    2015-04-21

    Time dependent density functional tight binding (TDDFTB) method is implemented with sparse matrix techniques and improved parallelization algorithms. The method is employed to calculate the optical properties of various Si nanocrystals (NCs). The calculated light absorption spectra of small Si NCs from TDDFTB were found to be comparable with many body perturbation methods utilizing planewave basis sets. For large Si NCs (more than a thousand atoms) that are beyond the reach of conventional approaches, the TDDFTB method is able to produce reasonable results that are consistent with prior experiments. We also employed the method to study the effects of surface chemistry on the optical properties of large Si NCs. We learned that the optical properties of Si NCs can be manipulated with small molecule passivations such as methyl, hydroxyl, amino, and fluorine. In general, the shifts and profiles in the absorption spectra can be tuned with suitably chosen passivants.

  5. FRACTAL PATTERN GROWTH OF METAL ATOM CLUSTERS IN ION IMPLANTED POLYMERS

    Institute of Scientific and Technical Information of China (English)

    ZHANG TONG-HE; WU YU-GUANG; SANG HAI-BO; ZHOU GU

    2001-01-01

    The fractal and multi-fractal patterns of metal atoms are observed in the surface layer and cross section of a metal ion implanted polymer using TEM and SEM for the first time. The surface structure in the metal ion implanted polyethylene terephthalane (PET) is the random fractal. Certain average quantities of the random geometric patterns contain self-similarity. Some growth origins appeared in the fractal pattern which has a dimension of 1.67. The network structure of the fractal patterns is formed in cross section, having a fractal dimension of 1.87. So it can be seen that the fractal pattern is three-dimensional space fractal. We also find the collision cascade fractal in the cross section of implanted nylon, which is similar to the collision cascade pattern in transverse view calculated by the TRIM computer program. Finally, the mechanism for the formation and growth of the fractal patterns during ion implantation is discussed.

  6. Embedded-cluster calculations in a numeric atomic orbital density-functional theory framework.

    Science.gov (United States)

    Berger, Daniel; Logsdail, Andrew J; Oberhofer, Harald; Farrow, Matthew R; Catlow, C Richard A; Sherwood, Paul; Sokol, Alexey A; Blum, Volker; Reuter, Karsten

    2014-07-14

    We integrate the all-electron electronic structure code FHI-aims into the general ChemShell package for solid-state embedding quantum and molecular mechanical (QM/MM) calculations. A major undertaking in this integration is the implementation of pseudopotential functionality into FHI-aims to describe cations at the QM/MM boundary through effective core potentials and therewith prevent spurious overpolarization of the electronic density. Based on numeric atomic orbital basis sets, FHI-aims offers particularly efficient access to exact exchange and second order perturbation theory, rendering the established QM/MM setup an ideal tool for hybrid and double-hybrid level density functional theory calculations of solid systems. We illustrate this capability by calculating the reduction potential of Fe in the Fe-substituted ZSM-5 zeolitic framework and the reaction energy profile for (photo-)catalytic water oxidation at TiO2(110).

  7. Embedded-cluster calculations in a numeric atomic orbital density-functional theory framework

    Science.gov (United States)

    Berger, Daniel; Logsdail, Andrew J.; Oberhofer, Harald; Farrow, Matthew R.; Catlow, C. Richard A.; Sherwood, Paul; Sokol, Alexey A.; Blum, Volker; Reuter, Karsten

    2014-07-01

    We integrate the all-electron electronic structure code FHI-aims into the general ChemShell package for solid-state embedding quantum and molecular mechanical (QM/MM) calculations. A major undertaking in this integration is the implementation of pseudopotential functionality into FHI-aims to describe cations at the QM/MM boundary through effective core potentials and therewith prevent spurious overpolarization of the electronic density. Based on numeric atomic orbital basis sets, FHI-aims offers particularly efficient access to exact exchange and second order perturbation theory, rendering the established QM/MM setup an ideal tool for hybrid and double-hybrid level density functional theory calculations of solid systems. We illustrate this capability by calculating the reduction potential of Fe in the Fe-substituted ZSM-5 zeolitic framework and the reaction energy profile for (photo-)catalytic water oxidation at TiO2(110).

  8. MEME-LaB: motif analysis in clusters.

    Science.gov (United States)

    Brown, Paul; Baxter, Laura; Hickman, Richard; Beynon, Jim; Moore, Jonathan D; Ott, Sascha

    2013-07-01

    Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets. MEME-LaB is freely accessible at: http://wsbc.warwick.ac.uk/wsbcToolsWebpage/. Supplementary data are available at Bioinformatics online.

  9. Cognitive analysis of multiple sclerosis utilizing fuzzy cluster means

    Directory of Open Access Journals (Sweden)

    Imianvan Anthony Agboizebeta

    2012-02-01

    Full Text Available Multiple sclerosis, often called MS, is a disease that affects the central nervous system (the brain andspinal cord. Myelin provides insulation for nerve cells improves the conduction of impulses along thenerves and is important for maintaining the health of the nerves. In multiple sclerosis, inflammationcauses the myelin to disappear. Genetic factors, environmental issues and viral infection may alsoplay a role in developing the disease. Ms is characterized by life threatening symptoms such as; loss ofbalance, hearing problem and depression. The application of Fuzzy Cluster Means (FCM or Fuzzy CMeananalysis to the diagnosis of different forms of multiple sclerosis is the focal point of this paper.Application of cluster analysis involves a sequence of methodological and analytical decision stepsthat enhances the quality and meaning of the clusters produced. Uncertainties associated withanalysis of multiple sclerosis test data are eliminated by the system

  10. Revision of single atom local density and capture number varying with coverage in uniform depletion approximation and its effect on coalescence and number of stable clusters

    Institute of Scientific and Technical Information of China (English)

    Shao Qing-Yi; Zhang Juan

    2011-01-01

    In vapour deposition,single atoms(adatoms)on the substrate surface are the main source of growth.The change in its density plays a decisive role in the growth of thin films and quantum size islands.In the nucleation and cluster coalescence stages of vapour deposition,the growth of stable clusters occurs on the substrate surface covered by stable clusters.Nucleation occurs in the non-covered part,while the total area covered by stable clusters on the substrate surface will gradually increase.Carefully taking into account the coverage effect,a revised single atom density rate equation is given for the famous and widely used thin-film rate equation theory,but the work of solving the revised equation has not been done.In this paper,we solve the equation and obtain the single-atom density and capture number by using a uniform depletion approximation.We determine that the single atom density is much lower than that evaluated from the single atom density rate equation in the traditional rate equation theory when the stable cluster coverage fraction is large,and it goes down very fast with an increase in the coverage fraction.The revised equation gives a higher value for the 'average' capture number than the present equation. It also increases with increasing coverage.That makes the preparation of single crystalline thin film materials difficult and the size control of quantum size islands complicated.We also discuss the effect of the revision on coalescence and the number of stable clusters in vapour deposition.

  11. Application of a convergent, composite coupled cluster approach to bound state, adiabatic electron affinities in atoms and small molecules

    Science.gov (United States)

    Feller, David

    2016-01-01

    Benchmark quality adiabatic electron affinities for a collection of atoms and small molecules were obtained with the Feller-Peterson-Dixon composite coupled cluster theory method. Prior applications of this method demonstrated its ability to accurately predict atomization energies/heats of formation for more than 170 molecules. In the current work, the 1-particle expansion involved very large correlation consistent basis sets, ranging up to aug-cc-pV9Z (aug-cc-pV10Z for H and H2), with the goal of minimizing the residual basis set truncation error that must otherwise be approximated with extrapolation formulas. The n-particle expansion begins with coupled cluster calculations through iterative single and double excitations plus a quasiperturbative treatment of "connected" triple excitations (CCSD(T)) pushed to the complete basis set limit followed by CCSDT, CCSDTQ, or CCSDTQ5 corrections. Due to the small size of the systems examined here, it was possible in many cases to extend the n-particle expansion to the full configuration interaction wave function limit. Additional, smaller corrections associated with core/valence correlation, scalar relativity, anharmonic zero point vibrational energies, and non-adiabatic effects were also included. The overall root mean square (RMS) deviation was 0.005 eV (0.12 kcal/mol). This level of agreement was comparable to what was found with molecular heats of formation. A 95% confidence level corresponds to roughly twice the RMS value or 0.01 eV. While the atomic electron affinities are known experimentally to high accuracy, the molecular values are less certain. This contributes to the difficulty of gauging the accuracy of the theoretical results. A limited number of electron affinities were determined with the explicitly correlated CCSD(T)-F12b method. After extending the VnZ-F12 orbital basis sets with additional diffuse functions, the F12b method was found to accurately reproduce the best F/F- value obtained with standard

  12. Evidence of superparamagnetic co clusters in pulsed laser deposition-grown Zn0.9Co0.1O thin films using atom probe tomography.

    Science.gov (United States)

    Lardé, Rodrigue; Talbot, Etienne; Pareige, Philippe; Bieber, Herrade; Schmerber, Guy; Colis, Silviu; Pierron-Bohnes, Véronique; Dinia, Aziz

    2011-02-09

    Nanosized Co clusters (of about 3 nm size) were unambiguously identified in Co-doped ZnO thin films by atom probe tomography. These clusters are directly correlated to the superparamagnetic relaxation observed by ZFC/FC magnetization measurements. These analyses provide strong evidence that the room-temperature ferromagnetism observed in the magnetization curves cannot be attributed to the observed Co clusters. Because there is no experimental evidence of the presence of other secondary phases, our results reinforce the assumption of a defect-induced ferromagnetism in Co-doped ZnO diluted magnetic semiconductors.

  13. Ultracold few fermionic atoms in needle-shaped double wells: spin chains and resonating spin clusters from microscopic Hamiltonians emulated via antiferromagnetic Heisenberg and t-J models

    Science.gov (United States)

    Yannouleas, Constantine; Brandt, Benedikt B.; Landman, Uzi

    2016-07-01

    Advances with trapped ultracold atoms intensified interest in simulating complex physical phenomena, including quantum magnetism and transitions from itinerant to non-itinerant behavior. Here we show formation of antiferromagnetic ground states of few ultracold fermionic atoms in single and double well (DW) traps, through microscopic Hamiltonian exact diagonalization for two DW arrangements: (i) two linearly oriented one-dimensional, 1D, wells, and (ii) two coupled parallel wells, forming a trap of two-dimensional, 2D, nature. The spectra and spin-resolved conditional probabilities reveal for both cases, under strong repulsion, atomic spatial localization at extemporaneously created sites, forming quantum molecular magnetic structures with non-itinerant character. These findings usher future theoretical and experimental explorations into the highly correlated behavior of ultracold strongly repelling fermionic atoms in higher dimensions, beyond the fermionization physics that is strictly applicable only in the 1D case. The results for four atoms are well described with finite Heisenberg spin-chain and cluster models. The numerical simulations of three fermionic atoms in symmetric DWs reveal the emergent appearance of coupled resonating 2D Heisenberg clusters, whose emulation requires the use of a t-J-like model, akin to that used in investigations of high T c superconductivity. The highly entangled states discovered in the microscopic and model calculations of controllably detuned, asymmetric, DWs suggest three-cold-atom DW quantum computing qubits.

  14. Implementation and Application of the Relativistic Equation of Motion Coupled-cluster Method for the Excited States of Closed-shell Atomic Systems

    CERN Document Server

    Nandy, D K; Sahoo, B K

    2014-01-01

    We report the implementation of equation-of-motion coupled-cluster (EOMCC) method in the four-component relativistic framework with the spherical atomic potential to generate the excited states from a closed-shell atomic configuration. This theoretical development will be very useful to carry out high precision calculations of varieties of atomic properties in many atomic systems. We employ this method to calculate excitation energies of many low-lying states in a few Ne-like highly charged ions, such as Cr XV, Fe XVII, Co XVIII and Ni XIX ions, and compare them against their corresponding experimental values to demonstrate the accomplishment of the EOMCC implementation. The considered ions are apt to substantiate accurate inclusion of the relativistic effects in the evaluation of the atomic properties and are also interesting for the astrophysical studies. Investigation of the temporal variation of the fine structure constant (\\alpha) from the astrophysical observations is one of the modern research problems...

  15. Natural atomic orbital based energy density analysis: Implementation and applications

    Science.gov (United States)

    Baba, Takeshi; Takeuchi, Mari; Nakai, Hiromi

    2006-06-01

    We present an improvement of energy density analysis (EDA), which partitions the total energy obtained by Hartree-Fock and/or density functional theory calculations, with the use of the natural atomic orbital (NAO) [A.E. Reed et al., J. Chem. Phys. 83 (1985) 735] and Löwdin's symmetric-orthogonal orbital (LSO). The present NAO- and LSO-EDA schemes are applied to analyses of CO 2 and Li9+ with various basis sets. Numerical results confirm that NAO-EDA exhibits less basis-set dependence, while the conventional results are very sensitive to the adopted basis sets.

  16. DGA Clustering and Analysis: Mastering Modern, Evolving Threats, DGALab

    Directory of Open Access Journals (Sweden)

    Alexander Chailytko

    2016-05-01

    Full Text Available Domain Generation Algorithms (DGA is a basic building block used in almost all modern malware. Malware researchers have attempted to tackle the DGA problem with various tools and techniques, with varying degrees of success. We present a complex solution to populate DGA feed using reversed DGAs, third-party feeds, and a smart DGA extraction and clustering based on emulation of a large number of samples. Smart DGA extraction requires no reverse engineering and works regardless of the DGA type or initialization vector, while enabling a cluster-based analysis. Our method also automatically allows analysis of the whole malware family, specific campaign, etc. We present our system and demonstrate its abilities on more than 20 malware families. This includes showing connections between different campaigns, as well as comparing results. Most importantly, we discuss how to utilize the outcome of the analysis to create smarter protections against similar malware.

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

    Directory of Open Access Journals (Sweden)

    Jeban Ganesalingam

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

  18. Behaviors of transmutation elements Re and Os and their effects on energetics and clustering of vacancy and self-interstitial atoms in W

    Science.gov (United States)

    Li, Yu-Hao; Zhou, Hong-Bo; Jin, Shuo; Zhang, Ying; Deng, Huiqiu; Lu, Guang-Hong

    2017-04-01

    We investigate the behaviors of rhenium (Re) and osmium (Os) and their interactions with point defects in tungsten (W) using a first-principles method. We show that Re atoms are energetically favorable to disperse separately in bulk W due to the Re–Re repulsive interaction. Despite the attractive interaction between Os atoms, there is still a large activation energy barrier of 1.10 eV at the critical number of 10 for the formation of Os clusters in bulk W based on the results of the total nucleation free energy change. Interestingly, the presence of vacancy can significantly reduce the total nucleation free energy change of Re/Os clusters, suggesting that vacancy can facilitate the nucleation of Re/Os in W. Re/Os in turn has an effect on the stability of the vacancy clusters (V n ) in W, especially for small vacancy clusters. A single Re/Os atom can raise the total binding energies of V2 and V3 obviously, thus enhancing their formation. Further, we demonstrate that there is a strong attractive interaction between Re/Os and self-interstitial atoms (SIAs). Re/Os could increase the diffusion barrier of SIAs and decrease their rotation barrier, while the interstitial-mediated path may be the optimal diffusion path of Re/Os in W. Consequently, the synergistic effect between Re/Os and point defects plays a key role in Re/Os precipitation and the evolution of defects in irradiated W.

  19. Clues on the Evolution of Cluster Galaxies From The Analysis of Their Orbital Anisotropies

    OpenAIRE

    Biviano, A.; Katgert, P.; Thomas, T; Mazure, A.

    2003-01-01

    We study the evolution of galaxies in clusters by the analysis of a sample of about 3000 galaxies, members of 59 clusters from the ESO Nearby Abell Cluster Survey (ENACS). We distinguish four cluster galaxy populations, based on their radial and velocity distributions within the clusters. Using the class of ellipticals and S0's (excluding the very bright ellipticals), we determine the average cluster mass profile, that we compare with mass models available from numerical simulations. We then ...

  20. The Productivity Analysis of Chennai Automotive Industry Cluster

    Science.gov (United States)

    Bhaskaran, E.

    2014-07-01

    Chennai, also called the Detroit of India, is India's second fastest growing auto market and exports auto components and vehicles to US, Germany, Japan and Brazil. For inclusive growth and sustainable development, 250 auto component industries in Ambattur, Thirumalisai and Thirumudivakkam Industrial Estates located in Chennai have adopted the Cluster Development Approach called Automotive Component Cluster. The objective is to study the Value Chain, Correlation and Data Envelopment Analysis by determining technical efficiency, peer weights, input and output slacks of 100 auto component industries in three estates. The methodology adopted is using Data Envelopment Analysis of Output Oriented Banker Charnes Cooper model by taking net worth, fixed assets, employment as inputs and gross output as outputs. The non-zero represents the weights for efficient clusters. The higher slack obtained reveals the excess net worth, fixed assets, employment and shortage in gross output. To conclude, the variables are highly correlated and the inefficient industries should increase their gross output or decrease the fixed assets or employment. Moreover for sustainable development, the cluster should strengthen infrastructure, technology, procurement, production and marketing interrelationships to decrease costs and to increase productivity and efficiency to compete in the indigenous and export market.

  1. Full text clustering and relationship network analysis of biomedical publications.

    Directory of Open Access Journals (Sweden)

    Renchu Guan

    Full Text Available Rapid developments in the biomedical sciences have increased the demand for automatic clustering of biomedical publications. In contrast to current approaches to text clustering, which focus exclusively on the contents of abstracts, a novel method is proposed for clustering and analysis of complete biomedical article texts. To reduce dimensionality, Cosine Coefficient is used on a sub-space of only two vectors, instead of computing the Euclidean distance within the space of all vectors. Then a strategy and algorithm is introduced for Semi-supervised Affinity Propagation (SSAP to improve analysis efficiency, using biomedical journal names as an evaluation background. Experimental results show that by avoiding high-dimensional sparse matrix computations, SSAP outperforms conventional k-means methods and improves upon the standard Affinity Propagation algorithm. In constructing a directed relationship network and distribution matrix for the clustering results, it can be noted that overlaps in scope and interests among BioMed publications can be easily identified, providing a valuable analytical tool for editors, authors and readers.

  2. Kinematic gait patterns in healthy runners: A hierarchical cluster analysis.

    Science.gov (United States)

    Phinyomark, Angkoon; Osis, Sean; Hettinga, Blayne A; Ferber, Reed

    2015-11-01

    Previous studies have demonstrated distinct clusters of gait patterns in both healthy and pathological groups, suggesting that different movement strategies may be represented. However, these studies have used discrete time point variables and usually focused on only one specific joint and plane of motion. Therefore, the first purpose of this study was to determine if running gait patterns for healthy subjects could be classified into homogeneous subgroups using three-dimensional kinematic data from the ankle, knee, and hip joints. The second purpose was to identify differences in joint kinematics between these groups. The third purpose was to investigate the practical implications of clustering healthy subjects by comparing these kinematics with runners experiencing patellofemoral pain (PFP). A principal component analysis (PCA) was used to reduce the dimensionality of the entire gait waveform data and then a hierarchical cluster analysis (HCA) determined group sets of similar gait patterns and homogeneous clusters. The results show two distinct running gait patterns were found with the main between-group differences occurring in frontal and sagittal plane knee angles (Pgait strategies. These results suggest care must be taken when selecting samples of subjects in order to investigate the pathomechanics of injured runners.

  3. Transcriptional analysis of exopolysaccharides biosynthesis gene clusters in Lactobacillus plantarum.

    Science.gov (United States)

    Vastano, Valeria; Perrone, Filomena; Marasco, Rosangela; Sacco, Margherita; Muscariello, Lidia

    2016-04-01

    Exopolysaccharides (EPS) from lactic acid bacteria contribute to specific rheology and texture of fermented milk products and find applications also in non-dairy foods and in therapeutics. Recently, four clusters of genes (cps) associated with surface polysaccharide production have been identified in Lactobacillus plantarum WCFS1, a probiotic and food-associated lactobacillus. These clusters are involved in cell surface architecture and probably in release and/or exposure of immunomodulating bacterial molecules. Here we show a transcriptional analysis of these clusters. Indeed, RT-PCR experiments revealed that the cps loci are organized in five operons. Moreover, by reverse transcription-qPCR analysis performed on L. plantarum WCFS1 (wild type) and WCFS1-2 (ΔccpA), we demonstrated that expression of three cps clusters is under the control of the global regulator CcpA. These results, together with the identification of putative CcpA target sequences (catabolite responsive element CRE) in the regulatory region of four out of five transcriptional units, strongly suggest for the first time a role of the master regulator CcpA in EPS gene transcription among lactobacilli.

  4. The Quantitative Analysis of Chennai Automotive Industry Cluster

    Science.gov (United States)

    Bhaskaran, Ethirajan

    2016-07-01

    Chennai, also called as Detroit of India due to presence of Automotive Industry producing over 40 % of the India's vehicle and components. During 2001-2002, the Automotive Component Industries (ACI) in Ambattur, Thirumalizai and Thirumudivakkam Industrial Estate, Chennai has faced problems on infrastructure, technology, procurement, production and marketing. The objective is to study the Quantitative Performance of Chennai Automotive Industry Cluster before (2001-2002) and after the CDA (2008-2009). The methodology adopted is collection of primary data from 100 ACI using quantitative questionnaire and analyzing using Correlation Analysis (CA), Regression Analysis (RA), Friedman Test (FMT), and Kruskall Wallis Test (KWT).The CA computed for the different set of variables reveals that there is high degree of relationship between the variables studied. The RA models constructed establish the strong relationship between the dependent variable and a host of independent variables. The models proposed here reveal the approximate relationship in a closer form. KWT proves, there is no significant difference between three locations clusters with respect to: Net Profit, Production Cost, Marketing Costs, Procurement Costs and Gross Output. This supports that each location has contributed for development of automobile component cluster uniformly. The FMT proves, there is no significant difference between industrial units in respect of cost like Production, Infrastructure, Technology, Marketing and Net Profit. To conclude, the Automotive Industries have fully utilized the Physical Infrastructure and Centralised Facilities by adopting CDA and now exporting their products to North America, South America, Europe, Australia, Africa and Asia. The value chain analysis models have been implemented in all the cluster units. This Cluster Development Approach (CDA) model can be implemented in industries of under developed and developing countries for cost reduction and productivity

  5. Subtyping demoralization in the medically ill by cluster analysis

    Directory of Open Access Journals (Sweden)

    Chiara Rafanelli

    2013-03-01

    Full Text Available Background and Objectives: There is increasing interest in the issue of demoralization, particularly in the setting of medical disease. The aim of this investigation was to use both DSM-IV comorbidity and the Diagnostic Criteria for Psychosomatic Research (DCPR in order to characterize demoralization in the medically ill. Methods: 1700 patients were recruited from 8 medical centers in the Italian Health System and 1560 agreed to participate. They all underwent a cross-sectional assessment with DSM-IV and DCPR structured interviews. 373 patients (23.9% received a diagnosis of demoralization. Data were submitted to cluster analysis. Results: Four clusters were identified: demoralization and comorbid depression; demoralization and comorbid somatoform/adjustment disorders; demoralization and comorbid anxiety; demoralization without any comorbid DSM disorder. The first cluster included 27.6% of the total sample and was characterized by the presence of DSM-IV mood disorders (mainly major depressive disorder. The second cluster had 18.2% of the cases and contained both DSM-IV somatoform (particularly, undifferentiated somatoform disorder and hypochondriasis and adjustment disorders. In the third cluster (24.7%, DSM-IV anxiety disorders in comorbidity with demoralization were predominant (particularly, generalized anxiety disorder, agoraphobia, panic disorder and obsessive-compulsive disorder. The fourth cluster had 29.5% of the patients and was characterized by the absence of any DSM-IV comorbid disorder. Conclusions: The findings indicate the need of expanding clinical assessment in the medically ill to include the various manifestations of demoralization as encompassed by the DCPR. Subtyping demoralization may yield improved targets for psychosomatic research and treatment trials.

  6. Bayesian Analysis of Multiple Populations in Galactic Globular Clusters

    Science.gov (United States)

    Wagner-Kaiser, Rachel A.; Sarajedini, Ata; von Hippel, Ted; Stenning, David; Piotto, Giampaolo; Milone, Antonino; van Dyk, David A.; Robinson, Elliot; Stein, Nathan

    2016-01-01

    We use GO 13297 Cycle 21 Hubble Space Telescope (HST) observations and archival GO 10775 Cycle 14 HST ACS Treasury observations of Galactic Globular Clusters to find and characterize multiple stellar populations. Determining how globular clusters are able to create and retain enriched material to produce several generations of stars is key to understanding how these objects formed and how they have affected the structural, kinematic, and chemical evolution of the Milky Way. We employ a sophisticated Bayesian technique with an adaptive MCMC algorithm to simultaneously fit the age, distance, absorption, and metallicity for each cluster. At the same time, we also fit unique helium values to two distinct populations of the cluster and determine the relative proportions of those populations. Our unique numerical approach allows objective and precise analysis of these complicated clusters, providing posterior distribution functions for each parameter of interest. We use these results to gain a better understanding of multiple populations in these clusters and their role in the history of the Milky Way.Support for this work was provided by NASA through grant numbers HST-GO-10775 and HST-GO-13297 from the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555. This material is based upon work supported by the National Aeronautics and Space Administration under Grant NNX11AF34G issued through the Office of Space Science. This project was supported by the National Aeronautics & Space Administration through the University of Central Florida's NASA Florida Space Grant Consortium.

  7. Study of Pair and many-body interactions in rare-gas halide atom clusters using negative ion zero electron kinetic energy (ZEKE) and threshold photodetachment spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Yourshaw, Ivan [Univ. of California, Berkeley, CA (United States)

    1998-07-09

    The diatomic halogen atom-rare gas diatomic complexes KrBr-, XeBr-, and KrCl- are studied in this work by zero electron kinetic energy (ZEKE) spectroscopy in order to characterize the weak intermolecular diatomic potentials of these species. Also, the ZEKE and threshold photodetachment spectra of the polyatomic clusters ArnBr- (n = 2-9) and ArnI- (n = 2-19) are studied to obtain information about the non-additive effects on the interactions among the atoms. This work is part of an ongoing effort to characterize the pair and many-body potentials of the complete series of rare gas halide clusters. In these studies we obtain information about both the anionic and neutral clusters.

  8. RCCPAC: A parallel relativistic coupled-cluster program for closed-shell and one-valence atoms and ions in FORTRAN

    Science.gov (United States)

    Mani, B. K.; Chattopadhyay, S.; Angom, D.

    2017-04-01

    We report the development of a parallel FORTRAN code, RCCPAC, to solve the relativistic coupled-cluster equations for closed-shell and one-valence atoms and ions. The parallelization is implemented through the use of message passing interface, which is suitable for distributed memory computers. The coupled-cluster equations are defined in terms of the reduced matrix elements, and solved iteratively using Jacobi method. The ground and excited states of coupled-cluster wave functions obtained from the code could be used to compute different properties of closed-shell and one-valence atom or ion. As an example we compute the ground state correlation energy, attachment energies, E1 reduced matrix elements and hyperfine structure constants.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jocelyn H Bolin

    2014-04-01

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

  11. Detection of Functional Change Using Cluster Trend Analysis in Glaucoma

    Science.gov (United States)

    Gardiner, Stuart K.; Mansberger, Steven L.; Demirel, Shaban

    2017-01-01

    Purpose Global analyses using mean deviation (MD) assess visual field progression, but can miss localized changes. Pointwise analyses are more sensitive to localized progression, but more variable so require confirmation. This study assessed whether cluster trend analysis, averaging information across subsets of locations, could improve progression detection. Methods A total of 133 test–retest eyes were tested 7 to 10 times. Rates of change and P values were calculated for possible re-orderings of these series to generate global analysis (“MD worsening faster than x dB/y with P trend analysis detects subsequently confirmed deterioration sooner than either global or pointwise analyses. PMID:28715580

  12. Segment clustering methodology for unsupervised Holter recordings analysis

    Science.gov (United States)

    Rodríguez-Sotelo, Jose Luis; Peluffo-Ordoñez, Diego; Castellanos Dominguez, German

    2015-01-01

    Cardiac arrhythmia analysis on Holter recordings is an important issue in clinical settings, however such issue implicitly involves attending other problems related to the large amount of unlabelled data which means a high computational cost. In this work an unsupervised methodology based in a segment framework is presented, which consists of dividing the raw data into a balanced number of segments in order to identify fiducial points, characterize and cluster the heartbeats in each segment separately. The resulting clusters are merged or split according to an assumed criterion of homogeneity. This framework compensates the high computational cost employed in Holter analysis, being possible its implementation for further real time applications. The performance of the method is measure over the records from the MIT/BIH arrhythmia database and achieves high values of sensibility and specificity, taking advantage of database labels, for a broad kind of heartbeats types recommended by the AAMI.

  13. Data Preprocessing in Cluster Analysis of Gene Expression

    Institute of Scientific and Technical Information of China (English)

    杨春梅; 万柏坤; 高晓峰

    2003-01-01

    Considering that the DNA microarray technology has generated explosive gene expression data and that it is urgent to analyse and to visualize such massive datasets with efficient methods, we investigate the data preprocessing methods used in cluster analysis, normalization or logarithm of the matrix, by using hierarchical clustering, principal component analysis (PCA) and self-organizing maps (SOMs). The results illustrate that when using the Euclidean distance as measuring metrics, logarithm of relative expression level is the best preprocessing method, while data preprocessed by normalization cannot attain the expected results because the data structure is ruined. If there are only a few principal components, the PCA is an effective method to extract the frame structure, while SOMs are more suitable for a specific structure.

  14. Atomic scale modelling of nanosize Ni sub 3 Al cluster beam deposition on Al, Ni and Ni sub 3 Al (1 1 1) surfaces

    CERN Document Server

    Kharlamov, V S; Hou, M

    2002-01-01

    The slowing down of Ni sub 3 Al clusters on a Al, Ni and Ni sub 3 Al (1 1 1) surfaces is studied by atomic scale modelling. The semi-grand canonical metropolis Monte Carlo is used for the preparation of isolated clusters at thermodynamic equilibrium. The cluster deposition on the surface is studied in detail by classical Molecular Dynamics simulations that include a model to account for electron-phonon coupling. Long- and short-range orders in the cluster are evaluated as functions of temperature in an impact energy range between 0 and 1.5 eV/atom. The interaction between the Ni sub 3 Al cluster and an Al surface is characterised low short range (chemical) disorder. No sizeable epitaxy is found, subsequent to the impact. In contrast, in the case of Ni and Ni sub 3 Al substrates, which are harder materials than aluminium, the chemical disorder is higher and epitaxial accommodation is possible. With these substrates, chemical disorder in the cluster is an increasing function of the impact energy, as well as of ...

  15. Post-irradiation annealing of Ni–Mn–Si-enriched clusters in a neutron-irradiated RPV steel weld using Atom Probe Tomography

    Energy Technology Data Exchange (ETDEWEB)

    Styman, P.D., E-mail: paul.styman@materials.ox.ac.uk [National Nuclear Laboratory, 168 Harwell Business Centre, Didcot, Oxon OX11 0QT (United Kingdom); Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Hyde, J.M. [National Nuclear Laboratory, 168 Harwell Business Centre, Didcot, Oxon OX11 0QT (United Kingdom); Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); School of Materials, University of Manchester, Manchester M13 9PL (United Kingdom); Parfitt, D.; Wilford, K. [Rolls-Royce, PO BOX 2000, Raynesway, Derby DE21 7XX (United Kingdom); Burke, M.G. [School of Materials, University of Manchester, Manchester M13 9PL (United Kingdom); English, C.A. [National Nuclear Laboratory, 168 Harwell Business Centre, Didcot, Oxon OX11 0QT (United Kingdom); Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); School of Materials, University of Manchester, Manchester M13 9PL (United Kingdom); Efsing, P. [Vattenfall Ringhals AB, Väröbacka (Sweden)

    2015-04-15

    Highlights: • Characterisation of high Ni neutron irradiated RPV surveillance samples at high fluence. • Post-irradiation annealing performed to give insight into the formation mechanisms of Ni–Mn–Si precipitates. • Dissolution of Ni–Mn–Si clusters appears to be lead by the removal of Mn. - Abstract: Atom Probe Tomography has been performed on as-irradiated and post-irradiation annealed surveillance weld samples from Ringhals Unit 3. The weld contains low Cu (0.07 at.%) and high Ni (1.5 at.%). A high number density (∼4 × 10{sup 23} m{sup −3}) of Ni–Mn–Si-enriched clusters was observed in the as-irradiated material. The onset of recovery was observed during the annealing for 30 min at 450 °C. Much more significant dissolution of clusters occurred during the 10 min 500 °C anneal, resulting in a reduction in mean cluster size and a halving of their volume fraction. Detailed analyses of the changes in microstructure demonstrate that the dissolution process is driven by migration of Mn atoms from the clusters. This may indicate a strong correlation between Mn and point defects. Dissolution of the clusters is shown to correlate with recovery of mechanical properties in this material.

  16. Prediction of the transition energies of atomic No and Lr by the intermediate Hamiltonian coupled cluster method

    Energy Technology Data Exchange (ETDEWEB)

    Borschevsky, A.; Eliav, E.; Kaldor, U. [School of Chemistry, Tel Aviv University, 69978 Tel Aviv, (Israel); Vilkas, M.J.; Ishikawa, Y. [Department of Chemistry, University of Puerto Rico, P.O. Box 23346, San Juan, Puerto Rico 00931-3346 (United States)

    2007-07-01

    Complete text of publication follows: Measurements of the spectroscopic properties of the superheavy elements present a serious challenge to the experimentalist. Their short lifetimes and the low quantities of their production necessitate reliable prediction of transition energies to avoid the need for broad wavelength scans and to assist in identifying the lines. Thus, reliable high-accuracy calculations are necessary prior and parallel to experimental research. Nobelium and Lawrencium are at present the two most likely candidates for spectroscopic measurements, with the first experiments planned at GSI, Darmstadt. The intermediate Hamiltonian (IH) coupled cluster method is applied to the ionization potentials, electron affinities, and excitation energies of atomic nobelium and lawrencium. Large basis sets are used (37s31p26d21f16g11h6i). All levels of a particular atom are obtained simultaneously by diagonalizing the IH matrix. The matrix elements correspond to all excitations from correlated occupied orbitals to virtual orbitals in a large P space, and are 'dressed' by folding in excitations to higher virtual orbitals (Q space) at the coupled cluster singles-and-doubles level. Lamb-shift corrections are included. The same approach was applied to the lighter homologues of Lr and No, lutetium and ytterbium, for which many transition energies are experimentally known, in order to assess the accuracy of the calculation. The average absolute error of 20 excitation energies of Lu is 423 cm{sup -1}, and the error limits for Lr are therefore put at 700 cm{sup -1}. Predicted Lr excitations with large transition moments in the prime range for the planned experiment, 20,000-30,000 cm{sup -1}, are 7p {yields} 8s at 20,100 cm{sup -1} and 7p {yields}p 7d at 28,100 cm{sup -1}. In case of Yb, the calculated ionization potential was within 20 cm{sup -1} of the experiment, and the average error of the 20 lowest calculated excitations was about 300 cm{sup -1}. Hence, the

  17. An Interpretation of the Boshier-Collins Cluster Analysis Testing Houle's Typology.

    Science.gov (United States)

    Furst, Edward J.

    1986-01-01

    This article speculates on an underlying order obscured by the details of the Boshier-Collins cluster analysis and the mapping of Houle's types onto it. A table illustrates an interpretation of cluster analysis on Boshier's Education Participation Scale. (CT)

  18. Sensory over responsivity and obsessive compulsive symptoms: A cluster analysis.

    Science.gov (United States)

    Ben-Sasson, Ayelet; Podoly, Tamar Yonit

    2017-02-01

    Several studies have examined the sensory component in Obsesseive Compulsive Disorder (OCD) and described an OCD subtype which has a unique profile, and that Sensory Phenomena (SP) is a significant component of this subtype. SP has some commonalities with Sensory Over Responsivity (SOR) and might be in part a characteristic of this subtype. Although there are some studies that have examined SOR and its relation to Obsessive Compulsive Symptoms (OCS), literature lacks sufficient data on this interplay. First to further examine the correlations between OCS and SOR, and to explore the correlations between SOR modalities (i.e. smell, touch, etc.) and OCS subscales (i.e. washing, ordering, etc.). Second, to investigate the cluster analysis of SOR and OCS dimensions in adults, that is, to classify the sample using the sensory scores to find whether a sensory OCD subtype can be specified. Our third goal was to explore the psychometric features of a new sensory questionnaire: the Sensory Perception Quotient (SPQ). A sample of non clinical adults (n=350) was recruited via e-mail, social media and social networks. Participants completed questionnaires for measuring SOR, OCS, and anxiety. SOR and OCI-F scores were moderately significantly correlated (n=274), significant correlations between all SOR modalities and OCS subscales were found with no specific higher correlation between one modality to one OCS subscale. Cluster analysis revealed four distinct clusters: (1) No OC and SOR symptoms (NONE; n=100), (2) High OC and SOR symptoms (BOTH; n=28), (3) Moderate OC symptoms (OCS; n=63), (4) Moderate SOR symptoms (SOR; n=83). The BOTH cluster had significantly higher anxiety levels than the other clusters, and shared OC subscales scores with the OCS cluster. The BOTH cluster also reported higher SOR scores across tactile, vision, taste and olfactory modalities. The SPQ was found reliable and suitable to detect SOR, the sample SPQ scores was normally distributed (n=350). SOR is a

  19. Energetic and structural analysis of 102-atom Pd-Pt nanoparticles

    Science.gov (United States)

    Pacheco-Contreras, Rafael; Arteaga-Guerrero, Alvaro; Borbon-Gonzalez, Dora Julia; Posada-Amarillas, Alvaro; Schoen, J. Christian; Johnston, Roy L.

    2009-03-01

    We present an extensive study of the structural and energetic changes of 102-atom PdmPt102-m nanoparticles as a function of composition m, where the interatomic interactions are modeled with the many-body Gupta potential. The minimum energy structures are obtained through a genetic algorithm. The excess energy is calculated, as well as the pair distribution function g(r). The radial distribution of the atoms is computed for each composition; the result indicates a multi-layer segregation for some compositions, with a shell growth sequence as follows: a core with a small number of Pd atoms is followed by an intermediate shell of Pt atoms and the external shell consists of Pd atoms. A region where Pd and Pt atoms are mixed is observed between the outermost and intermediate shells. Furthermore, the pure Pd102 and Pt102 nanoparticles have the same structure, while a variety of different structures are observed for the bimetallic clusters.

  20. Coupled Two-Way Clustering Analysis of Gene Microarray Data

    CERN Document Server

    Getz, G; Domany, E

    2000-01-01

    We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  1. Coupled two-way clustering analysis of gene microarray data

    Science.gov (United States)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

    We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  2. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    Science.gov (United States)

    Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  3. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis.

    Directory of Open Access Journals (Sweden)

    Nan Lin

    Full Text Available Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis.

  4. Toward an Empirical Taxonomy of Suicide Ideation: A Cluster Analysis of the Youth Risk Behavior Survey

    Science.gov (United States)

    Flannery, William Peter; Sneed, Carl D.; Marsh, Penny

    2003-01-01

    In this study we examined adolescent risk behaviors, giving special attention to suicide ideation. Cluster analysis was used to classify adolescents ( N = 2,730) on the Youth Risk Behavior Survey. Six clusters of adolescent risk behavior were identified. Although each risk cluster was distinct, some clusters shared overlapping risk behaviors.…

  5. SPECTROPHOTOMETRIC, ATOMIC ABSORPTION AND CONDUCTOMETRIC ANALYSIS OF TRAMADOL HYDROCHLORIDE

    Directory of Open Access Journals (Sweden)

    Sara M. Anis

    2011-09-01

    Full Text Available Six simple and sensitive spectroscopic and conductometric procedures (A-F were developed for the determination of tramadol hydrochloride. Methods A, B and C are based on the reaction of cobalt (II thiocyanate with tramadol to form a stable ternary complex, which could be measured by spectrophotometric (method A, atomic absorption (method B or conductometric (method C procedures. Methods D and E depend on the reaction of molybdenum thiocyanate with tramadol to form a stable ternary complex, measured by spectrophotometric means (method D or by atomic absorption procedures (method E, while method F depends on the formation of an ion pair complex between the studied drug and bromothymol blue which is extractable into methylene chloride. Tramadol hydrochloride could be assayed in the range of 80-560 and 40-–220 μg ml-1, 1-15 mg ml-1 and 2.5-22.5, 1.25-11.25 and 5-22 μg ml-1 using methods A,B,C,D,E and F, respectively. Various experimental conditions were studied. The results obtained showed good recoveries. The proposed procedures were applied successfully to the analysis of tramadol in its pharmaceutical preparations and the results were favorably comparable with the official method.

  6. Diagnostics of subtropical plants functional state by cluster analysis

    Directory of Open Access Journals (Sweden)

    Oksana Belous

    2016-05-01

    Full Text Available The article presents an application example of statistical methods for data analysis on diagnosis of the adaptive capacity of subtropical plants varieties. We depicted selection indicators and basic physiological parameters that were defined as diagnostic. We used evaluation on a set of parameters of water regime, there are: determination of water deficit of the leaves, determining the fractional composition of water and detection parameters of the concentration of cell sap (CCS (for tea culture flushes. These settings are characterized by high liability and high responsiveness to the effects of many abiotic factors that determined the particular care in the selection of plant material for analysis and consideration of the impact on sustainability. On the basis of the experimental data calculated the coefficients of pair correlation between climatic factors and used physiological indicators. The result was a selection of physiological and biochemical indicators proposed to assess the adaptability and included in the basis of methodical recommendations on diagnostics of the functional state of the studied cultures. Analysis of complex studies involving a large number of indicators is quite difficult, especially does not allow to quickly identify the similarity of new varieties for their adaptive responses to adverse factors, and, therefore, to set general requirements to conditions of cultivation. Use of cluster analysis suggests that in the analysis of only quantitative data; define a set of variables used to assess varieties (and the more sampling, the more accurate the clustering will happen, be sure to ascertain the measure of similarity (or difference between objects. It is shown that the identification of diagnostic features, which are subjected to statistical processing, impact the accuracy of the varieties classification. Selection in result of the mono-clusters analysis (variety tea Kolhida; hazelnut Lombardsky red; variety kiwi Monty

  7. On the use of big-bang method to generate low-energy structures of atomic clusters modeled with pair potentials of different ranges.

    Science.gov (United States)

    Marques, J M C; Pais, A A C C; Abreu, P E

    2012-02-05

    The efficiency of the so-called big-bang method for the optimization of atomic clusters is analysed in detail for Morse pair potentials with different ranges; here, we have used Morse potentials with four different ranges, from long- ρ = 3) to short-ranged ρ = 14) interactions. Specifically, we study the efficacy of the method in discovering low-energy structures, including the putative global minimum, as a function of the potential range and the cluster size. A new global minimum structure for long-ranged ρ = 3) Morse potential at the cluster size of n= 240 is reported. The present results are useful to assess the maximum cluster size for each type of interaction where the global minimum can be discovered with a limited number of big-bang trials.

  8. Monitoring Customer Satisfaction in Service Industry: A Cluster Analysis Approach

    Directory of Open Access Journals (Sweden)

    Matúš Horváth

    2012-10-01

    Full Text Available One of the key performance indicators of quality management system of an organization is customer satisfaction. The process of monitoring customer satisfaction is therefore an important part of the measuring processes of the quality management system. This paper deals with new ways how to analyse and monitor customer satisfaction using the analysis of data containing how the customers use the organisation services and customer leaving rates. The article used cluster analysis in this process for segmentation of customers with the aim to increase the accuracy of the results and on these results based decisions. The aplication example was created as a part of bachelor thesis.

  9. Monitoring Customer Satisfaction in Service Industry: A Cluster Analysis Approach

    Directory of Open Access Journals (Sweden)

    Matúš Horváth

    2012-11-01

    Full Text Available One of the key performance indicators of quality management system of an organization is customer satisfaction. The process of monitoring customer satisfaction is therefore an important part of the measuring processes of the quality management system. This paper deals with new ways how to analyse and monitor customer satisfaction using the analysis of data containing how the customers use the organisation services and customer leaving rates. The article used cluster analysis in this process for segmentation of customers with the aim to increase the accuracy of the results and on these results based decisions. The aplication example was created as a part of bachelor thesis.

  10. Using cluster analysis in measuring social domain of territorial brand

    Directory of Open Access Journals (Sweden)

    Zlata Stepanova

    2009-10-01

    Full Text Available Territorial brand has a social dimension reflected in the social equilibrium and measurable with social effectiveness indicators. The paper offers social effectiveness analysis of territory using investigation object “territorial and social systems (TSS” with their further classification according to social types based on cluster analysis. This method allows the authors to distinct four social types of TSS in Sverdlovsk region in accordance with such characteristics as financial activity, quality of life, social stability and ill-being levels. The results of investigation could be useful for brand policy of territorial authorities.

  11. Cluster analysis for DNA methylation profiles having a detection threshold

    Directory of Open Access Journals (Sweden)

    Siegmund Kimberly D

    2006-07-01

    Full Text Available Abstract Background DNA methylation, a molecular feature used to investigate tumor heterogeneity, can be measured on many genomic regions using the MethyLight technology. Due to the combination of the underlying biology of DNA methylation and the MethyLight technology, the measurements, while being generated on a continuous scale, have a large number of 0 values. This suggests that conventional clustering methodology may not perform well on this data. Results We compare performance of existing methodology (such as k-means with two novel methods that explicitly allow for the preponderance of values at 0. We also consider how the ability to successfully cluster such data depends upon the number of informative genes for which methylation is measured and the correlation structure of the methylation values for those genes. We show that when data is collected for a sufficient number of genes, our models do improve clustering performance compared to methods, such as k-means, that do not explicitly respect the supposed biological realities of the situation. Conclusion The performance of analysis methods depends upon how well the assumptions of those methods reflect the properties of the data being analyzed. Differing technologies will lead to data with differing properties, and should therefore be analyzed differently. Consequently, it is prudent to give thought to what the properties of the data are likely to be, and which analysis method might therefore be likely to best capture those properties.

  12. Coordination-resolved local bond strain and 3p energy entrapment of K atomic clusters and K(1 1 0) skin

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ting; Bo, Maolin; Guo, Yongling [Key Laboratory of Low-Dimensional Materials and Application Technologies (Ministry of Education), Faculty of Materials Science and Engineering, Xiangtan University, Hunan 411105 (China); Hunan Provincial Key Laboratory of Thin Film Materials and Devices, Faculty of Materials Science and Engineering, Xiangtan University, Hunan 411105 (China); Chen, Hefeng [United Superconductive Institution, Shanghai Jiaotong University, Shanghai 200240 (China); Wang, Yan [School of Information and Electronic Engineering, Hunan University of Science and Technology, Hunan 411201 (China); Huang, Yongli, E-mail: huangyongli@xtu.edu.cn [Key Laboratory of Low-Dimensional Materials and Application Technologies (Ministry of Education), Faculty of Materials Science and Engineering, Xiangtan University, Hunan 411105 (China); Hunan Provincial Key Laboratory of Thin Film Materials and Devices, Faculty of Materials Science and Engineering, Xiangtan University, Hunan 411105 (China); Sun, Chang Q., E-mail: ecqsun@ntu.edu.sg [Key Laboratory of Low-Dimensional Materials and Application Technologies (Ministry of Education), Faculty of Materials Science and Engineering, Xiangtan University, Hunan 411105 (China); Hunan Provincial Key Laboratory of Thin Film Materials and Devices, Faculty of Materials Science and Engineering, Xiangtan University, Hunan 411105 (China); School of Information and Electronic Engineering, Hunan University of Science and Technology, Hunan 411201 (China); NOVITAS, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore)

    2015-09-15

    Graphical abstract: - Highlights: • Coordination environment resolves electron binding-energy shift of K{sub 44}, K{sub 46}, K{sub 55} clusters. • Predict the effective coordination number of K nanoclusters when we get the atomic number N. • Atomic under coordination shortens the local bonds and entrapment. • XPS derives core level of an isolated atom and its bulk shift. - Abstract: We have examined the atomic coordination effect on the local bond strain and the 3p core-level shift of K(1 1 0) skin and nanoclusters using a combination of the bond order–length–strength correlation notion, tight-binding approach, density functional theory calculations, and photoelectron spectroscopy measurements. It turns out that: (i) the 3p core-level shifts from 15.595 ± 0.003 eV for an isolated K atom by 2.758 eV to the bulk value of 18.353 eV; (ii) the effective atomic coordination number reduces from the bulk value of 12 to 3.93 for the first layer and to 5.81 for the second layer of K(1 1 0) skin associated with the local lattice strain of 12.76%, a binding energy density 72.67%, and atomic cohesive energy −62.46% for the skin; and (iii) K cluster size reduction lowers the effective atomic coordination number and enhances further the skin electronic attribution. Results have revealed that the 3p core-level shifts of K(1 1 0) and nanoclusters originate from perturbation of the Hamiltonian by under-coordination induced charge densification and quantum entrapment.

  13. Weighing the Giants I: Weak Lensing Masses for 51 Massive Galaxy Clusters - Project Overview, Data Analysis Methods, and Cluster Images

    CERN Document Server

    von der Linden, Anja; Applegate, Douglas E; Kelly, Patrick L; Allen, Steven W; Ebeling, Harald; Burchat, Patricia R; Burke, David L; Donovan, David; Morris, R Glenn; Blandford, Roger; Erben, Thomas; Mantz, Adam

    2012-01-01

    This is the first in a series of papers in which we measure accurate weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known at redshifts 0.15cluster experiments. The primary aim is to improve the absolute mass calibration of cluster observables, currently the dominant systematic uncertainty for cluster count experiments. Key elements of this work are the rigorous quantification of systematic uncertainties, high-quality data reduction and photometric calibration, and the "blind" nature of the analysis to avoid confirmation bias. Our target clusters are drawn from RASS X-ray catalogs, and provide a versatile calibration sample for many aspects of cluster cosmology. We have acquired wide-field, high-quality imaging using the Subaru and CFHT telescopes for all 51 clusters, in at least three bands per cluster. For a subset of 27 clusters, we have data in at least five bands, allowing accurate photo-z estimates of...

  14. Cluster Analysis and Fuzzy Query in Ship Maintenance and Design

    Science.gov (United States)

    Che, Jianhua; He, Qinming; Zhao, Yinggang; Qian, Feng; Chen, Qi

    Cluster analysis and fuzzy query win wide-spread applications in modern intelligent information processing. In allusion to the features of ship maintenance data, a variant of hypergraph-based clustering algorithm, i.e., Correlation Coefficient-based Minimal Spanning Tree(CC-MST), is proposed to analyze the bulky data rooting in ship maintenance process, discovery the unknown rules and help ship maintainers make a decision on various device fault causes. At the same time, revising or renewing an existed design of ship or device maybe necessary to eliminate those device faults. For the sake of offering ship designers some valuable hints, a fuzzy query mechanism is designed to retrieve the useful information from large-scale complicated and reluctant ship technical and testing data. Finally, two experiments based on a real ship device fault statistical dataset validate the flexibility and efficiency of the CC-MST algorithm. A fuzzy query prototype demonstrates the usability of our fuzzy query mechanism.

  15. Analysis and Prediction of Crimes by Clustering and Classification

    Directory of Open Access Journals (Sweden)

    Rasoul Kiani

    2015-08-01

    Full Text Available Crimes will somehow influence organizations and institutions when occurred frequently in a society. Thus, it seems necessary to study reasons, factors and relations between occurrence of different crimes and finding the most appropriate ways to control and avoid more crimes. The main objective of this paper is to classify clustered crimes based on occurrence frequency during different years. Data mining is used extensively in terms of analysis, investigation and discovery of patterns for occurrence of different crimes. We applied a theoretical model based on data mining techniques such as clustering and classification to real crime dataset recorded by police in England and Wales within 1990 to 2011. We assigned weights to the features in order to improve the quality of the model and remove low value of them. The Genetic Algorithm (GA is used for optimizing of Outlier Detection operator parameters using RapidMiner tool.

  16. Analysis of intraocular lens surface adhesiveness by atomic force microscopy.

    Science.gov (United States)

    Lombardo, Marco; Carbone, Giovanni; Lombardo, Giuseppe; De Santo, Maria P; Barberi, Riccardo

    2009-07-01

    To analyze intraocular lens (IOL) optic surface adhesiveness using atomic force microscopy (AFM). LiCryL Laboratory, University of Calabria, Rende, Italy. The surface adhesive properties of poly(methyl methacrylate) (PMMA), silicone, hydrophilic acrylic, and hydrophobic acrylic IOLs were evaluated by AFM. Analysis was performed at room temperature (21 degrees C) in a liquid environment using the force-versus-distance mode of a commercial instrument (NanoScope III). Measurements were acquired with rectangular silicon cantilevers of a nominal elastic constant of 10 Newton/m. The nominal value of the tip's radius of curvature was 1 mum, and the scanning speed during the acquisitions ranged from 10 to 400 nm/s. The adhesion force measurements showed different characteristics for the various types of IOLs (Pdevelopment and the interface interactions between the IOL and capsule, the results in this study may bolster the theory of manufacturing more-adhesive materials to prevent PCO.

  17. Analysis of breast cancer progression using principal component analysis and clustering

    Indian Academy of Sciences (India)

    G Alexe; G S Dalgin; S Ganesan; C DeLisi; G Bhanot

    2007-08-01

    We develop a new technique to analyse microarray data which uses a combination of principal components analysis and consensus ensemble -clustering to find robust clusters and gene markers in the data. We apply our method to a public microarray breast cancer dataset which has expression levels of genes in normal samples as well as in three pathological stages of disease; namely, atypical ductal hyperplasia or ADH, ductal carcinoma in situ or DCIS and invasive ductal carcinoma or IDC. Our method averages over clustering techniques and data perturbation to find stable, robust clusters and gene markers. We identify the clusters and their pathways with distinct subtypes of breast cancer (Luminal, Basal and Her2+). We confirm that the cancer phenotype develops early (in early hyperplasia or ADH stage) and find from our analysis that each subtype progresses from ADH to DCIS to IDC along its own specific pathway, as if each was a distinct disease.

  18. Energetics and kinetics of Cu atoms and clusters on the Si(111)-7 × 7 surface: first-principles calculations.

    Science.gov (United States)

    Ren, Xiao-Yan; Niu, Chun-Yao; Chen, Wei-Guang; Tang, Ming-Sheng; Cho, Jun-Hyung

    2016-07-21

    Exploring the properties of noble metal atoms and nano- or subnano-clusters on the semiconductor surface is of great importance in many surface catalytic reactions, self-assembly processes, crystal growth, and thin film epitaxy. Here, the energetics and kinetic properties of a single Cu atom and previously reported Cu magic clusters on the Si(111)-(7 × 7) surface are re-examined by the state-of-the-art first-principles calculations based on density functional theory. First of all, the diffusion path and high diffusion rate of a Cu atom on the Si(111)-(7 × 7) surface are identified by mapping out the total potential energy surface of the Cu atom as a function of its positions on the surface, supporting previous experimental hypothesis that the apparent triangular light spots observed by scanning tunneling microscopy (STM) are resulted from a single Cu atom frequently hopping among adjacent adsorption sites. Furthermore, our findings confirm that in the low coverage of 0.15 monolayer (ML) the previously proposed hexagonal ring-like Cu6 cluster configuration assigned to the STM pattern is considerably unstable. Importantly, the most stable Cu6/Si(111) complex also possesses a distinct simulated STM pattern with the experimentally observed ones. Instead, an energetically preferred solid-centered Cu7 structure exhibits a reasonable agreement between the simulated STM patterns and the experimental images. Therefore, the present findings convincingly rule out the tentative six-atom model and provide new insights into the understanding of the well-defined Cu nanocluster arrays on the Si(111)-(7 × 7) surface.

  19. The clustering of galaxies as a function of their photometrically-estimated atomic gas content

    CERN Document Server

    Li, Cheng; Fu, Jian; Wang, Jing; Catinella, Barbara; Fabello, Silvia; Schiminovich, David; Zhang, Wei

    2012-01-01

    We introduce a new photometric estimator of the HI mass fraction (M_HI/M_*) in local galaxies, which is a linear combination of four parameters: stellar mass, stellar surface mass density, NUV-r colour, and g-i colour gradient. It is calibrated using samples of nearby galaxies (0.025analysis by studying the bias of HI-poor or HI-rich galaxies with respect to galaxie...

  20. Voronoi analysis of the short-range atomic structure in iron and iron-carbon melts

    Science.gov (United States)

    Sobolev, Andrey; Mirzoev, Alexander

    2015-08-01

    In this work, we simulated the atomic structure of liquid iron and iron-carbon alloys by means of ab initio molecular dynamics. Voronoi analysis was used to highlight changes in the close environments of Fe atoms as carbon concentration in the melt increases. We have found, that even high concentrations of carbon do not affect short-range atomic order of iron atoms — it remains effectively the same as in pure iron melts.

  1. Structural features of small benzene clusters (C6H6)n (n ≤ 30) as investigated with the all-atom OPLS potential.

    Science.gov (United States)

    Takeuchi, Hiroshi

    2012-10-18

    The structures of the simplest aromatic clusters, benzene clusters (C(6)H(6))(n), are not well elucidated. In the present study, benzene clusters (C(6)H(6))(n) (n ≤ 30) were investigated with the all-atom optimized parameters for liquid simulation (OPLS) potential. The global minima and low-lying minima of the benzene clusters were searched with the heuristic method combined with geometrical perturbations. The structural features and growth sequence of the clusters were examined by carrying out local structure analyses and structural similarity evaluation with rotational constants. Because of the anisotropic interaction between the benzene molecules, the local structures consisting of 13 molecules are considerably deviated from regular icosahedron, and the geometries of some of the clusters are inconsistent with the shapes constructed by the interior molecules. The distribution of the angle between the lines normal to two neighboring benzene rings is anisotropic in the clusters, whereas that in the liquid benzene is nearly isotropic. The geometries and energies of the low-lying configurations and the saddle points between them suggest that most of the configurations previously detected in supersonic expansions take different orientations for one to four neighboring molecules.

  2. Analysis of forest fires spatial clustering using local fractal measure

    Science.gov (United States)

    Kanevski, Mikhail; Rochat, Mikael; Timonin, Vadim

    2013-04-01

    The research deals with an application of local fractal measure - local sandbox counting or mass counting, for the characterization of patterns of spatial clustering. The main application concerns the simulated (random patterns within validity domain in forest regions) and real data (forest fires in Ticino, Switzerland) case studies. The global patterns of spatial clustering of forest fires were extensively studied using different topological (nearest-neighbours, Voronoi polygons), statistical (Ripley's k-function, Morisita diagram) and fractal/multifractal measures (box-counting, sandbox counting, lacunarity) (Kanevski, 2008). Generalizations of these measures to functional ones can reveal the structure of the phenomena, e.g. burned areas. All these measures are valuable and complementary tools to study spatial clustering. Moreover, application of the validity domain (complex domain where phenomena is studied) concept helps in understanding and interpretation of the results. In the present paper a sandbox counting method was applied locally, i.e. each point of ignition was considered as a centre of events counting with an increasing search radius. Then, the local relationships between the radius and the number of ignition points within the given radius were examined. Finally, the results are mapped using an interpolation algorithm for the visualization and analytical purposes. Both 2d (X,Y) and 3d (X,Y,Z) cases were studied and compared. Local "fractal" study gives an interesting spatially distributed picture of clustering. The real data case study was compared with a reference homogeneous pattern - complete spatial randomness. The difference between two patterns clearly indicates the regions with important spatial clustering. An extension to the local functional measure was applied taking into account the surface of burned area, i.e. by analysing only data with the fires above some threshold of burned area. Such analysis is similar to marked point processes and

  3. [The hierarchical clustering analysis of hyperspectral image based on probabilistic latent semantic analysis].

    Science.gov (United States)

    Yi, Wen-Bin; Shen, Li; Qi, Yin-Feng; Tang, Hong

    2011-09-01

    The paper introduces the Probabilistic Latent Semantic Analysis (PLSA) to the image clustering and an effective image clustering algorithm using the semantic information from PLSA is proposed which is used for hyperspectral images. Firstly, the ISODATA algorithm is used to obtain the initial clustering result of hyperspectral image and the clusters of the initial clustering result are considered as the visual words of the PLSA. Secondly, the object-oriented image segmentation algorithm is used to partition the hyperspectral image and segments with relatively pure pixels are regarded as documents in PLSA. Thirdly, a variety of identification methods which can estimate the best number of cluster centers is combined to get the number of latent semantic topics. Then the conditional distributions of visual words in topics and the mixtures of topics in different documents are estimated by using PLSA. Finally, the conditional probabilistic of latent semantic topics are distinguished using statistical pattern recognition method, the topic type for each visual in each document will be given and the clustering result of hyperspectral image are then achieved. Experimental results show the clusters of the proposed algorithm are better than K-MEANS and ISODATA in terms of object-oriented property and the clustering result is closer to the distribution of real spatial distribution of surface.

  4. Covariance analysis of differential drag-based satellite cluster flight

    Science.gov (United States)

    Ben-Yaacov, Ohad; Ivantsov, Anatoly; Gurfil, Pini

    2016-06-01

    One possibility for satellite cluster flight is to control relative distances using differential drag. The idea is to increase or decrease the drag acceleration on each satellite by changing its attitude, and use the resulting small differential acceleration as a controller. The most significant advantage of the differential drag concept is that it enables cluster flight without consuming fuel. However, any drag-based control algorithm must cope with significant aerodynamical and mechanical uncertainties. The goal of the current paper is to develop a method for examination of the differential drag-based cluster flight performance in the presence of noise and uncertainties. In particular, the differential drag control law is examined under measurement noise, drag uncertainties, and initial condition-related uncertainties. The method used for uncertainty quantification is the Linear Covariance Analysis, which enables us to propagate the augmented state and filter covariance without propagating the state itself. Validation using a Monte-Carlo simulation is provided. The results show that all uncertainties have relatively small effect on the inter-satellite distance, even in the long term, which validates the robustness of the used differential drag controller.

  5. Clustered Numerical Data Analysis Using Markov Lie Monoid Based Networks

    Science.gov (United States)

    Johnson, Joseph

    2016-03-01

    We have designed and build an optimal numerical standardization algorithm that links numerical values with their associated units, error level, and defining metadata thus supporting automated data exchange and new levels of artificial intelligence (AI). The software manages all dimensional and error analysis and computational tracing. Tables of entities verses properties of these generalized numbers (called ``metanumbers'') support a transformation of each table into a network among the entities and another network among their properties where the network connection matrix is based upon a proximity metric between the two items. We previously proved that every network is isomorphic to the Lie algebra that generates continuous Markov transformations. We have also shown that the eigenvectors of these Markov matrices provide an agnostic clustering of the underlying patterns. We will present this methodology and show how our new work on conversion of scientific numerical data through this process can reveal underlying information clusters ordered by the eigenvalues. We will also show how the linking of clusters from different tables can be used to form a ``supernet'' of all numerical information supporting new initiatives in AI.

  6. Cyber Profiling Using Log Analysis And K-Means Clustering

    Directory of Open Access Journals (Sweden)

    Muhammad Zulfadhilah

    2016-07-01

    Full Text Available The Activities of Internet users are increasing from year to year and has had an impact on the behavior of the users themselves. Assessment of user behavior is often only based on interaction across the Internet without knowing any others activities. The log activity can be used as another way to study the behavior of the user. The Log Internet activity is one of the types of big data so that the use of data mining with K-Means technique can be used as a solution for the analysis of user behavior. This study has been carried out the process of clustering using K-Means algorithm is divided into three clusters, namely high, medium, and low. The results of the higher education institution show that each of these clusters produces websites that are frequented by the sequence: website search engine, social media, news, and information. This study also showed that the cyber profiling had been done strongly influenced by environmental factors and daily activities.

  7. Dynamical analysis of galaxy cluster merger Abell 2146

    CERN Document Server

    White, J A; King, L J; Lee, B E; Russell, H R; Baum, S A; Clowe, D I; Coleman, J E; Donahue, M; Edge, A C; Fabian, A C; Johnstone, R M; McNamara, B R; ODea, C P; Sanders, J S

    2015-01-01

    We present a dynamical analysis of the merging galaxy cluster system Abell 2146 using spectroscopy obtained with the Gemini Multi-Object Spectrograph on the Gemini North telescope. As revealed by the Chandra X-ray Observatory, the system is undergoing a major merger and has a gas structure indicative of a recent first core passage. The system presents two large shock fronts, making it unique amongst these rare systems. The hot gas structure indicates that the merger axis must be close to the plane of the sky and that the two merging clusters are relatively close in mass, from the observation of two shock fronts. Using 63 spectroscopically determined cluster members, we apply various statistical tests to establish the presence of two distinct massive structures. With the caveat that the system has recently undergone a major merger, the virial mass estimate is M_vir = 8.5 +4.3 -4.7 x 10 ^14 M_sol for the whole system, consistent with the mass determination in a previous study using the Sunyaev-Zeldovich signal....

  8. Analysis of polarizability measurements made with atom interferometry

    CERN Document Server

    Gregoire, Maxwell D; Trubko, Raisa; Cronin, Alexander D

    2016-01-01

    We present revised measurements of the static electric dipole polarizabilities of K, Rb, and Cs based on atom interferometer experiments presented in [Phys. Rev. A 2015, 92, 052513] but now re-analyzed with new calibrations for the magnitude and geometry of the applied electric field gradient. The resulting polarizability values did not change, but the uncertainties were significantly reduced. Then we interpret several measurements of alkali metal atomic polarizabilities in terms of atomic oscillator strengths $f_{ik}$, Einstein coefficients $A_{ik}$, state lifetimes $\\tau_{k}$, transition dipole matrix elements $D_{ik}$, line strengths $S_{ik}$, and van der Waals $C_6$ coefficients. Finally, we combine atom interferometer measurements of polarizabilities with independent measurements of lifetimes and $C_6$ values in order to quantify the residual contribution to polarizability due to all atomic transitions other than the principal $ns$-$np_J$ transitions for alkali metal atoms.

  9. Analysis of Polarizability Measurements Made with Atom Interferometry

    Directory of Open Access Journals (Sweden)

    Maxwell D. Gregoire

    2016-07-01

    Full Text Available We present revised measurements of the static electric dipole polarizabilities of K, Rb, and Cs based on atom interferometer experiments presented in [Phys. Rev. A 2015, 92, 052513] but now re-analyzed with new calibrations for the magnitude and geometry of the applied electric field gradient. The resulting polarizability values did not change, but the uncertainties were significantly reduced. Then, we interpret several measurements of alkali metal atomic polarizabilities in terms of atomic oscillator strengths fik, Einstein coefficients Aik, state lifetimes τk, transition dipole matrix elements Dik, line strengths Sik, and van der Waals C6 coefficients. Finally, we combine atom interferometer measurements of polarizabilities with independent measurements of lifetimes and C6 values in order to quantify the residual contribution to polarizability due to all atomic transitions other than the principal ns-npJ transitions for alkali metal atoms.

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

    CERN Document Server

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

    2003-01-01

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

  11. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel-time se...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing...

  12. A cluster analysis on road traffic accidents using genetic algorithms

    Science.gov (United States)

    Saharan, Sabariah; Baragona, Roberto

    2017-04-01

    The analysis of traffic road accidents is increasingly important because of the accidents cost and public road safety. The availability or large data sets makes the study of factors that affect the frequency and severity accidents are viable. However, the data are often highly unbalanced and overlapped. We deal with the data set of the road traffic accidents recorded in Christchurch, New Zealand, from 2000-2009 with a total of 26440 accidents. The data is in a binary set and there are 50 factors road traffic accidents with four level of severity. We used genetic algorithm for the analysis because we are in the presence of a large unbalanced data set and standard clustering like k-means algorithm may not be suitable for the task. The genetic algorithm based on clustering for unknown K, (GCUK) has been used to identify the factors associated with accidents of different levels of severity. The results provided us with an interesting insight into the relationship between factors and accidents severity level and suggest that the two main factors that contributes to fatal accidents are "Speed greater than 60 km h" and "Did not see other people until it was too late". A comparison with the k-means algorithm and the independent component analysis is performed to validate the results.

  13. Analysis and application of the scale effect of flood discharge atomization model

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The phenomenon of discharge atomization occurs as hydraulic structures discharging,which influences the safety of power station,electrical equipment and produces environmental pollution.A series of physical model tests and feedback analysis are adapted to preliminarily study the scale effect of discharge atomization model by use of the field observation data of discharge atomization.The effect of Re and We numbers of flow on the atomization intensity is analyzed.A conversion relationship of atomization intensity between prototype and model results and the similarity criteria of the atomization range are developed. The conclusion is that the surface tension of discharge atomization model could be ignored when the Weber number is larger than 500.Some case studies are given by use of the similitude criteria of the atomization model.

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

    Directory of Open Access Journals (Sweden)

    Xuan HUANG

    2014-02-01

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

  15. Atomic Diffusion in Cu/Si (111) and Cu/SiO2/Si (111) Systems by Neutral Cluster Beam Deposition

    Institute of Scientific and Technical Information of China (English)

    CAO Bo; LI Gong-Ping; CHEN Xi-Meng; CHO Seong-Jin; KIM Hee

    2008-01-01

    @@ The Cu films are deposited on two kinds of p-type Si (111) substrates by ionized cluster beam (ICB) technique.The interface reaction and atomic diffusion of Cu/Si (111) and Cu/SiO2/Si (111) systems are studied at different annealing temperatures by x-ray diffraction (XRD) and Rutherford backscattering spectrometry (RBS). Some significant results are obtained: For the Cu/Si (111) samples prepared by neutral clusters, the interdiffusion of Cu and Si atoms occurs when annealed at 230℃. The diffusion coefficients of the samples annealed at 230℃and 500℃ are 8.5 × 10-15 cm2.s-1 and 3.0 × 10-14 cm2.s-1, respectively. The formation of the copper-silicide phase is observed by XRD, and its intensity becomes stronger with the increase of annealing temperature. For the Cu/SiO2/Si (111) samples prepared by neutral clusters, the interdiffusion of Cu and Si atoms occurs and copper silicides are formed when annealed at 450℃. The diffusion coefficients of Cu in Si are calculated to be 6.0 × 10-16 cm2.s-1 at 450℃, due to the fact that the existence of the SiO2 layer suppresses the interdiffusion of Cu and Si.

  16. Spectroscopic studies of OCS-doped 4He clusters with 9-72 helium atoms: observation of broad oscillations in the rotational moment of inertia.

    Science.gov (United States)

    McKellar, A R W; Xu, Yunjie; Jäger, Wolfgang

    2007-08-09

    High-resolution spectra of HeN-OCS clusters with N up to 39 in the microwave region and up to 72 in the infrared region were observed with apparatus-limited line widths of about 15 kHz and 0.001 cm(-1), respectively. The cold (approximately 0.2 K) clusters were produced in pulsed supersonic jet expansions of very dilute OCS + He mixtures and probed using a microwave Fourier transform spectrometer or a tunable infrared diode laser spectrometer. Consistent analyses of the microwave and infrared data yield band origins for the carbonyl stretching vibration, together with rotational parameters for the ground and excited vibrational states. The rotational constant, B, passes through a minimum at N = 9 and then rises as the He atoms uncouple from the OCS rotational motion as a result of superfluid effects. There are broad unexpected oscillations in B, with maxima at N = 24 and 47 and minima at N = 36 and 62. The change in B upon vibrational excitation, which is negative for the OCS molecule, converges to positive values for N > 15. These results help to bridge the gap between individual molecules and bulk matter with atom-by-atom resolution over a significant range of cluster sizes.

  17. Recombination radius of a Frenkel pair and capture radius of a self-interstitial atom by vacancy clusters in bcc Fe.

    Science.gov (United States)

    Nakashima, Kenichi; Stoller, Roger E; Xu, Haixuan

    2015-08-26

    The recombination radius of a Frenkel pair is a fundamental parameter for the object kinetic Monte Carlo (OKMC) and mean field rate theory (RT) methods that are used to investigate irradiation damage accumulation in irradiated materials. The recombination radius in bcc Fe has been studied both experimentally and numerically, however there is no general consensus about its value. The detailed atomistic processes of recombination also remain uncertain. Values from 1.0a0 to 3.3a0 have been employed as a recombination radius in previous studies using OKMC and RT. The recombination process of a Frenkel pair is investigated at the atomic level using the self-evolved atomistic kinetic Monte Carlo (SEAKMC) method in this paper. SEAKMC calculations reveal that a self-interstitial atom recombines with a vacancy in a spontaneous reaction from several nearby sites following characteristic pathways. The recombination radius of a Frenkel pair is estimated to be 2.26a0 by taking the average of the recombination distances from 80 simulation cases. In addition, we apply these procedures to the capture radius of a self-interstitial atom by a vacancy cluster. The capture radius is found to gradually increase with the size of the vacancy cluster. The fitting curve for the capture radius is obtained as a function of the number of vacancies in the cluster.

  18. The cosmological analysis of X-ray cluster surveys; III. Bypassing cluster mass measurements

    CERN Document Server

    Pierre, M; Faccioli, L; Clerc, N; Gastaud, R; Koulouridis, E; Pacaud, F

    2016-01-01

    Despite strong theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties impinging on cluster mass estimates. Our aim is to develop a fully self-consistent cosmological approach of X-ray cluster surveys, exclusively based on observable quantities, rather than masses. This procedure is justified given the possibility to directly derive the cluster properties via ab initio modelling, either analytically or by using hydrodynamical simulations. In this third paper, we evaluate the method on cluster toy-catalogues. We model the population of detected clusters in the count-rate -- hardness-ratio -- angular size -- redshift space and compare the corresponding 4-dimensional diagram with theoretical predictions. The best cosmology+physics parameter configuration is determined using a simple minimisation procedure; errors on the parameters are derived by scanning the likelihood hyper-surfaces with a wide range of starting values. The metho...

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

    Science.gov (United States)

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

    2014-07-01

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

  20. Si-rich W silicide films composed of W-atom-encapsulated Si clusters deposited using gas-phase reactions of WF6 with SiH4.

    Science.gov (United States)

    Okada, Naoya; Uchida, Noriyuki; Kanayama, Toshihiko

    2016-02-28

    We formed Si-rich W silicide films composed of Sin clusters, each of which encapsulates a W atom (WSi(n) clusters with 8 composed of WSi(n) clusters with a uniform n, which was determined by the gas temperature. The formed films were amorphous semiconductors with an optical gap of ∼0.8-1.5 eV and an electrical mobility gap of ∼0.05-0.12 eV, both of which increased as n increased from 8 to 12. We attribute this dependence to the reduction of randomness in the Si network as n increased, which decreased the densities of band tail states and localized states.

  1. Reliability analysis of cluster-based ad-hoc networks

    Energy Technology Data Exchange (ETDEWEB)

    Cook, Jason L. [Quality Engineering and System Assurance, Armament Research Development Engineering Center, Picatinny Arsenal, NJ (United States); Ramirez-Marquez, Jose Emmanuel [School of Systems and Enterprises, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ 07030 (United States)], E-mail: Jose.Ramirez-Marquez@stevens.edu

    2008-10-15

    The mobile ad-hoc wireless network (MAWN) is a new and emerging network scheme that is being employed in a variety of applications. The MAWN varies from traditional networks because it is a self-forming and dynamic network. The MAWN is free of infrastructure and, as such, only the mobile nodes comprise the network. Pairs of nodes communicate either directly or through other nodes. To do so, each node acts, in turn, as a source, destination, and relay of messages. The virtue of a MAWN is the flexibility this provides; however, the challenge for reliability analyses is also brought about by this unique feature. The variability and volatility of the MAWN configuration makes typical reliability methods (e.g. reliability block diagram) inappropriate because no single structure or configuration represents all manifestations of a MAWN. For this reason, new methods are being developed to analyze the reliability of this new networking technology. New published methods adapt to this feature by treating the configuration probabilistically or by inclusion of embedded mobility models. This paper joins both methods together and expands upon these works by modifying the problem formulation to address the reliability analysis of a cluster-based MAWN. The cluster-based MAWN is deployed in applications with constraints on networking resources such as bandwidth and energy. This paper presents the problem's formulation, a discussion of applicable reliability metrics for the MAWN, and illustration of a Monte Carlo simulation method through the analysis of several example networks.

  2. Time series clustering analysis of health-promoting behavior

    Science.gov (United States)

    Yang, Chi-Ta; Hung, Yu-Shiang; Deng, Guang-Feng

    2013-10-01

    Health promotion must be emphasized to achieve the World Health Organization goal of health for all. Since the global population is aging rapidly, ComCare elder health-promoting service was developed by the Taiwan Institute for Information Industry in 2011. Based on the Pender health promotion model, ComCare service offers five categories of health-promoting functions to address the everyday needs of seniors: nutrition management, social support, exercise management, health responsibility, stress management. To assess the overall ComCare service and to improve understanding of the health-promoting behavior of elders, this study analyzed health-promoting behavioral data automatically collected by the ComCare monitoring system. In the 30638 session records collected for 249 elders from January, 2012 to March, 2013, behavior patterns were identified by fuzzy c-mean time series clustering algorithm combined with autocorrelation-based representation schemes. The analysis showed that time series data for elder health-promoting behavior can be classified into four different clusters. Each type reveals different health-promoting needs, frequencies, function numbers and behaviors. The data analysis result can assist policymakers, health-care providers, and experts in medicine, public health, nursing and psychology and has been provided to Taiwan National Health Insurance Administration to assess the elder health-promoting behavior.

  3. Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

    Science.gov (United States)

    Youroukova, Vania M; Dimitrova, Denitsa G; Valerieva, Anna D; Lesichkova, Spaska S; Velikova, Tsvetelina V; Ivanova-Todorova, Ekaterina I; Tumangelova-Yuzeir, Kalina D

    2017-06-01

    Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.

  4. IPC two-color analysis of x ray galaxy clusters

    Science.gov (United States)

    White, Raymond E., III

    1990-01-01

    The mass distributions were determined of several clusters of galaxies by using X ray surface brightness data from the Einstein Observatory Imaging Proportional Counter (IPC). Determining cluster mass distributions is important for constraining the nature of the dark matter which dominates the mass of galaxies, galaxy clusters, and the Universe. Galaxy clusters are permeated with hot gas in hydrostatic equilibrium with the gravitational potentials of the clusters. Cluster mass distributions can be determined from x ray observations of cluster gas by using the equation of hydrostatic equilibrium and knowledge of the density and temperature structure of the gas. The x ray surface brightness at some distance from the cluster is the result of the volume x ray emissivity being integrated along the line of sight in the cluster.

  5. Atomic polarizabilities

    Energy Technology Data Exchange (ETDEWEB)

    Safronova, M. S. [Department of Physics and Astronomy, University of Delaware, Newark, DE 19716 (United States); Mitroy, J. [School of Engineering, Charles Darwin University, Darwin NT 0909 (Australia); Clark, Charles W. [Joint Quantum Institute, National Institute of Standards and Technology and the University of Maryland, Gaithersburg, Maryland 20899-8410 (United States); Kozlov, M. G. [Petersburg Nuclear Physics Institute, Gatchina 188300 (Russian Federation)

    2015-01-22

    The atomic dipole polarizability governs the first-order response of an atom to an applied electric field. Atomic polarization phenomena impinge upon a number of areas and processes in physics and have been the subject of considerable interest and heightened importance in recent years. In this paper, we will summarize some of the recent applications of atomic polarizability studies. A summary of results for polarizabilities of noble gases, monovalent, and divalent atoms is given. The development of the CI+all-order method that combines configuration interaction and linearized coupled-cluster approaches is discussed.

  6. Analysis of the physical atomic forces between noble gas atoms, alkali ions and halogen ions

    Science.gov (United States)

    Wilson, J. W.; Heinbockel, J. H.; Outlaw, R. A.

    1986-01-01

    The physical forces between atoms and molecules are important in a number of processes of practical importance, including line broadening in radiative processes, gas and crystal properties, adhesion, and thin films. The components of the physical forces between noble gas atoms, alkali ions, and halogen ions are analyzed and a data base for the dispersion forces is developed from the literature based on evaluations with the harmonic oscillator dispersion model for higher order coefficients. The Zener model of the repulsive core is used in the context of the recent asymptotic wave functions of Handler and Smith; and an effective ionization potential within the Handler and Smith wave functions is defined to analyze the two body potential data of Waldman and Gordon, the alkali-halide molecular data, and the noble gas crystal and salt crystal data. A satisfactory global fit to this molecular and crystal data is then reproduced by the model to within several percent. Surface potentials are evaluated for noble gas atoms on noble gas and salt crystal surfaces with surface tension neglected. Within this context, the noble gas surface potentials on noble gas and salt crystals are considered to be accurate to within several percent.

  7. CLUSTER ANALYSIS OF NATURAL DISASTER LOSSES IN POLISH AGRICULTURE

    Directory of Open Access Journals (Sweden)

    Grzegorz STRUPCZEWSKI

    2015-04-01

    Full Text Available Agricultural production risk is of special nature due to a great number of hazards, relative weakness of production entities on the market and high ambiguity which is greater than in industrial production. Natural disasters occurring very frequently, at simultaneous low percentage of insured farmers, cause damage of such sizes that force the state to organise current financial aid (for instance in the form of preferential natural disaster loans. This aid is usually not sufficient. On the other hand, regional diversity of the risk level does not positively affect the development of insurance. From the perspective of insurance companies and policymakers it becomes highly important to investigate the spatial structure of losses in agriculture caused by natural disasters. The purpose of the research is to classify the 16 Polish voivodeships into clusters in order to show differences between them according to the criterion of level of damage in agricultural farms caused by natural disasters. On the basis of the cluster analysis it was demonstrated that 11 voivodeships form quite a homogeneous group in terms of size of damage in agriculture (the value of damage in cultivations and the acreage of destroyed cultivations are two most important factors determining affiliation to the cluster, however, the profile of loss occurring in other five voivodeships has a very individual course and requires separate handling in the actuarial sense. It was also proved that high value of losses in agriculture in the absolute sense in given voivodeships do not have to mean high vulnerability of agricultural farms from these voivodeships to natural risks.

  8. Analysis of size correlations for microdroplets produced by ultrasonic atomization.

    Science.gov (United States)

    Dalmoro, Annalisa; Barba, Anna Angela; d'Amore, Matteo

    2013-01-01

    Microencapsulation techniques are widely applied in the field of pharmaceutical production to control drugs release in time and in physiological environments. Ultrasonic-assisted atomization is a new technique to produce microencapsulated systems by a mechanical approach. Interest in this technique is due to the advantages evidenceable (low level of mechanical stress in materials, reduced energy request, reduced apparatuses size) when comparing it to more conventional techniques. In this paper, the groundwork of atomization is introduced, the role of relevant parameters in ultrasonic atomization mechanism is discussed, and correlations to predict droplets size starting from process parameters and material properties are presented and tested.

  9. Analysis of Size Correlations for Microdroplets Produced by Ultrasonic Atomization

    Directory of Open Access Journals (Sweden)

    Annalisa Dalmoro

    2013-01-01

    Full Text Available Microencapsulation techniques are widely applied in the field of pharmaceutical production to control drugs release in time and in physiological environments. Ultrasonic-assisted atomization is a new technique to produce microencapsulated systems by a mechanical approach. Interest in this technique is due to the advantages evidenceable (low level of mechanical stress in materials, reduced energy request, reduced apparatuses size when comparing it to more conventional techniques. In this paper, the groundwork of atomization is introduced, the role of relevant parameters in ultrasonic atomization mechanism is discussed, and correlations to predict droplets size starting from process parameters and material properties are presented and tested.

  10. [Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses].

    Science.gov (United States)

    Ning, P; Guo, Y F; Sun, T Y; Zhang, H S; Chai, D; Li, X M

    2016-09-01

    To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis. A population sample of adult patients in Donghuamen community, Dongcheng district and Qinghe community, Haidian district, Beijing from April 2012 to January 2015, who had wheeze within the last 12 months, underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, total serum IgE levels, blood eosinophil level and a peak flow diary. Nine variables were chosen as evaluating parameters, including pre-salbutamol forced expired volume in one second(FEV1)/forced vital capacity(FVC) ratio, pre-salbutamol FEV1, percentage of post-salbutamol change in FEV1, residual capacity, diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level, peak expiratory flow(PEF) variability, serum IgE level, cumulative tobacco cigarette consumption (pack-years) and respiratory symptoms (cough and expectoration). Subjects' different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified. (1) Four clusters were identified by hierarchical cluster analysis. Cluster 1 was chronic bronchitis in smokers with normal pulmonary function. Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease (COPD) patients with mild airflow limitation. Cluster 3 included COPD patients with heavy smoking, poor quality of life and severe airflow limitation. Cluster 4 recognized atopic patients with mild airflow limitation, elevated serum IgE and clinical features of asthma. Significant differences were revealed regarding pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, maximal mid-expiratory flow curve(MMEF)% pred, carbon monoxide diffusing capacity per liter of alveolar(DLCO)/(VA)% pred, residual volume(RV)% pred, total serum IgE level, smoking history (pack-years), St.George's respiratory questionnaire

  11. Selections of data preprocessing methods and similarity metrics for gene cluster analysis

    Institute of Scientific and Technical Information of China (English)

    YANG Chunmei; WAN Baikun; GAO Xiaofeng

    2006-01-01

    Clustering is one of the major exploratory techniques for gene expression data analysis. Only with suitable similarity metrics and when datasets are properly preprocessed, can results of high quality be obtained in cluster analysis. In this study, gene expression datasets with external evaluation criteria were preprocessed as normalization by line, normalization by column or logarithm transformation by base-2, and were subsequently clustered by hierarchical clustering, k-means clustering and self-organizing maps (SOMs) with Pearson correlation coefficient or Euclidean distance as similarity metric. Finally, the quality of clusters was evaluated by adjusted Rand index. The results illustrate that k-means clustering and SOMs have distinct advantages over hierarchical clustering in gene clustering, and SOMs are a bit better than k-means when randomly initialized. It also shows that hierarchical clustering prefers Pearson correlation coefficient as similarity metric and dataset normalized by line. Meanwhile, k-means clustering and SOMs can produce better clusters with Euclidean distance and logarithm transformed datasets. These results will afford valuable reference to the implementation of gene expression cluster analysis.

  12. Principal Component Analysis and Cluster Analysis in Profile of Electrical System

    Science.gov (United States)

    Iswan; Garniwa, I.

    2017-03-01

    This paper propose to present approach for profile of electrical system, presented approach is combination algorithm, namely principal component analysis (PCA) and cluster analysis. Based on relevant data of gross domestic regional product and electric power and energy use. This profile is set up to show the condition of electrical system of the region, that will be used as a policy in the electrical system of spatial development in the future. This paper consider 24 region in South Sulawesi province as profile center points and use principal component analysis (PCA) to asses the regional profile for development. Cluster analysis is used to group these region into few cluster according to the new variable be produced PCA. The general planning of electrical system of South Sulawesi province can provide support for policy making of electrical system development. The future research can be added several variable into existing variable.

  13. CHOOSING A HEALTH INSTITUTION WITH MULTIPLE CORRESPONDENCE ANALYSIS AND CLUSTER ANALYSIS IN A POPULATION BASED STUDY

    Directory of Open Access Journals (Sweden)

    ASLI SUNER

    2013-06-01

    Full Text Available Multiple correspondence analysis is a method making easy to interpret the categorical variables given in contingency tables, showing the similarities, associations as well as divergences among these variables via graphics on a lower dimensional space. Clustering methods are helped to classify the grouped data according to their similarities and to get useful summarized data from them. In this study, interpretations of multiple correspondence analysis are supported by cluster analysis; factors affecting referred health institute such as age, disease group and health insurance are examined and it is aimed to compare results of the methods.

  14. Analysis of the Aberration in Directly-writing Atom Lithography

    Institute of Scientific and Technical Information of China (English)

    LI Chuanwen; CAI Weiquan; WANG Yuzhu

    2000-01-01

    After deriving the approximation solution which describes the motion of neutral atoms in an optical standing wave field with large detuning, the spherical aberration and the chromatic aberration are analyzed and possible methods to reduce these aberrations are discussed.

  15. Maximum-entropy clustering algorithm and its global convergence analysis

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Zhihua

    2001-01-01

    [1]Bezdek, J. C., Pattern Recognition with Fuzzy Objective Function Algorithm. New York: Plenum, 1981.[2]Krishnapuram, R., Keller, J., A possibilistic approach to clustering, IEEE Trans. on Fuzzy Systems, 1993, 1(2): 98.[3]Yair, E., Zeger, K., Gersho, A., Competitive learning and soft competition for vector quantizer design, IEEE Trans on Signal Processing, 1992, 40(2): 294.[4]Pal, N. R., Bezdek, J. C., Tsao, E. C. K., Generalized clustering networks and Kohonen's self-organizing scheme, IEEE Trans on Neural Networks, 1993, 4(4): 549.[5]Karayiannis, N. B., Bezdek, J. C., Pal, N. R. et al., Repair to GLVQ: a new family of competitive learning schemes, IEEE Trans on Neural Networks, 1996, 7(5): 1062.[6]Karayiannis, N. B., Pai, P. I., Fuzzy algorithms for learning vector quantization, IEEE Trans. on Neural Networks, 1996, 7(5): 1196.[7]Karayiannis, N. B., A methodology for constructing fuzzy algorithms for learning vector quantization, IEEE Trans. on Neural Networks, 1997, 8(3): 505.[8]Karayiannis, N. B., Bezdek, J. C., An integrated approach to fuzzy learning vector quantization and fuzzy C-Means clustering, IEEE Trans. on Fuzzy Systems, 1997, 5(4): 622.[9]Li Xing-si, An efficient approach to nonlinear minimax problems, Chinese Science Bulletin? 1992, 37(10): 802.[10]Li Xing-si, An efficient approach to a class of non-smooth optimization problems, Science in China, Series A,1994, 37(3): 323.[11]. Zangwill, W., Non-linear Programming: A Unified Approach, Englewood Cliffs: Prentice-Hall, 1969.[12]. Fletcher, R., Practical Methods of Optimization,2nd ed., New York: John Wiley & Sons, 1987.[13]. Zhang Zhihua, Zheng Nanning, Wang Tianshu, Behavioral analysis and improving of generalized LVQ neural network, Acta Automatica Sinica, 1999, 25(5): 582.[14]. Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P., Optimization by simulated annealing, Science, 1983, 220(3): 671.[15]. Ross, K., Deterministic annealing for

  16. The Quintuplet Cluster II. Analysis of the WN stars

    CERN Document Server

    Liermann, A; Oskinova, L M; Todt, H; Butler, K; 10.1051/0004-6361/200912612

    2010-01-01

    Based on $K$-band integral-field spectroscopy, we analyze four Wolf-Rayet stars of the nitrogen sequence (WN) found in the inner part of the Quintuplet cluster. All WN stars (WR102d, WR102i, WR102hb, and WR102ea) are of spectral subtype WN9h. One further star, LHO110, is included in the analysis which has been classified as Of/WN? previously but turns out to be most likely a WN9h star as well. The Potsdam Wolf-Rayet (PoWR) models for expanding atmospheres are used to derive the fundamental stellar and wind parameters. The stars turn out to be very luminous, $\\log{(L/L_\\odot)} > 6.0$, with relatively low stellar temperatures, $T_* \\approx$ 25--35\\,kK. Their stellar winds contain a significant fraction of hydrogen, up to $X_\\mathrm{H} \\sim 0.45$ (by mass). We discuss the position of the Galactic center WN stars in the Hertzsprung-Russell diagram and find that they form a distinct group. In this respect, the Quintuplet WN stars are similar to late-type WN stars found in the Arches cluster and elsewhere in the Ga...

  17. MMPI profiles of males accused of severe crimes: a cluster analysis

    NARCIS (Netherlands)

    Spaans, M.; Barendregt, M.; Muller, E.; Beurs, E. de; Nijman, H.L.I.; Rinne, T.

    2009-01-01

    In studies attempting to classify criminal offenders by cluster analysis of Minnesota Multiphasic Personality Inventory-2 (MMPI-2) data, the number of clusters found varied between 10 (the Megargee System) and two (one cluster indicating no psychopathology and one exhibiting serious psychopathology)

  18. Online Cluster Analysis Supporting Real Time Anomaly Detection in Hyperspectral Imagery

    Science.gov (United States)

    2013-06-01

    algorithm is accomplished for this exercise by performing the principal component analysis on the entire image after the removal of the noise and...cluster completely without fully capturing the intended cluster is easily explained by referencing Figure 29. The tree cluster in green is an eccentric

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

    Science.gov (United States)

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

    2017-11-01

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

  20. MMPI profiles of males accused of severe crimes: a cluster analysis

    NARCIS (Netherlands)

    Spaans, M.; Barendregt, M.; Muller, E.; Beurs, E. de; Nijman, H.L.I.; Rinne, T.

    2009-01-01

    In studies attempting to classify criminal offenders by cluster analysis of Minnesota Multiphasic Personality Inventory-2 (MMPI-2) data, the number of clusters found varied between 10 (the Megargee System) and two (one cluster indicating no psychopathology and one exhibiting serious

  1. Investigating Faculty Familiarity with Assessment Terminology by Applying Cluster Analysis to Interpret Survey Data

    Science.gov (United States)

    Raker, Jeffrey R.; Holme, Thomas A.

    2014-01-01

    A cluster analysis was conducted with a set of survey data on chemistry faculty familiarity with 13 assessment terms. Cluster groupings suggest a high, middle, and low overall familiarity with the terminology and an independent high and low familiarity with terms related to fundamental statistics. The six resultant clusters were found to be…

  2. Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

    Science.gov (United States)

    Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

    2015-09-01

    We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Investigating Faculty Familiarity with Assessment Terminology by Applying Cluster Analysis to Interpret Survey Data

    Science.gov (United States)

    Raker, Jeffrey R.; Holme, Thomas A.

    2014-01-01

    A cluster analysis was conducted with a set of survey data on chemistry faculty familiarity with 13 assessment terms. Cluster groupings suggest a high, middle, and low overall familiarity with the terminology and an independent high and low familiarity with terms related to fundamental statistics. The six resultant clusters were found to be…

  4. The Use of Cluster Analysis in Typological Research on Community College Students

    Science.gov (United States)

    Bahr, Peter Riley; Bielby, Rob; House, Emily

    2011-01-01

    One useful and increasingly popular method of classifying students is known commonly as cluster analysis. The variety of techniques that comprise the cluster analytic family are intended to sort observations (for example, students) within a data set into subsets (clusters) that share similar characteristics and differ in meaningful ways from other…

  5. Cluster stability in the analysis of mass cytometry data.

    Science.gov (United States)

    Melchiotti, Rossella; Gracio, Filipe; Kordasti, Shahram; Todd, Alan K; de Rinaldis, Emanuele

    2017-01-01

    Manual gating has been traditionally applied to cytometry data sets to identify cells based on protein expression. The advent of mass cytometry allows for a higher number of proteins to be simultaneously measured on cells, therefore providing a means to define cell clusters in a high dimensional expression space. This enhancement, whilst opening unprecedented opportunities for single cell-level analyses, makes the incremental replacement of manual gating with automated clustering a compelling need. To this aim many methods have been implemented and their successful applications demonstrated in different settings. However, the reproducibility of automatically generated clusters is proving challenging and an analytical framework to distinguish spurious clusters from more stable entities, and presumably more biologically relevant ones, is still missing. One way to estimate cell clusters' stability is the evaluation of their consistent re-occurrence within- and between-algorithms, a metric that is commonly used to evaluate results from gene expression. Herein we report the usage and importance of cluster stability evaluations, when applied to results generated from three popular clustering algorithms - SPADE, FLOCK and PhenoGraph - run on four different data sets. These algorithms were shown to generate clusters with various degrees of statistical stability, many of them being unstable. By comparing the results of automated clustering with manually gated populations, we illustrate how information on cluster stability can assist towards a more rigorous and informed interpretation of clustering results. We also explore the relationships between statistical stability and other properties such as clusters' compactness and isolation, demonstrating that whilst cluster stability is linked to other properties it cannot be reliably predicted by any of them. Our study proposes the introduction of cluster stability as a necessary checkpoint for cluster interpretation and

  6. Atomic collisions in suprafluid helium-nanodroplets: timescales for metal-cluster formation derived from He-density functional theory.

    Science.gov (United States)

    Hauser, Andreas W; Volk, Alexander; Thaler, Philipp; Ernst, Wolfgang E

    2015-04-28

    Collision times for the coinage metal atoms Cu, Ag and Au in He-droplets are derived from helium density functional theory and molecular dynamics simulations. The strength of the attractive interaction between the metal atoms turns out to be less important than the mass of the propagating metal atoms. Even for small droplets consisting of a few thousand helium atoms, the collision times are shortest for Cu, followed by Ag and Au, despite the higher binding energy of Au2 compared to Cu2.

  7. Maximum-entropy clustering algorithm and its global convergence analysis

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Constructing a batch of differentiable entropy functions touniformly approximate an objective function by means of the maximum-entropy principle, a new clustering algorithm, called maximum-entropy clustering algorithm, is proposed based on optimization theory. This algorithm is a soft generalization of the hard C-means algorithm and possesses global convergence. Its relations with other clustering algorithms are discussed.

  8. Population analysis of open clusters: radii and mass segregation

    CERN Document Server

    Schilbach, E; Piskunov, A E; Röser, S; Scholz, R D

    2006-01-01

    Aims: Based on our well-determined sample of open clusters in the all-sky catalogue ASCC-2.5 we derive new linear sizes of some 600 clusters, and investigate the effect of mass segregation of stars in open clusters. Methods: Using statistical methods, we study the distribution of linear sizes as a function of spatial position and cluster age. We also examine statistically the distribution of stars of different masses within clusters as a function of the cluster age. Results: No significant dependence of the cluster size on location in the Galaxy is detected for younger clusters (< 200 Myr), whereas older clusters inside the solar orbit turned out to be, on average, smaller than outside. Also, small old clusters are preferentially found close to the Galactic plane, whereas larger ones more frequently live farther away from the plane and at larger Galactocentric distances. For clusters with (V - M_V) < 10.5, a clear dependence of the apparent radius on age has been detected: the cluster radii decrease by ...

  9. Structure and property of metal melt Ⅱ—Evolution of atomic clusters in the not high temperature range above liquidus

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Based on the theory of micro-inhomogeneity of liquid metal,a calculation model is established for the quantitative description of the structural information of metal melts.Only by thermophysical property parameters and basic structural parameters of solid metal,can this model produce the main information of melt structure,including the relative concentration of active atoms,size of atomic clusters and number of short-range order atoms.Based on this model,the main structural information of Al and Ni melts in the not high range above the liquidus is calculated,with results in good agreement with experimental values.Besides,analyzed is the influence of superheating temperature and atomic number on the melt structural information of the first (IA) and second main group (IIA) elements.With temperature increasing,melt structural information regularly changes for both IA and IIA elements.With the atomic number increasing,melt structural information of IA elements changes regularly,for the crystal structures of the IA elements are all of bcc lattice type.However,no notable regular change of melt structural information for IIA elements has been found,mainly because the lattice type of IIA elements is of hcp-fcc-bcc transition.The present work presents an effective way for better understanding metal melt structure and for forecasting the change of the physical property of metal melts.

  10. Computational evaluation of sub-nanometer cluster activity of singly exposed copper atom with various coordinative environment in catalytic CO2 transformation

    Science.gov (United States)

    Shanmugam, Ramasamy; Thamaraichelvan, Arunachalam; Ganesan, Tharumeya Kuppusamy; Viswanathan, Balasubramanian

    2017-02-01

    Metal cluster, at sub-nanometer level has a unique property in the activation of small molecules, in contrast to that of bulk surface. In the present work, singly exposed active site of copper metal cluster at sub-nanometer level was designed to arrive at the energy minimised configurations, binding energy, electrostatic potential map, frontier molecular orbitals and partial density of states. The ab initio molecular dynamics was carried out to probe the catalytic nature of the cluster. Further, the stability of the metal cluster and its catalytic activity in the electrochemical reduction of CO2 to CO were evaluated by means of computational hydrogen electrode via calculation of the free energy profile using DFT/B3LYP level of theory in vacuum. The activity of the cluster is ascertained from the fact that the copper atom, present in a two coordinative environment, performs a more selective conversion of CO2 to CO at an applied potential of -0.35 V which is comparatively lower than that of higher coordinative sites. The present study helps to design any sub-nano level metal catalyst for electrochemical reduction of CO2 to various value added chemicals.

  11. Unsupervised analysis of classical biomedical markers: robustness and medical relevance of patient clustering using bioinformatics tools.

    Directory of Open Access Journals (Sweden)

    Michal Markovich Gordon

    Full Text Available MOTIVATION: It has been proposed that clustering clinical markers, such as blood test results, can be used to stratify patients. However, the robustness of clusters formed with this approach to data pre-processing and clustering algorithm choices has not been evaluated, nor has clustering reproducibility. Here, we made use of the NHANES survey to compare clusters generated with various combinations of pre-processing and clustering algorithms, and tested their reproducibility in two separate samples. METHOD: Values of 44 biomarkers and 19 health/life style traits were extracted from the National Health and Nutrition Examination Survey (NHANES. The 1999-2002 survey was used for training, while data from the 2003-2006 survey was tested as a validation set. Twelve combinations of pre-processing and clustering algorithms were applied to the training set. The quality of the resulting clusters was evaluated both by considering their properties and by comparative enrichment analysis. Cluster assignments were projected to the validation set (using an artificial neural network and enrichment in health/life style traits in the resulting clusters was compared to the clusters generated from the original training set. RESULTS: The clusters obtained with different pre-processing and clustering combinations differed both in terms of cluster quality measures and in terms of reproducibility of enrichment with health/life style properties. Z-score normalization, for example, dramatically improved cluster quality and enrichments, as compared to unprocessed data, regardless of the clustering algorithm used. Clustering diabetes patients revealed a group of patients enriched with retinopathies. This could indicate that routine laboratory tests can be used to detect patients suffering from complications of diabetes, although other explanations for this observation should also be considered. CONCLUSIONS: Clustering according to classical clinical biomarkers is a robust

  12. Cluster Analysis in Nursing Research: An Introduction, Historical Perspective, and Future Directions.

    Science.gov (United States)

    Dunn, Heather; Quinn, Laurie; Corbridge, Susan J; Eldeirawi, Kamal; Kapella, Mary; Collins, Eileen G

    2017-05-01

    The use of cluster analysis in the nursing literature is limited to the creation of classifications of homogeneous groups and the discovery of new relationships. As such, it is important to provide clarity regarding its use and potential. The purpose of this article is to provide an introduction to distance-based, partitioning-based, and model-based cluster analysis methods commonly utilized in the nursing literature, provide a brief historical overview on the use of cluster analysis in nursing literature, and provide suggestions for future research. An electronic search included three bibliographic databases, PubMed, CINAHL and Web of Science. Key terms were cluster analysis and nursing. The use of cluster analysis in the nursing literature is increasing and expanding. The increased use of cluster analysis in the nursing literature is positioning this statistical method to result in insights that have the potential to change clinical practice.

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

    OpenAIRE

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

    2014-01-01

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

  14. Application of atomic Hirshfeld surface analysis to intermetallic systems: is Mn in cubic CeMnNi4 a thermoelectric rattler atom?

    Science.gov (United States)

    Jørgensen, Mads R V; Skovsen, Iben; Clausen, Henrik F; Mi, Jian-Li; Christensen, Mogens; Nishibori, Eiji; Spackman, Mark A; Iversen, Bo B

    2012-02-06

    The Mn atom in the cubic polymorph of CeMnNi(4) appears to be located in an oversized cage-like structure, and anomalously large atomic displacement parameters (ADPs) for the Mn atom indicate that it is a potential "rattler" atom. Here, multitemperature synchrotron powder X-ray diffraction data measured between 110 and 900 K are used to estimate ADPs for the Mn "guest" atom and the "host" structure atoms in cubic CeMnNi(4). The ADPs are subsequently fitted with Debye and Einstein models, giving Θ(D) = 301(2) K for the "host" structure and Θ(E) = 165(2) K for the Mn atom. This is higher than typical Einstein temperatures for rattlers in thermoelectric skutterudites and clathrates (Θ(E) = 50-80 K), indicating that the Mn atom in cubic CeMnNi(4) is more strongly bonded. In order to probe the chemical interactions of the potential Mn rattler atom, atomic Hirshfeld surface (AHS) analysis is carried out and compared with AHS analysis of well-established guest atom rattlers in archetypical skutterudites, MCoSb(3). Surprisingly, the skutterudite rattlers have more deformed AHSs than the Mn atom in cubic CeMnNi(4). This is related to the highly ionic nature of the skutterudite rattlers, which is not taken into account in the neutral spherical atom approach of the AHS. Additionally, visualization of void spaces in the two materials using the procrystal electron density shows that while the Mn atom is tightly fitting in the CeMnNi(4) structure then the La atom in the skutterudite is truly situated in an oversized cage of the host structure. Overall, we conclude that the Mn atom in cubic CeMnNi(4) cannot be coined a rattler.

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

    Science.gov (United States)

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

    2013-10-01

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

  16. Challenges for Cluster Analysis in a Virtual Observatory

    CERN Document Server

    Djorgovski, S G; Mahabal, A A; Williams, R; Granat, R; Stolorz, P

    2002-01-01

    There has been an unprecedented and continuing growth in the volume, quality, and complexity of astronomical data sets over the past few years, mainly through large digital sky surveys. Virtual Observatory (VO) concept represents a scientific and technological framework needed to cope with this data flood. We review some of the applied statistics and computing challenges posed by the analysis of large and complex data sets expected in the VO-based research. The challenges are driven both by the size and the complexity of the data sets (billions of data vectors in parameter spaces of tens or hundreds of dimensions), by the heterogeneity of the data and measurement errors, the selection effects and censored data, and by the intrinsic clustering properties (functional form, topology) of the data distribution in the parameter space of observed attributes. Examples of scientific questions one may wish to address include: objective determination of the numbers of object classes present in the data, and the membersh...

  17. Higgs Pair Production: Choosing Benchmarks With Cluster Analysis

    CERN Document Server

    Dall'Osso, Martino; Gottardo, Carlo A; Oliveira, Alexandra; Tosi, Mia; Goertz, Florian

    2015-01-01

    New physics theories often depend on a large number of free parameters. The precise values of those parameters in some cases drastically affect the resulting phenomenology of fundamental physics processes, while in others finite variations can leave it basically invariant at the level of detail experimentally accessible. When designing a strategy for the analysis of experimental data in the search for a signal predicted by a new physics model, it appears advantageous to categorize the parameter space describing the model according to the corresponding kinematical features of the final state. A multi-dimensional test statistic can be used to gauge the degree of similarity in the kinematics of different models; a clustering algorithm using that metric may then allow the division of the space into homogeneous regions, each of which can be successfully represented by a benchmark point. Searches targeting those benchmark points are then guaranteed to be sensitive to a large area of the parameter space. In this doc...

  18. Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

    Science.gov (United States)

    Boccippio, Dennis J.

    2003-01-01

    It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description

  19. Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

    Science.gov (United States)

    Boccippio, Dennis J.

    2003-01-01

    It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description

  20. A COMPARISON BETWEEN SINGLE LINKAGE AND COMPLETE LINKAGE IN AGGLOMERATIVE HIERARCHICAL CLUSTER ANALYSIS FOR IDENTIFYING TOURISTS SEGMENTS

    OpenAIRE

    Noor Rashidah Rashid

    2012-01-01

    Cluster Analysis is a multivariate method in statistics. Agglomerative Hierarchical Cluster Analysis is one of approaches in Cluster Analysis. There are two linkage methods in Agglomerative Hierarchical Cluster Analysis which are Single Linkage and Complete Linkage. The purpose of this study is to compare between Single Linkage and Complete Linkage in Agglomerative Hierarchical Cluster Analysis. The comparison of performances between these linkage methods was shown by using Kruskal-Wallis tes...

  1. Outlier Identification in Model-Based Cluster Analysis.

    Science.gov (United States)

    Evans, Katie; Love, Tanzy; Thurston, Sally W

    2015-04-01

    In model-based clustering based on normal-mixture models, a few outlying observations can influence the cluster structure and number. This paper develops a method to identify these, however it does not attempt to identify clusters amidst a large field of noisy observations. We identify outliers as those observations in a cluster with minimal membership proportion or for which the cluster-specific variance with and without the observation is very different. Results from a simulation study demonstrate the ability of our method to detect true outliers without falsely identifying many non-outliers and improved performance over other approaches, under most scenarios. We use the contributed R package MCLUST for model-based clustering, but propose a modified prior for the cluster-specific variance which avoids degeneracies in estimation procedures. We also compare results from our outlier method to published results on National Hockey League data.

  2. Outlier Identification in Model-Based Cluster Analysis

    Science.gov (United States)

    Evans, Katie; Love, Tanzy; Thurston, Sally W.

    2015-01-01

    In model-based clustering based on normal-mixture models, a few outlying observations can influence the cluster structure and number. This paper develops a method to identify these, however it does not attempt to identify clusters amidst a large field of noisy observations. We identify outliers as those observations in a cluster with minimal membership proportion or for which the cluster-specific variance with and without the observation is very different. Results from a simulation study demonstrate the ability of our method to detect true outliers without falsely identifying many non-outliers and improved performance over other approaches, under most scenarios. We use the contributed R package MCLUST for model-based clustering, but propose a modified prior for the cluster-specific variance which avoids degeneracies in estimation procedures. We also compare results from our outlier method to published results on National Hockey League data. PMID:26806993

  3. Data analysis and other considerations concerning the study of precipitation in Al–Mg–Si alloys by Atom Probe Tomography

    Directory of Open Access Journals (Sweden)

    M.W. Zandbergen

    2015-12-01

    Full Text Available Atom Probe Tomography (APT analysis and hardness measurements were used to characterize the early stages of precipitation in an Al–0.51 at%Mg–0.94 at%Si alloy as reported in the accompanying Acta Materialia paper [1]. The changes in microstructure were investigated after single-stage or multi-stage heat treatments including natural ageing at 298 K (NA, pre-ageing at 353 K (PA, and automotive paint-bake ageing conditions at 453 K (PB. This article provides Supporting information and a detailed report on the experimental conditions and the data analysis methods used for this investigation. Careful design of experimental conditions and analysis methods was carried out to obtain consistent and reliable results. Detailed data on clustering for prolonged NA and PA treatments have been reported.

  4. Structures of Mn clusters

    Indian Academy of Sciences (India)

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

    2003-01-01

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

  5. Advancing health-related cluster analysis methodology: quantification of pairwise activity cluster similarities.

    Science.gov (United States)

    Ferrar, Katia; Maher, Carol; Petkov, John; Olds, Tim

    2015-03-01

    To date, most health-related time-use research has investigated behaviors in isolation; more recently, however, researchers have begun to conceptualize behaviors in the form of multidimensional patterns or clusters. The study employed 2 techniques: radar graphs and centroid vector length, angles and distance to quantify pairwise time-use cluster similarities among adolescents living in Australia (N = 1853) and in New Zealand (N = 679). Based on radar graph shape, 2 pairs of clusters were similar for both boys and girls. Using vector angles (VA), vector length (VL) and centroid distances (CD), 1 pair for each sex was considered most similar (boys: VA = 63°, VL = 44 and 50 units, and CD = 48 units; girls: VA = 23°, VL = 65 and 85 units, and CD = 36 units). Both methods employed to determine similarity had strengths and weaknesses. The description and quantification of cluster similarity is an important step in the research process. An ability to track and compare clusters may provide greater understanding of complex multidimensional relationships, and in relation to health behavior clusters, present opportunities to monitor and to intervene.

  6. Application of Multi-SOM clustering approach to macrophage gene expression analysis.

    Science.gov (United States)

    Ghouila, Amel; Yahia, Sadok Ben; Malouche, Dhafer; Jmel, Haifa; Laouini, Dhafer; Guerfali, Fatma Z; Abdelhak, Sonia

    2009-05-01

    The production of increasingly reliable and accessible gene expression data has stimulated the development of computational tools to interpret such data and to organize them efficiently. The clustering techniques are largely recognized as useful exploratory tools for gene expression data analysis. Genes that show similar expression patterns over a wide range of experimental conditions can be clustered together. This relies on the hypothesis that genes that belong to the same cluster are coregulated and involved in related functions. Nevertheless, clustering algorithms still show limits, particularly for the estimation of the number of clusters and the interpretation of hierarchical dendrogram, which may significantly influence the outputs of the analysis process. We propose here a multi level SOM based clustering algorithm named Multi-SOM. Through the use of clustering validity indices, Multi-SOM overcomes the problem of the estimation of clusters number. To test the validity of the proposed clustering algorithm, we first tested it on supervised training data sets. Results were evaluated by computing the number of misclassified samples. We have then used Multi-SOM for the analysis of macrophage gene expression data generated in vitro from the same individual blood infected with 5 different pathogens. This analysis led to the identification of sets of tightly coregulated genes across different pathogens. Gene Ontology tools were then used to estimate the biological significance of the clustering, which showed that the obtained clusters are coherent and biologically significant.

  7. Parallel tempering Monte Carlo combined with clustering Euclidean metric analysis to study the thermodynamic stability of Lennard-Jones nanoclusters

    Science.gov (United States)

    Cezar, Henrique M.; Rondina, Gustavo G.; Da Silva, Juarez L. F.

    2017-02-01

    A basic requirement for an atom-level understanding of nanoclusters is the knowledge of their atomic structure. This understanding is incomplete if it does not take into account temperature effects, which play a crucial role in phase transitions and changes in the overall stability of the particles. Finite size particles present intricate potential energy surfaces, and rigorous descriptions of temperature effects are best achieved by exploiting extended ensemble algorithms, such as the Parallel Tempering Monte Carlo (PTMC). In this study, we employed the PTMC algorithm, implemented from scratch, to sample configurations of LJn (n =38 , 55, 98, 147) particles at a wide range of temperatures. The heat capacities and phase transitions obtained with our PTMC implementation are consistent with all the expected features for the LJ nanoclusters, e.g., solid to solid and solid to liquid. To identify the known phase transitions and assess the prevalence of various structural motifs available at different temperatures, we propose a combination of a Leader-like clustering algorithm based on a Euclidean metric with the PTMC sampling. This combined approach is further compared with the more computationally demanding bond order analysis, typically employed for this kind of problem. We show that the clustering technique yields the same results in most cases, with the advantage that it requires no previous knowledge of the parameters defining each geometry. Being simple to implement, we believe that this straightforward clustering approach is a valuable data analysis tool that can provide insights into the physics of finite size particles with few to thousand atoms at a relatively low cost.

  8. Dynamic analysis of atomic magnetometer and co-magnetometer

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shihu, E-mail: 65980623@qq.com; Yu, Linke; Wang, Wei

    2016-03-01

    Some unsteady-state solutions of Bloch equation which well-describe the behavior of a magnetometer are obtained. These solutions are in accord with the experimental result of alkali-metal magnetometer and co-magnetometer gyroscope. Many interesting phenomena can be also achieved via the solutions. First, the measuring direction of a magnetometer changes with the variation of external magnetic field along z axis. And it could be used for measuring high frequency magnetic field. Then it can be extended that the co-magnetometer without compensated field can get better performance than simple atomic magnetometer due to the effect of polarized noble gas. Finally, we discussed the limits (bandwidth and so on) of atomic magnetometer and co-magnetometer with the Bloch equation of spins. These phenomena, which have not been mentioned before, may contribute to the development of atomic magnetometer and co-magnetometer gyroscope.

  9. Cluster analysis application in research on pork quality determinants

    Science.gov (United States)

    Przybylski, W.; Wasiewicz, P.; Zieliński, P.; Gromadzka-Ostrowska, J.; Olczak, E.; Jaworska, D.; Niemyjski, S.; Santé-Lhoutellier, V.

    2010-09-01

    In this paper data mining methods were applied to investigate features determining high quality pork meat. The aim of the study was analysis of conditionality of the pork meat quality defined in coherence with HDL and LDL cholesterol concentration, plasma leptin, triglycerides, plasma glucose and serum. The research was carried out on 54 pigs. originated from crossbreeding of Naima sows with P76-PenArLan boars hybrids line. Meat quality parameters were evaluated in samples derived from the Longissimus (LD) muscle taken behind the last rib on the basis: the pH value, meat colour, drip loss, the RTN, intramuscular fat and glycolytic potential. The results of this study were elaborated by using R environment and show that cluster and regression analysis can be a useful tool for in-depth analysis of the determinants of the quality of pig meat in homogeneous populations of pigs. However, the question of determinants of the level of glycogen and fat in meat requires further research.

  10. Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

    Directory of Open Access Journals (Sweden)

    Marco Borri

    Full Text Available To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment.The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4. Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters.The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4, determined with cluster validation, produced the best separation between reducing and non-reducing clusters.The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

  11. Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

    Science.gov (United States)

    Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

    2015-01-01

    To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

  12. A combined multidimensional scaling and hierarchical clustering view for the exploratory analysis of multidimensional data

    Science.gov (United States)

    Craig, Paul; Roa-Seïler, Néna

    2013-01-01

    This paper describes a novel information visualization technique that combines multidimensional scaling and hierarchical clustering to support the exploratory analysis of multidimensional data. The technique displays the results of multidimensional scaling using a scatter plot where the proximity of any two items' representations is approximate to their similarity according to a Euclidean distance metric. The results of hierarchical clustering are overlaid onto this view by drawing smoothed outlines around each nested cluster. The difference in similarity between successive cluster combinations is used to colour code clusters and make stronger natural clusters more prominent in the display. When a cluster or group of items is selected, multidimensional scaling and hierarchical clustering are re-applied to a filtered subset of the data, and animation is used to smooth the transition between successive filtered views. As a case study we demonstrate the technique being used to analyse survey data relating to the appropriateness of different phrases to different emotionally charged situations.

  13. AVES: A Computer Cluster System approach for INTEGRAL Scientific Analysis

    Science.gov (United States)

    Federici, M.; Martino, B. L.; Natalucci, L.; Umbertini, P.

    The AVES computing system, based on an "Cluster" architecture is a fully integrated, low cost computing facility dedicated to the archiving and analysis of the INTEGRAL data. AVES is a modular system that uses the software resource manager (SLURM) and allows almost unlimited expandibility (65,536 nodes and hundreds of thousands of processors); actually is composed by 30 Personal Computers with Quad-Cores CPU able to reach the computing power of 300 Giga Flops (300x10{9} Floating point Operations Per Second), with 120 GB of RAM and 7.5 Tera Bytes (TB) of storage memory in UFS configuration plus 6 TB for users area. AVES was designed and built to solve growing problems raised from the analysis of the large data amount accumulated by the INTEGRAL mission (actually about 9 TB) and due to increase every year. The used analysis software is the OSA package, distributed by the ISDC in Geneva. This is a very complex package consisting of dozens of programs that can not be converted to parallel computing. To overcome this limitation we developed a series of programs to distribute the workload analysis on the various nodes making AVES automatically divide the analysis in N jobs sent to N cores. This solution thus produces a result similar to that obtained by the parallel computing configuration. In support of this we have developed tools that allow a flexible use of the scientific software and quality control of on-line data storing. The AVES software package is constituted by about 50 specific programs. Thus the whole computing time, compared to that provided by a Personal Computer with single processor, has been enhanced up to a factor 70.

  14. Classification of persons attempting suicide. A review of cluster analysis research

    Directory of Open Access Journals (Sweden)

    Wołodźko, Tymoteusz

    2014-08-01

    Full Text Available Aim: Review of conclusions from cluster analysis research on suicide risk factors published after the year 1993. Methods: Search and analysis of cluster analysis research papers on suicidal behaviour. Results: Following groups where distinguished: (1 persons with comorbid mental disorders or with severe symptoms, (2 persons without mental disorders or with mild symptoms, (3 persons with personality disorders and externalizing psychopathology, (4 socially withdrawn persons with a tendency to avoid social contacts, (5 depressive persons Conclusions: Analysis of studies on characteristics of suicide attempters, with the application of cluster analysis, has indicated the possibility of differentiation of several groups of persons with significantly increased risk of suicide attempt. The reviewed cluster analysis research had multiple methodological limitations. Studies employing cluster analysis on large, representative and homogeneous population are needed.

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

    Science.gov (United States)

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

    2015-01-01

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

  16. Hierarchical Cluster Analysis: Comparison of Three Linkage Measures and Application to Psychological Data

    Directory of Open Access Journals (Sweden)

    Odilia Yim

    2015-02-01

    Full Text Available Cluster analysis refers to a class of data reduction methods used for sorting cases, observations, or variables of a given dataset into homogeneous groups that differ from each other. The present paper focuses on hierarchical agglomerative cluster analysis, a statistical technique where groups are sequentially created by systematically merging similar clusters together, as dictated by the distance and linkage measures chosen by the researcher. Specific distance and linkage measures are reviewed, including a discussion of how these choices can influence the clustering process by comparing three common linkage measures (single linkage, complete linkage, average linkage. The tutorial guides researchers in performing a hierarchical cluster analysis using the SPSS statistical software. Through an example, we demonstrate how cluster analysis can be used to detect meaningful subgroups in a sample of bilinguals by examining various language variables.

  17. Analysis of the entanglement between two individual atoms using global Raman rotations

    CERN Document Server

    Gaetan, A; Wolters, J; Grangier, P; Wilk, T; Browaeys, A

    2009-01-01

    Making use of the Rydberg blockade, we generate entanglement between two atoms individually trapped in two optical tweezers. In this paper we detail the analysis of the data and show that we can determine the amount of entanglement between the atoms in the presence of atom losses during the entangling sequence. Our model takes into account states outside the qubit basis and allows us to perform a partial reconstruction of the density matrix describing the two atom state. With this method we extract the amount of entanglement between pairs of atoms still trapped after the entangling sequence and measure the fidelity with respect to the expected Bell state. We find a fidelity $F_{\\rm pairs} =0.74(7)$ for the 62% of atom pairs remaining in the traps at the end of the entangling sequence.

  18. Analysis of the entanglement between two individual atoms using global Raman rotations

    Energy Technology Data Exchange (ETDEWEB)

    Gaetan, A; Evellin, C; Wolters, J; Grangier, P; Wilk, T; Browaeys, A, E-mail: antoine.browaeys@institutoptique.f [Laboratoire Charles Fabry, Institut d' Optique, CNRS, Univ Paris-Sud, Campus Polytechnique, RD 128, 91127 Palaiseau cedex (France)

    2010-06-15

    Making use of the Rydberg blockade, we generate entanglement between two atoms individually trapped in two optical tweezers. In this paper, we detail the analysis of the data and show that we can determine the amount of entanglement between the atoms in the presence of atom losses during the entangling sequence. Our model takes into account states outside the qubit basis and allows us to perform a partial reconstruction of the density matrix describing the two-atom state. With this method, we extract the amount of entanglement between pairs of atoms still trapped after the entangling sequence and measure the fidelity with respect to the expected Bell state. We find a fidelity F{sub pairs}=0.74(7) for the 62% of atom pairs remaining in the traps at the end of the entangling sequence.

  19. Profiles of exercise motivation, physical activity, exercise habit, and academic performance in Malaysian adolescents: A cluster analysis

    OpenAIRE

    Hairul Anuar Hashim; Freddy Golok; Rosmatunisah Ali

    2011-01-01

    Objectives: This study examined Malaysian adolescents’ profiles of exercise motivation, exercise habit strength, academic performance, and levels of physical activity (PA) using cluster analysis.Methods: The sample (n = 300) consisted of 65.6% males and 34.4% females with a mean age of 13.40 ± 0.49. Statistical analysis was performed using cluster analysis.Results: Cluster analysis revealed three distinct cluster groups. Cluster 1 is characterized by a moderate level of PA, relatively high in...

  20. Genome-scale analysis of positional clustering of mouse testis-specific genes

    Directory of Open Access Journals (Sweden)

    Lee Bernett TK

    2005-01-01

    Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

  1. Atoms in parallel fields: Analysis with diffractive periodic orbits

    Science.gov (United States)

    Owen, S. M.; Monteiro, T. S.; Dando, P. A.

    2000-11-01

    We show that fluctuations in the density of states of nonhydrogenic atoms in parallel fields are strongly influenced by diffractive periodic orbits. Unlike typical systems with a diffractive point scatterer, the atomic core of small atoms like lithium and helium is best understood as a combined geometric and diffractive scatterer. Each Gutzwiller (geometric) periodic orbit is paired with a diffractive orbit of the same action. We investigate, particularly, amplitudes for contributions from repetitions, and multiple scattering orbits. We find that periodic orbit repetitions are described by ``hybrid'' orbits, combining both diffractive and geometric core scatters, and that by including all possible permutations we can obtain excellent agreement between the semiclassical model and accurate fully quantal calculations. For high repetitions, we find even one-scatter diffractive contributions become of the same order as those of the geometric periodic orbit for repetition numbers n~ħ-1/2. Although the contribution of individual diffractive orbits is suppressed by O(ħ1/2) relative to the geometric periodic orbits, the proliferation of diffractive orbits with increasing period means that the diffractive effect for the atom can persist in the ħ-->0 limit.

  2. Identification and validation of asthma phenotypes in Chinese population using cluster analysis.

    Science.gov (United States)

    Wang, Lei; Liang, Rui; Zhou, Ting; Zheng, Jing; Liang, Bing Miao; Zhang, Hong Ping; Luo, Feng Ming; Gibson, Peter G; Wang, Gang

    2017-08-30

    Asthma is a heterogeneous airway disease, so it is crucial to clearly identify clinical phenotypes to achieve better asthma management. To identify and prospectively validate asthma clusters in a Chinese population. Two hundred eighty-four patients were consecutively recruited and 18 sociodemographic and clinical variables were collected. Hierarchical cluster analysis was performed by the Ward method followed by k-means cluster analysis. Then, a prospective 12-month cohort study was used to validate the identified clusters. Five clusters were successfully identified. Clusters 1 (n = 71) and 3 (n = 81) were mild asthma phenotypes with slight airway obstruction and low exacerbation risk, but with a sex differential. Cluster 2 (n = 65) described an "allergic" phenotype, cluster 4 (n = 33) featured a "fixed airflow limitation" phenotype with smoking, and cluster 5 (n = 34) was a "low socioeconomic status" phenotype. Patients in clusters 2, 4, and 5 had distinctly lower socioeconomic status and more psychological symptoms. Cluster 2 had a significantly increased risk of exacerbations (risk ratio [RR] 1.13, 95% confidence interval [CI] 1.03-1.25), unplanned visits for asthma (RR 1.98, 95% CI 1.07-3.66), and emergency visits for asthma (RR 7.17, 95% CI 1.26-40.80). Cluster 4 had an increased risk of unplanned visits (RR 2.22, 95% CI 1.02-4.81), and cluster 5 had increased emergency visits (RR 12.72, 95% CI 1.95-69.78). Kaplan-Meier analysis confirmed that cluster grouping was predictive of time to the first asthma exacerbation, unplanned visit, emergency visit, and hospital admission (P clusters as "allergic asthma," "fixed airflow limitation," and "low socioeconomic status" phenotypes that are at high risk of severe asthma exacerbations and that have management implications for clinical practice in developing countries. Copyright © 2017 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  3. A functional clustering algorithm for the analysis of neural relationships

    CERN Document Server

    Feldt, S; Hetrick, V L; Berke, J D; Zochowski, M

    2008-01-01

    We formulate a novel technique for the detection of functional clusters in neural data. In contrast to prior network clustering algorithms, our procedure progressively combines spike trains and derives the optimal clustering cutoff in a simple and intuitive manner. To demonstrate the power of this algorithm to detect changes in network dynamics and connectivity, we apply it to both simulated data and real neural data obtained from the mouse hippocampus during exploration and slow-wave sleep. We observe state-dependent clustering patterns consistent with known neurophysiological processes involved in memory consolidation.

  4. X-Ray Morphological Analysis of the Planck ESZ Clusters

    Science.gov (United States)

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

    2017-09-01

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

  5. The Galaxy Cluster RBS380: Xray and Optical Analysis

    OpenAIRE

    Gil-Merino, R.; Schindler, S.

    2002-01-01

    We present X-ray and optical observations of the z=0.52 galaxy cluster RBS380. This is the most distant cluster in the ROSAT Bright Source catalog. The cluster was observed with the CHANDRA satellite in September 2000. The optical observations were carried out with the NTT-SUSI2 camara in filters V and R in August and September 2001. The preliminary conclusions are that we see a very rich optical galaxy cluster but with a relative low X-ray luminosity. We also compare our results to other clu...

  6. Significance analysis and statistical mechanics: an application to clustering.

    Science.gov (United States)

    Łuksza, Marta; Lässig, Michael; Berg, Johannes

    2010-11-26

    This Letter addresses the statistical significance of structures in random data: given a set of vectors and a measure of mutual similarity, how likely is it that a subset of these vectors forms a cluster with enhanced similarity among its elements? The computation of this cluster p value for randomly distributed vectors is mapped onto a well-defined problem of statistical mechanics. We solve this problem analytically, establishing a connection between the physics of quenched disorder and multiple-testing statistics in clustering and related problems. In an application to gene expression data, we find a remarkable link between the statistical significance of a cluster and the functional relationships between its genes.

  7. Coupled cluster and density functional theory calculations of atomic hydrogen chemisorption on pyrene and coronene as model systems for graphene hydrogenation.

    Science.gov (United States)

    Wang, Ying; Qian, Hu-Jun; Morokuma, Keiji; Irle, Stephan

    2012-07-05

    Ab initio coupled cluster and density functional theory studies of atomic hydrogen addition to the central region of pyrene and coronene as molecular models for graphene hydrogenation were performed. Fully relaxed potential energy curves (PECs) were computed at the spin-unrestricted B3LYP/cc-pVDZ level of theory for the atomic hydrogen attack of a center carbon atom (site A), the midpoint of a neighboring carbon bond (site B), and the center of a central hexagon (site C). Using the B3LYP/cc-pVDZ PEC geometries, we evaluated energies at the PBE density functional, as well as ab initio restricted open-shell ROMP2, ROCCSD, and ROCCSD(T) levels of theory, employing cc-pVDZ and cc-pVTZ basis sets, and performed a G2MS extrapolation to the ROCCSD(T)/cc-pVTZ level of theory. In agreement with earlier studies, we find that only site A attack leads to chemisorption. The G2MS entrance channel barrier heights, binding energies, and PEC profiles are found to agree well with a recent ab initio multireference wave function theory study (Bonfanti et al. J. Chem. Phys.2011, 135, 164701), indicating that single-reference open-shell methods including B3LYP are sufficient for the theoretical treatment of the interaction of graphene with a single hydrogen atom.

  8. Study on Cluster Analysis Used with Laser-Induced Breakdown Spectroscopy

    Science.gov (United States)

    He, Li'ao; Wang, Qianqian; Zhao, Yu; Liu, Li; Peng, Zhong

    2016-06-01

    Supervised learning methods (eg. PLS-DA, SVM, etc.) have been widely used with laser-induced breakdown spectroscopy (LIBS) to classify materials; however, it may induce a low correct classification rate if a test sample type is not included in the training dataset. Unsupervised cluster analysis methods (hierarchical clustering analysis, K-means clustering analysis, and iterative self-organizing data analysis technique) are investigated in plastics classification based on the line intensities of LIBS emission in this paper. The results of hierarchical clustering analysis using four different similarity measuring methods (single linkage, complete linkage, unweighted pair-group average, and weighted pair-group average) are compared. In K-means clustering analysis, four kinds of choosing initial centers methods are applied in our case and their results are compared. The classification results of hierarchical clustering analysis, K-means clustering analysis, and ISODATA are analyzed. The experiment results demonstrated cluster analysis methods can be applied to plastics discrimination with LIBS. supported by Beijing Natural Science Foundation of China (No. 4132063)

  9. Using cluster analysis to identify phenotypes and validation of mortality in men with COPD.

    Science.gov (United States)

    Chen, Chiung-Zuei; Wang, Liang-Yi; Ou, Chih-Ying; Lee, Cheng-Hung; Lin, Chien-Chung; Hsiue, Tzuen-Ren

    2014-12-01

    Cluster analysis has been proposed to examine phenotypic heterogeneity in chronic obstructive pulmonary disease (COPD). The aim of this study was to use cluster analysis to define COPD phenotypes and validate them by assessing their relationship with mortality. Male subjects with COPD were recruited to identify and validate COPD phenotypes. Seven variables were assessed for their relevance to COPD, age, FEV(1) % predicted, BMI, history of severe exacerbations, mMRC, SpO(2), and Charlson index. COPD groups were identified by cluster analysis and validated prospectively against mortality during a 4-year follow-up. Analysis of 332 COPD subjects identified five clusters from cluster A to cluster E. Assessment of the predictive validity of these clusters of COPD showed that cluster E patients had higher all cause mortality (HR 18.3, p Cluster E patients also had higher all cause mortality (HR 14.3, p = 0.0002) and respiratory cause mortality (HR 10.1, p = 0.0013) than patients in cluster D alone. COPD patient with severe airflow limitation, many symptoms, and a history of frequent severe exacerbations was a novel and distinct clinical phenotype predicting mortality in men with COPD.

  10. The Norma Cluster (ACO 3627): I. A Dynamical Analysis of the Most Massive Cluster in the Great Attractor

    CERN Document Server

    Woudt, P A; Lucey, J; Fairall, A P; Moore, S A W

    2007-01-01

    A detailed dynamical analysis of the nearby rich Norma cluster (ACO 3627) is presented. From radial velocities of 296 cluster members, we find a mean velocity of 4871 +/- 54 km/s and a velocity dispersion of 925 km/s. The mean velocity of the E/S0 population (4979 +/- 85 km/s) is offset with respect to that of the S/Irr population (4812 +/- 70 km/s) by `Delta' v = 164 km/s in the cluster rest frame. This offset increases towards the core of the cluster. The E/S0 population is free of any detectable substructure and appears relaxed. Its shape is clearly elongated with a position angle that is aligned along the dominant large-scale structures in this region, the so-called Norma wall. The central cD galaxy has a very large peculiar velocity of 561 km/s which is most probably related to an ongoing merger at the core of the cluster. The spiral/irregular galaxies reveal a large amount of substructure; two dynamically distinct subgroups within the overall spiral-population have been identified, located along the Nor...

  11. Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials

    Science.gov (United States)

    Sanders, Elizabeth A.

    2011-01-01

    This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…

  12. Sequential Combination Methods forData Clustering Analysis

    Institute of Scientific and Technical Information of China (English)

    钱 涛; Ching Y.Suen; 唐远炎

    2002-01-01

    This paper proposes the use of more than one clustering method to improve clustering performance. Clustering is an optimization procedure based on a specific clustering criterion. Clustering combination can be regardedasatechnique that constructs and processes multiple clusteringcriteria.Sincetheglobalandlocalclusteringcriteriaarecomplementary rather than competitive, combining these two types of clustering criteria may enhance theclustering performance. In our past work, a multi-objective programming based simultaneous clustering combination algorithmhasbeenproposed, which incorporates multiple criteria into an objective function by a weighting method, and solves this problem with constrained nonlinear optimization programming. But this algorithm has high computationalcomplexity.Hereasequential combination approach is investigated, which first uses the global criterion based clustering to produce an initial result, then uses the local criterion based information to improve the initial result with aprobabilisticrelaxation algorithm or linear additive model.Compared with the simultaneous combination method, sequential combination haslow computational complexity. Results on some simulated data and standard test data arereported.Itappearsthatclustering performance improvement can be achieved at low cost through sequential combination.

  13. Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp. RFLP/PCR data set

    Science.gov (United States)

    Milagre, S. T.; Maciel, C. D.; Shinoda, A. A.; Hungria, M.; Almeida, J. R. B.

    2009-05-01

    The taxonomy of the N2-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradyrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster.

  14. Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

    Energy Technology Data Exchange (ETDEWEB)

    Hogan, Emilie A.; Cotilla Sanchez, Jose E.; Halappanavar, Mahantesh; Wang, Shaobu; Mackey, Patrick S.; Hines, Paul; Huang, Zhenyu

    2013-11-30

    Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques on two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.

  15. Mesoscopic analysis of networks: applications to exploratory analysis and data clustering

    CERN Document Server

    Granell, Clara; Arenas, Alex

    2011-01-01

    We investigate the adaptation and performance of modularity-based algorithms, designed in the scope of complex networks, to analyze the mesoscopic structure of correlation matrices. Using a multi-resolution analysis we are able to describe the structure of the data in terms of clusters at different topological levels. We demonstrate the applicability of our findings in two different scenarios: to analyze the neural connectivity of the nematode {\\em Caenorhabditis elegans}, and to automatically classify a typical benchmark of unsupervised clustering, the Iris data set, with considerable success.

  16. Common Factor Analysis Versus Principal Component Analysis: Choice for Symptom Cluster Research

    Directory of Open Access Journals (Sweden)

    Hee-Ju Kim, PhD, RN

    2008-03-01

    Conclusion: If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research, CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

  17. Finding "Problem Types" in Judgments of Problem-Similarity: Comparison of Cluster Analysis with Subject Protocols.

    Science.gov (United States)

    Herring, Richard D.

    Literature in mathematic problem-solving suggests that learners store information in memory which helps them solve stereotyped algebra word problems. Cluster analysis has been used as an exploratory tool to infer the types of problems which have common representations in memory. This study compares the results of a hierarchical cluster analysis of…

  18. Tracking Undergraduate Student Achievement in a First-Year Physiology Course Using a Cluster Analysis Approach

    Science.gov (United States)

    Brown, S. J.; White, S.; Power, N.

    2015-01-01

    A cluster analysis data classification technique was used on assessment scores from 157 undergraduate nursing students who passed 2 successive compulsory courses in human anatomy and physiology. Student scores in five summative assessment tasks, taken in each of the courses, were used as inputs for a cluster analysis procedure. We aimed to group…

  19. Schedulability Analysis and Optimization for the Synthesis of Multi-Cluster Distributed Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    2003-01-01

    An approach to schedulability analysis for the synthesis of multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways, is presented. A buffer size and worst case queuing delay analysis for the gateways, responsible for routing...

  20. Cluster Analysis of the Luria-Nebraska Neuropsychological Battery with Learning Disabled Adults.

    Science.gov (United States)

    McCue, Michael; And Others

    The study reports a cluster analysis of Luria-Nebraska Neuropsychological Battery sources of 25 learning disabled adults. The cluster analysis suggested the presence of three subgroups within this sample, one having high elevations on the Rhythm, Writing, Reading, and Arithmetic Rhythm scales, the second having an extremely high evelation on the…