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Sample records for modeling tev class

  1. New classes of polytropic models

    NASA Astrophysics Data System (ADS)

    Ngubelanga, S. A.; Maharaj, S. D.

    2017-03-01

    The gravitational behaviour of a dense compact object is studied in isotropic coordinates. We obtain new classes of static, spherically symmetric classes of solutions to the Einstein-Maxwell field equations by assuming an anisotropic pressures and a barotropic equation of state which is polytropic. Four new classes of exact solutions are found with different polytropic indices. We can regain masses of several observed astronomical objects. A physical analysis indicates that the models are well behaved.

  2. A Model Chemistry Class.

    ERIC Educational Resources Information Center

    Summerlin, Lee; Borgford, Christie

    1989-01-01

    Described is an activity which uses a 96-well reaction plate and soda straws to construct a model of the periodic table of the elements. The model illustrates the ionization energies of the various elements. Construction of the model and related concepts are discussed. (CW)

  3. A GENERAL RELATIVISTIC EXTERNAL COMPTON-SCATTERING MODEL FOR TeV EMISSION FROM M87

    SciTech Connect

    Cui Yudong; Yuan Yefei; Li Yanrong; Wang Jianmin

    2012-02-20

    M87 is the first detected non-blazar extragalactic tera-electron-volt (TeV) source with rapid variation and a very flat spectrum in the TeV band. To explain the two peaks in the spectral energy distribution of the nucleus of M87, which is similar to that of blazars, the most commonly adopted models are the synchrotron self-Compton-scattering models and the external inverse Compton (EIC) scattering models. Considering that there is no correlated variation in the soft band (from radio to X-ray) matching the TeV variation and that the TeV sources should not suffer from {gamma}{gamma} absorption due to the flat TeV spectrum, the EIC models are advantageous in modeling the TeV emission from M87. In this paper, we propose a self-consistent EIC model to explain the flat TeV spectrum of M87 within the framework of fully general relativity, where the background soft photons are from the advection-dominated accretion flow around the central black hole, and the high-energy electrons are from the mini-jets that are powered by the magnetic reconnection in the main jet. In our model, both the TeV flares observed in the years 2005 and 2008 could be well explained: the {gamma}{gamma} absorption for TeV photons is very low, even inside the region very close to the black hole 20R{sub g} {approx} 50R{sub g} ; at the same region, the average EIC cooling time ({approx}10{sup 2} {approx} 10{sup 3} s) is short, which is consistent with the observed timescale of the TeV variation. Furthermore, we also discuss the possibility that the accompanying X-ray flare in 2008 is due to the direct synchrotron radiation of the mini-jets.

  4. Modeling of 10 GeV-1 TeV laser-plasma accelerators using Lorentz boosted simulations

    SciTech Connect

    Vay, J. -L.; Geddes, C. G. R.; Esarey, E.; Schroeder, C. B.; Leemans, W. P.; Cormier-Michel, E.; Grote, D. P.

    2011-12-13

    We study modeling of laser-plasma wakefield accelerators in an optimal frame of reference [J.-L. Vay, Phys. Rev. Lett. 98, 130405 (2007)] that allows direct and efficient full-scale modeling of deeply depleted and beam loaded laser-plasma stages of 10 GeV-1 TeV (parameters not computationally accessible otherwise). This verifies the scaling of plasmaaccelerators to very high energies and accurately models the laser evolution and the accelerated electron beam transverse dynamics and energy spread. Over 4, 5, and 6 orders of magnitude speedup is achieved for the modeling of 10 GeV, 100 GeV, and 1 TeV class stages, respectively. Agreement at the percentage level is demonstrated between simulations using different frames of reference for a 0.1 GeV class stage. In addition, obtaining these speedups and levels of accuracy was permitted by solutions for handling data input (in particular, particle and laser beams injection) and output in a relativistically boosted frame of reference, as well as mitigation of a high-frequency instability that otherwise limits effectiveness.

  5. A Latent Class Model for Rating Data.

    ERIC Educational Resources Information Center

    Rost, Jurgen

    1985-01-01

    A latent class model for rating data is presented which provides an alternative to the latent trait approach of analyzing test data. It is the analog of Andrich's binomial Rasch model for Lazarsfeld's latent class analysis (LCA). Response probabilities for rating categories follow a binomial distribution and depend on class-specific item…

  6. Class Extraction and Classification Accuracy in Latent Class Models

    ERIC Educational Resources Information Center

    Wu, Qiong

    2009-01-01

    Despite the increasing popularity of latent class models (LCM) in educational research, methodological studies have not yet accumulated much information on the appropriate application of this modeling technique, especially with regard to requirement on sample size and number of indicators. This dissertation study represented an initial attempt to…

  7. Consequences of Fitting Nonidentified Latent Class Models

    ERIC Educational Resources Information Center

    Abar, Beau; Loken, Eric

    2012-01-01

    Latent class models are becoming more popular in behavioral research. When models with a large number of latent classes relative to the number of manifest indicators are estimated, researchers must consider the possibility that the model is not identified. It is not enough to determine that the model has positive degrees of freedom. A well-known…

  8. Bayesian variable selection for latent class models.

    PubMed

    Ghosh, Joyee; Herring, Amy H; Siega-Riz, Anna Maria

    2011-09-01

    In this article, we develop a latent class model with class probabilities that depend on subject-specific covariates. One of our major goals is to identify important predictors of latent classes. We consider methodology that allows estimation of latent classes while allowing for variable selection uncertainty. We propose a Bayesian variable selection approach and implement a stochastic search Gibbs sampler for posterior computation to obtain model-averaged estimates of quantities of interest such as marginal inclusion probabilities of predictors. Our methods are illustrated through simulation studies and application to data on weight gain during pregnancy, where it is of interest to identify important predictors of latent weight gain classes.

  9. Resonant leptogenesis in the minimal B-L extended standard model at TeV

    SciTech Connect

    Iso, Satoshi; Orikasa, Yuta; Okada, Nobuchika

    2011-05-01

    We investigate the resonant leptogenesis scenario in the minimal B-L extended standard model with the B-L symmetry breaking at the TeV scale. Through detailed analysis of the Boltzmann equations, we show how much the resultant baryon asymmetry via leptogenesis is enhanced or suppressed, depending on the model parameters, in particular, the neutrino Dirac-Yukawa couplings and the TeV scale Majorana masses of heavy degenerate neutrinos. In order to consider a realistic case, we impose a simple ansatz for the model parameters and analyze the neutrino oscillation parameters and the baryon asymmetry via leptogenesis as a function of only a single CP phase. We find that for a fixed CP phase all neutrino oscillation data and the observed baryon asymmetry of the present Universe can be simultaneously reproduced.

  10. Search for dijet resonances in proton-proton collisions at sqrt(s) = 13 TeV and constraints on dark matter and other models

    SciTech Connect

    Sirunyan, Albert M; et al.

    2016-11-10

    A search is presented for narrow resonances decaying to dijet final states in proton-proton collisions at sqrt(s)=13 TeV using data corresponding to an integrated luminosity of 12.9 inverse femtobarns. The dijet mass spectrum is well described by a smooth parameterization and no significant evidence for the production of new particles is observed. Upper limits at 95% confidence level are reported on the production cross section for narrow resonances with masses above 0.6 TeV. In the context of specific models, the limits exclude string resonances with masses below 7.4 TeV, scalar diquarks below 6.9 TeV, axigluons and colorons below 5.5 TeV, excited quarks below 5.4 TeV, color-octet ascalars below 3.0 TeV, W' bosons below 2.7 TeV, Z' bosons below 2.1 TeV and between 2.3 and 2.6 TeV, and RS gravitons below 1.9 TeV. These extend previous limits in the dijet channel. Vector and axial-vector mediators in a simplified model of interactions between quarks and dark matter are excluded below 2.0 TeV. The first limits in the dijet channel on dark matter mediators are presented as functions of dark matter mass and are compared to the exclusions of dark matter in direct detection experiments.

  11. Search for dijet resonances in proton-proton collisions at $\\sqrt{s}=$ 13 TeV and constraints on dark matter and other models

    SciTech Connect

    Sirunyan, Albert M; et al.

    2016-11-10

    A search is presented for narrow resonances decaying to dijet final states in proton-proton collisions at sqrt(s)=13 TeV using data corresponding to an integrated luminosity of 12.9 inverse femtobarns. The dijet mass spectrum is well described by a smooth parameterization and no significant evidence for the production of new particles is observed. Upper limits at 95% confidence level are reported on the production cross section for narrow resonances with masses above 0.6 TeV. In the context of specific models, the limits exclude string resonances with masses below 7.4 TeV, scalar diquarks below 6.9 TeV, axigluons and colorons below 5.5 TeV, excited quarks below 5.4 TeV, color-octet ascalars below 3.0 TeV, W' bosons below 2.7 TeV, Z' bosons below 2.1 TeV and between 2.3 and 2.6 TeV, and RS gravitons below 1.9 TeV. These extend previous limits in the dijet channel. Vector and axial-vector mediators in a simplified model of interactions between quarks and dark matter are excluded below 2.0 TeV. The first limits in the dijet channel on dark matter mediators are presented as functions of dark matter mass and are compared to the exclusions of dark matter in direct detection experiments.

  12. Java classes for nonprocedural variogram modeling

    NASA Astrophysics Data System (ADS)

    Faulkner, Barton R.

    2002-04-01

    A set of Java TM classes was written for variogram modeling to support research for US EPA's Regional Vulnerability Assessment Program (ReVA). The modeling objectives of this research program are to use conceptual programming tools for numerical analysis for regional risk assessment. The classes presented use of object-oriented design elements, and their use is described for the benefit of programmers. To help facilitate their use, class diagrams and standard JavaDoc commenting were employed. Java's support for polymorphism and inheritance is used and these are described as ways to promote extension of these classes for other geostatistical applications. Among the advantages is the ease of programming, code reuse, and conceptual, rather than procedural implementation. A graphical application for variogram modeling that uses the classes is also provided and described. It can also be used by non-programmers. This application uses a generalized least-squares fitting algorithm for robust parametric variogram model fitting through the variogram cloud. This feature makes this program unique from other freely available variogram modeling programs, though the classes are presented primarily so they may be extended for use in other Java programs. More traditional variogram plotting and fitting utilities are also provided. This application is graphical and platform-neutral. It uses classes of the recently proposed Java API for linear algebra, called the JAMA package.

  13. Variable Assessment in Latent Class Models

    PubMed Central

    Zhang, Q.; Ip, E. H.

    2014-01-01

    The latent class model provides an important platform for jointly modeling mixed-mode data — i.e., discrete and continuous data with various parametric distributions. Multiple mixed-mode variables are used to cluster subjects into latent classes. While the mixed-mode latent class analysis is a powerful tool for statisticians, few studies are focused on assessing the contribution of mixed-mode variables in discriminating latent classes. Novel measures are derived for assessing both absolute and relative impacts of mixed-mode variables in latent class analysis. Specifically, the expected posterior gradient and the Kolmogorov variation of the posterior distribution, as well as related properties are studied. Numerical results are presented to illustrate the measures. PMID:24910486

  14. Nonparametric Bayes Stochastically Ordered Latent Class Models

    PubMed Central

    Yang, Hongxia; O’Brien, Sean; Dunson, David B.

    2012-01-01

    Latent class models (LCMs) are used increasingly for addressing a broad variety of problems, including sparse modeling of multivariate and longitudinal data, model-based clustering, and flexible inferences on predictor effects. Typical frequentist LCMs require estimation of a single finite number of classes, which does not increase with the sample size, and have a well-known sensitivity to parametric assumptions on the distributions within a class. Bayesian nonparametric methods have been developed to allow an infinite number of classes in the general population, with the number represented in a sample increasing with sample size. In this article, we propose a new nonparametric Bayes model that allows predictors to flexibly impact the allocation to latent classes, while limiting sensitivity to parametric assumptions by allowing class-specific distributions to be unknown subject to a stochastic ordering constraint. An efficient MCMC algorithm is developed for posterior computation. The methods are validated using simulation studies and applied to the problem of ranking medical procedures in terms of the distribution of patient morbidity. PMID:22505787

  15. Les Houches 2015: Physics at TeV Colliders Standard Model Working Group Report

    SciTech Connect

    Andersen, J.R.; et al.

    2016-05-16

    This Report summarizes the proceedings of the 2015 Les Houches workshop on Physics at TeV Colliders. Session 1 dealt with (I) new developments relevant for high precision Standard Model calculations, (II) the new PDF4LHC parton distributions, (III) issues in the theoretical description of the production of Standard Model Higgs bosons and how to relate experimental measurements, (IV) a host of phenomenological studies essential for comparing LHC data from Run I with theoretical predictions and projections for future measurements in Run II, and (V) new developments in Monte Carlo event generators.

  16. Associated TeV Emission from the Double-Synchrotron Model for Large-Scale Quasar Jets

    NASA Astrophysics Data System (ADS)

    Whitley, Kevin Michael; Meyer, Eileen T.; Georganopoulos, Markos

    2017-01-01

    When the Chandra X-ray telescope launched, it discovered that the radio jets sometimes produced by active galactic nuclei (AGN) were anomalously bright in the X-ray band. The dominant model for explaining this X-ray emission is presently that the synchrotron-emitting electrons in the jet are Compton-scattering Cosmic Microwave Background photons (IC/CMB). This model requires highly relativistic bulk jet speeds far from the core of the AGN and a cutoff of the electron energy distribution in the jet below TeV energies. Based on recent results ruling out the IC/CMB model for anomalous X-ray jets, we consider instead that X-rays from a second electron energy distribution reaching up to TeV energies. As a mandatory process, IC/CMB emission at TeV energies will result from these jets, at a level dependent on the magnetic field and Doppler boosting factor. Using publicly available multi-wavelength observations of around three dozen anomalously X-ray bright jets, we predict the TeV gamma ray production of each jet subject to these unknowns. This will allow us to construct a catalog of potential TeV-producing active galaxies to observe with TeV telescopes currently being constructed. Such observations could be used to determine which, if either, of these two models is correct in explaining the X-ray emission of these jets.

  17. The latent class multitrait-multimethod model.

    PubMed

    Oberski, Daniel L; Hagenaars, Jacques A P; Saris, Willem E

    2015-12-01

    A latent class multitrait-multimethod (MTMM) model is proposed to estimate random and systematic measurement error in categorical survey questions while making fewer assumptions than have been made so far in such evaluations, allowing for possible extreme response behavior and other nonmonotone effects. The method is a combination of the MTMM research design of Campbell and Fiske (1959), the basic response model for survey questions of Saris and Andrews (1991), and the latent class factor model of Vermunt and Magidson (2004, pp. 227-230). The latent class MTMM model thus combines an existing design, model, and method to allow for the estimation of the degree to and manner in which survey questions are affected by systematic measurement error. Starting from a general form of the response function for a survey question, we present the MTMM experimental approach to identification of the response function's parameters. A "trait-method biplot" is introduced as a means of interpreting the estimates of systematic measurement error, whereas the quality of the questions can be evaluated by item information curves and the item information function. An experiment from the European Social Survey is analyzed and the results are discussed, yielding valuable insights into the functioning of a set of example questions on the role of women in society in 2 countries.

  18. Search for dijet resonances in proton-proton collisions at $$\\sqrt(s) = $$ 13 TeV and constraints on dark matter and other models

    DOE PAGES

    Sirunyan, Albert M.

    2017-02-14

    A search is presented for narrow resonances decaying to dijet final states in proton-proton collisions atmore » $$\\sqrt(s) = $$ 13 TeV using data corresponding to an integrated luminosity of 12.9 inverse femtobarns. The dijet mass spectrum is well described by a smooth parameterization and no significant evidence for the production of new particles is observed. Upper limits at 95% confidence level are reported on the production cross section for narrow resonances with masses above 0.6 TeV. In the context of specific models, the limits exclude string resonances with masses below 7.4 TeV, scalar diquarks below 6.9 TeV, axigluons and colorons below 5.5 TeV, excited quarks below 5.4 TeV, color-octet ascalars below 3.0 TeV, W' bosons below 2.7 TeV, Z' bosons below 2.1 TeV and between 2.3 and 2.6 TeV, and RS gravitons below 1.9 TeV. These extend previous limits in the dijet channel. Vector and axial-vector mediators in a simplified model of interactions between quarks and dark matter are excluded below 2.0 TeV. The first limits in the dijet channel on dark matter mediators are presented as functions of dark matter mass and are compared to the exclusions of dark matter in direct detection experiments.« less

  19. A Comprehensive Model of In-Class and Out-Of-Class Learning in Higher Education.

    ERIC Educational Resources Information Center

    Shaeffer, James M.; Menges, Robert J.

    A model of in-class and out-of-class learning in higher education is discussed, and the literature related to out-of-class factors and time factors in teaching-learning is reviewed. Three related models of school learning are briefly reviewed. John Carroll's model (1963) proposes that the degree of student learning is determined by the time needed…

  20. Model independent search for new phenomena in pp collisions at√s=1.96 TeV

    DOE PAGES

    Abazov, Victor Mukhamedovich; Abbott, Braden Keim; Acharya, Bannanje Sripath; ...

    2012-05-24

    We describe a model independent search for physics beyond the standard model in lepton final states. We examine 117 final states using 1.1 fb-1 of pp collisions data at √s = 1.96 TeV collected with the D0 detector. We conclude that all observed discrepancies between data and model can be attributed to uncertainties in the standard model background modeling, and hence we do not see any evidence for physics beyond the standard model.

  1. Unrestricted Mixture Models for Class Identification in Growth Mixture Modeling

    ERIC Educational Resources Information Center

    Liu, Min; Hancock, Gregory R.

    2014-01-01

    Growth mixture modeling has gained much attention in applied and methodological social science research recently, but the selection of the number of latent classes for such models remains a challenging issue, especially when the assumption of proper model specification is violated. The current simulation study compared the performance of a linear…

  2. Interaction of model class A1, class A2, and class Y amphipathic helical peptides with membranes.

    PubMed

    Mishra, V K; Palgunachari, M N

    1996-08-27

    To test the hypothesis that differences in the lipid affinity of exchangeable apolipoproteins are due to the presence of different classes of amphipathic alpha-helical motifs which differ primarily in the distribution of charged amino acid residues, we designed and synthesized model peptides mimicking class A1, class A2, and class Y amphipathic helices present in these apolipoproteins. Both class A1 and class A2 helices have positive residues at the polar-nonpolar interface and negative residues at the center of the polar face. However, clustering of positive and negative residues is less exact in class A1 compared to class A2 helices. The class Y helices have two negative residue clusters on the polar face separating the two arms and the base of the Y motif formed by three positive residue clusters. The lipid affinities of three 18 residue model peptides representing these classes, Ac-18A1-NH2 (Ac-ELLEKWAEKLAALKEALK-NH2), Ac-18A2-NH2 (Ac-ELLEKWKEALAALAEKLK-NH2), and Ac-18Y-NH2 (Ac-ELLKAWKEALEALKEKLA-NH2), were determined by right-angle light scattering, circular dichroism spectroscopy, differential scanning calorimetry, and fluorescence spectroscopy. The observed rank order of lipid affinity of these three peptides is: Ac-18A2-NH2 > Ac-18Y-NH2 > Ac-18A1-NH2. This order is consistent with the known lipid affinity of exchangeable apolipoproteins containing class A1, class A2, and class Y helices (class A2 > class Y > class A1). Results of this study illustrate the important role of interfacial lysine residues in modulating the lipid affinity of amphipathic helices and suggest that the effect of interfacial lysine residues in increasing lipid affinity is additive. We propose that interfacial lysine residues, in addition to widening the hydrophobic face because of snorkeling, also help anchor the amphipathic helix in the lipid bilayer.

  3. A class of well behaved charged superdense star models of embedding class one

    NASA Astrophysics Data System (ADS)

    Gupta, Y. K.; Kumar, Jitendra

    2011-12-01

    A class of well behaved charged superdense star models of embedding class one is obtained by taking perfect fluid to be interior matter. In the process we come across the models for white dwarf, quark and neutron stars. Maximum mass of the star of this class is found to be 6.716998 M Θ with its radius is 18.92112 Km. In the absence of charge the models reduce to Schwarzchild's interior model with constant density.

  4. Unitarity sum rules, three-site moose model, and the ATLAS 2 TeV diboson anomalies

    NASA Astrophysics Data System (ADS)

    Abe, Tomohiro; Nagai, Ryo; Okawa, Shohei; Tanabashi, Masaharu

    2015-09-01

    We investigate W' interpretations for the ATLAS 2 TeV diboson anomalies. The roles of the unitarity sum rules, which ensure the perturbativity of the longitudinal vector boson scattering amplitudes, are emphasized. We find the unitarity sum rules and the custodial symmetry are powerful enough to predict various nontrivial relations among W W Z', W Z W', W W h , W W'h and Z Z'h coupling strengths in a model independent manner. We also perform surveys in the general parameter space of W' models and find the ATLAS 2 TeV diboson anomalies may be interpreted as a W' particle of the three-site moose model, i.e., a Kaluza-Klein like particle in a deconstructed extra dimension model. It is also shown that the nonstandard-model-like Higgs boson is favored by the present data to interpret the ATLAS diboson anomalies as the consequences of the W' and Z' bosons.

  5. Les Houches Physics at TeV Colliders 2005 Beyond the Standard Model Working Group: Summary Report

    SciTech Connect

    Allanach, B.C.; Grojean, C.; Skands, P.; Accomando, E.; Azuelos, G.; Baer, H.; Balazs, C.; Belanger, G.; Benakli, K.; Boudjema, F.; Brelier, B.; Bunichev, V.; Cacciapaglia, G.; Carena, M.; Choudhury, D.; Delsart, P.-A.; De Sanctis, U.; Desch, K.; Dobrescu, B.A.; Dudko, L.; El Kacimi, M.; /Saclay, SPhT /CERN /Fermilab /INFN, Turin /Turin U. /Montreal U. /TRIUMF /Florida State U. /Argonne /Annecy, LAPTH /Paris, LPTHE /Moscow State U. /Cornell U., CIHEP /Delhi U. /Milan U. /INFN, Milan /Freiburg U. /Cadi Ayyad U., Marrakech /Orsay, LPT /Oslo U. /Lancaster U.

    2006-03-17

    The work contained herein constitutes a report of the ''Beyond the Standard Model'' working group for the Workshop ''Physics at TeV Colliders'', Les Houches, France, 2-20 May, 2005. We present reviews of current topics as well as original research carried out for the workshop. Supersymmetric and non-supersymmetric models are studied, as well as computational tools designed in order to facilitate their phenomenology.

  6. Model independent search for new phenomena in pp collisions at√s=1.96 TeV

    SciTech Connect

    Abazov, Victor Mukhamedovich; Abbott, Braden Keim; Acharya, Bannanje Sripath; Adams, Mark Raymond; Adams, Todd; Alexeev, Guennadi D; Alkhazov, Georgiy D; Alton, Andrew K; Alverson, George O; Alves, Gilvan Augusto; Aoki, Masato

    2012-05-24

    We describe a model independent search for physics beyond the standard model in lepton final states. We examine 117 final states using 1.1 fb-1 of pp collisions data at √s = 1.96 TeV collected with the D0 detector. We conclude that all observed discrepancies between data and model can be attributed to uncertainties in the standard model background modeling, and hence we do not see any evidence for physics beyond the standard model.

  7. Bianchi class A models in Sàez-Ballester's theory

    NASA Astrophysics Data System (ADS)

    Socorro, J.; Espinoza-García, Abraham

    2012-08-01

    We apply the Sàez-Ballester (SB) theory to Bianchi class A models, with a barotropic perfect fluid in a stiff matter epoch. We obtain exact classical solutions à la Hamilton for Bianchi type I, II and VIh=-1 models. We also find exact quantum solutions to all Bianchi Class A models employing a particular ansatz for the wave function of the universe.

  8. Search for physics beyond the standard model in dilepton mass spectra in proton-proton collisions at √s = 8 TeV

    SciTech Connect

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C. -E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D’Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santaolalla, J.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Genchev, V.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Zou, W.; Avila, C.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J. -L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J. -M.; Chabert, E. C.; Collard, C.; Conte, E.; Fontaine, J. -C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A. -C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Bontenackels, M.; Edelhoff, M.; Feld, L.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Perieanu, A.; Raupach, F.; Sammet, J.; Schael, S.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Pook, T.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Weber, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Heister, A.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Perchalla, L.; Pooth, O.; Stahl, A.; Asin, I.; Bartosik, N.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bell, A. J.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Horton, D.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I. -A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Mozer, M. U.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Modak, A.; Mukherjee, S.; Roy, D.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Barbone, L.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Zito, G.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D’Alessandro, R.; Focardi, E.; Gallo, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Ferretti, R.; Ferro, F.; Lo Vetere, M.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall’Osso, M.; Dorigo, T.; Dosselli, U.; Galanti, M.; Gasparini, F.; Gasparini, U.; Giubilato, P.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell’Orso, R.; Donato, S.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Moon, C. S.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Vernieri, C.; Barone, L.; Cavallari, F.; D’imperio, G.; Del Re, D.; Diemoz, M.; Grassi, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Casasso, S.; Costa, M.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, T. J.; Kim, J. Y.; Song, S.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K. S.; Park, S. K.; Roh, Y.; Yoo, H. D.; Choi, M.; Kim, J. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Ali, M. A. B. Md; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Casimiro Linares, E.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khalid, S.; Khan, W. A.; Khurshid, T.; Shah, M. A.; Shoaib, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Wolszczak, W.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Konoplyanikov, V.; Kozlov, G.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Vorobyev, An.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Safronov, G.; Semenov, S.; Spiridonov, A.; Stolin, V.; Vlasov, E.; Zhokin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; Snigirev, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Bernet, C.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D’Alfonso, M.; d’Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dorney, B.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Musella, P.; Orsini, L.; Pape, L.; Perez, E.; Perrozzi, L.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W. -S.; Kao, K. Y.; Lei, Y. J.; Liu, Y. F.; Lu, R. -S.; Majumder, D.; Petrakou, E.; Tzeng, Y. M.; Wilken, R.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Isildak, B.; Kaya, M.; Kaya, O.; Cankocak, K.; Vardarlı, F. I.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Senkin, S.; Smith, V. J.; Williams, T.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Gilbert, A.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A. -M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; John, J. St.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Nguyen, H.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Andrews, W.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D’Agnolo, R. T.; Evans, D.; Holzner, A.; Kelley, R.; Klein, D.; Lebourgeois, M.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Skinnari, L.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O’Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Cheng, T.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O’Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J. -P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y. -J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R. -J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Sakuma, T.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.

    2015-04-07

    Dimuon and dielectron mass spectra, obtained from data resulting from proton-proton collisions at 8 TeV and recorded by the CMS experiment, are used to search for both narrow resonances and broad deviations from standard model predictions. The data correspond to an integrated luminosity of 20.6 (19.7) fb–1 for the dimuon (dielectron) channel. No evidence for non-standard-model physics is observed and 95% confidence level limits are set on parameters from a number of new physics models. The narrow resonance analyses exclude a Sequential Standard Model Z SSM ' resonance lighter than 2.90 TeV, a superstring-inspired Z ψ ' lighter than 2.57 TeV, and Randall-Sundrum Kaluza-Klein gravitons with masses below 2.73, 2.35, and 1.27 TeV for couplings of 0.10, 0.05, and 0.01, respectively. A notable feature is that the limits have been calculated in a model-independent way to enable straightforward reinterpretation in any model predicting a resonance structure. The observed events are also interpreted within the framework of two non-resonant analyses: one based on a large extra dimensions model and one based on a quark and lepton compositeness model with a left-left isoscalar contact interaction. Lower limits are established on MS, the scale characterizing the onset of quantum gravity, which range from 4.9 to 3.3 TeV, where the number of additional spatial dimensions varies from 3 to 7. Thus lower limits on Λ, the energy scale parameter for the contact interaction, are found to be 12.0 (15.2) TeV for destructive (constructive) interference in the dimuon channel and 13.5 (18.3) TeV in the dielectron channel.

  9. Search for physics beyond the standard model in dilepton mass spectra in proton-proton collisions at √s = 8 TeV

    DOE PAGES

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; ...

    2015-04-07

    Dimuon and dielectron mass spectra, obtained from data resulting from proton-proton collisions at 8 TeV and recorded by the CMS experiment, are used to search for both narrow resonances and broad deviations from standard model predictions. The data correspond to an integrated luminosity of 20.6 (19.7) fb–1 for the dimuon (dielectron) channel. No evidence for non-standard-model physics is observed and 95% confidence level limits are set on parameters from a number of new physics models. The narrow resonance analyses exclude a Sequential Standard Model Z SSM ' resonance lighter than 2.90 TeV, a superstring-inspired Z ψ ' lighter than 2.57more » TeV, and Randall-Sundrum Kaluza-Klein gravitons with masses below 2.73, 2.35, and 1.27 TeV for couplings of 0.10, 0.05, and 0.01, respectively. A notable feature is that the limits have been calculated in a model-independent way to enable straightforward reinterpretation in any model predicting a resonance structure. The observed events are also interpreted within the framework of two non-resonant analyses: one based on a large extra dimensions model and one based on a quark and lepton compositeness model with a left-left isoscalar contact interaction. Lower limits are established on MS, the scale characterizing the onset of quantum gravity, which range from 4.9 to 3.3 TeV, where the number of additional spatial dimensions varies from 3 to 7. Thus lower limits on Λ, the energy scale parameter for the contact interaction, are found to be 12.0 (15.2) TeV for destructive (constructive) interference in the dimuon channel and 13.5 (18.3) TeV in the dielectron channel.« less

  10. Decelerating Flows in the TeV Blazars

    NASA Technical Reports Server (NTRS)

    Kazanas, Demosthenes

    2004-01-01

    TeV emission from a class of BL Lacertae (BL) objects is commonly modeled as radiation from relativistically moving homogeneous plasma blobs. In the context of these models, the blob Lorentz factors needed to reproduce the (corrected for absorption by the IR background) TeV emission are large ($\\delta \\gtrsim 50$) are required to reproduce via Synchrotron-Self Compton (SSC) the observed TeV emission. The main reason for this is that stronger beaming eases the problem of the lack of $\\sim$ IR-UV synchrotron seed photons needed to produce the de-absorbed $\\sim$ few TeV peak of the spectral energy distribution (SED). However, such high Doppler factors are in strong disagreement with the unified scheme, according to which BLs are FR I radio galaxies with their jets closely aligned to the line of sight. Here, motivated by the detection of sub-luminal velocities in the sub-pc scale jets of the best studied TeV blazars, MKN 421 and MKN 501. we examine the possibility that the relativistic flow in the TeV BLs is longitudinally decelerating. In this case, the problem of the missing seed photons is solved due to Upstream Compton (UC) scattering, a process in which the upstream energetic electrons from the fast base of the flow 'see' the synchrotron seed photons produced in the slow part of the flow relativistically beamed. Modest Lorentz factors ($\\Gamma kim 15s). decelerating down to values compatible with the recent radio interferometric observations, reproduce the $\\sim$ few TeV peak energy of these sources. Furthermore, such decelerating flows are shown to be in agreement with the BL - FR I unification.

  11. A dynamic trajectory class model for intensive longitudinal categorical outcome.

    PubMed

    Lin, Haiqun; Han, Ling; Peduzzi, Peter N; Murphy, Terrence E; Gill, Thomas M; Allore, Heather G

    2014-07-10

    This paper presents a novel dynamic latent class model for a longitudinal response that is frequently measured as in our prospective study of older adults with monthly data on activities of daily living for more than 10 years. The proposed method is especially useful when the longitudinal response is measured much more frequently than other relevant covariates. The trajectory classes are latent classes that represent distinct temporal patterns of the longitudinal response wherein an individual may remain in a trajectory class or switch to another as the class membership predictors are updated periodically over time. The identification of a common set of trajectory classes allows changes among the temporal patterns to be distinguished from local fluctuations in the response. Within a trajectory class, the longitudinal response is modeled by a class-specific generalized linear mixed model. An informative event such as death is jointly modeled by class-specific probability of the event through shared random effects with that for the longitudinal response. We do not impose the conditional independence assumption given the classes. We illustrate the method by analyzing the change over time in activities of daily living trajectory class among 754 older adults with 70,500 person-months of follow-up in the Precipitating Events Project. We also investigate the impact of jointly modeling the class-specific probability of the event on the parameter estimates in a simulation study. The primary contribution of our paper is the periodic updating of trajectory classes for a longitudinal categorical response without assuming conditional independence.

  12. Some classes of renormalizable tensor models

    NASA Astrophysics Data System (ADS)

    Geloun, Joseph Ben; Livine, Etera R.

    2013-08-01

    We identify new families of renormalizable tensor models from anterior renormalizable tensor models via a mapping capable of reducing or increasing the rank of the theory without having an effect on the renormalizability property. Mainly, a version of the rank 3 tensor model as defined by Ben Geloun and Samary [Ann. Henri Poincare 14, 1599 (2013); e-print arXiv:1201.0176 [hep-th

  13. Simulation Modeling of a Facility Layout in Operations Management Classes

    ERIC Educational Resources Information Center

    Yazici, Hulya Julie

    2006-01-01

    Teaching quantitative courses can be challenging. Similarly, layout modeling and lean production concepts can be difficult to grasp in an introductory OM (operations management) class. This article describes a simulation model developed in PROMODEL to facilitate the learning of layout modeling and lean manufacturing. Simulation allows for the…

  14. Class Ranking Models for Deans' Letters and Their Psychometric Evaluation.

    ERIC Educational Resources Information Center

    Blacklow, Robert S.; And Others

    1991-01-01

    A study developed and evaluated five class ranking models for graduating medical students (n=1,283) in which performance data from both basic and clinical sciences could be used to study the models' predictive validity. Two models yielded higher validity; one is recommended for balance of clinical and basic science measures. (MSE)

  15. Universality classes for models of inflation

    SciTech Connect

    Binétruy, P.; Kiritsis, E.; Mabillard, J.; Pieroni, M.; Rosset, C. E-mail: mpieroni@apc.univ-paris7.fr

    2015-04-01

    We show that the cosmological evolution of a scalar field in a potential can be obtained from a renormalisation group equation. The slow roll regime of inflation models is understood in this context as the slow evolution close to a fixed point, described by the methods of renormalisation group. This explains in part the universality observed in the predictions of a certain number of inflation models. We illustrate this behavior on a certain number of examples and discuss it in the context of the AdS/CFT correspondence.

  16. Credibility analysis of risk classes by generalized linear model

    NASA Astrophysics Data System (ADS)

    Erdemir, Ovgucan Karadag; Sucu, Meral

    2016-06-01

    In this paper generalized linear model (GLM) and credibility theory which are frequently used in nonlife insurance pricing are combined for reliability analysis. Using full credibility standard, GLM is associated with limited fluctuation credibility approach. Comparison criteria such as asymptotic variance and credibility probability are used to analyze the credibility of risk classes. An application is performed by using one-year claim frequency data of a Turkish insurance company and results of credible risk classes are interpreted.

  17. Searches for physics beyond the standard model in proton-proton interactions at {radical}s = 7 TeV in the CMS experiment at the LHC

    SciTech Connect

    Shmatov, S. V.

    2013-09-15

    The results obtained in the CMS experiment at the LHC from searches for various physics phenomena beyond the Standard Model in proton-proton interactions at the c.m. energy of 7 TeV are presented. The respective analysis is based on data measured in the CMS experiment over the period spanning 2010 and 2011.

  18. An approximation formula for a class of Markov reliability models

    NASA Technical Reports Server (NTRS)

    White, A. L.

    1984-01-01

    A way of considering a small but often used class of reliability model and approximating algebraically the systems reliability is shown. The models considered are appropriate for redundant reconfigurable digital control systems that operate for a short period of time without maintenance, and for such systems the method gives a formula in terms of component fault rates, system recovery rates, and system operating time.

  19. Teaching Service Modelling to a Mixed Class: An Integrated Approach

    ERIC Educational Resources Information Center

    Deng, Jeremiah D.; Purvis, Martin K.

    2015-01-01

    Service modelling has become an increasingly important area in today's telecommunications and information systems practice. We have adapted a Network Design course in order to teach service modelling to a mixed class of both the telecommunication engineering and information systems backgrounds. An integrated approach engaging mathematics teaching…

  20. Spurious Latent Classes in the Mixture Rasch Model

    ERIC Educational Resources Information Center

    Alexeev, Natalia; Templin, Jonathan; Cohen, Allan S.

    2011-01-01

    Mixture Rasch models have been used to study a number of psychometric issues such as goodness of fit, response strategy differences, strategy shifts, and multidimensionality. Although these models offer the potential for improving understanding of the latent variables being measured, under some conditions overextraction of latent classes may…

  1. Muon capture in a general class of weak models

    NASA Astrophysics Data System (ADS)

    Botella, F. J.

    1985-10-01

    We study muon capture by 12C in a general class of weak models. There is always a parameter characteristic of the weak model that can be extracted in a nuclear-model-independent way from the average polarization Pav, the longitudinal polarization PNL and the asymmetry α in the angular distribution of recoils. For a less general class of models the asymmetry α is unnecessary. Using the experimental values of PNL and Pav we get a lower bound for the mass of the right-handed gauge boson of the left-right-symmetric model, MWR>=2.5MWL, in a nuclear-model-independent way. The dependence of this bound on the experimental values is also discussed.

  2. Identifiability Results for Several Classes of Linear Compartment Models.

    PubMed

    Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa

    2015-08-01

    Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology.

  3. Universality class of the conserved Manna model in one dimension

    NASA Astrophysics Data System (ADS)

    Lee, Sang Bub

    2014-06-01

    The nonequilibrium absorbing phase transition of the discrete conserved Manna model was studied via Monte Carlo simulations on a one-dimensional chain, using the natural initial states with a sequential update. The critical density of the particles was found to be smaller than the recently reported value, and the order-parameter exponent was considerably different from the directed percolation (DP) value. The influence of quenched disorder was also studied on a diluted strip of Lx×Ly lattice sites with Lx≫Ly, and the results were compared with those of the contact process (CP). It was found that the Manna model and the CP exhibited distinctly different behaviors; the CP exhibited nonuniversal power-law decreases of active-site densities in the Griffith phase, whereas the Manna model showed a standard critical behavior. These results consistently suggest that the Manna model belongs to a universality class that is different from the DP class.

  4. A model for a multi-class classification machine

    NASA Astrophysics Data System (ADS)

    Rau, Albrecht; Nadal, Jean-Pierre

    1992-06-01

    We consider the properties of multi-class neural networks, where each neuron can be in several different states. The motivations for considering such systems are manifold. In image processing for example, the different states correspond to the different grey tone levels. Another multi-class classification task implemented on a feed-forward network is the analysis of DNA sequences or the prediction of the secondary structure of proteins from the sequence of amino acids. To investigate the behaviour of such systems, one specific dynamical rule - the “winner-take-all” rule - is studied. Gauge invariances of the model are analysed. For a multi-class perceptron with N Q-state input neurons and Q‧-state output neuron, the maximal number of patterns that can be stored in the large N limit is found to be proportional to N(Q - 1) ƒ(Q‧), where ƒ( Q‧) is a slowly increasing and bounded function of order 1.

  5. Search for Heavy Neutrinos and WR Bosons with Right-Handed Couplings in a Left-Right Symmetric Model in pp Collisions at s=7TeV

    NASA Astrophysics Data System (ADS)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Aguilo, E.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hammer, J.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Pernicka, M.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Reis, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Castello, R.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins Junior, M.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Malek, M.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Soares Jorge, L.; Sznajder, A.; Vilela Pereira, A.; Anjos, T. S.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, D.; Zhang, L.; Zou, W.; Avila, C.; Gomez, J. P.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Mekterovic, D.; Morovic, S.; Attikis, A.; Galanti, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M., Jr.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Khalil, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Müntel, M.; Raidal, M.; Rebane, L.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Heikkinen, A.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Ungaro, D.; Wendland, L.; Banzuzi, K.; Karjalainen, A.; Korpela, A.; Tuuva, T.; Besancon, M.; Choudhury, S.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Millischer, L.; Nayak, A.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Benhabib, L.; Bianchini, L.; Bluj, M.; Broutin, C.; Busson, P.; Charlot, C.; Daci, N.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Florent, A.; Granier de Cassagnac, R.; Haguenauer, M.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Sabes, D.; Salerno, R.; Sirois, Y.; Veelken, C.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Bodin, D.; Brom, J.-M.; Cardaci, M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Juillot, P.; Le Bihan, A.-C.; Van Hove, P.; Fassi, F.; Mercier, D.; Beauceron, S.; Beaupere, N.; Bondu, O.; Boudoul, G.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Sgandurra, L.; Sordini, V.; Tschudi, Y.; Verdier, P.; Viret, S.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Calpas, B.; Edelhoff, M.; Feld, L.; Heracleous, N.; Hindrichs, O.; Jussen, R.; Klein, K.; Merz, J.

    2012-12-01

    Results are presented from a search for heavy, right-handed muon neutrinos, Nμ, and right-handed WR bosons, which arise in the left-right symmetric extensions of the standard model. The analysis is based on a 5.0fb-1 sample of proton-proton collisions at a center-of-mass energy of 7 TeV, collected by the CMS detector at the Large Hadron Collider. No evidence is observed for an excess of events over the standard model expectation. For models with exact left-right symmetry, heavy right-handed neutrinos are excluded at 95% confidence level for a range of neutrino masses below the WR mass, dependent on the value of MWR. The excluded region in the two-dimensional (MWR, MNμ) mass plane extends to MWR=2.5TeV.

  6. Analysis of SPI drought class transitions using loglinear models

    NASA Astrophysics Data System (ADS)

    Moreira, Elsa E.; Paulo, Ana A.; Pereira, Luís S.; Mexia, João T.

    2006-11-01

    SummaryA total period of 67 years of standardized precipitation index (SPI) data sets were divided into three periods of 22/23 years and a loglinear modeling approach has been used to investigate differences relative to drought class transitions among these three periods. The study was applied to several locations in Alentejo region, southern Portugal, and four drought severity classes were considered. The drought class transitions were computed for the three periods to form a 3-dimensional contingency table. The application of loglinear modeling to these data allowed the comparison of the three periods in terms of probabilities of transition between drought classes in order to detect a possible trend in time evolution of droughts which could be related to climate change. Results show that the drought behavior for the first and last periods is similar, both showing worse drought events than the second. If just the second and third periods were compared one could conclude that droughts were aggravating and easily this behavior could be attributed to climate change, supporting the common assumption that a trend for progressive aggravation of drought occurrence exists. Therefore, results are more consistent with the existence of a long-term natural periodicity; however, this hypothesis should be tested using longer time series.

  7. Two classes of ODE models with switch-like behavior

    PubMed Central

    Just, Winfried; Korb, Mason; Elbert, Ben; Young, Todd

    2013-01-01

    In cases where the same real-world system can be modeled both by an ODE system ⅅ and a Boolean system 𝔹, it is of interest to identify conditions under which the two systems will be consistent, that is, will make qualitatively equivalent predictions. In this note we introduce two broad classes of relatively simple models that provide a convenient framework for studying such questions. In contrast to the widely known class of Glass networks, the right-hand sides of our ODEs are Lipschitz-continuous. We prove that if 𝔹 has certain structures, consistency between ⅅ and 𝔹 is implied by sufficient separation of time scales in one class of our models. Namely, if the trajectories of 𝔹 are “one-stepping” then we prove a strong form of consistency and if 𝔹 has a certain monotonicity property then there is a weaker consistency between ⅅ and 𝔹. These results appear to point to more general structure properties that favor consistency between ODE and Boolean models. PMID:24244061

  8. Latent class model characterization of neighborhood socioeconomic status

    PubMed Central

    Michael, Yvonne; Hyslop, Terry

    2016-01-01

    Purpose Neighborhood-level socioeconomic status (NSES) can influence breast cancer mortality and poorer health outcomes are observed in deprived neighborhoods. Commonly used NSES indexes are difficult to interpret. Latent class models allow for alternative characterization of NSES for use in studies of cancer causes and control. Methods Breast cancer data was from a cohort of women diagnosed at an academic medical center in Philadelphia, PA. NSES variables were defined using Census data. Latent class modeling was used to characterize NSES. Results Complete data was available for 1,664 breast cancer patients diagnosed between 1994 and 2002. Two separate latent variables, each with 2-classes (LC2) best represented NSES. LC2 demonstrated strong associations with race and tumor stage and size. Conclusions Latent variable models identified specific characteristics associated with advantaged or disadvantaged neighborhoods, potentially improving our understanding of the impact of socioeconomic influence on breast cancer prognosis. Improved classification will enhance our ability to identify vulnerable populations and prioritize the targeting of cancer control efforts. PMID:26797452

  9. An Agent Based Model for Social Class Emergence

    NASA Astrophysics Data System (ADS)

    Yang, Xiaoxiang; Rodriguez Segura, Daniel; Lin, Fei; Mazilu, Irina

    We present an open system agent-based model to analyze the effects of education and the society-specific wealth transactions on the emergence of social classes. Building on previous studies, we use realistic functions to model how years of education affect the income level. Numerical simulations show that the fraction of an individual's total transactions that is invested rather than consumed can cause wealth gaps between different income brackets in the long run. In an attempt to incorporate the network effects, we also explore how the probability of interactions among agents depending on the spread of their income brackets affects wealth distribution.

  10. Sloppy-model universality class and the Vandermonde matrix.

    PubMed

    Waterfall, Joshua J; Casey, Fergal P; Gutenkunst, Ryan N; Brown, Kevin S; Myers, Christopher R; Brouwer, Piet W; Elser, Veit; Sethna, James P

    2006-10-13

    In a variety of contexts, physicists study complex, nonlinear models with many unknown or tunable parameters to explain experimental data. We explain why such systems so often are sloppy: the system behavior depends only on a few "stiff" combinations of the parameters and is unchanged as other "sloppy" parameter combinations vary by orders of magnitude. We observe that the eigenvalue spectra for the sensitivity of sloppy models have a striking, characteristic form with a density of logarithms of eigenvalues which is roughly constant over a large range. We suggest that the common features of sloppy models indicate that they may belong to a common universality class. In particular, we motivate focusing on a Vandermonde ensemble of multiparameter nonlinear models and show in one limit that they exhibit the universal features of sloppy models.

  11. Poverty and Depression among Men: The Social Class Worldview Model and Counseling Implications.

    ERIC Educational Resources Information Center

    Liu, William M.

    This paper outlines a theory for understanding social class in men's lives, and argues that poverty and depression are a function of social class and internalized classism. It begins by defining poverty, then explains the Social Class Worldview Model, which is a subjective social class model, and the Modern Classism Theory, which allows clinicians…

  12. Evaluation of Structural Equation Mixture Models: Parameter Estimates and Correct Class Assignment

    ERIC Educational Resources Information Center

    Tueller, Stephen; Lubke, Gitta

    2010-01-01

    Structural equation mixture models (SEMMs) are latent class models that permit the estimation of a structural equation model within each class. Fitting SEMMs is illustrated using data from 1 wave of the Notre Dame Longitudinal Study of Aging. Based on the model used in the illustration, SEMM parameter estimation and correct class assignment are…

  13. X-ray variability and prediction of TeV emission in the HBL 1ES 1101-232

    NASA Astrophysics Data System (ADS)

    Wolter, A.; Tavecchio, F.; Caccianiga, A.; Ghisellini, G.; Tagliaferri, G.

    2000-05-01

    1ES 1101-232 is a bright BL Lac of the High frequency peak class. We present here the results of two BeppoSAX observations in which the source has shown a variation of about 30% in flux with a corresponding spectral variability. We interpret the overall spectral energy distribution in terms of an homogeneous SSC model and, by using also the TeV upper limit from a short Mark 6 pointing, derive constraints on the physical parameters of the source, in particular on the magnetic field strength. The overall Spectral Energy Distribution makes 1ES 1101-232 a very promising candidate for TeV detection.

  14. Regression mixture models: Does modeling the covariance between independent variables and latent classes improve the results?

    PubMed Central

    Lamont, Andrea E.; Vermunt, Jeroen K.; Van Horn, M. Lee

    2016-01-01

    Regression mixture models are increasingly used as an exploratory approach to identify heterogeneity in the effects of a predictor on an outcome. In this simulation study, we test the effects of violating an implicit assumption often made in these models – i.e., independent variables in the model are not directly related to latent classes. Results indicated that the major risk of failing to model the relationship between predictor and latent class was an increase in the probability of selecting additional latent classes and biased class proportions. Additionally, this study tests whether regression mixture models can detect a piecewise relationship between a predictor and outcome. Results suggest that these models are able to detect piecewise relations, but only when the relationship between the latent class and the predictor is included in model estimation. We illustrate the implications of making this assumption through a re-analysis of applied data examining heterogeneity in the effects of family resources on academic achievement. We compare previous results (which assumed no relation between independent variables and latent class) to the model where this assumption is lifted. Implications and analytic suggestions for conducting regression mixture based on these findings are noted. PMID:26881956

  15. Regression Mixture Models: Does Modeling the Covariance Between Independent Variables and Latent Classes Improve the Results?

    PubMed

    Lamont, Andrea E; Vermunt, Jeroen K; Van Horn, M Lee

    2016-01-01

    Regression mixture models are increasingly used as an exploratory approach to identify heterogeneity in the effects of a predictor on an outcome. In this simulation study, we tested the effects of violating an implicit assumption often made in these models; that is, independent variables in the model are not directly related to latent classes. Results indicate that the major risk of failing to model the relationship between predictor and latent class was an increase in the probability of selecting additional latent classes and biased class proportions. In addition, we tested whether regression mixture models can detect a piecewise relationship between a predictor and outcome. Results suggest that these models are able to detect piecewise relations but only when the relationship between the latent class and the predictor is included in model estimation. We illustrate the implications of making this assumption through a reanalysis of applied data examining heterogeneity in the effects of family resources on academic achievement. We compare previous results (which assumed no relation between independent variables and latent class) to the model where this assumption is lifted. Implications and analytic suggestions for conducting regression mixture based on these findings are noted.

  16. Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study

    ERIC Educational Resources Information Center

    Nylund, Karen L.; Asparouhov, Tihomir; Muthen, Bengt O.

    2007-01-01

    Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study…

  17. On the General Class of Models of Adiabatic Evolution

    NASA Astrophysics Data System (ADS)

    Sun, Jie; Lu, Songfeng; Liu, Fang

    2016-10-01

    The general class of models of adiabatic evolution was proposed to speed up the usual adiabatic computation in the case of quantum search problem. It was shown [8] that, by temporarily increasing the ground state energy of a time-dependent Hamiltonian to a suitable quantity, the quantum computation can perform the calculation in time complexity O(1). But it is also known that if the overlap between the initial and final states of the system is zero, then the computation based on the generalized models of adiabatic evolution can break down completely. In this paper, we find another severe limitation for this class of adiabatic evolution-based algorithms, which should be taken into account in applications. That is, it is still possible that this kind of evolution designed to deal with the quantum search problem fails completely if the interpolating paths in the system Hamiltonian are chosen inappropriately, while the usual adiabatic evolutions can do the same job relatively effectively. This implies that it is not always recommendable to use nonlinear paths in adiabatic computation. On the contrary, the usual simple adiabatic evolution may be sufficient for effective use.

  18. Latent Class Analysis with Distal Outcomes: A Flexible Model-Based Approach

    ERIC Educational Resources Information Center

    Lanza, Stephanie T.; Tan, Xianming; Bray, Bethany C.

    2013-01-01

    Although prediction of class membership from observed variables in latent class analysis is well understood, predicting an observed distal outcome from latent class membership is more complicated. A flexible model-based approach is proposed to empirically derive and summarize the class-dependent density functions of distal outcomes with…

  19. Search for a standard model Higgs boson in WH --> lvbb in pp collisions at square root s = 1.96 TeV.

    PubMed

    Aaltonen, T; Adelman, J; Akimoto, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burke, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cordelli, M; Cortiana, G; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heijboer, A; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Hussein, M; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, H S; Lee, S W; Leone, S; Lewis, J D; Lin, C-S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lucchesi, D; Luci, C; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Würthwein, F; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zhang, X; Zheng, Y; Zucchelli, S

    2009-09-04

    We present a search for a standard model Higgs boson produced in association with a W boson using 2.7 fb(-1) of integrated luminosity of pp collision data taken at square root s = 1.96 TeV. Limits on the Higgs boson production rate are obtained for masses between 100 and 150 GeV/c(2). Through the use of multivariate techniques, the analysis achieves an observed (expected) 95% confidence level upper limit of 5.6 (4.8) times the theoretically expected production cross section for a standard model Higgs boson with a mass of 115 GeV/c(2).

  20. Search for a Standard Model Higgs Boson in WH→ℓvb bmacr in p pmacr Collisions at s=1.96TeV

    NASA Astrophysics Data System (ADS)

    Aaltonen, T.; Adelman, J.; Akimoto, T.; Álvarez González, B.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Apresyan, A.; Arisawa, T.; Artikov, A.; Ashmanskas, W.; Attal, A.; Aurisano, A.; Azfar, F.; Azzurri, P.; Badgett, W.; Barbaro-Galtieri, A.; Barnes, V. E.; Barnett, B. A.; Bartsch, V.; Bauer, G.; Beauchemin, P.-H.; Bedeschi, F.; Beecher, D.; Behari, S.; Bellettini, G.; Bellinger, J.; Benjamin, D.; Beretvas, A.; Beringer, J.; Bhatti, A.; Binkley, M.; Bisello, D.; Bizjak, I.; Blair, R. E.; Blocker, C.; Blumenfeld, B.; Bocci, A.; Bodek, A.; Boisvert, V.; Bolla, G.; Bortoletto, D.; Boudreau, J.; Boveia, A.; Brau, B.; Bridgeman, A.; Brigliadori, L.; Bromberg, C.; Brubaker, E.; Budagov, J.; Budd, H. S.; Budd, S.; Burke, S.; Burkett, K.; Busetto, G.; Bussey, P.; Buzatu, A.; Byrum, K. L.; Cabrera, S.; Calancha, C.; Campanelli, M.; Campbell, M.; Canelli, F.; Canepa, A.; Carls, B.; Carlsmith, D.; Carosi, R.; Carrillo, S.; Carron, S.; Casal, B.; Casarsa, M.; Castro, A.; Catastini, P.; Cauz, D.; Cavaliere, V.; Cavalli-Sforza, M.; Cerri, A.; Cerrito, L.; Chang, S. H.; Chen, Y. C.; Chertok, M.; Chiarelli, G.; Chlachidze, G.; Chlebana, F.; Cho, K.; Chokheli, D.; Chou, J. P.; Choudalakis, G.; Chuang, S. H.; Chung, K.; Chung, W. H.; Chung, Y. S.; Chwalek, T.; Ciobanu, C. I.; Ciocci, M. A.; Clark, A.; Clark, D.; Compostella, G.; Convery, M. E.; Conway, J.; Cordelli, M.; Cortiana, G.; Cox, C. A.; Cox, D. J.; Crescioli, F.; Cuenca Almenar, C.; Cuevas, J.; Culbertson, R.; Cully, J. C.; Dagenhart, D.; Datta, M.; Davies, T.; de Barbaro, P.; de Cecco, S.; Deisher, A.; de Lorenzo, G.; Dell'Orso, M.; Deluca, C.; Demortier, L.; Deng, J.; Deninno, M.; Derwent, P. F.; di Giovanni, G. P.; Dionisi, C.; di Ruzza, B.; Dittmann, J. R.; D'Onofrio, M.; Donati, S.; Dong, P.; Donini, J.; Dorigo, T.; Dube, S.; Efron, J.; Elagin, A.; Erbacher, R.; Errede, D.; Errede, S.; Eusebi, R.; Fang, H. C.; Farrington, S.; Fedorko, W. T.; Feild, R. G.; Feindt, M.; Fernandez, J. P.; Ferrazza, C.; Field, R.; Flanagan, G.; Forrest, R.; Frank, M. J.; Franklin, M.; Freeman, J. C.; Furic, I.; Gallinaro, M.; Galyardt, J.; Garberson, F.; Garcia, J. E.; Garfinkel, A. F.; Genser, K.; Gerberich, H.; Gerdes, D.; Gessler, A.; Giagu, S.; Giakoumopoulou, V.; Giannetti, P.; Gibson, K.; Gimmell, J. L.; Ginsburg, C. M.; Giokaris, N.; Giordani, M.; Giromini, P.; Giunta, M.; Giurgiu, G.; Glagolev, V.; Glenzinski, D.; Gold, M.; Goldschmidt, N.; Golossanov, A.; Gomez, G.; Gomez-Ceballos, G.; Goncharov, M.; González, O.; Gorelov, I.; Goshaw, A. T.; Goulianos, K.; Gresele, A.; Grinstein, S.; Grosso-Pilcher, C.; Group, R. C.; Grundler, U.; Guimaraes da Costa, J.; Gunay-Unalan, Z.; Haber, C.; Hahn, K.; Hahn, S. R.; Halkiadakis, E.; Han, B.-Y.; Han, J. Y.; Happacher, F.; Hara, K.; Hare, D.; Hare, M.; Harper, S.; Harr, R. F.; Harris, R. M.; Hartz, M.; Hatakeyama, K.; Hays, C.; Heck, M.; Heijboer, A.; Heinrich, J.; Henderson, C.; Herndon, M.; Heuser, J.; Hewamanage, S.; Hidas, D.; Hill, C. S.; Hirschbuehl, D.; Hocker, A.; Hou, S.; Houlden, M.; Hsu, S.-C.; Huffman, B. T.; Hughes, R. E.; Husemann, U.; Hussein, M.; Husemann, U.; Huston, J.; Incandela, J.; Introzzi, G.; Iori, M.; Ivanov, A.; James, E.; Jayatilaka, B.; Jeon, E. J.; Jha, M. K.; Jindariani, S.; Johnson, W.; Jones, M.; Joo, K. K.; Jun, S. Y.; Jung, J. E.; Junk, T. R.; Kamon, T.; Kar, D.; Karchin, P. E.; Kato, Y.; Kephart, R.; Keung, J.; Khotilovich, V.; Kilminster, B.; Kim, D. H.; Kim, H. S.; Kim, H. W.; Kim, J. E.; Kim, M. J.; Kim, S. B.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kirsch, L.; Klimenko, S.; Knuteson, B.; Ko, B. R.; Kondo, K.; Kong, D. J.; Konigsberg, J.; Korytov, A.; Kotwal, A. V.; Kreps, M.; Kroll, J.; Krop, D.; Krumnack, N.; Kruse, M.; Krutelyov, V.; Kubo, T.; Kuhr, T.; Kulkarni, N. P.; Kurata, M.; Kwang, S.; Laasanen, A. T.; Lami, S.; Lammel, S.; Lancaster, M.; Lander, R. L.; Lannon, K.; Lath, A.; Latino, G.; Lazzizzera, I.; Lecompte, T.; Lee, E.; Lee, H. S.; Lee, S. W.; Leone, S.; Lewis, J. D.; Lin, C.-S.; Linacre, J.; Lindgren, M.; Lipeles, E.; Lister, A.; Litvintsev, D. O.; Liu, C.; Liu, T.; Lockyer, N. S.; Loginov, A.; Loreti, M.; Lovas, L.; Lucchesi, D.; Luci, C.; Lueck, J.; Lujan, P.; Lukens, P.; Lungu, G.; Lyons, L.; Lys, J.; Lysak, R.; MacQueen, D.; Madrak, R.; Maeshima, K.; Makhoul, K.; Maki, T.; Maksimovic, P.; Malde, S.; Malik, S.; Manca, G.; Manousakis-Katsikakis, A.; Margaroli, F.; Marino, C.; Marino, C. P.; Martin, A.; Martin, V.; Martínez, M.; Martínez-Ballarín, R.; Maruyama, T.; Mastrandrea, P.; Masubuchi, T.; Mathis, M.; Mattson, M. E.; Mazzanti, P.; McFarland, K. S.; McIntyre, P.; McNulty, R.; Mehta, A.; Mehtala, P.; Menzione, A.; Merkel, P.; Mesropian, C.; Miao, T.; Miladinovic, N.; Miller, R.; Mills, C.; Milnik, M.; Mitra, A.; Mitselmakher, G.; Miyake, H.; Moggi, N.; Moon, C. S.; Moore, R.; Morello, M. J.; Morlock, J.; Movilla Fernandez, P.; Mülmenstädt, J.; Mukherjee, A.; Muller, Th.; Mumford, R.; Murat, P.; Mussini, M.; Nachtman, J.; Nagai, Y.; Nagano, A.; Naganoma, J.; Nakamura, K.; Nakano, I.; Napier, A.; Necula, V.; Nett, J.; Neu, C.; Neubauer, M. S.; Neubauer, S.; Nielsen, J.; Nodulman, L.; Norman, M.; Norniella, O.; Nurse, E.; Oakes, L.; Oh, S. H.; Oh, Y. D.; Oksuzian, I.; Okusawa, T.; Orava, R.; Osterberg, K.; Pagan Griso, S.; Palencia, E.; Papadimitriou, V.; Papaikonomou, A.; Paramonov, A. A.; Parks, B.; Pashapour, S.; Patrick, J.; Pauletta, G.; Paulini, M.; Paus, C.; Peiffer, T.; Pellett, D. E.; Penzo, A.; Phillips, T. J.; Piacentino, G.; Pianori, E.; Pinera, L.; Pitts, K.; Plager, C.; Pondrom, L.; Poukhov, O.; Pounder, N.; Prakoshyn, F.; Pronko, A.; Proudfoot, J.; Ptohos, F.; Pueschel, E.; Punzi, G.; Pursley, J.; Rademacker, J.; Rahaman, A.; Ramakrishnan, V.; Ranjan, N.; Redondo, I.; Renton, P.; Renz, M.; Rescigno, M.; Richter, S.; Rimondi, F.; Ristori, L.; Robson, A.; Rodrigo, T.; Rodriguez, T.; Rogers, E.; Rolli, S.; Roser, R.; Rossi, M.; Rossin, R.; Roy, P.; Ruiz, A.; Russ, J.; Rusu, V.; Saarikko, H.; Safonov, A.; Sakumoto, W. K.; Saltó, O.; Santi, L.; Sarkar, S.; Sartori, L.; Sato, K.; Savoy-Navarro, A.; Schlabach, P.; Schmidt, A.; Schmidt, E. E.; Schmidt, M. A.; Schmidt, M. P.; Schmitt, M.; Schwarz, T.; Scodellaro, L.; Scribano, A.; Scuri, F.; Sedov, A.; Seidel, S.; Seiya, Y.; Semenov, A.; Sexton-Kennedy, L.; Sforza, F.; Sfyrla, A.; Shalhout, S. Z.; Shears, T.; Shepard, P. F.; Shimojima, M.; Shiraishi, S.; Shochet, M.; Shon, Y.; Shreyber, I.; Sidoti, A.; Sinervo, P.; Sisakyan, A.; Slaughter, A. J.; Slaunwhite, J.; Sliwa, K.; Smith, J. R.; Snider, F. D.; Snihur, R.; Soha, A.; Somalwar, S.; Sorin, V.; Spalding, J.; Spreitzer, T.; Squillacioti, P.; Stanitzki, M.; St. Denis, R.; Stelzer, B.; Stelzer-Chilton, O.; Stentz, D.; Strologas, J.; Strycker, G. L.; Stuart, D.; Suh, J. S.; Sukhanov, A.; Suslov, I.; Suzuki, T.; Taffard, A.; Takashima, R.; Takeuchi, Y.; Tanaka, R.; Tecchio, M.; Teng, P. K.; Terashi, K.; Thom, J.; Thompson, A. S.; Thompson, G. A.; Thomson, E.; Tipton, P.; Ttito-Guzmán, P.; Tkaczyk, S.; Toback, D.; Tokar, S.; Tollefson, K.; Tomura, T.; Tonelli, D.; Torre, S.; Torretta, D.; Totaro, P.; Tourneur, S.; Trovato, M.; Tsai, S.-Y.; Tu, Y.; Turini, N.; Ukegawa, F.; Vallecorsa, S.; van Remortel, N.; Varganov, A.; Vataga, E.; Vázquez, F.; Velev, G.; Vellidis, C.; Vidal, M.; Vidal, R.; Vila, I.; Vilar, R.; Vine, T.; Vogel, M.; Volobouev, I.; Volpi, G.; Wagner, P.; Wagner, R. G.; Wagner, R. L.; Wagner, W.; Wagner-Kuhr, J.; Wakisaka, T.; Wallny, R.; Wang, S. M.; Warburton, A.; Waters, D.; Weinberger, M.; Weinelt, J.; Wester, W. C., III; Whitehouse, B.; Whiteson, D.; Wicklund, A. B.; Wicklund, E.; Wilbur, S.; Williams, G.; Williams, H. H.; Wilson, P.; Winer, B. L.; Wittich, P.; Wolbers, S.; Wolfe, C.; Wright, T.; Wu, X.; Würthwein, F.; Xie, S.; Yagil, A.; Yamamoto, K.; Yamaoka, J.; Yang, U. K.; Yang, Y. C.; Yao, W. M.; Yeh, G. P.; Yoh, J.; Yorita, K.; Yoshida, T.; Yu, G. B.; Yu, I.; Yu, S. S.; Yun, J. C.; Zanello, L.; Zanetti, A.; Zhang, X.; Zheng, Y.; Zucchelli, S.

    2009-09-01

    We present a search for a standard model Higgs boson produced in association with a W boson using 2.7fb-1 of integrated luminosity of p pmacr collision data taken at s=1.96TeV. Limits on the Higgs boson production rate are obtained for masses between 100 and 150GeV/c2. Through the use of multivariate techniques, the analysis achieves an observed (expected) 95% confidence level upper limit of 5.6 (4.8) times the theoretically expected production cross section for a standard model Higgs boson with a mass of 115GeV/c2.

  1. Investigations of Standard Model and Exotic Monophoton Signatures at Center of Mass Energy = 7 TeV

    NASA Astrophysics Data System (ADS)

    Miceli, Tia Marie

    This dissertation describes the search for large extra dimensions. Such extra dimensions could solve the hierarchy problem, one of the greatest puzzles in the field of particle physics. The hierarchy problem is the mystery of why gravity is significantly weaker than the electromagnetic, strong, and weak forces. A solution would unify the strength of gravity with the strength of the other forces. There are many possible tests for extra dimensions. Presented is the analysis of proton-proton collisions with final states in which a single photon recoils from an invisible particle. These data were collected with the Compact Muon Solenoid detector during the 2011 Large Hadron Collider run at CERN, in Geneva, Switzerland, and correspond to an integrated luminosity of 5 fb-1 of proton-proton collisions at a center of mass energy of 7 TeV. Backgrounds are estimated using data driven techniques for those due to W → nue, hadronic jets, and non-collision backgrounds such as beam remnants faking a photon, and anomalous energy deposits in the electromagnetic calorimeter. The less significant backgrounds are estimated using Monte Carlo simulation, Wgamma, dijet, and jet + gamma. The irreducible Z(nunu)+ gamma background was estimated in Monte Carlo for the extra dimension search, but in later studies this component should be estimated by using a ratio of the measured Zgamma → mumugamma cross section. The results are consistent with the predicted Standard Model cross section of Z bosons decaying to neutrino pairs. Subsequently, the worlds best limits are placed on the monophoton topology of large extra dimensions. The same analysis provides a measurement of the Z(nunu)+gamma cross section consistent with next to leading order predictions.

  2. Surprising phenomena in a rich new class of inflationary models

    SciTech Connect

    Vaudrevange, Pascal M.; Podolsky, Dmitry I.; Starkman, Glenn D. E-mail: podolsky@phys.cwru.edu

    2010-04-01

    We report on a new class of fast-roll inflationary models. In a huge part of its parameter space, inflationary perturbations exhibit quite unusual phenomena such as scalar and tensor modes freezing out at widely different times, as well as scalar modes reentering the horizon during inflation. One specific point in parameter space is characterized by extraordinary behavior of the scalar perturbations. Freeze-out of scalar perturbations as well as particle production at horizon crossing are absent. Also the behavior of the perturbations around this quasi-de Sitter background is dual to a quantum field theory in flat space-time. Finally, the form of the primordial power spectrum is determined by the interaction between different modes of scalar perturbations.

  3. Search for minimal supersymmetric standard model Higgs Bosons H / A and for a Z^' } boson in the τ τ final state produced in pp collisions at √{s}= 13 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Baarreiro Guimrães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; De Mendizabal, J. Bilbao; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. 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A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolf, T. M. H.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Nedden, M. zur; Zwalinski, L.

    2016-11-01

    A search for neutral Higgs bosons of the minimal supersymmetric standard model (MSSM) and for a heavneutral Z^' } boson is performed using a data sample corresponding to an integrated luminosity of 3.2 fb^{-1} from proton-proton collisions at √{s} = 13 {TeV} recorded by the ATLAS detector at the LHC. The heavy resonance is assumed to decay to a τ ^+ τ ^- pair with at least one τ lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-1.2 {TeV} for the MSSM neutral Higgs bosons and 0.5-2.5 {TeV} for the heavy neutral Z^' } boson. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in MSSM and Z^' } benchmark scenarios. The most stringent constraints on the MSSM m_A-tan β space exclude at 95 % confidence level (CL) tan β > 7.6 for m_A = 200 {GeV} in the mh^{ {mod+}} MSSM scenario. For the Sequential Standard Model, a Z^' }_SSM mass up to 1.90 {TeV} is excluded at 95 % CL and masses up to 1.82-2.17 {TeV} are excluded for a Z^' }_{SFM} of the strong flavour model.

  4. Search for a Low Mass Standard Model Higgs Boson at D0 in ppbar Collisions at $\\sqrt{s}=1.96 TeV$

    SciTech Connect

    Rangel, Murilo

    2010-02-01

    We present combined searches for the low mass Standard Model Higgs boson at a center-of-mass energy of {radical}s = 1.96 TeV, using up to 5 fb{sup -1} of data collected with the D0 detector at the Fermilab Tevatron collider. The major contributing processes are associated production (WH {yields} lvbb, ZH {yields} vvbb, ZH {yields} llbb). The significant improvements across the full mass range resulting from the larger data sets and improved analyses as well as future prospects are discussed.

  5. Search for physics beyond the standard model in events with a Z boson, jets, and missing transverse energy in pp collisions at √{ s} = 7 TeV

    NASA Astrophysics Data System (ADS)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hammer, J.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Krammer, M.; Liko, D.; Mikulec, I.; Pernicka, M.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Teischinger, F.; Wagner, P.; Waltenberger, W.; Walzel, G.; Widl, E.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, S.; Cerny, K.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Maes, T.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Charaf, O.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Vanelderen, L.; Verwilligen, P.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Schul, N.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins, M.; De Jesus Damiao, D.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Oliveira Martins, C.; Fonseca De Souza, S.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Oguri, V.; Prado Da Silva, W. L.; Santoro, A.; Silva Do Amaral, S. M.; Soares Jorge, L.; Sznajder, A.; Anjos, T. S.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Karadzhinova, A.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, S.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, S.; Zhu, B.; Zou, W.; Avila, C.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Dzelalija, M.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Morovic, S.; Attikis, A.; Galanti, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Khalil, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Müntel, M.; Raidal, M.; Rebane, L.; Tiko, A.; Azzolini, V.; Eerola, P.; Fedi, G.; Voutilainen, M.; Czellar, S.; Härkönen, J.; Heikkinen, A.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Ungaro, D.; Wendland, L.; Banzuzi, K.; Korpela, A.; Tuuva, T.; Sillou, D.; Besancon, M.; Choudhury, S.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Millischer, L.; Rander, J.; Rosowsky, A.; Shreyber, I.; Titov, M.; Baffioni, S.; Beaudette, F.; Benhabib, L.; Bianchini, L.; Bluj, M.; Broutin, C.; Busson, P.; Charlot, C.; Daci, N.; Dahms, T.; Dobrzynski, L.; Granier de Cassagnac, R.; Haguenauer, M.; Miné, P.; Mironov, C.; Ochando, C.; Paganini, P.; Sabes, D.; Salerno, R.; Sirois, Y.; Veelken, C.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Bodin, D.; Brom, J.-M.; Cardaci, M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Ferro, C.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Juillot, P.; Karim, M.; Le Bihan, A.-C.; Van Hove, P.; Fassi, F.; Mercier, D.; Baty, C.; Beauceron, S.; Beaupere, N.; Bedjidian, M.; Bondu, O.; Boudoul, G.; Boumediene, D.; Brun, H.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Falkiewicz, A.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Le Grand, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Sordini, V.; Tosi, S.; Tschudi, Y.; Verdier, P.; Viret, S.; Rurua, L.; Anagnostou, G.; Beranek, S.; Edelhoff, M.; Feld, L.; Heracleous, N.

    2012-09-01

    A search is presented for physics beyond the standard model (BSM) in events with a Z boson, jets, and missing transverse energy (ETmiss). This signature is motivated by BSM physics scenarios, including supersymmetry. The study is performed using a sample of proton-proton collision data collected at √{ s} = 7 TeV with the CMS experiment at the LHC, corresponding to an integrated luminosity of 4.98 fb-1. The contributions from the dominant standard model backgrounds are estimated from data using two complementary strategies, the jet-Z balance technique and a method based on modeling ETmiss with data control samples. In the absence of evidence for BSM physics, we set limits on the non-standard-model contributions to event yields in the signal regions and interpret the results in the context of simplified model spectra. Additional information is provided to facilitate tests of other BSM physics models.

  6. BL LAC candidates for TeV observations

    SciTech Connect

    Massaro, F.; Paggi, A.; Errando, M.; D'Abrusco, R.; Masetti, N.; Tosti, G.; Funk, S.

    2013-07-01

    BL Lac objects are the most numerous class of extragalactic TeV-detected sources. One of the biggest difficulties in investigating their TeV emission is due to their limited number, since only 47 BL Lac objects are known to be TeV emitters. In this paper, we propose new criteria to select TeV BL Lac candidates based on infrared and X-ray observations. We apply our selection criteria to the BL Lac objects listed in the ROMA-BZCAT catalog, thereby identifying 41 potential TeV emitters. We then perform a search over a more extended sample combining the ROSAT bright source catalog and the WISE all-sky survey, revealing 54 additional candidates for TeV observations. Our investigation also led to a tentative classification of 16 unidentified X-ray sources as BL Lac candidates. This analysis provides new interesting BL Lac targets for future observations with ground-based Cherenkov telescopes.

  7. Latent Class Detection and Class Assignment: A Comparison of the MAXEIG Taxometric Procedure and Factor Mixture Modeling Approaches

    ERIC Educational Resources Information Center

    Lubke, Gitta; Tueller, Stephen

    2010-01-01

    Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class clustering, but they have very different sets of strengths and weaknesses. Taxometric procedures, popular in psychiatric and psychopathology applications, do not rely on distributional assumptions. Their sole purpose is to detect the presence of latent…

  8. Searches for Higgs bosons in pp collisions at √{ s} = 7 and 8 TeV in the context of four-generation and fermiophobic models

    NASA Astrophysics Data System (ADS)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Aguilo, E.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hammer, J.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Liko, D.; Mikulec, I.; Pernicka, M.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Waltenberger, W.; Walzel, G.; Widl, E.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Staykova, Z.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Reis, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Verwilligen, P.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Castello, R.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Schul, N.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins Junior, M.; De Jesus Damiao, D.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Oliveira Martins, C.; Fonseca De Souza, S.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Oguri, V.; Prado Da Silva, W. L.; Santoro, A.; Soares Jorge, L.; Sznajder, A.; Anjos, T. S.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, S.; Guo, Y.; Li, Q.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Zhang, L.; Zhu, B.; Zou, W.; Avila, C.; Gomez, J. P.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Morovic, S.; Attikis, A.; Galanti, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Müntel, M.; Raidal, M.; Rebane, L.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Heikkinen, A.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Ungaro, D.; Wendland, L.; Banzuzi, K.; Karjalainen, A.; Korpela, A.; Tuuva, T.; Besancon, M.; Choudhury, S.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Millischer, L.; Nayak, A.; Rander, J.; Rosowsky, A.; Shreyber, I.; Titov, M.; Baffioni, S.; Beaudette, F.; Benhabib, L.; Bianchini, L.; Bluj, M.; Broutin, C.; Busson, P.; Charlot, C.; Daci, N.; Dahms, T.; Dobrzynski, L.; Granier de Cassagnac, R.; Haguenauer, M.; Miné, P.; Mironov, C.; Nguyen, M.; Ochando, C.; Paganini, P.; Sabes, D.; Salerno, R.; Sirois, Y.; Veelken, C.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Bodin, D.; Brom, J.-M.; Cardaci, M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Ferro, C.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Juillot, P.; Le Bihan, A.-C.; Van Hove, P.; Fassi, F.; Mercier, D.; Beauceron, S.; Beaupere, N.; Bondu, O.; Boudoul, G.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Sordini, V.; Tschudi, Y.; Verdier, P.; Viret, S.; Tsamalaidze, Z.; Anagnostou, G.; Beranek, S.; Edelhoff, M.; Feld, L.; Heracleous, N.; Hindrichs, O.; Jussen, R.; Klein, K.; Merz, J.; Ostapchuk, A.; Perieanu, A.; Raupach, F.; Sammet, J.; Schael, S.

    2013-08-01

    Searches are reported for Higgs bosons in the context of either the standard model extended to include a fourth generation of fermions (SM4) with masses of up to 600 GeV or fermiophobic models. For the former, results from three decay modes (ττ, WW, and ZZ) are combined, whilst for the latter the diphoton decay is exploited. The analysed proton-proton collision data correspond to integrated luminosities of up to 5.1 fb-1 at 7 TeV and up to 5.3 fb-1 at 8 TeV. The observed results exclude the SM4 Higgs boson in the mass range 110-600 GeV at 99% confidence level (CL), and in the mass range 110-560 GeV at 99.9% CL. A fermiophobic Higgs boson is excluded in the mass range 110-147 GeV at 95% CL, and in the range 110-133 GeV at 99% CL. The recently observed boson with a mass near 125 GeV is not consistent with either an SM4 or a fermiophobic Higgs boson.

  9. Addressing the Problem of Switched Class Labels in Latent Variable Mixture Model Simulation Studies

    ERIC Educational Resources Information Center

    Tueller, Stephen J.; Drotar, Scott; Lubke, Gitta H.

    2011-01-01

    The discrimination between alternative models and the detection of latent classes in the context of latent variable mixture modeling depends on sample size, class separation, and other aspects that are related to power. Prior to a mixture analysis it is useful to investigate model performance in a simulation study that reflects the research…

  10. A latent class approach to treatment readiness corresponds to a transtheoretical ("Stages of Change") model.

    PubMed

    Harrell, Paul Truman; Trenz, R C; Scherer, M; Martins, S S; Latimer, W W

    2013-09-01

    Motivation for treatment among people with substance use problems is an important aspect of treatment success. Models for treatment motivation are widely debated. Latent Class Analysis can help to demonstrate the appropriateness of available models. The current study utilizes Latent Class Analysis to analyze treatment readiness statements as they relate to the reduction or cessation of marijuana, cocaine, and opioid use among 539 cocaine and opioid users recruited from the community of Baltimore, MD, USA. Participants completed an in-person structured interview including demographic questions, a treatment readiness questionnaire with items on Intention to Stop Use (ISU) and Problem Recognition (PR), current substance abuse treatment utilization, and urinalysis testing for marijuana, cocaine, and heroin. Latent class models were fit to the treatment readiness questionnaire. A four-class model provided the best fit with one class low on both ISU and PR ("Pre-contemplative"), a second class low on ISU but high on PR ("Contemplative"), a third class high on both ("Preparation/Action"), and a final class high on ISU but low on PR ("Post-Action"). Compared to the "Contemplative" class, the "Pre-contemplative" class was significantly more likely to be positive for marijuana, and the "Post-Action" class was significantly less likely to be positive for opioids. The "Preparation/Action" class was significantly more likely to be in treatment. With the exception of the "Post-Action" class, the analysis appears similar to the "Stages of Change" model and suggests that problem recognition and intention to stop use are important domains in the model. However, further longitudinal research is needed to assess predictive validity of model.

  11. Emanations of dark matter: Muon anomalous magnetic moment, radiative neutrino mass, and novel leptogenesis at the TeV scale

    SciTech Connect

    Hambye, Thomas; Kannike, Kristjan; Raidal, Martti; Ma, Ernest

    2007-05-01

    The evidence for dark matter signals a new class of particles at the TeV scale, which may manifest themselves indirectly through loop effects. In a simple model we show that these loop effects may be responsible for the enhanced muon anomalous magnetic moment, for the neutrino mass, as well as for leptogenesis in a novel way. This scenario can be verified at LHC and/or ILC experiments.

  12. Search for physics beyond the standard model in events with two leptons, jets, and missing transverse momentum in pp collisions at √s = 8 TeV

    DOE PAGES

    Khachatryan, Vardan

    2015-04-22

    Our search is presented for physics beyond the standard model in final states with two opposite-sign same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 19.4 fb-1 of proton-proton collisions at √s = 8 TeV collected with the CMS detector at the CERN LHC in 2012. The analysis focuses on searches for a kinematic edge in the invariant mass distribution of the oppositesign same-flavor lepton pair and for final states with an on-shell Z boson. Furthermore, the observations are consistent with expectations from standard model processes and are interpreted in terms of uppermore » limits on the production of supersymmetric particles.« less

  13. Search for physics beyond the standard model in events with two leptons, jets, and missing transverse momentum in pp collisions at √s = 8 TeV

    SciTech Connect

    Khachatryan, Vardan

    2015-04-22

    Our search is presented for physics beyond the standard model in final states with two opposite-sign same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 19.4 fb-1 of proton-proton collisions at √s = 8 TeV collected with the CMS detector at the CERN LHC in 2012. The analysis focuses on searches for a kinematic edge in the invariant mass distribution of the oppositesign same-flavor lepton pair and for final states with an on-shell Z boson. Furthermore, the observations are consistent with expectations from standard model processes and are interpreted in terms of upper limits on the production of supersymmetric particles.

  14. Search for Physics Beyond the Standard Model Using Multilepton Signatures in pp Collisions at sqrt(s)=7 TeV

    SciTech Connect

    Chatrchyan, Serguei; et al.

    2011-10-01

    A search for physics beyond the standard model in events with at least three leptons and any number of jets is presented. The data sample corresponds to 35 inverse picobarns of integrated luminosity in pp collisions at sqrt(s) = 7 TeV collected by the CMS experiment at the LHC. A number of exclusive multileptonic channels are investigated and standard model backgrounds are suppressed by requiring sufficient missing transverse energy, invariant mass inconsistent with that of the Z boson, or high jet activity. Control samples in data are used to ascertain the robustness of background evaluation techniques and to minimise the reliance on simulation. The observations are consistent with background expectations. These results constrain previously unexplored regions of supersymmetric parameter space.

  15. On Inclusion of Covariates for Class Enumeration of Growth Mixture Models.

    PubMed

    Li, Libo; Hser, Yih-Ing

    2011-01-01

    In this article, we directly questioned the common practice in growth mixture model (GMM) applications that exclusively rely on the fitting model without covariates for GMM class enumeration. We provided theoretical and simulation evidence to demonstrate that exclusion of covariates from GMM class enumeration could be problematic in many cases. Based on our findings, we provided recommendations for examining the class enumeration by the fitting model without covariates and discussed the potential of covariate inclusion as a remedy for the weakness of GMM class enumeration without including covariates. A real example on the development of children's cumulative exposure to risk factors for adolescent substance use was provided to illustrate our methodological developments.

  16. Modeling subsurface reactive flows using leadership-class computing

    NASA Astrophysics Data System (ADS)

    Tran Mills, Richard; Hammond, Glenn E.; Lichtner, Peter C.; Sripathi, Vamsi; Kumar Mahinthakumar, G.; Smith, Barry F.

    2009-07-01

    We describe our experiences running PFLOTRAN-a code for simulation of coupled hydro-thermal-chemical processes in variably saturated, non-isothermal, porous media- on leadership-class supercomputers, including initial experiences running on the petaflop incarnation of Jaguar, the Cray XT5 at the National Center for Computational Sciences at Oak Ridge National Laboratory. PFLOTRAN utilizes fully implicit time-stepping and is built on top of the Portable, Extensible Toolkit for Scientific Computation (PETSc). We discuss some of the hurdles to "at scale" performance with PFLOTRAN and the progress we have made in overcoming them on leadership-class computer architectures.

  17. Modeling Subsurface Reactive Flows Using Leadership-Class Computing

    SciTech Connect

    Mills, Richard T; Hammond, Glenn; Lichtner, Peter; Sripathi, Vamsi K; Mahinthakumar, Gnanamanika; Smith, Barry F

    2009-01-01

    We describe our experiences running PFLOTRAN - a code for simulation of coupled hydro-thermal-chemical processes in variably saturated, non-isothermal, porous media - on leadership-class supercomputers, including initial experiences running on the petaflop incarnation of Jaguar, the Cray XT5 at the National Center for Computational Sciences at Oak Ridge National Laboratory. PFLOTRAN utilizes fully implicit time-stepping and is built on top of the Portable, Extensible Toolkit for Scientific Computation (PETSc). We discuss some of the hurdles to 'at scale' performance with PFLOTRAN and the progress we have made in overcoming them on leadership-class computer architectures.

  18. Extending Positive CLASS Results across Multiple Instructors and Multiple Classes of Modeling Instruction

    ERIC Educational Resources Information Center

    Brewe, Eric; Traxler, Adrienne; de la Garza, Jorge; Kramer, Laird H.

    2013-01-01

    We report on a multiyear study of student attitudes measured with the Colorado Learning Attitudes about Science Survey in calculus-based introductory physics taught with the Modeling Instruction curriculum. We find that five of six instructors and eight of nine sections using Modeling Instruction showed significantly improved attitudes from pre-…

  19. Using multi-class queuing network to solve performance models of e-business sites.

    PubMed

    Zheng, Xiao-ying; Chen, De-ren

    2004-01-01

    Due to e-business's variety of customers with different navigational patterns and demands, multi-class queuing network is a natural performance model for it. The open multi-class queuing network(QN) models are based on the assumption that no service center is saturated as a result of the combined loads of all the classes. Several formulas are used to calculate performance measures, including throughput, residence time, queue length, response time and the average number of requests. The solution technique of closed multi-class QN models is an approximate mean value analysis algorithm (MVA) based on three key equations, because the exact algorithm needs huge time and space requirement. As mixed multi-class QN models, include some open and some closed classes, the open classes should be eliminated to create a closed multi-class QN so that the closed model algorithm can be applied. Some corresponding examples are given to show how to apply the algorithms mentioned in this article. These examples indicate that multi-class QN is a reasonably accurate model of e-business and can be solved efficiently.

  20. Distance Learning Class Model for Teaching a Foreign Language in University-Level Education Context

    ERIC Educational Resources Information Center

    Lee, Sun-Min

    2012-01-01

    This study aims to introduce the distance learning class model for a foreign language in university-level education context, and to prove that this class model is effective in cultivating the motivation and interest of university students for learning a foreign language. This distance learning lesson consists of two parts: Online chatting session,…

  1. Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses

    ERIC Educational Resources Information Center

    Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu

    2011-01-01

    Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…

  2. Measurement and Structural Model Class Separation in Mixture CFA: ML/EM versus MCMC

    ERIC Educational Resources Information Center

    Depaoli, Sarah

    2012-01-01

    Parameter recovery was assessed within mixture confirmatory factor analysis across multiple estimator conditions under different simulated levels of mixture class separation. Mixture class separation was defined in the measurement model (through factor loadings) and the structural model (through factor variances). Maximum likelihood (ML) via the…

  3. On Inclusion of Covariates for Class Enumeration of Growth Mixture Models

    ERIC Educational Resources Information Center

    Li, Libo; Hser, Yih-Ing

    2011-01-01

    In this article, we directly question the common practice in growth mixture model (GMM) applications that exclusively rely on the fitting model without covariates for GMM class enumeration. We provide theoretical and simulation evidence to demonstrate that exclusion of covariates from GMM class enumeration could be problematic in many cases. Based…

  4. Modeling and Verbalizations of Lower-Class, Black, Preschool Children: Educational Implications.

    ERIC Educational Resources Information Center

    Gottfried, Adele E.

    Two purposes guided this study: (1) to investigate the effects of modeling on the verbalizations of lower-class, black, preschool children; and (2) to investigate the relationships between the dialect employed by the model and children's language production. As subjects, 72 black, preschool children in lower-class neighborhood day care centers of…

  5. The Impact of Ignoring the Level of Nesting Structure in Nonparametric Multilevel Latent Class Models

    ERIC Educational Resources Information Center

    Park, Jungkyu; Yu, Hsiu-Ting

    2016-01-01

    The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…

  6. Science/Technology/Society: Model Lessons for Secondary Science Classes.

    ERIC Educational Resources Information Center

    Pearson, Janice V., Ed.

    This volume contains 35 lessons designed to be used in secondary science classes to introduce the science/technology/society (STS) themes and issues. While the first 11 lessons focus on general STS themes, the other 24 lessons cover specific STS issues that fall under such categories as population growth, water resources, world hunger, food…

  7. Multilevel Latent Class Analysis: Parametric and Nonparametric Models

    ERIC Educational Resources Information Center

    Finch, W. Holmes; French, Brian F.

    2014-01-01

    Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture…

  8. Search for neutral minimal supersymmetric standard model Higgs bosons decaying to tau pairs in pp collisions at √s=7 TeV.

    PubMed

    Chatrchyan, S; Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Bergauer, T; Dragicevic, M; Erö, J; Fabjan, C; Friedl, M; Frühwirth, R; Ghete, V M; Hammer, J; Hänsel, S; Hoch, M; Hörmann, N; Hrubec, J; Jeitler, M; Kasieczka, G; Kiesenhofer, W; Krammer, M; Liko, D; Mikulec, I; Pernicka, M; Rohringer, H; Schöfbeck, R; Strauss, J; Teischinger, F; Wagner, P; Waltenberger, W; Walzel, G; Widl, E; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Benucci, L; De Wolf, E A; Janssen, X; Maes, T; Mucibello, L; Ochesanu, S; Roland, B; Rougny, R; Selvaggi, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Blekman, F; Blyweert, S; D'Hondt, J; Devroede, O; Gonzalez Suarez, R; Kalogeropoulos, A; Maes, J; Maes, M; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Villella, I; Charaf, O; Clerbaux, B; De Lentdecker, G; Dero, V; Gay, A P R; Hammad, G H; Hreus, T; Marage, P E; Thomas, L; Vander Velde, C; Vanlaer, P; Adler, V; Cimmino, A; Costantini, S; Grunewald, M; Klein, B; Lellouch, J; Marinov, A; McCartin, J; Ryckbosch, D; Thyssen, F; Tytgat, M; Vanelderen, L; Verwilligen, P; Walsh, S; Zaganidis, N; Basegmez, S; Bruno, G; Caudron, J; Ceard, L; Cortina Gil, E; De Favereau De Jeneret, J; Delaere, C; Favart, D; Giammanco, A; Grégoire, G; Hollar, J; Lemaitre, V; Liao, J; Militaru, O; Ovyn, S; Pagano, D; Pin, A; Piotrzkowski, K; Schul, N; Beliy, N; Caebergs, T; Daubie, E; Alves, G A; Damiao, D De Jesus; Pol, M E; Souza, M H G; Carvalho, W; Da Costa, E M; Martins, C De Oliveira; De Souza, S Fonseca; Mundim, L; Nogima, H; Oguri, V; Da Silva, W L Prado; Santoro, A; Do Amaral, S M Silva; Sznajder, A; De Araujo, F Torres Da Silva; Dias, F A; Tomei, T R Fernandez Perez; Gregores, E M; Lagana, C; Marinho, F; Mercadante, P G; Novaes, S F; Padula, Sandra S; Darmenov, N; Dimitrov, L; Genchev, V; Iaydjiev, P; Piperov, S; Rodozov, M; Stoykova, S; Sultanov, G; Tcholakov, V; Trayanov, R; Vankov, I; Dimitrov, A; Hadjiiska, R; Karadzhinova, A; Kozhuharov, V; Litov, L; Mateev, M; Pavlov, B; Petkov, P; Bian, J G; Chen, G M; Chen, H S; Jiang, C H; Liang, D; Liang, S; Meng, X; Tao, J; Wang, J; Wang, J; Wang, X; Wang, Z; Xiao, H; Xu, M; Zang, J; Zhang, Z; Ban, Y; Guo, S; Guo, Y; Li, W; Mao, Y; Qian, S J; Teng, H; Zhang, L; Zhu, B; Zou, W; Cabrera, A; Moreno, B Gomez; Rios, A A Ocampo; Oliveros, A F Osorio; Sanabria, J C; Godinovic, N; Lelas, D; Lelas, K; Plestina, R; Polic, D; Puljak, I; Antunovic, Z; Dzelalija, M; Brigljevic, V; Duric, S; Kadija, K; Morovic, S; Attikis, A; Galanti, M; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Finger, M; Finger, M; Assran, Y; Khalil, S; Mahmoud, M A; Hektor, A; Kadastik, M; Müntel, M; Raidal, M; Rebane, L; Azzolini, V; Eerola, P; Fedi, G; Czellar, S; Härkönen, J; Heikkinen, A; Karimäki, V; Kinnunen, R; Kortelainen, M J; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Tuominen, E; Tuominiemi, J; Tuovinen, E; Ungaro, D; Wendland, L; Banzuzi, K; Korpela, A; Tuuva, T; Sillou, D; Besancon, M; Choudhury, S; Dejardin, M; Denegri, D; Fabbro, B; Faure, J L; Ferri, F; Ganjour, S; Gentit, F X; Givernaud, A; Gras, P; de Monchenault, G Hamel; Jarry, P; Locci, E; Malcles, J; Marionneau, M; Millischer, L; Rander, J; Rosowsky, A; Shreyber, I; Titov, M; Verrecchia, P; Baffioni, S; Beaudette, F; Benhabib, L; Bianchini, L; Bluj, M; Broutin, C; Busson, P; Charlot, C; Dahms, T; Dobrzynski, L; Elgammal, S; de Cassagnac, R Granier; Haguenauer, M; Miné, P; Mironov, C; Ochando, C; Paganini, P; Sabes, D; Salerno, R; Sirois, Y; Thiebaux, C; Wyslouch, B; Zabi, A; Agram, J-L; Andrea, J; Bloch, D; Bodin, D; Brom, J-M; Cardaci, M; Chabert, E C; Collard, C; Conte, E; Drouhin, F; Ferro, C; Fontaine, J-C; Gelé, D; Goerlach, U; Greder, S; Juillot, P; Karim, M; Le Bihan, A-C; Mikami, Y; Van Hove, P; Fassi, F; Mercier, D; Baty, C; Beauceron, S; Beaupere, N; Bedjidian, M; Bondu, O; Boudoul, G; Boumediene, D; Brun, H; Chierici, R; Contardo, D; Depasse, P; El Mamouni, H; Fay, J; Gascon, S; Ille, B; Kurca, T; Le Grand, T; Lethuillier, M; Mirabito, L; Perries, S; Sordini, V; Tosi, S; Tschudi, Y; Verdier, P; Lomidze, D; Anagnostou, G; Edelhoff, M; Feld, L; Heracleous, N; Hindrichs, O; Jussen, R; Klein, K; Merz, J; Mohr, N; Ostapchuk, A; Perieanu, A; Raupach, F; Sammet, J; Schael, S; Sprenger, D; Weber, H; Weber, M; Wittmer, B; Ata, M; Bender, W; Dietz-Laursonn, E; Erdmann, M; Frangenheim, J; Hebbeker, T; Hinzmann, A; Hoepfner, K; Klimkovich, T; Klingebiel, D; Kreuzer, P; Lanske, D; Magass, C; Merschmeyer, M; Meyer, A; Papacz, P; Pieta, H; Reithler, H; Schmitz, S A; Sonnenschein, L; Steggemann, J; Teyssier, D; Tonutti, M; Bontenackels, M; Davids, M; Duda, M; Flügge, G; Geenen, H; Giffels, M; Ahmad, W Haj; Heydhausen, D; Kress, T; Kuessel, Y; Linn, A; Nowack, A; Perchalla, L; Pooth, O; Rennefeld, J; Sauerland, P; Stahl, A; Thomas, M; Tornier, D; Zoeller, M H; Martin, M Aldaya; Behrenhoff, W; Behrens, U; Bergholz, M; Bethani, A; Borras, K; Cakir, A; Campbell, A; Castro, E; Dammann, D; Eckerlin, G; Eckstein, D; Flossdorf, A; 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Wittich, P; Biselli, A; Cirino, G; Winn, D; Abdullin, S; Albrow, M; Anderson, J; Apollinari, G; Atac, M; Bakken, J A; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bloch, I; Borcherding, F; Burkett, K; Butler, J N; Chetluru, V; Cheung, H W K; Chlebana, F; Cihangir, S; Cooper, W; Eartly, D P; Elvira, V D; Esen, S; Fisk, I; Freeman, J; Gao, Y; Gottschalk, E; Green, D; Gunthoti, K; Gutsche, O; Hanlon, J; Harris, R M; Hirschauer, J; Hooberman, B; Jensen, H; Johnson, M; Joshi, U; Khatiwada, R; Klima, B; Kousouris, K; Kunori, S; Kwan, S; Leonidopoulos, C; Limon, P; Lincoln, D; Lipton, R; Lykken, J; Maeshima, K; Marraffino, J M; Mason, D; McBride, P; Miao, T; Mishra, K; Mrenna, S; Musienko, Y; Newman-Holmes, C; O'Dell, V; Pordes, R; Prokofyev, O; Saoulidou, N; Sexton-Kennedy, E; Sharma, S; Spalding, W J; Spiegel, L; Tan, P; Taylor, L; Tkaczyk, S; Uplegger, L; Vaandering, E W; Vidal, R; Whitmore, J; Wu, W; Yang, F; Yumiceva, F; Yun, J C; Acosta, D; Avery, P; Bourilkov, D; Chen, M; De Gruttola, M; Di Giovanni, G P; Dobur, D; Drozdetskiy, A; Field, R D; Fisher, M; Fu, Y; Furic, I K; Gartner, J; Kim, B; Konigsberg, J; Korytov, A; Kropivnitskaya, A; Kypreos, T; Matchev, K; Mitselmakher, G; Muniz, L; Prescott, C; Remington, R; Schmitt, M; Scurlock, B; Sellers, P; Skhirtladze, N; Snowball, M; Wang, D; Yelton, J; Zakaria, M; Ceron, C; Gaultney, V; Kramer, L; Lebolo, L M; Linn, S; Markowitz, P; Martinez, G; Mesa, D; Rodriguez, J L; Adams, T; Askew, A; Bandurin, D; Bochenek, J; Chen, J; Diamond, B; Gleyzer, S V; Haas, J; Hagopian, S; Hagopian, V; Jenkins, M; Johnson, K F; Prosper, H; Quertenmont, L; Sekmen, S; Veeraraghavan, V; Baarmand, M M; Dorney, B; Guragain, S; Hohlmann, M; Kalakhety, H; Ralich, R; Vodopiyanov, I; Adams, M R; Anghel, I M; Apanasevich, L; Bai, Y; Bazterra, V E; Betts, R R; Callner, J; Cavanaugh, R; Dragoiu, C; Gauthier, L; Gerber, C E; Hofman, D J; Khalatyan, S; Kunde, G J; Lacroix, F; Malek, M; O'Brien, C; Silvestre, C; Smoron, A; Strom, D; Varelas, N; Akgun, U; Albayrak, E A; Bilki, B; Clarida, W; Duru, F; Lae, C K; McCliment, E; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Newsom, C R; Norbeck, E; Olson, J; Onel, Y; Ozok, F; Sen, S; Wetzel, J; Yetkin, T; Yi, K; Barnett, B A; Blumenfeld, B; Bonato, A; Eskew, C; Fehling, D; Giurgiu, G; Gritsan, A V; Guo, Z J; Hu, G; Maksimovic, P; Rappoccio, S; Swartz, M; Tran, N V; Whitbeck, A; Baringer, P; Bean, A; Benelli, G; Grachov, O; Kenny Iii, R P; Murray, M; Noonan, D; Sanders, S; Wood, J S; Zhukova, V; Barfuss, A F; Bolton, T; Chakaberia, I; Ivanov, A; Khalil, S; Makouski, M; Maravin, Y; Shrestha, S; Svintradze, I; Wan, Z; Gronberg, J; Lange, D; Wright, D; Baden, A; Boutemeur, M; Eno, S C; Ferencek, D; Gomez, J A; Hadley, N J; Kellogg, R G; Kirn, M; Lu, Y; Mignerey, A C; Rossato, K; Rumerio, P; Santanastasio, F; Skuja, A; Temple, J; Tonjes, M B; Tonwar, S C; Twedt, E; Alver, B; Bauer, G; Bendavid, J; Busza, W; Butz, E; Cali, I A; Chan, M; Dutta, V; Everaerts, P; Ceballos, G Gomez; Goncharov, M; Hahn, K A; Harris, P; Kim, Y; Klute, M; Lee, Y-J; Li, W; Loizides, C; Luckey, P D; Ma, T; Nahn, S; Paus, C; Ralph, D; Roland, C; Roland, G; Rudolph, M; Stephans, G S F; Stöckli, F; Sumorok, K; Sung, K; Wenger, E A; Xie, S; Yang, M; Yilmaz, Y; Yoon, A S; Zanetti, M; Cooper, S I; Cushman, P; Dahmes, B; De Benedetti, A; Dudero, P R; Franzoni, G; Haupt, J; Klapoetke, K; Kubota, Y; Mans, J; Rekovic, V; Rusack, R; Sasseville, M; Singovsky, A; Cremaldi, L M; Godang, R; Kroeger, R; Perera, L; Rahmat, R; Sanders, D A; Summers, D; Bloom, K; Bose, S; Butt, J; Claes, D R; Dominguez, A; Eads, M; Keller, J; Kelly, T; Kravchenko, I; Lazo-Flores, J; Malbouisson, H; Malik, S; Snow, G R; Baur, U; Godshalk, A; Iashvili, I; Jain, S; Kharchilava, A; Kumar, A; Shipkowski, S P; Smith, K; Alverson, G; Barberis, E; Baumgartel, D; Boeriu, O; Chasco, M; Reucroft, S; Swain, J; Trocino, D; Wood, D; Zhang, J; Anastassov, A; Kubik, A; Odell, N; Ofierzynski, R A; Pollack, B; Pozdnyakov, A; Schmitt, M; Stoynev, S; Velasco, M; Won, S; Antonelli, L; Berry, D; Hildreth, M; Jessop, C; Karmgard, D J; Kolb, J; Kolberg, T; Lannon, K; Luo, W; Lynch, S; Marinelli, N; Morse, D M; Pearson, T; Ruchti, R; Slaunwhite, J; Valls, N; Wayne, M; Ziegler, J; Bylsma, B; Durkin, L S; Gu, J; Hill, C; Killewald, P; Kotov, K; Ling, T Y; Rodenburg, M; Williams, G; Adam, N; Berry, E; Elmer, P; Gerbaudo, D; Halyo, V; Hebda, P; Hunt, A; Jones, J; Laird, E; Pegna, D Lopes; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Piroué, P; Quan, X; Saka, H; Stickland, D; Tully, C; Werner, J S; Zuranski, A; Acosta, J G; Huang, X T; Lopez, A; Mendez, H; Oliveros, S; Vargas, J E Ramirez; Zatserklyaniy, A; Alagoz, E; Barnes, V E; Bolla, G; Borrello, L; Bortoletto, D; Everett, A; Garfinkel, A F; Gutay, L; Hu, Z; Jones, M; Koybasi, O; Kress, M; Laasanen, A T; Leonardo, N; Liu, C; Maroussov, V; Merkel, P; Miller, D H; Neumeister, N; Shipsey, I; Silvers, D; Svyatkovskiy, A; Yoo, H D; Zablocki, J; Zheng, Y; Jindal, P; Parashar, N; Boulahouache, C; Cuplov, V; Ecklund, K M; Geurts, F J M; Padley, B P; Redjimi, R; Roberts, J; Zabel, J; Betchart, B; Bodek, A; Chung, Y S; Covarelli, R; de Barbaro, P; Demina, R; Eshaq, Y; Flacher, H; Garcia-Bellido, A; Goldenzweig, P; Gotra, Y; Han, J; Harel, A; Miner, D C; Orbaker, D; Petrillo, G; Vishnevskiy, D; Zielinski, M; Bhatti, A; Ciesielski, R; Demortier, L; Goulianos, K; Lungu, G; Malik, S; Mesropian, C; Yan, M; Atramentov, O; Barker, A; Duggan, D; Gershtein, Y; Gray, R; Halkiadakis, E; Hidas, D; Hits, D; Lath, A; Panwalkar, S; Patel, R; Richards, A; Rose, K; Schnetzer, S; Somalwar, S; Stone, R; Thomas, S; Cerizza, G; Hollingsworth, M; Spanier, S; Yang, Z C; York, A; Asaadi, J; Eusebi, R; Gilmore, J; Gurrola, A; Kamon, T; Khotilovich, V; Montalvo, R; Nguyen, C N; Osipenkov, I; Pakhotin, Y; Pivarski, J; Safonov, A; Sengupta, S; Tatarinov, A; Toback, D; Weinberger, M; Akchurin, N; Bardak, C; Damgov, J; Jeong, C; Kovitanggoon, K; Lee, S W; Roh, Y; Sill, A; Volobouev, I; Wigmans, R; Yazgan, E; Appelt, E; Brownson, E; Engh, D; Florez, C; Gabella, W; Issah, M; Johns, W; Kurt, P; Maguire, C; Melo, A; Sheldon, P; Snook, B; Tuo, S; Velkovska, J; Arenton, M W; Balazs, M; Boutle, S; Cox, B; Francis, B; Hirosky, R; Ledovskoy, A; Lin, C; Neu, C; Yohay, R; Gollapinni, S; Harr, R; Karchin, P E; Lamichhane, P; Mattson, M; Milstène, C; Sakharov, A; Anderson, M; Bachtis, M; Bellinger, J N; Carlsmith, D; Dasu, S; Efron, J; Flood, K; Gray, L; Grogg, K S; Grothe, M; Hall-Wilton, R; Herndon, M; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Leonard, J; Loveless, R; Mohapatra, A; Palmonari, F; Reeder, D; Ross, I; Savin, A; Smith, W H; Swanson, J; Weinberg, M

    2011-06-10

    A search for neutral minimal supersymmetric standard model (MSSM) Higgs bosons in pp collisions at the LHC at a center-of-mass energy of 7 TeV is presented. The results are based on a data sample corresponding to an integrated luminosity of 36  pb(-1) recorded by the CMS experiment. The search uses decays of the Higgs bosons to tau pairs. No excess is observed in the tau-pair invariant-mass spectrum. The resulting upper limits on the Higgs boson production cross section times branching fraction to tau pairs, as a function of the pseudoscalar Higgs boson mass, yield stringent new bounds in the MSSM parameter space.

  9. Search for Standard Model Production of Four Top Quarks in the Lepton + Jets Channel in pp Collisions at $$\\sqrt{s}$$ = 8 TeV

    DOE PAGES

    Khachatryan, Vardan

    2014-11-27

    Our search is presented for standard model (SM) production of four top quarks (t¯tt¯t) in pp collisions in the lepton + jets channel. The data correspond to an integrated luminosity of 19.6 fb-1 recorded at a centre-of-mass energy of 8 TeV with the CMS detector at the CERN LHC. The expected cross section for SM t¯tt¯t production is σSMt¯tt¯t≈1fb. A combination of kinematic reconstruction and multivariate techniques is used to distinguish between the small signal and large background. We determined that the data are consistent with expectations of the SM, and an upper limit of 32 fb is set atmore » a 95% confidence level on the cross section for producing four top quarks in the SM, where a limit of 32 ± 17 fb is expected.« less

  10. Search for Standard Model Production of Four Top Quarks in the Lepton + Jets Channel in pp Collisions at $\\sqrt{s}$ = 8 TeV

    SciTech Connect

    Khachatryan, Vardan

    2014-11-27

    Our search is presented for standard model (SM) production of four top quarks (t¯tt¯t) in pp collisions in the lepton + jets channel. The data correspond to an integrated luminosity of 19.6 fb-1 recorded at a centre-of-mass energy of 8 TeV with the CMS detector at the CERN LHC. The expected cross section for SM t¯tt¯t production is σSMt¯tt¯t≈1fb. A combination of kinematic reconstruction and multivariate techniques is used to distinguish between the small signal and large background. We determined that the data are consistent with expectations of the SM, and an upper limit of 32 fb is set at a 95% confidence level on the cross section for producing four top quarks in the SM, where a limit of 32 ± 17 fb is expected.

  11. Search for the Standard Model Higgs boson in the H to tau+ tau- decay mode in sqrt(s) = 7 TeV pp collisions with ATLAS

    DOE PAGES

    Aad, Georges

    2014-11-12

    A search for the neutral Higgs bosons predicted by the Minimal Supersymmetric Standard Model (MSSM) is reported. The analysis is performed on data from proton-proton collisions at a centre-of-mass energy of 8TeV collected with the ATLAS detector at the Large Hadron Collider. The samples used for this search were collected in 2012 and correspond to integrated luminosities in the range 19.5-20.3 fb-1. The MSSM Higgs bosons are searched for in the τ τ final state. No significant excess over the expected background is observed, and exclusion limits are derived for the production cross section times branching fraction of a scalarmore » particle as a function of its mass. The results are also interpreted in the MSSM parameter space for various benchmark scenarios.« less

  12. Search for the Standard Model Higgs boson in the H to tau+ tau- decay mode in sqrt(s) = 7 TeV pp collisions with ATLAS

    SciTech Connect

    Aad, Georges

    2014-11-12

    A search for the neutral Higgs bosons predicted by the Minimal Supersymmetric Standard Model (MSSM) is reported. The analysis is performed on data from proton-proton collisions at a centre-of-mass energy of 8TeV collected with the ATLAS detector at the Large Hadron Collider. The samples used for this search were collected in 2012 and correspond to integrated luminosities in the range 19.5-20.3 fb-1. The MSSM Higgs bosons are searched for in the τ τ final state. No significant excess over the expected background is observed, and exclusion limits are derived for the production cross section times branching fraction of a scalar particle as a function of its mass. The results are also interpreted in the MSSM parameter space for various benchmark scenarios.

  13. A class of cellular automata modeling winnerless competition

    NASA Astrophysics Data System (ADS)

    Afraimovich, V.; Ordaz, F. C.; Urías, J.

    2002-06-01

    Neural units introduced by Rabinovich et al. ("Sensory coding with dynamically competitive networks," UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift.

  14. Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models

    PubMed Central

    Nasserinejad, Kazem; van Rosmalen, Joost; de Kort, Wim; Lesaffre, Emmanuel

    2017-01-01

    Identifying the number of classes in Bayesian finite mixture models is a challenging problem. Several criteria have been proposed, such as adaptations of the deviance information criterion, marginal likelihoods, Bayes factors, and reversible jump MCMC techniques. It was recently shown that in overfitted mixture models, the overfitted latent classes will asymptotically become empty under specific conditions for the prior of the class proportions. This result may be used to construct a criterion for finding the true number of latent classes, based on the removal of latent classes that have negligible proportions. Unlike some alternative criteria, this criterion can easily be implemented in complex statistical models such as latent class mixed-effects models and multivariate mixture models using standard Bayesian software. We performed an extensive simulation study to develop practical guidelines to determine the appropriate number of latent classes based on the posterior distribution of the class proportions, and to compare this criterion with alternative criteria. The performance of the proposed criterion is illustrated using a data set of repeatedly measured hemoglobin values of blood donors. PMID:28081166

  15. Stochastic models of cover class dynamics. [remote sensing of vegetation

    NASA Technical Reports Server (NTRS)

    Barringer, T. H.; Robinson, V. B.

    1981-01-01

    Investigations related to satellite remote sensing of vegetation have been concerned with questions of signature identification and extension, cover inventory accuracy, and change detection and monitoring. Attention is given to models of ecological succession, present directions in successional modeling and analysis, nondynamic spatial models, issues in the analysis of spatial data, and aspects of spatial modeling. Issues in time-series analysis are considered along with dynamic spatial models, and problems of model specification and identification.

  16. Time-dependent modelling of the Markarian 501 X-ray and TeV gamma-ray data taken during 1997 March and April

    NASA Astrophysics Data System (ADS)

    Krawczynski, H.; Coppi, P. S.; Aharonian, F.

    2002-11-01

    If the high-energy emission from TeV blazars is produced by the Synchrotron Self-Compton (SSC) mechanism, then simultaneous X-ray and gamma-ray observations of these objects are a powerful probe of the electron (and positron) populations responsible for this emission. Understanding the emitting particle distributions and their temporal evolution in turn allows us to probe physical conditions in the inner blazar jet and test, for example, various acceleration scenarios. Furthermore, by constraining the SSC model parameters, such observations enable us to predict the intrinsic (unabsorbed) gamma-ray energy spectra of these sources, a major uncertainty in current attempts to use gamma-ray observations to constrain the intensity of the Diffuse Extragalactic Background Radiation (DEBRA) at optical/infrared wavelengths. As a next step in testing the SSC model and as a demonstration of the potential power of coordinated X-ray and gamma-ray observations, we model in detail the X-ray and gamma-ray light curves of the TeV blazar Mrk 501 during its 1997 April-May outburst with a time-dependent SSC model. Extensive, quasi-simultaneous X-ray and gamma-ray coverage exists for this period. We discuss and explore quantitatively several of the flare scenarios presented in the literature. We show that simple two-component models (with a soft, steady X-ray component plus a variable SSC component) involving substantial pre-acceleration of electrons to Lorentz factors on the order of γmin= 105 describe the data train surprisingly well. All considered models imply an emission region that is strongly out of equipartition and low radiative efficiencies (ratio between kinetic jet luminosity and comoving radiative luminosity) of 1 per-mill and less. Degeneracy in both, model variant and jet parameters, prevents us from using the time-resolved SSC calculations to tighten substantially the constraints on the amount of extragalactic gamma-ray extinction by the DEBRA in the relevant 0.5-50

  17. The Biplot as a diagnostic tool of local dependence in latent class models. A medical application.

    PubMed

    Sepúlveda, R; Vicente-Villardón, J L; Galindo, M P

    2008-05-20

    Latent class models (LCMs) can be used to assess diagnostic test performance when no reference test (a gold standard) is available, considering two latent classes representing disease or non-disease status. One of the basic assumptions in such models is that of local or conditional independence: all indicator variables (tests) are statistically independent within each latent class. However, in practice this assumption is often violated; hence, the two-LCM fits the data poorly. In this paper, we propose the use of Biplot methods to identify the conditional dependence between pairs of manifest variables within each latent class. Additionally, we propose incorporating such dependence in the corresponding latent class using the log-linear formulation of the model.

  18. On the initial value problem for a class of discrete velocity models.

    PubMed

    Bellandi, Davide

    2017-02-01

    In this paper we investigate the initial value problem for a class of hyperbolic systems relating the mathematical modeling of a class of complex phenomena, with emphasis on vehicular traffic flow. Existence and uniqueness for large times of solutions, a basic requisite both for models building and for their numerical implementation, are obtained under weak hypotheses on the terms modeling the interaction among agents. The results are then compared with the existing literature on the subject.

  19. Showcasing Modeling Strategies in the ESOL Writing Class: Blending Rhetorical Fluency with Grammatical Accuracy

    ERIC Educational Resources Information Center

    Pandey, Anjali

    2010-01-01

    This paper argues for an overt innovational shift in praxis, as well as classroom configuration in the ESOL writing class by calling for a move away from the current foci on process-based pedagogies for newcomer populations, to an explicit teaching of modeling strategies with concomitant practice opportunities provided in the ESOL writing class.…

  20. Evaluation of the Curriculum of English Preparatory Classes at Yildiz Technical University Using CIPP Model

    ERIC Educational Resources Information Center

    Akpur, Ugur; Alci, Bülent; Karatas, Hakan

    2016-01-01

    The purpose of this study is to evaluate the instruction program of preparatory classes at Yildiz Technical University using CIPP model. A total of 54 teachers and 753 university students attending preparatory classes in the Academic Year of 2014-2015 formed the study group. The research is based on a questionnaire applied to teachers and…

  1. A Connectionist Model of Stimulus Class Formation with a Yes/No Procedure and Compound Stimuli

    ERIC Educational Resources Information Center

    Tovar, Angel E.; Chavez, Alvaro Torres

    2012-01-01

    We analyzed stimulus class formation in a human study and in a connectionist model (CM) with a yes/no procedure, using compound stimuli. In the human study, the participants were six female undergraduate students; the CM was a feed-forward back-propagation network. Two 3-member stimulus classes were trained with a similar procedure in both the…

  2. Who Plans to Go to University? Statistical Modelling of Potential Working-Class Participants

    ERIC Educational Resources Information Center

    Collier, Tim; Gilchrist, Robert; Phillips, David

    2003-01-01

    This article develops a model for potential working-class applicants to university, using multinomial logit regression to analyse a national UK sample, drawn from lower middle and working-class adults aged 16-30. Influential factors are belief in ability, preference for university rather than earning money, qualifications and family encouragement;…

  3. Bottomonium suppression at sNN=2.76 TeV using a model based on color screening and gluonic dissociation with collisional damping

    NASA Astrophysics Data System (ADS)

    Ganesh, S.; Mishra, M.

    2013-10-01

    We present a model to explain the bottomonium suppression in Pb+Pb collisions at midrapidity obtained from Large Hadron Collider (LHC) energy, sNN=2.76 TeV. The model consists of two decoupled mechanisms, namely, color screening during bottomonium production followed by gluon induced dissociation along with collisional damping. The quasiparticle model (QPM) is used as equation of state (EOS) for the quark-gluon plasma (QGP) medium. The feed-down from higher Υ states, such as Υ(1P), Υ(2S), and Υ(2P), dilated formation times for bottomonium states, and viscous effect of the QGP medium are other ingredients included in the current formulation. We further assume that the QGP is expanding according to (1+1)-dimensional Bjorken's boost invariant scaling law. The net suppression (in terms of pT integrated survival probability) for bottomonium states at midrapidity is obtained as a function of centrality, and the result is then compared both quantitatively and qualitatively with the recent LHC experimental data in the midrapidity region recently published by the CMS Collaboration. We find that the current model, based on Debye color screening plus gluonic dissociation along with collisional damping, better describes the centrality dependence of bottomonium suppression at LHC energy as compared to the color screening model alone.

  4. Combined results of searches for the standard model Higgs boson in pp collisions at sqrt(s) = 7 TeV

    SciTech Connect

    Chatrchyan, Serguei; et al.

    2012-03-01

    Combined results are reported from searches for the standard model Higgs boson in proton-proton collisions at sqrt(s)=7 TeV in five Higgs boson decay modes: gamma pair, b-quark pair, tau lepton pair, W pair, and Z pair. The explored Higgs boson mass range is 110-600 GeV. The analysed data correspond to an integrated luminosity of 4.6-4.8 inverse femtobarns. The expected excluded mass range in the absence of the standard model Higgs boson is 118-543 GeV at 95% CL. The observed results exclude the standard model Higgs boson in the mass range 127-600 GeV at 95% CL, and in the mass range 129-525 GeV at 99% CL. An excess of events above the expected standard model background is observed at the low end of the explored mass range making the observed limits weaker than expected in the absence of a signal. The largest excess, with a local significance of 3.1 sigma, is observed for a Higgs boson mass hypothesis of 124 GeV. The global significance of observing an excess with a local significance greater than 3.1 sigma anywhere in the search range 110-600 (110-145) GeV is estimated to be 1.5 sigma (2.1 sigma). More data are required to ascertain the origin of this excess.

  5. Search for the standard model Higgs boson decaying into two photons in pp collisions at sqrt(s)=7 TeV

    SciTech Connect

    Chatrchyan, S.; et al.,

    2012-04-01

    A search for a Higgs boson decaying into two photons is described. The analysis is performed using a dataset recorded by the CMS experiment at the LHC from pp collisions at a centre-of-mass energy of 7 TeV, which corresponds to an integrated luminosity of 4.8 inverse femtobarns. Limits are set on the cross section of the standard model Higgs boson decaying to two photons. The expected exclusion limit at 95% confidence level is between 1.4 and 2.4 times the standard model cross section in the mass range between 110 and 150 GeV. The analysis of the data excludes, at 95% confidence level, the standard model Higgs boson decaying into two photons in the mass range 128 to 132 GeV. The largest excess of events above the expected standard model background is observed for a Higgs boson mass hypothesis of 124 GeV with a local significance of 3.1 sigma. The global significance of observing an excess with a local significance greater than 3.1 sigma anywhere in the search range 110-150 GeV is estimated to be 1.8 sigma. More data are required to ascertain the origin of this excess.

  6. ELASTIC SCATTERING OF PROTONS FROM $\\sqrt{s} = 23.5~{\\rm GeV}$ to 7 TeV FROM A GENERALIZED BIALAS-BZDAK MODEL

    NASA Astrophysics Data System (ADS)

    Csörgő, T.; Nemes, F.

    2014-01-01

    The Bialas-Bzdak model of elastic proton-proton scattering is generalized to the case when the real part of the parton-parton level forward scattering amplitude is nonvanishing. Such a generalization enables the model to describe well the dip region of the differential cross-section of elastic scattering at the intersecting storage rings (ISR) energies, and improves significantly the ability of the model to describe also the recent TOTEM data at √ {s} = 7 TeV LHC energy. Within this framework, both the increase of the total cross-section, as well as the decrease of the location of the dip with increasing colliding energies, is related to the increase of the quark-diquark distance and to the increase of the "fragility" of the protons with increasing energies. In addition, we present and test the validity of two new phenomenological relations: one of them relates the total p+p cross-section to an effective, model-independent proton radius, while the other relates the position of the dip in the differential elastic cross-section to the measured value of the total cross-section.

  7. Inferring Markov chains: Bayesian estimation, model comparison, entropy rate, and out-of-class modeling.

    PubMed

    Strelioff, Christopher C; Crutchfield, James P; Hübler, Alfred W

    2007-07-01

    Markov chains are a natural and well understood tool for describing one-dimensional patterns in time or space. We show how to infer kth order Markov chains, for arbitrary k , from finite data by applying Bayesian methods to both parameter estimation and model-order selection. Extending existing results for multinomial models of discrete data, we connect inference to statistical mechanics through information-theoretic (type theory) techniques. We establish a direct relationship between Bayesian evidence and the partition function which allows for straightforward calculation of the expectation and variance of the conditional relative entropy and the source entropy rate. Finally, we introduce a method that uses finite data-size scaling with model-order comparison to infer the structure of out-of-class processes.

  8. Theory and Practice: An Integrative Model Linking Class and Field

    ERIC Educational Resources Information Center

    Lesser, Joan Granucci; Cooper, Marlene

    2006-01-01

    Social work has evolved over the years taking on the challenges of the times. The profession now espouses a breadth of theoretical approaches and treatment modalities. We have developed a model to help graduate social work students master the skill of integrating theory and social work practice. The Integrative Model has five components: (l) The…

  9. Crossvalidation of Latent Class Models of Early Substance Use Onset.

    ERIC Educational Resources Information Center

    Collins, Linda M.; And Others

    1994-01-01

    Using cross-validation to test covariance structure models is illustrated through selecting models of early substance use onset in a sample of 3,643 adolescents. Results suggest that the use process is similar for males and females in seventh grade. They also suggest that double cross-validation is greatly preferable to single cross-validation.…

  10. Deriving the Dividend Discount Model in the Intermediate Microeconomics Class

    ERIC Educational Resources Information Center

    Norman, Stephen; Schlaudraff, Jonathan; White, Karianne; Wills, Douglas

    2013-01-01

    In this article, the authors show that the dividend discount model can be derived using the basic intertemporal consumption model that is introduced in a typical intermediate microeconomics course. This result will be of use to instructors who teach microeconomics to finance students in that it demonstrates the value of utility maximization in…

  11. Search for a two-Higgs-boson doublet using a simplified model in pp collisions at sqrt[s] = 1.96 TeV.

    PubMed

    Aaltonen, T; Adelman, J; Álvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Bae, T; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bedeschi, F; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Bisello, D; Bizjak, I; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Bromberg, C; Brucken, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Calamba, A; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chung, W H; Chung, Y S; Ciocci, M A; Clark, A; Clarke, C; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuevas, J; Culbertson, R; Dagenhart, D; d'Ascenzo, N; Datta, M; de Barbaro, P; Dell'Orso, M; Demortier, L; Deninno, M; Devoto, F; d'Errico, M; Di Canto, A; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, M; Dorigo, T; Ebina, K; Elagin, A; Eppig, A; Erbacher, R; Errede, S; Ershaidat, N; Eusebi, R; Farrington, S; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Funakoshi, Y; Furic, I; Gallinaro, M; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Grinstein, S; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Hahn, S R; Halkiadakis, E; Hamaguchi, A; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Hewamanage, S; Hocker, A; Hopkins, W; Horn, D; Hou, S; Hughes, R E; Hurwitz, M; Husemann, U; Hussain, N; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jindariani, S; Johnstone, A; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kim, Y J; Kimura, N; Kirby, M; Klimenko, S; Knoepfel, K; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Kruse, M; Krutelyov, V; Kuhr, T; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; LeCompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lin, C-J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, H; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maeshima, K; Maestro, P; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Martínez, M; Mastrandrea, P; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Noh, S Y; Norniella, O; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Paramonov, A A; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Prokoshin, F; Pranko, A; Ptohos, F; Punzi, G; Rahaman, A; Ramakrishnan, V; Ranjan, N; Rao, K; Redondo, I; Renton, P; Rescigno, M; Riddick, T; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Safonov, A; Sakumoto, W K; Sakurai, Y; Santi, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shochet, M; Shreyber-Tecker, I; Simonenko, A; Sinervo, P; Sliwa, K; Smith, J R; Snider, F D; Soha, A; Sorin, V; Song, H; Squillacioti, P; Stancari, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Truong, A; Ukegawa, F; Uozumi, S; Varganov, A; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wagner, R L; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Wester, W C; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Wick, F; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamato, D; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zhou, C; Zucchelli, S

    2013-03-22

    We present a search for new particles in an extension to the standard model that includes a heavy Higgs boson (H(0)), a lighter charged Higgs boson (H(±)), and an even lighter Higgs boson h(0), with decays leading to a W-boson pair and a bottom-antibottom quark pair in the final state. We use events with exactly one lepton, missing transverse momentum, and at least four jets in data corresponding to an integrated luminosity of 8.7 fb(-1) collected by the CDF II detector in proton-antiproton collisions at sqrt[s]= 1.96 TeV. We find the data to be consistent with standard model predictions and report the results in terms of a simplified Higgs-cascade-decay model, setting 95% confidence level upper limits on the product of cross section and branching fraction from 1.3 pb to 15 fb as a function of H(0) and H(±) masses for m(h)(0) = 126 GeV/c(2).

  12. Search for a Two-Higgs-Boson Doublet Using a Simplified Model in pp̄ Collisions at √s=1.96 TeV

    DOE PAGES

    Aaltonen, T.; Adelman, J.; Álvarez González, B.; ...

    2013-03-18

    We present a search for new particles in an extension to the standard model that includes a heavy Higgs boson (H⁰), a lighter charged Higgs boson (H±), and an even lighter Higgs boson h⁰, with decays leading to a W-boson pair and a bottom-antibottom quark pair in the final state. We use events with exactly one lepton, missing transverse momentum, and at least four jets in data corresponding to an integrated luminosity of 8.7 fb⁻¹ collected by the CDF II detector in proton-antiproton collisions at √s=1.96 TeV. We find the data to be consistent with standard model predictions and reportmore » the results in terms of a simplified Higgs-cascade-decay model, setting 95% confidence level upper limits on the product of cross section and branching fraction from 1.3 pb to 15 fb as a function of H⁰ and H± masses for m⁰h=126 GeV/c²« less

  13. Search for a Two-Higgs-Boson Doublet Using a Simplified Model in pp̄ Collisions at √s=1.96 TeV

    SciTech Connect

    Aaltonen, T.; Adelman, J.; Álvarez González, B.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Appel, J. A.; Arisawa, T.; Artikov, A.; Asaadi, J.; Ashmanskas, W.; Auerbach, B.; Aurisano, A.; Azfar, F.; Badgett, W.; Bae, T.; Barbaro-Galtieri, A.; Barnes, V. E.; Barnett, B. A.; Barria, P.; Bartos, P.; Bauce, M.; Bedeschi, F.; Behari, S.; Bellettini, G.; Bellinger, J.; Benjamin, D.; Beretvas, A.; Bhatti, A.; Bisello, D.; Bizjak, I.; Bland, K. R.; Blumenfeld, B.; Bocci, A.; Bodek, A.; Bortoletto, D.; Boudreau, J.; Boveia, A.; Brigliadori, L.; Bromberg, C.; Brucken, E.; Budagov, J.; Budd, H. S.; Burkett, K.; Busetto, G.; Bussey, P.; Buzatu, A.; Calamba, A.; Calancha, C.; Camarda, S.; Campanelli, M.; Campbell, M.; Canelli, F.; Carls, B.; Carlsmith, D.; Carosi, R.; Carrillo, S.; Carron, S.; Casal, B.; Casarsa, M.; Castro, A.; Catastini, P.; Cauz, D.; Cavaliere, V.; Cavalli-Sforza, M.; Cerri, A.; Cerrito, L.; Chen, Y. C.; Chertok, M.; Chiarelli, G.; Chlachidze, G.; Chlebana, F.; Cho, K.; Chokheli, D.; Chung, W. H.; Chung, Y. S.; Ciocci, M. A.; Clark, A.; Clarke, C.; Compostella, G.; Convery, M. E.; Conway, J.; Corbo, M.; Cordelli, M.; Cox, C. A.; Cox, D. J.; Crescioli, F.; Cuevas, J.; Culbertson, R.; Dagenhart, D.; d’Ascenzo, N.; Datta, M.; de Barbaro, P.; Dell’Orso, M.; Demortier, L.; Deninno, M.; Devoto, F.; d’Errico, M.; Di Canto, A.; Di Ruzza, B.; Dittmann, J. R.; D’Onofrio, M.; Donati, S.; Dong, P.; Dorigo, M.; Dorigo, T.; Ebina, K.; Elagin, A.; Eppig, A.; Erbacher, R.; Errede, S.; Ershaidat, N.; Eusebi, R.; Farrington, S.; Feindt, M.; Fernandez, J. P.; Field, R.; Flanagan, G.; Forrest, R.; Frank, M. J.; Franklin, M.; Freeman, J. C.; Funakoshi, Y.; Furic, I.; Gallinaro, M.; Garcia, J. E.; Garfinkel, A. F.; Garosi, P.; Gerberich, H.; Gerchtein, E.; Giagu, S.; Giakoumopoulou, V.; Giannetti, P.; Gibson, K.; Ginsburg, C. M.; Giokaris, N.; Giromini, P.; Giurgiu, G.; Glagolev, V.; Glenzinski, D.; Gold, M.; Goldin, D.; Goldschmidt, N.; Golossanov, A.; Gomez, G.; Gomez-Ceballos, G.; Goncharov, M.; González, O.; Gorelov, I.; Goshaw, A. T.; Goulianos, K.; Grinstein, S.; Grosso-Pilcher, C.; Group, R. C.; Guimaraes da Costa, J.; Hahn, S. R.; Halkiadakis, E.; Hamaguchi, A.; Han, J. Y.; Happacher, F.; Hara, K.; Hare, D.; Hare, M.; Harr, R. F.; Hatakeyama, K.; Hays, C.; Heck, M.; Heinrich, J.; Herndon, M.; Hewamanage, S.; Hocker, A.; Hopkins, W.; Horn, D.; Hou, S.; Hughes, R. E.; Hurwitz, M.; Husemann, U.; Hussain, N.; Hussein, M.; Huston, J.; Introzzi, G.; Iori, M.; Ivanov, A.; James, E.; Jang, D.; Jayatilaka, B.; Jeon, E. J.; Jindariani, S.; Johnstone, A.; Jones, M.; Joo, K. K.; Jun, S. Y.; Junk, T. R.; Kamon, T.; Karchin, P. E.; Kasmi, A.; Kato, Y.; Ketchum, W.; Keung, J.; Khotilovich, V.; Kilminster, B.; Kim, D. H.; Kim, H. S.; Kim, J. E.; Kim, M. J.; Kim, S. B.; Kim, S. H.; Kim, Y. K.; Kim, Y. J.; Kimura, N.; Kirby, M.; Klimenko, S.; Knoepfel, K.; Kondo, K.; Kong, D. J.; Konigsberg, J.; Kotwal, A. V.; Kreps, M.; Kroll, J.; Krop, D.; Kruse, M.; Krutelyov, V.; Kuhr, T.; Kurata, M.; Kwang, S.; Laasanen, A. T.; Lami, S.; Lammel, S.; Lancaster, M.; Lander, R. L.; Lannon, K.; Lath, A.; Latino, G.; LeCompte, T.; Lee, E.; Lee, H. S.; Lee, J. S.; Lee, S. W.; Leo, S.; Leone, S.; Lewis, J. D.; Limosani, A.; Lin, C.-J.; Lindgren, M.; Lipeles, E.; Lister, A.; Litvintsev, D. O.; Liu, C.; Liu, H.; Liu, Q.; Liu, T.; Lockwitz, S.; Loginov, A.; Lucchesi, D.; Lueck, J.; Lujan, P.; Lukens, P.; Lungu, G.; Lys, J.; Lysak, R.; Madrak, R.; Maeshima, K.; Maestro, P.; Malik, S.; Manca, G.; Manousakis-Katsikakis, A.; Margaroli, F.; Marino, C.; Martínez, M.; Mastrandrea, P.; Matera, K.; Mattson, M. E.; Mazzacane, A.; Mazzanti, P.; McFarland, K. S.; McIntyre, P.; McNulty, R.; Mehta, A.; Mehtala, P.; Mesropian, C.; Miao, T.; Mietlicki, D.; Mitra, A.; Miyake, H.; Moed, S.; Moggi, N.; Mondragon, M. N.; Moon, C. S.; Moore, R.; Morello, M. J.; Morlock, J.; Movilla Fernandez, P.; Mukherjee, A.; Muller, Th.; Murat, P.; Mussini, M.; Nachtman, J.; Nagai, Y.; Naganoma, J.; Nakano, I.; Napier, A.; Nett, J.; Neu, C.; Neubauer, M. S.; Nielsen, J.; Nodulman, L.; Noh, S. Y.; Norniella, O.; Oakes, L.; Oh, S. H.; Oh, Y. D.; Oksuzian, I.; Okusawa, T.; Orava, R.; Ortolan, L.; Pagan Griso, S.; Pagliarone, C.; Palencia, E.; Papadimitriou, V.; Paramonov, A. A.; Patrick, J.; Pauletta, G.; Paulini, M.; Paus, C.; Pellett, D. E.; Penzo, A.; Phillips, T. J.; Piacentino, G.; Pianori, E.; Pilot, J.; Pitts, K.; Plager, C.; Pondrom, L.; Poprocki, S.; Potamianos, K.; Prokoshin, F.; Pranko, A.; Ptohos, F.; Punzi, G.; Rahaman, A.; Ramakrishnan, V.; Ranjan, N.; Rao, K.; Redondo, I.; Renton, P.; Rescigno, M.; Riddick, T.; Rimondi, F.; Ristori, L.; Robson, A.; Rodrigo, T.; Rodriguez, T.; Rogers, E.; Rolli, S.; Roser, R.; Ruffini, F.; Ruiz, A.; Russ, J.; Rusu, V.; Safonov, A.; Sakumoto, W. K.; Sakurai, Y.; Santi, L.; Sato, K.; Saveliev, V.; Savoy-Navarro, A.; Schlabach, P.; Schmidt, A.; Schmidt, E. E.; Schwarz, T.; Scodellaro, L.; Scribano, A.; Scuri, F.; Seidel, S.; Seiya, Y.; Semenov, A.; Sforza, F.; Shalhout, S. Z.; Shears, T.; Shepard, P. F.; Shimojima, M.; Shochet, M.; Shreyber-Tecker, I.; Simonenko, A.; Sinervo, P.; Sliwa, K.; Smith, J. R.; Snider, F. D.; Soha, A.; Sorin, V.; Song, H.; Squillacioti, P.; Stancari, M.; Denis, R. St.; Stelzer, B.; Stelzer-Chilton, O.; Stentz, D.; Strologas, J.; Strycker, G. L.; Sudo, Y.; Sukhanov, A.; Suslov, I.; Takemasa, K.; Takeuchi, Y.; Tang, J.; Tecchio, M.; Teng, P. K.; Thom, J.; Thome, J.; Thompson, G. A.; Thomson, E.; Toback, D.; Tokar, S.; Tollefson, K.; Tomura, T.; Tonelli, D.; Torre, S.; Torretta, D.; Totaro, P.; Trovato, M.; Truong, A.; Ukegawa, F.; Uozumi, S.; Varganov, A.; Vázquez, F.; Velev, G.; Vellidis, C.; Vidal, M.; Vila, I.; Vilar, R.; Vizán, J.; Vogel, M.; Volpi, G.; Wagner, P.; Wagner, R. L.; Wakisaka, T.; Wallny, R.; Wang, S. M.; Warburton, A.; Waters, D.; Wester, W. C.; Whiteson, D.; Wicklund, A. B.; Wicklund, E.; Wilbur, S.; Wick, F.; Williams, H. H.; Wilson, J. S.; Wilson, P.; Winer, B. L.; Wittich, P.; Wolbers, S.; Wolfe, H.; Wright, T.; Wu, X.; Wu, Z.; Yamamoto, K.; Yamato, D.; Yang, T.; Yang, U. K.; Yang, Y. C.; Yao, W.-M.; Yeh, G. P.; Yi, K.; Yoh, J.; Yorita, K.; Yoshida, T.; Yu, G. B.; Yu, I.; Yu, S. S.; Yun, J. C.; Zanetti, A.; Zeng, Y.; Zhou, C.; Zucchelli, S.

    2013-03-18

    We present a search for new particles in an extension to the standard model that includes a heavy Higgs boson (H⁰), a lighter charged Higgs boson (H±), and an even lighter Higgs boson h⁰, with decays leading to a W-boson pair and a bottom-antibottom quark pair in the final state. We use events with exactly one lepton, missing transverse momentum, and at least four jets in data corresponding to an integrated luminosity of 8.7 fb⁻¹ collected by the CDF II detector in proton-antiproton collisions at √s=1.96 TeV. We find the data to be consistent with standard model predictions and report the results in terms of a simplified Higgs-cascade-decay model, setting 95% confidence level upper limits on the product of cross section and branching fraction from 1.3 pb to 15 fb as a function of H⁰ and H± masses for m⁰h=126 GeV/c²

  14. Search for standard model Higgs bosons decaying to w-boson pairs in proton-anti-proton collisions at √s= 1.96 TeV

    SciTech Connect

    Hidas, Dean Andrew

    2008-01-01

    This thesis describes a search for standard model Higgs bosons decaying to W boson pairs in proton-anti-proton collisions at a center of mass energy of 1.96 TeV using the CDF II detector. The decay to W bosons is dominant for Higgs masses greater than about 135 GeV. The final state examined consists of two leptons and missing transverse energy from the leptonic decay of one or more W bosons. The signal production mechanisms included are gluon fusion, associated production with a W or Z boson, and vector boson fusion. Matrix element calculations and artificial neural networks are used to discriminate signal from background for Higgs masses in the range 110 ≤MH ≤ 200 GeV. No significant excess of events is observed at any of the Higgs masses investigated. Upper limits on the standard model Higgs cross section are set at 95% confidence for each Higgs mass investigated, the most stringent limit being 1.63 times the predicted standard model cross section for a Higgs mass of 160 GeV.

  15. Search for the Standard Model Higgs Boson Decaying to Bottom Quarks in Proton-Proton Collisions at 8 TeV

    NASA Astrophysics Data System (ADS)

    Silkworth, Inga

    A search for the standard model Higgs boson (H) decaying to bottom quarks and produced in association with a Z boson is presented. The search uses 8 TeV center-of-mass energy proton-proton collision data recorded by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to integrated luminosity of 19.0 inverse femtobarns. The Z boson is reconstructed using two oppositely charged leptons -- either electrons or muons. Two techniques for reconstructing the Higgs candidate are discussed: the standard method using two jets reconstructed with the anti-kt algorithm and a second technique using jet substructure that was developed for highly boosted massive particles. Upper limits, at the 95% confidence level, on the production cross section times the branching ratio, with respect to the standard model expectations, are derived for a Higgs boson in a mass range 110-135 GeV. The results from the ZH channel are combined with five other channels, and an excess of events is observed consistent with the standard model Higgs boson with a local significance of 2.1 standard deviations at 125 GeV.

  16. Modeling self-consistent multi-class dynamic traffic flow

    NASA Astrophysics Data System (ADS)

    Cho, Hsun-Jung; Lo, Shih-Ching

    2002-09-01

    In this study, we present a systematic self-consistent multiclass multilane traffic model derived from the vehicular Boltzmann equation and the traffic dispersion model. The multilane domain is considered as a two-dimensional space and the interaction among vehicles in the domain is described by a dispersion model. The reason we consider a multilane domain as a two-dimensional space is that the driving behavior of road users may not be restricted by lanes, especially motorcyclists. The dispersion model, which is a nonlinear Poisson equation, is derived from the car-following theory and the equilibrium assumption. Under the concept that all kinds of users share the finite section, the density is distributed on a road by the dispersion model. In addition, the dynamic evolution of the traffic flow is determined by the systematic gas-kinetic model derived from the Boltzmann equation. Multiplying Boltzmann equation by the zeroth, first- and second-order moment functions, integrating both side of the equation and using chain rules, we can derive continuity, motion and variance equation, respectively. However, the second-order moment function, which is the square of the individual velocity, is employed by previous researches does not have physical meaning in traffic flow. Although the second-order expansion results in the velocity variance equation, additional terms may be generated. The velocity variance equation we propose is derived from multiplying Boltzmann equation by the individual velocity variance. It modifies the previous model and presents a new gas-kinetic traffic flow model. By coupling the gas-kinetic model and the dispersion model, a self-consistent system is presented.

  17. Mathematical modeling of a class of multibody flexible spacecraft structures

    NASA Technical Reports Server (NTRS)

    Kelkar, Atul, G.

    1994-01-01

    A mathematical model for a general multibody flexible spacecraft is obtained. The generic spacecraft considered consists of a flexible central body to which a number of flexible multibody structures are attached. The coordinate systems used in the derivation allow effective decoupling of the translational motion of the entire spacecraft from its rotational motion about its center of mass. The derivation assumes that the deformations in the bodies are only due to elastic motions. The dynamic model derived is a closed-form vector-matrix differential equation. The model developed can be used for analysis and simulation of many realistic spacecraft configurations.

  18. A Simple Class of Bayesian Nonparametric Autoregression Models.

    PubMed

    Di Lucca, Maria Anna; Guglielmi, Alessandra; Müller, Peter; Quintana, Fernando A

    2013-03-01

    We introduce a model for a time series of continuous outcomes, that can be expressed as fully nonparametric regression or density regression on lagged terms. The model is based on a dependent Dirichlet process prior on a family of random probability measures indexed by the lagged covariates. The approach is also extended to sequences of binary responses. We discuss implementation and applications of the models to a sequence of waiting times between eruptions of the Old Faithful Geyser, and to a dataset consisting of sequences of recurrence indicators for tumors in the bladder of several patients.

  19. On the Use of Covariates in a Latent Class Signal Detection Model, with Applications to Constructed Response Scoring

    ERIC Educational Resources Information Center

    Wang, Zijian Gerald

    2012-01-01

    A latent class signal detection (SDT) model was recently introduced as an alternative to traditional item response theory (IRT) methods in the analysis of constructed response data. This class of models can be represented as restricted latent class models and differ from the IRT approach in the way the latent construct is conceptualized. One…

  20. Lindley frailty model for a class of compound Poisson processes

    NASA Astrophysics Data System (ADS)

    Kadilar, Gamze Özel; Ata, Nihal

    2013-10-01

    The Lindley distribution gain importance in survival analysis for the similarity of exponential distribution and allowance for the different shapes of hazard function. Frailty models provide an alternative to proportional hazards model where misspecified or omitted covariates are described by an unobservable random variable. Despite of the distribution of the frailty is generally assumed to be continuous, it is appropriate to consider discrete frailty distributions In some circumstances. In this paper, frailty models with discrete compound Poisson process for the Lindley distributed failure time are introduced. Survival functions are derived and maximum likelihood estimation procedures for the parameters are studied. Then, the fit of the models to the earthquake data set of Turkey are examined.

  1. Class Evolution Tree: a graphical tool to support decisions on the number of classes in exploratory categorical latent variable modeling for rehabilitation research.

    PubMed

    Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

    2011-06-01

    The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was carried out in patients with cancer receiving an inpatient rehabilitation program to identify prototypical combinations of treatment elements. In the second study, growth mixture modeling was used to identify latent trajectory classes based on weekly symptom severity measurements during inpatient treatment of patients with mental disorders. A graphical tool, the Class Evolution Tree, was developed, and its central components were described. The Class Evolution Tree can be used in addition to statistical criteria to systematically address the issue of number of classes in explorative categorical latent variable modeling.

  2. Likelihood analysis of spatial capture-recapture models for stratified or class structured populations

    USGS Publications Warehouse

    Royle, J. Andrew; Sutherland, Christopher S.; Fuller, Angela K.; Sun, Catherine C.

    2015-01-01

    We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which frequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values. We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containing sex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.

  3. Search for Standard Model Higgs Boson Produced in Association with a Top-Antitop Quark Pair in 1.96 TeV Proton-Antiproton Collisions

    SciTech Connect

    Lai, Stanley T.

    2007-01-01

    This thesis describes the first search for Standard Model Higgs boson production in association with a top-antitop quark pair in proton-antiproton collisions at a centre of mass energy of 1.96 TeV. The integrated luminosity for othis search corresponds to 319 pb-1 of data recorded by the Collider Detector at Fermilab. We outline the even selection criteria, evaluate the even acceptance and estimate backgrounds from Standard Model sources. These events are observed that satisfy our event selection, while 2.16 ± 0.66 events are expected from background processes. no significant excess of events above background is thus observed, and we set 95% confidence level upper limits on the production cross section for this process as a function of the Higgs mass. For a Higgs boson mass of 115 GeV/c2 we find that σ$t\\bar{t}H$ x BR (Hbb) < 690 fb at 95% C.L. These are the first limits set for $t\\bar{t}H$ production. This search also allows us to anticipate the challenges and necessary strategies needed for future searches of $t\\bar{t}H$ production.

  4. Search for the standard model Higgs boson in the decay channel H→ZZ→4ℓ in pp collisions at √s=7 TeV.

    PubMed

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Pierro, G A; Ross, I; Savin, A; Smith, W H; Swanson, J

    2012-03-16

    A search for a Higgs boson in the four-lepton decay channel H→ZZ, with each Z boson decaying to an electron or muon pair, is reported. The search covers Higgs boson mass hypotheses in the range of 110TeV from the LHC. Seventy-two events are observed with four-lepton invariant mass m(4ℓ)>100 GeV (with 13 below 160 GeV), while 67.1±6.0 (9.5±1.3) events are expected from background. The four-lepton mass distribution is consistent with the expectation of standard model background production of ZZ pairs. Upper limits at 95% confidence level exclude the standard model Higgs boson in the ranges of 134-158 GeV, 180-305 GeV, and 340-465 GeV. Small excesses of events are observed around masses of 119, 126, and 320 GeV, making the observed limits weaker than expected in the absence of a signal.

  5. Interpretation of distributions on Kpi0 in pFe, nFe, and piFe interactions at 0.5-5.0 TeV in the framework of contemporary models

    NASA Astrophysics Data System (ADS)

    Avakyan, V. V.; Garyaka, A. P.; Zazyan, G. Z.

    Fluctuations of the observable parameters of nuclear electromagnetic cascades induced by 0.5-5.0 TeV cosmic ray protons, neutrons and pions are studied by the ionization calorimeter of the PION setup. The distributions of the inelasticity coefficient Kpi0 are measured for pFe, nFe and (pi)Fe interactions and compared with the predictions of various models. The probability of the inelastic charge exchange reaction in the (pi)Fe interactions is defined.

  6. Climate Ocean Modeling on a Beowulf Class System

    NASA Technical Reports Server (NTRS)

    Cheng, B. N.; Chao, Y.; Wang, P.; Bondarenko, M.

    2000-01-01

    With the growing power and shrinking cost of personal computers. the availability of fast ethernet interconnections, and public domain software packages, it is now possible to combine them to build desktop parallel computers (named Beowulf or PC clusters) at a fraction of what it would cost to buy systems of comparable power front supercomputer companies. This led as to build and assemble our own sys tem. specifically for climate ocean modeling. In this article, we present our experience with such a system, discuss its network performance, and provide some performance comparison data with both HP SPP2000 and Cray T3E for an ocean Model used in present-day oceanographic research.

  7. Dynamic behaviors of a class of HIV compartmental models

    NASA Astrophysics Data System (ADS)

    Chen, Xiaoyan; Huang, Lihong; Yu, Pei

    2015-06-01

    Based on heterogeneities in drug efficacy (either spatial or phenotypic), two HIV compartmental models were proposed in Callaway and Perelson (2002) to study the HIV virus dynamics under drug treatment. In this paper, we provide a global analysis on the two models, including the positivity and boundedness of solutions and the global stability of equilibrium solutions. In particular, we show that when the basic reproduction number R0 ⩽ 1 (for which the infection equilibrium does not exist), the infection-free equilibrium is globally asymptotically stable; while when R0 > 1 (for which the infection equilibrium exists), the infection equilibrium is globally asymptotically stable.

  8. A class of three-loop models with neutrino mass and dark matter

    NASA Astrophysics Data System (ADS)

    Chen, Chian-Shu; McDonald, Kristian L.; Nasri, Salah

    2014-06-01

    We study a class of three-loop models for neutrino mass in which dark matter plays a key role in enabling the mass diagram. The simplest models in this class have Majorana dark matter and include the proposal of Krauss, Nasri and Trodden; we identify the remaining related models, including the viable colored variants. The next-to-simplest models use either more multiplets and/or a slight modification of the loop-diagram, and predict inert N-tuplet scalar dark matter.

  9. Constraints on the pMSSM, AMSB model and on other models from the search for long-lived charged particles in proton-proton collisions at √s = 8 TeV

    SciTech Connect

    Khachatryan, Vardan

    2015-07-17

    Stringent limits are set on the long-lived lepton-like sector of the phenomenological minimal supersymmetric standard model (pMSSM) and the anomaly-mediated supersymmetry breaking (AMSB) model. We derived the limits from the results presented in a recent search for long-lived charged particles in proton–proton collisions, based on data collected by the CMS detector at a centre-of-mass energy of 8 TeV at the Large Hadron Collider. In the pMSSM parameter sub-space considered, 95.9 % of the points predicting charginos with a lifetime of at least 10 ns are excluded. Furthermore, these constraints on the pMSSM are the first obtained at the LHC. Charginos with a lifetime greater than 100 ns and masses up to about 800 GeV in the AMSB model are also excluded. Furthermore, the method described can also be used to set constraints on other models.

  10. Search for the neutral Higgs bosons of the minimal supersymmetric standard model in pp collisions at sqrt{s}=7 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abajyan, T.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdelalim, A. A.; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alam, M. A.; Albert, J.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alonso, F.; Altheimer, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amelung, C.; Ammosov, V. V.; Amor dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angelidakis, S.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aoun, S.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Arfaoui, S.; Arguin, J.-F.; Argyropoulos, S.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Atkinson, M.; Aubert, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Axen, D.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Mayes, J. Backus; Badescu, E.; Bagnaia, P.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartsch, V.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beale, S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Begel, M.; Harpaz, S. Behar; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertella, C.; Bertin, A.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bittner, B.; Black, C. W.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blocki, J.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boek, T. T.; Boelaert, N.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Bolnet, N. M.; Bomben, M.; Bona, M.; Boonekamp, M.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozovic-Jelisavcic, I.; Bracinik, J.; Branchini, P.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Brelier, B.; Bremer, J.; Brendlinger, K.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Broggi, F.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brown, G.; de Renstrom, P. A. Bruckman; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchanan, J.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Budick, B.; Büscher, V.; Bugge, L.; Bulekov, O.; Bundock, A. C.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Byszewski, M.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Caloi, R.; Calvet, D.; Calvet, S.; Toro, R. Camacho; Camarri, P.; Cameron, D.; Caminada, L. MCaminal .; Armadans, R.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Cantrill, R.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capriotti, D.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Cascella, M.; Caso, C.; Castaneda Hernandez, A. M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N. F.; Cataldi, G.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chan, K.; Chang, P.; Chapleau, B.; Chapman, J. D.; Chapman, J. W.; Charlton, D. G.; Chavda, V.; Barajas, C. A. Chavez; Cheatham, S.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, X.; Chen, Y.; Cheng, Y.; Cheplakov, A.; El Moursli, R. Cherkaoui; Chernyatin, V.; Cheu, E.; Cheung, S. L.; Chevalier, L.; Chiefari, G.; Chikovani, L.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Choudalakis, G.; Chouridou, S.; Christidi, I. A.; Christov, A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirilli, M.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Colas, J.; Cole, S.; Colijn, A. P.; Collins, N. J.; Collins-Tooth, C.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Courneyea, L.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crescioli, F.; Cristinziani, M.; Crosetti, G.; Crépé-Renaudin, S.; Cuciuc, C.-M.; Cuenca Almenar, C.; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Curtis, C. J.; Cuthbert, C.; Cwetanski, P.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dameri, M.; Damiani, D. S.; Danielsson, H. O.; Dao, V.; Darbo, G.; Darlea, G. L.; Dassoulas, J. A.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Cecco, S.; de Graat, J.; De Groot, N.; de Jong, P.; De La Taille, C.; De la Torre, H.; De Lorenzi, F.; De Nooij, L.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; De Zorzi, G.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Degenhardt, J.; Del Peso, J.; Del Prete, T.; Delemontex, T.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Devetak, E.; Deviveiros, P. O.; Dewhurst, A.; DeWilde, B.; Dhaliwal, S.; Dhullipudi, R.; Di Ciaccio, A.; Di Ciaccio, L.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Luise, S.; Di Mattia, A.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dinut, F.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; do Vale, M. A. B.; Wemans, A. Do Valle; Doan, T. K. O.; Dobbs, M.; Dobos, D.; Dobson, E.; Dodd, J.; Doglioni, C.; Doherty, T.; Doi, Y.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Dohmae, T.; Donadelli, M.; Donini, J.; Dopke, J.; Doria, A.; Anjos, A. Dos; Dotti, A.; Dova, M. T.; Doxiadis, A. D.; Doyle, A. T.; Dressnandt, N.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Duda, D.; Dudarev, A.; Dudziak, F.; Dührssen, M.; Duerdoth, I. P.; Duflot, L.; Dufour, M.-A.; Duguid, L.; Dunford, M.; Duran Yildiz, H.; Duxfield, R.; Dwuznik, M.; Düren, M.; Ebenstein, W. L.; Ebke, J.; Eckweiler, S.; Edson, W.; Edwards, C. A.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Eisenhandler, E.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Engelmann, R.; Engl, A.; Epp, B.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Curull, X. Espinal; Esposito, B.; Etienne, F.; Etienvre, A. I.; Etzion, E.; Evangelakou, D.; Evans, H.; Fabbri, L.; Fabre, C.; Fakhrutdinov, R. M.; Falciano, S.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farley, J.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Fatholahzadeh, B.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feligioni, L.; Feng, C.; Feng, E. J.; Fenyuk, A. B.; Ferencei, J.; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filthaut, F.; Fincke-Keeler, M.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, G.; Fisher, M. J.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleckner, J.; Fleischmann, P.; Fleischmann, S.; Fletcher, G.; Flick, T.; Floderus, A.; Castillo, L. R. Flores; Florez Bustos, A. C.; Flowerdew, M. J.; Fonseca Martin, T.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fowler, A. J.; Fox, H.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Frank, T.; Franklin, M.; Franz, S.; Fraternali, M.; Fratina, S.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fulsom, B. 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D.; Hayakawa, T.; Hayashi, T.; Hayden, D.; Hays, C. P.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Hedberg, V.; Heelan, L.; Heim, S.; Heinemann, B.; Heisterkamp, S.; Helary, L.; Heller, C.; Heller, M.; Hellman, S.; Hellmich, D.; Helsens, C.; Henderson, R. C. W.; Henke, M.; Henrichs, A.; Henriques Correia, A. M.; Henrot-Versille, S.; Hensel, C.; Hernandez, C. M.; Hernández Jiménez, Y.; Herrberg, R.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hickling, R.; Higón-Rodriguez, E.; Hill, J. C.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirsch, F.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoffman, J.; Hoffmann, D.; Hohlfeld, M.; Holder, M.; Holmgren, S. O.; Holy, T.; Holzbauer, J. L.; Hong, T. M.; Hooft van Huysduynen, L.; Horner, S.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hsu, P. 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A.; Scarcella, M.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schäfer, U.; Schaelicke, A.; Schaepe, S.; Schaetzel, S.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schioppa, M.; Schlenker, S.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schorlemmer, A. L. S.; Schott, M.; Schouten, D.; Schovancova, J.; Schram, M.; Schroeder, C.; Schroer, N.; Schultens, M. J.; Schultes, J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwegler, Ph.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Schwoerer, M.; Sciacca, F. G.; Scifo, E.; Sciolla, G.; Scott, W. G.; Searcy, J.; Sedov, G.; Sedykh, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekula, S. J.; Selbach, K. E.; Seliverstov, D. M.; Sellden, B.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Seuster, R.; Severini, H.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Sherman, D.; Sherwood, P.; Shimizu, S.; Shimojima, M.; Shin, T.; Shiyakova, M.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simoniello, R.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sircar, A.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skottowe, H. P.; Skovpen, K.; Skubic, P.; Slater, M.; Slavicek, T.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snyder, S.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E. Yu.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Solovyev, V.; Soni, N.; Sood, A.; Sopko, V.; Sopko, B.; Sosebee, M.; Soualah, R.; Soueid, P.; Soukharev, A.; South, D.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; Denis, R. D. St.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Staude, A.; Stavina, P.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stern, S.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Styles, N. A.; Soh, D. A.; Su, D.; Subramania, HS.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Suzuki, Y.; Svatos, M.; Swedish, S.; Sykora, I.; Sykora, T.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tani, K.; Tannoury, N.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tayalati, Y.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teinturier, M.; Teischinger, F. A.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thong, W. M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Triplett, N.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; True, P.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tudorache, A.; Tudorache, V.; Tuggle, J. M.; Turala, M.; Turecek, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Uhlenbrock, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urquijo, P.; Usai, G.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Gallego, E. Valladolid; Vallecorsa, S.; Valls Ferrer, J. A.; Van Berg, R.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; Van Der Leeuw, R.; van der Poel, E.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Schroeder, T. Vazquez; Vegni, G.; Veillet, J. J.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Virzi, J.; Vitells, O.; Viti, M.; Vivarelli, I.; Vaque, F. Vives; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorwerk, V.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wahrmund, S.; Wakabayashi, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Walsh, B.; Wang, C.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, R.; Wang, S. M.; Wang, T.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watanabe, I.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, M. S.; Webster, J. S.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Wessels, M.; Wetter, J.; Weydert, C.; Whalen, K.; White, A.; White, M. J.; White, S.; Whitehead, S. R.; Whiteson, D.; Whittington, D.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilhelm, I.; Wilkens, H. G.; Will, J. Z.; Williams, E.; Williams, H. H.; Williams, S.; Willis, W.; Willocq, S.; Wilson, J. A.; Wilson, M. G.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wong, W. C.; Wooden, G.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wraight, K.; Wright, M.; Wrona, B.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wynne, B. M.; Xella, S.; Xiao, M.; Xie, S.; Xu, C.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamada, M.; Yamaguchi, H.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamauchi, K.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, L.; Yasu, Y.; Yatsenko, E.; Ye, J.; Ye, S.; Yen, A. L.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J.; Youssef, S.; Yu, D.; Yu, D. R.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zanello, L.; Zanzi, D.; Zaytsev, A.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zenin, O.; Ženiš, T.; Zinonos, Z.; Zerwas, D.; Zevi della Porta, G.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zibell, A.; Zieminska, D.; Zimin, N. I.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zutshi, V.; Zwalinski, L.

    2013-02-01

    A search for neutral Higgs bosons of the Minimal Supersymmetric Standard Model (MSSM) is reported. The analysis is based on a sample of proton-proton collisions at a centre-of-mass energy of 7 TeV recorded with the ATLAS detector at the Large Hadron Collider. The data were recorded in 2011 and correspond to an integrated luminosity of 4.7 fb-1 to 4.8 fb-1. Higgs boson decays into oppositely-charged muon or τ lepton pairs are considered for final states requiring either the presence or absence of b-jets. No statistically significant excess over the expected background is observed and exclusion limits at the 95% confidence level are derived. The exclusion limits are for the production cross-section of a generic neutral Higgs boson, ϕ, as a function of the Higgs boson mass and for h/ A/ H production in the MSSM as a function of the parameters m A and tan β in the m_h^{max } scenario for m A in the range of 90 GeV to 500 GeV.[Figure not available: see fulltext.

  11. Search for the standard model Higgs boson produced in association with W and Z bosons in pp collisions at √{s}=7 TeV

    NASA Astrophysics Data System (ADS)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Aguilo, E.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hammer, J.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesen-hofer, W.; Knünz, V.; Krammer, M.; Liko, D.; Mikulec, I.; Pernicka, M.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Waltenberger, W.; Walzel, G.; Widl, E.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Staykova, Z.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Reis, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Verwilligen, P.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Castello, R.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Schul, N.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins, M.; De Jesus Damiao, D.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Oliveira Martins, C.; Fonseca De Souza, S.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Oguri, V.; Prado Da Silva, W. L.; Santoro, A.; Soares Jorge, L.; Sznajder, A.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, S.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, D.; Zhang, L.; Zhu, B.; Zou, W.; Avila, C.; Gomez, J. P.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Morovic, S.; Attikis, A.; Galanti, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Khalil, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Müntel, M.; Raidal, M.; Rebane, L.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Heikkinen, A.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Ungaro, D.; Wendland, L.; Banzuzi, K.; Karjalainen, A.; Korpela, A.; Tuuva, T.; Besancon, M.; Choudhury, S.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Millischer, L.; Nayak, A.; Rander, J.; Rosowsky, A.; Shreyber, I.; Titov, M.; Baffioni, S.; Beaudette, F.; Benhabib, L.; Bianchini, L.; Bluj, M.; Broutin, C.; Busson, P.; Charlot, C.; Daci, N.; Dahms, T.; Dobrzynski, L.; Granier de Cassagnac, R.; Haguenauer, M.; Miné, P.; Mironov, C.; Nguyen, M.; Ochando, C.; Paganini, P.; Sabes, D.; Salerno, R.; Sirois, Y.; Veelken, C.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Bodin, D.; Brom, J.-M.; Cardaci, M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Ferro, C.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Juillot, P.; Le Bihan, A.-C.; Van Hove, P.; Fassi, F.; Mercier, D.; Beauceron, S.; Beaupere, N.; Bondu, O.; Boudoul, G.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Sordini, V.; Tschudi, Y.; Verdier, P.; Viret, S.; Tsamalaidze, Z.; Anagnostou, G.; Beranek, S.; Edelhoff, M.; Feld, L.; Heracleous, N.; Hindrichs, O.; Jussen, R.; Klein, K.; Merz, J.; Ostapchuk, A.; Perieanu, A.; Raupach, F.; Sammet, J.; Schael, S.; Sprenger, D.; Weber, H.

    2012-11-01

    A search for the Higgs boson produced in association with a W or Z boson in proton-proton collisions at a center-of-mass energy of 7 TeV is performed with the CMS detector at the LHC using the full 2011 data sample, from an integrated luminosity of 5 fb-1. Higgs boson decay modes to ττ and WW are explored by selecting events with three or four leptons in the final state. No excess above background expectations is observed, resulting in exclusion limits on the product of Higgs associated production cross section and decay branching fraction for Higgs boson masses between 110 and 200 GeV in these channels. Combining these results with other CMS associated production searches using the same dataset in the H→ γγ and H→ b overline{b} decay modes, the cross section for associated Higgs boson production 3.3 times the standard model expectation or larger is ruled out at the 95% confidence level for a Higgs boson mass of 125 GeV.[Figure not available: see fulltext.

  12. Achieving World-Class Schools: Mastering School Improvement Using a Genetic Model.

    ERIC Educational Resources Information Center

    Kimmelman, Paul L.; Kroeze, David J.

    In providing its program for education reform, this book uses, as an analogy, the genetic model taken from the Human Genome project. In the first part, "Theoretical Underpinnings," the book explains why a genetic model can be used to improve school systems; describes the critical components of a world-class school system; and details the…

  13. Academic Achievement Effects of an In-Class Service Model on Students with and without Disabilities.

    ERIC Educational Resources Information Center

    Saint-Laurent, Lise; Dionne, Jean; Giasson, Jocelyne; Royer, Egide; Simard, Claude; Pierard, Brigitte

    1998-01-01

    This study evaluated an in-class service model for third graders at risk of school failure in 13 schools. The model included collaborative consultation, cooperative teaching, parent involvement, and strategic and adapted instruction. Significant effects were found on writing scores for students at risk (but not students with learning disabilities)…

  14. Educational Criteria for Evaluating Simple Class Diagrams Made by Novices for Conceptual Modeling

    ERIC Educational Resources Information Center

    Kayama, Mizue; Ogata, Shinpei; Asano, David K.; Hashimoto, Masami

    2016-01-01

    Conceptual modeling is one of the most important learning topics for higher education and secondary education. The goal of conceptual modeling in this research is to draw a class diagram using given notation to satisfy the given requirements. In this case, the subjects are asked to choose concepts to satisfy the given requirements and to correctly…

  15. A nonparametric vs. latent class model of general practitioner utilization: evidence from Canada.

    PubMed

    McLeod, Logan

    2011-12-01

    Predicting health care utilization is the foundation of many health economics analyses, such as calculating risk-adjustment capitation payments or measuring equity in health care utilization. The most common econometric models of physician utilization are parametric count data models, since the most common metric of physician utilization is the number of physician visits. This paper makes two distinct contributions to the literature analyzing GP utilization: (i) it is the first to use a nonparametric kernel conditional density estimator to model GP utilization and compare the predicted utilization with that from a latent class negative binomial model; and (ii) it uses panel data to control for the potential endogeneity between self-reported health status and the number of GP visits. The goodness-of-fit results show the kernel conditional density estimator provides a better fit to the observed distribution of GP visits than the latent class negative binomial model. There are some meaningful differences in how the predicted conditional mean number of GP visits changes with a change in an individual's characteristics, called the incremental effect (IE), between the kernel conditional density estimator and the latent class negative binomial model. The most notable differences are observed in the right tail of the distribution where the IEs from the latent class negative binomial model are up to 190 times the magnitude of the IEs from the kernel conditional density estimator.

  16. A general model of invariant chain association with class II major histocompatibility complex proteins.

    PubMed Central

    Lee, C; McConnell, H M

    1995-01-01

    The binding of invariant chain to major histocompatibility complex (MHC) proteins is an important step in processing of MHC class II proteins and in antigen presentation. The question of how invariant chain can bind to all MHC class II proteins is central to understanding these processes. We have employed molecular modeling to predict the structure of class II-associated invariant chain peptide (CLIP)-MHC protein complexes and to ask whether the predicted mode of association could be general across all MHC class II proteins. CLIP fits identically into the MHC class II alleles HLA-DR3, I-Ak, I-Au, and I-Ad, with a consistent pattern of hydrogen bonds, contacts, and hydrophobic burial and without bad contacts. Our model predicts the burial of CLIP residues Met-91 and Met-99 in the deep P1 and P9 anchor pockets and other detailed interactions, which we have compared with available data. The predicted pattern of I-A allele-specific effects on CLIP binding is very similar to that observed experimentally by alanine-scanning mutations of CLIP. Together, these results indicate that CLIP may bind in a single, general way across products of MHC class II alleles. Images Fig. 1 Fig. 2 Fig. 3 PMID:7667280

  17. Managerial performance and cost efficiency of Japanese local public hospitals: a latent class stochastic frontier model.

    PubMed

    Besstremyannaya, Galina

    2011-09-01

    The paper explores the link between managerial performance and cost efficiency of 617 Japanese general local public hospitals in 1999-2007. Treating managerial performance as unobservable heterogeneity, the paper employs a panel data stochastic cost frontier model with latent classes. Financial parameters associated with better managerial performance are found to be positively significant in explaining the probability of belonging to the more efficient latent class. The analysis of latent class membership was consistent with the conjecture that unobservable technological heterogeneity reflected in the existence of the latent classes is related to managerial performance. The findings may support the cause for raising efficiency of Japanese local public hospitals by enhancing the quality of management.

  18. An evaluation of the use of covariates to assist in class enumeration in linear growth mixture modeling.

    PubMed

    Hu, Jinxiang; Leite, Walter L; Gao, Miao

    2017-03-08

    This study examined whether the inclusion of covariates that predict class membership improves class identification in a growth mixture modeling (GMM). We manipulated the degree of class separation, sample size, the magnitude of covariate effect on class membership, the covariance between the intercept and the slope, and fit two models with covariates and an unconditional model. We concluded that correct class identification in GMM requires large sample sizes and class separation, and that unconditional GMM performs better than GMM with covariates if the sample size and class separation are sufficiently large. With small sample sizes, GMM with covariates outperformed unconditional GMM, but the percentage of correct class enumeration was low across different fit criteria.

  19. School climate and bullying victimization: a latent class growth model analysis.

    PubMed

    Gage, Nicholas A; Prykanowski, Debra A; Larson, Alvin

    2014-09-01

    Researchers investigating school-level approaches for bullying prevention are beginning to discuss and target school climate as a construct that (a) may predict prevalence and (b) be an avenue for school-wide intervention efforts (i.e., increasing positive school climate). Although promising, research has not fully examined and established the social-ecological link between school climate factors and bullying/peer aggression. To address this gap, we examined the association between school climate factors and bullying victimization for 4,742 students in Grades 3-12 across 3 school years in a large, very diverse urban school district using latent class growth modeling. Across 3 different models (elementary, secondary, and transition to middle school), a 3-class model was identified, which included students at high-risk for bullying victimization. Results indicated that, for all students, respect for diversity and student differences (e.g., racial diversity) predicted within-class decreases in reports of bullying. High-risk elementary students reported that adult support in school was a significant predictor of within-class reduction of bullying, and high-risk secondary students report peer support as a significant predictor of within-class reduction of bullying.

  20. Estimation of Parameters in Latent Class Models with Constraints on the Parameters.

    DTIC Science & Technology

    1986-06-01

    the item parameters. Let us briefly review the elements of latent class models. The reader desiring a thorough introduction can consult Lazarsfeld and...parameters, including most of the models which have been proposed to date. The latent distance model of Lazarsfeld and Henry (1968) and the quasi...Psychometrika, 1964, 29, 115-129. Lazarsfeld , P.F., and Henry, N.W. Latent structure analysis. Boston: Houghton-Mifflin, 1968. L6. - 29 References continued

  1. Dynamics of a Class of HIV Infection Models with Cure of Infected Cells in Eclipse Stage.

    PubMed

    Maziane, Mehdi; Lotfi, El Mehdi; Hattaf, Khalid; Yousfi, Noura

    2015-12-01

    In this paper, we propose two HIV infection models with specific nonlinear incidence rate by including a class of infected cells in the eclipse phase. The first model is described by ordinary differential equations (ODEs) and generalizes a set of previously existing models and their results. The second model extends our ODE model by taking into account the diffusion of virus. Furthermore, the global stability of both models is investigated by constructing suitable Lyapunov functionals. Finally, we check our theoretical results with numerical simulations.

  2. Inferring the structure of latent class models using a genetic algorithm.

    PubMed

    van der Maas, Han L J; Raijmakers, Maartje E J; Visser, Ingmar

    2005-05-01

    Present optimization techniques in latent class analysis apply the expectation maximization algorithm or the Newton-Raphson algorithm for optimizing the parameter values of a prespecified model. These techniques can be used to find maximum likelihood estimates of the parameters, given the specified structure of the model, which is defined by the number of classes and, possibly, fixation and equality constraints. The model structure is usually chosen on theoretical grounds. A large variety of structurally different latent class models can be compared using goodness-of-fit indices of the chi-square family, Akaike's information criterion, the Bayesian information criterion, and various other statistics. However, finding the optimal structure for a given goodness-of-fit index often requires a lengthy search in which all kinds of model structures are tested. Moreover, solutions may depend on the choice of initial values for the parameters. This article presents a new method by which one can simultaneously infer the model structure from the data and optimize the parameter values. The method consists of a genetic algorithm in which any goodness-of-fit index can be used as a fitness criterion. In a number of test cases in which data sets from the literature were used, it is shown that this method provides models that fit equally well as or better than the models suggested in the original articles.

  3. Determining the Number of Latent Classes in Single- and Multi-Phase Growth Mixture Models

    PubMed Central

    Kim, Su-Young

    2014-01-01

    Stage-sequential (or multiphase) growth mixture models are useful for delineating potentially different growth processes across multiple phases over time and for determining whether latent subgroups exist within a population. These models are increasingly important as social behavioral scientists are interested in better understanding change processes across distinctively different phases, such as before and after an intervention. One of the less understood issues related to the use of growth mixture models is how to decide on the optimal number of latent classes. The performance of several traditionally used information criteria for determining the number of classes is examined through a Monte Carlo simulation study in single- and multi-phase growth mixture models. For thorough examination, the simulation was carried out in two perspectives: the models and the factors. The simulation in terms of the models was carried out to see the overall performance of the information criteria within and across the models, while the simulation in terms of the factors was carried out to see the effect of each simulation factor on the performance of the information criteria holding the other factors constant. The findings not only support that sample size adjusted BIC (ADBIC) would be a good choice under more realistic conditions, such as low class separation, smaller sample size, and/or missing data, but also increase understanding of the performance of information criteria in single- and multi-phase growth mixture models. PMID:24729675

  4. Search for the Standard Model Higgs boson in its associated production with a W vector boson in pp collisions at (s) = 1.96TeV

    NASA Astrophysics Data System (ADS)

    Hegab, Hatim H.

    In this dissertation, results from a search for the Standard Model (SM) Higgs boson, at the DZERO experiment is shown. The SM is the theoretical framework which describes particles of matter and force carrier gauge bosons. To solve the mass problem in the SM, the Higgs mechanism was introduced. The Higgs mechanism causes an electroweak symmetry breaking and a new massive scalar boson was postulated. This particle is the Higgs boson. A search for the Higgs boson has been ongoing at the Tevatron where protons and antiprotons were allowed to collide at a center-of-mass energy of 1.96 TeV. For a low mass Higgs that is lower than 135 GeV, the dominant decay mode is Higgs to a pair of b-quarks. Work in this dissertation concentrated on a Higgs in the mass range of 100 - 150 GeV, where a W vector boson is produced in association with the Higgs boson. The final state chosen is one which contains a lepton (electron or a muon) a neutrino and a pair of b-quarks. This study used data provided by the DZERO experiment and computing resources provided by Fermilab. Results presented here are the outcome of analyzing 5.3 inverse-fb of data from RunII period. The analysis used different techniques to increase the sensitivity of the study. Data were subdivided based on lepton flavor, number of jets in sample, jets identified as b -jets and dates of collected data. A multivariate analysis technique based on boosted decision trees were used to separate signal from background processes, physical and instrumental. A good agreement between data and simulated events was observed. An observed (expected) upper limit of 4.5 (4.8) for a Higgs of mass 115 GeV was set on the ratio of the Higgs production to its decay branching ratio at the 95% confidence level.

  5. It Takes One to Know One: A Class Exercise in Mental Models

    ERIC Educational Resources Information Center

    Wilson, Theresa

    2014-01-01

    An active learning class exercise is presented that gives students the personal experience of the decision-making limitations of mental models. This innovative exercise was shown to increase student learning through greater understanding of the concept and higher retention of knowledge. The results suggest that student critical thinking skills…

  6. Modeling Individual Differences in Unfolding Preference Data: A Restricted Latent Class Approach.

    ERIC Educational Resources Information Center

    Bockenholt, Ulf; Bockenholt, Ingo

    1990-01-01

    A latent-class scaling approach is presented for modeling paired comparison and "pick any/t" data obtained in preference studies. The utility of this approach is demonstrated through analysis of data from studies involving consumer preference and preference for political candidates. (SLD)

  7. Comparison of Maximum Likelihood and Pearson Chi-Square Statistics for Assessing Latent Class Models.

    ERIC Educational Resources Information Center

    Holt, Judith A.; Macready, George B.

    When latent class parameters are estimated, maximum likelihood and Pearson chi-square statistics can be derived for assessing the fit of the model to the data. This study used simulated data to compare these two statistics, and is based on mixtures of latent binomial distributions, using data generated from five dichotomous manifest variables.…

  8. The Effect of the Green Class Model on Environmental Knowledge and Its Retention

    ERIC Educational Resources Information Center

    Uzun, Naim

    2009-01-01

    The purpose of the study is to investigate the effects of an applied environmental education project carried out using the green-class model on students' environmental knowledge and its retention. 101 7th grade students attending Nazim Akcan Primary School in the Altindag Province of Ankara participated in the study. The study was carried out in…

  9. A Class of Multidimensional IRT Models for Testing Unidimensionality and Clustering Items

    ERIC Educational Resources Information Center

    Bartolucci, Francesco

    2007-01-01

    We illustrate a class of multidimensional item response theory models in which the items are allowed to have different discriminating power and the latent traits are represented through a vector having a discrete distribution. We also show how the hypothesis of unidimensionality may be tested against a specific bidimensional alternative by using a…

  10. Mathematical Modelling: A Path to Political Reflection in the Mathematics Class

    ERIC Educational Resources Information Center

    Jacobini, Otavio Roberto; Wodewotzki, Maria Lucia L.

    2006-01-01

    This paper describes the construction of pedagogical environments in mathematics classes, centred on mathematical modelling and denominated "investigative scenarios", which stimulate students to investigation, to formulation of problems and to political reflection, as well as the sharing of acquired knowledge with other persons in the community.…

  11. Design, Development and Validation of a Model of Problem Solving for Egyptian Science Classes

    ERIC Educational Resources Information Center

    Shahat, Mohamed A.; Ohle, Annika; Treagust, David F.; Fischer, Hans E.

    2013-01-01

    Educators and policymakers envision the future of education in Egypt as enabling learners to acquire scientific inquiry and problem-solving skills. In this article, we describe the validation of a model for problem solving and the design of instruments for evaluating new teaching methods in Egyptian science classes. The instruments were based on…

  12. Using a Student-Manipulated Model to Enhance Student Learning in a Large Lecture Class

    ERIC Educational Resources Information Center

    Gray, Kyle; Steer, David; McConnell, David; Owens, Katharine

    2010-01-01

    Despite years of formal education, approximately one-third of all undergraduate students still cannot explain the causes of the seasons. Student manipulation of a handheld model is one approach to teaching this concept; however, the large number of students in many introductory classes can dissuade instructors from utilizing this teaching…

  13. World-Class Higher Education and the Emerging Chinese Model of the University

    ERIC Educational Resources Information Center

    Li, Jun

    2012-01-01

    China's recent quest to develop world-class universities is a significant phenomenon within the worldwide transformation of tertiary education. Taking a cultural approach and drawing on empirical findings, this article investigates the emerging Chinese model of the university, considering its key features and contributions to global communities.…

  14. Understanding Korean Transnational Girls in High School Science Classes: Beyond the Model Minority Stereotype

    ERIC Educational Resources Information Center

    Ryu, Minjung

    2015-01-01

    This study examines six Korean transnational girls enrolled in two advanced placement (AP) biology classes to understand their experiences in science classrooms at the intersection of race, language, and gender. Confronting the model minority stereotype for Asian students, which is particularly salient in science, technology, engineering, and…

  15. The Structure of Student Satisfaction with College Services: A Latent Class Model

    ERIC Educational Resources Information Center

    Adwere-Boamah, Joseph

    2011-01-01

    Latent Class Analysis (LCA) was used to identify distinct groups of Community college students based on their self-ratings of satisfaction with student service programs. The programs were counseling, financial aid, health center, student programs and student government. The best fitting model to describe the data was a two Discrete-Factor model…

  16. Diagram, a Learning Environment for Initiation to Object-Oriented Modeling with UML Class Diagrams

    ERIC Educational Resources Information Center

    Py, Dominique; Auxepaules, Ludovic; Alonso, Mathilde

    2013-01-01

    This paper presents Diagram, a learning environment for object-oriented modelling (OOM) with UML class diagrams. Diagram an open environment, in which the teacher can add new exercises without constraints on the vocabulary or the size of the diagram. The interface includes methodological help, encourages self-correcting and self-monitoring, and…

  17. The Use of Cooperative Round Robin Discussion Model to Improve Students' Holistic Ability in TEFL Class

    ERIC Educational Resources Information Center

    Asari, Slamet; Ma'rifah, Ulfatul; Arifani, Yudhi

    2017-01-01

    This classroom action research is carried out within two cycles to breed a strategy on how a" Round Robin Discussion Learning Model" enhance students' critical thinking, presentation skills, confidence, and independent learning in Teaching English as a Foreign Language (TEFL) class. Pop-up quiz, teacher made-tests, classroom…

  18. Bayesian Inference for Growth Mixture Models with Latent Class Dependent Missing Data

    ERIC Educational Resources Information Center

    Lu, Zhenqiu Laura; Zhang, Zhiyong; Lubke, Gitta

    2011-01-01

    "Growth mixture models" (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class…

  19. A Mixture Rasch Model-Based Computerized Adaptive Test for Latent Class Identification

    ERIC Educational Resources Information Center

    Jiao, Hong; Macready, George; Liu, Junhui; Cho, Youngmi

    2012-01-01

    This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback-Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was…

  20. The Effect of Direct Instruction Model on Intermediate Class Achievement and Attitudes toward English Grammar

    ERIC Educational Resources Information Center

    Kousar, Rubina

    2010-01-01

    This study was aimed at investigating the effect of the direct instruction model on intermediate class achievement and attitudes toward English grammar. It was an experimental study and the purpose was to explore the relative effectiveness of instructional methodology (independent variable) on students' achievement and attitude (dependent…

  1. Social Class and Pedagogy: A Model for the Investigation of Pedagogic Variation

    ERIC Educational Resources Information Center

    Hoadley, Ursula

    2008-01-01

    This article addresses an enduring concern in the sociology of education: how social class differences are reproduced through schooling. In particular it focuses on the functioning of pedagogy in this regard. The article presents a model that elucidates the inner logic of pedagogy in order to reveal the structuring of inequality with respect to…

  2. Search for the minimal universal extra dimension model at the LHC with {radical}(s)=7 TeV

    SciTech Connect

    Bhattacherjee, Biplob; Ghosh, Kirtiman

    2011-02-01

    The Universal Extra Dimension (UED) model is one of the popular extension of the standard model (SM) which offers interesting phenomenology. In the minimal UED (mUED) model, Kaluza-Klein (KK) parity conservation ensures that n=1 KK states can only be pair produced at colliders and the lightest KK particle is stable. In most of the parameter space, first KK excitation of SM hypercharge gauge boson is the lightest one and it can be a viable dark matter candidate. Thus, the decay of n=1 KK particles will always involve missing transverse energy.

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

  4. Stochastic models and numerical algorithms for a class of regulatory gene networks.

    PubMed

    Fournier, Thomas; Gabriel, Jean-Pierre; Pasquier, Jerôme; Mazza, Christian; Galbete, José; Mermod, Nicolas

    2009-08-01

    Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

  5. Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

    PubMed

    Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

    2015-09-01

    Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

  6. Adulthood Social Class and Union Interest: A First Test of a Theoretical Model.

    PubMed

    Mellor, Steven

    2016-10-02

    A serial mediation model of union interest was tested. Based on theoretical notes provided by Mellor and Golay (in press), adulthood social class was positioned as a predictor of willingness to join a labor union, with success/failure attributions at work and willingness to share work goals positioned as intervening variables. Data from U.S. nonunion employees (N = 560) suggested full mediation after effects were adjusted for childhood social class. In sequence, adulthood social class predicted success/failure attributions at work, success/failure attributions at work predicted willingness to share work goals, and willingness to share work goals predicted willingness to join. Implications for socioeconomic status (SES) research and union expansion are discussed.

  7. Z boson pair production at the LHC to O(α) in TeV scale gravity models

    NASA Astrophysics Data System (ADS)

    Agarwal, Neelima; Ravindran, V.; Tiwari, Vivek Kumar; Tripathi, Anurag

    2010-05-01

    The first results on next-to-leading order QCD corrections to production of two Z bosons in hadronic collisions in the large extra dimension ADD model are presented. Various kinematical distributions are obtained to order α in QCD by taking into account all the parton level subprocesses. We estimate the impact of the QCD corrections on various observables and find that they are significant. We also show the reduction in factorization scale uncertainty when O(α) effects are included.

  8. Dynamic analysis of a hepatitis B model with three-age-classes

    NASA Astrophysics Data System (ADS)

    Zhang, Suxia; Zhou, Yicang

    2014-07-01

    Based on the fact that the likelihood of becoming chronically infected is dependent on age at primary infection Kane (1995) [2], Edmunds et al. (1993) [3], Medley et al. (2001) [4], and Ganem and Prince (2004) [6], we formulate a hepatitis B transmission model with three age classes. The reproduction number, R0 is defined and the dynamical behavior of the model is analyzed. It is proved that the disease-free equilibrium is globally stable if R0<1, and there exists at least one endemic equilibrium and that the disease is uniformly persistent if R0>1. The unique endemic equilibrium and its global stability is obtained in a special case. Simulations are also conducted to compare the dynamical behavior of the model with and without age classes.

  9. Search for neutral Higgs bosons of the minimal supersymmetric standard model decaying to tau pairs in pp collisions at square root of s = 1.96 TeV.

    PubMed

    Abulencia, A; Acosta, D; Adelman, J; Affolder, T; Akimoto, T; Albrow, M G; Ambrose, D; Amerio, S; Amidei, D; Anastassov, A; Anikeev, K; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Arguin, J-F; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Bachacou, H; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Bedeschi, F; Behari, S; Belforte, S; Bellettini, G; Bellinger, J; Belloni, A; Ben-Haim, E; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bishai, M; Blair, R E; Blocker, C; Bloom, K; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Bourov, S; Boveia, A; Brau, B; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carron, S; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chapman, J; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, I; Cho, K; Chokheli, D; Chou, J P; Chu, P H; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciljak, M; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Coca, M; Connolly, A; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Cruz, A; Cuevas, J; Culbertson, R; Cyr, D; Daronco, S; D'Auria, S; D'onofrio, M; Dagenhart, D; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; Dell'Orso, M; Demers, S; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Dionisi, C; Dittmann, J; Dituro, P; Dörr, C; Dominguez, A; Donati, S; Donega, M; Dong, P; Donini, J; Dorigo, T; Dube, S; Ebina, K; Efron, J; Ehlers, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, I; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Flores-Castillo, L R; Foland, A; Forrester, S; Foster, G W; Franklin, M; Freeman, J C; Fujii, Y; Furic, I; Gajjar, A; Gallinaro, M; Galyardt, J; Garcia, J E; Garcia Sciveres, M; Garfinkel, A F; Gay, C; Gerberich, H; Gerchtein, E; Gerdes, D; Giagu, S; Giannetti, P; Gibson, A; Gibson, K; Ginsburg, C; Giolo, K; Giordani, M; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Goldstein, J; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Gotra, Y; Goulianos, K; Gresele, A; Griffiths, M; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Haber, C; Hahn, S R; Hahn, K; Halkiadakis, E; Hamilton, A; Han, B-Y; Handler, R; Happacher, F; Hara, K; Hare, M; Harper, S; Harr, R F; Harris, R M; Hatakeyama, K; Hauser, J; Hays, C; Hayward, H; Heijboer, A; Heinemann, B; Heinrich, J; Hennecke, M; Herndon, M; Heuser, J; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Holloway, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Huston, J; Ikado, K; Incandela, J; Introzzi, G; Iori, M; Ishizawa, Y; Ivanov, A; Iyutin, B; James, E; Jang, D; Jayatilaka, B; Jeans, D; Jensen, H; Jeon, E J; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Kang, J; Karagoz-Unel, M; Karchin, P E; Kato, Y; Kemp, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, M S; Kim, S B; Kim, S H; Kim, Y K; Kirby, M; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Kobayashi, H; Kondo, K; Kong, D J; Konigsberg, J; Kordas, K; Korytov, A; Kotwal, A V; Kovalev, A; Kraus, J; Kravchenko, I; Kreps, M; Kreymer, A; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kuhlmann, S E; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecci, C; Lecompte, T; Lee, J; Lee, J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Li, K; Lin, C; Lin, C S; Lindgren, M; Lipeles, E; Liss, T M; Lister, A; Litvintsev, D O; Liu, T; Liu, Y; Lockyer, N S; Loginov, A; Loreti, M; Loverre, P; Lu, R-S; Lucchesi, D; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Maksimovic, P; Manca, G; Margaroli, F; Marginean, R; Marino, C; Martin, A; Martin, M; Martin, V; Martínez, M; Maruyama, T; Matsunaga, H; Mattson, M E; Mazini, R; Mazzanti, P; McFarland, K S; McGivern, D; McIntyre, P; McNamara, P; McNulty, R; Mehta, A; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; von der Mey, M; Miao, T; Miladinovic, N; Miles, J; Miller, R; Miller, J S; Mills, C; Milnik, M; Miquel, R; Miscetti, S; Mitselmakher, G; Miyamoto, A; Moggi, N; Mohr, B; Moore, R; Morello, M; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Mulhearn, M; Muller, Th; Mumford, R; Murat, P; Nachtman, J; Nahn, S; Nakano, I; Napier, A; Naumov, D; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nigmanov, T; Nodulman, L; Norniella, O; Ogawa, T; Oh, S H; Oh, Y D; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Pagliarone, C; Palencia, E; Paoletti, R; Papadimitriou, V; Papikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pitts, K; Plager, C; Pondrom, L; Pope, G; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Rakitin, A; Rappoccio, S; Ratnikov, F; Reisert, B; Rekovic, V; van Remortel, N; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Rinnert, K; Ristori, L; Robertson, W J; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Rott, C; Ruiz, A; Russ, J; Rusu, V; Ryan, D; Saarikko, H; Sabik, S; Safonov, A; Sakumoto, W K; Salamanna, G; Salto, O; Saltzberg, D; Sanchez, C; Santi, L; Sarkar, S; Sato, K; Savard, P; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Semeria, F; Sexton-Kennedy, L; Sfiligoi, I; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sill, A; Sinervo, P; Sisakyan, A; Sjolin, J; Skiba, A; Slaughter, A J; Sliwa, K; Smirnov, D; Smith, J R; Snider, F D; Snihur, R; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; Squillacioti, P; Stanitzki, M; Staveris-Polykalas, A; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sumorok, K; Sun, H; Suzuki, T; Taffard, A; Tafirout, R; Takashima, R; Takeuchi, Y; Takikawa, K; Tanaka, M; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Tether, S; Thom, J; Thompson, A S; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tollefson, K; Tomura, T; Tonelli, D; Tönnesmann, M; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tsuchiya, R; Tsuno, S; Turini, N; Ukegawa, F; Unverhau, T; Uozumi, S; Usynin, D; Vacavant, L; Vaiciulis, A; Vallecorsa, S; Varganov, A; Vataga, E; Velev, G; Veramendi, G; Veszpremi, V; Vickey, T; Vidal, R; Vila, I; Vilar, R; Vollrath, I; Volobouev, I; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wallny, R; Walter, T; Wan, Z; Wang, M J; Wang, S M; Warburton, A; Ward, B; Waschke, S; Waters, D; Watts, T; Weber, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Worm, S; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, Y; Yang, C; Yang, U K; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zetti, F; Zhang, X; Zhou, J; Zucchelli, S

    2006-01-13

    We present a search for neutral supersymmetric Higgs bosons decaying to tau pairs produced in pp collisions at square root of s = 1.96 TeV. The data, corresponding to 310 pb(-1) integrated luminosity, were collected with the Collider Detector at Fermilab in run II of the Tevatron. No significant excess above the standard model backgrounds is observed. We set exclusion limits on the production cross section times branching fraction to tau pairs for Higgs boson masses in the range from 90 to 250 GeV/c2.

  10. Search for the Standard Model Higgs boson decaying into $ b\\overline{b} $ produced in association with top quarks decaying hadronically in pp collisions at $ \\sqrt{s}=8 $ TeV with the ATLAS detector

    SciTech Connect

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J. -B.; Blanco, J. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Brunt, BH

    2016-05-01

    In this paper, a search for Higgs boson production in association with a pair of top quarks ($ t\\overline{t} $H) is performed, where the Higgs boson decays to $ b\\overline{b} $ , and both top quarks decay hadronically. The data used correspond to an integrated luminosity of 20.3 fb –1 of pp collisions at √s = 8 TeV collected with the ATLAS detector at the Large Hadron Collider. The search selects events with at least six energetic jets and uses a boosted decision tree algorithm to discriminate between signal and Standard Model background. The dominant multijet background is estimated using a dedicated data-driven technique. For a Higgs boson mass of 125 GeV, an upper limit of 6.4 (5.4) times the Standard Model cross section is observed (expected) at 95% confidence level. The best-fit value for the signal strength is μ = 1.6 ± 2.6 times the Standard Model expectation for mH = 125 GeV. Combining all $ t\\overline{t}$H searches carried out by ATLAS at √s = 8 and 7 TeV, an observed (expected) upper limit of 3.1 (1.4) times the Standard Model expectation is obtained at 95% confidence level, with a signal strength μ = 1.7 ± 0.8.

  11. Search for the Standard Model Higgs boson decaying into $$ b\\overline{b} $$ produced in association with top quarks decaying hadronically in pp collisions at $$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

    DOE PAGES

    Aad, G.; Abbott, B.; Abdallah, J.; ...

    2016-05-01

    In this paper, a search for Higgs boson production in association with a pair of top quarks (more » $$ t\\overline{t} $$H) is performed, where the Higgs boson decays to $$ b\\overline{b} $$ , and both top quarks decay hadronically. The data used correspond to an integrated luminosity of 20.3 fb –1 of pp collisions at √s = 8 TeV collected with the ATLAS detector at the Large Hadron Collider. The search selects events with at least six energetic jets and uses a boosted decision tree algorithm to discriminate between signal and Standard Model background. The dominant multijet background is estimated using a dedicated data-driven technique. For a Higgs boson mass of 125 GeV, an upper limit of 6.4 (5.4) times the Standard Model cross section is observed (expected) at 95% confidence level. The best-fit value for the signal strength is μ = 1.6 ± 2.6 times the Standard Model expectation for mH = 125 GeV. Combining all $$ t\\overline{t}$$H searches carried out by ATLAS at √s = 8 and 7 TeV, an observed (expected) upper limit of 3.1 (1.4) times the Standard Model expectation is obtained at 95% confidence level, with a signal strength μ = 1.7 ± 0.8.« less

  12. Search for the Standard Model Higgs boson decaying into boverline{b} produced in association with top quarks decaying hadronically in pp collisions at √{s}=8 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blanco, J. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Caloba, L. P.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Colasurdo, L.; Cole, B.; Cole, S.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. 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A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. 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A.; Viel, S.; Vigani, L.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. 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    2016-05-01

    A search for Higgs boson production in association with a pair of top quarks ( toverline{t}H ) is performed, where the Higgs boson decays to boverline{b} , and both top quarks decay hadronically. The data used correspond to an integrated luminosity of 20.3 fb-1 of pp collisions at √{s}=8 TeV collected with the ATLAS detector at the Large Hadron Collider. The search selects events with at least six energetic jets and uses a boosted decision tree algorithm to discriminate between signal and Standard Model background. The dominant multijet background is estimated using a dedicated data-driven technique. For a Higgs boson mass of 125 GeV, an upper limit of 6.4 (5.4) times the Standard Model cross section is observed (expected) at 95% confidence level. The best-fit value for the signal strength is μ = 1.6 ± 2.6 times the Standard Model expectation for m H = 125 GeV. Combining all toverline{t}H searches carried out by ATLAS at √{s}=8 and 7 TeV, an observed (expected) upper limit of 3.1 (1.4) times the Standard Model expectation is obtained at 95% confidence level, with a signal strength μ = 1.7 ± 0.8. [Figure not available: see fulltext.

  13. Direct photon pair production at the LHC to O(α) in TeV scale gravity models

    NASA Astrophysics Data System (ADS)

    Kumar, M. C.; Mathews, Prakash; Ravindran, V.; Tripathi, Anurag

    2009-09-01

    The first results on next-to-leading order QCD corrections to production of direct photon pairs in hadronic collisions in the extra dimension models — ADD and RS are presented. Various kinematical distributions are obtained to order α in QCD by taking into account all the parton level subprocesses. Our Monte Carlo based code incorporates all the experimental cuts suitable for physics studies at the LHC. We estimate the impact of the QCD corrections on various observables and find that they are significant. We also show the reduction in factorization scale uncertainty when O(α) effects are included.

  14. Search for physics beyond the standard model in events with a Z boson, jets, and missing transverse energy in pp collisions at sqrt(s) = 7 TeV

    SciTech Connect

    Chatrchyan, S.; et al.,

    2012-09-01

    A search is presented for physics beyond the standard model (BSM) in events with a Z boson, jets, and missing transverse energy (MET). This signature is motivated by BSM physics scenarios, including supersymmetry. The study is performed using a sample of proton-proton collision data collected at sqrt(s) = 7 TeV with the CMS experiment at the LHC, corresponding to an integrated luminosity of 4.98 inverse femtobarns. The contributions from the dominant standard model backgrounds are estimated from data using two complementary strategies, the jet-Z balance technique and a method based on modeling MET with data control samples. In the absence of evidence for BSM physics, we set limits on the non-standard-model contributions to event yields in the signal regions and interpret the results in the context of simplified model spectra. Additional information is provided to facilitate tests of other BSM physics models.

  15. Time Dependent Multi Zone Modeling of X-ray and Gamma-ray Variability of the TeV Blazar Mrk 421.

    NASA Astrophysics Data System (ADS)

    Fossati, Giovanni; Chen, X.

    2010-03-01

    We present a new time-dependent multi-zone code and its first application to study the SSC emission of Blazar Mrk 421. The code couples Fokker-Planck and Monte Carlo methods. All the light travel time effects are fully considered, internal and external. It has long been realized that simple one-zone homogeneous models are not adequate to describe several aspects of the phenomenology, in particular those pertaining to the complex multiwavelength variability. Progress has been made by several groups but important trade-offs have always been necessary, such as neglecting internal light travel time or the inclusion of IC losses in the electron evolution. Our code fully accounts for all the relevant effects, and it also affords us significant freedom w.r.t. geometry and "variability". This latter is implemented as a shock traveling along the jet, with electrons being injected as it sweeps the blob. Results are compared with the 2001 observations of Mrk 421. We also analyzed cases including a pre-existing cospatial electron population contributing to the SED, and external radiation field. It seems to be possible to achieve adequate fits to the observations, but a there remain several open issues, such as a systematic soft X-ray intraband lag, and a delay of the gamma-ray flare with respect to the X-ray flare. The two principal challenges are: 1. The simulated VHE spectrum is always softer than the observed one. 2. The correlation between the TeV gamma-ray and X-ray does not reproduce the (super)quadratic relationship observed in multiple occasions. In fact we have not been able to reproduce anything close to it in this first suite of models. We will report also on the extension of the code, and case studies, to jet-in-jet and spine-layer configurations, as well as to the study of red blazars. We acknowledge support from Chandra Award AR9-0016X

  16. On the global well-posedness theory for a class of PDE models for criminal activity

    NASA Astrophysics Data System (ADS)

    Rodríguez, N.

    2013-10-01

    We study a class of ‘reaction-advection-diffusion’ system of partial differential equations, which can be taken as basic models for criminal activity. This class of models are based on routine activity theory and other theories, such as the ‘repeat and near-repeat victimization effect’ and were first introduced in Short et al. (2008) [11]. In these models the criminal density is advected by a velocity field that depends on a scalar field, which measures the appeal to commit a crime. We refer to this scalar field as the attractiveness field. We prove local well-posedness of solutions for the general class of models. Furthermore, we prove global well-posedness of solutions to a fully-parabolic system with a velocity field that depends logarithmically on the attractiveness field. Our final result is the global well-posedness of solutions the fully-parabolic system with velocity field that depends linearly on the attractiveness field for small initial mass.

  17. Universality class of the two-dimensional site-diluted Ising model.

    PubMed

    Martins, P H L; Plascak, J A

    2007-07-01

    In this work, we evaluate the probability distribution function of the order parameter for the two-dimensional site-diluted Ising model. Extensive Monte Carlo simulations have been performed for different spin concentrations p (0.70class of the diluted Ising model seems to be independent of the amount of dilution. Logarithmic corrections of the finite-size critical temperature behavior of the model can also be inferred even for such small lattices.

  18. Exact and Approximate Solutions for a Class of Cooperative Stochastic Models

    NASA Astrophysics Data System (ADS)

    Melkerson, Rebecca; Beck, Gillenhaal; Hall-Mejia, Estevan; Nshimyumukiza, Sabin; da Fonseca, Carlos; Mazilu, Dan; Mazilu, Irina

    We present a class of cooperative sequential adsorption models with evaporation defined on general lattice structures. Using matrix algebra theory to solve the associated master equations, we find the time-dependent probability distributions. We discuss these models in the context of ionic self-assembly of silica nanoparticles in order to also find the time-dependent surface coverage. To test the limits of the matrix theory, we add the possibilities for evaporation either once the surface is fully covered or at intermediate steps. We justify our mathematical models by comparing the results to customized experiments and computer simulations. Washington and Lee University Summer Research Scholars.

  19. Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 $$\\,\\text {TeV}$$

    DOE PAGES

    Khachatryan, Vardan

    2015-05-14

    Properties of the Higgs boson with mass near 125GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include γγ, ZZ, WW, ττ, bb, and μμ pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1fb-1 at 7TeV and up to 19.7fb-1 at 8TeV. From the high-resolution γγ and ZZ channels, the mass of the Higgs boson is determined to be 125.02+0.26–0.27 (stat) +0.14–0.15 (syst) GeV. For this mass value, the event yields obtained in themore » different analyses tagging specific decay channels and production mechanisms are consistent with those expected for the standard model Higgs boson. The combined best-fit signal relative to the standard model expectation is 1.00 ± 0.09(stat)+0.08–0.07 (theo) ± 0.07(syst) at the measured mass. The couplings of the Higgs boson are probed for deviations in magnitude from the standard model predictions in multiple ways, including searches for invisible and undetected decays. As a result, no significant deviations are found.« less

  20. Class Evolution Tree: A Graphical Tool to Support Decisions on the Number of Classes in Exploratory Categorical Latent Variable Modeling for Rehabilitation Research

    ERIC Educational Resources Information Center

    Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

    2011-01-01

    The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…

  1. Criterion for universality-class-independent critical fluctuations: example of the two-dimensional Ising model.

    PubMed

    Clusel, Maxime; Fortin, Jean-Yves; Holdsworth, Peter C W

    2004-10-01

    Order parameter fluctuations for the two-dimensional Ising model in the region of the critical temperature are presented. A locus of temperatures T(*) (L) and a locus of magnetic fields B(*) (L) are identified, for which the probability density function is similar to that for the two-dimensional XY model in the spin wave approximation. The characteristics of the fluctuations along these points are largely independent of universality class. We show that the largest range of fluctuations relative to the variance of the distribution occurs along these loci of points, rather than at the critical temperature itself and we discuss this observation in terms of intermittency. Our motivation is the identification of a generic form for fluctuations in correlated systems in accordance with recent experimental and numerical observations. We conclude that a universality-class-dependent form for the fluctuations is a particularity of critical phenomena related to the change in symmetry at a phase transition.

  2. New physics at the TeV scale

    NASA Astrophysics Data System (ADS)

    Chakdar, Shreyashi

    The Standard Model of particle physics is assumed to be a low-energy effective theory with new physics theoretically motivated to be around TeV scale. The thesis presents theories with new physics beyond the Standard Model in the TeV scale testable in the colliders. Work done in chapters 2, 3 and 5 in this thesis present some models incorporating different approaches of enlarging the Standard Model gauge group to a grand unified symmetry with each model presenting its unique signatures in the colliders. The study on leptoquarks gauge bosons in reference to TopSU(5) model in chapter 2 showed that their discovery mass range extends up to 1.5 TeV at 14 TeV LHC with luminosity of 100 fb--1. On the other hand, in chapter 3 we studied the collider phenomenology of TeV scale mirror fermions in Left-Right Mirror model finding that the reaches for the mirror quarks goes upto 750 GeV at the 14 TeV LHC with 300 fb--1 luminosity. In chapter 4 we have enlarged the bosonic symmetry to fermi-bose symmetry e.g. supersymmetry and have shown that SUSY with non-universalities in gaugino or scalar masses within high scale SUGRA set up can still be accessible at LHC with 14 TeV. In chapter 5, we performed a study in respect to the e+e-- collider and find that precise measurements of the higgs boson mass splittings up to ˜ 100 MeV may be possible with high luminosity in the International Linear Collider (ILC). In chapter 6 we have shown that the experimental data on neutrino masses and mixings are consistent with the proposed 4/5 parameter Dirac neutrino models yielding a solution for the neutrino masses with inverted mass hierarchy and large CP violating phase delta and thus can be tested experimentally. Chapter 7 of the thesis incorporates a warm dark matter candidate in context of two Higgs doublet model. The model has several testable consequences at colliders with the charged scalar and pseudoscalar being in few hundred GeV mass range. This thesis presents an endeavor to study

  3. Analysis of a Class of Low-Dimensional Models of Mutation and Predation

    NASA Astrophysics Data System (ADS)

    Abernethy, Gavin M.; McCartney, Mark

    We consider a class of simple two-dimensional discrete models representative of a system incorporating both mutation and predation. A selection of analytic and numerical results are presented, classifying the dynamic behavior of the system by means of Lyapunov exponents over a biologically-reasonable region of parameter space, and illustrating the occurrence of hyperchaos and a Neimark-Sacker bifurcation producing regions of quasiperiodicity.

  4. Constraints on the pMSSM, AMSB model and on other models from the search for long-lived charged particles in proton-proton collisions at √s = 8 TeV

    DOE PAGES

    Khachatryan, Vardan

    2015-07-17

    Stringent limits are set on the long-lived lepton-like sector of the phenomenological minimal supersymmetric standard model (pMSSM) and the anomaly-mediated supersymmetry breaking (AMSB) model. We derived the limits from the results presented in a recent search for long-lived charged particles in proton–proton collisions, based on data collected by the CMS detector at a centre-of-mass energy of 8 TeV at the Large Hadron Collider. In the pMSSM parameter sub-space considered, 95.9 % of the points predicting charginos with a lifetime of at least 10 ns are excluded. Furthermore, these constraints on the pMSSM are the first obtained at the LHC. Charginosmore » with a lifetime greater than 100 ns and masses up to about 800 GeV in the AMSB model are also excluded. Furthermore, the method described can also be used to set constraints on other models.« less

  5. SPI drought class prediction using log-linear models applied to wet and dry seasons

    NASA Astrophysics Data System (ADS)

    Moreira, Elsa E.

    2016-08-01

    A log-linear modelling for 3-dimensional contingency tables was used with categorical time series of SPI drought class transitions for prediction of monthly drought severity. Standardized Precipitation Index (SPI) time series in 12- and 6-month time scales were computed for 10 precipitation time series relative to GPCC datasets with 2.5° spatial resolution located over Portugal and with 112 years length (1902-2014). The aim was modelling two-month step class transitions for the wet and dry seasons of the year and then obtain probability ratios - Odds - as well as their respective confidence intervals to estimate how probable a transition is compared to another. The prediction results produced by the modelling applied to wet and dry season separately, for the 6- and the 12-month SPI time scale, were compared with the results produced by the same modelling without the split, using skill scores computed for the entire time series length. Results point to good prediction performances ranging from 70 to 80% in the percentage of corrects (PC) and 50-70% in the Heidke skill score (HSS), with the highest scores obtained when the modelling is applied to the SPI12. The adding up of the wet and dry seasons introduced in the modelling brought improvements in the predictions, of about 0.9-4% in the PC and 1.3-6.8% in the HSS, being the highest improvements obtained in the SPI6 application.

  6. Search for the standard model Higgs boson decaying to a $W$ pair in the fully leptonic final state in $pp$ collisions at $\\sqrt{s}=7$ TeV

    SciTech Connect

    Chatrchyan, Serguei; et al.

    2012-03-01

    A search for the standard model Higgs boson decaying to W+W- in pp collisions at sqrt(s) = 7 TeV is reported. The data are collected at the LHC with the CMS detector, and correspond to an integrated luminosity of 4.6 inverse femtobarns. The W+W- candidates are selected in events with two charged leptons and large missing transverse energy. No significant excess of events above the standard model background expectations is observed, and upper limits on the Higgs boson production relative to the standard model Higgs expectation are derived. The standard model Higgs boson is excluded in the mass range 129-270 GeV at 95% confidence level.

  7. Fixed-distance latent class models for the analysis of sets of two-way contingency tables.

    PubMed

    Formann, A K

    1993-06-01

    This paper develops and describes the application of modified latent class models for analyzing sets of two-way contingency tables. The proposed fixed-distance models differ from traditional latent class models in that the assumption of local stochastic independence is superseded by allowing interactions of the manifest variables within each class, which can be represented by a single association parameter. As an example, two data sets on eye color by hair color [collected in Caithness (N1 = 5,387) and Aberdeen (N2 = 22,361)] and fixed-distance models with up to six classes (three classes per data set) are considered, finally leading to satisfactory fit and rather simple interpretation.

  8. A Class of Semiparametric Transformation Models for Survival Data with a Cured Proportion

    PubMed Central

    Choi, Sangbum; Huang, Xuelin; Chen, Yi-Hau

    2013-01-01

    We propose a new class of semiparametric regression models based on a multiplicative frailty assumption with a discrete frailty, which may account for cured subgroup in population. The cure model framework is then recast as a problem with a transformation model. The proposed models can explain a broad range of nonproportional hazards structures along with a cured proportion. An efficient and simple algorithm based on the martingale process is developed to locate the nonparametric maximum likelihood estimator. Unlike existing expectation-maximization based methods, our approach directly maximizes a nonparametric likelihood function, and the calculation of consistent variance estimates is immediate. The proposed method is useful for resolving identifiability features embedded in semiparametric cure models. Simulation studies are presented to demonstrate the finite sample properties of the proposed method. A case study of stage III soft-tissue sarcoma is given as an illustration. PMID:23760878

  9. An investigation of difficulties experienced by students developing unified modelling language (UML) class and sequence diagrams

    NASA Astrophysics Data System (ADS)

    Sien, Ven Yu

    2011-12-01

    Object-oriented analysis and design (OOAD) is not an easy subject to learn. There are many challenges confronting students when studying OOAD. Students have particular difficulty abstracting real-world problems within the context of OOAD. They are unable to effectively build object-oriented (OO) models from the problem domain because they essentially do not know "what" to model. This article investigates the difficulties and misconceptions undergraduate students have with analysing systems using unified modelling language analysis class and sequence diagrams. These models were chosen because they represent important static and dynamic aspects of the software system under development. The results of this study will help students produce effective OO models, and facilitate software engineering lecturers design learning materials and approaches for introductory OOAD courses.

  10. Integrated ligand based pharmacophore model derived from diverse FAAH covalent ligand classes.

    PubMed

    Shen, Lingling; Huang, Hongwei; Makriyannis, Alexandros; Fisher, Luke S

    2012-12-01

    3D pharmacophore modeling is an important computational methodology for ligand-enzyme binding interactions in drug discovery. More specifically, a consensus pharmacophore model derived from diverse ligands is a key determinant upon which the prediction power of computational models is based for designing novel ligands. In this work, by merging the important pharmacophore features based on four classes of covalent FAAH ligands, and then integrating the exclusion volume spheres derived from the crystal structure, we created for the first time an integrated FAAH pharmacophore model to describe the ligand-enzyme binding interactions. This new integrated FAAH pharmacophore model can correctly predict the covalent ligand binding mode, which correlates with the SAR data. The study is expected to provide insights into novel covalent ligand-FAAH binding interactions, and facilitate the design of covalent ligands against FAAH.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  12. Statistical power of likelihood ratio and Wald tests in latent class models with covariates.

    PubMed

    Gudicha, Dereje W; Schmittmann, Verena D; Vermunt, Jeroen K

    2016-12-30

    This paper discusses power and sample-size computation for likelihood ratio and Wald testing of the significance of covariate effects in latent class models. For both tests, asymptotic distributions can be used; that is, the test statistic can be assumed to follow a central Chi-square under the null hypothesis and a non-central Chi-square under the alternative hypothesis. Power or sample-size computation using these asymptotic distributions requires specification of the non-centrality parameter, which in practice is rarely known. We show how to calculate this non-centrality parameter using a large simulated data set from the model under the alternative hypothesis. A simulation study is conducted evaluating the adequacy of the proposed power analysis methods, determining the key study design factor affecting the power level, and comparing the performance of the likelihood ratio and Wald test. The proposed power analysis methods turn out to perform very well for a broad range of conditions. Moreover, apart from effect size and sample size, an important factor affecting the power is the class separation, implying that when class separation is low, rather large sample sizes are needed to achieve a reasonable power level.

  13. Phenomenology of TeV little string theory from holography.

    PubMed

    Antoniadis, Ignatios; Arvanitaki, Asimina; Dimopoulos, Savas; Giveon, Amit

    2012-02-24

    We study the graviton phenomenology of TeV little string theory by exploiting its holographic gravity dual five-dimensional theory. This dual corresponds to a linear dilaton background with a large bulk that constrains the standard model fields on the boundary of space. The linear dilaton geometry produces a unique Kaluza-Klein graviton spectrum that exhibits a ~TeV mass gap followed by a near continuum of narrow resonances that are separated from each other by only ~30 GeV. Resonant production of these particles at the LHC is the signature of this framework that distinguishes it from large extra dimensions, where the Kaluza-Klein states are almost a continuum with no mass gap, and warped models, where the states are separated by a TeV.

  14. Latent class models in diagnostic studies when there is no reference standard--a systematic review.

    PubMed

    van Smeden, Maarten; Naaktgeboren, Christiana A; Reitsma, Johannes B; Moons, Karel G M; de Groot, Joris A H

    2014-02-15

    Latent class models (LCMs) combine the results of multiple diagnostic tests through a statistical model to obtain estimates of disease prevalence and diagnostic test accuracy in situations where there is no single, accurate reference standard. We performed a systematic review of the methodology and reporting of LCMs in diagnostic accuracy studies. This review shows that the use of LCMs in such studies increased sharply in the past decade, notably in the domain of infectious diseases (overall contribution: 59%). The 64 reviewed studies used a range of differently specified parametric latent variable models, applying Bayesian and frequentist methods. The critical assumption underlying the majority of LCM applications (61%) is that the test observations must be independent within 2 classes. Because violations of this assumption can lead to biased estimates of accuracy and prevalence, performing and reporting checks of whether assumptions are met is essential. Unfortunately, our review shows that 28% of the included studies failed to report any information that enables verification of model assumptions or performance. Because of the lack of information on model fit and adequate evidence "external" to the LCMs, it is often difficult for readers to judge the validity of LCM-based inferences and conclusions reached.

  15. Examining Class Differences in Method Effects Related to Negative Wording: An Example using Rasch Mixture Modeling.

    PubMed

    Morgan, Grant B; DiStefano, Christine; Motl, Robert W

    This study presents a mixture Rasch-based approach to investigating method effects associated with negatively worded items to illustrate how responses to this method effect vary depending on group characteristics. Using college students' responses on the Rosenberg Self-Esteem scale (Rosenberg, M., 1989), four latent classes were identified using six personality measures associated with the presence of this method effect. In addition, Rasch-based parameter estimates suggested latent classes differed in their use of the scale, showing that the method effect associated with negatively worded items may be more prominent for subjects possessing selected personality traits than for others. The mixture model approach to investigating method effects provides a way to address systematic methodological variation that is left unaccounted when a heterogeneous population is analyzed as one group.

  16. Modelling the benefits of a new class of anthelmintic in combination.

    PubMed

    Leathwick, D M

    2012-05-04

    Since 2009 two new classes of anthelmintics have been registered for use in sheep in New Zealand. This raises challenging questions about how such new actives should be used, not only to minimise the development of resistance to them, thereby ensuring their availability as effective treatments for as long as possible, but also to minimise the further development of resistance to the other anthelmintic classes. One strategy which appears to offer considerable potential for slowing the development of resistance is the use of combinations of different anthelmintic classes, although this approach remains contentious in some countries. The potential benefit of using anthelmintics in combination is particularly relevant to two recently released anthelmintic compounds because one, monepantel, is presently only available as a single active product while the other, derquantel, is only available in combination with abamectin. A simulation modelling approach was used to investigate the potential benefits of using anthelmintics in combination. The rate at which resistance develops to a new 'active' when used alone was compared to an equivalent compound used in combination with a second compound from an alternative class (in this case, abamectin), when various levels of resistance occur to the second active. In addition, the potential of a new active to reduce further development of resistance to the second compound in the combination was evaluated. Finally, the use of combinations as compared to sequential or rotational use patterns, in the presence of side resistance between two actives was investigated. The modelling simulations suggest a significant advantage to both compounds when they are used in combination, especially if both initially have high efficacy. The development of resistance to the new active was delayed, although to a lesser extent, even when the efficacy of the second active in the combination was only 50%. Under a 'low-refugia' management environment

  17. Cosmological consequences of nearly conformal dynamics at the TeV scale

    SciTech Connect

    Konstandin, Thomas; Servant, Géraldine E-mail: geraldine.servant@cern.ch

    2011-12-01

    Nearly conformal dynamics at the TeV scale as motivated by the hierarchy problem can be characterized by a stage of significant supercooling at the electroweak epoch. This has important cosmological consequences. In particular, a common assumption about the history of the universe is that the reheating temperature is high, at least high enough to assume that TeV-mass particles were once in thermal equilibrium. However, as we discuss in this paper, this assumption is not well justified in some models of strong dynamics at the TeV scale. We then need to reexamine how to achieve baryogenesis in these theories as well as reconsider how the dark matter abundance is inherited. We argue that baryonic and dark matter abundances can be explained naturally in these setups where reheating takes place by bubble collisions at the end of the strongly first-order phase transition characterizing conformal symmetry breaking, even if the reheating temperature is below the electroweak scale ∼ 100 GeV. In particular, non-thermal production of heavy WIMPs during bubble collisions becomes a well-motivated possibility. We also discuss inflation as well as gravity wave smoking gun signatures of this class of models.

  18. Class of gauge-invariant models of quantum electrodynamics with nonlocal interaction

    PubMed Central

    Mei, Tao

    2017-01-01

    We present a class of gauge-invariant models of quantum electrodynamics with nonlocal interaction. The models have translation, Lorentz and gauge invariance and reduce to the conventional local quantum electrodynamics under the appropriate limit conditions, both the equations of motion of the charged particle and electromagnetic field obtained by the action principle lead to the normal form of current conservation. Quantization of the models is realized by taking advantage of the formalism based on the Yang-Feldman equations and the Lehmann-Symanzik-Zimmermann reduction formulas. Finally, we employ a special choice of the models to calculate the vacuum polarization as an example to demonstrate the possibility of establishing a theory of quantum electrodynamics without divergence. PMID:28368044

  19. Evidence for an unconventional universality class from a two-dimensional dimerized quantum heisenberg model.

    PubMed

    Wenzel, Sandro; Bogacz, Leszek; Janke, Wolfhard

    2008-09-19

    The two-dimensional J-J' dimerized quantum Heisenberg model is studied on the square lattice by means of (stochastic series expansion) quantum Monte Carlo simulations as a function of the coupling ratio alpha=J'/J. The critical point of the order-disorder quantum phase transition in the J-J' model is determined as alpha_c=2.5196(2) by finite-size scaling for up to approximately 10 000 quantum spins. By comparing six dimerized models we show, contrary to the current belief, that the critical exponents of the J-J' model are not in agreement with the three-dimensional classical Heisenberg universality class. This lends support to the notion of nontrivial critical excitations at the quantum critical point.

  20. A Critical Protection Level Derived from Dengue Infection Mathematical Model Considering Asymptomatic and Symptomatic Classes

    NASA Astrophysics Data System (ADS)

    Anggriani, N.; Supriatna, A. K.; Soewono, E.

    2013-04-01

    In this paper we formulate a model of dengue fever transmission by considering the presence of asymptomatic and symptomatic compartments. The model takes the form as a system of differential equations representing a host-vector SIR (Susceptible - Infective -Recovered) disease transmission. It is assumed that both host and vector populations are constant. It is also assumed that reinfection of recovered hosts by the disease is possible due to a wanning immunity in human body. We analyze the model to determine the qualitative behavior of the model solution and use the concept of effective basic reproduction number (fraktur Rp) as a control criteria of the disease transmission. The effect of mosquito biting protection (e.g. by using insect repellent) is also considered. We compute the long-term ratio of the asymptomatic and symptomatic classes and show a condition for which the iceberg phenomenon could appear.

  1. Class of gauge-invariant models of quantum electrodynamics with nonlocal interaction.

    PubMed

    Mei, Tao

    2017-04-03

    We present a class of gauge-invariant models of quantum electrodynamics with nonlocal interaction. The models have translation, Lorentz and gauge invariance and reduce to the conventional local quantum electrodynamics under the appropriate limit conditions, both the equations of motion of the charged particle and electromagnetic field obtained by the action principle lead to the normal form of current conservation. Quantization of the models is realized by taking advantage of the formalism based on the Yang-Feldman equations and the Lehmann-Symanzik-Zimmermann reduction formulas. Finally, we employ a special choice of the models to calculate the vacuum polarization as an example to demonstrate the possibility of establishing a theory of quantum electrodynamics without divergence.

  2. Performance modeling and analysis of consumer classes in large scale systems

    NASA Astrophysics Data System (ADS)

    Al-Shukri, Sh.; Lenin, R. B.; Ramaswamy, S.; Anand, A.; Narasimhan, V. L.; Abraham, J.; Varadan, Vijay

    2009-03-01

    Peer-to-Peer (P2P) networks have been used efficiently as building blocks as overlay networks for large-scale distributed network applications with Internet Protocol (IP) based bottom layer networks. With large scale Wireless Sensor Networks (WSNs) becoming increasingly realistic, it is important to overlay networks with WSNs in the bottom layer. The suitable mathematical (stochastic) model that can model the overlay network over WSNs is Queuing Networks with Multi-Class customers. In this paper, we discuss how these mathematical network models can be simulated using the object oriented simulation package OMNeT++. We discuss the Graphical User Interface (GUI) which is developed to accept the input parameter files and execute the simulation using this interface. We compare the simulation results with analytical formulas available in the literature for these mathematical models.

  3. A new model for spherically symmetric charged compact stars of embedding class 1

    NASA Astrophysics Data System (ADS)

    Maurya, S. K.; Gupta, Y. K.; Ray, Saibal; Deb, Debabrata

    2017-01-01

    In the present study we search for a new stellar model with spherically symmetric matter and a charged distribution in a general relativistic framework. The model represents a compact star of embedding class 1. The solutions obtained here are general in nature, having the following two features: first of all, the metric becomes flat and also the expressions for the pressure, energy density, and electric charge become zero in all the cases if we consider the constant A=0, which shows that our solutions represent the so-called `electromagnetic mass model' [17], and, secondly, the metric function ν (r), for the limit n tending to infinity, converts to ν (r)=C{r}2+ ln B, which is the same as considered by Maurya et al. [11]. We have investigated several physical aspects of the model and find that all the features are acceptable within the requirements of contemporary theoretical studies and observational evidence.

  4. Active-absorbing-state phase transition beyond directed percolation: a class of exactly solvable models.

    PubMed

    Basu, Urna; Mohanty, P K

    2009-04-01

    We introduce and solve a model of hardcore particles on a one-dimensional periodic lattice which undergoes an active-absorbing-state phase transition at finite density. In this model, an occupied site is defined to be active if its left neighbor is occupied and the right neighbor is vacant. Particles from such active sites hop stochastically to their right. We show that both the density of active sites and the survival probability vanish as the particle density is decreased below half. The critical exponents and spatial correlations of the model are calculated exactly using the matrix product ansatz. Exact analytical study of several variations of the model reveals that these nonequilibrium phase transitions belong to a new universality class different from the generic active-absorbing-state phase transition, namely, directed percolation.

  5. Bayesian inference in camera trapping studies for a class of spatial capture-recapture models

    USGS Publications Warehouse

    Royle, J. Andrew; Karanth, K. Ullas; Gopalaswamy, Arjun M.; Kumar, N. Samba

    2009-01-01

    We develop a class of models for inference about abundance or density using spatial capture-recapture data from studies based on camera trapping and related methods. The model is a hierarchical model composed of two components: a point process model describing the distribution of individuals in space (or their home range centers) and a model describing the observation of individuals in traps. We suppose that trap- and individual-specific capture probabilities are a function of distance between individual home range centers and trap locations. We show that the models can be regarded as generalized linear mixed models, where the individual home range centers are random effects. We adopt a Bayesian framework for inference under these models using a formulation based on data augmentation. We apply the models to camera trapping data on tigers from the Nagarahole Reserve, India, collected over 48 nights in 2006. For this study, 120 camera locations were used, but cameras were only operational at 30 locations during any given sample occasion. Movement of traps is common in many camera-trapping studies and represents an important feature of the observation model that we address explicitly in our application.

  6. A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk.

    PubMed

    Yu, Rongjie; Wang, Xuesong; Abdel-Aty, Mohamed

    2017-04-01

    Crash risk analysis is rising as a hot research topic as it could reveal the relationships between traffic flow characteristics and crash occurrence risk, which is beneficial to understand crash mechanisms which would further refine the design of Active Traffic Management System (ATMS). However, the majority of the current crash risk analysis studies have ignored the impact of geometric characteristics on crash risk estimation while recent studies proved that crash occurrence risk was affected by the various alignment features. In this study, a hybrid Latent Class Analysis (LCA) modeling approach was proposed to account for the heterogeneous effects of geometric characteristics. Crashes were first segmented into homogenous subgroups, where the optimal number of latent classes was identified based on bootstrap likelihood ratio tests. Then, separate crash risk analysis models were developed using Bayesian random parameter logistic regression technique; data from Shanghai urban expressway system were employed to conduct the empirical study. Different crash risk contributing factors were unveiled by the hybrid LCA approach and better model goodness-of-fit was obtained while comparing to an overall total crash model. Finally, benefits of the proposed hybrid LCA approach were discussed.

  7. Modelling, Simulation, Animation, and Real-Time Control (Mosart) for a Class of Electromechanical Systems: A System-Theoretic Approach

    ERIC Educational Resources Information Center

    Rodriguez, Armando A.; Metzger, Richard P.; Cifdaloz, Oguzhan; Dhirasakdanon, Thanate; Welfert, Bruno

    2004-01-01

    This paper describes an interactive modelling, simulation, animation, and real-time control (MoSART) environment for a class of 'cart-pendulum' electromechanical systems that may be used to enhance learning within differential equations and linear algebra classes. The environment is useful for conveying fundamental mathematical/systems concepts…

  8. Search for Neutral Minimal Supersymmetric Standard Model Higgs Bosons Decaying to Tau Pairs in pp Collisions at sqrt[s]=7 TeV

    SciTech Connect

    Chatrchyan, Serguei; et al.

    2011-06-01

    A search for neutral MSSM Higgs bosons in pp collisions at the LHC at a center-of-mass energy of 7 TeV is presented. The results are based on a data sample corresponding to an integrated luminosity of 36 inverse picobarns recorded by the CMS experiment. The search uses decays of the Higgs bosons to tau pairs. No excess is observed in the tau-pair invariant-mass spectrum. The resulting upper limits on the Higgs boson production cross section times branching fraction to tau pairs, as a function of the pseudoscalar Higgs boson mass, yield stringent new bounds in the MSSM parameter space.

  9. A new class of ensemble conserving algorithms for approximate quantum dynamics: Theoretical formulation and model problems

    SciTech Connect

    Smith, Kyle K. G.; Poulsen, Jens Aage Nyman, Gunnar; Rossky, Peter J.

    2015-06-28

    We develop two classes of quasi-classical dynamics that are shown to conserve the initial quantum ensemble when used in combination with the Feynman-Kleinert approximation of the density operator. These dynamics are used to improve the Feynman-Kleinert implementation of the classical Wigner approximation for the evaluation of quantum time correlation functions known as Feynman-Kleinert linearized path-integral. As shown, both classes of dynamics are able to recover the exact classical and high temperature limits of the quantum time correlation function, while a subset is able to recover the exact harmonic limit. A comparison of the approximate quantum time correlation functions obtained from both classes of dynamics is made with the exact results for the challenging model problems of the quartic and double-well potentials. It is found that these dynamics provide a great improvement over the classical Wigner approximation, in which purely classical dynamics are used. In a special case, our first method becomes identical to centroid molecular dynamics.

  10. A new class of ensemble conserving algorithms for approximate quantum dynamics: Theoretical formulation and model problems.

    PubMed

    Smith, Kyle K G; Poulsen, Jens Aage; Nyman, Gunnar; Rossky, Peter J

    2015-06-28

    We develop two classes of quasi-classical dynamics that are shown to conserve the initial quantum ensemble when used in combination with the Feynman-Kleinert approximation of the density operator. These dynamics are used to improve the Feynman-Kleinert implementation of the classical Wigner approximation for the evaluation of quantum time correlation functions known as Feynman-Kleinert linearized path-integral. As shown, both classes of dynamics are able to recover the exact classical and high temperature limits of the quantum time correlation function, while a subset is able to recover the exact harmonic limit. A comparison of the approximate quantum time correlation functions obtained from both classes of dynamics is made with the exact results for the challenging model problems of the quartic and double-well potentials. It is found that these dynamics provide a great improvement over the classical Wigner approximation, in which purely classical dynamics are used. In a special case, our first method becomes identical to centroid molecular dynamics.

  11. The distribution of Fst and other genetic statistics for a class of population structure models.

    PubMed

    Leviyang, Sivan

    2011-02-01

    We examine genetic statistics used in the study of structured populations. In a 1999 paper, Wakeley observed that the coalescent process associated with the finite island model can be decomposed into a scattering phase and a collecting phase. This decomposition becomes exact in the large population limit with the coalescent at the end of the scattering phase converging to the Ewens sampling formula and the coalescent during the collecting phase converging to the Kingman coalescent. In this paper we introduce a class of limiting models, which we refer to as G/KC models, that generalize Wakeley's decomposition. G in G/KC represents a completely general limit for the scattering phase, while KC represents a Kingman coalescent limit for the collecting phase. We show that both the island and two-dimensional stepping stone models converge to G/KC models in the large population limit. We then derive the distribution of the statistic F(st) for all G/KC models under a large sample limit for the cases of strong or weak mutation, thereby deriving the large population, large sample limiting distribution of F(st) for the island and two-dimensional stepping stone models as a special case of a general formula. Our methods allow us to take the large population and large sample limits simultaneously. In the context of large population, large sample limits, we show that the variance of F(st) in the presence of weak mutation collapses as O(1/log d) where d is the number of demes sampled. Further, we show that this O(1/log d) is caused by a heavy tail in the distribution of F(st). Our analysis of F(st) can be extended to an entire class of genetic statistics, and we use our approach to examine homozygosity measures. Our analysis uses coalescent based methods.

  12. Molecular modeling indicates distinct classes of missense variants with mild and severe XLRS phenotypes.

    PubMed

    Sergeev, Yuri V; Vitale, Susan; Sieving, Paul A; Vincent, Ajoy; Robson, Anthony G; Moore, Anthony T; Webster, Andrew R; Holder, Graham E

    2013-12-01

    X-linked retinoschisis (XLRS) is a vitreo-retinal degeneration caused by mutations in the RS1 gene which encodes the protein retinoschisin (RS1), required for the structural and functional integrity of the retina. Data are presented from a group of 38 XLRS patients from Moorfields Eye Hospital (London, UK) who had one of 18 missense mutations in RS1. Patients were grouped based on mutation severity predicted by molecular modeling: mild (class I), moderate (intermediate) and severe (class II). Most patients had an electronegative scotopic bright flash electroretinogram (ERG) (reduced b/a-wave ratio) in keeping with predominant inner retinal dysfunction. An association between the type of structural RS1 alterations and the severity of b/a-wave reduction was found in all but the oldest group of patients, significant in patients aged 15-30 years. Severe RS1 missense changes were associated with a lower ERG b/a ratio than were mild changes, suggesting that the extent of inner retinal dysfunction is influenced by the effect of the mutations on protein structure. The majority of class I mutations showed no changes involving cysteine residues. Class II mutations caused severe perturbations due to the removal or insertion of cysteine residues or due to changes in the hydrophobic core. The ERG b/a ratio in intermediate cases was abnormal but showed significant variability, possibly related to the role of proline or arginine residues. We also conducted a second study, using a completely independent cohort, to indicate a genotype-ERG phenotype correlation.

  13. GTC Optical Spectroscopy of TeV Blazars

    NASA Astrophysics Data System (ADS)

    Paiano, Simona; Falomo, R.; Treves, A.; Landoni, M.; Scarpa, R.; Righi, C.

    2016-10-01

    We carried out an extensive spectroscopic campaign of blazars of unknown or uncertain redshift which are either detected in the TeV band by Cherenkov telescopes or good candidate as TeV emitters. We used the OSIRIS spectrograph at the Gran Telescopio of Canarias (GTC) at La Palma to secure high signal-to-noise ratio spectra at intermediate resolution in the range 3800-10000 Ang. These observations allow us to confirm the blazar classification, to find new redshift and/or to set stringent lower limits. The results are discussed in the context of emission modeling of TeV sources and are of importance for the characterization of the Extragalactic Background Light.

  14. Measures of success in a class of evolutionary models with fixed population size and structure.

    PubMed

    Allen, Benjamin; Tarnita, Corina E

    2014-01-01

    We investigate a class of evolutionary models, encompassing many established models of well-mixed and spatially structured populations. Models in this class have fixed population size and structure. Evolution proceeds as a Markov chain, with birth and death probabilities dependent on the current population state. Starting from basic assumptions, we show how the asymptotic (long-term) behavior of the evolutionary process can be characterized by probability distributions over the set of possible states. We then define and compare three quantities characterizing evolutionary success: fixation probability, expected frequency, and expected change due to selection. We show that these quantities yield the same conditions for success in the limit of low mutation rate, but may disagree when mutation is present. As part of our analysis, we derive versions of the Price equation and the replicator equation that describe the asymptotic behavior of the entire evolutionary process, rather than the change from a single state. We illustrate our results using the frequency-dependent Moran process and the birth-death process on graphs as examples. Our broader aim is to spearhead a new approach to evolutionary theory, in which general principles of evolution are proven as mathematical theorems from axioms.

  15. Measurements and modeling of total solar irradiance in X-class solar flares

    SciTech Connect

    Moore, Christopher Samuel; Chamberlin, Phillip Clyde; Hock, Rachel

    2014-05-20

    The Total Irradiance Monitor (TIM) from NASA's SOlar Radiation and Climate Experiment can detect changes in the total solar irradiance (TSI) to a precision of 2 ppm, allowing observations of variations due to the largest X-class solar flares for the first time. Presented here is a robust algorithm for determining the radiative output in the TIM TSI measurements, in both the impulsive and gradual phases, for the four solar flares presented in Woods et al., as well as an additional flare measured on 2006 December 6. The radiative outputs for both phases of these five flares are then compared to the vacuum ultraviolet (VUV) irradiance output from the Flare Irradiance Spectral Model (FISM) in order to derive an empirical relationship between the FISM VUV model and the TIM TSI data output to estimate the TSI radiative output for eight other X-class flares. This model provides the basis for the bolometric energy estimates for the solar flares analyzed in the Emslie et al. study.

  16. Symmetry classes of alternating sign matrices in a nineteen-vertex model

    NASA Astrophysics Data System (ADS)

    Hagendorf, Christian; Morin-Duchesne, Alexi

    2016-05-01

    The nineteen-vertex model of Fateev and Zamolodchikov on a periodic lattice with an anti-diagonal twist is investigated. Its inhomogeneous transfer matrix is shown to have a simple eigenvalue, with the corresponding eigenstate displaying intriguing combinatorial features. Similar results were previously found for the same model with a diagonal twist. The eigenstate for the anti-diagonal twist is explicitly constructed using the quantum separation of variables technique. A number of sum rules and special components are computed and expressed in terms of Kuperberg’s determinants for partition functions of the inhomogeneous six-vertex model. The computations of some components of the special eigenstate for the diagonal twist are also presented. In the homogeneous limit, the special eigenstates become eigenvectors of the Hamiltonians of the integrable spin-one XXZ chain with twisted boundary conditions. Their sum rules and special components for both twists are expressed in terms of generating functions arising in the weighted enumeration of various symmetry classes of alternating sign matrices (ASMs). These include half-turn symmetric ASMs, quarter-turn symmetric ASMs, vertically symmetric ASMs, vertically and horizontally perverse ASMs and double U-turn ASMs. As side results, new determinant and pfaffian formulas for the weighted enumeration of various symmetry classes of alternating sign matrices are obtained.

  17. Measurements and Modeling of Total Solar Irradiance in X-class Solar Flares

    NASA Technical Reports Server (NTRS)

    Moore, Christopher S.; Chamberlin, Phillip Clyde; Hock, Rachel

    2014-01-01

    The Total Irradiance Monitor (TIM) from NASA's SOlar Radiation and Climate Experiment can detect changes in the total solar irradiance (TSI) to a precision of 2 ppm, allowing observations of variations due to the largest X-class solar flares for the first time. Presented here is a robust algorithm for determining the radiative output in the TIM TSI measurements, in both the impulsive and gradual phases, for the four solar flares presented in Woods et al., as well as an additional flare measured on 2006 December 6. The radiative outputs for both phases of these five flares are then compared to the vacuum ultraviolet (VUV) irradiance output from the Flare Irradiance Spectral Model (FISM) in order to derive an empirical relationship between the FISM VUV model and the TIM TSI data output to estimate the TSI radiative output for eight other X-class flares. This model provides the basis for the bolometric energy estimates for the solar flares analyzed in the Emslie et al. study.

  18. Experimental analysis and constitutive modelling of steel of A-IIIN strength class

    NASA Astrophysics Data System (ADS)

    Kruszka, Leopold; Janiszewski, Jacek

    2015-09-01

    Fundamentally important is the better understanding of behaviour of new building steels under impact loadings, including plastic deformations. Results of the experimental analysis in wide range of strain rates in compression at room temperature, as well as constitutive modelling for and B500SP structural steels of new A-IIIN Polish strength class, examined dynamically by split Hopkinson pressure bar technique at high strain rates, are presented in table and graphic forms. Dynamic mechanical characteristics of compressive strength for tested building structural steel are determined as well as dynamic mechanical properties of this material are compared with 18G2-b steel of A-II strength class, including effects of the shape of tested specimens, i.e. their slenderness. The paper focuses the attention on those experimental tests, their interpretation, and constitutive semi-empirical modelling of the behaviour of tested steels based on Johnson-Cook's model. Obtained results of analyses presented here are used for designing and numerical simulations of reinforced concrete protective structures.

  19. Multiple model self-tuning control for a class of nonlinear systems

    NASA Astrophysics Data System (ADS)

    Huang, Miao; Wang, Xin; Wang, Zhenlei

    2015-10-01

    This study develops a novel nonlinear multiple model self-tuning control method for a class of nonlinear discrete-time systems. An increment system model and a modified robust adaptive law are proposed to expand the application range, thus eliminating the assumption that either the nonlinear term of the nonlinear system or its differential term is global-bounded. The nonlinear self-tuning control method can address the situation wherein the nonlinear system is not subject to a globally uniformly asymptotically stable zero dynamics by incorporating the pole-placement scheme. A novel, nonlinear control structure based on this scheme is presented to improve control precision. Stability and convergence can be confirmed when the proposed multiple model self-tuning control method is applied. Furthermore, simulation results demonstrate the effectiveness of the proposed method.

  20. Social Class Disparities in Health and Education: Reducing Inequality by Applying a Sociocultural Self Model of Behavior

    ERIC Educational Resources Information Center

    Stephens, Nicole M.; Markus, Hazel Rose; Fryberg, Stephanie A.

    2012-01-01

    The literature on social class disparities in health and education contains 2 underlying, yet often opposed, models of behavior: the individual model and the structural model. These models refer to largely unacknowledged assumptions about the sources of human behavior that are foundational to research and interventions. Our review and theoretical…

  1. The significance of the 1-TeV scale

    SciTech Connect

    Quigg, C.

    1988-01-01

    the Standard Model of elementary particle physics organizes our knowledge of the basic constituents and interactions, and achieves a wide-ranging synthesis of elementary phenomena, but leaves unanswered some fundamental questions. Important clues to a more complete understanding are to be found on the energy scale of 1 TeV, where the kinship between the weak and electromagnetic interactions will be illuminated. Exploration of the 1-TeV scale is an essential goal for the 1990s. 37 refs., 3 figs.

  2. Search for the Standard Model Higgs Boson in the Diphoton Decay Channel with 4.9fb-1 of pp Collision Data at s=7TeV with ATLAS

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abouzeid, O. S.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Aderholz, M.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Akiyama, A.; Alam, M. S.; Alam, M. A.; Albert, J.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allbrooke, B. M. M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amaral, P.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anisenkov, A.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Aubert, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barashkou, A.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, V.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beale, S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, S.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Behar Harpaz, S.; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertella, C.; Bertin, A.; Bertinelli, F.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blazek, T.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boelaert, N.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Bolnet, N. M.; Bomben, M.; Bona, M.; Bondarenko, V. G.; Bondioli, M.; Boonekamp, M.; Booth, C. N.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borri, M.; Borroni, S.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Botterill, D.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozhko, N. I.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Branchini, P.; Brandenburg, G. W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brelier, B.; Bremer, J.; Brenner, R.; Bressler, S.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brodbeck, T. J.; Brodet, E.; Broggi, F.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, W. K.; Brown, G.; Brown, H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.

    2012-03-01

    A search for the standard model Higgs boson is performed in the diphoton decay channel. The data used correspond to an integrated luminosity of 4.9fb-1 collected with the ATLAS detector at the Large Hadron Collider in proton-proton collisions at a center-of-mass energy of s=7TeV. In the diphoton mass range 110-150 GeV, the largest excess with respect to the background-only hypothesis is observed at 126.5 GeV, with a local significance of 2.8 standard deviations. Taking the look-elsewhere effect into account in the range 110-150 GeV, this significance becomes 1.5 standard deviations. The standard model Higgs boson is excluded at 95% confidence level in the mass ranges of 113-115 GeV and 134.5-136 GeV.

  3. Search for the standard model Higgs boson in the diphoton decay channel with 4.9 fb(-1) of pp collision data at √s=7 TeV with ATLAS.

    PubMed

    Aad, G; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdelalim, A A; Abdesselam, A; Abdinov, O; Abi, B; Abolins, M; Abouzeid, O S; Abramowicz, H; Abreu, H; Acerbi, E; Acharya, B S; Adamczyk, L; Adams, D L; Addy, T N; Adelman, J; Aderholz, M; Adomeit, S; Adragna, P; Adye, T; Aefsky, S; Aguilar-Saavedra, J A; Aharrouche, M; Ahlen, S P; Ahles, F; Ahmad, A; Ahsan, M; Aielli, G; Akdogan, T; Akesson, T P A; Akimoto, G; Akimov, A V; Akiyama, A; Alam, M S; Alam, M A; Albert, J; Albrand, S; Aleksa, M; Aleksandrov, I N; Alessandria, F; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Aliev, M; Alimonti, G; Alison, J; Aliyev, M; Allbrooke, B M M; Allport, P P; Allwood-Spiers, S E; Almond, J; Aloisio, A; Alon, R; Alonso, A; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amaral, P; Amelung, C; Ammosov, V V; Amorim, A; Amorós, G; Amram, N; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Andrieux, M-L; Anduaga, X S; Angerami, A; Anghinolfi, F; Anisenkov, A; Anjos, N; Annovi, A; Antonaki, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoun, S; Aperio Bella, L; Apolle, R; Arabidze, G; Aracena, I; Arai, Y; Arce, A T H; Arfaoui, S; Arguin, J-F; Arik, E; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arnault, C; Artamonov, A; Artoni, G; Arutinov, D; Asai, S; Asfandiyarov, R; Ask, S; Asman, B; Asquith, L; Assamagan, K; Astbury, A; Astvatsatourov, A; Aubert, B; Auge, E; Augsten, K; Aurousseau, M; Avolio, G; Avramidou, R; Axen, D; Ay, C; Azuelos, G; Azuma, Y; Baak, M A; Baccaglioni, G; Bacci, C; Bach, A M; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Badescu, E; Bagnaia, P; Bahinipati, S; Bai, Y; Bailey, D C; Bain, T; Baines, J T; Baker, O K; Baker, M D; Baker, S; Banas, E; Banerjee, P; Banerjee, Sw; Banfi, D; Bangert, A; Bansal, V; Bansil, H S; Barak, L; Baranov, S P; Barashkou, A; Barbaro Galtieri, A; Barber, T; Barberio, E L; Barberis, D; Barbero, M; Bardin, D Y; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; 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Shapiro, M; Shatalov, P B; Shaver, L; Shaw, K; Sherman, D; Sherwood, P; Shibata, A; Shichi, H; Shimizu, S; Shimojima, M; Shin, T; Shiyakova, M; Shmeleva, A; Shochet, M J; Short, D; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sidoti, A; Siegert, F; Sijacki, Dj; Silbert, O; Silva, J; Silver, Y; Silverstein, D; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simmons, B; Simoniello, R; Simonyan, M; Sinervo, P; Sinev, N B; Sipica, V; Siragusa, G; Sircar, A; Sisakyan, A N; Sivoklokov, S Yu; Sjölin, J; Sjursen, T B; Skinnari, L A; Skottowe, H P; Skovpen, K; Skubic, P; Skvorodnev, N; Slater, M; Slavicek, T; Sliwa, K; Sloper, J; Smakhtin, V; Smart, B H; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, B C; Smith, D; Smith, K M; Smizanska, M; Smolek, K; Snesarev, A A; Snow, S W; Snow, J; Snuverink, J; Snyder, S; Soares, M; Sobie, R; Sodomka, J; Soffer, A; Solans, C A; Solar, M; Solc, J; Soldatov, E; Soldevila, U; Solfaroli Camillocci, E; Solodkov, A A; Solovyanov, O V; Soni, N; Sopko, V; Sopko, B; Sosebee, M; Soualah, R; Soukharev, A; Spagnolo, S; Spanò, F; Spighi, R; Spigo, G; Spila, F; Spiwoks, R; Spousta, M; Spreitzer, T; Spurlock, B; St Denis, R D; Stahlman, J; Stamen, R; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staude, A; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stevenson, K; Stewart, G A; Stillings, J A; Stockton, M C; Stoerig, K; Stoicea, G; Stonjek, S; Strachota, P; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strang, M; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Strong, J A; Stroynowski, R; Strube, J; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Soh, D A; Su, D; Subramania, Hs; Succurro, A; Sugaya, Y; Sugimoto, T; Suhr, C; Suita, K; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Sushkov, S; Susinno, G; Sutton, M R; Suzuki, Y; Suzuki, Y; Svatos, M; Sviridov, Yu M; Swedish, S; Sykora, I; Sykora, T; Szeless, B; Sánchez, J; Ta, D; Tackmann, K; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A; Tamsett, M C; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanaka, Y; Tanasijczuk, A J; Tani, K; Tannoury, N; Tappern, G P; Tapprogge, S; Tardif, D; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tassi, E; Tatarkhanov, M; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teinturier, M; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Testa, M; Teuscher, R J; Thadome, J; Therhaag, J; Theveneaux-Pelzer, T; Thioye, M; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tipton, P; Tique Aires Viegas, F J; Tisserant, S; Tobias, J; Toczek, B; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokunaga, K; Tokushuku, K; Tollefson, K; Tomoto, M; Tompkins, L; Toms, K; Tong, G; Tonoyan, A; Topfel, C; Topilin, N D; Torchiani, I; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Trinh, T N; Tripiana, M F; Trischuk, W; Trivedi, A; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiakiris, M; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsung, J-W; Tsuno, S; Tsybychev, D; Tua, A; Tudorache, A; Tudorache, V; Tuggle, J M; Turala, M; Turecek, D; Turk Cakir, I; Turlay, E; Turra, R; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Tzanakos, G; Uchida, K; Ueda, I; Ueno, R; Ugland, M; Uhlenbrock, M; Uhrmacher, M; Ukegawa, F; Unal, G; Underwood, D G; Undrus, A; Unel, G; Unno, Y; Urbaniec, D; Usai, G; Uslenghi, M; Vacavant, L; Vacek, V; Vachon, B; Vahsen, S; Valenta, J; Valente, P; Valentinetti, S; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; van der Graaf, H; van der Kraaij, E; Van Der Leeuw, R; van der Poel, E; van der Ster, D; van Eldik, N; van Gemmeren, P; van Kesteren, Z; van Vulpen, I; Vanadia, M; Vandelli, W; Vandoni, G; Vaniachine, A; Vankov, P; Vannucci, F; Varela Rodriguez, F; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vassilakopoulos, V I; Vazeille, F; Vazquez Schroeder, T; Vegni, G; Veillet, J J; Vellidis, C; Veloso, F; Veness, R; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinek, E; Vinogradov, V B; Virchaux, M; Virzi, J; Vitells, O; Viti, M; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vlasov, N; Vogel, A; Vokac, P; Volpi, G; Volpi, M; Volpini, G; von der Schmitt, H; von Loeben, J; von Radziewski, H; von Toerne, E; Vorobel, V; Vorobiev, A P; Vorwerk, V; Vos, M; Voss, R; Voss, T T; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vu Anh, T; Vuillermet, R; Vukotic, I; Wagner, W; Wagner, P; Wahlen, H; Wakabayashi, J; Walch, S; Walder, J; Walker, R; Walkowiak, W; Wall, R; Waller, P; Wang, C; Wang, H; Wang, H; Wang, J; Wang, J; Wang, J C; Wang, R; Wang, S M; Warburton, A; Ward, C P; Warsinsky, M; Wasicki, C; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, A T; Waugh, B M; Weber, M; Weber, M S; Weber, P; Weidberg, A R; Weigell, P; Weingarten, J; Weiser, C; Wellenstein, H; Wells, P S; Wenaus, T; Wendland, D; Wendler, S; Weng, Z; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Werth, M; Wessels, M; Wetter, J; Weydert, C; Whalen, K; Wheeler-Ellis, S J; Whitaker, S P; White, A; White, M J; Whitehead, S R; Whiteson, D; Whittington, D; Wicek, F; Wicke, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik, L A M; Wijeratne, P A; Wildauer, A; Wildt, M A; Wilhelm, I; Wilkens, H G; Will, J Z; Williams, E; Williams, H H; Willis, W; Willocq, S; Wilson, J A; Wilson, M G; Wilson, A; Wingerter-Seez, I; Winkelmann, S; Winklmeier, F; Wittgen, M; Wolter, M W; Wolters, H; Wong, W C; Wooden, G; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wraight, K; Wright, C; Wright, M; Wrona, B; Wu, S L; Wu, X; Wu, Y; Wulf, E; Wunstorf, R; Wynne, B M; Xella, S; Xiao, M; Xie, S; Xie, Y; Xu, C; Xu, D; Xu, G; Yabsley, B; Yacoob, S; Yamada, M; Yamaguchi, H; Yamamoto, A; Yamamoto, K; Yamamoto, S; Yamamura, T; Yamanaka, T; Yamaoka, J; Yamazaki, T; Yamazaki, Y; Yan, Z; Yang, H; Yang, U K; Yang, Y; Yang, Y; Yang, Z; Yanush, S; Yao, Y; Yasu, Y; Ybeles Smit, G V; Ye, J; Ye, S; Yilmaz, M; Yoosoofmiya, R; Yorita, K; Yoshida, R; Young, C; Youssef, S; Yu, D; Yu, J; Yu, J; Yuan, L; Yurkewicz, A; Zabinski, B; Zaets, V G; Zaidan, R; Zaitsev, A M; Zajacova, Z; Zanello, L; Zaytsev, A; Zeitnitz, C; Zeller, M; Zeman, M; Zemla, A; Zendler, C; Zenin, O; Zeniš, T; Zenonos, Z; Zenz, S; Zerwas, D; Zevi della Porta, G; Zhan, Z; Zhang, D; Zhang, H; Zhang, J; Zhang, X; Zhang, Z; Zhao, L; Zhao, T; Zhao, Z; Zhemchugov, A; Zheng, S; Zhong, J; Zhou, B; Zhou, N; Zhou, Y; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhuravlov, V; Zieminska, D; Zimmermann, R; Zimmermann, S; Zimmermann, S; Ziolkowski, M; Zitoun, R; Zivković, L; Zmouchko, V V; Zobernig, G; Zoccoli, A; Zolnierowski, Y; Zsenei, A; zur Nedden, M; Zutshi, V; Zwalinski, L

    2012-03-16

    A search for the standard model Higgs boson is performed in the diphoton decay channel. The data used correspond to an integrated luminosity of 4.9 fb(-1) collected with the ATLAS detector at the Large Hadron Collider in proton-proton collisions at a center-of-mass energy of √s=7 TeV. In the diphoton mass range 110-150 GeV, the largest excess with respect to the background-only hypothesis is observed at 126.5 GeV, with a local significance of 2.8 standard deviations. Taking the look-elsewhere effect into account in the range 110-150 GeV, this significance becomes 1.5 standard deviations. The standard model Higgs boson is excluded at 95% confidence level in the mass ranges of 113-115 GeV and 134.5-136 GeV.

  4. Search for the standard model higgs Boson in the ZH-->nunubb channel in 5.2 fb{-1} of pp collisions at sqrt[s]=1.96 TeV.

    PubMed

    Abazov, V M; Abbott, B; Abolins, M; Acharya, B S; Adams, M; Adams, T; Aguilo, E; Alexeev, G D; Alkhazov, G; Alton, A; Alverson, G; Alves, G A; Ancu, L S; Aoki, M; Arnoud, Y; Arov, M; Askew, A; Asman, B; Atramentov, O; Avila, C; Backusmayes, J; Badaud, F; Bagby, L; Baldin, B; Bandurin, D V; Banerjee, S; Barberis, E; Barfuss, A-F; Baringer, P; Barreto, J; Bartlett, J F; Bassler, U; Bauer, D; Beale, S; Bean, A; Begalli, M; Begel, M; Belanger-Champagne, C; Bellantoni, L; Benitez, J A; Beri, S B; Bernardi, G; Bernhard, R; Bertram, I; Besançon, M; Beuselinck, R; Bezzubov, V A; Bhat, P C; Bhatnagar, V; Blazey, G; Blessing, S; Bloom, K; Boehnlein, A; Boline, D; Bolton, T A; Boos, E E; Borissov, G; Bose, T; Brandt, A; Brock, R; Brooijmans, G; Bross, A; Brown, D; Bu, X B; Buchholz, D; Buehler, M; Buescher, V; Bunichev, V; Burdin, S; Burnett, T H; Buszello, C P; Calfayan, P; Calpas, B; Calvet, S; Camacho-Pérez, E; Cammin, J; Carrasco-Lizarraga, M A; Carrera, E; Casey, B C K; Castilla-Valdez, H; Chakrabarti, S; Chakraborty, D; Chan, K M; Chandra, A; Cheu, E; Chevalier-Théry, S; Cho, D K; Cho, S W; Choi, S; Choudhary, B; Christoudias, T; Cihangir, S; Claes, D; Clutter, J; Cooke, M; Cooper, W E; Corcoran, M; Couderc, F; Cousinou, M-C; Cutts, D; Cwiok, M; Das, A; Davies, G; De, K; de Jong, S J; De La Cruz-Burelo, E; Devaughan, K; Déliot, F; Demarteau, M; Demina, R; Denisov, D; Denisov, S P; Desai, S; Diehl, H T; Diesburg, M; Dominguez, A; Dorland, T; Dubey, A; Dudko, L V; Duflot, L; Duggan, D; Duperrin, A; Dutt, S; Dyshkant, A; Eads, M; Edmunds, D; Ellison, J; Elvira, V D; Enari, Y; Eno, S; Evans, H; Evdokimov, A; Evdokimov, V N; Facini, G; Ferapontov, A V; Ferbel, T; Fiedler, F; Filthaut, F; Fisher, W; Fisk, H E; Fortner, M; Fox, H; Fuess, S; Gadfort, T; Galea, C F; Garcia-Bellido, A; Gavrilov, V; Gay, P; Geist, W; Geng, W; Gerbaudo, D; Gerber, C E; Gershtein, Y; Gillberg, D; Ginther, G; Golovanov, G; Gómez, B; Goussiou, A; Grannis, P D; Greder, S; Greenlee, H; Greenwood, Z D; Gregores, E M; Grenier, G; Gris, Ph; Grivaz, J-F; Grohsjean, A; Grünendahl, S; Grünewald, M W; Guo, F; Guo, J; Gutierrez, G; Gutierrez, P; Haas, A; Haefner, P; Hagopian, S; Haley, J; Hall, I; Han, L; Harder, K; Harel, A; Hauptman, J M; Hays, J; Hebbeker, T; Hedin, D; Hegeman, J G; Heinson, A P; Heintz, U; Hensel, C; Heredia-De La Cruz, I; Herner, K; Hesketh, G; Hildreth, M D; Hirosky, R; Hoang, T; Hobbs, J D; Hoeneisen, B; Hohlfeld, M; Hossain, S; Houben, P; Hu, Y; Hubacek, Z; Huske, N; Hynek, V; Iashvili, I; Illingworth, R; Ito, A S; Jabeen, S; Jaffré, M; Jain, S; Jamin, D; Jesik, R; Johns, K; Johnson, C; Johnson, M; Johnston, D; Jonckheere, A; Jonsson, P; Juste, A; Kajfasz, E; Karmanov, D; Kasper, P A; Katsanos, I; Kaushik, V; Kehoe, R; Kermiche, S; Khalatyan, N; Khanov, A; Kharchilava, A; Kharzheev, Y N; Khatidze, D; Kirby, M H; Kirsch, M; Kohli, J M; Kozelov, A V; Kraus, J; Kumar, A; Kupco, A; Kurca, T; Kuzmin, V A; Kvita, J; Lam, D; Lammers, S; Landsberg, G; Lebrun, P; Lee, H S; Lee, W M; Leflat, A; Lellouch, J; Li, L; Li, Q Z; Lietti, S M; Lim, J K; Lincoln, D; Linnemann, J; Lipaev, V V; Lipton, R; Liu, Y; Liu, Z; Lobodenko, A; Lokajicek, M; Love, P; Lubatti, H J; Luna-Garcia, R; Lyon, A L; Maciel, A K A; Mackin, D; Mättig, P; Magaña-Villalba, R; Mal, P K; Malik, S; Malyshev, V L; Maravin, Y; Martínez-Ortega, J; McCarthy, R; McGivern, C L; Meijer, M M; Melnitchouk, A; Mendoza, L; Menezes, D; Mercadante, P G; Merkin, M; Meyer, A; Meyer, J; Mommsen, R K; Mondal, N K; Moulik, T; Muanza, G S; Mulhearn, M; Mundal, O; Mundim, L; Nagy, E; Naimuddin, M; Narain, M; Nayyar, R; Neal, H A; Negret, J P; Neustroev, P; Nilsen, H; Nogima, H; Novaes, S F; Nunnemann, T; Obrant, G; Ochando, C; Onoprienko, D; Orduna, J; Osman, N; Osta, J; Otec, R; Otero Y Garzón, G J; Owen, M; Padilla, M; Padley, P; Pangilinan, M; Parashar, N; Parihar, V; Park, S-J; Park, S K; Parsons, J; Partridge, R; Parua, N; Patwa, A; Penning, B; Perfilov, M; Peters, K; Peters, Y; Pétroff, P; Piegaia, R; Piper, J; Pleier, M-A; Podesta-Lerma, P L M; Podstavkov, V M; Pol, M-E; Polozov, P; Popov, A V; Prewitt, M; Price, D; Protopopescu, S; Qian, J; Quadt, A; Quinn, B; Rangel, M S; Ranjan, K; Ratoff, P N; Razumov, I; Renkel, P; Rich, P; Rijssenbeek, M; Ripp-Baudot, I; Rizatdinova, F; Robinson, S; Rominsky, M; Royon, C; Rubinov, P; Ruchti, R; Safronov, G; Sajot, G; Sánchez-Hernández, A; Sanders, M P; Sanghi, B; Savage, G; Sawyer, L; Scanlon, T; Schaile, D; Schamberger, R D; Scheglov, Y; Schellman, H; Schliephake, T; Schlobohm, S; Schwanenberger, C; Schwienhorst, R; Sekaric, J; Severini, H; Shabalina, E; Shary, V; Shchukin, A A; Shivpuri, R K; Simak, V; Sirotenko, V; Skubic, P; Slattery, P; Smirnov, D; Snow, G R; Snow, J; Snyder, S; Söldner-Rembold, S; Sonnenschein, L; Sopczak, A; Sosebee, M; Soustruznik, K; Spurlock, B; Stark, J; Stolin, V; Stoyanova, D A; Strandberg, J; Strang, M A; Strauss, E; Strauss, M; Ströhmer, R; Strom, D; Stutte, L; Svoisky, P; Takahashi, M; Tanasijczuk, A; Taylor, W; Tiller, B; Titov, M; Tokmenin, V V; Tsybychev, D; Tuchming, B; Tully, C; Tuts, P M; Unalan, R; Uvarov, L; Uvarov, S; Uzunyan, S; van den Berg, P J; Van Kooten, R; van Leeuwen, W M; Varelas, N; Varnes, E W; Vasilyev, I A; Verdier, P; Vertogradov, L S; Verzocchi, M; Vesterinen, M; Vilanova, D; Vint, P; Vokac, P; Wahl, H D; Wang, M H L S; Warchol, J; Watts, G; Wayne, M; Weber, G; Weber, M; Wetstein, M; White, A; Wicke, D; Williams, M R J; Wilson, G W; Wimpenny, S J; Wobisch, M; Wood, D R; Wyatt, T R; Xie, Y; Xu, C; Yacoob, S; Yamada, R; Yang, W-C; Yasuda, T; Yatsunenko, Y A; Ye, Z; Yin, H; Yip, K; Yoo, H D; Youn, S W; Yu, J; Zeitnitz, C; Zelitch, S; Zhao, T; Zhou, B; Zhu, J; Zielinski, M; Zieminska, D; Zivkovic, L; Zutshi, V; Zverev, E G

    2010-02-19

    A search is performed for the standard model Higgs boson in 5.2 fb{-1} of pp collisions at sqrt[s]=1.96 TeV, collected with the D0 detector at the Fermilab Tevatron Collider. The final state considered is a pair of b jets and large missing transverse energy, as expected from pp-->ZH-->nunubb production. The search is also sensitive to the WH-->lnubb channel when the charged lepton is not identified. For a Higgs boson mass of 115 GeV, a limit is set at the 95% C.L. on the cross section multiplied by branching fraction for [pp-->(Z/W)H](H-->bb) that is a factor of 3.7 larger than the standard model value, consistent with the factor of 4.6 expected.

  5. Alternative approaches for econometric analysis of panel count data using dynamic latent class models (with application to doctor visits data).

    PubMed

    Hyppolite, Judex; Trivedi, Pravin

    2012-06-01

    Cross-sectional latent class regression models, also known as switching regressions or hidden Markov models, cannot identify transitions between classes that may occur over time. This limitation can potentially be overcome when panel data are available. For such data, we develop a sequence of models that combine features of the static cross-sectional latent class (finite mixture) models with those of hidden Markov models. We model the probability of movement between categories in terms of a Markovian structure, which links the current state with a previous state, where state may refer to the category of an individual. This article presents a suite of mixture models of varying degree of complexity and flexibility for use in a panel count data setting, beginning with a baseline model which is a two-component mixture of Poisson distribution in which latent classes are fixed and permanent. Sequentially, we extend this framework (i) to allow the mixing proportions to be smoothly varying continuous functions of time-varying covariates, (ii) to add time dependence to the benchmark model by modeling the class-indicator variable as a first-order Markov chain and (iii) to extend item (i) by making it dynamic and introducing covariate dependence in the transition probabilities. We develop and implement estimation algorithms for these models and provide an empirical illustration using 1995-1999 panel data on the number of doctor visits derived from the German Socio-Economic Panel.

  6. Exactly solvable spin chain models corresponding to BDI class of topological superconductors.

    PubMed

    Jafari, S A; Shahbazi, Farhad

    2016-09-06

    We present an exactly solvable extension of the quantum XY chain with longer range multi-spin interactions. Topological phase transitions of the model are classified in terms of the number of Majorana zero modes, nM which are in turn related to an integer winding number, nW. The present class of exactly solvable models belong to the BDI class in the Altland-Zirnbauer classification of topological superconductors. We show that time reversal symmetry of the spin variables translates into a sliding particle-hole (PH) transformation in the language of Jordan-Wigner fermions - a PH transformation followed by a π shift in the wave vector which we call it the πPH. Presence of πPH symmetry restricts the nW (nM) of time-reversal symmetric extensions of XY to odd (even) integers. The πPH operator may serve in further detailed classification of topological superconductors in higher dimensions as well.

  7. A class of exact isotropic solutions of Einstein's equations and relativistic stellar models in general relativity

    NASA Astrophysics Data System (ADS)

    Murad, Mohammad Hassan; Pant, Neeraj

    2014-03-01

    In this paper we have studied a particular class of exact solutions of Einstein's gravitational field equations for spherically symmetric and static perfect fluid distribution in isotropic coordinates. The Schwarzschild compactness parameter, GM/ c 2 R, can attain the maximum value 0.1956 up to which the solution satisfies the elementary tests of physical relevance. The solution also found to have monotonic decreasing adiabatic sound speed from the centre to the boundary of the fluid sphere. A wide range of fluid spheres of different mass and radius for a given compactness is possible. The maximum mass of the fluid distribution is calculated by using stellar surface density as parameter. The values of different physical variables obtained for some potential strange star candidates like Her X-1, 4U 1538-52, LMC X-4, SAX J1808.4-3658 given by our analytical model demonstrate the astrophysical significance of our class of relativistic stellar models in the study of internal structure of compact star such as self-bound strange quark star.

  8. Exactly solvable spin chain models corresponding to BDI class of topological superconductors

    PubMed Central

    Jafari, S. A.; Shahbazi, Farhad

    2016-01-01

    We present an exactly solvable extension of the quantum XY chain with longer range multi-spin interactions. Topological phase transitions of the model are classified in terms of the number of Majorana zero modes, nM which are in turn related to an integer winding number, nW. The present class of exactly solvable models belong to the BDI class in the Altland-Zirnbauer classification of topological superconductors. We show that time reversal symmetry of the spin variables translates into a sliding particle-hole (PH) transformation in the language of Jordan-Wigner fermions – a PH transformation followed by a π shift in the wave vector which we call it the πPH. Presence of πPH symmetry restricts the nW (nM) of time-reversal symmetric extensions of XY to odd (even) integers. The πPH operator may serve in further detailed classification of topological superconductors in higher dimensions as well. PMID:27596804

  9. Exactly solvable spin chain models corresponding to BDI class of topological superconductors

    NASA Astrophysics Data System (ADS)

    Jafari, S. A.; Shahbazi, Farhad

    2016-09-01

    We present an exactly solvable extension of the quantum XY chain with longer range multi-spin interactions. Topological phase transitions of the model are classified in terms of the number of Majorana zero modes, nM which are in turn related to an integer winding number, nW. The present class of exactly solvable models belong to the BDI class in the Altland-Zirnbauer classification of topological superconductors. We show that time reversal symmetry of the spin variables translates into a sliding particle-hole (PH) transformation in the language of Jordan-Wigner fermions – a PH transformation followed by a π shift in the wave vector which we call it the πPH. Presence of πPH symmetry restricts the nW (nM) of time-reversal symmetric extensions of XY to odd (even) integers. The πPH operator may serve in further detailed classification of topological superconductors in higher dimensions as well.

  10. Gauge coupling unification in a classically scale invariant model

    NASA Astrophysics Data System (ADS)

    Haba, Naoyuki; Ishida, Hiroyuki; Takahashi, Ryo; Yamaguchi, Yuya

    2016-02-01

    There are a lot of works within a class of classically scale invariant model, which is motivated by solving the gauge hierarchy problem. In this context, the Higgs mass vanishes at the UV scale due to the classically scale invariance, and is generated via the Coleman-Weinberg mechanism. Since the mass generation should occur not so far from the electroweak scale, we extend the standard model only around the TeV scale. We construct a model which can achieve the gauge coupling unification at the UV scale. In the same way, the model can realize the vacuum stability, smallness of active neutrino masses, baryon asymmetry of the universe, and dark matter relic abundance. The model predicts the existence vector-like fermions charged under SU(3) C with masses lower than 1 TeV, and the SM singlet Majorana dark matter with mass lower than 2.6 TeV.

  11. Class Schedules Need Class.

    ERIC Educational Resources Information Center

    Monfette, Ronald J.

    1986-01-01

    Argues that college publications, including class schedules, must be accurate, timely, and easy to read and follow. Describes Schoolcraft College's unified format approach to publications marketing. Offers suggestions on the design, format, and distribution of class schedules. (DMM)

  12. Dynamics of an HIV Model with Multiple Infection Stages and Treatment with Different Drug Classes.

    PubMed

    Wang, Xia; Song, Xinyu; Tang, Sanyi; Rong, Libin

    2016-02-01

    Highly active antiretroviral therapy can effectively control HIV replication in infected individuals. Some clinical and modeling studies suggested that viral decay dynamics may depend on the inhibited stages of the viral replication cycle. In this paper, we develop a general mathematical model incorporating multiple infection stages and various drug classes that can interfere with specific stages of the viral life cycle. We derive the basic reproductive number and obtain the global stability results of steady states. Using several simple cases of the general model, we study the effect of various drug classes on the dynamics of HIV decay. When drugs are assumed to be 100% effective, drugs acting later in the viral life cycle lead to a faster or more rapid decay in viremia. This is consistent with some patient and experimental data, and also agrees with previous modeling results. When drugs are not 100% effective, the viral decay dynamics are more complicated. Without a second population of long-lived infected cells, the viral load decline can have two phases if drugs act at an intermediate stage of the viral replication cycle. The slopes of viral load decline depend on the drug effectiveness, the death rate of infected cells at different stages, and the transition rate of infected cells from one to the next stage. With a second population of long-lived infected cells, the viral load decline can have three distinct phases, consistent with the observation in patients receiving antiretroviral therapy containing the integrase inhibitor raltegravir. We also fit modeling prediction to patient data under efavirenz (a nonnucleoside reverse-transcriptase inhibitor) and raltegravir treatment. The first-phase viral load decline under raltegravir therapy is longer than that under efavirenz, resulting in a lower viral load at initiation of the second-phase decline in patients taking raltegravir. This explains why patients taking a raltegravir-based therapy were faster to achieve

  13. Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 $\\,\\text {TeV}$

    SciTech Connect

    Khachatryan, Vardan

    2015-05-14

    Properties of the Higgs boson with mass near 125GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include γγ, ZZ, WW, ττ, bb, and μμ pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1fb-1 at 7TeV and up to 19.7fb-1 at 8TeV. From the high-resolution γγ and ZZ channels, the mass of the Higgs boson is determined to be 125.02+0.26–0.27 (stat) +0.14–0.15 (syst) GeV. For this mass value, the event yields obtained in the different analyses tagging specific decay channels and production mechanisms are consistent with those expected for the standard model Higgs boson. The combined best-fit signal relative to the standard model expectation is 1.00 ± 0.09(stat)+0.08–0.07 (theo) ± 0.07(syst) at the measured mass. The couplings of the Higgs boson are probed for deviations in magnitude from the standard model predictions in multiple ways, including searches for invisible and undetected decays. As a result, no significant deviations are found.

  14. Model reduction by trimming for a class of semi-Markov reliability models and the corresponding error bound

    NASA Technical Reports Server (NTRS)

    White, Allan L.; Palumbo, Daniel L.

    1991-01-01

    Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.

  15. Probing radiative neutrino mass models using trilepton channel at the LHC

    NASA Astrophysics Data System (ADS)

    Cherigui, Dounia; Guella, Chahrazed; Ahriche, Amine; Nasri, Salah

    2016-11-01

    In this work, we probe a class of neutrino mass models through the lepton flavor violating interactions of a singlet charged scalar, S± at the LHC proton-proton collisions with 8 TeV and 14 TeV energies. This scalar couples to the leptons and induces many processes such as pp →ℓ±ℓ±ℓ∓ +E̸T. In our analysis we discuss the opposite sign same flavor leptons signal, as well as the background free channel with the tau contribution which can enhance the signal/background ratio for center of mass energies √{ s} = 8 TeV and √{ s} = 14 TeV.

  16. A class of invisible axion models with FCNCs at tree level

    NASA Astrophysics Data System (ADS)

    Celis, Alejandro; Fuentes-Martín, Javier; Serôdio, Hugo

    2014-12-01

    We build a class of invisible axion models with tree-level Flavor Changing Neutral Currents completely controlled by the fermion mixing matrices. The scalar sector of these models contains three-Higgs doublets and a complex scalar gauge singlet, with the same fermionic content as in the Standard Model. A horizontal Peccei-Quinn symmetry provides a solution to the strong CP problem and predicts the existence of a very light and weakly coupled pseudo-Goldstone boson, the invisible axion or familon. A phenomenological analysis is performed taking into account familon searches in rare kaon and muon decays, astrophysical considerations and axion searches via axion-photon conversion. Drastic differences are found in the axion properties of different models due to the strong hierarchy of the CKM matrix, making some of the models considered much more constrained than others. We also obtain that a rich variety of these models avoid the domain wall problem. A possible mechanism to protect the solution to the strong CP problem against gravitational effects is also discussed.

  17. Identifying victims of workplace bullying by integrating traditional estimation approaches into a latent class cluster model.

    PubMed

    Leon-Perez, Jose M; Notelaers, Guy; Arenas, Alicia; Munduate, Lourdes; Medina, Francisco J

    2014-05-01

    Research findings underline the negative effects of exposure to bullying behaviors and document the detrimental health effects of being a victim of workplace bullying. While no one disputes its negative consequences, debate continues about the magnitude of this phenomenon since very different prevalence rates of workplace bullying have been reported. Methodological aspects may explain these findings. Our contribution to this debate integrates behavioral and self-labeling estimation methods of workplace bullying into a measurement model that constitutes a bullying typology. Results in the present sample (n = 1,619) revealed that six different groups can be distinguished according to the nature and intensity of reported bullying behaviors. These clusters portray different paths for the workplace bullying process, where negative work-related and person-degrading behaviors are strongly intertwined. The analysis of the external validity showed that integrating previous estimation methods into a single measurement latent class model provides a reliable estimation method of workplace bullying, which may overcome previous flaws.

  18. A class of regular and well behaved relativistic super-dense star models

    NASA Astrophysics Data System (ADS)

    Gupta, Y. K.; Maurya, Sunil Kumar

    2011-03-01

    We obtain a new class of charged super-dense star models after prescribing particular forms of the metric potential g 44 and electric intensity. The metric describing the superdense stars joins smoothly with the Reissner-Nordstrom metric at the pressure free boundary. The interior of the stars possess there energy density, pressure, pressure-density ratio and velocity of sound to be monotonically decreasing towards the pressure free interface. In view of the surface density 2×1014 g/cm3, the heaviest star occupies a mass 5.6996 M ⊙ with its radius 17.0960 km. The red shift at the centre and boundary are found to be 3.5120 and 1.1268 respectively. In absence of the charge we are left behind with the regular and well behaved fifth model of Durgapal (J. Phys. A 15:2637, 1982).

  19. Object-based class modelling for multi-scale riparian forest habitat mapping

    NASA Astrophysics Data System (ADS)

    Strasser, Thomas; Lang, Stefan

    2015-05-01

    Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m2 were modelled from 938 forest stand patches (MPS = 6868.20 m2) and 43,742 tree stand patches (MPS = 140.79 m2). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.

  20. Search for the Standard Model Higgs produced in association with a vector boson and decaying to a b b pair in pp collisions at √{ s} = 13 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Montalbano, Alyssa; Atlas Collaboration

    2017-01-01

    The Standard Model (SM) Higgs boson has yet to be measured in its predicted dominant decay mode, b b , owing to the high quantum chromodynamics (QCD) background at the Large Hadron Collider. This decay mode provides the largest avenue for new physics if the H -> b b measurement differs from the SM predictions. We significantly reduce the large QCD background by requiring the Higgs boson to be produced with an associated vector boson (Z,W) which then decays in a leptonic mode. I will discuss recent results from this search in pp collisions at √{ s} = 13 TeV with the ATLAS detector, a data-driven estimate of the QCD background, and optimizations for the measurement of VH production.

  1. Search for a Low-Mass Standard Model Higgs Boson in the ττ Decay Channel in pp̄ Collisions at √s=1.96 TeV

    SciTech Connect

    Aaltonen, T.; Álvarez González, B.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Appel, J. A.; Apresyan, A.; Arisawa, T.; Artikov, A.; Asaadi, J.; Ashmanskas, W.; Auerbach, B.; Aurisano, A.; Azfar, F.; Badgett, W.; Barbaro-Galtieri, A.; Barnes, V. E.; Barnett, B. A.; Barria, P.; Bartos, P.; Bauce, M.; Bauer, G.; Bedeschi, F.; Beecher, D.; Behari, S.; Bellettini, G.; Bellinger, J.; Benjamin, D.; Beretvas, A.; Bhatti, A.; Binkley, M.; Bisello, D.; Bizjak, I.; Bland, K. R.; Blumenfeld, B.; Bocci, A.; Bodek, A.; Bortoletto, D.; Boudreau, J.; Boveia, A.; Brau, B.; Brigliadori, L.; Brisuda, A.; Bromberg, C.; Brucken, E.; Bucciantonio, M.; Budagov, J.; Budd, H. S.; Budd, S.; Burkett, K.; Busetto, G.; Bussey, P.; Buzatu, A.; Calancha, C.; Camarda, S.; Campanelli, M.; Campbell, M.; Canelli, F.; Canepa, A.; Carls, B.; Carlsmith, D.; Carosi, R.; Carrillo, S.; Carron, S.; Casal, B.; Casarsa, M.; Castro, A.; Catastini, P.; Cauz, D.; Cavaliere, V.; Cavalli-Sforza, M.; Cerri, A.; Cerrito, L.; Chen, Y. C.; Chertok, M.; Chiarelli, G.; Chlachidze, G.; Chlebana, F.; Cho, K.; Chokheli, D.; Chou, J. P.; Chung, W. H.; Chung, Y. S.; Ciobanu, C. I.; Ciocci, M. A.; Clark, A.; Clarke, C.; Compostella, G.; Convery, M. E.; Conway, J.; Corbo, M.; Cordelli, M.; Cox, C. A.; Cox, D. J.; Crescioli, F.; Cuenca Almenar, C.; Cuevas, J.; Culbertson, R.; Dagenhart, D.; d’Ascenzo, N.; Datta, M.; de Barbaro, P.; De Cecco, S.; De Lorenzo, G.; Dell’Orso, M.; Deluca, C.; Demortier, L.; Deng, J.; Deninno, M.; Devoto, F.; d’Errico, M.; Di Canto, A.; Di Ruzza, B.; Dittmann, J. R.; D’Onofrio, M.; Donati, S.; Dong, P.; Dorigo, M.; Dorigo, T.; Ebina, K.; Elagin, A.; Eppig, A.; Erbacher, R.; Errede, D.; Errede, S.; Ershaidat, N.; Eusebi, R.; Fang, H. C.; Farrington, S.; Feindt, M.; Fernandez, J. P.; Ferrazza, C.; Field, R.; Flanagan, G.; Forrest, R.; Frank, M. J.; Franklin, M.; Freeman, J. C.; Funakoshi, Y.; Furic, I.; Gallinaro, M.; Galyardt, J.; Garcia, J. E.; Garfinkel, A. F.; Garosi, P.; Gerberich, H.; Gerchtein, E.; Giagu, S.; Giakoumopoulou, V.; Giannetti, P.; Gibson, K.; Ginsburg, C. M.; Giokaris, N.; Giromini, P.; Giunta, M.; Giurgiu, G.; Glagolev, V.; Glenzinski, D.; Gold, M.; Goldin, D.; Goldschmidt, N.; Golossanov, A.; Gomez, G.; Gomez-Ceballos, G.; Goncharov, M.; González, O.; Gorelov, I.; Goshaw, A. T.; Goulianos, K.; Grinstein, S.; Grosso-Pilcher, C.; Group, R. C.; Guimaraes da Costa, J.; Gunay-Unalan, Z.; Haber, C.; Hahn, S. R.; Halkiadakis, E.; Hamaguchi, A.; Han, J. Y.; Happacher, F.; Hara, K.; Hare, D.; Hare, M.; Harr, R. F.; Hatakeyama, K.; Hays, C.; Heck, M.; Heinrich, J.; Herndon, M.; Hewamanage, S.; Hidas, D.; Hocker, A.; Hopkins, W.; Horn, D.; Hou, S.; Hughes, R. E.; Hurwitz, M.; Husemann, U.; Hussain, N.; Hussein, M.; Huston, J.; Introzzi, G.; Iori, M.; Ivanov, A.; James, E.; Jang, D.; Jayatilaka, B.; Jeon, E. J.; Jha, M. K.; Jindariani, S.; Johnson, W.; Jones, M.; Joo, K. K.; Jun, S. Y.; Junk, T. R.; Kamon, T.; Karchin, P. E.; Kasmi, A.; Kato, Y.; Ketchum, W.; Keung, J.; Khotilovich, V.; Kilminster, B.; Kim, D. H.; Kim, H. S.; Kim, H. W.; Kim, J. E.; Kim, M. J.; Kim, S. B.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kirby, M.; Klimenko, S.; Kondo, K.; Kong, D. J.; Konigsberg, J.; Kotwal, A. V.; Kreps, M.; Kroll, J.; Krop, D.; Krumnack, N.; Kruse, M.; Krutelyov, V.; Kuhr, T.; Kurata, M.; Kwang, S.; Laasanen, A. T.; Lami, S.; Lammel, S.; Lancaster, M.; Lander, R. L.; Lannon, K.; Lath, A.; Latino, G.; LeCompte, T.; Lee, E.; Lee, H. S.; Lee, J. S.; Lee, S. W.; Leo, S.; Leone, S.; Lewis, J. D.; Limosani, A.; Lin, C.-J.; Linacre, J.; Lindgren, M.; Lipeles, E.; Lister, A.; Litvintsev, D. O.; Liu, C.; Liu, Q.; Liu, T.; Lockwitz, S.; Loginov, A.; Lucchesi, D.; Lueck, J.; Lujan, P.; Lukens, P.; Lungu, G.; Lys, J.; Lysak, R.; Madrak, R.; Maeshima, K.; Maestro, P.; Makhoul, K.; Malik, S.; Manca, G.; Manousakis-Katsikakis, A.; Margaroli, F.; Marino, C.; Martínez, M.; Martínez-Ballarín, R.; Mastrandrea, P.; Mattson, M. E.; Mazzanti, P.; McFarland, K. S.; McIntyre, P.; McNulty, R.; Mehta, A.; Mehtala, P.; Menzione, A.; Mesropian, C.; Miao, T.; Mietlicki, D.; Mitra, A.; Miyake, H.; Moed, S.; Moggi, N.; Mondragon, M. N.; Moon, C. S.; Moore, R.; Morello, M. J.; Morlock, J.; Movilla Fernandez, P.; Mukherjee, A.; Muller, Th.; Murat, P.; Mussini, M.; Nachtman, J.; Nagai, Y.; Naganoma, J.; Nakano, I.; Napier, A.; Nett, J.; Neu, C.; Neubauer, M. S.; Nielsen, J.; Nodulman, L.; Norniella, O.; Nurse, E.; Oakes, L.; Oh, S. H.; Oh, Y. D.; Oksuzian, I.; Okusawa, T.; Orava, R.; Ortolan, L.; Pagan Griso, S.; Pagliarone, C.; Palencia, E.; Papadimitriou, V.; Paramonov, A. A.; Patrick, J.; Pauletta, G.; Paulini, M.; Paus, C.; Pellett, D. E.; Penzo, A.; Phillips, T. J.; Piacentino, G.; Pianori, E.; Pilot, J.; Pitts, K.; Plager, C.; Pondrom, L.; Potamianos, K.; Poukhov, O.; Prokoshin, F.; Pronko, A.; Ptohos, F.; Pueschel, E.; Punzi, G.; Pursley, J.; Rahaman, A.; Ramakrishnan, V.; Ranjan, N.; Redondo, I.; Renton, P.; Rescigno, M.; Riddick, T.; Rimondi, F.; Ristori, L.; Robson, A.; Rodrigo, T.; Rodriguez, T.; Rogers, E.; Rolli, S.; Roser, R.; Rossi, M.; Rubbo, F.; Ruffini, F.; Ruiz, A.; Russ, J.; Rusu, V.; Safonov, A.; Sakumoto, W. K.; Sakurai, Y.; Santi, L.; Sartori, L.; Sato, K.; Saveliev, V.; Savoy-Navarro, A.; Schlabach, P.; Schmidt, A.; Schmidt, E. E.; Schmidt, M. P.; Schmitt, M.; Schwarz, T.; Scodellaro, L.; Scribano, A.; Scuri, F.; Sedov, A.; Seidel, S.; Seiya, Y.; Semenov, A.; Sforza, F.; Sfyrla, A.; Shalhout, S. Z.; Shears, T.; Shepard, P. F.; Shimojima, M.; Shiraishi, S.; Shochet, M.; Shreyber, I.; Simonenko, A.; Sinervo, P.; Sissakian, A.; Sliwa, K.; Smith, J. R.; Snider, F. D.; Soha, A.; Somalwar, S.; Sorin, V.; Squillacioti, P.; Stancari, M.; Stanitzki, M.; St. Denis, R.; Stelzer, B.; Stelzer-Chilton, O.; Stentz, D.; Strologas, J.; Strycker, G. L.; Sudo, Y.; Sukhanov, A.; Suslov, I.; Takemasa, K.; Takeuchi, Y.; Tang, J.; Tecchio, M.; Teng, P. K.; Thom, J.; Thome, J.; Thompson, G. A.; Thomson, E.; Ttito-Guzmán, P.; Tkaczyk, S.; Toback, D.; Tokar, S.; Tollefson, K.; Tomura, T.; Tonelli, D.; Torre, S.; Torretta, D.; Totaro, P.; Trovato, M.; Tu, Y.; Ukegawa, F.; Uozumi, S.; Varganov, A.; Vázquez, F.; Velev, G.; Vellidis, C.; Vidal, M.; Vila, I.; Vilar, R.; Vizán, J.; Vogel, M.; Volpi, G.; Wagner, P.; Wagner, R. L.; Wakisaka, T.; Wallny, R.; Wang, S. M.; Warburton, A.; Waters, D.; Weinberger, M.; Wester, W. C.; Whitehouse, B.; Whiteson, D.; Wicklund, A. B.; Wicklund, E.; Wilbur, S.; Wick, F.; Williams, H. H.; Wilson, J. S.; Wilson, P.; Winer, B. L.; Wittich, P.; Wolbers, S.; Wolfe, H.; Wright, T.; Wu, X.; Wu, Z.; Yamamoto, K.; Yamaoka, J.; Yang, T.; Yang, U. K.; Yang, Y. C.; Yao, W.-M.; Yeh, G. P.; Yi, K.; Yoh, J.; Yorita, K.; Yoshida, T.; Yu, G. B.; Yu, I.; Yu, S. S.; Yun, J. C.; Zanetti, A.; Zeng, Y.; Zucchelli, S.

    2012-05-02

    We report on a search for the standard model Higgs boson decaying into pairs of τ leptons in pp̄ collisions produced by the Tevatron at √s=1.96 TeV. The analyzed data sample was recorded by the CDFII detector and corresponds to an integrated luminosity of 6.0 fb⁻¹. The search is performed in the final state with one τ decaying leptonically and the second one identified through its semihadronic decay. Since no significant excess is observed, a 95% credibility level upper limit on the production cross section times branching ratio to the ττ final state is set for hypothetical Higgs boson masses between 100 and 150 GeV/c². For a Higgs boson of 120 GeV/c² the observed (expected) limit is 14.6 (15.3) the predicted value.

  2. Search for a Low-Mass Standard Model Higgs Boson in the ττ Decay Channel in pp̄ Collisions at √s=1.96 TeV

    DOE PAGES

    Aaltonen, T.; Álvarez González, B.; Amerio, S.; ...

    2012-05-02

    We report on a search for the standard model Higgs boson decaying into pairs of τ leptons in pp̄ collisions produced by the Tevatron at √s=1.96 TeV. The analyzed data sample was recorded by the CDFII detector and corresponds to an integrated luminosity of 6.0 fb⁻¹. The search is performed in the final state with one τ decaying leptonically and the second one identified through its semihadronic decay. Since no significant excess is observed, a 95% credibility level upper limit on the production cross section times branching ratio to the ττ final state is set for hypothetical Higgs boson massesmore » between 100 and 150 GeV/c². For a Higgs boson of 120 GeV/c² the observed (expected) limit is 14.6 (15.3) the predicted value.« less

  3. Model-independent measurement of $\\boldsymbol{t}$-channel single top quark production in $\\boldsymbol{p\\bar{p}}$ collisions at $\\boldsymbol{\\sqrt{s}=1.96}$ TeV

    SciTech Connect

    Abazov, Victor Mukhamedovich; Abbott, Braden Keim; Acharya, Bannanje Sripath; Adams, Mark Raymond; Adams, Todd; Alexeev, Guennadi D.; Alkhazov, Georgiy D.; Alton, Andrew K.; Alverson, George O.; Alves, Gilvan Augusto; Ancu, Lucian Stefan; /Nijmegen U. /Fermilab

    2011-05-01

    We present a model-independent measurement of t-channel electroweak production of single top quarks in p{bar p} collisions at {radical}s = 1.96 TeV. Using 5.4 fb{sup -1} of integrated luminosity collected by the D0 detector at the Fermilab Tevatron Collider, and selecting events containing an isolated electron or muon, missing transverse energy and one or two jets originating from the fragmentation of b quarks, we measure a cross section {sigma}(p{bar p} {yields} tqb + X) = 2.90 {+-} 0.59 (stat + syst) pb for a top quark mass of 172.5 GeV. The probability of the background to fluctuate and produce a signal as large as the one observed is 1.6 x 10{sup -8}, corresponding to a significance of 5.5 standard deviations.

  4. Search for the standard model Higgs boson produced in association with a vector boson and decaying into a tau pair in p p collisions at √{s }=8 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Aben, R.; Abolins, M.; Abouzeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansil, H. S.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Basye, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Beringer, J.; Bernard, C.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertsche, C.; Bertsche, D.; Besana, M. I.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bieniek, S. P.; Biglietti, M.; Bilbao de Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blanco, J. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozic, I.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, J.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruschi, M.; Bruscino, N.

    2016-05-01

    A search for the standard model Higgs boson produced in association with a vector boson with the decay H →τ τ is presented. The data correspond to 20.3 fb-1 of integrated luminosity from proton-proton collisions at √{s }=8 TeV recorded by the ATLAS experiment at the LHC during 2012. The data agree with the background expectation, and 95% confidence-level upper limits are placed on the cross section of this process. The observed (expected) limit, expressed in terms of the signal strength μ =σ /σSM for mH=125 GeV , is μ <5.6 (3.7). The measured value of the signal strength is μ =2.3 ±1.6 .

  5. Model-independent measurement of t-channel single top quark production in p(p)over-bar collisions at,root s=1.96 TeV

    SciTech Connect

    Abazov, V.M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Alverson, G.; Alves, G. A.; Ancu, L. S.; Aoki, M.; Arov, M.; Askew, A.; Asman, B.; Atramentov, O.; Avila, C.; BackusMayes, J.; Badaud, F.; Bagby, L.; Baldin, B.; Bandurin, D. V.; Banerjee, S.; Barberis, E.; Baringer, R.; Barreto, J.; Bartlett, J. F.; Bassler, U.; Bazterra, V.; Beale, S.; Bean, A.; Begalli, M.; Begel, M.; Belanger-Champagne, C.; Bellantoni, L.; Beri, S. B.; Bernardi, G.; Bernhard, R.; Bertram, I.; Besancon, M.; Beuselinck, R.; Bezzubov, V. A.; Bhat, P. C.; Bhatnagar, V.; Blazey, G.; Blessing, S.; Bloom, K.; Boehnlein, A.; Boline, D.; Boos, E. E.; Borissov, G.; Bose, T.; Brandt, A.; Brandt, O.; Brock, R.; Brooijmans, G.; Bross, A.; Brown, D.; Brown, J.; Bu, X. B.; Buehler, M.; Buescher, V.; Bunichev, V.; Burdin, S.; Burnett, T. H.; Buszello, C. P.; Calpas, B.; Camacho-Perez, E.; Carrasco-Lizarraga, M. A.; Casey, B. C. K.; Castilla-Valdez, H.; Chakrabarti, S.; Chakraborty, D.; Chan, K. M.; Chandra, A.; Chen, G.; Chevalier-Thery, S.; Cho, D. K.; Cho, S. W.; Choi, S.; Choudhary, B.; Cihangir, S.; Claes, D.; Clutter, J.; Cochran, J.; Cooke, M.; Cooper, W. E.; Corcoran, M.; Couderc, F.; Cousinou, M. -C.; Croc, A.; Cutts, D.; Das, A.; Davies, G.; De, K.; de Jong, S. J.; De La Cruz-Burelo, E.; Deliot, F.; Demarteau, M.; Demina, R.; Denisov, D.; Denisov, S. P.; Desai, S.; Deterre, C.; DeVaughan, K.; Diehl, H. T.; Diesburg, M.; Dominguez, A.; Dorland, T.; Dubey, A.; Dudko, L. V.; Duggan, D.; Duperrin, A.; Dutt, S.; Dyshkant, A.; Eads, M.; Edmunds, D.; Eller, P.; Ellison, J.; Elvira, V. D.; Enari, Y.; Evans, H.; Evdokimov, A.; Evdokimov, V. N.; Facini, G.; Ferbel, T.; Fiedler, F.; Filthaut, F.; Fisher, W.; Fisk, H. E.; Focke, C.; Fortner, M.; Fox, H.; Fuess, S.; Garcia-Bellido, A.; Gavrilov, V.; Gay, P.; Geng, W.; Gerbaudo, D.; Gerber, C. E.; Gershtein, Y.; Ginther, G.; Golovanov, G.; Goussiou, A.; Grannis, P. D.; Greder, S.; Greenlee, H.; Greenwood, Z. D.; Gregores, E. M.; Grenier, G.; Gris, Ph.; Grivaz, J. -F.; Grohsjean, A.; Gruenendahl, S.; Gruenewald, M. W.; Guillemin, T.; Guo, F.; Gutierrez, G.; Gutierrez, P.; Haas, A.; Hagopian, S.; Haley, J.; Han, L.; Harder, K.; Harel, A.; Hauptman, J. M.; Hays, J.; Head, T.; Hebbeker, T.; Hedin, D.; Hegab, H.; Heinson, A. P.; Heintz, U.; Hensel, C.; Heredia-De La Cruz, I.; Herner, K.; Hesketh, G.; Hildreth, M. D.; Hirosky, R.; Hoang, T.; Hobbs, J. D.; Hoeneisen, B.; Hohlfeld, M.; Hubacek, Z.; Huske, N.; Hynek, V.; Iashvili, I.; Illingworth, R.; Ito, A. S.; Jabeen, S.; Jaffre, M.; Jamin, D.; Jayasinghe, A.; Jesik, R.; Johns, K.; Johnson, M.; Johnston, D.; Jonckheere, A.; Jonsson, P.; Joshi, J.; Jung, A. W.; Juste, A.; Kaadze, K.; Kajfasz, E.; Karmanov, D.; Kasper, P. A.; Katsanos, I.; Kehoe, R.; Kermiche, S.; Khalatyan, N.; Khanov, A.; Kharchilava, A.; Kharzheev, Y. N.; Khatidze, D.; Kirby, M. H.; Kohli, J. M.; Kozelov, A. V.; Kraus, J.; Kulikov, S.; Kumar, A.; Kupco, A.; Kurca, T.; Kuzmin, V. A.; Kvita, J.; Lammers, S.; Landsberg, G.; Lebrun, P.; Lee, H. S.; Lee, S. W.; Lee, W. M.; Lellouch, J.; Li, L.; Li, Q. Z.; Lietti, S. M.; Lim, J. K.; Lincoln, D.; Linnemann, J.; Lipaev, V. V.; Lipton, R.; Liu, Y.; Liu, Z.; Lobodenko, A.; Lokajicek, M.; de Sa, R. Lopes; Lubatti, H. J.; Luna-Garcia, R.; Lyon, A. L.; Maciel, A. K. A.; Mackin, D.; Madar, R.; Magana-Villalba, R.; Malik, S.; Malyshev, V. L.; Maravin, Y.; Martinez-Ortega, J.; McCarthy, R.; McGivern, C. L.; Meijer, M. M.; et al.

    2011-11-17

    We present a model-independent measurement of t-channel electroweak production of single top quarks in p{bar p} collisions at {radical}s = 1.96 TeV. Using 5.4 fb{sup -1} of integrated luminosity collected by the D0 detector at the Fermilab Tevatron Collider, and selecting events containing an isolated electron or muon, missing transverse energy and one or two jets originating from the fragmentation of b quarks, we measure a cross section {sigma}(p{bar p} {yields} tqb + X) = 2.90 {+-} 0.59 (stat + syst) pb for a top quark mass of 172.5 GeV. The probability of the background to fluctuate and produce a signal as large as the one observed is 1.6 x 10{sup -8}, corresponding to a significance of 5.5 standard deviations.

  6. Search for a low mass Standard Model Higgs boson in the $\\tau-\\tau$ decay channel in $p\\bar{p}$ collisions at $\\sqrt{s}$ = 1.96 TeV

    SciTech Connect

    Aaltonen, T.; Alvarez Gonzalez, B.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Appel, J.A.; Apresyan, A.; Arisawa, T.; /Waseda U. /Dubna, JINR

    2012-01-01

    We report on a search for the standard model Higgs boson decaying into pairs of {tau} leptons in p{bar p} collisions produced by the Tevatron at {radical}s = 1.96 TeV. The analyzed data sample was recorded by the CDFII detector and corresponds to an integrated luminosity of 6.0 fb{sup -1}. The search is performed in the final state with one {tau} decaying leptonically and the second one identified through its semi-hadronic decay. Since no significant excess is observed, a 95% credibility level upper limit on the production cross section times branching ratio to the {tau}{tau} final state is set for hypothetical Higgs boson masses between 100 and 150 GeV/c{sup 2}. For a Higgs boson of 120 GeV/c{sup 2} the observed (expected) limit is 14.6 (15.3) the predicted value.

  7. Centrality Dependence of the Charged-Particle Multiplicity Density at Midrapidity in Pb-Pb Collisions at √{sN N }=5.02 TeV

    NASA Astrophysics Data System (ADS)

    Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Benacek, P.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botta, E.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa Del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; de, S.; de Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; de Falco, A.; de Gruttola, D.; De Marco, N.; de Pasquale, S.; Deisting, A.; Deloff, A.; Dénes, E.; Deplano, C.; Dhankher, P.; di Bari, D.; di Mauro, A.; di Nezza, P.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Horak, D.; Hosokawa, R.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Incani, E.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Mohisin Khan, M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kostarakis, P.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; León Vargas, H.; Leoncino, M.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martin Blanco, J.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; McDonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Moreira de Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pal, S. K.; Pan, J.; Pandey, A. K.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Pereira da Costa, H.; Peresunko, D.; Pérez Lara, C. E.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Šándor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarma, P.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; de Souza, R. D.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stankus, P.; Stefanek, G.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tangaro, M. A.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Valencia Palomo, L.; Vallero, S.; van der Maarel, J.; van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yang, H.; Yang, P.; Yano, S.; Yasar, C.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.; Alice Collaboration

    2016-06-01

    The pseudorapidity density of charged particles, d Nch/d η , at midrapidity in Pb-Pb collisions has been measured at a center-of-mass energy per nucleon pair of √{sN N}=5.02 TeV . For the 5% most central collisions, we measure a value of 1943 ±54 . The rise in d Nch/d η as a function of √{sN N} is steeper than that observed in proton-proton collisions and follows the trend established by measurements at lower energy. The increase of d Nch/d η as a function of the average number of participant nucleons, ⟨Npart⟩ , calculated in a Glauber model, is compared with the previous measurement at √{sN N}=2.76 TeV . A constant factor of about 1.2 describes the increase in d Nch/d η from √{sN N}=2.76 to 5.02 TeV for all centrality classes, within the measured range of 0%-80% centrality. The results are also compared to models based on different mechanisms for particle production in nuclear collisions.

  8. The Use of Bayesian Latent Class Cluster Models to Classify Patterns of Cognitive Performance in Healthy Ageing

    PubMed Central

    Cunha, Pedro; Palha, Joana Almeida; Sousa, Nuno

    2013-01-01

    The main focus of this study is to illustrate the applicability of latent class analysis in the assessment of cognitive performance profiles during ageing. Principal component analysis (PCA) was used to detect main cognitive dimensions (based on the neurocognitive test variables) and Bayesian latent class analysis (LCA) models (without constraints) were used to explore patterns of cognitive performance among community-dwelling older individuals. Gender, age and number of school years were explored as variables. Three cognitive dimensions were identified: general cognition (MMSE), memory (MEM) and executive (EXEC) function. Based on these, three latent classes of cognitive performance profiles (LC1 to LC3) were identified among the older adults. These classes corresponded to stronger to weaker performance patterns (LC1>LC2>LC3) across all dimensions; each latent class denoted the same hierarchy in the proportion of males, age and number of school years. Bayesian LCA provided a powerful tool to explore cognitive typologies among healthy cognitive agers. PMID:23977183

  9. Reply to ``Comment on `Linking population-level models with growing networks: A class of epidemic models' ''

    NASA Astrophysics Data System (ADS)

    Breban, Romulus; Vardavas, Raffaele; Blower, Sally

    2006-07-01

    We disagree with Bootsma and Diekmann that our formula for the basic reproduction ratio (R0) has an underlying conceptual mistake. In Phys. Rev. E 72, 046110 (2005), we propose a large class of growing networks (which we call Kinetic Monte Carlo (KMC) growing networks) as individual-level models for the transmission of infectious diseases. KMC growing networks are conceptually different from the well-established Crump-Mode-Jagers continuous-time branching processes. Thus, the branching process definition of R0 is not valid for KMC growing networks, and a different implementation of the biological definition of R0 is necessary.

  10. Online to offline teaching model in optics education: resource sharing course and flipped class

    NASA Astrophysics Data System (ADS)

    Li, Xiaotong; Cen, Zhaofeng; Liu, Xiangdong; Zheng, Zhenrong

    2016-09-01

    Since the platform "Coursera" is created by the professors of Stanford University Andrew Ng and Daphne Koller, more and more universities have joined in it. From the very beginning, online education is not only about education itself, but also connected with social equality. This is especially significant for the economic transformation in China. In this paper the research and practice on informatization of optical education are described. Online to offline (O2O) education activities, such as online learning and offline meeting, online homework and online to offline discussion, online tests and online to offline evaluation, are combined into our teaching model in the course of Applied Optics. These various O2O strategies were implemented respectively in the autumn-winter small class and the spring-summer middle class according to the constructivism and the idea of open education. We have developed optical education resources such as videos of lectures, light transmission or ray trace animations, online tests, etc. We also divide the learning procedure into 4 steps: First, instead of being given a course offline, students will learn the course online; Second, once a week or two weeks, students will have a discussion in their study groups; Third, students will submit their homework and study reports; Fourth, they will do online and offline tests. The online optical education resources have been shared in some universities in China, together with new challenges to teachers and students when facing the revolution in the e-learning future.

  11. Stochastic volatility models at ρ=±1 as second class constrained Hamiltonian systems

    NASA Astrophysics Data System (ADS)

    Contreras G., Mauricio

    2014-07-01

    The stochastic volatility models used in the financial world are characterized, in the continuous-time case, by a set of two coupled stochastic differential equations for the underlying asset price S and volatility σ. In addition, the correlations of the two Brownian movements that drive the stochastic dynamics are measured by the correlation parameter ρ (-1≤ρ≤1). This stochastic system is equivalent to the Fokker-Planck equation for the transition probability density of the random variables S and σ. Solutions for the transition probability density of the Heston stochastic volatility model (Heston, 1993) were explored in Dragulescu and Yakovenko (2002), where the fundamental quantities such as the transition density itself, depend on ρ in such a manner that these are divergent for the extreme limit ρ=±1. The same divergent behavior appears in Hagan et al. (2002), where the probability density of the SABR model was analyzed. In an option pricing context, the propagator of the bi-dimensional Black-Scholes equation was obtained in Lemmens et al. (2008) in terms of the path integrals, and in this case, the propagator diverges again for the extreme values ρ=±1. This paper shows that these similar divergent behaviors are due to a universal property of the stochastic volatility models in the continuum: all of them are second class constrained systems for the most extreme correlated limit ρ=±1. In this way, the stochastic dynamics of the ρ=±1 cases are different of the -1<ρ<1 case, and it cannot be obtained as a continuous limit from the ρ≠±1 regimen. This conclusion is achieved by considering the Fokker-Planck equation or the bi-dimensional Black-Scholes equation as a Euclidean quantum Schrödinger equation. Then, the analysis of the underlying classical mechanics of the quantum model, implies that stochastic volatility models at ρ=±1 correspond to a constrained system. To study the dynamics in an appropriate form, Dirac's method for constrained

  12. Estimating the Prevalence of Atrial Fibrillation from A Three-Class Mixture Model for Repeated Diagnoses

    PubMed Central

    Li, Liang; Mao, Huzhang; Ishwaran, Hemant; Rajeswaran, Jeevanantham; Ehrlinger, John; Blackstone, Eugene H.

    2016-01-01

    Atrial fibrillation (AF) is an abnormal heart rhythm characterized by rapid and irregular heart beat, with or without perceivable symptoms. In clinical practice, the electrocardiogram (ECG) is often used for diagnosis of AF. Since the AF often arrives as recurrent episodes of varying frequency and duration and only the episodes that occur at the time of ECG can be detected, the AF is often underdiagnosed when a limited number of repeated ECGs are used. In studies evaluating the efficacy of AF ablation surgery, each patient undergo multiple ECGs and the AF status at the time of ECG is recorded. The objective of this paper is to estimate the marginal proportions of patients with or without AF in a population, which are important measures of the efficacy of the treatment. The underdiagnosis problem is addressed by a three-class mixture regression model in which a patient’s probability of having no AF, paroxysmal AF, and permanent AF is modeled by auxiliary baseline covariates in a nested logistic regression. A binomial regression model is specified conditional on a subject being in the paroxysmal AF group. The model parameters are estimated by the EM algorithm. These parameters are themselves nuisance parameters for the purpose of this research, but the estimators of the marginal proportions of interest can be expressed as functions of the data and these nuisance parameters and their variances can be estimated by the sandwich method. We examine the performance of the proposed methodology in simulations and two real data applications. PMID:27983754

  13. Class Size and Student Performance at a Public Research University: A Cross-Classified Model

    ERIC Educational Resources Information Center

    Johnson, Iryna Y.

    2010-01-01

    This study addresses several methodological problems that have confronted prior research on the effect of class size on student achievement. Unlike previous studies, this analysis accounts for the hierarchical data structure of student achievement, where grades are nested within classes and students, and considers a wide range of class sizes…

  14. Development of class model based on blood biochemical parameters as a diagnostic tool of PSE meat.

    PubMed

    Qu, Daofeng; Zhou, Xu; Yang, Feng; Tian, Shiyi; Zhang, Xiaojun; Ma, Lin; Han, Jianzhong

    2017-06-01

    A fast, sensitive and effective method based on the blood biochemical parameters for the detection of PSE meat was developed in this study. A total of 200 pigs were slaughtered in the same slaughterhouse. Meat quality was evaluated by measuring pH, electrical conductivity and color at 45min, 2h and 24h after slaughtering in M. longissimus thoracis et lumborum (LD). Blood biochemical parameters were determined in blood samples collected during carcass bleeding. Principal component analysis (PCA) biplot showed that high levels of exsanguination Creatine Kinase, Lactate Dehydrogenase, Aspertate aminotransferase, blood glucose and lactate were associated with the PSE meat, and the five biochemical parameters were found to be good indicators of PSE meat Discriminant function analysis (DFA) was able to clearly identify PSE meat using the five biochemical parameters as input data, and the class model is an effective diagnostic tool in pigs which can be used to detect the PSE meat and reduce economic loss for the company.

  15. Toward a Network Model of MHC Class II-Restricted Antigen Processing

    PubMed Central

    Miller, Michael A.; Ganesan, Asha Purnima V.; Eisenlohr, Laurence C.

    2013-01-01

    The standard model of Major Histocompatibility Complex class II (MHCII)-restricted antigen processing depicts a straightforward, linear pathway: internalized antigens are converted into peptides that load in a chaperone dependent manner onto nascent MHCII in the late endosome, the complexes subsequently trafficking to the cell surface for recognition by CD4+ T cells (TCD4+). Several variations on this theme, both moderate and radical, have come to light but these alternatives have remained peripheral, the conventional pathway generally presumed to be the primary driver of TCD4+ responses. Here we continue to press for the conceptual repositioning of these alternatives toward the center while proposing that MHCII processing be thought of less in terms of discrete pathways and more in terms of a network whose major and minor conduits are variable depending upon many factors, including the epitope, the nature of the antigen, the source of the antigen, and the identity of the antigen-presenting cell. PMID:24379819

  16. A class of LQC-inspired models for homogeneous, anisotropic cosmology in higher dimensional early universe

    NASA Astrophysics Data System (ADS)

    Rama, S. Kalyana

    2016-12-01

    The dynamics of a (3 + 1) dimensional homogeneous anisotropic universe is modified by loop quantum cosmology and, consequently, it has generically a big bounce in the past instead of a big-bang singularity. This modified dynamics can be well described by effective equations of motion. We generalise these effective equations of motion empirically to (d + 1) dimensions. The generalised equations involve two functions and may be considered as a class of LQC-inspired models for (d + 1) dimensional early universe cosmology. As a special case, one can now obtain a universe which has neither a big bang singularity nor a big bounce but approaches asymptotically a `Hagedorn like' phase in the past where its density and volume remain constant. In a few special cases, we also obtain explicit solutions.

  17. Physicians' perception of demand-induced supply in the information age: a latent class model analysis.

    PubMed

    Shih, Ya-Chen Tina; Tai-Seale, Ming

    2012-03-01

    This paper introduces a concept called 'demand-induced supply' that reflects the excess supply of services due to an increase in demand initiated by patients. We examine its association with the proportion of information-savvy patients in physicians' practice. Using data from a national representative physician survey, we apply latent class models to analyze this association. Our analyses categorize physicians into three 'types' according to the frequency with which they provided additional medical services at their patients' requests: frequent, occasional, and rare. The proportion of information-savvy patients is significantly and positively correlated with demand-induced supply for the frequent or occasional type, but not among physicians in the rare type. Efforts to contain healthcare costs through utilization control need to recognize the pattern of responses from physicians who treat an increasing number of information-savvy patients.

  18. MODELING THE RESOLVED DISK AROUND THE CLASS 0 PROTOSTAR L1527

    SciTech Connect

    Tobin, John J.; Hartmann, Lee; Calvet, Nuria; Chiang, Hsin-Fang; Looney, Leslie W.; Wilner, David J.; Loinard, Laurent; D'Alessio, Paola

    2013-07-01

    We present high-resolution sub/millimeter interferometric imaging of the Class 0 protostar L1527 IRS (IRAS 04368+2557) at {lambda} = 870 {mu}m and 3.4 mm from the Submillimeter Array and Combined Array for Research in Millimeter Astronomy. We detect the signature of an edge-on disk surrounding the protostar with an observed diameter of 180 AU in the sub/millimeter images. The mass of the disk is estimated to be 0.007 M{sub Sun }, assuming optically thin, isothermal dust emission. The millimeter spectral index is observed to be quite shallow at all the spatial scales probed: {alpha} {approx} 2, implying a dust opacity spectral index {beta} {approx} 0. We model the emission from the disk and surrounding envelope using Monte Carlo radiative transfer codes, simultaneously fitting the sub/millimeter visibility amplitudes, sub/millimeter images, resolved L' image, spectral energy distribution, and mid-infrared spectrum. The best-fitting model has a disk radius of R = 125 AU, is highly flared (H{proportional_to}R {sup 1.3}), has a radial density profile {rho}{proportional_to}R {sup -2.5}, and has a mass of 0.0075 M{sub Sun }. The scale height at 100 AU is 48 AU, about a factor of two greater than vertical hydrostatic equilibrium. The resolved millimeter observations indicate that disks may grow rapidly throughout the Class 0 phase. The mass and radius of the young disk around L1527 are comparable to disks around pre-main-sequence stars; however, the disk is considerably more vertically extended, possibly due to a combination of lower protostellar mass, infall onto the disk upper layers, and little settling of {approx}1 {mu}m-sized dust grains.

  19. Mixed finite element - discontinuous finite volume element discretization of a general class of multicontinuum models

    NASA Astrophysics Data System (ADS)

    Ruiz-Baier, Ricardo; Lunati, Ivan

    2016-10-01

    We present a novel discretization scheme tailored to a class of multiphase models that regard the physical system as consisting of multiple interacting continua. In the framework of mixture theory, we consider a general mathematical model that entails solving a system of mass and momentum equations for both the mixture and one of the phases. The model results in a strongly coupled and nonlinear system of partial differential equations that are written in terms of phase and mixture (barycentric) velocities, phase pressure, and saturation. We construct an accurate, robust and reliable hybrid method that combines a mixed finite element discretization of the momentum equations with a primal discontinuous finite volume-element discretization of the mass (or transport) equations. The scheme is devised for unstructured meshes and relies on mixed Brezzi-Douglas-Marini approximations of phase and total velocities, on piecewise constant elements for the approximation of phase or total pressures, as well as on a primal formulation that employs discontinuous finite volume elements defined on a dual diamond mesh to approximate scalar fields of interest (such as volume fraction, total density, saturation, etc.). As the discretization scheme is derived for a general formulation of multicontinuum physical systems, it can be readily applied to a large class of simplified multiphase models; on the other, the approach can be seen as a generalization of these models that are commonly encountered in the literature and employed when the latter are not sufficiently accurate. An extensive set of numerical test cases involving two- and three-dimensional porous media are presented to demonstrate the accuracy of the method (displaying an optimal convergence rate), the physics-preserving properties of the mixed-primal scheme, as well as the robustness of the method (which is successfully used to simulate diverse physical phenomena such as density fingering, Terzaghi's consolidation

  20. Improved Transgenic Mouse Model for Studying HLA Class I Antigen Presentation

    PubMed Central

    Huang, Man; Zhang, Wei; Guo, Jie; Wei, Xundong; Phiwpan, Krung; Zhang, Jianhua; Zhou, Xuyu

    2016-01-01

    HLA class I (HLA-I) transgenic mice have proven to be useful models for studying human MHC-related immune responses over the last two decades. However, differences in the processing and presentation machinery between humans and mice may have profound effects on HLA-I restricted antigen presentation. In this study, we generated a novel human TAP-LMP (hTAP-LMP) gene cluster transgenic mouse model carrying an intact human TAP complex and two human immunoproteasome LMP subunits, PSMB8/PSMB9. By crossing the hTAP-LMP strain with different HLA-I transgenic mice, we found that the expression levels of human HLA-I molecules, especially the A3 supertype members (e.g., A11 and A33), were remarkably enhanced in corresponding HLA-I/hTAP-LMP transgenic mice. Moreover, we found that humanized processing and presentation machinery increased antigen presentation of HLA-A11-restricted epitopes and promoted the rapid reduction of hepatitis B virus (HBV) infection in HLA-A11/hTAP-LMP mice. Together, our study highlights that HLA-I/hTAP-LMP mice are an improved model for studying antigen presentation of HLA-I molecules and their related CTL responses. PMID:27634283

  1. One Class of Nonlinear Model Solutions for Flight Vehicles and Applications to Targeting and Guidance Schemes

    NASA Astrophysics Data System (ADS)

    Azimov, D.; Bishop, R.

    2012-09-01

    A complete analytical integration of the kinematic and dynamic equations of motion and applications of their integrals to targeting and guidance schemes for various dynamical models of various flight vehicles are presented. The general integral of these equations consists of six independent first integrals of motion and describes a class of non-steady flight trajectories in a maneuver plane. These first integrals represent explicit relationships for time, components of position and velocity vectors, and propulsive and aerodynamic accelerations. This explicitness with respect to the problem parameters can make these relationships useful in the design of airspace trajectories, and targeting and guidance schemes. It is also shown that the equations represent a 3rd-order vector differential equation used to develop the nonlinear maneuver model of a flight vehicle, and the state estimation and prediction schemes. Similarity in the dynamical models makes the first integrals valid for re-entry vehicles and missiles. An illustrative example has shown that the general integral provides a complete set of analytical solutions for nonlinear tracking, targeting, guidance and control problems with a wide range of terminal conditions, accelerations due to propulsive thrust and aerodynamic forces.

  2. MPSLIB: A C++ class for sequential simulation of multiple-point statistical models

    NASA Astrophysics Data System (ADS)

    Hansen, Thomas Mejer; Vu, Le Thanh; Bach, Torben

    Geostatistical simulation methods allow simulation of spatial structures and patterns based on a choice of statistical model. In the last few decades multiple-point statistics (MPS) has been developed that allows inferring the statistical model from a training image. This allows for a simpler quantification of the statistical model, and simulation of more realistic (Earth) structures. A number of different algorithms for MPS based simulation have been proposed, each associated with a unique set of pros or cons. MPSLIB is a C++ class that provides a framework for implementing most of the currently proposed multiple-point simulation methods based on sequential simulation. A number of the most widely used methods are provided as an example. The single normal equation simulation (SNESIM) method is implemented using both a tree and a list structure. A new generalized ENESIM (GENESIM) algorithm is proposed that can act as (in one extreme) the ENESIM algorithm, and (in another extreme) similar to the direct sampling algorithm. MPSLIB aims to be easy to compile on most platforms (standard C++11 is the only requirement) and is released under the Open Source LGPLv3 License to encourage reuse and further development.

  3. Investigating attribute non-attendance and its consequences in choice experiments with latent class models.

    PubMed

    Lagarde, Mylene

    2013-05-01

    A growing literature, mainly from transport and environment economics, has started to explore whether respondents violate some of the axioms about individuals' preferences in Discrete Choice Experiments (DCEs) and use simple strategies to make their choices. One of these strategies, termed attribute non-attendance (ANA), consists in ignoring one or more attributes. Using data from a DCE administered to healthcare providers in Ghana to evaluate their potential resistance to changes in clinical guidelines, this study illustrates how latent class models can be used in a step-wise approach to account for all possible ANA strategies used by respondents and explore the consequences of such behaviours. Results show that less than 3% of respondents considered all attributes when choosing between the two hypothetical scenarios proposed, with a majority looking at only one or two attributes. Accounting for ANA strategies improved the goodness-of-fit of the model and affected the magnitude of some of the coefficient and willingness-to-pay estimates. However, there was no difference in the predicted probabilities of the model taking into account ANA and the standard approach. Although the latter result is reassuring about the ability of DCEs to produce unbiased policy guidance, it should be confirmed by other studies.

  4. Universality class of the critical point in the restricted primitive model of ionic systems.

    PubMed

    Ciach, A

    2006-06-01

    A coarse-grained description of the restricted primitive model is considered in terms of the local charge- and number-density fields. Exact reduction to a one-field theory is derived, and exact expressions for the number-density correlation functions in terms of higher-order correlation functions for the charge-density are given. It is shown that in continuum space the singularity of the charge-density correlation function associated with short-wavelength charge-ordering disappears when charge-density fluctuations are included by following the Brazovskii approach. The related singularity of the individual Feynman diagrams contributing to the number-density correlation functions is cured when all the diagrams are segregated into disjoint sets according to their topological structure. By performing a resummation of all diagrams belonging to each set a regular expression represented by a secondary diagram is obtained. The secondary diagrams are again segregated into disjoint sets, and the series of all the secondary diagrams belonging to a given set is represented by a hyperdiagram. A one-to-one correspondence between the hyperdiagrams contributing to the number-density vertex functions, and diagrams contributing to the order-parameter vertex functions in a certain model system belonging to the Ising universality class is demonstrated. Corrections to scaling associated with irrelevant operators that are present in the model-system Hamiltonian, and other corrections specific to the RPM are also discussed.

  5. Reflections on implementing several models of teaching in a high school biology class

    NASA Astrophysics Data System (ADS)

    Baldwin, Michael E.

    This research investigates the challenges faced in enacting instructional models that previous research has found to foster student learning. In order to complete this study, the researcher documented, through a strategy of reflective practice, his return to teaching high school science after having served for a time as a science specialist and instructional coach. The study develops quality personal insights and questions that may be used by other educators and researchers to investigate the enactment of these different models and strategies. The research is limited to the spring of the 2010 school year and use notes, journals, and planner documents from the 2008--2009 school year. In order to appreciate complex interactions, triangulation was made through dovetailing personal observations with requested observations of the campus assistant principal, the district science specialist, and an out of district observer. Also, a short questionnaire administered to the students in these classes. Throughout this study, the researcher demonstrates that it is feasible to use these models. However, such external factors as imposed curriculum and standardized testing play a large role in everyday decision making of this particular teacher. The sheer amount of content to be covered under the Texas Essential Knowledge and Skills (TEKS) also influenced instructional decisions that were made. Choices about what strategy to use resided mainly within the teacher/researcher and were governed and affected mostly by his interactions with students and professional judgments about what would both bolster student understanding and help students score well on the Texas Assessment of Knowledge and Skills (TAKS).

  6. Two classes of alamethicin transmembrane channels: molecular models from single-channel properties.

    PubMed

    Mak, D O; Webb, W W

    1995-12-01

    Molecular structures of transmembrane channels formed by alamethicin polypeptide aggregates were analyzed by measuring open-channel conductances and state-transition kinetics using voltage-clamp technique with artificial phospholipid bilayers isolated onto micropipettes by a novel solvent-free tip-dip method. Two distinct classes of alamethicin channels, each with a unique set of conductance states and kinetic properties, were identified. Alamethicin Rf50 at low temperatures forms mostly nonpersistent channels with lifetimes of < 1 min. Long-lasting persistent channels are formed by alamethicin Rf30 at all temperatures and by alamethicin Rf50 at room temperature. In the "modified barrel-stave" model for persistent channels based on the crystalline alamethicin secondary structure, the aqueous pore of the channel surrounded by parallel alamethicin monomers has a constriction generated by amino acid side chains protruding from the alamethicin helices into the pore. The model explains quantitatively the nonohmic channel conductance at high applied voltages and the conductance values and ion selectivities of various persistent channel states. The kinetic properties of nonpersistent channels are explained qualitatively by the "reversed-molecule" model in which nonpersistent channels differ from persistent channels by having one of the channel-forming alamethicin monomers oriented antiparallel to the others.

  7. Two classes of alamethicin transmembrane channels: molecular models from single-channel properties.

    PubMed Central

    Mak, D O; Webb, W W

    1995-01-01

    Molecular structures of transmembrane channels formed by alamethicin polypeptide aggregates were analyzed by measuring open-channel conductances and state-transition kinetics using voltage-clamp technique with artificial phospholipid bilayers isolated onto micropipettes by a novel solvent-free tip-dip method. Two distinct classes of alamethicin channels, each with a unique set of conductance states and kinetic properties, were identified. Alamethicin Rf50 at low temperatures forms mostly nonpersistent channels with lifetimes of < 1 min. Long-lasting persistent channels are formed by alamethicin Rf30 at all temperatures and by alamethicin Rf50 at room temperature. In the "modified barrel-stave" model for persistent channels based on the crystalline alamethicin secondary structure, the aqueous pore of the channel surrounded by parallel alamethicin monomers has a constriction generated by amino acid side chains protruding from the alamethicin helices into the pore. The model explains quantitatively the nonohmic channel conductance at high applied voltages and the conductance values and ion selectivities of various persistent channel states. The kinetic properties of nonpersistent channels are explained qualitatively by the "reversed-molecule" model in which nonpersistent channels differ from persistent channels by having one of the channel-forming alamethicin monomers oriented antiparallel to the others. PMID:8599639

  8. Mixture Item Response Theory-MIMIC Model: Simultaneous Estimation of Differential Item Functioning for Manifest Groups and Latent Classes

    ERIC Educational Resources Information Center

    Bilir, Mustafa Kuzey

    2009-01-01

    This study uses a new psychometric model (mixture item response theory-MIMIC model) that simultaneously estimates differential item functioning (DIF) across manifest groups and latent classes. Current DIF detection methods investigate DIF from only one side, either across manifest groups (e.g., gender, ethnicity, etc.), or across latent classes…

  9. Race/Ethnicity and Social Capital among Middle- and Upper-Middle-Class Elementary School Families: A Structural Equation Model

    ERIC Educational Resources Information Center

    Caldas, Stephen J.; Cornigans, Linda

    2015-01-01

    This study used structural equation modeling to conduct a first and second order confirmatory factor analysis (CFA) of a scale developed by McDonald and Moberg (2002) to measure three dimensions of social capital among a diverse group of middle- and upper-middle-class elementary school parents in suburban New York. A structural path model was…

  10. Absence of neurological deficits following extensive demyelination in a class I-deficient murine model of multiple sclerosis

    PubMed Central

    Schmelzer, James D.; Hunter, Samuel F.; Low, Phillip A.; Rodriguez, Moses

    2017-01-01

    Demyelination alone has been considered sufficient for development of neurological deficits following central nervous system (CNS) disease. However, extensive demyelination is not always associated with clinical deficits in patients with multiple sclerosis (MS), the most common primary demyelinating disease in humans. We used the Theiler’s murine encephalomyelitis virus model of demyelination to investigate the role of major histocompatibility complex (MHC) class I and class II gene products in the development of functional and neurophysiological deficits following demyelination. We measured spontaneous clinical activity by two independent assays and recorded hind-limb motor-evoked potentials in infected class I-deficient and class II-deficient mice of an identical genetic background as well as in highly susceptible SJL/J mice. The results show that despite a similar distribution and extent of demyelinated lesions in all mice, only class I-deficient mice were functionally normal. We propose that the mechanism by which demyelinated class I-deficient mice maintain neurologic function results from increased sodium channel densities and the relative preservation of axons. These findings are the first to implicate a role for MHC class I in the development of neurological deficits following demyelination. PMID:9461192

  11. Combining local wavelength information and ensemble learning to enhance the specificity of class modeling techniques: Identification of food geographical origins and adulteration.

    PubMed

    Xu, Lu; Ye, Zi-Hong; Yan, Si-Min; Shi, Peng-Tao; Cui, Hai-Feng; Fu, Xian-Shu; Yu, Xiao-Ping

    2012-11-19

    Class modeling techniques are required to tackle various one-class problems. Because the training of class models is based on the target class and the origins of future test objects usually cannot be exactly predefined, the criteria for feature selection of class models are not very straightforward. Although feature reduction can be expected to improve class models performance, more features retained can provide a sufficient description of the sought-for class. This paper suggests a strategy to balance class description and model specificity by ensemble learning of sub-models based on separate local wavelength intervals. The acceptance or rejection of a future object can be explicitly determined by examining its acceptance frequency by sub-models. Considering the lack of information about sub-model independence, we propose to use a data-driven method to control the sensitivity of the ensemble model by cross validation. In this way, all the wavelength intervals are used for class description and the local wavelength intervals are highlighted to enhance the ability to detect out-of-class objects. The proposed strategy was performed on one-class partial least squares (OCPLS) and soft independent modeling of class analogy (SIMCA). By analysis of two infrared spectral data sets, one for geographical origin identification of white tea and the other for discrimination of adulterations in pure sesame oil, the proposed ensemble class modeling method was demonstrated to have similar sensitivity and better specificity compared with total-spectrum SIMCA and OCPLS models. The results indicate local spectral information can be extracted to enhance class model specificity.

  12. Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland.

    PubMed

    Li, Tingting; Raivonen, Maarit; Alekseychik, Pavel; Aurela, Mika; Lohila, Annalea; Zheng, Xunhua; Zhang, Qing; Wang, Guocheng; Mammarella, Ivan; Rinne, Janne; Yu, Lijun; Xie, Baohua; Vesala, Timo; Zhang, Wen

    2016-12-01

    Boreal/arctic wetlands are dominated by diverse plant species, which vary in their contribution to CH4 production, oxidation and transport processes. Earlier studies have often lumped the processes all together, which may induce large uncertainties into the results. We present a novel model, which includes three vegetation classes and can be used to simulate CH4 emissions from boreal and arctic treeless wetlands. The model is based on an earlier biogeophysical model, CH4MODwetland. We grouped the vegetation as graminoids, shrubs and Sphagnum and recalibrated the vegetation parameters according to their different CH4 production, oxidation and transport capacities. Then, we used eddy-covariance-based CH4 flux observations from a boreal (Siikaneva) and a subarctic fen (Lompolojänkkä) in Finland to validate the model. The results showed that the recalibrated model could generally simulate the seasonal patterns of the Finnish wetlands with different plant communities. The comparison between the simulated and measured daily CH4 fluxes resulted in a correlation coefficient (R(2)) of 0.82 with a slope of 1.0 and an intercept of -0.1mgm(-2)h(-1) for the Siikaneva site (n=2249, p<0.001) and an R(2) of 0.82 with a slope of 1.0 and an intercept of 0.0mgm(-2)h(-1) for the Lompolojänkkä site (n=1826, p<0.001). Compared with the original model, the recalibrated model in this study significantly improved the model efficiency (EF), from -5.5 to 0.8 at the Siikaneva site and from -0.4 to 0.8 at the Lompolojänkkä site. The simulated annual CH4 emissions ranged from 7 to 24gm(-2)yr(-1), which was consistent with the observations (7-22gm(-2)yr(-1)). However, there are some discrepancies between the simulated and observed daily CH4 fluxes for the Siikaneva site (RMSE=50.0%) and the Lompolojänkkä site (RMSE=47.9%). Model sensitivity analysis showed that increasing the proportion of the graminoids would significantly increase the CH4 emission levels. Our study demonstrated that

  13. Direct photon production in Pb-Pb collisions at √{sNN} = 2.76 TeV

    NASA Astrophysics Data System (ADS)

    Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anielski, J.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Awes, T. C.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botta, E.; Böttger, S.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deisting, A.; Deloff, A.; Dénes, E.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Heide, M.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Hosokawa, R.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jung, H.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Mohisin Khan, M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobayashi, T.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; León Vargas, H.; Leoncino, M.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martin Blanco, J.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pal, S. K.; Pan, J.; Pandey, A. K.; Papcun, P.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Peitzmann, T.; Pereira Da Costa, H.; Pereira De Oliveira Filho, E.; Peresunko, D.; Pérez Lara, C. E.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Šándor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stefanek, G.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tangaro, M. A.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Valencia Palomo, L.; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yang, H.; Yang, P.; Yano, S.; Yasar, C.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.

    2016-03-01

    Direct photon production at mid-rapidity in Pb-Pb collisions at √{sNN} = 2.76 TeV was studied in the transverse momentum range 0.9 classes. For all three classes, agreement was found with perturbative QCD calculations for pT ≳ 5 GeV / c. Direct photon spectra down to pT ≈ 1 GeV / c could be extracted for the 20-40% and 0-20% centrality classes. The significance of the direct photon signal for 0.9 class. The spectrum in this pT range and centrality class can be described by an exponential with an inverse slope parameter of (297 ±12stat ±41syst) MeV. State-of-the-art models for photon production in heavy-ion collisions agree with the data within uncertainties.

  14. Anisotropy of TeV Galactic cosmic rays

    NASA Astrophysics Data System (ADS)

    Zhang, Ming; Pogorelov, Nikolai; Desiati, Paolo; DuVernois, Michael

    2016-07-01

    TeV cosmic rays are significantly deflected by the magnetic field of the heliosphere, and they gain or lose energies in heliospheric electric field that in the meantime drives the motion of plasma. These propagation mechanisms will cause the map of TeV cosmic rays seen at the Earth to look different from the map seen in the local interstellar medium without the presence of the heliosphere. We have developed a method of using Liouville's theorem to map out particle distribution function to Earth from the local interstellar medium, where we assume that the cosmic rays have small pitch-angle anisotropy harmonics up to the second order and a small uniform spatial density gradient. The amount of heliospheric distortion can be determined by tracing the trajectories of cosmic rays propagating through the heliosphere. In this paper, we apply this method to TeV cosmic ray propagation through a MHD-kinetic model of the heliosphere and try to fit observations from Tibet ASgamma and IceCube experiments. We are able to locate features in the TeV cosmic ray anisotropy that are associated with the interstellar magnetic field, hydrogen deflection plane, heliotail, and solar corona. Some of the features are also slightly affected by the solar cycle and interstellar magnetic turbulence. The results provide us powerful tools to explore large-scale heliospheric structures as well as to determine the cosmic ray distribution in the local interstellar medium.

  15. STARD-BLCM: Standards for the Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models.

    PubMed

    Kostoulas, Polychronis; Nielsen, Søren S; Branscum, Adam J; Johnson, Wesley O; Dendukuri, Nandini; Dhand, Navneet K; Toft, Nils; Gardner, Ian A

    2017-03-01

    The Standards for the Reporting of Diagnostic Accuracy (STARD) statement, which was recently updated to the STARD2015 statement, was developed to encourage complete and transparent reporting of test accuracy studies. Although STARD principles apply broadly, the checklist is limited to studies designed to evaluate the accuracy of tests when the disease status is determined from a perfect reference procedure or an imperfect one with known measures of test accuracy. However, a reference standard does not always exist, especially in the case of infectious diseases with a long latent period. In such cases, a valid alternative to classical test evaluation involves the use of latent class models that do not require a priori knowledge of disease status. Latent class models have been successfully implemented in a Bayesian framework for over 20 years. The objective of this work was to identify the STARD items that require modification and develop a modified version of STARD for studies that use Bayesian latent class analysis to estimate diagnostic test accuracy in the absence of a reference standard. Examples and elaborations for each of the modified items are provided. The new guidelines, termed STARD-BLCM (Standards for Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models), will facilitate improved quality of reporting on the design, conduct and results of diagnostic accuracy studies that use Bayesian latent class models.

  16. Transverse momentum dependence of D-meson production in Pb-Pb collisions at $$ \\sqrt{{\\mathrm{s}}_{\\mathrm{NN}}}=2.76 $$ TeV

    DOE PAGES

    Adam, J.; Adamová, D.; Aggarwal, M. M.; ...

    2016-03-14

    The production of prompt charmed mesons D0, D+ and D*+, and their antiparticles, was measured with the ALICE detector in Pb-Pb collisions at the centre-of-mass energy per nucleon pair, √sNN, of 2.76 TeV. The production yields for rapidity |y| < 0.5 are presented as a function of transverse momentum, pT, in the interval 1–36 GeV/c for the centrality class 0–10% and in the interval 1–16 GeV/c for the centrality class 30–50%. The nuclear modification factor RAA was computed using a proton-proton reference at √s = 2.76 TeV, based on measurements at √s = 7 TeV and on theoretical calculations. Amore » maximum suppression by a factor of 5-6 with respect to binary-scaled pp yields is observed for the most central collisions at pT of about 10 GeV/c. A suppression by a factor of about 2-3 persists at the highest pT covered by the measurements. At low pT (1-3 GeV/c), the RAA has large uncertainties that span the range 0.35 (factor of about 3 suppression) to 1 (no suppression). In all pT intervals, the RAA is larger in the 30-50% centrality class compared to central collisions. Furthermore, the D-meson RAA is also compared with that of charged pions and, at large pT, charged hadrons, and with model calculations.« less

  17. Transverse momentum dependence of D-meson production in Pb-Pb collisions at sqrt{{s}_{NN}}=2.76 TeV

    NASA Astrophysics Data System (ADS)

    Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anielski, J.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botta, E.; Böttger, S.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deisting, A.; Deloff, A.; Dénes, E.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Heide, M.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Hosokawa, R.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jung, H.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Mohisin Khan, M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobayashi, T.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; León Vargas, H.; Leoncino, M.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martin Blanco, J.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pal, S. K.; Pan, J.; Pandey, A. K.; Papcun, P.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Peitzmann, T.; Pereira Da Costa, H.; Pereira De Oliveira Filho, E.; Peresunko, D.; Pérez Lara, C. E.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Šándor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stefanek, G.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tangaro, M. A.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Valencia Palomo, L.; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yang, H.; Yang, P.; Yano, S.; Yasar, C.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.

    2016-03-01

    The production of prompt charmed mesons D0, D+ and D∗+, and their antiparticles, was measured with the ALICE detector in Pb-Pb collisions at the centre-of-mass energy per nucleon pair, sqrt{s_{NN}} , of 2 .76 TeV. The production yields for rapidity | y| < 0 .5 are presented as a function of transverse momentum, p T, in the interval 1-36 GeV /c for the centrality class 0-10% and in the interval 1-16 GeV /c for the centrality class 30-50%. The nuclear modification factor R AA was computed using a proton-proton reference at sqrt{s}=2.76 TeV, based on measurements at sqrt{s}=7 TeV and on theoretical calculations. A maximum suppression by a factor of 5-6 with respect to binary-scaled pp yields is observed for the most central collisions at p T of about 10 GeV /c. A suppression by a factor of about 2-3 persists at the highest p T covered by the measurements. At low p T (1-3 GeV /c), the R AA has large uncertainties that span the range 0.35 (factor of about 3 suppression) to 1 (no suppression). In all p T intervals, the R AA is larger in the 30-50% centrality class compared to central collisions. The D-meson R AA is also compared with that of charged pions and, at large p T, charged hadrons, and with model calculations. [Figure not available: see fulltext.

  18. Transverse momentum dependence of D-meson production in Pb-Pb collisions at $ \\sqrt{{\\mathrm{s}}_{\\mathrm{NN}}}=2.76 $ TeV

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I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pal, S. K.; Pan, J.; Pandey, A. K.; Papcun, P.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Peitzmann, T.; Pereira Da Costa, H.; Pereira De Oliveira Filho, E.; Peresunko, D.; Pérez Lara, C. E.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Revol, J. -P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Šándor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stefanek, G.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tangaro, M. A.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Valencia Palomo, L.; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yang, H.; Yang, P.; Yano, S.; Yasar, C.; Yin, Z.; Yokoyama, H.; Yoo, I. -K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.

    2016-03-14

    The production of prompt charmed mesons D0, D+ and D*+, and their antiparticles, was measured with the ALICE detector in Pb-Pb collisions at the centre-of-mass energy per nucleon pair, √sNN, of 2.76 TeV. The production yields for rapidity |y| < 0.5 are presented as a function of transverse momentum, pT, in the interval 1–36 GeV/c for the centrality class 0–10% and in the interval 1–16 GeV/c for the centrality class 30–50%. The nuclear modification factor RAA was computed using a proton-proton reference at √s = 2.76 TeV, based on measurements at √s = 7 TeV and on theoretical calculations. A maximum suppression by a factor of 5-6 with respect to binary-scaled pp yields is observed for the most central collisions at pT of about 10 GeV/c. A suppression by a factor of about 2-3 persists at the highest pT covered by the measurements. At low pT (1-3 GeV/c), the RAA has large uncertainties that span the range 0.35 (factor of about 3 suppression) to 1 (no suppression). In all pT intervals, the RAA is larger in the 30-50% centrality class compared to central collisions. Furthermore, the D-meson RAA is also compared with that of charged pions and, at large pT, charged hadrons, and with model calculations.

  19. Eating disorder behaviours amongst adolescents: investigating classification, persistence and prospective associations with adverse outcomes using latent class models.

    PubMed

    Micali, Nadia; Horton, N J; Crosby, R D; Swanson, S A; Sonneville, K R; Solmi, F; Calzo, J P; Eddy, K T; Field, A E

    2017-02-01

    Diagnostic criteria for eating disorders (ED) remain largely based on clinical presentations, but do not capture the full range of behaviours in the population. We aimed to derive an empirically based ED behaviour classification using behavioural and body mass index (BMI) indicators at three time-points in adolescence, and to validate classes investigating prospective associations with adverse outcomes. Adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC) provided data on ED at age 14 (n = 6615), 16 (n = 5888), and 18 years (n = 5100), and had weight and height measured. Psychological and behavioural outcomes were assessed at 15.5/16 and 17.5/18 years. We fit gender- and age-stratified latent class models, and employed logistic regression to investigate associations between classes and later outcomes. One asymptomatic and two symptomatic (largely representing higher and lower frequency ED behaviours) classes were observed at each time-point, although their relative prevalence varied by age and gender. The majority of girls in symptomatic classes remained symptomatic at subsequent assessments. Girls in symptomatic classes had higher odds of subsequent anxiety and depressive disorders, binge drinking, drug use, and deliberate self-harm. Data analyses were underpowered amongst boys. The presence of two symptomatic classes (characterised by different ED behaviour frequency) and their prospective association with adverse outcomes suggest a need to refine diagnostic thresholds based on empirical data. Despite some instability of classes, particularly in mid-adolescence, evidence that half of girls in symptomatic classes remained symptomatic suggests persistence of ED behaviours in adolescence, and highlights a need for early identification to reduce chronicity.

  20. Modeling and simulation of a class of liquid propellant engine pressurization systems

    NASA Astrophysics Data System (ADS)

    Karimi, H.; Nassirharand, Amir; Mohseni, M.

    2010-02-01

    In this paper, a new approach for modeling a class of pressurization systems for liquid propellant engines is presented. High pressure gas stored in special capsules is injected in a controlled way onto the gas volume on top of the propellant tanks. Instantaneous pressure and temperature values of propellant tanks and the capsules are computed. The computed constitutive values are compared with experimental results. The modeling approach accounts for variations of pressure and density of the pressurant inside the capsules and propellant tanks. It also accounts for heat transfer between pressurant and its surroundings. Equations for determination of the pressurant shut-down time are developed. Similarly, equations for determination of the propellant pump inlet pressure are also derived. The final governing equations are in terms of a set of differential equations that are numerically solved using the modified Euler method. The primary application of this research is to determine the pressurization system exit pressure. In case of turbo-pump feed systems, this work may be used to detect the occurrence of the cavitation phenomenon in the pumps. The method is limited to: (1) thermally insulated propellant tanks and (2) use of several storage capsules that are made of insulating composite material (i.e., exit mass flow rate is small, pressurant is stored at high pressure and low volume, temperature variations are small, and pressure drop in the capsules is not appreciable).

  1. Search for the Standard Model Higgs boson produced by vector-boson fusion and decaying to bottom quarks in √{s}=8 TeV pp collisions with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blanco, J. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.

    2016-11-01

    A search with the ATLAS detector is presented for the Standard Model Higgs boson produced by vector-boson fusion and decaying to a pair of bottom quarks, using 20.2 fb-1 of LHC proton-proton collision data at √{s}=8 TeV. The signal is searched for as a resonance in the invariant mass distribution of a pair of jets containing b-hadrons in vector-boson-fusion candidate events. The yield is measured to be -0.8 ± 2.3 times the Standard Model cross-section for a Higgs boson mass of 125 GeV. The upper limit on the cross-section times the branching ratio is found to be 4.4 times the Standard Model cross-section at the 95% confidence level, consistent with the expected limit value of 5.4 (5.7) in the background-only (Standard Model production) hypothesis. [Figure not available: see fulltext.

  2. Search for the Standard Model Higgs Boson in the Missing Transverse Energy and b-jet signature in proton-antiproton collisions at a center-of-mass energy of 1.96 TeV

    SciTech Connect

    Apresyan, Artur

    2009-05-01

    We report on the results of a search for the standard model Higgs boson produced in association with a W or Z boson in p$\\bar{p}$ collisions at √s = 1.96 TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb-1. We consider events having no identified charged leptons, a large imbalance in transverse momentum, and two or three jets where at least one jet contains a secondary vertex consistent with the decay of a b hadron. The main backgrounds are modeled with innovative techniques using data. The sensitivity of the search is optimized using multivariate discriminant techniques. We find good agreement between data and the standard model predictions. We place 95% confidence level upper limits on production cross section times branching ratio for several Higgs boson masses ranging from 110 GeV=c2 to 150 GeV=c2. For a mass of 115 GeV=c2 the observed (expected) limit is 6.9 (5.6) times the standard model prediction.

  3. Test of the Standard Model of electroweak interactions by measuring the anomalous W W gamma couplings at √s = 1.8-TeV

    SciTech Connect

    Kelly, Michael Lawrence

    1996-04-01

    An analysis of Wγ events found in 73.0 pb-1 collected with the D0 detector during Tevatron Run 1b is presented. Forty-six candidate events are observed with a predicted background of 13.2 events. The total cross section for p$\\bar{p}$ → Wγ + X (for pTγ > 10 GeV/c and ΔR > 0.7) times the branching ratio of W bosons to electrons is measured to be: σ(p$\\bar{p}$ → Wγ + X) x BR(W → ev) = 11.19$+2.66\\atop{-2.32}$ ± 0.61 (syst) ± 0.56 (lum) pb. 95% confidence level limits on the CP-conserving anomalous coupling parameters are set using a fit to the photon transverse energy spectrum of the events with a three-body transverse cluster mass greater than 90 GeV/c2. The results are: -1.4 < Δκ < 1.4 (λ = 0) and -0.5 < λ < 0.5 (Δκ = 0) with similar limits are set on the CP-violating coupling parameters $\\bar{κ}$ and $\\bar{λ}$. These limits were set by assuming a dipole form factor with a scale factor of {Lambda} = 1.5 TeV.

  4. Spectral properties of the Preisach hysteresis model with random input. II. Universality classes for symmetric elementary loops

    NASA Astrophysics Data System (ADS)

    Radons, Günter

    2008-06-01

    The Preisach model with symmetric elementary hysteresis loops and uncorrelated input is treated analytically in detail. It is shown that the appearance of long-time tails in the output correlations is a quite general feature of this model. The exponent η of the algebraic decay t-η , which may take any positive value, is determined by the tails of the input and the Preisach density. We identify the system classes leading to identical algebraic tails. These results imply the occurrence of 1/f noise for a large class of hysteretic systems.

  5. TEV-48125 for the preventive treatment of chronic migraine

    PubMed Central

    Dodick, David W.; Krymchantowski, Abouch V.; VanderPluym, Juliana H.; Tepper, Stewart J.; Aycardi, Ernesto; Loupe, Pippa S.; Ma, Yuju; Goadsby, Peter J.

    2016-01-01

    Objective: To evaluate the onset of efficacy of TEV-48125, a monoclonal antibody against calcitonin gene-related peptide, recently shown to be effective for the preventive treatment of chronic migraine (CM) and high-frequency episodic migraine. Methods: A randomized placebo-controlled study tested once-monthly injections of TEV-48125 675/225 mg or 900 mg vs placebo. Headache information was captured daily using an electronic headache diary. The primary endpoint was change from baseline in the number of headache hours in month 3. Herein, we assess the efficacy of each dose at earlier time points. Results: The sample consisted of 261 patients. For headache hours, the 675/225-mg dose separated from placebo on day 7 and the 900-mg dose separated from placebo after 3 days of therapy (p = 0.048 and p = 0.033, respectively). For both the 675/225-mg and 900-mg doses, the improvement was sustained through the second (p = 0.004 and p < 0.001) and third (p = 0.025 and p < 0.001) weeks of therapy and throughout the study (month 3, p = 0.0386 and p = 0.0057). For change in weekly headache days of at least moderate intensity, both doses were superior to placebo at week 2 (p = 0.031 and p = 0.005). Conclusions: TEV-48125 demonstrated a significant improvement within 1 week of therapy initiation in patients with CM. Classification of evidence: This study provides Class II evidence that for patients with CM, TEV-48125 significantly decreases the number of headache hours within 3 to 7 days of injection. PMID:27281531

  6. The Earth2Class Model for Professional Development to Implement the Next Generation Science Standards

    NASA Astrophysics Data System (ADS)

    Passow, M. J.; Assumpcao, C. M.; Baggio, F. D.; Hemming, S. R.; Goodwillie, A. M.; Brenner, C.

    2014-12-01

    Professional development for teachers involved in the implementation of the Next Generation Science Standards (NGSS) will require a multifaceted approach combining curriculum development, understanding the nature of science, applications of engineering and technology, integrating reading and writing, and other pedagogical components. The Earth2Class Workshops (E2C) at the Lamont-Doherty Earth Observatory of Columbia University (LDEO) provides one model for creating effective training to meet the NGSS challenges. E2C has provided more than 135 workshops since 1998 that have brought together LDEO research scientists with classroom teachers and students from the New York metropolitan area and elsewhere. Each session provides teachers with the chance to learn first-hand about the wide range of investigations conducted at LDEO. This approach aligns strongly with the NGSS goals: mastery of the disciplinary core ideas, science and engineering practices, understanding the nature of science, and cross-cutting relationships. During workshops, participating teachers interact with scientists to gain understanding of what stimulated research questions, how scientists put together all the components of investigations, and ways in which results are disseminated. Networking among teachers often leads to developing lesson plans based on the science, as well as support for professional growth not always possible within the school setting. Through the E2C website www.earth2class.org, teachers and students not able to attend the live workshops can access archival versions of the sessions. The website also provides a wide variety of educational resources. These have proved to be valuable on a national basis, as evidenced by an average of more than 300,000 hits per month from thousands of site visitors. Participating researchers have found E2C to be an effective approach to provide broader outreach of their results. During the next couple of years, the E2C program will expand to provide

  7. A novel human immunodeficiency virus type 1 protein, tev, shares sequences with tat, env, and rev proteins.

    PubMed Central

    Benko, D M; Schwartz, S; Pavlakis, G N; Felber, B K

    1990-01-01

    We have characterized a novel 28-kilodalton protein, p28tev, detected in human immunodeficiency virus type 1-infected cells. tev is recognized by both tat and rev monospecific antibodies. tev is initiated at the tat AUG and contains the first exon of tat at its amino terminus, a small portion of env in the middle, and the second exon of rev at its carboxy terminus. A cDNA clone producing tev was cloned and expressed in human cells. Sequence analysis revealed that the tev mRNA is generated by splicing to a novel exon located in the env region. This identifies a fourth class of multiply spliced human immunodeficiency virus mRNAs, produced in infected and transfected cells. tev is regulated during the virus life cycle similarly to the other regulatory proteins, tat, rev, and nef, and displays both tat and rev activities in functional assays. Since tev contains important functional domains of tat and rev and is produced very early after transfection, it may be an important regulator in the initial phase of virus expression. Another rev-related protein, p18(6)Drev, containing env and rev sequences, was characterized and was found not to have detectable rev activity. Images PMID:2186172

  8. Class of cooperative stochastic models: Exact and approximate solutions, simulations, and experiments using ionic self-assembly of nanoparticles.

    PubMed

    Mazilu, I; Mazilu, D A; Melkerson, R E; Hall-Mejia, E; Beck, G J; Nshimyumukiza, S; da Fonseca, Carlos M

    2016-03-01

    We present exact and approximate results for a class of cooperative sequential adsorption models using matrix theory, mean-field theory, and computer simulations. We validate our models with two customized experiments using ionically self-assembled nanoparticles on glass slides. We also address the limitations of our models and their range of applicability. The exact results obtained using matrix theory can be applied to a variety of two-state systems with cooperative effects.

  9. Performance changes in world-class kayakers following two different training periodization models.

    PubMed

    García-Pallarés, Jesús; García-Fernández, Miguel; Sánchez-Medina, Luis; Izquierdo, Mikel

    2010-09-01

    This study was undertaken to compare training-induced changes in selected physiological, body composition and performance variables following two training periodization models: traditional (TP) versus block periodization (BP). Ten world-class kayakers were assessed four times during a training cycle over two consecutive seasons. On each occasion, subjects completed an incremental test to exhaustion on the kayak ergometer to determine peak oxygen uptake (VO(2peak)), VO(2) at second ventilatory threshold (VO(2) VT2), peak blood lactate, paddling speed at VO(2peak) (PS(peak)) and VT2 (PS( VT2)), power output at VO(2peak) (Pw(peak)) and VT2 (Pw( VT2)), stroke rate at VO(2peak) (SR(peak)) and VT2 (SR( VT2)) as well as heart rate at VO(2peak) and VT2. Volume and exercise intensity were quantified for each endurance training session. Both TP and BP cycles resulted in similar gains in VO(2peak) (11 and 8.1%) and VO(2) VT2 (9.8 and 9.4%), even though the TP cycle was 10 weeks and 120 training hours longer than the BP cycle. Following BP paddlers experienced larger gains in PS(peak), Pw(peak) and SR(peak) than those observed with TP. These findings suggest that BP may be more effective than TP for improving the performance of highly trained top-level kayakers. Although both models allowed significant improvements of selected physiological and kayaking performance variables, the BP program achieved similar results with half the endurance training volume used in the TP model. A BP design could be a more useful strategy than TP to maintain the residual training effects as well as to achieve greater improvements in certain variables related to kayaking performance.

  10. Partial least squares density modeling (PLS-DM) - a new class-modeling strategy applied to the authentication of olives in brine by near-infrared spectroscopy.

    PubMed

    Oliveri, Paolo; López, M Isabel; Casolino, M Chiara; Ruisánchez, Itziar; Callao, M Pilar; Medini, Luca; Lanteri, Silvia

    2014-12-03

    A new class-modeling method, referred to as partial least squares density modeling (PLS-DM), is presented. The method is based on partial least squares (PLS), using a distance-based sample density measurement as the response variable. Potential function probability density is subsequently calculated on PLS scores and used, jointly with residual Q statistics, to develop efficient class models. The influence of adjustable model parameters on the resulting performances has been critically studied by means of cross-validation and application of the Pareto optimality criterion. The method has been applied to verify the authenticity of olives in brine from cultivar Taggiasca, based on near-infrared (NIR) spectra recorded on homogenized solid samples. Two independent test sets were used for model validation. The final optimal model was characterized by high efficiency and equilibrate balance between sensitivity and specificity values, if compared with those obtained by application of well-established class-modeling methods, such as soft independent modeling of class analogy (SIMCA) and unequal dispersed classes (UNEQ).

  11. Constraints on non-Standard Model Higgs boson interactions in an effective Lagrangian using differential cross sections measured in the H → γγ decay channel at √{ s} = 8 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

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A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. 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X.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gray, H. M.; Graziani, E.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Grohs, J. P.; Grohsjean, A.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Guan, L.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, Y.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Haefner, P.; Hageböck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Haley, J.; Hall, D.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. 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C.; Hiller, K. H.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hinman, R. R.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohlfeld, M.; Hohn, D.; Holmes, T. R.; Homann, M.; Hong, T. M.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, C.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, Q.; Hu, X.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. 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F.-W.; Sadykov, R.; Safai Tehrani, F.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Saleem, M.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sasaki, Y.; Sato, K.; Sauvage, G.; Sauvan, E.; Savage, G.; Savard, P.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitt, S.; Schneider, B.; Schnellbach, Y. J.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schorlemmer, A. L. S.; Schott, M.; Schouten, D.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schroeder, C.; Schuh, N.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciacca, F. G.; Scifo, E.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Sedov, G.; Sedykh, E.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Serre, T.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Shushkevich, S.; Sicho, P.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silver, Y.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Song, H. Y.; Soni, N.; Sood, A.; Sopczak, A.; Sopko, B.; Sopko, V.; Sorin, V.; Sosa, D.; Sosebee, M.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Spearman, W. R.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Spreitzer, T.; St. Denis, R. D.; Stabile, A.; Staerz, S.; Stahlman, J.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, F. E.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thun, R. P.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Velz, T.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Wasicki, C.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Wharton, A. M.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, A.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamada, M.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yurkewicz, A.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zwalinski, L.

    2016-02-01

    The strength and tensor structure of the Higgs boson's interactions are investigated using an effective Lagrangian, which introduces additional CP-even and CP-odd interactions that lead to changes in the kinematic properties of the Higgs boson and associated jet spectra with respect to the Standard Model. The parameters of the effective Lagrangian are probed using a fit to five differential cross sections previously measured by the ATLAS experiment in the H → γγ decay channel with an integrated luminosity of 20.3 fb-1 at √{ s} = 8 TeV. In order to perform a simultaneous fit to the five distributions, the statistical correlations between them are determined by re-analysing the H → γγ candidate events in the proton-proton collision data. No significant deviations from the Standard Model predictions are observed and limits on the effective Lagrangian parameters are derived. The statistical correlations are made publicly available to allow for future analysis of theories with non-Standard Model interactions.

  12. Search for the Standard Model Higgs boson in the decay channel H → ZZ (*) → 4 ℓ with 4.8 fb-1 of pp collision data at √{ s} = 7 TeV with ATLAS

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abouzeid, O. S.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Aderholz, M.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Akiyama, A.; Alam, M. S.; Alam, M. A.; Albert, J.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allbrooke, B. M. M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amaral, P.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anisenkov, A.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Aubert, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barashkou, A.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, V.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beale, S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, S.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Behar Harpaz, S.; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertella, C.; Bertin, A.; Bertinelli, F.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blazek, T.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boelaert, N.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Bolnet, N. M.; Bomben, M.; Bona, M.; Bondarenko, V. G.; Bondioli, M.; Boonekamp, M.; Booth, C. N.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borri, M.; Borroni, S.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Botterill, D.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozhko, N. I.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Branchini, P.; Brandenburg, G. W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brelier, B.; Bremer, J.; Brendlinger, K.; Brenner, R.; Bressler, S.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brodbeck, T. J.; Brodet, E.; Broggi, F.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, W. K.; Brown, G.; Brown, H.; Bruckman de Renstrom, P. A.; Bruncko, D.

    2012-04-01

    This Letter presents a search for the Standard Model Higgs boson in the decay channel H → ZZ (*) →ℓ+ℓ-ℓ‧+ℓ‧-, where ℓ ,ℓ‧ = e or μ, using proton-proton collisions at √{ s} = 7 TeV recorded with the ATLAS detector and corresponding to an integrated luminosity of 4.8 fb-1. The four-lepton invariant mass distribution is compared with Standard Model background expectations to derive upper limits on the cross section of a Standard Model Higgs boson with a mass between 110 GeV and 600 GeV. The mass ranges 134-156 GeV, 182-233 GeV, 256-265 GeV and 268-415 GeV are excluded at the 95% confidence level. The largest upward deviations from the background-only hypothesis are observed for Higgs boson masses of 125 GeV, 244 GeV and 500 GeV with local significances of 2.1, 2.2 and 2.1 standard deviations, respectively. Once the look-elsewhere effect is considered, none of these excesses are significant.

  13. Search for the Standard Model Higgs boson produced in association with top quarks and decaying into bb¯ in pp collisions at √s = 8 TeV with the ATLAS detector

    SciTech Connect

    Aad, G.

    2015-07-29

    In this study, a search for the Standard Model Higgs boson produced in association with a top-quark pair, tt¯H, is presented. The analysis uses 20.3 fb–1 of pp collision data at √s=8 TeV, collected with the ATLAS detector at the Large Hadron Collider during 2012. The search is designed for the H→bb¯ decay mode and uses events containing one or two electrons or muons. In order to improve the sensitivity of the search, events are categorised according to their jet and b-tagged jet multiplicities. A neural network is used to discriminate between signal and background events, the latter being dominated by tt¯+jets production. In the single-lepton channel, variables calculated using a matrix element method are included as inputs to the neural network to improve discrimination of the irreducible tt¯+bb¯ background. No significant excess of events above the background expectation is found and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95 % confidence level. The ratio of the measured tt¯H signal cross section to the Standard Model expectation is found to be μ=1.5±1.1 assuming a Higgs boson mass of 125GeV.

  14. Search for the Standard Model Higgs boson produced in association with top quarks and decaying into bb¯ in pp collisions at √s = 8 TeV with the ATLAS detector

    DOE PAGES

    Aad, G.

    2015-07-29

    In this study, a search for the Standard Model Higgs boson produced in association with a top-quark pair, tt¯H, is presented. The analysis uses 20.3 fb–1 of pp collision data at √s=8 TeV, collected with the ATLAS detector at the Large Hadron Collider during 2012. The search is designed for the H→bb¯ decay mode and uses events containing one or two electrons or muons. In order to improve the sensitivity of the search, events are categorised according to their jet and b-tagged jet multiplicities. A neural network is used to discriminate between signal and background events, the latter being dominatedmore » by tt¯+jets production. In the single-lepton channel, variables calculated using a matrix element method are included as inputs to the neural network to improve discrimination of the irreducible tt¯+bb¯ background. No significant excess of events above the background expectation is found and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95 % confidence level. The ratio of the measured tt¯H signal cross section to the Standard Model expectation is found to be μ=1.5±1.1 assuming a Higgs boson mass of 125GeV.« less

  15. Local Integration Ontological Model of Creative Class Migrants for Creative Cities

    ERIC Educational Resources Information Center

    Sangkakorn, Korawan; Chakpitak, Nopasit; Yodmongkol, Pitipong

    2015-01-01

    An innovative creative class drives creative cities, urban areas in which diverse cultures are integrated into social and economic functions. The creative city of Chiang Mai, Thailand is renowned for its vibrant Lan Na culture and traditions, and draws new migrants from other areas in Thailand seeking to become part of the creative class. This…

  16. Using the Gravity Model to Delineate a Trade Area: A Class Project.

    ERIC Educational Resources Information Center

    Dzik, Anthony J.

    1992-01-01

    Reports that students who might be bored or intimidated by economic geographic theory become enthusiastic when they can apply it to their own experiences. Describes a class project involving fieldwork and in-class analysis on delineating the retail trade area of a small Ohio city. Includes three maps and mathematical formulae for data analysis.…

  17. Search for new phenomena in dijet mass and angular distributions from pp collisions at √{ s} = 13 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

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N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Song, H. Y.; Soni, N.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Staerz, S.; Stahlman, J.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tylmad, M.; Tyndel, M.; Ueda, I.; Ueno, R.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Wharton, A. M.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zwalinski, L.

    2016-03-01

    This Letter describes a model-agnostic search for pairs of jets (dijets) produced by resonant and non-resonant phenomena beyond the Standard Model in 3.6 fb-1 of proton-proton collisions with a centre-of-mass energy of √{ s} = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. The distribution of the invariant mass of the two leading jets is examined for local excesses above a data-derived estimate of the smoothly falling prediction of the Standard Model. The data are also compared to a Monte Carlo simulation of Standard Model angular distributions derived from the rapidity of the two jets. No evidence of anomalous phenomena is observed in the data, which are used to exclude, at 95% CL, quantum black holes with threshold masses below 8.3 TeV, 8.1 TeV, or 5.1 TeV in three different benchmark scenarios; resonance masses below 5.2 TeV for excited quarks, 2.6 TeV in a W‧ model, a range of masses starting from mZ‧ = 1.5 TeV and couplings from gq = 0.2 in a Z‧ model; and contact interactions with a compositeness scale below 12.0 TeV and 17.5 TeV respectively for destructive and constructive interference between the new interaction and QCD processes. These results significantly extend the ATLAS limits obtained from 8 TeV data. Gaussian-shaped contributions to the mass distribution are also excluded if the effective cross-section exceeds values ranging from approximately 50-300 fb for masses below 2 TeV to 2-20 fb for masses above 4 TeV.

  18. Search for new phenomena in dijet mass and angular distributions from pp collisions $\\sqrt{s}$ = 13 TeV with the ATLAS detector

    SciTech Connect

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaitia, Y.; Acharyaa, B. S.; Adamczyka, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.

    2016-01-20

    This Letter describes a model-agnostic search for pairs of jets (dijets) produced by resonant and non-resonant phenomena beyond the Standard Model in 3.6 fb$^{-1}$ of proton-proton collisions with a centre-of-mass energy of $\\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. The distribution of the invariant mass of the two leading jets is examined for local excesses above a data-derived estimate of the smoothly falling prediction of the Standard Model. The data are also compared to a Monte Carlo simulation of Standard Model angular distributions derived from the rapidity of the two jets. No evidence of anomalous phenomena is observed in the data, which are used to exclude, at 95% CL, quantum black holes with threshold masses below 8.3 TeV, 8.1 TeV, or 5.1 TeV in three different benchmark scenarios; resonance masses below 5.2 TeV for excited quarks, 2.6 TeV in a W' model, a range of masses starting from m$_{Z'}$=1.5 TeV and couplings from g$_q$=0.2 in a Z' model; and contact interactions with a compositeness scale below 12.0 TeV and 17.5 TeV respectively for destructive and constructive interference between the new interaction and QCD processes. These results significantly extend the ATLAS limits obtained from 8 TeV data. Gaussian-shaped contributions to the mass distribution are also excluded if the effective cross-section exceeds values ranging from approximately 50-300 fb for masses below 2 TeV to 2-20 fb for masses above 4 TeV.

  19. Relations of occupational stress to occupational class in Japanese civil servants--analysis by two occupational stress models.

    PubMed

    Kawaharada, Mariko; Saijo, Yasuaki; Yoshioka, Eiji; Sato, Tetsuro; Sato, Hirokazu; Kishi, Reiko

    2007-04-01

    The aim of the present study was to identify relations between occupational stress and occupational class in Japanese civil servants, using two occupational stress models-the Effort-Reward Imbalance (ERI) Model and the Job Demand-Control (JDC) Model. The subjects were employees of three local public organizations. We distributed self-administered questionnaires and assessed occupational stress by ERI and JDC. We used seven occupational categories based on the Standard Occupational Classification for Japan. The data of 6,423 male and 1,606 female subjects were analyzed by logistic regression analysis to obtain odds ratios (OR) for relations between occupational stress and occupational class. In JDC, male clerical workers, transport/communication workers and protective service workers showed a significantly higher OR of being in the high occupational stress group, compared to managers. In ERI, male professionals/technicians, transport/communication workers, clerical workers and protective service workers showed a significantly higher prevalence OR, compared to managers, the two models giving different results. In ERI, female production workers/laborers and clerical workers had a significantly lower prevalence OR, compared to managers. The results of this study showed that occupational stress differed by occupational class and the two occupational stress models gave different results for occupational classes with high occupational stress.

  20. TeV γ-ray source MGRO J2019+37 : PWN or SNR?

    NASA Astrophysics Data System (ADS)

    Saha, Lab; Bhattacharjee, Pijushpani

    2014-01-01

    Milagro has recently reported an extended TeV γ-ray source MGRO J2019+37 in the Cygnus region. It is the second brightest TeV source after Crab nebula in their source catalogue. No confirmed counterparts of this source are known although possible associations with several known sources have been suggested. We study leptonic as well as hadronic models of TeV emission within the context of Pulsar Wind Nebulae (PWN) and Supernova Remnant (SNR) type sources, using constraints from multi-wavelength data from observations made on sources around MGRO J2019+37. These include radio upper limit given by GMRT, GeV observations by Fermi-LAT, EGRET and AGILE and very high energy data taken from Milagro. We find that, within the PWN scenario, while both leptonic as well as hadronic models can explain the TeV flux from this source, the GMRT upper limit imposes a stringent upper limit on the size of the emission region in the case of leptonic model. In the SNR scenario, on the other hand, a purely leptonic origin of TeV flux is inconsistent with the GMRT upper limit. At the same time, a dominantly hadronic origin of the TeV flux is consistent with all observations, and the required hadronic energy budget is comparable to that of typical supernovae explosions.

  1. Class-conditional feature modeling for ignitable liquid classification with substantial substrate contribution in fire debris analysis.

    PubMed

    Lopatka, Martin; Sigman, Michael E; Sjerps, Marjan J; Williams, Mary R; Vivó-Truyols, Gabriel

    2015-07-01

    Forensic chemical analysis of fire debris addresses the question of whether ignitable liquid residue is present in a sample and, if so, what type. Evidence evaluation regarding this question is complicated by interference from pyrolysis products of the substrate materials present in a fire. A method is developed to derive a set of class-conditional features for the evaluation of such complex samples. The use of a forensic reference collection allows characterization of the variation in complex mixtures of substrate materials and ignitable liquids even when the dominant feature is not specific to an ignitable liquid. Making use of a novel method for data imputation under complex mixing conditions, a distribution is modeled for the variation between pairs of samples containing similar ignitable liquid residues. Examining the covariance of variables within the different classes allows different weights to be placed on features more important in discerning the presence of a particular ignitable liquid residue. Performance of the method is evaluated using a database of total ion spectrum (TIS) measurements of ignitable liquid and fire debris samples. These measurements include 119 nominal masses measured by GC-MS and averaged across a chromatographic profile. Ignitable liquids are labeled using the American Society for Testing and Materials (ASTM) E1618 standard class definitions. Statistical analysis is performed in the class-conditional feature space wherein new forensic traces are represented based on their likeness to known samples contained in a forensic reference collection. The demonstrated method uses forensic reference data as the basis of probabilistic statements concerning the likelihood of the obtained analytical results given the presence of ignitable liquid residue of each of the ASTM classes (including a substrate only class). When prior probabilities of these classes can be assumed, these likelihoods can be connected to class probabilities. In order to

  2. Qualitative analysis of Kantowski-Sachs metric in a generic class of f(R) models

    SciTech Connect

    Leon, Genly; Roque, Armando A. E-mail: arestrada@ucf.edu.cu

    2014-05-01

    In this paper we investigate, from the dynamical systems perspective, the evolution of a Kantowski-Sachs metric in a generic class of f(R) models. We present conditions (i.e., differentiability conditions, existence of minima, monotony intervals, etc.) for a free input function related to the f(R), that guarantee the asymptotic stability of well-motivated physical solutions, specially, self-accelerated solutions, allowing to describe both inflationary- and late-time acceleration stages of the cosmic evolution. We discuss which f(R) theories allows for a cosmic evolution with an acceptable matter era, in correspondence to the modern cosmological paradigm. We find a very rich behavior, and amongst others the universe can result in isotropized solutions with observables in agreement with observations, such as de Sitter, quintessence-like, or phantom solutions. Additionally, we find that a cosmological bounce and turnaround are realized in a part of the parameter-space as a consequence of the metric choice.

  3. Dispersion Modeling and Characterization of Particulates from Land Application of Class B Biosolids

    NASA Astrophysics Data System (ADS)

    Bhat, Abhishek S.

    This study presents a comprehensive approach to understand the particle characteristics, identify the source profile, develop new equations for emission rates, analyze the source-receptor relationship, and develop and evaluate a numerical model for the dispersion and transport of particles released during the injection of biosolids. Two field studies were conducted in the summer of 2008 and 2009 to collect airborne particulate matter emitted during the injection application of class B biosolids. The sampling was carried out before (pre-application), during (application), and after (post-application) the application. The research work characterized the particulate emissions deposited on the aerosols spectrometer. The mass concentrations of fine (PM2.5) and ultrafine (PM 1.0) particles were highest during the pre-application. The mass concentration of thoracic fraction (PM2.5-10) increased significantly during the application. A bimodal size distribution was observed throughout the sampling. Nuclei mode formation was predominant during the pre-application and the post-application, whereas the accumulation mode was distinctive during the application. Airborne particles were collected on filter papers during the biosolids application process using an aerosol spectrometer. Scanning electron microscopy (SEM) coupled with an energy dispersive spectrometry (EDS) tool was used to analyze particles collected before, during, and after injection of biosolids. The major emphasis of the analysis was on providing in depth information on particle count, size, shape, morphology, and chemical composition. The particle count was significantly sensitive towards the different activities surrounding the application. The combination of SEM, particle analysis software, and EDS technique was capable of revealing detailed information on the size, shape, morphology, and chemical composition of individual particles. These techniques proved to be an effective non-destructive method for the

  4. Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

    NASA Astrophysics Data System (ADS)

    Roy, A.; Royer, A.; Montpetit, B.; Bartlett, P. A.; Langlois, A.

    2012-12-01

    Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and the temperature gradient under dry snow conditions, whereas it considers the liquid water content for wet snow metamorphism. We compare the model with ground-based measurements from several sites (alpine, Arctic and sub-Arctic) with different types of snow. The model provides simulated SSA in good agreement with measurements with an overall point-to-point comparison RMSE of 8.1 m2 kg-1, and a RMSE of 4.9 m2 kg-1 for the snowpack average SSA. The model, however, is limited under wet conditions due to the single-layer nature of the CLASS model, leading to a single liquid water content value for the whole snowpack. The SSA simulations are of great interest for satellite passive microwave brightness temperature assimilations, snow mass balance retrievals and surface energy balance calculations with associated climate feedbacks.

  5. Search for New Phenomena in Dijet Angular Distributions in Proton-Proton Collisions at s = 8 TeV Measured with the ATLAS Det