WorldWideScience

Sample records for pairing model predictions

  1. Standard-model predictions for W-pair production in electron-positron collisions

    International Nuclear Information System (INIS)

    Beenakker, W.; Denner, A.

    1994-03-01

    We review the status of the theoretical predictions for W-pair production in e + e - collisions within the electroweak standard model (SM). We first consider for on-shell W-bosons the lowest-order cross-section within the SM, the general effects of anomalous couplings, the radiative corrections within the SM, and approximations for them. Then we discuss the inclusion of finite-width effects in lowest order and the existing results for radiative corrections to off-shell W-pair production, and we outline the general strategy to calculate radiative corrections within the pole scheme. We summarize the theoretical predictions for the total and partial W-boson widths including radiative corrections and discuss the quality of an improved Born approximation. Finally we provide a general discussion of the structure-function method to calculate large logarithmic higher-order corrections associated with collinear photon radiation. (orig.)

  2. Predictive labeling with dependency pairs using SAT

    NARCIS (Netherlands)

    Koprowski, A.; Middeldorp, A.; Pfenning, F.

    2007-01-01

    This paper combines predictive labeling with dependency pairs and reports on its implementation. Our starting point is the method of proving termination of rewrite systems using semantic labeling with infinite models in combination with lexicographic path orders. We replace semantic labeling with

  3. Use of Paired Simple and Complex Models to Reduce Predictive Bias and Quantify Uncertainty

    DEFF Research Database (Denmark)

    Doherty, John; Christensen, Steen

    2011-01-01

    -constrained uncertainty analysis. Unfortunately, however, many system and process details on which uncertainty may depend are, by design, omitted from simple models. This can lead to underestimation of the uncertainty associated with many predictions of management interest. The present paper proposes a methodology...... of these details born of the necessity for model outputs to replicate observations of historical system behavior. In contrast, the rapid run times and general numerical reliability of simple models often promulgates good calibration and ready implementation of sophisticated methods of calibration...... that attempts to overcome the problems associated with complex models on the one hand and simple models on the other hand, while allowing access to the benefits each of them offers. It provides a theoretical analysis of the simplification process from a subspace point of view, this yielding insights...

  4. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Directory of Open Access Journals (Sweden)

    Michael F Sloma

    2017-11-01

    Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  5. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Science.gov (United States)

    Sloma, Michael F; Mathews, David H

    2017-11-01

    Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  6. Combinatorial DNA Damage Pairing Model Based on X-Ray-Induced Foci Predicts the Dose and LET Dependence of Cell Death in Human Breast Cells

    Energy Technology Data Exchange (ETDEWEB)

    Vadhavkar, Nikhil [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Pham, Christopher [University of Texas, Houston, TX (United States). MD Anderson Cancer Center; Georgescu, Walter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; Deschamps, Thomas [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; Heuskin, Anne-Catherine [Univ. of Namur (Belgium). Namur Research inst. for Life Sciences (NARILIS), Research Center for the Physics of Matter and Radiation (PMR); Tang, Jonathan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.; Costes, Sylvain V. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Div.

    2014-09-01

    In contrast to the classic view of static DNA double-strand breaks (DSBs) being repaired at the site of damage, we hypothesize that DSBs move and merge with each other over large distances (m). As X-ray dose increases, the probability of having DSB clusters increases as does the probability of misrepair and cell death. Experimental work characterizing the X-ray dose dependence of radiation-induced foci (RIF) in nonmalignant human mammary epithelial cells (MCF10A) is used here to validate a DSB clustering model. We then use the principles of the local effect model (LEM) to predict the yield of DSBs at the submicron level. Two mechanisms for DSB clustering, namely random coalescence of DSBs versus active movement of DSBs into repair domains are compared and tested. Simulations that best predicted both RIF dose dependence and cell survival after X-ray irradiation favored the repair domain hypothesis, suggesting the nucleus is divided into an array of regularly spaced repair domains of ~;;1.55 m sides. Applying the same approach to high-linear energy transfer (LET) ion tracks, we are able to predict experimental RIF/m along tracks with an overall relative error of 12percent, for LET ranging between 30 350 keV/m and for three different ions. Finally, cell death was predicted by assuming an exponential dependence on the total number of DSBs and of all possible combinations of paired DSBs within each simulated RIF. Relative biological effectiveness (RBE) predictions for cell survival of MCF10A exposed to high-LET showed an LET dependence that matches previous experimental results for similar cell types. Overall, this work suggests that microdosimetric properties of ion tracks at the submicron level are sufficient to explain both RIF data and survival curves for any LET, similarly to the LEM assumption. Conversely, high-LET death mechanism does not have to infer linear-quadratic dose formalism as done in the LEM. In addition, the size of repair domains derived in our model

  7. Search for Higgs bosons predicted in two-Higgs-doublet models via decays to tau lepton pairs in 1.96 TeV pp collisions.

    Science.gov (United States)

    Aaltonen, T; Adelman, J; Akimoto, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burke, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cordelli, M; Cortiana, G; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'Orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; Di Canto, A; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Garosi, P; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Group, R C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heijboer, A; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Hussein, M; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; 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; Mondragon, M 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; Pagliarone, C; 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; Rutherford, B; 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; 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; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; 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; Yi, K; 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

    2009-11-13

    We present the results of a search for Higgs bosons predicted in two-Higgs-doublet models, in the case where the Higgs bosons decay to tau lepton pairs, using 1.8 fb(-1) of integrated luminosity of pp collisions recorded by the CDF II experiment at the Fermilab Tevatron. Studying the mass distribution in events where one or both tau leptons decay leptonically, no evidence for a Higgs boson signal is observed. The result is used to infer exclusion limits in the two-dimensional space of tanbeta versus m(A) (the ratio of the vacuum expectation values of the two Higgs doublets and the mass of the pseudoscalar boson, respectively).

  8. Predicting the Use of Paired Programming: Applying the Attitudes of Application Development Managers through the Technology Acceptance Model

    Science.gov (United States)

    Zecca, Mark S.

    2010-01-01

    Business managers who look for ways to cut costs face difficult questions about the efficiency and effectiveness of software engineering practices that are used to complete projects on time, on specification, and within budget (Johnson, 1995; Lindstrom & Jeffries, 2004). Theoretical models such as the Theory of Reasoned Action (TRA) have linked…

  9. Pair shell model description of collective motions

    International Nuclear Information System (INIS)

    Chen Hsitseng; Feng Dahsuan

    1996-01-01

    The shell model in the pair basis has been reviewed with a case study of four particles in a spherical single-j shell. By analyzing the wave functions according to their pair components, the novel concept of the optimum pairs was developed which led to the proposal of a generalized pair mean-field method to solve the many-body problem. The salient feature of the method is its ability to handle within the framework of the spherical shell model a rotational system where the usual strong configuration mixing complexity is so simplified that it is now possible to obtain analytically the band head energies and the moments of inertia. We have also examined the effects of pair truncation on rotation and found the slow convergence of adding higher spin pairs. Finally, we found that when the SDI and Q .Q interactions are of equal strengths, the optimum pair approximation is still valid. (orig.)

  10. Variational study of the pair hopping model

    International Nuclear Information System (INIS)

    Fazekas, P.

    1990-01-01

    We study the ground state of a Hamiltonian introduced by Kolb and Penson for modelling situations in which small electron pairs are formed. The Hamiltonian consists of a tight binding band term, and a term describing the nearest neighbour hopping of electron pairs. We give a Gutzwiller-type variational treatment, first with a single-parameter Ansatz treated in the single site Gutzwiller approximation, and then with more complicated trial wave functions, and an improved Gutzwiller approximation. The calculation yields a transition from a partially paired normal state, in which the spin susceptibility has a diminished value, into a fully paired state. (author). 16 refs, 2 figs

  11. Isovectorial pairing in solvable and algebraic models

    International Nuclear Information System (INIS)

    Lerma, Sergio; Vargas, Carlos E; Hirsch, Jorge G

    2011-01-01

    Schematic interactions are useful to gain some insight in the behavior of very complicated systems such as the atomic nuclei. Prototypical examples are, in this context, the pairing interaction and the quadrupole interaction of the Elliot model. In this contribution the interplay between isovectorial pairing, spin-orbit, and quadrupole terms in a harmonic oscillator shell (the so-called pairing-plus-quadrupole model) is studied by algebraic methods. The ability of this model to provide a realistic description of N = Z even-even nuclei in the fp-shell is illustrated with 44 Ti. Our calculations which derive from schematic and simple terms confirm earlier conclusions obtained by using realistic interactions: the SU(3) symmetry of the quadrupole term is broken mainly by the spin-orbit term, but the energies depends strongly on pairing.

  12. Model for pairing phase transition in atomic nuclei

    International Nuclear Information System (INIS)

    Schiller, A.; Guttormsen, M.; Hjorth-Jensen, M.; Rekstad, J.; Siem, S.

    2002-01-01

    A model is developed which allows the investigation and classification of the pairing phase transition in atomic nuclei. The regions of the parameter space are discussed for which a pairing phase transition can be observed. The model parameters include number of particles, attenuation of pairing correlations with increasing seniority, single-particle level spacing, and pairing gap parameter

  13. Models of charge pair generation in organic solar cells.

    Science.gov (United States)

    Few, Sheridan; Frost, Jarvist M; Nelson, Jenny

    2015-01-28

    Efficient charge pair generation is observed in many organic photovoltaic (OPV) heterojunctions, despite nominal electron-hole binding energies which greatly exceed the average thermal energy. Empirically, the efficiency of this process appears to be related to the choice of donor and acceptor materials, the resulting sequence of excited state energy levels and the structure of the interface. In order to establish a suitable physical model for the process, a range of different theoretical studies have addressed the nature and energies of the interfacial states, the energetic profile close to the heterojunction and the dynamics of excited state transitions. In this paper, we review recent developments underpinning the theory of charge pair generation and phenomena, focussing on electronic structure calculations, electrostatic models and approaches to excited state dynamics. We discuss the remaining challenges in achieving a predictive approach to charge generation efficiency.

  14. Pair formation models for sexually transmitted infections : A primer

    NARCIS (Netherlands)

    Kretzschmar, MEE; Heijne, Janneke C M

    For modelling sexually transmitted infections, duration of partnerships can strongly influence the transmission dynamics of the infection. If partnerships are monogamous, pairs of susceptible individuals are protected from becoming infected, while pairs of infected individuals delay onward

  15. Quasi spin pairing and the structure of the Lipkin model

    International Nuclear Information System (INIS)

    Cambiaggio, M.C.; Plastino, A.

    1978-01-01

    By introducing the concepts of quasi-spin pairing and quasi-spin seniority, the Lipkin model is extended to a variable number of particles. The properties of quasi-spin pairing are seen to be quite similar to those of ordinary pairing. The quasi-spin seniority allows one to obtain a simple classification of excited multiplets. A 'pairing plus monopole' model is studied in connection with the Hartree-Fock theory. (orig.) [de

  16. Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

    Directory of Open Access Journals (Sweden)

    Stéphanie Pérot

    Full Text Available Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely

  17. Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

    Science.gov (United States)

    Pérot, Stéphanie; Regad, Leslie; Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A; Villoutreix, Bruno O; Camproux, Anne-Claude

    2013-01-01

    Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket

  18. Early Psychosocial Stress Predicts Extra-Pair Copulations

    Directory of Open Access Journals (Sweden)

    Nicole Koehler

    2007-01-01

    Full Text Available Cheating on a mate, known as an extra-pair copulation (EPC, is considered unacceptable by most individuals. Nonetheless many individuals engage in such risky behaviors. Because individuals with high, as opposed to low, levels of early psychosocial stress are more risk prone and more likely to engage in opportunistic matings, we predicted that individuals reporting EPCs, one of many types of opportunistic mating (e.g., one-night stand, consecutive short-term relationships etc, have higher levels of early psychosocial stress than those who do not. Two types of EPCs were examined: EPC-self (EPC-S, having sex with someone other than one's mate, and EPC-other (EPC-O, having sex with someone else's mate. In a sample of 229 women and 161 men, significantly higher levels of early psychosocial stress were found amongst those reporting an EPC-S than those reporting none, irrespective of EPC-Os. Furthermore, the more EPC-Ss men, but not women, reported the higher their early psychosocial stress. Early psychosocial stress was not associated with EPC-Os irrespective of EPC-Ss. Participants were also classified into one of four groups (no EPCs, EPC-O only, EPC-S only, or EPC-S&O which significantly interacted with early psychosocial stress. Results are discussed from adaptationist and mechanist perspectives and why early psychosocial stress was higher in individuals reporting EPC-Ss irrespective of EPC-Os, but not EPC-Os irrespective of EPC-Ss, than those not reporting the EPC of interest.

  19. AGT, Burge pairs and minimal models

    International Nuclear Information System (INIS)

    Bershtein, M.; Foda, O.

    2014-01-01

    We consider the AGT correspondence in the context of the conformal field theory M p,p ′ ⊗M H , where M p,p ′ is the minimal model based on the Virasoro algebra V p,p ′ labeled by two co-prime integers {p,p ′ }, 1pairs {Y 1 ι ,Y 2 ι } that satisfy Y 2,σ ι,⊺ −Y 1,σ+r ι −1 ι,⊺ ≥1−s ι , and Y 1,σ ι,⊺ −Y 2,σ+p−r ι −1 ι,⊺ ≥1−p ′ +s ι , where Y i,σ ι,⊺ is the σ-column of Y i ι , i∈{1,2}, we obtain a well-defined expression that we identify with B n p,p ′ ,H . We check the correctness of this expression for 1. Any 1-point B 1 p,p ′ ,H on the torus, when the operator insertion is the identity, and 2. The 6-point B 3 3,4,H on the sphere that involves six Ising magnetic operators.

  20. Paired Model Evaluation of OCR Algorithms

    National Research Council Canada - National Science Library

    Kanungo, Tapas; Marton, Gregory A; Bulbul, Osama

    1998-01-01

    Characterizing the performance of Optical Character Recognition (OCR) systems is crucial for monitoring technical progress predicting, OCR performance, providing scientific explanations for system behavior and identifying open problems...

  1. AGT, Burge pairs and minimal models

    Energy Technology Data Exchange (ETDEWEB)

    Bershtein, M. [Landau Institute for Theoretical Physics,Chernogolovka (Russian Federation); Institute for Information Transmission Problems,Moscow (Russian Federation); National Research University Higher School of Economics, International Laboratory of Representation Theory and Mathematical Physics, Independent University of Moscow, Moscow (Russian Federation); Foda, O. [Mathematics and Statistics, University of Melbourne,Parkville, VIC 3010 (Australia)

    2014-06-30

    We consider the AGT correspondence in the context of the conformal field theory M{sup p,p{sup ′}}⊗M{sup H}, where M{sup p,p{sup ′}} is the minimal model based on the Virasoro algebra V{sup p,p{sup ′}} labeled by two co-prime integers {p,p"′}, 1pairs {Y_1"ι,Y_2"ι} that satisfy Y{sub 2,σ}{sup ι,⊺}−Y{sub 1,σ+r{sub ι−1}{sup ι,⊺}}≥1−s{sub ι}, and Y{sub 1,σ}{sup ι,⊺}−Y{sub 2,σ+p−r{sub ι−1}{sup ι,⊺}}≥1−p{sup ′}+s{sub ι}, where Y{sub i,σ}{sup ι,⊺} is the σ-column of Y{sub i}{sup ι}, i∈{1,2}, we obtain a well-defined expression that we identify with B{sub n}{sup p,p{sup ′,H}}. We check the correctness of this expression for 1. Any 1-point B{sub 1}{sup p,p{sup ′,H}} on the torus, when the operator insertion is the identity, and 2. The 6-point B{sub 3}{sup 3,4,H} on the sphere that involves six Ising magnetic operators.

  2. Model of pair aggregation on the Bethe lattice

    DEFF Research Database (Denmark)

    Baillet, M.V.-P.; Pacheco, A.F.; Gómez, J.B.

    1997-01-01

    We extend a recent model of aggregation of pairs of particles, analyzing the case in which the supporting framework is a Bethe lattice. The model exhibits a critical behavior of the percolation theory type....

  3. Comparability of results from pair and classical model formulations for different sexually transmitted infections.

    Directory of Open Access Journals (Sweden)

    Jimmy Boon Som Ong

    Full Text Available The "classical model" for sexually transmitted infections treats partnerships as instantaneous events summarized by partner change rates, while individual-based and pair models explicitly account for time within partnerships and gaps between partnerships. We compared predictions from the classical and pair models over a range of partnership and gap combinations. While the former predicted similar or marginally higher prevalence at the shortest partnership lengths, the latter predicted self-sustaining transmission for gonorrhoea (GC and Chlamydia (CT over much broader partnership and gap combinations. Predictions on the critical level of condom use (C(c required to prevent transmission also differed substantially when using the same parameters. When calibrated to give the same disease prevalence as the pair model by adjusting the infectious duration for GC and CT, and by adjusting transmission probabilities for HIV, the classical model then predicted much higher C(c values for GC and CT, while C(c predictions for HIV were fairly close. In conclusion, the two approaches give different predictions over potentially important combinations of partnership and gap lengths. Assuming that it is more correct to explicitly model partnerships and gaps, then pair or individual-based models may be needed for GC and CT since model calibration does not resolve the differences.

  4. Proton-neutron correlations in a broken-pair model

    International Nuclear Information System (INIS)

    Akkermans, J.N.L.

    1981-01-01

    In this thesis nuclear-structure calculations are reported which were performed with the broken-pair model. The model which is developed, is an extension of existing broken-pair models in so far that it includes both proton and neutron valence pairs. The relevant formalisms are presented. In contrast to the number-non-conserving model, a proton-neutron broken-pair model is well suited to study the correlations which are produced by the proton-neutron interaction. It is shown that the proton-neutron force has large matrix elements which mix the proton- with neutron broken-pair configurations. This occurs especially for Jsup(PI)=2 + and 3 - pairs. This property of the proton-neutron force is used to improve the spectra of single-closed shell nuclei, where particle-hole excitations of the closed shell are a special case of broken-pair configurations. Using Kr and Te isotopes it is demonstrated that the proton-neutron force gives rise to correlated pair structures, which remain remarkably constant with varying nucleon numbers. (Auth.)

  5. Fully-differential NNLO predictions for vector-boson pair production with MATRIX

    CERN Document Server

    Wiesemann, Marius; Kallweit, Stefan; Rathlev, Dirk

    2016-01-01

    We review the computations of the next-to-next-to-leading order (NNLO) QCD corrections to vector-boson pair production processes in proton–proton collisions and their implementation in the numerical code MATRIX. Our calculations include the leptonic decays of W and Z bosons, consistently taking into account all spin correlations, off-shell effects and non-resonant contributions. For massive vector-boson pairs we show inclusive cross sections, applying the respective mass windows chosen by ATLAS and CMS to define Z bosons from their leptonic decay products, as well as total cross sections for stable bosons. Moreover, we provide samples of differential distributions in fiducial phase-space regions inspired by typical selection cuts used by the LHC experiments. For the vast majority of measurements, the inclusion of NNLO corrections significantly improves the agreement of the Standard Model predictions with data.

  6. Intruder level and deformation in SD-pair shell model

    International Nuclear Information System (INIS)

    Luo Yan'an; Ning Pingzhi; Pan Feng

    2004-01-01

    The influence of intruder level on nuclear deformation is studied within the framework of the nucleon-pair shell model truncated to an SD-pair subspace. The results suggest that the intruder level has a tendency to reduce the deformation and plays an important role in determining the onset of rotational behavior. (authors)

  7. Identification of residue pairing in interacting β-strands from a predicted residue contact map.

    Science.gov (United States)

    Mao, Wenzhi; Wang, Tong; Zhang, Wenxuan; Gong, Haipeng

    2018-04-19

    Despite the rapid progress of protein residue contact prediction, predicted residue contact maps frequently contain many errors. However, information of residue pairing in β strands could be extracted from a noisy contact map, due to the presence of characteristic contact patterns in β-β interactions. This information may benefit the tertiary structure prediction of mainly β proteins. In this work, we propose a novel ridge-detection-based β-β contact predictor to identify residue pairing in β strands from any predicted residue contact map. Our algorithm RDb 2 C adopts ridge detection, a well-developed technique in computer image processing, to capture consecutive residue contacts, and then utilizes a novel multi-stage random forest framework to integrate the ridge information and additional features for prediction. Starting from the predicted contact map of CCMpred, RDb 2 C remarkably outperforms all state-of-the-art methods on two conventional test sets of β proteins (BetaSheet916 and BetaSheet1452), and achieves F1-scores of ~ 62% and ~ 76% at the residue level and strand level, respectively. Taking the prediction of the more advanced RaptorX-Contact as input, RDb 2 C achieves impressively higher performance, with F1-scores reaching ~ 76% and ~ 86% at the residue level and strand level, respectively. In a test of structural modeling using the top 1 L predicted contacts as constraints, for 61 mainly β proteins, the average TM-score achieves 0.442 when using the raw RaptorX-Contact prediction, but increases to 0.506 when using the improved prediction by RDb 2 C. Our method can significantly improve the prediction of β-β contacts from any predicted residue contact maps. Prediction results of our algorithm could be directly applied to effectively facilitate the practical structure prediction of mainly β proteins. All source data and codes are available at http://166.111.152.91/Downloads.html or the GitHub address of https://github.com/wzmao/RDb2C .

  8. Analysis model for forecasting extreme temperature using refined rank set pair

    Directory of Open Access Journals (Sweden)

    Qiao Ling-Xia

    2013-01-01

    Full Text Available In order to improve the precision of forecasting extreme temperature time series, a refined rank set pair analysis model with a refined rank transformation function is proposed to improve precision of its prediction. The measured values of the annual highest temperature of two China’s cities, Taiyuan and Shijiazhuang, in July are taken to examine the performance of a refined rank set pair model.

  9. An Intelligent Model for Pairs Trading Using Genetic Algorithms.

    Science.gov (United States)

    Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

  10. Nucleon-pair approximation to the nuclear shell model

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Y.M., E-mail: ymzhao@sjtu.edu.cn [Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240 (China); Arima, A. [Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240 (China); Musashi Gakuen, 1-26-1 Toyotamakami Nerima-ku, Tokyo 176-8533 (Japan)

    2014-12-01

    Atomic nuclei are complex systems of nucleons–protons and neutrons. Nucleons interact with each other via an attractive and short-range force. This feature of the interaction leads to a pattern of dominantly monopole and quadrupole correlations between like particles (i.e., proton–proton and neutron–neutron correlations) in low-lying states of atomic nuclei. As a consequence, among dozens or even hundreds of possible types of nucleon pairs, very few nucleon pairs such as proton and neutron pairs with spin zero, two (in some cases spin four), and occasionally isoscalar spin-aligned proton–neutron pairs, play important roles in low-energy nuclear structure. The nucleon-pair approximation therefore provides us with an efficient truncation scheme of the full shell model configurations which are otherwise too large to handle for medium and heavy nuclei in foreseeable future. Furthermore, the nucleon-pair approximation leads to simple pictures in physics, as the dimension of nucleon-pair subspace is always small. The present paper aims at a sound review of its history, formulation, validity, applications, as well as its link to previous approaches, with the focus on the new developments in the last two decades. The applicability of the nucleon-pair approximation and numerical calculations of low-lying states for realistic atomic nuclei are demonstrated with examples. Applications of pair approximations to other problems are also discussed.

  11. Pair formation models for sexually transmitted infections: A primer

    Directory of Open Access Journals (Sweden)

    Mirjam Kretzschmar

    2017-08-01

    Full Text Available For modelling sexually transmitted infections, duration of partnerships can strongly influence the transmission dynamics of the infection. If partnerships are monogamous, pairs of susceptible individuals are protected from becoming infected, while pairs of infected individuals delay onward transmission of the infection as long as they persist. In addition, for curable infections re-infection from an infected partner may occur. Furthermore, interventions based on contact tracing rely on the possibility of identifying and treating partners of infected individuals. To reflect these features in a mathematical model, pair formation models were introduced to mathematical epidemiology in the 1980's. They have since been developed into a widely used tool in modelling sexually transmitted infections and the impact of interventions. Here we give a basic introduction to the concepts of pair formation models for a susceptible-infected-susceptible (SIS epidemic. We review some results and applications of pair formation models mainly in the context of chlamydia infection. Keywords: Pair formation, Mathematical model, Partnership duration, Sexually transmitted infections, Basic reproduction number

  12. The Potts model and flows. 1. The pair correlation function

    International Nuclear Information System (INIS)

    Essam, J.W.; Tsallis, C.

    1985-01-01

    It is shown that the partition function for the lambda-state Potts model with pair-interactions is related to the expected number of integer mod-lambda flows in a percolation model. The relation is generalised to the pair correlation function. The resulting high temperature expansion coefficients are shown to be the flow polynomials of graph theory. An observation of Tsallis and Levy concerning the equivalent transmissivity of a cluster is also proved. (Author) [pt

  13. Species-environment associations and predicted distribution of Black Oystercatcher breeding pairs in Haida Gwaii, British Columbia, Canada

    Directory of Open Access Journals (Sweden)

    Sebastian Dalgarno

    2017-12-01

    Full Text Available We present a species distribution model (SDM for prediction of Black Oystercatcher (Haematopus bachmani breeding pair occurrence in Haida Gwaii, British Columbia. Boosted regression trees, a machine learning algorithm, was used to fit the model. In total, 14 predictors were selected a priori through development of a conceptual model. Breeding pair occurrence data were compiled from two available surveys conducted in 2005 and 2010 (545 km of shoreline surveyed in total. All data were aggregated to common model units (vector polyline shoreline segments approximately 100 m in length, which approximate breeding territory size. The final model, which included eight predictors (distance to treeline, island area, wave exposure, shoreline type, intertidal area within 50 m, segment length, rat occurrence, and intertidal area within 1000 m, had excellent predictive ability assessed by 10-fold cross-validation (AUC = 0.89. Predictive ability was reduced when the model was trained and tested on spatially (AUC = 0.86 and temporally (AUC = 0.83 independent data. Distance to treeline and island area had greatest influence on the model (RI = 41.5% and RI = 36.7%, respectively; we hypothesized that these predictors are related to avoidance of predators. Partial dependence plots revealed that breeding pairs tended to occur: further from the treeline, on small islands, at high wave exposures, at moderate intertidal area, on bedrock or gravel shoreline types, and on islands without rats. However, breeding pairs tended not to occur on very small islands and at very high wave exposures, which we hypothesize to reflect avoidance of nest washout. Results may inform local conservation and management efforts, i.e., from predictive maps, and eventual development of a high-resolution (~100 m model for prediction of Black Oystercatcher breeding pairs at a regional scale. Further, methods and GIS data sets developed may be used to model distribution of other coastal species

  14. Pairing gaps from nuclear mean-field models

    International Nuclear Information System (INIS)

    Bender, M.; Rutz, K.; Maruhn, J.A.

    2000-01-01

    We discuss the pairing gap, a measure for nuclear pairing correlations, in chains of spherical, semi-magic nuclei in the framework of self-consistent nuclear mean-field models. The equations for the conventional BCS model and the approximate projection-before-variation Lipkin-Nogami method are formulated in terms of local density functionals for the effective interaction. We calculate the Lipkin-Nogami corrections of both the mean-field energy and the pairing energy. Various definitions of the pairing gap are discussed as three-point, four-point and five-point mass-difference formulae, averaged matrix elements of the pairing potential, and single-quasiparticle energies. Experimental values for the pairing gap are compared with calculations employing both a delta pairing force and a density-dependent delta interaction in the BCS and Lipkin-Nogami model. Odd-mass nuclei are calculated in the spherical blocking approximation which neglects part of the the core polarization in the odd nucleus. We find that the five-point mass difference formula gives a very robust description of the odd-even staggering, other approximations for the gap may differ from that up to 30% for certain nuclei. (orig.)

  15. High-Precision Differential Predictions for Top-Quark Pairs at the LHC.

    Science.gov (United States)

    Czakon, Michal; Heymes, David; Mitov, Alexander

    2016-02-26

    We present the first complete next-to-next-to-leading order (NNLO) QCD predictions for differential distributions in the top-quark pair production process at the LHC. Our results are derived from a fully differential partonic Monte Carlo calculation with stable top quarks which involves no approximations beyond the fixed-order truncation of the perturbation series. The NNLO corrections improve the agreement between existing LHC measurements [V. Khachatryan et al. (CMS Collaboration), Eur. Phys. J. C 75, 542 (2015)] and standard model predictions for the top-quark transverse momentum distribution, thus helping alleviate one long-standing discrepancy. The shape of the top-quark pair invariant mass distribution turns out to be stable with respect to radiative corrections beyond NLO which increases the value of this observable as a place to search for physics beyond the standard model. The results presented here provide essential input for parton distribution function fits, implementation of higher-order effects in Monte Carlo generators, as well as top-quark mass and strong coupling determination.

  16. Alpha-transfer reactions and the pairing-vibration model

    International Nuclear Information System (INIS)

    Betts, R.R.

    1977-01-01

    The pairing-vibration model with isospin is extended to include α-transfer reactions. Selection rules and expressions for transition strengths are derived and compared with experimental results for A = 40--66 nuclei. The selection rules are found to be followed quite well in the examples studied. The systematics of ground-state transition strengths are qualitatively quite well reproduced although the quantitative agreement is poor. When the changing nature of the pairing quanta is incorporated using two-particle transfer data the agreement becomes quantitatively good. Evidence is presented for clustering other than that due to pairing in 40 Ca and 44 Ti

  17. Dependence of two-proton radioactivity on nuclear pairing models

    Science.gov (United States)

    Oishi, Tomohiro; Kortelainen, Markus; Pastore, Alessandro

    2017-10-01

    Sensitivity of two-proton emitting decay to nuclear pairing correlation is discussed within a time-dependent three-body model. We focus on the 6Be nucleus assuming α +p +p configuration, and its decay process is described as a time evolution of the three-body resonance state. For a proton-proton subsystem, a schematic density-dependent contact (SDDC) pairing model is employed. From the time-dependent calculation, we observed the exponential decay rule of a two-proton emission. It is shown that the density dependence does not play a major role in determining the decay width, which can be controlled only by the asymptotic strength of the pairing interaction. This asymptotic pairing sensitivity can be understood in terms of the dynamics of the wave function driven by the three-body Hamiltonian, by monitoring the time-dependent density distribution. With this simple SDDC pairing model, there remains an impossible trinity problem: it cannot simultaneously reproduce the empirical Q value, decay width, and the nucleon-nucleon scattering length. This problem suggests that a further sophistication of the theoretical pairing model is necessary, utilizing the two-proton radioactivity data as the reference quantities.

  18. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  19. Automated next-to-leading order predictions for new physics at the LHC: the case of colored scalar pair production

    CERN Document Server

    Degrande, Céline; Hirschi, Valentin; Proudom, Josselin; Shao, Hua-Sheng

    2015-01-01

    We present for the first time the full automation of collider predictions matched with parton showers at the next-to-leading accuracy in QCD within non-trivial extensions of the Standard Model. The sole inputs required from the user are the model Lagrangian and the process of interest. As an application of the above, we explore scenarios beyond the Standard Model where new colored scalar particles can be pair produced in hadron collisions. Using simplified models to describe the new field interactions with the Standard Model, we present precision predictions for the LHC within the MadGraph5 aMC@NLO framework.

  20. Massive mu pair production in a vector field theory model

    CERN Document Server

    Halliday, I G

    1976-01-01

    Massive electrodynamics is treated as a model for the production of massive mu pairs in high-energy hadronic collisions. The dominant diagrams in perturbation theory are identified and analyzed. These graphs have an eikonal structure which leads to enormous cancellations in the two-particle inclusive cross section but not in the n-particle production cross sections. Under the assumption that these cancellations are complete, a Drell-Yan structure appears in the inclusive cross section but the particles accompanying the mu pairs have a very different structure compared to the parton model. The pionization region is no longer empty of particles as in single parton models. (10 refs).

  1. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  2. A two-level solvable model involving competing pairing interactions

    International Nuclear Information System (INIS)

    Dussel, G.G.; Maqueda, E.E.; Perazzo, R.P.J.; Evans, J.A.

    1986-01-01

    A model is considered consisting of nucleons moving in two non-degenerate l-shells and interacting through two pairing residual interactions with (S, T) = (1, 0) and (0, 1). These, together with the single particle hamiltonian induce mutually destructive correlations, giving rise to various collective pictures that can be discussed as representing a two-dimensional space of phases. The model is solved exactly using an O(8)xO(8) group theoretical classification scheme. The transfer of correlated pairs and quartets is also discussed. (orig.)

  3. Current Hormonal Contraceptive Use Predicts Female Extra-Pair and Dyadic Sexual Behavior: Evidence Based on Czech National Survey Data

    Directory of Open Access Journals (Sweden)

    Kateřina Klapilová

    2014-01-01

    Full Text Available Data from 1155 Czech women (493 using oral contraception, 662 non-users, obtained from the Czech National Survey of Sexual Behavior, were used to investigate evolutionary-based hypotheses concerning the predictive value of current oral contraceptive (OC use on extra-pair and dyadic (in-pair sexual behavior of coupled women. Specifically, the aim was to determine whether current OC use was associated with lower extra-pair and higher in-pair sexual interest and behavior, because OC use suppresses cyclical shifts in mating psychology that occur in normally cycling women. Zero-inflated Poisson (ZIP regression and negative binomial models were used to test associations between OC use and these sexual measures, controlling for other relevant predictors (e.g., age, parity, in-pair sexual satisfaction, relationship length. The overall incidence of having had an extra-pair partner or one-night stand in the previous year was not related to current OC use (the majority of the sample had not. However, among the women who had engaged in extra-pair sexual behavior, OC users had fewer one-night stands than non-users, and tended to have fewer partners, than non-users. OC users also had more frequent dyadic intercourse than non-users, potentially indicating higher commitment to their current relationship. These results suggest that suppression of fertility through OC use may alter important aspects of female sexual behavior, with potential implications for relationship functioning and stability.

  4. Dancing to CHANGA: a self-consistent prediction for close SMBH pair formation time-scales following galaxy mergers

    Science.gov (United States)

    Tremmel, M.; Governato, F.; Volonteri, M.; Quinn, T. R.; Pontzen, A.

    2018-04-01

    We present the first self-consistent prediction for the distribution of formation time-scales for close supermassive black hole (SMBH) pairs following galaxy mergers. Using ROMULUS25, the first large-scale cosmological simulation to accurately track the orbital evolution of SMBHs within their host galaxies down to sub-kpc scales, we predict an average formation rate density of close SMBH pairs of 0.013 cMpc-3 Gyr-1. We find that it is relatively rare for galaxy mergers to result in the formation of close SMBH pairs with sub-kpc separation and those that do form are often the result of Gyr of orbital evolution following the galaxy merger. The likelihood and time-scale to form a close SMBH pair depends strongly on the mass ratio of the merging galaxies, as well as the presence of dense stellar cores. Low stellar mass ratio mergers with galaxies that lack a dense stellar core are more likely to become tidally disrupted and deposit their SMBH at large radii without any stellar core to aid in their orbital decay, resulting in a population of long-lived `wandering' SMBHs. Conversely, SMBHs in galaxies that remain embedded within a stellar core form close pairs in much shorter time-scales on average. This time-scale is a crucial, though often ignored or very simplified, ingredient to models predicting SMBH mergers rates and the connection between SMBH and star formation activity.

  5. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  6. Sensitivity analysis of physiochemical interaction model: which pair ...

    African Journals Online (AJOL)

    ... of two model parameters at a time on the solution trajectory of physiochemical interaction over a time interval. Our aim is to use this powerful mathematical technique to select the important pair of parameters of this physical process which is cost-effective. Keywords: Passivation Rate, Sensitivity Analysis, ODE23, ODE45 ...

  7. Predicting co-complexed protein pairs using genomic and proteomic data integration

    Directory of Open Access Journals (Sweden)

    King Oliver D

    2004-04-01

    Full Text Available Abstract Background Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H and affinity purification coupled with mass spectrometry (APMS have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship. Results Using a supervised machine learning approach – probabilistic decision tree, we integrated high-throughput protein interaction datasets and other gene- and protein-pair characteristics to predict co-complexed pairs (CCP of proteins. Our predictions proved more sensitive and specific than predictions based on Y2H or APMS methods alone or in combination. Among the top predictions not annotated as CCPs in our reference set (obtained from the MIPS complex catalogue, a significant fraction was found to physically interact according to a separate database (YPD, Yeast Proteome Database, and the remaining predictions may potentially represent unknown CCPs. Conclusions We demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP pairs from other characteristics. Our top-scoring CCP predictions provide testable hypotheses for experimental validation.

  8. Bayesian non parametric modelling of Higgs pair production

    Directory of Open Access Journals (Sweden)

    Scarpa Bruno

    2017-01-01

    Full Text Available Statistical classification models are commonly used to separate a signal from a background. In this talk we face the problem of isolating the signal of Higgs pair production using the decay channel in which each boson decays into a pair of b-quarks. Typically in this context non parametric methods are used, such as Random Forests or different types of boosting tools. We remain in the same non-parametric framework, but we propose to face the problem following a Bayesian approach. A Dirichlet process is used as prior for the random effects in a logit model which is fitted by leveraging the Polya-Gamma data augmentation. Refinements of the model include the insertion in the simple model of P-splines to relate explanatory variables with the response and the use of Bayesian trees (BART to describe the atoms in the Dirichlet process.

  9. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-27

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  10. Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices

    Directory of Open Access Journals (Sweden)

    David Ardia

    2016-03-01

    Full Text Available We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior, which is shown to be equivalent to a Jeffreys’ prior, has under an orthogonal normalization for the selection of pairs of cointegrated stock prices and further, its effect for the estimation and prediction of the spread between cointegrated stock prices. We distinguish between models with a normal and Student t distribution since the latter typically provides a better description of daily changes of prices on financial markets. As an empirical application, stocks are used that are ingredients of the Dow Jones Composite Average index. The results show that normalization has little effect on the selection of pairs of cointegrated stocks on the basis of Bayes factors. However, the results stress the importance of the orthogonal normalization for the estimation and prediction of the spread—the deviation from the equilibrium relationship—which leads to better results in terms of profit per capital engagement and risk than using a standard linear normalization.

  11. Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

    Science.gov (United States)

    Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

    2014-01-01

    Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

  12. Bayesian modeling to paired comparison data via the Pareto distribution

    Directory of Open Access Journals (Sweden)

    Nasir Abbas

    2017-12-01

    Full Text Available A probabilistic approach to build models for paired comparison experiments based on the comparison of two Pareto variables is considered. Analysis of the proposed model is carried out in classical as well as Bayesian frameworks. Informative and uninformative priors are employed to accommodate the prior information. Simulation study is conducted to assess the suitablily and performance of the model under theoretical conditions. Appropriateness of fit of the is also carried out. Entire inferential procedure is illustrated by comparing certain cricket teams using real dataset.

  13. PENERAPAN MODEL PEMBELAJARAN THINK PAIR SHARE DALAM MENINGKATKAN HASIL BELAJAR

    Directory of Open Access Journals (Sweden)

    Pramita Dewi Harjayanti

    2012-06-01

    Full Text Available Penelitian ini bertujuan� untuk mengetahui apakah ada peningkatan hasil pada kompetensi dasar memelihara peralatan kantor, setelah dilakukan penelitian tindakan kelas dengan model pembelajaran think pair share. Subyek penelitian ini adalah siswa kelas X AP SMK YPPM Boja. Hasil penelitian setelah dilakukan tindakan hasil belajar siswa pada post test meningkat hingga mencapai ketuntasan klasikal 66,67% dengan rata-rata nilai 72,45. Kemudian pada siklus II ketuntasan klasikal mengalami peningkatan menjadi 83,33% dengan nilai rata-rata siswa 77,45 sehingga peningkatan dari siklus I ke siklus II sebesar 16,67%. Pembelajaran dengan model pembelajaran think pair share mendapat respon baik dari siswa pada siklus I sebesar 77,5% meningkat menjadi 90% pada siklus II. Berdasarkan hasil penelitian disimpulkan bahwa ada peningkatan hasil belajar siswa kelas X AP SMK YPPM Boja pada kompetensi dasar memelihara peralatan kantor dengan model pembelajaran think pair share. This study aims to determine whether there is an increase in learning outcomes of administration on the subject of adjusting entries, having done research with the collaboration of a class action use method of think pair share. Subyek think this study is the students' high school grade� X AP SMK YPPM Boja. The results obtained student learning outcomes through before the action reaches 66,67% classical completeness with the average value 0f 72,45 in once siklus. After the students' actions in second siklus on the post test increased to 83,33% with the classical completeness the average value of 77,45. Resulting in an increase of 16,67%. Collaborative learning with the method of think pair share received good response from students with average percentage of responses 77,5% in first siklus and increased to 90% in second siklus. Based on the results of the study concluded that there was an increase in students' social studies class X AP on the subject of an adjusting entry through with the

  14. A community computational challenge to predict the activity of pairs of compounds.

    Science.gov (United States)

    Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

    2014-12-01

    Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

  15. Processes with weak gauge boson pairs at hadron colliders. Precise predictions and future prospects

    Energy Technology Data Exchange (ETDEWEB)

    Salfelder, Lukas

    2017-02-08

    In the last years, scattering processes comprising pairs of the massive weak gauge bosons gain more and more attention. Those reactions provide particularly promising means to investigate the very mechanism responsible for electroweak symmetry breaking in the Standard Model of particle physics and to search for new physics entering via the weak sector of the theory. Precisely predicting the differential distributions of the final-state particles in realistic conditions is an essential prerequisite to potentially reveal tiny deviations induced by physics beyond the Standard Model. In this thesis we present a calculation of the next-to-leading order (NLO) electroweak corrections to W-boson pair production at CERNs Large Hadron Collider (LHC), as well as a detailed analysis of vector-boson scattering (VBS) processes at a future high-energy proton.proton collider. In particular, our calculation of the NLO electroweak corrections to the hadronic process pp→W{sup +}W{sup -}→4 leptons takes the leptonic W-boson decays as well as all off-shell effects fully into account and, thus, is the first prediction providing NLO accuracy everywhere in phase space. Employing realistic event selection criteria, we study the influence of the corrections in situations that are typical for the experimental analyses in the high-energy region and for Higgs-boson precision studies in the channel H→WW{sup *}, to which direct W-boson pair production represents an important irreducible background. We observe non-trivial distortions of the differential distributions that, if not properly included in upcoming analyses, could easily be misidentified as first signs of new physics. Furthermore, we compare our predictions to previous results obtained by employing the so-called double-pole approximation. At small and intermediate scales the two approaches show the expected agreement at the level of fractions of a percent, while in the TeV range the differences may easily reach several tens of

  16. Top quark pair production and modeling via QCD in CMS

    CERN Document Server

    Gonzalez Fernandez, Juan Rodrigo

    2017-01-01

    Measurements of the inclusive and differential top quark pair ($\\textrm{t}\\bar{\\textrm{t}}$) production cross section at centre-of-mass energies of 13 TeV and 5.02 TeV are presented, performed using CMS data collected in 2015 and 2016. The inclusive cross section is measured in the lepton+jets, dilepton and fully hadronic channels. Top quark pair differential cross sections are measured and are given as functions of various kinematic observables of (anti)top quark, the $\\textrm{t}\\bar{\\textrm{t}}$ system, and of the jets and leptons in the final state. Furthermore, the multiplicity and kinematic distributions of the additional jets produced in $\\textrm{t}\\bar{\\textrm{t}}$ events are also investigated and its modeling is compared for several generators. A new tune of parameters is developed for some of the generators. In addition, first measurements of top quark pair production with additional b quarks in the final state are presented. Furthermore, searches for four top quark production in CMS are also present...

  17. Tyrosine Kinase Ligand-Receptor Pair Prediction by Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Masayuki Yarimizu

    2015-01-01

    Full Text Available Receptor tyrosine kinases are essential proteins involved in cellular differentiation and proliferation in vivo and are heavily involved in allergic diseases, diabetes, and onset/proliferation of cancerous cells. Identifying the interacting partner of this protein, a growth factor ligand, will provide a deeper understanding of cellular proliferation/differentiation and other cell processes. In this study, we developed a method for predicting tyrosine kinase ligand-receptor pairs from their amino acid sequences. We collected tyrosine kinase ligand-receptor pairs from the Database of Interacting Proteins (DIP and UniProtKB, filtered them by removing sequence redundancy, and used them as a dataset for machine learning and assessment of predictive performance. Our prediction method is based on support vector machines (SVMs, and we evaluated several input features suitable for tyrosine kinase for machine learning and compared and analyzed the results. Using sequence pattern information and domain information extracted from sequences as input features, we obtained 0.996 of the area under the receiver operating characteristic curve. This accuracy is higher than that obtained from general protein-protein interaction pair predictions.

  18. Massive lepton pair production: what has QCD done to the classical Drell-Yan model

    International Nuclear Information System (INIS)

    Berger, E.L.

    1982-11-01

    A report is presented of recent experimental and theoretical progress in studies of the production of massive lepton pairs in hadronic collisions. Among the topics discussed are deviations from scaling, the status of the proofs of factorization in the parton model, higher-order terms in the QCD expansion, the discrepancy between measured and predicted yields (K factor), high-twist terms, soft gluon effects, and transverse momentum distributions

  19. Effects of ion strength and ion pairing on (plant-wide) modelling of anaerobic digestion processes

    DEFF Research Database (Denmark)

    Flores-Alsina, Xavier; Mbamba, Christian Kazadi; Solon, Kimberly

    2014-01-01

    the effects that an improved physico-chemical description will have on the predicted effluent quality (EQI) and operational cost (OCI) indices. The acid-base equilibria implemented in the Anaerobic Digestion Model No.1 (ADM1) are modified to account for non-ideal aqueous-phase chemistry. The model corrects......The objective of this study is to show the influence of ionic strength (as activity corrections) andion pairing on (plant-wide) modelling of anaerobic digestion processes in wastewater treatment plants(WWTPs). Using the Benchmark Simulation Model No. 2 (BSM2) as a case study, this paper presents...... for ionic strength via the Davies approach to consider chemical activities instead of molar concentrations. Also, a speciation sub-routine based on a multi-dimensional Newton-Raphson iteration method accounts for the formation of some of the ion pairs playing an important role in wastewater treatment...

  20. Infants' Temperament and Mothers', and Fathers' Depression Predict Infants' Attention to Objects Paired with Emotional Faces.

    Science.gov (United States)

    Aktar, Evin; Mandell, Dorothy J; de Vente, Wieke; Majdandžić, Mirjana; Raijmakers, Maartje E J; Bögels, Susan M

    2016-07-01

    Between 10 and 14 months, infants gain the ability to learn about unfamiliar stimuli by observing others' emotional reactions to those stimuli, so called social referencing (SR). Joint processing of emotion and head/gaze direction is essential for SR. This study tested emotion and head/gaze direction effects on infants' attention via pupillometry in the period following the emergence of SR. Pupil responses of 14-to-17-month-old infants (N = 57) were measured during computerized presentations of unfamiliar objects alone, before-and-after being paired with emotional (happy, sad, fearful vs. neutral) faces gazing towards (vs. away) from objects. Additionally, the associations of infants' temperament, and parents' negative affect/depression/anxiety with infants' pupil responses were explored. Both mothers and fathers of participating infants completed questionnaires about their negative affect, depression and anxiety symptoms and their infants' negative temperament. Infants allocated more attention (larger pupils) to negative vs. neutral faces when the faces were presented alone, while they allocated less attention to objects paired with emotional vs. neutral faces independent of head/gaze direction. Sad (but not fearful) temperament predicted more attention to emotional faces. Infants' sad temperament moderated the associations of mothers' depression (but not anxiety) with infants' attention to objects. Maternal depression predicted more attention to objects paired with emotional expressions in infants low in sad temperament, while it predicted less attention in infants high in sad temperament. Fathers' depression (but not anxiety) predicted more attention to objects paired with emotional expressions independent of infants' temperament. We conclude that infants' own temperamental dispositions for sadness, and their exposure to mothers' and fathers' depressed moods may influence infants' attention to emotion-object associations in social learning contexts.

  1. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

    OpenAIRE

    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed...

  2. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    CR cultural resource CRM cultural resource management CRPM Cultural Resource Predictive Modeling DoD Department of Defense ESTCP Environmental...resource management ( CRM ) legal obligations under NEPA and the NHPA, military installations need to demonstrate that CRM decisions are based on objective...maxim “one size does not fit all,” and demonstrate that DoD installations have many different CRM needs that can and should be met through a variety

  3. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  4. Pairing of parafermions of order 2: seniority model

    International Nuclear Information System (INIS)

    Nelson, Charles A

    2004-01-01

    As generalizations of the fermion seniority model, four multi-mode Hamiltonians are considered to investigate some of the consequences of the pairing of parafermions of order 2. Two- and four-particle states are explicitly constructed for H A ≡ -GA†A with A† ≡ 1/2 Σ m>0 c† m c† -m and the distinct H C ≡ -GC†C with C† ≡ 1/2 Σ m>0 c† -m c† m , and for the time-reversal invariant H (-) ≡ -G(A† - C†)(A - C) and H (+) ≡ -G(A† + C†)(A + C), which has no analogue in the fermion case. The spectra and degeneracies are compared with those of the usual fermion seniority model

  5. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  6. A Model of Electron-Positron Pair Formation

    Directory of Open Access Journals (Sweden)

    Lehnert B.

    2008-01-01

    Full Text Available The elementary electron-positron pair formation process is consideredin terms of a revised quantum electrodynamic theory, with specialattention to the conservation of energy, spin, and electric charge.The theory leads to a wave-packet photon model of narrow line widthand needle-radiation properties, not being available from conventionalquantum electrodynamics which is based on Maxwell's equations. Themodel appears to be consistent with the observed pair productionprocess, in which the created electron and positron form two raysthat start within a very small region and have original directionsalong the path of the incoming photon. Conservation of angular momentum requires the photon to possess a spin, as given by the present theory but not by the conventional one. The nonzero electric field divergence further gives rise to a local intrinsic electric charge density within the photon body, whereas there is a vanishing total charge of the latter. This may explain the observed fact that the photon decays on account of the impact from an external electric field. Such a behaviour should not become possible for a photon having zero local electric charge density.

  7. Modelling the secular evolution of migrating planet pairs

    Science.gov (United States)

    Michtchenko, T. A.; Rodríguez, A.

    2011-08-01

    The subject of this paper is the secular behaviour of a pair of planets evolving under dissipative forces. In particular, we investigate the case when dissipative forces affect the planetary semimajor axes and the planets move inwards/outwards the central star, in a process known as planet migration. To perform this investigation, we introduce fundamental concepts of conservative and dissipative dynamics of the three-body problem. Based on these concepts, we develop a qualitative model of the secular evolution of the migrating planetary pair. Our approach is based on the analysis of the energy and the orbital angular momentum exchange between the two-planet system and an external medium; thus no specific kind of dissipative forces is invoked. We show that, under the assumption that dissipation is weak and slow, the evolutionary routes of the migrating planets are traced by the Mode I and Mode II stationary solutions of the conservative secular problem. The ultimate convergence and the evolution of the system along one of these secular modes of motion are determined uniquely by the condition that the dissipation rate is sufficiently smaller than the proper secular frequency of the system. We show that it is possible to reassemble the starting configurations and the migration history of the systems on the basis of their final states and consequently to constrain the parameters of the physical processes involved.

  8. General mirror pairs for gauged linear sigma models

    Energy Technology Data Exchange (ETDEWEB)

    Aspinwall, Paul S.; Plesser, M. Ronen [Departments of Mathematics and Physics, Duke University,Box 90320, Durham, NC 27708-0320 (United States)

    2015-11-05

    We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

  9. General mirror pairs for gauged linear sigma models

    International Nuclear Information System (INIS)

    Aspinwall, Paul S.; Plesser, M. Ronen

    2015-01-01

    We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

  10. Pairing from strong repulsion in triangular lattice Hubbard model

    Science.gov (United States)

    Zhang, Shang-Shun; Zhu, Wei; Batista, Cristian D.

    2018-04-01

    We propose a pairing mechanism between holes in the dilute limit of doped frustrated Mott insulators. Hole pairing arises from a hole-hole-magnon three-body bound state. This pairing mechanism has its roots on single-hole kinetic energy frustration, which favors antiferromagnetic (AFM) correlations around the hole. We demonstrate that the AFM polaron (hole-magnon bound state) produced by a single hole propagating on a field-induced polarized background is strong enough to bind a second hole. The effective interaction between these three-body bound states is repulsive, implying that this pairing mechanism is relevant for superconductivity.

  11. Modeling the secular evolution of migrating planet pairs

    Science.gov (United States)

    Michtchenko, T. A.; Rodríguez, A.

    2011-10-01

    The secular regime of motion of multi-planetary systems is universal; in contrast with the 'accidental' resonant motion, characteristic only for specific configurations of the planets, secular motion is present everywhere in phase space, even inside the resonant region. The secular behavior of a pair of planets evolving under dissipative forces is the principal subject of this study, particularly, the case when the dissipative forces affect the planetary semi-major axes and the planets move inward/outward the central star, the process known as planet migration. Based on the fundamental concepts of conservative and dissipative dynamics of the three-body problem, we develop a qualitative model of the secular evolution of the migrating planetary pair. Our approach is based on analysis of the energy and the orbital angular momentum exchange between the two-planet system and an external medium; thus no specific kind of dissipative forces is invoked. We show that, under assumption that dissipation is weak and slow, the evolutionary routes of the migrating planets are traced by the Mode I and Mode II stationary solutions of the conservative secular problem. The ultimate convergence and the evolution of the system along one of these secular modes of motion is determined uniquely by the condition that the dissipation rate is sufficiently smaller than the proper secular frequency of the system. We show that it is possible to reassemble the starting configurations and migration history of the systems on the basis of their final states and consequently to constrain the parameters of the physical processes involved.

  12. Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

    Directory of Open Access Journals (Sweden)

    Ruan Jishou

    2007-04-01

    Full Text Available Abstract Background Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP; the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction. Results The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are

  13. Pair truncation for rotational nuclei: j=17/2 model

    International Nuclear Information System (INIS)

    Halse, P.; Jaqua, L.; Barrett, B.R.

    1989-01-01

    The suitability of the pair condensate approach for rotational states is studied in a single j=17/2 shell of identical nucleons interacting through a quadrupole-quadrupole Hamiltonian. The ground band and a K=2 excited band are both studied in detail. A direct comparison of the exact states with those constituting the SD and SDG subspaces is used to identify the important degrees of freedom for these levels. The range of pairs necessary for a good description is found to be highly state dependent; S and D pairs are the major constituents of the low-spin ground-band levels, while G pairs are needed for those in the γ band. Energy spectra are obtained for each truncated subspace. SDG pairs allow accurate reproduction of the binding energy and K=2 excitation energy, but still give a moment of inertia which is about 30% too small even for the lowest levels

  14. Understanding valence-shell electron-pair repulsion (VSEPR) theory using origami molecular models

    International Nuclear Information System (INIS)

    Saraswati, Teguh Endah; Saputro, Sulistyo; Ramli, Murni; Praseptiangga, Danar; Khasanah, Nurul; Marwati, Sri

    2017-01-01

    Valence-shell electron-pair repulsion (VSEPR) theory is conventionally used to predict molecular geometry. However, it is difficult to explore the full implications of this theory by simply drawing chemical structures. Here, we introduce origami modelling as a more accessible approach for exploration of the VSEPR theory. Our technique is simple, readily accessible and inexpensive compared with other sophisticated methods such as computer simulation or commercial three-dimensional modelling kits. This method can be implemented in chemistry education at both the high school and university levels. We discuss the example of a simple molecular structure prediction for ammonia (NH 3 ). Using the origami model, both molecular shape and the scientific justification can be visualized easily. This ‘hands-on’ approach to building molecules will help promote understanding of VSEPR theory. (paper)

  15. Understanding valence-shell electron-pair repulsion (VSEPR) theory using origami molecular models

    Science.gov (United States)

    Endah Saraswati, Teguh; Saputro, Sulistyo; Ramli, Murni; Praseptiangga, Danar; Khasanah, Nurul; Marwati, Sri

    2017-01-01

    Valence-shell electron-pair repulsion (VSEPR) theory is conventionally used to predict molecular geometry. However, it is difficult to explore the full implications of this theory by simply drawing chemical structures. Here, we introduce origami modelling as a more accessible approach for exploration of the VSEPR theory. Our technique is simple, readily accessible and inexpensive compared with other sophisticated methods such as computer simulation or commercial three-dimensional modelling kits. This method can be implemented in chemistry education at both the high school and university levels. We discuss the example of a simple molecular structure prediction for ammonia (NH3). Using the origami model, both molecular shape and the scientific justification can be visualized easily. This ‘hands-on’ approach to building molecules will help promote understanding of VSEPR theory.

  16. Paired hormone response elements predict caveolin-1 as a glucocorticoid target gene.

    Directory of Open Access Journals (Sweden)

    Marinus F van Batenburg

    2010-01-01

    Full Text Available Glucocorticoids act in part via glucocorticoid receptor binding to hormone response elements (HREs, but their direct target genes in vivo are still largely unknown. We developed the criterion that genomic occurrence of paired HREs at an inter-HRE distance less than 200 bp predicts hormone responsiveness, based on synergy of multiple HREs, and HRE information from known target genes. This criterion predicts a substantial number of novel responsive genes, when applied to genomic regions 10 kb upstream of genes. Multiple-tissue in situ hybridization showed that mRNA expression of 6 out of 10 selected genes was induced in a tissue-specific manner in mice treated with a single dose of corticosterone, with the spleen being the most responsive organ. Caveolin-1 was strongly responsive in several organs, and the HRE pair in its upstream region showed increased occupancy by glucocorticoid receptor in response to corticosterone. Our approach allowed for discovery of novel tissue specific glucocorticoid target genes, which may exemplify responses underlying the permissive actions of glucocorticoids.

  17. High Level Rule Modeling Language for Airline Crew Pairing

    Science.gov (United States)

    Mutlu, Erdal; Birbil, Ş. Ilker; Bülbül, Kerem; Yenigün, Hüsnü

    2011-09-01

    The crew pairing problem is an airline optimization problem where a set of least costly pairings (consecutive flights to be flown by a single crew) that covers every flight in a given flight network is sought. A pairing is defined by using a very complex set of feasibility rules imposed by international and national regulatory agencies, and also by the airline itself. The cost of a pairing is also defined by using complicated rules. When an optimization engine generates a sequence of flights from a given flight network, it has to check all these feasibility rules to ensure whether the sequence forms a valid pairing. Likewise, the engine needs to calculate the cost of the pairing by using certain rules. However, the rules used for checking the feasibility and calculating the costs are usually not static. Furthermore, the airline companies carry out what-if-type analyses through testing several alternate scenarios in each planning period. Therefore, embedding the implementation of feasibility checking and cost calculation rules into the source code of the optimization engine is not a practical approach. In this work, a high level language called ARUS is introduced for describing the feasibility and cost calculation rules. A compiler for ARUS is also implemented in this work to generate a dynamic link library to be used by crew pairing optimization engines.

  18. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  19. Prediction of plant promoters based on hexamers and random triplet pair analysis

    Directory of Open Access Journals (Sweden)

    Noman Nasimul

    2011-06-01

    Full Text Available Abstract Background With an increasing number of plant genome sequences, it has become important to develop a robust computational method for detecting plant promoters. Although a wide variety of programs are currently available, prediction accuracy of these still requires further improvement. The limitations of these methods can be addressed by selecting appropriate features for distinguishing promoters and non-promoters. Methods In this study, we proposed two feature selection approaches based on hexamer sequences: the Frequency Distribution Analyzed Feature Selection Algorithm (FDAFSA and the Random Triplet Pair Feature Selecting Genetic Algorithm (RTPFSGA. In FDAFSA, adjacent triplet-pairs (hexamer sequences were selected based on the difference in the frequency of hexamers between promoters and non-promoters. In RTPFSGA, random triplet-pairs (RTPs were selected by exploiting a genetic algorithm that distinguishes frequencies of non-adjacent triplet pairs between promoters and non-promoters. Then, a support vector machine (SVM, a nonlinear machine-learning algorithm, was used to classify promoters and non-promoters by combining these two feature selection approaches. We referred to this novel algorithm as PromoBot. Results Promoter sequences were collected from the PlantProm database. Non-promoter sequences were collected from plant mRNA, rRNA, and tRNA of PlantGDB and plant miRNA of miRBase. Then, in order to validate the proposed algorithm, we applied a 5-fold cross validation test. Training data sets were used to select features based on FDAFSA and RTPFSGA, and these features were used to train the SVM. We achieved 89% sensitivity and 86% specificity. Conclusions We compared our PromoBot algorithm to five other algorithms. It was found that the sensitivity and specificity of PromoBot performed well (or even better with the algorithms tested. These results show that the two proposed feature selection methods based on hexamer frequencies

  20. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation,...

  1. Enhancing the prediction of protein pairings between interacting families using orthology information

    Directory of Open Access Journals (Sweden)

    Pazos Florencio

    2008-01-01

    Full Text Available Abstract Background It has repeatedly been shown that interacting protein families tend to have similar phylogenetic trees. These similarities can be used to predicting the mapping between two families of interacting proteins (i.e. which proteins from one family interact with which members of the other. The correct mapping will be that which maximizes the similarity between the trees. The two families may eventually comprise orthologs and paralogs, if members of the two families are present in more than one organism. This fact can be exploited to restrict the possible mappings, simply by impeding links between proteins of different organisms. We present here an algorithm to predict the mapping between families of interacting proteins which is able to incorporate information regarding orthologues, or any other assignment of proteins to "classes" that may restrict possible mappings. Results For the first time in methods for predicting mappings, we have tested this new approach on a large number of interacting protein domains in order to statistically assess its performance. The method accurately predicts around 80% in the most favourable cases. We also analysed in detail the results of the method for a well defined case of interacting families, the sensor and kinase components of the Ntr-type two-component system, for which up to 98% of the pairings predicted by the method were correct. Conclusion Based on the well established relationship between tree similarity and interactions we developed a method for predicting the mapping between two interacting families using genomic information alone. The program is available through a web interface.

  2. STUDI KOMPARATIF MODEL PEMBELAJARAN THINK PAIR SQUARE DAN THINK PAIR SHARE TERHADAP MOTIVASI DAN HASIL BELAJAR SISWA MAPEL TIK KELAS X SMA N 1 SUKASADA

    OpenAIRE

    Putu Deli Januartini; Ketut Agustini; I Gede Partha Sindu

    2016-01-01

    Abstrak Tujuan penelitian ini untuk mengetahui (1) pengaruh signifikan penggunaan model pembelajaran Think Pair Square dan Think Pair Share terhadap hasil belajar siswa, (2) hasil belajar yang lebih baik antara model pembelajaran Think Pair Square  atau  Think Pair Share, (3) motivasi belajar siswa, (4) respon siswa. Jenis penelitian ini adalah eksperimen semu dengan rancangan Post Test Only Control Group Design. Populasi penelitian ini adalah seluruh siswa kelas X. Sampel dalam penel...

  3. Comparison and Limitations of DVH-Based NTCP Models Derived From 3D-CRT and IMRT Data for Prediction of Gastrointestinal Toxicities in Prostate Cancer Patients by Using Propensity Score Matched Pair Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Troeller, Almut [Department of Radiation Oncology, William Beaumont Health System, Royal Oak, Michigan (United States); Department of Radiotherapy and Radiation Oncology, Ludwig-Maximilians-Universität, Munich (Germany); Yan, Di, E-mail: dyan@beaumont.edu [Department of Radiation Oncology, William Beaumont Health System, Royal Oak, Michigan (United States); Marina, Ovidiu; Schulze, Derek [Department of Radiation Oncology, William Beaumont Health System, Royal Oak, Michigan (United States); Alber, Markus [Department of Oncology, Aarhus University Hospital, Aarhus (Denmark); Parodi, Katia [Department of Medical Physics, Ludwig-Maximilians-Universität, Munich (Germany); Belka, Claus; Söhn, Matthias [Department of Radiotherapy and Radiation Oncology, Ludwig-Maximilians-Universität, Munich (Germany)

    2015-02-01

    Purpose: This study compared normal tissue complication probability (NTCP) modeling of chronic gastrointestinal toxicities following prostate cancer treatment for 2 treatment modalities. Possible factors causing discrepancies in optimal NTCP model parameters between 3-dimensional conformal radiation therapy (3D-CRT) and intensity modulated RT (IMRT) were analyzed and discussed, including the impact of patient characteristics, image guidance, toxicity scoring bias, and NTCP model limitations. Methods and Materials: Rectal wall dose-volume histograms of 1115 patients treated for prostate cancer under an adaptive radiation therapy protocol were used to model gastrointestinal toxicity grade ≥2 (according to Common Terminology Criteria for Adverse Events). A total of 457 patients were treated with 3D-CRT and 658 with IMRT. 3D-CRT patients were matched to IMRT patients based on various patient characteristics, using a propensity score–based algorithm. Parameters of the Lyman equivalent uniform dose and cut-off dose logistic regression NTCP models were estimated for the 2 matched treatment modalities and the combined group. Results: After they were matched, the 3D-CRT and IMRT groups contained 275 and 550 patients with a large discrepancy of 28.7% versus 7.8% toxicities, respectively (P<.001). For both NTCP models, optimal parameters found for the 3D-CRT groups did not fit the IMRT patients well and vice versa. Models developed for the combined data overestimated NTCP for the IMRT patients and underestimated NTCP for the 3D-CRT group. Conclusions: Our analysis did not reveal a single definitive cause for discrepancies of model parameters between 3D-CRT and IMRT. Patient characteristics and bias in toxicity scoring, as well as image guidance alone, are unlikely causes of the large discrepancy of toxicities. Whether the cause was inherent to the specific NTCP models used in this study needs to be verified by future investigations. Because IMRT is increasingly used

  4. Harnessing the landscape of microbial culture media to predict new organism–media pairings

    Science.gov (United States)

    Oberhardt, Matthew A.; Zarecki, Raphy; Gronow, Sabine; Lang, Elke; Klenk, Hans-Peter; Gophna, Uri; Ruppin, Eytan

    2015-01-01

    Culturing microorganisms is a critical step in understanding and utilizing microbial life. Here we map the landscape of existing culture media by extracting natural-language media recipes into a Known Media Database (KOMODO), which includes >18,000 strain–media combinations, >3300 media variants and compound concentrations (the entire collection of the Leibniz Institute DSMZ repository). Using KOMODO, we show that although media are usually tuned for individual strains using biologically common salts, trace metals and vitamins/cofactors are the most differentiating components between defined media of strains within a genus. We leverage KOMODO to predict new organism–media pairings using a transitivity property (74% growth in new in vitro experiments) and a phylogeny-based collaborative filtering tool (83% growth in new in vitro experiments and stronger growth on predicted well-scored versus poorly scored media). These resources are integrated into a web-based platform that predicts media given an organism's 16S rDNA sequence, facilitating future cultivation efforts. PMID:26460590

  5. Probabilistic Category Learning in Developmental Dyslexia: Evidence from Feedback and Paired-Associate Weather Prediction Tasks

    Science.gov (United States)

    Gabay, Yafit; Vakil, Eli; Schiff, Rachel; Holt, Lori L.

    2015-01-01

    Objective Developmental dyslexia is presumed to arise from specific phonological impairments. However, an emerging theoretical framework suggests that phonological impairments may be symptoms stemming from an underlying dysfunction of procedural learning. Method We tested procedural learning in adults with dyslexia (n=15) and matched-controls (n=15) using two versions of the Weather Prediction Task: Feedback (FB) and Paired-associate (PA). In the FB-based task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of response. In the PA-based learning task, participants viewed the cue and its associated outcome simultaneously without overt response or feedback. In both versions, participants trained across 150 trials. Learning was assessed in a subsequent test without presentation of the outcome, or corrective feedback. Results The Dyslexia group exhibited impaired learning compared with the Control group on both the FB and PA versions of the weather prediction task. Conclusions The results indicate that the ability to learn by feedback is not selectively impaired in dyslexia. Rather it seems that the probabilistic nature of the task, shared by the FB and PA versions of the weather prediction task, hampers learning in those with dyslexia. Results are discussed in light of procedural learning impairments among participants with dyslexia. PMID:25730732

  6. Long-term prediction of reading accuracy and speed: The importance of paired-associate learning

    DEFF Research Database (Denmark)

    Poulsen, Mads; Asmussen, Vibeke; Elbro, Carsten

    Purpose: Several cross-sectional studies have found a correlation between paired-associate learning (PAL) and reading (e.g. Litt et al., 2013; Messbauer & de Jong, 2003, 2006). These findings suggest that verbal learning of phonological forms is important for reading. However, results from...... longitudinal studies have been mixed (e.g. Lervåg & Hulme, 2009; Horbach et al. 2015). The present study investigated the possibility that the mixed results may be a result of a conflation of accuracy and speed. It is possible that PAL is a stronger correlate of reading accuracy than speed (Litt et al., 2013...... of reading comprehension and isolated sight word reading accuracy and speed. Results: PAL predicted unique variance in sight word accuracy, but not speed. Furthermore, PAL was indirectly linked to reading comprehension through sight word accuracy. RAN correlated with both accuracy and speed...

  7. A Search for Beyond Standard Model Light Bosons Decaying into Muon Pairs

    CERN Document Server

    CMS Collaboration

    2016-01-01

    A dataset corresponding to $2.8~\\mathrm{fb}^{-1}$ of proton-proton collisions at $\\sqrt{s} = 13~\\mathrm{TeV}$ was recorded by the CMS experiment at the CERN LHC. These data are used to search for new light bosons with a mass in the range $0.25-8.5~\\mathrm{GeV}/c^2$ decaying into muon pairs. No excess is observed in the data, and a model-independent upper limit on the product of the cross section, branching fraction and acceptance is derived. The results are interpreted in the context of two benchmark models, namely, the next-to-minimal supersymmetric standard model, and dark SUSY models including those predicting a non-negligible light boson lifetime.

  8. STUDI KOMPARATIF MODEL PEMBELAJARAN THINK PAIR SQUARE DAN THINK PAIR SHARE TERHADAP MOTIVASI DAN HASIL BELAJAR SISWA MAPEL TIK KELAS X SMA N 1 SUKASADA

    Directory of Open Access Journals (Sweden)

    Putu Deli Januartini

    2016-10-01

    Abstract The purpose of this study were to determine (1 the significant influence of the application of think pair square and think pair share learning model on student’s learning achievement, (2 better learning achievement between think pair square and think pair share learning model, (3 student’s motivation, (4 the student’s responses. The research was a quasi-experimental design experiment with post test only control group design. The population of study was all the students in grade X. The sample were as X1 class with the application of Think Pair Square learning model, X3 class with the application of Think Pair Share learning model, and X5 class with the application of Direct Instruction learning model. The data was collected by cognitive and psychomotor tests. The student’s learning achievement were analyzed by the prerequisite test with the results of the three groups at normal distribution and homogenous, and the hypothesis tested by One Way Anova which means there is a significant effect on the application of think pair square, think pair share, and direct instruction learning models. Then it was conducted a further test t-Scheffe with the results there are differences in the learning achievement between think pair square, think pair share, and direct instruction learning models. According to the average result we made a conclusion that Think Pair Square was better learning models with higher student’s learning achievement. The questionnaires results shows that Think Pair Square was very high positive response and very high learning motivation, Think Pair Share was high positive response and very high learning motivation.   Keywords :   Think Pair Square, Think Pair Share, Direct Instruction, learning achievement, learning motivation, and student response.

  9. Paired structures and other opposite-based models

    DEFF Research Database (Denmark)

    Rodríguez, J. Tinguaro; Franco, Camilo; Gómez, Daniel

    2015-01-01

    , that we will assume dependent on a specific negation, previously determined. In this way we can define a paired fuzzy set as a couple of opposite valuation fuzzy sets. Then we shall explore what kind of new valuation fuzzy sets can be generated from the semantic tension between those two poles, leading...... to a more complex valuation structure that still keeps the essence of being paired. In this way several neutral fuzzy sets can appear, in particular indeterminacy, ambivalence and conflict. Two consequences are then presented: on one hand, we will show how Atanassov´s Intuitionistic Fuzzy Sets can be viewed...

  10. PREDICTED PERCENTAGE DISSATISFIED (PPD) MODEL ...

    African Journals Online (AJOL)

    HOD

    their low power requirements, are relatively cheap and are environment friendly. ... PREDICTED PERCENTAGE DISSATISFIED MODEL EVALUATION OF EVAPORATIVE COOLING ... The performance of direct evaporative coolers is a.

  11. Exchange and spin-fluctuation superconducting pairing in the strong correlation limit of the Hubbard model

    International Nuclear Information System (INIS)

    Plakida, N. M.; Anton, L.; Adam, S. . Department of Theoretical Physics, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-76900 Bucharest - Magurele; RO); Adam, Gh. . Department of Theoretical Physics, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-76900 Bucharest - Magurele; RO)

    2001-01-01

    A microscopical theory of superconductivity in the two-band singlet-hole Hubbard model, in the strong coupling limit in a paramagnetic state, is developed. The model Hamiltonian is obtained by projecting the p-d model to an asymmetric Hubbard model with the lower Hubbard subband occupied by one-hole Cu d-like states and the upper Hubbard subband occupied by two-hole p-d singlet states. The model requires two microscopical parameters only, the p-d hybridization parameter t and the charge-transfer gap Δ. It was previously shown to secure an appropriate description of the normal state properties of the high -T c cuprates. To treat rigorously the strong correlations, the Hubbard operator technique within the projection method for the Green function is used. The Dyson equation is derived. In the molecular field approximation, d-wave superconducting pairing of conventional hole (electron) pairs in one Hubbard subband is found, which is mediated by the exchange interaction given by the interband hopping, J ij = 4 (t ij ) 2 / Δ. The normal and anomalous components of the self-energy matrix are calculated in the self-consistent Born approximation for the electron-spin-fluctuation scattering mediated by kinematic interaction of the second order of the intraband hopping. The derived numerical and analytical solutions predict the occurrence of singlet d x 2 -y 2 -wave pairing both in the d-hole and singlet Hubbard subbands. The gap functions and T c are calculated for different hole concentrations. The exchange interaction is shown to be the most important pairing interaction in the Hubbard model in the strong correlation limit, while the spin-fluctuation coupling results only in a moderate enhancement of T c . The smaller weight of the latter comes from two specific features: its vanishing inside the Brillouin zone (BZ) along the lines, |k x | + |k y |=π pointing towards the hot spots and the existence of a small energy shell within which the pairing is effective. By

  12. Paired structures in logical and semiotic models of natural language

    DEFF Research Database (Denmark)

    Rodríguez, J. Tinguaro; Franco, Camilo; Montero, Javier

    2014-01-01

    The evidence coming from cognitive psychology and linguistics shows that pairs of reference concepts (as e.g. good/bad, tall/short, nice/ugly, etc.) play a crucial role in the way we everyday use and understand natural languages in order to analyze reality and make decisions. Different situations...

  13. NMR and molecular modeling evidence for a G·A mismatch base pair in a purine-rich DNA duplex

    International Nuclear Information System (INIS)

    Li, Ying; Wilson, W.D.; Zon, G.

    1991-01-01

    1 H NMR experiments indicate that the oligomer 5'-d(ATGAGCGAATA) forms an unusual 10-base-pair duplex with 4 G·A base pairs and a 3' unpaired adenosine. NMR results indicate that guanoxine imino protons of the F·A mismatches are not hydrogen bonded but are stacked in the helix. A G→ I substitution in either G·A base pair causes a dramatic decrtease in duplex stability and indicates that hydrogen bonding of the guanosine amino group is critical. Nuclear Overhauser effect spectroscopy (NOESY) and two-dimensional correlated spectroscopy (COSY) results indicate that the overall duplex conformation is in the B-family. Cross-strand NOEs in two-dimensional NOESY spectra between a mismatched AH2 and an AH1' of the other mismatched base pair and between a mismatched GH8 and GNH1 of the other mismatch establish a purine-purine stacking pattern, adenosine over adenosine and guanosine over guanosine, which strongly stabilizes the duplex. A computer graphics molecular model of the ususual duplex was constructed with G·A base pairs containing A-NH 2 to GN3 and G-NH 2 to AN7 hydrogen bonds and B-form base pairs on both sides of the G·A pairs [5'-d(ATGAGC)]. The energy-minimized duplex satisfies all experimental constraints from NOESY and COSY results. A hydrogen bond from G-NH 2 of the mismatch to a phosphate oxygen is predicted

  14. Precise predictions for Higgs production in association with a W-boson pair at ILC

    International Nuclear Information System (INIS)

    Mao, Song; Wen-Gan, Ma; Ren-You, Zhang; Lei, Guo; Shao-Ming, Wang

    2009-01-01

    Higgs-boson production in association with a W-boson pair at e + e - linear colliders is one of the important processes in probing the coupling between the Higgs boson and vector gauge bosons and discovering the signature of new physics. We describe the impact of the complete electroweak (EW) radiative corrections of O(α ew ) to this process in the standard model (SM) at the International Linear Collider (ILC), and investigate the dependence of the lowest-order (LO) and EW next-to-leading order (NLO) corrected cross sections on the colliding energy √(s) and the Higgs-boson mass. The LO and NLO EW corrected distributions of the invariant mass of the W-boson pair and the transverse momenta of the final W-boson and Higgs boson are presented. Our numerical results show that the relative EW radiative correction (δ ew ) varies from -19.4% to 0.2% when m H =120 GeV and √(s) grows from 300 GeV to 1.2 TeV. (orig.)

  15. Chaos and order in models of black hole pairs

    International Nuclear Information System (INIS)

    Levin, Janna

    2006-01-01

    Chaos in the orbits of black hole pairs has by now been confirmed by several independent groups. While the chaotic behavior of binary black hole orbits is no longer argued, it remains difficult to quantify the importance of chaos to the evolutionary dynamics of a pair of comparable mass black holes. None of our existing approximations are robust enough to offer convincing quantitative conclusions in the most highly nonlinear regime. It is intriguing to note that, in three different approximations to a black hole pair built of a spinning black hole and a nonspinning companion, two approximations exhibit chaos and one approximation does not. The fully relativistic scenario of a spinning test mass around a Schwarzschild black hole shows chaos, as does the post-Newtonian Lagrangian approximation. However, the approximately equivalent post-Newtonian Hamiltonian approximation does not show chaos when only one body spins. It is well known in dynamical systems theory that one system can be regular while an approximately related system is chaotic, so there is no formal conflict. However, the physical question remains: Is there chaos for comparable mass binaries when only one object spins? We are unable to answer this question given the poor convergence of the post-Newtonian approximation to the fully relativistic system. A resolution awaits better approximations that can be trusted in the highly nonlinear regime

  16. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  17. The phase transition lines in pair approximation for the basic reinfection model SIRI

    International Nuclear Information System (INIS)

    Stollenwerk, Nico; Martins, Jose; Pinto, Alberto

    2007-01-01

    For a spatial stochastic epidemic model we investigate in the pair approximation scheme the differential equations for the moments. The basic reinfection model of susceptible-infected-recovered-reinfected or SIRI type is analysed, its phase transition lines calculated analytically in this pair approximation

  18. Predicting and Modeling RNA Architecture

    Science.gov (United States)

    Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

    2011-01-01

    SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

  19. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... signal based on a process model, coping with constraints on inputs and ... paper, we will present an introduction to the theory and application of MPC with Matlab codes ... section 5 presents the simulation results and section 6.

  20. Enhanced pairing susceptibility in a photodoped two-orbital Hubbard model

    Science.gov (United States)

    Werner, Philipp; Strand, Hugo U. R.; Hoshino, Shintaro; Murakami, Yuta; Eckstein, Martin

    2018-04-01

    Local spin fluctuations provide the glue for orbital-singlet spin-triplet pairing in the doped Mott insulating regime of multiorbital Hubbard models. At large Hubbard repulsion U , the pairing susceptibility is nevertheless tiny because the pairing interaction cannot overcome the suppression of charge fluctuations. Using nonequilibrium dynamical mean field simulations of the two-orbital Hubbard model, we show that out of equilibrium the pairing susceptibility in this large-U regime can be strongly enhanced by creating a photoinduced population of the relevant charge states. This enhancement is supported by the long lifetime of photodoped charge carriers and a built-in cooling mechanism in multiorbital Hubbard systems.

  1. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

    Science.gov (United States)

    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

  2. Model-free information-theoretic approach to infer leadership in pairs of zebrafish.

    Science.gov (United States)

    Butail, Sachit; Mwaffo, Violet; Porfiri, Maurizio

    2016-04-01

    Collective behavior affords several advantages to fish in avoiding predators, foraging, mating, and swimming. Although fish schools have been traditionally considered egalitarian superorganisms, a number of empirical observations suggest the emergence of leadership in gregarious groups. Detecting and classifying leader-follower relationships is central to elucidate the behavioral and physiological causes of leadership and understand its consequences. Here, we demonstrate an information-theoretic approach to infer leadership from positional data of fish swimming. In this framework, we measure social interactions between fish pairs through the mathematical construct of transfer entropy, which quantifies the predictive power of a time series to anticipate another, possibly coupled, time series. We focus on the zebrafish model organism, which is rapidly emerging as a species of choice in preclinical research for its genetic similarity to humans and reduced neurobiological complexity with respect to mammals. To overcome experimental confounds and generate test data sets on which we can thoroughly assess our approach, we adapt and calibrate a data-driven stochastic model of zebrafish motion for the simulation of a coupled dynamical system of zebrafish pairs. In this synthetic data set, the extent and direction of the coupling between the fish are systematically varied across a wide parameter range to demonstrate the accuracy and reliability of transfer entropy in inferring leadership. Our approach is expected to aid in the analysis of collective behavior, providing a data-driven perspective to understand social interactions.

  3. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Sweat loss prediction using a multi-model approach.

    Science.gov (United States)

    Xu, Xiaojiang; Santee, William R

    2011-07-01

    A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.

  5. Modelling bankruptcy prediction models in Slovak companies

    Directory of Open Access Journals (Sweden)

    Kovacova Maria

    2017-01-01

    Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

  6. Predictive models of moth development

    Science.gov (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  7. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  8. Predictive Modeling in Race Walking

    Directory of Open Access Journals (Sweden)

    Krzysztof Wiktorowicz

    2015-01-01

    Full Text Available This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers’ training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 122 training plans for 21 athletes. In order to choose the best model leave-one-out cross-validation method is used. The main contribution of the paper is to propose the nonlinear modifications for linear models in order to achieve smaller prediction error. It is shown that the best model is a modified LASSO regression with quadratic terms in the nonlinear part. This model has the smallest prediction error and simplified structure by eliminating some of the predictors.

  9. Predicting the Mechanism and Kinetics of the Watson-Crick to Hoogsteen Base Pairing Transition

    NARCIS (Netherlands)

    Vreede, J.; Bolhuis, P.G.; Swenson, D.W.H.

    2016-01-01

    DNA duplexes predominantly contain Watson-Crick (WC) base pairs. Yet, a non-negligible number of base pairs converts to the Hoogsteen (HG) hydrogen bonding pattern, involving a 180° rotation of the purine base relative to Watson-Crick. These WC to HG conversions alter the conformation of DNA, and

  10. PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast.

    Science.gov (United States)

    Lai, Fu-Jou; Chang, Hong-Tsun; Wu, Wei-Sheng

    2015-01-01

    Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Allowing users to select eight existing performance indices and 15

  11. A simple, analytical model of collisionless magnetic reconnection in a pair plasma

    International Nuclear Information System (INIS)

    Hesse, Michael; Zenitani, Seiji; Kuznetsova, Masha; Klimas, Alex

    2009-01-01

    A set of conservation equations is utilized to derive balance equations in the reconnection diffusion region of a symmetric pair plasma. The reconnection electric field is assumed to have the function to maintain the current density in the diffusion region and to impart thermal energy to the plasma by means of quasiviscous dissipation. Using these assumptions it is possible to derive a simple set of equations for diffusion region parameters in dependence on inflow conditions and on plasma compressibility. These equations are solved by means of a simple, iterative procedure. The solutions show expected features such as dominance of enthalpy flux in the reconnection outflow, as well as combination of adiabatic and quasiviscous heating. Furthermore, the model predicts a maximum reconnection electric field of E * =0.4, normalized to the parameters at the inflow edge of the diffusion region.

  12. A Simple, Analytical Model of Collisionless Magnetic Reconnection in a Pair Plasma

    Science.gov (United States)

    Hesse, Michael; Zenitani, Seiji; Kuznetova, Masha; Klimas, Alex

    2011-01-01

    A set of conservation equations is utilized to derive balance equations in the reconnection diffusion region of a symmetric pair plasma. The reconnection electric field is assumed to have the function to maintain the current density in the diffusion region, and to impart thermal energy to the plasma by means of quasi-viscous dissipation. Using these assumptions it is possible to derive a simple set of equations for diffusion region parameters in dependence on inflow conditions and on plasma compressibility. These equations are solved by means of a simple, iterative, procedure. The solutions show expected features such as dominance of enthalpy flux in the reconnection outflow, as well as combination of adiabatic and quasi-viscous heating. Furthermore, the model predicts a maximum reconnection electric field of E(sup *)=0.4, normalized to the parameters at the inflow edge of the diffusion region.

  13. A number-projected model with generalized pairing interaction in application to rotating nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Satula, W. [Warsaw Univ. (Poland)]|[Joint Institute for Heavy Ion Research, Oak Ridge, TN (United States)]|[Univ. of Tennessee, Knoxville, TN (United States)]|[Royal Institute of Technology, Stockholm (Sweden); Wyss, R. [Royal Institute of Technology, Stockholm (Sweden)

    1996-12-31

    A cranked mean-field model that takes into account both T=1 and T=0 pairing interactions is presented. The like-particle pairing interaction is described by means of a standard seniority force. The neutron-proton channel includes simultaneously correlations among particles moving in time reversed orbits (T=1) and identical orbits (T=0). The coupling between different pairing channels and nuclear rotation is taken into account selfconsistently. Approximate number-projection is included by means of the Lipkin-Nogami method. The transitions between different pairing phases are discussed as a function of neutron/proton excess, T{sub z}, and rotational frequency, {Dirac_h}{omega}.

  14. A pure Hubbard model with demonstrable pairing adjacent to the Mott-insulating phase

    International Nuclear Information System (INIS)

    Champion, J D; Long, M W

    2003-01-01

    We introduce a Hubbard model on a particular class of geometries, and consider the effect of doping the highly spin-degenerate Mott-insulating state with a microscopic number of holes in the extreme strong-coupling limit. The geometry is quite general, with pairs of atomic sites at each superlattice vertex, and a highly frustrated inter-atomic connectivity: the one-dimensional realization is a chain of edge-sharing tetrahedra. The sole model parameter is the ratio of intra-pair to inter-pair hopping matrix elements. If the intra-pair hopping is negligible then introducing a microscopic number of holes results in a ferromagnetic Nagaoka groundstate. Conversely, if the intra-pair hopping is comparable with the inter-pair hopping then the groundstate is low spin with short-ranged spin correlations. We exactly solve the correlated motion of a pair of holes in such a state and find that, in 1d and 2d, they form a bound pair on a length scale that increases with diminishing binding energy. This result is pertinent to the long-standing problem of hole motion in the CuO 2 planes of the high-temperature superconductors: we have rigorously shown that, on our frustrated geometry, the holes pair up and a short-ranged low-spin state is generated by hole motion alone

  15. The rotationally induced quadrupole pair field in the particle-rotor model

    International Nuclear Information System (INIS)

    Almberger, J.

    1980-04-01

    A formalism is developed which makes it possible to consider the influence of the rotationally induced quadrupole pair field and corresponding quasi-particle residual interactions within the particle-rotor model. The Y 21 pair field renormalizes both the Coriolis and the recoil interactions. (Auth.)

  16. A Novel Clustering Model Based on Set Pair Analysis for the Energy Consumption Forecast in China

    Directory of Open Access Journals (Sweden)

    Mingwu Wang

    2014-01-01

    Full Text Available The energy consumption forecast is important for the decision-making of national economic and energy policies. But it is a complex and uncertainty system problem affected by the outer environment and various uncertainty factors. Herein, a novel clustering model based on set pair analysis (SPA was introduced to analyze and predict energy consumption. The annual dynamic relative indicator (DRI of historical energy consumption was adopted to conduct a cluster analysis with Fisher’s optimal partition method. Combined with indicator weights, group centroids of DRIs for influence factors were transferred into aggregating connection numbers in order to interpret uncertainty by identity-discrepancy-contrary (IDC analysis. Moreover, a forecasting model based on similarity to group centroid was discussed to forecast energy consumption of a certain year on the basis of measured values of influence factors. Finally, a case study predicting China’s future energy consumption as well as comparison with the grey method was conducted to confirm the reliability and validity of the model. The results indicate that the method presented here is more feasible and easier to use and can interpret certainty and uncertainty of development speed of energy consumption and influence factors as a whole.

  17. Deformed model Sp(4) model for studying pairing correlations in atomic nuclei

    CERN Document Server

    Georgieva, A I; Sviratcheva, K

    2002-01-01

    A fermion representation of the compact symplectic sp(4) algebra introduces a theoretical framework for describing pairing correlations in atomic nuclei. The important non-deformed and deformed subalgebras of sp sub ( sub q sub ) (4) and the corresponding reduction chains are explored for the multiple orbit problem. One realization of the u sub ( sub q sub ) (2) subalgebra is associated with the valence isospin, other reductions describe coupling between identical nucleons or proton-neutron pairs. Microscopic non-deformed and deformed Hamiltonians are expressed in terms of the generators of the sp(4) and sp sub q (4) algebras. In both cases eigenvalues of the isospin breaking Hamiltonian are fit to experimental ground state energies. The theory can be used to investigate the origin of the deformation and predict binding energies of nuclei in proton-rich regions. The q-deformation parameter changes the pairing strength and in so doing introduces a non-linear coupling into the collective degree of freedom

  18. Paired fuzzy sets and other opposite-based models

    DEFF Research Database (Denmark)

    Montero, Javier; Gómez, Daniel; Tinguaro Rodríguez, J.

    2016-01-01

    In this paper we stress the relevance of those fuzzy models that impose a couple of simultaneous views in order to represent concepts. In particular, we point out that the basic model to start with should contain at least two somehow opposite valuations plus a number of neutral concepts that are ...

  19. PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE PAIR CHECKS PEMECAHAN MASALAH UNTUK MENINGKATKAN SOCIAL SKILL SISWA

    OpenAIRE

    R. Lestari; S. Linuwih

    2012-01-01

    Tujuan penelitian tindakan kelas ini untuk mengetahui pengaruh proses pembelajaran dengan menggunakan model pembelajaran kooperatif tipe Pair Checks pemecahan masalah terhadap peningkatan social skill siswa. Pada proses penerapan model pembelajaran kooperatif tipe Pair Checks pemecahan masalah siswa dibagi dalam kelompok-kelompok dan satu kelompok terdiri dari dua orang. Setiap kelompok berdiskusi untuk menyelesaikan suatu masalah, kemudian hasil diskusi kelompok akan dicek oleh pasangan dari...

  20. 3D Reflection Map Modeling for Optical Emitter-receiver Pairs

    DEFF Research Database (Denmark)

    Christensen, Henrik Vie

    2004-01-01

    A model for a model-based 3D-position determination system for a passive object is presented. Infrared emitter/receiver pairs are proposed as sensing part to acquire information on a ball shaped object's position. A 3D reflection map model is derived trough geometrical considerations. The model...

  1. CONSIDERATIONS UPON CONTACT STRESS MODELLING IN DENTAL ARTICULATOR PAIRS

    Directory of Open Access Journals (Sweden)

    Carmen Ciornei

    2012-05-01

    Full Text Available A dental articulator is a mechanism which simulates the temporo-mandibular joint. The articulator is essential as it replicates the basic motions of the upper and lower mandibles, both revolve and translational motions. In the present paper the stresses from an articulator TMJ modelled as a bronze sphere into a cylindrical steel cavity are analyzed by two methods, first applying the Hertzian contact theory and then numerically, by means of finite element analysis using the simulation module in CATIA.

  2. Gamma-Ray Pulsars Models and Predictions

    CERN Document Server

    Harding, A K

    2001-01-01

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...

  3. Modeling the Electrostatics of Hollow Shell Suspensions: Ion Distribution, Pair Interactions, and Many-Body Effects.

    Science.gov (United States)

    Hallez, Yannick; Meireles, Martine

    2016-10-11

    Electrostatic interactions play a key role in hollow shell suspensions as they determine their structure, stability, thermodynamics, and rheology and also the loading capacity of small charged species for nanoreservoir applications. In this work, fast, reliable modeling strategies aimed at predicting the electrostatics of hollow shells for one, two, and many colloids are proposed and validated. The electrostatic potential inside and outside a hollow shell with a finite thickness and a specific permittivity is determined analytically in the Debye-Hückel (DH) limit. An expression for the interaction potential between two such hollow shells is then derived and validated numerically. It follows a classical Yukawa form with an effective charge depending on the shell geometry, permittivity, and inner and outer surface charge densities. The predictions of the Ornstein-Zernike (OZ) equation with this pair potential to determine equations of state are then evaluated by comparison to results obtained with a Brownian dynamics algorithm coupled to the resolution of the linearized Poisson-Boltzmann and Laplace equations (PB-BD simulations). The OZ equation based on the DLVO-like potential performs very well in the dilute regime as expected, but also quite well, and more surprisingly, in the concentrated regime in which full spheres exhibit significant many-body effects. These effects are shown to vanish for shells with small thickness and high permittivity. For highly charged hollow shells, we propose and validate a charge renormalization procedure. Finally, using PB-BD simulations, we show that the cell model predicts the ion distribution inside and outside hollow shells accurately in both electrostatically dilute and concentrated suspensions. We then determine the shell loading capacity as a function of salt concentration, volume fraction, and surface charge density for nanoreservoir applications such as drug delivery, sensing, or smart coatings.

  4. Superconducting properties of the η-pairing state in the Penson-Kolb-Hubbard model

    International Nuclear Information System (INIS)

    Czart, W.R.; Robaszkiewicz, S.

    2004-01-01

    The Penson-Kolb-Hubbard model, i.e. the Hubbard model with the pair-hopping interaction J is studied. We focus on the properties of the superconducting state with the Cooper-pair center-of mass momentum q Q(η-phase). The transition into the η-phase, which is favorized by the repulsive J (J c |, dependent on band filling, on-site interaction U and band structure, and the system never exhibits standard BCS-like features. This is in obvious contrast with the properties of the isotropic s-wave state, stabilized by the attractive J and attractive U, which exhibit at T = 0 a smooth crossover from the BCS-like limit to that of tightly bound pairs with increasing pairing strength. (author)

  5. Quantum entanglement and phase transition in a two-dimensional photon-photon pair model

    International Nuclear Information System (INIS)

    Zhang Jianjun; Yuan Jianhui; Zhang Junpei; Cheng Ze

    2013-01-01

    We propose a two-dimensional model consisting of photons and photon pairs. In the model, the mixed gas of photons and photon pairs is formally equivalent to a two-dimensional system of massive bosons with non-vanishing chemical potential, which implies the existence of two possible condensate phases. Using the variational method, we discuss the quantum phase transition of the mixed gas and obtain the critical coupling line analytically. Moreover, we also find that the phase transition of the photon gas can be interpreted as enhanced second harmonic generation. We then discuss the entanglement between photons and photon pairs. Additionally, we also illustrate how the entanglement between photons and photon pairs can be associated with the phase transition of the system.

  6. The broken-pair model for nuclei and its extension with quadrupole vibrations

    International Nuclear Information System (INIS)

    Hofstra, P.

    1979-01-01

    The author presents calculations for low energy properties of nuclei with an odd number of particles. These are described in the Broken-Pair approximation, where it is assumed that all but three particles occur as ordered Cooper pairs; the unpaired (one or three) particles are called quasiparticles. A model is developed with which it is hoped to describe odd nuclei with two open shells in terms of both single-particle and collective degrees of freedom. (Auth.)

  7. BAYESIAN ANALYSIS FOR THE PAIRED COMPARISON MODEL WITH ORDER EFFECTS (USING NON-INFORMATIVE PRIORS

    Directory of Open Access Journals (Sweden)

    Ghausia Masood Gilani

    2008-07-01

    Full Text Available Sometimes it may be difficult for a panelist to rank or compare more than two objects or treatments at the same time. For this reason, paired comparison method is used. In this study, the Davidson and Beaver (1977 model for paired comparisons with order effects is analyzed through the Bayesian Approach. For this purpose, the posterior means and the posterior modes are compared using the noninformative priors.

  8. Joint Testlet Cognitive Diagnosis Modeling for Paired Local Item Dependence in Response Times and Response Accuracy

    Directory of Open Access Journals (Sweden)

    Peida Zhan

    2018-04-01

    Full Text Available In joint models for item response times (RTs and response accuracy (RA, local item dependence is composed of local RA dependence and local RT dependence. The two components are usually caused by the same common stimulus and emerge as pairs. Thus, the violation of local item independence in the joint models is called paired local item dependence. To address the issue of paired local item dependence while applying the joint cognitive diagnosis models (CDMs, this study proposed a joint testlet cognitive diagnosis modeling approach. The proposed approach is an extension of Zhan et al. (2017 and it incorporates two types of random testlet effect parameters (one for RA and the other for RTs to account for paired local item dependence. The model parameters were estimated using the full Bayesian Markov chain Monte Carlo (MCMC method. The 2015 PISA computer-based mathematics data were analyzed to demonstrate the application of the proposed model. Further, a brief simulation study was conducted to demonstrate the acceptable parameter recovery and the consequence of ignoring paired local item dependence.

  9. Virialization in N-body models of the expanding universe. I. Isolated pairs

    International Nuclear Information System (INIS)

    Evrard, A.E.; Yahil, A.; and Institute of Astronomy, University of Cambridge)

    1985-01-01

    The degree of virialization of isolated pairs of galaxies is investigated in the N-body simulations of Efstathiou and Eastwood for open (Ω 0 = 0.1) and critical (Ω 0 = 1.0) universes, utilizing the three-dimensional information available for both position and velocity. Roughly half of the particles in the models form isolated pairs whose dynamics is dominated by their own two-body force. Three-quarters or more of these pairs are bound, and this ensemble of bound isolated pairs is found to yield excellent mass estimates upon application of the virial theorem. Contamination from unbound pairs introduces error factors smaller than 2 in mass estimates, and these errors can be corrected by simple methods. Oribts of bound pairs are highly eccentric, but this does not lead to serious selection effects in orbital phases, since these are uniformly distributed. The relative velocity of these pairs of mass points shows a Keplerian falloff with separation, contrary to observational evidence for real galaxies. All the above results are independent of the value of Ω 0 , but may be sensitive to initial conditions and the point-mass nature of the particles

  10. Detection of no-model input-output pairs in closed-loop systems.

    Science.gov (United States)

    Potts, Alain Segundo; Alvarado, Christiam Segundo Morales; Garcia, Claudio

    2017-11-01

    The detection of no-model input-output (IO) pairs is important because it can speed up the multivariable system identification process, since all the pairs with null transfer functions are previously discarded and it can also improve the identified model quality, thus improving the performance of model based controllers. In the available literature, the methods focus just on the open-loop case, since in this case there is not the effect of the controller forcing the main diagonal in the transfer matrix to one and all the other terms to zero. In this paper, a modification of a previous method able to detect no-model IO pairs in open-loop systems is presented, but adapted to perform this duty in closed-loop systems. Tests are performed by using the traditional methods and the proposed one to show its effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  11. About long range pairing correlations in the Hubbard U-t-t' models

    International Nuclear Information System (INIS)

    Moreo, A.

    1991-01-01

    Using a quantum Monte Carlo method the authors measured pair correlation functions with different symmetries as a function of the filling, U/t and t'/t for the Hubbard and U-t-t' models. For the first time the Monte Carlo results are presented for U/t larger than the bandwidth 8t, away from half-filling. D-wave and extended S-wave pairing correlations are enhanced. D-wave pairing is stronger at half-filling but this behavior is reversed when the filling decreases. However, none of the eight pairing correlations that were studied increases as a function of lattice size, which makes the existence of long range superconducting order unlikely. (author). 10 refs.; 5 figs

  12. Pairing and superconductivity from weak to strong coupling in the attractive Hubbard model

    International Nuclear Information System (INIS)

    Toschi, A; Barone, P; Capone, M; Castellani, C

    2005-01-01

    The finite-temperature phase diagram of the attractive Hubbard model is studied by means of the dynamical mean-field theory. We first consider the normal phase of the model by explicitly frustrating the superconducting ordering. In this case, we obtain a first-order pairing transition between a metallic phase and a paired phase formed by strongly coupled incoherent pairs. The transition line ends in a finite temperature critical point, but a crossover between two qualitatively different solutions still occurs at higher temperature. Comparing the superconducting- and the normal-phase solutions, we find that the superconducting instability always occurs before the pairing transition in the normal phase, i.e. T c > T pairing . Nevertheless, the high-temperature phase diagram at T > T c is still characterized by a crossover from a metallic phase to a preformed pair phase. We characterize this crossover by computing different observables that can be used to identify the pseudogap region, like the spin susceptibility, the specific heat and the single-particle spectral function

  13. Modeling top quark pair production in the search of new, heavy resonance that decays into a pair of Higgs bosons

    CERN Document Server

    Liyanage, Kalpanie Madara

    2017-01-01

    The Higgs boson pair production process at the LHC provides an opportunity for performing a study of the trilinear Higgs boson self-coupling. We consider Higgs boson pair production in the bbWW*channel, with subsequent decay of the WW* pair into lνqq. Due to irreducible top quark backgrounds and the associated uncertainties, this is a challenging final state to explore. We apply appropriate selection cuts on suitable kinematic variables in order to obtain a signal-enriched region. Using several different Monte Carlo (MC) samples the top quark background process is then studied in this region of interest. We find that depending on the phase space, different MC samples lead to kinematic differences.

  14. Analysis of errors in spectral reconstruction with a Laplace transform pair model

    International Nuclear Information System (INIS)

    Archer, B.R.; Bushong, S.C.

    1985-01-01

    The sensitivity of a Laplace transform pair model for spectral reconstruction to random errors in attenuation measurements of diagnostic x-ray units has been investigated. No spectral deformation or significant alteration resulted from the simulated attenuation errors. It is concluded that the range of spectral uncertainties to be expected from the application of this model is acceptable for most scientific applications. (author)

  15. Exact solution of the p + ip pairing Hamiltonian and a hierarchy of integrable models

    International Nuclear Information System (INIS)

    Dunning, Clare; Ibañez, Miguel; Sierra, Germán; Links, Jon; Zhao, Shao-You

    2010-01-01

    Using the well-known trigonometric six-vertex solution of the Yang–Baxter equation we derive an integrable pairing Hamiltonian with anyonic degrees of freedom. The exact algebraic Bethe ansatz solution is obtained using standard techniques. From this model we obtain several limiting models, including the pairing Hamiltonian with p + ip-wave symmetry. An in-depth study of the p + ip model is then undertaken, including a mean-field analysis, analytical and numerical solutions of the Bethe ansatz equations and an investigation of the topological properties of the ground-state wavefunction. Our main result is that the ground-state phase diagram of the p + ip model consists of three phases. There is the known boundary line with gapless excitations that occurs for vanishing chemical potential, separating the topologically trivial strong pairing phase and the topologically non-trivial weak pairing phase. We argue that a second boundary line exists separating the weak pairing phase from a topologically trivial weak coupling BCS phase, which includes the Fermi sea in the limit of zero coupling. The ground state on this second boundary line is the Moore–Read state

  16. Innovation of Methods for Measurement and Modelling of Twisted Pair Parameters

    Directory of Open Access Journals (Sweden)

    Lukas Cepa

    2011-01-01

    Full Text Available The goal of this paper is to optimize a measurement methodology for the most accurate broadband modelling of characteristic impedance and other parameters for twisted pairs. Measured values and theirs comparison is presented in this article. Automated measurement facility was implemented at the Department of telecommunication of Faculty of electrical engineering of Czech technical university in Prague. Measurement facility contains RF switches allowing measurements up to 300 MHz or 1GHz. Measured twisted pair’s parameters can be obtained by measurement but for purposes of fundamental characteristics modelling is useful to define functions that model the properties of the twisted pair. Its primary and secondary parameters depend mostly on the frequency. For twisted pair deployment, we are interested in a frequency band range from 1 MHz to 100 MHz.

  17. A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

    Directory of Open Access Journals (Sweden)

    Mao Yu

    2009-07-01

    Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From

  18. Respon Belajar Penerapan Model Contextual Teaching And Learning Dibandingkan Dengan Think Pair Share Pada Siswa

    Directory of Open Access Journals (Sweden)

    Atan Pramana

    2017-10-01

    Full Text Available Penelitian ini dilaksanakan dengan tujuan untuk mengetahui sebagai berikutrespon belajar karena penerapan model Contextual Teaching And Learning dibandingkan dengan Think Pair Share terhadap hasil belajar perawatan PC siswa kelas X TKJ. Penelitian ini merupakan penelitian eksperimen semu (quasi eksperimen. Populasi penelitian ini adalah seluruh siswa kelas X SMK Negeri 3 Malang. Sampel ditentukan kelas X TKJ 3 dengan perlakuan model Contextual Teaching And Learning dan kelas X TKJ 1 dengan perlakuan model pembelajaran Think Pair Share. Instrumen pengukuran hasil belajar meliputi penilaian test, rubrik afektif, dan rubrik psikomotor yang sebelumnya dilakukan uji validasi instrumen. Teknik analisis data menggunakan uji-t berbantuan SPSS 20 yang digunakan untuk mengetahui respon belajar terhadap hasil belajar yaitu regresi linear sederhana untuk mengetahui besar sumbangan. Berdasarkan hasil penelitian dan analisis data yang dilakukan. Terdapat sumbangan respon belajar penerapan model pembelajaran Contextual Teaching and Learning sebesar 71,5%, sedangkan sumbangan respon belajar penerapan model pembelajaran Think Pair Share sebesar 67,8%. Dari besarnya persentase diketahui bahwa respon belajar siswa terhadap penerapan model Contextual Teaching And Learning lebih tinggi dari pada respon belajar siswa terhadap penerapan model pembelajaran Think Pair Share.

  19. Prediction of citrullination sites by incorporating k-spaced amino acid pairs into Chou's general pseudo amino acid composition.

    Science.gov (United States)

    Ju, Zhe; Wang, Shi-Yun

    2018-04-22

    As one of the most important and common protein post-translational modifications, citrullination plays a key role in regulating various biological processes and is associated with several human diseases. The accurate identification of citrullination sites is crucial for elucidating the underlying molecular mechanisms of citrullination and designing drugs for related human diseases. In this study, a novel bioinformatics tool named CKSAAP_CitrSite is developed for the prediction of citrullination sites. With the assistance of support vector machine algorithm, the highlight of CKSAAP_CitrSite is to adopt the composition of k-spaced amino acid pairs surrounding a query site as input. As illustrated by 10-fold cross-validation, CKSAAP_CitrSite achieves a satisfactory performance with a Sensitivity of 77.59%, a Specificity of 95.26%, an Accuracy of 89.37% and a Matthew's correlation coefficient of 0.7566, which is much better than those of the existing prediction method. Feature analysis shows that the N-terminal space containing pairs may play an important role in the prediction of citrullination sites, and the arginines close to N-terminus tend to be citrullinated. The conclusions derived from this study could offer useful information for elucidating the molecular mechanisms of citrullination and related experimental validations. A user-friendly web-server for CKSAAP_CitrSite is available at 123.206.31.171/CKSAAP_CitrSite/. Copyright © 2017. Published by Elsevier B.V.

  20. PENGARUH PENGGUNAAN ALAT PERAGA BERBASIS KONSEP GEOMETRI PADA MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SHARE

    Directory of Open Access Journals (Sweden)

    Sulaiman Sulaiman

    2015-10-01

    Full Text Available Abstract The research is experimental research. This study aims to determine the difference in average mathematics students learning outcomes between learning with and without the use of props Pythagoras on cooperative learning model Think Pair Share (TPS. The population was all the students in second grade of SMP Negeri 1 Sukoharjo in the academic year 2014-2015. The samples of the research were taken by using the cluster random sampling technique.Data analysis is using chi-square test andstatistical t-test. Based onthe results ofhypothesis test obtained that there is difference in the averageresult of learningmathematicsbetween experimental classandcontrol class and the averageresults oflearning mathematicsin experimental class is higherthan in control class. Thus,the averageresult of learningthatlearningto usepropsPythagorasoncooperative learning modelThink Pair Share (TPSis higherthanlearningwithout the use ofpropsPythagoras. Keywords:Props, Phytagoras, Think Pair Share

  1. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  2. PENERAPAN MODEL THINK-PAIR-SHARE UNTUK MENINGKATKAN KETERAMPILAN MENULIS KELAS II SDN 3 BANJAR JAWA

    Directory of Open Access Journals (Sweden)

    Ningsi Soisana Lakilaf

    2017-12-01

    Full Text Available Penelitian ini bertujuan untuk meningkatkan keterampilan menulis siswa  setelah penerapan model pembelajaran Think-Pear-Share bermediakan gambar pada siswa kelas II Semester I di SD Negeri 3 Banjar Jawa, Tahun Pelajaran 2017/2018.Pelaksanaan penelitian ini menggunakan penelitian tindakan kelas (PTK yang dilaksanakan dalam 2 silklus,  setiap siklus  terdiri dari 2 pertemua, dengan tahapan yang terdiri dari (1 perencanaan, (2 pelaksanaan, (3 pengamatan, dan (4 refleksi. Subjek penelitian ini adalah guru dan siswa kelas II SD Negeri 3 Banjar Jawa  dalam penelitian ini adalah teknik tes dan nontes.Hasil penelitian ini menunjukan bahwa dengan menggunakan model pembelajaran Think-Pair-Share bermedia gamabar diketahui bahwa ketuntasan hasil belajar siswa mengalami peningkatan dalam pembelajaran dengan hasil presentasi mendeskripsikan secara tertulis sebelum pelaksanaan tindakan 27%, siklus I 77% dan Siklus II 90 %. Pembelajaran dengan menerapkan model Think-Pair-Share bermedia gambar dapat meningkatkan keterampilan menulis. Kesimpulan dari penelitian ini adalah melalui penerapan model Think- Pair-Share bermedia gambar dapat meningkatkan keterampilan  menulis siswa kelas II SD Negeri 3 Banjar Jawa,. Saran yang dapat diberikan adalah sebaiknya guru lebih aktif dan kreatif dalam melaksanakan pembelajaran yang inovatif dan menyenangkan.   Kata Kunci : Keterampilan menulis, model Think-Pair-Share

  3. Erratum: A Simple, Analytical Model of Collisionless Magnetic Reconnection in a Pair Plasma

    Science.gov (United States)

    Hesse, Michael; Zenitani, Seiji; Kuznetsova, Masha; Klimas, Alex

    2011-01-01

    The following describes a list of errata in our paper, "A simple, analytical model of collisionless magnetic reconnection in a pair plasma." It supersedes an earlier erratum. We recently discovered an error in the derivation of the outflow-to-inflow density ratio.

  4. Treatment of the pairing force by cranked HFB. A model of back-bending

    Energy Technology Data Exchange (ETDEWEB)

    Sorensen, R A [Carnegie-Mellon Univ., Pittsburgh, Pa. (USA)

    1976-10-05

    The degenerate pairing force model, with a one-body angular momentum operator defined, is treated with the cranked HFB formalism. It is shown in detail that this treatment is accurate for all properties of states near the yrast line to order of the reciprocal of the degeneracy factor. The relevance to back-bending nuclear high-spin states is discussed.

  5. A model for the study of electrostatic binding between a pair of ...

    African Journals Online (AJOL)

    A model for the study of electrostatic binding between a pair of molecules at large distances. A Umar, G Hussin. Abstract. No Abstract. Nigerian Journal of Chemical Research Vol 5 2000: 1-9. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT.

  6. Shell-model calculations with a basis that contains correlated pairs

    International Nuclear Information System (INIS)

    Boisson, J.P.; Silvestre-Brac, B.A.; Liotta, R.J.

    1979-01-01

    A method to solve the shell-model equations within a basis that contains correlated pairs of particles is presented. The method is illustrated for the three-identical-particle system. Applications in nuclei around 208 Pb are given and comparisons with both experimental data and other calculations are carried out. (Auth.)

  7. Higgs pair production in the CP-violating two-Higgs-doublet model

    Science.gov (United States)

    Bian, Ligong; Chen, Ning; Jiang, Yun

    2017-12-01

    The SM-like Higgs pair production is discussed in the framework of the general CP-violating two-Higgs-doublet model, where we find that the CP-violating mixing angles can be related to the Higgs self-couplings. Therefore, the future experimental searches for Higgs boson pairs can be constrained by the improved precision of the electric dipole moment measurements. Based on a series of constraints of the SM-like Higgs boson signal fits, the perturbative unitarity and stability bounds to the Higgs potential, and the most recent LHC searches for heavy Higgs bosons, we suggest a set of benchmark models for the future high-energy collider searches for Higgs pair production. The e+e- colliders operating at s = (500GeV,1 TeV) are capable of measuring the Higgs cubic self-couplings of the benchmark models directly. We also estimate the cross sections of the resonance contributions to the Higgs pair productions for the benchmark models at the future LHC and SppC/FCC-hh runs.

  8. PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE PAIR CHECKS PEMECAHAN MASALAH UNTUK MENINGKATKAN SOCIAL SKILL SISWA

    Directory of Open Access Journals (Sweden)

    R. Lestari

    2012-07-01

    Full Text Available Tujuan penelitian tindakan kelas ini untuk mengetahui pengaruh proses pembelajaran dengan menggunakan model pembelajaran kooperatif tipe Pair Checks pemecahan masalah terhadap peningkatan social skill siswa. Pada proses penerapan model pembelajaran kooperatif tipe Pair Checks pemecahan masalah siswa dibagi dalam kelompok-kelompok dan satu kelompok terdiri dari dua orang. Setiap kelompok berdiskusi untuk menyelesaikan suatu masalah, kemudian hasil diskusi kelompok akan dicek oleh pasangan dari kelompok lain. Metode Penelitian yang digunakan adalah penelitian tindakan kelas yang dilaksanakan dua siklus. Metode pengumpulan data menggunakan tes dan angket skala sikap, sedangkan teknik analisis data menggunakan teknik analisis data kuantitatif. Social Skill siswa dari siklus I ke siklus II mengalami peningkatan. Hal ini didapatkan dari data angket skala sikap siklus I ke siklus II ketuntasan klasikalnya meningkat dan sebagian besar siswa sudah memiliki social skill yang baik. Hasil belajar kognitif siswa juga mengalami peningkatan. Model pembelajaran kooperatif tipe Pair Checks pemecahan masalah dapat meningkatkan social skill siswa.This two cycles-action research aimed to know learning process applying cooperative learning model-pair checks problem solving type and improvement of student’s social skills. The process of the model was as follows: deviding students into some groups consisting of two students, solving problem by each group and checking result of the discussion by other groups. Data collection method used was test and the use of attitude scale questionnaire, while technique of data analysis used was quantitative data analysis technique. The data analysis result showed that there was an increase of student’s social skill and students’ achievement from cycle one to two. It is concluded that cooperative learning model-pair checks problem solving type can enhance student’s social skills

  9. TDA's validity to study 18O collectivity in terms of collective pair model

    International Nuclear Information System (INIS)

    Gao Yuanyi; Vitturi, A.; Catara, F.; Sambataro, M.

    1991-01-01

    Conclusion proved that if the authors calculate 18 O collective spectra in terms of the Collective Pair Model, the authors can get the positive low laying levels of 18 O which are of the particle particle pair, independent on the excitation of hole within closed shell. 1 - low laying levels are of non-collective 3 particle 1 hole states. 1 - fourth level is of collective 3 particle 1 hole states. 3 - low laying levels are of collective 3 particle 1 hole states. 1 - , 3 - low laying levels agree very well with the experiment data. Hence the TDA is sufficient for the calculations of 1 - ,3 - collective low levels of 18 O

  10. J/ψ→γB anti B decays and the quark-pair creation model

    International Nuclear Information System (INIS)

    Ping Ronggang; Jiang Huanqing; Shen Pengnian; Zou Bingsong

    2002-01-01

    The authors generalize the quark-pair creation model to a study of the radiative decays J/ψ→γB anti B by assuming that the u, d or s quark pairs are created with the same interaction strength. From the calculation of the ratio of the decay widths Γ(J/ψ→γp anti B)/Γ(J/ψ→p anti p), the authors extract the quark-pair creation strength gI=15.40 GeV. Based on the SU(6) spin-flavour basis and the 'uds' basis, the radiative decay branching ratios containing strange baryons are evaluated. Measurements for these decay widths from the BESII data are suggested

  11. PENINGKATAN KEMAMPUAN REPRESENTASI MATEMATIS MELALUI MODEL PEMBELAJARAN KOOPERATIF THINK PAIR SHARE

    Directory of Open Access Journals (Sweden)

    Yunni Arnidha

    2016-04-01

    Full Text Available This study aims to analyze the improvement of students’ mathematicalrepresentation achievement taught by cooperative learning think pair share andstudents’ mathematical representation achievement taught by conventional method.This study is quasi experimental with Pretest –Posttest Control Group Design. Thisstudy conducted at SMPN 3 Pringsewu. The population was all of the eight gradestudents at SMPN 3 Pringsewu, with the samples of this study consists of the VIII-2class as the experiment class and VIII-5 class as the control class. To obtain thedata, it used mathematical representation achievement test instrument. The dataanalysis was conducted to know the average difference between two samples usingt-test. The result showed the improvement of mathematical representationachievement taught by cooperative learning think pair share is better than thestudents taught by conventional learning method.Keywords: think pair share model, conventional learning method,Mathematical representation

  12. J/psi-> gamma B anti B decays and the quark-pair creation model

    CERN Document Server

    Ping Rong Gang; Shen Peng Nian; Zou Bing Song

    2002-01-01

    The authors generalize the quark-pair creation model to a study of the radiative decays J/psi-> gamma B anti B by assuming that the u, d or s quark pairs are created with the same interaction strength. From the calculation of the ratio of the decay widths GAMMA(J/psi-> gamma p anti B)/GAMMA(J/psi->p anti p), the authors extract the quark-pair creation strength gI=15.40 GeV. Based on the SU(6) spin-flavour basis and the 'uds' basis, the radiative decay branching ratios containing strange baryons are evaluated. Measurements for these decay widths from the BESII data are suggested

  13. MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SHARE DAN HASIL BELAJAR DI SEKOLAH

    Directory of Open Access Journals (Sweden)

    Elhefni Elhefni

    2011-11-01

    Full Text Available Abstract Cooperative learning is learning that requires students to be responsible for himself and his group are responsible for. With cooperative learning students will more easily find and understand difficult concepts if they were in discussions with his students regularly work in groups to help each other in solving complex problems. In cooperative learning are learning techniques of the type of think-pair-share. Type of cooperative learning model think-pair-share it has the advantage that students can be a lot of time to think, respond, and help each other, the teacher only to deliver the material briefly, then ask a question, then the teacher wants students to think more deeply about the material that has been described and experienced. This technique can encourage students to enthusiastic in working together, and by applying a type of cooperative learning model think-pair-share is expected to better learning outcomes for students who learn on their own. Keywords: Type of cooperative learning model think-pair-share, learning outcomes

  14. Modeling age differences in effects of pair repetition and proactive interference using a single parameter.

    Science.gov (United States)

    Stephens, Joseph D W; Overman, Amy A

    2018-02-01

    In this article, we apply the REM model (Shiffrin & Steyvers, 1997) to age differences in associative memory. Using Criss and Shiffrin's (2005) associative version of REM, we show that in a task with pairs repeated across 2 study lists, older adults' reduced benefit of pair repetition can be produced by a general reduction in the diagnosticity of information stored in memory. This reduction can be modeled similarly well by reducing the overall distinctiveness of memory features, or by reducing the accuracy of memory encoding. We report a new experiment in which pairs are repeated across 3 study lists and extend the model accordingly. Finally, we extend the model to previously reported data using the same task paradigm, in which the use of a high-association strategy introduced proactive interference effects in young adults but not older adults. Reducing the diagnosticity of information in memory also reduces the proactive interference effect. Taken together, the modeling and empirical results reported here are consistent with the claim that some age differences that appear to be specific to associative information can be produced via general degradation of information stored in memory. The REM model provides a useful framework for examining age differences in memory as well as harmonizing seemingly conflicting prior modeling approaches for the associative deficit. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  15. From pair correlations to the quasi-particle-phonon nuclear model

    International Nuclear Information System (INIS)

    Solov'ev, V.G.

    1986-01-01

    Modern state of the nucleus theory is discussed. The main attention is paid to pair correlation theory of superconducting type and quasiparticle - phonon nucleus model. Pair correlation account allowed one to describe in detail a series of nucleus properties which did not fall within the framework of earlier known models as, for example, double-quasi-particle states in even-even deformed nuclei. To describe the wave function low-quasi-particle components at low, mean and high excitation energies, the nucleus quasi-particle-phonon model is formulated. The strength function method is used in the model and fragmentation of mono-quasi-particle, mono-phonon states and quasi-particle phonon state by many nuclear levels is calculated

  16. QSAR Modeling and Prediction of Drug-Drug Interactions.

    Science.gov (United States)

    Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

    2016-02-01

    Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

  17. Higgs boson pair productions in the Georgi-Machacek model at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Jung [Physics Division, National Center for Theoretical Sciences,Hsinchu, Taiwan 30013, R.O.C. (China); Chen, Chuan-Ren [Department of Physics, National Taiwan Normal University,Taipei, Taiwan 11677, R.O.C. (China); Chiang, Cheng-Wei [Department of Physics, National Taiwan University,Taipei, Taiwan 10617, R.O.C. (China); Institute of Physics, Academia Sinica,Taipei, Taiwan 11529, R.O.C. (China); Physics Division, National Center for Theoretical Sciences,Hsinchu, Taiwan 30013, R.O.C. (China)

    2017-03-27

    Higgs bosons pair production is well known for its sensitivity to probing the sign and size of Higgs boson self coupling, providing a way to determine whether there is an extended Higgs sector. The Georgi-Machacek (GM) model extends the Standard Model (SM) with an SU(2){sub L} triplet scalar field that has one real and one complex components. The Higgs self coupling now has a wider range than that in the SM, with even the possibility of a sign flip. The new heavy singlet Higgs boson H{sub 1}{sup 0} can contribute to s-channel production of the hh pairs. In this work, we study non-resonant/resonant Higgs boson pair productions pp→hh and pp→H{sub 1}{sup 0}→hh, focusing exclusively on the contribution of H{sub 1}{sup 0}. We show the sensitivity for Higgs boson pair production searches at the 13-TeV LHC with the luminosities of 3.2, 30 and 100 fb{sup −1}.

  18. Dispersion analysis of the Pn -Pn-1DG mixed finite element pair for atmospheric modelling

    Science.gov (United States)

    Melvin, Thomas

    2018-02-01

    Mixed finite element methods provide a generalisation of staggered grid finite difference methods with a framework to extend the method to high orders. The ability to generate a high order method is appealing for applications on the kind of quasi-uniform grids that are popular for atmospheric modelling, so that the method retains an acceptable level of accuracy even around special points in the grid. The dispersion properties of such schemes are important to study as they provide insight into the numerical adjustment to imbalance that is an important component in atmospheric modelling. This paper extends the recent analysis of the P2 - P1DG pair, that is a quadratic continuous and linear discontinuous finite element pair, to higher polynomial orders and also spectral element type pairs. In common with the previously studied element pair, and also with other schemes such as the spectral element and discontinuous Galerkin methods, increasing the polynomial order is found to provide a more accurate dispersion relation for the well resolved part of the spectrum but at the cost of a number of unphysical spectral gaps. The effects of these spectral gaps are investigated and shown to have a varying impact depending upon the width of the gap. Finally, the tensor product nature of the finite element spaces is exploited to extend the dispersion analysis into two-dimensions.

  19. Using pairs of physiological models to estimate temporal variation in amphibian body temperature.

    Science.gov (United States)

    Roznik, Elizabeth A; Alford, Ross A

    2014-10-01

    Physical models are often used to estimate ectotherm body temperatures, but designing accurate models for amphibians is difficult because they can vary in cutaneous resistance to evaporative water loss. To account for this variability, a recently published technique requires a pair of agar models that mimic amphibians with 0% and 100% resistance to evaporative water loss; the temperatures of these models define the lower and upper boundaries of possible amphibian body temperatures for the location in which they are placed. The goal of our study was to develop a method for using these pairs of models to estimate parameters describing the distributions of body temperatures of frogs under field conditions. We radiotracked green-eyed treefrogs (Litoria serrata) and collected semi-continuous thermal data using both temperature-sensitive radiotransmitters with an automated datalogging receiver, and pairs of agar models placed in frog locations, and we collected discrete thermal data using a non-contact infrared thermometer when frogs were located. We first examined the accuracy of temperature-sensitive transmitters in estimating frog body temperatures by comparing transmitter data with direct temperature measurements taken simultaneously for the same individuals. We then compared parameters (mean, minimum, maximum, standard deviation) characterizing the distributions of temperatures of individual frogs estimated from data collected using each of the three methods. We found strong relationships between thermal parameters estimated from data collected using automated radiotelemetry and both types of thermal models. These relationships were stronger for data collected using automated radiotelemetry and impermeable thermal models, suggesting that in the field, L. serrata has a relatively high resistance to evaporative water loss. Our results demonstrate that placing pairs of thermal models in frog locations can provide accurate estimates of the distributions of temperatures

  20. Experiment and modeling of paired effect on evacuation from a three-dimensional space

    Energy Technology Data Exchange (ETDEWEB)

    Jun, Hu [MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044 (China); School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); Faculty of Computer Science, Chengdu Normal University, Chengdu 611130 (China); Huijun, Sun, E-mail: hjsun1@bjtu.edu.cn [MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044 (China); School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); Juan, Wei [Faculty of Computer Science, Chengdu Normal University, Chengdu 611130 (China); Xiaodan, Chen [College of Information Science and Technology, Chengdu University, Chengdu 610106 (China); Lei, You [Faculty of Computer Science, Chengdu Normal University, Chengdu 611130 (China); College of Information Science and Technology, Chengdu University, Chengdu 610106 (China); Musong, Gu [Faculty of Computer Science, Chengdu Normal University, Chengdu 611130 (China)

    2014-10-24

    A novel three-dimensional cellular automata evacuation model was proposed based on stairs factor for paired effect and variety velocities in pedestrian evacuation. In the model pedestrians' moving probability of target position at the next moment was defined based on distance profit and repulsive force profit, and evacuation strategy was elaborated in detail through analyzing variety velocities and repulsive phenomenon in moving process. At last, experiments with the simulation platform were conducted to study the relationships of evacuation time, average velocity and pedestrian velocity. The results showed that when the ratio of single pedestrian was higher in the system, the shortest route strategy was good for improving evacuation efficiency; in turn, if ratio of paired pedestrians was higher, it is good for improving evacuation efficiency to adopt strategy that avoided conflicts, and priority should be given to scattered evacuation. - Highlights: • A novel three-dimensional evacuation model was presented with stair factor. • The paired effect and variety velocities were considered in evacuation model. • The cellular automata model is improved by repulsive force.

  1. Experiment and modeling of paired effect on evacuation from a three-dimensional space

    International Nuclear Information System (INIS)

    Jun, Hu; Huijun, Sun; Juan, Wei; Xiaodan, Chen; Lei, You; Musong, Gu

    2014-01-01

    A novel three-dimensional cellular automata evacuation model was proposed based on stairs factor for paired effect and variety velocities in pedestrian evacuation. In the model pedestrians' moving probability of target position at the next moment was defined based on distance profit and repulsive force profit, and evacuation strategy was elaborated in detail through analyzing variety velocities and repulsive phenomenon in moving process. At last, experiments with the simulation platform were conducted to study the relationships of evacuation time, average velocity and pedestrian velocity. The results showed that when the ratio of single pedestrian was higher in the system, the shortest route strategy was good for improving evacuation efficiency; in turn, if ratio of paired pedestrians was higher, it is good for improving evacuation efficiency to adopt strategy that avoided conflicts, and priority should be given to scattered evacuation. - Highlights: • A novel three-dimensional evacuation model was presented with stair factor. • The paired effect and variety velocities were considered in evacuation model. • The cellular automata model is improved by repulsive force

  2. Comparative analysis of magnetic resonance in the polaron pair recombination and the triplet exciton-polaron quenching models

    Science.gov (United States)

    Mkhitaryan, V. V.; Danilović, D.; Hippola, C.; Raikh, M. E.; Shinar, J.

    2018-01-01

    We present a comparative theoretical study of magnetic resonance within the polaron pair recombination (PPR) and the triplet exciton-polaron quenching (TPQ) models. Both models have been invoked to interpret the photoluminescence detected magnetic resonance (PLDMR) results in π -conjugated materials and devices. We show that resonance line shapes calculated within the two models differ dramatically in several regards. First, in the PPR model, the line shape exhibits unusual behavior upon increasing the microwave power: it evolves from fully positive at weak power to fully negative at strong power. In contrast, in the TPQ model, the PLDMR is completely positive, showing a monotonic saturation. Second, the two models predict different dependencies of the resonance signal on the photoexcitation power, PL. At low PL, the resonance amplitude Δ I /I is ∝PL within the PPR model, while it is ∝PL2 crossing over to PL3 within the TPQ model. On the physical level, the differences stem from different underlying spin dynamics. Most prominently, a negative resonance within the PPR model has its origin in the microwave-induced spin-Dicke effect, leading to the resonant quenching of photoluminescence. The spin-Dicke effect results from the spin-selective recombination, leading to a highly correlated precession of the on-resonance pair partners under the strong microwave power. This effect is not relevant for TPQ mechanism, where the strong zero-field splitting renders the majority of triplets off resonance. On the technical level, the analytical evaluation of the line shapes for the two models is enabled by the fact that these shapes can be expressed via the eigenvalues of a complex Hamiltonian. This bypasses the necessity of solving the much larger complex linear system of the stochastic Liouville equations. Our findings pave the way towards a reliable discrimination between the two mechanisms via cw PLDMR.

  3. Meningkatkan Prestasi Belajar IPA Melalui Model Pembelajaran Kooperatif Think-Pairs Share (TPS

    Directory of Open Access Journals (Sweden)

    Rusman Rusman

    2014-02-01

    Full Text Available Mata pelajaran IPA merupakan mata pelajaran yang menekankan siswa untuk mencari atau menemukan pengetahuanya sendiri. Model pembelajaran yang digunakan guru sangat berpengaruh dalam menciptakan situasi belajar yang benar-benar menyenangkan dan mendukung kelancaran proses belajar mengajar, serta sangat membantu dalam pencapaian prestasi belajar yang memuaskan. Akan tetapi, dalam pelaksanaan di lapangan pembelajaran banyak didominasi oleh guru sehingga kurang mampu membangun persepsi, minat, dan sikap siswa yang lebih baik. Hal tersebut juga dijumpai di SDN Pinggir Papas 1 Sumenep, siswa sulit memahami materi yang ada. Kendala yang terjadi adalah siswa merasa bosan dan tidak berminat mengikuti pembelajaran IPA. Hasil nilai ulangan harian dari 25 siswa hanya 9 siswa (36% yang mendapatkan nilai di atas KKM (65. Dari hasil tersebut, peneliti merasa perlu sekali melakukan perbaikan pembelajaran agar sehingga hasil belajar siswa dapat ditingkatkan, yaitu dengan menerapkan model  pembelajaran kooperatif Think-Pair-Share (TPS. Sesuai rumusan masalah “apakah model pembelajaran kooperatif Think-Pairs-Share (TPS dapat meningkatkan Prestasi Belajar IPA pada Siswa Kelas IIIA SDN Pinggir Papas 1 Sumenep?”, maka dilakukan metode penelitian dengan observasi dan tes. Hasil dari dua siklus penelitian yang melalui tahapan perencanaan, pelaksanaan, pengamatan, dan refleksi diperoleh hasil prestasi belajar siswa meningkat dari 67,8 dengan ketuntasan belajar 72% menjadi 80,4 dengan ketuntasan 100%. Sehingga dapat disimpulkan bahwa penerapan model pembelajaran kooperatif Think Pairs Share mampu meningkatkan prestasi belajar IPA pada siswa kelas IIIA SDN Pinggir Papas 1 Sumenep, dengan peningkatan yang sangat signifikan yaitu sebesar 28% melebihi kriteria peningkatan yang ditentukan yaitu 20%. Selain itu, model pembelajaran kooperatif Think Pairs Share efektif digunakan sebagai salah satu metode pembelajaran di kelas karena dapat menjadikan siswa aktif dalam

  4. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  5. PERAN GURU DALAM MEMBENTUK ARIF BUDAYA SISWA MELALUI MODEL PEMBELAJARAN THINK PAIR SHARE

    Directory of Open Access Journals (Sweden)

    Tarsisia Devi

    2016-12-01

    Full Text Available Artikel ini ditulis dengan tujuan untuk mengetahui peran guru dalam pembentukkan arif budaya siswa melalui model pembelajaran Think Pair Share. Model pembelajaran Think Pair Share diterapkan untuk meningkatkan daya pikir siswa dalam memecahkan suatu persoalan materi pelajaran, sehingga tercipta budaya siswa untuk berpikir cerdas. Guru mampu membentuk arif budaya siswa. Oleh karena itu guru harus dapat menjadi sumber inspirasi bagi siswa, mampu mengerakkan minat siswa untuk dapat tercipta arif budaya yang baik bagi dirinya. Guru tidak hanya menjadi pendidik, numun juga harus mampu membangkitkan semangat siswa untuk tidak malas berpikir. Metode kajian yang digunakan dalam penulisan artikel ini adalah observasi. Hasil yang diperoleh menunjukkan bahwa guru dituntut sebagai transformator, fasilitator dan motivator dalam pembentukkan arif budaya siswa.

  6. Predictive modeling of neuroanatomic structures for brain atrophy detection

    Science.gov (United States)

    Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

    2010-03-01

    In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.

  7. New Values of Cross-Talk Parameters for Twisted Pair Model

    OpenAIRE

    Milos Kozak; Lukas Cepa; Jiri Vodrazka

    2010-01-01

    Near-end Crosstalk (NEXT) and Far-end Crosstalk (FEXT) of unshielded twisted pair (UTP) cable are the main factors limiting the information capacity in data transmission. Crosstalk depends mostly on the frequency. Frequency dependent transfer functions and crosstalk attenuation may be obtained by measurement, but for the analytical description of the transmission channel's parameters is useful to define functions modelling the crosstalk. The paper describes the measuri...

  8. Penerapan Model Pembelajaran Think-Pair-Share untuk Meningkatkan Kemampuan Komunikasi Matematis Siswa SMP

    Directory of Open Access Journals (Sweden)

    Hartini Hartini

    2016-12-01

    Full Text Available Kemampuan komunikasi matematis merupakan salah satu kemampuan yang diukur pada studi PISA. Namun berdasarkan hasil studi PISA, kemampuan komunikasi matematis siswa Indonesia masih rendah. Penelitian ini bertujuan untuk melihat apakah terdapat peningkatan kemampuan komunikasi matematis siswa yang memperoleh pembelajaran menggunakan model pembelajaran Think-Pair-Share (TPS dengan siswa yang memperoleh  pembelajaran konvensional. Sampel dalam penelitian ini adalah siswa kelas VIII MTs Negeri Pagedangan, Tangerang. Dalam mengumpulkan data, peneliti menggunakan instrumen tes berupa soal uraian kemampuan komunikasi matematis. Penelitian ini menggunakan metode kuantitatif dengan desain kuasi eksperimen berbentuk Nonequivalent Control Group Design. Teknik analisis data yang digunakan adalah teknik statistik inferensial dengan melakukan uji-t. Berdasarkan analisis data menggunakan SPSS 16.0 dan Microsoft Excel 2013 penelitian menemukan bahwa peningkatan kemampuan komunikasi matematis siswa yang memperoleh pembelajaran menggunakan model pembelajaran Think-Pair-Share (TPS lebih baik dibandingkan dengan siswa yang memperoleh  pembelajaran konvensional.Mathematics communication ability is one of the skills that was measure in PISA. Based on the results of the PISA, mathematics communication ability Indonesian students is still low. The pupose this research is to see if there is an increase in mathematics communication ability students acquire learning using learning model Think-Pair-Share (TPS with students who obtain the conventional learning. The sample in this research is grade  MTs Negeri Pagedangan, Tangerang. In collecting the data, researchers use test instruments in the form of a question of mathematical communication ability essay test. This research using quantitative methods with quasi experimental design shaped Nonequivalent Control Group Design. Data analysis technique used is statistical techniques inferensial by doing the test-t. Based on

  9. Application of a Laplace transform pair model for high-energy x-ray spectral reconstruction.

    Science.gov (United States)

    Archer, B R; Almond, P R; Wagner, L K

    1985-01-01

    A Laplace transform pair model, previously shown to accurately reconstruct x-ray spectra at diagnostic energies, has been applied to megavoltage energy beams. The inverse Laplace transforms of 2-, 6-, and 25-MV attenuation curves were evaluated to determine the energy spectra of these beams. The 2-MV data indicate that the model can reliably reconstruct spectra in the low megavoltage range. Experimental limitations in acquiring the 6-MV transmission data demonstrate the sensitivity of the model to systematic experimental error. The 25-MV data result in a physically realistic approximation of the present spectrum.

  10. Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs

    Directory of Open Access Journals (Sweden)

    Girgis Hani Z

    2012-02-01

    Full Text Available Abstract Background Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF binding sites (TFBSs. Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed. Results We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinity of related genes. CrmMiner requires two sets of sequences: a mixed set and a control set. Sequences in the vicinity of the related genes comprise the mixed set, whereas the control set includes random genomic sequences. CrmMiner assumes that a large percentage of the mixed set is made of background sequences that do not include CRMs. The system identifies pairs of closely located motifs representing vertebrate TFBSs that are enriched in the training mixed set consisting of 50% of the gene loci. In addition, CrmMiner selects a group of the enriched pairs to represent the tissue-specific regulatory signature. The mixed and the control sets are searched for candidate sequences that include any of the selected pairs. Next, an optimal Bayesian classifier is used to distinguish candidates found in the mixed set from their control counterparts. Our study proposes 62 tissue-specific regulatory signatures and putative CRMs for different human tissues and cell types. These signatures consist of assortments of ubiquitously expressed TFs and tissue-specific TFs. Under controlled settings, CrmMiner identified known CRMs in noisy sets up to 1:25 signal-to-noise ratio. CrmMiner was

  11. Diverse effects of distance cutoff and residue interval on the performance of distance-dependent atom-pair potential in protein structure prediction.

    Science.gov (United States)

    Yao, Yuangen; Gui, Rong; Liu, Quan; Yi, Ming; Deng, Haiyou

    2017-12-08

    As one of the most successful knowledge-based energy functions, the distance-dependent atom-pair potential is widely used in all aspects of protein structure prediction, including conformational search, model refinement, and model assessment. During the last two decades, great efforts have been made to improve the reference state of the potential, while other factors that also strongly affect the performance of the potential have been relatively less investigated. Based on different distance cutoffs (from 5 to 22 Å) and residue intervals (from 0 to 15) as well as six different reference states, we constructed a series of distance-dependent atom-pair potentials and tested them on several groups of structural decoy sets collected from diverse sources. A comprehensive investigation has been performed to clarify the effects of distance cutoff and residue interval on the potential's performance. Our results provide a new perspective as well as a practical guidance for optimizing distance-dependent statistical potentials. The optimal distance cutoff and residue interval are highly related with the reference state that the potential is based on, the measurements of the potential's performance, and the decoy sets that the potential is applied to. The performance of distance-dependent statistical potential can be significantly improved when the best statistical parameters for the specific application environment are adopted.

  12. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  13. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  14. Pengaruh Model Pembelajaran Kooperatif Tipe Think-pair-share Terhadap Self-efficacy Siswa SMP Ditinjau Berdasarkan Gender

    OpenAIRE

    NI MADE SRI NUYAMI; Prof. Dr.I Wayan Suastra,M.Pd; Prof. Dr I Wayan Sadia,M.Pd

    2014-01-01

    Penelitian bertujuan menganalisis (1) perbedaan self-efficacy siswa yang belajar dengan model pembelajaran kooperatif tipe think-pair-share dan model pembelajaran konvensional, (2) perbedaan self-efficacy siswa laki-laki dan siswa perempuan,(3) pengaruh interaksi model pembelajaran dan jenis kelamin, (4) perbedaan self-efficacy yang belajar dengan model pembelajaran kooperatif tipe think-pair-share dan model pembelajaran konvensional untuk siswa laki-laki, (5) perbedaan self-efficacy yang b...

  15. Watson-Crick Base Pair Radical Cation as a Model for Oxidative Damage in DNA.

    Science.gov (United States)

    Feketeová, Linda; Chan, Bun; Khairallah, George N; Steinmetz, Vincent; Maitre, Philippe; Radom, Leo; O'Hair, Richard A J

    2017-07-06

    The deleterious cellular effects of ionizing radiation are well-known, but the mechanisms causing DNA damage are poorly understood. The accepted molecular events involve initial oxidation and deprotonation at guanine sites, triggering hydrogen atom abstraction reactions from the sugar moieties, causing DNA strand breaks. Probing the chemistry of the initially formed radical cation has been challenging. Here, we generate, spectroscopically characterize, and examine the reactivity of the Watson-Crick nucleobase pair radical cation in the gas phase. We observe rich chemistry, including proton transfer between the bases and propagation of the radical site in deoxyguanosine from the base to the sugar, thus rupturing the sugar. This first example of a gas-phase model system providing molecular-level details on the chemistry of an ionized DNA base pair paves the way toward a more complete understanding of molecular processes induced by radiation. It also highlights the role of radical propagation in chemistry, biology, and nanotechnology.

  16. A model of selective visual attention for a stereo pair of images

    Science.gov (United States)

    Park, Min Chul; Kim, Sung Kyu; Son, Jung-Young

    2005-11-01

    Human visual attention system has a remarkable ability to interpret complex scenes with the ease and simplicity by selecting or focusing on a small region of visual field without scanning the whole images. In this paper, a novel selective visual attention model by using 3D image display system for a stereo pair of images is proposed. It is based on the feature integration theory and locates ROI(region of interest) or FOA(focus of attention). The disparity map obtained from a stereo pair of images is exploited as one of spatial visual features to form a set of topographic feature maps in our approach. Though the true human cognitive mechanism on the analysis and integration process might be different from our assumption the proposed attention system matches well with the results found by human observers.

  17. Nonlinear chaotic model for predicting storm surges

    Directory of Open Access Journals (Sweden)

    M. Siek

    2010-09-01

    Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

  18. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  19. Predictive user modeling with actionable attributes

    NARCIS (Netherlands)

    Zliobaite, I.; Pechenizkiy, M.

    2013-01-01

    Different machine learning techniques have been proposed and used for modeling individual and group user needs, interests and preferences. In the traditional predictive modeling instances are described by observable variables, called attributes. The goal is to learn a model for predicting the target

  20. Conformational analysis of a covalently cross-linked Watson-Crick base pair model.

    Science.gov (United States)

    Jensen, Erik A; Allen, Benjamin D; Kishi, Yoshito; O'Leary, Daniel J

    2008-11-15

    Low-temperature NMR experiments and molecular modeling have been used to characterize the conformational behavior of a covalently cross-linked DNA base pair model. The data suggest that Watson-Crick or reverse Watson-Crick hydrogen bonding geometries have similar energies and can interconvert at low temperatures. This low-temperature process involves rotation about the crosslink CH(2)C(5') (psi) carbon-carbon bond, which is energetically preferred over the alternate CH(2)N(3) (phi) carbon-nitrogen bond rotation.

  1. Conformational Analysis of a Covalently Cross-Linked Watson-Crick Base Pair Model

    OpenAIRE

    Jensen, Erik A.; Allen, Benjamin D.; Kishi, Yoshito; O'Leary, Daniel J.

    2008-01-01

    Low temperature NMR experiments and molecular modeling have been used to characterize the conformational behavior of a covalently cross-linked DNA base pair model. The data suggest that Watson-Crick or reverse Watson-Crick hydrogen bonding geometries have similar energies and can interconvert at low temperatures. This low-temperature process involves rotation about the crosslink CH2–C(5′) (ψ) carbon-carbon bond, which is energetically preferred over the alternate CH2–N(3) (ϕ) carbon-nitrogen ...

  2. The path integral model of D-pairing for HTSC, heavy fermion superconductors, and superfluids

    International Nuclear Information System (INIS)

    Brusov, P.N.; Brusova, N.P.

    1996-01-01

    A model of d-pairing for superconducting and superfluid Fermi-systems has been formulated within the path integration technique. By path integration over open-quote fastclose quotes and open-quotes slowclose quotes Fermi-fields, the action functional (which determines all properties of model system) has been obtained. This functional could be used for the determination of different superconducting (superfluid) states, for calculation of the transition temperatures for these states, and for the calculation of the collective mode spectrum for HTSC, as well as for heavy fermion superconductors

  3. SDG fermion-pair algebraic SO(12) and Sp(10) models and their boson realizations

    International Nuclear Information System (INIS)

    Navatil, P.; Geyer, H.B.; Dobes, J.

    1995-01-01

    It is shown how the boson mapping formalism may be applied as a useful many-body tool to solve a fermion problem. This is done in the context of generalized Ginocchio models for which the authors introduce S-, D-, and G-pairs of fermions and subsequently construct the sdg-boson realizations of the generalized Dyson type. The constructed SO(12) and Sp(10) fermion models are solved beyond the explicit symmetry limits. Phase transitions to rotational structures are obtained also in situations where there is no underlying SU(3) symmetry. 34 refs., 5 figs., 2 tabs

  4. Higgs boson pair production at the photon linear collider in the two Higgs doublet model

    International Nuclear Information System (INIS)

    Asakawa, Eri; Harada, Daisuke; Okada, Yasuhiro; Kanemura, Shinya; Tsumura, Koji

    2009-02-01

    We calculate the cross section of the lightest Higgs boson pair production at the Photon Linear Collider in the two Higgs doublet model. We focus on the scenario in which the lightest Higgs boson has the standard model like couplings to gauge bosons. We take into account the one-loop correction to the hhh coupling as well as additional one-loop diagrams due to charged bosons to the γγ → hh helicity amplitudes. We discuss the impact of these corrections on the hhh coupling measurement at the Photon Linear Collider. (author)

  5. SDG Fermion-Pair Algebraic SO(12) and Sp(10) Models and Their Boson Realizations

    Science.gov (United States)

    Navratil, P.; Geyer, H. B.; Dobes, J.; Dobaczewski, J.

    1995-11-01

    It is shown how the boson mapping formalism may be applied as a useful many-body tool to solve a fermion problem. This is done in the context of generalized Ginocchio models for which we introduce S-, D-, and G-pairs of fermions and subsequently construct the sdg-boson realizations of the generalized Dyson type. The constructed SO(12) and Sp(10) fermion models are solved beyond the explicit symmetry limits. Phase transitions to rotational structures are obtained also in situations where there is no underlying SU(3) symmetry.

  6. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain, which...

  7. Major Mergers in CANDELS up to z=3: Calibrating the Close-Pair Method Using Semi-Analytic Models and Baryonic Mass Ratio Estimates

    Science.gov (United States)

    Mantha, Kameswara; McIntosh, Daniel H.; Conselice, Christopher; Cook, Joshua S.; Croton, Darren J.; Dekel, Avishai; Ferguson, Henry C.; Hathi, Nimish; Kodra, Dritan; Koo, David C.; Lotz, Jennifer M.; Newman, Jeffrey A.; Popping, Gergo; Rafelski, Marc; Rodriguez-Gomez, Vicente; Simmons, Brooke D.; Somerville, Rachel; Straughn, Amber N.; Snyder, Gregory; Wuyts, Stijn; Yu, Lu; Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) Team

    2018-01-01

    Cosmological simulations predict that the rate of merging between similar-mass massive galaxies should increase towards early cosmic-time. We study the incidence of major (stellar mass ratio SMR 10.3 galaxies spanning 01.5 in strong disagreement with theoretical merger rate predictions. On the other hand, if we compare to a simulation-tuned, evolving timescale prescription from Snyder et al., 2017, we find that the merger rate evolution agrees with theory out to z=3. These results highlight the need for robust calibrations on the complex and presumably redshift-dependent pair-to-merger-rate conversion factors to improve constraints of the empirical merger history. To address this, we use a unique compilation of mock datasets produced by three independent state-of-the-art Semi-Analytic Models (SAMs). We present preliminary calibrations of the close-pair observability timescale and outlier fraction as a function of redshift, stellar-mass, mass-ratio, and local over-density. Furthermore, to verify the hypothesis by previous empirical studies that SMR-selection of major pairs may be biased, we present a new analysis of the baryonic (gas+stars) mass ratios of a subset of close pairs in our sample. For the first time, our preliminary analysis highlights that a noticeable fraction of SMR-selected minor pairs (SMR>4) have major baryonic-mass ratios (BMR<4), which indicate that merger rates based on SMR selection may be under-estimated.

  8. Pulsational Pair-instability Model for Superluminous Supernova PTF12dam:Interaction and Radioactive Decay

    Energy Technology Data Exchange (ETDEWEB)

    Tolstov, Alexey; Nomoto, Ken’ichi; Blinnikov, Sergei; Quimby, Robert [Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8583 (Japan); Sorokina, Elena [Sternberg Astronomical Institute, M.V.Lomonosov Moscow State University, 119991 Moscow (Russian Federation); Baklanov, Petr, E-mail: alexey.tolstov@ipmu.jp [Institute for Theoretical and Experimental Physics (ITEP), 117218 Moscow (Russian Federation)

    2017-02-01

    Being a superluminous supernova, PTF12dam can be explained by a {sup 56}Ni-powered model, a magnetar-powered model, or an interaction model. We propose that PTF12dam is a pulsational pair-instability supernova, where the outer envelope of a progenitor is ejected during the pulsations. Thus, it is powered by a double energy source: radioactive decay of {sup 56}Ni and a radiative shock in a dense circumstellar medium. To describe multicolor light curves and spectra, we use radiation-hydrodynamics calculations of the STELLA code. We found that light curves are well described in the model with 40 M {sub ⊙} ejecta and 20–40 M {sub ⊙} circumstellar medium. The ejected {sup 56}Ni mass is about 6 M {sub ⊙}, which results from explosive nucleosynthesis with large explosion energy (2–3)×10{sup 52} erg. In comparison with alternative scenarios of pair-instability supernova and magnetar-powered supernova, in the interaction model, all the observed main photometric characteristics are well reproduced: multicolor light curves, color temperatures, and photospheric velocities.

  9. Robust predictions of the interacting boson model

    International Nuclear Information System (INIS)

    Casten, R.F.; Koeln Univ.

    1994-01-01

    While most recognized for its symmetries and algebraic structure, the IBA model has other less-well-known but equally intrinsic properties which give unavoidable, parameter-free predictions. These predictions concern central aspects of low-energy nuclear collective structure. This paper outlines these ''robust'' predictions and compares them with the data

  10. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...

  11. Bifurcation structure and stability in models of opposite-signed vortex pairs

    Energy Technology Data Exchange (ETDEWEB)

    Luzzatto-Fegiz, Paolo, E-mail: Paolo.Luzzatto-Fegiz@damtp.cam.ac.uk [Churchill College, Cambridge CB3 0DS (United Kingdom)

    2014-06-01

    We employ a recently developed numerical method to examine in detail the properties of opposite-signed, translating vortex pairs. We first consider a uniform-vortex approximation; for this flow, previous studies have found essential differences between rotating and translating configurations, and have encountered numerical difficulties at the boundary between the two types of equilibria. Recently, Luzzatto-Fegiz and Williamson (2012 J. Fluid Mech. 706 323–50) used an imperfect velocity-impulse (IVI) diagram to show that the rotating pairs have a translating counterpart, arising from a bifurcation of the classical translating configurations. In this paper, we expand this IVI diagram to find two new branches of steady vortices, including antisymmetric pairs, as well as vortices without any symmetry. We next consider more realistic models for flows at moderate Reynolds number Re, by computing solution families based on a discretized Chaplygin–Lamb dipole. We find that, as the accuracy of the discretization improves, the bifurcated branches shrink rapidly, while the unstable portion of the basic solution family becomes smaller. These results indicate that the bifurcation structure of moderate-Re flows can be very different from that of solutions that use a single patch per vortex. (papers)

  12. Bifurcation structure and stability in models of opposite-signed vortex pairs

    International Nuclear Information System (INIS)

    Luzzatto-Fegiz, Paolo

    2014-01-01

    We employ a recently developed numerical method to examine in detail the properties of opposite-signed, translating vortex pairs. We first consider a uniform-vortex approximation; for this flow, previous studies have found essential differences between rotating and translating configurations, and have encountered numerical difficulties at the boundary between the two types of equilibria. Recently, Luzzatto-Fegiz and Williamson (2012 J. Fluid Mech. 706 323–50) used an imperfect velocity-impulse (IVI) diagram to show that the rotating pairs have a translating counterpart, arising from a bifurcation of the classical translating configurations. In this paper, we expand this IVI diagram to find two new branches of steady vortices, including antisymmetric pairs, as well as vortices without any symmetry. We next consider more realistic models for flows at moderate Reynolds number Re, by computing solution families based on a discretized Chaplygin–Lamb dipole. We find that, as the accuracy of the discretization improves, the bifurcated branches shrink rapidly, while the unstable portion of the basic solution family becomes smaller. These results indicate that the bifurcation structure of moderate-Re flows can be very different from that of solutions that use a single patch per vortex. (papers)

  13. Pairing tendencies in a two-orbital Hubbard model in one dimension

    Energy Technology Data Exchange (ETDEWEB)

    Patel, Niravkumar D. [The Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Nocera, Adriana [The Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Alvarez, Gonzalo [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Moreo, A. [The Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Dagotto, Elbio R. [The Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-07-31

    The recent discovery of superconductivity under high pressure in the ladder compound BaFe2S3 has opened a new field of research in iron-based superconductors with focus on quasi-one-dimensional geometries. In this publication, using the density matrix renormalization group technique, we study a two-orbital Hubbard model defined in one-dimensional chains. Our main result is the presence of hole binding tendencies at intermediate Hubbard U repulsion and robust Hund coupling JH / U = 0.25. Binding does not occur either in weak coupling or at very strong coupling. The pair-pair correlations that are dominant near half-filling, or of similar strength as the charge and spin correlation channels, involve hole-pair operators that are spin singlets, use nearest-neighbor sites, and employ different orbitals for each hole. As a result, the Hund coupling strength, presence of robust magnetic moments, and antiferromagnetic correlations among them are important for the binding tendencies found here.

  14. The lateral mesodermal divide: an epigenetic model of the origin of paired fins.

    Science.gov (United States)

    Nuño de la Rosa, Laura; Müller, Gerd B; Metscher, Brian D

    2014-01-01

    By examining development at the level of tissues and processes, rather than focusing on gene expression, we have formulated a general hypothesis to explain the dorso-ventral and anterior-posterior placement of paired appendage initiation sites in vertebrates. According to our model, the number and position of paired appendages are due to a commonality of embryonic tissue environments determined by the global interactions involving the two separated layers (somatic and visceral) of lateral plate mesoderm along the dorso-ventral and anterior-posterior axes of the embryo. We identify this distribution of developmental conditions, as modulated by the separation/contact of the two LPM layers and their interactions with somitic mesoderm, ectoderm, and endoderm as a dynamic developmental entity which we have termed the lateral mesodermal divide (LMD). Where the divide results in a certain tissue environment, fin bud initiation can occur. According to our hypothesis, the influence of the developing gut suppresses limb initiation along the midgut region and the ventral body wall owing to an "endodermal predominance." From an evolutionary perspective, the lack of gut regionalization in agnathans reflects the ancestral absence of these conditions, and the elaboration of the gut together with the concomitant changes to the LMD in the gnathostomes could have led to the origin of paired fins. © 2013 Wiley Periodicals, Inc.

  15. Combined search for the standard model Higgs boson decaying to a bb pair using the full CDF data set.

    Science.gov (United States)

    Aaltonen, T; 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; Binkley, M E; 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; Ferrazza, C; 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; Jeans, D T; Jeon, E J; Jindariani, S; 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; 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; Tipton, P; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; 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

    2012-09-14

    We combine the results of searches for the standard model (SM) Higgs boson based on the full CDF Run II data set obtained from sqrt[s]=1.96  TeV pp collisions at the Fermilab Tevatron corresponding to an integrated luminosity of 9.45  fb(-1). The searches are conducted for Higgs bosons that are produced in association with a W or Z boson, have masses in the range 90-150  GeV/c(2), and decay into bb pairs. An excess of data is present that is inconsistent with the background prediction at the level of 2.5 standard deviations (the most significant local excess is 2.7 standard deviations).

  16. Residual sweeping errors in turbulent particle pair diffusion in a Lagrangian diffusion model.

    Science.gov (United States)

    Malik, Nadeem A

    2017-01-01

    Thomson, D. J. & Devenish, B. J. [J. Fluid Mech. 526, 277 (2005)] and others have suggested that sweeping effects make Lagrangian properties in Kinematic Simulations (KS), Fung et al [Fung J. C. H., Hunt J. C. R., Malik N. A. & Perkins R. J. J. Fluid Mech. 236, 281 (1992)], unreliable. However, such a conclusion can only be drawn under the assumption of locality. The major aim here is to quantify the sweeping errors in KS without assuming locality. Through a novel analysis based upon analysing pairs of particle trajectories in a frame of reference moving with the large energy containing scales of motion it is shown that the normalized integrated error [Formula: see text] in the turbulent pair diffusivity (K) due to the sweeping effect decreases with increasing pair separation (σl), such that [Formula: see text] as σl/η → ∞; and [Formula: see text] as σl/η → 0. η is the Kolmogorov turbulence microscale. There is an intermediate range of separations 1 < σl/η < ∞ in which the error [Formula: see text] remains negligible. Simulations using KS shows that in the swept frame of reference, this intermediate range is large covering almost the entire inertial subrange simulated, 1 < σl/η < 105, implying that the deviation from locality observed in KS cannot be atributed to sweeping errors. This is important for pair diffusion theory and modeling. PACS numbers: 47.27.E?, 47.27.Gs, 47.27.jv, 47.27.Ak, 47.27.tb, 47.27.eb, 47.11.-j.

  17. NASA AVOSS Fast-Time Wake Prediction Models: User's Guide

    Science.gov (United States)

    Ahmad, Nash'at N.; VanValkenburg, Randal L.; Pruis, Matthew

    2014-01-01

    The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.

  18. Extracting falsifiable predictions from sloppy models.

    Science.gov (United States)

    Gutenkunst, Ryan N; Casey, Fergal P; Waterfall, Joshua J; Myers, Christopher R; Sethna, James P

    2007-12-01

    Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte-Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

  19. The prediction of epidemics through mathematical modeling.

    Science.gov (United States)

    Schaus, Catherine

    2014-01-01

    Mathematical models may be resorted to in an endeavor to predict the development of epidemics. The SIR model is one of the applications. Still too approximate, the use of statistics awaits more data in order to come closer to reality.

  20. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  1. Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

    Science.gov (United States)

    Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

    2017-12-01

    Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model

  2. Top pair cross section measurements and event modelling with the CMS detector

    CERN Document Server

    Keaveney, James Michael

    2016-01-01

    Precision measurements are presented of the top-quark pair inclusive production cross section in proton-proton collisions at the LHC at centre-of-mass energies of 7, 8 and 13 TeV. The data are collected with the CMS experiment during the years 2011, 2012, and 2015. The analyses profit from different top quark final states and make use of events with two, one or no reconstructed charged leptons. In most analyses b-jet identification is used to increase the purity of the selection. The backgrounds are determined using data-driven techniques. The results are combined with each other and compared with theory predictions. Indirect constraints on both the top quark mass and alpha_s are obtained through their relation to the inclusive cross section.Differential top quark pair production cross sections are measured in proton-proton collisions at the LHC at centre-of-mass energies of 7, 8, and 13 TeV, using data collected by the CMS experiment in the years 2011, 2012, and 2015. The differential cross sections are meas...

  3. Extinction of drug- and withdrawal-paired cues in animal models: relevance to the treatment of addiction.

    Science.gov (United States)

    Myers, Karyn M; Carlezon, William A

    2010-11-01

    Conditioned drug craving and withdrawal elicited by cues paired with drug use or acute withdrawal are among the many factors contributing to compulsive drug taking. Understanding how to stop these cues from having these effects is a major goal of addiction research. Extinction is a form of learning in which associations between cues and the events they predict are weakened by exposure to the cues in the absence of those events. Evidence from animal models suggests that conditioned responses to drug cues can be extinguished, although the degree to which this occurs in humans is controversial. Investigations into the neurobiological substrates of extinction of conditioned drug craving and withdrawal may facilitate the successful use of drug cue extinction within clinical contexts. While this work is still in the early stages, there are indications that extinction of drug- and withdrawal-paired cues shares neural mechanisms with extinction of conditioned fear. Using the fear extinction literature as a template, it is possible to organize the observations on drug cue extinction into a cohesive framework. Copyright © 2010 Elsevier Ltd. All rights reserved.

  4. Condensation in models with factorized and pair-factorized stationary states

    International Nuclear Information System (INIS)

    Evans, M R; Waclaw, B

    2015-01-01

    Non-equilibrium real-space condensation is a phenomenon in which a finite fraction of some conserved quantity (mass, particles, etc) becomes spatially localized. We review two popular stochastic models of hopping particles that lead to condensation and whose stationary states assume a factorized form: the zero-range process and the misanthrope process, and their various generalizations. We also introduce a new model—a misanthrope process with parallel dynamics—that exhibits condensation and has a pair-factorized stationary state

  5. Anomalous resonance of the symmetric single-impurity Anderson model in the presence of pairing fluctuations

    International Nuclear Information System (INIS)

    Guang-Ming Zhang; Lu Yu

    1998-10-01

    We consider the symmetric single-impurity Anderson model in the presence of pairing fluctuations. In the isotropic limit, the degrees of freedom of the local impurity are separated into hybridizing and non-hybridizing modes. The self-energy for the hybridizing modes can be obtained exactly, leading to two subbands centered at ±U/2. For the non-hybridizing modes, the second order perturbation yields a singular resonance of the marginal Fermi liquid form. By multiplicative renormalization, the self-energy is derived exactly, showing the resonance is pinned at the Fermi level, while its strength is weakened by renormalization. (author)

  6. Case studies in archaeological predictive modelling

    NARCIS (Netherlands)

    Verhagen, Jacobus Wilhelmus Hermanus Philippus

    2007-01-01

    In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing

  7. EVENT GENERATION OF STANDARD MODEL HIGGS DECAY TO DIMUON PAIRS USING PYTHIA SOFTWARE

    CERN Document Server

    Yusof, Adib

    2015-01-01

    My project for CERN Summer Student Programme 2015 is on Event Generation of Standard Model Higgs Decay to Dimuon Pairs using Pythia Software. Briefly, Pythia or specifically, Pythia 8.1 is a program for the generation of high-energy Physics events that is able to describe the collisions at any given energies between elementary particles such as Electron, Positron, Proton as well as anti-Proton. It contains theory and models for a number of Physics aspects, including hard and soft interactions, parton distributions, initial-state and final-state parton showers, multiparton interactions, fragmentation and decay. All programming code is to be written in C++ language for this version (the previous version uses FORTRAN) and can be linked to ROOT software for displaying output in form of histogram. For my project, I need to generate events for standard model Higgs Boson into Muon and anti-Muon pairs (H→μ+ μ) to study the expected significance value for this particular process at centre-of-mass energy of 13 TeV...

  8. Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies.

    Directory of Open Access Journals (Sweden)

    Tanmay A Gokhale

    2017-01-01

    Full Text Available To understand how excitable tissues give rise to arrhythmias, it is crucially necessary to understand the electrical dynamics of cells in the context of their environment. Multicellular monolayer cultures have proven useful for investigating arrhythmias and other conduction anomalies, and because of their relatively simple structure, these constructs lend themselves to paired computational studies that often help elucidate mechanisms of the observed behavior. However, tissue cultures of cardiomyocyte monolayers currently require the use of neonatal cells with ionic properties that change rapidly during development and have thus been poorly characterized and modeled to date. Recently, Kirkton and Bursac demonstrated the ability to create biosynthetic excitable tissues from genetically engineered and immortalized HEK293 cells with well-characterized electrical properties and the ability to propagate action potentials. In this study, we developed and validated a computational model of these excitable HEK293 cells (called "Ex293" cells using existing electrophysiological data and a genetic search algorithm. In order to reproduce not only the mean but also the variability of experimental observations, we examined what sources of variation were required in the computational model. Random cell-to-cell and inter-monolayer variation in both ionic conductances and tissue conductivity was necessary to explain the experimentally observed variability in action potential shape and macroscopic conduction, and the spatial organization of cell-to-cell conductance variation was found to not impact macroscopic behavior; the resulting model accurately reproduces both normal and drug-modified conduction behavior. The development of a computational Ex293 cell and tissue model provides a novel framework to perform paired computational-experimental studies to study normal and abnormal conduction in multidimensional excitable tissue, and the methodology of modeling

  9. Measurement of the branching ratios for the Standard Model Higgs decays into muon pairs and into Z boson pairs at a 1.4 TeV CLIC

    CERN Document Server

    AUTHOR|(SzGeCERN)701211; Bozovic-Jelisavcic, Ivanka; Grefe, Christian; Kacarevic, Goran; Lukic, Strahinja; Pandurovic, Mila; Roloff, Philipp Gerhard; Smiljanic, Ivan

    2016-01-01

    The measurement of the Higgs production cross-section times the branching ratios for its decays into μ+μ- and ZZ* pairs at a 1.4 TeV CLIC collider is investigated in this paper. The Standard Model Higgs boson with a mass of 126 GeV is dominantly produced via WW fusion in e+e- collisions at 1.4 TeV centre-of-mass energy. Analyses for both decay channels are based on a full simulation of the CLIC_ILD detector. All relevant physics and beam-induced background processes are taken into account. An integrated luminosity of 1.5 ab 1 and unpolarised beams are assumed. For the H-->ZZ* decay, the purely hadronic final state (ZZ*--> qq ̄qq ̄) is considered as well as ZZ* decays into two jets and two leptons (ZZ*--> qq ̄l+l- ). It is shown that the branching ratio for the Higgs decay into a muon pair times the Higgs production cross-section can be measured with 38% statistical uncertainty. It is also shown that the statistical uncertainty of the Higgs branching fraction for decay into a Z boson pair times the Hi...

  10. Incorporating uncertainty in predictive species distribution modelling.

    Science.gov (United States)

    Beale, Colin M; Lennon, Jack J

    2012-01-19

    Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

  11. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

  12. Pairing FLUXNET sites to validate model representations of land-use/land-cover change

    Science.gov (United States)

    Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

    2018-01-01

    Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

  13. Evaluating the Predictive Value of Growth Prediction Models

    Science.gov (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.

    2014-01-01

    This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

  14. [Biological and neural bases of partner preferences in rodents: models to understand human pair bonds].

    Science.gov (United States)

    Coria-Avila, G A; Hernández-Aguilar, M E; Toledo-Cárdenas, R; García-Hernández, L I; Manzo, J; Pacheco, P; Miquel, M; Pfaus, J G

    To analyse the biological and neural bases of partner preference formation in rodents as models to understand human pair bonding. Rodents are social individuals, capable of forming short- or long-lasting partner preferences that develop slowly by stimuli like cohabitation, or rapidly by stimuli like sex and stress. Dopamine, corticosteroids, oxytocin, vasopressin, and opioids form the neurochemical substrate for pair bonding in areas like the nucleus accumbens, the prefrontal cortex, the piriform cortex, the medial preoptic area, the ventral tegmental area and the medial amygdala, among others. Additional areas may participate depending on the nature of the conditioned stimuli by which and individual recognizes a preferred partner. Animal models help us understand that the capacity of an individual to display long-lasting and selective preferences depends on neural bases, selected throughout evolution. The challenge in neuroscience is to use this knowledge to create new solutions for mental problems associated with the incapacity of an individual to display a social bond, keep one, or cope with the disruption of a consolidated one.

  15. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  16. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  17. Deep Predictive Models in Interactive Music

    OpenAIRE

    Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

    2018-01-01

    Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

  18. Algebraic approach to q-deformed supersymmetric variants of the Hubbard model with pair hoppings

    International Nuclear Information System (INIS)

    Arnaudon, D.

    1997-01-01

    Two quantum spin chains Hamiltonians with quantum sl(2/1) invariance are constructed. These spin chains define variants of the Hubbard model and describe electron models with pair hoppings. A cubic algebra that admits the Birman-Wenzl-Murakami algebra as a quotient allows exact solvability of the periodic chain. The two Hamiltonians, respectively built using the distinguished and the fermionic bases of U q (sl(2/1)) differ only in the boundary terms. They are actually equivalent, but the equivalence is non local. Reflection equations are solved to get exact solvability on open chains with non trivial boundary conditions. Two families of diagonal solutions are found. The centre and the s-Casimir of the quantum enveloping algebra of sl(2/1) appear as tools for the construction of exactly solvable Hamiltonians. (author)

  19. Neutrino masses in RPV models with two pairs of Higgs doublets

    Energy Technology Data Exchange (ETDEWEB)

    Grossman, Yuval [Laboratory for Elementary-Particle Physics, Cornell University,Ithaca, N.Y. (United States); Peset, Clara [Institut de Fisica d’Altes Energies (IFAE), Universitat Autònoma de Barcelona,08193 Bellaterra, Barcelona (Spain)

    2014-04-07

    We study the generation of neutrino masses and mixing in supersymmetric R-parity violating models containing two pairs of Higgs doublets. In these models, new RPV terms H^{sub D{sub 1}}H^{sub D{sub 2}}E^ arise in the superpotential, as well as new soft terms. Such terms give new contributions to neutrino masses. We identify the different parameters and suppression/enhancement factors that control each of these contributions. At tree level, just like in the MSSM, only one neutrino acquires a mass due to neutrino-neutralino mixing. There are no new one loop effects. We study the two loop contributions and find the conditions under which they can be important.

  20. A search for beyond the Standard Model physics using a final state with light and boosted muon pairs at CMS experiment

    CERN Document Server

    Castaneda Hernandez, Alfredo Martin

    2017-01-01

    A search for new physics phenomena is presented using a final state with multi-muons, the topology studied considers pairs of opposite sign muons (dimuons) with a low invariant mass and potentially produced far from the interaction point (displaced). Several beyond the Standard Model scenarios fit into this category, including those predicting Dark matter particles (i.e. dark photons) which weakly interact with SM particles via a kinetic mixing parameter and could have a non-negligible lifetime. Other scenario is the Next-to-Minimal Supersymmetric Standard Model (NMSSM) that extends the higgs sector introducing new light bosons that can decay to muon pairs. The data analyzed corresponds to the one collected by CMS experiment during 2015 using 13 TeV collision energy. This search constrains a large, previously unconstrained area of the parameter space for each mode and allows for an easy reinterpretation for new physics models with similar final state.

  1. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...... steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  2. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

    Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

  3. Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

    OpenAIRE

    David Ebert

    2006-01-01

    One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

  4. Fingerprint verification prediction model in hand dermatitis.

    Science.gov (United States)

    Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah

    2015-07-01

    Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

  5. Retention modeling under organic modifier gradient conditions in ion-pair reversed-phase chromatography. Application to the separation of a set of underivatized amino acids.

    Science.gov (United States)

    Pappa-Louisi, A; Agrafiotou, P; Papachristos, K

    2010-07-01

    The combined effect of the ion-pairing reagent concentration, C(ipr), and organic modifier content, phi, on the retention under phi-gradient conditions at different constant C(ipr) was treated in this study by using two approaches. In the first approach, the prediction of the retention time of a sample solute is based on a direct fitting procedure of a proper retention model to 3-D phi-gradient retention data obtained under the same phi-linear variation but with different slope and time duration of the initial isocratic part and in the presence of various constant C(ipr) values in the eluent. The second approach is based on a retention model describing the combined effect of C(ipr) and phi on the retention of solutes in isocratic mode and consequently analyzes isocratic data obtained in mobile phases containing different C(ipr) values. The effectiveness of the above approaches was tested in the retention prediction of a mixture of 16 underivatized amino acids using mobile phases containing acetonitrile as organic modifier and sodium dodecyl sulfate as ion-pairing reagent. From these approaches, only the first one gives satisfactory predictions and can be successfully used in optimization of ion-pair chromatographic separations under gradient conditions. The failure of the second approach to predict the retention of solutes in the gradient elution mode in the presence of different C(ipr) values was attributed to slow changes in the distribution equilibrium of ion-pairing reagents caused by phi-variation.

  6. Massive Predictive Modeling using Oracle R Enterprise

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  7. Multi-model analysis in hydrological prediction

    Science.gov (United States)

    Lanthier, M.; Arsenault, R.; Brissette, F.

    2017-12-01

    Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

  8. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp

    2016-01-01

    Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...

  20. A Bethe ansatz solvable model for superpositions of Cooper pairs and condensed molecular bosons

    International Nuclear Information System (INIS)

    Hibberd, K.E.; Dunning, C.; Links, J.

    2006-01-01

    We introduce a general Hamiltonian describing coherent superpositions of Cooper pairs and condensed molecular bosons. For particular choices of the coupling parameters, the model is integrable. One integrable manifold, as well as the Bethe ansatz solution, was found by Dukelsky et al. [J. Dukelsky, G.G. Dussel, C. Esebbag, S. Pittel, Phys. Rev. Lett. 93 (2004) 050403]. Here we show that there is a second integrable manifold, established using the boundary quantum inverse scattering method. In this manner we obtain the exact solution by means of the algebraic Bethe ansatz. In the case where the Cooper pair energies are degenerate we examine the relationship between the spectrum of these integrable Hamiltonians and the quasi-exactly solvable spectrum of particular Schrodinger operators. For the solution we derive here the potential of the Schrodinger operator is given in terms of hyperbolic functions. For the solution derived by Dukelsky et al., loc. cit. the potential is sextic and the wavefunctions obey PT-symmetric boundary conditions. This latter case provides a novel example of an integrable Hermitian Hamiltonian acting on a Fock space whose states map into a Hilbert space of PT-symmetric wavefunctions defined on a contour in the complex plane

  1. Multicritical phase diagrams of the Blume-Emery-Griffiths model with repulsive biquadratic coupling including metastable phases: the pair approximation and the path probability method with pair distribution

    International Nuclear Information System (INIS)

    Keskin, Mustafa; Erdinc, Ahmet

    2004-01-01

    As a continuation of the previously published work, the pair approximation of the cluster variation method is applied to study the temperature dependences of the order parameters of the Blume-Emery-Griffiths model with repulsive biquadratic coupling on a body centered cubic lattice. We obtain metastable and unstable branches of the order parameters besides the stable branches and phase transitions of these branches are investigated extensively. We study the dynamics of the model by the path probability method with pair distribution in order to make sure that we find and define the metastable and unstable branches of the order parameters completely and correctly. We present the metastable phase diagram in addition to the equilibrium phase diagram and also the first-order phase transition line for the unstable branches of the quadrupole order parameter is superimposed on the phase diagrams. It is found that the metastable phase diagram and the first-order phase boundary for the unstable quadrupole order parameter always exist at the low temperatures which are consistent with experimental and theoretical works

  2. Predictive Model of Systemic Toxicity (SOT)

    Science.gov (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  3. Spent fuel: prediction model development

    International Nuclear Information System (INIS)

    Almassy, M.Y.; Bosi, D.M.; Cantley, D.A.

    1979-07-01

    The need for spent fuel disposal performance modeling stems from a requirement to assess the risks involved with deep geologic disposal of spent fuel, and to support licensing and public acceptance of spent fuel repositories. Through the balanced program of analysis, diagnostic testing, and disposal demonstration tests, highlighted in this presentation, the goal of defining risks and of quantifying fuel performance during long-term disposal can be attained

  4. Navy Recruit Attrition Prediction Modeling

    Science.gov (United States)

    2014-09-01

    have high correlation with attrition, such as age, job characteristics, command climate, marital status, behavior issues prior to recruitment, and the...the additive model. glm(formula = Outcome ~ Age + Gender + Marital + AFQTCat + Pay + Ed + Dep, family = binomial, data = ltraining) Deviance ...0.1 ‘ ‘ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance : 105441 on 85221 degrees of freedom Residual deviance

  5. Predictive Models and Computational Toxicology (II IBAMTOX)

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  6. Finding furfural hydrogenation catalysts via predictive modelling

    NARCIS (Netherlands)

    Strassberger, Z.; Mooijman, M.; Ruijter, E.; Alberts, A.H.; Maldonado, A.G.; Orru, R.V.A.; Rothenberg, G.

    2010-01-01

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes

  7. FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL ...

    African Journals Online (AJOL)

    FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL STRESSES IN ... the transverse residual stress in the x-direction (σx) had a maximum value of 375MPa ... the finite element method are in fair agreement with the experimental results.

  8. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico; Kryshtafovych, Andriy; Tramontano, Anna

    2009-01-01

    established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic

  9. PERBEDAAN HASIL BELAJAR EKONOMI ANTARA MODEL THINK-PAIR-SHARE DAN MODEL CONCEPT MAPPING PADA SISWA SMA 1 NGUTER SUKOHARJO

    Directory of Open Access Journals (Sweden)

    Nina Mahardani

    2014-02-01

    Full Text Available Pemilihan model belajar yang tepat oleh guru dalam proses belajar mengajar mampu menciptakan suasana belajar yang efektif dan menyenangkan, serta dapat mempermudah siswa dalam menerima dan memahami materi yang dipelajari. Hal itu terlihat pada pencapaian hasil belajar yang berkualitas ditunjukkan dengan capaian nilai diatas standar ketuntasan. Salah satu cara yang dapat dilakukan oleh guru dalam pembelajaran adalah dengan menerapkan model pembelajaran think pair share dan concept mapping. Sampel dalam penelitian ini yaitu 72 siswa kelas X SMA I Nguter Sukoharjo. Teknik pengumpulan data yang digunakan yaitu kuisioner, observasi, dan dokumentasi. Teknik analisis data yang digunakan dalam penelitian ini adalah statistik deskriptif dengan analisis frekuensi dan uji statistik t tes. Berdasarkan hasil penelitian tersebut menunjukkan adanya perbedaan, hal ini ditunjukkan dengan uji t diperoleh t hitung = 2.31 > t tabel = 1.99 yang berada pada daerah penolakan Ho untuk α = 5% dengan dk = 36+36-2 = 70. Disimpulkan bahwa model pembelajaran concept mapping lebih baik dibanding model pembelajaran think pair share dalam meningkatkan hasil belajar siswa. Selection of an appropriate model of learning by the teacher in the learning process to create an effective learning environment and fun, and can facilitate students to receive and understand the material being studied. It was seen on achieving quality learning outcomes indicated by values ​​above performance standards mastery. One way that can be done by the teacher in learning is to apply a think pair share and concept mapping learning model. The sample for this study are 72 students grade ten in SMA 1 Nguter Sukoharjo . Data collection techniques were used questionnaires, observation, and documentation. Data analysis techniques in this research were used descriptive statistical analysis of the frequency and statistical test by t test. Based on these results reveal differences, as shown by the t

  10. Simple concentration-dependent pair interaction model for large-scale simulations of Fe-Cr alloys

    International Nuclear Information System (INIS)

    Levesque, Maximilien; Martinez, Enrique; Fu, Chu-Chun; Nastar, Maylise; Soisson, Frederic

    2011-01-01

    This work is motivated by the need for large-scale simulations to extract physical information on the iron-chromium system that is a binary model alloy for ferritic steels used or proposed in many nuclear applications. From first-principles calculations and the experimental critical temperature we build a new energetic rigid lattice model based on pair interactions with concentration and temperature dependence. Density functional theory calculations in both norm-conserving and projector augmented-wave approaches have been performed. A thorough comparison of these two different ab initio techniques leads to a robust parametrization of the Fe-Cr Hamiltonian. Mean-field approximations and Monte Carlo calculations are then used to account for temperature effects. The predictions of the model are in agreement with the most recent phase diagram at all temperatures and compositions. The solubility of Cr in Fe below 700 K remains in the range of about 6 to 12%. It reproduces the transition between the ordering and demixing tendency and the spinodal decomposition limits are also in agreement with the values given in the literature.

  11. Mental models accurately predict emotion transitions.

    Science.gov (United States)

    Thornton, Mark A; Tamir, Diana I

    2017-06-06

    Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

  12. Mental models accurately predict emotion transitions

    Science.gov (United States)

    Thornton, Mark A.; Tamir, Diana I.

    2017-01-01

    Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

  13. Modelling the structure factors and pair distribution functions of amorphous germanium, silicon and carbon

    International Nuclear Information System (INIS)

    Dalgic, Seyfettin; Gonzalez, Luis Enrique; Baer, Shalom; Silbert, Moises

    2002-01-01

    We present the results of calculations of the static structure factor S(k) and the pair distribution function g(r) of the tetrahedral amorphous semiconductors germanium, silicon and carbon using the structural diffusion model (SDM). The results obtained with the SDM for S(k) and g(r) are of comparable quality with those obtained by the unconstrained Reverse Monte Carlo simulations and existing ab initio molecular dynamics simulations for these systems. We have found that g(r) exhibits a small peak, or shoulder, a weak remnant of the prominent third neighbour peak present in the crystalline phase of these systems. This feature has been experimentally found to be present in recently reported high energy X-ray experiments of amorphous silicon (Phys. Rev. B 60 (1999) 13520), as well as in the previous X-ray diffraction of as-evaporated amorphous germanium (Phys. Rev. B 50 (1994) 539)

  14. Modelling the structure factors and pair distribution functions of amorphous germanium, silicon and carbon

    Energy Technology Data Exchange (ETDEWEB)

    Dalgic, Seyfettin; Gonzalez, Luis Enrique; Baer, Shalom; Silbert, Moises

    2002-12-01

    We present the results of calculations of the static structure factor S(k) and the pair distribution function g(r) of the tetrahedral amorphous semiconductors germanium, silicon and carbon using the structural diffusion model (SDM). The results obtained with the SDM for S(k) and g(r) are of comparable quality with those obtained by the unconstrained Reverse Monte Carlo simulations and existing ab initio molecular dynamics simulations for these systems. We have found that g(r) exhibits a small peak, or shoulder, a weak remnant of the prominent third neighbour peak present in the crystalline phase of these systems. This feature has been experimentally found to be present in recently reported high energy X-ray experiments of amorphous silicon (Phys. Rev. B 60 (1999) 13520), as well as in the previous X-ray diffraction of as-evaporated amorphous germanium (Phys. Rev. B 50 (1994) 539)

  15. Seniority structure of the cranked shell model wave function and the pairing phase transition

    International Nuclear Information System (INIS)

    Wu, C.S.; Zeng, J.Y.; Center of Theoretical Physics, China Center of Advanced Science and Technology

    1989-01-01

    The accurate solutions to the low-lying eigenstates of the cranked shell model Hamiltonian are obtained by the particle-number-conserving treatment, in which a many-particle configuration truncation is adopted instead of the conventional single-particle level truncation. The variation of the seniority structures of low-lying eigenstates with rotational frequency ω is analyzed. The gap parameter of the yrast band decreases with ω very slowly, though the seniority structure has undergone a great change. It is suggested to use the seniority structure to indicate the possible pairing phase transition from a superconducting state to a normal state. The important blocking effects on the low-lying eigenstates are discussed

  16. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

  17. Model predictive Controller for Mobile Robot

    OpenAIRE

    Alireza Rezaee

    2017-01-01

    This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is...

  18. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  19. Accuracy assessment of landslide prediction models

    International Nuclear Information System (INIS)

    Othman, A N; Mohd, W M N W; Noraini, S

    2014-01-01

    The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones

  20. Detection and 3d Modelling of Vehicles from Terrestrial Stereo Image Pairs

    Science.gov (United States)

    Coenen, M.; Rottensteiner, F.; Heipke, C.

    2017-05-01

    The detection and pose estimation of vehicles plays an important role for automated and autonomous moving objects e.g. in autonomous driving environments. We tackle that problem on the basis of street level stereo images, obtained from a moving vehicle. Processing every stereo pair individually, our approach is divided into two subsequent steps: the vehicle detection and the modelling step. For the detection, we make use of the 3D stereo information and incorporate geometric assumptions on vehicle inherent properties in a firstly applied generic 3D object detection. By combining our generic detection approach with a state of the art vehicle detector, we are able to achieve satisfying detection results with values for completeness and correctness up to more than 86%. By fitting an object specific vehicle model into the vehicle detections, we are able to reconstruct the vehicles in 3D and to derive pose estimations as well as shape parameters for each vehicle. To deal with the intra-class variability of vehicles, we make use of a deformable 3D active shape model learned from 3D CAD vehicle data in our model fitting approach. While we achieve encouraging values up to 67.2% for correct position estimations, we are facing larger problems concerning the orientation estimation. The evaluation is done by using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012).

  1. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  2. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  3. Microscopic model of quasiparticle wave packets in superfluids, superconductors, and paired Hall states.

    Science.gov (United States)

    Parameswaran, S A; Kivelson, S A; Shankar, R; Sondhi, S L; Spivak, B Z

    2012-12-07

    We study the structure of Bogoliubov quasiparticles, bogolons, the fermionic excitations of paired superfluids that arise from fermion (BCS) pairing, including neutral superfluids, superconductors, and paired quantum Hall states. The naive construction of a stationary quasiparticle in which the deformation of the pair field is neglected leads to a contradiction: it carries a net electrical current even though it does not move. However, treating the pair field self-consistently resolves this problem: in a neutral superfluid, a dipolar current pattern is associated with the quasiparticle for which the total current vanishes. When Maxwell electrodynamics is included, as appropriate to a superconductor, this pattern is confined over a penetration depth. For paired quantum Hall states of composite fermions, the Maxwell term is replaced by a Chern-Simons term, which leads to a dipolar charge distribution and consequently to a dipolar current pattern.

  4. Dynamics in a one-dimensional ferrogel model: relaxation, pairing, shock-wave propagation.

    Science.gov (United States)

    Goh, Segun; Menzel, Andreas M; Löwen, Hartmut

    2018-05-23

    Ferrogels are smart soft materials, consisting of a polymeric network and embedded magnetic particles. Novel phenomena, such as the variation of the overall mechanical properties by external magnetic fields, emerge consequently. However, the dynamic behavior of ferrogels remains largely unveiled. In this paper, we consider a one-dimensional chain consisting of magnetic dipoles and elastic springs between them as a simple model for ferrogels. The model is evaluated by corresponding simulations. To probe the dynamics theoretically, we investigate a continuum limit of the energy governing the system and the corresponding equation of motion. We provide general classification scenarios for the dynamics, elucidating the touching/detachment dynamics of the magnetic particles along the chain. In particular, it is verified in certain cases that the long-time relaxation corresponds to solutions of shock-wave propagation, while formations of particle pairs underlie the initial stage of the dynamics. We expect that these results will provide insight into the understanding of the dynamics of more realistic models with randomness in parameters and time-dependent magnetic fields.

  5. Finding Furfural Hydrogenation Catalysts via Predictive Modelling.

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-09-10

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (k(H):k(D)=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R(2)=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model's predictions, demonstrating the validity and value of predictive modelling in catalyst optimization.

  6. Genomic value prediction for quantitative traits under the epistatic model

    Directory of Open Access Journals (Sweden)

    Xu Shizhong

    2011-01-01

    Full Text Available Abstract Background Most quantitative traits are controlled by multiple quantitative trait loci (QTL. The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects and marker pairs (epistatic effects to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement. Results In this study, we created 126 recombinant inbred lines of soybean and genotyped 80 makers across the genome. We applied the genome selection technique to predict the genomic value of somatic embryo number (a quantitative trait for each line. Cross validation analysis showed that the squared correlation coefficient between the observed and predicted embryo numbers was 0.33 when only main (additive effects were used for prediction. When the interaction (epistatic effects were also included in the model, the squared correlation coefficient reached 0.78. Conclusions This study provided an excellent example for the application of genome selection to plant breeding.

  7. Corporate prediction models, ratios or regression analysis?

    NARCIS (Netherlands)

    Bijnen, E.J.; Wijn, M.F.C.M.

    1994-01-01

    The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in

  8. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

  9. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  10. Comparative Study of Bancruptcy Prediction Models

    Directory of Open Access Journals (Sweden)

    Isye Arieshanti

    2013-09-01

    Full Text Available Early indication of bancruptcy is important for a company. If companies aware of  potency of their bancruptcy, they can take a preventive action to anticipate the bancruptcy. In order to detect the potency of a bancruptcy, a company can utilize a a model of bancruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully. Because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for bancruptcy prediction. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP, Hybrid of MLP + Multiple Linear Regression, it can be showed that fuzzy k-NN method achieve the best performance with accuracy 77.5%

  11. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  12. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  13. Finding Furfural Hydrogenation Catalysts via Predictive Modelling

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-01-01

    Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

  14. Wind farm production prediction - The Zephyr model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)

    2002-06-01

    This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)

  15. Too Much Matching: A Social Relations Model Enhancement of the Pairing Game

    Science.gov (United States)

    Eastwick, Paul W.; Buck, April A.

    2014-01-01

    The Pairing Game is a popular classroom demonstration that illustrates how people select romantic partners who approximate their own desirability. However, this game produces matching correlations that greatly exceed the correlations that characterize actual romantic pairings, perhaps because the game does not incorporate the social relations…

  16. Comparison of muon-pair production to the quark-antiquark annihilation model

    International Nuclear Information System (INIS)

    Hogan, G.E.; Anderson, K.J.; Coleman, R.N.; Karhi, K.P.; McDonald, K.T.; Newman, C.B.; Pilcher, J.E.; Rosenberg, E.I.; Sanders, G.H.; Smith, A.J.S.; Thaler, J.J.

    1979-01-01

    New data on muon-pair production at 225 GeV/c by π - , π + , and proton beams are analyzed with regard to the production mechanism. The observed spin alignment of the pair and the dependence of the cross section on beam-particle type are strong indications that the production is through electromagnetic quark-antiquark annihilation

  17. PENGARUH PELAKSANAAN MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SHARE TERHADAP HASIL BELAJAR IPS SISWA

    Directory of Open Access Journals (Sweden)

    andi fathur asdar

    2016-08-01

    Full Text Available The objective of this research was to describe: 1 Teacher ability in the implementation of cooperative learning Think Pair Share, 2 Ttudent activities in the implementation of cooperative learning Think Pair Share, 3 Tearning result on IPS before and after the implementation of cooperative learning Think Pair Share, 4 learning result on IPS before and after learning process with lecture method, 5 to find out the influence of the implementation of cooperative learning Think Pair Share toward learning result on IPS. The method used was true experiment with pre-test post-test control group design. The population in the study are 4th grade student at SDN Sungguminasa II Somba Opu District Gowa Regency. Samples used are 40 student 20 student each from experiment and comparing group. chosen by simple random sampling. The data obtained from samples were analyzed with descritive and inferensial statistic. The result shows: 1 teacher ability in the implementation of cooperative learning Think Pair Share have increased, 2 student activities in the implementation of cooperative learning Think Pair Share, 3 student learning result who teached by cooperative learning Think Pair Share have increased, 4 student learning result who teached by lecture method have not increased, 5 the implementation of cooperative learning Think Pair Share is influencing toward learning result on IPS in 4th grade student at SDN Sungguminasa II Somba Opu District Gowa Regency.

  18. Eliciting hyperparameters of prior distributions for the parameters of paired comparison models

    Directory of Open Access Journals (Sweden)

    Nasir Abbas

    2013-02-01

    Full Text Available Normal 0 false false false EN-US X-NONE AR-SA In the study of paired comparisons (PC, items may be ranked or issues may be prioritized through subjective assessment of certain judges. PC models are developed and then used to serve the purpose of ranking. The PC models may be studied through classical or Bayesian approach. Bayesian inference is a modern statistical technique used to draw conclusions about the population parameters. Its beauty lies in incorporating prior information about the parameters into the analysis in addition to current information (i.e. data. The prior and current information are formally combined to yield a posterior distribution about the population parameters, which is the work bench of the Bayesian statisticians. However, the problems the Bayesians face correspond to the selection and formal utilization of prior distribution. Once the type of prior distribution is decided to be used, the problem of estimating the parameters of the prior distribution (i.e. elicitation still persists. Different methods are devised to serve the purpose. In this study an attempt is made to use Minimum Chi-square (hence forth MCS for the elicitation purpose. Though it is a classical estimation technique, but is used here for the election purpose. The entire elicitation procedure is illustrated through a numerical data set.

  19. Feature-opinion pair identification of product reviews in Chinese: a domain ontology modeling method

    Science.gov (United States)

    Yin, Pei; Wang, Hongwei; Guo, Kaiqiang

    2013-03-01

    With the emergence of the new economy based on social media, a great amount of consumer feedback on particular products are conveyed through wide-spreading product online reviews, making opinion mining a growing interest for both academia and industry. According to the characteristic mode of expression in Chinese, this research proposes an ontology-based linguistic model to identify the basic appraisal expression in Chinese product reviews-"feature-opinion pair (FOP)." The product-oriented domain ontology is constructed automatically at first, then algorithms to identify FOP are designed by mapping product features and opinions to the conceptual space of the domain ontology, and finally comparative experiments are conducted to evaluate the model. Experimental results indicate that the performance of the proposed approach in this paper is efficient in obtaining a more accurate result compared to the state-of-art algorithms. Furthermore, through identifying and analyzing FOPs, the unstructured product reviews are converted into structured and machine-sensible expression, which provides valuable information for business application. This paper contributes to the related research in opinion mining by developing a solid foundation for further sentiment analysis at a fine-grained level and proposing a general way for automatic ontology construction.

  20. Investigation of the chiral antiferromagnetic Heisenberg model using projected entangled pair states

    Science.gov (United States)

    Poilblanc, Didier

    2017-09-01

    A simple spin-1/2 frustrated antiferromagnetic Heisenberg model (AFHM) on the square lattice—including chiral plaquette cyclic terms—was argued [A. E. B. Nielsen, G. Sierra, and J. I. Cirac, Nat. Commun. 4, 2864 (2013), 10.1038/ncomms3864] to host a bosonic Kalmeyer-Laughlin (KL) fractional quantum Hall ground state [V. Kalmeyer and R. B. Laughlin, Phys. Rev. Lett. 59, 2095 (1987), 10.1103/PhysRevLett.59.2095]. Here, we construct generic families of chiral projected entangled pair states (chiral PEPS) with low bond dimension (D =3 ,4 ,5 ) which, upon optimization, provide better variational energies than the KL Ansatz. The optimal D =3 PEPS exhibits chiral edge modes described by the Wess-Zumino-Witten SU(2) 1 model, as expected for the KL spin liquid. However, we find evidence that, in contrast to the KL state, the PEPS spin liquids have power-law dimer-dimer correlations and exhibit a gossamer long-range tail in the spin-spin correlations. We conjecture that these features are genuine to local chiral AFHM on bipartite lattices.

  1. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2011-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  2. A study of electron-positron pair equilibria in models of compact X- and gamma-ray sources

    International Nuclear Information System (INIS)

    Bjoernsson, G.

    1990-01-01

    Thermal electron-positron pair equilibria in two temperature models of compact x ray and gamma ray sources are studied. The pairs are assumed to be heated by Coulomb interaction with the much hotter protons and cooled by bremsstrahlung emission, Compton scattering, and annihilation. Two parameters, the proton optical depth and the compactness, characterize each equilibrium state. It is shown that a careful account of the energy balance is very important when the stability properties of the pair equilibria in a spherical plasma cloud are determined. The equilibria are found to be unstable in a very limited range of compactness and proton optical depth. This particular instability is unlikely to be the cause of the observed variability of the compact sources and implies that it is possible to build up high pair densities by a thermal mechanism in two temperature environments. The most important result considers the effects of pairs on the structure of geometrically and effectively optically thin accretion disks. A new approach for solving for the equilibrium structure of the disks is presented. In effect, the pair equilibrium states are projected into the space spanned by the disk structure parameters. This allows a direct visualization of all possible disk solutions at once. Each solution profile needs to be calculated only once and a complete disk solution is obtained by a simple radial coordinate transformation. The disk solutions are thus seen to be scale free in terms of the radial coordinate as well as in terms of the mass of the central object and the accretion rate. Two particular disk solutions are given. It is shown that including electron-positron pairs in the disk structure calculations leads to a breakdown of the thin disk assumptions and that more detailed disk modeling is required before electron-positron pairs can be self-consistently included

  3. Simulations of the Madden-Julian oscillation in four pairs of coupled and uncoupled global models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Chidong; Dong, Min [RSMAS, University of Miami, Miami, FL (United States); Gualdi, Silvio [National Institute of Geophysics and Volcanology, Bologna (Italy); Hendon, Harry H. [BMRC, Melbourne, VIC (Australia); Maloney, Eric D. [Oregon State University, Corvallis, OR (United States); Marshall, Andrew [Monash University, Melbourne, VIC (Australia); Sperber, Kenneth R. [PCMDI, Lawrence Livermore National Laboratory, Livermore, CA (United States); Wang, Wanqiu [CPC/NCEP/NOAA, Camp Springs, MD (United States)

    2006-11-15

    The status of the numerical reproduction of the Madden-Julian Oscillation (MJO) by current global models was assessed through diagnoses of four pairs of coupled and uncoupled simulations. Slow eastward propagation of the MJO, especially in low-level zonal wind, is realistic in all these simulations. However, the simulated MJO suffers from several common problems. The MJO signal in precipitation is generally too weak and often eroded by an unrealistic split of an equatorial maximum of precipitation into a double ITCZ structure over the western Pacific. The MJO signal in low-level zonal wind, on the other hand, is sometimes too strong over the eastern Pacific but too weak over the Indian Ocean. The observed phase relationship between precipitation and low-level zonal wind associated with the MJO in the western Pacific and their coherence in general are not reproduced by the models. The seasonal migration in latitude of MJO activity is missing in most simulations. Air-sea coupling generally strengthens the simulated eastward propagating signal, but its effects on the phase relationship and coherence between precipitation and low-level zonal wind, and on their geographic distributions, seasonal cycles, and interannual variability are inconsistent among the simulations. Such inconsistency cautions generalization of results from MJO simulations using a single model. In comparison to observations, biases in the simulated MJO appear to be related to biases in the background state of mean precipitation, low-level zonal wind, and boundary-layer moisture convergence. This study concludes that, while the realistic simulations of the eastward propagation of the MJO are encouraging, reproducing other fundamental features of the MJO by current global models remains an unmet challenge. (orig.)

  4. Pair correlation function decay in models of simple fluids that contain dispersion interactions.

    Science.gov (United States)

    Evans, R; Henderson, J R

    2009-11-25

    We investigate the intermediate-and longest-range decay of the total pair correlation function h(r) in model fluids where the inter-particle potential decays as -r(-6), as is appropriate to real fluids in which dispersion forces govern the attraction between particles. It is well-known that such interactions give rise to a term in q(3) in the expansion of [Formula: see text], the Fourier transform of the direct correlation function. Here we show that the presence of the r(-6) tail changes significantly the analytic structure of [Formula: see text] from that found in models where the inter-particle potential is short ranged. In particular the pure imaginary pole at q = iα(0), which generates monotonic-exponential decay of rh(r) in the short-ranged case, is replaced by a complex (pseudo-exponential) pole at q = iα(0)+α(1) whose real part α(1) is negative and generally very small in magnitude. Near the critical point α(1)∼-α(0)(2) and we show how classical Ornstein-Zernike behaviour of the pair correlation function is recovered on approaching the mean-field critical point. Explicit calculations, based on the random phase approximation, enable us to demonstrate the accuracy of asymptotic formulae for h(r) in all regions of the phase diagram and to determine a pseudo-Fisher-Widom (pFW) line. On the high density side of this line, intermediate-range decay of rh(r) is exponentially damped-oscillatory and the ultimate long-range decay is power-law, proportional to r(-6), whereas on the low density side this damped-oscillatory decay is sub-dominant to both monotonic-exponential and power-law decay. Earlier analyses did not identify the pseudo-exponential pole and therefore the existence of the pFW line. Our results enable us to write down the generic wetting potential for a 'real' fluid exhibiting both short-ranged and dispersion interactions. The monotonic-exponential decay of correlations associated with the pseudo-exponential pole introduces additional terms into

  5. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  6. EFEKTIVITAS PENERAPAN MODEL PEMBELAJARAN THINK PAIR SHARE (TPS TERHADAP HASIL BELAJAR DAN AKTIVITAS SISWA PADA MATERI SISTEM PERNAPASAN MANUSIA

    Directory of Open Access Journals (Sweden)

    Maria Yashinta Afoan

    2016-10-01

    Tujuan dari penelitian ini adalah untuk mengetahui efektivitas penerapan model pembelajaran kooperatif melalui pendekatan Think Pair Share terhadap hasil belajar dan aktivitas siswa. Data dikumpulkan melalui wawancara dan tes esai hasil belajar. Data hasil wawancara dianalisis secara deskriptif kualitatif, sedangkan tes esai hasil belajar dianalisis secara deskriptif kuantitatif. Hasil penelitian menunjukkan bahwa penerapan model pembelajaran Think Pair Share (TPS efektif dapat meningkatkan hasil belajar siswa. Hal ini dilihat dari rata-rata pretest sebesar 34,06% mengalami peningkatan pada posttest sebesar 83,13 % dengan rata-rata peningkatann pretest ke posttest sebesar 49,06 %, dan ketuntasan klasikal hasil belajar sebesar 87,50% begitu juga dengan penerapan model pembelajaran Think Pair Share (TPS aktivitas belajar siswa dapat ditingkatkan.

  7. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. PREDICTIVE CAPACITY OF ARCH FAMILY MODELS

    Directory of Open Access Journals (Sweden)

    Raphael Silveira Amaro

    2016-03-01

    Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.

  9. Alcator C-Mod predictive modeling

    International Nuclear Information System (INIS)

    Pankin, Alexei; Bateman, Glenn; Kritz, Arnold; Greenwald, Martin; Snipes, Joseph; Fredian, Thomas

    2001-01-01

    Predictive simulations for the Alcator C-mod tokamak [I. Hutchinson et al., Phys. Plasmas 1, 1511 (1994)] are carried out using the BALDUR integrated modeling code [C. E. Singer et al., Comput. Phys. Commun. 49, 275 (1988)]. The results are obtained for temperature and density profiles using the Multi-Mode transport model [G. Bateman et al., Phys. Plasmas 5, 1793 (1998)] as well as the mixed-Bohm/gyro-Bohm transport model [M. Erba et al., Plasma Phys. Controlled Fusion 39, 261 (1997)]. The simulated discharges are characterized by very high plasma density in both low and high modes of confinement. The predicted profiles for each of the transport models match the experimental data about equally well in spite of the fact that the two models have different dimensionless scalings. Average relative rms deviations are less than 8% for the electron density profiles and 16% for the electron and ion temperature profiles

  10. Three-dimensional structure discrepancy between HLA alleles for effective prediction of aGVHD severity and optimal selection of recipient-donor pairs: a proof-of-concept study.

    Science.gov (United States)

    Han, Hongxing; Yuan, Fang; Sun, Yuying; Liu, Jinfeng; Liu, Shuguang; Luo, Yuan; Liang, Fei; Liu, Nan; Long, Juan; Zhao, Xiao; Kong, Fanhua; Xi, Yongzhi

    2015-11-24

    The optimal selection of recipient-donor pair and accurate prediction of acute graft-versus-host disease (aGVHD) severity are always the two most crucial works in allogeneic hematopoietic stem cell transplantation (allo-HSCT), which currently rests mostly with HLA compatibility, the most polymorphic loci in the human genome, in clinic. Thus, there is an urgent need for a rapid and reliable quantitative system for optimal recipient-donor pairs selection and accurate prediction of aGVHD severity prior to allo-HSCT. For these reasons, we have developed a new selection/prediction system for optimal recipient-donor selection and effective prediction of aGVHD severity based on HLA three-dimensional (3D) structure modeling (HLA-TDSM) discrepancy, and applied this system in a pilot randomized clinical allo-HSCT study. The 37 patient-donor pairs in the study were typed at low- and high-resolution levels for HLA-A/-B/-DRB1/-DQB1 loci. HLA-TDSM system covering the 10000 alleles in HLA class I and II consists of the revised local and coordinate root-mean-square deviation (RMSD) values for each locus. Its accuracy and reliability were confirmed using stably transfected Hmy2.CIR-HLA-B cells, TCR Vβ gene scan, and antigen-specific alloreactive cytotoxic lymphocytes. Based on the preliminary results, we theoretically defined all HLA acceptable versus unacceptable mismatched alleles. More importantly, HLA-TDSM enabled a successful retrospective verification and prospective prediction for aGVHD severity in a pilot randomized clinical allo-HSCT study of 32 recipient-donor transplant pairs. There was a strong direct correlation between single/total revised RMSD and aGVHD severity (92% in retrospective group vs 95% in prospective group). These results seem to be closely related to the 3D structure discrepancy of mismatched HLA-alleles, but not the number or loci of mismatched HLA-alleles. Our data first provide the proof-of-concept that HLA-TDSM is essential for optimal selection of

  11. PENINGKATAN MOTIVASI DAN HASIL BELAJAR MELALUI MODEL PEMBELAJARAN THINK PAIR SHARE BERBANTUAN MEDIA GAMBAR DI SEKOLAH DASAR

    Directory of Open Access Journals (Sweden)

    Yonarlianto Tembang

    2017-06-01

    Penelitian ini bertujuan untuk mengetahui peningkatan motivasi dan hasil belajar siswa dengan menggunakan model pembelajaran think pair share berbantuan media gambar. Subjek penelitian ini adalah siswa kelas IV SD Inpres Mangga Dua Merauke. Teknik analisis menggunakan analisis deskriptif. Pengumpulan data menggunakan observasi, angket, dan tes. Hasil penelitian ini terdapat peningkatan motivasi belajar siswa rata-rata 74,91% pada siklus I menjadi 87,27% pada siklus 2. Peningkatan hasil belajar kognitif siswa meningkat pada siklus I sebesar 68,81% pada siklus II mencapai 86,36%. Dengan demikian, hasil ini menunjukkan bahwa melalui model pembelajaran think pair share berbantuan media gambar dapat meningkatkan motivasi dan hasil belajar siswa.

  12. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  13. PENERAPAN MODEL THINK PAIR SHARE BERBANTUAN MEDIA UNTUK MENINGKATKAN AKTIVITAS, SIKAP, DAN HASIL BELAJAR IPS

    Directory of Open Access Journals (Sweden)

    Muhamad Ngafifi

    2014-03-01

    Full Text Available Penelitian ini bertujuan untuk meningkatkan: (1 Aktivitas Belajar Siswa, (2 Sikap Siswa, dan (3 Hasil Belajar IPS siswa kelas VIII B SMP Negeri 2 Sukoharjo, Wonosobo. Penelitian ini merupakan penelitian tindakan kelas (PTK yang terlaksana dalam dua siklus dengan menggunakan desain Kemmis & Taggart. Teknik pengumpulan data yang digunakan adalah observasi, tes hasil belajar, angket, dokumentasi, dan catatan lapangan. Teknik analisis data menggunakan analisis deskriptif kuantitatif. Hasil penelitian ini adalah: (1 Terjadi peningkatan aktivitas belajar siswa; pada akhir siklus I dengan rata-rata 67,84 menjadi 81,20 pada akhir siklus II. (2 Ada peningkatan nilai sikap siswa. Rata-rata nilai sikap siswa pada akhir siklus I 77,20 menjadi 84,49 pada akhir siklus II. (3 Terjadi Peningkatan hasil belajar dari kondisi awal dengan nilai rata-rata 65,58, pada akhir siklus I menjadi 79,10, dan pada akhir siklus II menjadi 85,90.Kata Kunci: model Think Pair Share, media pembelajaran, hasil belajar

  14. PENERAPAN MODEL PEMBELAJARAN THINK PAIR SHARE UNTUK MENINGKATKAN HASIL BELAJAR IPA SISWA

    Directory of Open Access Journals (Sweden)

    Sudirman Sudirman

    2016-03-01

    Full Text Available Learning science in junior high school raises many problems found on direct instruction, students learn such activity is very low. Students lacking the spirit to learn science, pretend to understand the teacher's explanations. Students in learning activities mediocre both classical learning and teamwork that ultimately student learning outcomes many incompletes. To overcome this, then do action research in order to improve the results of junior high school students learn science through learning model Think Pair Share for Class VIII.1 second-semester students of SMP Negeri 2 Metro in the academic year 2012/2013. This study time is 3 months. Based on the recapitulation of the data observation learning process and the work of the group, the student learning outcomes can be summarized as follows. In observation of the learning process from the first meeting until the meeting of the 6th, there is increased an activity of students in learning. This happened after learning that teachers undertake improvements at each meeting.

  15. Comparison of two ordinal prediction models

    DEFF Research Database (Denmark)

    Kattan, Michael W; Gerds, Thomas A

    2015-01-01

    system (i.e. old or new), such as the level of evidence for one or more factors included in the system or the general opinions of expert clinicians. However, given the major objective of estimating prognosis on an ordinal scale, we argue that the rival staging system candidates should be compared...... on their ability to predict outcome. We sought to outline an algorithm that would compare two rival ordinal systems on their predictive ability. RESULTS: We devised an algorithm based largely on the concordance index, which is appropriate for comparing two models in their ability to rank observations. We...... demonstrate our algorithm with a prostate cancer staging system example. CONCLUSION: We have provided an algorithm for selecting the preferred staging system based on prognostic accuracy. It appears to be useful for the purpose of selecting between two ordinal prediction models....

  16. Dietary lead intakes for mother/child pairs and relevance to pharmacokinetic models.

    Science.gov (United States)

    Gulson, B L; Mahaffey, K R; Vidal, M; Jameson, C W; Law, A J; Mizon, K J; Smith, A J; Korsch, M J

    1997-12-01

    Blood and environmental samples, including a quarterly 6-day duplicate diet, for nine mother/child pairs from Eastern Europe have been monitored for 12 to >24 months with high precision stable lead isotope analysis to evaluate the changes that occur when the subjects moved from one environment (Eastern Europe) to another with different stable lead isotopes (Australia). The children were between 6 and 11 years of age and the mothers were between 29 and 37 years of age. These data were compared with an Australian control mother/child pair, aged 31 and 6 years, respectively. A rationale for undertaking this study of mother/child pairs was to evaluate if there were differences in the patterns and clearance rates of lead from blood in children compared with their mothers. Blood lead concentrations ranged from 2.1 to 3.9 microg/dl in the children and between 1.8 and 4.5 microg/dl in the mothers, but the mean of differences between each mother and her child did not differ significantly from zero. Duplicate diets contained from 2.4 to 31.8 microg Pb/kg diet; the mean+/- standard deviation was 5.5 +/- 2.1 microg Pb/kg and total daily dietary intakes ranged from 1.6 to 21.3 microg/day. Mean daily dietary intakes relative to body weight showed that the intake for children was approximately double that for the mothers (0.218 vs. 0. 113 microg Pb/kg body weight/day). The correlations between blood lead concentration and mean daily dietary intake either relative to body weight or total dietary intake did not reach statistical significance (p>0.05). Estimation of the lead coming from skeletal (endogenous) sources relative to the contribution from environmental (exogenous) sources ranges from 8 to 70% for the mothers and 12 to 66% for the children. The difference between mothers and children is not statistically significant (p = 0.28). The children do not appear to achieve the Australian lead isotopic profile at a faster rate than their mothers. These data provide evidence that

  17. Outputs of paired Gabor filters summed across the background frame of reference predict the direction of movement

    Science.gov (United States)

    Lawton, Teri B.

    1989-01-01

    A cortical neural network that computes the visibility of shifts in the direction of movement is proposed. The network computes: (1) the magnitude of the position difference between the test and background patterns, (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern, and (3) using global processes that pool the output from paired even- and odd-symmetric simple and complex cells across the spatial extent of the background frame of reference the direction a test pattern moved relative to a textured background. Evidence that magnocellular pathways are used to discriminate the direction of movement is presented. Since magnocellular pathways are used to discriminate the direction of movement, this task is not affected by small pattern changes such as jitter, short presentations, blurring, and different background contrasts that result when the veiling illumination in a scene changes.

  18. Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

    Science.gov (United States)

    Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

    2015-09-01

    Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

  19. Inferring microRNA regulation of mRNA with partially ordered samples of paired expression data and exogenous prediction algorithms.

    Directory of Open Access Journals (Sweden)

    Brian Godsey

    Full Text Available MicroRNAs (miRs are known to play an important role in mRNA regulation, often by binding to complementary sequences in "target" mRNAs. Recently, several methods have been developed by which existing sequence-based target predictions can be combined with miR and mRNA expression data to infer true miR-mRNA targeting relationships. It has been shown that the combination of these two approaches gives more reliable results than either by itself. While a few such algorithms give excellent results, none fully addresses expression data sets with a natural ordering of the samples. If the samples in an experiment can be ordered or partially ordered by their expected similarity to one another, such as for time-series or studies of development processes, stages, or types, (e.g. cell type, disease, growth, aging, there are unique opportunities to infer miR-mRNA interactions that may be specific to the underlying processes, and existing methods do not exploit this. We propose an algorithm which specifically addresses [partially] ordered expression data and takes advantage of sample similarities based on the ordering structure. This is done within a Bayesian framework which specifies posterior distributions and therefore statistical significance for each model parameter and latent variable. We apply our model to a previously published expression data set of paired miR and mRNA arrays in five partially ordered conditions, with biological replicates, related to multiple myeloma, and we show how considering potential orderings can improve the inference of miR-mRNA interactions, as measured by existing knowledge about the involved transcripts.

  20. Possibility of ΛΛ pairing and its dependence on background density in a relativistic Hartree-Bogoliubov model

    International Nuclear Information System (INIS)

    Tanigawa, Tomonori; Matsuzaki, Masayuki; Chiba, Satoshi

    2003-01-01

    We calculate a ΛΛ pairing gap in binary mixed matter of nucleons and Λ hyperons within the relativistic Hartree-Bogoliubov model. Λ hyperons to be paired up are immersed in background nucleons in a normal state. The gap is calculated with a one-boson-exchange interaction obtained from a relativistic Lagrangian. It is found that at background density ρ N =2.5ρ 0 the ΛΛ pairing gap is very small, and that a denser background makes it rapidly suppressed. This result suggests a mechanism, specific to mixed matter dealt with relativistic models, of its dependence on the nucleon density. An effect of weaker ΛΛ attraction on the gap is also examined in connection with the revised information of the ΛΛ interaction

  1. Predictive analytics can support the ACO model.

    Science.gov (United States)

    Bradley, Paul

    2012-04-01

    Predictive analytics can be used to rapidly spot hard-to-identify opportunities to better manage care--a key tool in accountable care. When considering analytics models, healthcare providers should: Make value-based care a priority and act on information from analytics models. Create a road map that includes achievable steps, rather than major endeavors. Set long-term expectations and recognize that the effectiveness of an analytics program takes time, unlike revenue cycle initiatives that may show a quick return.

  2. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  3. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  4. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  5. EM Transition Sum Rules Within the Framework of sdg Proton-Neutron Interacting Boson Model, Nuclear Pair Shell Model and Fermion Dynamical Symmetry Model

    Science.gov (United States)

    Zhao, Yumin

    1997-07-01

    By the techniques of the Wick theorem for coupled clusters, the no-energy-weighted electromagnetic sum-rule calculations are presented in the sdg neutron-proton interacting boson model, the nuclear pair shell model and the fermion-dynamical symmetry model. The project supported by Development Project Foundation of China, National Natural Science Foundation of China, Doctoral Education Fund of National Education Committee, Fundamental Research Fund of Southeast University

  6. A stepwise model to predict monthly streamflow

    Science.gov (United States)

    Mahmood Al-Juboori, Anas; Guven, Aytac

    2016-12-01

    In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

  7. RNAHelix: computational modeling of nucleic acid structures with Watson-Crick and non-canonical base pairs.

    Science.gov (United States)

    Bhattacharyya, Dhananjay; Halder, Sukanya; Basu, Sankar; Mukherjee, Debasish; Kumar, Prasun; Bansal, Manju

    2017-02-01

    Comprehensive analyses of structural features of non-canonical base pairs within a nucleic acid double helix are limited by the availability of a small number of three dimensional structures. Therefore, a procedure for model building of double helices containing any given nucleotide sequence and base pairing information, either canonical or non-canonical, is seriously needed. Here we describe a program RNAHelix, which is an updated version of our widely used software, NUCGEN. The program can regenerate duplexes using the dinucleotide step and base pair orientation parameters for a given double helical DNA or RNA sequence with defined Watson-Crick or non-Watson-Crick base pairs. The original structure and the corresponding regenerated structure of double helices were found to be very close, as indicated by the small RMSD values between positions of the corresponding atoms. Structures of several usual and unusual double helices have been regenerated and compared with their original structures in terms of base pair RMSD, torsion angles and electrostatic potentials and very high agreements have been noted. RNAHelix can also be used to generate a structure with a sequence completely different from an experimentally determined one or to introduce single to multiple mutation, but with the same set of parameters and hence can also be an important tool in homology modeling and study of mutation induced structural changes.

  8. Electrostatic ion thrusters - towards predictive modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)

    2014-02-15

    The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  9. An Intelligent Model for Stock Market Prediction

    Directory of Open Access Journals (Sweden)

    IbrahimM. Hamed

    2012-08-01

    Full Text Available This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP Artificial Neural Networks (ANN. Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems of prediction accuracy and lack of generalization. Kullback Leibler Divergence (KLD is used, as a learning algorithm, because it converges fast and provides generalization in the learning mechanism. Both accuracy and efficiency of the proposed model were confirmed through the Microsoft stock, from wall-street market, and various data sets, from different sectors of the Egyptian stock market. In addition, sensitivity analysis was conducted on the various parameters of the model to ensure the coverage of the generalization issue. Finally, statistical significance was examined using ANOVA test.

  10. Predictive Models, How good are they?

    DEFF Research Database (Denmark)

    Kasch, Helge

    The WAD grading system has been used for more than 20 years by now. It has shown long-term viability, but with strengths and limitations. New bio-psychosocial assessment of the acute whiplash injured subject may provide better prediction of long-term disability and pain. Furthermore, the emerging......-up. It is important to obtain prospective identification of the relevant risk underreported disability could, if we were able to expose these hidden “risk-factors” during our consultations, provide us with better predictive models. New data from large clinical studies will present exciting new genetic risk markers...

  11. Pairing in a two-dimensional two-band very anisotropic model in the mean field approximation

    International Nuclear Information System (INIS)

    Fazakas, A.B.; Pitis, R.

    1993-09-01

    A two-dimensional model is proposed: there are two kinds of sites, with one electronic state per site; tunneling takes place only in one direction; the interaction involves only electrons on different sites. The existence of a phase transition involving interband pairing of electrons is discussed in the mean field approximation. (author)

  12. Jagiellonian University Searches for the Standard Model Higgs boson decay to $\\tau $ lepton pairs at the CMS experiment

    CERN Document Server

    Pyskir, Andrzej

    2017-01-01

    We present results of searches for the Standard Model Higgs boson decaying to tau lepton pairs at the CMS experiment with data collected during the LHC Run 1. We also present some insight into the analysis with Run 2 data. CP sensitive variables are described and an experimental method of probing CP of the Higgs boson is presented.

  13. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    SILVA R. G.

    1999-01-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  14. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

  15. A computational model that predicts behavioral sensitivity to intracortical microstimulation

    Science.gov (United States)

    Kim, Sungshin; Callier, Thierri; Bensmaia, Sliman J.

    2017-02-01

    Objective. Intracortical microstimulation (ICMS) is a powerful tool to investigate the neural mechanisms of perception and can be used to restore sensation for patients who have lost it. While sensitivity to ICMS has previously been characterized, no systematic framework has been developed to summarize the detectability of individual ICMS pulse trains or the discriminability of pairs of pulse trains. Approach. We develop a simple simulation that describes the responses of a population of neurons to a train of electrical pulses delivered through a microelectrode. We then perform an ideal observer analysis on the simulated population responses to predict the behavioral performance of non-human primates in ICMS detection and discrimination tasks. Main results. Our computational model can predict behavioral performance across a wide range of stimulation conditions with high accuracy (R 2 = 0.97) and generalizes to novel ICMS pulse trains that were not used to fit its parameters. Furthermore, the model provides a theoretical basis for the finding that amplitude discrimination based on ICMS violates Weber’s law. Significance. The model can be used to characterize the sensitivity to ICMS across the range of perceptible and safe stimulation regimes. As such, it will be a useful tool for both neuroscience and neuroprosthetics.

  16. A pair natural orbital implementation of the coupled cluster model CC2 for excitation energies.

    Science.gov (United States)

    Helmich, Benjamin; Hättig, Christof

    2013-08-28

    We demonstrate how to extend the pair natural orbital (PNO) methodology for excited states, presented in a previous work for the perturbative doubles correction to configuration interaction singles (CIS(D)), to iterative coupled cluster methods such as the approximate singles and doubles model CC2. The original O(N(5)) scaling of the PNO construction is reduced by using orbital-specific virtuals (OSVs) as an intermediate step without spoiling the initial accuracy of the PNO method. Furthermore, a slower error convergence for charge-transfer states is analyzed and resolved by a numerical Laplace transformation during the PNO construction, so that an equally accurate treatment of local and charge-transfer excitations is achieved. With state-specific truncated PNO expansions, the eigenvalue problem is solved by combining the Davidson algorithm with deflation to project out roots that have already been determined and an automated refresh with a generation of new PNOs to achieve self-consistency of the PNO space. For a large test set, we found that truncation errors for PNO-CC2 excitation energies are only slightly larger than for PNO-CIS(D). The computational efficiency of PNO-CC2 is demonstrated for a large organic dye, where a reduction of the doubles space by a factor of more than 1000 is obtained compared to the canonical calculation. A compression of the doubles space by a factor 30 is achieved by a unified OSV space only. Moreover, calculations with the still preliminary PNO-CC2 implementation on a series of glycine oligomers revealed an early break even point with a canonical RI-CC2 implementation between 100 and 300 basis functions.

  17. Updated predictions for the total production cross sections of top and of heavier quark pairs at the Tevatron and at the LHC

    CERN Document Server

    Cacciari, Matteo; Mangano, Michelangelo L; Nason, Paolo; Ridolfi, Giovanni

    2008-01-01

    We present updated predictions for the total production cross section of top-quark pairs at the Tevatron and at the LHC, and, at the LHC, of heavy-quark pairs with mass in the range 0.5-2 TeV. For t\\bar{t} production at the LHC we also present results at \\sqrt{S}= 10 TeV, in view of the expected accelerator conditions during the forthcoming 2008 run. Our results are accurate at the level of next-to-leading order in alpha_s, and of next-to-leading threshold logarithms (NLO+NLL). We adopt the most recent parametrizations of parton distribution functions, and compute the corresponding uncertainties. We study the dependence of the results on the top mass, and we assess the impact of missing higher-order corrections by independent variations of factorisation and renormalisation scales.

  18. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to

  19. Tevatron constraints on models of the Higgs boson with exotic spin and parity using decays to bottom-antibottom quark pairs.

    Science.gov (United States)

    Aaltonen, T; Abazov, V M; Abbott, B; Acharya, B S; Adams, M; Adams, T; Agnew, J P; Alexeev, G D; Alkhazov, G; Alton, A; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Askew, A; Atkins, S; Auerbach, B; Augsten, K; Aurisano, A; Avila, C; Azfar, F; Badaud, F; Badgett, W; Bae, T; Bagby, L; Baldin, B; Bandurin, D V; Banerjee, S; Barbaro-Galtieri, A; Barberis, E; Baringer, P; Barnes, V E; Barnett, B A; Barria, P; Bartlett, J F; Bartos, P; Bassler, U; Bauce, M; Bazterra, V; Bean, A; Bedeschi, F; Begalli, M; Behari, S; Bellantoni, L; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beri, S B; Bernardi, G; Bernhard, R; Bertram, I; Besançon, M; Beuselinck, R; Bhat, P C; Bhatia, S; Bhatnagar, V; Bhatti, A; Bland, K R; Blazey, G; Blessing, S; Bloom, K; Blumenfeld, B; Bocci, A; Bodek, A; Boehnlein, A; Boline, D; Boos, E E; Borissov, G; Bortoletto, D; Borysova, M; Boudreau, J; Boveia, A; Brandt, A; Brandt, O; Brigliadori, L; Brock, R; Bromberg, C; Bross, A; Brown, D; Brucken, E; Bu, X B; Budagov, J; Budd, H S; Buehler, M; Buescher, V; Bunichev, V; Burdin, S; Burkett, K; Busetto, G; Bussey, P; Buszello, C P; Butti, P; Buzatu, A; Calamba, A; Camacho-Pérez, E; Camarda, S; Campanelli, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Casal, B; Casarsa, M; Casey, B C K; Castilla-Valdez, H; Castro, A; Catastini, P; Caughron, S; Cauz, D; Cavaliere, V; Cerri, A; Cerrito, L; Chakrabarti, S; Chan, K M; Chandra, A; Chapon, E; Chen, G; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Cho, K; Cho, S W; Choi, S; Chokheli, D; Choudhary, B; Cihangir, S; Claes, D; Clark, A; Clarke, C; Clutter, J; Convery, M E; Conway, J; Cooke, M; Cooper, W E; Corbo, M; Corcoran, M; Cordelli, M; Couderc, F; Cousinou, M-C; Cox, C A; Cox, D J; Cremonesi, M; Cruz, D; Cuevas, J; Culbertson, R; Cutts, D; Das, A; d'Ascenzo, N; Datta, M; Davies, G; de Barbaro, P; de Jong, S J; De La Cruz-Burelo, E; Déliot, F; Demina, R; Demortier, L; Deninno, M; Denisov, D; Denisov, S P; D'Errico, M; Desai, S; Deterre, C; DeVaughan, K; Devoto, F; Di Canto, A; Di Ruzza, B; Diehl, H T; Diesburg, M; Ding, P F; Dittmann, J R; Dominguez, A; Donati, S; D'Onofrio, M; Dorigo, M; Driutti, A; Dubey, A; Dudko, L V; Duperrin, A; Dutt, S; Eads, M; Ebina, K; Edgar, R; Edmunds, D; Elagin, A; Ellison, J; Elvira, V D; Enari, Y; Erbacher, R; Errede, S; Esham, B; Evans, H; Evdokimov, V N; Farrington, S; Fauré, A; Feng, L; Ferbel, T; Fernández Ramos, J P; Fiedler, F; Field, R; Filthaut, F; Fisher, W; Fisk, H E; Flanagan, G; Forrest, R; Fortner, M; Fox, H; Franklin, M; Freeman, J C; Frisch, H; Fuess, S; Funakoshi, Y; Galloni, C; Garbincius, P H; Garcia-Bellido, A; García-González, J A; Garfinkel, A F; Garosi, P; Gavrilov, V; Geng, W; Gerber, C E; Gerberich, H; Gerchtein, E; Gershtein, Y; Giagu, S; Giakoumopoulou, V; Gibson, K; Ginsburg, C M; Ginther, G; Giokaris, N; Giromini, P; Glagolev, V; Glenzinski, D; Gogota, O; Gold, M; Goldin, D; Golossanov, A; Golovanov, G; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González López, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gramellini, E; Grannis, P D; Greder, S; Greenlee, H; Grenier, G; Gris, Ph; Grivaz, J-F; Grohsjean, A; Grosso-Pilcher, C; Group, R C; Grünendahl, S; Grünewald, M W; Guillemin, T; Guimaraes da Costa, J; Gutierrez, G; Gutierrez, P; Hahn, S R; Haley, J; Han, J Y; Han, L; Happacher, F; Hara, K; Harder, K; Hare, M; Harel, A; Harr, R F; Harrington-Taber, T; Hatakeyama, K; Hauptman, J M; Hays, C; Hays, J; Head, T; Hebbeker, T; Hedin, D; Hegab, H; Heinrich, J; Heinson, A P; Heintz, U; Hensel, C; Heredia-De La Cruz, I; Herndon, M; Herner, K; Hesketh, G; Hildreth, M D; Hirosky, R; Hoang, T; Hobbs, J D; Hocker, A; Hoeneisen, B; Hogan, J; Hohlfeld, M; Holzbauer, J L; Hong, Z; Hopkins, W; Hou, S; Howley, I; Hubacek, Z; Hughes, R E; Husemann, U; Hussein, M; Huston, J; Hynek, V; Iashvili, I; Ilchenko, Y; Illingworth, R; Introzzi, G; Iori, M; Ito, A S; Ivanov, A; Jabeen, S; Jaffré, M; James, E; Jang, D; Jayasinghe, A; Jayatilaka, B; Jeon, E J; Jeong, M S; Jesik, R; Jiang, P; Jindariani, S; Johns, K; Johnson, E; Johnson, M; Jonckheere, A; Jones, M; Jonsson, P; Joo, K K; Joshi, J; Jun, S Y; Jung, A W; Junk, T R; Juste, A; Kajfasz, E; Kambeitz, M; Kamon, T; Karchin, P E; Karmanov, D; Kasmi, A; Kato, Y; Katsanos, I; Kaur, M; Kehoe, R; Kermiche, S; Ketchum, W; Keung, J; Khalatyan, N; Khanov, A; Kharchilava, A; Kharzheev, Y N; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S H; Kim, S B; Kim, Y J; Kim, Y K; Kimura, N; Kirby, M; Kiselevich, I; Knoepfel, K; Kohli, J M; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kozelov, A V; Kraus, J; Kreps, M; Kroll, J; Kruse, M; Kuhr, T; Kumar, A; Kupco, A; Kurata, M; Kurča, T; Kuzmin, V A; Laasanen, A T; Lammel, S; Lammers, S; Lancaster, M; Lannon, K; Latino, G; Lebrun, P; Lee, H S; Lee, H S; Lee, J S; Lee, S W; Lee, W M; Lei, X; Lellouch, J; Leo, S; Leone, S; Lewis, J D; Li, D; Li, H; Li, L; Li, Q Z; Lim, J K; Limosani, A; Lincoln, D; Linnemann, J; Lipaev, V V; Lipeles, E; Lipton, R; Lister, A; Liu, H; Liu, H; Liu, Q; Liu, T; Liu, Y; Lobodenko, A; Lockwitz, S; Loginov, A; Lokajicek, M; Lopes de Sa, R; Lucchesi, D; Lucà, A; Lueck, J; Lujan, P; Lukens, P; Luna-Garcia, R; Lungu, G; Lyon, A L; Lys, J; Lysak, R; Maciel, A K A; Madar, R; Madrak, R; Maestro, P; Magaña-Villalba, R; Malik, S; Malik, S; Malyshev, V L; Manca, G; Manousakis-Katsikakis, A; Mansour, J; Marchese, L; Margaroli, F; Marino, P; Martínez-Ortega, J; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McCarthy, R; McGivern, C L; McNulty, R; Mehta, A; Mehtala, P; Meijer, M M; Melnitchouk, A; Menezes, D; Mercadante, P G; Merkin, M; Mesropian, C; Meyer, A; Meyer, J; Miao, T; Miconi, F; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Mondal, N K; Moon, C S; Moore, R; Morello, M J; Mukherjee, A; Mulhearn, M; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nagy, E; Nakano, I; Napier, A; Narain, M; Nayyar, R; Neal, H A; Negret, J P; Nett, J; Neu, C; Neustroev, P; Nguyen, H T; Nigmanov, T; Nodulman, L; Noh, S Y; Norniella, O; Nunnemann, T; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Orduna, J; Ortolan, L; Osman, N; Osta, J; Pagliarone, C; Pal, A; Palencia, E; Palni, P; Papadimitriou, V; Parashar, N; Parihar, V; Park, S K; Parker, W; Partridge, R; Parua, N; Patwa, A; Pauletta, G; Paulini, M; Paus, C; Penning, B; Perfilov, M; Peters, Y; Petridis, K; Petrillo, G; Pétroff, P; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pleier, M-A; Podstavkov, V M; Pondrom, L; Popov, A V; Poprocki, S; Potamianos, K; Pranko, A; Prewitt, M; Price, D; Prokopenko, N; Prokoshin, F; Ptohos, F; Punzi, G; Qian, J; Quadt, A; Quinn, B; Ratoff, P N; Razumov, I; Redondo Fernández, I; Renton, P; Rescigno, M; Rimondi, F; Ripp-Baudot, I; Ristori, L; Rizatdinova, F; Robson, A; Rodriguez, T; Rolli, S; Rominsky, M; Ronzani, M; Roser, R; Rosner, J L; Ross, A; Royon, C; Rubinov, P; Ruchti, R; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Sajot, G; Sakumoto, W K; Sakurai, Y; Sánchez-Hernández, A; Sanders, M P; Santi, L; Santos, A S; Sato, K; Savage, G; Saveliev, V; Savitskyi, M; Savoy-Navarro, A; Sawyer, L; Scanlon, T; Schamberger, R D; Scheglov, Y; Schellman, H; Schlabach, P; Schmidt, E E; Schwanenberger, C; Schwarz, T; Schwienhorst, R; Scodellaro, L; Scuri, F; Seidel, S; Seiya, Y; Sekaric, J; Semenov, A; Severini, H; Sforza, F; Shabalina, E; Shalhout, S Z; Shary, V; Shaw, S; Shchukin, A A; Shears, T; Shepard, P F; Shimojima, M; Shochet, M; Shreyber-Tecker, I; Simak, V; Simonenko, A; Skubic, P; Slattery, P; Sliwa, K; Smirnov, D; Smith, J R; Snider, F D; Snow, G R; Snow, J; Snyder, S; Söldner-Rembold, S; Song, H; Sonnenschein, L; Sorin, V; Soustruznik, K; St Denis, R; Stancari, M; Stark, J; Stentz, D; Stoyanova, D A; Strauss, M; Strologas, J; Sudo, Y; Sukhanov, A; Suslov, I; Suter, L; Svoisky, P; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thomson, E; Thukral, V; Titov, M; Toback, D; Tokar, S; Tokmenin, V V; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Tsai, Y-T; Tsybychev, D; Tuchming, B; Tully, C; Ukegawa, F; Uozumi, S; Uvarov, L; Uvarov, S; Uzunyan, S; Van Kooten, R; van Leeuwen, W M; Varelas, N; Varnes, E W; Vasilyev, I A; Vázquez, F; Velev, G; Vellidis, C; Verkheev, A Y; Vernieri, C; Vertogradov, L S; Verzocchi, M; Vesterinen, M; Vidal, M; Vilanova, D; Vilar, R; Vizán, J; Vogel, M; Vokac, P; Volpi, G; Wagner, P; Wahl, H D; Wallny, R; Wang, M H L S; Wang, S M; Warchol, J; Waters, D; Watts, G; Wayne, M; Weichert, J; Welty-Rieger, L; Wester, W C; Whiteson, D; Wicklund, A B; Wilbur, S; Williams, H H; Williams, M R J; Wilson, G W; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wobisch, M; Wolbers, S; Wolfe, H; Wood, D R; Wright, T; Wu, X; Wu, Z; Wyatt, T R; Xie, Y; Yamada, R; Yamamoto, K; Yamato, D; Yang, S; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yasuda, T; Yatsunenko, Y A; Ye, W; Ye, Z; Yeh, G P; Yi, K; Yin, H; Yip, K; Yoh, J; Yorita, K; Yoshida, T; Youn, S W; Yu, G B; Yu, I; Yu, J M; Zanetti, A M; Zeng, Y; Zennamo, J; Zhao, T G; Zhou, B; Zhou, C; Zhu, J; Zielinski, M; Zieminska, D; Zivkovic, L; Zucchelli, S

    2015-04-17

    Combined constraints from the CDF and D0 Collaborations on models of the Higgs boson with exotic spin J and parity P are presented and compared with results obtained assuming the standard model value JP=0+. Both collaborations analyzed approximately 10  fb(-) of proton-antiproton collisions with a center-of-mass energy of 1.96 TeV collected at the Fermilab Tevatron. Two models predicting exotic Higgs bosons with JP=0- and JP=2+ are tested. The kinematic properties of exotic Higgs boson production in association with a vector boson differ from those predicted for the standard model Higgs boson. Upper limits at the 95% credibility level on the production rates of the exotic Higgs bosons, expressed as fractions of the standard model Higgs boson production rate, are set at 0.36 for both the JP=0- hypothesis and the JP=2+ hypothesis. If the production rate times the branching ratio to a bottom-antibottom pair is the same as that predicted for the standard model Higgs boson, then the exotic bosons are excluded with significances of 5.0 standard deviations and 4.9 standard deviations for the JP=0- and JP=2+ hypotheses, respectively.

  20. Neuro-fuzzy modeling in bankruptcy prediction

    Directory of Open Access Journals (Sweden)

    Vlachos D.

    2003-01-01

    Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

  1. Neutral $Z$ boson pair production due to radion resonance in the Randall-Sundrum model: prospects at the CERN LHC

    CERN Document Server

    Das-Prasanta, Kumar

    2005-01-01

    The Neutral $Z$ boson pair production due to radion resonance at the Large Hadron Collider is an interesting process to explore the notion of warped geometry (Randall-Sundrum model). Because of the enhanced coupling of radion with a pair of gluons due to trace enomaly and top(quark)-loop, the radion can provide larger event rate possibility as compared to any New Physics effect. Using the proper radion-top-antitop (with the quarks being off-shell) coupling, we obtain the correct radion production rate at LHC and explore several features of a heavier radion decaying into a pair of real Z bosons which subsequently decays into charged 4 l (l=e, \\mu) leptons (the gold-plated mode). Using the signal and background event rate, we obtain bounds on radion mass $m_\\phi$ and radion vev $\\vphi$ at the $5\\sigma$, $10\\sigma$ discovery level.

  2. Effects of ion pairs on the dynamics of erbium doped fiber laser in the inhomogeneous model

    International Nuclear Information System (INIS)

    Keyvaninia, Sh.; Karvar, M.; Bahrampour, A.

    2006-01-01

    In a high concentration erbium doped fiber, the erbium ions are so closed together that the ion pairs and clusters are formed. In such fiber amplifiers, the ion pairs and clusters acting as a saturable absorber are distributed along the fiber laser. The inhomogeneous rate equations for the laser modes in a high-concentration EDFA are written. The governing equations are an uncountable system of partial differential equations. For the first time we introduced an approximation method that the system of partial differential equations is converted to a finite system of ordinary differential equations. The effects of ion pairs concentration on erbium doped fiber are analyzed that is in good agreement whit the experimental result.

  3. Predictive Models for Carcinogenicity and Mutagenicity ...

    Science.gov (United States)

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include VitotoxTM, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-t

  4. RNA secondary structure prediction with pseudoknots: Contribution of algorithm versus energy model.

    Science.gov (United States)

    Jabbari, Hosna; Wark, Ian; Montemagno, Carlo

    2018-01-01

    RNA is a biopolymer with various applications inside the cell and in biotechnology. Structure of an RNA molecule mainly determines its function and is essential to guide nanostructure design. Since experimental structure determination is time-consuming and expensive, accurate computational prediction of RNA structure is of great importance. Prediction of RNA secondary structure is relatively simpler than its tertiary structure and provides information about its tertiary structure, therefore, RNA secondary structure prediction has received attention in the past decades. Numerous methods with different folding approaches have been developed for RNA secondary structure prediction. While methods for prediction of RNA pseudoknot-free structure (structures with no crossing base pairs) have greatly improved in terms of their accuracy, methods for prediction of RNA pseudoknotted secondary structure (structures with crossing base pairs) still have room for improvement. A long-standing question for improving the prediction accuracy of RNA pseudoknotted secondary structure is whether to focus on the prediction algorithm or the underlying energy model, as there is a trade-off on computational cost of the prediction algorithm versus the generality of the method. The aim of this work is to argue when comparing different methods for RNA pseudoknotted structure prediction, the combination of algorithm and energy model should be considered and a method should not be considered superior or inferior to others if they do not use the same scoring model. We demonstrate that while the folding approach is important in structure prediction, it is not the only important factor in prediction accuracy of a given method as the underlying energy model is also as of great value. Therefore we encourage researchers to pay particular attention in comparing methods with different energy models.

  5. Pair and triplet approximation of a spatial lattice population model with multiscale dispersal using Markov chains for estimating spatial autocorrelation.

    Science.gov (United States)

    Hiebeler, David E; Millett, Nicholas E

    2011-06-21

    We investigate a spatial lattice model of a population employing dispersal to nearest and second-nearest neighbors, as well as long-distance dispersal across the landscape. The model is studied via stochastic spatial simulations, ordinary pair approximation, and triplet approximation. The latter method, which uses the probabilities of state configurations of contiguous blocks of three sites as its state variables, is demonstrated to be greatly superior to pair approximations for estimating spatial correlation information at various scales. Correlations between pairs of sites separated by arbitrary distances are estimated by constructing spatial Markov processes using the information from both approximations. These correlations demonstrate why pair approximation misses basic qualitative features of the model, such as decreasing population density as a large proportion of offspring are dropped on second-nearest neighbors, and why triplet approximation is able to include them. Analytical and numerical results show that, excluding long-distance dispersal, the initial growth rate of an invading population is maximized and the equilibrium population density is also roughly maximized when the population spreads its offspring evenly over nearest and second-nearest neighboring sites. Copyright © 2011 Elsevier Ltd. All rights reserved.

  6. Gamma rays from Cygnus X-1: Modeling and nonthermal pair production

    International Nuclear Information System (INIS)

    Dermer, C.D.; Liang, E.P.

    1988-02-01

    The gamma-ray bump observed between 0.5 and 2 MeV in the spectrum of Cygnus X-1 can be interpreted as the thermal emissions from a hot (kT/approximately/400 keV) pair-dominated cloud. We argue that the X-rays and gamma rays are produced in separate emission regions, and calculate the photon-photon pair production rate from X-ray and gamma-ray interactions in the vicinity of Cyg X-1 by employing a simplified geometry for the two emitting regions

  7. Validated predictive modelling of the environmental resistome.

    Science.gov (United States)

    Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

    2015-06-01

    Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

  8. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  9. Baryogenesis model predicting antimatter in the Universe

    International Nuclear Information System (INIS)

    Kirilova, D.

    2003-01-01

    Cosmic ray and gamma-ray data do not rule out antimatter domains in the Universe, separated at distances bigger than 10 Mpc from us. Hence, it is interesting to analyze the possible generation of vast antimatter structures during the early Universe evolution. We discuss a SUSY-condensate baryogenesis model, predicting large separated regions of matter and antimatter. The model provides generation of the small locally observed baryon asymmetry for a natural initial conditions, it predicts vast antimatter domains, separated from the matter ones by baryonically empty voids. The characteristic scale of antimatter regions and their distance from the matter ones is in accordance with observational constraints from cosmic ray, gamma-ray and cosmic microwave background anisotropy data

  10. Finding Furfural Hydrogenation Catalysts via Predictive Modelling

    OpenAIRE

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-01-01

    Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre t...

  11. Predictive Modeling in Actinide Chemistry and Catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-16

    These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.

  12. Tectonic predictions with mantle convection models

    Science.gov (United States)

    Coltice, Nicolas; Shephard, Grace E.

    2018-04-01

    Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough

  13. Breast cancer risks and risk prediction models.

    Science.gov (United States)

    Engel, Christoph; Fischer, Christine

    2015-02-01

    BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

  14. Fermion pair physics at LEP2

    International Nuclear Information System (INIS)

    Georgios, Anagnostou

    2004-01-01

    Combined measurements of the 4 LEP collaborations for the fermion pair processes e + e - →f anti f are presented. The results show no significant deviations when compared with the Standard Model predictions and are used to set limits on contact interactions, Z' gauge bosons and low scale gravity models with large extra dimensions. (orig.)

  15. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...... values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  16. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Predicting extinction rates in stochastic epidemic models

    International Nuclear Information System (INIS)

    Schwartz, Ira B; Billings, Lora; Dykman, Mark; Landsman, Alexandra

    2009-01-01

    We investigate the stochastic extinction processes in a class of epidemic models. Motivated by the process of natural disease extinction in epidemics, we examine the rate of extinction as a function of disease spread. We show that the effective entropic barrier for extinction in a susceptible–infected–susceptible epidemic model displays scaling with the distance to the bifurcation point, with an unusual critical exponent. We make a direct comparison between predictions and numerical simulations. We also consider the effect of non-Gaussian vaccine schedules, and show numerically how the extinction process may be enhanced when the vaccine schedules are Poisson distributed

  18. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert F.; Knox, James C.

    2016-01-01

    As part of NASA's Advanced Exploration Systems (AES) program and the Life Support Systems Project (LSSP), fully predictive models of the Four Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) on the International Space Station (ISS) are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.

  19. A new model of paired clinical teaching of international and Danish medical students

    DEFF Research Database (Denmark)

    Cortes, Dina; Pinborg, Anja; Teilmann, Grete

    2016-01-01

    and more I- than Danish (DK) students failed exams. Therefore, in 2012 we started a three-year internationalisation project (I-project) at two hospitals. The primary intervention was to pair training for I- and DK-students at clinical contact, and to offer an exclusive daily lecturer for I-teams. METHODS...

  20. A method for conversion of Hounsfield number to electron density and prediction of macroscopic pair production cross-sections

    International Nuclear Information System (INIS)

    Knoeoes, T.; Nilsson, M.; Ahlgren, L.

    1986-01-01

    A method for the determination of electron density using a narrow beam attenuation geometry is described. The method does not require that the elemental composition of the phantom materials is known. The Hounsfield numbers for the phantom materials used were determined using five different CT scanners. A relationship between Hounsfield number and electron density can thus be established, which is of considerable value in radiation therapy treatment planning procedures. Measurements of the ratio coherent/incoherent scattering of low energy photons in a certain geometry has proven valuable for determination of atomic number, which in its turn can be used for estimation of macroscopic pair production coefficients for high energy photons. The combination of knowledge of electron density with methods for determination of processes, dependent on atomic number, can form a base for adequate composition of phantom materials for purposes of testing dose calculation algorithms for photons and electrons. (orig.)

  1. arXiv NLO predictions for Higgs boson pair production with full top quark mass dependence matched to parton showers

    CERN Document Server

    Heinrich, G.; Kerner, M.; Luisoni, G.; Vryonidou, E.

    2017-08-21

    We present the first combination of NLO QCD matrix elements for di-Higgs production, retaining the full top quark mass dependence, with a parton shower. Results are provided within both the POWHEG-BOX and MadGraph5_aMC@NLO Monte Carlo frameworks. We assess in detail the theoretical uncertainties and provide differential results. We find that, as expected, the shower effects are relatively large for observables like the transverse momentum of the Higgs boson pair, which are sensitive to extra radiation. However, these shower effects are still much smaller than the differences between the Born-improved HEFT approximation and the full NLO calculation in the tails of the distributions.

  2. Data Driven Economic Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Masoud Kheradmandi

    2018-04-01

    Full Text Available This manuscript addresses the problem of data driven model based economic model predictive control (MPC design. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. The economic improvements yielded by the proposed method are illustrated through simulations on a nonlinear chemical process system example.

  3. Solvent effect on the intermolecular proton transfer of the Watson and Crick guanine-cytosine and adenine-thymine base pairs: a polarizable continuum model study.

    Science.gov (United States)

    Romero, Eduardo E; Hernandez, Florencio E

    2018-01-03

    Herein we present our results on the study of the double proton transfer (DPT) mechanism in the adenine-thymine (AT) and guanine-cytosine (GC) base pairs, both in gas phase and in solution. The latter was modeled using the polarizable continuum method (PCM) in different solvents. According to our DFT calculations, the DPT may occur for both complexes in a stepwise mechanism in condensate phase. In gas phase only the GC base pair exhibits a concerted DPT mechanism. Using the Wigner's tunneling corrections to the transition state theory we demonstrate that such corrections are important for the prediction of the rate constants of both systems in gas and in condensate phase. We also show that (i) as the polarity of the medium decreases the equilibrium constant of the DPT reaction increases in both complexes, and (ii) that the equilibrium constant in the GC complex is four orders of magnitude larger than in AT. This observation suggests that the spontaneous mutations in DNA base pairs are more probable in GC than in AT.

  4. Search for beyond the standard model Higgs bosons decaying into a $ \\mathrm{b\\bar{b}} $ pair in pp collisions at $\\sqrt{s} = $ 13 TeV

    CERN Document Server

    Sirunyan, Albert M; CMS Collaboration; Adam, Wolfgang; Ambrogi, Federico; Asilar, Ece; Bergauer, Thomas; Brandstetter, Johannes; Brondolin, Erica; Dragicevic, Marko; Erö, Janos; Escalante Del Valle, Alberto; Flechl, Martin; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Hrubec, Josef; Jeitler, Manfred; Krammer, Natascha; Krätschmer, Ilse; Liko, Dietrich; Madlener, Thomas; Mikulec, Ivan; Rad, Navid; Rohringer, Herbert; Schieck, Jochen; Schöfbeck, Robert; Spanring, Markus; Spitzbart, Daniel; Taurok, Anton; Waltenberger, Wolfgang; Wittmann, Johannes; Wulz, Claudia-Elisabeth; Zarucki, Mateusz; Chekhovsky, Vladimir; Mossolov, Vladimir; Suarez Gonzalez, Juan; De Wolf, Eddi A; Di Croce, Davide; Janssen, Xavier; Lauwers, Jasper; Pieters, Maxim; Van De Klundert, Merijn; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Abu Zeid, Shimaa; Blekman, Freya; D'Hondt, Jorgen; De Bruyn, Isabelle; De Clercq, Jarne; Deroover, Kevin; Flouris, Giannis; Lontkovskyi, Denys; Lowette, Steven; Marchesini, Ivan; Moortgat, Seth; Moreels, Lieselotte; Python, Quentin; Skovpen, Kirill; Tavernier, Stefaan; Van Doninck, Walter; Van Mulders, Petra; Van Parijs, Isis; Beghin, Diego; Bilin, Bugra; Brun, Hugues; Clerbaux, Barbara; De Lentdecker, Gilles; Delannoy, Hugo; Dorney, Brian; Fasanella, Giuseppe; Favart, Laurent; Goldouzian, Reza; Grebenyuk, Anastasia; Kalsi, Amandeep Kaur; Lenzi, Thomas; Luetic, Jelena; Postiau, Nicolas; Starling, Elizabeth; Thomas, Laurent; Vander Velde, Catherine; Vanlaer, Pascal; Vannerom, David; Wang, Qun; Cornelis, Tom; Dobur, Didar; Fagot, Alexis; Gul, Muhammad; Khvastunov, Illia; Poyraz, Deniz; Roskas, Christos; Trocino, Daniele; Tytgat, Michael; Verbeke, Willem; Vermassen, Basile; Vit, Martina; Zaganidis, Nicolas; Bakhshiansohi, Hamed; Bondu, Olivier; Brochet, Sébastien; Bruno, Giacomo; Caputo, Claudio; David, Pieter; Delaere, Christophe; Delcourt, Martin; Francois, Brieuc; Giammanco, Andrea; Krintiras, Georgios; Lemaitre, Vincent; Magitteri, Alessio; Mertens, Alexandre; Musich, Marco; Piotrzkowski, Krzysztof; Saggio, Alessia; Vidal Marono, Miguel; Wertz, Sébastien; Zobec, Joze; Alves, Fábio Lúcio; Alves, Gilvan; Brito, Lucas; Correia Silva, Gilson; Hensel, Carsten; Moraes, Arthur; Pol, Maria Elena; Rebello Teles, Patricia; Belchior Batista Das Chagas, Ewerton; Carvalho, Wagner; Chinellato, Jose; Coelho, Eduardo; Melo Da Costa, Eliza; Da Silveira, Gustavo Gil; De Jesus Damiao, Dilson; De Oliveira Martins, Carley; Fonseca De Souza, Sandro; Malbouisson, Helena; Matos Figueiredo, Diego; Melo De Almeida, Miqueias; Mora Herrera, Clemencia; Mundim, Luiz; Nogima, Helio; Prado Da Silva, Wanda Lucia; Sanchez Rosas, Luis Junior; Santoro, Alberto; Sznajder, Andre; Thiel, Mauricio; Tonelli Manganote, Edmilson José; Torres Da Silva De Araujo, Felipe; Vilela Pereira, Antonio; Ahuja, Sudha; Bernardes, Cesar Augusto; Calligaris, Luigi; Tomei, Thiago; De Moraes Gregores, Eduardo; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Romero Abad, David; Aleksandrov, Aleksandar; Hadjiiska, Roumyana; Iaydjiev, Plamen; Marinov, Andrey; Misheva, Milena; Rodozov, Mircho; Shopova, Mariana; Sultanov, Georgi; Dimitrov, Anton; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Fang, Wenxing; Gao, Xuyang; Yuan, Li; Ahmad, Muhammad; Bian, Jian-Guo; Chen, Guo-Ming; Chen, He-Sheng; Chen, Mingshui; Chen, Ye; Jiang, Chun-Hua; Leggat, Duncan; Liao, Hongbo; Liu, Zhenan; Romeo, Francesco; Shaheen, Sarmad Masood; Spiezia, Aniello; Tao, Junquan; Wang, Chunjie; Wang, Zheng; Yazgan, Efe; Zhang, Huaqiao; Zhao, Jingzhou; Ban, Yong; Chen, Geng; Li, Jing; Li, Qiang; Mao, Yajun; Qian, Si-Jin; Wang, Dayong; Xu, Zijun; Wang, Yi; Avila, Carlos; Cabrera, Andrés; Carrillo Montoya, Camilo Andres; Chaparro Sierra, Luisa Fernanda; Florez, Carlos; González Hernández, Carlos Felipe; Segura Delgado, Manuel Alejandro; Courbon, Benoit; Godinovic, Nikola; Lelas, Damir; Puljak, Ivica; Sculac, Toni; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Ferencek, Dinko; Kadija, Kreso; Mesic, Benjamin; Starodumov, Andrei; Susa, Tatjana; Ather, Mohsan Waseem; Attikis, Alexandros; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Rykaczewski, Hans; Finger, Miroslav; Finger Jr, Michael; Ayala, Edy; Carrera Jarrin, Edgar; Abdalla, Hassan; Abdelalim, Ahmed Ali; Khalil, Shaaban; Bhowmik, Sandeep; Carvalho Antunes De Oliveira, Alexandra; Dewanjee, Ram Krishna; Ehataht, Karl; Kadastik, Mario; Perrini, Lucia; Raidal, Martti; Veelken, Christian; Eerola, Paula; Kirschenmann, Henning; Pekkanen, Juska; Voutilainen, Mikko; Havukainen, Joona; Heikkilä, Jaana Kristiina; Jarvinen, Terhi; Karimäki, Veikko; Kinnunen, Ritva; Lampén, Tapio; Lassila-Perini, Kati; Laurila, Santeri; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Mäenpää, Teppo; Siikonen, Hannu; Tuominen, Eija; Tuominiemi, Jorma; Tuuva, Tuure; Besancon, Marc; Couderc, Fabrice; Dejardin, Marc; Denegri, Daniel; Faure, Jean-Louis; Ferri, Federico; Ganjour, Serguei; Givernaud, Alain; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Leloup, Clément; Locci, Elizabeth; Malcles, Julie; Negro, Giulia; Rander, John; Rosowsky, André; Sahin, Mehmet Özgür; Titov, Maksym; Abdulsalam, Abdulla; Amendola, Chiara; Antropov, Iurii; Beaudette, Florian; Busson, Philippe; Charlot, Claude; Granier de Cassagnac, Raphael; Kucher, Inna; Lisniak, Stanislav; Lobanov, Artur; Martin Blanco, Javier; Nguyen, Matthew; Ochando, Christophe; Ortona, Giacomo; Pigard, Philipp; Salerno, Roberto; Sauvan, Jean-Baptiste; Sirois, Yves; Stahl Leiton, Andre Govinda; Zabi, Alexandre; Zghiche, Amina; Agram, Jean-Laurent; Andrea, Jeremy; Bloch, Daniel; Brom, Jean-Marie; Chabert, Eric Christian; Cherepanov, Vladimir; Collard, Caroline; Conte, Eric; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Jansová, Markéta; Le Bihan, Anne-Catherine; Tonon, Nicolas; Van Hove, Pierre; Gadrat, Sébastien; Beauceron, Stephanie; Bernet, Colin; Boudoul, Gaelle; Chanon, Nicolas; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fay, Jean; Finco, Linda; Gascon, Susan; Gouzevitch, Maxime; Grenier, Gérald; Ille, Bernard; Lagarde, Francois; Laktineh, Imad Baptiste; Lattaud, Hugues; Lethuillier, Morgan; Mirabito, Laurent; Pequegnot, Anne-Laure; Perries, Stephane; Popov, Andrey; Sordini, Viola; Vander Donckt, Muriel; Viret, Sébastien; Zhang, Sijing; Khvedelidze, Arsen; Tsamalaidze, Zviad; Autermann, Christian; Feld, Lutz; Kiesel, Maximilian Knut; Klein, Katja; Lipinski, Martin; Preuten, Marius; Rauch, Max Philip; Schomakers, Christian; Schulz, Johannes; Teroerde, Marius; Wittmer, Bruno; Zhukov, Valery; Albert, Andreas; Duchardt, Deborah; Endres, Matthias; Erdmann, Martin; Erdweg, Sören; Esch, Thomas; Fischer, Robert; Ghosh, Saranya; Güth, Andreas; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Knutzen, Simon; Mastrolorenzo, Luca; Merschmeyer, Markus; Meyer, Arnd; Millet, Philipp; Mukherjee, Swagata; Pook, Tobias; Radziej, Markus; Reithler, Hans; Rieger, Marcel; Scheuch, Florian; Schmidt, Alexander; Teyssier, Daniel; Thüer, Sebastian; Flügge, Günter; Hlushchenko, Olena; Kargoll, Bastian; Kress, Thomas; Künsken, Andreas; Müller, Thomas; Nehrkorn, Alexander; Nowack, Andreas; Pistone, Claudia; Pooth, Oliver; Sert, Hale; Stahl, Achim; Aldaya Martin, Maria; Arndt, Till; Asawatangtrakuldee, Chayanit; Babounikau, Illia; Beernaert, Kelly; Behnke, Olaf; Behrens, Ulf; Bermúdez Martínez, Armando; Bertsche, David; Bin Anuar, Afiq Aizuddin; Borras, Kerstin; Botta, Valeria; Campbell, Alan; Connor, Patrick; Contreras-Campana, Christian; Costanza, Francesco; Danilov, Vladyslav; De Wit, Adinda; Defranchis, Matteo Maria; Diez Pardos, Carmen; Domínguez Damiani, Daniela; Eckerlin, Guenter; Eichhorn, Thomas; Elwood, Adam; Eren, Engin; Gallo, Elisabetta; Geiser, Achim; Grados Luyando, Juan Manuel; Grohsjean, Alexander; Gunnellini, Paolo; Guthoff, Moritz; Harb, Ali; Hauk, Johannes; Jung, Hannes; Kasemann, Matthias; Keaveney, James; Kleinwort, Claus; Knolle, Joscha; Krücker, Dirk; Lange, Wolfgang; Lelek, Aleksandra; Lenz, Teresa; Lipka, Katerina; Lohmann, Wolfgang; Mankel, Rainer; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Meyer, Mareike; Missiroli, Marino; Mittag, Gregor; Mnich, Joachim; Myronenko, Volodymyr; Pflitsch, Svenja Karen; Pitzl, Daniel; Raspereza, Alexei; Savitskyi, Mykola; Saxena, Pooja; Schütze, Paul; Schwanenberger, Christian; Shevchenko, Rostyslav; Singh, Akshansh; Stefaniuk, Nazar; Tholen, Heiner; Vagnerini, Antonio; Van Onsem, Gerrit Patrick; Walsh, Roberval; Wen, Yiwen; Wichmann, Katarzyna; Wissing, Christoph; Zenaiev, Oleksandr; Aggleton, Robin; Bein, Samuel; Benecke, Anna; Blobel, Volker; Centis Vignali, Matteo; Dreyer, Torben; Garutti, Erika; Gonzalez, Daniel; Haller, Johannes; Hinzmann, Andreas; Hoffmann, Malte; Karavdina, Anastasia; Kasieczka, Gregor; Klanner, Robert; Kogler, Roman; Kovalchuk, Nataliia; Kurz, Simon; Kutzner, Viktor; Lange, Johannes; Marconi, Daniele; Multhaup, Jens; Niedziela, Marek; Nowatschin, Dominik; Perieanu, Adrian; Reimers, Arne; Rieger, Oliver; Scharf, Christian; Schleper, Peter; Schumann, Svenja; Schwandt, Joern; Sonneveld, Jory; Stadie, Hartmut; Steinbrück, Georg; Stober, Fred-Markus Helmut; Stöver, Marc; Troendle, Daniel; Usai, Emanuele; Vanhoefer, Annika; Vormwald, Benedikt; Akbiyik, Melike; Barth, Christian; Baselga, Marta; Baur, Sebastian; Butz, Erik; Caspart, René; Chwalek, Thorsten; Colombo, Fabio; De Boer, Wim; Dierlamm, Alexander; Faltermann, Nils; Freund, Benedikt; Giffels, Manuel; Harrendorf, Marco Alexander; Hartmann, Frank; Heindl, Stefan Michael; Husemann, Ulrich; Kassel, Florian; Katkov, Igor; Kudella, Simon; Mildner, Hannes; Mitra, Soureek; Mozer, Matthias Ulrich; Müller, Thomas; Plagge, Michael; Quast, Gunter; Rabbertz, Klaus; Schröder, Matthias; Shvetsov, Ivan; Sieber, Georg; Simonis, Hans-Jürgen; Ulrich, Ralf; Wayand, Stefan; Weber, Marc; Weiler, Thomas; Williamson, Shawn; Wöhrmann, Clemens; Wolf, Roger; Anagnostou, Georgios; Daskalakis, Georgios; Geralis, Theodoros; Kyriakis, Aristotelis; Loukas, Demetrios; Paspalaki, Garyfallia; Topsis-Giotis, Iasonas; Karathanasis, George; Kesisoglou, Stilianos; Kontaxakis, Pantelis; Panagiotou, Apostolos; Saoulidou, Niki; Tziaferi, Eirini; Vellidis, Konstantinos; Kousouris, Konstantinos; Papakrivopoulos, Ioannis; Tsipolitis, Georgios; Evangelou, Ioannis; Foudas, Costas; Gianneios, Paraskevas; Katsoulis, Panagiotis; Kokkas, Panagiotis; Mallios, Stavros; Manthos, Nikolaos; Papadopoulos, Ioannis; Paradas, Evangelos; Strologas, John; Triantis, Frixos A; Tsitsonis, Dimitrios; Csanad, Mate; Filipovic, Nicolas; Major, Péter; Nagy, Marton Imre; Pasztor, Gabriella; Surányi, Olivér; Veres, Gabor Istvan; Bencze, Gyorgy; Hajdu, Csaba; Horvath, Dezso; Hunyadi, Ádám; Sikler, Ferenc; Vámi, Tamás Álmos; Veszpremi, Viktor; Vesztergombi, Gyorgy; Beni, Noemi; Czellar, Sandor; Karancsi, János; Makovec, Alajos; Molnar, Jozsef; Szillasi, Zoltan; Bartók, Márton; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Choudhury, Somnath; Komaragiri, Jyothsna Rani; Bahinipati, Seema; Mal, Prolay; Mandal, Koushik; Nayak, Aruna; Sahoo, Deepak Kumar; Swain, Sanjay Kumar; Bansal, Sunil; Beri, Suman Bala; Bhatnagar, Vipin; Chauhan, Sushil; Chawla, Ridhi; Dhingra, Nitish; Gupta, Rajat; Kaur, Anterpreet; Kaur, Amandeep; Kaur, Manjit; Kaur, Sandeep; Kumar, Ramandeep; Kumari, Priyanka; Lohan, Manisha; Mehta, Ankita; Sharma, Sandeep; Singh, Jasbir; Walia, Genius; Bhardwaj, Ashutosh; Choudhary, Brajesh C; Garg, Rocky Bala; Gola, Mohit; Keshri, Sumit; Kumar, Ashok; Malhotra, Shivali; Naimuddin, Md; Priyanka, Priyanka; Ranjan, Kirti; Shah, Aashaq; Sharma, Ramkrishna; Bhardwaj, Rishika; Bharti, Monika; Bhattacharya, Rajarshi; Bhattacharya, Satyaki; Bhawandeep, Bhawandeep; Bhowmik, Debabrata; Dey, Sourav; Dutt, Suneel; Dutta, Suchandra; Ghosh, Shamik; Mondal, Kuntal; Nandan, Saswati; Purohit, Arnab; Rout, Prasant Kumar; Roy, Ashim; Roy Chowdhury, Suvankar; Sarkar, Subir; Sharan, Manoj; Singh, Bipen; Thakur, Shalini; Behera, Prafulla Kumar; Chudasama, Ruchi; Dutta, Dipanwita; Jha, Vishwajeet; Kumar, Vineet; Netrakanti, Pawan Kumar; Pant, Lalit Mohan; Shukla, Prashant; Aziz, Tariq; Bhat, Muzamil Ahmad; Dugad, Shashikant; Mahakud, Bibhuprasad; Mohanty, Gagan Bihari; Sur, Nairit; Sutar, Bajrang; Ravindra Kumar Verma, Ravindra; Banerjee, Sudeshna; Bhattacharya, Soham; Chatterjee, Suman; Das, Pallabi; Guchait, Monoranjan; Jain, Sandhya; Kumar, Sanjeev; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Sahoo, Niladribihari; Sarkar, Tanmay; Chauhan, Shubhanshu; Dube, Sourabh; Hegde, Vinay; Kapoor, Anshul; Kothekar, Kunal; Pandey, Shubham; Rane, Aditee; Sharma, Seema; Chenarani, Shirin; Eskandari Tadavani, Esmaeel; Etesami, Seyed Mohsen; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Naseri, Mohsen; Rezaei Hosseinabadi, Ferdos; Safarzadeh, Batool; Zeinali, Maryam; Felcini, Marta; Grunewald, Martin; Abbrescia, Marcello; Calabria, Cesare; Colaleo, Anna; Creanza, Donato; Cristella, Leonardo; De Filippis, Nicola; De Palma, Mauro; Di Florio, Adriano; Errico, Filippo; Fiore, Luigi; Gelmi, Andrea; Iaselli, Giuseppe; Lezki, Samet; Maggi, Giorgio; Maggi, Marcello; Miniello, Giorgia; My, Salvatore; Nuzzo, Salvatore; Pompili, Alexis; Pugliese, Gabriella; Radogna, Raffaella; Ranieri, Antonio; Selvaggi, Giovanna; Sharma, Archana; Silvestris, Lucia; Venditti, Rosamaria; Verwilligen, Piet; Zito, Giuseppe; Abbiendi, Giovanni; Battilana, Carlo; Bonacorsi, Daniele; Borgonovi, Lisa; Braibant-Giacomelli, Sylvie; Brigliadori, Luca; Campanini, Renato; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Chhibra, Simranjit Singh; Codispoti, Giuseppe; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Montanari, Alessandro; Navarria, Francesco; Perrotta, Andrea; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Tosi, Nicolò; Albergo, Sebastiano; Di Mattia, Alessandro; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Chatterjee, Kalyanmoy; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Latino, Giuseppe; Lenzi, Piergiulio; Meschini, Marco; Paoletti, Simone; Russo, Lorenzo; Sguazzoni, Giacomo; Strom, Derek; Viliani, Lorenzo; Benussi, Luigi; Bianco, Stefano; Fabbri, Franco; Piccolo, Davide; Primavera, Federica; Ferro, Fabrizio; Ravera, Fabio; Robutti, Enrico; Tosi, Silvano; Benaglia, Andrea; Beschi, Andrea; Brianza, Luca; Brivio, Francesco; Ciriolo, Vincenzo; Di Guida, Salvatore; Dinardo, Mauro Emanuele; Fiorendi, Sara; Gennai, Simone; Ghezzi, Alessio; Govoni, Pietro; Malberti, Martina; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Massironi, Andrea; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pedrini, Daniele; Ragazzi, Stefano; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Cavallo, Nicola; Di Crescenzo, Antonia; Fabozzi, Francesco; Fienga, Francesco; Galati, Giuliana; Iorio, Alberto Orso Maria; Khan, Wajid Ali; Lista, Luca; Meola, Sabino; Paolucci, Pierluigi; Sciacca, Crisostomo; Voevodina, Elena; Azzi, Patrizia; Bacchetta, Nicola; Bellato, Marco; Benato, Lisa; Bisello, Dario; Boletti, Alessio; Bragagnolo, Alberto; Carlin, Roberto; Checchia, Paolo; Dall'Osso, Martino; De Castro Manzano, Pablo; Dorigo, Tommaso; Dosselli, Umberto; Gasparini, Ugo; Gozzelino, Andrea; Lacaprara, Stefano; Lujan, Paul; Margoni, Martino; Meneguzzo, Anna Teresa; Pozzobon, Nicola; Ronchese, Paolo; Rossin, Roberto; Simonetto, Franco; Tiko, Andres; Torassa, Ezio; Zanetti, Marco; Zotto, Pierluigi; Braghieri, Alessandro; Magnani, Alice; Montagna, Paolo; Ratti, Sergio P; Re, Valerio; Ressegotti, Martina; Riccardi, Cristina; Salvini, Paola; Vai, Ilaria; Vitulo, Paolo; Alunni Solestizi, Luisa; Biasini, Maurizio; Bilei, Gian Mario; Cecchi, Claudia; Ciangottini, Diego; Fanò, Livio; Lariccia, Paolo; Manoni, Elisa; Mantovani, Giancarlo; Mariani, Valentina; Menichelli, Mauro; Rossi, Alessandro; Santocchia, Attilio; Spiga, Daniele; Androsov, Konstantin; Azzurri, Paolo; Bagliesi, Giuseppe; Bianchini, Lorenzo; Boccali, Tommaso; Borrello, Laura; Castaldi, Rino; Ciocci, Maria Agnese; Dell'Orso, Roberto; Fedi, Giacomo; Giannini, Leonardo; Giassi, Alessandro; Grippo, Maria Teresa; Ligabue, Franco; Manca, Elisabetta; Mandorli, Giulio; Messineo, Alberto; Palla, Fabrizio; Rizzi, Andrea; Spagnolo, Paolo; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Barone, Luciano; Cavallari, Francesca; Cipriani, Marco; Daci, Nadir; Del Re, Daniele; Di Marco, Emanuele; Diemoz, Marcella; Gelli, Simone; Longo, Egidio; Marzocchi, Badder; Meridiani, Paolo; Organtini, Giovanni; Pandolfi, Francesco; Paramatti, Riccardo; Preiato, Federico; Rahatlou, Shahram; Rovelli, Chiara; Santanastasio, Francesco; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Bartosik, Nazar; Bellan, Riccardo; Biino, Cristina; Cartiglia, Nicolo; Cenna, Francesca; Costa, Marco; Covarelli, Roberto; Demaria, Natale; Kiani, Bilal; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Monteil, Ennio; Monteno, Marco; Obertino, Maria Margherita; Pacher, Luca; Pastrone, Nadia; Pelliccioni, Mario; Pinna Angioni, Gian Luca; Romero, Alessandra; Ruspa, Marta; Sacchi, Roberto; Shchelina, Ksenia; Sola, Valentina; Solano, Ada; Staiano, Amedeo; Belforte, Stefano; Candelise, Vieri; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Vazzoler, Federico; Zanetti, Anna; Kim, Dong Hee; Kim, Gui Nyun; Kim, Min Suk; Lee, Jeongeun; Lee, Sangeun; Lee, Seh Wook; Moon, Chang-Seong; Oh, Young Do; Sekmen, Sezen; Son, Dong-Chul; Yang, Yu Chul; Kim, Hyunchul; Moon, Dong Ho; Oh, Geonhee; Goh, Junghwan; Kim, Tae Jeong; Cho, Sungwoong; Choi, Suyong; Go, Yeonju; Gyun, Dooyeon; Ha, Seungkyu; Hong, Byung-Sik; Jo, Youngkwon; Lee, Kisoo; Lee, Kyong Sei; Lee, Songkyo; Lim, Jaehoon; Park, Sung Keun; Roh, Youn; Kim, Hyunsoo; Almond, John; Kim, Junho; Kim, Jae Sung; Lee, Haneol; Lee, Kyeongpil; Nam, Kyungwook; Oh, Sung Bin; Radburn-Smith, Benjamin Charles; Seo, Seon-hee; Yang, Unki; Yoo, Hwi Dong; Yu, Geum Bong; Kim, Hyunyong; Kim, Ji Hyun; Lee, Jason Sang Hun; Park, Inkyu; Choi, Young-Il; Hwang, Chanwook; Lee, Jongseok; Yu, Intae; Dudenas, Vytautas; Juodagalvis, Andrius; Vaitkus, Juozas; Ahmed, Ijaz; Ibrahim, Zainol Abidin; Md Ali, Mohd Adli Bin; Mohamad Idris, Faridah; Wan Abdullah, Wan Ahmad Tajuddin; Yusli, Mohd Nizam; Zolkapli, Zukhaimira; Duran-Osuna, Cecilia; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Ramirez-Sanchez, Gabriel; Heredia-De La Cruz, Ivan; Rabadán-Trejo, Raúl Iraq; Lopez-Fernandez, Ricardo; Mejia Guisao, Jhovanny; Reyes-Almanza, Rogelio; Sánchez Hernández, Alberto; Carrillo Moreno, Salvador; Oropeza Barrera, Cristina; Vazquez Valencia, Fabiola; Eysermans, Jan; Pedraza, Isabel; Salazar Ibarguen, Humberto Antonio; Uribe Estrada, Cecilia; Morelos Pineda, Antonio; Krofcheck, David; Bheesette, Srinidhi; Butler, Philip H; Ahmad, Ashfaq; Ahmad, Muhammad; Asghar, Muhammad Irfan; Hassan, Qamar; Hoorani, Hafeez R; Saddique, Asif; Shah, Mehar Ali; Shoaib, Muhammad; Waqas, Muhammad; Bialkowska, Helena; Bluj, Michal; Boimska, Bozena; Frueboes, Tomasz; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Szleper, Michal; Traczyk, Piotr; Zalewski, Piotr; Bunkowski, Karol; Byszuk, Adrian; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Misiura, Maciej; Olszewski, Michal; Pyskir, Andrzej; Walczak, Marek; Bargassa, Pedrame; Beirão Da Cruz E Silva, Cristóvão; Di Francesco, Agostino; Faccioli, Pietro; Galinhas, Bruno; Gallinaro, Michele; Hollar, Jonathan; Leonardo, Nuno; Lloret Iglesias, Lara; Nemallapudi, Mythra Varun; Seixas, Joao; Strong, Giles; Toldaiev, Oleksii; Vadruccio, Daniele; Varela, Joao; Alexakhin, Vadim; Golunov, Alexander; Golutvin, Igor; Gorbounov, Nikolai; Gorbunov, Ilya; Kamenev, Alexey; Karjavine, Vladimir; Lanev, Alexander; Malakhov, Alexander; Matveev, Viktor; Moisenz, Petr; Palichik, Vladimir; Perelygin, Victor; Savina, Maria; Shmatov, Sergey; Shulha, Siarhei; Skatchkov, Nikolai; Smirnov, Vitaly; Zarubin, Anatoli; Golovtsov, Victor; Ivanov, Yury; Kim, Victor; Kuznetsova, Ekaterina; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sosnov, Dmitry; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Karneyeu, Anton; Kirsanov, Mikhail; Krasnikov, Nikolai; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Gavrilov, Vladimir; Lychkovskaya, Natalia; Popov, Vladimir; Pozdnyakov, Ivan; Safronov, Grigory; Spiridonov, Alexander; Stepennov, Anton; Stolin, Viatcheslav; Toms, Maria; Vlasov, Evgueni; Zhokin, Alexander; Aushev, Tagir; Bylinkin, Alexander; Chistov, Ruslan; Danilov, Mikhail; Parygin, Pavel; Philippov, Dmitry; Polikarpov, Sergey; Tarkovskii, Evgenii; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Rusakov, Sergey V; Terkulov, Adel; Baskakov, Alexey; Belyaev, Andrey; Boos, Edouard; Bunichev, Viacheslav; Dubinin, Mikhail; Dudko, Lev; Klyukhin, Vyacheslav; Kodolova, Olga; Lokhtin, Igor; Miagkov, Igor; Obraztsov, Stepan; Perfilov, Maxim; Petrushanko, Sergey; Savrin, Viktor; Snigirev, Alexander; Blinov, Vladimir; Dimova, Tatyana; Kardapoltsev, Leonid; Shtol, Dmitry; Skovpen, Yuri; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Elumakhov, Dmitry; Godizov, Anton; Kachanov, Vassili; Kalinin, Alexey; Konstantinov, Dmitri; Mandrik, Petr; Petrov, Vladimir; Ryutin, Roman; Slabospitskii, Sergei; Sobol, Andrei; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Babaev, Anton; Adzic, Petar; Cirkovic, Predrag; Devetak, Damir; Dordevic, Milos; Milosevic, Jovan; Alcaraz Maestre, Juan; Álvarez Fernández, Adrian; Bachiller, Irene; Barrio Luna, Mar; Brochero Cifuentes, Javier Andres; Cerrada, Marcos; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Flix, Jose; Fouz, Maria Cruz; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Moran, Dermot; Pérez-Calero Yzquierdo, Antonio María; Puerta Pelayo, Jesus; Redondo, Ignacio; Romero, Luciano; Senghi Soares, Mara; Triossi, Andrea; Albajar, Carmen; de Trocóniz, Jorge F; Cuevas, Javier; Erice, Carlos; Fernandez Menendez, Javier; Folgueras, Santiago; Gonzalez Caballero, Isidro; González Fernández, Juan Rodrigo; Palencia Cortezon, Enrique; Rodríguez Bouza, Víctor; Sanchez Cruz, Sergio; Vischia, Pietro; Vizan Garcia, Jesus Manuel; Cabrillo, Iban Jose; Calderon, Alicia; Chazin Quero, Barbara; Duarte Campderros, Jordi; Fernandez, Marcos; Fernández Manteca, Pedro José; García Alonso, Andrea; Garcia-Ferrero, Juan; Gomez, Gervasio; Lopez Virto, Amparo; Marco, Jesus; Martinez Rivero, Celso; Martinez Ruiz del Arbol, Pablo; Matorras, Francisco; Piedra Gomez, Jonatan; Prieels, Cédric; Rodrigo, Teresa; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Trevisani, Nicolò; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Akgun, Bora; Auffray, Etiennette; Baillon, Paul; Ball, Austin; Barney, David; Bendavid, Joshua; Bianco, Michele; Bocci, Andrea; Botta, Cristina; Camporesi, Tiziano; Cepeda, Maria; Cerminara, Gianluca; Chapon, Emilien; Chen, Yi; Cucciati, Giacomo; D'Enterria, David; Dabrowski, Anne; Daponte, Vincenzo; David Tinoco Mendes, Andre; De Roeck, Albert; Deelen, Nikkie; Dobson, Marc; Du Pree, Tristan; Dünser, Marc; Dupont, Niels; Elliott-Peisert, Anna; Everaerts, Pieter; Fallavollita, Francesco; Fasanella, Daniele; Franzoni, Giovanni; Fulcher, Jonathan; Funk, Wolfgang; Gigi, Dominique; Gilbert, Andrew; Gill, Karl; Glege, Frank; Gulhan, Doga; Hegeman, Jeroen; Innocente, Vincenzo; Jafari, Abideh; Janot, Patrick; Karacheban, Olena; Kieseler, Jan; Knünz, Valentin; Kornmayer, Andreas; Krammer, Manfred; Lange, Clemens; Lecoq, Paul; Lourenco, Carlos; Lucchini, Marco Toliman; Malgeri, Luca; Mannelli, Marcello; Meijers, Frans; Merlin, Jeremie Alexandre; Mersi, Stefano; Meschi, Emilio; Milenovic, Predrag; Moortgat, Filip; Mulders, Martijn; Neugebauer, Hannes; Ngadiuba, Jennifer; Orfanelli, Styliani; Orsini, Luciano; Pantaleo, Felice; Pape, Luc; Perez, Emmanuel; Peruzzi, Marco; Petrilli, Achille; Petrucciani, Giovanni; Pfeiffer, Andreas; Pierini, Maurizio; Pitters, Florian Michael; Rabady, Dinyar; Racz, Attila; Reis, Thomas; Rolandi, Gigi; Rovere, Marco; Sakulin, Hannes; Schäfer, Christoph; Schwick, Christoph; Seidel, Markus; Selvaggi, Michele; Sharma, Archana; Silva, Pedro; Sphicas, Paraskevas; Stakia, Anna; Steggemann, Jan; Tosi, Mia; Treille, Daniel; Tsirou, Andromachi; Veckalns, Viesturs; Verweij, Marta; Zeuner, Wolfram Dietrich; Bertl, Willi; Caminada, Lea; Deiters, Konrad; Erdmann, Wolfram; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; Kotlinski, Danek; Langenegger, Urs; Rohe, Tilman; Wiederkehr, Stephan Albert; Backhaus, Malte; Bäni, Lukas; Berger, Pirmin; Casal, Bruno; Chernyavskaya, Nadezda; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dorfer, Christian; Grab, Christoph; Heidegger, Constantin; Hits, Dmitry; Hoss, Jan; Klijnsma, Thomas; Lustermann, Werner; Marionneau, Matthieu; Meinhard, Maren Tabea; Meister, Daniel; Micheli, Francesco; Musella, Pasquale; Nessi-Tedaldi, Francesca; Pata, Joosep; Pauss, Felicitas; Perrin, Gaël; Perrozzi, Luca; Pigazzini, Simone; Quittnat, Milena; Reichmann, Michael; Ruini, Daniele; Sanz Becerra, Diego Alejandro; Schönenberger, Myriam; Shchutska, Lesya; Tavolaro, Vittorio Raoul; Theofilatos, Konstantinos; Vesterbacka Olsson, Minna Leonora; Wallny, Rainer; Zhu, De Hua; Aarrestad, Thea Klaeboe; Amsler, Claude; Brzhechko, Danyyl; Canelli, Maria Florencia; De Cosa, Annapaola; Del Burgo, Riccardo; Donato, Silvio; Galloni, Camilla; Hreus, Tomas; Kilminster, Benjamin; Neutelings, Izaak; Pinna, Deborah; Rauco, Giorgia; Robmann, Peter; Salerno, Daniel; Schweiger, Korbinian; Seitz, Claudia; Takahashi, Yuta; Zucchetta, Alberto; Chang, Yu-Hsiang; Cheng, Kai-yu; Doan, Thi Hien; Jain, Shilpi; Khurana, Raman; Kuo, Chia-Ming; Lin, Willis; Pozdnyakov, Andrey; Yu, Shin-Shan; Chang, Paoti; Chao, Yuan; Chen, Kai-Feng; Chen, Po-Hsun; Hou, George Wei-Shu; Kumar, Arun; Li, You-ying; Lu, Rong-Shyang; Paganis, Efstathios; Psallidas, Andreas; Steen, Arnaud; Tsai, Jui-fa; Asavapibhop, Burin; Srimanobhas, Norraphat; Suwonjandee, Narumon; Bat, Ayse; Boran, Fatma; Cerci, Salim; Damarseckin, Serdal; Demiroglu, Zuhal Seyma; Dozen, Candan; Dumanoglu, Isa; Girgis, Semiray; Gokbulut, Gul; Guler, Yalcin; Gurpinar, Emine; Hos, Ilknur; Kangal, Evrim Ersin; Kara, Ozgun; Kayis Topaksu, Aysel; Kiminsu, Ugur; Oglakci, Mehmet; Onengut, Gulsen; Ozdemir, Kadri; Ozturk, Sertac; Sunar Cerci, Deniz; Tali, Bayram; Tok, Ufuk Guney; Turkcapar, Semra; Zorbakir, Ibrahim Soner; Zorbilmez, Caglar; Isildak, Bora; Karapinar, Guler; Yalvac, Metin; Zeyrek, Mehmet; Atakisi, Ismail Okan; Gülmez, Erhan; Kaya, Mithat; Kaya, Ozlem; Tekten, Sevgi; Yetkin, Elif Asli; Agaras, Merve Nazlim; Atay, Serhat; Cakir, Altan; Cankocak, Kerem; Komurcu, Yildiray; Sen, Sercan; Grynyov, Boris; Levchuk, Leonid; Titterton, Alexander; Ball, Fionn; Beck, Lana; Brooke, James John; Burns, Douglas; Clement, Emyr; Cussans, David; Davignon, Olivier; Flacher, Henning; Goldstein, Joel; Heath, Greg P; Heath, Helen F; Kreczko, Lukasz; Newbold, Dave M; Paramesvaran, Sudarshan; Penning, Bjoern; Sakuma, Tai; Smith, Dominic; Smith, Vincent J; Taylor, Joseph; Bell, Ken W; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Cieri, Davide; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Linacre, Jacob; Olaiya, Emmanuel; Petyt, David; Shepherd-Themistocleous, Claire; Thea, Alessandro; Tomalin, Ian R; Williams, Thomas; Womersley, William John; Auzinger, Georg; Bainbridge, Robert; Bloch, Philippe; Borg, Johan; Breeze, Shane; Buchmuller, Oliver; Bundock, Aaron; Casasso, Stefano; Colling, David; Corpe, Louie; Dauncey, Paul; Davies, Gavin; Della Negra, Michel; Di Maria, Riccardo; Haddad, Yacine; Hall, Geoffrey; Iles, Gregory; James, Thomas; Komm, Matthias; Laner, Christian; Lyons, Louis; Magnan, Anne-Marie; Malik, Sarah; Martelli, Arabella; Nash, Jordan; Nikitenko, Alexander; Palladino, Vito; Pesaresi, Mark; Richards, Alexander; Rose, Andrew; Scott, Edward; Seez, Christopher; Shtipliyski, Antoni; Singh, Gurpreet; Stoye, Markus; Strebler, Thomas; Summers, Sioni; Tapper, Alexander; Uchida, Kirika; Virdee, Tejinder; Wardle, Nicholas; Winterbottom, Daniel; Wright, Jack; Zenz, Seth Conrad; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Mackay, Catherine Kirsty; Morton, Alexander; Reid, Ivan; Teodorescu, Liliana; Zahid, Sema; Borzou, Ahmad; Call, Kenneth; Dittmann, Jay; Hatakeyama, Kenichi; Liu, Hongxuan; Madrid, Christopher; Mcmaster, Brooks; Pastika, Nathaniel; Smith, Caleb; Bartek, Rachel; Dominguez, Aaron; Buccilli, Andrew; Cooper, Seth; Henderson, Conor; Rumerio, Paolo; West, Christopher; Arcaro, Daniel; Bose, Tulika; Gastler, Daniel; Rankin, Dylan; Richardson, Clint; Rohlf, James; Sulak, Lawrence; Zou, David; Benelli, Gabriele; Coubez, Xavier; Cutts, David; Hadley, Mary; Hakala, John; Heintz, Ulrich; Hogan, Julie Managan; Kwok, Ka Hei Martin; Laird, Edward; Landsberg, Greg; Lee, Jangbae; Mao, Zaixing; Narain, Meenakshi; Pazzini, Jacopo; Piperov, Stefan; Sagir, Sinan; Syarif, Rizki; Yu, David; Band, Reyer; Brainerd, Christopher; Breedon, Richard; Burns, Dustin; Calderon De La Barca Sanchez, Manuel; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Erbacher, Robin; Flores, Chad; Funk, Garrett; Ko, Winston; Kukral, Ota; Lander, Richard; Mclean, Christine; Mulhearn, Michael; Pellett, Dave; Pilot, Justin; Shalhout, Shalhout; Shi, Mengyao; Stolp, Dustin; Taylor, Devin; Tos, Kyle; Tripathi, Mani; Wang, Zhangqier; Zhang, Fengwangdong; Bachtis, Michail; Bravo, Cameron; Cousins, Robert; Dasgupta, Abhigyan; Florent, Alice; Hauser, Jay; Ignatenko, Mikhail; Mccoll, Nickolas; Regnard, Simon; Saltzberg, David; Schnaible, Christian; Valuev, Vyacheslav; Bouvier, Elvire; Burt, Kira; Clare, Robert; Gary, J William; Ghiasi Shirazi, Seyyed Mohammad Amin; Hanson, Gail; Karapostoli, Georgia; Kennedy, Elizabeth; Lacroix, Florent; Long, Owen Rosser; Olmedo Negrete, Manuel; Paneva, Mirena Ivova; Si, Weinan; Wang, Long; Wei, Hua; Wimpenny, Stephen; Yates, Brent; Branson, James G; Cittolin, Sergio; Derdzinski, Mark; Gerosa, Raffaele; Gilbert, Dylan; Hashemi, Bobak; Holzner, André; Klein, Daniel; Kole, Gouranga; Krutelyov, Vyacheslav; Letts, James; Masciovecchio, Mario; Olivito, Dominick; Padhi, Sanjay; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Simon, Sean; Tadel, Matevz; Vartak, Adish; Wasserbaech, Steven; Wood, John; Würthwein, Frank; Yagil, Avraham; Zevi Della Porta, Giovanni; Amin, Nick; Bhandari, Rohan; Bradmiller-Feld, John; Campagnari, Claudio; Citron, Matthew; Dishaw, Adam; Dutta, Valentina; Franco Sevilla, Manuel; Gouskos, Loukas; Heller, Ryan; Incandela, Joe; Ovcharova, Ana; Qu, Huilin; Richman, Jeffrey; Stuart, David; Suarez, Indara; Wang, Sicheng; Yoo, Jaehyeok; Anderson, Dustin; Bornheim, Adolf; Bunn, Julian; Lawhorn, Jay Mathew; Newman, Harvey B; Nguyen, Thong; Spiropulu, Maria; Vlimant, Jean-Roch; Wilkinson, Richard; Xie, Si; Zhang, Zhicai; Zhu, Ren-Yuan; Andrews, Michael Benjamin; Ferguson, Thomas; Mudholkar, Tanmay; Paulini, Manfred; Sun, Menglei; Vorobiev, Igor; Weinberg, Marc; Cumalat, John Perry; Ford, William T; Jensen, Frank; Johnson, Andrew; Krohn, Michael; Leontsinis, Stefanos; MacDonald, Emily; Mulholland, Troy; Stenson, Kevin; Ulmer, Keith; Wagner, Stephen Robert; Alexander, James; Chaves, Jorge; Cheng, Yangyang; Chu, Jennifer; Datta, Abhisek; Mcdermott, Kevin; Mirman, Nathan; Patterson, Juliet Ritchie; Quach, Dan; Rinkevicius, Aurelijus; Ryd, Anders; Skinnari, Louise; Soffi, Livia; Tan, Shao Min; Tao, Zhengcheng; Thom, Julia; Tucker, Jordan; Wittich, Peter; Zientek, Margaret; Abdullin, Salavat; Albrow, Michael; Alyari, Maral; Apollinari, Giorgio; Apresyan, Artur; Apyan, Aram; Banerjee, Sunanda; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Bolla, Gino; Burkett, Kevin; Butler, Joel Nathan; Canepa, Anadi; Cerati, Giuseppe Benedetto; Cheung, Harry; Chlebana, Frank; Cremonesi, Matteo; Duarte, Javier; Elvira, Victor Daniel; Freeman, Jim; Gecse, Zoltan; Gottschalk, Erik; Gray, Lindsey; Green, Dan; Grünendahl, Stefan; Gutsche, Oliver; Hanlon, Jim; Harris, Robert M; Hasegawa, Satoshi; Hirschauer, James; Hu, Zhen; Jayatilaka, Bodhitha; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Klima, Boaz; Kortelainen, Matti J; Kreis, Benjamin; Lammel, Stephan; Lincoln, Don; Lipton, Ron; Liu, Miaoyuan; Liu, Tiehui; Lykken, Joseph; Maeshima, Kaori; Magini, Nicolo; Marraffino, John Michael; Mason, David; McBride, Patricia; Merkel, Petra; Mrenna, Stephen; Nahn, Steve; O'Dell, Vivian; Pedro, Kevin; Pena, Cristian; Prokofyev, Oleg; Rakness, Gregory; Ristori, Luciano; Savoy-Navarro, Aurore; Schneider, Basil; Sexton-Kennedy, Elizabeth; Soha, Aron; Spalding, William J; Spiegel, Leonard; Stoynev, Stoyan; Strait, James; Strobbe, Nadja; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vernieri, Caterina; Verzocchi, Marco; Vidal, Richard; Wang, Michael; Weber, Hannsjoerg Artur; Whitbeck, Andrew; Acosta, Darin; Avery, Paul; Bortignon, Pierluigi; Bourilkov, Dimitri; Brinkerhoff, Andrew; Cadamuro, Luca; Carnes, Andrew; Carver, Matthew; Curry, David; Field, Richard D; Gleyzer, Sergei V; Joshi, Bhargav Madhusudan; Konigsberg, Jacobo; Korytov, Andrey; Ma, Peisen; Matchev, Konstantin; Mei, Hualin; Mitselmakher, Guenakh; Shi, Kun; Sperka, David; Wang, Jian; Wang, Sean-Jiun; Joshi, Yagya Raj; Linn, Stephan; Ackert, Andrew; Adams, Todd; Askew, Andrew; Hagopian, Sharon; Hagopian, Vasken; Johnson, Kurtis F; Kolberg, Ted; Martinez, German; Perry, Thomas; Prosper, Harrison; Saha, Anirban; Santra, Arka; Sharma, Varun; Yohay, Rachel; Baarmand, Marc M; Bhopatkar, Vallary; Colafranceschi, Stefano; Hohlmann, Marcus; Noonan, Daniel; Roy, Titas; Yumiceva, Francisco; Adams, Mark Raymond; Apanasevich, Leonard; Berry, Douglas; Betts, Russell Richard; Cavanaugh, Richard; Chen, Xuan; Dittmer, Susan; Evdokimov, Olga; Gerber, Cecilia Elena; Hangal, Dhanush Anil; Hofman, David Jonathan; Jung, Kurt; Kamin, Jason; Mills, Corrinne; Sandoval Gonzalez, Irving Daniel; Tonjes, Marguerite; Varelas, Nikos; Wang, Hui; Wu, Zhenbin; Zhang, Jingyu; Alhusseini, Mohammad; Bilki, Burak; Clarida, Warren; Dilsiz, Kamuran; Durgut, Süleyman; Gandrajula, Reddy Pratap; Haytmyradov, Maksat; Khristenko, Viktor; Merlo, Jean-Pierre; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Ogul, Hasan; Onel, Yasar; Ozok, Ferhat; Penzo, Aldo; Snyder, Christina; Tiras, Emrah; Wetzel, James; Blumenfeld, Barry; Cocoros, Alice; Eminizer, Nicholas; Fehling, David; Feng, Lei; Gritsan, Andrei; Hung, Wai Ting; Maksimovic, Petar; Roskes, Jeffrey; Sarica, Ulascan; Swartz, Morris; Xiao, Meng; You, Can; Al-bataineh, Ayman; Baringer, Philip; Bean, Alice; Boren, Samuel; Bowen, James; Castle, James; Khalil, Sadia; Kropivnitskaya, Anna; Majumder, Devdatta; Mcbrayer, William; Murray, Michael; Rogan, Christopher; Sanders, Stephen; Schmitz, Erich; Tapia Takaki, Daniel; Wang, Quan; Ivanov, Andrew; Kaadze, Ketino; Kim, Doyeong; Maravin, Yurii; Mendis, Dalath Rachitha; Mitchell, Tyler; Modak, Atanu; Mohammadi, Abdollah; Saini, Lovedeep Kaur; Skhirtladze, Nikoloz; Rebassoo, Finn; Wright, Douglas; Baden, Drew; Baron, Owen; Belloni, Alberto; Eno, Sarah Catherine; Feng, Yongbin; Ferraioli, Charles; Hadley, Nicholas John; Jabeen, Shabnam; Jeng, Geng-Yuan; Kellogg, Richard G; Kunkle, Joshua; Mignerey, Alice; Ricci-Tam, Francesca; Shin, Young Ho; Skuja, Andris; Tonwar, Suresh C; Wong, Kak; Abercrombie, Daniel; Allen, Brandon; Azzolini, Virginia; Barbieri, Richard; Baty, Austin; Bauer, Gerry; Bi, Ran; Brandt, Stephanie; Busza, Wit; Cali, Ivan Amos; D'Alfonso, Mariarosaria; Demiragli, Zeynep; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Harris, Philip; Hsu, Dylan; Hu, Miao; Iiyama, Yutaro; Innocenti, Gian Michele; Klute, Markus; Kovalskyi, Dmytro; Lee, Yen-Jie; Levin, Andrew; Luckey, Paul David; Maier, Benedikt; Marini, Andrea Carlo; Mcginn, Christopher; Mironov, Camelia; Narayanan, Siddharth; Niu, Xinmei; Paus, Christoph; Roland, Christof; Roland, Gunther; Stephans, George; Sumorok, Konstanty; Tatar, Kaya; Velicanu, Dragos; Wang, Jing; Wang, Ta-Wei; Wyslouch, Bolek; Zhaozhong, Shi; Benvenuti, Alberto; Chatterjee, Rajdeep Mohan; Evans, Andrew; Hansen, Peter; Kalafut, Sean; Kubota, Yuichi; Lesko, Zachary; Mans, Jeremy; Nourbakhsh, Shervin; Ruckstuhl, Nicole; Rusack, Roger; Turkewitz, Jared; Wadud, Mohammad Abrar; Acosta, John Gabriel; Oliveros, Sandra; Avdeeva, Ekaterina; Bloom, Kenneth; Claes, Daniel R; Fangmeier, Caleb; Golf, Frank; Gonzalez Suarez, Rebeca; Kamalieddin, Rami; Kravchenko, Ilya; Monroy, Jose; Siado, Joaquin Emilo; Snow, Gregory R; Stieger, Benjamin; Godshalk, Andrew; Harrington, Charles; Iashvili, Ia; Kharchilava, Avto; Nguyen, Duong; Parker, Ashley; Rappoccio, Salvatore; Roozbahani, Bahareh; Alverson, George; Barberis, Emanuela; Freer, Chad; Hortiangtham, Apichart; Morse, David Michael; Orimoto, Toyoko; Teixeira De Lima, Rafael; Wamorkar, Tanvi; Wang, Bingran; Wisecarver, Andrew; Wood, Darien; Bhattacharya, Saptaparna; Charaf, Otman; Hahn, Kristan Allan; Mucia, Nicholas; Odell, Nathaniel; Schmitt, Michael Henry; Sung, Kevin; Trovato, Marco; Velasco, Mayda; Bucci, Rachael; Dev, Nabarun; Hildreth, Michael; Hurtado Anampa, Kenyi; Jessop, Colin; Karmgard, Daniel John; Kellams, Nathan; Lannon, Kevin; Li, Wenzhao; Loukas, Nikitas; Marinelli, Nancy; Meng, Fanbo; Mueller, Charles; Musienko, Yuri; Planer, Michael; Reinsvold, Allison; Ruchti, Randy; Siddireddy, Prasanna; Smith, Geoffrey; Taroni, Silvia; Wayne, Mitchell; Wightman, Andrew; Wolf, Matthias; Woodard, Anna; Alimena, Juliette; Antonelli, Louis; Bylsma, Ben; Durkin, Lloyd Stanley; Flowers, Sean; Francis, Brian; Hart, Andrew; Hill, Christopher; Ji, Weifeng; Ling, Ta-Yung; Luo, Wuming; Winer, Brian L; Wulsin, Howard Wells; Cooperstein, Stephane; Elmer, Peter; Hardenbrook, Joshua; Hebda, Philip; Higginbotham, Samuel; Kalogeropoulos, Alexis; Lange, David; Luo, Jingyu; Marlow, Daniel; Mei, Kelvin; Ojalvo, Isabel; Olsen, James; Palmer, Christopher; Piroué, Pierre; Salfeld-Nebgen, Jakob; Stickland, David; Tully, Christopher; Malik, Sudhir; Norberg, Scarlet; Barker, Anthony; Barnes, Virgil E; Das, Souvik; Gutay, Laszlo; Jones, Matthew; Jung, Andreas Werner; Khatiwada, Ajeeta; Miller, David Harry; Neumeister, Norbert; Peng, Cheng-Chieh; Qiu, Hao; Schulte, Jan-Frederik; Sun, Jian; Wang, Fuqiang; Xiao, Rui; Xie, Wei; Cheng, Tongguang; Dolen, James; Parashar, Neeti; Chen, Zhenyu; Ecklund, Karl Matthew; Freed, Sarah; Geurts, Frank JM; Guilbaud, Maxime; Kilpatrick, Matthew; Li, Wei; Michlin, Benjamin; Padley, Brian Paul; Roberts, Jay; Rorie, Jamal; Shi, Wei; Tu, Zhoudunming; Zabel, James; Zhang, Aobo; Bodek, Arie; de Barbaro, Pawel; Demina, Regina; Duh, Yi-ting; Dulemba, Joseph Lynn; Fallon, Colin; Ferbel, Thomas; Galanti, Mario; Garcia-Bellido, Aran; Han, Jiyeon; Hindrichs, Otto; Khukhunaishvili, Aleko; Lo, Kin Ho; Tan, Ping; Taus, Rhys; Verzetti, Mauro; Agapitos, Antonis; Chou, John Paul; Gershtein, Yuri; Gómez Espinosa, Tirso Alejandro; Halkiadakis, Eva; Heindl, Maximilian; Hughes, Elliot; Kaplan, Steven; Kunnawalkam Elayavalli, Raghav; Kyriacou, Savvas; Lath, Amitabh; Montalvo, Roy; Nash, Kevin; Osherson, Marc; Saka, Halil; Salur, Sevil; Schnetzer, Steve; Sheffield, David; Somalwar, Sunil; Stone, Robert; Thomas, Scott; Thomassen, Peter; Walker, Matthew; Delannoy, Andrés G; Heideman, Joseph; Riley, Grant; Rose, Keith; Spanier, Stefan; Thapa, Krishna; Bouhali, Othmane; Castaneda Hernandez, Alfredo; Celik, Ali; Dalchenko, Mykhailo; De Mattia, Marco; Delgado, Andrea; Dildick, Sven; Eusebi, Ricardo; Gilmore, Jason; Huang, Tao; Kamon, Teruki; Mueller, Ryan; Pakhotin, Yuriy; Patel, Rishi; Perloff, Alexx; Perniè, Luca; Rathjens, Denis; Safonov, Alexei; Tatarinov, Aysen; Akchurin, Nural; Damgov, Jordan; De Guio, Federico; Dudero, Phillip Russell; Kunori, Shuichi; Lamichhane, Kamal; Lee, Sung Won; Mengke, Tielige; Muthumuni, Samila; Peltola, Timo; Undleeb, Sonaina; Volobouev, Igor; Wang, Zhixing; Greene, Senta; Gurrola, Alfredo; Janjam, Ravi; Johns, Willard; Maguire, Charles; Melo, Andrew; Ni, Hong; Padeken, Klaas; Ruiz Alvarez, José David; Sheldon, Paul; Tuo, Shengquan; Velkovska, Julia; Xu, Qiao; Arenton, Michael Wayne; Barria, Patrizia; Cox, Bradley; Hirosky, Robert; Joyce, Matthew; Ledovskoy, Alexander; Li, Hengne; Neu, Christopher; Sinthuprasith, Tutanon; Wang, Yanchu; Wolfe, Evan; Xia, Fan; Harr, Robert; Karchin, Paul Edmund; Poudyal, Nabin; Sturdy, Jared; Thapa, Prakash; Zaleski, Shawn; Brodski, Michael; Buchanan, James; Caillol, Cécile; Carlsmith, Duncan; Dasu, Sridhara; Dodd, Laura; Duric, Senka; Gomber, Bhawna; Grothe, Monika; Herndon, Matthew; Hervé, Alain; Hussain, Usama; Klabbers, Pamela; Lanaro, Armando; Levine, Aaron; Long, Kenneth; Loveless, Richard; Ruggles, Tyler; Savin, Alexander; Smith, Nicholas; Smith, Wesley H; Woods, Nathaniel

    2018-01-01

    A search for Higgs bosons that decay into a bottom quark-antiquark pair and are accompanied by at least one additional bottom quark is performed with the CMS detector. The data analyzed were recorded in proton-proton collisions at a centre-of-mass energy of $\\sqrt{s} = $ 13 TeV at the LHC, corresponding to an integrated luminosity of 35.7 fb$^{-1}$. The final state considered in this analysis is particularly sensitive to signatures of a Higgs sector beyond the standard model, as predicted in the generic class of two Higgs doublet models (2HDMs). No signal above the standard model background expectation is observed. Stringent upper limits on the cross section times branching fraction are set for Higgs bosons with masses up to 1300 GeV. The results are interpreted within several MSSM and 2HDM scenarios.

  5. Tests of the Standard Model and Constraints on New Physics from Measurements of Fermion-Pair Production at 189-209 GeV at LEP

    CERN Document Server

    Abbiendi, G.; Akesson, P.F.; Alexander, G.; Allison, John; Amaral, P.; Anagnostou, G.; Anderson, K.J.; Arcelli, S.; Asai, S.; Axen, D.; Azuelos, G.; Bailey, I.; Barberio, E.; Barillari, T.; Barlow, R.J.; Batley, R.J.; Bechtle, P.; Behnke, T.; Bell, Kenneth Watson; Bell, P.J.; Bella, G.; Bellerive, A.; Benelli, G.; Bethke, S.; Biebel, O.; Boeriu, O.; Bock, P.; Boutemeur, M.; Braibant, S.; Brigliadori, L.; Brown, Robert M.; Buesser, K.; Burckhart, H.J.; Campana, S.; Carnegie, R.K.; Caron, B.; Carter, A.A.; Carter, J.R.; Chang, C.Y.; Charlton, David G.; Ciocca, C.; Csilling, A.; Cuffiani, M.; Dado, S.; De Roeck, A.; De Wolf, E.A.; Desch, K.; Dienes, B.; Donkers, M.; Dubbert, J.; Duchovni, E.; Duckeck, G.; Duerdoth, I.P.; Etzion, E.; Fabbri, F.; Feld, L.; Ferrari, P.; Fiedler, F.; Fleck, I.; Ford, M.; Frey, A.; Furtjes, A.; Gagnon, P.; Gary, John William; Gaycken, G.; Geich-Gimbel, C.; Giacomelli, G.; Giacomelli, P.; Giunta, Marina; Goldberg, J.; Gross, E.; Grunhaus, J.; Gruwe, M.; Gunther, P.O.; Gupta, A.; Hajdu, C.; Hamann, M.; Hanson, G.G.; Harel, A.; Hauschild, M.; Hawkes, C.M.; Hawkings, R.; Hemingway, R.J.; Hensel, C.; Herten, G.; Heuer, R.D.; Hill, J.C.; Hoffman, Kara Dion; Horvath, D.; Igo-Kemenes, P.; Ishii, K.; Jeremie, H.; Jovanovic, P.; Junk, T.R.; Kanaya, N.; Kanzaki, J.; Karlen, D.; Kawagoe, K.; Kawamoto, T.; Keeler, R.K.; Kellogg, R.G.; Kennedy, B.W.; Klein, K.; Klier, A.; Kluth, S.; Kobayashi, T.; Kobel, M.; Komamiya, S.; Kormos, Laura L.; Kramer, T.; Krieger, P.; von Krogh, J.; Kruger, K.; Kuhl, T.; Kupper, M.; Lafferty, G.D.; Landsman, H.; Lanske, D.; Layter, J.G.; Lellouch, D.; Lettso, J.; Levinson, L.; Lillich, J.; Lloyd, S.L.; Loebinger, F.K.; Lu, J.; Ludwig, A.; Ludwig, J.; Macpherson, A.; Mader, W.; Marcellini, S.; Martin, A.J.; Masetti, G.; Mashimo, T.; Mattig, Peter; McDonald, W.J.; McKenna, J.; McMahon, T.J.; McPherson, R.A.; Meijers, F.; Menges, W.; Merritt, F.S.; Mes, H.; Michelini, A.; Mihara, S.; Mikenberg, G.; Miller, D.J.; Moed, S.; Mohr, W.; Mori, T.; Mutter, A.; Nagai, K.; Nakamura, I.; Nanjo, H.; Neal, H.A.; Nisius, R.; O'Neale, S.W.; Oh, A.; Okpara, A.; Oreglia, M.J.; Orito, S.; Pahl, C.; Pasztor, G.; Pater, J.R.; Pilcher, J.E.; Pinfold, J.; Plane, David E.; Poli, B.; Polok, J.; Pooth, O.; Przybycien, M.; Quadt, A.; Rabbertz, K.; Rembser, C.; Renkel, P.; Roney, J.M.; Rosati, S.; Rozen, Y.; Runge, K.; Sachs, K.; Saeki, T.; Sarkisyan, E.K.G.; Schaile, A.D.; Schaile, O.; Scharff-Hansen, P.; Schieck, J.; Schoerner-Sadenius, Thomas; Schroder, Matthias; Schumacher, M.; Schwick, C.; Scott, W.G.; Seuster, R.; Shears, T.G.; Shen, B.C.; Sherwood, P.; Skuja, A.; Smith, A.M.; Sobie, R.; Soldner-Rembold, S.; Spano, F.; Stahl, A.; Stephens, K.; Strom, David M.; Strohmer, R.; Tarem, S.; Tasevsky, M.; Teuscher, R.; Thomson, M.A.; Torrence, E.; Toya, D.; Tran, P.; Trigger, I.; Trocsanyi, Z.; Tsur, E.; Turner-Watson, M.F.; Ueda, I.; Ujvari, B.; Vollmer, C.F.; Vannerem, P.; Vertesi, R.; Verzocchi, M.; Voss, H.; Vossebeld, J.; Waller, D.; Ward, C.P.; Ward, D.R.; Watkins, P.M.; Watson, A.T.; Watson, N.K.; Wells, P.S.; Wengler, T.; Wermes, N.; Wetterling, D.; Wilson, G.W.; Wilson, J.A.; Wolf, G.; Wyatt, T.R.; Yamashita, S.; Zer-Zion, D.; Zivkovic, Lidija

    2004-01-01

    Cross-section and angular distributions for hadronic and lepton-pair final states in e+e- collisions at centre-of-mass energies between 189 GeV and 209 GeV, measured with the OPAL detector at LEP, are presented and compared with the predictions of the Standard Model. The measurements are used to determine the electromagnetic coupling constant alphaem at LEP2 energies. In addition, the results are used together with OPAL measurements at 91-183 GeV within the S-matrix formalism to determine the gamma-Z interference term and to make an almost model-independent measurement of the Z mass. Limits on extensions to the Standard Model described by effective four-fermion contact interactions or the addition of a heavy Z boson are also presented.

  6. Plant control using embedded predictive models

    International Nuclear Information System (INIS)

    Godbole, S.S.; Gabler, W.E.; Eschbach, S.L.

    1990-01-01

    B and W recently undertook the design of an advanced light water reactor control system. A concept new to nuclear steam system (NSS) control was developed. The concept, which is called the Predictor-Corrector, uses mathematical models of portions of the controlled NSS to calculate, at various levels within the system, demand and control element position signals necessary to satisfy electrical demand. The models give the control system the ability to reduce overcooling and undercooling of the reactor coolant system during transients and upsets. Two types of mathematical models were developed for use in designing and testing the control system. One model was a conventional, comprehensive NSS model that responds to control system outputs and calculates the resultant changes in plant variables that are then used as inputs to the control system. Two other models, embedded in the control system, were less conventional, inverse models. These models accept as inputs plant variables, equipment states, and demand signals and predict plant operating conditions and control element states that will satisfy the demands. This paper reports preliminary results of closed-loop Reactor Coolant (RC) pump trip and normal load reduction testing of the advanced concept. Results of additional transient testing, and of open and closed loop stability analyses will be reported as they are available

  7. Diagnosing holographic type dark energy models with the Statefinder hierarchy, composite null diagnostic and w- w' pair

    Science.gov (United States)

    Zhao, Ze; Wang, Shuang

    2018-03-01

    The main purpose of this work is to distinguish various holographic type dark energy (DE) models, including the ΛHDE, HDE, NADE, and RDE model, by using various diagnostic tools. The first diagnostic tool is the Statefinder hierarchy, in which the evolution of Statefinder hierarchy parmeter S (1) 3( z) and S (1) 4( z) are studied. The second is composite null diagnostic (CND), in which the trajectories of { S (1) 3, ɛ} and { S (1) 4, ɛ} are investigated, where ɛ is the fractional growth parameter. The last is w-w' analysis, where w is the equation of state for DE and the prime denotes derivative with respect to ln a. In the analysis we consider two cases: varying current fractional DE density Ω de0 and varying DE model parameter C. We find that: (1) both the Statefinder hierarchy and the CND have qualitative impact on ΛHDE, but only have quantitative impact on HDE. (2) S (1) 4 can lead to larger differences than S (1) 3, while the CND pair has a stronger ability to distinguish different models than the Statefinder hierarchy. (3) For the case of varying C, the { w,w'} pair has qualitative impact on ΛHDE; for the case of varying Ω de0, the { w, w'} pair only has quantitative impact; these results are different from the cases of HDE, RDE, and NADE, in which the {w,w'} pair only has quantitative impact on these models. In conclusion, compared with HDE, RDE, and NADE, the ΛHDE model can be easily distinguished by using these diagnostic tools.

  8. Pair- ${v}$ -SVR: A Novel and Efficient Pairing nu-Support Vector Regression Algorithm.

    Science.gov (United States)

    Hao, Pei-Yi

    This paper proposes a novel and efficient pairing nu-support vector regression (pair--SVR) algorithm that combines successfully the superior advantages of twin support vector regression (TSVR) and classical -SVR algorithms. In spirit of TSVR, the proposed pair--SVR solves two quadratic programming problems (QPPs) of smaller size rather than a single larger QPP, and thus has faster learning speed than classical -SVR. The significant advantage of our pair--SVR over TSVR is the improvement in the prediction speed and generalization ability by introducing the concepts of the insensitive zone and the regularization term that embodies the essence of statistical learning theory. Moreover, pair--SVR has additional advantage of using parameter for controlling the bounds on fractions of SVs and errors. Furthermore, the upper bound and lower bound functions of the regression model estimated by pair--SVR capture well the characteristics of data distributions, thus facilitating automatic estimation of the conditional mean and predictive variance simultaneously. This may be useful in many cases, especially when the noise is heteroscedastic and depends strongly on the input values. The experimental results validate the superiority of our pair--SVR in both training/prediction speed and generalization ability.This paper proposes a novel and efficient pairing nu-support vector regression (pair--SVR) algorithm that combines successfully the superior advantages of twin support vector regression (TSVR) and classical -SVR algorithms. In spirit of TSVR, the proposed pair--SVR solves two quadratic programming problems (QPPs) of smaller size rather than a single larger QPP, and thus has faster learning speed than classical -SVR. The significant advantage of our pair--SVR over TSVR is the improvement in the prediction speed and generalization ability by introducing the concepts of the insensitive zone and the regularization term that embodies the essence of statistical learning theory

  9. Ground Motion Prediction Models for Caucasus Region

    Science.gov (United States)

    Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

    2016-04-01

    Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

  10. Modeling and Prediction of Krueger Device Noise

    Science.gov (United States)

    Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

    2016-01-01

    This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.

  11. Prediction of Chemical Function: Model Development and ...

    Science.gov (United States)

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

  12. Evaluating Predictive Models of Software Quality

    Science.gov (United States)

    Ciaschini, V.; Canaparo, M.; Ronchieri, E.; Salomoni, D.

    2014-06-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  13. Predicting FLDs Using a Multiscale Modeling Scheme

    Science.gov (United States)

    Wu, Z.; Loy, C.; Wang, E.; Hegadekatte, V.

    2017-09-01

    The measurement of a single forming limit diagram (FLD) requires significant resources and is time consuming. We have developed a multiscale modeling scheme to predict FLDs using a combination of limited laboratory testing, crystal plasticity (VPSC) modeling, and dual sequential-stage finite element (ABAQUS/Explicit) modeling with the Marciniak-Kuczynski (M-K) criterion to determine the limit strain. We have established a means to work around existing limitations in ABAQUS/Explicit by using an anisotropic yield locus (e.g., BBC2008) in combination with the M-K criterion. We further apply a VPSC model to reduce the number of laboratory tests required to characterize the anisotropic yield locus. In the present work, we show that the predicted FLD is in excellent agreement with the measured FLD for AA5182 in the O temper. Instead of 13 different tests as for a traditional FLD determination within Novelis, our technique uses just four measurements: tensile properties in three orientations; plane strain tension; biaxial bulge; and the sheet crystallographic texture. The turnaround time is consequently far less than for the traditional laboratory measurement of the FLD.

  14. PREDICTION MODELS OF GRAIN YIELD AND CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    Narciso Ysac Avila Serrano

    2009-06-01

    Full Text Available With the objective to characterize the grain yield of five cowpea cultivars and to find linear regression models to predict it, a study was developed in La Paz, Baja California Sur, Mexico. A complete randomized blocks design was used. Simple and multivariate analyses of variance were carried out using the canonical variables to characterize the cultivars. The variables cluster per plant, pods per plant, pods per cluster, seeds weight per plant, seeds hectoliter weight, 100-seed weight, seeds length, seeds wide, seeds thickness, pods length, pods wide, pods weight, seeds per pods, and seeds weight per pods, showed significant differences (P≤ 0.05 among cultivars. Paceño and IT90K-277-2 cultivars showed the higher seeds weight per plant. The linear regression models showed correlation coefficients ≥0.92. In these models, the seeds weight per plant, pods per cluster, pods per plant, cluster per plant and pods length showed significant correlations (P≤ 0.05. In conclusion, the results showed that grain yield differ among cultivars and for its estimation, the prediction models showed determination coefficients highly dependable.

  15. Evaluating predictive models of software quality

    International Nuclear Information System (INIS)

    Ciaschini, V; Canaparo, M; Ronchieri, E; Salomoni, D

    2014-01-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  16. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  17. Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

    Science.gov (United States)

    Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

    2015-01-01

    Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

  18. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  19. An Anisotropic Hardening Model for Springback Prediction

    Science.gov (United States)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  20. An Anisotropic Hardening Model for Springback Prediction

    International Nuclear Information System (INIS)

    Zeng, Danielle; Xia, Z. Cedric

    2005-01-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test

  1. Dietary lead intakes for mother/child pairs and relevance to pharmacokinetic models.

    OpenAIRE

    Gulson, B L; Mahaffey, K R; Vidal, M; Jameson, C W; Law, A J; Mizon, K J; Smith, A J; Korsch, M J

    1997-01-01

    Blood and environmental samples, including a quarterly 6-day duplicate diet, for nine mother/child pairs from Eastern Europe have been monitored for 12 to >24 months with high precision stable lead isotope analysis to evaluate the changes that occur when the subjects moved from one environment (Eastern Europe) to another with different stable lead isotopes (Australia). The children were between 6 and 11 years of age and the mothers were between 29 and 37 years of age. These data were compared...

  2. Exactly solvable model of transitional nuclei based on dual algebraic structure for the three level pairing model in the framework of sdg interacting boson model

    Science.gov (United States)

    Jafarizadeh, M. A.; Ranjbar, Z.; Fouladi, N.; Ghapanvari, M.

    2018-01-01

    In this paper, a successful algebraic method based on the dual algebraic structure for three level pairing model in the framework of sdg IBM is proposed for transitional nuclei which show transitional behavior from spherical to gamma-unstable quantum shape phase transition. In this method complicated sdg Hamiltonian, which is a three level pairing Hamiltonian is determined easily via the exactly solvable method. This description provides a better interpretation of some observables such as BE (4) in nuclei which exhibits the necessity of inclusion of g boson in the sd IBM, while BE (4) cannot be explained in the sd boson model. Some observables such as Energy levels, BE (2), BE (4), the two neutron separation energies signature splitting of the γ-vibrational band and expectation values of the g-boson number operator are calculated and examined for 46 104 - 110Pd isotopes.

  3. Sordaria, a model system to uncover links between meiotic pairing and recombination.

    Science.gov (United States)

    Zickler, Denise; Espagne, Eric

    2016-06-01

    The mycelial fungus Sordaria macrospora was first used as experimental system for meiotic recombination. This review shows that it provides also a powerful cytological system for dissecting chromosome dynamics in wild-type and mutant meioses. Fundamental cytogenetic findings include: (1) the identification of presynaptic alignment as a key step in pairing of homologous chromosomes. (2) The discovery that biochemical complexes that mediate recombination at the DNA level concomitantly mediate pairing of homologs. (3) This pairing process involves not only resolution but also avoidance of chromosomal entanglements and the resolution system includes dissolution of constraining DNA recombination interactions, achieved by a unique role of Mlh1. (4) Discovery that the central components of the synaptonemal complex directly mediate the re-localization of the recombination proteins from on-axis to in-between homologue axis positions. (5) Identification of putative STUbL protein Hei10 as a structure-based signal transduction molecule that coordinates progression and differentiation of recombinational interactions at multiple stages. (6) Discovery that a single interference process mediates both nucleation of the SC and designation of crossover sites, thereby ensuring even spacing of both features. (7) Discovery of local modulation of sister-chromatid cohesion at sites of crossover recombination. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. The prediction of semantic consistency in self-descriptions: characteristics of persons and of terms that affect the consistency of responses to synonym and antonym pairs.

    Science.gov (United States)

    Goldberg, L R; Kilkowski, J M

    1985-01-01

    Subjects described themselves, using an alphabetically ordered list of 191 trait adjectives, which included sets of synonyms and antonyms, half of each type more difficult than the other half. Subjects were randomly assigned to one of two experimental conditions. In one condition, each adjective was listed with its dictionary definition; in the other condition, only the adjectives were listed. All subjects were administered a battery of demographic, cognitive, and personality measures. We analyzed both the relative consistency elicited by different pairs of terms and the individual differences in semantic consistency displayed by different sorts of subjects. Although the provision of definitions served to increase consistency (especially for the difficult antonyms), it did not decrease the range of consistency values across either synonym or antonym pairs. And, although interpair differences in semantic consistency were as difficult to predict in this study as in previous ones, individual differences were highly predictable. The implications of our many findings are discussed in the context of various hypotheses about semantic inconsistency in self-reports.

  5. Search for a non-standard-model Higgs boson decaying to a pair of new light bosons in four-muon final states

    Energy Technology Data Exchange (ETDEWEB)

    Chatrchyan, Serguei; et al.

    2013-11-01

    Results are reported from a search for non-standard-model Higgs boson decays to pairs of new light bosons, each of which decays into the μ+μ- final state. The new bosons may be produced either promptly or via a decay chain. The data set corresponds to an integrated luminosity of 5.3 fb-1 of proton–proton collisions at √s = 7 TeV, recorded by the CMS experiment at the LHC in 2011. Such Higgs boson decays are predicted in several scenarios of new physics, including supersymmetric models with extended Higgs sectors or hidden valleys. Thus, the results of the search are relevant for establishing whether the new particle observed in Higgs boson searches at the LHC has the properties expected for a standard model Higgs boson. No excess of events is observed with respect to the yields expected from standard model processes. A model-independent upper limit of 0.86±0.06 fb on the product of the cross section times branching fraction times acceptance is obtained. Finally, the results, which are applicable to a broad spectrum of new physics scenarios, are compared with the predictions of two benchmark models as functions of a Higgs boson mass larger than 86 GeV/c2 and of a new light boson mass within the range 0.25–3.55 GeV/c2.

  6. Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

    Directory of Open Access Journals (Sweden)

    Donald Adjeroh

    2018-03-01

    Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

  7. Mahonian pairs

    OpenAIRE

    Sagan, Bruce E.; Savage, Carla D.

    2012-01-01

    We introduce the notion of a Mahonian pair. Consider the set, P^*, of all words having the positive integers as alphabet. Given finite subsets S,T of P^*, we say that (S,T) is a Mahonian pair if the distribution of the major index, maj, over S is the same as the distribution of the inversion number, inv, over T. So the well-known fact that maj and inv are equidistributed over the symmetric group, S_n, can be expressed by saying that (S_n,S_n) is a Mahonian pair. We investigate various Mahonia...

  8. Energies of the ground state and first excited 0 sup + state in an exactly solvable pairing model

    CERN Document Server

    Dinh Dang, N

    2003-01-01

    Several approximations are tested by calculating the ground-state energy and the energy of the first excited 0 sup + state using an exactly solvable model with two symmetric levels interacting via a pairing force. They are the BCS approximation (BCS), Lipkin-Nogami (LN) method, random-phase approximation (RPA), quasiparticle RPA (QRPA), the renormalized RPA (RRPA), and renormalized QRPA (RQRPA). It is shown that, in the strong-coupling regime, the QRPA which neglects the scattering term of the model Hamiltonian offers the best fit to the exact solutions. A recipe is proposed using the RRPA and RQRPA in combination with the pairing gap given by the LN method. Applying this recipe, it is shown that the superfluid-normal phase transition is avoided, and a reasonably good description for both of the ground-state energy and the energy of the first excited 0 sup + state is achieved. (orig.)

  9. A mathematical model for source separation of MMG signals recorded with a coupled microphone-accelerometer sensor pair.

    Science.gov (United States)

    Silva, Jorge; Chau, Tom

    2005-09-01

    Recent advances in sensor technology for muscle activity monitoring have resulted in the development of a coupled microphone-accelerometer sensor pair for physiological acousti signal recording. This sensor can be used to eliminate interfering sources in practical settings where the contamination of an acoustic signal by ambient noise confounds detection but cannot be easily removed [e.g., mechanomyography (MMG), swallowing sounds, respiration, and heart sounds]. This paper presents a mathematical model for the coupled microphone-accelerometer vibration sensor pair, specifically applied to muscle activity monitoring (i.e., MMG) and noise discrimination in externally powered prostheses for below-elbow amputees. While the model provides a simple and reliable source separation technique for MMG signals, it can also be easily adapted to other aplications where the recording of low-frequency (< 1 kHz) physiological vibration signals is required.

  10. PENINGKATAN HASIL BELAJAR PAI DENGAN MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SHARE DI SDN 2 PALAK TANAH MUARA ENIM

    Directory of Open Access Journals (Sweden)

    Elhefni Elhefni

    2010-11-01

    Full Text Available Abstract Teachers are expected to increase quality of learning outcomes in the learning process. This research aims to know whether Cooperative Learning type of think pair can improve learning outcomes of Islamic religious subject. Based on data analysis it conclude that before deploying this learning model the frequency of the overall student learning outcomes as follows: 6 students (15% is high (good, 26 students (65% classified as medium, and 8 students (20% is low. After application of the model the outcomes are as follows: high category (good 4 people (10% of students, moderate 28 people (70% of students, and a low 8 people (20% of students.  Keywords: religious subjects, type think pair share, learning outcomes 

  11. Web tools for predictive toxicology model building.

    Science.gov (United States)

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  12. Predictions of models for environmental radiological assessment

    International Nuclear Information System (INIS)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa; Mahler, Claudio Fernando

    2011-01-01

    In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for 137 Cs and 60 Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)

  13. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time......). Five technical and economic aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality...

  14. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  15. Effective modelling for predictive analytics in data science ...

    African Journals Online (AJOL)

    Effective modelling for predictive analytics in data science. ... the nearabsence of empirical or factual predictive analytics in the mainstream research going on ... Keywords: Predictive Analytics, Big Data, Business Intelligence, Project Planning.

  16. Combining GPS measurements and IRI model predictions

    International Nuclear Information System (INIS)

    Hernandez-Pajares, M.; Juan, J.M.; Sanz, J.; Bilitza, D.

    2002-01-01

    The free electrons distributed in the ionosphere (between one hundred and thousands of km in height) produce a frequency-dependent effect on Global Positioning System (GPS) signals: a delay in the pseudo-orange and an advance in the carrier phase. These effects are proportional to the columnar electron density between the satellite and receiver, i.e. the integrated electron density along the ray path. Global ionospheric TEC (total electron content) maps can be obtained with GPS data from a network of ground IGS (international GPS service) reference stations with an accuracy of few TEC units. The comparison with the TOPEX TEC, mainly measured over the oceans far from the IGS stations, shows a mean bias and standard deviation of about 2 and 5 TECUs respectively. The discrepancies between the STEC predictions and the observed values show an RMS typically below 5 TECUs (which also includes the alignment code noise). he existence of a growing database 2-hourly global TEC maps and with resolution of 5x2.5 degrees in longitude and latitude can be used to improve the IRI prediction capability of the TEC. When the IRI predictions and the GPS estimations are compared for a three month period around the Solar Maximum, they are in good agreement for middle latitudes. An over-determination of IRI TEC has been found at the extreme latitudes, the IRI predictions being, typically two times higher than the GPS estimations. Finally, local fits of the IRI model can be done by tuning the SSN from STEC GPS observations

  17. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  18. Mathematical models for indoor radon prediction

    International Nuclear Information System (INIS)

    Malanca, A.; Pessina, V.; Dallara, G.

    1995-01-01

    It is known that the indoor radon (Rn) concentration can be predicted by means of mathematical models. The simplest model relies on two variables only: the Rn source strength and the air exchange rate. In the Lawrence Berkeley Laboratory (LBL) model several environmental parameters are combined into a complex equation; besides, a correlation between the ventilation rate and the Rn entry rate from the soil is admitted. The measurements were carried out using activated carbon canisters. Seventy-five measurements of Rn concentrations were made inside two rooms placed on the second floor of a building block. One of the rooms had a single-glazed window whereas the other room had a double pane window. During three different experimental protocols, the mean Rn concentration was always higher into the room with a double-glazed window. That behavior can be accounted for by the simplest model. A further set of 450 Rn measurements was collected inside a ground-floor room with a grounding well in it. This trend maybe accounted for by the LBL model

  19. Towards predictive models for transitionally rough surfaces

    Science.gov (United States)

    Abderrahaman-Elena, Nabil; Garcia-Mayoral, Ricardo

    2017-11-01

    We analyze and model the previously presented decomposition for flow variables in DNS of turbulence over transitionally rough surfaces. The flow is decomposed into two contributions: one produced by the overlying turbulence, which has no footprint of the surface texture, and one induced by the roughness, which is essentially the time-averaged flow around the surface obstacles, but modulated in amplitude by the first component. The roughness-induced component closely resembles the laminar steady flow around the roughness elements at the same non-dimensional roughness size. For small - yet transitionally rough - textures, the roughness-free component is essentially the same as over a smooth wall. Based on these findings, we propose predictive models for the onset of the transitionally rough regime. Project supported by the Engineering and Physical Sciences Research Council (EPSRC).

  20. Comparisons of Crosswind Velocity Profile Estimates Used in Fast-Time Wake Vortex Prediction Models

    Science.gov (United States)

    Pruis, Mathew J.; Delisi, Donald P.; Ahmad, Nashat N.

    2011-01-01

    Five methods for estimating crosswind profiles used in fast-time wake vortex prediction models are compared in this study. Previous investigations have shown that temporal and spatial variations in the crosswind vertical profile have a large impact on the transport and time evolution of the trailing vortex pair. The most important crosswind parameters are the magnitude of the crosswind and the gradient in the crosswind shear. It is known that pulsed and continuous wave lidar measurements can provide good estimates of the wind profile in the vicinity of airports. In this study comparisons are made between estimates of the crosswind profiles from a priori information on the trajectory of the vortex pair as well as crosswind profiles derived from different sensors and a regional numerical weather prediction model.

  1. Resource-estimation models and predicted discovery

    International Nuclear Information System (INIS)

    Hill, G.W.

    1982-01-01

    Resources have been estimated by predictive extrapolation from past discovery experience, by analogy with better explored regions, or by inference from evidence of depletion of targets for exploration. Changes in technology and new insights into geological mechanisms have occurred sufficiently often in the long run to form part of the pattern of mature discovery experience. The criterion, that a meaningful resource estimate needs an objective measure of its precision or degree of uncertainty, excludes 'estimates' based solely on expert opinion. This is illustrated by development of error measures for several persuasive models of discovery and production of oil and gas in USA, both annually and in terms of increasing exploration effort. Appropriate generalizations of the models resolve many points of controversy. This is illustrated using two USA data sets describing discovery of oil and of U 3 O 8 ; the latter set highlights an inadequacy of available official data. Review of the oil-discovery data set provides a warrant for adjusting the time-series prediction to a higher resource figure for USA petroleum. (author)

  2. Enol tautomers of Watson-Crick base pair models are metastable because of nuclear quantum effects.

    Science.gov (United States)

    Pérez, Alejandro; Tuckerman, Mark E; Hjalmarson, Harold P; von Lilienfeld, O Anatole

    2010-08-25

    Intermolecular enol tautomers of Watson-Crick base pairs could emerge spontaneously via interbase double proton transfer. It has been hypothesized that their formation could be facilitated by thermal fluctuations and proton tunneling, and possibly be relevant to DNA damage. Theoretical and computational studies, assuming classical nuclei, have confirmed the dynamic stability of these rare tautomers. However, by accounting for nuclear quantum effects explicitly through Car-Parrinello path integral molecular dynamics calculations, we find the tautomeric enol form to be dynamically metastable, with lifetimes too insignificant to be implicated in DNA damage.

  3. Prediction of pipeline corrosion rate based on grey Markov models

    International Nuclear Information System (INIS)

    Chen Yonghong; Zhang Dafa; Peng Guichu; Wang Yuemin

    2009-01-01

    Based on the model that combined by grey model and Markov model, the prediction of corrosion rate of nuclear power pipeline was studied. Works were done to improve the grey model, and the optimization unbiased grey model was obtained. This new model was used to predict the tendency of corrosion rate, and the Markov model was used to predict the residual errors. In order to improve the prediction precision, rolling operation method was used in these prediction processes. The results indicate that the improvement to the grey model is effective and the prediction precision of the new model combined by the optimization unbiased grey model and Markov model is better, and the use of rolling operation method may improve the prediction precision further. (authors)

  4. An Operational Model for the Prediction of Jet Blast

    Science.gov (United States)

    2012-01-09

    This paper presents an operational model for the prediction of jet blast. The model was : developed based upon three modules including a jet exhaust model, jet centerline decay : model and aircraft motion model. The final analysis was compared with d...

  5. Data driven propulsion system weight prediction model

    Science.gov (United States)

    Gerth, Richard J.

    1994-10-01

    The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.

  6. Predictive modeling of emergency cesarean delivery.

    Directory of Open Access Journals (Sweden)

    Carlos Campillo-Artero

    Full Text Available To increase discriminatory accuracy (DA for emergency cesarean sections (ECSs.We prospectively collected data on and studied all 6,157 births occurring in 2014 at four public hospitals located in three different autonomous communities of Spain. To identify risk factors (RFs for ECS, we used likelihood ratios and logistic regression, fitted a classification tree (CTREE, and analyzed a random forest model (RFM. We used the areas under the receiver-operating-characteristic (ROC curves (AUCs to assess their DA.The magnitude of the LR+ for all putative individual RFs and ORs in the logistic regression models was low to moderate. Except for parity, all putative RFs were positively associated with ECS, including hospital fixed-effects and night-shift delivery. The DA of all logistic models ranged from 0.74 to 0.81. The most relevant RFs (pH, induction, and previous C-section in the CTREEs showed the highest ORs in the logistic models. The DA of the RFM and its most relevant interaction terms was even higher (AUC = 0.94; 95% CI: 0.93-0.95.Putative fetal, maternal, and contextual RFs alone fail to achieve reasonable DA for ECS. It is the combination of these RFs and the interactions between them at each hospital that make it possible to improve the DA for the type of delivery and tailor interventions through prediction to improve the appropriateness of ECS indications.

  7. EKSPERIMEN MODEL PEMBELAJARAN THINK-PAIR-SHARE DENGAN MODUL(TPS-M TERHADAP PRESTASI BELAJAR MATEMATIKA DITINJAU DARI MINAT BELAJAR

    Directory of Open Access Journals (Sweden)

    Jatmiko Jatmiko

    2015-02-01

    Full Text Available Penelitian ini bertujuan untuk mengetahui : (1 manakah diantara Model PembelajaranTPS-M atau Think-Pair-Share” (TPS yang menghasilkan prestasi yang lebih baik, (2 Manakah yang lebih baik, prestasi belajar matematika siswa yang mempunyai minat belajar tinggi, sedang atau rendah, (3 manakah yang menghasilkan prestasi belajar matematika yang lebih baik, di antara Model Pembelajaran TPS-M dan Think-Pair-Share (TPS pada siswa yang mempunyai minat belajar tinggi, sedang dan rendah.Penelitian ini menggunakan metode eksperimental semu (Quasi experimental, dengan desain faktorial 2x3. Populasi penelitian ini adalah semua siswa kelas X SMK kelompok Teknik di Kabupaten Nganjuk Tahun Akademik 2012/2013. Sampel terbagi dalam 2 kelompok, yaitu kelompok eksperimen dan kelompok kontrol. Teknik analisis data yang digunakan dalam penelitian ini, yaitu analisis variansi dua jalan dengan sel tak sama. Berdasarkan hasil analisis diperoleh kesimpulan bahwa: (1 Model pembelajaran TPS-M menghasilkan prestasi belajar matematika yang lebih baik dibandingkan model pembelajaran. (2 Siswa dengan minat belajartinggi, sedang dan rendah memiliki hasil belajar matematika yang sama.(3 Pada masing-masing minat belajar siswa baik tinggi, sedang ataupun rendah prestasi belajar matematika pada model pembelajaran TPS-Mlebih baik dari pada model pembelajaran TPS.

  8. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

  9. An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube

    Science.gov (United States)

    2009-01-01

    Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS) is presented to solve this problem. The proposed ANFIS approach can construct an input–output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input–output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down. PMID:20596382

  10. Methodology for Designing Models Predicting Success of Infertility Treatment

    OpenAIRE

    Alireza Zarinara; Mohammad Mahdi Akhondi; Hojjat Zeraati; Koorsh Kamali; Kazem Mohammad

    2016-01-01

    Abstract Background: The prediction models for infertility treatment success have presented since 25 years ago. There are scientific principles for designing and applying the prediction models that is also used to predict the success rate of infertility treatment. The purpose of this study is to provide basic principles for designing the model to predic infertility treatment success. Materials and Methods: In this paper, the principles for developing predictive models are explained and...

  11. Finite Unification: Theory, Models and Predictions

    CERN Document Server

    Heinemeyer, S; Zoupanos, G

    2011-01-01

    All-loop Finite Unified Theories (FUTs) are very interesting N=1 supersymmetric Grand Unified Theories (GUTs) realising an old field theory dream, and moreover have a remarkable predictive power due to the required reduction of couplings. The reduction of the dimensionless couplings in N=1 GUTs is achieved by searching for renormalization group invariant (RGI) relations among them holding beyond the unification scale. Finiteness results from the fact that there exist RGI relations among dimensional couplings that guarantee the vanishing of all beta-functions in certain N=1 GUTs even to all orders. Furthermore developments in the soft supersymmetry breaking sector of N=1 GUTs and FUTs lead to exact RGI relations, i.e. reduction of couplings, in this dimensionful sector of the theory, too. Based on the above theoretical framework phenomenologically consistent FUTs have been constructed. Here we review FUT models based on the SU(5) and SU(3)^3 gauge groups and their predictions. Of particular interest is the Hig...

  12. Revised predictive equations for salt intrusion modelling in estuaries

    NARCIS (Netherlands)

    Gisen, J.I.A.; Savenije, H.H.G.; Nijzink, R.C.

    2015-01-01

    For one-dimensional salt intrusion models to be predictive, we need predictive equations to link model parameters to observable hydraulic and geometric variables. The one-dimensional model of Savenije (1993b) made use of predictive equations for the Van der Burgh coefficient $K$ and the dispersion

  13. Having a New Pair of Glassess : Applying Systemic Accident Models on Road Safety

    OpenAIRE

    Huang, Yu-Hsing

    2007-01-01

    The main purpose of the thesis is to discuss the accident models which underlie accident prevention in general and road safety in particular, and the consequences of relying on a particular model have for actual preventive work. The discussion centres on two main topics. The first topic is whether the underlying accident model, or paradigm, of traditional road safety should be exchanged for a more complex accident model, and if so, which model(s) are appropriate. From a discussion of current ...

  14. Neutrino nucleosynthesis in supernovae: Shell model predictions

    International Nuclear Information System (INIS)

    Haxton, W.C.

    1989-01-01

    Almost all of the 3 · 10 53 ergs liberated in a core collapse supernova is radiated as neutrinos by the cooling neutron star. I will argue that these neutrinos interact with nuclei in the ejected shells of the supernovae to produce new elements. It appears that this nucleosynthesis mechanism is responsible for the galactic abundances of 7 Li, 11 B, 19 F, 138 La, and 180 Ta, and contributes significantly to the abundances of about 15 other light nuclei. I discuss shell model predictions for the charged and neutral current allowed and first-forbidden responses of the parent nuclei, as well as the spallation processes that produce the new elements. 18 refs., 1 fig., 1 tab

  15. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...

  16. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  17. Model predictive control of a wind turbine modelled in Simpack

    International Nuclear Information System (INIS)

    Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

    2014-01-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

  18. Model predictive control of a wind turbine modelled in Simpack

    Science.gov (United States)

    Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

    2014-06-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

  19. Hadronic production of massive lepton pairs

    International Nuclear Information System (INIS)

    Berger, E.L.

    1982-12-01

    A review is presented of recent experimental and theoretical progress in studies of the production of massive lepton pairs in hadronic collisions. I begin with the classical Drell-Yan annihilation model and its predictions. Subsequently, I discuss deviations from scaling, the status of the proofs of factorization in the parton model, higher-order terms in the perturbative QCD expansion, the discrepancy between measured and predicted yields (K factor), high-twist terms, soft gluon effects, transverse-momentum distributions, implications for weak vector boson (W +- and Z 0 ) yields and production properties, nuclear A dependence effects, correlations of the lepton pair with hadrons in the final state, and angular distributions in the lepton-pair rest frame

  20. Poisson Mixture Regression Models for Heart Disease Prediction.

    Science.gov (United States)

    Mufudza, Chipo; Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

  1. The empirical form of the effective nucleon-nucleon interaction in a model space with correlated J = O pairs

    International Nuclear Information System (INIS)

    Akkermans, J.N.L.; Allaart, K.

    1982-01-01

    Like in earlier work by Schiffer et al. the effective interaction is derived from experimental two-body multiplets. However, now the assumption is that a multiplet state is formed by two unpaired fermions relative to a core of correlated J = 0 pairs. Then the need for two ranges, as proposed Schiffer, disappears for the force between identical nucleons in a model space which is large enough to include pairing correlations. A form with a single attractive medium range is preferred for the identical nucleon interaction in order to reproduce collective 2 + states in even-even nuclei. In contrast, the proton-neutron force requires a very short range or two ranges to reproduce the empirical values of multipole coefficients, observed in odd-odd nuclei. Therefore we discuss the fact that the effective interaction is not always isospin invariant. As a typical case broken-pair calculations in the N = 50 region are considered. But the conclusions drawn, will also apply to other regions of the periodic table. (orig.)

  2. Tests of the Standard Model and Constraints on New Physics from Measurements of Fermion-pair Production at 189 GeV at LEP

    CERN Document Server

    Abbiendi, G.; Alexander, G.; Allison, John; Anderson, K.J.; Anderson, S.; Arcelli, S.; Asai, S.; Ashby, S.F.; Axen, D.; Azuelos, G.; Ball, A.H.; Barberio, E.; Barlow, Roger J.; Batley, J.R.; Baumann, S.; Bechtluft, J.; Behnke, T.; Bell, Kenneth Watson; Bella, G.; Bellerive, A.; Bentvelsen, S.; Bethke, S.; Betts, S.; Biebel, O.; Biguzzi, A.; Bloodworth, I.J.; Bock, P.; Bohme, J.; Boeriu, O.; Bonacorsi, D.; Boutemeur, M.; Braibant, S.; Bright-Thomas, P.; Brigliadori, L.; Brown, Robert M.; Burckhart, H.J.; Capiluppi, P.; Carnegie, R.K.; Carter, A.A.; Carter, J.R.; Chang, C.Y.; Charlton, David G.; Chrisman, D.; Ciocca, C.; Clarke, P.E.L.; Clay, E.; Cohen, I.; Conboy, J.E.; Cooke, O.C.; Couchman, J.; Couyoumtzelis, C.; Coxe, R.L.; Cuffiani, M.; Dado, S.; Dallavalle, G.Marco; Dallison, S.; Davis, R.; De Jong, S.; de Roeck, A.; Dervan, P.; Desch, K.; Dienes, B.; Dixit, M.S.; Donkers, M.; Dubbert, J.; Duchovni, E.; Duckeck, G.; Duerdoth, I.P.; Estabrooks, P.G.; Etzion, E.; Fabbri, F.; Fanfani, A.; Fanti, M.; Faust, A.A.; Feld, L.; Ferrari, P.; Fiedler, F.; Fierro, M.; Fleck, I.; Frey, A.; Furtjes, A.; Futyan, D.I.; Gagnon, P.; Gary, J.W.; Gaycken, G.; Geich-Gimbel, C.; Giacomelli, G.; Giacomelli, P.; Gibson, W.R.; Gingrich, D.M.; Glenzinski, D.; Goldberg, J.; Gorn, W.; Grandi, C.; Graham, K.; Gross, E.; Grunhaus, J.; Gruwe, M.; Hajdu, C.; Hanson, G.G.; Hansroul, M.; Hapke, M.; Harder, K.; Harel, A.; Hargrove, C.K.; Harin-Dirac, M.; Hauschild, M.; Hawkes, C.M.; Hawkings, R.; Hemingway, R.J.; Herten, G.; Heuer, R.D.; Hildreth, M.D.; Hill, J.C.; Hobson, P.R.; Hocker, James Andrew; Hoffman, Kara Dion; Homer, R.J.; Honma, A.K.; Horvath, D.; Hossain, K.R.; Howard, R.; Huntemeyer, P.; Igo-Kemenes, P.; Imrie, D.C.; Ishii, K.; Jacob, F.R.; Jawahery, A.; Jeremie, H.; Jimack, M.; Jones, C.R.; Jovanovic, P.; Junk, T.R.; Kanaya, N.; Kanzaki, J.; Karlen, D.; Kartvelishvili, V.; Kawagoe, K.; Kawamoto, T.; Kayal, P.I.; Keeler, R.K.; Kellogg, R.G.; Kennedy, B.W.; Kim, D.H.; Klier, A.; Kobayashi, T.; Kobel, M.; Kokott, T.P.; Kolrep, M.; Komamiya, S.; Kowalewski, Robert V.; Kress, T.; Krieger, P.; von Krogh, J.; Kuhl, T.; Kyberd, P.; Lafferty, G.D.; Landsman, H.; Lanske, D.; Lauber, J.; Lawson, I.; Layter, J.G.; Lellouch, D.; Letts, J.; Levinson, L.; Liebisch, R.; Lillich, J.; List, B.; Littlewood, C.; Lloyd, A.W.; Lloyd, S.L.; Loebinger, F.K.; Long, G.D.; Losty, M.J.; Lu, J.; Ludwig, J.; Lui, D.; Macchiolo, A.; Macpherson, A.; Mader, W.; Mannelli, M.; Marcellini, S.; Marchant, T.E.; Martin, A.J.; Martin, J.P.; Martinez, G.; Mashimo, T.; Mattig, Peter; McDonald, W.John; McKenna, J.; Mckigney, E.A.; McMahon, T.J.; McPherson, R.A.; Meijers, F.; Mendez-Lorenzo, P.; Merritt, F.S.; Mes, H.; Meyer, I.; Michelini, A.; Mihara, S.; Mikenberg, G.; Miller, D.J.; Mohr, W.; Montanari, A.; Mori, T.; Nagai, K.; Nakamura, I.; Neal, H.A.; Nisius, R.; O'Neale, S.W.; Oakham, F.G.; Odorici, F.; Ogren, H.O.; Okpara, A.; Oreglia, M.J.; Orito, S.; Pasztor, G.; Pater, J.R.; Patrick, G.N.; Patt, J.; Perez-Ochoa, R.; Petzold, S.; Pfeifenschneider, P.; Pilcher, J.E.; Pinfold, J.; Plane, David E.; Poffenberger, P.; Poli, B.; Polok, J.; Przybycien, M.; Quadt, A.; Rembser, C.; Rick, H.; Robertson, S.; Robins, S.A.; Rodning, N.; Roney, J.M.; Rosati, S.; Roscoe, K.; Rossi, A.M.; Rozen, Y.; Runge, K.; Runolfsson, O.; Rust, D.R.; Sachs, K.; Saeki, T.; Sahr, O.; Sang, W.M.; Sarkisian, E.K.G.; Sbarra, C.; Schaile, A.D.; Schaile, O.; Scharff-Hansen, P.; Schieck, J.; Schmitt, S.; Schoning, A.; Schroder, Matthias; Schumacher, M.; Schwick, C.; Scott, W.G.; Seuster, R.; Shears, T.G.; Shen, B.C.; Shepherd-Themistocleous, C.H.; Sherwood, P.; Siroli, G.P.; Skuja, A.; Smith, A.M.; Snow, G.A.; Sobie, R.; Soldner-Rembold, S.; Spagnolo, S.; Sproston, M.; Stahl, A.; Stephens, K.; Stoll, K.; Strom, David M.; Strohmer, R.; Surrow, B.; Talbot, S.D.; Taras, P.; Tarem, S.; Teuscher, R.; Thiergen, M.; Thomas, J.; Thomson, M.A.; Torrence, E.; Towers, S.; Trefzger, T.; Trigger, I.; Trocsanyi, Z.; Tsur, E.; Turner-Watson, M.F.; Ueda, I.; Van Kooten, Rick J.; Vannerem, P.; Verzocchi, M.; Voss, H.; Wackerle, F.; Wagner, A.; Waller, D.; Ward, C.P.; Ward, D.R.; Watkins, P.M.; Watson, A.T.; Watson, N.K.; Wells, P.S.; Wermes, N.; Wetterling, D.; White, J.S.; Wilson, G.W.; Wilson, J.A.; Wyatt, T.R.; Yamashita, S.; Zacek, V.; Zer-Zion, D.

    2000-01-01

    Cross-sections and angular distributions for hadronic and lepton pair final states in e+e- collisions at a centre-of-mass energy near 189 GeV, measured with the OPAL detector at LEP, are presented and compared with the predictions of the Standard Model. The results are used to measure the energy dependence of the electromagnetic coupling constant alpha_em, and to place limits on new physics as described by four-fermion contact interactions or by the exchange of a new heavy particle such as a sneutrino in supersymmetric theories with R-parity violation. A search for the indirect effects of the gravitational interaction in extra dimensions on the mu+mu- and tau+tau- final states is also presented.

  3. Tests of the Standard Model and constraints on new physics from measurements of fermion-pair production at 183 GeV at LEP

    CERN Document Server

    Abbiendi, G.; Alexander, G.; Allison, John; Altekamp, N.; Anderson, K.J.; Anderson, S.; Arcelli, S.; Asai, S.; Ashby, S.F.; Axen, D.; Azuelos, G.; Ball, A.H.; Barberio, E.; Barlow, Roger J.; Bartoldus, R.; Batley, J.R.; Baumann, S.; Bechtluft, J.; Behnke, T.; Bell, Kenneth Watson; Bella, G.; Bellerive, A.; Bentvelsen, S.; Bethke, S.; Betts, S.; Biebel, O.; Biguzzi, A.; Bird, S.D.; Blobel, V.; Bloodworth, I.J.; Bobinski, M.; Bock, P.; Bohme, J.; Bonacorsi, D.; Boutemeur, M.; Braibant, S.; Bright-Thomas, P.; Brigliadori, L.; Brown, Robert M.; Burckhart, H.J.; Burgard, C.; Burgin, R.; Capiluppi, P.; Carnegie, R.K.; Carter, A.A.; Carter, J.R.; Chang, C.Y.; Charlton, David G.; Chrisman, D.; Ciocca, C.; Clarke, P.E.L.; Clay, E.; Cohen, I.; Conboy, J.E.; Cooke, O.C.; Couyoumtzelis, C.; Coxe, R.L.; Cuffiani, M.; Dado, S.; Dallavalle, G.Marco; Davis, R.; De Jong, S.; del Pozo, L.A.; De Roeck, A.; Desch, K.; Dienes, B.; Dixit, M.S.; Dubbert, J.; Duchovni, E.; Duckeck, G.; Duerdoth, I.P.; Eatough, D.; Estabrooks, P.G.; Etzion, E.; Evans, H.G.; Fabbri, F.; Fanti, M.; Faust, A.A.; Fiedler, F.; Fierro, M.; Fleck, I.; Folman, R.; Furtjes, A.; Futyan, D.I.; Gagnon, P.; Gary, J.W.; Gascon, J.; Gascon-Shotkin, S.M.; Gaycken, G.; Geich-Gimbel, C.; Giacomelli, G.; Giacomelli, P.; Gibson, V.; Gibson, W.R.; Gingrich, D.M.; Glenzinski, D.; Goldberg, J.; Gorn, W.; Grandi, C.; Gross, E.; Grunhaus, J.; Gruwe, M.; Hanson, G.G.; Hansroul, M.; Hapke, M.; Harder, K.; Hargrove, C.K.; Hartmann, C.; Hauschild, M.; Hawkes, C.M.; Hawkings, R.; Hemingway, R.J.; Herndon, M.; Herten, G.; Heuer, R.D.; Hildreth, M.D.; Hill, J.C.; Hillier, S.J.; Hobson, P.R.; Hocker, James Andrew; Homer, R.J.; Honma, A.K.; Horvath, D.; Hossain, K.R.; Howard, R.; Huntemeyer, P.; Igo-Kemenes, P.; Imrie, D.C.; Ishii, K.; Jacob, F.R.; Jawahery, A.; Jeremie, H.; Jimack, M.; Jones, C.R.; Jovanovic, P.; Junk, T.R.; Karlen, D.; Kartvelishvili, V.; Kawagoe, K.; Kawamoto, T.; Kayal, P.I.; Keeler, R.K.; Kellogg, R.G.; Kennedy, B.W.; Klier, A.; Kluth, S.; Kobayashi, T.; Kobel, M.; Koetke, D.S.; Kokott, T.P.; Kolrep, M.; Komamiya, S.; Kowalewski, Robert V.; Kress, T.; Krieger, P.; von Krogh, J.; Kuhl, T.; Kyberd, P.; Lafferty, G.D.; Lanske, D.; Lauber, J.; Lautenschlager, S.R.; Lawson, I.; Layter, J.G.; Lazic, D.; Lee, A.M.; Lellouch, D.; Letts, J.; Levinson, L.; Liebisch, R.; List, B.; Littlewood, C.; Lloyd, A.W.; Lloyd, S.L.; Loebinger, F.K.; Long, G.D.; Losty, M.J.; Ludwig, J.; Lui, D.; Macchiolo, A.; Macpherson, A.; Mader, W.; Mannelli, M.; Marcellini, S.; Markopoulos, C.; Martin, A.J.; Martin, J.P.; Martinez, G.; Mashimo, T.; Mattig, Peter; McDonald, W.John; McKenna, J.; Mckigney, E.A.; McMahon, T.J.; McPherson, R.A.; Meijers, F.; Menke, S.; Merritt, F.S.; Mes, H.; Meyer, J.; Michelini, A.; Mihara, S.; Mikenberg, G.; Miller, D.J.; Mir, R.; Mohr, W.; Montanari, A.; Mori, T.; Nagai, K.; Nakamura, I.; Neal, H.A.; Nellen, B.; Nisius, R.; O'Neale, S.W.; Oakham, F.G.; Odorici, F.; Ogren, H.O.; Oreglia, M.J.; Orito, S.; Palinkas, J.; Pasztor, G.; Pater, J.R.; Patrick, G.N.; Patt, J.; Perez-Ochoa, R.; Petzold, S.; Pfeifenschneider, P.; Pilcher, J.E.; Pinfold, J.; Plane, David E.; Poffenberger, P.; Polok, J.; Przybycien, M.; Rembser, C.; Rick, H.; Robertson, S.; Robins, S.A.; Rodning, N.; Roney, J.M.; Roscoe, K.; Rossi, A.M.; Rozen, Y.; Runge, K.; Runolfsson, O.; Rust, D.R.; Sachs, K.; Saeki, T.; Sahr, O.; Sang, W.M.; Sarkisian, E.K.G.; Sbarra, C.; Schaile, A.D.; Schaile, O.; Scharf, F.; Scharff-Hansen, P.; Schieck, J.; Schmitt, B.; Schmitt, S.; Schoning, A.; Schroder, Matthias; Schumacher, M.; Schwick, C.; Scott, W.G.; Seuster, R.; Shears, T.G.; Shen, B.C.; Shepherd-Themistocleous, C.H.; Sherwood, P.; Siroli, G.P.; Sittler, A.; Skuja, A.; Smith, A.M.; Snow, G.A.; Sobie, R.; Soldner-Rembold, S.; Sproston, M.; Stahl, A.; Stephens, K.; Steuerer, J.; Stoll, K.; Strom, David M.; Strohmer, R.; Surrow, B.; Talbot, S.D.; Tanaka, S.; Taras, P.; Tarem, S.; Teuscher, R.; Thiergen, M.; Thomson, M.A.; von Torne, E.; Torrence, E.; Towers, S.; Trigger, I.; Trocsanyi, Z.; Tsur, E.; Turcot, A.S.; Turner-Watson, M.F.; Van Kooten, Rick J.; Vannerem, P.; Verzocchi, M.; Voss, H.; Wackerle, F.; Wagner, A.; Ward, C.P.; Ward, D.R.; Watkins, P.M.; Watson, A.T.; Watson, N.K.; Wells, P.S.; Wermes, N.; White, J.S.; Wilson, G.W.; Wilson, J.A.; Wyatt, T.R.; Yamashita, S.; Yekutieli, G.; Zacek, V.; Zer-Zion, D.

    1999-01-01

    Cross-sections for hadronic, b-bbar and lepton pair final states in e+e- collisions at sqrt(s) = 183 GeV, measured with the OPAL detector at LEP, are presented and compared with the predictions of the Standard Model. Forward-backward asymmetries for the leptonic final states have also been measured. Cross-sections and asymmetries are also presented for data recorded in 1997 at sqrt(s) = 130 and 136 GeV. The results are used to measure the energy dependence of the electromagnetic coupling constant alpha_em, and to place limits on new physics as described by four-fermion contact interactions or by the exchange of a new heavy particle such as a leptoquark, or of a squark or sneutrino in supersymmetric theories with R-parity violation.

  4. Predictive integrated modelling for ITER scenarios

    International Nuclear Information System (INIS)

    Artaud, J.F.; Imbeaux, F.; Aniel, T.; Basiuk, V.; Eriksson, L.G.; Giruzzi, G.; Hoang, G.T.; Huysmans, G.; Joffrin, E.; Peysson, Y.; Schneider, M.; Thomas, P.

    2005-01-01

    The uncertainty on the prediction of ITER scenarios is evaluated. 2 transport models which have been extensively validated against the multi-machine database are used for the computation of the transport coefficients. The first model is GLF23, the second called Kiauto is a model in which the profile of dilution coefficient is a gyro Bohm-like analytical function, renormalized in order to get profiles consistent with a given global energy confinement scaling. The package of codes CRONOS is used, it gives access to the dynamics of the discharge and allows the study of interplay between heat transport, current diffusion and sources. The main motivation of this work is to study the influence of parameters such plasma current, heat, density, impurities and toroidal moment transport. We can draw the following conclusions: 1) the target Q = 10 can be obtained in ITER hybrid scenario at I p = 13 MA, using either the DS03 two terms scaling or the GLF23 model based on the same pedestal; 2) I p = 11.3 MA, Q = 10 can be reached only assuming a very peaked pressure profile and a low pedestal; 3) at fixed Greenwald fraction, Q increases with density peaking; 4) achieving a stationary q-profile with q > 1 requires a large non-inductive current fraction (80%) that could be provided by 20 to 40 MW of LHCD; and 5) owing to the high temperature the q-profile penetration is delayed and q = 1 is reached about 600 s in ITER hybrid scenario at I p = 13 MA, in the absence of active q-profile control. (A.C.)

  5. A plant-wide aqueous phase chemistry module describing pH variations and ion speciation/pairing in wastewater treatment process models.

    Science.gov (United States)

    Flores-Alsina, Xavier; Kazadi Mbamba, Christian; Solon, Kimberly; Vrecko, Darko; Tait, Stephan; Batstone, Damien J; Jeppsson, Ulf; Gernaey, Krist V

    2015-11-15

    There is a growing interest within the Wastewater Treatment Plant (WWTP) modelling community to correctly describe physico-chemical processes after many years of mainly focusing on biokinetics. Indeed, future modelling needs, such as a plant-wide phosphorus (P) description, require a major, but unavoidable, additional degree of complexity when representing cationic/anionic behaviour in Activated Sludge (AS)/Anaerobic Digestion (AD) systems. In this paper, a plant-wide aqueous phase chemistry module describing pH variations plus ion speciation/pairing is presented and interfaced with industry standard models. The module accounts for extensive consideration of non-ideality, including ion activities instead of molar concentrations and complex ion pairing. The general equilibria are formulated as a set of Differential Algebraic Equations (DAEs) instead of Ordinary Differential Equations (ODEs) in order to reduce the overall stiffness of the system, thereby enhancing simulation speed. Additionally, a multi-dimensional version of the Newton-Raphson algorithm is applied to handle the existing multiple algebraic inter-dependencies. The latter is reinforced with the Simulated Annealing method to increase the robustness of the solver making the system not so dependent of the initial conditions. Simulation results show pH predictions when describing Biological Nutrient Removal (BNR) by the activated sludge models (ASM) 1, 2d and 3 comparing the performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) treatment plant configuration under different anaerobic/anoxic/aerobic conditions. The same framework is implemented in the Benchmark Simulation Model No. 2 (BSM2) version of the Anaerobic Digestion Model No. 1 (ADM1) (WWTP3) as well, predicting pH values at different cationic/anionic loads. In this way, the general applicability/flexibility of the proposed approach is demonstrated, by implementing the aqueous phase chemistry module in some

  6. The predator-prey models for the mechanism of autocatalysis, pair wise interactions and movements to free places

    Directory of Open Access Journals (Sweden)

    Muhammad Shakil

    2015-12-01

    Full Text Available In this paper we aim to develop the modeled equations for different types of mechanism of the predator-prey interactions with the help of a quasi chemical approach while taking a special study case of foxes and rabbits, these mechanisms include autocatalysis mechanism, pair wise interactions and the mechanism of their movements to some free places. The chemical reactions representing the interactions obey the mass action law. The territorial animal like fox is assigned a simple cell as its territory. Under the proper relations between coefficients, this system may demonstrate globally stable dynamics.

  7. PENINGKATAN KETERAMPILAN MENULIS   NASKAH DRAMA SATU BABAK MENGGUNAKAN MODEL THINK-PAIR-SHARE BERBANTUAN ALAT PERAGA GAMBAR BERSERI

    Directory of Open Access Journals (Sweden)

    Suhartini Suhartini

    2015-12-01

    Full Text Available Tujuan penelitian ini adalah untuk meningkatkan keterampilan menulis naskah drama satu babak menggunakan model pembelajaran Think Pare Share. Penelitian ini merupakan penelitian tindakan kelas yang diterapkan pada siswa kelas VIIIA SMPN1 Tanjungsari pada materi menulis naskah drama satu babak menggunakan alat peraga gambar berseri. Penelitian tindakan kelas (PTK dalam penelitian ini dilaksanakan dalam dua siklus, yaitu proses tindakan pada siklus I dan siklus II. Penelitian tindakan kelas (PTK dilaksanakan dalam proses pengkajian berdaur pada setiap siklusnya yakni perencanaan, pelksanaan tindakan, observasi, dan refleksi Berdasarkan analisis data diperoleh hasil ulangan harian meningkat. Peningkatan hasil tersebut sangat signifikan, 28 siswa memperoleh nilai di atas KKM dan rerata kelas menjadi 80,55 dan persentase ketuntasan sebesar 96,5%. Hasil penelitian menunjukkan ada peningkatan keterampilan dalam menulis naskah drama satu babak. Hal ini ditunjukkan pada hasil tes, yakni  28 orang (100% memperoleh nilai di atas KKM, dengan nilai rata-rata 83,4. Simpulan penelitian adalah model pembelajaran Think Pair Share menggunakan alat peraga gambar berseri dapat meningkatkan keterampilan menulis naskah drama satu babak. Berdasarkan simpulan penelitian, maka dalam pembelajaran menulis naskah drama satu babak sebaiknya dapat menerapkan model pembelajaran Think Pair Share berbantuan alat peraga gambar berseri.

  8. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  9. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  10. PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

    Directory of Open Access Journals (Sweden)

    Greenblatt Jack

    2006-07-01

    Full Text Available Abstract Background Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions. Results Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30 and YMR135C (gid8 yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c. The observed interaction was confirmed by tandem affinity purification (TAP tag, verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not

  11. Search for a non-standard-model Higgs boson decaying to a pair of new light bosons in four-muon final states

    CERN Document Server

    Chatrchyan, Serguei; Sirunyan, Albert M; Tumasyan, Armen; Adam, Wolfgang; Aguilo, Ernest; Bergauer, Thomas; Dragicevic, Marko; Erö, Janos; Fabjan, Christian; Friedl, Markus; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Hammer, Josef; Hörmann, Natascha; Hrubec, Josef; Jeitler, Manfred; Kiesenhofer, Wolfgang; Knünz, Valentin; Krammer, Manfred; Krätschmer, Ilse; Liko, Dietrich; Mikulec, Ivan; Pernicka, Manfred; Rahbaran, Babak; Rohringer, Christine; Rohringer, Herbert; Schöfbeck, Robert; Strauss, Josef; Taurok, Anton; Waltenberger, Wolfgang; Walzel, Gerhard; Widl, Edmund; Wulz, Claudia-Elisabeth; Mossolov, Vladimir; Shumeiko, Nikolai; Suarez Gonzalez, Juan; Bansal, Monika; Bansal, Sunil; Cornelis, Tom; De Wolf, Eddi A; Janssen, Xavier; Luyckx, Sten; Mucibello, Luca; Ochesanu, Silvia; Roland, Benoit; Rougny, Romain; Selvaggi, Michele; Staykova, Zlatka; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Van Spilbeeck, Alex; Blekman, Freya; Blyweert, Stijn; D'Hondt, Jorgen; Gonzalez Suarez, Rebeca; Kalogeropoulos, Alexis; Maes, Michael; Olbrechts, Annik; Van Doninck, Walter; Van Mulders, Petra; Van Onsem, Gerrit Patrick; Villella, Ilaria; Clerbaux, Barbara; De Lentdecker, Gilles; Dero, Vincent; Gay, Arnaud; Hreus, Tomas; Léonard, Alexandre; Marage, Pierre Edouard; Mohammadi, Abdollah; Reis, Thomas; Thomas, Laurent; Vander Marcken, Gil; Vander Velde, Catherine; Vanlaer, Pascal; Wang, Jian; Adler, Volker; Beernaert, Kelly; Cimmino, Anna; Costantini, Silvia; Garcia, Guillaume; Grunewald, Martin; Klein, Benjamin; Lellouch, Jérémie; Marinov, Andrey; Mccartin, Joseph; Ocampo Rios, Alberto Andres; Ryckbosch, Dirk; Strobbe, Nadja; Thyssen, Filip; Tytgat, Michael; Verwilligen, Piet; Walsh, Sinead; Yazgan, Efe; Zaganidis, Nicolas; Basegmez, Suzan; Bruno, Giacomo; Castello, Roberto; Ceard, Ludivine; Delaere, Christophe; Du Pree, Tristan; Favart, Denis; Forthomme, Laurent; Giammanco, Andrea; Hollar, Jonathan; Lemaitre, Vincent; Liao, Junhui; Militaru, Otilia; Nuttens, Claude; Pagano, Davide; Pin, Arnaud; Piotrzkowski, Krzysztof; Schul, Nicolas; Vizan Garcia, Jesus Manuel; Beliy, Nikita; Caebergs, Thierry; Daubie, Evelyne; Hammad, Gregory Habib; Alves, Gilvan; Correa Martins Junior, Marcos; Martins, Thiago; Pol, Maria Elena; Henrique Gomes E Souza, Moacyr; Aldá Júnior, Walter Luiz; Carvalho, Wagner; Custódio, Analu; Melo Da Costa, Eliza; De Jesus Damiao, Dilson; De Oliveira Martins, Carley; Fonseca De Souza, Sandro; Matos Figueiredo, Diego; Mundim, Luiz; Nogima, Helio; Oguri, Vitor; Prado Da Silva, Wanda Lucia; Santoro, Alberto; Soares Jorge, Luana; Sznajder, Andre; Souza Dos Anjos, Tiago; Bernardes, Cesar Augusto; De Almeida Dias, Flavia; Tomei, Thiago; De Moraes Gregores, Eduardo; Lagana, Caio; Da Cunha Marinho, Franciole; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Genchev, Vladimir; Iaydjiev, Plamen; Piperov, Stefan; Rodozov, Mircho; Stoykova, Stefka; Sultanov, Georgi; Tcholakov, Vanio; Trayanov, Rumen; Vutova, Mariana; Dimitrov, Anton; Hadjiiska, Roumyana; Kozhuharov, Venelin; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Bian, Jian-Guo; Chen, Guo-Ming; Chen, He-Sheng; Jiang, Chun-Hua; Liang, Dong; Liang, Song; Meng, Xiangwei; Tao, Junquan; Wang, Jian; Wang, Xianyou; Wang, Zheng; Xiao, Hong; Xu, Ming; Zang, Jingjing; Zhang, Zhen; Asawatangtrakuldee, Chayanit; Ban, Yong; Guo, Yifei; Li, Wenbo; Liu, Shuai; Mao, Yajun; Qian, Si-Jin; Teng, Haiyun; Wang, Dayong; Zhang, Linlin; Zou, Wei; Avila, Carlos; Gomez, Juan Pablo; Gomez Moreno, Bernardo; Osorio Oliveros, Andres Felipe; Sanabria, Juan Carlos; Godinovic, Nikola; Lelas, Damir; Plestina, Roko; Polic, Dunja; Puljak, Ivica; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Duric, Senka; Kadija, Kreso; Luetic, Jelena; Morovic, Srecko; Attikis, Alexandros; Galanti, Mario; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Finger, Miroslav; Finger Jr, Michael; Assran, Yasser; Elgammal, Sherif; Ellithi Kamel, Ali; Mahmoud, Mohammed; Radi, Amr; Kadastik, Mario; Müntel, Mait; Raidal, Martti; Rebane, Liis; Tiko, Andres; Eerola, Paula; Fedi, Giacomo; Voutilainen, Mikko; Härkönen, Jaakko; Heikkinen, Mika Aatos; Karimäki, Veikko; Kinnunen, Ritva; Kortelainen, Matti J; Lampén, Tapio; Lassila-Perini, Kati; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Mäenpää, Teppo; Peltola, Timo; Tuominen, Eija; Tuominiemi, Jorma; Tuovinen, Esa; Ungaro, Donatella; Wendland, Lauri; Banzuzi, Kukka; Karjalainen, Ahti; Korpela, Arja; Tuuva, Tuure; Besancon, Marc; Choudhury, Somnath; Dejardin, Marc; Denegri, Daniel; Fabbro, Bernard; Faure, Jean-Louis; Ferri, Federico; Ganjour, Serguei; Givernaud, Alain; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Locci, Elizabeth; Malcles, Julie; Millischer, Laurent; Nayak, Aruna; Rander, John; Rosowsky, André; Shreyber, Irina; Titov, Maksym; Baffioni, Stephanie; Beaudette, Florian; Benhabib, Lamia; Bianchini, Lorenzo; Bluj, Michal; Broutin, Clementine; Busson, Philippe; Charlot, Claude; Daci, Nadir; Dahms, Torsten; Dalchenko, Mykhailo; Dobrzynski, Ludwik; Granier de Cassagnac, Raphael; Haguenauer, Maurice; Miné, Philippe; Mironov, Camelia; Naranjo, Ivo Nicolas; Nguyen, Matthew; Ochando, Christophe; Paganini, Pascal; Sabes, David; Salerno, Roberto; Sirois, Yves; Veelken, Christian; Zabi, Alexandre; Agram, Jean-Laurent; Andrea, Jeremy; Bloch, Daniel; Bodin, David; Brom, Jean-Marie; Cardaci, Marco; Chabert, Eric Christian; Collard, Caroline; Conte, Eric; Drouhin, Frédéric; Ferro, Cristina; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Juillot, Pierre; Le Bihan, Anne-Catherine; Van Hove, Pierre; Fassi, Farida; Mercier, Damien; Beauceron, Stephanie; Beaupere, Nicolas; Bondu, Olivier; Boudoul, Gaelle; Chasserat, Julien; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fay, Jean; Gascon, Susan; Gouzevitch, Maxime; Ille, Bernard; Kurca, Tibor; Lethuillier, Morgan; Mirabito, Laurent; Perries, Stephane; Sgandurra, Louis; Sordini, Viola; Tschudi, Yohann; Verdier, Patrice; Viret, Sébastien; Tsamalaidze, Zviad; Anagnostou, Georgios; Autermann, Christian; Beranek, Sarah; Edelhoff, Matthias; Feld, Lutz; Heracleous, Natalie; Hindrichs, Otto; Jussen, Ruediger; Klein, Katja; Merz, Jennifer; Ostapchuk, Andrey; Perieanu, Adrian; Raupach, Frank; Sammet, Jan; Schael, Stefan; Sprenger, Daniel; Weber, Hendrik; Wittmer, Bruno; Zhukov, Valery; Ata, Metin; Caudron, Julien; Dietz-Laursonn, Erik; Duchardt, Deborah; Erdmann, Martin; Fischer, Robert; Güth, Andreas; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Klingebiel, Dennis; Kreuzer, Peter; Merschmeyer, Markus; Meyer, Arnd; Olschewski, Mark; Papacz, Paul; Pieta, Holger; Reithler, Hans; Schmitz, Stefan Antonius; Sonnenschein, Lars; Steggemann, Jan; Teyssier, Daniel; Weber, Martin; Bontenackels, Michael; Cherepanov, Vladimir; Erdogan, Yusuf; Flügge, Günter; Geenen, Heiko; Geisler, Matthias; Haj Ahmad, Wael; Hoehle, Felix; Kargoll, Bastian; Kress, Thomas; Kuessel, Yvonne; Lingemann, Joschka; Nowack, Andreas; Perchalla, Lars; Pooth, Oliver; Sauerland, Philip; Stahl, Achim; Aldaya Martin, Maria; Behr, Joerg; Behrenhoff, Wolf; Behrens, Ulf; Bergholz, Matthias; Bethani, Agni; Borras, Kerstin; Burgmeier, Armin; Cakir, Altan; Calligaris, Luigi; Campbell, Alan; Castro, Elena; Costanza, Francesco; Dammann, Dirk; Diez Pardos, Carmen; Eckerlin, Guenter; Eckstein, Doris; Flucke, Gero; Geiser, Achim; Glushkov, Ivan; Gunnellini, Paolo; Habib, Shiraz; Hauk, Johannes; Hellwig, Gregor; Jung, Hannes; Kasemann, Matthias; Katsas, Panagiotis; Kleinwort, Claus; Kluge, Hannelies; Knutsson, Albert; Krämer, Mira; Krücker, Dirk; Kuznetsova, Ekaterina; Lange, Wolfgang; Lohmann, Wolfgang; Lutz, Benjamin; Mankel, Rainer; Marfin, Ihar; Marienfeld, Markus; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Mnich, Joachim; Mussgiller, Andreas; Naumann-Emme, Sebastian; Novgorodova, Olga; Olzem, Jan; Perrey, Hanno; Petrukhin, Alexey; Pitzl, Daniel; Raspereza, Alexei; Ribeiro Cipriano, Pedro M; Riedl, Caroline; Ron, Elias; Rosin, Michele; Salfeld-Nebgen, Jakob; Schmidt, Ringo; Schoerner-Sadenius, Thomas; Sen, Niladri; Spiridonov, Alexander; Stein, Matthias; Walsh, Roberval; Wissing, Christoph; Blobel, Volker; Draeger, Jula; Enderle, Holger; Erfle, Joachim; Gebbert, Ulla; Görner, Martin; Hermanns, Thomas; Höing, Rebekka Sophie; Kaschube, Kolja; Kaussen, Gordon; Kirschenmann, Henning; Klanner, Robert; Lange, Jörn; Mura, Benedikt; Nowak, Friederike; Peiffer, Thomas; Pietsch, Niklas; Rathjens, Denis; Sander, Christian; Schettler, Hannes; Schleper, Peter; Schlieckau, Eike; Schmidt, Alexander; Schröder, Matthias; Schum, Torben; Seidel, Markus; Sibille, Jennifer; Sola, Valentina; Stadie, Hartmut; Steinbrück, Georg; Thomsen, Jan; Vanelderen, Lukas; Barth, Christian; Berger, Joram; Böser, Christian; Chwalek, Thorsten; De Boer, Wim; Descroix, Alexis; Dierlamm, Alexander; Feindt, Michael; Guthoff, Moritz; Hackstein, Christoph; Hartmann, Frank; Hauth, Thomas; Heinrich, Michael; Held, Hauke; Hoffmann, Karl-Heinz; Husemann, Ulrich; Katkov, Igor; Komaragiri, Jyothsna Rani; Lobelle Pardo, Patricia; Martschei, Daniel; Mueller, Steffen; Müller, Thomas; Niegel, Martin; Nürnberg, Andreas; Oberst, Oliver; Oehler, Andreas; Ott, Jochen; Quast, Gunter; Rabbertz, Klaus; Ratnikov, Fedor; Ratnikova, Natalia; Röcker, Steffen; Schilling, Frank-Peter; Schott, Gregory; Simonis, Hans-Jürgen; Stober, Fred-Markus Helmut; Troendle, Daniel; Ulrich, Ralf; Wagner-Kuhr, Jeannine; Wayand, Stefan; Weiler, Thomas; Zeise, Manuel; Daskalakis, Georgios; Geralis, Theodoros; Kesisoglou, Stilianos; Kyriakis, Aristotelis; Loukas, Demetrios; Manolakos, Ioannis; Markou, Athanasios; Markou, Christos; Mavrommatis, Charalampos; Ntomari, Eleni; Gouskos, Loukas; Mertzimekis, Theodoros; Panagiotou, Apostolos; Saoulidou, Niki; Evangelou, Ioannis; Foudas, Costas; Kokkas, Panagiotis; Manthos, Nikolaos; Papadopoulos, Ioannis; Patras, Vaios; Bencze, Gyorgy; Hajdu, Csaba; Hidas, Pàl; Horvath, Dezso; Sikler, Ferenc; Veszpremi, Viktor; Vesztergombi, Gyorgy; Beni, Noemi; Czellar, Sandor; Molnar, Jozsef; Palinkas, Jozsef; Szillasi, Zoltan; Karancsi, János; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Beri, Suman Bala; Bhatnagar, Vipin; Dhingra, Nitish; Gupta, Ruchi; Kaur, Manjit; Mehta, Manuk Zubin; Nishu, Nishu; Saini, Lovedeep Kaur; Sharma, Archana; Singh, Jasbir; Kumar, Ashok; Kumar, Arun; Ahuja, Sudha; Bhardwaj, Ashutosh; Choudhary, Brajesh C; Malhotra, Shivali; Naimuddin, Md; Ranjan, Kirti; Sharma, Varun; Shivpuri, Ram Krishen; Banerjee, Sunanda; Bhattacharya, Satyaki; Dutta, Suchandra; Gomber, Bhawna; Jain, Sandhya; Jain, Shilpi; Khurana, Raman; Sarkar, Subir; Sharan, Manoj; Abdulsalam, Abdulla; Choudhury, Rajani Kant; Dutta, Dipanwita; Kailas, Swaminathan; Kumar, Vineet; Mehta, Pourus; Mohanty, Ajit Kumar; Pant, Lalit Mohan; Shukla, Prashant; Aziz, Tariq; Ganguly, Sanmay; Guchait, Monoranjan; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Mohanty, Gagan Bihari; Parida, Bibhuti; Sudhakar, Katta; Wickramage, Nadeesha; Banerjee, Sudeshna; Dugad, Shashikant; Arfaei, Hessamaddin; Bakhshiansohi, Hamed; Etesami, Seyed Mohsen; Fahim, Ali; Hashemi, Majid; Hesari, Hoda; Jafari, Abideh; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Paktinat Mehdiabadi, Saeid; Safarzadeh, Batool; Zeinali, Maryam; Abbrescia, Marcello; Barbone, Lucia; Calabria, Cesare; Chhibra, Simranjit Singh; Colaleo, Anna; Creanza, Donato; De Filippis, Nicola; De Palma, Mauro; Fiore, Luigi; Iaselli, Giuseppe; Maggi, Giorgio; Maggi, Marcello; Marangelli, Bartolomeo; My, Salvatore; Nuzzo, Salvatore; Pacifico, Nicola; Pompili, Alexis; Pugliese, Gabriella; Selvaggi, Giovanna; Silvestris, Lucia; Singh, Gurpreet; Venditti, Rosamaria; Zito, Giuseppe; Abbiendi, Giovanni; Benvenuti, Alberto; Bonacorsi, Daniele; Braibant-Giacomelli, Sylvie; Brigliadori, Luca; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Fasanella, Daniele; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Meneghelli, Marco; Montanari, Alessandro; Navarria, Francesco; Odorici, Fabrizio; Perrotta, Andrea; Primavera, Federica; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Travaglini, Riccardo; Albergo, Sebastiano; Cappello, Gigi; Chiorboli, Massimiliano; Costa, Salvatore; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Frosali, Simone; Gallo, Elisabetta; Gonzi, Sandro; Meschini, Marco; Paoletti, Simone; Sguazzoni, Giacomo; Tropiano, Antonio; Benussi, Luigi; Bianco, Stefano; Colafranceschi, Stefano; Fabbri, Franco; Piccolo, Davide; Fabbricatore, Pasquale; Musenich, Riccardo; Tosi, Silvano; Benaglia, Andrea; De Guio, Federico; Di Matteo, Leonardo; Fiorendi, Sara; Gennai, Simone; Ghezzi, Alessio; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Martelli, Arabella; Massironi, Andrea; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pedrini, Daniele; Ragazzi, Stefano; Redaelli, Nicola; Sala, Silvano; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Carrillo Montoya, Camilo Andres; Cavallo, Nicola; De Cosa, Annapaola; Dogangun, Oktay; Fabozzi, Francesco; Iorio, Alberto Orso Maria; Lista, Luca; Meola, Sabino; Merola, Mario; Paolucci, Pierluigi; Azzi, Patrizia; Bacchetta, Nicola; Bisello, Dario; Branca, Antonio; Carlin, Roberto; Checchia, Paolo; Dorigo, Tommaso; Gasparini, Fabrizio; Gasparini, Ugo; Gozzelino, Andrea; Kanishchev, Konstantin; Lacaprara, Stefano; Lazzizzera, Ignazio; Margoni, Martino; Meneguzzo, Anna Teresa; Passaseo, Marina; Pazzini, Jacopo; Pegoraro, Matteo; Pozzobon, Nicola; Ronchese, Paolo; Simonetto, Franco; Torassa, Ezio; Tosi, Mia; Vanini, Sara; Zotto, Pierluigi; Gabusi, Michele; Ratti, Sergio P; Riccardi, Cristina; Torre, Paola; Vitulo, Paolo; Biasini, Maurizio; Bilei, Gian Mario; Fanò, Livio; Lariccia, Paolo; Mantovani, Giancarlo; Menichelli, Mauro; Nappi, Aniello; Romeo, Francesco; Saha, Anirban; Santocchia, Attilio; Spiezia, Aniello; Taroni, Silvia; Azzurri, Paolo; Bagliesi, Giuseppe; Bernardini, Jacopo; Boccali, Tommaso; Broccolo, Giuseppe; Castaldi, Rino; D'Agnolo, Raffaele Tito; Dell'Orso, Roberto; Fiori, Francesco; Foà, Lorenzo; Giassi, Alessandro; Kraan, Aafke; Ligabue, Franco; Lomtadze, Teimuraz; Martini, Luca; Messineo, Alberto; Palla, Fabrizio; Rizzi, Andrea; Serban, Alin Titus; Spagnolo, Paolo; Squillacioti, Paola; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Barone, Luciano; Cavallari, Francesca; Del Re, Daniele; Diemoz, Marcella; Fanelli, Cristiano; Grassi, Marco; Longo, Egidio; Meridiani, Paolo; Micheli, Francesco; Nourbakhsh, Shervin; Organtini, Giovanni; Paramatti, Riccardo; Rahatlou, Shahram; Sigamani, Michael; Soffi, Livia; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Biino, Cristina; Cartiglia, Nicolo; Costa, Marco; Demaria, Natale; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Musich, Marco; Obertino, Maria Margherita; Pastrone, Nadia; Pelliccioni, Mario; Potenza, Alberto; Romero, Alessandra; Ruspa, Marta; Sacchi, Roberto; Solano, Ada; Staiano, Amedeo; Vilela Pereira, Antonio; Belforte, Stefano; Candelise, Vieri; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Gobbo, Benigno; Marone, Matteo; Montanino, Damiana; Penzo, Aldo; Schizzi, Andrea; Heo, Seong Gu; Kim, Tae Yeon; Nam, Soon-Kwon; Chang, Sunghyun; Kim, Dong Hee; Kim, Gui Nyun; Kong, Dae Jung; Park, Hyangkyu; Ro, Sang-Ryul; Son, Dong-Chul; Son, Taejin; Kim, Jae Yool; Kim, Zero Jaeho; Song, Sanghyeon; Choi, Suyong; Gyun, Dooyeon; Hong, Byung-Sik; Jo, Mihee; Kim, Hyunchul; Kim, Tae Jeong; Lee, Kyong Sei; Moon, Dong Ho; Park, Sung Keun; Choi, Minkyoo; Kim, Ji Hyun; Park, Chawon; Park, Inkyu; Park, Sangnam; Ryu, Geonmo; Cho, Yongjin; Choi, Young-Il; Choi, Young Kyu; Goh, Junghwan; Kim, Min Suk; Kwon, Eunhyang; Lee, Byounghoon; Lee, Jongseok; Lee, Sungeun; Seo, Hyunkwan; Yu, Intae; Bilinskas, Mykolas Jurgis; Grigelionis, Ignas; Janulis, Mindaugas; Juodagalvis, Andrius; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Heredia-de La Cruz, Ivan; Lopez-Fernandez, Ricardo; Magaña Villalba, Ricardo; Martínez-Ortega, Jorge; Sánchez Hernández, Alberto; Villasenor-Cendejas, Luis Manuel; Carrillo Moreno, Salvador; Vazquez Valencia, Fabiola; Salazar Ibarguen, Humberto Antonio; Casimiro Linares, Edgar; Morelos Pineda, Antonio; Reyes-Santos, Marco A; Krofcheck, David; Bell, Alan James; Butler, Philip H; Doesburg, Robert; Reucroft, Steve; Silverwood, Hamish; Ahmad, Muhammad; Ansari, Muhammad Hamid; Asghar, Muhammad Irfan; Butt, Jamila; Hoorani, Hafeez R; Khalid, Shoaib; Khan, Wajid Ali; Khurshid, Taimoor; Qazi, Shamona; Shah, Mehar Ali; Shoaib, Muhammad; Bialkowska, Helena; Boimska, Bozena; Frueboes, Tomasz; Gokieli, Ryszard; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Romanowska-Rybinska, Katarzyna; Szleper, Michal; Wrochna, Grzegorz; Zalewski, Piotr; Brona, Grzegorz; Bunkowski, Karol; Cwiok, Mikolaj; Dominik, Wojciech; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Almeida, Nuno; Bargassa, Pedrame; David Tinoco Mendes, Andre; Faccioli, Pietro; Ferreira Parracho, Pedro Guilherme; Gallinaro, Michele; Seixas, Joao; Varela, Joao; Vischia, Pietro; Belotelov, Ivan; Bunin, Pavel; Golutvin, Igor; Gorbunov, Ilya; Kamenev, Alexey; Karjavin, Vladimir; Kozlov, Guennady; Lanev, Alexander; Malakhov, Alexander; Moisenz, Petr; Palichik, Vladimir; Perelygin, Victor; Savina, Maria; Shmatov, Sergey; Smirnov, Vitaly; Volodko, Anton; Zarubin, Anatoli; Evstyukhin, Sergey; Golovtsov, Victor; Ivanov, Yury; Kim, Victor; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Vorobyev, Andrey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Kirsanov, Mikhail; Krasnikov, Nikolai; Matveev, Viktor; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Erofeeva, Maria; Gavrilov, Vladimir; Kossov, Mikhail; Lychkovskaya, Natalia; Popov, Vladimir; Safronov, Grigory; Semenov, Sergey; Stolin, Viatcheslav; Vlasov, Evgueni; Zhokin, Alexander; Belyaev, Andrey; Boos, Edouard; Dubinin, Mikhail; Dudko, Lev; Ershov, Alexander; Gribushin, Andrey; Klyukhin, Vyacheslav; Kodolova, Olga; Lokhtin, Igor; Markina, Anastasia; Obraztsov, Stepan; Perfilov, Maxim; Petrushanko, Sergey; Popov, Andrey; Sarycheva, Ludmila; Savrin, Viktor; Snigirev, Alexander; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Leonidov, Andrey; Mesyats, Gennady; Rusakov, Sergey V; Vinogradov, Alexey; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Grishin, Viatcheslav; Kachanov, Vassili; Konstantinov, Dmitri; Krychkine, Victor; Petrov, Vladimir; Ryutin, Roman; Sobol, Andrei; Tourtchanovitch, Leonid; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Adzic, Petar; Djordjevic, Milos; Ekmedzic, Marko; Krpic, Dragomir; Milosevic, Jovan; Aguilar-Benitez, Manuel; Alcaraz Maestre, Juan; Arce, Pedro; Battilana, Carlo; Calvo, Enrique; Cerrada, Marcos; Chamizo Llatas, Maria; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Domínguez Vázquez, Daniel; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Ferrando, Antonio; Flix, Jose; Fouz, Maria Cruz; Garcia-Abia, Pablo; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Merino, Gonzalo; Puerta Pelayo, Jesus; Quintario Olmeda, Adrián; Redondo, Ignacio; Romero, Luciano; Santaolalla, Javier; Senghi Soares, Mara; Willmott, Carlos; Albajar, Carmen; Codispoti, Giuseppe; de Trocóniz, Jorge F; Brun, Hugues; Cuevas, Javier; Fernandez Menendez, Javier; Folgueras, Santiago; Gonzalez Caballero, Isidro; Lloret Iglesias, Lara; Piedra Gomez, Jonatan; Brochero Cifuentes, Javier Andres; Cabrillo, Iban Jose; Calderon, Alicia; Chuang, Shan-Huei; Duarte Campderros, Jordi; Felcini, Marta; Fernandez, Marcos; Gomez, Gervasio; Gonzalez Sanchez, Javier; Graziano, Alberto; Jorda, Clara; Lopez Virto, Amparo; Marco, Jesus; Marco, Rafael; Martinez Rivero, Celso; Matorras, Francisco; Munoz Sanchez, Francisca Javiela; Rodrigo, Teresa; Rodríguez-Marrero, Ana Yaiza; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Auffray, Etiennette; Auzinger, Georg; Bachtis, Michail; Baillon, Paul; Ball, Austin; Barney, David; Benitez, Jose F; Bernet, Colin; Bianchi, Giovanni; Bloch, Philippe; Bocci, Andrea; Bonato, Alessio; Botta, Cristina; Breuker, Horst; Camporesi, Tiziano; Cerminara, Gianluca; Christiansen, Tim; Coarasa Perez, Jose Antonio; D'Enterria, David; Dabrowski, Anne; De Roeck, Albert; Di Guida, Salvatore; Dobson, Marc; Dupont-Sagorin, Niels; Elliott-Peisert, Anna; Frisch, Benjamin; Funk, Wolfgang; Georgiou, Georgios; Giffels, Manuel; Gigi, Dominique; Gill, Karl; Giordano, Domenico; Girone, Maria; Giunta, Marina; Glege, Frank; Gomez-Reino Garrido, Robert; Govoni, Pietro; Gowdy, Stephen; Guida, Roberto; Hansen, Magnus; Harris, Philip; Hartl, Christian; Harvey, John; Hegner, Benedikt; Hinzmann, Andreas; Innocente, Vincenzo; Janot, Patrick; Kaadze, Ketino; Karavakis, Edward; Kousouris, Konstantinos; Lecoq, Paul; Lee, Yen-Jie; Lenzi, Piergiulio; Lourenco, Carlos; Magini, Nicolo; Maki, Tuula; Malberti, Martina; Malgeri, Luca; Mannelli, Marcello; Masetti, Lorenzo; Meijers, Frans; Mersi, Stefano; Meschi, Emilio; Moser, Roland; Mozer, Matthias Ulrich; Mulders, Martijn; Musella, Pasquale; Nesvold, Erik; Orimoto, Toyoko; Orsini, Luciano; Palencia Cortezon, Enrique; Perez, Emmanuelle; Perrozzi, Luca; Petrilli, Achille; Pfeiffer, Andreas; Pierini, Maurizio; Pimiä, Martti; Piparo, Danilo; Polese, Giovanni; Quertenmont, Loic; Racz, Attila; Reece, William; Rodrigues Antunes, Joao; Rolandi, Gigi; Rovelli, Chiara; Rovere, Marco; Sakulin, Hannes; Santanastasio, Francesco; Schäfer, Christoph; Schwick, Christoph; Segoni, Ilaria; Sekmen, Sezen; Sharma, Archana; Siegrist, Patrice; Silva, Pedro; Simon, Michal; Sphicas, Paraskevas; Spiga, Daniele; Tsirou, Andromachi; Veres, Gabor Istvan; Vlimant, Jean-Roch; Wöhri, Hermine Katharina; Worm, Steven; Zeuner, Wolfram Dietrich; Bertl, Willi; Deiters, Konrad; Erdmann, Wolfram; Gabathuler, Kurt; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; König, Stefan; Kotlinski, Danek; Langenegger, Urs; Meier, Frank; Renker, Dieter; Rohe, Tilman; Bäni, Lukas; Bortignon, Pierluigi; Buchmann, Marco-Andrea; Casal, Bruno; Chanon, Nicolas; Deisher, Amanda; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dünser, Marc; Eugster, Jürg; Freudenreich, Klaus; Grab, Christoph; Hits, Dmitry; Lecomte, Pierre; Lustermann, Werner; Marini, Andrea Carlo; Martinez Ruiz del Arbol, Pablo; Mohr, Niklas; Moortgat, Filip; Nägeli, Christoph; Nef, Pascal; Nessi-Tedaldi, Francesca; Pandolfi, Francesco; Pape, Luc; Pauss, Felicitas; Peruzzi, Marco; Ronga, Frederic Jean; Rossini, Marco; Sala, Leonardo; Sanchez, Ann - Karin; Starodumov, Andrei; Stieger, Benjamin; Takahashi, Maiko; Tauscher, Ludwig; Thea, Alessandro; Theofilatos, Konstantinos; Treille, Daniel; Urscheler, Christina; Wallny, Rainer; Weber, Hannsjoerg Artur; Wehrli, Lukas; Amsler, Claude; Chiochia, Vincenzo; De Visscher, Simon; Favaro, Carlotta; Ivova Rikova, Mirena; Millan Mejias, Barbara; Otiougova, Polina; Robmann, Peter; Snoek, Hella; Tupputi, Salvatore; Verzetti, Mauro; Chang, Yuan-Hann; Chen, Kuan-Hsin; Kuo, Chia-Ming; Li, Syue-Wei; Lin, Willis; Liu, Zong-Kai; Lu, Yun-Ju; Mekterovic, Darko; Singh, Anil; Volpe, Roberta; Yu, Shin-Shan; Bartalini, Paolo; Chang, Paoti; Chang, You-Hao; Chang, Yu-Wei; Chao, Yuan; Chen, Kai-Feng; Dietz, Charles; Grundler, Ulysses; Hou, George Wei-Shu; Hsiung, Yee; Kao, Kai-Yi; Lei, Yeong-Jyi; Lu, Rong-Shyang; Majumder, Devdatta; Petrakou, Eleni; Shi, Xin; Shiu, Jing-Ge; Tzeng, Yeng-Ming; Wan, Xia; Wang, Minzu; Asavapibhop, Burin; Srimanobhas, Norraphat; Adiguzel, Aytul; Bakirci, Mustafa Numan; Cerci, Salim; Dozen, Candan; Dumanoglu, Isa; Eskut, Eda; Girgis, Semiray; Gokbulut, Gul; Gurpinar, Emine; Hos, Ilknur; Kangal, Evrim Ersin; Karaman, Turker; Karapinar, Guler; Kayis Topaksu, Aysel; Onengut, Gulsen; Ozdemir, Kadri; Ozturk, Sertac; Polatoz, Ayse; Sogut, Kenan; Sunar Cerci, Deniz; Tali, Bayram; Topakli, Huseyin; Vergili, Latife Nukhet; Vergili, Mehmet; Akin, Ilina Vasileva; Aliev, Takhmasib; Bilin, Bugra; Bilmis, Selcuk; Deniz, Muhammed; Gamsizkan, Halil; Guler, Ali Murat; Ocalan, Kadir; Ozpineci, Altug; Serin, Meltem; Sever, Ramazan; Surat, Ugur Emrah; Yalvac, Metin; Yildirim, Eda; Zeyrek, Mehmet; Gülmez, Erhan; Isildak, Bora; Kaya, Mithat; Kaya, Ozlem; Ozkorucuklu, Suat; Sonmez, Nasuf; Cankocak, Kerem; Levchuk, Leonid; Brooke, James John; Clement, Emyr; Cussans, David; Flacher, Henning; Frazier, Robert; Goldstein, Joel; Grimes, Mark; Heath, Greg P; Heath, Helen F; Kreczko, Lukasz; Metson, Simon; Newbold, Dave M; Nirunpong, Kachanon; Poll, Anthony; Senkin, Sergey; Smith, Vincent J; Williams, Thomas; Basso, Lorenzo; Bell, Ken W; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Jackson, James; Kennedy, Bruce W; Olaiya, Emmanuel; Petyt, David; Radburn-Smith, Benjamin Charles; Shepherd-Themistocleous, Claire; Tomalin, Ian R; Womersley, William John; Bainbridge, Robert; Ball, Gordon; Beuselinck, Raymond; Buchmuller, Oliver; Colling, David; Cripps, Nicholas; Cutajar, Michael; Dauncey, Paul; Davies, Gavin; Della Negra, Michel; Ferguson, William; Fulcher, Jonathan; Futyan, David; Gilbert, Andrew; Guneratne Bryer, Arlo; Hall, Geoffrey; Hatherell, Zoe; Hays, Jonathan; Iles, Gregory; Jarvis, Martyn; Karapostoli, Georgia; Lyons, Louis; Magnan, Anne-Marie; Marrouche, Jad; Mathias, Bryn; Nandi, Robin; Nash, Jordan; Nikitenko, Alexander; Papageorgiou, Anastasios; Pela, Joao; Pesaresi, Mark; Petridis, Konstantinos; Pioppi, Michele; Raymond, David Mark; Rogerson, Samuel; Rose, Andrew; Ryan, Matthew John; Seez, Christopher; Sharp, Peter; Sparrow, Alex; Stoye, Markus; Tapper, Alexander; Vazquez Acosta, Monica; Virdee, Tejinder; Wakefield, Stuart; Wardle, Nicholas; Whyntie, Tom; Chadwick, Matthew; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Leggat, Duncan; Leslie, Dawn; Martin, William; Reid, Ivan; Symonds, Philip; Teodorescu, Liliana; Turner, Mark; Hatakeyama, Kenichi; Liu, Hongxuan; Scarborough, Tara; Charaf, Otman; Henderson, Conor; Rumerio, Paolo; Avetisyan, Aram; Bose, Tulika; Fantasia, Cory; Heister, Arno; St John, Jason; Lawson, Philip; Lazic, Dragoslav; Rohlf, James; Sperka, David; Sulak, Lawrence; Alimena, Juliette; Bhattacharya, Saptaparna; Cutts, David; Demiragli, Zeynep; Ferapontov, Alexey; Garabedian, Alex; Heintz, Ulrich; Jabeen, Shabnam; Kukartsev, Gennadiy; Laird, Edward; Landsberg, Greg; Luk, Michael; Narain, Meenakshi; Nguyen, Duong; Segala, Michael; Sinthuprasith, Tutanon; Speer, Thomas; Tsang, Ka Vang; Breedon, Richard; Breto, Guillermo; Calderon De La Barca Sanchez, Manuel; Chauhan, Sushil; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Dolen, James; Erbacher, Robin; Gardner, Michael; Houtz, Rachel; Ko, Winston; Kopecky, Alexandra; Lander, Richard; Mall, Orpheus; Miceli, Tia; Pellett, Dave; Ricci-Tam, Francesca; Rutherford, Britney; Searle, Matthew; Smith, John; Squires, Michael; Tripathi, Mani; Vasquez Sierra, Ricardo; Yohay, Rachel; Andreev, Valeri; Cline, David; Cousins, Robert; Duris, Joseph; Erhan, Samim; Everaerts, Pieter; Farrell, Chris; Hauser, Jay; Ignatenko, Mikhail; Jarvis, Chad; Plager, Charles; Rakness, Gregory; Schlein, Peter; Traczyk, Piotr; Valuev, Vyacheslav; Weber, Matthias; Babb, John; Clare, Robert; Dinardo, Mauro Emanuele; Ellison, John Anthony; Gary, J William; Giordano, Ferdinando; Hanson, Gail; Jeng, Geng-Yuan; Liu, Hongliang; Long, Owen Rosser; Luthra, Arun; Nguyen, Harold; Paramesvaran, Sudarshan; Sturdy, Jared; Sumowidagdo, Suharyo; Wilken, Rachel; Wimpenny, Stephen; Andrews, Warren; Branson, James G; Cerati, Giuseppe Benedetto; Cittolin, Sergio; Evans, David; Golf, Frank; Holzner, André; Kelley, Ryan; Lebourgeois, Matthew; Letts, James; Macneill, Ian; Mangano, Boris; Padhi, Sanjay; Palmer, Christopher; Petrucciani, Giovanni; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Simon, Sean; Sudano, Elizabeth; Tadel, Matevz; Tu, Yanjun; Vartak, Adish; Wasserbaech, Steven; Würthwein, Frank; Yagil, Avraham; Yoo, Jaehyeok; Barge, Derek; Bellan, Riccardo; Campagnari, Claudio; D'Alfonso, Mariarosaria; Danielson, Thomas; Flowers, Kristen; Geffert, Paul; Incandela, Joe; Justus, Christopher; Kalavase, Puneeth; Koay, Sue Ann; Kovalskyi, Dmytro; Krutelyov, Vyacheslav; Lowette, Steven; Mccoll, Nickolas; Pavlunin, Viktor; Rebassoo, Finn; Ribnik, Jacob; Richman, Jeffrey; Rossin, Roberto; Stuart, David; To, Wing; West, Christopher; Apresyan, Artur; Bornheim, Adolf; Chen, Yi; Di Marco, Emanuele; Duarte, Javier; Gataullin, Marat; Ma, Yousi; Mott, Alexander; Newman, Harvey B; Rogan, Christopher; Spiropulu, Maria; Timciuc, Vladlen; Veverka, Jan; Wilkinson, Richard; Xie, Si; Yang, Yong; Zhu, Ren-Yuan; Akgun, Bora; Azzolini, Virginia; Calamba, Aristotle; Carroll, Ryan; Ferguson, Thomas; Iiyama, Yutaro; Jang, Dong Wook; Liu, Yueh-Feng; Paulini, Manfred; Vogel, Helmut; Vorobiev, Igor; Cumalat, John Perry; Drell, Brian Robert; Ford, William T; Gaz, Alessandro; Luiggi Lopez, Eduardo; Smith, James; Stenson, Kevin; Ulmer, Keith; Wagner, Stephen Robert; Alexander, James; Chatterjee, Avishek; Eggert, Nicholas; Gibbons, Lawrence Kent; Heltsley, Brian; Khukhunaishvili, Aleko; Kreis, Benjamin; Mirman, Nathan; Nicolas Kaufman, Gala; Patterson, Juliet Ritchie; Ryd, Anders; Salvati, Emmanuele; Sun, Werner; Teo, Wee Don; Thom, Julia; Thompson, Joshua; Tucker, Jordan; Vaughan, Jennifer; Weng, Yao; Winstrom, Lucas; Wittich, Peter; Winn, Dave; Abdullin, Salavat; Albrow, Michael; Anderson, Jacob; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Bloch, Ingo; Burkett, Kevin; Butler, Joel Nathan; Chetluru, Vasundhara; Cheung, Harry; Chlebana, Frank; Elvira, Victor Daniel; Fisk, Ian; Freeman, Jim; Gao, Yanyan; Green, Dan; Gutsche, Oliver; Hanlon, Jim; Harris, Robert M; Hirschauer, James; Hooberman, Benjamin; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Kilminster, Benjamin; Klima, Boaz; Kunori, Shuichi; Kwan, Simon; Leonidopoulos, Christos; Linacre, Jacob; Lincoln, Don; Lipton, Ron; Lykken, Joseph; Maeshima, Kaori; Marraffino, John Michael; Maruyama, Sho; Mason, David; McBride, Patricia; Mishra, Kalanand; Mrenna, Stephen; Musienko, Yuri; Newman-Holmes, Catherine; O'Dell, Vivian; Prokofyev, Oleg; Sexton-Kennedy, Elizabeth; Sharma, Seema; Spalding, William J; Spiegel, Leonard; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vidal, Richard; Whitmore, Juliana; Wu, Weimin; Yang, Fan; Yumiceva, Francisco; Yun, Jae Chul; Acosta, Darin; Avery, Paul; Bourilkov, Dimitri; Chen, Mingshui; Cheng, Tongguang; Das, Souvik; De Gruttola, Michele; Di Giovanni, Gian Piero; Dobur, Didar; Drozdetskiy, Alexey; Field, Richard D; Fisher, Matthew; Fu, Yu; Furic, Ivan-Kresimir; Gartner, Joseph; Hugon, Justin; Kim, Bockjoo; Konigsberg, Jacobo; Korytov, Andrey; Kropivnitskaya, Anna; Kypreos, Theodore; Low, Jia Fu; Matchev, Konstantin; Milenovic, Predrag; Mitselmakher, Guenakh; Muniz, Lana; Park, Myeonghun; Remington, Ronald; Rinkevicius, Aurelijus; Sellers, Paul; Skhirtladze, Nikoloz; Snowball, Matthew; Yelton, John; Zakaria, Mohammed; Gaultney, Vanessa; Hewamanage, Samantha; Lebolo, Luis Miguel; Linn, Stephan; Markowitz, Pete; Martinez, German; Rodriguez, Jorge Luis; Adams, Todd; Askew, Andrew; Bochenek, Joseph; Chen, Jie; Diamond, Brendan; Gleyzer, Sergei V; Haas, Jeff; Hagopian, Sharon; Hagopian, Vasken; Jenkins, Merrill; Johnson, Kurtis F; Prosper, Harrison; Veeraraghavan, Venkatesh; Weinberg, Marc; Baarmand, Marc M; Dorney, Brian; Hohlmann, Marcus; Kalakhety, Himali; Vodopiyanov, Igor; Adams, Mark Raymond; Anghel, Ioana Maria; Apanasevich, Leonard; Bai, Yuting; Bazterra, Victor Eduardo; Betts, Russell Richard; Bucinskaite, Inga; Callner, Jeremy; Cavanaugh, Richard; Evdokimov, Olga; Gauthier, Lucie; Gerber, Cecilia Elena; Hofman, David Jonathan; Khalatyan, Samvel; Lacroix, Florent; Malek, Magdalena; O'Brien, Christine; Silkworth, Christopher; Strom, Derek; Turner, Paul; Varelas, Nikos; Akgun, Ugur; Albayrak, Elif Asli; Bilki, Burak; Clarida, Warren; Duru, Firdevs; Merlo, Jean-Pierre; Mermerkaya, Hamit; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Newsom, Charles Ray; Norbeck, Edwin; Onel, Yasar; Ozok, Ferhat; Sen, Sercan; Tan, Ping; Tiras, Emrah; Wetzel, James; Yetkin, Taylan; Yi, Kai; Barnett, Bruce Arnold; Blumenfeld, Barry; Bolognesi, Sara; Fehling, David; Giurgiu, Gavril; Gritsan, Andrei; Guo, Zijin; Hu, Guofan; Maksimovic, Petar; Rappoccio, Salvatore; Swartz, Morris; Whitbeck, Andrew; Baringer, Philip; Bean, Alice; Benelli, Gabriele; Kenny Iii, Raymond Patrick; Murray, Michael; Noonan, Daniel; Sanders, Stephen; Stringer, Robert; Tinti, Gemma; Wood, Jeffrey Scott; Zhukova, Victoria; Barfuss, Anne-Fleur; Bolton, Tim; Chakaberia, Irakli; Ivanov, Andrew; Khalil, Sadia; Makouski, Mikhail; Maravin, Yurii; Shrestha, Shruti; Svintradze, Irakli; Gronberg, Jeffrey; Lange, David; Wright, Douglas; Baden, Drew; Boutemeur, Madjid; Calvert, Brian; Eno, Sarah Catherine; Gomez, Jaime; Hadley, Nicholas John; Kellogg, Richard G; Kirn, Malina; Kolberg, Ted; Lu, Ying; Marionneau, Matthieu; Mignerey, Alice; Pedro, Kevin; Skuja, Andris; Temple, Jeffrey; Tonjes, Marguerite; Tonwar, Suresh C; Twedt, Elizabeth; Apyan, Aram; Bauer, Gerry; Bendavid, Joshua; Busza, Wit; Butz, Erik; Cali, Ivan Amos; Chan, Matthew; Dutta, Valentina; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Hahn, Kristan Allan; Kim, Yongsun; Klute, Markus; Krajczar, Krisztian; Luckey, Paul David; Ma, Teng; Nahn, Steve; Paus, Christoph; Ralph, Duncan; Roland, Christof; Roland, Gunther; Rudolph, Matthew; Stephans, George; Stöckli, Fabian; Sumorok, Konstanty; Sung, Kevin; Velicanu, Dragos; Wenger, Edward Allen; Wolf, Roger; Wyslouch, Bolek; Yang, Mingming; Yilmaz, Yetkin; Yoon, Sungho; Zanetti, Marco; Cooper, Seth; Dahmes, Bryan; De Benedetti, Abraham; Franzoni, Giovanni; Gude, Alexander; Kao, Shih-Chuan; Klapoetke, Kevin; Kubota, Yuichi; Mans, Jeremy; Pastika, Nathaniel; Rusack, Roger; Sasseville, Michael; Singovsky, Alexander; Tambe, Norbert; Turkewitz, Jared; Cremaldi, Lucien Marcus; Kroeger, Rob; Perera, Lalith; Rahmat, Rahmat; Sanders, David A; Avdeeva, Ekaterina; Bloom, Kenneth; Bose, Suvadeep; Claes, Daniel R; Dominguez, Aaron; Eads, Michael; Keller, Jason; Kravchenko, Ilya; Lazo-Flores, Jose; Malbouisson, Helena; Malik, Sudhir; Snow, Gregory R; Godshalk, Andrew; Iashvili, Ia; Jain, Supriya; Kharchilava, Avto; Kumar, Ashish; Alverson, George; Barberis, Emanuela; Baumgartel, Darin; Chasco, Matthew; Haley, Joseph; Nash, David; Trocino, Daniele; Wood, Darien; Zhang, Jinzhong; Anastassov, Anton; Kubik, Andrew; Lusito, Letizia; Mucia, Nicholas; Odell, Nathaniel; Ofierzynski, Radoslaw Adrian; Pollack, Brian; Pozdnyakov, Andrey; Schmitt, Michael Henry; Stoynev, Stoyan; Velasco, Mayda; Won, Steven; Antonelli, Louis; Berry, Douglas; Brinkerhoff, Andrew; Chan, Kwok Ming; Hildreth, Michael; Jessop, Colin; Karmgard, Daniel John; Kolb, Jeff; Lannon, Kevin; Luo, Wuming; Lynch, Sean; Marinelli, Nancy; Morse, David Michael; Pearson, Tessa; Planer, Michael; Ruchti, Randy; Slaunwhite, Jason; Valls, Nil; Wayne, Mitchell; Wolf, Matthias; Bylsma, Ben; Durkin, Lloyd Stanley; Hill, Christopher; Hughes, Richard; Kotov, Khristian; Ling, Ta-Yung; Puigh, Darren; Rodenburg, Marissa; Vuosalo, Carl; Williams, Grayson; Winer, Brian L; Adam, Nadia; Berry, Edmund; Elmer, Peter; Gerbaudo, Davide; Halyo, Valerie; Hebda, Philip; Hegeman, Jeroen; Hunt, Adam; Jindal, Pratima; Lopes Pegna, David; Lujan, Paul; Marlow, Daniel; Medvedeva, Tatiana; Mooney, Michael; Olsen, James; Piroué, Pierre; Quan, Xiaohang; Raval, Amita; Safdi, Ben; Saka, Halil; Stickland, David; Tully, Christopher; Werner, Jeremy Scott; Zuranski, Andrzej; Brownson, Eric; Lopez, Angel; Mendez, Hector; Ramirez Vargas, Juan Eduardo; Alagoz, Enver; Barnes, Virgil E; Benedetti, Daniele; Bolla, Gino; Bortoletto, Daniela; De Mattia, Marco; Everett, Adam; Hu, Zhen; Jones, Matthew; Koybasi, Ozhan; Kress, Matthew; Laasanen, Alvin T; Leonardo, Nuno; Maroussov, Vassili; Merkel, Petra; Miller, David Harry; Neumeister, Norbert; Shipsey, Ian; Silvers, David; Svyatkovskiy, Alexey; Vidal Marono, Miguel; Yoo, Hwi Dong; Zablocki, Jakub; Zheng, Yu; Guragain, Samir; Parashar, Neeti; Adair, Antony; Boulahouache, Chaouki; Ecklund, Karl Matthew; Geurts, Frank JM; Li, Wei; Padley, Brian Paul; Redjimi, Radia; Roberts, Jay; Zabel, James; Betchart, Burton; Bodek, Arie; Chung, Yeon Sei; Covarelli, Roberto; de Barbaro, Pawel; Demina, Regina; Eshaq, Yossof; Ferbel, Thomas; Garcia-Bellido, Aran; Goldenzweig, Pablo; Han, Jiyeon; Harel, Amnon; Miner, Daniel Carl; Vishnevskiy, Dmitry; Zielinski, Marek; Bhatti, Anwar; Ciesielski, Robert; Demortier, Luc; Goulianos, Konstantin; Lungu, Gheorghe; Malik, Sarah; Mesropian, Christina; Arora, Sanjay; Barker, Anthony; Chou, John Paul; Contreras-Campana, Christian; Contreras-Campana, Emmanuel; Duggan, Daniel; Ferencek, Dinko; Gershtein, Yuri; Gray, Richard; Halkiadakis, Eva; Hidas, Dean; Lath, Amitabh; Panwalkar, Shruti; Park, Michael; Patel, Rishi; Rekovic, Vladimir; Robles, Jorge; Rose, Keith; Salur, Sevil; Schnetzer, Steve; Seitz, Claudia; Somalwar, Sunil; Stone, Robert; Thomas, Scott; Walker, Matthew; Cerizza, Giordano; Hollingsworth, Matthew; Spanier, Stefan; Yang, Zong-Chang; York, Andrew; Eusebi, Ricardo; Flanagan, Will; Gilmore, Jason; Kamon, Teruki; Khotilovich, Vadim; Montalvo, Roy; Osipenkov, Ilya; Pakhotin, Yuriy; Perloff, Alexx; Roe, Jeffrey; Safonov, Alexei; Sakuma, Tai; Sengupta, Sinjini; Suarez, Indara; Tatarinov, Aysen; Toback, David; Akchurin, Nural; Damgov, Jordan; Dragoiu, Cosmin; Dudero, Phillip Russell; Jeong, Chiyoung; Kovitanggoon, Kittikul; Lee, Sung Won; Libeiro, Terence; Roh, Youn; Volobouev, Igor; Appelt, Eric; Delannoy, Andrés G; Florez, Carlos; Greene, Senta; Gurrola, Alfredo; Johns, Willard; Kurt, Pelin; Maguire, Charles; Melo, Andrew; Sharma, Monika; Sheldon, Paul; Snook, Benjamin; Tuo, Shengquan; Velkovska, Julia; Arenton, Michael Wayne; Balazs, Michael; Boutle, Sarah; Cox, Bradley; Francis, Brian; Goodell, Joseph; Hirosky, Robert; Ledovskoy, Alexander; Lin, Chuanzhe; Neu, Christopher; Wood, John; Gollapinni, Sowjanya; Harr, Robert; Karchin, Paul Edmund; Kottachchi Kankanamge Don, Chamath; Lamichhane, Pramod; Sakharov, Alexandre; Anderson, Michael; Belknap, Donald; Borrello, Laura; Carlsmith, Duncan; Cepeda, Maria; Dasu, Sridhara; Friis, Evan; Gray, Lindsey; Grogg, Kira Suzanne; Grothe, Monika; Hall-Wilton, Richard; Herndon, Matthew; Hervé, Alain; Klabbers, Pamela; Klukas, Jeffrey; Lanaro, Armando; Lazaridis, Christos; Leonard, Jessica; Loveless, Richard; Mohapatra, Ajit; Ojalvo, Isabel; Palmonari, Francesco; Pierro, Giuseppe Antonio; Ross, Ian; Savin, Alexander; Smith, Wesley H; Swanson, Joshua

    2013-11-04

    Results are reported from a search for non-standard-model Higgs boson decays to pairs of new light bosons, each of which decays into the oppositely charged dimuon final state. The new bosons may be produced either promptly or via a decay chain. The data set corresponds to an integrated luminosity of 5.3 inverse femtobarns of proton-proton collisions at $\\sqrt{s}$ = 7 TeV, recorded by the CMS experiment at the LHC. Such Higgs boson decays are predicted in several scenarios of new physics, including supersymmetric models with extended Higgs sectors or hidden valleys. Thus, the results of the search are relevant for establishing whether the new particle observed in Higgs boson searches at the LHC has the properties expected for a standard model Higgs boson. No excess of events is observed with respect to the yields expected from standard model processes. A model-independent upper limit of 0.78 +/- 0.05 fb on the product of the cross section times branching fraction times acceptance is obtained. The results are a...

  12. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  13. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  14. Predictive Modelling of Heavy Metals in Urban Lakes

    OpenAIRE

    Lindström, Martin

    2000-01-01

    Heavy metals are well-known environmental pollutants. In this thesis predictive models for heavy metals in urban lakes are discussed and new models presented. The base of predictive modelling is empirical data from field investigations of many ecosystems covering a wide range of ecosystem characteristics. Predictive models focus on the variabilities among lakes and processes controlling the major metal fluxes. Sediment and water data for this study were collected from ten small lakes in the ...

  15. Meningkatkan Aktivitas dan Hasil Belajar Siswa dengan Menerapkan Pembelajaran Kooperatif Model Think Pair Share Berbasis Kurikulum 2013

    Directory of Open Access Journals (Sweden)

    Achmad Alfian Irawan

    2015-11-01

    Full Text Available This research aims to determine the Increase Activity and Student’s Results in Analysis and Market Research subject for the tenth grade students of Marketing 1 at SMK Negeri 1 Pasuruan in 2014/2015 academic year. The type of this research is classroom action research (CAR. Subjects are the tenth grade students of Marketing 1 class X SMK 1 Pasuruan in 2014/2015 academic year. Data collection was done by using tests, observations, field notes, interviews, student questionnaire responses and documentation. The research is implemented within two cycles. Each cycle includes four phases of activities, which are: 1 planning the action, 2 implementing the action, 3 observation, and 4 reflection. The research findings showed that the implementation Think Pair Share that is: (a thinking, (b pairing (c sharing. Results of the research showed that (1 Implementation of the learning goes well, as evidenced by an increase in activity and student learning outcomes, (2 learning activities of students increased from 37.91% the percentage of the first cycle to 87.60% in the second cycle, (3 the results of student learning consists of cognitive, affective, and psychomotor percentage 44.19% increase from the first cycle to 85.56% in the second cycle (4 barriers that occur can be overcome with the reflection solutions in the form of advice from teachers subjects and observer (5 The response of students to the implementation of cooperative learning model of TPS to get a good appreciation and enthusiasm by the students with an average value of percentage of 87.76%. One of the constraints of the application of the learning model think pair share that need better time management so that teachers should be more careful in managing time. Abstrak: Penelitian ini bertujuan untuk mengetahui peningkatan aktivitas dan hasil belajar siswa dalam mata pelajaran analisis dan riset pasar kelas X Pemasaran 1 semester genap 2014/2015 di SMK PGRI 3 Malang. Jenis penelitian ini

  16. Relation between quantum phase transitions and classical instability points in the pairing model

    International Nuclear Information System (INIS)

    Reis, Mauricio; Terra Cunha, M.O.; Oliveira, Adelcio C.; Nemes, M.C.

    2005-01-01

    A quantum phase transition, characterized by an accumulation of energy levels in the espectrum of the model, is associated with a qualitative change in the corresponding classical dynamic obtained upon generalized coherent states of angular momentum

  17. The Effectiveness of Cooperative Learning Model of Pair Checks Type on Motivation and Mathematics Learning Outcomes of 8th Grade Junior High School Students

    Directory of Open Access Journals (Sweden)

    Wahyu Budi Wicaksono

    2017-08-01

    Full Text Available The purpose of this research was to know the effectiveness of Pair Checks cooperative model towards students’ learning result and learning motivation of eight grade. Population of this research were students of eight grade Junior High School 2 Pati in the academic year 2016/1017. The research used cluster random sampling technique.Where the selected samples were students of class VIII H as experimental class and class VIII G as control class. The data collected by the method of documentation, test methods, and scale methods. The analyzed of data used completeness test and average different test. The results showed that: (1 students’ learning result who join Pair Checks cooperative model have classical study completeness; (2 students’ mathematics learning result who join Pair Checks cooperative model is better than students mathematics learning result who join ekspository learning; (3 students’ learning motivation who join Pair Checks cooperative model is better than students’ learning motivation who join ekspository learning.

  18. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  19. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  20. Predicting knee replacement damage in a simulator machine using a computational model with a consistent wear factor.

    Science.gov (United States)

    Zhao, Dong; Sakoda, Hideyuki; Sawyer, W Gregory; Banks, Scott A; Fregly, Benjamin J

    2008-02-01

    Wear of ultrahigh molecular weight polyethylene remains a primary factor limiting the longevity of total knee replacements (TKRs). However, wear testing on a simulator machine is time consuming and expensive, making it impractical for iterative design purposes. The objectives of this paper were first, to evaluate whether a computational model using a wear factor consistent with the TKR material pair can predict accurate TKR damage measured in a simulator machine, and second, to investigate how choice of surface evolution method (fixed or variable step) and material model (linear or nonlinear) affect the prediction. An iterative computational damage model was constructed for a commercial knee implant in an AMTI simulator machine. The damage model combined a dynamic contact model with a surface evolution model to predict how wear plus creep progressively alter tibial insert geometry over multiple simulations. The computational framework was validated by predicting wear in a cylinder-on-plate system for which an analytical solution was derived. The implant damage model was evaluated for 5 million cycles of simulated gait using damage measurements made on the same implant in an AMTI machine. Using a pin-on-plate wear factor for the same material pair as the implant, the model predicted tibial insert wear volume to within 2% error and damage depths and areas to within 18% and 10% error, respectively. Choice of material model had little influence, while inclusion of surface evolution affected damage depth and area but not wear volume predictions. Surface evolution method was important only during the initial cycles, where variable step was needed to capture rapid geometry changes due to the creep. Overall, our results indicate that accurate TKR damage predictions can be made with a computational model using a constant wear factor obtained from pin-on-plate tests for the same material pair, and furthermore, that surface evolution method matters only during the initial

  1. Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs

    Directory of Open Access Journals (Sweden)

    Sheng Zhi-Ya

    2008-02-01

    Full Text Available Abstract Background As one of the most common protein post-translational modifications, glycosylation is involved in a variety of important biological processes. Computational identification of glycosylation sites in protein sequences becomes increasingly important in the post-genomic era. A new encoding scheme was employed to improve the prediction of mucin-type O-glycosylation sites in mammalian proteins. Results A new protein bioinformatics tool, CKSAAP_OGlySite, was developed to predict mucin-type O-glycosylation serine/threonine (S/T sites in mammalian proteins. Using the composition of k-spaced amino acid pairs (CKSAAP based encoding scheme, the proposed method was trained and tested in a new and stringent O-glycosylation dataset with the assistance of Support Vector Machine (SVM. When the ratio of O-glycosylation to non-glycosylation sites in training datasets was set as 1:1, 10-fold cross-validation tests showed that the proposed method yielded a high accuracy of 83.1% and 81.4% in predicting O-glycosylated S and T sites, respectively. Based on the same datasets, CKSAAP_OGlySite resulted in a higher accuracy than the conventional binary encoding based method (about +5.0%. When trained and tested in 1:5 datasets, the CKSAAP encoding showed a more significant improvement than the binary encoding. We also merged the training datasets of S and T sites and integrated the prediction of S and T sites into one single predictor (i.e. S+T predictor. Either in 1:1 or 1:5 datasets, the performance of this S+T predictor was always slightly better than those predictors where S and T sites were independently predicted, suggesting that the molecular recognition of O-glycosylated S/T sites seems to be similar and the increase of the S+T predictor's accuracy may be a result of expanded training datasets. Moreover, CKSAAP_OGlySite was also shown to have better performance when benchmarked against two existing predictors. Conclusion Because of CKSAAP

  2. MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

    Science.gov (United States)

    Son, S. W.; Lim, Y.; Kim, D.

    2017-12-01

    The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

  3. Effects of ionic strength and ion pairing on (plant-wide) modelling of anaerobic digestion

    DEFF Research Database (Denmark)

    Solon, Kimberly; Flores Alsina, Xavier; Mbamba, Christian Kazadi

    2015-01-01

    Plant-wide models of wastewater treatment (such as the Benchmark Simulation Model No. 2 or BSM2) are gaining popularity for use in holistic virtual studies of treatment plant control and operations. The objective of this study is to show the influence of ionic strength (as activity corrections....... The paper describes: 1) how the anaerobic digester performance is affected by physico-chemical corrections; 2) the effect on pH and the anaerobic digestion products (CO2, CH4 and H2); and, 3) how these variations are propagated from the sludge treatment to the water line. Results at high ionic strength...

  4. Butterfly, Recurrence, and Predictability in Lorenz Models

    Science.gov (United States)

    Shen, B. W.

    2017-12-01

    Over the span of 50 years, the original three-dimensional Lorenz model (3DLM; Lorenz,1963) and its high-dimensional versions (e.g., Shen 2014a and references therein) have been used for improving our understanding of the predictability of weather and climate with a focus on chaotic responses. Although the Lorenz studies focus on nonlinear processes and chaotic dynamics, people often apply a "linear" conceptual model to understand the nonlinear processes in the 3DLM. In this talk, we present examples to illustrate the common misunderstandings regarding butterfly effect and discuss the importance of solutions' recurrence and boundedness in the 3DLM and high-dimensional LMs. The first example is discussed with the following folklore that has been widely used as an analogy of the butterfly effect: "For want of a nail, the shoe was lost.For want of a shoe, the horse was lost.For want of a horse, the rider was lost.For want of a rider, the battle was lost.For want of a battle, the kingdom was lost.And all for the want of a horseshoe nail."However, in 2008, Prof. Lorenz stated that he did not feel that this verse described true chaos but that it better illustrated the simpler phenomenon of instability; and that the verse implicitly suggests that subsequent small events will not reverse the outcome (Lorenz, 2008). Lorenz's comments suggest that the verse neither describes negative (nonlinear) feedback nor indicates recurrence, the latter of which is required for the appearance of a butterfly pattern. The second example is to illustrate that the divergence of two nearby trajectories should be bounded and recurrent, as shown in Figure 1. Furthermore, we will discuss how high-dimensional LMs were derived to illustrate (1) negative nonlinear feedback that stabilizes the system within the five- and seven-dimensional LMs (5D and 7D LMs; Shen 2014a; 2015a; 2016); (2) positive nonlinear feedback that destabilizes the system within the 6D and 8D LMs (Shen 2015b; 2017); and (3

  5. Improved Medical Student Perception of Ultrasound Using a Paired Anatomy Teaching Assistant and Clinician Teaching Model

    Science.gov (United States)

    Smith, Jacob P.; Kendall, John L.; Royer, Danielle F.

    2018-01-01

    This study describes a new teaching model for ultrasound (US) training, and evaluates its effect on medical student attitudes toward US. First year medical students participated in hands-on US during human gross anatomy (2014 N = 183; 2015 N = 182). The sessions were facilitated by clinicians alone in 2014, and by anatomy teaching assistant…

  6. Quantum-critical scaling of fidelity in 2D pairing models

    Energy Technology Data Exchange (ETDEWEB)

    Adamski, Mariusz, E-mail: mariusz.adamski@ift.uni.wroc.pl [Institute of Theoretical Physics, University of Wrocław, pl. Maksa Borna 9, 50–204, Wrocław (Poland); Jȩdrzejewski, Janusz [Institute of Theoretical Physics, University of Wrocław, pl. Maksa Borna 9, 50–204, Wrocław (Poland); Krokhmalskii, Taras [Institute for Condensed Matter Physics, 1 Svientsitski Street, 79011, Lviv (Ukraine)

    2017-01-15

    The laws of quantum-critical scaling theory of quantum fidelity, dependent on the underlying system dimensionality D, have so far been verified in exactly solvable 1D models, belonging to or equivalent to interacting, quadratic (quasifree), spinless or spinfull, lattice-fermion models. The obtained results are so appealing that in quest for correlation lengths and associated universal critical indices ν, which characterize the divergence of correlation lengths on approaching critical points, one might be inclined to substitute the hard task of determining an asymptotic behavior at large distances of a two-point correlation function by an easier one, of determining the quantum-critical scaling of the quantum fidelity. However, the role of system's dimensionality has been left as an open problem. Our aim in this paper is to fill up this gap, at least partially, by verifying the laws of quantum-critical scaling theory of quantum fidelity in a 2D case. To this end, we study correlation functions and quantum fidelity of 2D exactly solvable models, which are interacting, quasifree, spinfull, lattice-fermion models. The considered 2D models exhibit new, as compared with 1D ones, features: at a given quantum-critical point there exists a multitude of correlation lengths and multiple universal critical indices ν, since these quantities depend on spatial directions, moreover, the indices ν may assume larger values. These facts follow from the obtained by us analytical asymptotic formulae for two-point correlation functions. In such new circumstances we discuss the behavior of quantum fidelity from the perspective of quantum-critical scaling theory. In particular, we are interested in finding out to what extent the quantum fidelity approach may be an alternative to the correlation-function approach in studies of quantum-critical points beyond 1D.

  7. Auditing predictive models : a case study in crop growth

    NARCIS (Netherlands)

    Metselaar, K.

    1999-01-01

    Methods were developed to assess and quantify the predictive quality of simulation models, with the intent to contribute to evaluation of model studies by non-scientists. In a case study, two models of different complexity, LINTUL and SUCROS87, were used to predict yield of forage maize

  8. Models for predicting compressive strength and water absorption of ...

    African Journals Online (AJOL)

    This work presents a mathematical model for predicting the compressive strength and water absorption of laterite-quarry dust cement block using augmented Scheffe's simplex lattice design. The statistical models developed can predict the mix proportion that will yield the desired property. The models were tested for lack of ...

  9. Na Cl ion pair association in water-DMSO mixtures: Effect of ion pair ...

    Indian Academy of Sciences (India)

    The 12-6-1 potential model predicts running coordination numbers closest to experimental data. Keywords. ... value of interaction energy minimum between the Na. + and Cl. − ..... ion pair mostly remains as a CIP, a fair amount of SAIP is also ...

  10. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  11. Application of a Regge model to the photoproduction of pion pairs

    Energy Technology Data Exchange (ETDEWEB)

    Bolz, Arthur; Sauter, Michel; Schoening, Andre [Physikalisches Institut, Universitaet Heidelberg, Im Neuenheimer Feld 226, D-69120 Heidelberg (Germany); Ewerz, Carlo [Institut fuer Theoretische Physik, Universitaet Heidelberg, Philosophenweg 16, D-69120 Heidelberg (Germany); ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum fuer Schwerionenforschung, Planckstrasse 1, D-64291 Darmstadt (Germany); Maniatis, Markos [Departamento de Ciencias Basicas, Universidad del Bio-Bio, Avda. Andres Bello s/n, Casilla 447, Chillan 3780000 (Chile); Nachtmann, Otto [Institut fuer Theoretische Physik, Universitaet Heidelberg, Philosophenweg 16, D-69120 Heidelberg (Germany)

    2015-07-01

    In a recent publication (arXiv:1409.8483) a model in the spirit of Regge theory is used to describe the reaction γp → π{sup +}π{sup -} p at high energies. Both resonant pion-pion production via the meson resonances ρ(770), ω(782), ρ(1450) and f{sub 2}(1270) as well as non-resonant amplitudes are considered. Photon and proton interact by the exchange of the photon, the pomeron and reggeons as well as by a yet unobserved but possible odderon. Cross sections calculated from this model and their dependencies on various kinematic quantities are discussed and compared to experimental data. The focus is on angular distributions which feature asymmetries that could be used for an odderon discovery.

  12. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara

    2017-01-01

    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...

  13. Accurate and dynamic predictive model for better prediction in medicine and healthcare.

    Science.gov (United States)

    Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

    2018-05-01

    Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

  14. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

  15. Testing the predictive power of nuclear mass models

    International Nuclear Information System (INIS)

    Mendoza-Temis, J.; Morales, I.; Barea, J.; Frank, A.; Hirsch, J.G.; Vieyra, J.C. Lopez; Van Isacker, P.; Velazquez, V.

    2008-01-01

    A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool

  16. From Predictive Models to Instructional Policies

    Science.gov (United States)

    Rollinson, Joseph; Brunskill, Emma

    2015-01-01

    At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…

  17. Kink-pair formation on dislocations within the framework of the line-tension model

    International Nuclear Information System (INIS)

    Lay, W.

    1991-01-01

    This article deals with the plastic deformation of crystals under an applied stress and summarizes various theoretical concepts within the framework of a model of dislocation migration in crystals. The migration of one type of dislocations in their glide plane is described within the framework of a continuum approximation. The dynamics of the physical system is treated by a Hamiltonian method describing solitonic vibrations of a one-dimensional field added by discussions of a special perturbation which models the applied stress in the glide plane of the dislocation. Dislocation migration is governed by nucleation processes. Therefore, one has to apply thermodynamical concepts in order to calculate the formation rate of the nucleation configuration of the dislocation. This is done here by mapping the solitonic field onto a Brownian particle and using Kramers' famous work on nucleation in chemical reactions. The last section is devoted to an approach involving quantum thermodynamical effects and relating them to tunnelling processes of kinks on dislocations. The method used for calculating tunnelling rates is based on Feynman's path integral method in imaginary time formulation. (author). 26 refs, 12 figs

  18. Bridging cancer biology with the clinic: relative expression of a GRHL2-mediated gene-set pair predicts breast cancer metastasis.

    Directory of Open Access Journals (Sweden)

    Xinan Yang

    Full Text Available Identification and characterization of crucial gene target(s that will allow focused therapeutics development remains a challenge. We have interrogated the putative therapeutic targets associated with the transcription factor Grainy head-like 2 (GRHL2, a critical epithelial regulatory factor. We demonstrate the possibility to define the molecular functions of critical genes in terms of their personalized expression profiles, allowing appropriate functional conclusions to be derived. A novel methodology, relative expression analysis with gene-set pairs (RXA-GSP, is designed to explore the potential clinical utility of cancer-biology discovery. Observing that Grhl2-overexpression leads to increased metastatic potential in vitro, we established a model assuming Grhl2-induced or -inhibited genes confer poor or favorable prognosis respectively for cancer metastasis. Training on public gene expression profiles of 995 breast cancer patients, this method prioritized one gene-set pair (GRHL2, CDH2, FN1, CITED2, MKI67 versus CTNNB1 and CTNNA3 from all 2717 possible gene-set pairs (GSPs. The identified GSP significantly dichotomized 295 independent patients for metastasis-free survival (log-rank tested p = 0.002; severe empirical p = 0.035. It also showed evidence of clinical prognostication in another independent 388 patients collected from three studies (log-rank tested p = 3.3e-6. This GSP is independent of most traditional prognostic indicators, and is only significantly associated with the histological grade of breast cancer (p = 0.0017, a GRHL2-associated clinical character (p = 6.8e-6, Spearman correlation, suggesting that this GSP is reflective of GRHL2-mediated events. Furthermore, a literature review indicates the therapeutic potential of the identified genes. This research demonstrates a novel strategy to integrate both biological experiments and clinical gene expression profiles for extracting and elucidating the genomic

  19. The Complexity of Developmental Predictions from Dual Process Models

    Science.gov (United States)

    Stanovich, Keith E.; West, Richard F.; Toplak, Maggie E.

    2011-01-01

    Drawing developmental predictions from dual-process theories is more complex than is commonly realized. Overly simplified predictions drawn from such models may lead to premature rejection of the dual process approach as one of many tools for understanding cognitive development. Misleading predictions can be avoided by paying attention to several…

  20. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  1. On the gluonic correction to lepton-pair decays in a relativistic quarkonium model

    International Nuclear Information System (INIS)

    Ito, Hitoshi

    1987-01-01

    The gluonic correction to the leptonic decay of the heavy vector meson is investigated by using the perturbation theory to the order α s . The on-mass-shell approximation is assumed for the constituent quarks so that we assure the gauge independence of the correction. The decay rates in the model based on the Bethe-Salpeter equation are also shown, in which the gluonic correction with a high-momentum cutoff is calculated for the off-shell quarks. It is shown that the static approximation to the correction factor (1 - 16α s /3π) is not adequate and the gluonic correction does not suppress but enhance the decay rates of the ground states for the c anti c and b anti b systems. (author)

  2. An experimental modeling and acoustic emission monitoring of abrasive wear in a steel/diabase pair

    Science.gov (United States)

    Korchuganov, M. A.; Filippov, A. V.; Tarasov, S. Yu.; Podgornyh, O. A.; Shamarin, N. N.; Filippova, E. O.

    2016-11-01

    The earthmoving of permafrost soil is a critical task for excavation of minerals and construction on new territories. Failure by abrasive wear is the main reason for excavation parts of earthmoving and soil cutting machines. Therefore investigation of this type of wear is a challenge for developing efficient and wear resistant working parts. This paper is focused on conducting tribological experiments with sliding the steel samples over the surface of diabase stone sample where abrasive wear conditions of soil cutting are modeled experimentally. The worn surfaces of all samples have been examined and transfer of metal and stone particles revealed. The acoustic emission (AE) signals have been recorded and related to the results of worn surface analysis. he acoustic emission (AE) signals have been recorded and related to the results of worn surface analysis. As shown the wear intensity correlates to that of acoustic emission. Both acoustic emission signal median frequency and energy are found to be sensitive to the wear mode.

  3. Assessing risk to birds from industrial wind energy development via paired resource selection models.

    Science.gov (United States)

    Miller, Tricia A; Brooks, Robert P; Lanzone, Michael; Brandes, David; Cooper, Jeff; O'Malley, Kieran; Maisonneuve, Charles; Tremblay, Junior; Duerr, Adam; Katzner, Todd

    2014-06-01

    When wildlife habitat overlaps with industrial development animals may be harmed. Because wildlife and people select resources to maximize biological fitness and economic return, respectively, we estimated risk, the probability of eagles encountering and being affected by turbines, by overlaying models of resource selection for each entity. This conceptual framework can be applied across multiple spatial scales to understand and mitigate impacts of industry on wildlife. We estimated risk to Golden Eagles (Aquila chrysaetos) from wind energy development in 3 topographically distinct regions of the central Appalachian Mountains of Pennsylvania (United States) based on models of resource selection of wind facilities (n = 43) and of northbound migrating eagles (n = 30). Risk to eagles from wind energy was greatest in the Ridge and Valley region; all 24 eagles that passed through that region used the highest risk landscapes at least once during low altitude flight. In contrast, only half of the birds that entered the Allegheny Plateau region used highest risk landscapes and none did in the Allegheny Mountains. Likewise, in the Allegheny Mountains, the majority of wind turbines (56%) were situated in poor eagle habitat; thus, risk to eagles is lower there than in the Ridge and Valley, where only 1% of turbines are in poor eagle habitat. Risk within individual facilities was extremely variable; on average, facilities had 11% (SD 23; range = 0-100%) of turbines in highest risk landscapes and 26% (SD 30; range = 0-85%) of turbines in the lowest risk landscapes. Our results provide a mechanism for relocating high-risk turbines, and they show the feasibility of this novel and highly adaptable framework for managing risk of harm to wildlife from industrial development. © 2014 Society for Conservation Biology.

  4. Modeling of Complex Life Cycle Prediction Based on Cell Division

    Directory of Open Access Journals (Sweden)

    Fucheng Zhang

    2017-01-01

    Full Text Available Effective fault diagnosis and reasonable life expectancy are of great significance and practical engineering value for the safety, reliability, and maintenance cost of equipment and working environment. At present, the life prediction methods of the equipment are equipment life prediction based on condition monitoring, combined forecasting model, and driven data. Most of them need to be based on a large amount of data to achieve the problem. For this issue, we propose learning from the mechanism of cell division in the organism. We have established a moderate complexity of life prediction model across studying the complex multifactor correlation life model. In this paper, we model the life prediction of cell division. Experiments show that our model can effectively simulate the state of cell division. Through the model of reference, we will use it for the equipment of the complex life prediction.

  5. Risk prediction model: Statistical and artificial neural network approach

    Science.gov (United States)

    Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

    2017-04-01

    Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

  6. Predictive modeling and reducing cyclic variability in autoignition engines

    Science.gov (United States)

    Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

    2016-08-30

    Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

  7. Dynamic Simulation of Human Gait Model With Predictive Capability.

    Science.gov (United States)

    Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

    2018-03-01

    In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

  8. Blind intercomparison of nuclear models for predicting charged particle emission

    International Nuclear Information System (INIS)

    Shibata, K.; Cierjacks, S.

    1994-01-01

    Neutron activation data are important for dosimetry, radiation-damage and production of long-lived activities. For fusion energy applications, it is required to develop 'low-activation materials' from the viewpoints of safety, maintenance and waste disposal. Existing evaluated activation cross-section libraries are to a large extent based on nuclear-model calculations. The former Nuclear Energy Agency Nuclear Data Committee, NEANDC, (presently replaced by the NEA Nuclear Science Committee) organized the working group on activation cross sections. The first meeting of the group was held in 1989, and it was then agreed that a blind intercomparison of nuclear-model calculations should be undertaken in order to test the predictive power of the theoretical calculations. As a first stage the working group selected the reactions 60g Co(n,p) 60 Fe and 60m Co(n,p) 60 Fe, for which no experimental data were available, in the energy range from 1 to 20 MeV. The preliminary results compiled at the NEA Data Bank were sent to each participant and a meeting was held during the International Conference on Nuclear Data for Science and Technology in Julich 1991 to discuss the results. Following the outcome of the discussion in Julich, it was decided to extend this intercomparison. In the second-stage calculation, the same optical-model parameters were employed for neutrons, protons and α-particles, i.e., V = 50 MeV, W = 10 MeV, r = 1.25 fm and a = 0.6 fm with the Woods-Saxon volume-type form factors. No spin-orbit interaction was considered. Concerning the level density, the Fermi gas model with a = A/8 MeV -1 was assumed without pairing corrections. Moreover, gamma-ray competition was neglected to simplify the calculation. This report describes the final results of the blind comparison. Section 2 deals with a survey of the received contributions. The final results are graphically presented in section 3. 67 figs., 1 tab., 12 refs

  9. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of ...

  10. A model to predict the power output from wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

  11. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  12. Ocean wave prediction using numerical and neural network models

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    This paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for ocean wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena...

  13. Search for the standard model Higgs boson produced in association with a top-quark pair in pp collisions at the LHC

    CERN Document Server

    Chatrchyan, Serguei; Sirunyan, Albert M; Tumasyan, Armen; Adam, Wolfgang; Bergauer, Thomas; Dragicevic, Marko; Erö, Janos; Fabjan, Christian; Friedl, Markus; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Hörmann, Natascha; Hrubec, Josef; Jeitler, Manfred; Kiesenhofer, Wolfgang; Knünz, Valentin; Krammer, Manfred; Krätschmer, Ilse; Liko, Dietrich; Mikulec, Ivan; Rabady, Dinyar; Rahbaran, Babak; Rohringer, Christine; Rohringer, Herbert; Schöfbeck, Robert; Strauss, Josef; Taurok, Anton; Treberer-Treberspurg, Wolfgang; Waltenberger, Wolfgang; Wulz, Claudia-Elisabeth; Mossolov, Vladimir; Shumeiko, Nikolai; Suarez Gonzalez, Juan; Alderweireldt, Sara; Bansal, Monika; Bansal, Sunil; Cornelis, Tom; De Wolf, Eddi A; Janssen, Xavier; Knutsson, Albert; Luyckx, Sten; Mucibello, Luca; Ochesanu, Silvia; Roland, Benoit; Rougny, Romain; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Van Spilbeeck, Alex; Blekman, Freya; Blyweert, Stijn; D'Hondt, Jorgen; Gonzalez Suarez, Rebeca; Kalogeropoulos, Alexis; Keaveney, James; Maes, Michael; Olbrechts, Annik; Tavernier, Stefaan; Van Doninck, Walter; Van Mulders, Petra; Van Onsem, Gerrit Patrick; Villella, Ilaria; Clerbaux, Barbara; De Lentdecker, Gilles; Dero, Vincent; Gay, Arnaud; Hreus, Tomas; Léonard, Alexandre; Marage, Pierre Edouard; Mohammadi, Abdollah; Reis, Thomas; Thomas, Laurent; Vander Velde, Catherine; Vanlaer, Pascal; Wang, Jian; Adler, Volker; Beernaert, Kelly; Benucci, Leonardo; Cimmino, Anna; Costantini, Silvia; Garcia, Guillaume; Grunewald, Martin; Klein, Benjamin; Lellouch, Jérémie; Marinov, Andrey; Mccartin, Joseph; Ocampo Rios, Alberto Andres; Ryckbosch, Dirk; Sigamani, Michael; Strobbe, Nadja; Thyssen, Filip; Tytgat, Michael; Walsh, Sinead; Yazgan, Efe; Zaganidis, Nicolas; Basegmez, Suzan; Bruno, Giacomo; Castello, Roberto; Ceard, Ludivine; Delaere, Christophe; Du Pree, Tristan; Favart, Denis; Forthomme, Laurent; Giammanco, Andrea; Hollar, Jonathan; Lemaitre, Vincent; Liao, Junhui; Militaru, Otilia; Nuttens, Claude; Pagano, Davide; Pin, Arnaud; Piotrzkowski, Krzysztof; Popov, Andrey; Selvaggi, Michele; Vizan Garcia, Jesus Manuel; Beliy, Nikita; Caebergs, Thierry; Daubie, Evelyne; Hammad, Gregory Habib; Alves, Gilvan; Correa Martins Junior, Marcos; Martins, Thiago; Pol, Maria Elena; Henrique Gomes E Souza, Moacyr; Aldá Júnior, Walter Luiz; Carvalho, Wagner; Chinellato, Jose; Custódio, Analu; Melo Da Costa, Eliza; De Jesus Damiao, Dilson; De Oliveira Martins, Carley; Fonseca De Souza, Sandro; Malbouisson, Helena; Malek, Magdalena; Matos Figueiredo, Diego; Mundim, Luiz; Nogima, Helio; Prado Da Silva, Wanda Lucia; Santoro, Alberto; Soares Jorge, Luana; Sznajder, Andre; Tonelli Manganote, Edmilson José; Vilela Pereira, Antonio; Souza Dos Anjos, Tiago; Bernardes, Cesar Augusto; De Almeida Dias, Flavia; Tomei, Thiago; De Moraes Gregores, Eduardo; Lagana, Caio; Da Cunha Marinho, Franciole; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Genchev, Vladimir; Iaydjiev, Plamen; Piperov, Stefan; Rodozov, Mircho; Stoykova, Stefka; Sultanov, Georgi; Tcholakov, Vanio; Trayanov, Rumen; Vutova, Mariana; Dimitrov, Anton; Hadjiiska, Roumyana; Kozhuharov, Venelin; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Bian, Jian-Guo; Chen, Guo-Ming; Chen, He-Sheng; Jiang, Chun-Hua; Liang, Dong; Liang, Song; Meng, Xiangwei; Tao, Junquan; Wang, Jian; Wang, Xianyou; Wang, Zheng; Xiao, Hong; Xu, Ming; Asawatangtrakuldee, Chayanit; Ban, Yong; Guo, Yifei; Li, Qiang; Li, Wenbo; Liu, Shuai; Mao, Yajun; Qian, Si-Jin; Wang, Dayong; Zhang, Linlin; Zou, Wei; Avila, Carlos; Carrillo Montoya, Camilo Andres; Gomez, Juan Pablo; Gomez Moreno, Bernardo; Sanabria, Juan Carlos; Godinovic, Nikola; Lelas, Damir; Plestina, Roko; Polic, Dunja; Puljak, Ivica; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Duric, Senka; Kadija, Kreso; Luetic, Jelena; Mekterovic, Darko; Morovic, Srecko; Tikvica, Lucija; Attikis, Alexandros; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Finger, Miroslav; Finger Jr, Michael; Assran, Yasser; Ellithi Kamel, Ali; Kuotb Awad, Alaa Metwaly; Mahmoud, Mohammed; Radi, Amr; Kadastik, Mario; Müntel, Mait; Murumaa, Marion; Raidal, Martti; Rebane, Liis; Tiko, Andres; Eerola, Paula; Fedi, Giacomo; Voutilainen, Mikko; Härkönen, Jaakko; Karimäki, Veikko; Kinnunen, Ritva; Kortelainen, Matti J; Lampén, Tapio; Lassila-Perini, Kati; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Mäenpää, Teppo; Peltola, Timo; Tuominen, Eija; Tuominiemi, Jorma; Tuovinen, Esa; Wendland, Lauri; Korpela, Arja; Tuuva, Tuure; Besancon, Marc; Choudhury, Somnath; Couderc, Fabrice; Dejardin, Marc; Denegri, Daniel; Fabbro, Bernard; Faure, Jean-Louis; Ferri, Federico; Ganjour, Serguei; Givernaud, Alain; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Locci, Elizabeth; Malcles, Julie; Millischer, Laurent; Nayak, Aruna; Rander, John; Rosowsky, André; Titov, Maksym; Baffioni, Stephanie; Beaudette, Florian; Benhabib, Lamia; Bianchini, Lorenzo; Bluj, Michal; Busson, Philippe; Charlot, Claude; Daci, Nadir; Dahms, Torsten; Dalchenko, Mykhailo; Dobrzynski, Ludwik; Florent, Alice; Granier de Cassagnac, Raphael; Haguenauer, Maurice; Miné, Philippe; Mironov, Camelia; Naranjo, Ivo Nicolas; Nguyen, Matthew; Ochando, Christophe; Paganini, Pascal; Sabes, David; Salerno, Roberto; Sirois, Yves; Veelken, Christian; Zabi, Alexandre; Agram, Jean-Laurent; Andrea, Jeremy; Bloch, Daniel; Bodin, David; Brom, Jean-Marie; Chabert, Eric Christian; Collard, Caroline; Conte, Eric; Drouhin, Frédéric; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Goetzmann, Christophe; Juillot, Pierre; Le Bihan, Anne-Catherine; Van Hove, Pierre; Beauceron, Stephanie; Beaupere, Nicolas; Bondu, Olivier; Boudoul, Gaelle; Brochet, Sébastien; Chasserat, Julien; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fay, Jean; Gascon, Susan; Gouzevitch, Maxime; Ille, Bernard; Kurca, Tibor; Lethuillier, Morgan; Mirabito, Laurent; Perries, Stephane; Sgandurra, Louis; Sordini, Viola; Tschudi, Yohann; Vander Donckt, Muriel; Verdier, Patrice; Viret, Sébastien; Tsamalaidze, Zviad; Autermann, Christian; Beranek, Sarah; Calpas, Betty; Edelhoff, Matthias; Feld, Lutz; Heracleous, Natalie; Hindrichs, Otto; Jussen, Ruediger; Klein, Katja; Merz, Jennifer; Ostapchuk, Andrey; Perieanu, Adrian; Raupach, Frank; Sammet, Jan; Schael, Stefan; Sprenger, Daniel; Weber, Hendrik; Wittmer, Bruno; Zhukov, Valery; Ata, Metin; Caudron, Julien; Dietz-Laursonn, Erik; Duchardt, Deborah; Erdmann, Martin; Fischer, Robert; Güth, Andreas; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Klingebiel, Dennis; Kreuzer, Peter; Merschmeyer, Markus; Meyer, Arnd; Olschewski, Mark; Padeken, Klaas; Papacz, Paul; Pieta, Holger; Reithler, Hans; Schmitz, Stefan Antonius; Sonnenschein, Lars; Steggemann, Jan; Teyssier, Daniel; Thüer, Sebastian; Weber, Martin; Bontenackels, Michael; Cherepanov, Vladimir; Erdogan, Yusuf; Flügge, Günter; Geenen, Heiko; Geisler, Matthias; Haj Ahmad, Wael; Hoehle, Felix; Kargoll, Bastian; Kress, Thomas; Kuessel, Yvonne; Lingemann, Joschka; Nowack, Andreas; Nugent, Ian Michael; Perchalla, Lars; Pooth, Oliver; Stahl, Achim; Aldaya Martin, Maria; Asin, Ivan; Bartosik, Nazar; Behr, Joerg; Behrenhoff, Wolf; Behrens, Ulf; Bergholz, Matthias; Bethani, Agni; Borras, Kerstin; Burgmeier, Armin; Cakir, Altan; Calligaris, Luigi; Campbell, Alan; Costanza, Francesco; Dammann, Dirk; Diez Pardos, Carmen; Dorland, Tyler; Eckerlin, Guenter; Eckstein, Doris; Flucke, Gero; Geiser, Achim; Glushkov, Ivan; Gunnellini, Paolo; Habib, Shiraz; Hauk, Johannes; Hellwig, Gregor; Jung, Hannes; Kasemann, Matthias; Katsas, Panagiotis; Kleinwort, Claus; Kluge, Hannelies; Krämer, Mira; Krücker, Dirk; Kuznetsova, Ekaterina; Lange, Wolfgang; Leonard, Jessica; Lohmann, Wolfgang; Lutz, Benjamin; Mankel, Rainer; Marfin, Ihar; Marienfeld, Markus; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Mnich, Joachim; Mussgiller, Andreas; Naumann-Emme, Sebastian; Novgorodova, Olga; Nowak, Friederike; Olzem, Jan; Perrey, Hanno; Petrukhin, Alexey; Pitzl, Daniel; Raspereza, Alexei; Ribeiro Cipriano, Pedro M; Riedl, Caroline; Ron, Elias; Rosin, Michele; Salfeld-Nebgen, Jakob; Schmidt, Ringo; Schoerner-Sadenius, Thomas; Sen, Niladri; Stein, Matthias; Walsh, Roberval; Wissing, Christoph; Blobel, Volker; Enderle, Holger; Erfle, Joachim; Gebbert, Ulla; Görner, Martin; Gosselink, Martijn; Haller, Johannes; Höing, Rebekka Sophie; Kaschube, Kolja; Kaussen, Gordon; Kirschenmann, Henning; Klanner, Robert; Lange, Jörn; Peiffer, Thomas; Pietsch, Niklas; Rathjens, Denis; Sander, Christian; Schettler, Hannes; Schleper, Peter; Schlieckau, Eike; Schmidt, Alexander; Schum, Torben; Seidel, Markus; Sibille, Jennifer; Sola, Valentina; Stadie, Hartmut; Steinbrück, Georg; Thomsen, Jan; Vanelderen, Lukas; Barth, Christian; Baus, Colin; Berger, Joram; Böser, Christian; Chwalek, Thorsten; De Boer, Wim; Descroix, Alexis; Dierlamm, Alexander; Feindt, Michael; Guthoff, Moritz; Hackstein, Christoph; Hartmann, Frank; Hauth, Thomas; Heinrich, Michael; Held, Hauke; Hoffmann, Karl-Heinz; Husemann, Ulrich; Katkov, Igor; Komaragiri, Jyothsna Rani; Kornmayer, Andreas; Lobelle Pardo, Patricia; Martschei, Daniel; Mueller, Steffen; Müller, Thomas; Niegel, Martin; Nürnberg, Andreas; Oberst, Oliver; Ott, Jochen; Quast, Gunter; Rabbertz, Klaus; Ratnikov, Fedor; Ratnikova, Natalia; Röcker, Steffen; Schilling, Frank-Peter; Schott, Gregory; Simonis, Hans-Jürgen; Stober, Fred-Markus Helmut; Troendle, Daniel; Ulrich, Ralf; Wagner-Kuhr, Jeannine; Wayand, Stefan; Weiler, Thomas; Zeise, Manuel; Anagnostou, Georgios; Daskalakis, Georgios; Geralis, Theodoros; Kesisoglou, Stilianos; Kyriakis, Aristotelis; Loukas, Demetrios; Markou, Athanasios; Markou, Christos; Ntomari, Eleni; Gouskos, Loukas; Mertzimekis, Theodoros; Panagiotou, Apostolos; Saoulidou, Niki; Stiliaris, Efstathios; Aslanoglou, Xenofon; Evangelou, Ioannis; Flouris, Giannis; Foudas, Costas; Kokkas, Panagiotis; Manthos, Nikolaos; Papadopoulos, Ioannis; Paradas, Evangelos; Bencze, Gyorgy; Hajdu, Csaba; Hidas, Pàl; Horvath, Dezso; Radics, Balint; Sikler, Ferenc; Veszpremi, Viktor; Vesztergombi, Gyorgy; Zsigmond, Anna Julia; Beni, Noemi; Czellar, Sandor; Molnar, Jozsef; Palinkas, Jozsef; Szillasi, Zoltan; Karancsi, János; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Beri, Suman Bala; Bhatnagar, Vipin; Dhingra, Nitish; Gupta, Ruchi; Kaur, Manjit; Mehta, Manuk Zubin; Mittal, Monika; Nishu, Nishu; Saini, Lovedeep Kaur; Sharma, Archana; Singh, Jasbir; Kumar, Ashok; Kumar, Arun; Ahuja, Sudha; Bhardwaj, Ashutosh; Choudhary, Brajesh C; Malhotra, Shivali; Naimuddin, Md; Ranjan, Kirti; Saxena, Pooja; Sharma, Varun; Shivpuri, Ram Krishen; Banerjee, Sunanda; Bhattacharya, Satyaki; Chatterjee, Kalyanmoy; Dutta, Suchandra; Gomber, Bhawna; Jain, Sandhya; Jain, Shilpi; Khurana, Raman; Modak, Atanu; Mukherjee, Swagata; Roy, Debarati; Sarkar, Subir; Sharan, Manoj; Abdulsalam, Abdulla; Dutta, Dipanwita; Kailas, Swaminathan; Kumar, Vineet; Mohanty, Ajit Kumar; Pant, Lalit Mohan; Shukla, Prashant; Topkar, Anita; Aziz, Tariq; Chatterjee, Rajdeep Mohan; Ganguly, Sanmay; Guchait, Monoranjan; Gurtu, Atul; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Mohanty, Gagan Bihari; Parida, Bibhuti; Sudhakar, Katta; Wickramage, Nadeesha; Banerjee, Sudeshna; Dugad, Shashikant; Arfaei, Hessamaddin; Bakhshiansohi, Hamed; Etesami, Seyed Mohsen; Fahim, Ali; Hesari, Hoda; Jafari, Abideh; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Paktinat Mehdiabadi, Saeid; Safarzadeh, Batool; Zeinali, Maryam; Abbrescia, Marcello; Barbone, Lucia; Calabria, Cesare; Chhibra, Simranjit Singh; Colaleo, Anna; Creanza, Donato; De Filippis, Nicola; De Palma, Mauro; Fiore, Luigi; Iaselli, Giuseppe; Maggi, Giorgio; Maggi, Marcello; Marangelli, Bartolomeo; My, Salvatore; Nuzzo, Salvatore; Pacifico, Nicola; Pompili, Alexis; Pugliese, Gabriella; Selvaggi, Giovanna; Silvestris, Lucia; Singh, Gurpreet; Venditti, Rosamaria; Verwilligen, Piet; Zito, Giuseppe; Abbiendi, Giovanni; Benvenuti, Alberto; Bonacorsi, Daniele; Braibant-Giacomelli, Sylvie; Brigliadori, Luca; Campanini, Renato; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Fasanella, Daniele; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Meneghelli, Marco; Montanari, Alessandro; Navarria, Francesco; Odorici, Fabrizio; Perrotta, Andrea; Primavera, Federica; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Tosi, Nicolò; Travaglini, Riccardo; Albergo, Sebastiano; Chiorboli, Massimiliano; Costa, Salvatore; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Frosali, Simone; Gallo, Elisabetta; Gonzi, Sandro; Lenzi, Piergiulio; Meschini, Marco; Paoletti, Simone; Sguazzoni, Giacomo; Tropiano, Antonio; Benussi, Luigi; Bianco, Stefano; Colafranceschi, Stefano; Fabbri, Franco; Piccolo, Davide; Fabbricatore, Pasquale; Musenich, Riccardo; Tosi, Silvano; Benaglia, Andrea; De Guio, Federico; Di Matteo, Leonardo; Fiorendi, Sara; Gennai, Simone; Ghezzi, Alessio; Lucchini, Marco Toliman; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Martelli, Arabella; Massironi, Andrea; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pedrini, Daniele; Ragazzi, Stefano; Redaelli, Nicola; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Cavallo, Nicola; De Cosa, Annapaola; Dogangun, Oktay; Fabozzi, Francesco; Iorio, Alberto Orso Maria; Lista, Luca; Meola, Sabino; Merola, Mario; Paolucci, Pierluigi; Azzi, Patrizia; Bacchetta, Nicola; Biasotto, Massimo; Bisello, Dario; Branca, Antonio; Carlin, Roberto; Checchia, Paolo; Dorigo, Tommaso; Galanti, Mario; Gasparini, Fabrizio; Gasparini, Ugo; Giubilato, Piero; Gozzelino, Andrea; Kanishchev, Konstantin; Lacaprara, Stefano; Lazzizzera, Ignazio; Margoni, Martino; Meneguzzo, Anna Teresa; Passaseo, Marina; Pazzini, Jacopo; Pozzobon, Nicola; Ronchese, Paolo; Simonetto, Franco; Torassa, Ezio; Tosi, Mia; Vanini, Sara; Ventura, Sandro; Zotto, Pierluigi; Zucchetta, Alberto; Zumerle, Gianni; Gabusi, Michele; Ratti, Sergio P; Riccardi, Cristina; Vitulo, Paolo; Biasini, Maurizio; Bilei, Gian Mario; Fanò, Livio; Lariccia, Paolo; Mantovani, Giancarlo; Menichelli, Mauro; Nappi, Aniello; Romeo, Francesco; Saha, Anirban; Santocchia, Attilio; Spiezia, Aniello; Taroni, Silvia; Azzurri, Paolo; Bagliesi, Giuseppe; Boccali, Tommaso; Broccolo, Giuseppe; Castaldi, Rino; D'Agnolo, Raffaele Tito; Dell'Orso, Roberto; Fiori, Francesco; Foà, Lorenzo; Giassi, Alessandro; Kraan, Aafke; Ligabue, Franco; Lomtadze, Teimuraz; Martini, Luca; Messineo, Alberto; Palla, Fabrizio; Rizzi, Andrea; Serban, Alin Titus; Spagnolo, Paolo; Squillacioti, Paola; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Vernieri, Caterina; Barone, Luciano; Cavallari, Francesca; Del Re, Daniele; Diemoz, Marcella; Fanelli, Cristiano; Grassi, Marco; Longo, Egidio; Margaroli, Fabrizio; Meridiani, Paolo; Micheli, Francesco; Nourbakhsh, Shervin; Organtini, Giovanni; Paramatti, Riccardo; Rahatlou, Shahram; Soffi, Livia; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Biino, Cristina; Cartiglia, Nicolo; Casasso, Stefano; Costa, Marco; Demaria, Natale; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Musich, Marco; Obertino, Maria Margherita; Ortona, Giacomo; Pastrone, Nadia; Pelliccioni, Mario; Potenza, Alberto; Romero, Alessandra; Sacchi, Roberto; Solano, Ada; Staiano, Amedeo; Tamponi, Umberto; Belforte, Stefano; Candelise, Vieri; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Gobbo, Benigno; Marone, Matteo; Montanino, Damiana; Penzo, Aldo; Schizzi, Andrea; Zanetti, Anna; Kim, Tae Yeon; Nam, Soon-Kwon; Chang, Sunghyun; Kim, Dong Hee; Kim, Gui Nyun; Kim, Ji Eun; Kong, Dae Jung; Oh, Young Do; Park, Hyangkyu; Son, Dong-Chul; Kim, Jae Yool; Kim, Zero Jaeho; Song, Sanghyeon; Choi, Suyong; Gyun, Dooyeon; Hong, Byung-Sik; Jo, Mihee; Kim, Hyunchul; Kim, Tae Jeong; Lee, Kyong Sei; Moon, Dong Ho; Park, Sung Keun; Roh, Youn; Choi, Minkyoo; Kim, Ji Hyun; Park, Chawon; Park, Inkyu; Park, Sangnam; Ryu, Geonmo; Choi, Young-Il; Choi, Young Kyu; Goh, Junghwan; Kim, Min Suk; Kwon, Eunhyang; Lee, Byounghoon; Lee, Jongseok; Lee, Sungeun; Seo, Hyunkwan; Yu, Intae; Grigelionis, Ignas; Juodagalvis, Andrius; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Heredia-de La Cruz, Ivan; Lopez-Fernandez, Ricardo; Martínez-Ortega, Jorge; Sánchez Hernández, Alberto; Villasenor-Cendejas, Luis Manuel; Carrillo Moreno, Salvador; Vazquez Valencia, Fabiola; Salazar Ibarguen, Humberto Antonio; Casimiro Linares, Edgar; Morelos Pineda, Antonio; Reyes-Santos, Marco A; Krofcheck, David; Bell, Alan James; Butler, Philip H; Doesburg, Robert; Reucroft, Steve; Silverwood, Hamish; Ahmad, Muhammad; Asghar, Muhammad Irfan; Butt, Jamila; Hoorani, Hafeez R; Khalid, Shoaib; Khan, Wajid Ali; Khurshid, Taimoor; Qazi, Shamona; Shah, Mehar Ali; Shoaib, Muhammad; Bialkowska, Helena; Boimska, Bożena; Frueboes, Tomasz; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Romanowska-Rybinska, Katarzyna; Szleper, Michal; Wrochna, Grzegorz; Zalewski, Piotr; Brona, Grzegorz; Bunkowski, Karol; Cwiok, Mikolaj; Dominik, Wojciech; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Misiura, Maciej; Wolszczak, Weronika; Almeida, Nuno; Bargassa, Pedrame; David Tinoco Mendes, Andre; Faccioli, Pietro; Ferreira Parracho, Pedro Guilherme; Gallinaro, Michele; Seixas, Joao; Varela, Joao; Vischia, Pietro; Bunin, Pavel; Golutvin, Igor; Gorbunov, Ilya; Karjavin, Vladimir; Konoplyanikov, Viktor; Kozlov, Guennady; Lanev, Alexander; Malakhov, Alexander; Moisenz, Petr; Palichik, Vladimir; Perelygin, Victor; Savina, Maria; Shmatov, Sergey; Shulha, Siarhei; Smirnov, Vitaly; Volodko, Anton; Zarubin, Anatoli; Evstyukhin, Sergey; Golovtsov, Victor; Ivanov, Yury; Kim, Victor; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Vorobyev, Andrey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Kirsanov, Mikhail; Krasnikov, Nikolai; Matveev, Viktor; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Erofeeva, Maria; Gavrilov, Vladimir; Lychkovskaya, Natalia; Popov, Vladimir; Safronov, Grigory; Semenov, Sergey; Spiridonov, Alexander; Stolin, Viatcheslav; Vlasov, Evgueni; Zhokin, Alexander; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Leonidov, Andrey; Mesyats, Gennady; Rusakov, Sergey V; Vinogradov, Alexey; Belyaev, Andrey; Boos, Edouard; Bunichev, Viacheslav; Dubinin, Mikhail; Dudko, Lev; Ershov, Alexander; Gribushin, Andrey; Klyukhin, Vyacheslav; Kodolova, Olga; Lokhtin, Igor; Markina, Anastasia; Obraztsov, Stepan; Petrushanko, Sergey; Savrin, Viktor; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Kachanov, Vassili; Kalinin, Alexey; Konstantinov, Dmitri; Krychkine, Victor; Petrov, Vladimir; Ryutin, Roman; Sobol, Andrei; Tourtchanovitch, Leonid; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Adzic, Petar; Ekmedzic, Marko; Krpic, Dragomir; Milosevic, Jovan; Aguilar-Benitez, Manuel; Alcaraz Maestre, Juan; Battilana, Carlo; Calvo, Enrique; Cerrada, Marcos; Chamizo Llatas, Maria; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Domínguez Vázquez, Daniel; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Ferrando, Antonio; Flix, Jose; Fouz, Maria Cruz; Garcia-Abia, Pablo; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Merino, Gonzalo; Puerta Pelayo, Jesus; Quintario Olmeda, Adrián; Redondo, Ignacio; Romero, Luciano; Santaolalla, Javier; Senghi Soares, Mara; Willmott, Carlos; Albajar, Carmen; de Trocóniz, Jorge F; Brun, Hugues; Cuevas, Javier; Fernandez Menendez, Javier; Folgueras, Santiago; Gonzalez Caballero, Isidro; Lloret Iglesias, Lara; Piedra Gomez, Jonatan; Brochero Cifuentes, Javier Andres; Cabrillo, Iban Jose; Calderon, Alicia; Chuang, Shan-Huei; Duarte Campderros, Jordi; Fernandez, Marcos; Gomez, Gervasio; Gonzalez Sanchez, Javier; Graziano, Alberto; Jorda, Clara; Lopez Virto, Amparo; Marco, Jesus; Marco, Rafael; Martinez Rivero, Celso; Matorras, Francisco; Munoz Sanchez, Francisca Javiela; Rodrigo, Teresa; Rodríguez-Marrero, Ana Yaiza; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Auffray, Etiennette; Auzinger, Georg; Bachtis, Michail; Baillon, Paul; Ball, Austin; Barney, David; Bendavid, Joshua; Benitez, Jose F; Bernet, Colin; Bianchi, Giovanni; Bloch, Philippe; Bocci, Andrea; Bonato, Alessio; Botta, Cristina; Breuker, Horst; Camporesi, Tiziano; Cerminara, Gianluca; Christiansen, Tim; Coarasa Perez, Jose Antonio; D'Enterria, David; Dabrowski, Anne; De Roeck, Albert; De Visscher, Simon; Di Guida, Salvatore; Dobson, Marc; Dupont-Sagorin, Niels; Elliott-Peisert, Anna; Eugster, Jürg; Funk, Wolfgang; Georgiou, Georgios; Giffels, Manuel; Gigi, Dominique; Gill, Karl; Giordano, Domenico; Giunta, Marina; Glege, Frank; Gomez-Reino Garrido, Robert; Govoni, Pietro; Gowdy, Stephen; Guida, Roberto; Hammer, Josef; Hansen, Magnus; Harris, Philip; Hartl, Christian; Harvey, John; Hegner, Benedikt; Hinzmann, Andreas; Innocente, Vincenzo; Janot, Patrick; Kaadze, Ketino; Karavakis, Edward; Kousouris, Konstantinos; Krajczar, Krisztian; Lecoq, Paul; Lee, Yen-Jie; Lourenco, Carlos; Malberti, Martina; Malgeri, Luca; Mannelli, Marcello; Masetti, Lorenzo; Meijers, Frans; Mersi, Stefano; Meschi, Emilio; Moser, Roland; Mulders, Martijn; Musella, Pasquale; Nesvold, Erik; Orsini, Luciano; Palencia Cortezon, Enrique; Perez, Emmanuelle; Perrozzi, Luca; Petrilli, Achille; Pfeiffer, Andreas; Pierini, Maurizio; Pimiä, Martti; Piparo, Danilo; Polese, Giovanni; Quertenmont, Loic; Racz, Attila; Reece, William; Rodrigues Antunes, Joao; Rolandi, Gigi; Rovelli, Chiara; Rovere, Marco; Sakulin, Hannes; Santanastasio, Francesco; Schäfer, Christoph; Schwick, Christoph; Segoni, Ilaria; Sekmen, Sezen; Sharma, Archana; Siegrist, Patrice; Silva, Pedro; Simon, Michal; Sphicas, Paraskevas; Spiga, Daniele; Stoye, Markus; Tsirou, Andromachi; Veres, Gabor Istvan; Vlimant, Jean-Roch; Wöhri, Hermine Katharina; Worm, Steven; Zeuner, Wolfram Dietrich; Bertl, Willi; Deiters, Konrad; Erdmann, Wolfram; Gabathuler, Kurt; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; König, Stefan; Kotlinski, Danek; Langenegger, Urs; Meier, Frank; Renker, Dieter; Rohe, Tilman; Bachmair, Felix; Bäni, Lukas; Bortignon, Pierluigi; Buchmann, Marco-Andrea; Casal, Bruno; Chanon, Nicolas; Deisher, Amanda; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dünser, Marc; Eller, Philipp; Grab, Christoph; Hits, Dmitry; Lecomte, Pierre; Lustermann, Werner; Marini, Andrea Carlo; Martinez Ruiz del Arbol, Pablo; Mohr, Niklas; Moortgat, Filip; Nägeli, Christoph; Nef, Pascal; Nessi-Tedaldi, Francesca; Pandolfi, Francesco; Pape, Luc; Pauss, Felicitas; Peruzzi, Marco; Ronga, Frederic Jean; Rossini, Marco; Sala, Leonardo; Sanchez, Ann - Karin; Starodumov, Andrei; Stieger, Benjamin; Takahashi, Maiko; Tauscher, Ludwig; Thea, Alessandro; Theofilatos, Konstantinos; Treille, Daniel; Urscheler, Christina; Wallny, Rainer; Weber, Hannsjoerg Artur; Amsler, Claude; Chiochia, Vincenzo; Favaro, Carlotta; Ivova Rikova, Mirena; Kilminster, Benjamin; Millan Mejias, Barbara; Otiougova, Polina; Robmann, Peter; Snoek, Hella; Tupputi, Salvatore; Verzetti, Mauro; Cardaci, Marco; Chen, Kuan-Hsin; Ferro, Cristina; Kuo, Chia-Ming; Li, Syue-Wei; Lin, Willis; Lu, Yun-Ju; Volpe, Roberta; Yu, Shin-Shan; Bartalini, Paolo; Chang, Paoti; Chang, You-Hao; Chang, Yu-Wei; Chao, Yuan; Chen, Kai-Feng; Dietz, Charles; Grundler, Ulysses; Hou, George Wei-Shu; Hsiung, Yee; Kao, Kai-Yi; Lei, Yeong-Jyi; Lu, Rong-Shyang; Majumder, Devdatta; Petrakou, Eleni; Shi, Xin; Shiu, Jing-Ge; Tzeng, Yeng-Ming; Wang, Minzu; Asavapibhop, Burin; Suwonjandee, Narumon; Adiguzel, Aytul; Bakirci, Mustafa Numan; Cerci, Salim; Dozen, Candan; Dumanoglu, Isa; Eskut, Eda; Girgis, Semiray; Gokbulut, Gul; Gurpinar, Emine; Hos, Ilknur; Kangal, Evrim Ersin; Kayis Topaksu, Aysel; Onengut, Gulsen; Ozdemir, Kadri; Ozturk, Sertac; Polatoz, Ayse; Sogut, Kenan; Sunar Cerci, Deniz; Tali, Bayram; Topakli, Huseyin; Vergili, Mehmet; Akin, Ilina Vasileva; Aliev, Takhmasib; Bilin, Bugra; Bilmis, Selcuk; Deniz, Muhammed; Gamsizkan, Halil; Guler, Ali Murat; Karapinar, Guler; Ocalan, Kadir; Ozpineci, Altug; Serin, Meltem; Sever, Ramazan; Surat, Ugur Emrah; Yalvac, Metin; Zeyrek, Mehmet; Gülmez, Erhan; Isildak, Bora; Kaya, Mithat; Kaya, Ozlem; Ozkorucuklu, Suat; Sonmez, Nasuf; Bahtiyar, Hüseyin; Barlas, Esra; Cankocak, Kerem; Günaydin, Yusuf Oguzhan; Vardarli, Fuat Ilkehan; Yücel, Mete; Levchuk, Leonid; Sorokin, Pavel; Brooke, James John; Clement, Emyr; Cussans, David; Flacher, Henning; Frazier, Robert; Goldstein, Joel; Grimes, Mark; Heath, Greg P; Heath, Helen F; Kreczko, Lukasz; Metson, Simon; Newbold, Dave M; Nirunpong, Kachanon; Poll, Anthony; Senkin, Sergey; Smith, Vincent J; Williams, Thomas; Basso, Lorenzo; Bell, Ken W; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Jackson, James; Olaiya, Emmanuel; Petyt, David; Radburn-Smith, Benjamin Charles; Shepherd-Themistocleous, Claire; Tomalin, Ian R; Womersley, William John; Bainbridge, Robert; Ball, Gordon; Buchmuller, Oliver; Colling, David; Cripps, Nicholas; Cutajar, Michael; Dauncey, Paul; Davies, Gavin; Della Negra, Michel; Ferguson, William; Fulcher, Jonathan; Gilbert, Andrew; Guneratne Bryer, Arlo; Hall, Geoffrey; Hatherell, Zoe; Hays, Jonathan; Iles, Gregory; Jarvis, Martyn; Karapostoli, Georgia; Kenzie, Matthew; Lyons, Louis; Magnan, Anne-Marie; Marrouche, Jad; Mathias, Bryn; Nandi, Robin; Nash, Jordan; Nikitenko, Alexander; Pela, Joao; Pesaresi, Mark; Petridis, Konstantinos; Pioppi, Michele; Raymond, David Mark; Rogerson, Samuel; Rose, Andrew; Seez, Christopher; Sharp, Peter; Sparrow, Alex; Tapper, Alexander; Vazquez Acosta, Monica; Virdee, Tejinder; Wakefield, Stuart; Wardle, Nicholas; Whyntie, Tom; Chadwick, Matthew; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Leggat, Duncan; Leslie, Dawn; Martin, William; Reid, Ivan; Symonds, Philip; Teodorescu, Liliana; Turner, Mark; Dittmann, Jay; Hatakeyama, Kenichi; Kasmi, Azeddine; Liu, Hongxuan; Scarborough, Tara; Charaf, Otman; Cooper, Seth; Henderson, Conor; Rumerio, Paolo; Avetisyan, Aram; Bose, Tulika; Fantasia, Cory; Heister, Arno; Lawson, Philip; Lazic, Dragoslav; Rohlf, James; Sperka, David; St John, Jason; Sulak, Lawrence; Alimena, Juliette; Bhattacharya, Saptaparna; Christopher, Grant; Cutts, David; Demiragli, Zeynep; Ferapontov, Alexey; Garabedian, Alex; Heintz, Ulrich; Kukartsev, Gennadiy; Laird, Edward; Landsberg, Greg; Luk, Michael; Narain, Meenakshi; Segala, Michael; Sinthuprasith, Tutanon; Speer, Thomas; Breedon, Richard; Breto, Guillermo; Calderon De La Barca Sanchez, Manuel; Caulfield, Matthew; Chauhan, Sushil; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Dolen, James; Erbacher, Robin; Gardner, Michael; Houtz, Rachel; Ko, Winston; Kopecky, Alexandra; Lander, Richard; Mall, Orpheus; Miceli, Tia; Nelson, Randy; Pellett, Dave; Ricci-Tam, Francesca; Rutherford, Britney; Searle, Matthew; Smith, John; Squires, Michael; Tripathi, Mani; Yohay, Rachel; Andreev, Valeri; Cline, David; Cousins, Robert; Duris, Joseph; Erhan, Samim; Everaerts, Pieter; Farrell, Chris; Felcini, Marta; Hauser, Jay; Ignatenko, Mikhail; Jarvis, Chad; Rakness, Gregory; Schlein, Peter; Traczyk, Piotr; Valuev, Vyacheslav; Weber, Matthias; Babb, John; Clare, Robert; Dinardo, Mauro Emanuele; Ellison, John Anthony; Gary, J William; Giordano, Ferdinando; Hanson, Gail; Liu, Hongliang; Long, Owen Rosser; Luthra, Arun; Nguyen, Harold; Paramesvaran, Sudarshan; Sturdy, Jared; Sumowidagdo, Suharyo; Wilken, Rachel; Wimpenny, Stephen; Andrews, Warren; Branson, James G; Cerati, Giuseppe Benedetto; Cittolin, Sergio; Evans, David; Holzner, André; Kelley, Ryan; Lebourgeois, Matthew; Letts, James; Macneill, Ian; Mangano, Boris; Padhi, Sanjay; Palmer, Christopher; Petrucciani, Giovanni; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Simon, Sean; Sudano, Elizabeth; Tadel, Matevz; Tu, Yanjun; Vartak, Adish; Wasserbaech, Steven; Würthwein, Frank; Yagil, Avraham; Yoo, Jaehyeok; Barge, Derek; Bellan, Riccardo; Campagnari, Claudio; D'Alfonso, Mariarosaria; Danielson, Thomas; Flowers, Kristen; Geffert, Paul; George, Christopher; Golf, Frank; Incandela, Joe; Justus, Christopher; Kalavase, Puneeth; Kovalskyi, Dmytro; Krutelyov, Vyacheslav; Lowette, Steven; Magaña Villalba, Ricardo; Mccoll, Nickolas; Pavlunin, Viktor; Ribnik, Jacob; Richman, Jeffrey; Rossin, Roberto; Stuart, David; To, Wing; West, Christopher; Apresyan, Artur; Bornheim, Adolf; Bunn, Julian; Chen, Yi; Di Marco, Emanuele; Duarte, Javier; Kcira, Dorian; Ma, Yousi; Mott, Alexander; Newman, Harvey B; Rogan, Christopher; Spiropulu, Maria; Timciuc, Vladlen; Veverka, Jan; Wilkinson, Richard; Xie, Si; Yang, Yong; Zhu, Ren-Yuan; Azzolini, Virginia; Calamba, Aristotle; Carroll, Ryan; Ferguson, Thomas; Iiyama, Yutaro; Jang, Dong Wook; Liu, Yueh-Feng; Paulini, Manfred; Russ, James; Vogel, Helmut; Vorobiev, Igor; Cumalat, John Perry; Drell, Brian Robert; Ford, William T; Gaz, Alessandro; Luiggi Lopez, Eduardo; Nauenberg, Uriel; Smith, James; Stenson, Kevin; Ulmer, Keith; Wagner, Stephen Robert; Alexander, James; Chatterjee, Avishek; Eggert, Nicholas; Gibbons, Lawrence Kent; Hopkins, Walter; Khukhunaishvili, Aleko; Kreis, Benjamin; Mirman, Nathan; Nicolas Kaufman, Gala; Patterson, Juliet Ritchie; Ryd, Anders; Salvati, Emmanuele; Sun, Werner; Teo, Wee Don; Thom, Julia; Thompson, Joshua; Tucker, Jordan; Weng, Yao; Winstrom, Lucas; Wittich, Peter; Winn, Dave; Abdullin, Salavat; Albrow, Michael; Anderson, Jacob; Apollinari, Giorgio; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Burkett, Kevin; Butler, Joel Nathan; Chetluru, Vasundhara; Cheung, Harry; Chlebana, Frank; Cihangir, Selcuk; Elvira, Victor Daniel; Fisk, Ian; Freeman, Jim; Gao, Yanyan; Gottschalk, Erik; Gray, Lindsey; Green, Dan; Gutsche, Oliver; Harris, Robert M; Hirschauer, James; Hooberman, Benjamin; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Klima, Boaz; Kunori, Shuichi; Kwan, Simon; Linacre, Jacob; Lincoln, Don; Lipton, Ron; Lykken, Joseph; Maeshima, Kaori; Marraffino, John Michael; Martinez Outschoorn, Verena Ingrid; Maruyama, Sho; Mason, David; McBride, Patricia; Mishra, Kalanand; Mrenna, Stephen; Musienko, Yuri; Newman-Holmes, Catherine; O'Dell, Vivian; Prokofyev, Oleg; Sexton-Kennedy, Elizabeth; Sharma, Seema; Spalding, William J; Spiegel, Leonard; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vidal, Richard; Whitmore, Juliana; Wu, Weimin; Yang, Fan; Yun, Jae Chul; Acosta, Darin; Avery, Paul; Bourilkov, Dimitri; Chen, Mingshui; Cheng, Tongguang; Das, Souvik; De Gruttola, Michele; Di Giovanni, Gian Piero; Dobur, Didar; Drozdetskiy, Alexey; Field, Richard D; Fisher, Matthew; Fu, Yu; Furic, Ivan-Kresimir; Hugon, Justin; Kim, Bockjoo; Konigsberg, Jacobo; Korytov, Andrey; Kropivnitskaya, Anna; Kypreos, Theodore; Low, Jia Fu; Matchev, Konstantin; Milenovic, Predrag; Mitselmakher, Guenakh; Muniz, Lana; Remington, Ronald; Rinkevicius, Aurelijus; Skhirtladze, Nikoloz; Snowball, Matthew; Yelton, John; Zakaria, Mohammed; Gaultney, Vanessa; Hewamanage, Samantha; Lebolo, Luis Miguel; Linn, Stephan; Markowitz, Pete; Martinez, German; Rodriguez, Jorge Luis; Adams, Todd; Askew, Andrew; Bochenek, Joseph; Chen, Jie; Diamond, Brendan; Gleyzer, Sergei V; Haas, Jeff; Hagopian, Sharon; Hagopian, Vasken; Johnson, Kurtis F; Prosper, Harrison; Veeraraghavan, Venkatesh; Weinberg, Marc; Baarmand, Marc M; Dorney, Brian; Hohlmann, Marcus; Kalakhety, Himali; Yumiceva, Francisco; Adams, Mark Raymond; Apanasevich, Leonard; Bazterra, Victor Eduardo; Betts, Russell Richard; Bucinskaite, Inga; Callner, Jeremy; Cavanaugh, Richard; Evdokimov, Olga; Gauthier, Lucie; Gerber, Cecilia Elena; Hofman, David Jonathan; Khalatyan, Samvel; Kurt, Pelin; Lacroix, Florent; O'Brien, Christine; Silkworth, Christopher; Strom, Derek; Turner, Paul; Varelas, Nikos; Akgun, Ugur; Albayrak, Elif Asli; Bilki, Burak; Clarida, Warren; Dilsiz, Kamuran; Duru, Firdevs; Griffiths, Scott; Merlo, Jean-Pierre; Mermerkaya, Hamit; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Newsom, Charles Ray; Ogul, Hasan; Onel, Yasar; Ozok, Ferhat; Sen, Sercan; Tan, Ping; Tiras, Emrah; Wetzel, James; Yetkin, Taylan; Yi, Kai; Barnett, Bruce Arnold; Blumenfeld, Barry; Bolognesi, Sara; Fehling, David; Giurgiu, Gavril; Gritsan, Andrei; Hu, Guofan; Maksimovic, Petar; Swartz, Morris; Whitbeck, Andrew; Baringer, Philip; Bean, Alice; Benelli, Gabriele; Kenny III, Raymond Patrick; Murray, Michael; Noonan, Daniel; Sanders, Stephen; Stringer, Robert; Wood, Jeffrey Scott; Barfuss, Anne-Fleur; Chakaberia, Irakli; Ivanov, Andrew; Khalil, Sadia; Makouski, Mikhail; Maravin, Yurii; Shrestha, Shruti; Svintradze, Irakli; Gronberg, Jeffrey; Lange, David; Rebassoo, Finn; Wright, Douglas; Baden, Drew; Calvert, Brian; Eno, Sarah Catherine; Gomez, Jaime; Hadley, Nicholas John; Kellogg, Richard G; Kolberg, Ted; Lu, Ying; Marionneau, Matthieu; Mignerey, Alice; Pedro, Kevin; Peterman, Alison; Skuja, Andris; Temple, Jeffrey; Tonjes, Marguerite; Tonwar, Suresh C; Apyan, Aram; Bauer, Gerry; Busza, Wit; Butz, Erik; Cali, Ivan Amos; Chan, Matthew; Dutta, Valentina; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Kim, Yongsun; Klute, Markus; Levin, Andrew; Luckey, Paul David; Ma, Teng; Nahn, Steve; Paus, Christoph; Ralph, Duncan; Roland, Christof; Roland, Gunther; Stephans, George; Stöckli, Fabian; Sumorok, Konstanty; Sung, Kevin; Velicanu, Dragos; Wolf, Roger; Wyslouch, Bolek; Yang, Mingming; Yilmaz, Yetkin; Yoon, Sungho; Zanetti, Marco; Zhukova, Victoria; Dahmes, Bryan; De Benedetti, Abraham; Franzoni, Giovanni; Gude, Alexander; Haupt, Jason; Kao, Shih-Chuan; Klapoetke, Kevin; Kubota, Yuichi; Mans, Jeremy; Pastika, Nathaniel; Rusack, Roger; Sasseville, Michael; Singovsky, Alexander; Tambe, Norbert; Turkewitz, Jared; Cremaldi, Lucien Marcus; Kroeger, Rob; Perera, Lalith; Rahmat, Rahmat; Sanders, David A; Summers, Don; Avdeeva, Ekaterina; Bloom, Kenneth; Bose, Suvadeep; Claes, Daniel R; Dominguez, Aaron; Eads, Michael; Keller, Jason; Kravchenko, Ilya; Lazo-Flores, Jose; Malik, Sudhir; Snow, Gregory R; Godshalk, Andrew; Iashvili, Ia; Jain, Supriya; Kharchilava, Avto; Kumar, Ashish; Rappoccio, Salvatore; Wan, Zongru; Alverson, George; Barberis, Emanuela; Baumgartel, Darin; Chasco, Matthew; Haley, Joseph; Nash, David; Orimoto, Toyoko; Trocino, Daniele; Wood, Darien; Zhang, Jinzhong; Anastassov, Anton; Hahn, Kristan Allan; Kubik, Andrew; Lusito, Letizia; Mucia, Nicholas; Odell, Nathaniel; Pollack, Brian; Pozdnyakov, Andrey; Schmitt, Michael Henry; Stoynev, Stoyan; Velasco, Mayda; Won, Steven; Berry, Douglas; Brinkerhoff, Andrew; Chan, Kwok Ming; Hildreth, Michael; Jessop, Colin; Karmgard, Daniel John; Kolb, Jeff; Lannon, Kevin; Luo, Wuming; Lynch, Sean; Marinelli, Nancy; Morse, David Michael; Pearson, Tessa; Planer, Michael; Ruchti, Randy; Slaunwhite, Jason; Valls, Nil; Wayne, Mitchell; Wolf, Matthias; Antonelli, Louis; Bylsma, Ben; Durkin, Lloyd Stanley; Hill, Christopher; Hughes, Richard; Kotov, Khristian; Ling, Ta-Yung; Puigh, Darren; Rodenburg, Marissa; Smith, Geoffrey; Timcheck, Jonathan; Vuosalo, Carl; Williams, Grayson; Winer, Brian L; Wolfe, Homer; Berry, Edmund; Elmer, Peter; Halyo, Valerie; Hebda, Philip; Hegeman, Jeroen; Hunt, Adam; Jindal, Pratima; Koay, Sue Ann; Lopes Pegna, David; Lujan, Paul; Marlow, Daniel; Medvedeva, Tatiana; Mooney, Michael; Olsen, James; Piroué, Pierre; Quan, Xiaohang; Raval, Amita; Saka, Halil; Stickland, David; Tully, Christopher; Werner, Jeremy Scott; Zenz, Seth Conrad; Zuranski, Andrzej; Brownson, Eric; Lopez, Angel; Mendez, Hector; Ramirez Vargas, Juan Eduardo; Alagoz, Enver; Benedetti, Daniele; Bolla, Gino; Bortoletto, Daniela; De Mattia, Marco; Everett, Adam; Hu, Zhen; Jones, Matthew; Koybasi, Ozhan; Kress, Matthew; Leonardo, Nuno; Maroussov, Vassili; Merkel, Petra; Miller, David Harry; Neumeister, Norbert; Shipsey, Ian; Silvers, David; Svyatkovskiy, Alexey; Vidal Marono, Miguel; Yoo, Hwi Dong; Zablocki, Jakub; Zheng, Yu; Guragain, Samir; Parashar, Neeti; Adair, Antony; Akgun, Bora; Ecklund, Karl Matthew; Geurts, Frank JM; Li, Wei; Padley, Brian Paul; Redjimi, Radia; Roberts, Jay; Zabel, James; Betchart, Burton; Bodek, Arie; Covarelli, Roberto; de Barbaro, Pawel; Demina, Regina; Eshaq, Yossof; Ferbel, Thomas; Garcia-Bellido, Aran; Goldenzweig, Pablo; Han, Jiyeon; Harel, Amnon; Miner, Daniel Carl; Petrillo, Gianluca; Vishnevskiy, Dmitry; Zielinski, Marek; Bhatti, Anwar; Ciesielski, Robert; Demortier, Luc; Goulianos, Konstantin; Lungu, Gheorghe; Malik, Sarah; Mesropian, Christina; Arora, Sanjay; Barker, Anthony; Chou, John Paul; Contreras-Campana, Christian; Contreras-Campana, Emmanuel; Duggan, Daniel; Ferencek, Dinko; Gershtein, Yuri; Gray, Richard; Halkiadakis, Eva; Hidas, Dean; Lath, Amitabh; Panwalkar, Shruti; Park, Michael; Patel, Rishi; Rekovic, Vladimir; Robles, Jorge; Rose, Keith; Salur, Sevil; Schnetzer, Steve; Seitz, Claudia; Somalwar, Sunil; Stone, Robert; Walker, Matthew; Cerizza, Giordano; Hollingsworth, Matthew; Spanier, Stefan; Yang, Zong-Chang; York, Andrew; Eusebi, Ricardo; Flanagan, Will; Gilmore, Jason; Kamon, Teruki; Khotilovich, Vadim; Montalvo, Roy; Osipenkov, Ilya; Pakhotin, Yuriy; Perloff, Alexx; Roe, Jeffrey; Safonov, Alexei; Sakuma, Tai; Suarez, Indara; Tatarinov, Aysen; Toback, David; Akchurin, Nural; Damgov, Jordan; Dragoiu, Cosmin; Dudero, Phillip Russell; Jeong, Chiyoung; Kovitanggoon, Kittikul; Lee, Sung Won; Libeiro, Terence; Volobouev, Igor; Appelt, Eric; Delannoy, Andrés G; Greene, Senta; Gurrola, Alfredo; Johns, Willard; Maguire, Charles; Mao, Yaxian; Melo, Andrew; Sharma, Monika; Sheldon, Paul; Snook, Benjamin; Tuo, Shengquan; Velkovska, Julia; Arenton, Michael Wayne; Balazs, Michael; Boutle, Sarah; Cox, Bradley; Francis, Brian; Goodell, Joseph; Hirosky, Robert; Ledovskoy, Alexander; Lin, Chuanzhe; Neu, Christopher; Wood, John; Gollapinni, Sowjanya; Harr, Robert; Karchin, Paul Edmund; Kottachchi Kankanamge Don, Chamath; Lamichhane, Pramod; Sakharov, Alexandre; Anderson, Michael; Belknap, Donald; Borrello, Laura; Carlsmith, Duncan; Cepeda, Maria; Dasu, Sridhara; Friis, Evan; Grogg, Kira Suzanne; Grothe, Monika; Hall-Wilton, Richard; Herndon, Matthew; Hervé, Alain; Klabbers, Pamela; Klukas, Jeffrey; Lanaro, Armando; Lazaridis, Christos; Loveless, Richard; Mohapatra, Ajit; Mozer, Matthias Ulrich; Ojalvo, Isabel; Pierro, Giuseppe Antonio; Ross, Ian; Savin, Alexander; Smith, Wesley H; Swanson, Joshua

    2013-05-28

    A search for the standard model Higgs boson produced in association with a top-quark pair is presented using data samples corresponding to an integrated luminosity of 5.0 inverse femtobarns (5.1 inverse femtobarns) collected in pp collisions at the center-of-mass energy of 7 TeV (8 TeV). Events are considered where the top-quark pair decays to either one lepton+jets ($t\\bar{t} \\to \\ell\

  14. A mathematical model for predicting earthquake occurrence ...

    African Journals Online (AJOL)

    We consider the continental crust under damage. We use the observed results of microseism in many seismic stations of the world which was established to study the time series of the activities of the continental crust with a view to predicting possible time of occurrence of earthquake. We consider microseism time series ...

  15. Model for predicting the injury severity score.

    Science.gov (United States)

    Hagiwara, Shuichi; Oshima, Kiyohiro; Murata, Masato; Kaneko, Minoru; Aoki, Makoto; Kanbe, Masahiko; Nakamura, Takuro; Ohyama, Yoshio; Tamura, Jun'ichi

    2015-07-01

    To determine the formula that predicts the injury severity score from parameters that are obtained in the emergency department at arrival. We reviewed the medical records of trauma patients who were transferred to the emergency department of Gunma University Hospital between January 2010 and December 2010. The injury severity score, age, mean blood pressure, heart rate, Glasgow coma scale, hemoglobin, hematocrit, red blood cell count, platelet count, fibrinogen, international normalized ratio of prothrombin time, activated partial thromboplastin time, and fibrin degradation products, were examined in those patients on arrival. To determine the formula that predicts the injury severity score, multiple linear regression analysis was carried out. The injury severity score was set as the dependent variable, and the other parameters were set as candidate objective variables. IBM spss Statistics 20 was used for the statistical analysis. Statistical significance was set at P  Watson ratio was 2.200. A formula for predicting the injury severity score in trauma patients was developed with ordinary parameters such as fibrin degradation products and mean blood pressure. This formula is useful because we can predict the injury severity score easily in the emergency department.

  16. Predicting Career Advancement with Structural Equation Modelling

    Science.gov (United States)

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  17. Statistical model based gender prediction for targeted NGS clinical panels

    Directory of Open Access Journals (Sweden)

    Palani Kannan Kandavel

    2017-12-01

    The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

  18. A predictive pilot model for STOL aircraft landing

    Science.gov (United States)

    Kleinman, D. L.; Killingsworth, W. R.

    1974-01-01

    An optimal control approach has been used to model pilot performance during STOL flare and landing. The model is used to predict pilot landing performance for three STOL configurations, each having a different level of automatic control augmentation. Model predictions are compared with flight simulator data. It is concluded that the model can be effective design tool for studying analytically the effects of display modifications, different stability augmentation systems, and proposed changes in the landing area geometry.

  19. Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

    Science.gov (United States)

    Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

    2016-01-01

    Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

  20. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

    2006-01-01

    Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions...

  1. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  2. Testing and analysis of internal hardwood log defect prediction models

    Science.gov (United States)

    R. Edward Thomas

    2011-01-01

    The severity and location of internal defects determine the quality and value of lumber sawn from hardwood logs. Models have been developed to predict the size and position of internal defects based on external defect indicator measurements. These models were shown to predict approximately 80% of all internal knots based on external knot indicators. However, the size...

  3. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.