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Sample records for modeling tev class

  1. 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)

  2. A compact 341 model at TeV scale

    SciTech Connect

    Dias, A.G.; Pinheiro, P.R.D.; Pires, C.A. S de; Rodrigues da Silva, P.S.

    2014-10-15

    We build a gauge model based on the SU(3){sub c}⊗SU(4){sub L}⊗U(1){sub X} symmetry where the scalar spectrum needed to generate gauge boson and fermion masses has a smaller scalar content than usually assumed in literature. We compute the running of its abelian gauge coupling and show that a Landau pole shows up at the TeV scale, a fact that we use to consistently implement those fermion masses that are not generated by Yukawa interactions, including neutrino masses. This is appropriately achieved by non renormalizable effective operators, suppressed by the Landau pole scale. Also, SU(3){sub c}⊗SU(3){sub L}⊗U(1){sub N} models embedded in this gauge structure are bound to be strongly coupled at this same energy scale, contrary to what is generally believed, and neutrino mass generation is rather explained through the same effective operators used in the larger gauge group. Besides, their nice features, as the existence of cold dark matter candidates and the ability to reproduce the observed standard model Higgs-like phenomenology, are automatically inherited by our model. Finally, our results imply that this model is constrained to be observed or discarded soon, since it must be realized at the currently probed energy scale in LHC. - Highlights: • We build a SU(4){sub L}⊗U(1){sub N} electroweak model with a reduced scalar spectrum. • The existence of a Landau pole at TeV scale is investigated. • Fermion masses in this model, including neutrinos, emerge from effective operators. • Imposition of an extra Z{sub 2} symmetry avoids fast proton decay.

  3. 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.

  4. 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…

  5. 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.

  6. Role models face class expulsion.

    PubMed

    Sprinks, Jennifer

    There are plans to drop Mary Seacole and Florence Nightingale from the curriculum taught in schools, according to leaked reports. Here, nurse leaders protest that this would rob young people of valuable role models and undermine the image of the profession. It is also suggested that a person's contribution to society is more important than their personality. PMID:23427681

  7. Minimal B-L model naturally realized at the TeV scale

    SciTech Connect

    Iso, Satoshi; Orikasa, Yuta; Okada, Nobuchika

    2009-12-01

    In a previous paper [S. Iso, N. Okada, and Y. Orikasa, Phys. Lett. B 676, 81 (2009).], we have proposed the minimal B-L extended standard model as a phenomenologically viable model that realizes the Coleman-Weinberg-type breaking of the electroweak symmetry. Assuming the classical conformal invariance and stability up to the Planck scale, we will show in this paper that the model naturally predicts TeV scale B-L breaking as well as a light standard-model singlet Higgs boson and light right-handed neutrinos around the same energy scale. We also study phenomenology and detectability of the model at the Large Hadron Collider and the International Linear Collider.

  8. Predictions for √{sNN}=5.02 TeV Pb + Pb collisions from a multiphase transport model

    NASA Astrophysics Data System (ADS)

    Ma, Guo-Liang; Lin, Zi-Wei

    2016-05-01

    We present predictions from the string melting version of a multiphase transport model on various observables in Pb+Pb collisions at √{sNN}=5.02 TeV . We use the same version of the model as an earlier study that reasonably reproduced d N /d y , pT spectra and elliptic flow of charged pions and kaons at low-pT for central and semicentral heavy ion collisions at 200 GeV and 2.76 TeV. While we compare with the already-available centrality dependence data on charged particle d N /d η at mid-pseudorapidity in Pb+Pb collisions at 5.02 TeV, we make predictions on identified particle d N /d y , pT spectra, azimuthal anisotropies vn(n =2 ,3 ,4 ) , and factorization ratios rn(ηa,ηb) (n =2 ,3 ) for longitudinal correlations.

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

    DOE PAGESBeta

    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; et al

    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.

  10. 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…

  11. Flavour-changing Higgs couplings in a class of two Higgs doublet models

    NASA Astrophysics Data System (ADS)

    Botella, F. J.; Branco, G. C.; Nebot, M.; Rebelo, M. N.

    2016-03-01

    We analyse various flavour-changing processes like trightarrow hu,hc, hrightarrow τ e,τ μ as well as hadronic decays hrightarrow bs,bd, in the framework of a class of two Higgs doublet models where there are flavour-changing neutral scalar currents at tree level. These models have the remarkable feature of having these flavour-violating couplings entirely determined by the CKM and PMNS matrices as well as tan β . The flavour structure of these scalar currents results from a symmetry of the Lagrangian and therefore it is natural and stable under the renormalisation group. We show that in some of the models the rates of the above flavour-changing processes can reach the discovery level at the LHC at 13 TeV even taking into account the stringent bounds on low energy processes, in particular μ rightarrow eγ.

  12. Modelling Symmetry Classes 233 and 432.

    ERIC Educational Resources Information Center

    Dutch, Steven I.

    1986-01-01

    Offers instructions and geometrical data for constructing solids of the enantiomorphous symmetry classes 233 and 432. Provides background information for each class and highlights symmetrical relationships and construction patterns. (ML)

  13. 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.

  14. 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.

  15. A Laboratory Model for Studying Response-Class Hierarchies

    ERIC Educational Resources Information Center

    Shabani, Daniel B.; Carr, James E.; Petursdottir, Anna Ingeborg

    2009-01-01

    If the members of a functional response class occur in a predictable order, a response-class hierarchy is said to exist. Although this topic has received some attention in the applied literature, it remains relatively understudied. The purpose of the current investigation was to develop an analogue model of a response-class hierarchy. Children…

  16. 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.

  17. 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.

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

    DOE PAGESBeta

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; et al

    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

  19. 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. 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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.

  20. A Class of Lattice Boltzmann Models with the Energy Equation

    NASA Astrophysics Data System (ADS)

    Li, Yuanxiang; Xiong, Shengwu; Zou, Xiufen

    In this paper a class of lattice Boltzmann models with the energy equation for simulating fluid thermodynamics are studied. The features of this class of models are that the discrete velocity set consists of multi-speed velocities and the internal energy of fluid is introduced by a multi-speed. Therefore, the energy term appears in the local equilibrium distribution functions of these models. Two examples are given in this paper. One is a 1D model and the other is a 2D model, which are used to model a shock wave tube problem and the Benard convection problem, respectively. Keywords: lattice Boltzmann model, energy equation, shock wave tube, Benard convection

  1. 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

  2. Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques.

    PubMed

    Zang, Qingda; Keire, David A; Wood, Richard D; Buhse, Lucinda F; Moore, Christine M V; Nasr, Moheb; Al-Hakim, Ali; Trehy, Michael L; Welsh, William J

    2011-02-01

    To differentiate heparin samples with varying amounts of dermatan sulfate (DS) impurities and oversulfated chondroitin sulfate (OSCS) contaminants, proton NMR spectral data for heparin sodium active pharmaceutical ingredient samples from different manufacturers were analyzed using multivariate chemometric techniques. A total of 168 samples were divided into three groups: (a) Heparin, [DS] ≤ 1.0% and [OSCS] = 0%; (b) DS, [DS] > 1.0% and [OSCS] = 0%; (c) OSCS, [OSCS] > 0% with any content of DS. The chemometric models were constructed and validated using two well-established methods: soft independent modeling of class analogy (SIMCA) and unequal class modeling (UNEQ). While SIMCA modeling was conducted using the entire set of variables extracted from the NMR spectral data, UNEQ modeling was combined with variable reduction using stepwise linear discriminant analysis to comply with the requirement that the number of samples per class exceed the number of variables in the model by at least 3-fold. Comparison of the results from these two modeling approaches revealed that UNEQ had greater sensitivity (fewer false positives) while SIMCA had greater specificity (fewer false negatives). For Heparin, DS, and OSCS, respectively, the sensitivity was 78% (56/72), 74% (37/50), and 85% (39/46) from SIMCA modeling and 88% (63/72), 90% (45/50), and 91% (42/46) from UNEQ modeling. Importantly, the specificity of both the SIMCA and UNEQ models was 100% (46/46) for Heparin with respect to OSCS; no OSCS-containing sample was misclassified as Heparin. The specificity of the SIMCA model (45/50, or 90%) was superior to that of the UNEQ model (27/50, or 54%) for Heparin with respect to DS samples. However, the overall prediction ability of the UNEQ model (85%) was notably better than that of the SIMCA model (76%) for the Heparin vs DS vs OSCS classes. The models were challenged with blends of heparin spiked with nonsulfated, partially sulfated, or fully oversulfated chondroitin sulfate

  3. 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…

  4. Stimulus generalization and equivalence classes: a model for natural categories.

    PubMed Central

    Fields, L; Reeve, K F; Adams, B J; Verhave, T

    1991-01-01

    Two three-member classes were formed by training AB and BC using a conditional discrimination procedure. The A and B stimuli were nonsense syllables, and the C stimuli were sets of "short" or "long" lines. To test for equivalence, C1 or C2 was presented as a sample with A1 and A2 as comparisons. Once the class-related comparison was chosen consistently, different line lengths were substituted for the training lines in the CA tests. In general, the likelihood of choosing a given comparison was an inverse function of the difference in the length of the test line from the training line. Stimuli in an equivalence class became functionally related not only to each other but also to novel stimuli that resembled a member of the equivalence class. The combination of primary generalization and equivalence class formation, then, can serve as a model to account for the development of naturally occurring categories. PMID:2066703

  5. 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.

  6. 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.

  7. Analysis for a class of winner-take-all model.

    PubMed

    Sum, J P; Leung, C S; Tam, P K; Young, G H; Kan, W K; Chan, L W

    1999-01-01

    Recently we have proposed a simple circuit of winner-take-all (WTA) neural network. Assuming no external input, we have derived an analytic equation for its network response time. In this paper, we further analyze the network response time for a class of winner-take-all circuits involving self-decay and show that the network response time of such a class of WTA is the same as that of the simple WTA model.

  8. Beswitched. The looping out model for immunoglobulin class switching.

    PubMed

    von Schwedler, U; Jäck, H M; Wabl, M

    1990-08-01

    During the switch in expression of an immunoglobulin class, the gene segment encoding the constant region of the heavy chain is replaced in a way that leads to a deletion. Three different models of how this deletion is generated have been proposed: recombination between homologs, unequal sister chromatid exchange, and looping out and deletion. While none of the predicted recombination products of the first two models have been found, the products of the looping out--inversions and circular DNA--have been isolated. Thus looping out and deletion appears to be the appropriate model to explain the genetic events leading to the immunoglobulin heavy chain class switch. PMID:2282364

  9. 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.

  10. 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…

  11. 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…

  12. 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.

  13. Reconciling the 2 TeV excesses at the LHC in a linear seesaw left-right model

    NASA Astrophysics Data System (ADS)

    Deppisch, Frank F.; Graf, Lukas; Kulkarni, Suchita; Patra, Sudhanwa; Rodejohann, Werner; Sahu, Narendra; Sarkar, Utpal

    2016-01-01

    We interpret the 2 TeV excesses at the LHC in a left-right symmetric model with Higgs doublets and spontaneous D -parity violation. The light neutrino masses are understood via a linear seesaw, suppressed by a high D -parity breaking scale, and the heavy neutrinos have a pseudo-Dirac character. In addition, with a suppressed right-handed gauge coupling gR/gL≈0.6 in an S O (10 ) embedding, we can thereby interpret the observed e e j j excess at CMS. We show that it can be reconciled with the diboson and dijet excesses within a simplified scenario based on our model. Moreover, we find that the mixing between the light and heavy neutrinos can be potentially large, which would induce dominant nonstandard contributions to neutrinoless double beta decay via long-range λ and η neutrino exchange.

  14. 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.

  15. 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.

  16. 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. PMID:26337290

  17. 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

  18. Combined upper limit on standard model higgs boson production at D0 in $p \\bar{p}$ collisions at $\\sqrt{s} = 1.96-TeV

    SciTech Connect

    Bernhard, Ralf; /Freiburg U.

    2010-12-01

    The latest searches for the Standard Model Higgs boson at a centre-of-mass energy of {radical}s = 1.96 TeV with the D0 and the CDF detectors at the Fermilab Tevatron collider are presented. For the first time since the LEP experiments the sensitivity for a Standard Model Higgs boson has been reached at a Higgs boson mass of 170 GeV/c{sup 2}.

  19. 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.

  20. 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.

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

    PubMed

    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 L_{x}×L_{y} lattice sites with L_{x}≫L_{y}, 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. PMID:25019704

  2. Hierarchical Classes Models for Three-Way Three-Mode Binary Data: Interrelations and Model Selection

    ERIC Educational Resources Information Center

    Ceulemans, Eva; Van Mechelen, Iven

    2005-01-01

    Several hierarchical classes models can be considered for the modeling of three-way three-mode binary data, including the INDCLAS model (Leenen, Van Mechelen, De Boeck, and Rosenberg, 1999), the Tucker3-HICLAS model (Ceulemans,VanMechelen, and Leenen, 2003), the Tucker2-HICLAS model (Ceulemans and Van Mechelen, 2004), and the Tucker1-HICLAS model…

  3. 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…

  4. 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.

  5. 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…

  6. New class of SO(10) models for flavor

    NASA Astrophysics Data System (ADS)

    Babu, K. S.; Bajc, Borut; Saad, Shaikh

    2016-07-01

    We present a new class of unified models based on S O (10 ) symmetry which provides insights into the masses and mixings of quarks and leptons, including the neutrinos. The key feature of our proposal is the absence of the Higgs boson 1 0H belonging to the fundamental representation that is normally employed. Flavor mixing is induced via vectorlike fermions in the 16 +16 ¯ representation. A variety of scenarios, both supersymmetric and otherwise, are analyzed involving a 126¯ H along with either a 4 5H or a 21 0H of the Higgs boson employed for symmetry breaking. It is shown that this framework, with only a limited number of parameters, provides an excellent fit to the full fermion spectrum, utilizing either the type-I or type-II seesaw mechanism. These flavor models can be potentially tested and distinguished in their predictions for proton decay branching ratios, which are analyzed.

  7. Exact dynamics of a class of aggregation models

    NASA Astrophysics Data System (ADS)

    Majumdar, Satya N.; Sire, Clément

    1993-11-01

    The dynamics of a class of aggregation models proposed by Takayasu and co-workers are solved exactly in one dimension and in the mean field limit. These models describe the aggregation of positive and negative charges. In one dimension, we find the dynamical cluster-size exponents z=3/2 and zc=3/4 when the average flux of injected charges is nonzero and zero, respectively. We also find the crossover exponent near the transition to be φ=4/3. Within mean field theory, we find these exponents to be z=2, zc=1, and φ=1. Assuming dynamic scaling, we show that in any dimension, these exponents are related to one single static exponent.

  8. 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…

  9. Simple Estimators for the Simple Latent Class Mastery Testing Model. Twente Educational Memorandum No. 19.

    ERIC Educational Resources Information Center

    van der Linden, Wim J.

    Latent class models for mastery testing differ from continuum models in that they do not postulate a latent mastery continuum but conceive mastery and non-mastery as two latent classes, each characterized by different probabilities of success. Several researchers use a simple latent class model that is basically a simultaneous application of the…

  10. Model Selection Information Criteria for Non-Nested Latent Class Models.

    ERIC Educational Resources Information Center

    Lin, Ting Hsiang; Dayton, C. Mitchell

    1997-01-01

    The use of these three model selection information criteria for latent class models was studied for nonnested models: (1) Akaike's information criterion (H. Akaike, 1973) (AIC); (2) the Schwarz information (G. Schwarz, 1978) (SIC) criterion; and (3) the Bozdogan version of the AIC (CAIC) (H. Bozdogan, 1987). Situations in which each is preferable…

  11. Experimental refutation of a class of ψ-epistemic models

    NASA Astrophysics Data System (ADS)

    Patra, M. K.; Olislager, L.; Duport, F.; Safioui, J.; Pironio, S.; Massar, S.

    2013-09-01

    The quantum state ψ is a mathematical object used to determine the outcome probabilities of measurements on physical systems. Its fundamental nature has been the subject of discussions since the origin of the theory: Is it ontic, that is, does it correspond to a real property of the physical system? Or is it epistemic, that is, does it merely represent our knowledge about the system? Recent advances in the foundations of quantum theory show that epistemic models that obey a simple continuity condition are in conflict with quantum theory already at the level of a single system. Here we report an experimental test of continuous epistemic models using high-dimensional attenuated coherent states of light traveling in an optical fiber. Due to nonideal state preparation (of coherent states with imperfectly known phase) and nonideal measurements (arising from losses and inefficient detection), this experiment tests only epistemic models that satisfy additional constraints which we discuss in detail. Our experimental results are in agreement with the predictions of quantum theory and provide constraints on a class of ψ-epistemic models.

  12. Geometrical clusters of Darcy's reservoir model and Ising universality class

    NASA Astrophysics Data System (ADS)

    Najafi, M. N.; Ghaedi, M.

    2015-06-01

    In this paper the geometrical features of the fluid propagation in two-dimensional petroleum reservoir described by Darcy equations are studied. The porous media are considered to be tuned by the occupancy parameter p being the probability that a pore is occupied. We analyze the statistical geometrical observables of the Darcy model. To this end we let the water to be injected into random sites of the porous media and solve numerically the Darcy equations to describe the flow motion pattern, using the control volume finite difference (CVFD) method. The fractal dimension of the frontier of the avalanches (defined as the set of the sites through which the fluid passed) and the distribution functions of gyration radius, loop length and cluster mass are numerically obtained revealing that at p =pc (the critical occupancy parameter above which there is definitely a spanning cluster in the system) this model lies within a universality class compatible with the Ising model. We observe that for p >pc, although the model shows critical behaviors, this duality is broken. The mentioned exponents are reported in this paper.

  13. 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.

  14. Network Models in Class C on Arbitrary Graphs

    NASA Astrophysics Data System (ADS)

    Cardy, John

    2005-08-01

    We consider network models of quantum localisation in which a particle with a two-component wave function propagates through the nodes and along the edges of an arbitrary directed graph, subject to a random SU(2) rotation on each edge it traverses. The propagation through each node is specified by an arbitrary but fixed S-matrix. Such networks model localisation problems in class C of the classification of Altland and Zirnbauer [1], and, on suitable graphs, they model the spin quantum Hall transition. We extend the analyses of Gruzberg, Ludwig and Read [5] and of Beamond, Cardy and Chalker [2] to show that, on an arbitrary graph, the mean density of states and the mean conductance may be calculated in terms of observables of a classical history-dependent random walk on the same graph. The transition weights for this process are explicitly related to the elements of the S-matrices. They are correctly normalised but, on graphs with nodes of degree greater than 4, not necessarily non-negative (and therefore interpretable as probabilities) unless a sufficient number of them happen to vanish. Our methods use a supersymmetric path integral formulation of the problem which is completely finite and rigorous.

  15. A class of effective field theory models of cosmic acceleration

    SciTech Connect

    Bloomfield, Jolyon K.; Flanagan, Éanna É. E-mail: eef3@cornell.edu

    2012-10-01

    We explore a class of effective field theory models of cosmic acceleration involving a metric and a single scalar field. These models can be obtained by starting with a set of ultralight pseudo-Nambu-Goldstone bosons whose couplings to matter satisfy the weak equivalence principle, assuming that one boson is lighter than all the others, and integrating out the heavier fields. The result is a quintessence model with matter coupling, together with a series of correction terms in the action in a covariant derivative expansion, with specific scalings for the coefficients. After eliminating higher derivative terms and exploiting the field redefinition freedom, we show that the resulting theory contains nine independent free functions of the scalar field when truncated at four derivatives. This is in contrast to the four free functions found in similar theories of single-field inflation, where matter is not present. We discuss several different representations of the theory that can be obtained using the field redefinition freedom. For perturbations to the quintessence field today on subhorizon lengthscales larger than the Compton wavelength of the heavy fields, the theory is weakly coupled and natural in the sense of t'Hooft. The theory admits a regime where the perturbations become modestly nonlinear, but very strong nonlinearities lie outside its domain of validity.

  16. 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

    2009-09-01

    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).

  17. Experimental Constraints on γ-Ray Pulsar Gap Models and the Pulsar GeV to Pulsar Wind Nebula TeV Connection

    NASA Astrophysics Data System (ADS)

    Abeysekara, A. U.; Linnemann, J. T.

    2015-05-01

    The pulsar emission mechanism in the gamma ray energy band is poorly understood. Currently, there are several models under discussion in the pulsar community. These models can be constrained by studying the collective properties of a sample of pulsars, which became possible with the large sample of gamma ray pulsars discovered by the Fermi Large Area Telescope. In this paper we develop a new experimental multi-wavelength technique to determine the beaming factor ≤ft( {{f}{Ω }} \\right) dependance on spin-down luminosity of a set of GeV pulsars. This technique requires three input parameters: pulsar spin-down luminosity, pulsar phase-averaged GeV flux, and TeV or X-ray flux from the associated pulsar wind nebula (PWN). The analysis presented in this paper uses the PWN TeV flux measurements to study the correlation between {{f}{Ω }} and \\dot{E}. The measured correlation has some features that favor the Outer Gap model over the Polar Cap, Slot Gap, and One Pole Caustic models for pulsar emission in the energy range of 0.1-100 GeV, but one must keep in mind that these simulated models failed to explain many of the most important pulsar population characteristics. A tight correlation between the pulsar GeV emission and PWN TeV emission was also observed, which suggests the possibility of a linear relationship between the two emission mechanisms. In this paper we also discuss a possible mechanism to explain this correlation.

  18. On a class of scaling FRW cosmological models

    SciTech Connect

    Cataldo, Mauricio; Arevalo, Fabiola; Minning, Paul E-mail: pminning@udec.cl

    2010-02-01

    We study Friedmann-Robertson-Walker cosmological models with matter content composed of two perfect fluids ρ{sub 1} and ρ{sub 2}, with barotropic pressure densities p{sub 1}/ρ{sub 1} = ω{sub 1} = const and p{sub 2}/ρ{sub 2} = ω{sub 2} = const, where one of the energy densities is given by ρ{sub 1} = C{sub 1}a{sup α}+C{sub 2}a{sup β}, with C{sub 1}, C{sub 2}, α and β taking constant values. We solve the field equations by using the conservation equation without breaking it into two interacting parts with the help of a coupling interacting term Q. Nevertheless, with the found solution may be associated an interacting term Q, and then a number of cosmological interacting models studied in the literature correspond to particular cases of our cosmological model. Specifically those models having constant coupling parameters α-tilde , β-tilde and interacting terms given by Q = α-tilde Hρ{sub D{sub M}}, Q = α-tilde Hρ{sub D{sub E}}, Q = α-tilde H(ρ{sub D{sub M}}+ρ{sub D{sub E}}) and Q = α-tilde Hρ{sub D{sub M}}+β-tilde Hρ{sub D{sub E}}, where ρ{sub D{sub M}} and ρ{sub D{sub E}} are the energy densities of dark matter and dark energy respectively. The studied set of solutions contains a class of cosmological models presenting a scaling behavior at early and at late times. On the other hand the two-fluid cosmological models considered in this paper also permit a three fluid interpretation which is also discussed. In this reinterpretation, for flat Friedmann-Robertson-Walker cosmologies, the requirement of positivity of energy densities of the dark matter and dark energy components allows the state parameter of dark energy to be in the range −1.37∼<ω{sub D{sub E}} < −1/3.

  19. 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…

  20. Class Stratification in Introductory Textbooks: Relational or Distributional Models?

    ERIC Educational Resources Information Center

    Lucal, Betsy

    1994-01-01

    Maintains that most students learn how sociologists study social stratification in introductory sociology courses. Presents a content analysis of 15 introductory college textbooks to determine whether they use distributional or relational approaches as the basis for their treatment of social class. Finds that depictions of class are…

  1. Thor: Modeling of a Megabar Class Pulsed Power Accelerator

    NASA Astrophysics Data System (ADS)

    Haill, T. A.; Reisman, D. B.; Stoltzfus, B. S.; Austin, K. N.; Stygar, W. A.; Brown, J. L.; Davis, J.-P.; Waisman, E. M.

    2015-06-01

    Thor is a compact, economical machine to drive megabar-class shockless compression material physics experiments and multi-mega-ampere HEDP experiments for the physics community. It is capable of driving peak currents up to 7 MA with rise times of 200-500 ns, resulting in material pressures between 1 to 5 Mbar depending upon the load design, and incorporates a pulse tailoring capability required to maintain shockless loading of many materials. Thor is modular in nature with 200 capacitive bricks triggered in groups by independent, de-coupled switches. The current pulse at the load is a simple linear combination of the 200 time-shifted basis pulses. This enables a variety of experiments including shockless compression experiments using smooth ramped pulses, shock-ramp compression experiments using tailored pulses, and strength measurement experiments using flat top pulses. This paper overviews the Thor design and describes an equivalent circuit model of the machine that drives MHD simulations of the load region. 3D ALEGRA MHD simulations explore topics such as the uniformity of the magnetic field along the stripline load and the design modifications to improve uniformity. Optimized current drives and simulations of the aforementioned applications are also presented. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Company, for the U.S. DOE's NNSA under Contract DE-AC04-94AL85000.

  2. Lepton flavor violation in the supersymmetric seesaw model after the LHC 8 TeV run

    NASA Astrophysics Data System (ADS)

    Goto, Toru; Okada, Yasuhiro; Shindou, Tetsuo; Tanaka, Minoru; Watanabe, Ryoutaro

    2015-02-01

    We study the lepton flavor violation in the supersymmetric seesaw model, taking into account recent experimental improvements, especially for the Higgs boson mass measurement, direct searches of superpartners, and the rare decay of Bs→μ+μ- at the LHC; the neutrino mixing angle of θ13 in the neutrino experiments; and the search of μ →e γ in the MEG experiment. We obtain the latest constraints on the parameters in the supersymmetry-breaking terms and study the effect on the lepton-flavor-violating decays of τ →μ γ and μ →e γ . In particular, we consider two kinds of assumption on the structures in the Majorana mass matrix and the neutrino Yukawa matrix. In the case of the Majorana mass matrix proportional to the unit matrix, allowing nonvanishing C P -violating parameters in the neutrino Yukawa matrix, we find that the branching ratio of τ →μ γ can be larger than 10-9 within the improved experimental limit of μ →e γ . We also consider the neutrino Yukawa matrix that includes the mixing only in the second and third generations, and we find that a larger branching ratio of τ →μ γ than 10-9 is possible while satisfying the recent constraints.

  3. 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…

  4. Performance of Factor Mixture Models as a Function of Model Size, Covariate Effects, and Class-Specific Parameters

    ERIC Educational Resources Information Center

    Lubke, Gitta; Muthen, Bengt O.

    2007-01-01

    Factor mixture models are designed for the analysis of multivariate data obtained from a population consisting of distinct latent classes. A common factor model is assumed to hold within each of the latent classes. Factor mixture modeling involves obtaining estimates of the model parameters, and may also be used to assign subjects to their most…

  5. 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. 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A.; Sonnenschein, L.; Steggemann, J.; Teyssier, D.; Weber, M.; Bontenackels, M.; Cherepanov, V.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Nowack, A.; Perchalla, L.; Pooth, O.; Sauerland, P.; Stahl, A.; Aldaya Martin, M.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Castro, E.; Costanza, F.; Dammann, D.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Flucke, G.; Geiser, A.; Glushkov, I.; Gunnellini, P.; Habib, S.; Hauk, J.; Hellwig, G.; Jung, H.; Kasemann, M.; Katsas, P.; Kleinwort, C.; Kluge, H.; Knutsson, A.; Krämer, M.; Krücker, D.; Kuznetsova, E.; Lange, W.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Marienfeld, M.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Olzem, J.; Perrey, H.; Petrukhin, A.; Pitzl, D.; Raspereza, A.; Ribeiro Cipriano, P. 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R.; Lobelle Pardo, P.; Martschei, D.; Mueller, S.; Müller, Th.; Niegel, M.; Nürnberg, A.; Oberst, O.; Oehler, A.; Ott, J.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Ratnikova, N.; Röcker, S.; Scheurer, A.; Schilling, F.-P.; Schott, G.; Simonis, H. J.; Stober, F. M.; Troendle, D.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Zeise, M.; Daskalakis, G.; Geralis, T.; Kesisoglou, S.; Kyriakis, A.; Loukas, D.; Manolakos, I.; Markou, A.; Markou, C.; Mavrommatis, C.; Ntomari, E.; Gouskos, L.; Mertzimekis, T. J.; Panagiotou, A.; Saoulidou, N.; Evangelou, I.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Patras, V.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Beni, N.; Czellar, S.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Karancsi, J.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Bansal, M.; Beri, S. B.; Bhatnagar, V.; Dhingra, N.; Gupta, R.; Kaur, M.; Mehta, M. Z.; Nishu, N.; Saini, L. K.; Sharma, A.; Singh, J. 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S.; Kwon, E.; Lee, B.; Lee, J.; Lee, S.; Seo, H.; Yu, I.; Bilinskas, M. J.; Grigelionis, I.; Janulis, M.; Juodagalvis, A.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Lopez-Fernandez, R.; Magaña Villalba, R.; Martínez-Ortega, J.; Sanchez-Hernandez, A.; Villasenor-Cendejas, L. M.; Carrillo Moreno, S.; Vazquez Valencia, F.; Salazar Ibarguen, H. A.; Casimiro Linares, E.; Morelos Pineda, A.; Reyes-Santos, M. A.; Krofcheck, D.; Bell, A. J.; Butler, P. H.; Doesburg, R.; Reucroft, S.; Silverwood, H.; Ahmad, M.; Asghar, M. I.; Hoorani, H. R.; Khalid, S.; Khan, W. A.; Khurshid, T.; Qazi, S.; Shah, M. A.; Shoaib, M.; Bialkowska, H.; Boimska, B.; Frueboes, T.; Gokieli, R.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Wrochna, G.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Almeida, N.; Bargassa, P.; David, A.; Faccioli, P.; Ferreira Parracho, P. 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A.; D'Enterria, D.; Dabrowski, A.; De Roeck, A.; Di Guida, S.; Dobson, M.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Frisch, B.; Funk, W.; Georgiou, G.; Giffels, M.; Gigi, D.; Gill, K.; Giordano, D.; Giunta, M.; Glege, F.; Gomez-Reino Garrido, R.; Govoni, P.; Gowdy, S.; Guida, R.; Hansen, M.; Harris, P.; Hartl, C.; Harvey, J.; Hegner, B.; Hinzmann, A.; Innocente, V.; Janot, P.; Kaadze, K.; Karavakis, E.; Kousouris, K.; Lecoq, P.; Lee, Y.-J.; Lenzi, P.; Lourenço, C.; Mäki, T.; Malberti, M.; Malgeri, L.; Mannelli, M.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moser, R.; Mozer, M. U.; Mulders, M.; Musella, P.; Nesvold, E.; Orimoto, T.; Orsini, L.; Palencia Cortezon, E.; Perez, E.; Perrozzi, L.; Petrilli, A.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Polese, G.; Quertenmont, L.; Racz, A.; Reece, W.; Rodrigues Antunes, J.; Rolandi, G.; Rommerskirchen, T.; Rovelli, C.; Rovere, M.; Sakulin, H.; Santanastasio, F.; Schäfer, C.; Schwick, C.; Segoni, I.; Sekmen, S.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Tsirou, A.; Veres, G. I.; Vlimant, J. R.; Wöhri, H. K.; Worm, S. D.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Gabathuler, K.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; König, S.; Kotlinski, D.; Langenegger, U.; Meier, F.; Renker, D.; Rohe, T.; Sibille, J.; Bäni, L.; Bortignon, P.; Buchmann, M. A.; Casal, B.; Chanon, N.; Deisher, A.; Dissertori, G.; Dittmar, M.; Dünser, M.; Eugster, J.; Freudenreich, K.; Grab, C.; Hits, D.; Lecomte, P.; Lustermann, W.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Mohr, N.; Moortgat, F.; Nägeli, C.; Nef, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pape, L.; Pauss, F.; Peruzzi, M.; Ronga, F. J.; Rossini, M.; Sala, L.; Sanchez, A. K.; Starodumov, A.; Stieger, B.; Takahashi, M.; Tauscher, L.; Thea, A.; Theofilatos, K.; Treille, D.; Urscheler, C.; Wallny, R.; Weber, H. A.; Wehrli, L.; Amsler, C.; Chiochia, V.; De Visscher, S.; Favaro, C.; Ivova Rikova, M.; Millan Mejias, B.; Otiougova, P.; Robmann, P.; Snoek, H.; Tupputi, S.; Verzetti, M.; Chang, Y. H.; Chen, K. H.; Kuo, C. M.; Li, S. W.; Lin, W.; Liu, Z. K.; Lu, Y. J.; Mekterovic, D.; Singh, A. P.; Volpe, R.; Yu, S. S.; Bartalini, P.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Dietz, C.; Grundler, U.; Hou, W.-S.; Hsiung, Y.; Kao, K. Y.; Lei, Y. J.; Lu, R.-S.; Majumder, D.; Petrakou, E.; Shi, X.; Shiu, J. G.; Tzeng, Y. M.; Wan, X.; Wang, M.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Karaman, T.; Karapinar, G.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sogut, K.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, L. N.; Vergili, M.; Akin, I. V.; Aliev, T.; Bilin, B.; Bilmis, S.; Deniz, M.; Gamsizkan, H.; Guler, A. M.; Ocalan, K.; Ozpineci, A.; Serin, M.; Sever, R.; Surat, U. E.; Yalvac, M.; Yildirim, E.; Zeyrek, M.; Gülmez, E.; Isildak, B.; Kaya, M.; Kaya, O.; Ozkorucuklu, S.; Sonmez, N.; Cankocak, K.; Levchuk, L.; Bostock, F.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Frazier, R.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Kreczko, L.; Metson, S.; Newbold, D. M.; Nirunpong, K.; Poll, A.; Senkin, S.; Smith, V. J.; Williams, T.; Basso, L.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Jackson, J.; Kennedy, B. W.; Olaiya, E.; Petyt, D.; Radburn-Smith, B. C.; Shepherd-Themistocleous, C. H.; Tomalin, I. R.; Womersley, W. J.; Bainbridge, R.; Ball, G.; Beuselinck, R.; Buchmuller, O.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Ferguson, W.; Fulcher, J.; Futyan, D.; Gilbert, A.; Guneratne Bryer, A.; Hall, G.; Hatherell, Z.; Hays, J.; Iles, G.; Jarvis, M.; Karapostoli, G.; Lyons, L.; Magnan, A.-M.; Marrouche, J.; Mathias, B.; Nandi, R.; Nash, J.; Nikitenko, A.; Papageorgiou, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Pioppi, M.; Raymond, D. M.; Rogerson, S.; Rose, A.; Ryan, M. J.; Seez, C.; Sharp, P.; Sparrow, A.; Stoye, M.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Wakefield, S.; Wardle, N.; Whyntie, T.; Chadwick, M.; 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.; Hatakeyama, K.; Liu, H.; Scarborough, T.; Charaf, O.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Heister, A.; Lawson, P.; Lazic, D.; Rohlf, J.; Sperka, D.; St. John, J.; Sulak, L.; Alimena, J.; Bhattacharya, S.; Cutts, D.; Ferapontov, A.; Heintz, U.; Jabeen, S.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Nguyen, D.; Segala, M.; Sinthuprasith, T.; Speer, T.; Tsang, K. V.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Dolen, J.; Erbacher, R.; Gardner, M.; Houtz, R.; Ko, W.; Kopecky, A.; Lander, R.; Miceli, T.; Pellett, D.; Ricci-Tam, F.; Rutherford, B.; Searle, M.; Smith, J.; Squires, M.; Tripathi, M.; Vasquez Sierra, R.; Andreev, V.; Cline, D.; Cousins, R.; Duris, J.; Erhan, S.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Jarvis, C.; Plager, C.; Rakness, G.; Schlein, P.; Valuev, V.; Weber, M.; Babb, J.; Clare, R.; Dinardo, M. E.; Ellison, J.; Gary, J. W.; Giordano, F.; Hanson, G.; Jeng, G. Y.; Liu, H.; Long, O. R.; Luthra, A.; Nguyen, H.; Paramesvaran, S.; Sturdy, J.; Sumowidagdo, S.; Wilken, R.; Wimpenny, S.; Andrews, W.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Evans, D.; Golf, F.; Holzner, A.; Kelley, R.; Lebourgeois, M.; Letts, J.; Macneill, I.; Mangano, B.; Padhi, S.; Palmer, C.; Petrucciani, G.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Wasserbaech, S.; Würthwein, F.; Yagil, A.; Yoo, J.; Barge, D.; Bellan, R.; Campagnari, C.; D'Alfonso, M.; Danielson, T.; Flowers, K.; Geffert, P.; Incandela, J.; Justus, C.; Kalavase, P.; Koay, S. A.; Kovalskyi, D.; Krutelyov, V.; Lowette, S.; Mccoll, N.; Pavlunin, V.; Rebassoo, F.; Ribnik, J.; Richman, J.; Rossin, R.; Stuart, D.; To, W.; West, C.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Di Marco, E.; Duarte, J.; Gataullin, M.; Kcira, D.; Ma, Y.; Mott, A.; Newman, H. B.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Traczyk, P.; Veverka, J.; Wilkinson, R.; Yang, Y.; Zhu, R. Y.; Akgun, B.; Azzolini, V.; Carroll, R.; Ferguson, T.; Iiyama, Y.; Jang, D. W.; Liu, Y. F.; Paulini, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Drell, B. R.; Edelmaier, C. J.; Ford, W. T.; Gaz, A.; Heyburn, B.; Luiggi Lopez, E.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Eggert, N.; Gibbons, L. K.; Heltsley, B.; Khukhunaishvili, A.; Kreis, B.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Vaughan, 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.; Bloch, I.; Burkett, K.; Butler, J. N.; Chetluru, V.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Green, D.; Gutsche, O.; Hanlon, J.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kilminster, B.; Klima, B.; Kunori, S.; Kwan, S.; Leonidopoulos, C.; Linacre, J.; Lincoln, D.; Lipton, R.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Newman-Holmes, C.; O'Dell, V.; Sexton-Kennedy, E.; Sharma, S.; Spalding, W. J.; Spiegel, L.; Tan, P.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; 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.; Cheng, T.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Dobur, D.; Drozdetskiy, A.; Field, R. D.; Fisher, M.; Fu, Y.; Furic, I. K.; Gartner, J.; Hugon, J.; Kim, B.; Konigsberg, J.; Korytov, A.; Kropivnitskaya, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Remington, R.; Rinkevicius, A.; Sellers, P.; Skhirtladze, N.; Snowball, M.; Yelton, J.; Zakaria, M.; Gaultney, V.; Hewamanage, S.; Lebolo, L. M.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Chen, J.; Diamond, B.; Gleyzer, S. V.; Haas, J.; Hagopian, S.; Hagopian, V.; Jenkins, M.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Dorney, B.; Hohlmann, M.; Kalakhety, H.; Vodopiyanov, I.; Adams, M. R.; Anghel, I. M.; Apanasevich, L.; Bai, Y.; Bazterra, V. E.; Betts, R. R.; Bucinskaite, I.; Callner, J.; Cavanaugh, R.; Dragoiu, C.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Lacroix, F.; Malek, M.; O'Brien, C.; Silkworth, C.; Strom, D.; Varelas, N.; Akgun, U.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Duru, F.; Griffiths, S.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Newsom, C. R.; Norbeck, E.; Onel, Y.; Ozok, F.; Sen, S.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Giurgiu, G.; Gritsan, A. V.; Guo, Z. J.; Hu, G.; Maksimovic, P.; Rappoccio, S.; Swartz, M.; Whitbeck, A.; Baringer, P.; Bean, A.; Benelli, G.; Grachov, O.; Kenny, R. P.; Murray, M.; Noonan, D.; Sanders, S.; Stringer, R.; Tinti, G.; Wood, J. S.; Zhukova, V.; Barfuss, A. F.; Bolton, T.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Shrestha, S.; Svintradze, I.; Gronberg, J.; Lange, D.; Wright, D.; Baden, A.; Boutemeur, M.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kirn, M.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Peterman, A.; Skuja, A.; Temple, J.; Tonjes, M. B.; Tonwar, S. C.; Twedt, E.; Apyan, A.; Bauer, G.; Bendavid, J.; Busza, W.; Butz, E.; Cali, I. A.; Chan, M.; Dutta, V.; Gomez Ceballos, G.; Goncharov, M.; Hahn, K. A.; Kim, Y.; Klute, M.; Krajczar, K.; Li, W.; 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.; Velicanu, D.; Wenger, E. A.; Wolf, R.; Wyslouch, B.; Xie, S.; Yang, M.; Yilmaz, Y.; Yoon, A. S.; Zanetti, M.; Cooper, S. I.; Dahmes, B.; De Benedetti, A.; Franzoni, G.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Sasseville, M.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Cremaldi, L. M.; Kroeger, R.; Perera, L.; Rahmat, R.; Sanders, D. A.; Avdeeva, E.; Bloom, K.; Bose, S.; Butt, J.; Claes, D. R.; Dominguez, A.; Eads, M.; Keller, J.; 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.; Chasco, M.; Haley, J.; Nash, D.; Trocino, D.; Wood, D.; Zhang, J.; Anastassov, A.; Kubik, A.; Mucia, N.; Odell, N.; Ofierzynski, R. A.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Velasco, M.; Won, S.; Antonelli, L.; Berry, D.; Brinkerhoff, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kolb, J.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Morse, D. M.; Pearson, T.; Ruchti, R.; Slaunwhite, J.; Valls, N.; Wayne, M.; Wolf, M.; Bylsma, B.; Durkin, L. S.; Hill, C.; Hughes, R.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Vuosalo, C.; Williams, G.; Winer, B. L.; Adam, N.; Berry, E.; Elmer, P.; Gerbaudo, D.; Halyo, V.; Hebda, P.; Hegeman, J.; Hunt, A.; Jindal, P.; Lopes Pegna, D.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Raval, A.; Safdi, B.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Acosta, J. G.; Brownson, E.; Huang, X. T.; Lopez, A.; Mendez, H.; Oliveros, S.; Ramirez Vargas, J. E.; Zatserklyaniy, A.; Alagoz, E.; Barnes, V. E.; Benedetti, D.; Bolla, G.; Bortoletto, D.; De Mattia, M.; Everett, A.; Hu, Z.; Jones, M.; Koybasi, O.; Kress, M.; Laasanen, A. T.; Leonardo, N.; Maroussov, V.; Merkel, P.; Miller, D. H.; Neumeister, N.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Vidal Marono, M.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Guragain, S.; Parashar, N.; Adair, A.; Boulahouache, C.; 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.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Miner, D. C.; Vishnevskiy, D.; Zielinski, M.; Bhatti, A.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Malik, S.; 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.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Rekovic, V.; Robles, J.; Rose, K.; Salur, S.; Schnetzer, S.; Seitz, C.; Somalwar, S.; Stone, R.; Thomas, S.; Cerizza, G.; Hollingsworth, M.; Spanier, S.; Yang, Z. C.; York, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Safonov, A.; Sakuma, T.; Sengupta, S.; Suarez, I.; Tatarinov, A.; Toback, D.; Akchurin, N.; Damgov, J.; Dudero, P. R.; Jeong, C.; Kovitanggoon, K.; Lee, S. W.; Libeiro, T.; Roh, Y.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Florez, C.; Greene, S.; Gurrola, A.; Johns, W.; Johnston, C.; Kurt, P.; Maguire, C.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Balazs, M.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Lin, C.; Neu, C.; Wood, J.; Yohay, R.; Gollapinni, S.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sakharov, A.; Anderson, M.; Bachtis, M.; Belknap, D. A.; Borrello, L.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Friis, E.; Gray, L.; Grogg, K. S.; Grothe, M.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Klukas, J.; Lanaro, A.; Lazaridis, C.; Leonard, J.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Palmonari, F.; Pierro, G. A.; Ross, I.; Savin, A.; Smith, W. H.; Swanson, J.

    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.

  6. How many of the scaling trends in p p collisions will be violated at √{sNN }=14 TeV ? Predictions from Monte Carlo quark-gluon string model

    NASA Astrophysics Data System (ADS)

    Bleibel, J.; Bravina, L. V.; Zabrodin, E. E.

    2016-06-01

    Multiplicity, rapidity and transverse momentum distributions of hadrons produced both in inelastic and nondiffractive p p collisions at energies from √{s }=200 GeV to 14 TeV are studied within the Monte Carlo quark-gluon string model. Good agreement with the available experimental data up to √{s }=13 TeV is obtained, and predictions are made for the collisions at top LHC energy √{s }=14 TeV . The model indicates that Feynman scaling and extended longitudinal scaling remain valid in the fragmentation regions, whereas strong violation of Feynman scaling is observed at midrapidity. The Koba-Nielsen-Olesen (KNO) scaling in multiplicity distributions is violated at LHC also. The origin of both maintenance and violation of the scaling trends is traced to short range correlations of particles in the strings and interplay between the multistring processes at ultrarelativistic energies.

  7. A Latent Class Approach to Treatment Readiness Corresponds to Transtheoretical (“Stages of Change”) Model

    PubMed Central

    Harrell, PT; Trenz, RC; Scherer, M; Martins, SS; Latimer, WW

    2014-01-01

    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. PMID:23706606

  8. Pulsars at TeV

    NASA Astrophysics Data System (ADS)

    Edwards, P.

    1994-04-01

    The atmospheric Cerenkov technique is used to search for emission at energies above several hundred GeV from a variety of objects, including pulsars (see, e.g., reviews by Weekes, 1988, Phys. Rep., 160, 1; Weekes, 1992, Sp. Sci. Rev., 59, 315). Claims for TeV emission (from any source) should be of high significance, show gamma-ray-like properties, and be independently confirmed. By these criteria the Crab nebula is currently the only established pulsar-driven system to be observed at TeV energies (Weekes et al., 1989, Astrophys. J., 342, 379; Vacanti et al., 1991, Astrophys. J., 377, 467; Goret et al., 1993, Astron. Astrophys., 270, 401). The gamma-ray signal is not pulsed at TeV energies, leading to models of synchrotron self-Compton emission from the Crab nebula (e.g., De Jager and Harding, 1992, Astrophys. J., 396, 161), although other models have also been proposed (Kwok et al., 1991, Astrophys. J., 379, 653). While claims exist for TeV emission from, amongst others, the Vela pulsar (e.g., Bhat et al., 1987, Astron. Astrophys., 178, 242, Geminga (Vishwanath et al., 1993, Astron. Astrophys., 267, L5; Bowden et al., 1993, J. Phys. G: Nucl. Part. Phys., 19, L29), and PSR 1509-58 (Nel et al., 1992, Astrophys. TeV sources. *The detection of TeV gamma-rays from millisecond pulsars has been considered recently by Smith (1993, Astrophys. -J., 408, 468).

  9. 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.

  10. 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.

  11. 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-…

  12. 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.

  13. VHE Observations of TeV Gamma-Ray Binaries by VERITAS

    NASA Astrophysics Data System (ADS)

    Kar, Payel; VERITAS Collaboration

    2016-03-01

    Among many High Mass X-ray Binary (HMXB) systems, only a few exhibit TeV gamma-ray emission. Contemporaneous multi-wavelength observations of these sources are crucial for understanding their astrophysical properties. LS I +61 303 and HESS J0632 +057 are two such TeV Binaries which have been observed by VERITAS and its multiwavelength partners over years. As previously seen at X-ray wavelengths, a TeV flux enhancement for HESS J0632 +057 near orbital phase 0.75 has now been seen for the first time by VERITAS. This was found using updated analysis techniques implemented on the entire 200 hour data set spanning December 2006 to January 2015. From October 2014 to November 2014, LS I +61 303 exhibited its brightest flare ever observed. The flare provided evidence for TeV flux correlations with the emission at X-ray wavelengths. Previous flares of this system observed by VERITAS (2011-2012) had no such correlations. Studies made with multiwavelength observations facilitate our understanding of the gamma ray emission models from these HMXB systems. The results for the above two sources will be presented, along with other new results from VERITAS, improving our knowledge of this sparsely populated class of sources. https://veritas.sao.arizona.edu.

  14. 750 GeV diphoton resonance in a vector-like extension of Hill model at a 100 TeV hadron collider

    NASA Astrophysics Data System (ADS)

    Liu, Ning; Wang, Wenyu; Zhang, Mengchao; Zheng, Rui

    2016-09-01

    In this paper, we study the recent 750 GeV diphoton excess in the Hill model with vector-like fermions. The singlet-like Hill boson is chosen as the 750 GeV diphoton resonance. Such a scalar is mainly produced by gluon fusion via vector-like top and bottom quark loops and decays to diphoton via the vector-like quark and lepton loops. Under the current experimental and theoretical constraints, we find that the mixing angle of the singlet and doublet Higgs bosons lies within |sin 𝜃|≲ 0.03 and the 750 GeV diphoton cross-section can be maximally enhanced to about 6 fb at 13 TeV LHC. Moreover, we find that the Hill boson pair production in jjγγ channel can be probed at 3σ significance if 375GeV < mF < 1500GeV and 1.4 < yF < 3 at a 100 TeV collider with 3000 fb-1 luminosity.

  15. 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…

  16. 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…

  17. 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,…

  18. 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…

  19. 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…

  20. The CLASS Course Design Model for Web-Based Instruction.

    ERIC Educational Resources Information Center

    Smith, Kevin; Northrop, Kathy

    The CLASS (Communication, Learning, and Assessment in a Student-centered System) Project is creating a complete, accredited, high school sequence for delivery on the World Wide Web. The Department of Distance Education of the University of Nebraska-Lincoln (UNL) is a recipient of $18 million in federal funding to develop the sequence. When…

  1. 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…

  2. 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…

  3. 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.

  4. 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.

  5. 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 PAGESBeta

    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

  6. Modeling Photodisintegration-induced TeV Photon Emission from Low-luminosity Gamma-Ray Bursts

    NASA Astrophysics Data System (ADS)

    Liu, Xue-Wen; Wu, Xue-Feng; Lu, Tan

    2012-05-01

    Ultra-high-energy cosmic-ray heavy nuclei have recently been considered as originating from nearby low-luminosity gamma-ray bursts that are associated with Type Ibc supernovae. Unlike the power-law decay in long duration gamma-ray bursts, the light curve of these bursts exhibits complex UV/optical behavior: shock breakout dominated thermal radiation peaks at about 1 day, and, after that, nearly constant emission sustained by radioactive materials for tens of days. We show that the highly boosted heavy nuclei at PeV energy interacting with the UV/optical photon field will produce considerable TeV photons via the photodisintegration/photo-de-excitation process. It was later predicted that a thermal-like γ-ray spectrum peaks at about a few TeV, which may serve as evidence of nucleus acceleration. The future observations by the space telescope Fermi and by the ground atmospheric Cherenkov telescopes such as H.E.S.S., VERITAS, and MAGIC will shed light on this prediction.

  7. 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

    2014-09-27

    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.

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

    DOE PAGESBeta

    Khachatryan, Vardan

    2014-09-27

    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

  9. Search for neutral Higgs bosons of the minimal supersymmetric standard model in pp collisions at TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdinov, O.; Aben, R.; Abi, B.; 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.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; 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.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Apolle, R.; 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.; 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.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Axen, B.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baas, A. E.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Backus Mayes, J.; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; 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.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Beringer, J.; Bernard, C.; Bernat, P.; 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, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boddy, C. R.; Boehler, M.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutouil, S.; 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.; Brelier, B.; Brendlinger, K.; Brennan, A. J.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, J.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camarda, S.; Cameron, D.; Caminada, L. M.; Caminal Armadans, R.; Campana, S.; Campanelli, M.; 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.; Cardarelli, R.; 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.; Castaneda-Miranda, E.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caudron, J.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B. C.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Cole, B.; Cole, S.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuciuc, C.-M.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; 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.; Daniells, A. C.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; 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.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Domenico, A.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Mattia, A.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Valle Wemans, A. Do; Dobos, D.; Doglioni, C.; Doherty, T.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Dwuznik, M.; Dyndal, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Fernandez Perez, S.; Ferrag, S.; Ferrando, J.; 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.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Florez Bustos, A. C.; Flowerdew, M. J.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Franz, S.; Fraternali, M.; French, S. 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    2014-11-01

    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 8 TeV 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. [Figure not available: see fulltext.

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

    PubMed

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Colling, D; Cripps, N; Cutajar, M; Davies, G; Della Negra, M; Ferguson, W; Fulcher, J; Futyan, D; Gilbert, A; Bryer, A Guneratne; Hall, G; Hatherell, Z; Hays, J; Iles, G; Jarvis, M; Karapostoli, G; Lyons, L; Macevoy, B C; Magnan, A-M; Marrouche, J; Mathias, B; Nandi, R; Nash, J; Nikitenko, A; Papageorgiou, A; Pesaresi, M; Petridis, K; Pioppi, M; Raymond, D M; Rogerson, S; Rompotis, N; Rose, A; Ryan, M J; Seez, C; Sharp, P; Sparrow, A; Tapper, A; Tourneur, S; Acosta, M Vazquez; Virdee, T; Wakefield, S; Wardle, N; Wardrope, D; Whyntie, T; Barrett, M; Chadwick, M; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Leslie, D; Martin, W; Reid, I D; Teodorescu, L; Hatakeyama, K; Bose, T; Jarrin, E Carrera; Fantasia, C; Heister, A; St John, J; Lawson, P; Lazic, D; Rohlf, J; Sperka, D; Sulak, L; Avetisyan, A; Bhattacharya, S; Chou, J P; Cutts, D; Ferapontov, A; Heintz, U; Jabeen, S; Kukartsev, G; Landsberg, G; Narain, M; Nguyen, D; Segala, M; Sinthuprasith, T; Speer, T; Tsang, K V; Breedon, R; Sanchez, M Calderon De La Barca; Chauhan, S; Chertok, M; Conway, J; Cox, P T; Dolen, J; Erbacher, R; Friis, E; Ko, W; Kopecky, A; Lander, R; Liu, H; Maruyama, S; Miceli, T; Nikolic, M; Pellett, D; Robles, J; Salur, S; Schwarz, T; Searle, M; Smith, J; Squires, M; Tripathi, M; Sierra, R Vasquez; Veelken, C; Andreev, V; Arisaka, K; Cline, D; Cousins, R; Deisher, A; Duris, J; Erhan, S; Farrell, C; Hauser, J; Ignatenko, M; Jarvis, C; Plager, C; Rakness, G; Schlein, P; Tucker, J; Valuev, V; Babb, J; Chandra, A; Clare, R; Ellison, J; Gary, J W; Giordano, F; Hanson, G; Jeng, G Y; Kao, S C; Liu, F; Liu, H; Long, O R; Luthra, A; Nguyen, H; Shen, B C; Stringer, R; Sturdy, J; Sumowidagdo, S; Wilken, R; Wimpenny, S; Andrews, W; Branson, J G; Cerati, G B; Dusinberre, E; Evans, D; Golf, F; Holzner, A; Kelley, R; Lebourgeois, M; Letts, J; Mangano, B; Padhi, S; Palmer, C; Petrucciani, G; Pi, H; Pieri, M; Ranieri, R; Sani, M; Sharma, V; Simon, S; Tu, Y; Vartak, A; Wasserbaech, S; Würthwein, F; Yagil, A; Yoo, J; Barge, D; Bellan, R; Campagnari, C; D'Alfonso, M; Danielson, T; Flowers, K; Geffert, P; Incandela, J; Justus, C; Kalavase, P; Koay, S A; Kovalskyi, D; Krutelyov, V; Lowette, S; McColl, N; Pavlunin, V; Rebassoo, F; Ribnik, J; Richman, J; Rossin, R; Stuart, D; To, W; Vlimant, J R; Apresyan, A; Bornheim, A; Bunn, J; Chen, Y; Gataullin, M; Ma, Y; Mott, A; Newman, H B; Rogan, C; Shin, K; Timciuc, V; Traczyk, P; Veverka, J; Wilkinson, R; Yang, Y; Zhu, R Y; Akgun, B; Carroll, R; Ferguson, T; Iiyama, Y; Jang, D W; Jun, S Y; Liu, Y F; Paulini, M; Russ, J; Vogel, H; Vorobiev, I; Cumalat, J P; Dinardo, M E; Drell, B R; Edelmaier, C J; Ford, W T; Gaz, A; Heyburn, B; Lopez, E Luiggi; Nauenberg, U; Smith, J G; Stenson, K; Ulmer, K A; Wagner, S R; Zang, S L; Agostino, L; Alexander, J; Cassel, D; Chatterjee, A; Das, S; Eggert, N; Gibbons, L K; Heltsley, B; Hopkins, W; Khukhunaishvili, A; Kreis, B; Kaufman, G Nicolas; Patterson, J R; Puigh, D; Ryd, A; Salvati, E; Shi, X; Sun, W; Teo, W D; Thom, J; Thompson, J; Vaughan, J; Weng, Y; Winstrom, L; 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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; 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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; 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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.

  11. 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

    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. PMID:21770497

  12. Mentoring for Inclusion: A Model Class for Special and General Educators.

    ERIC Educational Resources Information Center

    Hobbs, Tim; Westling, David L.

    2002-01-01

    Describes a model class for instructing general and special educators in best practices in inclusive education. The class emphasized cooperative learning and decision making, highly structured problem solving activities, and use of in vivo case studies involving children with disabilities in local schools. These components were designed to model…

  13. 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.…

  14. 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…

  15. Multi-class and multi-scale models of complex biological phenomena.

    PubMed

    Yu, Jessica S; Bagheri, Neda

    2016-06-01

    Computational modeling has significantly impacted our ability to analyze vast (and exponentially increasing) quantities of experimental data for a variety of applications, such as drug discovery and disease forecasting. Single-scale, single-class models persist as the most common group of models, but biological complexity often demands more sophisticated approaches. This review surveys modeling approaches that are multi-class (incorporating multiple model types) and/or multi-scale (accounting for multiple spatial or temporal scales) and describes how these models, and combinations thereof, should be used within the context of the problem statement. We end by highlighting agent-based models as an intuitive, modular, and flexible framework within which multi-scale and multi-class models can be implemented. PMID:27115496

  16. TeV emission from close binaries

    NASA Astrophysics Data System (ADS)

    Moskalenko, I. V.

    1995-05-01

    It is commonly accepted that candidates for very high energy γ-ray sources are neutron stars, binary systems, black holes etc. Close binary systems containing a normal hot star and a neutron star (or a black hole) form an important class of very high energy γ-ray sources. Such systems are variable in any region of the electromagnetic spectrum and they enable us to study various stages of stellar evolution, accretion processes, mechanisms of particle acceleration, etc. Phenomena connected with this class of very high energy γ-ray sources are discussed. Particular emphasis has been placed on the TeV energy region.

  17. 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

  18. Efficiency improvement in a class of survival models through model-free covariate incorporation.

    PubMed

    Garcia, Tanya P; Ma, Yanyuan; Yin, Guosheng

    2011-10-01

    In randomized clinical trials, we are often concerned with comparing two-sample survival data. Although the log-rank test is usually suitable for this purpose, it may result in substantial power loss when the two groups have nonproportional hazards. In a more general class of survival models of Yang and Prentice (Biometrika 92:1-17, 2005), which includes the log-rank test as a special case, we improve model efficiency by incorporating auxiliary covariates that are correlated with the survival times. In a model-free form, we augment the estimating equation with auxiliary covariates, and establish the efficiency improvement using the semiparametric theories in Zhang et al. (Biometrics 64:707-715, 2008) and Lu and Tsiatis (Biometrics, 95:674-679, 2008). Under minimal assumptions, our approach produces an unbiased, asymptotically normal estimator with additional efficiency gain. Simulation studies and an application to a leukemia study show the satisfactory performance of the proposed method. PMID:21455700

  19. 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…

  20. 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…

  1. 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.

  2. 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.

  3. 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.

  4. Modelling and Analysis of a Class of Phase Field Systems

    NASA Astrophysics Data System (ADS)

    Colli, Pierluigi

    2008-09-01

    A phase transition model based on a reduced energy balance equation will be discussed. The model is derived from free energy and pseudo-potential of dissipation, according to well known thermodynamical laws. We point out analytical results for the related PDE's system. The note reports on a joint work, partly in progress, with ELENA BONETTI, MAURO FABRIZIO and GIANNI GILARDI, to whom I am very grateful for our collaboration.

  5. 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.

  6. 75 FR 6092 - Special Conditions: Model C-27J Airplane; Class E Cargo Compartment Lavatory

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-08

    ... Federal Aviation Administration 14 CFR Part 25 Special Conditions: Model C-27J Airplane; Class E Cargo.... SUMMARY: These special conditions are issued for the Alenia Model C-27J airplane. This airplane has novel... certification of a twin-engine, commercial transport designated as the Model C-27J. The C-27J is a...

  7. 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.

  8. 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.

  9. Elliptic flow in Pb+Pb collisions at {radical}(s{sub NN}) = 2.76 TeV: Hybrid model assessment of the first data

    SciTech Connect

    Hirano, Tetsufumi; Huovinen, Pasi; Nara, Yasushi

    2011-07-15

    We analyze the elliptic flow parameter v{sub 2} in Pb+Pb collisions at {radical}(s{sub NN}) = 2.76 TeV and in Au+Au collisions at {radical}(s{sub NN})=200 GeV using a hybrid model in which the evolution of the quark gluon plasma is described by ideal hydrodynamics with a state-of-the-art lattice QCD equation of state, and the subsequent hadronic stage by a hadron cascade model. For initial conditions, we employ Monte Carlo versions of the Glauber and the Kharzeev-Levin-Nardi models and compare results with each other. We demonstrate that the differential elliptic flow v{sub 2}(p{sub T}) hardly changes when the collision energy increases, whereas the integrated v{sub 2} increases due to the enhancement of mean transverse momentum. The amount of increase of both v{sub 2} and mean p{sub T} depends significantly on the model of initialization.

  10. 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.

  11. 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.

  12. Stochastic Control for a Class of Random Evolution Models

    SciTech Connect

    Hongler, Max-Olivier Soner, Halil Mete Streit, Ludwig

    2004-03-15

    We construct the explicit connection existing between a solvable model of the discrete velocities non-linear Boltzmann equation and the Hamilton-Bellman-Jacobi equation associated with a simple optimal control of a piecewise deterministic process. This study extends the known relation that exists between the Burgers equation and a simple controlled diffusion problem. In both cases the resulting partial differential equations can be linearized via a logarithmic transformation and hence offer the possibility to solve physically relevant non-linear field models in full generality.

  13. Modeling Secondary Instructional Strategies in a Teacher Education Class

    ERIC Educational Resources Information Center

    Watson, Sandy White; Bradley, Janetta Fleming

    2009-01-01

    In most teacher education courses, instructional strategies are merely listed and explained. Students rarely have the opportunity to see these strategies in use until they become student teachers. What better way to teach secondary instructional strategies to pre-service teachers than by modeling these strategies using teacher education content?…

  14. A general class of multinomial mixture models for anuran calling survey data

    USGS Publications Warehouse

    Royle, J. Andrew; Link, W.A.

    2005-01-01

    We propose a general framework for modeling anuran abundance using data collected from commonly used calling surveys. The data generated from calling surveys are indices of calling intensity (vocalization of males) that do not have a precise link to actual population size and are sensitive to factors that influence anuran behavior. We formulate a model for calling-index data in terms of the maximum potential calling index that could be observed at a site (the 'latent abundance class'), given its underlying breeding population, and we focus attention on estimating the distribution of this latent abundance class. A critical consideration in estimating the latent structure is imperfect detection, which causes the observed abundance index to be less than or equal to the latent abundance class. We specify a multinomial sampling model for the observed abundance index that is conditional on the latent abundance class. Estimation of the latent abundance class distribution is based on the marginal likelihood of the index data, having integrated over the latent class distribution. We apply the proposed modeling framework to data collected as part of the North American Amphibian Monitoring Program (NAAMP).

  15. 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.

  16. 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). PMID:25166791

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

    DOE PAGESBeta

    Aaltonen, T.; Adelman, J.; Álvarez González, B.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Appel, J. A.; et al

    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

  18. 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

  19. 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 genetic…

  20. Critical Coarsening without Surface Tension: The Universality Class of the Voter Model

    SciTech Connect

    Dornic, Ivan; Chate, Hugues; Chave, Jerome; Hinrichsen, Haye

    2001-07-23

    We show that the two-dimensional voter model, usually considered to be only a marginal coarsening system, represents a broad class of models for which phase ordering takes place without surface tension. We argue that voter-like growth is generically observed at order-disorder nonequilibrium transitions solely driven by interfacial noise between dynamically symmetric absorbing states.

  1. 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.

  2. Search for the standard model Higgs boson in the decay channel H→ZZ→4ℓ 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; Hoch, M; 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; Benucci, L; 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; Hammad, G H; Hreus, T; Léonard, A; Marage, P E; Thomas, L; Vander Velde, C; Vanlaer, P; Wickens, 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; Vanelderen, L; Verwilligen, P; Walsh, S; Yazgan, E; Zaganidis, N; Basegmez, S; Bruno, G; Ceard, L; De Favereau De Jeneret, J; Delaere, C; du Pree, T; Favart, D; Forthomme, L; Giammanco, A; Grégoire, G; Hollar, J; Lemaitre, V; Liao, J; Militaru, O; Nuttens, C; Pagano, D; Pin, A; Piotrzkowski, K; Schul, N; Beliy, N; Caebergs, T; Daubie, E; 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; 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; Cabrera, A; 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; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Finger, M; Finger, M; Assran, Y; Ellithi Kamel, A; Khalil, S; Mahmoud, M A; Radi, A; Hektor, 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; Elgammal, S; Granier de Cassagnac, R; Haguenauer, M; Miné, P; Mironov, C; Ochando, C; Paganini, P; Sabes, D; Salerno, R; Sirois, Y; Thiebaux, C; 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; Lomidze, D; 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; Wittmer, B; Zhukov, V; Ata, M; Caudron, J; Dietz-Laursonn, E; Erdmann, M; Güth, A; Hebbeker, T; Heidemann, C; Hoepfner, K; Klimkovich, T; Klingebiel, D; Kreuzer, P; Lanske, D; Lingemann, J; Magass, C; Merschmeyer, M; Meyer, A; Olschewski, M; Papacz, P

    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. PMID:22540464

  3. 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.

  4. State-space reduction and equivalence class sampling for a molecular self-assembly model.

    PubMed

    Packwood, Daniel M; Han, Patrick; Hitosugi, Taro

    2016-07-01

    Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models. PMID:27493765

  5. State-space reduction and equivalence class sampling for a molecular self-assembly model

    PubMed Central

    Han, Patrick; Hitosugi, Taro

    2016-01-01

    Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving ‘target information’ from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models. PMID:27493765

  6. 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. PMID:24933216

  7. 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.

  8. 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.

  9. A Class of Semiparametric Mixture Cure Survival Models with Dependent Censoring

    PubMed Central

    Othus, Megan; Li, Yi; Tiwari, Ram C.

    2010-01-01

    Modern cancer treatments have substantially improved cure rates and have generated a great interest in and need for proper statistical tools to analyze survival data with non-negligible cure fractions. Data with cure fractions are often complicated by dependent censoring, and the analysis of this type of data typically involves untestable parametric assumptions on the dependence of the censoring mechanism and the true survival times. Motivated by the analysis of prostate cancer survival trends, we propose a class of semiparametric transformation cure models that allows for dependent censoring without making parametric assumptions on the dependence relationship. The proposed class of models encompasses a number of common models for the latency survival function, including the proportional hazards model and the proportional odds model, and also allows for time-dependent covariates. An inverse censoring probability reweighting scheme is used to derive unbiased estimating equations. We validate small sample properties with simulations and demonstrate the method with a data application. PMID:20706564

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

    PubMed

    Vera, José Fernando; de Rooij, Mark; Heiser, Willem J

    2014-11-01

    In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low-dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented.

  11. 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…

  12. 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…

  13. 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…

  14. Promoting Powerful Parents: A Model for Parent Discussion Groups and Classes.

    ERIC Educational Resources Information Center

    Kohm, Barbara

    A model program to provide family services, the Family Center is a facility of a public school system in Clayton, a suburb of St. Louis, Missouri. Components of the program include parent classes based on the age and developmental level of the child; workshops; informal support groups; individual counseling; activity workshops; for parents and…

  15. 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…

  16. 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…

  17. 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…

  18. 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…

  19. 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…

  20. Kardar-Parisi-Zhang universality class of a discrete erosion model

    NASA Astrophysics Data System (ADS)

    Nath, Palash; Mandal, Pradipta Kumar; Jana, Debnarayan

    2015-09-01

    We investigate a novel (d + 1)-dimensional discrete erosion model for d = 1, 2 and 3. The dynamics of the model is controlled by the physically motivated erosion mechanism. The coarse grained nature of this erosion process has been well compared with the Kardar-Parisi-Zhang (KPZ) equation. The kinetic roughening of the discrete model shows the same scaling behavior as that of the KPZ equation in the dimensions d = 1, 2. Moreover, in this present discrete model in (3 + 1)-dimension almost smooth interface has been obtained with vanishingly small roughness exponent, indicating the model belongs to the weak coupling regime of KPZ universality class.

  1. 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…

  2. Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

    PubMed Central

    Vêncio, Ricardo ZN; Brentani, Helena; Patrão, Diogo FC; Pereira, Carlos AB

    2004-01-01

    Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site. PMID:15339345

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

    PubMed

    Mellor, Steven

    2016-10-01

    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.

  4. Dirac vs Majorana gauginos at a 100 TeV collider

    NASA Astrophysics Data System (ADS)

    di Cortona, Giovanni Grilli; Hardy, Edward; Powell, Andrew J.

    2016-08-01

    We compare the prospects for observing theories with Majorana or Dirac gauginos at a future 100 TeV proton-proton collider. Calculating the expected discovery and exclusion regions, we find that for heavy gluino masses the squark discovery reach is significantly reduced in Dirac gluino models relative to the Majorana case. However, if the squark and gluino masses are close the reach is similar in both scenarios. We also consider the electroweak fine tuning of theories observable at such a collider, and the impact of existing constraints from flavour and CP violating observables. Models with Majorana gluinos that are fine tuned to less than one part in 10, 000 can typically be discovered or excluded, and Dirac models with tuning of one part in 1, 000 can be probed. The flavour structure of Majorana models is highly constrained if they have observable squarks, while O(1) violation is possible in accessible Dirac models. In both cases new sources of CP violation must be very suppressed. Future collider searches can also give important information on possible dark matter candidates. We study the relation of this to indirect and direct detection searches, and find that if dark matter is a neutralino, a 100 TeV collider could probe the viable dark matter candidates in large classes of both Dirac and Majorana models.

  5. 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.

  6. Java Analysis Studio and the hep.lcd class library

    SciTech Connect

    Ronan, M.T.

    2000-02-14

    The Java Analysis Studio and the hep.lcd class library provide a general framework for performing Java-based Linear Collider Detector (LCD) studies. The package is being developed to fully reconstruct 500 GeV to 1.5 TeV e{sup +}e{sup {minus}} annihilation events for analyzing detector options and performance. The current North American LCD reconstruction effort is aimed at comparing different detailed detector models by performing full detector simulation and reconstruction. This paper describes the JAS/hep.lcd distributed analysis framework and some aspects of the reconstruction and analysis object modeling.

  7. 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.

  8. Hazardous gas dispersion: a CFD model accounting for atmospheric stability classes.

    PubMed

    Pontiggia, M; Derudi, M; Busini, V; Rota, R

    2009-11-15

    Nowadays, thanks to the increasing CPU power the use of Computational Fluid Dynamics (CFD) is rapidly imposing also in the industrial risk assessment area, replacing integral models when particular situations, such as those involving complex terrains or large obstacles, are involved. Nevertheless, commercial CFD codes usually do not provide specific turbulence model for simulating atmospheric stratification effects, which are accounted of by the integral models through the well-known stability-class approach. In this work, a new approach able to take account of atmospheric features in CFD simulations has been developed and validated by comparison with available experimental data. PMID:19619939

  9. Damage modeling and statistical analysis of optics damage performance in MJ-class laser systems.

    PubMed

    Liao, Zhi M; Raymond, B; Gaylord, J; Fallejo, R; Bude, J; Wegner, P

    2014-11-17

    Modeling the lifetime of a fused silica optic is described for a multiple beam, MJ-class laser system. This entails combining optic processing data along with laser shot data to account for complete history of optic processing and shot exposure. Integrating with online inspection data allows for the construction of a performance metric to describe how an optic performs with respect to the model. This methodology helps to validate the damage model as well as allows strategic planning and identifying potential hidden parameters that are affecting the optic's performance.

  10. Hazardous gas dispersion: a CFD model accounting for atmospheric stability classes.

    PubMed

    Pontiggia, M; Derudi, M; Busini, V; Rota, R

    2009-11-15

    Nowadays, thanks to the increasing CPU power the use of Computational Fluid Dynamics (CFD) is rapidly imposing also in the industrial risk assessment area, replacing integral models when particular situations, such as those involving complex terrains or large obstacles, are involved. Nevertheless, commercial CFD codes usually do not provide specific turbulence model for simulating atmospheric stratification effects, which are accounted of by the integral models through the well-known stability-class approach. In this work, a new approach able to take account of atmospheric features in CFD simulations has been developed and validated by comparison with available experimental data.

  11. 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…

  12. A mathematical model of the class D converter for compact fluorescent ballasts

    SciTech Connect

    Nerone, L.R.

    1995-11-01

    The time-harmonic analysis is often used to design the class D converter. Since the Q of the resonant network is often low, this analysis, in the form of the sinusoidal approximation, begins to lose accuracy. This paper explores an improved method of designing compact fluorescent ballasts via the square wave approximation (SWA), where the time domain equations are solved for the general case of arbitrary Q, duty ratio, and frequency. A precise mathematical model of the Class D converter is developed that predicts the currents and voltages of the converter and these solutions are compared with computer simulation. Nonlinear programming (NLP) is introduced as a means to design the ballast for the lowest conduction losses. The equations developed in the mathematical model are formulated into a NLP format that includes the self-oscillating case.

  13. Spectrum of classes of point emitters: new tool for nonparaxial optical field modeling.

    PubMed

    Castañeda, Román; Muñoz, Hernán

    2016-08-01

    Numerical modeling of optical fields provides valuable support to both theoretical research and technological development in many optics fields. Fourier methods have been the most widely used tools of numerical modeling. However, important limitations have restricted their application in contemporary research that involve high numerical apertures, short propagation distances, and spatially partially coherent states of light, for instance. The spectrum of classes of point emitters is introduced as a numerical tool that overcomes such limitations for the design, analysis, and synthesis of nonparaxial optical fields in arbitrary states of spatial coherence. In this context, optical processing is realized as the filtering on the spectrum of classes of point emitters performed by the complex degree of spatial coherence that could be implemented dynamically by using programmable devices.

  14. Search for physics beyond the standard model in final states with a lepton and missing transverse energy in proton-proton collisions at $\\sqrt{s}$ = 8 TeV

    SciTech Connect

    Khachatryan, Vardan

    2015-05-22

    A search for new physics in proton-proton collisions having final states with an electron or muon and missing transverse energy is presented. The analysis uses data collected in 2012 with the CMS detector, at an LHC center-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of 19.7 fb$^{-1}$. No significant deviation of the transverse mass distribution of the charged lepton-neutrino system from the standard model prediction is found. Mass exclusion limits of up to 3.28 TeV at a 95% confidence level for a W$^{\\prime}$ boson with the same couplings as that of the standard model W boson are determined. Results are also derived in the framework of split universal extra dimensions, and exclusion limits on Kaluza-Klein W$^{(2)}_{{\\rm KK}}$ states are found. The final state with large missing transverse energy also enables a search for dark matter production with a recoiling W boson, with limits set on the mass and the production cross section of potential candidates. Finally, limits are established for a model including interference between a left-handed W$^{\\prime}$ boson and the standard model W boson, and for a compositeness model.

  15. Search for physics beyond the standard model in final states with a lepton and missing transverse energy in proton-proton collisions at $$\\sqrt{s}$$ = 8 TeV

    DOE PAGESBeta

    Khachatryan, Vardan

    2015-05-22

    A search for new physics in proton-proton collisions having final states with an electron or muon and missing transverse energy is presented. The analysis uses data collected in 2012 with the CMS detector, at an LHC center-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of 19.7 fbmore » $$^{-1}$$. No significant deviation of the transverse mass distribution of the charged lepton-neutrino system from the standard model prediction is found. Mass exclusion limits of up to 3.28 TeV at a 95% confidence level for a W$$^{\\prime}$$ boson with the same couplings as that of the standard model W boson are determined. Results are also derived in the framework of split universal extra dimensions, and exclusion limits on Kaluza-Klein W$$^{(2)}_{{\\rm KK}}$$ states are found. The final state with large missing transverse energy also enables a search for dark matter production with a recoiling W boson, with limits set on the mass and the production cross section of potential candidates. Finally, limits are established for a model including interference between a left-handed W$$^{\\prime}$$ boson and the standard model W boson, and for a compositeness model.« less

  16. Distinguishing between Latent Classes and Continuous Factors with Categorical Outcomes: Class Invariance of Parameters of Factor Mixture Models

    ERIC Educational Resources Information Center

    Lubke, Gitta; Neale, Michael

    2008-01-01

    Factor mixture models are latent variable models with categorical and continuous latent variables that can be used as a model-based approach to clustering. A previous article covered the results of a simulation study showing that in the absence of model violations, it is usually possible to choose the correct model when fitting a series of models…

  17. 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.

  18. 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. PMID:16486438

  19. 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.

  20. 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. 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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.; 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.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; 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.; Valdes Santurio, E.; 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.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; 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.; 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. 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.

    2016-05-01

    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.

  1. 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.

  2. Observer design for a class of nonlinear piecewise systems. Application to an epidemic model with treatment.

    PubMed

    Abdelhedi, Abdessamad; Boutat, Driss; Sbita, Lassaad; Tami, Ramdane; Liu, Da-Yan

    2016-01-01

    Susceptible Exposed Infectious and Recovered epidemic model endowed with a treatment function (SEIR-T model) is a well-known model used to reproduce the behavior of an epidemic, where the susceptible population and the exposed population need to be estimated to predict and control the propagation of a contagious disease. This paper focuses on the nonlinear observer design for a class of nonlinear piecewise systems including SEIR-T models. For this purpose, two changes of coordinates are provided to transform the considered systems into an extended nonlinear observer normal form, on which a high gain observer can be applied. Then, the proposed method is applied to a SEIR-T model. Finally, simulation results are given to show its efficiency. PMID:26606994

  3. 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.

  4. Metal artifact reduction in CT using tissue-class modeling and adaptive prefiltering

    SciTech Connect

    Bal, Matthieu; Spies, Lothar

    2006-08-15

    High-density objects such as metal prostheses, surgical clips, or dental fillings generate streak-like artifacts in computed tomography images. We present a novel method for metal artifact reduction by in-painting missing information into the corrupted sinogram. The information is provided by a tissue-class model extracted from the distorted image. To this end the image is first adaptively filtered to reduce the noise content and to smooth out streak artifacts. Consecutively, the image is segmented into different material classes using a clustering algorithm. The corrupted and missing information in the original sinogram is completed using the forward projected information from the tissue-class model. The performance of the correction method is assessed on phantom images. Clinical images featuring a broad spectrum of metal artifacts are studied. Phantom and clinical studies show that metal artifacts, such as streaks, are significantly reduced and shadows in the image are eliminated. Furthermore, the novel approach improves detectability of organ contours. This can be of great relevance, for instance, in radiation therapy planning, where images affected by metal artifacts may lead to suboptimal treatment plans.

  5. 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.

  6. Unsupervised segmentation of broad classes from waveforms: Towards a model of early phonological acquisition

    NASA Astrophysics Data System (ADS)

    Lin, Ying

    2005-09-01

    It is commonly held that an important aspect of early phonological acquisition is the ability to learn sound distributions, or statistical learning. Yet significant differences in lexical representations are often observed in studies of infant speech perception, suggesting a protracted process of phonological development. The goal of the current project is to develop a model that links holistic and segmental representation of spoken words, using tools from contemporary speech recognition. In the present stage, the model focuses on the pre-lexical level of phonological development, and tries to identify segmental representations from acoustic signals of isolated words. The segmental representations are based on units that correspond to acoustic phonetic classes, and learning involves updating the unit models in parallel with updating phonotactics. Starting from acoustic segmentations, the model iteratively updates knowledge of the units and phonotactics, and renews segmentation hypotheses regarding each word until convergence. The results of running this algorithm on TIMIT and infant-directed speech data suggest that the model approximately identifies segment-sized broad classes in an unsupervised manner. This statistical approach also provides a different perspective on the role of lexicon in phonological development.

  7. 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 PAGESBeta

    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

  8. Critical behavior of a class of nonlinear stochastic models of diffusion of information

    NASA Astrophysics Data System (ADS)

    Sharma, C. L.; Pathria, R. K.; Karmeshu

    1982-12-01

    A theoretical analysis based on the concepts and techniques of statistical physics is carried out for two nonlinear models of diffusion of information-one in a closed population and the other in an open one. Owing to interpersonal contacts among the members of the population, the models exhibit a cooperative behavior when a certain parameter of the problem approaches a critical value. Mathematical similarities in the behavior of the two models, in the vicinity of the critical point, are so impelling that one is tempted to investigate the corresponding behavior of a generalized model, which can be done by carrying out a systematic system-size expansion of the master equation of the process and thereby deriving a nonlinear Fokker-Planck equation for the relevant probability distribution. This establishes a broader class of systems displaying identical behavior in the critical region and also elucidates the role played by fluctuations in bringing about the cooperative phenomenon.

  9. A Hierarchical Multiobjective Routing Model for MPLS Networks with Two Service Classes

    NASA Astrophysics Data System (ADS)

    Craveirinha, José; Girão-Silva, Rita; Clímaco, João; Martins, Lúcia

    This work presents a model for multiobjective routing in MPLS networks formulated within a hierarchical network-wide optimization framework, with two classes of services, namely QoS and Best Effort (BE) services. The routing model uses alternative routing and hierarchical optimization with two optimization levels, including fairness objectives. Another feature of the model is the use of an approximate stochastic representation of the traffic flows in the network, based on the concept of effective bandwidth. The theoretical foundations of a heuristic strategy for finding “good” compromise solutions to the very complex bi-level routing optimization problem, based on a conjecture concerning the definition of marginal implied costs for QoS flows and BE flows, will be described. The main features of a first version of this heuristic based on a bi-objective shortest path model and some preliminary results for a benchmark network will also be revealed.

  10. 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.

  11. 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.

  12. 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 PAGESBeta

    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

  13. TESTING MAGNETIC FIELD MODELS FOR THE CLASS 0 PROTOSTAR L1527

    SciTech Connect

    Davidson, J. A.; Li, Z.-Y.; Hull, C. L. H.; Plambeck, R. L.; Kwon, W.; Crutcher, R. M.; Looney, L. W.; Novak, G.; Chapman, N. L.; Matthews, B. C.; Stephens, I. W.; Tobin, J. J.; Jones, T. J.

    2014-12-20

    For the Class 0 protostar L1527 we compare 131 polarization vectors from SCUPOL/JCMT, SHARP/CSO, and TADPOL/CARMA observations with the corresponding model polarization vectors of four ideal-MHD, nonturbulent, cloud core collapse models. These four models differ by their initial magnetic fields before collapse; two initially have aligned fields (strong and weak) and two initially have orthogonal fields (strong and weak) with respect to the rotation axis of the L1527 core. Only the initial weak orthogonal field model produces the observed circumstellar disk within L1527. This is a characteristic of nearly all ideal-MHD, nonturbulent, core collapse models. In this paper we test whether this weak orthogonal model also has the best agreement between its magnetic field structure and that inferred from the polarimetry observations of L1527. We found that this is not the case; based on the polarimetry observations, the most favored model of the four is the weak aligned model. However, this model does not produce a circumstellar disk, so our result implies that a nonturbulent, ideal-MHD global collapse model probably does not represent the core collapse that has occurred in L1527. Our study also illustrates the importance of using polarization vectors covering a large area of a cloud core to determine the initial magnetic field orientation before collapse; the inner core magnetic field structure can be highly altered by a collapse, and so measurements from this region alone can give unreliable estimates of the initial field configuration before collapse.

  14. 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.

  15. 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…

  16. 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.

  17. 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.

  18. 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. PMID:26133415

  19. 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.

  20. A new class of biophysical models for predicting the probability of decompression sickness in scuba diving.

    PubMed

    Goldman, Saul

    2007-08-01

    Interconnected compartmental models have been used for decades in physiology and medicine to account for the observed multi-exponential washout kinetics of a variety of solutes (including inert gases) both from single tissues and from the body as a whole. They are used here as the basis for a new class of biophysical probabilistic decompression models. These models are characterized by a relatively well-perfused, risk-bearing, central compartment and one or two non-risk-bearing, relatively poorly perfused, peripheral compartment(s). The peripheral compartments affect risk indirectly by diffusive exchange of dissolved inert gas with the central compartment. On the basis of the accuracy of their respective predictions beyond the calibration regime, the three-compartment interconnected models were found to be significantly better than the two-compartment interconnected models. The former, on the basis of a number of criteria, was also better than a two-compartment parallel model used for comparative purposes. In these latter comparisons, the models all had the same number of fitted parameters (four), were based on linear kinetics, had the same risk function, and were calibrated against the same dataset. The interconnected models predict that inert gas washout during decompression is relatively fast, initially, but slows rapidly with time compared with the more uniform washout rate predicted by an independent parallel compartment model. If empirically verified, this may have important implications for diving practice.

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

    PubMed Central

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

    2013-01-01

    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. PMID:23847049

  2. Diabetic peripheral neuropathy class prediction by multicategory support vector machine model: a cross-sectional study

    PubMed Central

    2016-01-01

    OBJECTIVES Diabetes is increasing in worldwide prevalence, toward epidemic levels. Diabetic neuropathy, one of the most common complications of diabetes mellitus, is a serious condition that can lead to amputation. This study used a multicategory support vector machine (MSVM) to predict diabetic peripheral neuropathy severity classified into four categories using patients’ demographic characteristics and clinical features. METHODS In this study, the data were collected at the Diabetes Center of Hamadan in Iran. Patients were enrolled by the convenience sampling method. Six hundred patients were recruited. After obtaining informed consent, a questionnaire collecting general information and a neuropathy disability score (NDS) questionnaire were administered. The NDS was used to classify the severity of the disease. We used MSVM with both one-against-all and one-against-one methods and three kernel functions, radial basis function (RBF), linear, and polynomial, to predict the class of disease with an unbalanced dataset. The synthetic minority class oversampling technique algorithm was used to improve model performance. To compare the performance of the models, the mean of accuracy was used. RESULTS For predicting diabetic neuropathy, a classifier built from a balanced dataset and the RBF kernel function with a one-against-one strategy predicted the class to which a patient belonged with about 76% accuracy. CONCLUSIONS The results of this study indicate that, in terms of overall classification accuracy, the MSVM model based on a balanced dataset can be useful for predicting the severity of diabetic neuropathy, and it should be further investigated for the prediction of other diseases. PMID:27032459

  3. Well-posedness for a class of biological diffusion models with hysteresis effect

    NASA Astrophysics Data System (ADS)

    Zheng, Jiashan; Wang, Yifu

    2015-06-01

    This paper is concerned with a class of biological models which consist of nonlinear diffusion equations and a hysteresis operator describing the relationship between some variables of the equations. The existence of solutions to the analogous problem was ever considered by Aiki and Minchev (SIAM J Math Anal 36:2020-2032, 2005) under some assumptions including the global Lipschitz continuity of reaction terms. We show the existence of nonnegative solutions to the problem under consideration using the approximation method when the reaction terms are locally Lipschitz continuous. Moreover, we discuss the continuous dependence of solutions on initial data.

  4. 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.

  5. 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.

  6. Multi-class SVM model for fMRI-based classification and grading of liver fibrosis

    NASA Astrophysics Data System (ADS)

    Freiman, M.; Sela, Y.; Edrei, Y.; Pappo, O.; Joskowicz, L.; Abramovitch, R.

    2010-03-01

    We present a novel non-invasive automatic method for the classification and grading of liver fibrosis from fMRI maps based on hepatic hemodynamic changes. This method automatically creates a model for liver fibrosis grading based on training datasets. Our supervised learning method evaluates hepatic hemodynamics from an anatomical MRI image and three T2*-W fMRI signal intensity time-course scans acquired during the breathing of air, air-carbon dioxide, and carbogen. It constructs a statistical model of liver fibrosis from these fMRI scans using a binary-based one-against-all multi class Support Vector Machine (SVM) classifier. We evaluated the resulting classification model with the leave-one out technique and compared it to both full multi-class SVM and K-Nearest Neighbor (KNN) classifications. Our experimental study analyzed 57 slice sets from 13 mice, and yielded a 98.2% separation accuracy between healthy and low grade fibrotic subjects, and an overall accuracy of 84.2% for fibrosis grading. These results are better than the existing image-based methods which can only discriminate between healthy and high grade fibrosis subjects. With appropriate extensions, our method may be used for non-invasive classification and progression monitoring of liver fibrosis in human patients instead of more invasive approaches, such as biopsy or contrast-enhanced imaging.

  7. 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.

  8. 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.

  9. Long-time dynamics for a class of Kirchhoff models with memory

    NASA Astrophysics Data System (ADS)

    Jorge Silva, Marcio Antonio; Ma, To Fu

    2013-02-01

    This paper is concerned with a class of Kirchhoff models with memory effects u_{tt} + α Δ ^2 u - div(\\vert nabla u \\vert ^{p-2}nabla u) - int 0^{infty } μ (s) Δ 2u(t-s)ds - Δ u_t + f(u) = h, defined in a bounded domain of {R}^N. This non-autonomous equation corresponds to a viscoelastic version of Kirchhoff models arising in dynamics of elastoplastic flows and plate vibrations. Under assumptions that the exponent p and the growth of f(u) are up to the critical range, it turns out that the model corresponds to an autonomous dynamical system in a larger phase space, by adding a component which describes the relative displacement history. Then the existence of a global attractor is granted. Furthermore, in the subcritical case, this global attractor has finite Hausdorff and fractal dimensions.

  10. A new class of stratospheric vacillations in a highly truncated model due to wave interference

    NASA Technical Reports Server (NTRS)

    Yoden, Shigeo

    1987-01-01

    A new class of vacillations is obtained in the Holton and Mass model with a different bottom boundary condition. The model is a highly truncated spectral model describing wave-zonal flow interactions in a forced-dissipative system. The mean zonal wind and the wave change their vertical structures periodically with a period of the wave progression (5-10 days for the parameters used in this study). The vacillations are interpreted as an interference between a stationary wave and a topographically modified Rossby wave. The modified Rossby wave is an eigenmode of baroclinic flow in the presence of bottom topography within the framework of the highly truncated system. Time variations of the mean zonal wind are essential for the modification of the Rossby wave.

  11. Single-sample face recognition based on intra-class differences in a variation model.

    PubMed

    Cai, Jun; Chen, Jing; Liang, Xing

    2015-01-01

    In this paper, a novel random facial variation modeling system for sparse representation face recognition is presented. Although recently Sparse Representation-Based Classification (SRC) has represented a breakthrough in the field of face recognition due to its good performance and robustness, there is the critical problem that SRC needs sufficiently large training samples to achieve good performance. To address these issues, we challenge the single-sample face recognition problem with intra-class differences of variation in a facial image model based on random projection and sparse representation. In this paper, we present a developed facial variation modeling systems composed only of various facial variations. We further propose a novel facial random noise dictionary learning method that is invariant to different faces. The experiment results on the AR, Yale B, Extended Yale B, MIT and FEI databases validate that our method leads to substantial improvements, particularly in single-sample face recognition problems. PMID:25580904

  12. Single-Sample Face Recognition Based on Intra-Class Differences in a Variation Model

    PubMed Central

    Cai, Jun; Chen, Jing; Liang, Xing

    2015-01-01

    In this paper, a novel random facial variation modeling system for sparse representation face recognition is presented. Although recently Sparse Representation-Based Classification (SRC) has represented a breakthrough in the field of face recognition due to its good performance and robustness, there is the critical problem that SRC needs sufficiently large training samples to achieve good performance. To address these issues, we challenge the single-sample face recognition problem with intra-class differences of variation in a facial image model based on random projection and sparse representation. In this paper, we present a developed facial variation modeling systems composed only of various facial variations. We further propose a novel facial random noise dictionary learning method that is invariant to different faces. The experiment results on the AR, Yale B, Extended Yale B, MIT and FEI databases validate that our method leads to substantial improvements, particularly in single-sample face recognition problems. PMID:25580904

  13. 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. PMID:22556003

  14. Substructure and strong interactions at the TeV scale

    SciTech Connect

    Peskin, M.E.

    1985-12-01

    A review is given of the current status of the three main theoretical ideas relevant to strong-interaction 1 TeV physics. These are composite vector bosons, Higgs bosons (''Technicolor''), and matter fermions. All involve the assumption that some object which is assumed to be fundamental in the standard model actually has dynamical internal structure. Complex, mechanistic models of the new physics are discussed. A brief digression is then made on how the weak interaction allows probing for this new structure. Direct manifestations of new 1 TeV strong interactions are discussed. 125 refs., 18 figs. (LEW)

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Konstandin, Thomas; Servant, Géraldine

    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.

  17. 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.

  18. 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.

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

    PubMed

    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

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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%.

  6. New physics at 1 TeV?

    NASA Astrophysics Data System (ADS)

    Godunov, S. I.; Rozanov, A. N.; Vysotsky, M. I.; Zhemchugov, E. V.

    2016-05-01

    If decays of a heavy particle S are responsible for the diphoton excess with invariant mass 750 GeV observed at the 13 TeV LHC run, it can be easily accommodated in the Standard Model. Two scenarios are considered: production in gluon fusion through a loop of heavy isosinglet quark(s) and production in photon fusion through a loop of heavy isosinglet leptons. In the second case, many heavy leptons are needed or/and they should have large electric charges in order to reproduce experimental data on σ pp → SX · Br( S → γγ).

  7. 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. PMID:20366871

  8. A new class of actuator surface models incorporating wind turbine blade and nacelle geometry effects

    NASA Astrophysics Data System (ADS)

    Yang, Xiaolei; Sotiropoulos, Fotis

    2015-11-01

    It was shown by Kang, Yang and Sotiropoulos that the nacelle has significant effects on the turbine wake even in the far wake region, which the standard actuator line model is not able to predict. We develop a new class of actuator surface models for the blades and nacelle, which is able to resolve the effects of both tip vortices and nacelle vortex. The new nacelle model, which is based on distributing forces from the actual nacelle geometry as in the diffused interface immersed boundary methods, is first tested by carrying out LES of the flow past a sphere and demonstrating good agreement with available in the literature DNS results. The proposed model is subsequently validated by simulating the flow past the hydrokinetic turbine used in the simulations of Kang et al. and good agreement with the measurements is demonstrated. Finally, the proposed model is applied to utility scale wind turbines to elucidate the role of nacelle vortex dynamics on turbine wake meandering. This work was supported by Department of Energy DOE (DE-EE0002980, DE-EE0005482 and DE-AC04-94AL85000), and Sandia National Laboratories. Computational resources were provided by SNL and MSI.

  9. 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.

  10. 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…

  11. 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.

  12. Persistence and extinction for a class of stochastic SIS epidemic models with nonlinear incidence rate

    NASA Astrophysics Data System (ADS)

    Teng, Zhidong; Wang, Lei

    2016-06-01

    In this paper, a class of stochastic SIS epidemic models with nonlinear incidence rate is investigated. It is shown that the extinction and persistence of the disease in probability are determined by a threshold value R˜0. That is, if R˜0 < 1 and an additional condition holds then disease dies out, and if R˜0 > 1 then disease is weak permanent with probability one. To obtain the permanence in the mean of the disease, a new quantity R̂0 is introduced, and it is proved that if R̂0 > 1 the disease is permanent in the mean with probability one. Furthermore, the numerical simulations are presented to illustrate some open problems given in Remarks 1-3 and 5 of this paper.

  13. A class of physical modeling recurrent networks for analysis/synthesis of plucked string instruments.

    PubMed

    Su, A Y; Liang, Sheng-Fu

    2002-01-01

    A new approach is proposed that closely synthesizes tones of plucked string instruments by using a class of physical modeling recurrent networks. The strategies employed consist of a fast training algorithm and a multistage training procedure that are able to obtain the synthesis parameters for a specific instrument automatically. The training vector can be recorded tones of most target plucked instruments with ordinary microphones. The proposed approach delivers encouraging results when it is applied to different types of plucked string instruments such as steel-string guitar, nylon-string guitar, harp, Chin, Yueh-chin, and Pipa. The synthesized tones sound very close to the originals produced by their acoustic counterparts. In addition, the paper presents an embedded technique that can produce special effects such as vibrato and portamento that are vital to the playing of plucked-string instruments. The computation required in the resynthesis processing is also reasonable. PMID:18244510

  14. Transition from diffusive to ballistic dynamics for a class of finite quantum models.

    PubMed

    Steinigeweg, Robin; Breuer, Heinz-Peter; Gemmer, Jochen

    2007-10-12

    The transport of excitation probabilities amongst weakly coupled subunits is investigated for a class of finite quantum systems. It is demonstrated that the dynamical behavior of the transported quantity depends on the considered length scale; e.g., the introduced distinction between diffusive and ballistic transport appears to be a scale-dependent concept, especially since a transition from diffusive to ballistic behavior is found in the limit of small as well as in the limit of large length scales. All these results are derived by an application of the time-convolutionless projection operator technique and are verified by the numerical solution of the full time-dependent Schrödinger equation which is obtained by exact diagonalization for a range of model parameters. PMID:17995149

  15. 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.

  16. Secondary structure and 3D homology modeling of swine leukocyte antigen class 2 (SLA-2) molecules.

    PubMed

    Gao, Feng-Shan; Xu, Chong-bo; Long, Yi-hou; Xia, Chun

    2009-01-01

    No information to date is available to elucidate the structure of swine leukocyte antigen class I (SLA-I) molecule which is comprised by a heavy chain of SLA-I non-covalently associated with a light chain, beta(2)-microglobulin (beta(2)m) proteins. Presently, one of SLA-I gene SLA-2 and beta(2)m gene were expressed as soluble maltose binding proteins (MBP-proteins) in a pMAL-p2X/Escherichia coli TB1 system and identified by western blotting with anti-MBP polyclonal antibodies. The expressed proteins MBP-SLA-2 and MBP-beta(2)m were purified on amylose affinity columns followed by DEAE-Sepharose. The purified products were cleaved by Factor Xa, respectively, and the interest of proteins SLA-2 and beta(2)m were purified on amylose affinity columns followed by separation from MBP on DEAE-Sepharose. The secondary structures of SLA-2 and beta(2)m were analyzed by circular dichroism (CD) spectrophotometry. The three-dimensional (3D) structure of their peptide-binding domain (PBD) was modeled-based sequence homology. The content of the alpha-helix, beta-sheet, turn, and random coil in the SLA-2 protein were 76, 95, 36, and 67aa, respectively. In the 98aa of beta(2)m, the contents of the alpha-helix, beta-sheet, turn, and random coil were 0, 45, 8, and 45aa, respectively. The SLA-2 protein displayed a typical alpha-helix structure while beta(2)m protein displayed a typical beta-sheet structure. Homology modeling of the SLA-2 and beta(2)m proteins demonstrated similarities with the structure of human and mouse MHC (major histocompatibility complex) class I proteins.

  17. 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

  18. A note regarding the mathematical treatment of a class of steady-state compartmental models of the circulation.

    PubMed

    White, Ronald J

    2016-09-01

    A class of steady-state compartmental models of the circulation is examined and it is shown that the mathematical problem for this model class involves a single nonlinear equation. In an important subclass and with certain assumptions regarding the form of the Starling-type cardiac function curves, the single equation is of the form Z = μ + λ log[(1 - Z)/Z] where μ and λ are mathematical parameters related to the physiological parameters of the system and Z is proportional to the cardiac output. This result holds regardless of the number and arrangement of compartments within the model itself or of the number of physiological parameters the model contains. An example of this class with 25 physiological parameters is presented to illustrate this approach. PMID:27587712

  19. 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.

  20. 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.

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

    DOE PAGESBeta

    Aaltonen, T.; Álvarez González, B.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Appel, J. A.; Apresyan, A.; et al

    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

  2. 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.

  3. 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.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Butt, A. I.; 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.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Campana, S.; Campanelli, M.; 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.; Cardarelli, R.; Cardillo, F.; 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.; Castaneda-Miranda, E.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B. C.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; 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.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Choi, K.; 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, P. J.; Clarke, R. N.; Cleland, W.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; 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.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. 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. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Ciaccio, A.; di Ciaccio, L.; di Domenico, A.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Mattia, A.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; 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.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Fitzgerald, E. A.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Fletcher, R. R. M.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Flowerdew, M. 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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.; Atlas Collaboration

    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 .

  4. 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.

  5. Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models.

    PubMed

    Yang, Chenguang; Li, Zhijun; Li, Jing

    2013-02-01

    In this paper, we investigate optimized adaptive control and trajectory generation for a class of wheeled inverted pendulum (WIP) models of vehicle systems. Aiming at shaping the controlled vehicle dynamics to be of minimized motion tracking errors as well as angular accelerations, we employ the linear quadratic regulation optimization technique to obtain an optimal reference model. Adaptive control has then been developed using variable structure method to ensure the reference model to be exactly matched in a finite-time horizon, even in the presence of various internal and external uncertainties. The minimized yaw and tilt angular accelerations help to enhance the vehicle rider's comfort. In addition, due to the underactuated mechanism of WIP, the vehicle forward velocity dynamics cannot be controlled separately from the pendulum tilt angle dynamics. Inspired by the control strategy of human drivers, who usually manipulate the tilt angle to control the forward velocity, we design a neural-network-based adaptive generator of implicit control trajectory (AGICT) of the tilt angle which indirectly "controls" the forward velocity such that it tracks the desired velocity asymptotically. The stability and optimal tracking performance have been rigorously established by theoretic analysis. In addition, simulation studies have been carried out to demonstrate the efficiency of the developed AGICT and optimized adaptive controller.

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

    PubMed

    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

  7. 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.

  8. An exclusion principle and the importance of mobility for a class of biofilm models.

    PubMed

    Klapper, Isaac; Szomolay, Barbara

    2011-09-01

    Much of the earth's microbial biomass resides in sessile, spatially structured communities such as biofilms and microbial mats, systems consisting of large numbers of single-celled organisms living within self-secreted matrices made of polymers and other molecules. As a result of their spatial structure, these communities differ in important ways from well-mixed (and well-studied) microbial systems such as those present in chemostats. Here we consider a widely used class of 1D biofilm models in the context of a description of their basic ecology. It will be shown via an exclusion principle resulting from competition for space that these models lead to restrictions on ecological structure. Mathematically, this result follows from a classification of steady-state solutions based on a 0-stability condition: 0-stable solutions are in some sense determined by competitive balance at the biofilm base, whereas solutions that are not 0-stable, while less dependent on conditions at the biofilm base, are unstable at the base. As a result of the exclusion principle, it is argued that some form of downward mobility, against the favorable substrate gradient direction, is needed at least in models and possibly in actuality.

  9. 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

  10. 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).

  11. A class representative model for Pure Parsimony Haplotyping under uncertain data.

    PubMed

    Catanzaro, Daniele; Labbé, Martine; Porretta, Luciano

    2011-01-01

    The Pure Parsimony Haplotyping (PPH) problem is a NP-hard combinatorial optimization problem that consists of finding the minimum number of haplotypes necessary to explain a given set of genotypes. PPH has attracted more and more attention in recent years due to its importance in analysis of many fine-scale genetic data. Its application fields range from mapping complex disease genes to inferring population histories, passing through designing drugs, functional genomics and pharmacogenetics. In this article we investigate, for the first time, a recent version of PPH called the Pure Parsimony Haplotype problem under Uncertain Data (PPH-UD). This version mainly arises when the input genotypes are not accurate, i.e., when some single nucleotide polymorphisms are missing or affected by errors. We propose an exact approach to solution of PPH-UD based on an extended version of Catanzaro et al.[1] class representative model for PPH, currently the state-of-the-art integer programming model for PPH. The model is efficient, accurate, compact, polynomial-sized, easy to implement, solvable with any solver for mixed integer programming, and usable in all those cases for which the parsimony criterion is well suited for haplotype estimation. PMID:21464966

  12. A class-oriented model for hyperspectral image classification through hierarchy-tree-based selection

    NASA Astrophysics Data System (ADS)

    Tang, Zhongqi; Fu, Guangyuan; Zhao, XiaoLin; Chen, Jin; Zhang, Li

    2016-03-01

    With the development of hyperspectral sensors over the last few decades, hyperspectral images (HSIs) face new challenges in the field of data analysis. Due to those high-dimensional data, the most challenging issue is to select an effective yet minimal subset from a mass of bands. This paper proposes a class-oriented model to solve the task of classification by incorporating spectral prior of the target, since different targets have different characteristics in spectral correlation. This model operates feature selection after a partition of hyperspectral data into groups along the spectral dimension. In the process of spectral partition, we group the raw data into several subsets by a hierarchy tree structure. In each group, band selection is performed via a recursive support vector machine (R-SVM) learning, which reduces the computational cost as well as preserves the accuracy of classification. To ensure the robustness of the result, we also present a weight-voting strategy for result merging, in which the spectral independency and the classification effectivity are both considered. Extensive experiments show that our model achieves better performance than the existing methods in task-dependent classifications, such as target detection and identification.

  13. 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

  14. 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.

  15. 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…

  16. Towards an Empirical Model of Parental Discipline Reactions, Family Climate, Child-Rearing Values and Social Class.

    ERIC Educational Resources Information Center

    Janssens, Jan M. A. M.; Gerris, Jan R. M.

    A starting model consisting of nine latent factors referring to parental discipline reactions, child-rearing values, family climate, and social class was developed and tested by means of a LISREL approach. Data were obtained from 300 families, including 245 two-parent and 55 one-parent families. In the main outline of this model, the following…

  17. 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…

  18. 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.

  19. Observation and Modeling of the Solar Transition Region. II. Identification of New Classes of Solutions of Coronal Loop Models

    NASA Astrophysics Data System (ADS)

    Oluseyi, Hakeem M.; Walker, A. B. C., II; Santiago, David I.; Hoover, Richard B.; Barbee, Troy W., Jr.

    1999-12-01

    In the present work we undertake a study of the quasi-static loop model and the observational consequences of the various solutions found. We obtain the most general solutions consistent with certain initial conditions. Great care is exercised in choosing these conditions to be physically plausible (motivated by observations). We show that the assumptions of previous quasi-static loop models, such as the models of Rosner, Tucker, & Vaiana (RTV) and Veseckey, Antiochos, & Underwood, (VAU) are not necessarily valid for small loops at transition region temperatures. We find three general classes of solutions for the quasi-static loop model, which we denote radiation-dominated loops, conduction-dominated loops, and classical loops. These solutions are then compared with observations. Departures from the classical scaling law of RTV are found for the solutions obtained. It is shown that loops of the type that we model here can make a significant contribution to lower transition regions emission via thermal conduction from the upper transition region.

  20. 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. PMID:24257593

  1. 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).

  2. Conditions for global dynamic stability of a class of resource-bounded model ecosystems.

    PubMed

    Seymour, Robert M; Knight, Gwenan; Fung, Tak

    2010-11-01

    This paper studies a class of dynamical systems that model multi-species ecosystems. These systems are 'resource bounded' in the sense that species compete to utilize an underlying limiting resource or substrate. This boundedness means that the relevant state space can be reduced to a simplex, with coordinates representing the proportions of substrate utilized by the various species. If the vector field is inward pointing on the boundary of the simplex, the state space is forward invariant under the system flow, a requirement that can be interpreted as the presence of non-zero exogenous recruitment. We consider conditions under which these model systems have a unique interior equilibrium that is globally asymptotically stable. The systems we consider generalize classical multi-species Lotka-Volterra systems, the behaviour of which is characterized by properties of the community (or interaction) matrix. However, the more general systems considered here are not characterized by a single matrix, but rather a family of matrices. We develop a set of 'explicit conditions' on the basis of a notion of 'uniform diagonal dominance' for such a family of matrices, that allows us to extract a set of sufficient conditions for global asymptotic stability based on properties of a single, derived matrix. Examples of these explicit conditions are discussed. PMID:20195913

  3. Natural origin of inflation within a class of supersymmetric preon models

    NASA Astrophysics Data System (ADS)

    Cveti, Mirjam; Hübsch, Tristan; Pati, Jogesh C.; Stremnitzer, Hanns

    1989-08-01

    Derivation of a desired potential for implementing the idea of new inflation from an underlying theory of particle physics has so far remained a challenging task in that it requires unusually small quartic coupling (~10-13+/-1) and an even smaller mass term for the relevant field (the inflaton) in units of its true vacuum expectation value. It is shown that a class of viable locally supersymmetric preon models naturally give rise to the desired potential for a composite field ΔR commonly used as a Higgs field to break left-right symmetry and B-L, so that ΔR can serve as the inflaton. We show that both the quartic coupling and the mass of ΔR vanish in the limit of supersymmetry, U(1)X, U(1)V and gauge invariance. Radiative corrections, in the presence of soft supersymmetry-breaking mass terms, which arise dynamically in the model, give rise to a miniscule quartic coupling and a negligible mass for ΔR, just as desired. This turns out to be the case in spite of the fact that ΔR is a gauge nonsinglet.

  4. Contextual-Guided Bag-of-Visual-Words Model for Multi-class Object Categorization

    NASA Astrophysics Data System (ADS)

    Mirza-Mohammadi, Mehdi; Escalera, Sergio; Radeva, Petia

    Bag-of-words model (BOW) is inspired by the text classification problem, where a document is represented by an unsorted set of contained words. Analogously, in the object categorization problem, an image is represented by an unsorted set of discrete visual words (BOVW). In these models, relations among visual words are performed after dictionary construction. However, close object regions can have far descriptions in the feature space, being grouped as different visual words. In this paper, we present a method for considering geometrical information of visual words in the dictionary construction step. Object interest regions are obtained by means of the Harris-Affine detector and then described using the SIFT descriptor. Afterward, a contextual-space and a feature-space are defined, and a merging process is used to fuse feature words based on their proximity in the contextual-space. Moreover, we use the Error Correcting Output Codes framework to learn the new dictionary in order to perform multi-class classification. Results show significant classification improvements when spatial information is taken into account in the dictionary construction step.

  5. 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.

  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. Search for Narrow Resonances Decaying to Dijets in Proton-Proton Collisions at √{s }=13 TeV

    NASA Astrophysics Data System (ADS)

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Knünz, V.; König, A.; Krammer, M.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Cornelis, T.; de Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; van de Klundert, M.; van Haevermaet, H.; van Mechelen, P.; van Remortel, N.; van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; de Bruyn, I.; Deroover, K.; Heracleous, N.; Keaveney, J.; Lowette, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; van Doninck, W.; van Mulders, P.; van Onsem, G. P.; van Parijs, I.; Barria, P.; Brun, H.; Caillol, C.; Clerbaux, B.; de Lentdecker, G.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Maerschalk, T.; Marinov, A.; Perniè, L.; Randle-Conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Beernaert, K.; Benucci, L.; Cimmino, A.; Crucy, S.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; McCartin, J.; Ocampo Rios, A. A.; Poyraz, D.; Ryckbosch, D.; Salva, S.; Sigamani, M.; Tytgat, M.; van Driessche, W.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; Ceard, L.; Delaere, C.; Favart, D.; Forthomme, L.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Mertens, A.; Musich, M.; Nuttens, C.; Perrini, L.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Beliy, N.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. 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M.; Fahim, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; de Filippis, N.; de Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Abbiendi, G.; Battilana, C.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; 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.; Rossi, A. M.; Rovelli, T.; Siroli, G. 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M.; Lanza, G.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Maron, G.; Meneguzzo, A. T.; Montecassiano, F.; Passaseo, M.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; D'Imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Zanetti, A.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. 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V.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Myagkov, I.; Obraztsov, S.; Petrushanko, S.; 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.; Cirkovic, P.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; de La Cruz, B.; Delgado Peris, A.; 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.; Santaolalla, J.; Soares, M. S.; Albajar, C.; de Trocóniz, J. 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M.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Breuker, H.; Camporesi, T.; Castello, R.; Cerminara, G.; D'Alfonso, M.; D'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; de Gruttola, M.; de Guio, F.; de Roeck, A.; de Visscher, S.; di Marco, E.; Dobson, M.; Dordevic, M.; Dorney, B.; Du Pree, T.; Duggan, D.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kirschenmann, H.; Kortelainen, M. J.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Magini, N.; Malgeri, L.; Mannelli, M.; Martelli, A.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Nemallapudi, M. V.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Piparo, D.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Triossi, A.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Zagozdzinska, A.; 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.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz Del Arbol, P.; Masciovecchio, M.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Takahashi, M.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; Chiochia, V.; de Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Ronga, F. J.; Salerno, D.; Yang, Y.; Cardaci, M.; Chen, K. H.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Grundler, U.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Petrakou, E.; Tsai, J. F.; Tzeng, Y. M.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Bat, A.; Demiroglu, Z. S.; Dozen, C.; Gecit, F. H.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozcan, M.; Ozdemir, K.; Ozturk, S.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Zorbilmez, C.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, E. A.; Yetkin, T.; Cakir, A.; Cankocak, K.; Sen, S.; Vardarlı, F. I.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; 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.; Sakuma, T.; Seif El Nasr-Storey, S.; Senkin, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; de Wit, A.; Della Negra, M.; Dunne, P.; Elwood, A.; Futyan, D.; Hall, G.; Iles, G.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Alimena, J.; Berry, E.; Cutts, D.; Ferapontov, A.; Garabedian, A.; Hakala, J.; Heintz, U.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Syarif, R.; Breedon, R.; Breto, G.; Calderon de La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; McLean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Florent, A.; Hauser, J.; Ignatenko, M.; Saltzberg, D.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Paneva, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Derdzinski, M.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; MacNeill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Incandela, J.; McColl, N.; Mullin, S. D.; Richman, J.; Stuart, D.; Suarez, I.; West, C.; Yoo, J.; Anderson, D.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Nauenberg, U.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Sun, W.; Tan, S. M.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Wittich, P.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; 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.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes de Sá, R.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Rossin, R.; Shchutska, L.; Snowball, M.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Weinberg, M.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Kalakhety, H.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wu, Z.; Zakaria, M.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Barnett, B. A.; Blumenfeld, B.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Osherson, M.; Roskes, J.; Sady, A.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P.; Majumder, D.; Malek, M.; Murray, M.; Sanders, S.; Stringer, R.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Baty, A.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; McGinn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Dahmes, B.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bartek, R.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Knowlton, D.; Kravchenko, I.; Meier, F.; Monroy, J.; Ratnikov, F.; Siado, J. E.; Snow, G. R.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira de Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Bhattacharya, S.; Hahn, K. A.; Kubik, A.; Low, J. F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M.; Sung, K.; Trovato, M.; Velasco, M.; Brinkerhoff, A.; Dev, N.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; 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.; Ji, W.; Ling, T. Y.; Liu, B.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Saka, H.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Kumar, A.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Harel, A.; Hindrichs, O.; Khukhunaishvili, A.; Petrillo, G.; Tan, P.; Verzetti, M.; Chou, J. P.; Contreras-Campana, E.; Ferencek, D.; Gershtein, Y.; Halkiadakis, E.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Lath, A.; Nash, K.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Riley, G.; Rose, K.; Spanier, S.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; de Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Krutelyov, V.; Mueller, R.; Osipenkov, I.; Pakhotin, Y.; Patel, R.; Perloff, A.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Wood, J.; Xia, F.; 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.; Gomber, B.; Grothe, M.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Sarangi, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Woods, N.; Cms Collaboration

    2016-02-01

    A search for narrow resonances in proton-proton collisions at √{s }=13 TeV is presented. The invariant mass distribution of the two leading jets is measured with the CMS detector using a data set corresponding to an integrated luminosity of 2.4 fb-1 . The highest observed dijet mass is 6.1 TeV. The distribution is smooth and no evidence for resonant particles is observed. Upper limits at 95% confidence level are set on the production cross section for narrow resonances with masses above 1.5 TeV. When interpreted in the context of specific models, the limits exclude string resonances with masses below 7.0 TeV, scalar diquarks below 6.0 TeV, axigluons and colorons below 5.1 TeV, excited quarks below 5.0 TeV, color-octet scalars below 3.1 TeV, and W' bosons below 2.6 TeV. These results significantly extend previously published limits.

  8. 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

    2014-12-01

    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).

  9. Increasing Student Engagement in Large Classes: The ARC Model of Application, Response, and Collaboration

    ERIC Educational Resources Information Center

    Hourigan, Kristen Lee

    2013-01-01

    This article introduces a simple, flexible approach to engaging students within large classes, known as ARC (application, response, collaboration). ARC encourages each student's presence and engagement in class; creates a sense of excitement and anticipation; breaks down passivity and anonymity; effectively gains, maintains, and utilizes…

  10. The role of certain Post classes in Boolean network models of genetic networks.

    PubMed

    Shmulevich, Ilya; Lähdesmäki, Harri; Dougherty, Edward R; Astola, Jaakko; Zhang, Wei

    2003-09-16

    A topic of great interest and debate concerns the source of order and remarkable robustness observed in genetic regulatory networks. The study of the generic properties of Boolean networks has proven to be useful for gaining insight into such phenomena. The main focus, as regards ordered behavior in networks, has been on canalizing functions, internal homogeneity or bias, and network connectivity. Here we examine the role that certain classes of Boolean functions that are closed under composition play in the emergence of order in Boolean networks. The closure property implies that any gene at any number of steps in the future is guaranteed to be governed by a function from the same class. By means of Derrida curves on random Boolean networks and percolation simulations on square lattices, we demonstrate that networks constructed from functions belonging to these classes have a tendency toward ordered behavior. Thus they are not overly sensitive to initial conditions, and damage does not readily spread throughout the network. In addition, the considered classes are significantly larger than the class of canalizing functions as the connectivity increases. The functions in these classes exhibit the same kind of preference toward biased functions as do canalizing functions, meaning that functions from this class are likely to be biased. Finally, functions from this class have a natural way of ensuring robustness against noise and perturbations, thus representing plausible evolutionarily selected candidates for regulatory rules in genetic networks. PMID:12963822

  11. The Slovene Model of Sports Classes in Grammar Schools: Psychological and Educational Point of View.

    ERIC Educational Resources Information Center

    Zupancic, Maja; Justin, Janez

    1998-01-01

    Results with 54 pairs of Slovenian students, matched for participation or nonparticipation in intensive sports classes in elementary school, indicate that a combination of flexible organization of academic work and intensive sports classes does not have a negative impact on intellectual, academic, or personality development. (SLD)

  12. 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.…

  13. 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…

  14. 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.

  15. A Class of Random Walks in Reversible Dynamic Environments: Antisymmetry and Applications to the East Model

    NASA Astrophysics Data System (ADS)

    Avena, Luca; Blondel, Oriane; Faggionato, Alessandra

    2016-10-01

    We introduce via perturbation a class of random walks in reversible dynamic environments having a spectral gap. In this setting one can apply the mathematical results derived in Avena et al. (L^2-Perturbed Markov processes and applications to random walks in dynamic random environments, Preprint, 2016). As first results, we show that the asymptotic velocity is antisymmetric in the perturbative parameter and, for a subclass of random walks, we characterize the velocity and a stationary distribution of the environment seen from the walker as suitable series in the perturbative parameter. We then consider as a special case a random walk on the East model that tends to follow dynamical interfaces between empty and occupied regions. We study the asymptotic velocity and density profile for the environment seen from the walker. In particular, we determine the sign of the velocity when the density of the underlying East process is not 1 / 2, and we discuss the appearance of a drift in the balanced setting given by density 1 / 2.

  16. Prospects for electroweakino discovery at a 100 TeV hadron collider

    NASA Astrophysics Data System (ADS)

    Gori, Stefania; Jung, Sunghoon; Wang, Lian-Tao; Wells, James D.

    2014-12-01

    We investigate the prospects of discovering split Supersymmetry at a future 100 TeV proton-proton collider through the direct production of electroweakino next-to-lightest- supersymmetric-particles (NLSPs). We focus on signatures with multi-lepton and missing energy: 3ℓ, opposite-sign dileptons and same-sign dileptons. We perform a comprehensive study of different electroweakino spectra. A 100 TeV collider with 3000 /fb data is expected to exclude Higgsino thermal dark matter candidates with m LSP ~ 1 TeV if Wino NLSPs are lighter than about 3.2 TeV. The 3ℓ search usually offers the highest mass reach, which varies in the range of (2-4) TeV depending on scenarios. In particular, scenarios with light Higgsinos have generically simplified parameter dependences. We also demonstrate that, at a 100 TeV collider, lepton collimation becomes a crucial issue for NLSPs heavier than about 2.5 TeV. We finally compare our results with the discovery prospects of gluino pair productions and deduce which SUSY breaking model can be discovered first by electroweakino searches.

  17. 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.

  18. Earth2Class workshops for teachers: effective model linking researchers, educators, and students

    NASA Astrophysics Data System (ADS)

    Passow, M. J.; Assumpcao, C. M.; Baggio, F. D.

    2011-12-01

    The Earth2Class Workshops for Teachers at the Lamont-Doherty Earth Observatory of Columbia University (E2C) provide a successful model for disseminating scientific research to teachers and students. E2C takes a multifaceted approach to sharing cutting-edge discoveries, including monthly workshops that bring investigators together with classroom educator and their students, archived versions of the workshops and other educational resources accessible at www.earth2class.org, and active promotion of opportunities for teachers and students to engage directly with research scientists. The wide array of exploration conducted at LDEO have been showcased in more than 115 Saturday workshops since 1998, enabling more than 75 scientists to share their findings directly with over 250 middle and high school teachers and students. Each workshop features an introductory slideshow to provide background knowledge of the theme, the scientist(s)' presentation, and discussion of classroom applications. E2C website resources attract an average of more than 400,000 hits per month during the school year, extending the reach of the program to those unable to attend the workshops in Palisades, NY. E2C has come to be viewed at LDEO as a valid, effective venue to provide broader outreach, and several funded grants have included an E2C workshop in their proposals. Lamont scientists have easily been able to draw on E2C to connect with classroom teachers for a variety of research projects, including "River Summer," "A Day in the Life of the Hudson River," and "Data Puzzles." E2C teachers have assisted scientists during the annual Lamont Open House, which draws about 4,000 visitors. During the last two years, E2C has also co-organized the International Student and Teacher Exchange Program (ISTEP.) ISTEP has brought together high school students from New York City, Singapore, and the Netherlands to conduct field studies about water and soil chemistry, tree rings and forest diversity, and

  19. An Emerging Class of Gamma-ray Flares from Blazars: Beyond One-zone Models

    NASA Astrophysics Data System (ADS)

    Tavani, M.; Vittorini, V.; Cavaliere, A.

    2015-11-01

    Blazars radiate from relativistic plasma jets with bulk Lorentz factors {{Γ }}∼ 10, closely aligned along our line of sight. In a number of blazars of the flat-spectrum radio quasar type, such as 3C 454.3 and 3C 279, gamma-ray flares have recently been detected with very high luminosity and few or no counterparts in the optical and soft X-ray bands. They challenge the current one-zone leptonic models of emissions from within the broad-line region (BLR). The latter envisage the optical/X-ray emissions to be produced as synchrotron radiation by the same population of highly relativistic electrons in the jet that would also yield the gamma rays by inverse Compton upscattering of surrounding soft photons. To meet the challenge, we present here a model based on primary synchrotron photons emitted in the BLR by a plasmoid moving out with the jet and scattered back toward the incoming plasmoid by an outer plasma clump acting as a mirror. We consider both a scenario based on a static mirror located outside the BLR and an alternative provided by a moving mirror geometry. We show that mirroring phenomena can locally enhance the density and anisotropy with associated relativistic boosting of soft photons within the jet, so as to trigger bright inverse Compton gamma-ray transients from nearly steady optical/X-ray synchrotron emissions. In this picture we interpret the peculiarly asymmetric light curves of the recently detected gamma-ray flares from 3C 279. Our scenario provides a promising start to understanding the widening class of bright and transient gamma-ray activities in blazars.

  20. 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.

  1. 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.

  2. Guaranteed and prospective Galactic TeV neutrino sources

    SciTech Connect

    Kistler, Matthew D.; Beacom, John F.

    2006-09-15

    Recent observations, particularly from the HESS Collaboration, have revealed rich Galactic populations of TeV gamma-ray sources, including a collection unseen in other wavelengths. Many of these gamma-ray spectra are well measured up to {approx}10 TeV, where low statistics make observations by air Cerenkov telescopes difficult. To understand these mysterious sources, especially at much higher energies--where a cutoff should eventually appear--new techniques are needed. We point out the following: (1) For a number of sources, it is very likely that pions, and hence TeV neutrinos, are produced; (2) As a general point, neutrinos should be a better probe of the highest energies than gamma rays, due to increasing detector efficiency; and (3) For several specific sources, the detection prospects for km{sup 3} neutrino telescopes are very good, {approx}1-10 events/year, with low atmospheric neutrino background rates above reasonable energy thresholds. Such signal rates, as small as they may seem, will allow neutrino telescopes to powerfully discriminate between models for the Galactic TeV sources, with important consequences for our understanding of cosmic-ray production.

  3. Test of the Standard Model of electroweak interactions by measuring the anomalous W W gamma couplings at s**(1/2) = 1.8-TeV

    SciTech Connect

    Kelly, Michael Lawrence

    1996-04-01

    An analysis of W{gamma} events found in 73.0 pb{sup -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} {yields} W{gamma} + X (for p{sub T}{sup {gamma}} > 10 GeV/c and {Delta}R{sub e{gamma}} > 0.7) times the branching ratio of W bosons to electrons is measured to be: {sigma}(p{bar p} {yields} W{gamma} + X) x BR(W {yields} e{nu}) = 11.19{sub -2.32}{sup +2.66} {+-} 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/c{sup 2}. The results are: -1.4 < {Delta}{kappa} < 1.4 ({lambda} = 0) and -0.5 < {lambda} < 0.5 ({Delta}{kappa} = 0) with similar limits are set on the CP-violating coupling parameters {bar {kappa}} and {bar {lambda}}. These limits were set by assuming a dipole form factor with a scale factor of {Lambda} = 1.5 TeV.

  4. 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.

  5. The Application of SECI Model as a Framework of Knowledge Creation in Virtual Learning: Case Study of IUST Virtual Classes

    ERIC Educational Resources Information Center

    Hosseini, Seyede Mehrnoush

    2011-01-01

    The research aims to define SECI model of knowledge creation (socialization, externalization, combination, and internalization) as a framework of Virtual class management which can lead to better online teaching-learning mechanisms as well as knowledge creation. It has used qualitative research methodology including researcher's close observation…

  6. Multivariate class modeling techniques applied to multielement analysis for the verification of the geographical origin of chili pepper.

    PubMed

    Naccarato, Attilio; Furia, Emilia; Sindona, Giovanni; Tagarelli, Antonio

    2016-09-01

    Four class-modeling techniques (soft independent modeling of class analogy (SIMCA), unequal dispersed classes (UNEQ), potential functions (PF), and multivariate range modeling (MRM)) were applied to multielement distribution to build chemometric models able to authenticate chili pepper samples grown in Calabria respect to those grown outside of Calabria. The multivariate techniques were applied by considering both all the variables (32 elements, Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Fe, Ga, La, Li, Mg, Mn, Na, Nd, Ni, Pb, Pr, Rb, Sc, Se, Sr, Tl, Tm, V, Y, Yb, Zn) and variables selected by means of stepwise linear discriminant analysis (S-LDA). In the first case, satisfactory and comparable results in terms of CV efficiency are obtained with the use of SIMCA and MRM (82.3 and 83.2% respectively), whereas MRM performs better than SIMCA in terms of forced model efficiency (96.5%). The selection of variables by S-LDA permitted to build models characterized, in general, by a higher efficiency. MRM provided again the best results for CV efficiency (87.7% with an effective balance of sensitivity and specificity) as well as forced model efficiency (96.5%).

  7. Multivariate class modeling techniques applied to multielement analysis for the verification of the geographical origin of chili pepper.

    PubMed

    Naccarato, Attilio; Furia, Emilia; Sindona, Giovanni; Tagarelli, Antonio

    2016-09-01

    Four class-modeling techniques (soft independent modeling of class analogy (SIMCA), unequal dispersed classes (UNEQ), potential functions (PF), and multivariate range modeling (MRM)) were applied to multielement distribution to build chemometric models able to authenticate chili pepper samples grown in Calabria respect to those grown outside of Calabria. The multivariate techniques were applied by considering both all the variables (32 elements, Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Fe, Ga, La, Li, Mg, Mn, Na, Nd, Ni, Pb, Pr, Rb, Sc, Se, Sr, Tl, Tm, V, Y, Yb, Zn) and variables selected by means of stepwise linear discriminant analysis (S-LDA). In the first case, satisfactory and comparable results in terms of CV efficiency are obtained with the use of SIMCA and MRM (82.3 and 83.2% respectively), whereas MRM performs better than SIMCA in terms of forced model efficiency (96.5%). The selection of variables by S-LDA permitted to build models characterized, in general, by a higher efficiency. MRM provided again the best results for CV efficiency (87.7% with an effective balance of sensitivity and specificity) as well as forced model efficiency (96.5%). PMID:27041319

  8. Aspirations and Expectations of West Malaysian Youth: Two Models of Social Class Values

    ERIC Educational Resources Information Center

    Takei, Yoshimitsu; And Others

    1973-01-01

    While the occupational aspirations of Malay and Chinese male students in the secondary schools reveal fairly similar configurations, the socio-economic expectations of Malays are higher and largely independent of social class origins. (Authors)

  9. Heterotopic expression of class B floral homeotic genes supports a modified ABC model for tulip (Tulipa gesneriana).

    PubMed

    Kanno, Akira; Saeki, Hiroshi; Kameya, Toshiaki; Saedler, Heinz; Theissen, Günter

    2003-07-01

    In higher eudicotyledonous angiosperms the floral organs are typically arranged in four different whorls, containing sepals, petals, stamens and carpels. According to the ABC model, the identity of these organs is specified by floral homeotic genes of class A, A+B, B+C and C, respectively. In contrast to the sepal and petal whorls of eudicots, the perianths of many plants from the Liliaceae family have two outer whorls of almost identical petaloid organs, called tepals. To explain the Liliaceae flower morphology, van Tunen et al. (1993) proposed a modified ABC model, exemplified with tulip. According to this model, class B genes are not only expressed in whorls 2 and 3, but also in whorl 1. Thus the organs of both whorls 1 and 2 express class A plus class B genes and, therefore, get the same petaloid identity. To test this modified ABC model we have cloned and characterized putative class B genes from tulip. Two DEF- and one GLO-like gene were identified, named TGDEFA, TGDEFB and TGGLO. Northern hybridization analysis showed that all of these genes are expressed in whorls 1, 2 and 3 (outer and inner tepals and stamens), thus corroborating the modified ABC model. In addition, these experiments demonstrated that TGGLO is also weakly expressed in carpels, leaves, stems and bracts. Gel retardation assays revealed that TGGLO alone binds to DNA as a homodimer. In contrast, TGDEFA and TGDEFB cannot homodimerize, but make heterodimers with PI. Homodimerization of GLO-like protein has also been reported for lily, suggesting that this phenomenon is conserved within Liliaceae plants or even monocot species.

  10. 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

  11. 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

  12. Common Mental Disorders among Occupational Groups: Contributions of the Latent Class Model.

    PubMed

    Bernardes Santos, Kionna Oliveira; Martins Carvalho, Fernando; de Araújo, Tânia Maria

    2016-01-01

    Background. The Self-Reporting Questionnaire (SRQ-20) is widely used for evaluating common mental disorders. However, few studies have evaluated the SRQ-20 measurements performance in occupational groups. This study aimed to describe manifestation patterns of common mental disorders symptoms among workers populations, by using latent class analysis. Methods. Data derived from 9,959 Brazilian workers, obtained from four cross-sectional studies that used similar methodology, among groups of informal workers, teachers, healthcare workers, and urban workers. Common mental disorders were measured by using SRQ-20. Latent class analysis was performed on each database separately. Results. Three classes of symptoms were confirmed in the occupational categories investigated. In all studies, class I met better criteria for suspicion of common mental disorders. Class II discriminated workers with intermediate probability of answers to the items belonging to anxiety, sadness, and energy decrease that configure common mental disorders. Class III was composed of subgroups of workers with low probability to respond positively to questions for screening common mental disorders. Conclusions. Three patterns of symptoms of common mental disorders were identified in the occupational groups investigated, ranging from distinctive features to low probabilities of occurrence. The SRQ-20 measurements showed stability in capturing nonpsychotic symptoms. PMID:27630999

  13. Common Mental Disorders among Occupational Groups: Contributions of the Latent Class Model

    PubMed Central

    Martins Carvalho, Fernando; de Araújo, Tânia Maria

    2016-01-01

    Background. The Self-Reporting Questionnaire (SRQ-20) is widely used for evaluating common mental disorders. However, few studies have evaluated the SRQ-20 measurements performance in occupational groups. This study aimed to describe manifestation patterns of common mental disorders symptoms among workers populations, by using latent class analysis. Methods. Data derived from 9,959 Brazilian workers, obtained from four cross-sectional studies that used similar methodology, among groups of informal workers, teachers, healthcare workers, and urban workers. Common mental disorders were measured by using SRQ-20. Latent class analysis was performed on each database separately. Results. Three classes of symptoms were confirmed in the occupational categories investigated. In all studies, class I met better criteria for suspicion of common mental disorders. Class II discriminated workers with intermediate probability of answers to the items belonging to anxiety, sadness, and energy decrease that configure common mental disorders. Class III was composed of subgroups of workers with low probability to respond positively to questions for screening common mental disorders. Conclusions. Three patterns of symptoms of common mental disorders were identified in the occupational groups investigated, ranging from distinctive features to low probabilities of occurrence. The SRQ-20 measurements showed stability in capturing nonpsychotic symptoms.

  14. Common Mental Disorders among Occupational Groups: Contributions of the Latent Class Model

    PubMed Central

    Martins Carvalho, Fernando; de Araújo, Tânia Maria

    2016-01-01

    Background. The Self-Reporting Questionnaire (SRQ-20) is widely used for evaluating common mental disorders. However, few studies have evaluated the SRQ-20 measurements performance in occupational groups. This study aimed to describe manifestation patterns of common mental disorders symptoms among workers populations, by using latent class analysis. Methods. Data derived from 9,959 Brazilian workers, obtained from four cross-sectional studies that used similar methodology, among groups of informal workers, teachers, healthcare workers, and urban workers. Common mental disorders were measured by using SRQ-20. Latent class analysis was performed on each database separately. Results. Three classes of symptoms were confirmed in the occupational categories investigated. In all studies, class I met better criteria for suspicion of common mental disorders. Class II discriminated workers with intermediate probability of answers to the items belonging to anxiety, sadness, and energy decrease that configure common mental disorders. Class III was composed of subgroups of workers with low probability to respond positively to questions for screening common mental disorders. Conclusions. Three patterns of symptoms of common mental disorders were identified in the occupational groups investigated, ranging from distinctive features to low probabilities of occurrence. The SRQ-20 measurements showed stability in capturing nonpsychotic symptoms. PMID:27630999

  15. 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.

  16. 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 PAGESBeta

    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

  17. Leukocyte Ig-Like Receptors – A Model for MHC Class I Disease Associations

    PubMed Central

    Hudson, Laura Emily; Allen, Rachel Louise

    2016-01-01

    MHC class I (MHC-I) polymorphisms are associated with the outcome of some viral infections and autoimmune diseases. MHC-I proteins present antigenic peptides and are recognized by receptors on natural killer cells and cytotoxic T lymphocytes, thus enabling the immune system to detect self-antigens and eliminate targets lacking self or expressing foreign antigens. Recognition of MHC-I, however, extends beyond receptors on cytotoxic leukocytes. Members of the leukocyte Ig-like receptor (LILR) family are expressed on monocytic cells and can recognize both classical and non-classical MHC-I alleles. Despite their relatively broad specificity when compared to the T cell receptor or killer Ig-like receptors, variations in the strength of LILR binding between different MHC-I alleles have recently been shown to correlate with control of HIV infection. We suggest that LILR recognition may mediate MHC-I disease association in a manner that does not depend on a binary discrimination of self/non-self by cytotoxic cells. Instead, the effects of LILR activity following engagement by MHC-I may represent a “degrees of self” model, whereby strength of binding to different alleles determines the degree of influence exerted by these receptors on immune cell functions. LILRs are expressed by myelomonocytic cells and lymphocytes, extending their influence across antigen-presenting cell subsets including dendritic cells, macrophages, and B cells. They have been identified as important players in the response to infection, inflammatory diseases, and cancer, with recent literature to indicate that MHC-I recognition by these receptors and consequent allelic effects could extend an influence beyond the immune system. PMID:27504110

  18. Modelling and analysis of a high-performance Class D audio amplifier using unipolar pulse-width-modulation

    NASA Astrophysics Data System (ADS)

    Zhou, Zekun; Shi, Yue; Ming, Xin; Zhang, Bo; Li, Zhaoji; Chen, Zao

    2012-02-01

    A high-performance class D audio amplifier using unipolar pulse-width-modulation (PWM) with double-sided natural sampling is presented in this article. In order to comprehend and design the system properly, the class D audio amplifier is modelled and analysed. A wide range triangle-wave signal with good linearity and magnitude proportional to supply voltage is embedded in the proposed class D audio amplifier for maximum output power, high power supply rejection ratio (PSRR) and low total harmonic distortion (THD). Design results based on CSMC 0.5-µm 5-V complementary metal-oxide-semiconductor process demonstrate that the proposed class D audio amplifier can operate with supply voltage in the range 2.4-5.5 V and supports 2.8 W output power from a 5.5 V supply; the maximum efficiency is above 95%, the PSRR is -82 dB, the signal-to-noise ratio (SNR) is 97 dB and the total harmonic distortion plus noise (THD+N) is less than 0.1% between 20 and 20 kHz with output power 0.4 W; the quiescent current without load is 1.8 mA, and the shutdown current is 0.01 µA. The active area of the class-D audio power amplifier is 1.5 mm × 1.5 mm.

  19. NK Cell Responsiveness is Tuned Commensurate with the Number of Inhibitory Receptors for Self MHC Class I: the Rheostat Model

    PubMed Central

    Joncker, Nathalie T.; Fernandez, Nadine C.; Treiner, Emmanuel; Vivier, Eric; Raulet, David H.

    2010-01-01

    Inhibitory receptors that engage self-MHC class I molecules enable NK cells to detect disease-associated loss of MHC class I on surrounding cells. Previous studies showed that some NK cells lack all receptors for self-MHC class I, yet fail to exhibit autoimmunity because they are generally hyporesponsive to stimulation. We asked whether NK cells exist in only two states, responsive and hyporesponsive, corresponding to cells that express or fail to express inhibitory receptors for self-MHC class I. The alternative model is that NK cells vary continuously in their responsiveness, based on variations in the number of different inhibitory and stimulatory receptors they express, which is known to vary. Here we show in the murine system that NK cell responsiveness increases quantitatively with each added self MHC-specific inhibitory receptor. Genetic analysis demonstrated that interactions of each of the receptors with self-MHC class I were necessary to observe augmented responsiveness. These findings suggest that NK cell responsiveness is comparable to a rheostat: it is tuned to an optimal set point depending on the inhibitory and stimulatory interactions encountered in the normal environment, so as to ensure self-tolerance and yet optimize sensitivity to changes in normal cells. PMID:19342631

  20. The major histocompatibility class I locus in Atlantic salmon (Salmo salar L.): polymorphism, linkage analysis and protein modelling.

    PubMed

    Grimholt, Unni; Drabløs, Finn; Jørgensen, Sven Martin; Høyheim, Bjørn; Stet, René J M

    2002-11-01

    A cDNA library screening using the conserved exon 4 of Atlantic salmon Mhc class I as probe provided the basis for a study on Mhc class I polymorphism in a breeding population. Twelve different alleles were identified in the 82 dams and sires studied. No individual expressed more than two alleles, which corresponded to the diploid segregation patterns of the polymorphic marker residing within the 3'-untranslated tail. Close linkage between the Sasa-UBA and Sasa-TAP2B loci strengthens the claim that Sasa-UBA is the major Mhc class I locus in Atlantic salmon. We found no evidence for a second expressed classical or non-classical Mhc class I locus in Atlantic salmon. A phylogenetic analysis of salmonid Mhc class I sequences showed domains conserved between rainbow trout, brown trout and Atlantic salmon. Evidence for shuffling of the alpha(1) domain was identified and lineages of the remaining alpha(2) through the cytoplasmic tail gene segment can be defined. The coding sequence of one allele was found associated with two different markers, suggesting recombination within the 3'-tail dinucleotide repeat itself. Protein modelling of several Sasa-UBA alleles shows distinct differences in their peptide binding domains and enables a further understanding of the functionality of the high polymorphism. PMID:12439620

  1. Numerical study of two classes of cellular automaton models for traffic flow on a two-lane roadway

    NASA Astrophysics Data System (ADS)

    Moussa, N.; Daoudia, A. K.

    2003-02-01

    In this paper, we present computer simulation results of traffic flow on a two-lane roadway with different types of vehicles, cars and trucks for example. We consider two classes of two-lane traffic cellular automaton models, namely the well known Nagel-Schreckenberg model and an extension of the Fukui-Ishibashi model. These two models, which differ in their acceleration limits, show an important differences in their fundamental diagrams, lane-changing and ping-pong behaviors. Moreover, we investigate the importance of braking noise and the proportion of trucks on the traffic flow of a two-lane roadway.

  2. 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)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; 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.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; 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.; 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.; Barisonzi, M.; 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.; 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.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; 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, J.; 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.; 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.; Bousson, N.; 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.; 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.; Butt, A. I.; 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.; 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, 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. 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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.

  3. 2 TeV walking technirho at LHC?

    NASA Astrophysics Data System (ADS)

    Fukano, Hidenori S.; Kurachi, Masafumi; Matsuzaki, Shinya; Terashi, Koji; Yamawaki, Koichi

    2015-11-01

    The ATLAS collaboration has recently reported an excess of about 2.5 σ global significance at around 2 TeV in the diboson channel with the boson-tagged fat dijets, which may imply a new resonance beyond the standard model. We provide a possible explanation of the excess as the isospin-triplet technivector mesons (technirhos, denoted as ρΠ±,3) of the walking technicolor in the case of the one-family model as a benchmark. As the effective theory for the walking technicolor at the scales relevant to the LHC experiment, we take a scale-invariant version of the hidden local symmetry model so constructed as to accommodate technipions, technivector mesons, and the technidilaton in such a way that the model respects spontaneously broken chiral and scale symmetries of the underlying walking technicolor. In particular, the technidilaton, a (pseudo) Nambu-Goldstone boson of the (approximate) scale symmetry predicted in the walking technicolor, has been shown to be successfully identified with the 125 GeV Higgs. Currently available LHC limits on those technihadrons are used to fix the couplings of technivector mesons to the standard-model fermions and weak gauge bosons. We find that the technirhos are mainly produced through the Drell-Yan process and predominantly decay to the dibosons, which accounts for the currently reported excess at around 2 TeV. The consistency with the electroweak precision test and other possible discovery channels of the 2 TeV technirhos are also addressed.

  4. CONSTRAINTS ON THE GALACTIC POPULATION OF TeV PULSAR WIND NEBULAE USING FERMI LARGE AREA TELESCOPE OBSERVATIONS

    SciTech Connect

    Acero, F.; Brandt, T. J.; Ackermann, M.; Ajello, M.; Allafort, A.; Bechtol, K.; Blandford, R. D.; Bloom, E. D.; Bottacini, E.; Buehler, R.; Baldini, L.; Ballet, J.; Bastieri, D.; Buson, S.; Bellazzini, R.; Bregeon, J.; Bonamente, E.; Brigida, M.; Bruel, P. E-mail: joshualande@gmail.com E-mail: rousseau@cenbg.in2p3.fr [Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS and others

    2013-08-10

    Pulsar wind nebulae (PWNe) have been established as the most populous class of TeV {gamma}-ray emitters. Since launch, the Fermi Large Area Telescope (LAT) has identified five high-energy (100 MeV < E < 100 GeV) {gamma}-ray sources as PWNe and detected a large number of PWN candidates, all powered by young and energetic pulsars. The wealth of multi-wavelength data available and the new results provided by Fermi-LAT give us an opportunity to find new PWNe and to explore the radiative processes taking place in known ones. The TeV {gamma}-ray unidentified (UNID) sources are the best candidates for finding new PWNe. Using 45 months of Fermi-LAT data for energies above 10 GeV, an analysis was performed near the position of 58 TeV PWNe and UNIDs within 5 Degree-Sign of the Galactic plane to establish new constraints on PWN properties and find new clues on the nature of UNIDs. Of the 58 sources, 30 were detected, and this work provides their {gamma}-ray fluxes for energies above 10 GeV. The spectral energy distributions and upper limits, in the multi-wavelength context, also provide new information on the source nature and can help distinguish between emission scenarios, i.e., between classification as a pulsar candidate or as a PWN candidate. Six new GeV PWN candidates are described in detail and compared with existing models. A population study of GeV PWN candidates as a function of the pulsar/PWN system characteristics is presented.

  5. Phenotyping chronic pelvic pain based on latent class modeling of physical examination.

    PubMed

    Fenton, B W; Grey, S F; Reichenbach, M; McCarroll, M; Von Gruenigen, V

    2013-01-01

    Introduction. Defining clinical phenotypes based on physical examination is required for clarifying heterogeneous disorders such as chronic pelvic pain (CPP). The objective of this study was to determine the number of classes within 4 examinable regions and then establish threshold and optimal exam criteria for the classes discovered. Methods. A total of 476 patients meeting the criteria for CPP were examined using pain pressure threshold (PPT) algometry and standardized numeric scale (NRS) pain ratings at 30 distinct sites over 4 pelvic regions. Exploratory factor analysis, latent profile analysis, and ROC curves were then used to identify classes, optimal examination points, and threshold scores. Results. Latent profile analysis produced two classes for each region: high and low pain groups. The optimal examination sites (and high pain minimum thresholds) were for the abdominal wall region: the pair at the midabdomen (PPT threshold depression of > 2); vulvar vestibule region: 10:00 position (NRS > 2); pelvic floor region: puborectalis (combined NRS > 6); vaginal apex region: uterosacral ligaments (combined NRS > 8). Conclusion. Physical examination scores of patients with CPP are best categorized into two classes: high pain and low pain. Standardization of the physical examination in CPP provides both researchers and general gynecologists with a validated technique.

  6. Avalanches in Self-Organized Critical Neural Networks: A Minimal Model for the Neural SOC Universality Class

    PubMed Central

    Rybarsch, Matthias; Bornholdt, Stefan

    2014-01-01

    The brain keeps its overall dynamics in a corridor of intermediate activity and it has been a long standing question what possible mechanism could achieve this task. Mechanisms from the field of statistical physics have long been suggesting that this homeostasis of brain activity could occur even without a central regulator, via self-organization on the level of neurons and their interactions, alone. Such physical mechanisms from the class of self-organized criticality exhibit characteristic dynamical signatures, similar to seismic activity related to earthquakes. Measurements of cortex rest activity showed first signs of dynamical signatures potentially pointing to self-organized critical dynamics in the brain. Indeed, recent more accurate measurements allowed for a detailed comparison with scaling theory of non-equilibrium critical phenomena, proving the existence of criticality in cortex dynamics. We here compare this new evaluation of cortex activity data to the predictions of the earliest physics spin model of self-organized critical neural networks. We find that the model matches with the recent experimental data and its interpretation in terms of dynamical signatures for criticality in the brain. The combination of signatures for criticality, power law distributions of avalanche sizes and durations, as well as a specific scaling relationship between anomalous exponents, defines a universality class characteristic of the particular critical phenomenon observed in the neural experiments. Thus the model is a candidate for a minimal model of a self-organized critical adaptive network for the universality class of neural criticality. As a prototype model, it provides the background for models that may include more biological details, yet share the same universality class characteristic of the homeostasis of activity in the brain. PMID:24743324

  7. Avalanches in self-organized critical neural networks: a minimal model for the neural SOC universality class.

    PubMed

    Rybarsch, Matthias; Bornholdt, Stefan

    2014-01-01

    The brain keeps its overall dynamics in a corridor of intermediate activity and it has been a long standing question what possible mechanism could achieve this task. Mechanisms from the field of statistical physics have long been suggesting that this homeostasis of brain activity could occur even without a central regulator, via self-organization on the level of neurons and their interactions, alone. Such physical mechanisms from the class of self-organized criticality exhibit characteristic dynamical signatures, similar to seismic activity related to earthquakes. Measurements of cortex rest activity showed first signs of dynamical signatures potentially pointing to self-organized critical dynamics in the brain. Indeed, recent more accurate measurements allowed for a detailed comparison with scaling theory of non-equilibrium critical phenomena, proving the existence of criticality in cortex dynamics. We here compare this new evaluation of cortex activity data to the predictions of the earliest physics spin model of self-organized critical neural networks. We find that the model matches with the recent experimental data and its interpretation in terms of dynamical signatures for criticality in the brain. The combination of signatures for criticality, power law distributions of avalanche sizes and durations, as well as a specific scaling relationship between anomalous exponents, defines a universality class characteristic of the particular critical phenomenon observed in the neural experiments. Thus the model is a candidate for a minimal model of a self-organized critical adaptive network for the universality class of neural criticality. As a prototype model, it provides the background for models that may include more biological details, yet share the same universality class characteristic of the homeostasis of activity in the brain.

  8. Search for the standard model Higgs boson in the decay channel $H$ to $Z Z$ to 4 leptons in $pp$ collisions at $\\sqrt{s}=7$ TeV

    SciTech Connect

    Chatrchyan, Serguei; et al.

    2012-03-01

    A search for a Higgs boson in the four-lepton decay channel H to ZZ, with each Z boson decaying to an electron or muon pair, is reported. The search covers Higgs boson mass hypotheses in the range 110 < mH < 600 GeV. The analysis uses data corresponding to an integrated luminosity of 4.7 inverse femtobarns recorded by the CMS detector in pp collisions at sqrt(s) = 7 TeV from the LHC. Seventy-two events are observed with four-lepton invariant mass m[4 leptons] > 100 GeV (with thirteen 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 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.

  9. Search for the production of the standard model z boson in association with W± boson in proton anti-p collisions at 1.96 TeV center of mass energy

    SciTech Connect

    Keung, Justin Kien

    2010-01-01

    The search for the production of the Standard Model Z boson in association with a W boson is motivated and discussed. This is performed using 4.3 fb-1 of Tevatron Run II data collected with the CDF detector in √s = 1.96 TeV proton anti-proton collisions. This is a signature-based analysis where the W boson decays semileptonically into a high-PT electron or muon plus a neutrino, and where the Z boson decays into two b quark jets (b-jets). We increase the signal-to-background ratio by identifying the b-quarks in the jets with a new neural network-based algorithm. Another neural network then uses kinematic information to distinguish WZ to further increase the signal-to-background ratio. Since our sensitivity is still not enough to achieve an observation, we set a 95% Confidence Level upper limit on the product of the WZ production cross section and its branching fraction to the decay products specified above, and express it as a ratio to the theoretical Standard Model prediction. The resulting limit is 3.9 x SM (3.9 x SM expected).

  10. Search for the Standard Model Higgs Boson in ZH → v$\\bar{v}$b$\\bar{b}$ channel in p$\\bar{p}$ collisions at √s= 1.96 TeV

    SciTech Connect

    Dubey, Abhinav

    2011-01-01

    A search for the standard model Higgs boson is performed in 5.2 fb-1 of p$\\bar{p}$ collisions at p √s = 1.96 TeV, collected with the DØ detector at the Fermilab Tevatron. The final state considered is a pair of b jets with large missing transverse energy, as expected from p$\\bar{p}$→ ZH → v$\\bar{v}$b$\\bar{b}$ production. The search is also sensitive to the WH → ℓvb$\\bar{b}$ channel, where the charged lepton is not identified. Boosted decision trees are used to discriminate signal from background. Good agreement is observed between data and expected backgrounds, and, for a Higgs-boson mass of 115 GeV, a limit is set at 95% C.L. on the cross section multiplied by branching fraction of (p$\\bar{p}$ → (Z/W)H) × (H → b$\\bar{b}$) that is a factor 4.57 expected and 3.73 observed larger than the value expected from the standard model.

  11. Search for the Standard Model Higgs Boson in Missing Transverse Energy and $b$-quark Final States Using Proton-Antiproton Collisions at 1.96 TeV

    SciTech Connect

    Dorland, Tyler McMillan

    2011-01-01

    A search for the standard model Higgs boson is performed in 6.4 fb-1 of p$\\bar{p}$ collisions at √s = 1.96 TeV, collected with the DØ detector during Run II of the Fermilab Tevatron. The final state considered is a pair of jets originating from b quarks and missing transverse energy, as expected from p$\\bar{p}$ → ZH → v$\\bar{v}$b$\\bar{b}$ production. The search is also sensitive to the WH → ℓvb$\\bar{b}$ channel, where the charged lepton is not identified. Boosted decision trees are used to discriminate signal from background. Good agreement is observed between data and expected backgrounds, and a limit is set at 95% C.L. on the section multiplied by branching fraction of (p$\\bar{p}$ → (Z/W)H) x (H → b$\\bar{b}$). For a Higgs boson mass of 115 GeV, the observed limit is a factor of 3.5 larger than the value expected from the standard model.

  12. Search for the Standard Model Higgs Boson in the Diphoton Final State in $p\\bar{p}$ Collisions at $\\sqrt{s}$ = 1.96 TeV Using the CDF II Detector

    SciTech Connect

    Bland, Karen Renee

    2012-01-01

    We present a search for the Standard Model Higgs boson decaying into a pair of photons produced in p$p\\bar{p}$ collisions with a center of mass energy of 1.96 TeV. The results are based on data corresponding to an integrated luminosity of 10 fb-1 collected by the CDF II detector. Higgs boson candidate events are identified by reconstructing two photons in either the central or plug regions of the detector. The acceptance for identifying photons is significantly increased by using a new algorithm designed to reconstruct photons in the central region that have converted to an electron-positron pair. In addition, a new neural network discriminant is employed to improve the identification of non-converting central photons. No evidence for the Higgs boson is observed in the data, and we set an upper limit on the cross section for Higgs boson production multiplied by the H → γγ branching ratio. For a Higgs boson mass of 125 GeV/c 2 , we obtain an observed (expected) limit of 12.2 (10.8) times the Standard Model prediction at the 95% credibility level.

  13. Search for the standard model Higgs boson in the ZH->vvbb channel in 5.2 fb-1 of p-pbar collisions at sqrt(s)=1.96 TeV

    SciTech Connect

    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.; /Northeastern U. /Rio de Janeiro, CBPF

    2009-12-01

    A search is performed for the standard model Higgs boson in 5.2 fb{sup -1} of p{bar p} collisions at {radical}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 p{bar p} {yields} ZH {yields} {nu}{bar {nu}}b{bar b} production. The search is also sensitive to the WH {yields} {ell}{nu}b{bar b} 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 (p{bar p} {yields} (Z/W)H) x (H {yields} b{bar b}) that is a factor of 3.7 larger than the standard model value, consistent with the factor of 4.6 expected.

  14. Search for New Phenomena in Dijet Angular Distributions in Proton-Proton Collisions at sqrt[s]=8 TeV Measured with the ATLAS Detector.

    PubMed

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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; 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; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; 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, 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

    2015-06-01

    A search for new phenomena in LHC proton-proton collisions at a center-of-mass energy of sqrt[s]=8 TeV was performed with the ATLAS detector using an integrated luminosity of 17.3 fb^{-1}. The angular distributions are studied in events with at least two jets; the highest dijet mass observed is 5.5 TeV. All angular distributions are consistent with the predictions of the standard model. In a benchmark model of quark contact interactions, a compositeness scale below 8.1 TeV in a destructive interference scenario and 12.0 TeV in a constructive interference scenario is excluded at 95% C.L.; median expected limits are 8.9 TeV for the destructive interference scenario and 14.1 TeV for the constructive interference scenario. PMID:26196615

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

    DOE PAGESBeta

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; et al

    2015-06-04

    A search for new phenomena in LHC proton-proton collisions at a center-of-mass energy of √s=8 TeV was performed with the ATLAS detector using an integrated luminosity of 17.3 fb⁻¹. The angular distributions are studied in events with at least two jets; the highest dijet mass observed is 5.5 TeV. All angular distributions are consistent with the predictions of the standard model. In a benchmark model of quark contact interactions, a compositeness scale below 8.1 TeV in a destructive interference scenario and 12.0 TeV in a constructive interference scenario is excluded at 95% C.L.; median expected limits are 8.9 TeV formore » the destructive interference scenario and 14.1 TeV for the constructive interference scenario.« less

  16. Search for New Phenomena in Dijet Angular Distributions in Proton-Proton Collisions at √{s }=8 TeV Measured 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.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimoto, G.; 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.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Balek, P.; Balestri, T.; Balli, F.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. 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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.; Bieniek, S. P.; Biglietti, M.; Bilbao de Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; 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.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. 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F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B. C.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Childers, J. T.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Citron, Z. H.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Cole, B.; Cole, S.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; 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 Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; 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.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Ciaccio, A.; di Ciaccio, L.; di Domenico, A.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Mattia, A.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrag, S.; Ferrando, J.; 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.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Flowerdew, M. J.; Formica, A.; Forti, A.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Fraternali, M.; Freeborn, D.; French, S. T.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gao, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; Garberson, F.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gauzzi, P.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Ge, P.; Gecse, Z.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Geisler, M. P.; Gemme, C.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerbaudo, D.; Gershon, A.; Ghazlane, H.; Giacobbe, B.; Giagu, S.; Giangiobbe, V.; Giannetti, P.; Gibbard, B.; Gibson, S. M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Goddard, J. R.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, L.; González de La Hoz, S.; Gonzalez Parra, G.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Grabas, H. M. X.; Graber, L.; Grabowska-Bold, I.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Graziani, E.; Greenwood, Z. D.; 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.; Gupta, S.; Gutierrez, P.; Gutierrez Ortiz, N. 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E.; Primavera, M.; Prince, S.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopapadaki, E.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Ptacek, E.; Puddu, D.; Pueschel, E.; Puldon, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Raymond, M.; Read, A. L.; Readioff, N. P.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reisin, H.; Relich, M.; Rembser, C.; Ren, H.; Renaud, A.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Roe, S.; Røhne, O.; Rolli, S.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosendahl, P. L.; Rosenthal, O.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rubinskiy, I.; Rud, V. I.; Rudolph, C.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryder, N. C.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Saddique, A.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saimpert, M.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Saleem, M.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; 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.; Schmidt, E.; 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.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Schwoerer, M.; 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.; Selbach, K. E.; 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.; 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.; Simoniello, R.; Sinervo, P.; Sinev, N. B.; 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.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; 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.; Soueid, P.; Soukharev, A. M.; South, D.; Spagnolo, S.; Spalla, M.; Spanò, F.; Spearman, W. R.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Spreitzer, T.; St. Denis, R. D.; 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.; Stavina, P.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stern, S.; 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.; Suhr, C.; 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.; Suzuki, Y.; Svatos, M.; Swedish, S.; 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, W.; Teischinger, F. A.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Therhaag, 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.; 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.; True, P.; 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.; Uhlenbrock, 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 der Leeuw, R.; 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.; 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, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; 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, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yao, L.; 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.; 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.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; 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, 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.; Atlas Collaboration

    2015-06-01

    A search for new phenomena in LHC proton-proton collisions at a center-of-mass energy of √{s }=8 TeV was performed with the ATLAS detector using an integrated luminosity of 17.3 fb-1 . The angular distributions are studied in events with at least two jets; the highest dijet mass observed is 5.5 TeV. All angular distributions are consistent with the predictions of the standard model. In a benchmark model of quark contact interactions, a compositeness scale below 8.1 TeV in a destructive interference scenario and 12.0 TeV in a constructive interference scenario is excluded at 95% C.L.; median expected limits are 8.9 TeV for the destructive interference scenario and 14.1 TeV for the constructive interference scenario.

  17. Codon-substitution models to detect adaptive evolution that account for heterogeneous selective pressures among site classes.

    PubMed

    Yang, Ziheng; Swanson, Willie J

    2002-01-01

    The nonsynonymous to synonymous substitution rate ratio (omega = d(N)/d(S)) provides a sensitive measure of selective pressure at the protein level, with omega values <1, =1, and >1 indicating purifying selection, neutral evolution, and diversifying selection, respectively. Maximum likelihood models of codon substitution developed recently account for variable selective pressures among amino acid sites by employing a statistical distribution for the omega ratio among sites. Those models, called random-sites models, are suitable when we do not know a priori which sites are under what kind of selective pressure. Sometimes prior information (such as the tertiary structure of the protein) might be available to partition sites in the protein into different classes, which are expected to be under different selective pressures. It is then sensible to use such information in the model. In this paper, we implement maximum likelihood models for prepartitioned data sets, which account for the heterogeneity among site partitions by using different omega parameters for the partitions. The models, referred to as fixed-sites models, are also useful for combined analysis of multiple genes from the same set of species. We apply the models to data sets of the major histocompatibility complex (MHC) class I alleles from human populations and of the abalone sperm lysin genes. Structural information is used to partition sites in MHC into two classes: those in the antigen recognition site (ARS) and those outside. Positive selection is detected in the ARS by the fixed-sites models. Similarly, sites in lysin are classified into the buried and solvent-exposed classes according to the tertiary structure, and positive selection was detected at the solvent-exposed sites. The random-sites models identified a number of sites under positive selection in each data set, confirming and elaborating the results of the fixed-sites models. The analysis demonstrates the utility of the fixed-sites models

  18. "Racializing" Class

    ERIC Educational Resources Information Center

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

    2003-01-01

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

  19. TeV scale dark matter and electroweak radiative corrections

    SciTech Connect

    Ciafaloni, Paolo; Urbano, Alfredo

    2010-08-15

    Recent anomalies in cosmic rays data, namely, from the PAMELA Collaboration, can be interpreted in terms of TeV scale decaying/annihilating dark matter. We analyze the impact of radiative corrections coming from the electroweak sector of the standard model on the spectrum of the final products at the interaction point. As an example, we consider virtual one loop corrections and real gauge bosons emission in the case of a very heavy vector boson annihilating into fermions. We find electroweak corrections that are relevant, but not as big as sometimes found in the literature; we relate this mismatch to the issue of gauge invariance. At scales much higher than the symmetry breaking scale, one loop electroweak effects are so big that eventually higher orders/resummations have to be considered: we advocate for the inclusion of these effects in parton shower Monte Carlo models aiming at the description of TeV scale physics.

  20. Dual topological unitarization of hard and soft hadronic cross sections: A new approach to multiparticle production at hadron colliders in the TeV energy range

    SciTech Connect

    Ranft, J.; Hahn, K. . SSC Central Design Group); Aurenche, P.; Maire, P. . Lab. de Physique des Particules Elementaires); Bopp, F. . Fachbereich Physik); Capella, A.; Tran Thanh Van, J. . Lab. de Physique Theorique et Particules Elementaires); Kwi

    1987-12-01

    The dual topological unitarization of hard and soft hadronic collisions is formulated as a Monte-Carlo event generator for events containing both the soft (low p{perpendicular}) and hard (jets, minijets) component of hadron production. The parameters of the model are determined from fits to the energy dependence of the total and inelastic hadron cross-sections and from the predictions of the QCD-parton model for the perturbative hard constituent scattering cross sections. The properties of the model are studied. Good agreement of the model predictions is found with data at present accelerator and collider energies. The predictions of the model for TeV colliders are presented. Interesting changes of the produced multiparticle system are formed when selecting classes of events with and without hard jets or minijets. 35 refs., 22 figs., 3 tabs.

  1. Numerical simulation of a class of models that combine several mechanisms of dissipation: Fracture, plasticity, viscous dissipation

    NASA Astrophysics Data System (ADS)

    Bonnetier, Eric; Jakabčin, Lukáš; Labbé, Stéphane; Replumaz, Anne

    2014-08-01

    We study a class of time evolution models that contain dissipation mechanisms exhibited by geophysical materials during deformation: plasticity, viscous dissipation and fracture. We formally prove that they satisfy a Clausius-Duhem type inequality. We describe a semi-discrete time evolution associated with these models, and report numerical 1D and 2D traction experiments, that illustrate that several dissipation regimes can indeed take place during the deformation. Finally, we report 2D numerical simulation of an experiment by Peltzer and Tapponnier, who studied the indentation of a layer of plasticine as an analogue model for geological materials.

  2. 40 CFR Table 3 to Subpart Bbbb of... - Model Rule-Class I Nitrogen Oxides Emission Limits for Existing Small Municipal Waste Combustion...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 6 2011-07-01 2011-07-01 false Model Rule-Class I Nitrogen Oxides... 3 to Subpart BBBB of Part 60—Model Rule—Class I Nitrogen Oxides Emission Limits for Existing Small... greater than 250 tons per day of municipal solid waste. See § 60.1940 for definitions. b Nitrogen...

  3. 40 CFR Table 3 to Subpart Bbbb of... - Model Rule-Class I Nitrogen Oxides Emission Limits for Existing Small Municipal Waste Combustion...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 7 2014-07-01 2014-07-01 false Model Rule-Class I Nitrogen Oxides... 3 to Subpart BBBB of Part 60—Model Rule—Class I Nitrogen Oxides Emission Limits for Existing Small... greater than 250 tons per day of municipal solid waste. See § 60.1940 for definitions. b Nitrogen...

  4. 40 CFR Table 3 to Subpart Bbbb of... - Model Rule-Class I Nitrogen Oxides Emission Limits for Existing Small Municipal Waste Combustion...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 7 2013-07-01 2013-07-01 false Model Rule-Class I Nitrogen Oxides... 3 to Subpart BBBB of Part 60—Model Rule—Class I Nitrogen Oxides Emission Limits for Existing Small... greater than 250 tons per day of municipal solid waste. See § 60.1940 for definitions. b Nitrogen...

  5. 40 CFR Table 3 to Subpart Bbbb of... - Model Rule-Class I Nitrogen Oxides Emission Limits for Existing Small Municipal Waste Combustion...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 6 2010-07-01 2010-07-01 false Model Rule-Class I Nitrogen Oxides... 3 to Subpart BBBB of Part 60—Model Rule—Class I Nitrogen Oxides Emission Limits for Existing Small... greater than 250 tons per day of municipal solid waste. See § 60.1940 for definitions. b Nitrogen...

  6. 40 CFR Table 3 to Subpart Bbbb of... - Model Rule-Class I Nitrogen Oxides Emission Limits for Existing Small Municipal Waste Combustion...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 7 2012-07-01 2012-07-01 false Model Rule-Class I Nitrogen Oxides... 3 to Subpart BBBB of Part 60—Model Rule—Class I Nitrogen Oxides Emission Limits for Existing Small... greater than 250 tons per day of municipal solid waste. See § 60.1940 for definitions. b Nitrogen...

  7. Impact of Full-Day Head Start Prekindergarten Class Model on Student Academic Performance, Cognitive Skills, and Learning Behaviors by the End of Grade 2. Evaluation Brief

    ERIC Educational Resources Information Center

    Zhao, Huafang; Modarresi, Shahpar

    2013-01-01

    This brief describes the impact of the Montgomery County (Maryland) Public Schools (MCPS) 2007-2008 full-day Head Start prekindergarten (pre-K) class model on student academic performance, cognitive skills, and learning behaviors by the end of Grade 2. This is the fourth impact study of the MCPS full-day Head Start pre-K class model. The following…

  8. Science/Technology/Society: Model Lessons for Secondary Social Studies Classes.

    ERIC Educational Resources Information Center

    LaRue, Robert D., Jr., Ed.

    This volume contains 36 lessons designed to be used in secondary social studies classes to introduce the science/technology/society (STS) themes and issues. While the first 11 lessons focus on general STS themes, the other 25 lessons cover specific STS issues that fall under such categories as population growth, water resources, world hunger, food…

  9. Following the Leader? Network Models of "World-Class" Universities on Twitter

    ERIC Educational Resources Information Center

    Shields, Robin

    2016-01-01

    Much research on higher education has discussed the positional competition induced by global rankings and the complementary concept of "world-class" universities. This paper investigates the network of social media communication between globally ranked universities. Specifically, it examines whether universities seek to preserve and…

  10. Urban Agriculture Programs on the Rise: Agriculture Education Model Can Reach Students Other Classes Leave Behind

    ERIC Educational Resources Information Center

    Fritsch, Julie M.

    2013-01-01

    Agricultural education begins with hands-on classroom and laboratory instruction. Because agriculture is such a broad topic, schools typically tailor agriculture class offerings to match the interests of the student population, needs of nearby businesses and industry, or topics relevant to their state's standard assessments. Within most…

  11. Views and Workshops of a Master's Class in Intercultural Competence: Mill's Model of Intercultural Action

    ERIC Educational Resources Information Center

    Ioannitou, Gina

    2010-01-01

    This paper is the result of a participative process in which the students of the Master's Degree "Didactique des Langues" (foreign language didactics) at Universite du Maine (Le Mans, France) explored through whole-class activities the field of intercultural dialog and intercultural competence teaching. Our approach to intercultural teaching…

  12. Eating Order: A 13-Week Trust Model Class for Dieting Casualties

    ERIC Educational Resources Information Center

    Jackson, Elizabeth G.

    2008-01-01

    Chronic dieting distorts eating behaviors and causes weight escalation. Desperation about losing weight results in pursuit of extreme weight loss measures. Instead of offering yet another diet, nutrition educators can teach chronic dieters (dieting casualties) to develop eating competence. Eating Order, a 13-week class for chronic dieters based on…

  13. An International Model of World-Class Education: The International Baccalaureate

    ERIC Educational Resources Information Center

    Hill, Ian

    2012-01-01

    This article posits that world-class education is international education, as defined by UNESCO, and presents International Baccalaureate (IB) programmes as examples of this phenomenon. It begins with the IB's 1960s origins in international schools, which educated the children of globally mobile parents who worked principally in the UN and its…

  14. Measurement of polarisation in collisions at = 7 TeV

    NASA Astrophysics Data System (ADS)

    Aaij, R.; Adeva, B.; Adinolfi, M.; Affolder, A.; Ajaltouni, Z.; Albrecht, J.; Alessio, F.; Alexander, M.; Ali, S.; Alkhazov, G.; Alvarez Cartelle, P.; Alves, A. A.; Amato, S.; Amerio, S.; Amhis, Y.; An, L.; Anderlini, L.; Anderson, J.; Andreassen, R.; Andreotti, M.; Andrews, J. E.; Appleby, R. B.; Aquines Gutierrez, O.; Archilli, F.; Artamonov, A.; Artuso, M.; Aslanides, E.; Auriemma, G.; Baalouch, M.; Bachmann, S.; Back, J. J.; Badalov, A.; Balagura, V.; Baldini, W.; Barlow, R. J.; Barschel, C.; Barsuk, S.; Barter, W.; Batozskaya, V.; Bauer, Th.; Bay, A.; Beddow, J.; Bedeschi, F.; Bediaga, I.; Belogurov, S.; Belous, K.; Belyaev, I.; Ben-Haim, E.; Bencivenni, G.; Benson, S.; Benton, J.; Berezhnoy, A.; Bernet, R.; Bettler, M.-O.; van Beuzekom, M.; Bien, A.; Bifani, S.; Bird, T.; Bizzeti, A.; Bjørnstad, P. M.; Blake, T.; Blanc, F.; Blouw, J.; Blusk, S.; Bocci, V.; Bondar, A.; Bondar, N.; Bonivento, W.; Borghi, S.; Borgia, A.; Borsato, M.; Bowcock, T. J. V.; Bowen, E.; Bozzi, C.; Brambach, T.; van den Brand, J.; Bressieux, J.; Brett, D.; Britsch, M.; Britton, T.; Brook, N. H.; Brown, H.; Bursche, A.; Busetto, G.; Buytaert, J.; Cadeddu, S.; Calabrese, R.; Callot, O.; Calvi, M.; Calvo Gomez, M.; Camboni, A.; Campana, P.; Campora Perez, D.; Carbone, A.; Carboni, G.; Cardinale, R.; Cardini, A.; Carranza-Mejia, H.; Carson, L.; Carvalho Akiba, K.; Casse, G.; Cassina, L.; Castillo Garcia, L.; Cattaneo, M.; Cauet, Ch.; Cenci, R.; Charles, M.; Charpentier, Ph.; Cheung, S.-F.; Chiapolini, N.; Chrzaszcz, M.; Ciba, K.; Cid Vidal, X.; Ciezarek, G.; Clarke, P. E. L.; Clemencic, M.; Cliff, H. V.; Closier, J.; Coca, C.; Coco, V.; Cogan, J.; Cogneras, E.; Collins, P.; Comerma-Montells, A.; Contu, A.; Cook, A.; Coombes, M.; Coquereau, S.; Corti, G.; Corvo, M.; Counts, I.; Couturier, B.; Cowan, G. A.; Craik, D. C.; Cruz Torres, M.; Cunliffe, S.; Currie, R.; D'Ambrosio, C.; Dalseno, J.; David, P.; David, P. N. Y.; Davis, A.; De Bruyn, K.; De Capua, S.; De Cian, M.; De Miranda, J. M.; De Paula, L.; De Silva, W.; De Simone, P.; Decamp, D.; Deckenhoff, M.; Del Buono, L.; Déléage, N.; Derkach, D.; Deschamps, O.; Dettori, F.; Di Canto, A.; Dijkstra, H.; Donleavy, S.; Dordei, F.; Dorigo, M.; Dosil Suárez, A.; Dossett, D.; Dovbnya, A.; Dupertuis, F.; Durante, P.; Dzhelyadin, R.; Dziurda, A.; Dzyuba, A.; Easo, S.; Egede, U.; Egorychev, V.; Eidelman, S.; Eisenhardt, S.; Eitschberger, U.; Ekelhof, R.; Eklund, L.; El Rifai, I.; Elsasser, Ch.; Esen, S.; Evans, T.; Falabella, A.; Färber, C.; Farinelli, C.; Farry, S.; Ferguson, D.; Fernandez Albor, V.; Ferreira Rodrigues, F.; Ferro-Luzzi, M.; Filippov, S.; Fiore, M.; Fiorini, M.; Firlej, M.; Fitzpatrick, C.; Fiutowski, T.; Fontana, M.; Fontanelli, F.; Forty, R.; Francisco, O.; Frank, M.; Frei, C.; Frosini, M.; Fu, J.; Furfaro, E.; Gallas Torreira, A.; Galli, D.; Gandelman, M.; Gandini, P.; Gao, Y.; Garofoli, J.; Garra Tico, J.; Garrido, L.; Gaspar, C.; Gauld, R.; Gavardi, L.; Gersabeck, E.; Gersabeck, M.; Gershon, T.; Ghez, Ph.; Gianelle, A.; Giani, S.; Gibson, V.; Giubega, L.; Gligorov, V. V.; Göbel, C.; Golubkov, D.; Golutvin, A.; Gomes, A.; Gordon, H.; Gotti, C.; Grabalosa Gándara, M.; Graciani Diaz, R.; Granado Cardoso, L. A.; Graugés, E.; Graziani, G.; Grecu, A.; Greening, E.; Gregson, S.; Griffith, P.; Grillo, L.; Grünberg, O.; Gui, B.; Gushchin, E.; Guz, Yu.; Gys, T.; Hadjivasiliou, C.; Haefeli, G.; Haen, C.; Haines, S. C.; Hall, S.; Hamilton, B.; Hampson, T.; Han, X.; Hansmann-Menzemer, S.; Harnew, N.; Harnew, S. T.; Harrison, J.; Hartmann, T.; He, J.; Head, T.; Heijne, V.; Hennessy, K.; Henrard, P.; Henry, L.; Hernando Morata, J. A.; van Herwijnen, E.; Heß, M.; Hicheur, A.; Hill, D.; Hoballah, M.; Hombach, C.; Hulsbergen, W.; Hunt, P.; Hussain, N.; Hutchcroft, D.; Hynds, D.; Iakovenko, V.; Idzik, M.; Ilten, P.; Jacobsson, R.; Jaeger, A.; Jalocha, J.; Jans, E.; Jaton, P.; Jawahery, A.; Jezabek, M.; Jing, F.; John, M.; Johnson, D.; Jones, C. R.; Joram, C.; Jost, B.; Jurik, N.; Kaballo, M.; Kandybei, S.; Kanso, W.; Karacson, M.; Karbach, T. M.; Kelsey, M.; Kenyon, I. R.; Ketel, T.; Khanji, B.; Khurewathanakul, C.; Klaver, S.; Kochebina, O.; Kolpin, M.; Komarov, I.; Koopman, R. F.; Koppenburg, P.; Korolev, M.; Kozlinskiy, A.; Kravchuk, L.; Kreplin, K.; Kreps, M.; Krocker, G.; Krokovny, P.; Kruse, F.; Kucharczyk, M.; Kudryavtsev, V.; Kurek, K.; Kvaratskheliya, T.; La Thi, V. N.; Lacarrere, D.; Lafferty, G.; Lai, A.; Lambert, D.; Lambert, R. W.; Lanciotti, E.; Lanfranchi, G.; Langenbruch, C.; Latham, T.; Lazzeroni, C.; Le Gac, R.; van Leerdam, J.; Lees, J.-P.; Lefèvre, R.; Leflat, A.; Lefrançois, J.; Leo, S.; Leroy, O.; Lesiak, T.; Leverington, B.; Li, Y.; Liles, M.; Lindner, R.; Linn, C.; Lionetto, F.; Liu, B.; Liu, G.; Lohn, S.; Longstaff, I.; Longstaff, I.; Lopes, J. H.; Lopez-March, N.; Lowdon, P.; Lu, H.; Lucchesi, D.; Luisier, J.; Luo, H.; Lupato, A.; Luppi, E.; Lupton, O.; Machefert, F.; Machikhiliyan, I. V.; Maciuc, F.; Maev, O.; Malde, S.; Manca, G.; Mancinelli, G.; Manzali, M.; Maratas, J.; Marchand, J. F.; Marconi, U.; Marino, P.; Märki, R.; Marks, J.; Martellotti, G.; Martens, A.; Martín Sánchez, A.; Martinelli, M.; Martinez Santos, D.; Martinez Vidal, F.; Martins Tostes, D.; Massafferri, A.; Matev, R.; Mathe, Z.; Matteuzzi, C.; Mazurov, A.; McCann, M.; McCarthy, J.; McNab, A.; McNulty, R.; McSkelly, B.; Meadows, B.; Meier, F.; Meissner, M.; Merk, M.; Milanes, D. A.; Minard, M.-N.; Molina Rodriguez, J.; Monteil, S.; Moran, D.; Morandin, M.; Morawski, P.; Mordà, A.; Morello, M. J.; Moron, J.; Mountain, R.; Muheim, F.; Müller, K.; Muresan, R.; Muster, B.; Naik, P.; Nakada, T.; Nandakumar, R.; Nasteva, I.; Needham, M.; Neri, N.; Neubert, S.; Neufeld, N.; Neuner, M.; Nguyen, A. D.; Nguyen, T. D.; Nguyen-Mau, C.; Nicol, M.; Niess, V.; Niet, R.; Nikitin, N.; Nikodem, T.; Novoselov, A.; Oblakowska-Mucha, A.; Obraztsov, V.; Oggero, S.; Ogilvy, S.; Okhrimenko, O.; Oldeman, R.; Onderwater, G.; Orlandea, M.; Otalora Goicochea, J. M.; Owen, P.; Oyanguren, A.; Pal, B. K.; Palano, A.; Palombo, F.; Palutan, M.; Panman, J.; Papanestis, A.; Pappagallo, M.; Parkes, C.; Parkinson, C. J.; Passaleva, G.; Patel, G. D.; Patel, M.; Patrignani, C.; Pazos Alvarez, A.; Pearce, A.; Pellegrino, A.; Penso, G.; Pepe Altarelli, M.; Perazzini, S.; Perez Trigo, E.; Perret, P.; Perrin-Terrin, M.; Pescatore, L.; Pesen, E.; Petridis, K.; Petrolini, A.; Picatoste Olloqui, E.; Pietrzyk, B.; Pilař, T.; Pinci, D.; Pistone, A.; Playfer, S.; Plo Casasus, M.; Polci, F.; Polok, G.; Poluektov, A.; Polycarpo, E.; Popov, A.; Popov, D.; Popovici, B.; Potterat, C.; Powell, A.; Prisciandaro, J.; Pritchard, A.; Prouve, C.; Pugatch, V.; Puig Navarro, A.; Punzi, G.; Qian, W.; Rachwal, B.; Rademacker, J. H.; Rakotomiaramanana, B.; Rama, M.; Rangel, M. S.; Raniuk, I.; Rauschmayr, N.; Raven, G.; Redford, S.; Reichert, S.; Reid, M. M.; dos Reis, A. C.; Ricciardi, S.; Richards, A.; Rinnert, K.; Rives Molina, V.; Roa Romero, D. A.; Robbe, P.; Rodrigues, A. B.; Rodrigues, E.; Rodriguez Perez, P.; Roiser, S.; Romanovsky, V.; Romero Vidal, A.; Rotondo, M.; Rouvinet, J.; Ruf, T.; Ruffini, F.; Ruiz, H.; Ruiz Valls, P.; Sabatino, G.; Saborido Silva, J. J.; Sagidova, N.; Sail, P.; Saitta, B.; Salustino Guimaraes, V.; Sanchez Mayordomo, C.; Sanmartin Sedes, B.; Santacesaria, R.; Santamarina Rios, C.; Santovetti, E.; Sapunov, M.; Sarti, A.; Satriano, C.; Satta, A.; Savrie, M.; Savrina, D.; Schiller, M.; Schindler, H.; Schlupp, M.; Schmelling, M.; Schmidt, B.; Schneider, O.; Schopper, A.; Schune, M.-H.; Schwemmer, R.; Sciascia, B.; Sciubba, A.; Seco, M.; Semennikov, A.; Senderowska, K.; Sepp, I.; Serra, N.; Serrano, J.; Sestini, L.; Seyfert, P.; Shapkin, M.; Shapoval, I.; Shcheglov, Y.; Shears, T.; Shekhtman, L.; Shevchenko, V.; Shires, A.; Silva Coutinho, R.; Simi, G.; Sirendi, M.; Skidmore, N.; Skwarnicki, T.; Smith, N. A.; Smith, E.; Smith, E.; Smith, J.; Smith, M.; Snoek, H.; Sokoloff, M. D.; Soler, F. J. P.; Soomro, F.; Souza, D.; Souza De Paula, B.; Spaan, B.; Sparkes, A.; Spinella, F.; Spradlin, P.; Stagni, F.; Stahl, S.; Steinkamp, O.; Stenyakin, O.; Stevenson, S.; Stoica, S.; Stone, S.; Storaci, B.; Stracka, S.; Straticiuc, M.; Straumann, U.; Stroili, R.; Subbiah, V. K.; Sun, L.; Sutcliffe, W.; Swientek, K.; Swientek, S.; Syropoulos, V.; Szczekowski, M.; Szczypka, P.; Szilard, D.; Szumlak, T.; T'Jampens, S.; Teklishyn, M.; Tellarini, G.; Teodorescu, E.; Teubert, F.; Thomas, C.; Thomas, E.; van Tilburg, J.; Tisserand, V.; Tobin, M.; Tolk, S.; Tomassetti, L.; Tonelli, D.; Topp-Joergensen, S.; Torr, N.; Tournefier, E.; Tourneur, S.; Tran, M. T.; Tresch, M.; Tsaregorodtsev, A.; Tsopelas, P.; Tuning, N.; Ubeda Garcia, M.; Ukleja, A.; Ustyuzhanin, A.; Uwer, U.; Vagnoni, V.; Valenti, G.; Vallier, A.; Vazquez Gomez, R.; Vazquez Regueiro, P.; Vázquez Sierra, C.; Vecchi, S.; Velthuis, J. J.; Veltri, M.; Veneziano, G.; Vesterinen, M.; Viaud, B.; Vieira, D.; Vieites Diaz, M.; Vilasis-Cardona, X.; Vollhardt, A.; Volyanskyy, D.; Voong, D.; Vorobyev, A.; Vorobyev, V.; Voß, C.; Voss, H.; de Vries, J. A.; Waldi, R.; Wallace, C.; Wallace, R.; Walsh, J.; Wandernoth, S.; Wang, J.; Ward, D. R.; Watson, N. K.; Webber, A. D.; Websdale, D.; Whitehead, M.; Wicht, J.; Wiedner, D.; Wiggers, L.; Wilkinson, G.; Williams, M. P.; Williams, M.; Wilson, F. F.; Wimberley, J.; Wishahi, J.; Wislicki, W.; Witek, M.; Wormser, G.; Wotton, S. A.; Wright, S.; Wu, S.; Wyllie, K.; Xie, Y.; Xing, Z.; Xu, Z.; Yang, Z.; Yuan, X.; Yushchenko, O.; Zangoli, M.; Zavertyaev, M.; Zhang, F.; Zhang, L.; Zhang, W. C.; Zhang, Y.; Zhelezov, A.; Zhokhov, A.; Zhong, L.; Zvyagin, A.

    2014-05-01

    The polarisation of prompt mesons is measured by performing an angular analysis of decays using proton-proton collision data, corresponding to an integrated luminosity of 1.0, collected by the LHCb detector at a centre-of-mass energy of 7 TeV. The polarisation is measured in bins of transverse momentum and rapidity in the kinematic region and , and is compared to theoretical models. No significant polarisation is observed.

  15. Social class disparities in health and education: reducing inequality by applying a sociocultural self model of behavior.

    PubMed

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

    2012-10-01

    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 integration proposes that, in contrast to how the 2 models are typically represented, they are not opposed, but instead they are complementary sets of understandings that inform and extend each other. Further, we elaborate the theoretical rationale and predictions for a third model: the sociocultural self model of behavior. This model incorporates and extends key tenets of the individual and structural models. First, the sociocultural self model conceptualizes individual characteristics (e.g., skills) and structural conditions (e.g., access to resources) as interdependent forces that mutually constitute each other and that are best understood together. Second, the sociocultural self model recognizes that both individual characteristics and structural conditions indirectly influence behavior through the selves that emerge in the situation. These selves are malleable psychological states that are a product of the ongoing mutual constitution of individuals and structures and serve to guide people's behavior by systematically shaping how people construe situations. The theoretical foundation of the sociocultural self model lays the groundwork for a more complete understanding of behavior and provides new tools for developing interventions that will reduce social class disparities in health and education. The model predicts that intervention efforts will be more effective at producing sustained behavior change when (a) current selves are congruent, rather than incongruent, with the desired behavior and (b) individual characteristics and structural conditions provide ongoing support for the selves that are necessary to support

  16. Triangular flow of thermal photons from an event-by-event hydrodynamic model for 2.76 A TeV Pb + Pb collisions at the CERN Large Hadron Collider

    NASA Astrophysics Data System (ADS)

    Chatterjee, Rupa; Srivastava, Dinesh K.; Renk, Thorsten

    2016-07-01

    We calculate the triangular flow parameter v3 of thermal photons from an event-by-event ideal hydrodynamic model for 0-40% central collisions of Pb nuclei at √{sN N}=2.76 TeV at the CERN Large Hadron Collider. v3 determined with respect to the participant plane (PP) is found to be nonzero and positive, and its pT dependence is qualitatively similar to the elliptic flow parameter v2(PP) of thermal photons in the range 1 ≤pT≤6 GeV/c . In the range pT≤ 3 GeV/c , v3(PP) is found to be about 50-75% of v2(PP) and for pT> 3 GeV/c the two anisotropy parameters become comparable. The value of v3 is driven by local density fluctuations both directly via the creation of triangular geometry and indirectly via additional flow. As expected, the triangular flow parameter calculated with respect to the reaction plane v3(RP) is found to be close to zero. We show that v3(PP) strongly depends on the spatial size of fluctuations, especially in the higher pT(≥3 GeV /c ) region where a larger value of σ results in a smaller v3(PP ) . In addition, v3(PP ) is found to increase with the assumed formation time of the thermalized system.

  17. Combined search for the Standard Model Higgs boson using up to 4.9 fb⁻¹ of pp collision data at √s = 7 TeV with the ATLAS detector at the LHC

    DOE PAGESBeta

    Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; AbouZeid, O. S.; et al

    2012-03-01

    A combined search for the Standard Model Higgs boson with the ATLAS experiment at the LHC using datasets corresponding to integrated luminosities from 1.04 fb⁻¹ to 4.9 fb⁻¹ of pp collisions collected at √s=7 TeV is presented. The Higgs boson mass ranges 112.9–115.5 GeV, 131–238 GeV and 251–466 GeV are excluded at the 95% confidence level (CL), while the range 124–519 GeV is expected to be excluded in the absence of a signal. An excess of events is observed around mH~126 GeV with a local significance of 3.5 standard deviations (σ ). The local significances of H → γγ, Hmore » → ZZ(⁎) → ℓ⁺ℓ⁻ℓ′⁺ℓ′⁻ and H → WW(⁎) → ℓ⁺νℓ′⁻ν¯, the three most sensitive channels in this mass range, are 2.8σ, 2.1σ and 1.4σ, respectively. The global probability for the background to produce such a fluctuation anywhere in the explored Higgs boson mass range 110–600 GeV is estimated to be ~1.4% or, equivalently, 2.2σ.« less

  18. Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays

    PubMed Central

    Noor, Zainab; Afzal, Noreen; Rashid, Sajid

    2015-01-01

    Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC50 values and experimental energy scores with extensive validations. The QSAR model having an external R2 value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy. PMID:26431201

  19. Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays.

    PubMed

    Noor, Zainab; Afzal, Noreen; Rashid, Sajid

    2015-01-01

    Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC50 values and experimental energy scores with extensive validations. The QSAR model having an external R2 value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy.

  20. Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma.

    PubMed

    Leichtle, Alexander Benedikt; Ceglarek, Uta; Weinert, Peter; Nakas, Christos T; Nuoffer, Jean-Marc; Kase, Julia; Conrad, Tim; Witzigmann, Helmut; Thiery, Joachim; Fiedler, Georg Martin

    2013-06-01

    Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings. PMID:23678345

  1. TeV and Multi-wavelength Observations of Mrk 421 in 2006-2008

    NASA Astrophysics Data System (ADS)

    Acciari, V. A.; Aliu, E.; Arlen, T.; Aune, T.; Beilicke, M.; Benbow, W.; Boltuch, D.; Bradbury, S. M.; Buckley, J. H.; Bugaev, V.; Byrum, K.; Cannon, A.; Cesarini, A.; Ciupik, L.; Cui, W.; Dickherber, R.; Duke, C.; Falcone, A.; Finley, J. P.; Finnegan, G.; Fortson, L.; Furniss, A.; Galante, N.; Gall, D.; Gillanders, G. H.; Godambe, S.; Grube, J.; Guenette, R.; Gyuk, G.; Hanna, D.; Holder, J.; Hui, C. M.; Humensky, T. B.; Imran, A.; Kaaret, P.; Karlsson, N.; Kertzman, M.; Kieda, D.; Konopelko, A.; Krawczynski, H.; Krennrich, F.; Lang, M. J.; Maier, G.; McArthur, S.; McCutcheon, M.; Moriarty, P.; Ong, R. A.; Otte, A. N.; Ouellette, M.; Pandel, D.; Perkins, J. S.; Pichel, A.; Pohl, M.; Quinn, J.; Ragan, K.; Reyes, L. C.; Reynolds, P. T.; Roache, E.; Rose, H. J.; Rovero, A. C.; Schroedter, M.; Sembroski, G. H.; Senturk, G. Demet; Steele, D.; Swordy, S. P.; Theiling, M.; Thibadeau, S.; Varlotta, A.; Vassiliev, V. V.; Vincent, S.; Wagner, R. G.; Wakely, S. P.; Ward, J. E.; Weekes, T. C.; Weinstein, A.; Weisgarber, T.; Williams, D. A.; Wissel, S.; Wood, M.; Zitzer, B.; Garson, A., III; Lee, K.; Sadun, A. C.; Carini, M.; Barnaby, D.; Cook, K.; Maune, J.; Pease, A.; Smith, S.; Walters, R.; Berdyugin, A.; Lindfors, E.; Nilsson, K.; Pasanen, M.; Sainio, J.; Sillanpaa, A.; Takalo, L. O.; Villforth, C.; Montaruli, T.; Baker, M.; Lahteenmaki, A.; Tornikoski, M.; Hovatta, T.; Nieppola, E.; Aller, H. D.; Aller, M. F.

    2011-09-01

    We report on TeV γ-ray observations of the blazar Mrk 421 (redshift of 0.031) with the VERITAS observatory and the Whipple 10 m Cherenkov telescope. The excellent sensitivity of VERITAS allowed us to sample the TeV γ-ray fluxes and energy spectra with unprecedented accuracy where Mrk 421 was detected in each of the pointings. A total of 47.3 hr of VERITAS and 96 hr of Whipple 10 m data were acquired between 2006 January and 2008 June. We present the results of a study of the TeV γ-ray energy spectra as a function of time and for different flux levels. On 2008 May 2 and 3, bright TeV γ-ray flares were detected with fluxes reaching the level of 10 Crab. The TeV γ-ray data were complemented with radio, optical, and X-ray observations, with flux variability found in all bands except for the radio wave band. The combination of the Rossi X-ray Timing Explorer and Swift X-ray data reveal spectral hardening with increasing flux levels, often correlated with an increase of the source activity in TeV γ-rays. Contemporaneous spectral energy distributions were generated for 18 nights, each of which are reasonably described by a one-zone synchrotron self-Compton model.

  2. Lower limits on ultrahigh-energy cosmic ray and jet powers of TeV blazars

    NASA Astrophysics Data System (ADS)

    Razzaque, Soebur; Dermer, Charles; Finke, Justin

    2012-03-01

    Lower limits on the power emitted in ultrahigh-energy cosmic ray (UHECR) protons are derived for TeV blazars with the assumption that the observed TeV gamma rays are generated due to interactions of these protons with cosmic microwave photons. This mechanism may be at work in four blazars, namely 1ES 0229+200; 1ES 1101-232; 1ES 0347-121 and 1ES 1426+428, which are at sufficiently high redshift (>0.1) that allow efficient cascade development to make TeV emission and which are non-varying or very weakly varying at >TeV energies. The lower limits on the UHECR power are lower than the respective synchrotron luminosities in case of all blazars except for 1ES 1426+428. The proposed Auger North Observatory can detect 40 EeV cosmic rays from this extraordinary source and test the UHECR-generated TeV emission model, which requires the intergalactic magnetic field strength to be below 10-16 G. The lower limits on the jet power for all four TeV blazars exceed the Eddington luminosity of a 10^9 solar mass black hole in case the injected UHECR spectrum is softer than -2.2.

  3. TeV AND MULTI-WAVELENGTH OBSERVATIONS OF Mrk 421 IN 2006-2008

    SciTech Connect

    Acciari, V. A.; Benbow, W.; Aliu, E.; Arlen, T.; Aune, T.; Beilicke, M.; Buckley, J. H.; Bugaev, V.; Dickherber, R.; Boltuch, D.; Bradbury, S. M.; Byrum, K.; Cannon, A.; Cesarini, A.; Ciupik, L.; Cui, W.; Finley, J. P.; Duke, C.; Falcone, A.; Finnegan, G.

    2011-09-01

    We report on TeV {gamma}-ray observations of the blazar Mrk 421 (redshift of 0.031) with the VERITAS observatory and the Whipple 10 m Cherenkov telescope. The excellent sensitivity of VERITAS allowed us to sample the TeV {gamma}-ray fluxes and energy spectra with unprecedented accuracy where Mrk 421 was detected in each of the pointings. A total of 47.3 hr of VERITAS and 96 hr of Whipple 10 m data were acquired between 2006 January and 2008 June. We present the results of a study of the TeV {gamma}-ray energy spectra as a function of time and for different flux levels. On 2008 May 2 and 3, bright TeV {gamma}-ray flares were detected with fluxes reaching the level of 10 Crab. The TeV {gamma}-ray data were complemented with radio, optical, and X-ray observations, with flux variability found in all bands except for the radio wave band. The combination of the Rossi X-ray Timing Explorer and Swift X-ray data reveal spectral hardening with increasing flux levels, often correlated with an increase of the source activity in TeV {gamma}-rays. Contemporaneous spectral energy distributions were generated for 18 nights, each of which are reasonably described by a one-zone synchrotron self-Compton model.

  4. Length-independent structural similarities enrich the antibody CDR canonical class model

    PubMed Central

    Nowak, Jaroslaw; Baker, Terry; Georges, Guy; Kelm, Sebastian; Klostermann, Stefan; Shi, Jiye; Sridharan, Sudharsan; Deane, Charlotte M.

    2016-01-01

    ABSTRACT Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variable structural clusters show strong sequence patterns suggesting either that they evolved from the same original structure or result from some form of convergence. We find that our length-independent method not only clusters a larger number of CDRs, but also predicts canonical class from sequence better than the standard length-dependent approach. To demonstrate the usefulness of our findings, we predicted cluster membership of CDR-L3 sequences from 3 next-generation sequencing datasets of the antibody repertoire (over 1,000,000 sequences). Using the length-independent clusters, we can structurally classify an additional 135,000 sequences, which represents a ∼20% improvement over the standard approach. This suggests that our length-independent canonical classes might be a highly prevalent feature of antibody space, and could substantially improve our ability to accurately predict the structure of novel CDRs identified by next-generation sequencing. PMID:26963563

  5. Hadron supercolliders: The 1-TeV scale and beyond

    SciTech Connect

    Quigg, C.

    1990-08-10

    Greater understanding of the connection between the weak and electromagnetic interactions is central to progress in elementary-particle physics. A definitive exploration of the mechanism for electroweak symmetry breaking will require collisions between fundamental constituents at energies on the order of 1 TeV. This goal drives the design of high-energy, high-luminosity hadron colliders that will be commissioned during the next decade, but by no means completely defines their scientific potential. These three lectures are devoted to a review of the standard-model issues that motivated an experimental assault on the 1-TeV scale, an introduction to the machines and the experimental environment they will present, and a survey of possibilities for measurement and discovery with a multi-TeV hadron collider. 72 refs., 29 figs.

  6. Phenomenology of NMSSM in TeV scale mirage mediation

    NASA Astrophysics Data System (ADS)

    Hagimoto, Kei; Kobayashi, Tatsuo; Makino, Hiroki; Okumura, Ken-ichi; Shimomura, Takashi

    2016-02-01

    We study the next-to-minimal supersymmetric standard model (NMSSM) with the TeV scale mirage mediation, which is known as a solution for the little hierarchy problem in supersymmetry. Our previous study showed that 125 GeV Higgs boson is realized with {O} (10)% fine-tuning for 1.5 TeV gluino (1 TeV stop) mass. The μ term could be as large as 500 GeV without sacrificing the fine-tuning thanks to a cancellation mechanism. The singlet-doublet mixing is suppressed by tan β. In this paper, we further extend this analysis. We argue that approximate scale symmetries play a role behind the suppression of the singlet-doublet mixing. They reduce the mixing matrix to a simple form that is useful to understand the results of the numerical analysis. We perform a comprehensive analysis of the fine-tuning including the singlet sector by introducing a simple formula for the fine-tuning measure. This shows that the singlet mass of the least fine-tuning is favored by the LEP anomaly for moderate tan β. We also discuss prospects for the precision measurements of the Higgs couplings at LHC and ILC and direct/indirect dark matter searches in the model.

  7. Prospects for Higgs physics at energies up to 100 TeV

    NASA Astrophysics Data System (ADS)

    Baglio, Julien; Djouadi, Abdelhak; Quevillon, Jérémie

    2016-11-01

    We summarize the prospects for Higgs boson physics at future proton–proton colliders with centre of mass (c.m.) energies up to 100 TeV. We first provide the production cross sections for the Higgs boson of the Standard Model from 13 TeV to 100 TeV, in the main production mechanisms and in subleading but important ones such as double Higgs production, triple production and associated production with two gauge bosons or with a single top quark. We then discuss the production of Higgs particles in beyond the Standard Model scenarios, starting with the one in the continuum of a pair of scalar, fermionic and vector dark matter particles in Higgs-portal models in various channels with virtual Higgs exchange. The cross sections for the production of the heavier CP-even and CP-odd neutral Higgs states and the charged Higgs states in two-Higgs doublet models, with a specific study of the case of the Minimal Supersymmetric Standard Model, are then given. The sensitivity of a 100 TeV proton machine to probe the new Higgs states is discussed and compared to that of the LHC with a c.m. energy of 14 TeV and at high luminosity.

  8. A Stochastic Kinematic Model of Class Averaging in Single-Particle Electron Microscopy

    PubMed Central

    Park, Wooram; Midgett, Charles R.; Madden, Dean R.; Chirikjian, Gregory S.

    2011-01-01

    Single-particle electron microscopy is an experimental technique that is used to determine the 3D structure of biological macromolecules and the complexes that they form. In general, image processing techniques and reconstruction algorithms are applied to micrographs, which are two-dimensional (2D) images taken by electron microscopes. Each of these planar images can be thought of as a projection of the macromolecular structure of interest from an a priori unknown direction. A class is defined as a collection of projection images with a high degree of similarity, presumably resulting from taking projections along similar directions. In practice, micrographs are very noisy and those in each