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Sample records for modeling tev class

  1. Modeling TeV Class Plasma Afterburners

    SciTech Connect

    Huang, C.; Clayton, C.; Johnson, d.; Joshi, C.; Lu, W.; Mori, W.; Zhou, M.; Barnes, C.; Decker, F.-J.; Hogan, M.; Iverson, R.; Deng, S.; Katsouleas, T.; Muggli, P.; Oz, E.; /Southern California U.

    2006-01-30

    Plasma wakefield acceleration can sustain acceleration gradients three orders of magnitude larger than conventional RF accelerator. In the recent E164X experiment, substantial energy gain of about 3-4 GeV has been observed. Thus, a plasma afterburner, which has been proposed to double the incoming beam energy for a future linear collider, is now of great interest. In an afterburner, a particle beam drives a plasma wave and generates a strong wakefield which has a phase velocity equal to the velocity of the beam. This wakefield can then be used to accelerate part of the drive beam or a trailing beam. Several issues such as the efficient transfer of energy and the stable propagation of both the drive and trailing beams in the plasma are critical to the afterburner concept. We investigate the nonlinear beam-plasma interaction in such scenario using the 3D computer modeling code QuickPIC. We will report on the preliminary simulation results of both 100 GeV and 1 TeV plasma afterburner stages for electrons including the beam-loading of a trailing beam. Analytic analysis of hosing instability in this regime will be presented.

  2. Double seesaw mechanism in a left-right symmetric model with TeV neutrinos

    SciTech Connect

    Almeida, F. M. L. Jr. de; Coutinho, Y. A.; Simoes, J. A. Martins; Ramalho, A. J.; Pinto, L. Ribeiro; Wulck, S.; Vale, M. A. B. do

    2010-03-01

    A left-right symmetric model is discussed with new mirror fermions and a Higgs sector with two doublets and neutral scalar singlets. The seesaw mechanism is generalized, including not only neutrino masses but also charged fermion masses. The spectrum of heavy neutrinos presents a second seesaw mass matrix and has neutrinos masses naturally in the TeV region. The model has very clear signatures for the new neutral vector gauge bosons. Two classes of models are discussed. New mirror neutrinos can be very light and a new Z{sup '} can be discriminated from other models by a very high invisible branching fraction. The other possibility is that mirror neutrinos can have masses naturally in the TeV region and can be produced through Z{sup '} decays into heavy neutrino pairs. Signatures and production processes for the model at the LHC energy are also presented.

  3. 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)

  4. 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.

  5. First class models from linear and nonlinear second class constraints

    NASA Astrophysics Data System (ADS)

    Dehghani, Mehdi; Mardaani, Maryam; Monemzadeh, Majid; Nejad, Salman Abarghouei

    2015-10-01

    Two models with linear and nonlinear second class constraints are considered and gauged by embedding in an extended phase space. These models are studied by considering a free non-relativistic particle on the hyperplane and hypersphere in the configuration space. The gauged theory of the first model is obtained by converting the very second class system to the first class one directly. In contrast, the first class system related to the free particle on the hypersphere is derived with the help of the infinite Batalin-Fradkin-Tyutin (BFT) embedding procedure. We propose a practical formula, based on the simplified BFT method, which is practical in gauging linear and some nonlinear second class systems. As a result of gauging these two models, we show that in the conversion of second class constraints to the first class ones, the minimum number of phase space degrees of freedom for both systems is a pair of phase space coordinates. This pair is made up of a coordinate and its conjugate momentum for the first model, but the corresponding Poisson structure of the embedded non-relativistic particle on hypersphere is a nontrivial one. We derive infinite correction terms for the Hamiltonian of the nonlinear constraints and an interacting gauged Hamiltonian is constructed by summing over them. At the end, we find an open algebra for three first class objects of the embedded nonlinear system.

  6. Class Extraction and Classification Accuracy in Latent Class Models

    ERIC Educational Resources Information Center

    Wu, Qiong

    2009-01-01

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

  7. Consequences of Fitting Nonidentified Latent Class Models

    ERIC Educational Resources Information Center

    Abar, Beau; Loken, Eric

    2012-01-01

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

  8. 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.

    2011-12-15

    Modeling of laser-plasma wakefield accelerators in an optimal frame of reference [J.-L. Vay, Phys. Rev. Lett. 98, 130405 (2007)] 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 plasma accelerators 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. 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.

  9. 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.

  10. Java classes for nonprocedural variogram modeling

    NASA Astrophysics Data System (ADS)

    Faulkner, Barton R.

    2002-04-01

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

  11. Rating Scale Analysis with Latent Class Models.

    ERIC Educational Resources Information Center

    Rost, Jurgen

    1988-01-01

    A general approach for analyzing rating data with latent class models is described, paralleling rating models in the framework of latent trait theory. A general rating model and a two-parameter model with location and dispersion parameters are derived and illustrated. (Author/SLD)

  12. Modeling of the TeV galactic cosmic-ray anisotropy

    NASA Astrophysics Data System (ADS)

    Sako, Takashi

    2012-07-01

    A possible origin of the large-scale anisotropy of TeV galactic cosmic rays is discussed. It can be well modeled by the superposition of the Global Anisotropy and the Midscale Anisotropy. The Global Anisotropy would be generated by galactic cosmic rays interacting with the magnetic field in the local (a few parsecs) interstellar space surrounding the heliosphere. On the other hand, the Midscale Anisotropy, possibly caused by the modulation of galactic cosmic rays in the heliotail, can be expressed as two enhancements of the cosmic-ray intensity placed along the Hydrogen Deflection Plane, each symmetrically centered away from the heliotail direction. It is also found that the separation angle between the heliotail direction and each of the two enhancements monotonously decreases as the cosmic-ray enegy increases from 4 TeV to 30 TeV.

  13. Hierarchical Classes Modeling of Rating Data

    ERIC Educational Resources Information Center

    Van Mechelen, Iven; Lombardi, Luigi; Ceulemans, Eva

    2007-01-01

    Hierarchical classes (HICLAS) models constitute a distinct family of structural models for N-way N-mode data. All members of the family include N simultaneous and linked classifications of the elements of the N modes implied by the data; those classifications are organized in terms of hierarchical, if-then-type relations. Moreover, the models are…

  14. 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

  15. 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.

  16. Search for physics beyond the standard model in dilepton mass spectra in proton-proton collisions at TeV

    NASA Astrophysics Data System (ADS)

    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. 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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. 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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. 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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. 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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.

    2015-04-01

    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. Similarly, 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. [Figure not available: see fulltext.

  17. 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…

  18. Vacuum stability constraints on the minimal singlet TeV seesaw model

    NASA Astrophysics Data System (ADS)

    Khan, Subrata; Goswami, Srubabati; Roy, Sourov

    2014-04-01

    We consider the minimal seesaw model in which two gauge singlet right-handed neutrinos with opposite lepton numbers are added to the Standard Model. In this model, the smallness of the neutrino mass is explained by the tiny lepton number violating coupling between one of the singlets with the standard left-handed neutrinos. This allows one to have the right-handed neutrino mass at the TeV scale as well as appreciable mixing between the light and heavy states. This model is fully reconstructible in terms of the neutrino oscillation parameters apart from the overall coupling strengths. We show that the overall coupling strength yν for the Dirac-type coupling between the left-handed neutrino and one of the singlets can be restricted by consideration of the (meta)stability bounds on the electroweak vacuum. In this scenario the lepton flavor violating decays of charged leptons can be appreciable, which can put further constraint on yν for right-handed neutrinos at TeV scale. We discuss the combined constraints on yν for this scenario from the process μ→eγ and from the consideration of vacuum (meta)stability constraints on the Higgs self-coupling. We also briefly discuss the implications for neutrinoless double beta decay and possible signatures of the model that can be expected at colliders.

  19. 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)

  20. 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.

  1. A Multizone Model for Simulating the High-Energy Variability of TeV Blazars

    NASA Astrophysics Data System (ADS)

    Graff, Philip B.; Georganopoulos, Markos; Perlman, Eric S.; Kazanas, Demosthenes

    2008-12-01

    We present a time-dependent multizone code for simulating the variability of synchrotron self-Compton (SSC) sources. The code adopts a multizone pipe geometry for the emission region, appropriate for simulating emission from a standing or propagating shock in a collimated jet. Variations in the injection of relativistic electrons in the inlet propagate along the length of the pipe, cooling radiatively. Our code for the first time takes into account the nonlocal, time-retarded nature of SSC losses that are thought to be dominant in TeV blazars. The observed synchrotron and SSC emission is followed self-consistently, taking into account light-travel time delays. At any given time, the emitting portion of the pipe depends on the frequency and the nature of the variation followed. Our simulation employs only one additional physical parameter relative to one-zone models, that of the pipe length, and is computationally very efficient, using simplified expressions for the SSC processes. The code will be useful for observers modeling Fermi, TeV, and X-ray observations of SSC blazars.

  2. 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.

  3. 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.

  4. TeV cosmic-ray proton and helium spectra in the myriad model

    NASA Astrophysics Data System (ADS)

    Bernard, G.; Delahaye, T.; Keum, Y.-Y.; Liu, W.; Salati, P.; Taillet, R.

    2013-07-01

    Context. Recent measurements of cosmic ray proton and helium spectra show a hardening above a few hundred GeV. This excess is hard to understand in the framework of the conventional models of Galactic cosmic ray production and propagation. Aims: We propose here to explain this anomaly by the presence of local sources (myriad model). Methods: Cosmic ray propagation is described as a diffusion process taking place inside a two-zone magnetic halo. We calculate the proton and helium fluxes at the Earth between 50 GeV and 100 TeV. As an improvement over a similar analysis, we consistently derive these fluxes by taking both local and remote sources for which a unique injection rate is assumed into account. Results: We find cosmic ray propagation parameters compatible with B/C measurements for which the proton and helium spectra agree remarkably with the PAMELA and CREAM measurements over four decades in energy.

  5. 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.

  6. 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.

  7. 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.

  8. Feedforward neural network models for handling class overlap and class imbalance.

    PubMed

    Kretzschmar, Ralf; Karayiannis, Nicolaos B; Eggimann, Fritz

    2005-10-01

    This paper proposes a framework for training feedforward neural network models capable of handling class overlap and imbalance by minimizing an error function that compensates for such imperfections of the training set. A special case of the proposed error function can be used for training variance-controlled neural networks (VCNNs), which are developed to handle class overlap by minimizing an error function involving the class-specific variance (CSV) computed at their outputs. Another special case of the proposed error function can be used for training class-balancing neural networks (CBNNs), which are developed to handle class imbalance by relying on class-specific correction (CSC). VCNNs and CBNNs are compared with conventional feedforward neural networks (FFNNs), quantum neural networks (QNNs), and resampling techniques. The properties of VCNNs and CBNNs are illustrated by experiments on artificial data. Various experiments involving real-world data reveal the advantages offered by VCNNs and CBNNs in the presence of class overlap and class imbalance. PMID:16278937

  9. 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.

  10. A Class of Pattern-Forming Models

    NASA Astrophysics Data System (ADS)

    Fife, P. C.; Kowalczyk, M.

    1999-12-01

    A general class of nonlinear evolution equations is described, which support stable spatially oscillatory steady solutions. These equations are composed of an indefinite self-adjoint linear operator acting on the solution plus a nonlinear function, a typical example of the latter being a double-well potential. Thus a Lyapunov functional exists. The linear operator contains a parameter ρ which could be interpreted as a measure of the pattern-forming tendency for the equation. Examples in this class of equations are an integrodifferential equation studied by Goldstein, Muraki, and Petrich and others in an activator-inhibitor context, and a class of fourth-order parabolic PDE's appearing in the literature in various physical connections and investigated rigorously by Coleman, Leizarowitz, Marcus, Mizel, Peletier, Troy, Zaslavskii, and others. The former example reduces to the real Ginzburg-Landau equation when ρ = 0 . The most complete results, including threshold results for the appearance of globally minimizing patterns and many other properties of the patterns themselves, are given for complex-valued solutions in one space variable. A complete linear stability analysis for all such sinusoidal solutions is also given; it extends the set of stable solutions considerably beyond the global minimizers. Other results, including threshold results and the existence of large amplitude patterns as well as of bifurcating solutions, are provided for real-valued solutions; these results are relatively independent of the number of space variables. Finally, a slightly different class of evolution equations is given for which no patterned global minimizer exists, but a sequence of patterned solutions exist whose instabilities (if they are unstable) become ever weaker and the fineness of the oscillation becomes ever more pronounced.

  11. TeV Scale Lepton Number Violation and Baryogenesis

    NASA Astrophysics Data System (ADS)

    Bhupal Dev, P. S.; Lee, Chang-Hun; Mohapatra, R. N.

    2015-07-01

    Contrary to the common lore based on naive dimensional analysis, the seesaw scale for neutrino masses can be naturally in the TeV range, with small parameters coming from radiative corrections. We present one such class of type-I seesaw models, based on the left-right gauge group SU(2)L × SU(2)R × U(1)B-L realized at the TeV scale, which fits the observed neutrino oscillation parameters as well as other low energy constraints. We discuss how the small parameters of this scenario can arise naturally from one loop effects. The neutrino fits in this model use quasi-degenerate heavy Majorana neutrinos, as also required to explain the matter-antimatter asymmetry in our Universe via resonant leptogenesis mechanism. We discuss the constraints implied by the dynamics of this mechanism on the mass of the right-handed gauge boson in this class of models with enhanced neutrino Yukawa couplings compared to the canonical seesaw model and find a lower bound of mWR ≥ 9.9 TeV for successful leptogenesis assuming maximal CP asymmetry for each flavor. We also present a model with explicit neutrino mass fit, where the lower bound goes up to 13.1 TeV due to less than maximal primordial CP asymmetry predicted by the model.

  12. Class Model Development Using Business Rules

    NASA Astrophysics Data System (ADS)

    Skersys, Tomas; Gudas, Saulius

    New developments in the area of computer-aided system engineering (CASE) greatly improve processes of the information systems development life cycle (ISDLC). Much effort is put into the quality improvement issues, but IS development projects still suffer from the poor quality of models during the system analysis and design cycles. At some degree, quality of models that are developed using CASE tools can be assured using various. automated. model comparison, syntax. checking procedures. It. is also reasonable to check these models against the business domain knowledge, but the domain knowledge stored in the repository of CASE tool (enterprise model) is insufficient (Gudas et al. 2004). Involvement of business domain experts into these processes is complicated because non- IT people often find it difficult to understand models that were developed by IT professionals using some specific modeling language.

  13. A Penalized Latent Class Model for Ordinal Data

    PubMed Central

    Houseman, E. Andrés; Coull, Brent A.; Stemmer-Rachamimov, Anat; Betensky, Rebecca A.

    2016-01-01

    Latent class models provide a useful framework for clustering observations based on several features. Application of latent class methodology to correlated, high-dimensional ordinal data poses many challenges. Unconstrained analyses may not result in an estimable model. Thus, information contained in ordinal variables may not be fully exploited by researchers. We develop a penalized latent class model to facilitate analysis of high-dimensional ordinal data. By stabilizing maximum likelihood estimation, we are able to fit an ordinal latent class model that would otherwise not be identifiable without application of strict constraints. We illustrate our methodology in a study of schwannoma, a peripheral nerve sheath tumor, that included three clinical subtypes and 23 ordinal histological measures. PMID:17626225

  14. 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

  15. 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

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

    SciTech Connect

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

    2015-04-07

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

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

    PubMed Central

    2014-01-01

    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 classes. The procedures capitalize on the assumption that, due to mean differences between two classes, item covariances within class are smaller than item covariances between the classes. FMM goes beyond class detection and permits the specification of hypothesis-based within-class covariance structures ranging from local independence to multidimensional within-class factor models. In principle, FMM permits the comparison of alternative models using likelihood-based indexes. These advantages come at the price of distributional assumptions. In addition, models are often highly parameterized and susceptible to misspecifications of the within-class covariance structure. Following an illustration with an empirical data set of binary depression items, the MAXEIG procedure and FMM are compared in a simulation study focusing on class detection and the assignment of subjects to the latent classes. FMM generally outperformed MAXEIG in terms of class detection and class assignment. Substantially different class sizes negatively impacted the performance of both approaches, whereas low class separation was much more problematic for MAXEIG than for the FMM. PMID:24648712

  18. 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…

  19. The 14 TeV LHC takes aim at SUSY: a No-Scale supergravity model for LHC Run 2

    NASA Astrophysics Data System (ADS)

    Li, Tianjun; Maxin, James A.; Nanopoulos, Dimitri V.; Walker, Joel W.

    2015-09-01

    The supergravity model named No-Scale {F}-{SU}(5), which is based upon the flipped SU(5) grand unified theory (GUT) with additional TeV-scale vector-like flippon multiplets, has been partially probed during the Large Hadron Collider Run 1 at 7-8 TeV, though the majority of its model space remains viable and should be accessible by the 13-14 TeV LHC during Run 2. The model framework possesses the rather unique capacity to provide a light CP-even Higgs boson mass in the favored 124-126 GeV window while simultaneously retaining a testably light supersymmetry spectrum. We summarize the outlook for No-Scale {F}-{SU}(5) at the 13-14 TeV LHC and review a promising methodology for the discrimination of its long-chain cascade decay signature. We further show that proportional dependence of all model scales upon the unified gaugino mass {M}1/2 minimizes electroweak fine-tuning, allowing the Z-boson mass MZ to be expressed as an explicit function of {M}1/2, {M}Z2={M}Z2({M}1/22), with implicit dependence upon a dimensionless ratio c of the supersymmetric Higgs mixing parameter μ and {M}1/2. Finally, we elucidate an empirical connection between recent scalar tensor measurements and No-Scale supergravity cosmological models that mimic the Starobinsky model of inflation. In memory of Richard Arnowitt, a true giant. And of Tristan Leggett, a friend and colleague taken too soon.

  20. Multilevel Latent Class Models with Dirichlet Mixing Distribution

    PubMed Central

    Di, Chong-Zhi; Bandeen-Roche, Karen

    2010-01-01

    Summary Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social science and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we consider multilevel latent class models, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data. PMID:20560936

  1. 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.

  2. Class Practise of Cognitive Science by Creating Models

    NASA Astrophysics Data System (ADS)

    Miwa, Kazuhisa; Terai, Hitoshi; Morita, Jyunya; Nakaike, Ryuichi; Saito, Hitomi

    We designed and practiced a cognitive science class for graduate students. In the class, the participants were required to build three cognitive models: a bug model, a trace model, and an individual model. In the construction of the bug model, the participants learn to construct a cognitive model by monitoring their mental processing. The participants confirmed that the trace model can explain human normative behavior; and also understood that the individual model can explain various patterns of human behavior that are generated by different problem solving strategies. The post questionnaire analysis shows that the participants successfully understood various aspects of advantages of the mode-based approach in cognitive science and important features of human cognitive processing.

  3. 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…

  4. 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.

  5. 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…

  6. Global stability for a class of discrete SIR epidemic models.

    PubMed

    Enatsu, Yoichi; Nakata, Yukihiko; Muroya, Yoshiaki

    2010-04-01

    In this paper, we propose a class of discrete SIR epidemic models which are derived from SIR epidemic models with distributed delays by using a variation of the backward Euler method. Applying a Lyapunov functional technique, it is shown that the global dynamics of each discrete SIR epidemic model are fully determined by a single threshold parameter and the effect of discrete time delays are harmless for the global stability of the endemic equilibrium of the model. PMID:20462293

  7. Correlation model for a class of medical images

    NASA Astrophysics Data System (ADS)

    Zhang, Ya-Qin; Loew, Murray H.; Pickholtz, Raymond L.

    1991-06-01

    In this paper, correlation properties of a class of chest X-ray medical images are examined and different 1-D and 2-D correlation models are applied to this class of image sources. Correlation structures for different scanning methods including row-by-row, column-by- column, diagonal and Peano are compared. It is suggested that the Peano scanning best reserves the inter-pixel correlation, which coincides with an earlier observation made by Lempel and Ziv. The rate-distortion properties are also discussed in terms of different 1-D and 2-D correlation models.

  8. 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.

  9. Understanding the TeV emission from a distant blazar PKS 1424+240 in a lepto-hadronic jet model

    NASA Astrophysics Data System (ADS)

    Yan, Dahai; Zhang, Li

    2015-03-01

    We investigate the formation of the TeV spectrum of a distant blazar PKS 1424+240 residing at a redshift z ≥ 0.6 in two scenarios in the frame of a lepto-hadronic jet model, taking the uncertainties of both extragalactic background light (EBL) and its redshift into account. In the first scenario, TeV emission is attributed to the synchrotron emission of pair cascades resulting from the pγ interaction. In the second scenario, TeV emission is attributed to the proton-synchrotron emission, and an internal absorption due to interaction with the photons around the jet is included. Our results show that in the first scenario the 68 per cent upper limit of its redshift, within which this scenario can explain the VERITAS TeV spectrum in 2009 well, is ˜0.75. In the second scenario, this upper limit of the redshift becomes ˜1.03. However, the second scenario can be excluded because it requires an unreasonable photon field around the jet with a luminosity of ˜1043 erg s-1. In conclusion, the jet model can explain its TeV spectrum with a low EBL density if 0.6 < z < 0.75.

  10. 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.

  11. 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

  12. MODELING THE HARD TeV SPECTRA OF BLAZARS 1ES 0229+200 AND 3C 66A WITH AN INTERNAL ABSORPTION SCENARIO

    SciTech Connect

    Zacharopoulou, O.; Aharonian, F. A.; Khangulyan, D.

    2011-09-10

    We study the applicability of the idea of internal absorption of {gamma}-rays produced through synchrotron radiation of ultrarelativistic protons in highly magnetized blobs to 1ES 0229+200 and 3C 66A, the two TeV blazars which show unusually hard intrinsic {gamma}-ray spectra after being corrected for the intergalactic absorption. We show that for certain combinations of reasonable model parameters, even with quite modest energy requirements, the scenario allows a self-consistent explanation of the non-thermal emission of these objects in the keV, GeV, and TeV energy bands.

  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. 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

  15. 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.

  16. 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.

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

    ERIC Educational Resources Information Center

    Liu, William M.

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

  18. 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

  19. 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…

  20. 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…

  1. Special class of nonlinear damping models in flexible space structures

    NASA Technical Reports Server (NTRS)

    Hu, Anren; Singh, Ramendra P.; Taylor, Lawrence W.

    1991-01-01

    A special class of nonlinear damping models is investigated in which the damping force is proportional to the product of positive integer or the fractional power of the absolute values of displacement and velocity. For a one-degree-of-freedom system, the classical Krylov-Bogoliubov 'averaging' method is used, whereas for a distributed system, both an ad hoc perturbation technique and the finite difference method are employed to study the effects of nonlinear damping. The results are compared with linear viscous damping models. The amplitude decrement of free vibration for a single mode system with nonlinear models depends not only on the damping ratio but also on the initial amplitude, the time to measure the response, the frequency of the system, and the powers of displacement and velocity. For the distributed system, the action of nonlinear damping is found to reduce the energy of the system and to pass energy to lower modes.

  2. HVAC component data modeling using industry foundation classes

    SciTech Connect

    Bazjanac, Vladimir; Forester, James; Haves, Philip; Sucic, Darko; Xu, Peng

    2002-07-01

    The Industry Foundation Classes (IFC) object data model of buildings is being developed by the International Alliance for Interoperability (IAI). The aim is to support data sharing and exchange in the building and construction industry across the life-cycle of a building. This paper describes a number of aspects of a major extension of the HVAC part of the IFC data model. First is the introduction of a more generic approach for handling HVAC components. This includes type information, which corresponds to catalog data, occurrence information, which defines item-specific attributes such as location and connectivity, and performance history information, which documents the actual performance of the component instance over time. Other IFC model enhancements include an extension of the connectivity model used to specify how components forming a system can be traversed and the introduction of time-based data streams. This paper includes examples of models of particular types of HVAC components, such as boilers and actuators, with all attributes included in the definitions. The paper concludes by describing the on-going process of model testing, implementation and integration into the complete IFC model and how the model can be used by software developers to support interoperability between HVAC-oriented design and analysis tools.

  3. Evaluation of structural equation mixture models Parameter estimates and correct class assignment

    PubMed Central

    Tueller, Stephen; Lubke, Gitta

    2009-01-01

    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 one 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 investigated in a large scale simulation study. Design factors of the simulation study are (im)balanced class proportions, (im)balanced factor variances, sample size, and class separation. We compare the fit of models with correct and misspecified within-class structural relations. In addition, we investigate the potential to fit SEMMs with binary indicators. The structure of within-class distributions can be recovered under a wide variety of conditions, indicating the general potential and flexibility of SEMMs to test complex within-class models. Correct class assignment is limited. PMID:20582328

  4. 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}.

  5. A low-energy compatible SU(4)-type model for vector leptoquarks of mass ≤ 1 TeV

    NASA Astrophysics Data System (ADS)

    Blumhofer, A.; Lampe, B.

    1999-02-01

    The Standard Model is extended by a SU(2)_L singlet of vector leptoquarks. An additional SU(4) gauge symmetry between right-handed up quarks and right-handed leptons is introduced to render the model renormalizable. The arrangement is made in such a way that no conflict with low energy restrictions is encountered. The SU(2)_L singlet mediates interactions between the right-handed leptons and up type quarks for which only moderate low energy restrictions M_{LQ}/g_{LQ} > few hundred GeV exist. However, it is not a candidate to explain the anomalous HERA data at large Q^2 because theoretical reasons imply that g_{LQ} ≥ g_s which would give a much stronger anomalous HERA effect. We furthermore argue that the inequality g_{LQ} ≥ g_s is a general feature of consistent vector leptoquark models. Although our model is not relevant for HERA, it is interesting per se as a description of leptoquarks of mass ≤ 1 TeV consistent with all low-energy requirements.

  6. 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…

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

    NASA Astrophysics Data System (ADS)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Aguilo, E.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hammer, J.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Pernicka, M.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Reis, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Castello, R.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins Junior, M.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Malek, M.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Soares Jorge, L.; Sznajder, A.; Vilela Pereira, A.; Anjos, T. S.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, D.; Zhang, L.; Zou, W.; Avila, C.; Gomez, J. P.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Mekterovic, D.; Morovic, S.; Attikis, A.; Galanti, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M., Jr.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Khalil, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Müntel, M.; Raidal, M.; Rebane, L.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Heikkinen, A.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Ungaro, D.; Wendland, L.; Banzuzi, K.; Karjalainen, A.; Korpela, A.; Tuuva, T.; Besancon, M.; Choudhury, S.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Millischer, L.; Nayak, A.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Benhabib, L.; Bianchini, L.; Bluj, M.; Broutin, C.; Busson, P.; Charlot, C.; Daci, N.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Florent, A.; Granier de Cassagnac, R.; Haguenauer, M.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Sabes, D.; Salerno, R.; Sirois, Y.; Veelken, C.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Bodin, D.; Brom, J.-M.; Cardaci, M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Juillot, P.; Le Bihan, A.-C.; Van Hove, P.; Fassi, F.; Mercier, D.; Beauceron, S.; Beaupere, N.; Bondu, O.; Boudoul, G.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Sgandurra, L.; Sordini, V.; Tschudi, Y.; Verdier, P.; Viret, S.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Calpas, B.; Edelhoff, M.; Feld, L.; Heracleous, N.; Hindrichs, O.; Jussen, R.; Klein, K.; Merz, J.; 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.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Olschewski, M.; Papacz, P.; Pieta, H.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Steggemann, J.; Teyssier, D.; Thüer, S.; Weber, M.; Bontenackels, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Lingemann, J.; 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.; Leonard, J.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Marienfeld, M.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Novgorodova, O.; Olzem, J.; Perrey, H.; Petrukhin, A.; Pitzl, D.; Raspereza, A.; Ribeiro Cipriano, P. M.; Riedl, C.; Ron, E.; Rosin, M.; Salfeld-Nebgen, J.; Schmidt, R.; Schoerner-Sadenius, T.; Sen, N.; Spiridonov, A.; Stein, M.; Walsh, R.; Wissing, C.; Blobel, V.; Enderle, H.; Erfle, J.; Gebbert, U.; Görner, M.; Gosselink, M.; Haller, J.; Hermanns, T.; Höing, R. S.; Kaschube, K.; Kaussen, G.; Kirschenmann, H.; Klanner, R.; Lange, J.; Nowak, F.; Peiffer, T.; Pietsch, N.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Schröder, M.; Schum, T.; Seidel, M.; Sibille, J.; Sola, V.; Stadie, H.; Steinbrück, G.; Thomsen, J.; Vanelderen, L.; Barth, C.; Berger, J.; Böser, C.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Guthoff, M.; Hackstein, C.; Hartmann, F.; Hauth, T.; Heinrich, M.; Held, H.; Hoffmann, K. H.; Husemann, U.; Katkov, I.; Komaragiri, J. 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.; Schilling, F.-P.; Schott, G.; Simonis, H. J.; Stober, F. M.; Troendle, D.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Zeise, M.; Anagnostou, G.; 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.; Beri, S. B.; Bhatnagar, V.; Dhingra, N.; Gupta, R.; Kaur, M.; Mehta, M. Z.; Nishu, N.; Saini, L. K.; Sharma, A.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Shivpuri, R. K.; Banerjee, S.; Bhattacharya, S.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Aziz, T.; Ganguly, S.; Guchait, M.; Gurtu, A.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Banerjee, S.; Dugad, S.; Arfaei, H.; Bakhshiansohi, H.; Etesami, S. M.; Fahim, A.; Hashemi, M.; Hesari, H.; Jafari, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Paktinat Mehdiabadi, S.; Safarzadeh, B.; Zeinali, 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.; Marangelli, B.; My, S.; Nuzzo, S.; Pacifico, N.; Pompili, A.; Pugliese, G.; Selvaggi, G.; Silvestris, L.; Singh, G.; Venditti, R.; Verwilligen, P.; Zito, G.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Meneghelli, M.; Montanari, A.; Navarria, F. L.; Odorici, F.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Cappello, G.; Chiorboli, M.; Costa, S.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Frosali, S.; Gallo, E.; Gonzi, S.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Colafranceschi, S.; Fabbri, F.; Piccolo, D.; Fabbricatore, P.; Musenich, R.; Tosi, S.; Benaglia, A.; De Guio, F.; Di Matteo, L.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Massironi, A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Sala, S.; Tabarelli de Fatis, T.; Buontempo, S.; Carrillo Montoya, C. A.; Cavallo, N.; De Cosa, A.; Dogangun, O.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bellan, P.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Lazzizzera, I.; Margoni, M.; Meneguzzo, A. T.; Nespolo, M.; Pazzini, J.; Ronchese, P.; Simonetto, F.; Torassa, E.; Vanini, S.; Zotto, P.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Riccardi, C.; Torre, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Nappi, A.; Romeo, F.; Saha, A.; Santocchia, A.; Spiezia, A.; Taroni, S.; Azzurri, P.; Bagliesi, G.; Boccali, T.; Broccolo, G.; Castaldi, R.; D'Agnolo, R. T.; Dell'Orso, R.; Fiori, F.; Foà, L.; Giassi, A.; Kraan, A.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. 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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.; Martínez-Ortega, J.; Sánchez-Hernández, 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.; Butt, J.; Hoorani, H. R.; Khalid, S.; Khan, W. A.; Khurshid, T.; Qazi, S.; Shah, M. A.; Shoaib, M.; Bialkowska, H.; Boimska, B.; Frueboes, T.; 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.; Misiura, M.; Almeida, N.; Bargassa, P.; David, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Seixas, J.; Varela, J.; Vischia, P.; Belotelov, I.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Kozlov, G.; Lanev, A.; Malakhov, A.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Smirnov, V.; Volodko, A.; Zarubin, A.; Evstyukhin, S.; 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.; Matveev, V.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Erofeeva, M.; Gavrilov, V.; Kossov, M.; Lychkovskaya, N.; Popov, V.; Safronov, G.; Semenov, S.; Shreyber, I.; Stolin, V.; Vlasov, E.; Zhokin, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Markina, A.; Obraztsov, S.; Perfilov, M.; Petrushanko, S.; Popov, A.; Sarycheva, L.; Savrin, V.; Snigirev, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Grishin, V.; Kachanov, V.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Djordjevic, M.; Ekmedzic, M.; Krpic, D.; Milosevic, J.; Aguilar-Benitez, M.; Alcaraz Maestre, J.; Arce, P.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Ferrando, A.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Merino, G.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Santaolalla, J.; Soares, M. S.; Willmott, C.; Albajar, C.; Codispoti, G.; de Trocóniz, J. F.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Lloret Iglesias, L.; Piedra Gomez, J.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Chuang, S. H.; Duarte Campderros, J.; Felcini, M.; Fernandez, M.; Gomez, G.; Gonzalez Sanchez, J.; Graziano, A.; Jorda, C.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. 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.; Benitez, J. F.; Bernet, C.; Bianchi, G.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Christiansen, T.; Coarasa Perez, J. 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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.; 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.; Bäni, L.; Bortignon, P.; Buchmann, M. A.; Casal, B.; Chanon, N.; Deisher, A.; Dissertori, G.; Dittmar, M.; Donegà, 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.; Kilminster, B.; Millan Mejias, B.; Otiougova, P.; Robmann, P.; Snoek, H.; Tupputi, S.; Verzetti, M.; Chang, Y. H.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Li, S. W.; Lin, W.; Lu, Y. J.; 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.; Asavapibhop, B.; Srimanobhas, 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.; 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.; 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. 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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.; St. John, J.; Lawson, P.; Lazic, D.; Rohlf, J.; Sperka, D.; Sulak, L.; Alimena, J.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Jabeen, S.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Nguyen, D.; Segala, M.; Sinthuprasith, T.; Speer, T.; 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.; Mall, O.; Miceli, T.; Pellett, D.; Ricci-tam, F.; Rutherford, B.; Searle, M.; Smith, J.; Squires, M.; Tripathi, M.; Vasquez Sierra, R.; Yohay, R.; Andreev, V.; Cline, D.; Cousins, R.; Duris, J.; Erhan, S.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Jarvis, C.; Rakness, G.; Schlein, P.; Traczyk, 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.; 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.; Golf, F.; Incandela, J.; Justus, C.; Kalavase, P.; Kovalskyi, D.; Krutelyov, V.; Lowette, S.; Magaña Villalba, R.; Mccoll, N.; Pavlunin, V.; Ribnik, J.; Richman, J.; Rossin, R.; Stuart, D.; To, W.; West, C.; Apresyan, A.; Bornheim, A.; Chen, Y.; Di Marco, E.; Duarte, J.; Gataullin, M.; Ma, Y.; Mott, A.; Newman, H. B.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Veverka, J.; Wilkinson, R.; Xie, S.; Yang, Y.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carroll, R.; Ferguson, T.; Iiyama, Y.; Jang, D. W.; Liu, Y. F.; Paulini, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Drell, B. R.; Ford, W. T.; Gaz, A.; 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.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Burkett, K.; Butler, J. N.; Chetluru, V.; Cheung, H. W. K.; Chlebana, F.; 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.; Klima, B.; Kunori, S.; Kwan, S.; Leonidopoulos, C.; Linacre, J.; Lincoln, D.; Lipton, R.; Lykken, J.; Maeshima, K.; Marraffino, J. 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P., Iii; Murray, M.; Noonan, D.; Sanders, S.; Stringer, R.; Tinti, G.; Wood, J. S.; Barfuss, A. F.; Bolton, T.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Shrestha, S.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; 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.; Skuja, A.; Temple, J.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Bauer, G.; Bendavid, J.; Busza, W.; Butz, E.; Cali, I. A.; Chan, M.; Dutta, V.; Gomez Ceballos, G.; Goncharov, M.; Kim, Y.; Klute, M.; Krajczar, K.; Levin, A.; 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.; Yang, M.; Yilmaz, Y.; Yoon, A. S.; Zanetti, M.; Zhukova, V.; 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.; Claes, D. R.; Dominguez, A.; Eads, M.; Keller, J.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Snow, G. R.; Godshalk, A.; Iashvili, I.; Jain, S.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Nash, D.; Trocino, D.; Wood, D.; Zhang, J.; Anastassov, A.; Hahn, K. A.; Kubik, A.; Lusito, L.; 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.; Chan, K. M.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kolb, J.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Morse, D. M.; Pearson, T.; Planer, M.; Ruchti, R.; Slaunwhite, J.; Valls, N.; Wayne, M.; Wolf, M.; Bylsma, B.; Durkin, L. S.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Vuosalo, C.; Williams, G.; Winer, B. L.; Berry, E.; Elmer, P.; Halyo, V.; Hebda, P.; Hegeman, J.; Hunt, A.; Jindal, P.; Koay, S. A.; Lopes Pegna, D.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Raval, A.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Lopez, A.; Mendez, H.; Ramirez Vargas, J. E.; 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.; Akgun, B.; Boulahouache, C.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; 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.; Ferbel, T.; 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.; Walker, M.; 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.; Dragoiu, C.; 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.; 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.; Gollapinni, S.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sakharov, A.; Anderson, M.; Belknap, D.; 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.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Palmonari, F.; Pierro, G. A.; Ross, I.; Savin, A.; Smith, W. H.; Swanson, J.

    2012-12-01

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

  8. 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.

  9. 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…

  10. 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.

  11. 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…

  12. 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.

  13. Comparison of occlusal contact areas of class I and class II molar relationships at finishing using three-dimensional digital models

    PubMed Central

    Lee, Hyejoon; Kim, Minji

    2015-01-01

    Objective This study compared occlusal contact areas of ideally planned set-up and accomplished final models against the initial in class I and II molar relationships at finishing. Methods Evaluations were performed for 41 post-orthodontic treatment cases, of which 22 were clinically diagnosed as class I and the remainder were diagnosed as full cusp class II. Class I cases had four first premolars extracted, while class II cases had maxillary first premolars extracted. Occlusal contact areas were measured using a three-dimensional scanner and RapidForm 2004. Independent t-tests were used to validate comparison values between class I and II finishings. Repeated measures analysis of variance was used to compare initial, set up, and final models. Results Molars from cases in the class I finishing for the set-up model showed significantly greater contact areas than those from class II finishing (p < 0.05). The final model class I finishing showed significantly larger contact areas for the second molars (p < 0.05). The first molars of the class I finishing for the final model showed a tendency to have larger contact areas than those of class II finishing, although the difference was not statistically significant (p = 0.078). Conclusions In set-up models, posterior occlusal contact was better in class I than in class II finishing. In final models, class I finishing tended to have larger occlusal contact areas than class II finishing. PMID:26023539

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

    NASA Astrophysics Data System (ADS)

    Bloomfield, Jolyon K.; Flanagan, Éanna É.

    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.

  15. 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…

  16. 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.

  17. Condensate-enclosed chiral-bag model of the proton and pp elastic scattering at LHC 13 TeV

    NASA Astrophysics Data System (ADS)

    Islam, M. M.; Luddy, R. J.

    2015-11-01

    Our investigation of high energy pp and p¯p elastic scattering over the last ten years has led us to consider that the proton has three regions: (i) an outer region consisting of a quark-antiquark (qq¯) condensate ground state (also described as quark-antiquark outer cloud), (ii) an inner shell of topological (geometrical) baryonic charge of size ˜ 0.44 fm, and (iii) a core of size ˜ 0.2 fm, where the three valence quarks of a proton with baryonic charges are confined. The proton structure that has emerged leads to four main elastic scattering processes in pp scattering. The first process (which gives rise to diffraction scattering) is described by a profile function. The second process involves multiple ω-exchanges. The third process in pp scattering is quark-quark scattering via gluon-gluon interaction. The fourth process — which appears for the first time in our investigation of pp scattering — is a glancing collision at the boundary of a proton with that of the other proton. To describe quantitatively the four processes, their parameters have to be determined. For this purpose, we investigate: (i) pp 7 TeV dσ/dt measured by the TOTEM Collaboration and (ii) p¯p 1.96 TeV dσ/dt measured by the D0 Collaboration. Once the parameters are satisfactorily obtained, we calculate pp dσ/dt at 7 TeV and compare with the TOTEM data. We also calculate p¯p dσ/dt at 1.96 TeV and compare with the D0 data. We then predict pp elastic dσ/dt at 13 TeV which will soon be measured at LHC by the TOTEM Collaboration. This measurement will establish how well we have predicted the 13 TeV dσ/dt and determined the structure of the proton.

  18. 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.

  19. Two-component model in quantum statistical framework compared with multiplicity distributions in proton-proton collisions at energies up to √{ s} = 7 TeV

    NASA Astrophysics Data System (ADS)

    Ghosh, Premomoy

    2011-11-01

    Proton-proton collisions at new high energies (√{ s} = 2.36 and 7 TeV) at LHC resulted into greater mean multiplicities (< n >) of charged particles in the mid-rapidity region than estimated ones by different models and event generators. Another significant observation in multiplicity data is the change in slope in the distribution of primary charged hadrons in symmetric pseudorapidity interval | η | < 2.4. The change is most prominent with data at √{ s} = 7 TeV. These new observations merit further studies. We consider a two-component model of particle production to analyze multiplicity distributions of charged hadrons from proton-proton collisions at centre-of-mass energies √{ s} = 0.9, 2.36 and 7 TeV in symmetric pseudorapidity intervals | η | of increasing width around the centre-of-mass pseudorapidity ηcm = 0. The model, based on Quantum Statistical (QS) formalism, describes multiplicity distribution by convolution of a Negative Binomial Distribution (NBD), representing a chaotic component, and a Poisson Distribution (PD), representing a coherent component of particle productions. The behaviour of characteristic parameters of the model is followed by the LHC data, while a scaling law, involving information entropy in quantum statistical viewpoint and derived as a function of chaotic multiplicity obtained from the two-component model, is not obeyed by the data, satisfactorily. An attempt to match the measured multiplicity distributions and suggested convolutions with values of characteristic parameters extracted from the data confirms disagreement between the data and the model.

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

    PubMed

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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). PMID:19792296

  1. 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.

  2. Detailed Analysis of p+p Elastic Scattering Data in the Quark-Diquark Model of Bialas and Bzdak from \\sqrt{s} = 23.5~{\\rm GeV} TO 7 TeV

    NASA Astrophysics Data System (ADS)

    Nemes, F.; Csörgő, T.

    2012-12-01

    Final results of a detailed analysis of p+p elastic scattering data are presented, utilizing the quark-diquark model of protons in a form proposed by Bialas and Bzdak. The differential cross-section of elastic proton-proton collisions is analyzed in a detailed and systematic manner at small momentum transfers, starting from the energy range of CERN ISR at √ {s} = 23.5 GeV, including also recent TOTEM data at the present LHC energies at √ {s} = 7 TeV. These studies confirm the picture that the size of proton increases systematically with increasing energies, while the size of the constituent quarks and diquarks remains approximately independent of (or only increases slightly with) the colliding energy. The detailed analysis indicates correlations between model parameters and also indicates an increasing role of shadowing at LHC energies. Within the investigated class of models, a simple and model-independent phenomenological relation was discovered that connects the total p+p scattering cross-section to the effective quark, diquark size and their average separation. Our best fits indicate that the relative error of this phenomenological relation is 10-15% in the considered energy range.

  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. 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

  6. Initial conditions from the shadowed Glauber model for Pb + Pb collisions at √{sN N}=2.76 TeV

    NASA Astrophysics Data System (ADS)

    Ghosh, Snigdha; Singh, Sushant K.; Chatterjee, Sandeep; Alam, Jane; Sarkar, Sourav

    2016-05-01

    We study the initial conditions for Pb +Pb collisions at √{sN N}=2.76 TeV using the two-component Monte-Carlo Glauber model with shadowing of the nucleons in the interior by the leading ones. The model parameters are fixed by comparing them to the multiplicity data of p +Pb and Pb +Pb collisions at √{sN N}=5.02 and 2.76 TeV, respectively. We then compute the centrality dependence of the eccentricities up to the fourth order as well as their event-by-event distributions. The inclusion of shadowing brings the Monte-Carlo Glauber model predictions in agreement with data as well as with results from other dynamical models of initial conditions based on gluon saturation at high-energy nuclear collisions. Further, we find that the shadowed Glauber model provides the desired relative magnitude between the ellipticity and the triangularity of the initial energy distribution required to explain the data on the even and odd flow harmonics v2 and v3, respectively, at the CERN Large Hadron Collider.

  7. 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-…

  8. 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.

  9. 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.

  10. 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. PMID:14663849

  11. 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,…

  12. 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…

  13. 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…

  14. 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…

  15. 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…

  16. 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…

  17. 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.

  18. TCD: A Text-Based UML Class Diagram Notation and Its Model Converters

    NASA Astrophysics Data System (ADS)

    Washizaki, Hironori; Akimoto, Masayoshi; Hasebe, Atsushi; Kubo, Atsuto; Fukazawa, Yoshiaki

    Among several diagrams defined in UML, the class diagram is particularly useful through entire software development process, from early domain analysis stages to later maintenance stages. However conventional UML environments are often inappropriate for collaborative modeling in physically remote locations, such as exchanging models on a public mailing list via email. To overcome this issue, we propose a new diagram notation, called "TCD" (Text-based uml Class Diagram), for describing UML class diagrams using ASCII text. Since text files can be easily created, modified and exchanged in anywhere by any computing platforms, TCD facilitates the collaborative modeling with a number of unspecified people. Moreover, we implemented model converters for converting in both directions between UML class diagrams described in the XMI form and those in the TCD form. By using the converters, the reusability of models can be significantly improved because many of UML modeling tools support the XMI for importing and exporting modeling data.

  19. Elliptic flow in Pb+Pb collisions at sNN = 2.76 TeV: Hybrid model assessment of the first data

    NASA Astrophysics Data System (ADS)

    Hirano, Tetsufumi; Huovinen, Pasi; Nara, Yasushi

    2011-07-01

    We analyze the elliptic flow parameter v2 in Pb+Pb collisions at sNN = 2.76 TeV and in Au+Au collisions at sNN=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 v2(pT) hardly changes when the collision energy increases, whereas the integrated v2 increases due to the enhancement of mean transverse momentum. The amount of increase of both v2 and mean pT depends significantly on the model of initialization.

  20. 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.

  1. 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).

  2. 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.

  3. The Accounting Class as Accounting Firm: A Model Program for Developing Technical and Managerial Skills

    ERIC Educational Resources Information Center

    Docherty, Gary

    1976-01-01

    One way to bring the accounting office into the classroom is to conduct the class as a "company." Such a class is aimed at developing students' technical and managerial skills, as well as their career awareness and career goals. Performance goals, a course description, and overall objectives of the course are given and might serve as a model.…

  4. 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.…

  5. 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…

  6. 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…

  7. 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

  8. 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

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; 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.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; 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.; Randle-conde, A.; 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.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Poyraz, D.; 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, W. L.; Alves, G. A.; Brito, L.; Correa Martins, M.; Dos Reis Martins, T.; Molina, J.; Mora Herrera, C.; Pol, M. E.; Rebello Teles, P.; 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.; Hadjiiska, R.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Zhang, F.; Zhang, L.; Zou, W.; Avila, C.; Cabrera, A.; 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.; Rykaczewski, H.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Ellithi Kamel, A.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; 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.; Chapon, E.; Charlot, C.; Dahms, T.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; 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.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Bernet, C.; Boudoul, G.; Bouvier, E.; Brochet, S.; CarrilloMontoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. 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.; Heister, A.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Sammet, J.; Schael, S.; Schomakers, C.; Schulte, J. F.; Sprenger, D.; 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.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asin, I.; Bartosik, N.; Behr, J.; Behrens, U.; Bell, A. J.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, I.; 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.; 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.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Junkes, A.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Ott, J.; Peiffer, T.; Perieanu, A.; 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.; Gilbert, A.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Lobelle Pardo, P.; Mozer, M. U.; Müller, T.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; 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.; Tziaferi, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; 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.; Makovec, A.; 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.; 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.; Gan-guly, 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.; Sharma, S.; 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.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; Cristella, L.; 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.; Verwilligen, P.; 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.; 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.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Fanzago, F.; Gasparini, F.; Gasparini, U.; Gonella, F.; Gozzelino, A.; 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.; Fedi, G.; 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.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; 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.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; 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.; Ryu, M. S.; Kim, J. Y.; Moon, D. H.; 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.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Ali, M. A. B. Md; Wan Abdullah, W. A. T.; Casimiro Linares, E.; 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.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Khurshid, T.; 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.; 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.; Vadruccio, D.; Varela, J.; Vischia, P.; Bunin, P.; Golutvin, I.; Gorbunov, I.; 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.; Kuznetsova, E.; 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.; Pozdnyakov, I.; 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.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, 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.; 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.; 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.; 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.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; 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.; Kasieczka, G.; Lustermann, W.; Mangano, B.; Marini, A. C.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Musella, P.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Perrozzi, L.; 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.; Ngadiuba, J.; Pinna, D.; Robmann, P.; Ronga, F. J.; Taroni, S.; 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.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Petrakou, E.; Tsai, J. F.; 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.; Guler, Y.; 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.; Zorbilmez, C.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Isildak, B.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; 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.; Sakuma, T.; Seif El Nasr-storey, S.; Senkin, S.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Elwood, A.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Pastika, N.; Scarborough, T.; Wu, Z.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Sagir, S.; 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.; 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.; 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.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; 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.; Mullin, S. D.; 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.; Pierini, M.; Spiropulu, M.; 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.; Krohn, M.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; 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.; 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.; 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.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; 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.; 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.; Mei, H.; 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, J. R.; 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.; 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.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Haytmyradov, M.; Khristenko, V.; 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.; Yi, K.; Anderson, I.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Xiao, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Gray, J.; Kenny, R. P.; Majumder, D.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Mignerey, A. C.; Pedro, K.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bierwagen, K.; Busza, W.; Cali, I. A.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. 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.; Nourbakhsh, S.; 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.; Meier, F.; Ratnikov, 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.; 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.; Trovato, M.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Lynch, S.; Marinelli, N.; Musienko, Y.; Pearson, T.; Planer, M.; Ruchti, R.; Smith, G.; 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.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; 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.; Malik, S.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Miller, D. H.; Neumeister, N.; Primavera, F.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; 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.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Hindrichs, O.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Verzetti, M.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; 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.; Hughes, E.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Dalchenko, M.; De Mattia, M.; Dildick, S.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Patel, R.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Ulmer, K. 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.; Wolfe, E.; 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.; Vuosalo, C.; Woods, N.

    2015-04-01

    A 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 = 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. The observations are consistent with expectations from standard model processes and are interpreted in terms of upper limits on the production of supersymmetric particles. [Figure not available: see fulltext.

  11. 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.

  12. 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.

  13. Hierarchical Multinomial Processing Tree Models: A Latent-Class Approach

    ERIC Educational Resources Information Center

    Klauer, Karl Christoph

    2006-01-01

    Multinomial processing tree models are widely used in many areas of psychology. Their application relies on the assumption of parameter homogeneity, that is, on the assumption that participants do not differ in their parameter values. Tests for parameter homogeneity are proposed that can be routinely used as part of multinomial model analyses to…

  14. 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…

  15. 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…

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

    NASA Astrophysics Data System (ADS)

    Cho, Hsun-Jung; Lo, Shih-Ching

    2002-09-01

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

  17. Robust Validation of ENSO in IPCC-Class Coupled Models

    NASA Astrophysics Data System (ADS)

    Stevenson, Samantha; Fox-Kemper, Baylor; Jochum, Markus

    2010-05-01

    Wavelet probability analysis, a new method of model validation, is used to assess the performance of ENSO in a variety of coupled climate models. Wavelet probability analysis relies on wavelet spectra for a given time series, for which the amount of spectral overlap between subsets is measured using a quantity known as the wavelet probability index (WPI). This approach provides quantitative estimates of model agreement relative to either observations or other models, accompanied by well-defined confidence levels. ENSO, as represented by the NINO3.4 index, has been examined in 2,000 year long coupled integrations of both the new NCAR CCSM3.5 and GFDL's CM2.1; interestingly, it is not possible to distinguish either model from observations of NINO3.4 during 1949-2003, for runs shorter than 200 years. At longer model run lengths, some inaccuracies are seen in both CCSM3.5 and CM2.1 relative to observations. CCSM3.5 and CM2.1 are compared to one another using hypothesis testing procedures, and changes in model physics discussed in terms of their impact on ENSO. Finally, the method is applied to non-equilibrium simulations, using both high-CO2 'ramp-up' runs and selected IPCC AR4 integrations. This allows the effect of changing CO2 levels on ENSO activity to be examined, and the statistical significance of such effects to be determined.

  18. 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.

  19. Similarity between class A and class B G-protein-coupled receptors exemplified through calcitonin gene-related peptide receptor modelling and mutagenesis studies

    PubMed Central

    Vohra, Shabana; Taddese, Bruck; Conner, Alex C.; Poyner, David R.; Hay, Debbie L.; Barwell, James; Reeves, Philip J.; Upton, Graham J. G.; Reynolds, Christopher A.

    2013-01-01

    Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A–class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg2.39, His2.43 and Glu3.46, which makes a polar lock with T6.37. These alignments and models provide useful tools for understanding class B GPCR function. PMID:23235263

  20. Detection of new genes in a bacterial genome using Markov models for three gene classes.

    PubMed

    Borodovsky, M; McIninch, J D; Koonin, E V; Rudd, K E; Médigue, C; Danchin, A

    1995-09-11

    We further investigated the statistical features of the three classes of Escherichia coli genes that have been previously delineated by factorial correspondence analysis and dynamic clustering methods. A phased Markov model for a nucleotide sequence of each gene class was developed and employed for gene prediction using the GeneMark program. The protein-coding region prediction accuracy was determined for class-specific Markov models of different orders when the programs implementing these models were applied to gene sequences from the same or other classes. It is shown that at least two training sets and two program versions derived for different classes of E. coli genes are necessary in order to achieve a high accuracy of coding region prediction for uncharacterized sequences. Some annotated E. coli genes from Class I and Class III are shown to be spurious, whereas many open reading frames (ORFs) that have not been annotated in GenBank as genes are predicted to encode proteins. The amino acid sequences of the putative products of these ORFs initially did not show similarity to already known proteins. However, conserved regions have been identified in several of them by screening the latest entries in protein sequence databases and applying methods for motif search, while some other of these new genes have been identified in independent experiments. PMID:7567469

  1. TeV lepton number violation: From neutrinoless double-β decay to the LHC

    NASA Astrophysics Data System (ADS)

    Peng, Tao; Ramsey-Musolf, Michael J.; Winslow, Peter

    2016-05-01

    We analyze the sensitivity of next-generation tonne-scale neutrinoless double-β decay (0 ν β β ) experiments and searches for same-sign di-electrons plus jets at the Large Hadron Collider to TeV scale lepton number violating interactions. Taking into account previously unaccounted for physics and detector backgrounds at the LHC, renormalization group evolution, and long-range contributions to 0 ν β β nuclear matrix elements, we find that the reach of tonne-scale 0 ν β β generally exceeds that of the LHC for a class of simplified models. However, for a range of heavy particle masses near the TeV scale, the high luminosity LHC and tonne-scale 0 ν β β may provide complementary probes.

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

    USGS Publications Warehouse

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

    2015-01-01

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

  3. Modeling instruction: Positive attitudinal shifts in introductory physics measured with CLASS

    NASA Astrophysics Data System (ADS)

    Brewe, Eric; Kramer, Laird; O'Brien, George

    2009-06-01

    Among the most surprising findings in Physics Education Research is the lack of positive results on attitudinal measures, such as Colorado Learning Attitudes about Science Survey (CLASS) and Maryland Physics Expectations Survey (MPEX). The uniformity with which physics teaching manages to negatively shift attitudes toward physics learning is striking. Strategies which have been shown to improve conceptual learning, such as interactive engagement and studio-format classes, provide more authentic science experiences for students; yet do not seem to be sufficient to produce positive attitudinal results. Florida International University’s Physics Education Research Group has implemented Modeling Instruction in University Physics classes as part of an overall effort toward building a research and learning community. Modeling Instruction is explicitly designed to engage students in scientific practices that include model building, validation, and revision. Results from a preinstruction/postinstruction CLASS measurement show attitudinal improvements through both semesters of an introductory physics sequence, as well as over the entire two-course sequence. In this Brief Report, we report positive shifts from the CLASS in one section of a modeling-based introductory physics sequence, for both mechanics (N=22) and electricity and magnetism (N=23) . Using the CLASS results and follow up interviews, we examine how these results reflect on modeling instruction and the unique student community and population at FIU.

  4. 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...

  5. Evolution of perturbations in distinct classes of canonical scalar field models of dark energy

    SciTech Connect

    Jassal, H. K.

    2010-04-15

    Dark energy must cluster in order to be consistent with the equivalence principle. The background evolution can be effectively modeled by either a scalar field or by a barotropic fluid. The fluid model can be used to emulate perturbations in a scalar field model of dark energy, though this model breaks down at large scales. In this paper we study evolution of dark energy perturbations in canonical scalar field models: the classes of thawing and freezing models. The dark energy equation of state evolves differently in these classes. In freezing models, the equation of state deviates from that of a cosmological constant at early times. For thawing models, the dark energy equation of state remains near that of the cosmological constant at early times and begins to deviate from it only at late times. Since the dark energy equation of state evolves differently in these classes, the dark energy perturbations too evolve differently. In freezing models, since the equation of state deviates from that of a cosmological constant at early times, there is a significant difference in evolution of matter perturbations from those in the cosmological constant model. In comparison, matter perturbations in thawing models differ from the cosmological constant only at late times. This difference provides an additional handle to distinguish between these classes of models and this difference should manifest itself in the integrated Sachs-Wolfe effect.

  6. 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.

  7. 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

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

    PubMed

    Chatrchyan, S; Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Bergauer, T; Dragicevic, M; Erö, J; Fabjan, C; Friedl, M; Frühwirth, R; Ghete, V M; Hammer, J; Hänsel, S; Hoch, M; Hörmann, N; Hrubec, J; Jeitler, M; Kasieczka, G; Kiesenhofer, W; Krammer, M; Liko, D; Mikulec, I; Pernicka, M; Rohringer, H; Schöfbeck, R; Strauss, J; Teischinger, F; Wagner, P; Waltenberger, W; Walzel, G; Widl, E; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Benucci, L; De Wolf, E A; Janssen, X; Maes, T; Mucibello, L; Ochesanu, S; Roland, B; Rougny, R; Selvaggi, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Blekman, F; Blyweert, S; D'Hondt, J; Devroede, O; Gonzalez Suarez, R; Kalogeropoulos, A; Maes, J; Maes, M; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Villella, I; Charaf, O; Clerbaux, B; De Lentdecker, G; Dero, V; Gay, A P R; Hammad, G H; Hreus, T; Marage, P E; Thomas, L; Vander Velde, C; Vanlaer, P; Adler, V; Cimmino, A; Costantini, S; Grunewald, M; Klein, B; Lellouch, J; Marinov, A; McCartin, J; Ryckbosch, D; Thyssen, F; Tytgat, M; Vanelderen, L; Verwilligen, P; Walsh, S; Zaganidis, N; Basegmez, S; Bruno, G; Caudron, J; Ceard, L; Cortina Gil, E; De Favereau De Jeneret, J; Delaere, C; Favart, D; Giammanco, A; Grégoire, G; Hollar, J; Lemaitre, V; Liao, J; Militaru, O; Ovyn, S; Pagano, D; Pin, A; Piotrzkowski, K; Schul, N; Beliy, N; Caebergs, T; Daubie, E; Alves, G A; Damiao, D De Jesus; Pol, M E; Souza, M H G; Carvalho, W; Da Costa, E M; Martins, C De Oliveira; De Souza, S Fonseca; Mundim, L; Nogima, H; Oguri, V; Da Silva, W L Prado; Santoro, A; Do Amaral, S M Silva; Sznajder, A; De Araujo, F Torres Da Silva; Dias, F A; Tomei, T R Fernandez Perez; Gregores, E M; Lagana, C; Marinho, F; Mercadante, P G; Novaes, S F; Padula, Sandra S; Darmenov, N; Dimitrov, L; Genchev, V; Iaydjiev, P; Piperov, S; Rodozov, M; Stoykova, S; Sultanov, G; Tcholakov, V; Trayanov, R; Vankov, I; Dimitrov, A; Hadjiiska, R; Karadzhinova, A; Kozhuharov, V; Litov, L; Mateev, M; Pavlov, B; Petkov, P; Bian, J G; Chen, G M; Chen, H S; Jiang, C H; Liang, D; Liang, S; Meng, X; Tao, J; Wang, J; Wang, J; Wang, X; Wang, Z; Xiao, H; Xu, M; Zang, J; Zhang, Z; Ban, Y; Guo, S; Guo, Y; Li, W; Mao, Y; Qian, S J; Teng, H; Zhang, L; Zhu, B; Zou, W; Cabrera, A; Moreno, B Gomez; Rios, A A Ocampo; Oliveros, A F Osorio; Sanabria, J C; Godinovic, N; Lelas, D; Lelas, K; Plestina, R; Polic, D; Puljak, I; Antunovic, Z; Dzelalija, M; Brigljevic, V; Duric, S; Kadija, K; Morovic, S; Attikis, A; Galanti, M; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Finger, M; Finger, M; Assran, Y; Khalil, S; Mahmoud, M A; Hektor, A; Kadastik, M; Müntel, M; Raidal, M; Rebane, L; Azzolini, V; Eerola, P; Fedi, G; Czellar, S; Härkönen, J; Heikkinen, A; Karimäki, V; Kinnunen, R; Kortelainen, M J; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Tuominen, E; Tuominiemi, J; Tuovinen, E; Ungaro, D; Wendland, L; Banzuzi, K; Korpela, A; Tuuva, T; Sillou, D; Besancon, M; Choudhury, S; Dejardin, M; Denegri, D; Fabbro, B; Faure, J L; Ferri, F; Ganjour, S; Gentit, F X; Givernaud, A; Gras, P; de Monchenault, G Hamel; Jarry, P; Locci, E; Malcles, J; Marionneau, M; Millischer, L; Rander, J; Rosowsky, A; Shreyber, I; Titov, M; Verrecchia, P; Baffioni, S; Beaudette, F; Benhabib, L; Bianchini, L; Bluj, M; Broutin, C; Busson, P; Charlot, C; Dahms, T; Dobrzynski, L; Elgammal, S; de Cassagnac, R Granier; Haguenauer, M; Miné, P; Mironov, C; Ochando, C; Paganini, P; Sabes, D; Salerno, R; Sirois, Y; Thiebaux, C; Wyslouch, B; Zabi, A; Agram, J-L; Andrea, J; Bloch, D; Bodin, D; Brom, J-M; Cardaci, M; Chabert, E C; Collard, C; Conte, E; Drouhin, F; Ferro, C; Fontaine, J-C; Gelé, D; Goerlach, U; Greder, S; Juillot, P; Karim, M; Le Bihan, A-C; Mikami, Y; Van Hove, P; Fassi, F; Mercier, D; Baty, C; Beauceron, S; Beaupere, N; Bedjidian, M; Bondu, O; Boudoul, G; Boumediene, D; Brun, H; Chierici, R; Contardo, D; Depasse, P; El Mamouni, H; Fay, J; Gascon, S; Ille, B; Kurca, T; Le Grand, T; Lethuillier, M; Mirabito, L; Perries, S; Sordini, V; Tosi, S; Tschudi, Y; Verdier, P; Lomidze, D; Anagnostou, G; Edelhoff, M; Feld, L; Heracleous, N; Hindrichs, O; Jussen, R; Klein, K; Merz, J; Mohr, N; Ostapchuk, A; Perieanu, A; Raupach, F; Sammet, J; Schael, S; Sprenger, D; Weber, H; Weber, M; Wittmer, B; Ata, M; Bender, W; Dietz-Laursonn, E; Erdmann, M; Frangenheim, J; Hebbeker, T; Hinzmann, A; Hoepfner, K; Klimkovich, T; Klingebiel, D; Kreuzer, P; Lanske, D; Magass, C; Merschmeyer, M; Meyer, A; Papacz, P; Pieta, H; Reithler, H; Schmitz, S A; Sonnenschein, L; Steggemann, J; Teyssier, D; Tonutti, M; Bontenackels, M; Davids, M; Duda, M; Flügge, G; Geenen, H; Giffels, M; Ahmad, W Haj; Heydhausen, D; Kress, T; Kuessel, Y; Linn, A; Nowack, A; Perchalla, L; Pooth, O; Rennefeld, J; Sauerland, P; Stahl, A; Thomas, M; Tornier, D; Zoeller, M H

    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

  9. 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.

  10. Dynamic behaviors of a class of HIV compartmental models

    NASA Astrophysics Data System (ADS)

    Chen, Xiaoyan; Huang, Lihong; Yu, Pei

    2015-06-01

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

  11. 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.

  12. 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?…

  13. Parametric latent class joint model for a longitudinal biomarker and recurrent events

    PubMed Central

    Han, Jun; Slate, Elizabeth H.; Peña, Edsel A.

    2014-01-01

    SUMMARY A joint model for a longitudinal biomarker and recurrent events is proposed. This general model accommodates the effects of covariates on the biomarker and event processes, the effects of accumulating event occurrences, and effects caused by interventions after each event occurrence. Association between the biomarker and recurrent event processes is captured through a latent class structure, which also serves to handle an underlying heterogeneous population. We use the EM algorithm for maximum likelihood estimation of the model parameters and a penalized likelihood measure to determine the number of latent classes. This joint model is validated by simulation and illustrated with a data set from epileptic seizure study. PMID:17542002

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

    PubMed Central

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

    2014-01-01

    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 probabilities depend on some observed explanatory variables and data missingness depends on both the explanatory variables and a latent class variable. A full Bayesian method is then proposed to estimate the model. Through the data augmentation method, conditional posterior distributions for all model parameters and missing data are obtained. A Gibbs sampling procedure is then used to generate Markov chains of model parameters for statistical inference. The application of the model and the method is first demonstrated through the analysis of mathematical ability growth data from the National Longitudinal Survey of Youth 1997 (Bureau of Labor Statistics, U.S. Department of Labor, 1997). A simulation study considering 3 main factors (the sample size, the class probability, and the missing data mechanism) is then conducted and the results show that the proposed Bayesian estimation approach performs very well under the studied conditions. Finally, some implications of this study, including the misspecified missingness mechanism, the sample size, the sensitivity of the model, the number of latent classes, the model comparison, and the future directions of the approach, are discussed. PMID:24790248

  15. 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).

  16. Unsupervised learning of broad phonetic classes with a statistical mixture model

    NASA Astrophysics Data System (ADS)

    Lin, Ying

    2001-05-01

    Unsupervised learning of broad phonetic classes by infants was simulated using a statistical mixture model. A mixture model assumes that data are generated by a certain number of different sources-in this case, broad phonetic classes. With the phonetic labels removed, hand-transcribed segments from the TIMIT database were used in model-based clustering to obtain data-driven classes. Simple hidden Markov models were chosen to be the components of the mixture, with mel-cepstral coefficients as the front end. The mixture model was trained using an expectation-maximization-like algorithm. The EM-like algorithm was initialized by a K-means procedure and then applied to estimate the parameters of the mixture model after iteratively partitioning the clusters. The results of running this algorithm on the TIMIT segments suggested that the partitions may be interpreted as gradient acoustic features, and that to some degree the resulting clusters correspond to knowledge-based phonetic classes. Although such correspondences are rather rough, a careful examination of the clusters showed that the class membership of some sounds is highly dependent on their phonetic contexts. Thus, the clusters may reflect the preliminary phonological categories formed during language learning in early childhood.

  17. 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.

  18. 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

  19. Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons.

    PubMed

    Pospischil, Martin; Toledo-Rodriguez, Maria; Monier, Cyril; Piwkowska, Zuzanna; Bal, Thierry; Frégnac, Yves; Markram, Henry; Destexhe, Alain

    2008-11-01

    We review here the development of Hodgkin-Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected the four most prominent electrophysiological classes of neurons. These four classes are "fast spiking", "regular spiking", "intrinsically bursting" and "low-threshold spike" cells. For each class, we fit "minimal" HH type models to experimental data. The models contain the minimal set of voltage-dependent currents to account for the data. To obtain models as generic as possible, we used data from different preparations in vivo and in vitro, such as rat somatosensory cortex and thalamus, guinea-pig visual and frontal cortex, ferret visual cortex, cat visual cortex and cat association cortex. For two cell classes, we used automatic fitting procedures applied to several cells, which revealed substantial cell-to-cell variability within each class. The selection of such cellular models constitutes a necessary step towards building network simulations of the thalamocortical system with realistic cellular dynamical properties. PMID:19011929

  20. The Motivational Construct in Mathematics Learning Using Structural Equation Modeling: The Korean Elementary School Math Class.

    ERIC Educational Resources Information Center

    Seo, Daeryong

    This study was undertaken to understand a motivation model in the context of the Korean elementary school mathematics class. The sample consisted of 178 fourth graders (boys=95; girls=83) from 2 Korean elementary schools. This study showed that a goal mediational model could be modified and successfully applied to the context of the Korean…

  1. 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…

  2. Building an Identifiable Latent Class Model with Covariate Effects on Underlying and Measured Variables

    ERIC Educational Resources Information Center

    Huang, Guan-Hua; Bandeen-Roche, Karen

    2004-01-01

    In recent years, latent class models have proven useful for analyzing relationships between measured multiple indicators and covariates of interest. Such models summarize shared features of the multiple indicators as an underlying categorical variable, and the indicators' substantive associations with predictors are built directly and indirectly…

  3. Limits on the production of the standard model Higgs boson in pp collisions at sqrt{s} = 7 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

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J.; Sloper, J.; Smakhtin, V.; Smirnov, S. Yu.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, D.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snuverink, J.; Snyder, S.; Soares, M.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Sondericker, J.; Soni, N.; Sopko, V.; Sopko, B.; Sorbi, M.; Sosebee, M.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiriti, E.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; Denis, R. D. St.; Stahl, T.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Stavropoulos, G.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G. A.; Stillings, J. A.; Stockmanns, T.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Soh, D. A.; Su, D.; Subramania, H. S.; Succurro, A.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Sviridov, Yu. M.; Swedish, S.; Sykora, I.; Sykora, T.; Szeless, B.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taga, A.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanaka, Y.; Tani, K.; Tannoury, N.; Tappern, G. P.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Castanheira, M. Teixeira Dias; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R. J.; Thadome, J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomson, E.; Thomson, M.; Thun, R. P.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timmermans, C. J. W. P.; Tipton, P.; Tique Aires Viegas, F. J.; Tisserant, S.; Tobias, J.; Toczek, B.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokunaga, K.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, G.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torchiani, I.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Traynor, D.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Trinh, T. N.; Tripiana, M. F.; Trischuk, W.; Trivedi, A.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Tyrvainen, H.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Underwood, D. G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urkovsky, E.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valenta, J.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van der Graaf, H.; van der Kraaij, E.; Van Der Leeuw, R.; van der Poel, E.; van der Ster, D.; Van Eijk, B.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vandoni, G.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Varela Rodriguez, F.; Vari, R.; Varnes, E. W.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Vegni, G.; Veillet, J. J.; Vellidis, C.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Virzi, J.; Vitells, O.; Viti, M.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobiev, A. P.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Anh, T. Vu; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wakabayashi, J.; Walbersloh, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Wang, C.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, J. C.; Wang, R.; Wang, S. M.; Warburton, A.; Ward, C. P.; Warsinsky, M.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, J.; Weber, M.; Weber, M. S.; Weber, P.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P. 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M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xie, Y.; Xu, C.; Xu, D.; Xu, G.; Yabsley, B.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, W.-M.; Yao, Y.; Yasu, Y.; Ybeles Smit, G. V.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.; Yu, D.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaets, V. G.; Zaidan, R.; Zaitsev, A. M.; Zajacova, Z.; Zalite, Yo. K.; Zanello, L.; Zarzhitsky, P.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zemla, A.; Zendler, C.; Zenin, A. V.; Zenin, O.; Ženiš, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; della Porta, G. Zevi; Zhan, Z.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zheng, S.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zieminska, D.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zolnierowski, Y.; Zsenei, A.; zur Nedden, M.; Zutshi, V.; Zwalinski, L.

    2011-09-01

    A search for the Standard Model Higgs boson at the Large Hadron Collider (LHC) running at a centre-of-mass energy of 7 TeV is reported, based on a total integrated luminosity of up to 40 pb-1 collected by the ATLAS detector in 2010. Several Higgs boson decay channels: H→ γγ, H→ ZZ (∗)→ ℓℓℓℓ, H→ ZZ→ ℓℓνν, H→ ZZ→ ℓℓqq, H→ WW (∗)→ ℓνℓν and H→ WW→ ℓνqq ( ℓ is e, μ) are combined in a mass range from 110 GeV to 600 GeV. The highest sensitivity is achieved in the mass range between 160 GeV and 170 GeV, where the expected 95% CL exclusion sensitivity is at Higgs boson production cross sections 2.3 times the Standard Model prediction. Upper limits on the cross section for its production are determined. Models with a fourth generation of heavy leptons and quarks with Standard Model-like couplings to the Higgs boson are also investigated and are excluded at 95% CL for a Higgs boson mass in the range from 140 GeV to 185 GeV.

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

    SciTech Connect

    Chatrchyan, Serguei; et al.

    2012-03-01

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

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

    SciTech Connect

    Chatrchyan, S.; et al.,

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Csörgő, T.; Nemes, F.

    2014-01-01

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

  7. 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.

  8. 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

  9. 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

  10. 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

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

    PubMed

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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

  12. 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.

  13. 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

  14. 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.

    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

  15. 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. PMID:26082312

  16. A Structural Model of Task Values, Goal Orientations, and Learning Strategies in Elementary School Mathematics Class.

    ERIC Educational Resources Information Center

    Seo, Daeryong; Park, Yong Hui

    A goal mediational model to conceptualize the effects of students' motivational beliefs on their learning strategies was modified with the three goal orientations: task, performance-approach, and performance-avoidance goals. Questionnaires were administered to 161 Korean fifth graders (boys = 88; girls = 73) in an elementary school math class.…

  17. 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…

  18. 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…

  19. 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…

  20. 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…

  1. 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…

  2. 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…

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

    ERIC Educational Resources Information Center

    Li, Jun

    2012-01-01

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

  4. 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…

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

    ERIC Educational Resources Information Center

    Adwere-Boamah, Joseph

    2011-01-01

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

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

    ERIC Educational Resources Information Center

    Uzun, Naim

    2009-01-01

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

  7. Azimuthal anisotropies of reconstructed jets in Pb + Pb collisions at √sNN =2.76 TeV in a multiphase transport model

    NASA Astrophysics Data System (ADS)

    Nie, Mao-Wu; Ma, Guo-Liang

    2014-07-01

    Azimuthal anisotropies of reconstructed jets [vnjet(n=2,3)] have been investigated in Pb + Pb collisions at the center of mass energy √sNN =2.76 TeV within a framework of a multiphase transport (AMPT) model. The v2jet is in good agreement with the recent ATLAS data. However, the v3jet shows a smaller magnitude than v2jet, and approaches zero at a larger transverse momentum. It is attributed to the path-length dependence in which the jet energy loss fraction depends on the azimuthal angles with respect to different orders of event planes. The ratio vnjet/εn increases from peripheral to noncentral collisions, and vnjet increases with the initial spatial asymmetry (εn) for a given centrality bin. These behaviors indicate that the vnjet is produced by the strong interactions between jet and the partonic medium with different initial geometry shapes. Therefore, azimuthal anisotropies of reconstructed jet are proposed as a good probe to study the initial spatial fluctuations, which are expected to provide constraints on the path-length dependence of jet quenching models.

  8. 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

  9. 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.

  10. New class of Johnson SB distributions and its associated regression model for rates and proportions.

    PubMed

    Lemonte, Artur J; Bazán, Jorge L

    2016-07-01

    By starting from the Johnson SB distribution pioneered by Johnson (), we propose a broad class of distributions with bounded support on the basis of the symmetric family of distributions. The new class of distributions provides a rich source of alternative distributions for analyzing univariate bounded data. A comprehensive account of the mathematical properties of the new family is provided. We briefly discuss estimation of the model parameters of the new class of distributions based on two estimation methods. Additionally, a new regression model is introduced by considering the distribution proposed in this article, which is useful for situations where the response is restricted to the standard unit interval and the regression structure involves regressors and unknown parameters. The regression model allows to model both location and dispersion effects. We define two residuals for the proposed regression model to assess departures from model assumptions as well as to detect outlying observations, and discuss some influence methods such as the local influence and generalized leverage. Finally, an application to real data is presented to show the usefulness of the new regression model. PMID:26659998

  11. 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.

  12. Implications of the diboson excess for neutrinoless double beta decay and lepton flavor violation in TeV scale left-right symmetric model

    NASA Astrophysics Data System (ADS)

    Awasthi, Ram Lal; Dev, P. S. Bhupal; Mitra, Manimala

    2016-01-01

    Inspired by the recent diboson excess observed at the LHC and possible interpretation within a TeV-scale left-right symmetric framework, we explore its implications for low-energy experiments searching for lepton number and flavor violation. Assuming a simple type-II seesaw mechanism for neutrino masses, we show that for the right-handed (RH) gauge boson mass and coupling values required to explain the LHC anomalies, the RH contribution to the lepton number violating process of neutrinoless double beta decay (0 ν β β ) is already constrained by current experiments for relatively low-mass (MeV-GeV) RH neutrinos. The future ton-scale 0 ν β β experiments could probe most of the remaining parameter space, irrespective of the neutrino mass hierarchy and uncertainties in the oscillation parameters and nuclear matrix elements. On the other hand, the RH contribution to the lepton flavor violating process of μ →e γ is constrained for relatively heavier (TeV) RH neutrinos, thus providing a complementary probe of the model. Finally, a measurement of the absolute light neutrino mass scale from future precision cosmology could make this scenario completely testable.

  13. Search for scalar top quark pair production in natural gauge mediated supersymmetry models with the ATLAS detector in pp collisions at √{ s} = 7 TeV

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdelalim, A. A.; Abdinov, O.; Abi, B.; Abolins, M.; Abouzeid, O. S.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Akiyama, A.; Alam, M. S.; Alam, M. A.; Albert, J.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Allbrooke, B. M. M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anisenkov, A.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Aubert, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Avramidou, R.; Axen, D.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, V.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beale, S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, S.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Behar Harpaz, S.; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertella, C.; Bertin, A.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blazek, T.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boelaert, N.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Bolnet, N. M.; Bomben, M.; Bona, M.; Bondioli, M.; Boonekamp, M.; Booth, C. N.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borri, M.; Borroni, S.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Botterill, D.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozhko, N. I.; Bozovic-Jelisavcic, I.; Bracinik, J.; Branchini, P.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brelier, B.; Bremer, J.; Brendlinger, K.; Brenner, R.; Bressler, S.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brodet, E.; Broggi, F.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, W. K.; Brown, G.; Brown, H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Buanes, T.; Buat, Q.; Bucci, F.; Buchanan, J.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Budick, B.; Büscher, V.; Bugge, L.; Bulekov, O.; Bundock, A. C.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Caloi, R.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camarri, P.; Cameron, D.; Caminada, L. M.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Capasso, L.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capriotti, D.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, B.; Caron, S.; Carquin, E.; Carrillo Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Cascella, M.; Caso, C.; Castaneda Hernandez, A. M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N. F.; Cataldi, G.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cauz, D.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chan, K.; Chapleau, B.; Chapman, J. D.; Chapman, J. W.; Chareyre, E.; Charlton, D. G.; Chavda, V.; Chavez Barajas, C. A.; Cheatham, S.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, X.; Cheplakov, A.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Cheung, S. L.; Chevalier, L.; Chiefari, G.; Chikovani, L.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chizhov, M. V.; Choudalakis, G.; Chouridou, S.; Christidi, I. A.; Christov, A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocca, C.; Ciocio, A.; Cirilli, M.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coe, P.; Cogan, J. G.; Coggeshall, J.; Cogneras, E.; Colas, J.; Colijn, A. P.; Collins, N. J.; Collins-Tooth, C.; Collot, J.; Colon, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Costin, T.; Côté, D.; Courneyea, L.; Cowan, G.; Cowden, C.; Cox, B. E.; Cranmer, K.; Crescioli, F.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crépé-Renaudin, S.; Cuciuc, C.-M.; Cuenca Almenar, C.; Cuhadar Donszelmann, T.; Curatolo, M.; Curtis, C. J.; Cuthbert, C.; Cwetanski, P.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dallapiccola, C.; Dam, M.; Dameri, M.; Damiani, D. S.; Danielsson, H. O.; Dao, V.; Darbo, G.; Darlea, G. L.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, E.; Davies, M.; Davison, A. R.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; de, K.; de Asmundis, R.; de Castro, S.; de Cecco, S.; de Graat, J.; de Groot, N.; de Jong, P.; de La Taille, C.; de la Torre, H.; de Lorenzi, F.; de Lotto, B.; de Mora, L.; de Nooij, L.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; de Zorzi, G.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Degenhardt, J.; Del Papa, C.; Del Peso, J.; Del Prete, T.; Delemontex, T.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Deng, J.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Devetak, E.; Deviveiros, P. O.; Dewhurst, A.; Dewilde, B.; Dhaliwal, S.; Dhullipudi, R.; di Ciaccio, A.; di Ciaccio, L.; di Girolamo, A.; di Girolamo, B.; di Luise, S.; di Mattia, A.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; Diaz, M. A.; Diblen, F.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobbs, M.; Dobinson, R.; Dobos, D.; Dobson, E.; Dodd, J.; Doglioni, C.; Doherty, T.; Doi, Y.; Dolejsi, J.; Dolenc, I.; Dolezal, Z.; Dolgoshein, B. A.; Dohmae, T.; Donadelli, M.; Donega, M.; Donini, J.; Dopke, J.; Doria, A.; Dos Anjos, A.; Dotti, A.; Dova, M. T.; Doxiadis, A. D.; Doyle, A. 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C.; Meyer, W. T.; Miao, J.; Michal, S.; Micu, L.; Middleton, R. P.; Migas, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Miller, D. W.; Miller, R. J.; Mills, W. J.; Mills, C.; Milov, A.; Milstead, D. A.; Milstein, D.; Minaenko, A. A.; Miñano Moya, M.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mirabelli, G.; Mitrevski, J.; Mitsou, V. A.; Mitsui, S.; Miyagawa, P. S.; Miyazaki, K.; Mjörnmark, J. U.; Moa, T.; Mockett, P.; Moed, S.; Moeller, V.; Mönig, K.; Möser, N.; Mohapatra, S.; Mohr, W.; Moles-Valls, R.; Molina-Perez, J.; Monk, J.; Monnier, E.; Montesano, S.; Monticelli, F.; Monzani, S.; Moore, R. W.; Moorhead, G. F.; Mora Herrera, C.; Moraes, A.; Morange, N.; Morel, J.; Morello, G.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, M.; Morii, M.; Morin, J.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moser, H. G.; Mosidze, M.; Moss, J.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Mueller, F.; Mueller, J.; Mueller, K.; Müller, T. A.; Mueller, T.; Muenstermann, D.; Munwes, Y.; Murray, W. J.; Mussche, I.; Musto, E.; Myagkov, A. G.; Myska, M.; Nadal, J.; Nagai, K.; Nagano, K.; Nagarkar, A.; Nagasaka, Y.; Nagel, M.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Nanava, G.; Napier, A.; Narayan, R.; Nash, M.; Nattermann, T.; Naumann, T.; Navarro, G.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negri, G.; Nektarijevic, S.; Nelson, A.; Nelson, T. K.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neusiedl, A.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen Thi Hong, V.; Nickerson, R. B.; Nicolaidou, R.; Nicolas, L.; Nicquevert, B.; Niedercorn, F.; Nielsen, J.; Nikiforou, N.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolics, K.; Nikolopoulos, K.; Nilsen, H.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishiyama, T.; Nisius, R.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Nordberg, M.; Norton, P. R.; Novakova, J.; Nozaki, M.; Nozka, L.; Nugent, I. M.; Nuncio-Quiroz, A.-E.; Nunes Hanninger, G.; Nunnemann, T.; Nurse, E.; O'Brien, B. J.; O'Neale, S. W.; O'Neil, D. C.; O'Shea, V.; Oakes, L. B.; Oakham, F. G.; Oberlack, H.; Ocariz, J.; Ochi, A.; Oda, S.; Odaka, S.; Odier, J.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohshima, T.; Okada, S.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Olchevski, A. G.; Olivares Pino, S. A.; Oliveira, M.; Oliveira Damazio, D.; Oliver Garcia, E.; Olivito, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onyisi, P. U. E.; Oram, C. J.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orlov, I.; Oropeza Barrera, C.; Orr, R. S.; Osculati, B.; Ospanov, R.; Osuna, C.; Otero Y Garzon, G.; Ottersbach, J. P.; Ouchrif, M.; Ouellette, E. A.; Ould-Saada, F.; Ouraou, A.; Ouyang, Q.; Ovcharova, A.; Owen, M.; Owen, S.; Ozcan, V. E.; Ozturk, N.; Pacheco Pages, A.; Padilla Aranda, C.; Pagan Griso, S.; Paganis, E.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Paleari, C. P.; Palestini, S.; Pallin, D.; Palma, A.; Palmer, J. D.; Pan, Y. B.; Panagiotopoulou, E.; Panikashvili, N.; Panitkin, S.; Pantea, D.; Papadelis, A.; Papadopoulou, Th. D.; Paramonov, A.; Paredes Hernandez, D.; Park, W.; Parker, M. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pashapour, S.; Pasqualucci, E.; Passaggio, S.; Passeri, A.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N.; Pater, J. R.; Patricelli, S.; Pauly, T.; Pecsy, M.; Pedraza Morales, M. I.; Peleganchuk, S. V.; Pelikan, D.; Peng, H.; Penning, B.; Penson, A.; Penwell, J.; Perantoni, M.; Perez, K.; Perez Cavalcanti, T.; Perez Codina, E.; Pérez García-Estañ, M. T.; Perez Reale, V.; Perini, L.; Pernegger, H.; Perrino, R.; Perrodo, P.; Persembe, S.; Peshekhonov, V. D.; Peters, K.; Petersen, B. A.; Petersen, J.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Petschull, D.; Petteni, M.; Pezoa, R.; Phan, A.; Phillips, P. W.; Piacquadio, G.; Picazio, A.; Piccaro, E.; Piccinini, M.; Piec, S. M.; Piegaia, R.; Pignotti, D. T.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Pinto, B.; Pizio, C.; Plamondon, M.; Pleier, M.-A.; Plotnikova, E.; Poblaguev, A.; Poddar, S.; Podlyski, F.; Poggioli, L.; Poghosyan, T.; Pohl, M.; Polci, F.; Polesello, G.; Policicchio, A.; Polini, A.; Poll, J.; Polychronakos, V.; Pomarede, D. M.; Pomeroy, D.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Portell Bueso, X.; Pospelov, G. E.; Pospisil, S.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Prabhu, R.; Pralavorio, P.; Pranko, A.; Prasad, S.; Pravahan, R.; Prell, S.; Pretzl, K.; Price, D.; Price, J.; Price, L. E.; Prieur, D.; Primavera, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Prudent, X.; Przybycien, M.; Przysiezniak, H.; Psoroulas, S.; Ptacek, E.; Pueschel, E.; Purdham, J.; Purohit, M.; Puzo, P.; Pylypchenko, Y.; Qian, J.; Qin, Z.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Quinonez, F.; Raas, M.; Radescu, V.; Radloff, P.; Rador, T.; Ragusa, F.; Rahal, G.; Rahimi, A. M.; Rahm, D.; Rajagopalan, S.; Rammensee, M.; Rammes, M.; Randle-Conde, A. S.; Randrianarivony, K.; Rauscher, F.; Rave, T. C.; Raymond, M.; Read, A. L.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Reinherz-Aronis, E.; Reinsch, A.; Reisinger, I.; Rembser, C.; Ren, Z. L.; Renaud, A.; Rescigno, M.; Resconi, S.; Resende, B.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter-Was, E.; Ridel, M.; Rijpstra, M.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Rios, R. R.; Riu, I.; Rivoltella, G.; Rizatdinova, F.; Rizvi, E.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocha de Lima, J. G.; Roda, C.; Roda Dos Santos, D.; Rodriguez, D.; Roe, A.; Roe, S.; Røhne, O.; Rolli, S.; Romaniouk, A.; Romano, M.; Romeo, G.; Romero Adam, E.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, A.; Rose, M.; Rosenbaum, G. A.; Rosenberg, E. I.; Rosendahl, P. L.; Rosenthal, O.; Rosselet, L.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rubinskiy, I.; Ruckert, B.; Ruckstuhl, N.; Rud, V. I.; Rudolph, C.; Rudolph, G.; Rühr, F.; Ruggieri, F.; Ruiz-Martinez, A.; Rumyantsev, L.; Runge, K.; Rurikova, Z.; Rusakovich, N. A.; Rutherfoord, J. P.; Ruwiedel, C.; Ruzicka, P.; Ryabov, Y. F.; Ryan, P.; Rybar, M.; Rybkin, G.; Ryder, N. C.; Saavedra, A. F.; Sadeh, I.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Sakamoto, H.; Salamanna, G.; Salamon, A.; Saleem, M.; Salek, D.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvachua Ferrando, B. M.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sampsonidis, D.; Samset, B. H.; Sanchez, A.; Sanchez Martinez, V.; Sandaker, H.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, T.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sansoni, A.; Santamarina Rios, C.; Santoni, C.; Santonico, R.; Santos, H.; Saraiva, J. G.; Sarangi, T.; Sarkisyan-Grinbaum, E.; Sarri, F.; Sartisohn, G.; Sasaki, O.; Sasao, N.; Satsounkevitch, I.; Sauvage, G.; Sauvan, E.; Sauvan, J. B.; Savard, P.; Savinov, V.; Savu, D. O.; Sawyer, L.; Saxon, D. H.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scallon, O.; Scannicchio, D. A.; Scarcella, M.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schäfer, U.; Schaepe, S.; Schaetzel, S.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schamov, A. G.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schioppa, M.; Schlenker, S.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, M.; Schöning, A.; Schott, M.; Schouten, D.; Schovancova, J.; Schram, M.; Schroeder, C.; Schroer, N.; Schultens, M. J.; Schultes, J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, J. W.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwemling, Ph.; Schwienhorst, R.; Schwierz, R.; Schwindling, J.; Schwindt, T.; Schwoerer, M.; Sciolla, G.; Scott, W. G.; Searcy, J.; Sedov, G.; Sedykh, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekula, S. J.; Selbach, K. E.; Seliverstov, D. M.; Sellden, B.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Seuster, R.; Severini, H.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Sherman, D.; Sherwood, P.; Shibata, A.; Shichi, H.; Shimizu, S.; Shimojima, M.; Shin, T.; Shiyakova, M.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simmons, B.; Simoniello, R.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sircar, A.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skottowe, H. P.; Skovpen, K.; Skubic, P.; Slater, M.; Slavicek, T.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, D.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snyder, S.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Soni, N.; Sopko, V.; Sopko, B.; Sosebee, M.; Soualah, R.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stern, S.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Styles, N. A.; Soh, D. A.; Su, D.; Subramania, Hs.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Suzuki, Y.; Svatos, M.; Swedish, S.; Sykora, I.; Sykora, T.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tani, K.; Tannoury, N.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Tayalati, Y.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teinturier, M.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timoshenko, S.; Tipton, P.; Tique Aires Viegas, F. J.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokunaga, K.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torchiani, I.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tudorache, A.; Tudorache, V.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valenta, J.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van der Graaf, H.; van der Kraaij, E.; van der Leeuw, R.; van der Poel, E.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; van Vulpen, I.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vari, R.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Vazquez Schroeder, T.; Vegni, G.; Veillet, J. J.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Virzi, J.; Vitells, O.; Viti, M.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wahrmund, S.; Wakabayashi, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Wang, C.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, J. C.; Wang, R.; Wang, S. M.; Wang, T.; Warburton, A.; Ward, C. P.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, M.; Weber, M. S.; Weber, P.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Wessels, M.; Wetter, J.; Weydert, C.; Whalen, K.; Wheeler-Ellis, S. J.; White, A.; White, M. J.; White, S.; Whitehead, S. R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilhelm, I.; Wilkens, H. G.; Will, J. Z.; Williams, E.; Williams, H. H.; Willis, W.; Willocq, S.; Wilson, J. A.; Wilson, M. G.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wolter, M. W.; Wolters, H.; Wong, W. C.; Wooden, G.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wraight, K.; Wright, C.; Wright, M.; Wrona, B.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wynne, B. M.; Xella, S.; Xiao, M.; Xie, S.; Xu, C.; Xu, D.; Yabsley, B.; Yacoob, S.; Yamada, M.; Yamaguchi, H.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, L.; Yao, Y.; Yasu, Y.; Ybeles Smit, G. V.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Young, C. J.; Youssef, S.; Yu, D.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zajacova, Z.; Zanello, L.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zeman, M.; Zemla, A.; Zendler, C.; Zenin, O.; Ženiš, T.; Zinonos, Z.; Zenz, S.; Zerwas, D.; Zevi Della Porta, G.; Zhan, Z.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zieminska, D.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zutshi, V.; Zwalinski, L.; Atlas Collaboration

    2012-08-01

    The results of a search for pair production of the lighter scalar partners of top quarks (t˜1) in 2.05 fb-1 of pp collisions at √{ s} = 7 TeV using the ATLAS experiment at the LHC are reported. Scalar top quarks are searched for in events with two same flavour opposite-sign leptons (e , μ) with invariant mass consistent with the Z boson mass, large missing transverse momentum and jets in the final state. At least one of the jets is identified as originating from a b-quark. No excess over Standard Model expectations is found. The results are interpreted in the framework of R-parity conserving, gauge mediated Supersymmetry breaking 'natural' scenarios, where the neutralino (χ˜10) is the next-to-lightest supersymmetric particle. Scalar top quark masses up to 310 GeV are excluded for 115 GeV mZ.

  14. 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.

  15. Semiparametric Inference for a General Class of Models for Recurrent Events

    PubMed Central

    Peña, Edsel A.; Slate, Elizabeth H.; González, Juan R.

    2006-01-01

    Procedures for estimating the parameters of the general class of semiparametric models for recurrent events proposed by Peña and Hollander (2004) are developed. This class of models incorporates an effective age function encoding the effect of changes after each event occurrence such as the impact of an intervention, it models the impact of accumulating event occurrences on the unit, it admits a link function in which the effect of possibly time-dependent covariates are incorporated, and it allows the incorporation of unobservable frailty components which induce dependencies among the inter-event times for each unit. The estimation procedures are semiparametric in that a baseline hazard function is nonparametrically specified. The sampling distribution properties of the estimators are examined through a simulation study, and the consequences of mis-specifying the model are analyzed. The results indicate that the flexibility of this general class of models provides a safeguard for analyzing recurrent event data, even data possibly arising from a frailtyless mechanism. The estimation procedures are applied to real data sets arising in the biomedical and public health settings, as well as from reliability and engineering situations. In particular, the procedures are applied to a data set pertaining to times to recurrence of bladder cancer and the results of the analysis are compared to those obtained using three methods of analyzing recurrent event data. PMID:19823592

  16. Regularized lattice Boltzmann model for a class of convection-diffusion equations.

    PubMed

    Wang, Lei; Shi, Baochang; Chai, Zhenhua

    2015-10-01

    In this paper, a regularized lattice Boltzmann model for a class of nonlinear convection-diffusion equations with variable coefficients is proposed. The main idea of the present model is to introduce a set of precollision distribution functions that are defined only in terms of macroscopic moments. The Chapman-Enskog analysis shows that the nonlinear convection-diffusion equations can be recovered correctly. Numerical tests, including Fokker-Planck equations, Buckley-Leverett equation with discontinuous initial function, nonlinear convection-diffusion equation with anisotropic diffusion, are carried out to validate the present model, and the results show that the present model is more accurate than some available lattice Boltzmann models. It is also demonstrated that the present model is more stable than the traditional single-relaxation-time model for the nonlinear convection-diffusion equations. PMID:26565368

  17. Predictions for 5.023 TeV Pb + Pb collisions at the CERN Large Hadron Collider

    NASA Astrophysics Data System (ADS)

    Niemi, H.; Eskola, K. J.; Paatelainen, R.; Tuominen, K.

    2016-01-01

    We compute predictions for various low-transverse-momentum bulk observables in √{sN N}=5.023 TeV Pb+Pb collisions at the CERN Large Hadron Collider (LHC) from the event-by-event next-to-leading-order perturbative-QCD + saturation + viscous hydrodynamics ("EKRT") model. In particular, we consider the centrality dependence of charged hadron multiplicity, flow coefficients of the azimuth-angle asymmetries, and correlations of event-plane angles. The centrality dependencies of the studied observables are predicted to be very similar to those at 2.76 TeV, and the magnitudes of the flow coefficients and event-plane angle correlations are predicted to be close to those at 2.76 TeV. The flow coefficients may, however, offer slightly more discriminating power on the temperature dependence of QCD matter viscosity than the 2.76 TeV measurements. Our prediction for the multiplicity in the 0-5 % centrality class, obtained using the two temperature-dependent shear-viscosity-to-entropy ratios that give the best overall fit to BNL Relativistic Heavy Ion Collider (RHIC) and LHC data is d Nch/d η ||η|≤0.5=1876 ⋯2046 . We also predict a power-law increase from 200 GeV Au+Au collisions at RHIC to 2.76 and 5.023 TeV Pb+Pb collisions at the LHC, d Nch/d η ||η|≤0.5∝s0.164 ⋯0.174 .

  18. 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…

  19. 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.

  20. 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. PMID:27505639

  1. 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.

  2. Downscaling parameters from groundwater model scale to properties of the constituting litho classes

    NASA Astrophysics Data System (ADS)

    Lourens, Aris; van Geer, Frans

    2015-04-01

    Like other numerical models, groundwater models are created using the best knowledge available. Still, these models usually suffer from data uncertainty and model misconceptions. Calibration of such a model may yield parameter values with which the model produces output more closely to the observed values of the dependent variables than the uncalibrated model does. In groundwater models, the model parameters are often an aggregation of two or more observed properties. For example, the transmissivity is defined as the product of the layer thickness and the conductivity of the deposits, and the vertical resistance as the quotient of the layer thickness and the conductivity. Moreover, the parameters used in groundwater models are often constructed by vertical upscaling and horizontally interpolation of small geological units (litho-layers). When calibrating the groundwater model parameters, a better fit to the groundwater head data is achieved, but it is not clear to what extent the thickness or the conductivity of the individual litho-layers should be modified. This may yield parameter values at the litho-layer scale which are not very likely from geological point of view. The question is how can we downscale the calibrated model parameters to arrive at the most likely set of conductivities and thicknesses of the individual litho-layers, respecting the prior uncertainty from geological point of view. Here, we present a method to find the most likely values of parameters of constituting litho-layers of an aquitard, based on the parameter values of a calibrated groundwater model. The objective of this method is twofold. On one hand, finding the most likely parameter values for the thicknesses and the hydraulic conductivities of each individual litho layer. On the other hand, the most likely parameter values of the litho-layers may be very unlikely from geological perspective and, herewith, indicate connectional model errors. The properties of each litho-class at the

  3. A class of transient acceleration models consistent with Big Bang cosmology

    NASA Astrophysics Data System (ADS)

    Zu, Tian-Long; Chen, Jie-Wen; Zhang, Yang

    2014-02-01

    Is it possible that the current cosmic accelerating expansion will turn into a decelerating one? Can this transition be realized by some viable theoretical model that is consistent with the standard Big Bang cosmology? We study a class of phenomenological models with a transient acceleration, based on a dynamical dark energy with a very general form of equation of state pde = βρde - βρdem. It mimics the cosmological constant ρde → const for a small scale factor a, and behaves as a barotropic gas with ρde → a-3(α+1) with α >= 0 for large a. The cosmic evolution of four models in the class has been examined in detail, and all yield a smooth transient acceleration. Depending on the specific model, the future universe may be dominated by either dark energy or by matter. In two models, the dynamical dark energy can be explicitly realized by a scalar field with an analytical potential V(φ). Moreover, a statistical analysis shows that the models can be as robust as ΛCDM in confronting the observational data of Type Ia supernovae, cosmic microwave background (CMB) and baryon acoustic oscillation. As improvements over previous studies, our models overcome the problem of over-abundance of dark energy during early eras, and satisfy the constraints on dark energy from WMAP observations of CMB.

  4. 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…

  5. CpG-ODN Class C Mediated Immunostimulation in Rabbit Model of Trypanosoma evansi Infection

    PubMed Central

    Kumar, Parveen; Kumar, Rakesh; Manuja, Balvinder Kumar; Singha, Harisankar; Sharma, Anshu; Virmani, Nitin; Yadav, Suresh Chandra; Manuja, Anju

    2015-01-01

    CpG oligodeoxynucleotides (CpG-ODN) stimulate immune cells from a wide spectrum of mammalian species. Class C CpG-ODN is relatively stable and has the combined immune effects of both A and B classes of CpG-ODN. Trypanosoma evansi produces the state of immuno-suppression in the infected hosts. The current chemotherapeutic agents against this parasite are limited in number and usually associated with severe side effects. The present work aimed to determine the immunostimulatory effects of CpG-ODN class C in T. evansi infected rabbits. Rabbits inoculated with CpG C and challenged with T. evansi resulted in delayed onset of clinical signs with reduced severity in comparison to that of T. evansi infected rabbits. The treatment also enhanced humoral immune responses. Histopathological findings in liver and spleen revealed enhancement of mononuclear cell infiltration and secondary B cell follicles. These results demonstrate that CpG-ODN class C, has immunostimulatory properties in rabbit model of trypanosomosis. The use of booster doses or sustained delivery of CpG-ODN will further elucidate the prolonged CpG-ODN generated immune responses. PMID:26039713

  6. 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.

  7. Unified description of 0+ states in a large class of nuclear collective models.

    PubMed

    Bonatsos, Dennis; McCutchan, E A; Casten, R F

    2008-07-11

    A remarkably simple regularity in the energies of 0+ states in a broad class of collective models is discussed. A single formula for all 0+ states in flat-bottomed infinite potentials that depends only on the number of dimensions and a simpler expression applicable to all three interacting boson approximation symmetries in the large N(B) limit are presented. Finally, a connection between the energy expression for 0+ states given by the X5 model and the predictions of the interacting boson approximation near the critical point of the first order phase transition is explored. PMID:18764176

  8. 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.

  9. 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

  10. Critical behavior of absorbing phase transitions for models in the Manna class with natural initial states.

    PubMed

    Lee, Sang Bub

    2014-06-01

    The critical behavior of absorbing phase transitions for two typical models in the Manna universality class, the conserved Manna model and the conserved lattice gas model, both on a square lattice, was investigated using the natural initial states. Various critical exponents were estimated using the static and dynamic simulations. The exponents characterizing dynamics of active particles differ considerably from the known exponents obtained using the random initial states, whereas those associated with the steady-state quantities remain the same. The critical exponents for both models were consistent with errors of less than 1% and satisfied the known scaling relations; thus, the known violation of scaling relations for models with a conserved field was resolved using the natural initial states. The results differed by 7%∼12% from the directed percolation values. PMID:25019750

  11. 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.

  12. An adjustable aperiodic model class of genomic interactions using continuous time Boolean networks (Boolean delay equations)

    NASA Astrophysics Data System (ADS)

    Öktem, Hakan; Pearson, Ronald; Egiazarian, Karen

    2003-12-01

    Following the complete sequencing of several genomes, interest has grown in the construction of genetic regulatory networks, which attempt to describe how different genes work together in both normal and abnormal cells. This interest has led to significant research in the behavior of abstract network models, with Boolean networks emerging as one particularly popular type. An important limitation of these networks is that their time evolution is necessarily periodic, motivating our interest in alternatives that are capable of a wider range of dynamic behavior. In this paper we examine one such class, that of continuous-time Boolean networks, a special case of the class of Boolean delay equations (BDEs) proposed for climatic and seismological modeling. In particular, we incorporate a biologically motivated refractory period into the dynamic behavior of these networks, which exhibit binary values like traditional Boolean networks, but which, unlike Boolean networks, evolve in continuous time. In this way, we are able to overcome both computational and theoretical limitations of the general class of BDEs while still achieving dynamics that are either aperiodic or effectively so, with periods many orders of magnitude longer than those of even large discrete time Boolean networks.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    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.

  14. 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.

  15. 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.

  16. Universality Class of the Nishimori Point in the 2D +/-J Random-Bond Ising Model

    NASA Astrophysics Data System (ADS)

    Honecker, A.; Picco, M.; Pujol, P.

    2001-07-01

    We study the universality class of the Nishimori point in the 2D +/-J random-bond Ising model by means of the numerical transfer-matrix method. Using the domain-wall free energy, we locate the position of the fixed point along the Nishimori line at the critical concentration value pc = 0.1094+/-0.0002 and estimate ν = 1.33+/-0.03. Then, we obtain the exponents for the moments of the spin-spin correlation functions as well as the value for the central charge c = 0.464+/-0.004. The main qualitative result is the fact that percolation is now excluded as a candidate for describing the universality class of this fixed point.

  17. Universality class of the Nishimori point in the 2D +/- J random-bond Ising model.

    PubMed

    Honecker, A; Picco, M; Pujol, P

    2001-07-23

    We study the universality class of the Nishimori point in the 2D +/- J random-bond Ising model by means of the numerical transfer-matrix method. Using the domain-wall free energy, we locate the position of the fixed point along the Nishimori line at the critical concentration value p(c) = 0.1094 +/- 0.0002 and estimate nu = 1.33 +/- 0.03. Then, we obtain the exponents for the moments of the spin-spin correlation functions as well as the value for the central charge c = 0.464 +/- 0.004. The main qualitative result is the fact that percolation is now excluded as a candidate for describing the universality class of this fixed point. PMID:11461639

  18. Evaluating Historic Carbon Budget in Temperate Pacific Northwestern Conifer Forest Landscape Using CN-CLASS Model

    NASA Astrophysics Data System (ADS)

    Chen, B.; Arain, M. A.; Black, T. A.

    2009-05-01

    We used carbon and nitrogen coupled Canadian Land Surface Scheme (CN-CLASS), a process-based model, to simulate the historic carbon stocks and fluxes in a 2500 ha temperate Pacific Northwest conifer forest landscape from 1920 to 2004. Hourly meteorological data was provided from historic climate records. Site maps of soils, topography, vegetation and disturbance type (logging, fire events) were provided by the historic carbon modeling project of the Canadian Carbon Program (CCP). The initial aboveground tree biomass in 1920 and the disturbance matrices were produced by the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Over the study period from 1920-2004, CN-CLASS simulated 188 Mg C ha-1 loss of ecosystem carbon as compared to 200 Mg C ha-1 loss suggested by CBM-CFS3. From 1928 to 1944, burning, historic harvest and slash burning resulted in large losses of carbon to the atmosphere. In this period, the study area was a large carbon source with simulated net carbon loss of 282 Mg C ha-1. From 1945 to 1989, there were very few disturbance events and the study area started to recover with simulated net carbon uptake of 87 Mg C ha-1. During this period, CN-CLASS modeled annual Net Biome Productivity (NBP) ranged from 27 g C m-2 y-1 in 1945 to 590 g C m-2 y-1 in 1964. CN-CLASS simulated summer (July-September) NEP deviations during the undisturbed period (1945-1989), showed a negative relationship with the daily maximum air temperature and precipitation. As harvest of second-growth stands began in 1990s, disturbance again had significant impact on the landscape's carbon budget, and this effect was partially offset by ongoing C uptake in recovering young stands. CN-CLASS underestimated NEP as compared to observed eddy covariance flux measurements because of high temperature sensitivity of its soil respiration algorithm. Simulated mean annual NEP from 1998 to 2004 was 190 g C m-2 y-1 as compared to observed eddy covariance value of 352 g C m-2 y-1. This

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

    SciTech Connect

    Bhattacherjee, Biplob; Ghosh, Kirtiman

    2011-02-01

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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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…

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

    NASA Astrophysics Data System (ADS)

    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.; Roland, B.; 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.; Kalogeropoulos, A.; Keaveney, J.; Kim, T. 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.; 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.; Jez, P.; Komm, M.; Lemaitre, V.; Liao, J.; 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.; Correa Martins Junior, M.; Dos Reis Martins, T.; 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.; Malek, M.; 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.; Dias, F. A.; 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.; 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.; Liang, D.; Liang, S.; Plestina, R.; Tao, J.; Wang, X.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, Y.; Li, Q.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Zhang, L.; 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.; 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.; 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.; 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.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Erdweg, S.; 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.; 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.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; 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.; Hellwig, G.; Hempel, M.; Horton, D.; Jung, H.; 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.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Nowak, F.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Ron, E.; Sahin, M. Ã.-.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; 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.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sibille, J.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; 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.; 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.; Dhingra, N.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; 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. 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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.; 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.; Fantinel, S.; 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.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Romeo, F.; 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.; 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.; Montanino, D.; 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, 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.; Choi, M.; Kim, J. H.; Park, I. C.; Park, S.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; 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.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Kamenev, A.; Karjavin, V.; Konoplyanikov, V.; 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.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; 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.; Dordevic, M.; Ekmedzic, M.; Milosevic, J.; 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.; Merino, G.; 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.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Lloret Iglesias, L.; 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.; Bianchi, G.; 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.; Dobson, M.; 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.; Sekmen, S.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Treille, D.; Tsirou, A.; Veres, G. I.; Vlimant, J. R.; Wardle, N.; Wöhri, H. K.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; König, S.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Bortignon, P.; Buchmann, M. A.; Casal, B.; Chanon, N.; Deisher, A.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Meister, D.; Mohr, N.; Nägeli, C.; Nef, P.; 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.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Snoek, H.; 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.; 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.; Sogut, K.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Karapinar, G.; Ocalan, K.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Isildak, B.; Kaya, M.; Kaya, O.; Bahtiyar, H.; Barlas, E.; Cankocak, K.; Vardarlı, F. I.; Yücel, M.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Frazier, R.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Senkin, S.; Smith, V. J.; Williams, T.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Gilbert, A.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Heister, A.; Lawson, P.; Richardson, C.; Rohlf, J.; Sperka, D.; St. John, J.; Sulak, L.; Alimena, J.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Jabeen, S.; 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.; Babb, J.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Liu, H.; Long, O. R.; Luthra, A.; Malberti, M.; Nguyen, H.; 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.; Yoo, J.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; 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.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Di Marco, E.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Drell, B. R.; 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.; 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.; 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.; 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.; Skhirtladze, N.; Snowball, M.; 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.; Gray, J.; Kenny, R. P.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Barfuss, A. F.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; 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.; Dutta, V.; 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.; 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.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Vuosalo, C.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Berry, E.; 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.; Zenz, S. C.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Alagoz, E.; Barnes, V. E.; Benedetti, D.; Bolla, G.; Bortoletto, D.; De Mattia, M.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Merkel, P.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Yoo, H. D.; 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.; Miner, D. C.; 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.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Rekovic, V.; Salur, S.; Schnetzer, S.; Seitz, C.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; 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.; Gollapinni, S.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; 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.; Woods, N.; CMS Collaboration

    2015-05-01

    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 95% confidence level for a W' -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 WKK(2 ) 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' -boson and the standard model W -boson and for a compositeness model.

  6. 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.

  7. 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

  8. 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.

  9. Molecular modelling based target identification for endo-peroxides class of antimalarials.

    PubMed

    Gupta, Amit K; Saxena, Anil K

    2015-01-01

    The emerging cases of artemisinin and endoperoxide drug resistance are becoming a challenge to antimalarial drug discovery and therapy. The exact mode of action of this class of antimalarials is still unknown which presents a bottleneck for the understanding of drug resistance as well as designing new lead molecules of this class. To address this issue, the molecular docking and scoring studies of a homogeneous and structurally diverse dataset of artemisinin derived trioxanes have been performed on each of the two plausible targets of this class viz. heme and PfATP6. Since the crystal structure of PfATP6 is unknown, its homology model was built utilizing the human SERCA1 protein crystallized structure as a template. The binding energies of the heme binding site of the docked artemisinin derivatives showed very good correlation with the antimalarial activity (r(2) = 0.69), whereas the same study with the binding site of pfATP6 showed a very poor correlation (r(2) = 0.12), suggesting heme to be the possible target of artemisinin derived endoperoxides. PMID:25543685

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

    PubMed

    Leviyang, Sivan

    2011-02-01

    We examine genetic statistics used in the study of structured populations. In a 1999 paper, Wakeley observed that the coalescent process associated with the finite island model can be decomposed into a scattering phase and a collecting phase. This decomposition becomes exact in the large population limit with the coalescent at the end of the scattering phase converging to the Ewens sampling formula and the coalescent during the collecting phase converging to the Kingman coalescent. In this paper we introduce a class of limiting models, which we refer to as G/KC models, that generalize Wakeley's decomposition. G in G/KC represents a completely general limit for the scattering phase, while KC represents a Kingman coalescent limit for the collecting phase. We show that both the island and two-dimensional stepping stone models converge to G/KC models in the large population limit. We then derive the distribution of the statistic F(st) for all G/KC models under a large sample limit for the cases of strong or weak mutation, thereby deriving the large population, large sample limiting distribution of F(st) for the island and two-dimensional stepping stone models as a special case of a general formula. Our methods allow us to take the large population and large sample limits simultaneously. In the context of large population, large sample limits, we show that the variance of F(st) in the presence of weak mutation collapses as O(1/log d) where d is the number of demes sampled. Further, we show that this O(1/log d) is caused by a heavy tail in the distribution of F(st). Our analysis of F(st) can be extended to an entire class of genetic statistics, and we use our approach to examine homozygosity measures. Our analysis uses coalescent based methods. PMID:20186418

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  13. 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.

  14. Model Reference Adaptive H∞ Control for a Class of Mixed Parameter Systems by Finite Dimensional Controllers

    NASA Astrophysics Data System (ADS)

    Miyasato, Yoshihiko

    The problem of constructing model reference adaptive H∞ control for a class of mixed parameter systems is considered in this manuscript. Mixed parameter systems are complex processes composed of distributed parameter systems (infinite dimensional systems) and lumped parameter systems (finite dimensional systems). Owing to infinite dimensional modes of distributed parameter systems, control of those complex systems via finite dimensional compensators, is a difficult but important problem from both theoretical and practical viewpoints. A stabilizing control signal is added to regulate the effect of infinite dimensional modes, and it is derived as a solution of certain H∞ control problem where the effect of infinite dimensional modes are considered as external disturbances to the process.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Hagendorf, Christian; Morin-Duchesne, Alexi

    2016-05-01

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

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blanco, J. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Caloba, L. P.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Colasurdo, L.; Cole, B.; Cole, S.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. 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.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davison, P.; 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.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; 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.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Duflot, L.; Duguid, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Ennis, J. S.; 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, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; 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.; 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.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. 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C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Padilla Aranda, C.; Pagáčová, M.; Pagan Griso, S.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palestini, S.; Palka, M.; Pallin, D.; Palma, A.; Panagiotopoulou, E. St.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Perez Codina, E.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Puldon, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; 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.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; 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.; Reichert, J.; Reisin, H.; Rembser, C.; Ren, H.; 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.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; 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.; Rosenthal, O.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rud, V. I.; 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.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sandhoff, M.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sasaki, Y.; Sato, K.; Sauvage, G.; Sauvan, E.; Savage, G.; Savard, P.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schorlemmer, A. L. S.; Schott, M.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; 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.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  6. Global Monitoring of Tropical Forest Fires Using A New Predictive Modeling Approach for Rare Classes

    NASA Astrophysics Data System (ADS)

    Mithal, V.; Nayak, G.; Khandelwal, A.; Kumar, V.; Oza, N.; Nemani, R. R.

    2015-12-01

    The traditional classification approaches use labeled training data to select the best classification model from a family of models. Since collecting labeled samples is often tedious and sometimes even infeasible, recent research in machine learning has focused on developing algorithms to train classification models in scarcity of labeled training samples. In contrast, the focus of our research is to address problem settings where acquiring even a small number of expert-annotated labeled samples for supervision is infeasible. I will present RAPT, a new predictive modeling framework for identifying rare classes when there is a complete absence of labeled data. The RAPT framework is designed to use imperfectly annotated training data to learn classification models in the absence of expert-annotated training samples. Our results show that, under some reasonable assumptions, the classifiers trained from imperfectly labeled training data using the RAPT approach have performance comparable to the classification models trained using expert-annotated training data. This capability of learning from imperfect supervision is advantageous in a wide range of applications where the target class of interest is relatively rare and obtaining a precise labeling of even a small number of training samples is infeasible. I will also present the application of the RAPT framework for creating historical maps of forest fires from satellite data for the tropical forests. This new forest fire product identifies approximately 1 million sq. km. of burned areas in the tropical forests in South America and South-east Asia during years 2001-2014, which is more than three times the total burned area reported by the state-of-art NASA products. We show validation of these results using burn-scars visible in satellite images, including high resolution Landsat images, to confirm the veracity of the previously unreported forest fires.

  7. 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

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

    NASA Astrophysics Data System (ADS)

    Fossati, Giovanni; Chen, X.

    2010-02-01

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

  9. 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

  10. 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

  11. Constitutive modeling of coronary arterial media--comparison of three model classes.

    PubMed

    Hollander, Yaniv; Durban, David; Lu, Xiao; Kassab, Ghassan S; Lanir, Yoram

    2011-06-01

    Accurate modeling of arterial elasticity is imperative for predicting pulsatile blood flow and transport to the periphery, and for evaluating the mechanical microenvironment of the vessel wall. The goal of the present study is to compare a recently developed structural model of porcine left anterior descending artery media to two commonly used typical representatives of phenomenological and structure-motivated invariant-based models, in terms of the number of model parameters, model descriptive and predictive powers, and requisite different test protocols for reliable parameter estimation. The three models were compared against 3D data of radial inflation, axial extension, and twist tests. Also checked are the models predictive capabilities to response data not used for estimation, including both tests outside the range of estimation database, as well as protocols of a different nature. The results show that the descriptive estimation error (model fit to estimation database), measured by the sum of squared residuals (SSE) between full 3D data and model predictions, was about twice as low for the structural (4.58%) model compared to the other two (9.71 and 8.99% for the phenomenological and structure-motivated models, respectively). Similar SSE ratios were obtained for the predictive capabilities. Prediction SSE at high stretch based on estimation of two low stretches yielded an SSE value of 2.81% for the structural model, and 10.54% and 7.87% for the phenomenological and structure-motivated models, respectively. For the prediction of twist from inflation-extension data, SSE values for the torsional stiffness was 1.76% for the structural model and 39.62 and 2.77% for the phenomenological and structure-motivated models. The required number of model parameters for the structural model is four, whereas the phenomenological model requires six to nine and the structure-motivated has four parameters. These results suggest that modeling based on the tissue structural

  12. 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

  13. 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

  14. Stochastic optimization model for order acceptance with multiple demand classes and uncertain demand/supply

    NASA Astrophysics Data System (ADS)

    Yang, Wen; Fung, Richard Y. K.

    2014-06-01

    This article considers an order acceptance problem in a make-to-stock manufacturing system with multiple demand classes in a finite time horizon. Demands in different periods are random variables and are independent of one another, and replenishments of inventory deviate from the scheduled quantities. The objective of this work is to maximize the expected net profit over the planning horizon by deciding the fraction of the demand that is going to be fulfilled. This article presents a stochastic order acceptance optimization model and analyses the existence of the optimal promising policies. An example of a discrete problem is used to illustrate the policies by applying the dynamic programming method. In order to solve the continuous problems, a heuristic algorithm based on stochastic approximation (HASA) is developed. Finally, the computational results of a case example illustrate the effectiveness and efficiency of the HASA approach, and make the application of the proposed model readily acceptable.

  15. 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

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

    NASA Technical Reports Server (NTRS)

    White, Allan L.; Palumbo, Daniel L.

    1991-01-01

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

  17. 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%.

  18. New physics at the TeV scale

    NASA Astrophysics Data System (ADS)

    Chakdar, Shreyashi

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

  19. Compliance mixture modelling with a zero-effect complier class and missing data.

    PubMed

    Sobel, Michael E; Muthén, Bengt

    2012-12-01

    Randomized experiments are the gold standard for evaluating proposed treatments. The intent to treat estimand measures the effect of treatment assignment, but not the effect of treatment if subjects take treatments to which they are not assigned. The desire to estimate the efficacy of the treatment in this case has been the impetus for a substantial literature on compliance over the last 15 years. In papers dealing with this issue, it is typically assumed there are different types of subjects, for example, those who will follow treatment assignment (compliers), and those who will always take a particular treatment irrespective of treatment assignment. The estimands of primary interest are the complier proportion and the complier average treatment effect (CACE). To estimate CACE, researchers have used various methods, for example, instrumental variables and parametric mixture models, treating compliers as a single class. However, it is often unreasonable to believe all compliers will be affected. This article therefore treats compliers as a mixture of two types, those belonging to a zero-effect class, others to an effect class. Second, in most experiments, some subjects drop out or simply do not report the value of the outcome variable, and the failure to take into account missing data can lead to biased estimates of treatment effects. Recent work on compliance in randomized experiments has addressed this issue by assuming missing data are missing at random or latently ignorable. We extend this work to the case where compliers are a mixture of types and also examine alternative types of nonignorable missing data assumptions. PMID:22985224

  20. 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.

  1. Collapse and restoration of MHC class-I-dependent immune privilege: exploiting the human hair follicle as a model.

    PubMed

    Ito, Taisuke; Ito, Natsuho; Bettermann, Albrecht; Tokura, Yoshiki; Takigawa, Masahiro; Paus, Ralf

    2004-02-01

    The collapse of major histocompatibility complex (MHC) class-I-dependent immune privilege can lead to autoimmune disease or fetal rejection. Pragmatic and instructive models are needed to clarify the as yet obscure controls of MHC class I down-regulation in situ, to dissect the principles of immune privilege generation, maintenance, and collapse as well as to develop more effective strategies for immune privilege restoration. Here, we propose that human scalp hair follicles, which are abundantly available and easily studied, are ideally suited for this purpose: interferon-gamma induces ectopic MHC class I expression in the constitutively MHC class-I-negative hair matrix epithelium of organ-cultured anagen hair bulbs, likely via interferon regulatory factor-1, along with up-regulation of the MHC class I pathway molecules beta(2)microglobulin and transporter associated with antigen processing (TAP-2). In the first report to identify natural immunomodulators capable of down-regulating MHC class I expression in situ in a normal, neuroectoderm-derived human tissue, we show that ectopic MHC class I expression in human anagen hair bulbs can be normalized by treatment with alpha-MSH, IGF-1, or TGF-beta1, all of which are locally generated, as well as by FK506. These agents are promising candidates for immune privilege restoration and for suppressing MHC class I expression where this is clinically desired (eg, in alopecia areata, multiple sclerosis, autoimmune uveitis, mumps orchitis, and fetal or allograft rejection). PMID:14742267

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

    NASA Astrophysics Data System (ADS)

    Contreras G., Mauricio

    2014-07-01

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

  3. 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.

  4. 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.

  5. 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)

  6. Lattice model for spontaneous imbibition in porous media: the role of effective tension and universality class.

    PubMed

    Lee, Deok-Sun; Sadjadi, Zeinab; Rieger, Heiko

    2014-07-01

    Recently, anomalous scaling properties of front broadening during spontaneous imbibition of water in Vycor glass, a nanoporous medium, were reported: the mean height and the width of the propagating front increase with time t both proportional to t(1/2). Here, we propose a simple lattice imbibition model and elucidate quantitatively how the correlation range of the hydrostatic pressure and the disorder strength of the pore radii affect the scaling properties of the imbibition front. We introduce an effective tension of liquid across neighboring pores, which depends on the aspect ratio of each pore, and show that it leads to a dynamical crossover: both the mean height and the roughness grow faster in the presence of tension in the intermediate-time regime but eventually saturate in the long-time regime. The universality class of the long-time behavior is discussed by examining the associated scaling exponents and their relation to directed percolation. PMID:25122378

  7. 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.

  8. 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. PMID:22463515

  9. Using latent class analysis to model prescription medications in the measurement of falling among a community elderly population

    PubMed Central

    2013-01-01

    Background Falls among the elderly are a major public health concern. Therefore, the possibility of a modeling technique which could better estimate fall probability is both timely and needed. Using biomedical, pharmacological and demographic variables as predictors, latent class analysis (LCA) is demonstrated as a tool for the prediction of falls among community dwelling elderly. Methods Using a retrospective data-set a two-step LCA modeling approach was employed. First, we looked for the optimal number of latent classes for the seven medical indicators, along with the patients’ prescription medication and three covariates (age, gender, and number of medications). Second, the appropriate latent class structure, with the covariates, were modeled on the distal outcome (fall/no fall). The default estimator was maximum likelihood with robust standard errors. The Pearson chi-square, likelihood ratio chi-square, BIC, Lo-Mendell-Rubin Adjusted Likelihood Ratio test and the bootstrap likelihood ratio test were used for model comparisons. Results A review of the model fit indices with covariates shows that a six-class solution was preferred. The predictive probability for latent classes ranged from 84% to 97%. Entropy, a measure of classification accuracy, was good at 90%. Specific prescription medications were found to strongly influence group membership. Conclusions In conclusion the LCA method was effective at finding relevant subgroups within a heterogenous at-risk population for falling. This study demonstrated that LCA offers researchers a valuable tool to model medical data. PMID:23705639

  10. Search for direct chargino production in anomaly-mediated supersymmetry breaking models based on a disappearing-track signature in pp collisions at sqrt{s}=7TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abajyan, T.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdelalim, A. A.; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Agustoni, M.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alam, M. S.; Alam, M. A.; Albert, J.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Allbrooke, B. M. M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alonso, F.; Altheimer, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amelung, C.; Ammosov, V. V.; Amor Dos Santos, S. P.; Amorim, A.; Amram, N.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angelidakis, S.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Atkinson, M.; Aubert, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Avramidou, R.; Axen, D.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Backus Mayes, J.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Balek, P.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, V.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beale, S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, A. K.; Becker, S.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Begel, M.; Behar Harpaz, S.; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertella, C.; Bertin, A.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bittner, B.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blazek, T.; Bloch, I.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. 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    2013-01-01

    A search for direct chargino production in anomaly-mediated supersymmetry breaking scenarios is performed in pp collisions at sqrt{s}=7TeV using 4.7 fb-1 of data collected with the ATLAS experiment at the LHC. In these models, the lightest chargino is predicted to have a lifetime long enough to be detected in the tracking detectors of collider experiments. This analysis explores such models by searching for chargino decays that result in tracks with few associated hits in the outer region of the tracking system. The transverse-momentum spectrum of candidate tracks is found to be consistent with the expectation from the Standard Model background processes and constraints on chargino properties are obtained.